Mitch Goldberg National Oceanic & Atmospheric Administration NOAA JPSS Program Scientist

Transcription

1 Mitch Goldberg National Oceanic & Atmospheric Administration NOAA JPSS Program Scientist

2 JPSS consists of three satellites (Suomi NPP, JPSS-1, JPSS- 2), ground system and operations through 2025 JPSS mission is to provide global imagery and atmospheric measurements using polar-orbiting satellites JPSS is a partnership between NOAA and NASA NOAA has final decision authority and is responsible for overall program commitment NASA is the acquisition agent for the flight system (satellite, instruments and launch vehicle), ground system, leads program systems engineering, and program safety and mission assurance NOAA is responsible for operations, science, data exploitation and archiving, infrastructure

3 Overview of JPSS and instruments Algorithm Status Proving Ground 3

4 JPSS Instrument ATMS - Advanced Technology Microwave Sounder CrIS - Cross-track Infrared Sounder VIIRS Visible Infrared Imaging Radiometer Suite Measurement ATMS and CrIS together provide high vertical resolution temperature and water vapor information needed to maintain and improve forecast skill out to 5 to 7 days in advance for extreme weather events, including hurricanes and severe weather outbreaks VIIRS provides many critical imagery products including snow/ice cover, clouds, fog, aerosols, fire, smoke plumes, vegetation health, phytoplankton abundance/chlorophyll OMPS - Ozone Mapping and Profiler Suite Ozone spectrometers for monitoring ozone hole and recovery of stratospheric ozone and for UV index forecasts CERES - Clouds and the Earth s Radiant Energy System Scanning radiometer which supports studies of Earth Radiation Budget

5 5 Advanced Features Three instruments (AMSU-A1, AMSU-A2 and MHS) in one instrument less power and weight Better spatial resolution (~48 to 32 km) for key temperature sounding channels Oversampled footprints for improved warm core anomalies for tropical cyclones and precipitation Wider swath

6 JPSS ATMS-Based TC Intensity Estimates Calculate TC Warm Core Anomalies from ATMS Microwave Radiances and Relate to Storm Intensity using Method Developed at UW-CIMSS Based on AMSU and SSMIS AMSU 06UTC Typhoon Bopha, Dec ATMS 04UTC Est. Intensity = 937hPa, 130kt max winds Vertical cross-sections through TC Bopha center (red line on left panel indicates storm center). Warm anomalies in green/yellows (contour interval=0.5c), with max around 200 hpa. Correction for rain scattering in ATMS not yet applied (cool/blue signal in lower levels (eyewall). NPP ATMS FOV resolution is 32km at nadir versus AMSU 48km >> Better depiction of warm core. NPP ATMS FOV resolution is 32km at nadir versus AMSU 48km >> Better Depiction of Warm Core.

7 Source: Surussavadee and Staelin, NASA PMM Presentation, 7/08

8 T TPW WV RR Courtesy of Sid Boukabara (STAR)

9 ATMS Data Products ATMS TDRs, SDRs (radiances) CLOUD LIQUID WATER PRECIPITATION RATE PRECIPITABLE WATER LAND SURFACE EMISSIVITY ICE WATER PATH LAND SURFACE TEMPERATURE SEA ICE CONCENTRATION SNOW COVER SNOW WATER EQUIVALENT ATM VERT TEMPERATURE PROFILE ATM VERT MOISTURE PROFILE

10 10 Advanced Features Lower power, volume and mass when compared to AIRS and IASI, and excellent signal to noise Significantly improved vertical resolution of temperature and water vapor when compared to POES HIRS and AMSU (1 2 km instead of - 6 km) Combined with ATMS for cloud clearing provides precision of about 1 Celsius for temperature and 15% for water vapor at vertical resolutions of 1-2 km Also provides information on trace gases O3, CO2, CO, CH4 - monitor continental transport of greenhouse gases Provides accurate cloud properties (at 14 km resolution near nadir)

11 Window Channel Water vapor Channel SC V 11

12 Statistics for May 15, 2012 focus day in which Aqua and NPP orbits has high coincidence. 12

13 13

14 Sounding retrievals provide quantitative interpretation of satellite imagery

15 Sounding retrievals provide 3-d structure of storm systems

16 Hyperspectral Infrared Sounders and Advanced Microwave Sounders are the top two contributors for reducing forecast errors Forecast error reduction contribution (%) 16

17 ECMWF forecasts of Mean Sea Level Pressure, 5 days in advance of the 30 th October 2012 for the landfall of Hurricane Sandy. Forecasts from an assimilation system with no polar satellites fail to predict the landfall of the storm on the US east coast. ECMWF OPS NO POLAR SAT VERIFICATION 5 day forecast: Base time z Valid Time: z

