Ms. Prathana Khakurel Profile

Prathana Khakurel

at Science Systems and Applications, Inc.

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Author

Publications (5)

Proceedings Article | 4 October 2023 Presentation + Paper

Improved characterization of Libya-4 and Dome-C for consistent radiometric scaling between VIIRS sensors

David Doelling, Conor Haney, Prathana Khakurel, Rajendra Bhatt, Benjamin Scarino, Arun Gopalan

Proceedings Volume 12685, 1268519 (2023) https://doi.org/10.1117/12.2677789

KEYWORDS: Atmospheric corrections, MODIS, Ozone, Absorption, Tunable filters, Sensors, Bidirectional reflectance transmission function, Imaging systems, Clouds, Aerosols

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The NASA Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) product provides the scientific community observed TOA SW and LW fluxes for climate monitoring and climate model validation. To provide continuity for cloud retrievals between MODIS and VIIRS, the CERES project inter-calibrates MODIS and VIIRS utilizing coincident ray-matched radiance pairs over all-sky tropical ocean. The Aqua and Terra satellites have started drifting, thereby preventing any coincident tropical MODIS and VIIRS inter-calibration events. Similarly, no simultaneous nadir overpasses (SNOs) will exist between SNPP and NOAA satellites, which will fly in the same 1:30 PM orbit but positioned a half an orbit apart. The CERES project will utilize the Libya-4 and Dome-C invariant targets to radiometrically scale between MODIS and VIIRS reflective solar bands. This study has advanced the Libya-4 and Dome-C characterization by considering all angular conditions, improving clear-sky identification and atmospheric corrections. The BRDF for each VZA and RAA stratified angular bin is approximated using a 2^nd order regression with respect to cos(SZA). The clear-sky filtering utilized spatial homogeneity thresholds applied to channels not impacted by atmospheric parameters and additional angular bin specific dynamic filtering. Multiple sources of PW, ozone and aerosol optical depth are considered. The improved atmospheric characterization is evaluated by comparing the trendSE consistency across channels. For Libya-4 the 2.2μm and 0.91μm strong water vapor absorption bands, the trendSE was reduced by ~60% and ~80% by including the PW term. The Libya- 4 trendSE with atmospheric correction was reduced from within 2% to 1% for all channels except MODIS B17. The Dome-C 0.55mm and 0.65μm band trendSE was reduced by between 40% to 60% after accounting for ozone absorption. The Dome-C imager channel trendSE was reduced from within 2% to 1% by including atmospheric corrections. The Dome-C post-solstice ozone and PW daily variations are much smaller than prior to solstice. The Dome-C resulting post-solstice imager channel trendSE was reduced from 1% to 0.85% by including atmospheric corrections and closer to the 0.48μm band trendSE of 0.6%, which was not impacted by the atmosphere. Smaller trend_SE can be realized by limiting the large VZA observations over Libya-4 as well as utilizing only post-solstice observations over Dome-C.

Proceedings Article | 4 October 2023 Presentation + Paper

The impact of pixel size on the characterization of deep convective clouds for calibration

Conor Haney, David Doelling, Rajendra Bhatt, Prathana Khakurel, Benjamin Scarino, Arun Gopalan

Proceedings Volume 12685, 1268518 (2023) https://doi.org/10.1117/12.2677709

KEYWORDS: Reflectivity, Pixel resolution, Landsat, Clouds, Calibration, Image resolution, Imaging systems, Sensors, Spatial resolution

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The NASA CERES project provides the scientific community the observed TOA SW and LW fluxes for climate monitoring and climate model validation. CERES utilizes hourly geostationary imager derived broadband fluxes, which rely on the channel radiances and associated cloud retrievals, are used to estimate the broadband fluxes between CERES observations. This requires stable and consistent cross-platform imager visible channel calibration. The CERES project utilizes deep convective clouds (DCC) as an invariant Earth target to both monitor the stability of sensors and for radiometric scaling. GSICS, an international collaboration, is also evaluating and implementing the DCC invariant target calibration methodology to provide consistent calibration coefficients across geostationary imagers anchored to the Aqua- MODIS or the NOAA-20 VIIRS calibration reference. Tropical DCC are the brightest, coldest, most Lambertian, top of the atmosphere Earth targets. The DCC invariant target calibration methodology relies on a large ensemble of tropical DCC-identified pixel-level reflectances, which are aggregated as probability density functions (PDF). By assuming the monthly PDF shape is otherwise consistent in time excepting shifts in reflectance caused by changes in the sensor calibration, the imager stability is monitored. Radiometric scaling is accomplished by ratioing the sensor pair DCC PDF reflectance values. The success of the DCC methodology relies on consistent PDF distributions. The goal of this study is to determine the impact of pixel resolution on the DCC reflectance distribution. Single SNPP-VIIRS 750-m and Landsat 8 OLI 30-m granules are aggregated to degrade the pixel resolution from the native level. The DCC pixels are identified using a BT threshold. Most of the brightest DCC pixels are also the coldest, although there are exceptions. It was found that increasing the BT threshold exponentially increased the number of darker pixels. The pixel resolution did not seem to impact the DCC reflectance PDF distribution for pixel resolutions less than 3 km, which suggests that imagers of varying pixel resolutions may be radiometrically scaled to each other using DCC targets.

