61 research outputs found

    S-NPP ATMS Instrument Prelaunch and On-Orbit Performance Evaluation

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    The first of a new generation of microwave sounders was launched aboard the Suomi-National Polar-Orbiting Partnership satellite in October 2011. The Advanced Technology Microwave Sounder (ATMS) combines the capabilities and channel sets of three predecessor sounders into a single package to provide information on the atmospheric vertical temperature and moisture profiles that are the most critical observations needed for numerical weather forecast models. Enhancements include size/mass/power approximately one third of the previous total, three new sounding channels, the first space-based, Nyquist-sampled cross-track microwave temperature soundings for improved fusion with infrared soundings, plus improved temperature control and reliability. This paper describes the ATMS characteristics versus its predecessor, the advanced microwave sounding unit (AMSU), and presents the first comprehensive evaluation of key prelaunch and on-orbit performance parameters. Two-year on-orbit performance shows that the ATMS has maintained very stable radiometric sensitivity, in agreement with prelaunch data, meeting requirements for all channels (with margins of ~40% for channels 1-15), and improvements over AMSU-A when processed for equivalent spatial resolution. The radiometric accuracy, determined by analysis from ground test measurements, and using on-orbit instrument temperatures, also shows large margins relative to requirements (specified as <1.0K for channels 1, 2, and 16-22 and <0.75 K for channels 3-15). A thorough evaluation of the performance of ATMS is especially important for this first proto-flight model unit of what will eventually be a series of ATMS sensors providing operational sounding capability for the U.S. and its international partners well into the next decade

    The Moon as a photometric calibration standard for microwave sensors

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    IMPROVED SATELLITE MICROWAVE RETRIEVALS AND THEIR INCORPORATION INTO A SIMPLIFIED 4D-VAR VORTEX INITIALIZATION USING ADJOINT TECHNIQUES

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    Microwave instruments provide unique radiance measurements for observing surface properties and vertical atmosphere profiles in almost all weather conditions except for heavy precipitation. The Advanced Microwave Scanning Radiometer 2 (AMSR2) observes radiation emitted by Earth at window channels, which helps to retrieve surface and column integrated geophysical variables. However, observations at some X- and K-band channels are susceptible to interference by television signals transmitted from geostationary satellites when AMSR2 is scanning regions including the U.S. and Europe, which is referred to as Television Frequency Interference (TFI). It is found that high reflectivity over the ocean surface is favorable for the television signals to be reflected back to space. When the angle between the Earth scene vector and the reflected signal vector is small enough, the reflected TV signals will enter AMSR2’s antenna. As a consequence, TFI will introduce erroneous information to retrieved geophysical products if not detected. This study proposes a TFI correction algorithm for observations over ocean. Microwave imagers are mostly for observing surface or column-integrated properties. In order to have vertical temperature profiles of the atmosphere, a study focusing on the Advanced Technology Microwave Sounder (ATMS) is included. A traditional AMSU-A temperature retrieval algorithm is modified to remove the scan biases in the temperature retrieval and to include only those ATMS sounding channels that are correlated with the atmospheric temperatures on the pressure level of the retrieval. The warm core structures derived for Hurricane Sandy when it moved from the tropics to the mid-latitudes are examined. Significant improvements have been obtained for the forecasts of hurricane track, but not intensity, especially during the first 6-12 hours. In this study, a simplified four-dimensional variational (4D-Var) vortex initialization model is developed to assimilate the geophysical products retrieved from the observations of both microwave imagers and microwave temperature sounders. The goal is to generate more realistic initial vortices than the bogus vortices currently incorporated in the Hurricane Weather Research and Forecasting (HWRF) model in order to improve hurricane intensity forecasts. The case included in this study is Hurricane Gaston (2016). The numerical results show that the satellite geophysical products have a desirable impact on the structure of the initialized vortex

    Inter-channel uniformity of a microwave sounder in space

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    We analyzed intrusions of the Moon in the deep space view of the Advanced Microwave Sounding Unit-B on the NOAA-16 satellite and found no significant discrepancies in the signals from the different sounding channels between 2001 and 2008. However, earlier investigations had detected biases of up to 10 K, by using simultaneous nadir overpasses of NOAA-16 with other satellites. These discrepancies in the observations of Earth scenes cannot be due to non-linearity of the receiver or contamination of the deep space view without affecting the signal from the Moon as well. As neither major anomalies of the on-board calibration target nor the local oscillator were present, we consider radio frequency interference in combination with a strongly decreasing gain the most obvious reason for the degrading photometric stability. By means of the chosen example we demonstrate the usefulness of the Moon for investigations of the performance of microwave sounders in flight.</p

    CIRA annual report FY 2015/2016

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    Reporting period April 1, 2015-March 31, 2016

    Study of Mars geoscience orbiter and lunar geoscience orbiter, revision 1. Volume 1: Technical

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    The feasibility and efficiency of using an existing Earth orbiter to perform planetary missions was evaluated

    CIRA annual report FY 2013/2014

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    Research theme reports from April 1, 2019 - March 31, 2020

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    CIRA annual report FY 2016/2017

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    Reporting period April 1, 2016-March 31, 2017

    CIRA annual report FY 2017/2018

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    Reporting period April 1, 2017-March 31, 2018
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