18 VIIRS

19 VIIRS: Next Gen Operational Polar Orbiting Imaging Radiometer VIS/NIR FPA S/MWIR LWIR Silicon PIN Diodes PV HgCdTe (HCT) PV HCT 22 spectral bands Visible to LWIR Spatially registered Better spatial resolution Reduced variation over scan Higher resolution imaging bands High radiometric accuracy NIST-traceable Supported by on-board calibrators CCD Band No. Wavelength Horiz Sample Interval (km Downtrack x Crosstrack) Driving EDRs Ra an Ran ( m) Nadir End of Scan M x x 1.58 Ocean Color Lo Aerosols Hig M x x 1.58 Ocean Color Lo Aerosols Hig M x x 1.58 Ocean Color Lo Aerosols Hig M x x 1.58 Ocean Color Lo Aerosols Hig I x x Imagery Sin M x x 1.58 Ocean Color Lo Aerosols Hig M x x 1.58 Atmospheric Corr'n Sin I x x NDVI Sin M x x 1.58 Ocean Color Lo Aerosols Hig DNB x x Imagery Va M x x 1.58 Cloud Particle Size Sin M x x 1.58 Cirrus/Cloud Cover Sin I x x Binary Snow Map Sin M x x 1.58 Snow Fraction Sin M x x 1.58 Clouds Sin I x x Imagery Clouds Sin M x x 1.58 SST Sin M x x 1.58 SST Lo Fires Hig M x x 1.58 Cloud Top Properties Sin M x x 1.58 SST Sin I x x Cloud Imagery Sin M x x 1.58 SST Sin 19

20 Land Active Fire Land Surface Albedo Land Surface Temperature Vegetation Index & Fraction Surface Type Ice Surface Temperature Sea Ice Characterization Snow Cover/Depth Ocean Clouds Cloud Mask Cloud Optical Thickness Cloud Effective Particle Size Parameter Cloud Top Height Cloud Fraction Polar winds Aerosols Aerosol Optical Thickness Aerosol Particle Size Parameter Suspended Matter (Volcanic Ash) Sea Surface Temperature Ocean Color/Chlorophyll

21 21

22

23 Suomi NPP Day Night Band Chukchi Sea Now you don t RUSSIA Snow and Ice applications courtesy of Steve Miller (CIRA) 23

24 1 km resolution NDVI shows many features which is hard to see with 4 km data: small lakes & reservoirs river valleys; forest Michigan

25 25 Advanced Features Three hyperspectral imaging spectrometers: Nadir Mapper: 50 km spatial with 2600 km swath Nadir Profiler: 250 km spatial, 8 km vertical resolution Limb: 3 km vertical, three crosssections separated by 500 km

26 Copahue Eruption Dec. 13, 2012 June 23, 2012 (NASA Science Team)

27

28

29

30 Algorithm Validation Process Timeline Four Phases of Calibration/Validation (Cal/Val): 1. Pre-Launch (all time prior to launch) Algorithm verification, sensor testing, and validation preparation 2. Early Orbit Check-out (first days) System calibration and characterization 3. Intensive Cal/Val (extending to approximately 24 months post-launch) Product validation 4. Long-Term Monitoring (through life of sensors) For each phase: Exit Criteria established Activities summarized Products mature through phases independently We Are Here

31 Algorithm Status Algorithm Maturity Definitions Beta Early release product Initial calibration applied Minimally validated and may still contain significant errors (rapid changes can be expected, version changes will not be identified as errors are corrected as on-orbit baseline is not established) Available to allow users to gain familiarity with data formats and parameters Product is not appropriate as the basis for quantitative scientific publications, studies and applications. Provisional Product quality may not be optimal Incremental product improvements are still occurring as calibration parameters are adjusted with sensor on-orbit characterization (versions will be tracked) General research community is encouraged to participate in the QA and validation of the product, but need to be aware that product validation and QA are ongoing Users are urged to contact JPSS NPP Cal/Val representatives prior to use of the data in publications Validated/Calibrated On-orbit sensor performance characterized and calibration parameters adjusted accordingly Ready for use by the users and in scientific publications There may be later improved versions There will be strong versioning with documentation Stage 1: product accuracy has been estimated using a small number of independent measurements obtained from selected locations, periods, and associated ground-truth/field program efforts. Stage 2: Product accuracy has been assessed over a widely distributed set of locations and periods via several ground-truth and validation efforts Stage 3: Product accuracy has been assessed and the uncertainties in the product well established via independent measurements in a systematic and statistically robust way representing global conditions. 31

