Annual Tropical Cyclone Report 2017

Transcription

1 Joint Typhoon Warning Center Annual Tropical Cyclone Report 2017 JILLENE M. BUSHNELL Commander, United States Navy Commanding Officer ROBERT J. FALVEY Director, Joint Typhoon Warning Center

2 Cover: Typhoon Noru as seen from the International Space Station on August 1, Noru s intensity at the time of this photo was approximately 105kts, shortly after it had reached a maximum intensity of 135kt. - Jack Fischer/NASA/Twitter 1

3 Executive Summary The Annual Tropical Cyclone Report (ATCR) is prepared by the staff of the Joint Typhoon Warning Center (JTWC), a jointly manned United States Navy / Air Force organization under the operational command of the Commanding Officer, JTWC. The original JTWC was established on 1 May 1959 when the Joint Chiefs of Staff directed Commander-in- Chief, US Pacific Command (USCINCPAC) to provide a single tropical cyclone warning center for the western North Pacific region. USCINCPAC delegated the tropical cyclone forecast and warning mission to Commander, Pacific Fleet (PACFLT). A subsequent USCINCPAC directive further tasked Commander, Pacific Air Force (PACAF) to provide for tropical cyclone (TC) reconnaissance support to the JTWC. This edition of the ATCR documents the 2017 TC season and details operationally or meteorologically significant cyclones noted within the JTWC area of responsibility which encompasses the western North Pacific Ocean, the North Indian Ocean, and the Southern Hemisphere Pacific and Indian Oceans. Details are provided to describe either significant challenges and/or shortfalls in the TC warning system and to serve as a focal point for future research and development efforts. Also included are TC reconnaissance statistics and a summary of TC research as well as tactics, techniques and procedure (TTP) development that members of the JTWC conducted. The central Pacific Ocean sea-surface temperatures continued to cool after the 2015 strong El Nino and the neutral conditions seen in 2016 transitioned into a weak La Nina. The net result was a further shift of the western North Pacific primary TC formation region westward. The total number of TCs in the western North Pacific reached 33, two above the 25-year mean, but there were an above-average number of tropical depressions and tropical storms and a below-average number of typhoons and super typhoons. Okinawa was impacted by one cyclone, mainland Japan was impacted by five cyclones, and Guam and South Korea were not impacted this season. The north Indian Ocean experienced normal activity of four cyclones, all in the Bay of Bengal, with one that moved into the Arabian Sea. Southern Hemisphere activity continued to be well below the long term average of 28, with only 19 cyclones. However, TC activity returned to the area around Australia, with four making landfall. The remainder of the Southern Hemisphere activity was equally spread between the South Indian and Pacific Oceans. Meteorological satellite data remained critical to the TC reconnaissance mission of the JTWC. Satellite analysts administratively assigned to the 17th Operational Weather Squadron, exploited a wide variety of electro-optic (EO), infrared (IR) and microwave satellite data to produce 6,913 position and intensity estimates (fixes), down from 8,274 in The USAF Mark IVB was the primary platform used by satellite analysts. The USN FMQ-17 satellite direct readout system was unavailable due to a system upgrade delay; the upgrade completion that occurred in mid-2018 allows for the direct read-out ingest of Japan Meteorological Agency (JMA) Himawari 8 (and eventually 9). Geo-located microwave and scatterometer imagery overlays available via the Automated Tropical Cyclone Forecast (ATCF) system from Fleet Numerical Meteorology and Oceanography Center (FNMOC) and Naval Research Laboratory, Monterey (NRL-MRY) were also used by JTWC to make TC fixes and to help determine TC structure and wind fields. METEOSAT-8, which the European Space Agency moved to 41.5 o E longitude, was the primary geostationary satellite used in the Indian Ocean, although its positioning creates a gap in geostationary coverage east of the Bay of Bengal to East Java. 2

4 The USAF Weather Satellite Follow-on (WSF) program moved slowly forward, with vendor selection for the microwave instance (WSF-M) and USAF Weather leadership discussion with the National Oceanic and Atmospheric Administration (NOAA) about possible options including moving an older GOES geostationary satellite, designated WSF-G, over the Indian Ocean. DMSP F-19, the most recently launched USAF legacy polar orbiting satellite, had a command and control communications failure, resulting in a rapidly decaying orbit, rendering the satellite unusable. JTWC began evaluating scatterometer data from the Indian Space Research Organization (ISRO) ScatSat-1 satellite and data from NASA s Soil Moisture Active Passive (SMAP). Scientists at the Jet Propulsion Lab (JPL) discovered they could also derive extreme winds data over oceanic areas with the data collected by the SMAP sensor. JTWC also continued to monitor the progress of various Cube Sat and Micro Sat research projects, including Cyclone Global Navigation Satellite System (CYGNSS) and the Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS). JTWC continued to collaborate with TC forecast support and research organizations such as the FNMOC, NRLMRY, the Naval Post Graduate School, the Office of Naval Research (ONR), the 557 Weather Wing, and NOAA Line Offices for continued development of TC reconnaissance tools, numerical models and forecast aids. The U.S. Navy collaboration with NOAA, contracted with Raytheon, for the Advanced Weather Interactive Processing System continued to move forward, with installation at JTWC expected in May 2018 and network authority to operate in Behind all these efforts are the dedicated team of men and women, military and civilian at JTWC. Special thanks to the entire JTWC Information Services Department for their continued outstanding information technology support and the Support Services, Training and Strategy and Requirements Departments for working tirelessly to ensure JTWC had the necessary training and resources to get the mission done. A special thanks also to: FNMOC for their operational data and modeling support; the NRLMRY and ONR for its dedicated TC research; the NOAA National Environmental Satellite, Data, and Information Service for satellite reconnaissance support; Jim Vermuelen, Yiping Wang, Richard Bankert, Josh Cossuth, Mark DeMaria, John Knaff, and Chris Velden for their continuing efforts to exploit remote sensing technologies in new and innovative ways; as well as Charles R. Buck Sampson and Mike Frost for their outstanding support and continued development of the ATCF system. 3

5 JTWC Personnel 2017 Leadership CDR Jillene Bushnell, Commanding Officer ( present) Mr. Robert Falvey, Director ( present) CDR Thomas Keefer, Executive Officer ( ) LCDR Katherine Coyle, Executive Officer ( present) AGCS Tom Brickler, Senior Enlisted Advisor ( ) AGC William Cady, Senior Enlisted Advisor ( present) Support Services Department Mr. Roberto Macias, Support Services Department Head ( present) Mrs. Sharee Evans, Administrative Assistant (2017) Vacant, Financial Technician (2017) LSC Arcyria Lockley, Logistics Specialist ( ) LS1 Kristofer Gaffud, Logistics Specialist ( present) Satellite Reconnaissance Department Maj Brian DeCicco, Satellite Operations Flight Commander ( )* Capt Sean Zoufaly, Satellite Operations Flight Commander ( present)* TSgt Matthew Drew, Satellite Operations NCOIC ( )*** MSgt Sonny Richardson, Satellite Operations NCOIC ( present)*** SSgt Donald Chappotin, Satellite Analyst ( ) SrA Francisco Martinez, Satellite Analyst ( ) Mrs. Brittany Bermea, Satellite Analyst ( present) SSgt Kyle Hart, Satellite Analyst ( ) SSgt Cheyenne Lembke, Satellite Analyst ( present) SrA Thomas Lowe, Satellite Analyst ( present) A1C Myles Davis, Satellite Analyst ( present) SSgt Lyndsay Veerkamp, Satellite Analyst ( present) Operations Department LCDR Brian Howell, Operations Department Head ( present)* AGC Justin Coryell, Operations Department LCPO ( )** LT Amy Price, Command Duty Officer ( ) LTJG Chi Maxey, Command Duty Officer ( ) AG1 Michael Schmidt, Command Duty Officer ( ) LT Edward Jacobs, Command Duty Officer ( present) LTJG Raul Ramirez, Command Duty Officer ( present) LT Stephanie Geant, Command Duty Officer ( present) ENS Ricardo Uribe, Command Duty Officer ( present) AG2 Janie Sherrock, Geophysical Technician ( ) AG3 Jeremiah Meeker, Geophysical Technician ( ) AG2 Dakota Bennett, Geophysical Technician ( ) AG3 Frandys Ferreras, Geophysical Technician ( present) AG3 Cole Bedgood, Geophysical Technician ( present) AGAN Austin Beauchamp, Geophysical Technician ( ) Mr. Stephen Barlow, Typhoon Duty Officer ( present) Mr. Richard Ballucanag, Typhoon Duty Officer ( present) LT Vincent Chamberlain, Typhoon Duty Officer ( )** LT Christopher Machado, Typhoon Duty Officer ( )** LT David Price, Typhoon Duty Officer ( present) LT Andrew Sweeney, Typhoon Duty Officer ( present) Plans and Requirements Department Mr. Brian Strahl, Plans and Requirements Department Head ( present)* AG2 Christopher Hoole, Geophysical Technician ( ) Information Services Department Mr. Joshua Nelson, Information Services Department Head ( present) Mr. Angelo Alvarez, System Administrator (2003- present) Mr. Andrew Rhoades, Information Assurance Officer ( present) Mr. Brandon Brevard, System Administrator ( present) IT1 Jeffery Gross, Information Technology ( ) IT1 Ken Surline, Information Technology ( present) IT2 Devon Herron, Information Technology ( ) IT2 Isaac Wilson, Information Technology ( ) IT3 Sha nae Wilson, Information Technology ( present) IT3 Khristian Ebreo, Information Technology ( present) Training Department Mr. Owen Shieh, Training Department Head ( present)* AG2 Carol Fisher, Geophysical Technician ( ) Technical Services Department Mr. Matt Kucas, Technical Services Department Head ( present)* Mr. James Darlow, Technical Services Technician ( present)*** * Typhoon Duty Officer (augmentation) ** Command Duty Officer (augmentation) *** Satellite Analyst (augmentation) 4

6 Table of Contents CHAPTER 1 WESTERN NORTH PACIFIC OCEAN TROPICAL CYCLONES... 6 Section 1 Informational Tables... 6 Section 2 Cyclone Summaries Section 3 Detailed Cyclone Reviews CHAPTER 2 NORTH INDIAN OCEAN TROPICAL CYCLONES Section 1 Informational Tables Section 2 Cyclone Summaries CHAPTER 3 SOUTH PACIFIC AND SOUTH INDIAN OCEAN TROPICAL CYCLONES..80 Section 1 Informational Tables Section 2 Cyclone Summaries CHAPTER 4 TROPICAL CYCLONE FIX DATA Section 1 Background Section 2 Fix Summary by Basin CHAPTER 5 TECHNICAL DEVELOPMENT SUMMARY Section 1 Operational Priorities Section 2 Research and Development Priorities Section 3 Technical Development Projects Section 4 Other Scientific Collaborations Section 5 Scientific and Technical Exchanges CHAPTER 6 SUMMARY OF FORECAST VERIFICATION Section 1 Annual Forecast Verification

7 Chapter 1 Western North Pacific Ocean Tropical Cyclones Section 1 Informational Tables Table 1-1 is a summary of TC activity in the western North Pacific Ocean during the 2017 season. JTWC issued warnings on 33 tropical cyclones. Table 1-2 shows the monthly distribution of TC activity summarized for and Table 1-3 shows the monthly average occurrence of TC s separated into: (1) typhoons and (2) tropical storms and typhoons. Table 1-4 summarizes Tropical Cyclone Formation Alerts issued. Figures 1-1 depicts the 2017 western North Pacific Ocean TC tracks. The annual number of TC s of tropical storm (TS) strength or higher appears in Figure 1-2, while the number of TC s of super typhoon (STY) intensity appears in Figure 1-3. Figure 1-4 illustrates a monthly average number of cyclones based on intensity categories. 6

