OSSE OSE activities with Multivariate Ocean VariationalEstimation (MOVE)System. II:Impacts ofsalinity and TAO/TRITON.
|
|
|
- Gerard Parrish
- 5 years ago
- Views:
Transcription
1 G ODAE/O O P O SSE O SE m eeting,nov.5 7th,2007 in IO,Paris OSSE OSE activities with Multivariate Ocean VariationalEstimation (MOVE)System. II:Impacts ofsalinity and TAO/TRITON. S.Matsumoto,Y.Fujii,T.Soga,T.Yasuda,S.Ishizaki,N.Usui,and M. Kamachi (MOVE/MRI.OM group) Japan MeteorologicalAgency (JMA)/ MeteorologicalResearch Institute (MRI) Outline 2. Ocean data assimilation system in MRI 3. Impact of salinity 4. Impact of Argo 5. Impact of TAO/TRITON 6. Summary
2 1. Ocean data assimilation system in MRI
3 MOVE System MOVE/MRI.OM Multivariate Ocean VariationalEstimation (MOVE)System Ocean Data Assimilation System in MRI/JMA. Model TS fields are corrected by IAU. Variational Q Scheme for avoiding density inversion
4 Kuroshio Prediction with MOVE-WNP The current Kuroshio prediction system in JMA (OMPASS-K) will be replaced with MOVE-WNP next April. Prediction of Kuroshio meandering in 2004 Real state (assimilation) Growth of SSH RMSE in prediction south of Japan Prediction Mean SSHvariability south of Japan (15.3cm)
5 ENSO Forecast with MOVE-G AThe of 10ENSO member ensemble forecast 10 forecasting NINO3.4A NINO3.4A(Saha system in JMA will benep replaced next April. et al MOVE-G provides initial state of the Ocean for the coupled model in the next system. SST Anomaly Initial: 1997/03/02 Real Forecast The NINO3.4 forecast score is similar to the system of NEP
6 2. Impact of salinity
7 Experimental onfiguration Purpose MOVE system corrects model salinity field using temperature and SSH observation as well as salinity observation through oupled T-S EOF. The purpose is evaluating the impact of the salinity correction. Experiment TL: Standard result the MOVE system. NOS: Assimilation run without the correction of the model salinity field. (All other conditions are the same as TL.) The both experimental runs are performed using MOVE-G and MOVE-NP.
8 Impact to the near-surface T at the Eq. Pac. TL Difference (TL NOS) of Heat content in the water warmer than 28 (cal/cm2) at the equator. PSU NOS PSU T (contour) and S (color) in the vertical section in the Eq. Pac. in Sep Salinity affects (through density) temperature!
9 Impact on the subarctic gyre (MOVE-NP) mean acceleration potential on 26.5σθ surface TL NOS The subarctic circulation (Oyashio current) is intensified in the run with salinity correction (TL).
10 3. Impact of Argo
11 Impacts on 0-300m averaged T (OH) in MOVE-G ALL - NoArgo ALL 2001 Assimilation result with Argo float NoArgo Assimilation result without Argo floats As floats increases, the difference between the two cases becomes larger. Differences are relatively small in the equatorial Pacific, probably due to existence of TAO/TRITON buoys. Differences are larger in the Indian Ocean, where other data are very sparse.
12 Time series of 0-300/0-700 averaged T in MOVE-G Tropical Pacific (10S-10N, 120E-80W) 0-300m 18.8 Indian Ocean (50S-20N, 30E-110E) m m OH has larger difference than 300m between ALL and NOARGO. (TAO moorings observe top 500m.) NOARGO Few Argo data ALL Both 700m and 300m OH has larger difference than in Tropical Pacific. (Almost all in-situ data are Argo.) Argo data causes a data gap.
13 Impact on the Oyashio (MOVE-WNP) Assimilation result, 100mT ALL NOAA/AVHRR(12 19 ) NoArgo NOAA/AVHRR(1 19 )
14 Impact on the Kuroshio prediction Prediction (Initial: 01May2004) SSH ALL m NoArgo m Assimilation m
15 4. Impact of TAO/TRITON
16 Experimental onfiguration Purpose Evaluating the impact of TAO/TRITON after 2000 when ARGO- float observation is started. Outline ALL: Standard result of MOVE-G with TAO/TRITON. JRA25 is used for forcing data. Period: ) TAO/TRITON wind data is already included in JRA25. NTT: Assimilation run started from the result at the beginning of 2000 in the standard run without TAO/TRITON. Forecast 13-month Five-member ensemble forecasts. The initial state of an ensemble member is one of the last five days in the month. (LAF Method)
17 Forecast, Analysis, assimilation ycle in MOVE-G Past Day0 Observation Day30 Future Day20 Day10 Observation Observation 5-day Forecast Forecast 3DVAR Assimilation Assimilation Forecast 3DVAR 3DVAR Assimilation Q and generating super observation (Observation data at the same position is combined.) Hourly data of TAO/TRITON is averaged in 10 days before 3DVAR. We cannot take advantage of high time-resolution of TAO/TRITON.
