Overview: Scope and Goals

Transcription

1 Overview: Scope and Goals Current operational NOAA instruments: AVHRR, HIRS, SBUV, GOES Imagers/Sounders; Non-NOAA satellites/sensors; Future: MetOP and NPP/NPOESS; GOES-R Assure Functionality of Current/Near-Future Operational Systems Develop & maintain on-orbit calibration approach, algorithms, & databases Oversee pre-launch sensor calibration Perform post-launch checkout, monitoring, and trouble-shooting Apply Experience to Design of Future systems Define future measurement requirements & support development of future systems (NPP, NPOESS, GOES-R, active sensors) Assure Required Accuracy, Stability, Inter-comparability Serve Community of Data Providers and Users NOAA customers Other US Government Agencies Academia and Industry International partners 1 of 20

2 Examples Sensors, observations, and products Calibration or validation method & results Emphasis on topics not covered at IVOS 9 Broader ORA, NOAA, and external perspective than previously reported 2 of 20

3 Rapid Scan Winds and Hurricane Isabel mb mb mb 3 of 20 September 15, 2003

4 GOES-10 IR Cloud Drift Winds mb mb mb 4 of mb mb mb

5 GOES-10 Visible Cloud-Drift Winds 5 of 20

6 GOES-12 Water Vapor Winds mb mb mb mb mb mb 6 of 20

7 Winds from MODIS: An Arctic Example Cloud-track winds from MODIS for a case in the western Arctic. The wind vectors were derived from a sequence of three images, each separated by 100 minutes. They are plotted on the first 11 µ m image in the sequence. 7 of 20

8 An Arctic Example, cont. Water vapor winds from MODIS for a case in the western Arctic. The wind vectors were derived from a sequence of three images, each separated by 100 minutes. They are plotted on the first 6.7 µ m image in the sequence. 8 of 20

9 Validation of Satellite Derived Winds Daily Comparisons With Radiosonde Observations Statistics reported quarterly to the World Meteorological Organization (WMO)/Coordination Group for Meteorological Satellites (CGMS) NOAA Wind Profiler Observations Network of 34 profilers (central U.S.) National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) Analyses 9 of 20

10 Monitoring the Quality of GOES Wind Products nesdis.noaa.gov gov/smcd smcd/opdb 10 of 20 opdb/goes/winds/html/ /goes/winds/html/tseries.html

11 Monitoring the Quality of GOES Wind Products nesdis.noaa.gov gov/smcd smcd/opdb 11 of 20 opdb/goes/winds/html/ /goes/winds/html/tseries.html

12 12 of 20 Merriman, Nebraska

13 Objective Height Assignment Level of Best-Fit Analysis Characterize heights assigned to Atmospheric Motion Vectors (AMVs( AMVs) Data Source Database of collocated GOES-8 AMVs and Radiosonde Wind Profiles (Jan-Dec 2002) Level of Best-Fit Defined to be the level at which vector difference between the satellite wind and the radiosonde wind is a minimum 13 of 20

14 Jan-Dec 2002 GOES-8 Cloud-drift winds assigned at 300mb Original height assignment (OPW); no speed bias correction All Height assignment methods (H 2 O-intercept, window) Vector Difference (m/s) 14 of 20

15 Ocean Color - MOBY Vicarious Calibration Vicarious Calibration Required for Ocean Color Science Pre-flight Laboratory and On-board Sensor Calibrations (TOA 4-5%) Cannot Meet the Accuracy Requirements for Ocean Color Science Applications. A Minimum of an Order of Magnitude Improvement in Calibration Accuracy is Required. MOBY Presently Provides Water-Leaving Radiances at the 5% (surface) uncertainty Level Which Meets the Minimum Accuracy Requirement. MOBY has demonstrated excellent long-term Stability over the past 6.5 yrs. MOBY has provided a NIST Traceable Scale for all of the Major Ocean Color Missions Since the mid 1990 s. A necessary requirement for producing Climate Quality Data Records. Courtesy D. Clark 15 of 20