8 Figure 1-1. Western North Pacific Tropical Cyclones. 7

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10 9

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12 Figure 1-2. Annual number of western North Pacific TCs greater than 34 knots intensity. Figure 1-3. Annual number of western North Pacific TCs greater than 129 knots intensity. 11

13 Figure 1-4. Average number of western North Pacific TCs (all intensities) by month

14 Section 2 Cyclone Summaries This section presents a synopsis of each cyclone that occurred during 2017 in the western North Pacific Ocean. Each cyclone is presented, with the number and basin identifier used by JTWC, along with the name assigned by Regional Specialized Meteorological Center (RSMC) Tokyo. Dates are also listed when JTWC first designated various stages of pre-warning development: LOW, MEDIUM, and HIGH (concurrent with TC formation alert (TCFA)). These classifications are defined as follows: - Low formation potential describes an area that is being monitored for development, but is unlikely to develop within the next 24 hours. - Medium formation potential describes an area that is being monitored for development and has an elevated potential to develop, but development will likely occur beyond 24 hours. - High formation potential describes an area that is being monitored for development and is either expected to develop within 24 hours or development has already started, but warning criteria have not yet been met. All areas designated as High are accompanied by a TCFA. Initial and final JTWC warning dates are also presented with the number of warnings issued by JTWC. Landfall over major landmasses with approximate locations is presented as well. The JTWC post-event, reanalysis best track is provided for each cyclone. Data included on the best track are position and intensity noted with color coded, cyclone symbols and track line. Best track position labels include the date, time, track speed in knots, maximum wind speed in knots, as well as the approximate locations where the cyclone made landfall over major landmasses. A second graph depicts best track intensity versus time, where fix plots are color coded by fixing agency. In addition, when this document is viewed as a pdf, each map has been hyperlinked to the appropriate keyhole markup language (kmz) file that will allow the reader to access and view the best-track data interactively on their computer using Geographic Information System (GIS) software. Simply hold the control button and click the map image. The link will open, allowing the reader to download and open the file. Users may retrieve kmz files for the entire season from: 13

15 01W TROPICAL DEPRESSION ONE ISSUED LOW: 06 Jan / 0600Z ISSUED MED: N/A FIRST TCFA: N/A FIRST WARNING: 07 Jan / 1800Z LAST WARNING: 16 Jan / 0000Z MAX INTENSITY: 30 WARNINGS: 12 14

16 02W TROPICAL DEPRESSION TWO ISSUED LOW: N/A ISSUED MED: 13 Apr / 0100Z FIRST TCFA: 13 Apr / 1000Z FIRST WARNING: 14 Apr / 0600Z LAST WARNING: 15 Apr / 0600Z MAX INTENSITY: 25 WARNINGS: 5 15

17 03W TROPICAL STORM MUIFA ISSUED LOW: 21 Apr / 0100Z ISSUED MED: 23 Apr / 2100Z FIRST TCFA: 24 Apr / 0500Z FIRST WARNING: 24 Apr / 1800Z LAST WARNING: 27 Apr / 1800Z MAX INTENSITY: 40 WARNINGS: 13 16

18 04W TROPICAL STORM MERBOK ISSUED LOW: 09 Jun / 0600Z ISSUED MED: 10 Jun / 0100Z FIRST TCFA: 10 Jun / 1200Z FIRST WARNING: 11 Jun / 0000Z LAST WARNING: 12 Jun / 1800Z MAX INTENSITY: 45 WARNINGS: 8 17

19 05W TYPHOON NANMADOL ISSUED LOW: N/A ISSUED MED: 30 Jun / 0130Z FIRST TCFA: 01 Jul / 0600Z FIRST WARNING: 02 Jul / 0000Z LAST WARNING: 04 Jul / 1800Z MAX INTENSITY: 65 WARNINGS: 12 18

20 06W TROPICAL STORM TALAS ISSUED LOW: 13 Jul / 0600Z ISSUED MED: 14 Jul / 2000Z FIRST TCFA: 15 Jul / 0230Z FIRST WARNING: 15 Jul / 1200Z LAST WARNING: 16 Jul / 1800Z MAX INTENSITY: 50 WARNINGS: 6 19

21 07W SUPER TYPHOON NORU ISSUED LOW: 19 Jul / 0000Z ISSUED MED: 19 Jul / 2100Z FIRST TCFA: 20 Jul / 0530Z FIRST WARNING: 20 Jul / 1800Z LAST WARNING: 08 Aug / 1200Z MAX INTENSITY: 135 WARNINGS: 76 20

22 08W TROPICAL STORM SONCA ISSUED LOW: N/A ISSUED MED: N/A FIRST TCFA: N/A FIRST WARNING: 21 Jul / 0000Z LAST WARNING: 25 Jul / 0600Z MAX INTENSITY: 45 WARNINGS: 18 21

23 09W TROPICAL STORM KULAP ISSUED LOW: 19 Jul / 2100Z ISSUED MED: 20 Jul / 0600Z FIRST TCFA: 21 Jul / 0530Z FIRST WARNING: 21 Jul / 0600Z LAST WARNING: 26 Jul / 0000Z MAX INTENSITY: 50 WARNINGS: 20 22

24 10W TROPICAL STORM ROKE ISSUED LOW: N/A ISSUED MED: N/A FIRST TCFA: 21 Jul / 0430Z FIRST WARNING: 21 Jul / 1800Z LAST WARNING: 23 Jul / 0000Z MAX INTENSITY: 35 WARNINGS: 6 23

25 11W TYPHOON NESAT ISSUED LOW: N/A ISSUED MED: 21 Jul / 0600Z FIRST TCFA: 25 Jul / 1100Z FIRST WARNING: 26 Jul / 0000Z LAST WARNING: 30 Jul / 0000Z MAX INTENSITY: 90 WARNINGS: 17 24

26 12W TROPICAL STORM HAITANG ISSUED LOW: N/A ISSUED MED: 26 Jul / 2200Z FIRST TCFA: 27 Jul / 2100Z FIRST WARNING: 28 Jul / 0600Z LAST WARNING: 31 Jul / 0000Z MAX INTENSITY: 40 WARNINGS: 12 25

27 13W TROPICAL STORM NALGAE ISSUED LOW: N/A ISSUED MED: 31 Jul / 1400Z FIRST TCFA: N/A FIRST WARNING: 01 Aug / 0000Z LAST WARNING: 05 Aug / 1200Z MAX INTENSITY: 60 WARNINGS: 19 26

28 14W TYPHOON BANYAN ISSUED LOW: N/A ISSUED MED: N/A FIRST TCFA: 10 Aug / 2000Z FIRST WARNING: 11 Aug / 0000Z LAST WARNING: 16 Aug / 1800Z MAX INTENSITY: 110 WARNINGS: 24 27

29 15W TYPHOON HATO ISSUED LOW: 19 Aug / 0200Z ISSUED MED: N/A FIRST TCFA: 19 Aug / 1400Z FIRST WARNING: 20 Aug / 0000Z LAST WARNING: 23 Aug / 0600Z MAX INTENSITY: 100 WARNINGS: 14 28

30 16W TROPICAL STORM PAKHAR ISSUED LOW: 23 Aug / 0900Z ISSUED MED: N/A FIRST TCFA: 24 Aug / 0100Z FIRST WARNING: 24 Aug / 1200Z LAST WARNING: 27 Aug / 0000Z MAX INTENSITY: 60 WARNINGS: 11 29

31 17W TYPHOON SANVU ISSUED LOW: 25 Aug / 1900Z ISSUED MED: 26 Aug / 0600Z FIRST TCFA: 27 Aug / 0600Z FIRST WARNING: 28 Aug / 1200Z LAST WARNING: 02 Sep / 1800Z MAX INTENSITY: 90 WARNINGS: 22 30

32 18W TROPICAL STORM MAWAR ISSUED LOW: N/A ISSUED MED: 30 Aug / 0600Z FIRST TCFA: 31 Aug / 0200Z FIRST WARNING: 31 Aug / 1800Z LAST WARNING: 03 Sep / 1800Z MAX INTENSITY: 45 WARNINGS: 13 31

33 19W TROPICAL DEPRESSION GUCHOL ISSUED LOW: 03 Sep / 1130Z ISSUED MED: 04 Sep / 0230Z FIRST TCFA: 04 Sep / 0530Z FIRST WARNING: 04 Sep / 1800Z LAST WARNING: 06 Sep / 1800Z MAX INTENSITY: 30 WARNINGS: 7 32

34 20W TYPHOON TALIM ISSUED LOW: 06 Sep / 2130Z ISSUED MED: 07 Sep / 0600Z FIRST TCFA: 08 Sep / 0200Z FIRST WARNING: 08 Sep / 1800Z LAST WARNING: 18 Sep / 0000Z MAX INTENSITY: 120 WARNINGS: 38 33

35 21W TYPHOON DOKSURI ISSUED LOW: 10 Sep / 0600Z ISSUED MED: 10 Sep / 1900Z FIRST TCFA: 11 Sep / 1700Z FIRST WARNING: 11 Sep / 1800Z LAST WARNING: 15 Sep / 0600Z MAX INTENSITY: 95 WARNINGS: 15 34

36 22W TROPICAL DEPRESSION TWENTYTWO ISSUED LOW: 20 Sep / 2000Z ISSUED MED: 23 Sep / 0600Z FIRST TCFA: 23 Sep / 1500Z FIRST WARNING: 23 Sep / 1800Z LAST WARNING: 25 Sep / 0600Z MAX INTENSITY: 30 WARNINGS: 7 35

37 23W TROPICAL DEPRESSION TWENTYTHREE ISSUED LOW: N/A ISSUED MED: 07 Oct / 2100Z FIRST TCFA: 08 Oct / 1000Z FIRST WARNING: 08 Oct / 1800Z LAST WARNING: 10 Oct / 0000Z MAX INTENSITY: 30 WARNINGS: 6 36

38 24W TYPHOON KHANUN ISSUED LOW: 10 Oct / 2000Z ISSUED MED: 11 Oct / 1330Z FIRST TCFA: 11 Oct / 2000Z FIRST WARNING: 12 Oct / 0600Z LAST WARNING: 16 Oct / 0600Z MAX INTENSITY: 90 WARNINGS: 17 37

39 25W SUPER TYPHOON LAN ISSUED LOW: N/A ISSUED MED: 13 Oct / 1430Z FIRST TCFA: 14 Oct / 0230Z FIRST WARNING: 15 Oct / 1200Z LAST WARNING: 23 Oct / 0000Z MAX INTENSITY: 135 WARNINGS: 31 38

40 26W TROPICAL DEPRESSION TWENTYSIX ISSUED LOW: 17 Oct / 0600Z ISSUED MED: 18 Oct / 0600Z FIRST TCFA: 18 Oct / 0830Z FIRST WARNING: 18 Oct / 1800Z LAST WARNING: 19 Oct / 0600Z MAX INTENSITY: 25 WARNINGS: 3 39

41 27W TYPHOON SAOLA ISSUED LOW: N/A ISSUED MED: 17 Oct / 2330Z FIRST TCFA: 18 Oct / 2030Z FIRST WARNING: 19 Oct / 1800Z LAST WARNING: 29 Oct / 1200Z MAX INTENSITY: 65 WARNINGS: 40 40

42 28W TYPHOON DAMREY ISSUED LOW: 31 Oct / 0600Z ISSUED MED: 31 Oct / 1400Z FIRST TCFA: 31 Oct / 2030Z FIRST WARNING: 01 Nov / 1800Z LAST WARNING: 03 Nov / 1800Z MAX INTENSITY: 90 WARNINGS: 10 41

