Radiative Transfer Model based Bias Correction in INSAT-3D/3DR Thermal Observations to Improve Sea Surface Temperature Retrieval

Transcription

1 Radiative Transfer Model based Bias Correction in INSAT-3D/3DR Thermal Observations to Improve Sea Surface Temperature Retrieval Rishi K Gangwar, Buddhi P Jangid, and Pradeep K Thapliyal Space Applications Centre Indian Space Research Organisation (ISRO) Ahmedabad, India pkthapliyal@sac.isro.gov.in

2 ISRO Current satellites for Earth Observations YEAR G E O KALPANA-1 (VHRR) INSAT-3A (VHRR, CCD) INSAT-3D (IMAGER & SOUNDER) INSAT-3DR (IMAGER & SOUNDER) INSAT-3DS (IMAGER & SOUNDER) L E O Atmosphere & Ocean GISAT (MX-VNIR, HyS-VNIR, HyS-SWIR, MX-LWIR) Oceansat-2 (OCM, SCAT, ROSA) CNES-ISRO MT (MADRAS, SAPHIR, ScaRaB, ROSA) CNES-ISRO SARAL (ALTIKA, ARGOS) SCATSAT-1 (Scatterometer) Oceansat-3 (OCM, SSTM, SCAT) NASA-ISRO NISAR Land & Water Resourcesat-2 (LISS-3/4, AWiFS) RISAT-1 (C-SAR) Resourcesat-2A (LISS-3/4, AWiFS) Cartographic CARTOSAT-1 (Stereo PAN) CARTOSAT-2 (PAN) CARTOSAT-2E (PAN) CARTOSAT-3 (PAN) YEAR

3 INSAT-3D/3DR/3DS Sounder Detector Ch. No. l c (mm) n c (cm -1 ) NE Principal absorbing gas Purpose Launch 3D: 26-Jul-2013, 82E 3DR: 08-Sep-2016, 74E Sounder Products Vertical Profiles of: Temperature Humidity Surface Skin Temperature Total Column Integrated Ozone Derived Products * Geopotential height * Layer and total precipitable water * Lifted index * Dry microburst index * Maximum vertical theta-e differential * Wind index CO 2 Stratosphere temperature CO 2 Tropopause temperature CO 2 Upper-level temperature LWIR CO 2 Mid-level temperature CO 2 Low-level temperature water vapor Total precipitable water water vapor Surface temp., moisture window Surface temperature ozone Total ozone MWIR water vapor Low-level moisture water vapor Mid-level moisture water vapor Upper-level moisture N 2 O Low-level temperature N 2 O Mid-level temperature SWIR CO 2 Upper-level temperature CO 2 Boundary-level temp window Surface temperature window Surface temp., moisture Visible visible Cloud

4 INSAT-3D/3DR/3DS Imager Products Channels Channel Wavelength (mm) Resolution (Km) Atmospheric Motion Vector (AMV) - Cloud Motion Vector (CMV) - Water Vapor Winds (WVW) Outgoing Longwave Radiation (OLR) Upper Tropospheric Humidity (UTH) Rainfall (QPE) GPI, IMSRA Hydro-Estimator (H-E) Sea Surface Temperature (SST) Cloud Mask Fog Snow Cover Aerosol Fire Smoke

5 INSAT-3D Imager

6 FUTURE INDIAN GEO SATELLITES: (GISAT) Launch Schedule: 2019, Geostationary orbit, 83E MX-VNIR: Multispectral - Visible Near Infrared, HySI-VNIR: Hyperspectral Imager - Visible Near Infrared, HySI-SWIR: Hyperspectral Imager - Short Wave Infrared, MX-LWIR: Multispectral - Long Wave Infrared. Band Ch SNR/ NEdT IFO V (m) Range (mm) Channels (mm) GISAT Scan scenario Scan area for two scan scenario (5 & 10 ) MX- VNIR HyS- VNIR HyS- SWIR MX- LWIR 4 > > B1: B2: B3: B4: B5N: B6N: l < 10 nm 150 > l < 10 nm 6 NEdT < 0.15K CH1: CH2: CH3: CH4: CH5: CH6: Tropical Cyclone Nowcasting Cloud properties SST/LST Rainfall Radiance Assim Winds Every 10 minute interval 30-minutes triplet every 6 hour for winds Ozone wind Total Ozone SO2 Monitoring Atmospheric turbulence Fog application Climate application

