Meteorological element data acquisition system suitable for small laboratories

Abstract

The invention discloses a meteorological element data acquisition system suitable for a small laboratory. The system is composed of at least one high-performance computing platform, a data preprocessing system, a WRF numerical weather forecast mode, a data post-processing system and a database system. The high-performance computing hardware platform is innovatively provided to acquire meteorological data in an area lacking meteorological data and a coarse-resolution gridding meteorological data downscaling system. In a specific area required by a user, meteorological data variables required bythe user are output; grid meteorological data with high spatial-temporal resolution and high precision are made. Medium and long term city group scale high spatial resolution weather forecast is carried out, basic meteorological data can be provided for air pollution, land surface hydrological process, urban climate, urban traffic and other disciplines, and finer regional scale climate change data can be provided for future climate change scene estimation (CMIP5).

Description

technical field [0001] The invention relates to the field of gridded meteorological data generation and production, in particular to a meteorological element data acquisition system suitable for small laboratories. Background technique [0002] Under the demand of scientific and refined management, design, planning and operation require meteorological data with high temporal and spatial resolution. At present, the China Meteorological Administration, the Ministry of Water Resources and the Ministry of Agriculture are sparing no effort to build a ground-based meteorological observation network. After nearly 60 years of construction, the number of stations in China's ground automatic weather observation network has exceeded 300,000. In eastern China, the spatial distribution density of weather stations has reached 1 / 10km 2 . In western China, meteorological stations are mainly deployed in areas with good ecological environment, but in complex mountainous areas with large sp...

AI Technical Summary

Problems solved by technology

[0010] First, the spatial heterogeneity of land cover is not considered, for example, the change of temperature on the windward slope with elevation is completely different from that on the leeward slope;

[0011] Second, the present invention requires relatively dense ground stations, or directly use coarse grid data as stations, but in western China or areas lacking meteorological observations, there may be generally not enough stations to fit the coefficients of the formula, so that the method cannot have universality;

[0013] Fourth, the probability distribution of precipitation is a gamma distribution, which cannot be superimposed in step 3, otherwise the magnitude and intensity accuracy of precipitation will be affected

This monthly-scale relationship has a very good relationship in areas with complex terrain in China. However, the land in eastern China is mainly farmland, and NDVI information is affected by farmland irrigation, so the accuracy of the statistical model with precipitation is not very good.

Secondly, the relationship between precipitation, NDVI and terrain information generally exists on a monthly scale. For daily and hourly scale information, there is currently no existing statistical distribution function for fitting

Therefore, in terms of time, the model can only be applied on the monthly scale, and its application is limited.

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