S-NPP CrIS Full Resolution Sensor Data Record Processing and Evaluations

Similar documents
Suomi NPP CrIS Reprocessed SDR Long-term Accuracy and Stability

Reprocessing of Suomi NPP CrIS SDR and Impacts on Radiometric and Spectral Long-term Accuracy and Stability

Evaluation of Different Calibration Approaches for JPSS CrIS

CrIS SDR Calibration and Cross-sensor Comparisons

VIIRS Radiance Cluster Analysis under CrIS Field of Views

CrIS Full Spectral Resolution SDR and S-NPP/JPSS-1 CrIS Performance Status

Comparison of Full-resolution S-NPP CrIS Radiance with Radiative Transfer Model

Monitoring of IR Clear-sky Radiances over Oceans for SST (MICROS) for Himawari-8 AHI

IASI spectral calibration monitoring on MetOp-A and MetOp-B

Updates on Operational Processing of ATMS TDR and SDR Products

IASI on MetOp-B Radiometric Calibration

Onboard Blackbody Calibration Algorithm of Chinese FY-2 Geostationary Imager Based on GSICS Reference Radiances

Utilization of AGI STK and S-NPP Operational Data to Generate JPSS-1 Proxy Test Data

Preliminary validation of Himawari-8/AHI navigation and calibration

Improvements to Ozone Mapping Profiler Suite (OMPS) Sensor Data Record (SDR)

TES Algorithm Status. Helen Worden

The IASI Instrument. on the assimilation of IASI in NWP Reading, May 6-8, ECMWF / NWP-SAF Workshop ! "# $ !" #$%& #$!$$

Radiance Based VIIRS LST Product Validation

VIIRS-CrIS Mapping. P. Brunel, P. Roquet. Météo-France, Lannion. CSPP/IMAPP USERS GROUP MEETING 2015 EUMETSAT Darmstadt, Germany

The NIR- and SWIR-based On-orbit Vicarious Calibrations for VIIRS

GEOG 4110/5100 Advanced Remote Sensing Lecture 4

SST Retrieval Methods in the ESA Climate Change Initiative

Satellite Infrared Radiance Validation Studies using a Multi-Sensor/Model Data Fusion Approach

Geolocation assessment for CrIS sensor data records

Challenges in data compression for current and future imagers and hyperspectral sounders

How GOSAT has provided uniform-quality spectra and optimized global sampling patterns for seven years

The 4A/OP model: from NIR to TIR, new developments for time computing gain and validation results within the frame of international space missions

Atmospheric Emitted Radiance Interferometer. Part II: Instrument Performance

COMPARISON OF LOCAL CSPP VIIRS SDRS WITH GLOBAL NOAA PRODUCTS FOR VALIDATION AND MONITORING OF THE EARS-VIIRS SERVICE STEPHAN ZINKE

2.1 RADIATIVE TRANSFER AND SURFACE PROPERTY MODELLING Web site:

Implementation of Version 6 AQUA and TERRA SST processing. K. Kilpatrick, G. Podesta, S. Walsh, R. Evans, P. Minnett University of Miami March 2014

MTG-FCI: ATBD for Outgoing Longwave Radiation Product

Converging Remote Sensing and Data Assimilation through Data Fusion

Prototyping GOES-R Albedo Algorithm Based on MODIS Data Tao He a, Shunlin Liang a, Dongdong Wang a

Extension of the CREWtype Analysis to VIIRS. Andrew Heidinger, Andi Walther, Yue Li and Denis Botambekov NOAA/NESDIS and UW/CIMSS, Madison, WI, USA

Assessments of MODIS On-orbit Spatial and Spectral Characterization

Challenges in data compression for current and future imagers and hyperspectral sounders. Nigel Atkinson

Menghua Wang NOAA/NESDIS/STAR Camp Springs, MD 20746, USA

Ice Cover and Sea and Lake Ice Concentration with GOES-R ABI

Hyperspectral Infrared Measurements Simulation and Collection for GOES-R Sounder Lossless and Lossy Data Compression Study and Beyond

On-orbit Calibration of the Geostationary Imaging Fourier Transform Spectrometer (GIFTS)

Infrared Scene Simulation for Chemical Standoff Detection System Evaluation

Important Notes on the Release of FTS SWIR Level 2 Data Products For General Users (Version 02.xx) June, 1, 2012 NIES GOSAT project

Interactive comment on Quantification and mitigation of the impact of scene inhomogeneity on Sentinel-4 UVN UV-VIS retrievals by S. Noël et al.