43 29W TROPICAL DEPRESSION TWENTYNINE ISSUED LOW: 30 Oct / 1930Z ISSUED MED: 05 Nov / 0600Z FIRST TCFA: 05 Nov / 0730Z FIRST WARNING: 06 Nov / 0000Z LAST WARNING: 08 Nov / 0000Z MAX INTENSITY: 25 WARNINGS: 8 42

44 30W TROPICAL STORM HAIKUI ISSUED LOW: 08 Nov / 0130Z ISSUED MED: N/A FIRST TCFA: 08 Nov / 1930Z FIRST WARNING: 09 Nov / 0000Z LAST WARNING: 12 Nov / 0000Z MAX INTENSITY: 45 WARNINGS: 13 43

45 31W TROPICAL STORM KIROGI ISSUED LOW: 15 Nov / 1500Z ISSUED MED: 15 Nov / 2000Z FIRST TCFA: 16 Nov / 2100Z FIRST WARNING: 17 Nov / 1200Z LAST WARNING: 19 Nov / 0600Z MAX INTENSITY: 40 WARNINGS: 8 44

46 32W TROPICAL STORM KAI-TAK ISSUED LOW: 10 Dec / 1430Z ISSUED MED: 11 Dec / 0600Z FIRST TCFA: 13 Dec / 0130Z FIRST WARNING: 13 Dec / 1800Z LAST WARNING: 22 Dec / 0000Z MAX INTENSITY: 50 WARNINGS: 33 45

47 33W TYPHOON TEMBIN ISSUED LOW: 14 Dec / 0600Z ISSUED MED: 15 Dec / 1430Z FIRST TCFA: 20 Dec / 0900Z FIRST WARNING: 20 Dec / 1800Z LAST WARNING: 26 Dec / 0600Z MAX INTENSITY: 85 WARNINGS: 23 46

48 Section 3 Detailed Cyclone Reviews An Overview of High-Latitude Tropical Cyclone (TC) Formations Observed in the Western North Pacific During July and August 2017 Introduction Between 20 July 2017 and 01 August 2017, three TCs formed at an atypically high latitude in the western North Pacific basin (Table 1-5). These formations were supported by an unusual synoptic pattern, and each TC exhibited several interesting characteristics during its lifecycle. This overview discusses the characteristics of the synoptic environment observed during development of these high-latitude systems, posits a large-scale mechanism related to the synoptic pattern, and highlights key characteristics of each of the three cyclones. TC First warning time Final warning time First warning position Max intensity (kts) 07W (Noru) 20 Jul / 1800Z 08 Aug / 1200Z 27.7 N E W (Kulap) 21 Jul / 0600Z 25 Jul / 0600Z 26.5 N E 50 13W (Nalgae) 01 Aug / 0000Z 05 Aug / 1200Z 26.6 N E 60 Table 1-5. Characteristics of 2017 high-latitude, western North Pacific TCs 07W, 09W and 13W. Synoptic overview Three TCs formed in high latitudes north of the tropics in July and August of 2017: STY 07W (Noru), TS 09W (Kulap), and TS 13W (Nalgae). Both 07W and 09W began their life cycles as low-level waves transiting westward through the eastern portion of the western North Pacific Ocean basin. These nascent waves were positioned equatorward of an extensive STR evident in low-level and deep-layer flow analyses dated 18 July at 1200Z (Figure 1-5). These two disturbances formed into cyclones nearly simultaneously; JTWC issued first warnings for 07W and 09W on 20 July at 1800Z and 21 July at 0600Z, respectively. 47

49 Figure 1-5. Manual low-level streamline (left) and operational GFS deep-layer mean flow (right) analyses from 18 July 2017 at 1200Z showing two disturbances that would later develop into tropical cyclones 07W and 09W. The high latitude steering ridge initially built to the east of a meridional trough situated over northeastern Asia and extended westward over time as the trough moved eastward, allowing the developing tropical cyclones 07W and 09W to maintain generally westward motion (Figure 1-6). Simultaneously, a train of cyclonic cells embedded within a tropical upper tropospheric trough (TUTT) and shortwave, upper-level ridges developed over the incipient disturbances. This pattern introduced favorable upperlevel outflow mechanisms equatorward for 07W and poleward for 09W (Figure 1-7). 48

50 Figure 1-6. Operational GFS deep-layer mean flow analyses from 18 July at 1200Z (upper left), 19 July at 1200Z (upper right), 20 July at 1200Z (lower left) and 21 July at 1200Z (lower right); tropical cyclones 07W and 09W, and their incipient disturbances, progressed westward as the steering ridge to the north reoriented in the wake of a meridionally-oriented mid-latitude trough. 49

51 Figure 1-7. Operational GFS 200mb flow analyses from 19 July at 0000Z (left), 21 July at 1200Z (right); A developing train of tropical upper tropospheric trough (TUTT) cells and shortwave ridges become increasingly pronounced over time, reinforcing upper level outflow from both developing cyclones (enhanced outflow regions highlighted by orange arrows). 07W eventually intensified into a STY and meandered across the northern portion of the western North Pacific for nearly 19 days, anchoring a high-latitude trough that persisted throughout the system s life cycle. Multiple cyclonic disturbances formed along the eastern end of this persistent trough, including TS 13W and non-developing invests 93W, 95W, 96W and 98W (Figure 1-8). A combination of equatorward westerly low-level flow and divergent westerly upper-level outflow supported the formation and development of TS 13W (Figure 1-9). 50

52 Figure 1-8. Manual low-level streamline analyses showing the major features of monsoon and highlatitude low-level troughs on 26 July 2017 at 1200Z (top), 29 July 2017 at 1200Z (second from top), 01 August 2017 at 1200Z (second from bottom) and 03 August 2017 at 1200Z (bottom). 51

53 Figure 1-9. Operational GFS surface flow (left) and 200mb flow (right) analyses from 31 July 2017 at 1800Z, six hours prior to formation of TS 13W (enhanced westerly surface flow region highlighted by yellow arrow; enhanced upper-level outflow region highlighted by orange arrow). Climatology of high-latitude tropical cyclones The three TCs that formed over the high latitudes north of 25 N (Figure 1-10) comprised a small subset of the 33 total western North Pacific cyclones in All three systems were noteworthy in that they developed east of 140 E, within the subtropics (see Table 1-5 and Figure 1-10), via atypical development mechanisms associated with subtropical influences. In contrast, greater than 70% of western North Pacific TCs typically form in the deep tropics in association with the monsoon trough (Molinari and Vollaro 2013). 07W 09W 13W Figure 1-10: JTWC best tracks for 01W-33W with high-latitude box overlaid (area bounded N and E as defined in Feng et al. (2017) see next unit). Formation locations for 07W, 09W and 13W denoted by red circles. 52

54 Over a 58-year period ( ), only 98 of 1,773 (5.5%) TCs formed 1 at high latitudes, i.e., within the region denoted by the yellow box in Figure Of these 98 high-latitude tropical cyclones 11.2% (11/98) occurred during El Niño, 38.8% (38/98) occurred during La Niña and 50% (49/98) occurred during El Nino/ Southern Oscillation (ENSO) neutral conditions. Figure 1-11: Tropical cyclone formation location ( ) and associated ENSO state (Red=El Niño, Green=La Niña, Gray=ENSO-neutral). Based on the Oceanic Niño Index, Jan-Sep 2017 was characterized as ENSO-neutral, i.e., a period when neither El Niño nor La Niña conditions were present. These periods are generally characterized by near long-term average sea surface temperatures, tropical rainfall patterns and wind flow over the equatorial Pacific Ocean. As shown in Figure 1-12, ENSO-neutral years are associated with a fairly homogeneous distribution of TC formation points across the South China Sea and western North Pacific to about 160 E, with the highest concentration in the western portion of the basin and a less dense distribution to the east. 1 Formation here is defined as the time at which maximum sustained wind speed associated with the TC first equaled or exceeded 25 knots according to the JTWC best track dataset. 53

55 Figure 1-12: Tropical cyclone formation locations ( ) associated with ENSO-neutral conditions. In 2017, 24 (72.7%) tropical cyclones formed primarily west of 135 E with three additional systems forming in the high latitude region (Figure 1-13). This distribution was generally consistent with the typical TC formation pattern observed during ENSOneutral years (Figure 1-12), albeit with fewer formations to the east of 135 E than might be expected. The distribution was also consistent with the formation pattern associated with the La Niña conditions, which developed late in the season. Figure 1-13: Tropical cyclone formation locations in the western North Pacific basin, (Green=La Niña, Gray=Neutral). 54

56 Cross-equatorial flow background information As discussed in the synoptic overview of this report, three uncommonly highlatitude tropical cyclones formed within the subtropics in the western North Pacific during July and August 2017, far from the climatologically-favored monsoon trough development region. Synoptic analyses indicated the monsoon trough was present over the South China Sea but extended eastward to only about 140 E, with atypically extensive easterly flow dominating the tropics and subtropics to the east. Although a subtropical jet was observed to the south and several subtropical lows were present within the high-latitude formation region, these three cyclones developed vigorous outflow channels and consolidated over a sufficiently warm ocean surface. We propose that the synoptic pattern and formation of high-latitude systems observed in summer 2017 may be related to a cross-equatorial flow (CEF) pattern described comprehensively in Feng et al. (2017). The study cites CEF as a primary mechanism for the large-scale transfer of momentum and moisture between the northern and southern hemispheres. The extent of observed CEF varies with the monsoon pattern, ENSO, TC activity and winter cold surges (Feng et al. 2017; Love 1985a). Feng et al. (2017) identified three dominant channels of CEF over the western North Pacific, and defined three indices (VI1, VI2, and VI3) to represent the overall magnitude of CEF through these channels. Each index represents mean meridional wind speeds at 925mb where meridional flow is maximized - during the June through October time period within defined geographic regions ( E, 5 S-5 N; E, 5 S-5 N; and E, 5 S-5 N). Feng et al. (2017) related meridional flow observed in the three dominant channels to TC formation activity in five development regions labeled D1 through D5. This review will focus on only two of the three dominant channels of CEF, VI2 and VI3, and the high-latitude development area with which they are associated, D5, highlighted in Figure

57 Figure 1-14: Low-level meridional flow, cross-equatorial flow regions and primary TC formation regions in the western North Pacific basin according to Feng et al. (2017). Contours show mean 925mb meridional flow during the western North Pacific TC season (June-October) averaged over the time period. Solid contours indicate mean southerly flow, dashed contours indicate mean northerly flow. Regions VI1 through VI3 mark major cross-equatorial flow channels and regions D1 through D5 are primary TC formation regions. Region D5, the high-latitude TC formation region, and regions VI1 and VI2 the primary CEF channels associated with high-latitude TC formations are highlighted (figure adapted from Feng et al. (2017), p. 70). Feng et al. (2017) examined 579 tropical cyclones that formed in the western North Pacific over a 32-year period ( ) and found that 47 tropical cyclones, approximately 8.1% of the total, formed 2 in the high-latitude area (D5). The study identified a connection between TC formation in the D5 region and synoptic systems present in the mid-latitude westerly flow pattern. The authors also found a clear negative correlation between meridional wind anomalies observed in region VI2 and VI3 and the number of TC formations that occurred in region D5. In other words, more TC formations occurred when CEF (as measured through regions VI2 and VI3) was anomalously weak, and fewer TC formations occurred when CEF was anomalously strong. 2 Formation here is defined as the time at which maximum sustained wind speed associated with the TC first equaled or exceeded 35 knots according to the JTWC best track dataset. 56

