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  • Author or Editor: F. K. Li x
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S. L. Durden
,
E. Im
,
F. K. Li
,
W. Ricketts
,
A. Tanner
, and
W. Wilson

Abstract

A new airborne rain-mapping radar (ARMAR) has been developed by NASA and the Jet Propulsion Laboratory for operation on the NASA Ames DC-8 aircraft. The radar operates at 13.8 GHz, the frequency to be used by the radar on the Tropical Rainfall Measuring Mission (TRMM). ARMAR simulates the TRMM radar geometry by looking downward and scanning its antenna in the cross-track direction. This basic compatibility between ARMAR and TRMM allows ARMAR to provide information useful for the TRMM radar design, for rain retrieval algorithm development, and for postlaunch calibration. ARMAR has additional capabilities, including multiple polarization, Doppler velocity measurement, and a radiometer channel for brightness temperature measurement. The system has been tested in both ground-based and airborne configurations. This paper describes the design of the system and shows results of field tests.

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S. L. Durden
,
Z. S. Haddad
,
A. Kitiyakara
, and
F. K. Li

Abstract

The Tropical Rainfall Measuring Mission (TRMM) will carry the first spaceborne radar for rainfall observation. Because the TRMM Precipitation Radar (PR) footprint size of 4.3 km is greater than the scale of some convective rainfall events, there is concern that nonuniform filling of the PR antenna beam may bias the retrieved rain-rate profile. The authors investigate this effect theoretically and then observationally using data from the NASA Jet Propulsion Laboratory Airborne Rain Mapping Radar (ARMAR), acquired during Tropical Oceans Global Atmosphere Coupled Ocean–Atmosphere Response Experiment in early 1993. The authors’ observational approach is to simulate TRMM PR data using the ARMAR data and compare the radar observables and retrieved rain rate from the simulated PR data with those corresponding to the high-resolution radar measurements. The authors find that the path-integrated attenuation and the resulting path-averaged rain rate are underestimated. The reflectivity and rain rate near the top of the rainfall column are overestimated. The near-surface reflectivity can be overestimated or underestimated, with a mean error very close to zero. The near-surface rain rate, however, is usually underestimated, sometimes severely.

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Sid-Ahmed Boukabara
,
Isaac Moradi
,
Robert Atlas
,
Sean P. F. Casey
,
Lidia Cucurull
,
Ross N. Hoffman
,
Kayo Ide
,
V. Krishna Kumar
,
Ruifang Li
,
Zhenglong Li
,
Michiko Masutani
,
Narges Shahroudi
,
Jack Woollen
, and
Yan Zhou

Abstract

A modular extensible framework for conducting observing system simulation experiments (OSSEs) has been developed with the goals of 1) supporting decision-makers with quantitative assessments of proposed observing systems investments, 2) supporting readiness for new sensors, 3) enhancing collaboration across the community by making the most up-to-date OSSE components accessible, and 4) advancing the theory and practical application of OSSEs. This first implementation, the Community Global OSSE Package (CGOP), is for short- to medium-range global numerical weather prediction applications. The CGOP is based on a new mesoscale global nature run produced by NASA using the 7-km cubed sphere version of the Goddard Earth Observing System, version 5 (GEOS-5), atmospheric general circulation model and the January 2015 operational version of the NOAA global data assimilation (DA) system. CGOP includes procedures to simulate the full suite of observing systems used operationally in the global DA system, including conventional in situ, satellite-based radiance, and radio occultation observations. The methodology of adding a new proposed observation type is documented and illustrated with examples of current interest. The CGOP is designed to evolve, both to improve its realism and to keep pace with the advance of operational systems.

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