Interactive comment on Quantification and mitigation of the impact of scene inhomogeneity on Sentinel-4 UVN UV-VIS retrievals by S. Noël et al.

Sentinel-2 Calibration and Validation : from the Instrument to Level 2 Products

YONG CHEN. Earth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, Maryland YONG HAN

Products and Software Working Group

GSICS Coordination Center Update GSICS Executive Panel Meeting 12. Fuzhong Weng and Fangfang Yu GSICS Coordination Center

Working with M 3 Data. Jeff Nettles M 3 Data Tutorial at AGU December 13, 2010

The status of the RTTOV forward model and an assessment of its accuracy using high spectral resolution satellite data Marco Matricardi

CRISM (Compact Reconnaissance Imaging Spectrometer for Mars) on MRO. Calibration Upgrade, version 2 to 3

Overview of Atmospheric Radiative Transfer. Sergio De Souza-Machado, L. Larrabee Strow, Scott Hannon, Howard Motteler

Estimating land surface albedo from polar orbiting and geostationary satellites

Calibration of SMOS geolocation biases

11.2 ABI s Unique Calibration and Validation Capabilities

Uncertainties in the Products of Ocean-Colour Remote Sensing

Retrieval of Sea Surface Temperature from TRMM VIRS

AAPP version 8.1 Release Note

AAPP status report and preparations for processing METOP data

Climate Data Record (CDR) Program

Results of Cross-comparisons using multiple sites

GEOG 4110/5100 Advanced Remote Sensing Lecture 2

An Observatory for Ocean, Climate and Environment. SAC-D/Aquarius. MWR Geometric Correction Algorithms. Felipe Madero

MHS Instrument Pre-Launch Characteristics

SINGLE FOOTPRINT ALL-SKY RETRIEVALS USING A FAST, ACCURATE TWOSLAB CLOUD REPRESENTATION

GOCI Post-launch calibration and GOCI-II Pre-launch calibration plan

Description of NOMAD Observation Types and HDF5 Datasets NOT YET COMPLETE

Falcon Sensor Image Generator Toolkit

Current Joint Polar Satellite System (JPSS) Common Ground System (CGS) Technical Performance Measures (TPMs)

Beginner s Guide to VIIRS Imagery Data. Curtis Seaman CIRA/Colorado State University 10/29/2013

Correction and Calibration 2. Preprocessing

VIIRS-CrIS mapping. NWP SAF AAPP VIIRS-CrIS Mapping

High Spectral Resolution Infrared Radiance Modeling Using Optimal Spectral Sampling (OSS) Method

The Gain setting for Landsat 7 (High or Low Gain) depends on: Sensor Calibration - Application. the surface cover types of the earth and the sun angle

Thermal And Near infrared Sensor for carbon Observation (TANSO) onboard the Greenhouse gases Observing SATellite (GOSAT) Research Announcement

CWG Analysis: ABI Max/Min Radiance Characterization and Validation

GOES-R AWG Radiation Budget Team: Absorbed Shortwave Radiation at surface (ASR) algorithm June 9, 2010

S2 MPC Data Quality Report Ref. S2-PDGS-MPC-DQR

Prof. Vidya Manian Dept. of Electrical l and Comptuer Engineering. INEL6007(Spring 2010) ECE, UPRM

Algorithm Theoretical Basis Document (ATBD) for ray-matching technique of calibrating GEO sensors with Aqua-MODIS for GSICS.