58 Table 1-6: Correlation between the three primary CEF indices defined in Feng et al (2017) and the frequency of TC formation observed during the June through October western North Pacific TC season. Negative correlations between CEF in regions VI2 and VI3 and TC formations in D5 indicate that less high-latitude TC formations occur when CEF is stronger, and more high-latitude formations occur when CEF is weaker (figure adapted from Feng et al. (2017), p. 70). Additionally, Feng et al. (2017) found that when CEF is anomalously weak, more TCs form over the northern portion of the western North Pacific compared to the center to eastern portion of the basin. Western North Pacific TC formations observed in 2017 (Figure 1-10) were consistent with this pattern, with the majority of cyclones having formed and tracked to the west of 140 E and sparse activity observed in the centraleastern, western North Pacific. Feng et al. (2017) notes that when strong southerly meridional CEF is present along the equator near 125 E and 150 E, Coriolis force deflects the southerly flow northeastward after it crosses the equator and consequently intensifies low-level westerly flow at low-latitudes (Figure 1-15a). In this scenario, the monsoon trough extends further east to near 160 E due to the strengthened near-equatorial, low-level westerly flow. Tropical cyclogenesis occurs over the entire tropical western North Pacific, including regions near the dateline. In contrast, when weaker meridional CEF is observed along the equator near 125 E and 150 E, there is a lack of northeastwarddeflected low-level flow to the north. Low-level, westerly flow is consequently weaker at low-latitudes in the western North Pacific and the monsoon trough extends only to about 135 E (Figure 1-15b). Because the zonal extent of the monsoon trough is limited during these periods of weaker CEF, TC formation occurs more frequently in the western part of the western North Pacific in association with the trough. They also occur more frequently at higher latitudes. 57

59 Figure 1-15: Mean 850mb flow (wind barbs) and TC formation locations (TC symbols) during the June through October period during years with strong CEF (Figure 3-2a) and weak CEF (Figure 3-2b) between 1979 and The mean location of the monsoon trough is annotated with a dashed red line. During strong CEF years, the monsoon trough extends eastward to about 160 E. During weak CEF years, the eastern end of the trough is situated near 135 E (figure adapted from Feng et al. (2017), p. 72). Feng et al. (2017) identified several changes in large-scale environmental variables associated with TC formation that occur at higher latitudes (25 N to 35 N) in the western North Pacific as CEF varies. These changes include: o Higher low-level (850mb) relative vorticity during weak CEF years, and lower vorticity during strong CEF years o Higher divergence at 200mb during weak CEF years, and lower divergence during strong CEF years (the opposite relationship is evident at lower latitudes) o Lower vertical wind shear during weak CEF years, and higher vertical wind shear during strong CEF years o Lower outgoing longwave radiation (more convective activity) during weak CEF years, and higher outgoing longwave radiation (less convective activity) during strong CEF years Each of these relationships reflect a more favorable, large-scale environment for TC formation at higher latitudes during weak CEF years. Additionally, short-term variations in the monsoon trough are related to CEF. Namely, during strong CEF years, CEF quickly intensifies on a regular basis, resulting in farther eastward extensions of the monsoon trough and more TC formations within the trough. In contrast, variations in the monsoon trough evolve more slowly in weak CEF years and TC formations are frequently observed at the eastern end of the trough. 58

60 Reanalysis of the synoptic pattern during the 2017 western North Pacific TC season and high-latitude formation period In order to explore the possible relationship between CEF and TC formation activity during the 2017 western North Pacific TC season, we plotted several key CEF variables using NCEP reanalysis tools available online at We focused on 925mb meridional wind, sea level pressure and 850mb vector wind. For each variable, we examined climatology, seasonal anomalies and shorter-term (July through August) anomalies present during the high-latitude TC formation period. As a documented measure of CEF magnitude, the 925mb June-Oct 2017 composite anomaly indicates negative values in regions VI2 and VI3, indicating weaker than normal CEF (Figure 1-16). Based on Feng et al. (2017), this pattern is associated with high-latitude TC formation, primarily to the west of 140 E. Figure 1-16: 925mb meridional wind climatology (upper left), 925mb meridional wind composite mean for the 2017 June through October period (upper right) and 925mb meridional wind composite anomaly for the 2017 June through October period (lower). Red boxes highlight CEF regions VI2 and VI3. (based on NCEP/NCAR reanalysis data) 925mb composite mean and anomaly plots restricted to July and August 2017, when the three high-latitude TCs discussed in this study formed, indicate even weaker CEF in VI2 and VI3 with larger negative anomalies (Figure 1-17). 59

61 Figure 1-17: 925mb meridional wind composite mean (left) and 925mb meridional wind composite anomaly (right) for the July through August 2017 period. Red boxes highlight CEF regions VI2 and VI3. (based on NCEP/NCAR reanalysis data) Climatologically, low pressure associated with the monsoon trough is present over the South China Sea and extends southeastward to the International Dateline during the June through October period. Additionally, extensive high pressure associated with the STR is entrenched to east of Japan. Although sea level pressure during the June to October 2017 period was similar to the long-term mean, values were anomalously low north of 25 N. Normal to slightly higher values were observed equatorward of 25 N, suggesting a slightly weaker-than-normal monsoon trough (Figure 1-18). Figure 1-18: Sea level pressure composite anomaly for the June through October 2017 period. (based on NCEP/NCAR reanalysis data) During the narrower July to August 2017 period, sea level pressure anomalies were significantly higher across the southern portion of the western North Pacific, and anomalously low in the higher latitudes. Sea level pressure values near the center of the STR and along an extension to the south were much higher than normal (Figure 1-19). 60

62 Figure 1-19: Sea level pressure composite anomaly for the July through August 2017 period. (based on NCEP/NCAR reanalysis data) During the June to October 2017 period, the monsoon trough extended eastward only to about 130 E, limited in extent due in large part to the anomalously strong eastward flow associated with an equatorward extension of the STR (Figure 1-20). Figure 1-20: 850mb vector wind climatology (upper left), 850mb vector wind composite mean (upper right) and 850mb vector wind composite anomaly (lower) for the June to October 2017 period. Dashed red lines indicate geographic location of 850mb trough. (based on NCEP/NCAR reanalysis data) 61

63 During the narrower July to August 2017 period, the monsoon trough was weaker, with stronger easterly flow anomalies evident in the reanalysis data (Figure 1-21). Figure 1-21: 850mb vector wind composite mean (left) and 850mb vector wind composite anomaly (right) for the July through August 2017 period. Dashed red line indicates geographic location of 850mb trough. (based on NCEP/NCAR reanalysis data) In sum, the NCEP reanalysis data indicate that anomalies in the synoptic pattern conducive to high-latitude TC formation were present across the western North Pacific during the 2017 typhoon season, particularly during the months of July and August when three such high latitude formations occurred. These favorable large-scale conditions developed during periods of weak cross-equatorial flow. The coincident occurrences of these large-scale patterns and TC activity are consistent with the mechanism for high-latitude TC formation detailed in Feng et al. (2017) western North Pacific high-latitude tropical cyclone reviews Super Typhoon 07W (Noru) STY 07W (Noru) formed as a weak subtropical cyclone on 19 Jul 2017 at 1200Z near 26.3 N E, approximately 1015 nautical miles east of Iwo-To. The disturbance gradually intensified while initially tracking westward under the steering influence of a low-level reflection of the STR to the north. Just after a day, on 20 Jul at 1800Z, JTWC issued the first warning on a 30-knot TD 07W. Within 18 hours the system had intensified into a tropical storm. On 23 Jul at 0600Z, shortly after it strengthened to a typhoon, Noru turned sharply southward, east-southeastward, then due eastward as the STR receded and the near-equatorial ridge (NER) to the south became the primary steering mechanism. This eastward motion continued for about two days, until a deeper reflection of the STR to the northeast began to steer the cyclone northward, northwestward, then westward. The STR re-oriented as a series of transitory mid-latitude troughs passed to the north, carrying STY 07W along a meandering westward and equatorward track before finally receding and enabling 07W to recurve northeast just south of Kyushu, 62

64 Japan. STY 07W brushed the coast of Shikoku before making landfall over southern Honshu and moving across the Japanese Alps into the Sea of Japan, where it finally dissipated. In response to changes in the orientation and strength of the NER and STR, STY Noru tracked across the northern portion of the western North Pacific basin for more than 17 days (Figure 1-22). Fortunately, no major damage was incurred as the cyclone made landfall during its final weakening stage. Figure 1-22: STY 07W (Noru) 20-day best track. STY Noru s complex track proved challenging to JTWC, which is evident in an analysis of mean forecast track errors. JTWC track forecast errors (homogeneous comparison with the multi-model consensus, CONW) were consistently higher than CONW at all TAUs. Of note, however, both JTWC and CONW s track errors were above USPACOM goals at all TAUs (Table 1-7), indicating that the numerical models had difficulty predicting the track. Track Error (NM) Tau 24 Tau 48 Tau 72 Tau 96 Tau 120 JTWC CONW # Cases USPACOM GOALS Table 1-7: STY 07W forecast track error: homogeneous comparison (JTWC vs. CONW). 63

65 Several factors may have contributed to STY 07W s complex track: 1. Subtropical formation area. At about 26 N, 07 W formed well outside of the tropics, and did not conform to standard tropical steering patterns. 2. Binary interaction. Another cyclone, TS 09W, developed to the east of 07W at about the same time and passed within 300nm at its closest proximity. This interaction coincided with the looping motion observed 23 and 25 July. 3. STR in unusually high latitude area. The steering STR axis was oriented generally west-east near 50 N during most of 07W s lifespan. This may have allowed an extended period of minimal latitude gain during most of the cyclone s lifecycle. Figure 1-23: Final best track and all JTWC track forecasts for STY 07W (Noru). Rapid Intensification. STY 07W underwent two rapid intensification (RI) events, defined as an increase in intensity of 30 knots or greater within 24 hours. The first RI event occurred between 23 Jul 2017 at 0000Z and 24 Jul 2017 at 0000Z, when the TC intensified from 50 to 90 knots. The second RI event occurred between 29 Jul 2017 at 1800Z to 30 Jul 2017 at 1800Z, during which time the system intensified from 60 knots to its peak of 140 knots approximately 130 nm to the south of Iwo To (Figure 1-24). 64

66 Figure 1-24: Fix and best track intensity history for STY 07W (Noru) indicating two rapid intensification events. Tropical Storm 09W (Kulap) TS 09W (Kulap) formed from a high-latitude (20-25 N) wave in the easterlies as it tracked westward into the western North Pacific. The system was located under a 500mb subtropical low and was initially classified as a subtropical wave (Figures ). The system was noteworthy due to the vigorous (25-30 knots) easterly flow and strongly-convergent inflow (Figures 1-27,1-28). 65

67 Figure 1-25: 500mb chart (July 20 / 00Z). Figure 1-26: Surface chart (July 20 / 00Z). Figure 1-27: Z GCOM-W1 89GHz (NRL). Figure 1-28: Z GCOM-W1 composite (NRL). TS 09W continued to consolidate, with deep convective banding wrapping over the western semicircle into a well-defined, compact, low-level circulation center (Figures 1-29,1-30). Coincidentally, JTWC issued the first warning on 21 July at 0600Z, noting the transition from a subtropical system to a warm-core system based on recent Advanced Microwave Sounding Unit (AMSU) temperature anomaly crosssections and the increased core convection. There was evidence the system retained some subtropical characteristics, with weak baroclinicity associated with a broadening 200mb trough. However, the system underwent tropical development as the 200mb low shifted northwest (Figure 1-33) and poleward outflow improved. 66

