This dataset is derived from ERA5 atmospheric reanalysis data and ground-based meteorological observations across China. By employing a research-developed adaptive optimal interpolation assimilation method that accounts for the spatial distribution of observational stations, a daily gridded meteorological dataset with a spatial resolution of 25 km has been constructed. It covers mainland China (excluding territorial waters) and is tailored to support the new-type power systems. The dataset also includes high-impact weather events closely associated with the generation-side, grid-side, and demand-side of the new-type power systems. Its English designation is the China New-type Power Systems Meteorological dataset (CNPS-Met). This dataset provides a foundational resource for advancing interdisciplinary research and applications bridging meteorology and new-type power systems. Dataset files are named in the format: CNPS_Type_History_Daily_Variable_CCYY.nc, with all times provided in Coordinated Universal Time (UTC). Here, “Type” denotes the category related to meteorology and the components of the new-type power system, abbreviated as: Meteo (meteorological), Generation (generation-side), Grid (grid-side), and Demand (demand-side). “Variable” refers to the abbreviated variable name, and “CCYY” indicates the year (e.g., 1980). The meteorological variables include: tas (mean temperature at 2 m), tmax (maximum temperature at 2 m), tmin (minimum temperature at 2 m), precip (accumulated precipitation), wind (mean wind speed at 10 m), rhum (mean relative humidity at 2 m), shum (mean specific humidity at 2 m), pres (mean surface pressure). The high-impact weather events for the generation-side include: Vout (cut-out wind speed), Vin (cut-in wind speed), Lowrad (low solar radiation), Tmaxg (extreme high temperature), Tming (extreme low temperature). The high-impact weather events for the grid-side include: Icing (Ice accretion), Snowing (Snowfall), and Galloping (Conductor galloping). The high-impact weather events for the demand-side include: Tmaxd (extreme high temperature), Tmind (extreme low temperature), HHE (heat and humid environment or High enthalpy environment).
(1) ERA5 Land hourly data: 10m wind speed, 2m temperature, accumulated precipitation, 2m relative humidity, surface pressure. Download link: https://cds.climate.copernicus.eu/datasets/reanalysis-era5-land?tab=overview.
(2) Ground-based meteorological observations: 10m wind speed, 2m temperature, accumulated precipitation, 2m relative humidity, surface pressure. There are a total of 2598 sites. Download link: https://data.cma.cn/.
(1) Data preparation and preprocessing: Collect and organize data sources, complete unit conversion and format unification, and eliminate outliers through the "3 σ criterion".
(2) Assimilation based on the spatially adaptive optimal interpolation assimilation scheme proposed by our research group: this method dynamically adjusts the influence radius of the observation operator in the optimal interpolation assimilation scheme according to the spatial distribution and density of observation stations around the target grid point in the background field. The process iteratively optimizes the observation operator with the objectives of minimizing analysis field errors and maximizing correlation, thereby enhancing the effectiveness of the optimal interpolation assimilation scheme.
(3) Identification and extraction of high-impact weather events: high-impact weather events related to the generation-side, grid-side, and demand-side of the new-type power system are identified and extracted from multiple dimensions and levels, including power generation efficiency loss, equipment damage, and supply-demand imbalance. Their frequency, intensity, and other relevant metrics are calculated.
(4) Dataset output: the final data undergo format conversion and quality control, and are stored in a NetCDF format.
Evaluation results demonstrate that this dataset is of high quality, with the mean relative errors of wind speed, temperature, humidity, precipitation, and surface pressure across China all lower than those of the ERA5 reanalysis data and other datasets.
| # | number | name | type |
| 1 | SGGE0000JJJS2500093, SGGE0000JYJS2400043 | Research Program of Global Energy Interconnection Group Co., Ltd. | other |
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CSTR:11738.11.NCDC.NIEER.DB6972.2025
10.12072/ncdc.nieer.db6972.2025