Quality assessment of RS data. Remote Sensing (GRS-20306)

7.1 Advanced Himawari Imager (AHI) Design and Operational Flexibility Dr. Paul C. Griffith

Combining Ray matching (SNO) with Invariant Target Methods for GSICS GEO LEO Inter Calibration

An Innovative Satellite SO 2 and HCHO Retrieval Algorithm based on Principal Component Analysis: Contribution to the Sentinel-5P Mission

RAL IASI MetOp-A TIR Methane Dataset User Guide. Reference : RAL_IASI_TIR_CH4_PUG Version : 1.0 Page Date : 17 Aug /12.

Creating a global aerosol data time series from two MODISs, Suomi-NPP VIIRS and beyond: Applying the MODIS Dark Target algorithm

Preprocessed Input Data. Description MODIS

Modeling of the ageing effects on Meteosat First Generation Visible Band

McIDAS-V - A powerful data analysis and visualization tool for multi and hyperspectral environmental satellite data *

Update on Pre-Cursor Calibration Analysis of Sentinel 2. Dennis Helder Nischal Mishra Larry Leigh Dave Aaron

MATISSE : MODELISATION AVANCEE de la TERRE pour l IMAGERIE et la SIMULATION des SCENES et de leur ENVIRONNEMENT

TOA RADIANCE SIMULATOR FOR THE NEW HYPERSPECTRAL MISSIONS: STORE (SIMULATOR OF TOA RADIANCE)

Analysis Ready Data For Land

Information Content of Limb Radiances from MIPAS

Improvements to the SHDOM Radiative Transfer Modeling Package

HARMONIE ATOVS data assimilation and coordinated impact study

Calibration of HY-2A Satellite Scatterometer with Ocean and Considerations of Calibration of CFOSAT Scatterometer

Hyperspectral Remote Sensing

NPP VIIRS for Land Studies

Transcription:

S-NPP CrIS Full Resolution Sensor Data Record Processing and Evaluations Yong Chen 1* Yong Han 2, Likun Wang 1, Denis Tremblay 3, Xin Jin 4, and Fuzhong Weng 2 1 ESSIC, University of Maryland, College Park, MD, Yong.Chen@noaa.gov 2 NOAA/NESDIS/STAR, College Park, MD 3 Science Data Processing Inc., Laurel, MD 4 ERT, Laurel, MD Third Annual CICS-MD Science, November 12-13, 2014

Outlines Upgraded ADL to generate CrIS full resolution mode Sensor Data Records (SDR) Radiometric accuracy assessment Difference between observation and forward model simulation Double difference (DD) between CrIS and IASI Simultaneous Nadir Overpass (SNO) between CrIS and IASI Spectral accuracy assessment Absolute spectral validation Relative spectral validation Summary 2

CrIS on Suomi NPP CrIS Operational Concept ±50 Cross track Scans RDR = Raw Data Record SDR = Sensor Data Record EDR = Environmental Data Record RDRs RDRs 30 Earth Scenes Ground Station Decode Spacecraft Data Interferograms SDRs 2,200 km Swath CrIS SDR Algorithm Calibrated / Geolocated Spectra EDRs Co-Located ATMS SDRs NWP, EDR Applications Global Temperature, Moisture, Pressure Profiles 3

CrIS Normal Resolution and Full Resolution SDR CrIS can be operated in the full spectral resolution (FSR) mode with 0.625 cm -1 for all three bands, total 2211 channels, in addition to normal mode with 1305 channels NOAA will operate CrIS in FSR mode in December 2014 to improve the profile of H 2 O, and the retrieval of atmospheric greenhouse gases CO, CO 2, and CH 4 Frequency Band Spectral Range (cm -1 ) Number of Channel (unapodized) Spectral Resolution (cm -1 ) Red: Full resolution Effective MPD (cm) LWIR 650 to 1095 713* (717) 0.625 0.8 MWIR 1210 to 1750 433* (437) 1.25 0.4 865* (869) 0.625 0.8 SWIR 2155 to 2550 159* (163) 2.5 0.2 633* (637) 0.625 0.8 CH 4 CO CO 2 4