16 MOBY Instrument and Spectral Time Series of MODIS ocean color bands (Accuracy ~4-5%) Courtesy D. Clark 16 of 20

17 NOAA Ocean Color Validation System and Related Activities Needed to assess accuracy of NOAA generated ocean color products Maintained and enhanced NOAA Ocean Color Validation system and WWW homepage Initiated development of automated NRT ocean color product QC procedure Evaluated difference between near-real time and climatological ancillary data in operational ocean color processing 17 of 20

18 NOAA Ocean Color Validation System Contains 9842 in-situ measurements of chlorophyll concentration collected by numerous sources in U.S. coastal waters Regression analysis performed on estimates derived from SeaWiFS imagery for evaluation purposes (n 2130) Comparison between in-situ and SeaWiFS-derived chlorophyll concentrations(oc4v4 generated for all CoastWatch regions. 18 of 20

19 SST Product Validation Periodic global GAC AVHRR SST validation has been conducted continuously since 1983 SST retrieval precision has gradually improved to within 0.5 K rms of buoy matchups GOES SST became operational since Dec Global (GAC) AVHRR Courtesy ORA/ORAD/SST Team 19 of 20

20 SST Analysis with Imager Radiances Contributors: EMC: John Derber (PI), Xu Li; ORA/CIRA: Alexander Ignotov, Nick Nalli NCEP Retrieval NCEP First Guess Summary of Accomplishments Differences between Navy NOAA-16 Brightness Temperatures (BTs) and simulated BTs w/o bias correction Sensitivities to changes in SST, Ta (atmos. temperature) and Qa (atmos. moisture) Bias correction of simulated observations Retrieved SSTs compared to Navy retrievals and NCEP SST analyses and Buoy data This analysis is significantly important for JCSDA future activities of direct uses of window channel radiances Navy retrieval NCEP Analysis

21 GOES Aerosol and Smoke Product (GASP) Transport of smoke from forest fires in Canada/Alaska July 2004 Ongoing validation work Monthly mean aerosol optical depth (AOD) comparisons with sunphotometer Comparisons with MODIS AODs Correlation studies with surface measurements of particulate concentrations Future work Use aircraft and Lidar aerosol profile data over the northeastern US from July 2004 to assess aerosol model assumptions and to evaluate retrievals 21 of 20

22 Temperature Bias and RMS (Land and Sea Samples) With Cloud Test 10 Bias and RMS (Deg. K), NSAMP=8238 (land2_dep.txt, RAOB LS Coef, TP2_LS) COLLOCATED RADIOSONDES Pressure (mb) 100 airs Noaa AIRS-F258+AQ:AMSU (192 P) N-16(ATOVS) AIRS- F258+AQ:AMSU(192 P) N-16(ATOVS) Courtesy Mitch Goldberg 22 of 20

23 GPS IPW (Integrated Precipitable Water) stations operated by the NOAA Forecast Systems Lab. Courtesy NOAA/FSL (S. Gutman) 23 of 20

24 GPS measured vs. AIRS derived IPW for the CONUS (All match-ups within 0.25 deg lat/lon and within 30min) (a) (b) (c) (d) Figure of 20 Red line: linear fit for the match-up data.

25 NDVI Calibration/Validation MODIS and AVHRR NDVIs Compared for a Site in South Dakota (16 day composites in 2001) Effect of AVHRR Spectral Response on longterm NDVI time series studies Courtesy X. Wu Courtesy ORA/SMCD/EMB 25 of 20

26 SBUV/2 Ozone Cal/Val Level 2 Ground-based Comparisons In press, Miller et al., JGR Atmospheres 26 of 20

27 NIST verification of HIRS spectral response functions (HIRS Ch 1, CO 2 Q-branch, 25mb, worst case) Vendor NIST at 30, 25, 20, and 15 C 27 of 20

