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Derived Observations From Frequently Sampled Microwave Measurements of Precipitation. Part II: Sensitivity to Atmospheric Variables and Instrument Parameters.
- Source :
- IEEE Transactions on Geoscience & Remote Sensing; May2017, Vol. 55 Issue 5, p2898-2912, 15p
- Publication Year :
- 2017
-
Abstract
- This is the second of two papers that quantify the high added value of frequent 3-D radar observations of the atmosphere to capture the dynamics of weather systems. Recent advances in small-satellite and radar technologies, such as the “Radar in Cubesat” developed at the Jet Propulsion Laboratory, are paving the way for the design of convoys of spaceborne radars that can directly observe the evolution of severe weather at very fine temporal scales. The analyses presented here are to establish the relation between such observations to the underlying cloud variables and processes, and to quantify the sensitivity to the different physical and instrument parameters. In this paper, we quantify the uncertainty in the relation between the measured radar reflectivities Z and their time derivatives d_{t} Z , on one hand, and the underlying rate of change of the condensed-water mass M$ , and fluxes of dry and moist air in convection, on the other hand. The uncertainties are due to the variability of the atmospheric parameters as well as the constraints of an observation strategy that would use pairs of spaceborne instruments. We specifically analyze the sensitivities for pairs of satellites, each carrying a Ka-band profiling radar. Our simulations show that, with a convoy of two spacecraft separated by ~90 s, each with a pointing accuracy of ~0.025° in rms error, a sensitivity of 17 dBZ and a precision of 1 dBZ, the proposed observation strategy would capture more than 70% of the tropical convection between 5 and 10 km of altitude and resolve the air-mass and condensed-water fluxes. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01962892
- Volume :
- 55
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Geoscience & Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 124146482
- Full Text :
- https://doi.org/10.1109/TGRS.2017.2656061