Meteorological element determination method for 30m resolution interpolation

Abstract

The invention discloses a meteorological element determination method for 30m resolution interpolation. The method comprises the following steps of: obtaining low-spatial resolution DEM data through spatial aggregation by utilizing 30m resolution digital elevation data, constructing a linear regression relationship among air temperature, specific humidity and the like in CLDAS data, terrain and geographic position factors on a low-spatial resolution scale, and then, applying the constructed linear relationship to a high-resolution scale, and estimating meteorological factors such as air temperature and specific humidity at the resolution of 30m by utilizing the elevation, gradient, slope direction, longitude and latitude of the resolution of 30m, thereby realizing the generation of a refined and high-resolution grid product of air temperature, air humidity and sunshine duration.

Description

Technical field [0001] The present invention relates to the field of meteorological detection, and more particularly to a meteorological element determination method for 30M resolution interpolation. Background technique [0002] Characteristic crop plantation, agricultural meteorological disaster monitoring, early warning, agricultural products quality assessment and forecast, agricultural insurance, etc. Although the spatial resolution of climate model products at home and abroad is increasing, such as meteorological information center land surface assimilation system (CLDAS) atmospheric-driven product spatial resolution can reach 0.0625 ° × 0.0625 °, but the upper mat is complex, terrain Duplex area, due to meteorological elements, such as temperature, humidity, solar radiation, etc., the spatial resolution of climate mode products is still low, and it is still not possible to apply to agricultural meteorological services. Therefore, it is necessary to develop a desiration tec...

AI Technical Summary

Problems solved by technology

Although the spatial resolution of climate model products at home and abroad is getting higher and higher, for example, the spatial resolution of atmospheric drive field products of the Meteorological Information Center Land Assimilation System (CLDAS) can reach 0.0625°×0.0625°. In areas with large fluctuations, due to the large spatial differences of meteorological elements (such as temperature, humidity, solar radiation, etc.), the spatial resolution of climate model products is still significantly low, and they cannot be well applied to agricultural meteorological services.

Images