CrIS SDR Processing Major Modules I Part Load Data 9 granules O Part SDR Output Fifth Granule Pre-process: sort EP, SciCalP & IFGM packets into sequences; truncate full resolution RDRs if needed Quality Flag & Variable Settings CMO Build if needed Geolocation Calculation P Part IFGM to raw spectra conversion Update ICT, DS & ES sliding windows CMO Residual ILS Correction Self-apodization Correction Spectral Resampling FCE Handling (currently disabled) Post-calibration Filter Nonlinearity correction Radiometric Calibration NEdN Calculation Lunar intrusion handling FSR/J1 code change 5

CrIS Full Resolution SDR ADL Code The FSR ADL code is based on the IDPS Block 2.0, Mx8.5 Different calibration approaches are implemented in the code in order to study the ringing effect observed in CrIS normal mode SDR and to support to select the best calibration algorithm for J1 Code is modularized and flexible to run different calibration approaches The same source code can be compiled into normal-resolution executable or FSR executable: Normal-resolution RDRs or FSR RDRs Same source code Normal-resolution executable Normal-resolution SDRs FSR RDRs FSR executable FSR SDRs The FSR ADL code is completed and delivered to CrIS SDR science team members and Raytheon Company to test 6

FSR SDR Processing Plan S-NPP CrIS will be switched from the normal spectral resolution mode to the full spectral resolution mode in early December, 2014 IDPS and CLASS will continue producing and archiving normal resolution SDRs NOAA/STAR will routinely process the full resolution data and generate the FSR SDRs with a latency of ~24 hours, beginning on the first day of the CrIS FSR mode operation The data will be available on a STAR FTP site using the upgraded ADL CrIS SDR code Up to date, the FSR mode has been commanded three times in-orbit (02/23/2012, 03/12/2013, and 08/27/2013) August 27, 2013, before FSR August 27 and 28, 2013, FSR BT ΔBT Ch 848, 1377.5 cm -1, water vapor channel Results show that the SDR from FSR has similar features compared to SDR 7 generated from low resolution RDR BT ΔBT

CrIS Radiometric Assessment Validation of August 27-28, 2013 full spectral resolution data Upgraded ADL code used to generate full spectral resolution SDRs with updated non-linearity coefficients, ILS parameters, and sincq function for Correction Matrix Operator (CMO) for IDPS calibration approach. Assessment approach 1: Biases between CrIS observations and simulations using ECMWF analysis/forecast fields and forward model CRTM (Community Radiative Transfer Model) BIAS = ( Obs CRTM ) Assessment approach 2: Double difference between CrIS and IASI on MetOp-a/b (converted to CrIS) using CRTM simulation as a transfer tool Obs CRTM DD = ( Obs CRTM ) CrIS ( ) IASI 2CrIS Assessment approach 3: SNO difference between CrIS and IASI converted to CrIS BTdiff = BTCrIS BTIASI 2CrIS Three Approaches Forward Model Simulation O-B CrIS Double Difference SNO IASI 8

Resample IASI to CrIS IASI Observed Spectra FFT -1 Inverse Fourier transform of the spectra to the interferogram space Apodization Function CrIS IASI2CrIS 1)De-Apodization with IASI SRF 2)Truncation to CrIS OPD 3)Apodization with CrIS SRF Resampling error from IASI to CrIS resolution is very small (less than 0.02 K) since IASI spectra cover CrIS spectra for all three bands 9 FFT Fourier transform of the products to spectra space, resampling the spectra on CrIS wavenumber basis.