68 Figure 1-29: 20/1921Z NOAA-18 89GHz (NRL). Figure 1-30: 21/0358Z SSMIS 91GHz (NRL). Figure 1-31: 500mb chart (July 21 / 06Z). Figure 1-32: Surface chart (July 21 / 06Z). Figure 1-33: 200mb chart (July 21 / 06Z). TS 09W quickly reached a peak intensity of 50 knots by 22 July at 0000Z (Figure 1-35), but gradually weakened thereafter as it remained situated within a marginal environment under a broad upper-level low. After 25 July, TS 09W weakened significantly as it approached STY 07W and encountered strong vertical wind shear. After a short period of binary interaction (Table 1-8) with STY 07W (Noru), TS 09W dissipated on 28 July (Figure 1-34). 67

69 Figure 1-34: JTWC best track for TS 09W and STY 07W depicting the binary interaction. Figure 1-35: Fix Time Intensity chart for TS 09W. 68

70 DATE (DDHH) SEPARATION DISTANCE (NM) APPROACH VELOCITY (KTS) Table 1-8: Separation distances and approach velocities between 09W and 07W. Values of these metrics during the approach phase are highlighted. Tropical Storm 13W (Nalgae) TS 13W (Nalgae) formed on 01 August near 26 N 162 E after 09W had already dissipated, and as 07W was undergoing RI near Iwo To, Japan, to the west. Among the three high-latitude TCs, neither the motion nor intensity change of 13W were particularly remarkable. The system did not interact with any other TC, did not undergo RI and followed a rather straightforward track. After drifting east-southeast along the shallow northern boundary of the near equatorial ridge for about 24 hours, 13W reached TS intensity and took a U-turn northwest, following the flow associated with a deep-layer STR to the northeast. On 04 Aug at 0000Z, following the passage of a mid-latitude shortwave trough to the north which slightly weakened the STR, TS 13W turned northnorthwest (Figure 1-36). The system gradually intensified in response to improved poleward outflow enhanced by the mid-latitude westerlies. After a day and half, its intensity peaked at 60 knots. After reaching this peak, the system began weakening and transitioning into an extratropical system under the influence of increasing vertical wind shear and cooling sea surface temperatures. By 06 Aug at 1200Z, 13W had completed the transition into a gale-force, cold-core low well to the east of Hokkaido, Japan. 69

71 Figure 1-36: Final best track and all JTWC track forecasts for TS 13W (Nalgae). JTWC track forecasts underperformed relative to CONW and USPACOM goals for most forecast taus but were reasonable through tau 96. However, TAU 120 track forecast errors were impacted by a few early-lifecycle forecasts that estimated a slower poleward turn than was eventually observed (Table 1-9). Track Error (NM) Tau 24 Tau 48 Tau 72 Tau 96 Tau 120 JTWC CONW # Cases USPACOM GOALS Table 1-9: TS 13W forecast track error: homogeneous comparison (JTWC vs. CONW). 70

72 Summary and conclusions The TC formation pattern during the 2017 western North Pacific TC season was consistent with the climatological pattern for ENSO-neutral years. The monsoon trough was mostly limited to western portion of the basin, where the majority of TC formations were consequently observed. Cross-equatorial flow was weak, relative to climatology, throughout the season. Three high-latitude TC formations were observed in the western North Pacific during July and August 2017 during a period of exceptionally weak CEF. We propose that the coincident weak CEF and high-latitude TC formations are consistent with the relationships identified in Feng et al. (2017). Our findings suggest that tracking real- time CEF anomalies during and throughout western North Pacific TC seasons, in addition to traditional large-scale patterns associated with ENSO, the Madden-Julian Oscillation and other tropical climate features, could provide additional insight regarding favored potential TC formation areas. References Feng, T., Shen, X., Huang, R., and Chen, G., Influence of the interannual variation of cross-equatorial flow on tropical cyclogenesis over the western North Pacific. J. Trop. Meteorol. 23, Love, G., Cross-equatorial influence of winter hemisphere subtropical cold surges. Mon. Wea. Rev. 113, Love, G., Cross-equatorial interactions during tropical cyclogenesis. Mon. Wea. Rev., 113, Molinari, J. and Vollaro, D., 2013: What percentage of western North Pacific tropical cyclones form with the monsoon trough? Mon. Wea. Rev. 141,

73 Chapter 2 North Indian Ocean Tropical Cyclones Section 1 Informational Tables Table 2-1 is a summary of TC activity in the north Indian Ocean during the 2017 season. Four cyclones occurred in 2017, with two systems reaching intensity greater than 64 knots. Table 2-2 shows the monthly distribution of Tropical Cyclone activity for

74 Figure 2-1. North Indian Ocean Tropical Cyclones. 73

75 74

76 Section 2 Cyclone Summaries Each cyclone is presented with the number and basin identifier assigned by JTWC, as well as the RSMC assigned cyclone name. Dates are listed when JTWC first designated Low and Medium stages of development, as well as when the first TCFA, first and last warning dates and times. Lastly depicted in the maximum intensity and the total number of warnings issued by JTWC. The JTWC post-event, reanalysis best track is provided for each cyclone. Data included on the best track are position and intensity noted with color coded, cyclone symbols and track line. Best track position labels include the date, time, track speed in knots, maximum wind speed in knots, as well as the approximate locations where the cyclone made landfall over major landmasses. A second graph depicts best track intensity versus time, where fix plots are color coded by fixing agency. In addition, when this document is viewed as a pdf, each map has been hyperlinked to the appropriate keyhole markup language (kmz) file that will allow the reader to access and view the best-track data interactively on their computer using Geographic Information System (GIS) software. Simply hold the control button and click the map image; the link will open allowing the reader to download and open the file. Users may also retrieve kmz files for the entire season from: 75

77 01B TROPICAL CYCLONE MAARUTHA ISSUED LOW: 13 Apr / 1800Z ISSUED MED: 14 Apr / 0400Z FIRST TCFA: 15 Apr / 0100Z FIRST WARNING: 15 Apr / 1200Z LAST WARNING: 16 Apr / 1800Z MAX INTENSITY: 50 WARNINGS: 6 76

78 02B TROPICAL CYCLONE MORA ISSUED LOW: 26 May / 0130Z ISSUED MED: 27 May / 0200Z FIRST TCFA: 27 May / 1430Z FIRST WARNING: 27 May / 1800Z LAST WARNING: 30 May / 0600Z MAX INTENSITY: 80 WARNINGS: 11 77

79 03B TROPICAL CYCLONE OCKHI ISSUED LOW: 28 Nov / 0230Z ISSUED MED: 28 Nov / 1800Z FIRST TCFA: 29 Nov / 0200Z FIRST WARNING: 29 Nov / 1800Z LAST WARNING: 05 Dec / 0600Z MAX INTENSITY: 100 WARNINGS: 23 78

80 04B TROPICAL CYCLONE FOUR ISSUED LOW: 29 Nov / 0600Z ISSUED MED: 06 Dec / 1000Z FIRST TCFA: 07 Dec / 0030Z FIRST WARNING: 08 Dec / 1800Z LAST WARNING: 09 Dec / 0600Z MAX INTENSITY: 45 WARNINGS: 3 79

81 Chapter 3 South Pacific and South Indian Ocean Tropical Cyclones This chapter contains information on South Pacific and South Indian Ocean TC activity that occurred during the 2017 season (1 July June 2017) and the monthly distribution of TC activity summarized for Section 1 Informational Tables Table 3-1 is a summary of TC activity in the Southern Hemisphere during the 2017 season. 80

82 Figure 3-1. Southern Indian Ocean Tropical Cyclones. Figure 3-2. Southern Pacific Tropical Cyclones. 81

83 Table 3-2 Monthly distribution of Tropical Cyclone activity summarized for

84 Section 2 Cyclone Summaries Each cyclone is presented with the number and basin identifier assigned by JTWC, as well as the RSMC assigned cyclone name. Dates are listed when JTWC first designated Low and Medium stages of development, as well as when the first TCFA, first and last warning dates and times. Lastly depicted in the maximum intensity and the total number of warnings issued by JTWC. The JTWC post-event, reanalysis best track is provided for each cyclone. Data included on the best track are position and intensity noted with color coded, cyclone symbols and track line. Best track position labels include the date, time, track speed in knots, maximum wind speed in knots, as well as the approximate locations where the cyclone made landfall over major landmasses. A second graph depicts best track intensity versus time, where fix plots are color coded by fixing agency. In addition, when this document is viewed as a pdf, each map has been hyperlinked to the appropriate keyhole markup language (kmz) file that will allow the reader to access and view the best-track data interactively on their computer using Geographic Information System (GIS) software. Simply hold the control button and click the map image; the link will open allowing the reader to download and open the file. Users may also retrieve kmz files for the entire season from: 83

85 01S TROPICAL CYCLONE ABELA ISSUED LOW: 11 Jul / 1800Z ISSUED MED: 13 Jul / 1800Z FIRST TCFA: 15 Jul / 1600Z FIRST WARNING: 16 Jul / 0600Z LAST WARNING: 19 Jul / 1800Z MAX INTENSITY: 55 WARNINGS: 8 84

86 02S TROPICAL CYCLONE YVETTE ISSUED LOW: N/A ISSUED MED: 19 Dec / 0630Z FIRST TCFA: 19 Dec / 0900Z FIRST WARNING: 19 Dec / 1800Z LAST WARNING: 23 Dec / 1800Z MAX INTENSITY: 50 WARNINGS: 9 85

87 03S TROPICAL CYCLONE THREE ISSUED LOW: 25 Jan / 0230Z ISSUED MED: 25 Jan / 1800Z FIRST TCFA: 26 Jan / 1400Z FIRST WARNING: 27 Jan / 0600Z LAST WARNING: 29 Jan / 0600Z MAX INTENSITY: 50 WARNINGS: 8 86

88 04S TROPICAL CYCLONE CARLOS ISSUED LOW: 31 Jan / 1800Z ISSUED MED: 02 Feb / 1800Z FIRST TCFA: 03 Feb / 1300Z FIRST WARNING: 04 Feb / 1200Z LAST WARNING: 11 Feb / 1200Z MAX INTENSITY: 70 WARNINGS: 15 87

89 05S TROPICAL CYCLONE DINEO ISSUED LOW: N/A ISSUED MED: 12 Feb / 1030Z FIRST TCFA: 12 Feb / 1300Z FIRST WARNING: 13 Feb / 1200Z LAST WARNING: 16 Feb / 0000Z MAX INTENSITY: 85 WARNINGS: 6 88

90 06P TROPICAL CYCLONE ALFRED ISSUED LOW: 16 Feb / 0600Z ISSUED MED: 16 Feb / 1230Z FIRST TCFA: 16 Feb / 1830Z FIRST WARNING: 20 Feb / 0000Z LAST WARNING: 20 Feb / 1200Z MAX INTENSITY: 50 WARNINGS: 2 89

91 07P TROPICAL CYCLONE BART ISSUED LOW: N/A ISSUED MED: N/A FIRST TCFA: N/A FIRST WARNING: 21 Feb / 0000Z LAST WARNING: 22 Feb / 0000Z MAX INTENSITY: 40 WARNINGS: 3 90

92 08P TROPICAL CYCLONE EIGHT ISSUED LOW: N/A ISSUED MED: 21 Feb / 0200Z FIRST TCFA: N/A FIRST WARNING: 22 Feb / 0000Z LAST WARNING: 22 Feb / 1800Z MAX INTENSITY: 45 WARNINGS: 3 91

93 09S TROPICAL CYCLONE ENAWO ISSUED LOW: 28 Feb / 2000Z ISSUED MED: 01 Mar / 1800Z FIRST TCFA: 02 Mar / 1930Z FIRST WARNING: 03 Mar / 0600Z LAST WARNING: 10 Mar / 1200Z MAX INTENSITY: 130 WARNINGS: 12 92

