Meteorological element data acquisition system suitable for small laboratories

A meteorological element and data acquisition technology, applied in the field of meteorological element data acquisition system, can solve problems such as large application limitations, influence of precipitation magnitude and intensity accuracy, and failure to take into account the spatial heterogeneity of the surface, so as to achieve improved spatial resolution, Improve the effect of time

Pending Publication Date: 2019-11-08
北京中科资环信息技术研究院
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AI-Extracted 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 in...
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Method used

Reanalysis data has adopted global data assimilation system and perfect database, the observation data of various sources (ground, ship, radiosonde, wind balloon, aircraft, satellite etc.) are carried out quality control...
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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).

Application Domain

Technology Topic

High performance computationFuture climate +14

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  • Meteorological element data acquisition system suitable for small laboratories

Examples

  • Experimental program(1)

Example Embodiment

[0050] A specific embodiment of the present invention will be described in detail below with reference to the accompanying drawings, but it should be understood that the protection scope of the present invention is not limited by the specific embodiment.
[0051] Embodiments of the present invention relate to definitions of acronyms and key terms
[0052] extrapolate
[0053] The process of estimating data for unobserved points outside the area of ​​observed points is called extrapolation.
[0054] Interpolate
[0055] The process of estimating data for unobserved points within an area of ​​observed points is called interpolation.
[0056] WRF
[0057] The full English name is The Weather Research and Forecasting Model, the weather forecast model. WRF mode is fully compressible and non-static mode, written in F90 language. Arakawa C grid points are used in the horizontal direction, and terrain following mass coordinates are used in the vertical direction. The WRF mode uses a third- or fourth-order Runge-Kutta algorithm for time integration. The WRF model can not only be used for the case simulation of real weather, but also can be used as a theoretical basis for the discussion of basic physical processes by using the modules it contains to reanalyze data.
[0058] The re-analysis data adopts the global data assimilation system and perfect database to conduct quality control and assimilation of observation data from various sources (ground, ship, radiosonde, wind balloon, aircraft, satellite, etc.), and obtain a set of The complete reanalysis data set not only contains many elements and a wide range, but also extends over a long period of time. It is a comprehensive data set.
[0059] CRA40
[0060] Global atmospheric reanalysis produced by the China Meteorological Administration.
[0061] ground data
[0062] The data obtained by the ground meteorological observation instruments at the specified time and at the specified location.
[0063] CMIP5
[0064] The full English name is the Coupled Model Inter-comparison Project, Phase 5, which is the fifth coupled model comparison plan. It is to archive the results of global models such as atmospheric models and ocean models under the same boundary conditions and the same simulation time. At present, it is mainly used in future climate change research.
[0065] DEM
[0066] Digital Elevation Model.
[0067] GCM
[0068] Generalized general circulation (atmosphere or ocean) model, computed using Navier–Stokes on a rotating sphere and thermodynamic terms. This enables simulations of the Earth's atmosphere and ocean circulation. At present, it is mainly used in climate forecasting and climate change research.
[0069] GFS
[0070] The full English name is The Global Forecast System (GFS). This is the mode of operation with the National Centers for Environmental Prediction (NCEP) in the United States. This model can carry out medium-term weather forecasts up to 384 hours, the highest spatial resolution can reach 28km, and can output a large number of variables of atmospheric and land surface processes.
[0071] spatiotemporal resolution
[0072] Shorthand for temporal resolution and spatial resolution. Temporal resolution refers to the smallest interval at which data can reflect a time scale, such as days, hours, minutes, etc. Spatial resolution refers to gridded data, the interval between grid points, such as km.
[0073] like figure 1 On the basis of global/regional forecast data, this system can carry out high spatial resolution weather forecast at the scale of medium and long-term urban agglomerations from 240 hours to 384 hours. Transportation and other disciplines provide basic meteorological data, and this system can provide more refined regional-scale climate change data for future climate change scenario projections (CMIP5).
[0074] The above disclosures are only a few specific embodiments of the present invention, however, the embodiments of the present invention are not limited thereto, and any changes that can be conceived by those skilled in the art should fall within the protection scope of the present invention.
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