18 Increase of observed profiles with ARGO floats Jan TAO/TRITON ARGO Others (XBT, TD) Jan. 2006
19 Decrease of the impact of TAO/TRITON Lon.-Time Section of 100m Temp. at the equator Impact is decreasing.
20 Temperature climatology in the equatorial Pacific Shade Anomaly (ALL-NTT), ontour NTT Increase of Argo
21 Snapshot of T differences in the Eq. 10-day mean increase the vertical gradient Deepening the thermocline 13Oct May Apr Jan.2001 The impact of assimilating TAO/TRITON is different from different times. Increase the horizontal gradient Shallowing the thermocline TAO/TRITON data is essential for reproducing accurate 25Jun.2004 variability of the thermocline. 06Jun Feb May2000
22 Salinity climatology in the equatorial Pacific Shade anomaly (ALL-NTT), ontour NTT PSU PSU Increase of ARGO
23 limatology of the barrier layer thickness Shade anomaly (ALL-NTT), ontour NTT m
24 Snapshot of the current field at 170W Zonal Obs. ALL NTT Meridional 2002/06/15-06/24
25 Examples of NINO3.4 forecasts ALL NTT ALL NTT Spread is larger with TAO/TRION (?) Solid line Ensemble mean, Dotted Line Forecast of each member Red from Oct., Blue from Jan., Green: from Apr.
26 Difference of the equatorial temp. (Ensemble mean) Initial: Oct.2001 Vertical section of ALL-NTT at the Eq. Lower thermocline: cold anomaly La Nina-like? Upper thermocline: warm anomaly west wind burst El-Nino-like?
27 Difference of the equatorial temp. (Ensemble mean) Initial: Oct.2004 Vertical section of ALL-NTT at the Eq. Lower thermocline: cold La Nina-like? Upper thermocline: warm burst (Background T is low?)
28 Non-deterministic evolution of the initial difference Initial: Z20 SST ALL-NTT Initial: SST Z20 Evolution of each members are not always the same as the ensemble mean. Impact of TAO/TRITON is not deterministic.
29 5. Summary
30 Impact of Salinity and Argo floats Impact of correcting model salinity field using observation. Improve the near-surface temperature field in the equatorial Pacific. Essential for the density and current fields in subarctic gyres. Impact of Argo floats The impact is relatively small in the equatorial Pacific because of TAO/TRITON. There is large improvement in the Indian Ocean. But Argo data causes data gap around Argo floats also affect the expression of the Kuroshio meandering and Oyashio water. (We need more experiments in order to confirm that Argo data improves the results.)
31 Impact of TAO/TRITON Impact in the data assimilation system In average, the thermocline is sharpened in the central equatorial pacific. But the effect is not always the same. (Deepening, shallowing, sharpening, etc.) TAO/TRITON is necessary for accurate reproduction of the thermocline variability. Impact in the ENSO forecast We need more ensemble members to evaluate the effect of TAO/TRITON on the forecast result. Spread becomes larger with TAO/TRITON (?) Results of OSE depends on the model, and data assimilation scheme. OSE should be performed with multi systems
32 Thank you.
ENSO Outlook by JMA. Hiroyuki Sugimoto. El Niño Monitoring and Prediction Group Climate Prediction Division Japan Meteorological Agency
ENSO Outlook by JMA Hiroyuki Sugimoto El Niño Monitoring and Prediction Group Climate Prediction Division Outline 1. ENSO impacts on the climate 2. Current Conditions 3. Prediction by JMA/MRI-CGCM 4. Summary
JMA s Seasonal Prediction of South Asian Climate for Summer 2018
JMA s Seasonal Prediction of South Asian Climate for Summer 2018 Atsushi Minami Tokyo Climate Center (TCC) Japan Meteorological Agency (JMA) Contents Outline of JMA s Seasonal Ensemble Prediction System
Background of Symposium/Workshop Yuhei Takaya Climate Prediction Division Japan Meteorological Agency
Background of Symposium/Workshop Yuhei Takaya ytakaya@met.kishou.go.jp Climate Prediction Division Japan Meteorological Agency 1 Long-Range Forecast, Tokyo Japan, 8-10 December Outline Background of Dynamical
Development of a coastal monitoring and forecasting system at MRI/JMA
COSS-TT and ARCOM Development of a coastal monitoring and forecasting system at MRI/JMA N. USUI, Y. Fujii, K, Sakamoto, H. Tsujino, T. Kuragano & Masa KAMACHI Meteorological Research Institute, Japan Sept
Ocean data assimilation systems in JMA and their representation of SST and sea ice fields
SST-WS, Jan. 6 th, 2018, ECMWF, Reading, UK Ocean data assimilation systems in JMA and their representation of SST and sea ice fields Yosuke Fujii 1, Takahiro Toyoda 1, Norihisa Usui 1, Nariaki Hirose
Recent Development of Ocean Data Assimilation Systems and Recent Observing System Evaluation Studies in JMA/MRI
GOV DA-TT & OSEval TT MT 2017, Oct. 13 th, 2017, La Spezia, Italy Recent Development of Ocean Data Assimilation Systems and Recent Observing System Evaluation Studies in JMA/MRI Yosue Fujii, Norihisa Usui,
Evaluation of Tropical Pacific Observing Systems Using NCEP and GFDL Ocean Data Assimilation Systems
Evaluation of Tropical Pacific Observing Systems Using NCEP and GFDL Ocean Data Assimilation Systems Y. Xue 1, C. Wen 1, X. Yang 2, D. Behringer 1, A. Kumar 1, G. Vecchi 2, A. Rosati 2, R. Gudgel 2 1 NCEP/NOAA,
Tropical Indian Ocean Observing System - Present Status and Highlights of 2006 IOD -
Tropical Indian Ocean Observing System - Present Status and Highlights of 2006 IOD - Takanori Horii, Hideaki Hase, Iwao Ueki, Kentarou Ando, Yosifumi Kuroda,Kunio Yoneyama, Keisuke Mizuno Institute of
Interpretation of Outputs from Numerical Prediction System
Interpretation of Outputs from Numerical Prediction System Hiroshi OHNO Tokyo Climate Center (TCC)/ Climate Prediction Division of Japan Meteorological Agency (JMA) Procedure of Seasonal Forecast (1) 1.