94 10S TROPICAL CYCLONE BLANCHE ISSUED LOW: 02 Mar / 2030Z ISSUED MED: 03 Mar / 1800Z FIRST TCFA: 05 Mar / 0200Z FIRST WARNING: 05 Mar / 1200Z LAST WARNING: 06 Mar / 1200Z MAX INTENSITY: 55 WARNINGS: 3 93

95 11S TROPICAL CYCLONE FERNANDO ISSUED LOW: 05 Mar / 0300Z ISSUED MED: 06 Mar / 1800Z FIRST TCFA: 07 Mar / 0430Z FIRST WARNING: 08 Mar / 1800Z LAST WARNING: 10 Mar / 1800Z MAX INTENSITY: 45 WARNINGS: 5 94

96 12S TROPICAL CYCLONE CALEB ISSUED LOW: N/A ISSUED MED: 21 Mar / 1800Z FIRST TCFA: N/A FIRST WARNING: 23 Mar / 0600Z LAST WARNING: 27 Mar / 0600Z MAX INTENSITY: 45 WARNINGS: 9 95

97 13P TROPICAL CYCLONE DEBBIE ISSUED LOW: 22 Mar / 1330Z ISSUED MED: 23 Mar / 1300Z FIRST TCFA: 24 Mar / 0130Z FIRST WARNING: 24 Mar / 1800Z LAST WARNING: 28 Mar / 0600Z MAX INTENSITY: 115 WARNINGS: 8 96

98 14P TROPICAL CYCLONE FOURTEEN ISSUED LOW: 03 Apr / 1300Z ISSUED MED: 04 Apr / 1400Z FIRST TCFA: 05 Apr / 0130Z FIRST WARNING: 05 Apr / 1200Z LAST WARNING: 06 Apr / 1200Z MAX INTENSITY: 40 WARNINGS: 3 97

99 15S TROPICAL CYCLONE ERNIE ISSUED LOW: N/A ISSUED MED: 05 Apr / 1500Z FIRST TCFA: 06 Apr / 0130Z FIRST WARNING: 06 Apr / 0600Z LAST WARNING: 10 Apr / 0600Z MAX INTENSITY: 140 WARNINGS: 9 98

100 16P TROPICAL CYCLONE COOK ISSUED LOW: N/A ISSUED MED: 06 Apr / 2230Z FIRST TCFA: 07 Apr / 0530Z FIRST WARNING: 08 Apr / 0000Z LAST WARNING: 11 Apr / 1200Z MAX INTENSITY: 90 WARNINGS: 8 99

101 17S TROPICAL CYCLONE FRANCES ISSUED LOW: 23 Apr / 2100Z ISSUED MED: 25 Apr / 1800Z FIRST TCFA: 26 Apr / 0300Z FIRST WARNING: 27 Apr / 0000Z LAST WARNING: 30 Apr / 0000Z MAX INTENSITY: 80 WARNINGS: 7 100

102 18P TROPICAL CYCLONE DONNA ISSUED LOW: 01 May / 0000Z ISSUED MED: 01 May / 0600Z FIRST TCFA: 01 May / 2100Z FIRST WARNING: 02 May / 1800Z LAST WARNING: 10 May / 0600Z MAX INTENSITY: 125 WARNINGS:

103 19P TROPICAL CYCLONE ELLA ISSUED LOW: 07 May / 1430Z ISSUED MED: 07 May / 2330Z FIRST TCFA: 08 May / 1430Z FIRST WARNING: 09 May / 0000Z LAST WARNING: 14 May / 1200Z MAX INTENSITY: 70 WARNINGS:

104 Chapter 4 Tropical Cyclone Fix Data Section 1 Background Meteorological satellite data continued to be the mainstay for the TC reconnaissance mission at JTWC. JTWC satellite analysts produced 6,913 position and intensity estimates. A total of 3,493 of those 6,913 fixes were made using microwave imagery, amounting to just over 50 percent of the total number of fixes. A total of 565 of those 6,913 fixes were scatterometry fixes amounting to just over 8 percent of the total number of fixes. The USAF primary weather satellite direct readout system, Mark IVB, and the USN FMQ-17 continued to be invaluable tools in the TC reconnaissance mission. Section 2 tables depict fixes produced by JTWC satellite analysts, stratified by basin and storm number. Following the final numbered storm for each section, is a value representing the number of fixes for invests considered as Did Not Develop (DND) areas. DNDs are areas that were fixed on but did not reach warning criteria. The total DND fixes for all basins was 1,183, which accounted for approximately 17% of all fixes in

105 Section 2 Fix Summary by Basin 104

106 105

107 Chapter 5 Technical Development Summary Section 1 Operational Priorities The top operational priority of the JTWC remains the sustained development and support of the Automated Tropical Cyclone Forecast System (ATCF) (Sampson and Schrader, 2000). ATCF is the DoD s primary software for analyzing and forecasting TCs, and the principal platform through which emerging research transitions into JTWC operations. The JTWC cannot generate TCFAs or warnings without the capabilities ATCF provides. The system tracks all invest areas (developing disturbances) and TC activity, automatically processes objective forecasting aids, produces TCFAs, warning text and graphical products, as well as provides core capabilities for analyzing TCs and their environment. Additionally, ATCF offers the JTWC Contingency of Operations Plan (COOP) backup capabilities to Fleet Weather Center (FWC) Norfolk and analytic support to FWC San Diego for tasks such as setting Tropical Cyclone Conditions of Readiness (TCCOR), forecasting onstation wind speed, designating Optimum Track Ship Routing (OTSR) MODSTORM locations and preparing diverts and advisories. The current version of ATCF, installed in 2017, incorporated numerous improvements, including operationalizing new rapid intensification forecast guidance described in Knaff et al. (2018), provided objective ASCAT 34 knot wind radii (R34) routine, Statistical Hurricane Intensity Prediction Scheme (SHIPS) wind radii estimates, a 7-day trajectory Climatology and Persistence (CLIPER), a wind radii Goerss Predicted Consensus Errors (GPCE), National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) data ingest and display, as well as updates to numerous wind radii and consensus aids. For external customers, the most noticeable change was the format and appearance of the warning graphic product, the first major overhaul in over a decade (figure 5-1). Additional ATCF updates expected in summer 2018, will further improve JTWC s analysis and forecast capabilities and accuracy. Figure 5-1. Comparison of old (left) versus new (right) JTWC warning graphic formats. 106

108 The JTWC has also prioritized operationalizing the NOAA National Weather Service (NWS) Advanced Weather Interactive Processing System (AWIPS-II) to facilitate visualization and evaluation of meteorological data. The AWIPS-II was installed at the JTWC in Spring 2018, and is awaiting approval for Navy network connection in early The command's Technical Services Department is currently configuring the system and will be developing standard operating procedures. The AWIPS-II promises many enhanced data synthesis capabilities to supplement ATCF data visualization and fusion; however, replicating the functionality, cost-effectiveness and long-term research to operations (R2O) efficiency of ATCF remains a significant challenge. The JTWC is participating in discussions with the NWS, which is working to develop an ATCF-like capability within the AWIPS-II framework, under NOAA NWS acquisition contract. Section 2 Research and Development Priorities The consistent top five requirements for TC research and development (provided as inputs to the FY18 annual report of the Office of the Federal Coordinator for Meteorological Services, Supporting Research at the Interdepartmental Hurricane Conference, as well as during the call for topics at the Office of Naval Research) are presented in Table 5-1. Developing guidance to accurately forecast TC intensity change, particularly the onset, duration, and magnitude of rapid intensity change remains the highest priorities. In 2017, 34% of all WESTPAC tropical cyclones reaching tropical storm intensity or higher experienced at least one period of 30-knot intensification over a 24-hour period. In 2017, the JTWC shifted TC structure specification improvement up to its number two priority because R34 impacts the 34 knot danger swath, wind speed probabilities, TCCOR and wave forecasting. Additionally, Bender et al. (2017) indicates that improved R34 inputs to the GFDL TC model, using objective best track wind radii (OBTK) described in section 3, reduced intensity forecast errors for TCs undergoing rapid intensification by 14-17% up to two days in advance in the western North Pacific, and reduced negative intensity biases by 25-75% up to three days in advance. Table JTWC R&D priorities. 107

109 Section 3 Technical Development Projects The JTWC personnel collaborated on numerous efforts evaluation promising research efforts and to transfer mature projects into operations in accordance with priorities listed above. 1. Tropical cyclone intensity change a. Intensity consensus (ICNW) New SHIPS rapid intensification guidance for the 24, 36 and 48-hour forecast periods were incorporated into the operational intensity forecast consensus, ICNW, in 2017 (Knaff et al. 2018). Current ICNW members are listed in table 5-2. Current ICNW members DSHN (SHIPS) DSHA (SHIPS) COAMPS-TC CHIPS HWRF RI40 RI55 RI70 Table 5-2. Primary objective aids comprising the operational JTWC tropical cyclone intensity (ICNW) consensus (current members as of July 2018). b. Deterministic rapid intensity forecast guidance A new rapid intensification prediction aid (RIPA) was made operational late in Described in Knaff et al. (2018), RIPA uses probabilistic forecasts based on two methods (linear discriminant analysis and logistic regression) to forecast the likelihood of 25, 30, 35 and 40 knots of intensification within a 24-hour forecast period, 45 and 55 knots of intensification within a 36-hour forecast period and 70 knots of intensification within a 48-hour forecast period. The linear discriminant analysis probability forecasts, which execute like on/off switches, are combined with the smoother, and more conservative, logistic regression forecasts using a simple, equal weighting. If the consensus probability exceeds 50% for any intensification threshold within the 24, 36 and/or 48-hour forecast period, a separate deterministic forecast will be triggered for each forecast lead time. These shortterm, deterministic, rapid intensification forecasts will be integrated into the intensity consensus whenever they are available. Independent results based on 2016 western North Pacific retrospective model runs indicate intensity consensus forecast biases were significantly reduced and error biases were slightly reduced when these deterministic RI forecasts were incorporated. Initial operational results support this testing, indicating that deterministic forecasts are triggered approximately 20%- 25% of the time in the RI-conducive western North Pacific. Slight modifications were made to RIPA in 2018 to better handle RI forecasts for storms approaching landfall, as well as for invest areas that 108

110 have not yet reached tropical storm intensity. Additionally, the intensity GPCE was re-derived to account for the new RI guidance, providing a more realistic spread in potential RI cases. JTWC will contribute more detailed information on RI forecasting and the use of RIPA in operations at the upcoming World Meteorological Organization (WMO) 9 th International Workshop on TCs. Figure 5-2. Example RI guidance displayed in ATCF for TC 09P, Figure 5-3. Example of consensus intensity aids with RIPA added, and re-derived GPCE spread. 109