Proceedings Article | 4 October 2023 Presentation + Paper

Estimating bidirectional reflectance and monitoring stability of SNPP-VIIRS reflective solar bands using a deep neural network

Benjamin Scarino, David Doelling, Rajendra Bhatt, Conor Haney, Prathana Khakurel, Arun Gopalan, Xiaoxiong Xiong

Proceedings Volume 12685, 1268517 (2023) https://doi.org/10.1117/12.2677687

KEYWORDS: Reflectivity, Short wave infrared radiation, Neural networks, Clouds

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Proceedings Article | 30 September 2022 Presentation + Paper

Additional characterization of Libya-4 in support of post-launch vicarious calibration of satellite imagers

David Doelling, Prathana Khakurel, Conor Haney, Rajendra Bhatt, Benjamin Scarino, Arun Gopalan

Proceedings Volume 12232, 1223219 (2022) https://doi.org/10.1117/12.2633118

KEYWORDS: Clouds, Reflectivity, Imaging systems, Sensors, Photonic integrated circuits, Ozone, Aerosols, Atmospheric particles

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Proceedings Article | 30 September 2022 Presentation + Paper

Evaluation of spectral band adjustment factors for cross-calibration of visible imagers

David Doelling, Conor Haney, Rajendra Bhatt, Benjamin Scarino, Arun Gopalan, Prathana Khakurel

Proceedings Volume 12232, 122321A (2022) https://doi.org/10.1117/12.2633113

KEYWORDS: Reflectivity, Clouds, Sensors, Neodymium, Satellites, Imaging systems

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The NASA Clouds and the Earth's Radiant Energy System (CERES) energy balanced and filled (EBAF) product provides top of atmosphere SW and LW fluxes for monitoring the Earth’s energy budget and to validate climate models. The current EBAF Ed4.1 products, based on the Terra and Aqua CERES instrument observed radiances, rely on MODIS cloud properties to determine the scene-selected angular distribution model used to convert the CERES radiances into fluxes. The CERES EBAF Ed4.2 product will be based on NOAA-20 CERES observations beginning with the data month of April 2022. A seamless transition of fluxes and clouds can only occur if the analogous MODIS and VIIRS channels are properly inter-calibrated. The spectral response functions (SRF) of these bands differ noticeably and will require scene-dependent spectral band adjustment factors (SBAF) for proper radiometric scaling between them. VIIRS I1 and M5 same-granule reflectance measurements provide the optimal opportunity to validate SBAFs over many surface and cloud conditions. The CERES project maintains SCIAMACHY-, GOME-2-, and Hyperion-based scene-stratified hyper-spectral reflectance measurements that can be convolved with sensor pair SRFs to compute the corresponding SBAFs. The SCIAMACHY 2^nd order and GOME-2 linear fit SBAFs were optimal in providing spatially uniform M5/I1 spectrally corrected reflectance ratios over all-sky tropical ocean scenes, which corrected both clear-sky and bright cloud reflectances simultaneously by varying the SBAF as a function of the reflectance. Dome-C and deep convective cloud (DCC) SBAFs had a small M5/I1 SBAF reflectance correction of ~1.03, whereas Libya-4 had a large M5/I1 SBAF reflectance correction of ~1.085. DCC, Dome-C and Libya-4 are spectrally uniform spatial targets with site M5/I1 reflectance ratio spatial homogeneity within 0.2%. The impact of cloud contamination from both the cloud tops and shadows over Libya-4 reduced the M5/I1 reflectance ratio. Over Dome-C, cloud contamination did not significantly shift the M5/I1 reflectance ratio. The Hyperion spectral reflectances are too coarse to be convolved with the narrow M5 SRF, which resulted in M5/I1 SBAFs that differed significantly from those based on SCIAMACHY and GOME-2.

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