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Evaluation of the Climate Prediction System CMA-CPSv3 on Performances of Precipitation and Temperature Prediction over the Tibetan Plateau

DOI: 10.4236/jdaip.2024.124026, PP. 495-509

Keywords: CMA-CPSv3, Prediction Assessment, Precipitation, Temperature, Tibetan Plateau

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Abstract:

In order to evaluate the prediction performances of the climate prediction system developed by the China Meteorological Administration (CMA-CPSv3) over the Tibetan Plateau region, the precipitation and temperature predicted by CMA-CPSv3 at different lead time was evaluated for the period of 2001-2023, by comparing with observations—the monthly precipitation of the CMAP and 2 m temperature data of the NCEP/DOE reanalysis data. The main conclusions were as follows: 1) the forecast skill of the model is very sensitive to the initial conditions and value, and the model forecast capability decreases rapidly as the lead time is extended. 2) CPSv3 performed well in capturing the spatial distribution of precipitation over Tibet in January, August, October, November and December at 0-month lead, and the forecast skill is relatively poor in March and April. CPSv3 has better performance in the east-central part of the land in January, in the central and western part of the region in March, in the whole region in April, in the northern part of Nagchu, northern part of Chamdo and central part of Shigatse in July, in the eastern part of Chamdo, northern part of Nagchu and northern part of Ali in August, in the whole region in September, and in the cities of Shigatse and Shannan in November. 3) At each lead time, the forecast skill for 2-m temperatures was higher than that for precipitation. For 2-m temperature, CPSv3 performed best in January, May, July, August, September, October, and December, while performing relatively poor in March, April, and November. Specifically, the prediction skill is higher in January and December for most of the regions, for Shigatse and Ali in May, for southern Shannan in July, and for northern Nagchu and southern Shannan in August, and there is some prediction skill in March, April and October, while CPSv3 performed poorly in November.

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