111 c. Eyewall replacement cycle forecast guidance Eyewall replacement cycles (ERC) are a significant contributor to JTWC intensity forecast errors due to the complexity of forecasting the timing, duration and scale of such events. The Cooperative Institute for Meteorological Satellite Studies (CIMSS) recently developed and fielded the Microwave Prediction of ERC (M-PERC) model at the National Hurricane Center (NHC) as a Joint Hurricane Testbed (JHT) project (Wimmers et al., 2018). M-PERC objectively analyzes trends in microwave satellite imagery of TCs to produce an output of probability of an emerging ERC. Using these probability data, forecasters can apply additional guidance to estimate an upcoming decrease in maximum sustained winds (sometimes as much as 20 knots) and increase in the radius of damaging winds. JTWC is pursuing funding to optimize the M-PERC model for its forecast basins for further evaluation. 2. TC structure specification a. TC wind radii post analysis quality assurance In 2017, the JTWC continued efforts to provide best track data with post-analyzed R34 information for the western North Pacific basin. The JTWC best track post-analysis has historically been limited to position and intensity. However, beginning in 2015, the NRL-MRY and JTWC initiated an effort to reanalyze R34 in order to facilitate development and maintenance of new techniques for analyzing and forecasting TC wind structure and to streamline the operational workflow. Archived 2016 and 2017 best track data contain quality-controlled R34 data. Because of a lack of observational data, R50 and R64 values were derived via linear regression from the R34 values. The JTWC is seeking funding to continue post-analysis of wind structure to extend this work to other basins. b. NASA SMAP wind radii estimates Wind radii estimates from SMAP (described below) have been incorporated into the OBTK guidance. These near real-time estimates are being produced by Remote Sensing Systems (Meissner et al., 2017) and ingested into the ATCF. Data from another L-band radiometer onboard the Soil Moisture and Ocean Salinity (SMOS) satellite, as well as the NASA Cyclone Global Navigation Satellite System (CYGNSS) mission, are being evaluated for potential incorporation into the OBTK as well. c. SHIPS wind radii R34/50/64 wind radii estimates based on SHIPS statistical-dynamical data (Knaff et al., 2017) were added to ATCF, and these estimates have been incorporated into the Wind Radii Consensus (RVCN) forecast wind radii consensus (aid name is DSHA). SHIPS computes these estimates using track, intensity and diagnostic information from the GFS model, as well as IR imagery. The routine availability of SHIPS radii provides additional stability to the RVCN, particularly for R50/64, and overall SHIPS wind radii bias is less than numerical weather prediction aids. 110

112 d. Objective ASCAT fix generation The ATCF upgrade included an objective, scatterometry-based, R34 estimate algorithm implemented by NRL-MRY. Since becoming operational, this routine has produced nearly 250 automated R34 estimates, which have contributed to improvements in objective, best track, wind radii estimates described in the next section, particularly for cases with limited consensus members (e.g., early in the TC lifecycle), adding stability to OBTK estimates. Sampson et al. (2018) estimated R34 root mean square error when scatterometry data is available to be 17 nm, equivalent to 15% of mean R34, and higher without these data. Figure 5-4. Example objective scatterometry estimate (dashed line) versus OBTK (blue line) and working best track estimate (green line) for Typhoon Goni, WP e. Objective best track wind radii (OBTK) Analyzed TC structure parameters (e.g. R34/50/64) are critical numerical weather prediction inputs, and form the basis for subsequent forecast wind radii values that are used to generate the swath of potential 34 knot winds depicted on JTWC warning graphics, as well as TCCOR setting guidance, wind probabilities and wave forecasts. Due to infrequent and/or incomplete scatterometer overpasses and the lack of in-situ observational data throughout the JTWC area of responsibility, TC structure analysis has a high degree of uncertainty, resulting in a documented historical small bias for large TCs and frequent step function-like growth in the non-quality controlled, operational best track wind radii data. A non-weighted average of R34 estimates (OBTK; Sampson et al. 2017), developed using AMSU estimates (Demuth et al. 2004), multi-platform TC surface wind analyses (CIRW; Knaff et al. 2011), Dvorak wind radii estimates (DVRK; Knaff et al. 2016), automated NRL- MRY ASCAT estimates, and 6-hour numerical weather prediction forecasts (Sampson et al. 2017), became operational with the upgrade to ATCF. Verification for (Figure 5-5) indicates the OBTK has lower mean errors than any of the individual members of the consensus, greatly reducing the previously-observed small bias, and resulted in smooth R34 growth curves. The OBTK in ATCF provides typhoon duty officers pre-filled, first-guess R34 estimates which streamlines the production process. 111

113 Figure knot wind radii estimate mean errors (brown) and biases (blue) relative to JTWC best tracks coincident with ASCAT. Standard error is indicated by the black error bars that overlap the means. f. Forecast wind radii consensus (RVCN) The NRL-MRY continued to refine RVCN and in 2017 added SHIPS-based estimates. Current RVCN members are listed in table 5-3. Retrospective tests of the 2017 version of the RVCN on data indicates improvement between 5-10% over the previous version beyond tau 48, with decreased positive bias. Mean average error increases from approximately 20% of mean R34 at tau 24 to about 30% at tau 120. The addition of new or improved model guidance to supplement the limited skill, current, numerical weather prediction wind radii guidance remains a top priority. The UKMET office announced (J. Heming, personal communication) that its global deterministic model will begin outputting wind radii in ATCF A-deck format beginning July 25, These data will be evaluated for potential future addition into the RVCN. Finally, a wind radii GPCE for RVCN has been implemented in ATCF to provide statistical confidence information based on the consensus spread (figure 5-6). Further details about operational use of RVCN and OBTK guidance can be found in Strahl et al. (2018). Additionally, the JTWC will contribute more detailed information on operational TC wind structure analysis and forecasting at the upcoming WMO 9th International Workshop on TCs. Current RVCN members AHNI HHFI EMXI CHTI DSHA Table 5-3. Primary objective aids comprising the operational JTWC TC wind radii consensus (RVCN) (as of July 2018). 112

114 Figure RVCN performance (western North Pacific) versus OBTK using NRL-MRY ASCAT. Figure 5-7. Tau R34 forecast (blue solid line) and 67th percentile (blue dashed) by quadrant for Typhoon Lionrock, Best track R34 shown as black solid line. 113

115 g. Dynamically sized swath of potential gale force winds The swath of potential 34 knot winds that accompanies the JTWC TC forecasts, also known as the 34 knot wind danger area, is a function of TC forecast wind radii and the JTWC s five-year average forecast track errors. A dynamically-sized swath that adjusts the radius by the ratio of GPCE climatology to GPCE was tested in 2015 (Strahl et al. 2016). This study indicated that applying the traditional GPCE method yielded the JTWC swath sizes that were appropriately scaled in high certainty scenarios. However, in cases of very high uncertainty, the swath size could become unrealistically large. Another undesirable effect is that across-track swath radius was increased even for cases in which consensus spread was predominately a result of along-track speed differences. Beginning in 2018, two follow-on iterations of the dynamically-sized swath work will be evaluated for potential implementation into operations. The first utilizes the earlier GPCE-based swath work and incorporates an adjustment to swath growth for along-track speed uncertainty, while the second approach tests the applicability of the 5% R34 wind probability contour as the swath definition (DeMaria et al., 2013). If successful, the later technique would provide customers a probabilistic, situation-based swath that maintains dependence on the GPCE information used in the existing wind probability code. Finally, an update to the wind probability code implemented at the JTWC in July 2018 adds decay effects over land (figure 5-8). The current, operational swath does not account for over-land decay, but establishing this dependence in an updated 34 knot wind swath is highly desirable. Figure 5-8. Example wind probability graphic with (right) and without (L) over-land decay. 114

116 3. Data exploitation/applications of environmental satellite data a. MK-IVB MK-IVB is the JTWC s primary software for displaying and analyzing meteorological satellite imagery. The JTWC improved and expanded various applications of MK-IVB software throughout 2017, developing multiple enhancements for imagery regularly referenced by Satellite Analysts and forecasters, integrating TC position estimates into the main display, improving the quality of stormcentered images provided to customers, and designing new processes to distribute formatted imagery generated in MK-IVB to other data analysis platforms. With excellent support from Lockheed Martin s system development team, the command's Technical Services Department developed the capability to produce tailored, satellite imagery overlays in MK-IVB for display in ATCF. With this capability, storm-centered imagery with unique enhancements highlighting key TC structural features, such as rain bands and eyewalls, can be designed and generated in MK-IVB as well as uploaded into ATCF at the JTWC. This capability enables Satellite Analysts and Typhoon Duty Officers to more accurately estimate TC position, intensity and wind radii using high-quality imagery from MK-IVB alongside observational and model-based datasets already available in ATCF. A prototype automation process and associated imagery enhancement will be developed in b. NASA SMAP radiometer wind data In 2017, JTWC began ingesting near-real time 10-min maximum-sustained wind data from the SMAP L-band (Meissner et al., 2017 and 2018). SMAP sea surface wind data are produced by Remote Sensing Systems and sponsored by NASA Earth Science funding. Forecasters can visualize SMAP winds in ATCF and fuse with other available data or best track information. The authors note that while the horizontal resolution is somewhat less than other active and passive microwave satellite sensors and with slightly higher root mean square, SMAP winds have been shown to accurately quantify open-ocean wind speeds up to 70 m/s (136 knots), without experiencing the degree of rainfall-induced signal attenuation that limits measurements from other sensors. SMAP provides a unique capability for the JTWC forecasters who rely on the Dvorak technique for intensity estimation due to the lack of aerial reconnaissance. Figure 5-9. Example SMAP winds displayed in ATCF for Tropical Cyclone Gita. Red pixels indicate winds in excess of 64 knots. A few periwinkle pixels within the R64 indicate winds in excess of 100 knots. 115

117 c. Proxy visible satellite imagery The JTWC relies on geo-stationary satellite imagery from the Himawari-8 satellite to perform reconnaissance of TCs in the western Pacific Ocean. However, the absence of EO imagery at night significantly limits the amount of information available to forecasters due to limits of existing nighttime, low-level cloud products. The Cooperative Institute for Research in the Atmosphere (CIRA) utilized the next-generation imager available on the newly operational GOES-16 satellite to develop IR imagery enhancements that simulate visible imagery and provide forecasters higher quality data throughout the nighttime hours (Chirokova et al., 2018). Because the Himawari-8 sensor contains the same set of channels as the GOES-16, this methodology can be adapted for the JTWC in the western Pacific basin. The JTWC is pursuing funding to facilitate adding proxy visible Himawari-8 data to the CIRA online visualization website (SLIDER) for further evaluation. Pending final evaluation, this capability may be transitioned to the MK-IVB or FMQ-17 platforms. d. Estimation of TC intensity from microwave satellite imagery Analysts at tropical forecasting agencies, including the JTWC, have manually estimated TC intensity using EO and IR satellite imagery for decades, primarily following guidelines established by Dvorak (1984). However, no analogous technique for manually analyzing microwave frequency imagery is currently applied at the JTWC. Forecasters anecdotally note that various structural features become evident in high-resolution, microwave, satellite imagery as TC intensity changes. Whether it is possible to develop a method for estimating TC intensity through subjective analysis of these structural features, analogous to the Dvorak Technique, is the subject of ongoing study. From mid-2017 through early 2018, the command's Technical Services Department collaborated with Air Force Institute of Technology (AFIT) student Capt. Matthew Perkins, who successfully completed a Master s thesis exploring the viability of manually estimating TC intensity using microwave satellite imagery. In his study, Capt. Perkins applied an imagery compositing technique to identify convective banding patterns, evident in GHz microwave channels, that may distinguish higher intensity from lower intensity typhoons. He further proposed a methodology to formulate subjective TC intensity estimates for cyclones using microwave imagery (Perkins 2018). This research established a prototype for future operational testing and laid the groundwork for follow-on study. 4. TC track improvement: improved and extended TC forecast track guidance a. TC track consensus (CONW) The NRL-MRY and JTWC annually review performance and reliability of various U.S. and international agency models to assess sensitivity of CONW accuracy to each member and to optimize overall accuracy of the consensus. The USAF GALWEM model (AFUM) replaced the JMA TC ensemble mean track forecasts (JENI) in the CONW track forecast consensus Current members are listed in table