7 INSAT-3D Operational SST Algorithm Based on simulated dataset (MODTRAN RT Model). Basic Data set: Thermodynamic Initial Guess Retrieval (TIGR) INSAT-3D Spectral Response Functions and NE T. Coefficients generation for seven satellite zenith angles (0, 24, 36, 42, 48, 54, 60 deg) Day-time Equation: SST = A 0 + A 1 T 11 + A 2 T 11 T 12 + A 3 T 11 T 2 12 Night-time: SST = B 0 + B 1 T B 2 T 11 T 12 + B 3 (T 11 T 12 ) 2 where, A and B are the regression coefficients. T 11, T 12 and T 3.9 are the brightness temperatures of TIR-1, TIR-2 and MIR channels, respectively.

8 New Algorithm Based on simulated dataset (PFAAST RT Model), ECMWF diverse training dataset SST Equation: SST = A 0 + A 1 T 11 + A 2 T 11 T 12 + A 3 T 11 T A 4 T 11 T 12 [sec(θ) 1] Cloud detection algorithm to identify clear pixels (using VIS, MIR, TIR1, TIR2) Averaging brightness temperature of clear pixels in the neighboring 3 x 3 pixels to reduce the noise Computation of SST using modified retrieval algorithm. Quality control of the derived SST: Only those retrievals are retained that satisfy the following condition: (SST clim - 3 σ) <= SST <= (SST clim + 3 σ) where, σ is the standard deviation of the daily climatological SST and SST clim is the climatological value of daily SST.

9 Bias correction in observations with respect to RT simulations SST(INSAT-3D) SST(MODIS) For INSAT-3D: BT corr (TIR 1) = BT obs (TIR 1) ( θ θ ) BT corr (TIR 2) = BT obs (TIR 2) ( θ θ ) BT corr (MIR) = BT obs (MIR) ( θ θ + 2.4) For INSAT-3DR: BT corr (TIR 1) = BT obs (TIR 1) ( θ θ + 1.6) BT corr (TIR 2) = BT obs (TIR 2) ( θ θ + 1.2) BT corr (MIR) = BT obs (MIR) ( θ θ + 2.5) SST(INSAT-3DR) SST(MODIS) Channel Bias (K) RMSD (K) STD (K) TIR-1 Before After TIR-2 Before After MIR Before After

10 TIR1 before correction TIR2 before correction TIIR1 before correction TIR1 after correction TIR2 after correction TIIR1 after correction

11 Operational Modified Comparison of INSAT-3D Day-time SST with MODIS for 17 December, 2016

12 Operational Modified Comparison of INSAT-3DR Day-time SST with MODIS for 17 December, 2016

13 Validation with in-situ SST measurements Operational INSAT-3D INSAT-3D Modified INSAT-3D INSAT-3D

14 Modified Operational Comparison of INSAT-3D SST with MODIS for December, 2016 Day-time Night-time Operational Modified Algorithm Statistics Daytime Nighttime Bias (K) RMSD (K) STD (K) Bias (K) RMSD (K) STD (K) Day-time Night-time

15 Modified Operational Comparison of INSAT-3DR SST with MODIS for December, 2016 Day-time Night-time Operational Modified Algorithm Statistics Daytime Nighttime Bias (K) RMSD (K) STD (K) Bias (K) RMSD (K) STD (K) Day-time Night-time

16 Conclusions SST products from INSAT-3D/3DR evaluated w.r.t. MODIS-SST shows that there are zenith angle dependent biases. Zenith angle dependent RT model bias correction procedure developed using ECMWF analysis and INSAT-3D/3DR matchup data. The modified algorithm shows an improvement over the operational algorithm for INSAT-3D/3DR observations. The zenith angle dependency in observed TIR-1/2 brightness temperatures need to be studied further. Further improvements will be attempted using LBL-RT model and improved cloud detection algorithm

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