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Ben Scarino

Publications and source records attributed to Ben Scarino.

6 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

TPSAS-NF1676L-13349-DND

Progress on the effort to calibrate historical AVHRR solar channels and derive a CERES-consistent cloud climatology form AVHRR data is presented.

Patrick Minnis↗
NASA NTRSDate not supplied

Examination of Regional Trends in Low Level Cloud Properties Found in the Aqua-MODIS Satellite Record

Clouds have a pronounced influence on the Earth?s climate. Relative to cloud free conditions, they cool the planet by increasing the amount of solar radiation reflected back to space and reducing the amount of sunlight reaching the surface, but they warm the planet by decreasing the amount of thermal infrared radiation escaping to space and increasing the amount reaching the surface (a greenhouse effect). The global mean net cloud radiative effect (CRE) is about -20 W/m2, a cooling effect at both the top-ofatmosphere and surface. Given the magnitude of CRE?s, it is expected that changes in cloud properties could be a significant factor in climate change due to anthropogenic forcing?s, yet cloud feedbacks are not well known and remain one of the largest uncertainties in climate prediction. This paper explores relationships between coincident observations of atmospheric aerosols, clouds and radiation derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and from the Clouds and the Earth?s Radiant Energy System (CERES) instruments on the Aqua satellite. We investigate several interesting regional trends that have emerged in the nearly 18-year satellite record that suggest correlation between changes in low-level cloud properties and changes in aerosol optical depth that may be associated with changes in pollution emissions and possibly with other factors. MERRA reanalysis of meteorological conditions and aerosol particulate species are investigated to help better understand the potential mechanisms responsible for the observed cloud property trends. Finally, we analyze a new CERES flux by cloud type dataset in order to try and isolate the associated trends in low-level cloud radiative effects. It is anticipated that this study using long-term observations of clouds, aerosols and radiative fluxes combined with model reanalysis data will contribute to an improved understanding of cloud climate feedbacks.

William L Smith Jr.↗
NASA NTRSDate not supplied

Seasonal Surface Spectral Emissivity Derived From MODIS Data

Surface emissivity is essential for many remote-sensing applications including the retrieval of surface skin temperature from satellite-based infrared measurements, the determination of cloud detection thresholds, and the estimation of the surface longwave radiation emission, an important component of the energy budget of the surface-atmosphere interface. The CERES (Clouds and the Earth’s Radiant Energy System) Project is measuring broadband shortwave and longwave radiances and deriving cloud properties from the MODIS on Terra and Aqua and from the VIIRS on NOAA-19 and NOAA-20 orbiters to produce combined global radiation and cloud property data sets. Zhou et al. (IEEE Trans. Geosci. Remote Sens., 49, 2011) used Infrared Atmospheric Sounding Interferometer (IASI) data to create a high spectral resolution surface emissivity atlas for remote sensing and modeling applications. The IASI measures spectral radiances between 3.62 and 15.5 μm. The VIIRS I4 channel width is from 3.55 to 3.93 μm, while MODIS Band 20 is from 3.66 to 3.84 m. Comparisons of top-of-atmosphere (TOA) radiance calculations with MODIS and VIIRS observations for these bands relative to bands in the mid-infrared suggest that the IASI emissivity atlas near 3.7 µm may not be suitable for CERES cloud retrievals. In this paper, the IASI emissivities for the VIIRS and MODIS bands centered near 11m are used to derive surface skin temperature from nighttime MODIS/VIIRS data. The Goddard Earth Observing System for Instrument Teams (GEOS-IT) numerical weather analyses provide temperature and water vapor profiles fused to correct the observed radiances for atmospheric absorption and emission. Global seasonal emissivity maps are then derived for the VIIRS and MODIS 3.7-m bands that are consistent with the derived skin temperatures and the observed TOA radiances. These seasonal climatology maps are validated and will be used in CERES Edition 5 and other CERES-related cloud retrieval algorithms to provide improved clear-sky radiances and derived cloud properties.

Surface Emissivity↗
NASA NTRSDate not supplied

Seasonal Surface Spectral Emissivity Derived from VIIRS Data

Surface emissivity is essential for many remote-sensing applications including the retrieval of surface skin temperature from satellite-based infrared measurements, the determination of cloud detection thresholds, and the estimation of the surface longwave radiation emission, an important component of the energy budget of the surface-atmosphere interface. The CERES (Clouds and the Earth’s Radiant Energy System) Project is measuring broadband shortwave and longwave radiances and deriving cloud properties from the MODIS on Terra and Aqua and from the VIIRS on NOAA-19 and NOAA-20 orbiters to produce combined global radiation and cloud property data sets. Zhou et al. (IEEE Trans. Geosci. Remote Sens., 49, 2011) used Infrared Atmospheric Sounding Interferometer (IASI) data to create a high spectral resolution surface emissivity atlas for remote sensing and modeling applications. The IASI measures spectral radiances between 3.62 and 15.5 µm. The VIIRS I4 channel width is from 3.55 to 3.93 µm, while MODIS Band 20 is from 3.66 to 3.84 µm. Comparisons of top-of-atmosphere (TOA) radiance calculations with MODIS and VIIRS observations for these bands suggest that the IASI emissivity atlas near 3.7 µm may not be suitable for CERES cloud retrievals. In this paper, the IASI emissivities for the VIIRS and MODIS bands centered near 11µm are used to derive surface skin temperature from nighttime MODIS/VIIRS data. The Goddard Earth Observing System for Instrument Teams (GEOS-IT) numerical weather analyses provide temperature and water vapor profiles fused to correct the observed radiances for atmospheric absorption and emission. Global seasonal emissivity maps are then derived for the VIIRS and MODIS 3.7µm bands that are consistent with the derived skin temperatures and the observed TOA radiances. These seasonal climatology maps will be validated and used in CERES Edition 5 and other CERES-related cloud retrieval algorithms to provide improved clear-sky radiances and derived cloud properties.

Surface Emissivity↗