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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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101 records · Page 6
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NASA NTRS2022

An Assessment of SNPP and NOAA20 VIIRS RSB Calibration Performance in NASA SIPS Reprocessed Collection-2 L1B Data Products

Two VIIRS sensors onboard the SNPP and NOAA20 satellites have been successfully operating for over 10 and 4 years, respectively, providing the worldwide user community with high-quality imagery and radiometric measurements of the land, atmosphere, cryosphere, and oceans. This study provides a temporal radiometric stability and calibration consistency assessment of the SNPP and NOAA20 VIIRS reflective solar bands using the latest NASA SIPS C2 L1B products. Several independent vicarious approaches are used to examine the stability of SNPP VIIRS and consistency of the at-sensor reflectance between the two VIIRS instruments. These approaches include observations from simultaneous nadir overpasses, the Libya-4 desert and Dome C snow/ice sites, and deep convective clouds. The impact of existing band spectral differences on the reflectance measurements is accounted for utilizing scene-specific hyperspectral observations provided by the SCIAMACHY sensor onboard the ENVISAT platform. Results indicate that both SNPP and NOAA20 VIIRS reflectances are stable within 1% over their mission periods for all bands, except for a few bands in the visible range from SNPP VIIRS that show more upward drifts at high radiances. NOAA20 VIIRS reflectances are systematically lower than SNPP by 2 to 4% for most bands, with the exception of few short wavelength bands where it is seen to be up to 7%.

VIIRS↗
NASA NTRS2023

DPOD2020: A DORIS Extension of the ITRF2020 for Precise Orbit Determination

As one of the tracking systems used to determine orbits of the altimeter mission satellites (such as TOPEX/Poseidon, Envisat, Jason-1/-2/-3, CryoSat-2, Saral/Altika, Sentinel-3A/-3B, HY-2A/C/D, Jason-CS/Sentinel-6A, SWOT), DORIS (Doppler Orbitography Radiopositionning Integrated by Satellite) allows to determine positions and velocities of tracking stations that define a stable reference for the estimation of the precise orbits and thus are fundamental for the quality of the altimeter data and derived mean sea level products. Due to the time evolution of the DORIS ground network, some stations included in the 2020 realization of the International Terrestrial Reference Frame (ITRF2020) have been decommissioned and since 2021.0 a few new stations were added to the tracking network. Therefore, to satisfy operational requirements for POD (Precise Orbit Determination) and routine delivery of geodetic products, the International DORIS Service (IDS) regularly updates the DPOD (DORIS terrestrial reference frame for Precise Orbit Determination). The DPOD solutions include mean positions and velocities of all the DORIS stations since 1993.0 derived from the stacking of the latest IDS weekly combined series aligned to the current ITRF. In this paper, we first present the stacking process of the DPOD2020 version 1.0. Then, we address the validation procedure of the DPO2020 including comparison with ITRF2020 and POD tests. For eighty percent of all the time segments of all the DORIS stations, the station position differences between DPOD2020 version 1.0 and ITRF2020 are smaller than ten millimeters. The major position differences between these two solutions are associated with the DORIS sites either localized in the South Atlantic Anomaly region or with time spans smaller than one year. Compared to DPOD2014, the DPOD2020 shows reduction of the main statistics of the DORIS-to-DORIS tie residuals (differences between the estimated and measured ties). The POD tests showed similar results for DPOD2020 and DPOD2014 for most of the altimetric satellites (TOPEX/Poseidon, Jason-1, CryoSat-2, Jason-3). In addition, we observed better POD results with DPOD2020 for the latest altimetric satellite Sentinel-3A as well as a slight degradation for Jason-2. That degradation was fully explained by slightly worst results for the stations localized in the South Atlantic Anomaly region.

DORIS↗
NASA NTRSDate not supplied

Impact of DORISx Post Seismic Deformation and Seasonal Corrections on the DPOD2020 Solution

As one of the tracking systems used for the altimeter missions (such as TOPEX/Poseidon, Envisat, Jason-1/-2/-3, CryoSat-2, Saral/AltiKa, Sentinel-3A/-3B, HY-2A/C/D, Jason-CS/Sentinel-6A, SWOT), the position of the DORIS tracking stations provides a fundamental reference for the estimation of the precise orbits and so, by extension is fundamental for the quality of the altimeter data analysis and derived products. Due to the time evolution of the DORIS ground network, stations included in ITRF2020 may have been decommissioned and stations that were added to the tracking network after 2021.0 are, by definition, not part of ITRF2020. Therefore, to satisfy operational requirements for precise orbit determination and routine delivery of geodetic products, the International DORIS Service maintains the DORIS terrestrial reference frame for Precise Orbit Determination (DPOD) solutions. Since 2016, the DPOD products are computed by the IDS Combination Center (CC) as a DORIS cumulative position and linear velocity solution aligned to the latest available ITRF and using the latest IDS weekly combined series. Mid-2023, the IDS CC started the computation of the second version of the DPOD2020 based on the IDS 20 weekly solutions from 1993.0 to 2023.0. With that new solution, the IDS CC will include Post Seismic Deformation (PSD) corrections for some DORIS sites such as Socorro Island. These DPOD PSD corrections are determined from the analysis of DORIS coordinate time series only. The second version will also include optional annual and semi-annual station corrections. The presentation will describe the analysis used for extracting the PSD and seasonal DORIS station corrections, compare such corrections to those derived for ITRF2020, and evaluate the impact these new corrections have on station positioning and satellite POD.

Guilhem Moreaux↗
NASA NTRS2024

CREST: a Climate Data Record of Stratospheric Aerosols

Climate-related studies need information about the distribution of stratospheric aerosols, which influence the energy balance of the Earth’s atmosphere. In this work, we present a merged dataset of vertically resolved stratospheric aerosol extinction coefficients, which is derived using data from six limb and occultation satellite instruments: SAGE (Stratospheric Aerosol and Gas Experiment) II on ERBS (Earth Radiation Budget Satellite), GOMOS (Global Ozone Monitoring by Occultation of Stars) and SCIAMACHY (Scanning Imaging Spectrometer for Atmospheric Chartography) on Envisat, OSIRIS (Optical Spectrograph and InfraRed Imaging System) on Odin, OMPS (Ozone Monitor Profiling Suite Limb Profiler) on Suomi NPP, and SAGE III on the ISS (International Space Station). The merging of aerosol profiles is performed via the transformation of the aerosol datasets from individual satellite instruments to the same wavelength (750 nm) and their de-biasing and homogenization by adjusting the seasonal cycles. After such homogenization, the data from individual satellite instruments are in good agreement. The merged aerosol extinction coefficient is computed as the median of the adjusted data from the individual instruments. The merged time series of vertically resolved monthly mean aerosol extinction coefficients at 750 nm is provided in 10° latitudinal bins from 90° S to 90° N, in the altitude range from 8.5 to 39.5 km. The time series of the stratospheric aerosol optical depth (SAOD) is created via the integration of aerosol extinction profiles from the tropopause to 39.5 km; it is also provided as monthly mean data in 10° latitudinal bins. The created aerosol climate record covers the period from October 1984 until December 2023, and it is intended to be extended in the future. The merged CREST aerosol dataset (v2) is available at https://doi.org/10.57707/fmib2share.dfe14351fd8548bcaca3c2956b17f665 (Sofieva et al., 2024a). It can be used in various climate-related studies.

Viktoria F Sofieva↗