Hiromichi Igarashi 1,2, Y. Ishikawa 1, T. Wakamatsu 1, Y. Tanaka 1, M. Kamachi 1,3, N. Usui 3, M. Sakai 4, S. Saitoh 2 and Y.
PICES2015,Qingdao Oct.20,2015 Relationships between ocean conditions and interannual variability of habitat suitability index (HSI) distribution for neon flying squid in central North Pacific examined
Winter Forecast for GPC Tokyo. Shotaro TANAKA Tokyo Climate Center (TCC) Japan Meteorological Agency (JMA)
Winter Forecast for 2013 2014 GPC Tokyo Shotaro TANAKA Tokyo Climate Center (TCC) Japan Meteorological Agency (JMA) NEACOF 5, October 29 November 1, 2013 1 Outline 1. Numerical prediction 2. Interannual
ECMWF: Weather and Climate Dynamical Forecasts
ECMWF: Weather and Climate Dynamical Forecasts Medium-Range (0-day) Partial coupling Extended + Monthly Fully coupled Seasonal Forecasts Fully coupled Atmospheric model Atmospheric model Wave model Wave
Data Assimilation of Argo Profiles in Northwest Pacific Yun LI National Marine Environmental Forecasting Center, Beijing
Data Assimilation of Argo Profiles in Northwest Pacific Yun LI National Marine Environmental Forecasting Center, Beijing www.nmefc.gov.cn National Marine Environmental Forecasting Center Established in
Global Ocean Monitoring: Recent Evolution, Current Status, and Predictions
Global Ocean Monitoring: Recent Evolution, Current Status, and Predictions Prepared by Climate Prediction Center, NCEP November 6, 2009 http://www.cpc.ncep.noaa.gov/products/godas/ This project to deliver
Lab 12: El Nino Southern Oscillation
Name: Date: OCN 104: Our Dynamic Ocean Lab 12: El Nino Southern Oscillation Part 1: Observations of the tropical Pacific Ocean during a normal year The National Oceanographic and Atmospheric Administration
Ocean Observations for an End-to-End Seasonal Forecasting System
Ocean Observations for an End-to-End Seasonal Forecasting System Magdalena A. Balmaseda Yosuke Fujii Oscar Alves Tong Lee Michele Rienecker Tony Rosati Detlef Stammer Yan Xue Howard Freeland Michael McPhaden
The Oceanic Component of CFSR
1 The Oceanic Component of CFSR Yan Xue 1, David Behringer 2, Boyin Huang 1,Caihong Wen 1,Arun Kumar 1 1 Climate Prediction Center, NCEP/NOAA, 2 Environmental Modeling Center, NCEP/NOAA, The 34 th Annual
Ocean Reanalysis and its Application to Water Mass Analyses in the Pacific
Ocean Reanalysis and its Application to Water Mass Analyses in the Pacific Masafumi Kamachi 1, Satoshi Matsumoto 1, Toshiya Nakano 1, Yosuke Fujii 1, Norihisa Usui 1, and Tamaki Yasuda 2 1 Oceanographic
GODAE Ocean View Activities in JMA (and Japan)
GOVST VIII, Nov. 6 th, 2017, Bergen, Norway GODAE Ocean View Activities in JMA (and Japan) Yosuke Fujii 1, Norihisa Usui 1, Takahiro Toyoda 1, Nariaki Hirose 1, Hiromichi Igarashi 2, and Japan GODAE group
Applications of an ensemble Kalman Filter to regional ocean modeling associated with the western boundary currents variations
Applications of an ensemble Kalman Filter to regional ocean modeling associated with the western boundary currents variations Miyazawa, Yasumasa (JAMSTEC) Collaboration with Princeton University AICS Data
From El Nino to Atlantic Nino: pathways as seen in the QuikScat winds
From El Nino to Atlantic Nino: pathways as seen in the QuikScat winds Rong Fu 1, Lei Huang 1, Hui Wang 2 Presented by Nicole Smith-Downey 1 1 Jackson School of Geosciences, The University of Texas at Austin
Atmospheric circulation analysis for seasonal forecasting
Training Seminar on Application of Seasonal Forecast GPV Data to Seasonal Forecast Products 18 21 January 2011 Tokyo, Japan Atmospheric circulation analysis for seasonal forecasting Shotaro Tanaka Climate
ENSO UPDATE By Joseph D Aleo, CCM
ENSO UPDATE By Joseph D Aleo, CCM El Nino is still hanging on but likely not for very long. Warmer than normal water can still be seen along the equator in the tropical Pacific. It is even warmer in the
