An assessment of the impact of ATMS and CrIS data assimilation on precipitation prediction over the Tibetan Plateau
Using the National Oceanic and Atmospheric Administration's Gridpoint Statistical Interpolation data assimilation system and the National Center for Atmospheric Research's Advanced Research Weather Research and Forecasting (WRF-ARW) regional model, the impact of assimilating Advanced Te...
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2017-07-01
|
Series: | Atmospheric Measurement Techniques |
Online Access: | https://www.atmos-meas-tech.net/10/2517/2017/amt-10-2517-2017.pdf |
Summary: | Using the National Oceanic and Atmospheric Administration's Gridpoint
Statistical Interpolation data assimilation system and the National Center
for Atmospheric Research's Advanced Research Weather Research and Forecasting
(WRF-ARW) regional model, the impact of assimilating Advanced Technology
Microwave Sounder (ATMS) and Cross-track Infrared Sounder (CrIS) satellite
data on precipitation prediction over the Tibetan Plateau in July 2015 was
evaluated. Four experiments were designed: a control experiment and three
data assimilation experiments with different data sets injected: conventional
data only, a combination of conventional and ATMS satellite data, and a
combination of conventional and CrIS satellite data. The results showed that
the monthly mean of precipitation is shifted northward in the simulations and
showed an orographic bias described as an overestimation upwind of the
mountains and an underestimation in the south of the rain belt. The rain
shadow mainly influenced prediction of the quantity of precipitation,
although the main rainfall pattern was well simulated. For the first 24 h
and last 24 h of accumulated daily precipitation, the model generally
overestimated the amount of precipitation, but it was underestimated in the
heavy-rainfall periods of 3–5, 13–16, and 22–25 July. The observed water
vapor conveyance from the southeastern Tibetan Plateau was larger than in the
model simulations, which induced inaccuracies in the forecast of heavy rain
on 3–5 July. The data assimilation experiments, particularly the ATMS
assimilation, were closer to the observations for the heavy-rainfall process
than the control. Overall, based on the experiments in July 2015, the
satellite data assimilation improved to some extent the prediction of the
precipitation pattern over the Tibetan Plateau, although the simulation of
the rain belt without data assimilation shows the regional shifting. |
---|---|
ISSN: | 1867-1381 1867-8548 |