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Development and Evaluation of an Ensemble-Based Data Assimilation System for Regional Reanalysis Over the Tibetan Plateau and Surrounding Regions

Journal article
Authors J. He
F. Q. Zhang
X. C. Chen
X. H. Bao
Deliang Chen
H. M. Kim
Hui-Wen Lai
L. R. Leung
X. L. Ma
Z. Y. Meng
Tinghai Ou
Z. N. Xiao
E. Y. O. Yang
K. Yang
Published in Journal of Advances in Modeling Earth Systems
Volume 11
Issue 8
Pages 2503-2522
Publication year 2019
Published at Department of Earth Sciences
Pages 2503-2522
Language en
Links https://doi.org/10.1029/2019MS00166...
Keywords scale data assimilation, variational data assimilation, doppler radar, observations, sky infrared radiances, kalman filter, operational, implementation, era-interim, precipitation event, ncep-ncar, prediction
Subject categories Earth and Related Environmental Sciences

Abstract

The Tibetan Plateau is regarded as the Earth's Third Pole, which is the source region of several major rivers that impact more 20% the world population. This high‐altitude region is reported to have been undergoing much greater rate of weather changes under global warming, but the existing reanalysis products are inadequate for depicting the state of the atmosphere, particularly with regard to the amount of precipitation and its diurnal cycle. An ensemble Kalman filter (EnKF) data assimilation system based on the limited‐area Weather Research and Forecasting (WRF) model was evaluated for use in developing a regional reanalysis over the Tibetan Plateau and the surrounding regions. A 3‐month prototype reanalysis over the summer months (June−August) of 2015 using WRF‐EnKF at a 30‐km grid spacing to assimilate nonradiance observations from the Global Telecommunications System was developed and evaluated against independent sounding and satellite observations in comparison to the ERA‐Interim and fifth European Centre for Medium‐Range Weather Forecasts Reanalysis (ERA5) global reanalysis. Results showed that both the posterior analysis and the subsequent 6‐ to 12‐hr WRF forecasts of the prototype regional reanalysis compared favorably with independent sounding observations, satellite‐based precipitation versus those from ERA‐Interim and ERA5 during the same period. In particular, the prototype regional reanalysis had clear advantages over the global reanalyses of ERA‐Interim and ERA5 in the analysis accuracy of atmospheric humidity, as well as in the subsequent downscale‐simulated precipitation intensity, spatial distribution, diurnal evolution, and extreme occurrence.

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