How DBCP Data Contributes to Ocean Forecasting at the UK Met Office
How DBCP Data Contributes to Ocean Forecasting at the UK Met Office Ed Blockley DBCP XXVI Science & Technical Workshop, 27 th September 2010 Contents This presentation covers the following areas Introduction
Masa Kamachi JAMSTEC/CEIST
Drift simulation of Japan Tsunami Marine Debris (JTMD) as an application of data assimilation 4F.1 Masa Kamachi JAMSTEC/CEIST H. Kawamura, Y. Ishikawa, N. Usui (JAEA) (JAMSTEC) (MRI/JMA) N. Maximenko,
C
C 0.8 0.4 0.2 0.0-0.2-0.6 Fig. 1. SST-wind relation in the North Pacific and Atlantic Oceans. Left panel: COADS SST (color shade), surface wind vectors, and SLP regressed upon the Pacific Decadal Oscillation
El Niño: How it works, how we observe it. William Kessler and the TAO group NOAA / Pacific Marine Environmental Laboratory
El Niño: How it works, how we observe it William Kessler and the TAO group NOAA / Pacific Marine Environmental Laboratory The normal situation in the tropical Pacific: a coupled ocean-atmosphere system
GSOP Activities related to Ocean Reanalysis Intercomparison and Observing System Assessments
GSOP-9 Panel Meeting, September 18 th, 2016, 青島, 中国 GSOP Activities related to Ocean Reanalysis Intercomparison and Observing System Assessments Yosuke Fujii JMA/MRI GSOP Member GODAE OCEAN VIEW OSEval
Decadal variability in the Kuroshio and Oyashio Extension frontal regions in an eddy-resolving OGCM
Decadal variability in the Kuroshio and Oyashio Extension frontal regions in an eddy-resolving OGCM Masami Nonaka 1, Hisashi Nakamura 1,2, Youichi Tanimoto 1,3, Takashi Kagimoto 1, and Hideharu Sasaki
Coupled ocean-atmosphere ENSO bred vector
Coupled ocean-atmosphere ENSO bred vector Shu-Chih Yang 1,2, Eugenia Kalnay 1, Michele Rienecker 2 and Ming Cai 3 1 ESSIC/AOSC, University of Maryland 2 GMAO, NASA/ Goddard Space Flight Center 3 Dept.
An Introduction to Coupled Models of the Atmosphere Ocean System
An Introduction to Coupled Models of the Atmosphere Ocean System Jonathon S. Wright jswright@tsinghua.edu.cn Atmosphere Ocean Coupling 1. Important to climate on a wide range of time scales Diurnal to
Variability and trend of the heat balance in the southeast Indian Ocean
Variability and trend of the heat balance in the southeast Indian Ocean Ming Feng, CSIRO Marine & Atmospheric Research Arne Biastoch, Claus Böning, Leibniz-Institut für Meeresforschung Nick Caputi, Department
ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 23 April 2012
ENSO Cycle: Recent Evolution, Current Status and Predictions Update prepared by Climate Prediction Center / NCEP 23 April 2012 Outline Overview Recent Evolution and Current Conditions Oceanic Niño Index
The Forcing of the Pacific Decadal Oscillation
The Forcing of the Pacific Decadal Oscillation Schneider and Cornuelle, 2005 Patrick Shaw 3/29/06 Overlying Questions What processes statistically influence variability in the PDO? On what time scales
Contents of this file
Geophysical Research Letters Supporting Information for Future changes in tropical cyclone activity in high-resolution large-ensemble simulations Kohei Yoshida 1, Masato Sugi 1, Ryo Mizuta 1, Hiroyuki
Introduction of products for Climate System Monitoring
Introduction of products for Climate System Monitoring 1 Typical flow of making one month forecast Textbook P.66 Observed data Atmospheric and Oceanic conditions Analysis Numerical model Ensemble forecast
Global Ocean Monitoring: A Synthesis of Atmospheric and Oceanic Analysis
Extended abstract for the 3 rd WCRP International Conference on Reanalysis held in Tokyo, Japan, on Jan. 28 Feb. 1, 2008 Global Ocean Monitoring: A Synthesis of Atmospheric and Oceanic Analysis Yan Xue,
Masa Kamachi Japan Met. Agency/ Met. Res. Inst.