118 Model CONW Tracker Model Type NAVGEM GALWEM GFS UKMET Office Global Model JMA Global Spectral Model ECMWF Global Model COAMPS-TC HWRF GEFS ECMWF EPS NVGI AFUI AVNI EGRI JGSI ECMI CTCI HWFI AEMI EEMI Global Global Global Global Global Global Mesoscale Mesoscale Ensemble Ensemble Table 5-4. Primary objective aids comprising the operational JTWC tropical cyclone track (CONW) consensus (as of July 2018). In addition to the CONW forecast models, JTWC evaluates TC track forecasts from ACCESS- TC, TWRF, CMC, ARPEGE, MEPS and the UK Met Office global ensemble (MOGREPS). A COAMPS-TC ensemble is expected to be available to JTWC forecasters beginning in late b. Trajectory Climatology and Persistence (CLIPER) model (TCLP) In 2017, the 7-day TCLP model developed at CIRA was added to ATCF for the western North Pacific. TCLP is a baseline forecast skill assessment tool for TC track and intensity. While not directly contributing to forecast improvement, the 7-day TCLP will allow the JTWC to assess model performance and forecast skill out to longer lead times, a necessary step toward the future capability to extend the JTWC forecast period to 168 hours. c. Time of arrival graphic The NHC operationalized new probability-based graphics denoting the earliest reasonable and most likely time of arrival of tropical storm force winds in At the 2018 PACOM Joint TC Forecast Program Assembly (JTCFPA), the Central Pacific Hurricane Center presented a brief describing their upcoming adaptation of these new products. Based on customer feedback, the JTWC is planning to implement this product in The time of arrival graphic generation code was kindly supplied by the NHC Technology & Science Branch. More information on this product is available from 117

119 Figure Example NHC time of arrival graphic 5. TC genesis timing and forecasts a. Two week TC formation outlooks The JTWC continued to provide weekly input to the Climate Prediction Center s Global Tropics Hazards / Benefits Outlook throughout Additionally, the JTWC finalized plans for operational transition of a two week TC forecasting process highlighted in the 2014 Annual Tropical Cyclone Report (JTWC 2014). The JTWC Two Week TC Formation Outlooks highlight geographic areas and timeframes that forecasters consider suspect for formation of a significant TC during the upcoming 14 day period. Highlighted locations are referred to as a Potential Formation Areas (PFAs). Two Week Formation Outlooks cover the western North Pacific Ocean, Indian Ocean and South Pacific Ocean basins (central and eastern North Pacific basins are not included). The JTWC plans to distribute two types of graphical Formation Outlook products to DoD customers through the organization s TC Decision Support Portal. The JTWC Two-Week Formation Outlook graphic provides multi-basin graphic of potential formation areas. The PFA status graphic details the anticipated TC development timeline. An example of each type of graphic follows. 118

120 Figure Example Two-week TC Formation Outlook (top) and Potential Formation Area Status (bottom) graphics. Formation Outlooks will be regularly issued twice daily, with 0000Z and 1200Z valid times. They may also be reissued at any hour, on the hour, in order to maintain horizontal consistency with corresponding invest area classifications (i.e., low, medium, high or upgrade to warning status). Additional guidance to accompany the existing product suite is under development. 119

121 Section 4 Other Scientific Collaborations a. Joint Hurricane Testbed The JTWC is collaborating with principal investigators to test and evaluate two JHT funded projects. 1) Improvements to operational statistical TC intensity forecast models using wind structure and eye predictors, G. Chirokova (CSU/CIRA), John Kaplan (AOML/HRD) This project addresses TC Intensity Change (Priority #1), via the following efforts: Completing a number of upgrades to SHIPS/LGEM intensity models, the multi-lead time probabilistic RI Index (MLTRII), and the global RI Index (GRII). Adding a TC wind structure based predictor or combination of predictors. Adding a predictor or a group of predictors based on the probability of the eye existence and the code to calculate that probability. 2) Ensemble-Based Pre-Genesis Watches and Warnings for Atlantic and North Pacific TCs, Russ Elsberry (UC-CS) This project addresses TC Genesis Timing and Forecast (Priority #5), via the following efforts: Providing GEFS and ECMWF ensemble-based guidance products for the genesis timing and locations (with uncertainty measures) along ensemble storm forecast tracks that will be useful for issuing pre-genesis watches and warnings in the North Atlantic and throughout the North Pacific basin. Providing seven day intensity and intensity spread guidance products that are fully compatible with the GEFS and ECMWF ensemble-based genesis in timing and locations along the ensemble storm forecast track. b. Hurricane Forecast Improvement Project (HFIP) The JTWC has benefited significantly from work performed under the auspices of the HFIP, particularly with respect to the improvements in data assimilation, numerical TC track and intensity forecasting, RI prediction, ensemble modeling, and tropical cyclogenesis forecasting. The JTWC maintains ongoing collaborative efforts with HFIP modeling teams from NRL-MRY, NCEP and GFDL. Section 5 Scientific and Technical Exchanges Participating in national and international level meetings and conducting technical exchanges with members of the scientific community are essential to the success of the JTWC s strategic development efforts. A summary of the JTWC s 2017 conference attendance and technical exchange meetings follows. 120

122 97 th AMS Annual Meeting (Jan 2017) PACOM Joint Tropical Cyclone Forecasting Program Assembly (Feb 2017) Liaison visit by Dr. Joshua Cossuth, NRL-MRY (Feb 2017) 71 st Interdepartmental Hurricane Conference (Mar 2017) Naval Research Laboratory 6.2/6.4 Program Review (Apr 2017) TROPICS Applications Workshop (May 2017) CYGNSS Applications Workshop (Oct-Nov 2017) Liaison visit by Ms. Kate Musgrave CIRA (Oct 2017) Liaison visit by Mr. Carey Dickerman - FNMOC (Oct 2017) ATCF Annual Requirements Meeting (Nov 2017) Hurricane Forecast Improvement Program (HFIP) Annual Meeting (Nov 2017) Liaison visit by Mr. Tony Wimmers CIMSS (Dec 2017) References Bender, M.A., T.P. Marchok, C.R. Sampson, J.A. Knaff, and M.J. Morin, 2017: Impact of storm size on prediction of storm track and intensity using the 2016 operational GFDL hurricane rodel. Wea. Forecasting. 32, Chirokova, G., J. A. Knaff, and J. L. Beven, 2018: Proxy Visible Satellite Imagery. Presentation at the 98 AMS Annual Meeting, 22nd Conference on Satellite Meteorology and Oceanography, 7 11 January, 2018, Texas, Austin. DeMaria, M., J.A. Knaff, M.J. Brennan, D. Brown, R.D. Knabb, R.T. DeMaria, A. Schumacher, C.A. Lauer, D.P. Roberts, C.R. Sampson, P. Santos, D. Sharp, and K.A. Winters, 2013: Improvements to the Operational Tropical Cyclone Wind Speed Probability Model. Wea. Forecasting, 28, Demuth, J. L., DeMaria, M., Knaff, J. A., and Vonder Haar, T. H., 2004: Validation of an Advanced Microwave Sounding Unit tropical cyclone intensity and size estimation algorithm. J. Appl. Meteor., 43, Dvorak, V.F.,1984: Tropical cyclone intensity analysis using satellite data. NOAA Technical Report NESDIS 11, U.S. Department of Commerce, National Oceanographic and Atmospheric Administration, National Environmental Satellite Data and Information Service, Washington, DC, 47 pp. Joint Typhoon Warning Center, 2014: Annual Tropical Cyclone Report, 104 pp. Knaff, J. A., C. J. Slocum, K. D. Musgrave, C. R. Sampson, and B. R. Strahl, 2016: Using routinely available information to estimate tropical cyclone wind structure. Mon. Wea. Rev., 144(4),

123 Knaff, J. A., C.R. Sampson, and G. Chirokova, 2017: A global statistical dynamical tropical cyclone wind radii forecast scheme. Wea. Forecasting, 32(2), Knaff, J.A., C.R. Sampson, and K.D. Musgrave, 2018: An operational rapid intensification prediction aid for the western North Pacific. Wea. Forecasting, 33(3), Knaff, J.A., M. DeMaria, D. Molenar, C.R. Sampson, and M.G. Seybold, 2011: An automated, objective, multiple-satellite-platform tropical cyclone surface wind analysis. J. Appl. Meteor. Climatol., 50, Meissner, T., L. Ricciardulli, and F. Wentz, 2018: Remote Sensing Systems SMAP daily Sea Surface Winds Speeds on 0.25 deg grid, Version [NRT or FINAL]. Remote Sensing Systems, Santa Rosa, CA. Available online at Meissner, T., L. Ricciardulli, and F.J. Wentz, 2017: Capability of the SMAP mission to measure ocean surface winds in storms. Bull. Amer. Meteor. Soc., 98, Perkins, M.W., 2018: Methodology to analyze tropical cyclone intensity from microwave imagery. Master s thesis, Air Force Institute of Technology, Wright-Patterson AFB, OH, 96 pp. Sampson, C.R. and A.J. Schrader, 2000: The Automated Tropical Cyclone Forecasting System (version 3.2). Bull. Amer. Meteor. Soc., 81, Sampson, C.R., E.M. Fukada, J.A. Knaff, B.R. Strahl, M.J. Brennan, and T. Marchok, 2017: Tropical cyclone gale wind radii estimates for the western North Pacific. Wea. Forecasting, 32, Sampson, C. R., J. S. Goerss, J. A. Knaff, B. R. Strahl, E. M. Fukada, E. A. Serra, 2018: Tropical cyclone gale wind radii estimates, forecasts and error forecast for the western North Pacific, Wea. Forecasting, in press Strahl, B.R., Sampson, C.R, and J. Knaff, 2018: Joint Typhoon Warning Center 5-day operational tropical cyclone wind radii. Oral presentation, 33 rd Conference On Hurricanes and Tropical Meteorology, Punta Vedra, FL, Amer. Meteor. Soc. Strahl, B.R., Sampson, C.R. and J. Tracey, 2016: Evaluation of an experimental potential gale force wind swath using GPCE to account for JTWC forecast confidence. Preprints, 32 nd Conf. on Hurr. and Trop. Meteor., San Juan, PR, Amer. Meteor. Soc. Wimmers, A., D. Herndon and J. Kossin, 2018: Improved eyewall replacement cycle forecasting using a modified microwave-based algorithm (ARCHER). Joint Hurricane Testbed, Accessed 1 August 2018, 122

124 Chapter 6 Summary of Forecast Verification Verification of warning position and intensities at 24, 48, 72, 96 and 120-hour forecast periods are made against the final best track. The (scalar) track forecast, along and cross track errors were calculated for each verifying JTWC forecast (illustrated in Figure 6-1), included in this chapter. This section summarizes verification data for the 2017 season and contrasts it with annual verification statistics from previous years. Figure 6-1. Definition of cross track error (XTE), along track error (ATE), and forecast track error (FTE). In this example, the forecast position is ahead of and to the right of the verifying best track position. Therefore, the XTE is positive (to the right of track) and the ATE is positive (ahead of the best track). Adapted from Tsui and Miller (1988). 123

125 Section 1 Annual Forecast Verification 124

126 Figure 6-2. JTWC forecast errors and five year running mean errors for the western North Pacific at 24, 48 and 72 hours. Figure 6-3. JTWC forecast errors and five year running mean errors for the western North Pacific at 96 and 120 hours. 125

127 126

128 Figure 6-4. JTWC forecast errors and five year running mean errors for the north Indian Ocean at 24, 48, 72, 96 and 120 hours. (Note: No 96 HR, 120 HR data for 2012) 127

129 128

130 Figure 6-5. JTWC forecast errors for the Southern Hemisphere at 24, 48, 72, 96, and 120 hours. 129

131 Figure 6-6. JTWC intensity forecast errors for the western North Pacific at 24, 48, 72, 96 and 120 hours. 130

132 Figure 6-7. JTWC intensity forecast errors for the North Indian Ocean at 24, 48, 72, 96, and 120 hours. (Note: No 96 HR, 120 HR data for 2012) 131

133 Figure 6-8. JTWC intensity forecast errors for the Southern Hemisphere at 24, 48, 72, 96 and 120 hours. 132