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  • Author or Editor: Walter Wolf x
  • Journal of Atmospheric and Oceanic Technology x
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Kexin Zhang
,
Mitchell D. Goldberg
,
Fengying Sun
,
Lihang Zhou
,
Walter W. Wolf
,
Changyi Tan
,
Nicholas R. Nalli
, and
Quanhua Liu

Abstract

This study describes the algorithm for deriving near-real-time outgoing longwave radiation (OLR) from Cross-Track Infrared Sounder (CrIS) hyperspectral infrared sounder radiance measurements. The estimation of OLR on a near-real-time basis provides a unique perspective for studying the variability of Earth’s current atmospheric radiation budget. CrIS-derived OLR values are estimated as a weighted linear combination of CrIS-adjusted “pseudochannel” radiances. The algorithm uses the Atmospheric Infrared Sounder (AIRS) as the transfer instrument, and a least squares regression algorithm is applied to generate two sets of regression coefficients. The first set of regression coefficients is derived from collocated Clouds and the Earth’s Radiant Energy System (CERES) OLR on Aqua and pseudochannel radiances calculated from AIRS radiances. The second set of coefficients is derived to adjust the CrIS pseudochannel radiance to account for the differences in pseudochannel radiances between AIRS and CrIS. The CrIS-derived OLR is then validated by using a limited set of available CERES SNPP OLR observations over 1° × 1° global grids, as well as monthly OLR mean and interannual differences against CERES OLR datasets from SNPP and Aqua. The results show that the bias of global CrIS OLR estimation is within ±2 W m−2 and that the standard deviation is within 5 W m−2 for all conditions, and ±1 and 3 W m−2 for homogeneous scenes. The interannual CrIS-derived OLR differences agree well with Aqua CERES interannual OLR differences on a 1° × 1° spatial scale, with only a small drift of the global mean of these two datasets of around 0.004 W m−2.

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Hua Xie
,
Nicholas R. Nalli
,
Shanna Sampson
,
Walter W. Wolf
,
Jun Li
,
Timothy J. Schmit
,
Christopher D. Barnet
,
Everette Joseph
,
Vernon R. Morris
, and
Fanglin Yang

Abstract

An ocean-based prelaunch evaluation of the Geostationary Operational Environmental Satellite (GOES)-R series Advanced Baseline Imager (ABI) legacy atmospheric profile (LAP) products is conducted using proxy data based upon the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board the Meteosat Second Generation satellite. SEVIRI-based LAP temperature and moisture profile retrievals are validated against in situ correlative data obtained over the open ocean from multiple years of the National Oceanic and Atmospheric Administration (NOAA) Aerosols and Ocean Science Expeditions (AEROSE). The NOAA AEROSE data include dedicated radiosonde observations (RAOBs) launched from the NOAA ship Ronald H. Brown over the tropical Atlantic: a region optimally situated within the full-disk scanning range of SEVIRI and one of great meteorological importance as the main development area of Atlantic hurricanes. The most recent versions of the GOES-R Algorithm Working Group team algorithms (e.g., cloud mask, aerosol detection products, and LAP) implemented within the algorithms integration team framework (the NOAA operational system that will host these operational product algorithms) are used in the analyses. Forecasts from the National Centers for Environmental Prediction Global Forecasting System (NCEP GFS) are used for the LAP regression and direct comparisons. The GOES-R LAP retrievals are found to agree reasonably with the AEROSE RAOB observations, and overall retrievals improve both temperature and moisture against computer model NCEP GFS outputs. The validation results are then interpreted within the context of a difficult meteorological regime (e.g., Saharan air layers and dust) coupled with the difficulty of using a narrowband imager for the purpose of atmospheric sounding.

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Eric S. Maddy
,
Thomas S. King
,
Haibing Sun
,
Walter W. Wolf
,
Christopher D. Barnet
,
Andrew Heidinger
,
Zhaohui Cheng
,
Mitchell D. Goldberg
,
Antonia Gambacorta
,
Chen Zhang
, and
Kexin Zhang

Abstract

High spatial resolution measurements from the Advanced Very High Resolution Radiometer (AVHRR) on the Meteorological Operation (MetOp)-A satellite that are collocated to the footprints from the Infrared Atmospheric Sounding Interferometer (IASI) on the satellite are exploited to improve and quality control cloud-cleared radiances obtained from the IASI. For a partial set of mostly ocean MetOp-A orbits collected on 3 October 2010 for latitudes between 70°S and 75°N, these cloud-cleared radiances and clear-sky subpixel AVHRR measurements within the IASI footprint agree to better than 0.25-K root-mean-squared difference for AVHRR window channels with almost zero bias. For the same dataset, surface skin temperatures retrieved using the combined AVHRR, IASI, and Advanced Microwave Sounding Unit (AMSU) cloud-clearing algorithm match well with ECMWF model surface skin temperatures over ocean, yielding total uncertainties ≤1.2 K for scenes with up to 97% cloudiness.

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