An example of operational ocean data assimilation and prediction Masa Kamachi Japan Met. Agency/ Met. Res. Inst. JMA & MRI Ocean Data Assimilation Group T. Nakano, S. Matsumoto, N. Usui, Y. Fujii, T. Yasuda,
ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 24 September 2012
ENSO Cycle: Recent Evolution, Current Status and Predictions Update prepared by Climate Prediction Center / NCEP 24 September 2012 Outline Overview Recent Evolution and Current Conditions Oceanic Niño
11/24/09 OCN/ATM/ESS The Pacific Decadal Oscillation. What is the PDO? Causes of PDO Skepticism Other variability associated with PDO
11/24/09 OCN/ATM/ESS 587.. The Pacific Decadal Oscillation What is the PDO? Causes of PDO Skepticism Other variability associated with PDO The Pacific Decadal Oscillation (PDO). (+) ( ) EOF 1 of SST (+)
the 2 past three decades
SUPPLEMENTARY INFORMATION DOI: 10.1038/NCLIMATE2840 Atlantic-induced 1 pan-tropical climate change over the 2 past three decades 3 4 5 6 7 8 9 10 POP simulation forced by the Atlantic-induced atmospheric
ENSO prediction using Multi ocean Analysis Ensembles (MAE) with NCEP CFSv2: Deterministic skill and reliability
The World Weather Open Science Conference (WWOSC 2014) 16 21 August 2014, Montreal, Canada ENSO prediction using Multi ocean Analysis Ensembles (MAE) with NCEP CFSv2: Deterministic skill and reliability
Patterns and impacts of ocean warming and heat uptake
Patterns and impacts of ocean warming and heat uptake Shang-Ping Xie Scripps Inst of Oceanography, UCSD Ocean warming & circulation change Ocean heat uptake & meridional overturning circulation Global
Twentieth-Century Sea Surface Temperature Trends M.A. Cane, et al., Science 275, pp (1997) Jason P. Criscio GEOS Apr 2006
Twentieth-Century Sea Surface Temperature Trends M.A. Cane, et al., Science 275, pp. 957-960 (1997) Jason P. Criscio GEOS 513 12 Apr 2006 Questions 1. What is the proposed mechanism by which a uniform
Initial Results of Altimetry Assimilation in POP2 Ocean Model
Initial Results of Altimetry Assimilation in POP2 Ocean Model Svetlana Karol and Alicia R. Karspeck With thanks to the DART Group, CESM Software Development Group, Climate Modeling Development Group POP-DART
ALASKA REGION CLIMATE OUTLOOK BRIEFING. July 20, 2018 Rick Thoman National Weather Service Alaska Region
ALASKA REGION CLIMATE OUTLOOK BRIEFING July 20, 2018 Rick Thoman National Weather Service Alaska Region Today s Outline Feature of the month: 2018 Wildfire Season Update Climate Forecast Basics Climate
Introduction of climate monitoring and analysis products for one-month forecast
Introduction of climate monitoring and analysis products for one-month forecast TCC Training Seminar on One-month Forecast on 13 November 2018 10:30 11:00 1 Typical flow of making one-month forecast Observed
JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 108, NO. C9, 3297, doi: /2002jc001745, 2003
JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 108, NO. C9, 3297, doi:10.1029/2002jc001745, 2003 Three-dimensional analysis of temperature and salinity in the equatorial Pacific using a variational method with
Evaluating Ocean Wind Products for Short-range Forecast Analyses of Wind-Driven Surface Currents
OVWST Meeting November, p. Evaluating Ocean Wind Products for Short-range Forecast Analyses of Wind-Driven Surface Currents John T. Gunn, Kathleen Dohan, Gary S. E. Lagerloef, and Fabrice Bonjean Earth
El Niño, South American Monsoon, and Atlantic Niño links as detected by a. TOPEX/Jason Observations
El Niño, South American Monsoon, and Atlantic Niño links as detected by a decade of QuikSCAT, TRMM and TOPEX/Jason Observations Rong Fu 1, Lei Huang 1, Hui Wang 2, Paola Arias 1 1 Jackson School of Geosciences,
ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 5 August 2013
ENSO Cycle: Recent Evolution, Current Status and Predictions Update prepared by Climate Prediction Center / NCEP 5 August 2013 Outline Overview Recent Evolution and Current Conditions Oceanic Niño Index
ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 25 February 2013
ENSO Cycle: Recent Evolution, Current Status and Predictions Update prepared by Climate Prediction Center / NCEP 25 February 2013 Outline Overview Recent Evolution and Current Conditions Oceanic Niño Index
Probabilistic predictions of monsoon rainfall with the ECMWF Monthly and Seasonal Forecast Systems
Probabilistic predictions of monsoon rainfall with the ECMWF Monthly and Seasonal Forecast Systems Franco Molteni, Frederic Vitart, Tim Stockdale, Laura Ferranti, Magdalena Balmaseda European Centre for
ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 11 November 2013
