Разработка и применение программы для автоматического нахождения невязки при пространственном контроле режимной метеорологической информации

Abstract

Objective: to develop and apply software for automatic finding of discrepancies in automated meteorological stations in order to identify dubious and unreliable data without direct manual control in Fortran using PostgreSQL programming language queries. Write a program block for processing data from the archive of the database of meteorological stations of the unified network. Having provided a connection, with the help of requests, to ensure the receipt of data of the averaged values of ten-minute meteorological reports according to a special processing technique. Create a subroutine for solving the equation by the least squares matrix method, compare it to check the results with the linear regression method in a third-party application. Ensure proper recording of data before sending them to the database, prepare the necessary table for correct demonstration of data and user convenience in their use. Formulate correct queries to send the results of finding the discrepancy to the database. Formulate queries to create the necessary table, formulate queries and identify conditions for the implementation of the program for its more “flexible”functioning, that is, the ability to process data and find a discrepancy in the case of non-daily operation of the program. Methods: the methodology is similar to the principles of recommendations for the analysis of the results of spatial monitoring of regime meteorological information of the Main Geophysical Observatory named after Voeikova A. I. Methods include the translation of coordinates into a Cartesian system and the implementation of the solution of equation systems by the least squares method. Results: a program has been created that can work without the participation of an operator, performing automatic startup, data processing and data recording for further storage. Practical importance: the program allows you to receive data quickly due to the fast processing speed without errors caused by the human factor.