32

33 Key Milestones JDE Satellite Products (from Feb 2013) Project Capability Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 NOAA Unique CrIS- ATMS Product System ATMS-CrIS Radiances OPS Temp/Moisture profiles, Trace Gases Carbon, ozone, cloud cleared radiances SRR DAP OPS CDR DAP OPS CrIS-VIIRS colocated, clouds DR DR DAP OPS NetCDF4 Reformatting Toolkit BUFR (Radiances, SST) TRR DAP OPS BUFR (Ozone, AOT) TRR DAP OPS BUFR (Polar Winds) GRIB2 (GVF) TRR DAP OPS BUFR AMSR-2 TRR ARR DAP OPS Microwave Integrated Retrieval System Advanced Clear Sky Processor for Oceans Surface/hydrology products DAP DAP OPS SST, Level 3 Products DAP DAP OPS VIIRS Polar Winds Polar Winds DAP OPS Green Vegetation Fraction Green Veg Fraction CDR TRR DAP DAP OPS DAP Delivered Algorithm Package OPS Operational ESPC CDR Critical Design Review TRR Test Readiness Review PDR Preliminary Design Review DR Design Review SRR System Readiness Review ARR Algorithm Readiness Review 33

34 Key Milestones JDE Satellite Products Project Capability Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 OMPS Limb Profiler OMPS Limb Profiler Sensor Data Record PDR CDR SRR DAP OPS OMPS Limb Profiler Environmental Data Record PDR CDR TRR SRR DAP OPS Microwave Tropical Cyclone Products NPP microwave sounderbased tropical cyclone products PDR CDR DAP OPS VIIRS Vegetation Health VIIRS-Veg Health PDR CDR MiRS High Resolution Snow Grain and Sea Ice Age MIRS High Resolution Products Snow grain size and Sea ice age PDR CDR SRR CrIS Outgoing Longwave Radiation CrIS OLR CDR DAP SRR OPS DAP Delivered Algorithm Package OPS Operational ESPC CDR Critical Design Review TRR Test Readiness Review PDR Preliminary Design Review DR Design Review SRR System Readiness Review ARR Algorithm Readiness Review 34

35 Key Milestones JDE Satellite Products Project Capability Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Interactive Multi-sensor Snow and Ice Mapping System (IMS) IMS version 3 using NPP VIIRS data CDR TRR SRR DAP to ESPC OPS Global Soil Moisture Product System Global Soil Moisture Products Using ASCAT, AMSR2 and SMOS NRT Data SRR DAP to ESPC OPS Polar-Geo Blended Hydrometeorological Products Enhanced Blended TPW, TPW anomaly and Rain Rate products with NPP/ATMS DAP to ESPC OPS Enhanced Blended TPW, TPW anomaly and Rain Rate products with GCOM- W1 AMSR-2 DR ARR DAP to ESPC OPS Total Ozone Analysis (TOAST) Enhanced TOAST with NPP Data PDR CDR DAP to ESPC OPS Ensemble Tropical Rainfall Potential (etrap) etrap Upgrade NPP DAP to ESPC OPS Microwave and Diurnal Corrected Blended SST Blended SST with Microwave Data CDR DAP to ESPC OPS Ocean Color Ocean Color S-NPP NUPs CDR DAP to ESPC DAP to ESPC DAP Delivered Algorithm Package OPS Operational ESPC CDR Critical Design Review TRR Test Readiness Review PDR Preliminary Design Review DR Design Review SRR System Readiness Review ARR Algorithm Readiness Review 35

36 Key Milestones JDE Satellite Products Project Capability Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Product Monitoring Tool NDE Product Monitoring PDR CDR TRR DAP to ESPC SRR OPS Phase II Product Monitoring CDR TRR DAP to ESPC AMSR2 McIDAS Tailoring Toolkit Day 1 AMSR-2 Data and Products in McIDAS DR DAP to ESPC OPS Day 2 AMSR-2 Data and Products in McIDAS DR DAP to ESPC OPS DAP Delivered Algorithm Package OPS Operational ESPC CDR Critical Design Review TRR Test Readiness Review PDR Preliminary Design Review DR Design Review SRR System Readiness Review ARR Algorithm Readiness Review 36

37 JPSS Proving Ground and Risk Reduction Application Areas Weather Forecasting (Improving Global, Regional forecasts) Tropical Cyclones Severe Weather (Nowcasting) Ocean/Coastal (Coral Bleaching, Harmful Algal Bloom alerts) Land (Droughts, Agriculture) Hazards (Smoke, Fire, Volcanic Ash, Air Quality) Hydrological (Precipitation, Floods, Soil Moisture, Snow/Ice, River Ice) Climate (integrated products, real-time anomaly products) Education and Training Infrastructure (Direct Readout and Software (CSPP), Airborne campaigns) JPSS Proving Ground Partners : NWS, NOS, NMFS, OAR, NESDIS, NOAA Cooperative Institutes, NASA, and NRL 37