ENSO Cycle: Recent Evolution, Current Status and Predictions Update prepared by Climate Prediction Center / NCEP 11 November 2013 Outline Overview Recent Evolution and Current Conditions Oceanic Niño Index
ALASKA REGION CLIMATE OUTLOOK BRIEFING. December 22, 2017 Rick Thoman National Weather Service Alaska Region
ALASKA REGION CLIMATE OUTLOOK BRIEFING December 22, 2017 Rick Thoman National Weather Service Alaska Region Today s Outline Feature of the month: Autumn sea ice near Alaska Climate Forecast Basics Climate
ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 15 July 2013
ENSO Cycle: Recent Evolution, Current Status and Predictions Update prepared by Climate Prediction Center / NCEP 15 July 2013 Outline Overview Recent Evolution and Current Conditions Oceanic Niño Index
Decadal predictability of tropical Indo-Pacific Ocean temperature trends due to anthropogenic forcing
Decadal predictability of tropical Indo-Pacific Ocean temperature trends due to anthropogenic forcing CCSM3 DJF A1B Surface Temperature Trend 2018-2062 Amy Solomon and Matt Newman CIRES/University of Colorado
GFDL, NCEP, & SODA Upper Ocean Assimilation Systems
GFDL, NCEP, & SODA Upper Ocean Assimilation Systems Jim Carton (UMD) With help from Gennady Chepurin, Ben Giese (TAMU), David Behringer (NCEP), Matt Harrison & Tony Rosati (GFDL) Description Goals Products
PICES XIV (2005) in Vladivostok
PICES XIV (2005) in Vladivostok Present and future of the North Pacific simulated by a high resolution coupled atmosphere-ocean model Hiroyasu HASUMI (CCSR) Tatsuo SUZUKI (FRCGC) Takashi SAKAMOTO (FRCGC)
How far in advance can we forecast cold/heat spells?
Sub-seasonal time scales: a user-oriented verification approach How far in advance can we forecast cold/heat spells? Laura Ferranti, L. Magnusson, F. Vitart, D. Richardson, M. Rodwell Danube, Feb 2012
High Baroclinic Equatorial Kelvin Waves and Central Pacific Surface Warming
High Baroclinic Equatorial Kelvin Waves and Central Pacific Surface Warming Peter C Chu Naval Postgraduate School Monterey, CA, USA Jilin Sun and Qinyu Liu Ocean University of China Qingdao, China IUGG2003,
Primary Factors Contributing to Japan's Extremely Hot Summer of 2010
temperature anomalies by its standard deviation for JJA 2010 Primary Factors Contributing to Japan's Extremely Hot Summer of 2010 Nobuyuki Kayaba Climate Prediction Division,Japan Meteorological Agancy
Introduction of Seasonal Forecast Guidance. TCC Training Seminar on Seasonal Prediction Products November 2013
Introduction of Seasonal Forecast Guidance TCC Training Seminar on Seasonal Prediction Products 11-15 November 2013 1 Outline 1. Introduction 2. Regression method Single/Multi regression model Selection
Regional eddy-permitting state estimation of the circulation in the Northern Philippine Sea
Regional eddy-permitting state estimation of the circulation in the Northern Philippine Sea Bruce D. Cornuelle, Ganesh Gopalakrishnan, Peter F. Worcester, Matthew A. Dzieciuch, and Matthew Mazloff Scripps
The ECMWF coupled data assimilation system
The ECMWF coupled data assimilation system Patrick Laloyaux Acknowledgments: Magdalena Balmaseda, Kristian Mogensen, Peter Janssen, Dick Dee August 21, 214 Patrick Laloyaux (ECMWF) CERA August 21, 214
Introduction to Climate ~ Part I ~
2015/11/16 TCC Seminar JMA Introduction to Climate ~ Part I ~ Shuhei MAEDA (MRI/JMA) Climate Research Department Meteorological Research Institute (MRI/JMA) 1 Outline of the lecture 1. Climate System (
Seasonal Climate Watch February to June 2018
Seasonal Climate Watch February to June 2018 Date issued: Jan 26, 2018 1. Overview The El Niño-Southern Oscillation (ENSO) is expected to remain in a weak La Niña phase through to early autumn (Feb-Mar-Apr).
Q.1 The most abundant gas in the atmosphere among inert gases is (A) Helium (B) Argon (C) Neon (D) Krypton
Q. 1 Q. 9 carry one mark each & Q. 10 Q. 22 carry two marks each. Q.1 The most abundant gas in the atmosphere among inert gases is (A) Helium (B) Argon (C) Neon (D) Krypton Q.2 The pair of variables that
Skillful climate forecasts using model-analogs
Skillful climate forecasts using model-analogs Hui Ding 1,2, Matt Newman 1,2, Mike Alexander 2, and Andrew Wittenberg 3 1. CIRES, University of Colorado Boulder 2. NOAA ESRL PSD 3. NOAA GFDL NCEP operational
ENSO, AO, and climate in Japan. 15 November 2016 Yoshinori Oikawa, Tokyo Climate Center, Japan Meteorological Agency
ENSO, AO, and climate in Japan 15 November 2016 Yoshinori Oikawa, Tokyo Climate Center, Japan Meteorological Agency Aims of this lecture At the end of the yesterday s lecture, Hare-run said, - In the exercise
TCC Training Seminar on 17 th Nov 2015 JMA s Ensemble Prediction Systems (EPSs) and their Products for Climate Forecast.