CrIS Nadir FOV-2-FOV Variability (FOR 15 and 16) for Clear Sky over Oceans S/C Velocity BIAS FOV = ( Obs CRTM ) ( Obs CRTM ) i FOV i all FOV-2-FOV variability is small, within ±0.3 K for all the channels 10

CrIS and IASI2CrIS NWP Biases: Clear Ocean Scenes CrIS IASI2CrIS MetOp-a IASI2CrIS MetOp-b Good agreement between CrIS observation and simulation using ECMWF Very good agreement between CrIS and IASI Smaller standard deviation for CrIS than IASI in band 3 11

CrIS Nadir Bias for Shortwave BIAS = ( Obs CRTM ) FOVi FOV i CO absorption lines Good agreement between IASI and CrIS, better than bias with CRTM CO high bias errors due to CO default profile in CRTM CrIS and IASI window channels differ by 0.1 K due to diurnal variation in the SST 12

Double Difference between CrIS and IASI2CrIS DD = ( Obs CRTM ) CrIS ( Obs CRTM ) IASI 2CrIS Double difference between CrIS and IASI using CRTM simulations as transfer target are within ±0.3 K for most of channels For 4.3 µm CO 2 strong absorption region, CrIS is warmer than IASI about 0.3-0.5 K CrIS and IASI window channels differ by 0.1 K due to diurnal variation in the SST 13

SNOs between CrIS and IASI SNO Criteria Time difference: <= 120 seconds Pixel distance: <=(12+14)/4.0 km = 6.5 km Zenith angle difference: ABS(cos(a1)/cos(a2)-1) <= 0.01 SNO agreement is very good for band 1. Also good for band 2, but larger BT difference toward the end of band edge Large BT differences in cold channels for band 3 14

SNOs between CrIS and IASI: Details Although there is large BT difference in band 3, line structures in CO and CO 2 regions show very good agreement between CrIS and IASI Line structure in CO (2155-2190 cm -1 ) region provides very good information to retrieve CO amount, and line structure in CO 2 absorption band (2300-2370 cm -1 ) 15 provides very good spectral calibration information

CrIS Spectral Assessment: Cross-Correlation Method Two basic spectral validation methods are used to assess the CrIS SDR spectral accuracy Relative spectral validation, which uses two uniform observations to determine frequency offsets relative to each other Absolute spectral validation, which requires an accurate forward model to simulate the top of atmosphere radiance under clear conditions and correlates the simulation with the observed radiance to find the maximum correlation Correlation coefficient between the two spectra: r S1S2 = n i= 1 ( S 1, i S )( S 1 s1 2, i ( n 1) D D S2 S 2 ) = n i= 1 n i= 1 ( S ( S 1, i 1, i S )( S 2 S ) ( S Standard deviation based on the difference of the two spectra: n 1 1 2, i 2, i S 2 S 2 DS = [( 1, 1) ( 2, 2 )] ( 1). 1S2 S i S S i S n i= 1 The cross-correlation method is applied to a pair fine grid spectra to get the maximum correlation and minimum standard deviation by shifting one of the spectra in a given shift factor ) 2 ) 2, 16

CrIS Spectral Uncertainty LWIR MWIR SWIR Absolute cross-correlation method: between observations and CRTM simulations under clear sky over oceans to detect the spectral shift Relative method: observations from FOV 5 to other FOVs Frequency used: 710-760 cm -1, 1340-1390 cm -1, and 2310-2370 cm -1 Spectral shift relative to FOV5 are within 1 ppm Absolute spectral shift relative to CRTM within 3 ppm 17

Summary The CrIS full resolution SDRs generated from the upgraded ADL were assessed CrIS full resolution SDR radiometric uncertainty: FOV-2-FOV radiometric differences are small, within ±0.3 K for all the channels Double difference with IASI are within ±0.3K for most of channels SNO results versus IASI show that agreement is very good for band 1 and band 2, but large BT differences in cold channels for band 3 CrIS full resolution SDR spectral uncertainty: Spectral shift relative to FOV5 are within 1 ppm Absolute spectral shift relative to CRTM simulation are within 3 ppm Future Work: assessing different calibration approaches which are implemented in ADL to study the ringing effect to choose the best one for J1 18