CSTR:11738.11.ncdc.XBSAQ.db2225.2022
10.12072/ncdc.XBSAQ.db2225.2022
Based on the basic theory of air water resources, the water substances in the atmosphere locked by the secondary circulation formed by the special boundary layer and with the potential of phase transformation into clouds and precipitation are defined as effective water vapor, and then the effective water vapor identification algorithm is developed based on the water vapor convergence area, and the regional exploitable air water resources (i.e. effective water vapor) The total amount and air water resources precipitation potential are evaluated.
& emsp; The source data is the monthly grid data of the new generation typical concentration emission path scenario (rcp4.5) in the fifth coupled mode comparison plan (cmip5). The download address is: https://esgf-node.llnl.gov/search/cmip5/
& emsp; (1) Based on cmip5 specific humidity data, the spatial resolution is unified to 0.75 ° × 0.75 °, the precipitable water matrix is calculated by using the integral formula of the whole layer.
& emsp; (2) Based on cmip5 monthly precipitation grid data, the spatial resolution is unified to 0.75 ° × 0.75 °, calculate the ratio matrix of precipitation and available precipitation in each grid point, that is, the precipitation conversion rate matrix. Use Python statistical analysis library to cut the data points in the study area and make the regional average to obtain the available precipitation conversion rate data.
& emsp; (3) Based on cmip5 specific humidity and wind speed data, the spatial resolution is unified to 0.75 ° × 0.75 °, the water vapor flux divergence matrix is calculated, and the air water resource enrichment area is identified.
& emsp; (4) Considering that artificial rainfall enhancement measures can increase rainfall efficiency, the rainfall matrix can be obtained by implementing the rainfall enhancement operation theory in the air water resources enrichment area.
& emsp; (5) Based on cmip5 runoff data, the spatial resolution is unified to 0.75 ° × 0.75 °, calculate the runoff conversion coefficient of each grid point to obtain the theoretically increased runoff matrix.
& emsp; (6) Finally, the seasonal average and annual average are carried out to obtain the seasonal data at all levels in the region.
Statistical analysis was carried out in strict accordance with relevant methods, standards and specifications, and the data quality was good.
| # | number | name | type |
| 1 | 2017YFC0404300 | National key R & D plan |
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