TCC Training Seminar on 17 th Nov 2015 JMA s Ensemble Prediction Systems (EPSs) and their Products for Climate Forecast Takashi Yamada Climate Prediction Division Japan Meteorological Agency 1 Contents
ENSO and short-term variability of the South Equatorial Current
ENSO and short-term variability of the South Equatorial Current William S. Kessler and Sophie Cravatte NOAA / PMEL (USA) IRD (France) Extend transport estimates back to 1985 using XBT data ENSO signal:
ALASKA REGION CLIMATE OUTLOOK BRIEFING. June 22, 2018 Rick Thoman National Weather Service Alaska Region
ALASKA REGION CLIMATE OUTLOOK BRIEFING June 22, 2018 Rick Thoman National Weather Service Alaska Region Today s Outline Feature of the month: Ocean Warmth Headed into Summer Climate Forecast Basics Climate
The new ECMWF seasonal forecast system (system 4)
The new ECMWF seasonal forecast system (system 4) Franco Molteni, Tim Stockdale, Magdalena Balmaseda, Roberto Buizza, Laura Ferranti, Linus Magnusson, Kristian Mogensen, Tim Palmer, Frederic Vitart Met.
Assessing the Quality of Regional Ocean Reanalysis Data from ENSO Signals
ATMOSPHERIC AND OCEANIC SCIENCE LETTERS, 2012, VOL. 5, NO. 1, 55 61 Assessing the Quality of Regional Ocean Reanalysis Data from ENSO Signals WANG Lu 1, 2 and ZHOU Tian-Jun 1 1 State Key Laboratory of
Observations assimilated
Observations assimilated R-factor to adjust model error variances and K-Factor to adjust observation error variances. ETKF employs SST and SLA bias correction via AR() model fit. TABLE Summary of ocean
ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP July 26, 2004
ENSO Cycle: Recent Evolution, Current Status and Predictions Update prepared by Climate Prediction Center / NCEP July 26, 2004 Outline Overview Recent Evolution and Current Conditions Oceanic NiZo Index
JMA s Ensemble Prediction System for One-month and Seasonal Predictions
JMA s Ensemble Prediction System for One-month and Seasonal Predictions Akihiko Shimpo Japan Meteorological Agency Seasonal Prediction Modeling Team: H. Kamahori, R. Kumabe, I. Ishikawa, T. Tokuhiro, S.
Decadal prediction using a recent series of MIROC global climate models
PICES2011 @ Khabarovsk (20 October 2011) Decadal prediction using a recent series of MIROC global climate models Takashi Mochizuki (JAMSTEC, Japan) M. Kimoto, Y. Chikamoto, M. Watanabe, M. Mori (AORI,
O.M Smedstad 1, E.J. Metzger 2, R.A. Allard 2, R. Broome 1, D.S. Franklin 1 and A.J. Wallcraft 2. QinetiQ North America 2. Naval Research Laboratory
An eddy-resolving ocean reanalysis using the 1/12 global HYbrid Coordinate Ocean Model (HYCOM) and the Navy Coupled Ocean Data Assimilation (NCODA) scheme O.M Smedstad 1, E.J. Metzger 2, R.A. Allard 2,
1/12 Pacific HYCOM: The End Of A Long Simulation
1/12 Pacific HYCOM: The End Of A Long Simulation E. Joseph Metzger,, Harley E. Hurlburt and Alan J. Wallcraft Naval Research Laboratory, Stennis Space Center, MS HYCOM NOPP GODAE Meeting 27-29 29 October
lecture 10 El Niño and the Southern Oscillation (ENSO) Part I sea surface height anomalies as measured by satellite altimetry
lecture 10 El Niño and the Southern Oscillation (ENSO) Part I sea surface height anomalies as measured by satellite altimetry SPATIAL STRUCTURE OF ENSO In 1899, the Indian monsoon failed, leading to drought
The 2009 Hurricane Season Overview
The 2009 Hurricane Season Overview Jae-Kyung Schemm Gerry Bell Climate Prediction Center NOAA/ NWS/ NCEP 1 Overview outline 1. Current status for the Atlantic, Eastern Pacific and Western Pacific basins
Responding to the 2016 and 2017 Mass Coral Bleaching events on the Great Barrier Reef: from Observations to Modelling
Responding to the 2016 and 2017 Mass Coral Bleaching events on the Great Barrier Reef: from Observations to Modelling EMatson@aims Craig Steinberg & Claire Spillman N. Cantin, J. Benthuysen, H. Tonin,
Products of the JMA Ensemble Prediction System for One-month Forecast
Products of the JMA Ensemble Prediction System for One-month Forecast Shuhei MAEDA, Akira ITO, and Hitoshi SATO Climate Prediction Division Japan Meteorological Agency smaeda@met.kishou.go.jp Contents
EVALUATION OF THE GLOBAL OCEAN DATA ASSIMILATION SYSTEM AT NCEP: THE PACIFIC OCEAN
