A data assimilation technique to account for the nonlinear dependence of scattering microwave observations of precipitation-Reference-Cited by-同舟云学术

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A data assimilation technique to account for the nonlinear dependence of scattering microwave observations of precipitation

Published:2015-06-05 Issue:11 Volume:120 Page:5548-5563
ISSN:2169-897X
Container-title:Journal of Geophysical Research: Atmospheres
language:en
Short-container-title:J. Geophys. Res. Atmos.

Author:

Haddad Z. S.¹²,Steward J. L.¹²,Tseng H.‐C.³,Vukicevic T.⁴,Chen S.‐H.³,Hristova‐Veleva S.¹²

Affiliation:

1. Jet Propulsion LaboratoryCalifornia Institute of Technology Pasadena California USA

2. Joint Institute For Regional Earth System Science and EngineeringUniversity of California Los Angeles California USA

3. Department of Land, Air and Water ResourcesUniversity of California Davis California USA

4. AOMLNOAA Miami Florida USA

Funder

National Oceanic and Atmospheric Administration

Publisher

American Geophysical Union (AGU)

Subject

Space and Planetary Science,Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/2015JD023107

Reference19 articles.

1. The HWRF Hurricane Ensemble Data Assimilation System (HEDAS) for High-Resolution Data: The Impact of Airborne Doppler Radar Observations in an OSSE

2. Displaced Ensemble Variational Assimilation Method to Incorporate Microwave Imager Brightness Temperatures into a Cloud-resolving Model

3. Implementation of 1D+4D-Var assimilation of precipitation-affected microwave radiances at ECMWF. I: 1D-Var

4. MiRS: An All-Weather 1DVAR Satellite Data Assimilation and Retrieval System

5. The Impact of Assimilating SSM/I and QuikSCAT Satellite Winds on Hurricane Isidore Simulations

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2. Developing a Radar Signal Simulator for the Community Radiative Transfer Model;IEEE Transactions on Geoscience and Remote Sensing;2023

3. A Neural Network-Based Observation Operator for Coupled Ocean-Acoustic Variational Data Assimilation;Monthly Weather Review;2021-04-13

4. A 1D Bayesian Inversion Applied to GPM Microwave Imager Observations: Sensitivity Studies;Journal of the Meteorological Society of Japan. Ser. II;2021

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