A Comparison of Hybrid‐Gain Versus Hybrid‐Covariance Data Assimilation for Global NWP-Reference-Cited by-同舟云学术

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A Comparison of Hybrid‐Gain Versus Hybrid‐Covariance Data Assimilation for Global NWP

Published:2022-08 Issue:8 Volume:14 Page:
ISSN:1942-2466
Container-title:Journal of Advances in Modeling Earth Systems
language:en
Short-container-title:J Adv Model Earth Syst

Author:

Whitaker Jeffrey S.¹^ORCID,Shlyaeva Anna²,Penny Stephen G.³⁴^ORCID

Affiliation:

1. NOAA Physical Sciences Laboratory Boulder CO USA

2. Joint Center for Satellite Data Assimilation University Corporation for Atmospheric Research Boulder CO USA

3. Cooperative Institute for Research in Environmental Sciences University of Colorado Boulder Boulder CO USA

4. Sofar Ocean Technologies San Francisco CA USA

Funder

Office of Naval Research Global

NOAA Research

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Environmental Chemistry,Global and Planetary Change

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2022MS003036

Reference21 articles.

1. Surface‐dependent correlated infrared observation errors and quality control in the FV3 framework

2. Four-dimensional ensemble variational data assimilation and the unstable subspace

3. EnKF and Hybrid Gain Ensemble Data Assimilation. Part II: EnKF and Hybrid Gain Results

4. The effect of improved ensemble covariances on hybrid variational data assimilation

5. Intercomparison of Variational Data Assimilation and the Ensemble Kalman Filter for Global Deterministic NWP. Part I: Description and Single-Observation Experiments

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1. Blending of global and regional ensembles in cycling hybrid ensemble-variational data assimilation for the convection-permitting prediction of typhoon Merbok (2017);Atmospheric Research;2024-09

2. Performance of a Hybrid Gain Ensemble Data Assimilation Scheme in Tropical Cyclone Forecasting with the GRAPES Model;Atmosphere;2023-03-16

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