2.3 Eighth Symposium on Integrated Observing and Assimilation Systems for Atmosphere, Oceans, and Land Surface, AMS 84th Annual Meeting, Washington State Convention and Trade Center, Seattle, Washington,
Forecasting. Theory Types Examples
Forecasting Theory Types Examples How Good Are Week Out Weather Forecasts? For forecasts greater than nine days out, weather forecasters do WORSE than the climate average forecast. Why is there predictability
Cold air outbreak over the Kuroshio Extension Region
Cold air outbreak over the Kuroshio Extension Region Jensen, T. G. 1, T. Campbell 1, T. A. Smith 1, R. J. Small 2 and R. Allard 1 1 Naval Research Laboratory, 2 Jacobs Engineering NRL, Code 7320, Stennis
STRONGLY COUPLED ENKF DATA ASSIMILATION
STRONGLY COUPLED ENKF DATA ASSIMILATION WITH THE CFSV2 Travis Sluka Acknowledgements: Eugenia Kalnay, Steve Penny, Takemasa Miyoshi CDAW Toulouse Oct 19, 2016 Outline 1. Overview of strongly coupled DA
Verification at JMA on Ensemble Prediction
Verification at JMA on Ensemble Prediction - Part Ⅱ : Seasonal prediction - Yukiko Naruse, Hitoshi Sato Climate Prediction Division Japan Meteorological Agency 05/11/08 05/11/08 Training seminar on Forecasting
Forced and internal variability of tropical cyclone track density in the western North Pacific
Forced and internal variability of tropical cyclone track density in the western North Pacific Wei Mei 1 Shang-Ping Xie 1, Ming Zhao 2 & Yuqing Wang 3 Climate Variability and Change and Paleoclimate Working
Application and improvement of Ensemble Optimal Interpolation on Regional Ocean Modeling System (ROMS)
Application and improvement of Ensemble Optimal Interpolation on Regional Ocean Modeling System (ROMS) Zhaoyi Wang Guokun Lyu, Hui Wang, Jiang Zhu, Guimei Liu et al. National Marine Environmental Forecasting
Data assimilation for ocean climate studies
Data assimilation for ocean climate studies James Carton, Gennady Chepurin, Steven Penny, and David Behringer (thanks Eugenia) University of Maryland, NOAA/NCEP, College Park, MD USA Chl concentration
Comparison of the ECMWF seasonal forecast Systems 1 and 2, including the relative performance for the 1997/8 El Nino
Comparison of the ECMWF seasonal forecast Systems and, including the relative performance for the 997/ El Nino David Anderson, Tim Stockdale, Magdalena Balmaseda, Laura Ferranti, Frederic Vitart, Paco
How to Use the Guidance Tool (Producing Guidance and Verification)
How to Use the Guidance Tool (Producing Guidance and Verification) Hiroshi Ohno Tokyo Climate Center (TCC)/ Climate Prediction Division of Japan Meteorological Agency (JMA) Workflow of the Excel Guidance
Intraseasonal and seasonal variations in in the eastern equatorial Indian Ocean. Y. Masumoto, H. Hase, Y. Kuroda, and H. Sasaki
Intraseasonal and seasonal variations in in the eastern equatorial Indian Ocean -A -A high-resolution OGCM and and ADCP Observation- Y. Masumoto, H. Hase, Y. Kuroda, and H. Sasaki FRCGC/IORGC/ESC JAMSTEC
ALASKA REGION CLIMATE FORECAST BRIEFING. January 23, 2015 Rick Thoman ESSD Climate Services
ALASKA REGION CLIMATE FORECAST BRIEFING January 23, 2015 Rick Thoman ESSD Climate Services Today Climate Forecast Basics Review of recent climate forecasts and conditions CPC Forecasts and observations
Pacific HYCOM. E. Joseph Metzger, Harley E. Hurlburt, Alan J. Wallcraft, Luis Zamudio and Patrick J. Hogan
Pacific HYCOM E. Joseph Metzger, Harley E. Hurlburt, Alan J. Wallcraft, Luis Zamudio and Patrick J. Hogan Naval Research Laboratory, Stennis Space Center, MS Center for Ocean-Atmospheric Prediction Studies,
Evaluation of the Tropical Pacific Observing System from the ocean data assimilation perspective
QuarterlyJournalof theroyalmeteorologicalsociety Q. J. R. Meteorol. Soc. 141: 2481 2496, October 215 A DOI:1.12/qj.2579 Evaluation of the Tropical Pacific Observing System from the ocean data assimilation
ALASKA REGION CLIMATE OUTLOOK BRIEFING. November 17, 2017 Rick Thoman National Weather Service Alaska Region
ALASKA REGION CLIMATE OUTLOOK BRIEFING November 17, 2017 Rick Thoman National Weather Service Alaska Region Today Feature of the month: More climate models! Climate Forecast Basics Climate System Review