28 Intersatellite Calibration with Simultaneous Nadir Overpass (SNO) Observations Two satellites pass the same place at their nadirs within a few seconds Occurs for all satellites with different altitudes (typically once every few days); In the polar regions for sun synchronous satellites SNO time series very useful for intersatellite calibration of IR/VIS/NIR, and Microwave sensors Website: calibration/intercal/ Several publications Cao et al, J. Atmospheric & Oceanic Tech, of 20

29 Applications of SNO method Used for postlaunch checkout, longterm monitoring of instrument performance, and re-analysis of historical data for time-series analysis to achieve intersatellite calibration consistency Procedure is being implemented for NOAA s AVHRR, HIRS, and AMSU instruments; also used for Terra/Aqua MODIS/AVHRR by MCST Future work for inflight spectral cal with hyperspectral thermal sensors Complement to GOES/POES intercal HIRS stratosphere channel (longwave infrared) AMSU mid-troposphere channel (Microwave) Examples (to the right) SNO method reveals seasonal biases caused by spectral response differences for HIRS (upper right) SNO method shows excellent agreement between satellites for AMSU (low right) 29 of 20

30 AVHRR Reprocessing Project Re-processing of AVHRR data for better product quality for climate studies Standardize calibration coefficients and radiance calculation procedure, such as non-linearity correction, and band correction coefficients Use the SNO method to establish the calibration link among satellites Provide consistent calibration coefficients with improved calibration accuracy T in Brightness temperature (K) AVHRR Channel 4 NOAA10 v.s. NOAA11 NOAA11 v.s. NOAA12 NOAA14 v.s. NOAA15 NOAA15 v.s. NOAA16 NOAA16 v.s. NOAA Year 30 of 20

31 AVHRR VIS/NIR Vicarious Calibration using the Libyan Desert Target NOAA 16 AVHRR Albedo NOAA 17 AVHRR Albedo CH1 CH2 CH3 Courtesy X. Wu 31 of 20

32 GOES Star Based Calibration GOES 8 stars(520,820,934,1191) G8-934 G8-520 normalized signal Star 934 y = e x R 2 = star 520 y = e x R 2 = Star 820 y = e x R 2 = Star 1191 y = e x R 2 = G8-820 G Expon. (G8-934) Expon. (G8-520) Expon. (G8-820) Expon. (G8-1191) date Courtesy X. Wu, of 20

33 Status of NESDIS Uniform Instrument Monitoring System User-friendly (web-based) system with high level info, documentation, meta-data, eng & radiometric data archived undertaken at NRC recommendation System requirements document completed December 2003 System specification document in final stage of preparation Government team met 14 June 2004 to decide which architecture to employ Funding in place to develop prototype system in FY Courtesy T. Kleespies 33 of 20

34 NPP/NPOESS Cal/Val Activities VIIRS, CrIS, ATMS, and OMPS will replace AVHRR, HIRS, AMSU, and SBUV NPP = NPOESS Preparatory Project (IPO/NASA) NPOESS Data Exploitation Team: Oversight of and support to NPOESS cal/val Independent verification and monitoring Liaison between IPO and NOAA central/civilian users on cal/val issues Cal/val support to NOAA unique products Ensure continuity from POES to NPOESS NPOESS Prelaunch/postlaunch cal/val meetings Currently focus on prelaunch tests, instrument performance issues and potential science impacts 34 of 20

35 Summary NOAA/NESDIS has extensive calibration/validation experience in both prelaunch and postlaunch, atmosphere, sea surface temperature, ocean color, ozone, and land; validation using a variety of sources, including other satellites, in-situ, and ground-based remote sensors In partnership w/ other NOAA, NASA, USGA, Academia, International SNO method very useful for cal/val on-orbit for all radiometers, and will be used for calibrating future instruments Continued support to NOAA operational instruments, including AVHRR, HIRS, AMSU, SBUV/2, and reprocessing for climate studies Preparing for the transition to MetOP, NPOESS and GOES-R 35 of 20