Quality control method and quality monitoring device of upper-air wind data

Abstract

The invention discloses a quality control method of upper-air wind data and a quality monitoring device of the upper-air wind data. The quality control method of the upper-air wind data comprises the following steps that: whether thermal wind residual errors of sounding data collected by each sounding station, in corresponding standard constant-pressure surfaces, is in a pre-set maximally-permissible error range, is judged; whether dynamic coordination exists in wind fields and temperature fields of the sounding data collected by each sounding station on two adjacent standard constant-pressure surfaces is judged; and therefore, corresponding quality control codes can be provided for the sounding data collected by each sounding station. With the quality control method of the upper-air wind data of the invention, a situation that large scale dynamics balance constraints are mainly adopted in current upper-air data quality control are changed. The quality control method of the upper-air data is based on statistical distribution of thermal wind residual errors. According to the quality control method of the upper-air wind data, full consideration is given to temporal and spatial distribution characteristics of difference values between thermal wind and actual wind shear, and requirements of work such as increasingly-refined climate statistics and numerical value forecast for accuracy and integrity of upper-air observation data can be satisfied.

Description

technical field [0001] The invention relates to a quality control method of high-altitude wind data and a quality monitoring device thereof, in particular to a method for quality control of high-altitude wind observation data aiming at the dynamic synergy between high-altitude wind field and temperature field, belonging to the field of atmospheric science research , used to effectively reduce the uncertainty of regional climate change analysis results in China. Background technique [0002] Before using meteorological data for climate change research, such as climate statistics and numerical forecasting, quality control is generally required. The reason is that, on the one hand, there may be errors in meteorological data in the process of observation, data processing, coding, sending and interpreting; on the other hand, changes in sounding observation instruments and measurement methods may also lead to errors in observation results. ; Therefore, if the quality control of m...

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Problems solved by technology

However, in the actual atmospheric movement, these balance relations, especially the geostrophic balance, do not always hold true everywhere, so it is inevitable to lead to misjudgments and missed judgments in the process of quality control.

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