38 JPSS Significant Proving Ground Accomplishments S-NPP Direct Broadcast for Alaska, Hawaii Continental US, and World Wide Users Routine use of VIIRS Imagery by forecast offices (significant use by Alaska) VIIRS Active Fire, Air Quality, and Ocean Color imagery and data portals Tropical Cyclone Forecasting Improvements using ATMS and CrIS Global Data Assimilation Experiments of ATMS and CriS (ATMS is now operational!) Education and Training (New COMET VIIRS Day Night Module) First Airborne Validation Campaign via NASA ER2 Enterprise Algorithms 38 38

39 JPSS PGRR Supports Education/Training Modules 39

40 JPSS PGRR Deep-Dive Validation First S-NPP ER-2 Aircraft Campaign to provide validation for CrIS, ATMS and VIIRS NIST traceable absolute calibration for CrIS May 10, 2013 first look ER-2 with aircraft validation sensors under flies Suomi NPP sensors. In the case of CrIS, the validation sensor in this example is from the Scanning High-resolution Interferometer Sounder (S-HIS) which has been tied to a NIST traceable calibration source. Quick look comparisons show excellent agreement. Significance NIST traceable validation is critical for uncertainty analysis needed to fully assess data quality of S-NPP and JPSS sensors. 40

41

42

43 NWS in Alaska, through the JPSS Proving Ground, has become a primary and proactive user of VIIRS products and imagery. The examples demonstrates exploitation of critical data for arctic access and navigation, and safe transportation. VIIRS being used for sea ice analysis VIIRS animation showing strong Easterly Flow (Polynyas* and Leads) in Ice. Barrow * An area of open water surrounded by sea ice. It is now used as a geographical term for an area of unfrozen sea within the ice pack. 43

44

45 Blogs have become a conduit for communication 45

46 River Flooding first identified with VIIRS by CIMSS 46

47 VIIRS Flood Maps for Decision Support for Yukon River Flooding May VIIRS Flood Map Layer in Google Earth (Flooded land nearly 16 miles wide on 5/29) Rapid river ice melting and ice jams resulted in major flooding from the Yukon River which impacted the town of Galena, Alaska (pop. ~ 500). Nearly the entire town was evacuated. As part of JPSS Proving Ground - VIIRS imagery first identified the flooded region and then our VIIRS flood- standing water experimental products were derived. JPSS is also supporting a river ice jam identification project. JPSS and NWS are working together to determine the best way VIIRS can be used for improved river flooding decision support. 47

48 Active Fires Webpage The National Weather Service and US Forest Service both depend on VIIRS data to predict, identify and monitor wildfires. JPSS has funded development and implementation of the Active Fires program through its Proving Ground.

49 The cyclonic spin of the eddy causes the nutricline at its core to shoal, bringing deep nutrients to surface waters resulting in increased phytoplankton. These eddies appear to create food webs resulting in foraging habitat for apex species including tunas and cetaceans off the coast of Hawaii. VIIRS ocean color derived Chlorophyll-A 49

50 April 7, 2013 Through NOAA Coastwatch, JPSS will continue to support operational monitoring of US coastlines for health hazards

51 In 2010, major bleaching occurred to coral reefs throughout much of the Indian Ocean, Southeast Asia, the Coral Triangle, and the Caribbean Coral Reef Watch (using AVHRR) provide a nowcast of current bleaching environmental conditions as derived from sea surface temperature anomalies

52 Vegetation Fraction Surface Type Understanding climatically-induced changes allows for NOAA to better support land, ecosystem and drought monitoring to provide decision support to US stakeholders Drought

53 Need to Exploit Strength of LEO and GEO LEO sounders provide the vertical dimension but lower temporal resolution GEO- provides the high temporal imagery LEO (VIIRS) has superb spatial resolution and global coverage Excellent land ecosystems, sharp sea surface temperature gradients Data of opportunity for nowcasting 53

54 JPSS is a major contributor to the global observing system. Suomi NPP instruments are performing exceptionally well!! Many applications will benefit and JPSS has a data exploitation proving ground effort with each NOAA line office to improve product and services. International partnerships are essential. Observations coupled with modeling, data fusion, with the underpinning research, are essential for transforming observations to the products, applications, and services needed to address environmental impacts on society. 54