The Central Asia Reanalysis (CAR) dataset is generated based on the Weather Research and Forecast (WRF) model version 4.1.2 and WRF Data Assimilation (WRFDA) Version 4.1.2. Variables include temperature,, pressure, wind speed, precipitation and radiation. The reanalysis is established through cyclic assimilation, which performs data assimilation every 6 hours by 3DVAR. The assimilated data include conventional atmospheric observation and satellite radiation data. The main source of conventional data is Global Teleconnection System (GTS), including surface station, automatic station, radiosonde and aircraft report, and the observation elements include temperature, air pressure, wind speed and humidity. Satellite observations include retrievals and radiation data, The retrievals are mainly atmospheric motion vectors from polar orbiting meteorological satellites (NOAA-18, NOAA-19, MetOP-A and MetOP-B) and resampled to a horizontal resolution of 54km; the radiation data includes microwave radiation from MSU, AMSU and MHS and HIRS infrared radiation data. The simulation applies nesting with a horizontal resolution of 27km and 9km respectively, a total of 38 layers in the vertical direction and a top of the model layer of 10hPa. The lateral boundary conditions of the model are provided by ERA-Interim every 6 hours. The physical schemes used in the model are Thompson microphysics scheme, CAM radiation scheme, MYJ boundary layer scheme, Grell convection scheme and Noah land surface model. The data covers five countries in Central Asia, including Kazakhstan, Tajikistan, Kyrgyzstan, Turkmenistan and Uzbekistan, as well as lakes in Central Asia, such as Caspian Sea, Aral Sea, Balkash lake and Isaac lake, which can be used for the study of climate, ecology and hydrology in the region. Compared with gauge-based precipitation in Central Asia, the simulation by CAR shows similar performance with MSWEP ( a merged product) and outperforms ERA5 and ERA-Interim.

File naming and required software

The data storage format is NetCDF, which is a self describing file. The data file itself contains the description information The name of the data file is "var_car_freq_res_yyyy. nc". The static information (terrain height, land use, vegetation cover, etc.) file name is "geo_res.nc". "var" represents variables, for example, "ta" represents mean temperature, "ws" represents wind speed, "ps" represents surface pressure, "lw" represents surface downward longwave radiation, "sw" represents surface downward shortwave radiation, "pr" represents precipitation, "tmax" represents daily maximum temperature and "tmin" represents daily minimum temperature. "freq" and "res" stand for temporal and horizontal resolution respectively. Daily and monthly data at resolutions of 27km and 9km are available. "yyyy" stands for year.
It is recommended to use NCL or Python related modules (such as xarray) to process data.

Data Citations Data citation guideline What's data citation?

Cite as:

Yao, Y. (2021). Central Asia Reanalysis dataset (1979-2017). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Atmos.tpdc.271917. CSTR: 18406.11.Atmos.tpdc.271917. (Download the reference： RIS | Bibtex )

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.

References literature

1.Yao, Y., Luo, Y., Huang, J.B., & Ma, J.Y. (2020). Improving the downscaled springtime temperature in Central Asia through assimilating meteorological and snow cover observations. Atmospheric Research, 258, 105619 (View Details )

Support Program

Pan-Third Pole Environment Study for a Green Silk Road-A CAS Strategic Priority A Program (No:XDA20000000)

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