| Observation errors of GPS radio occultation(RO)data is estimated by using the three-cornered hat method based on the five data sources: GPS RO observations,radiosonde observations,satellite Microwave Integrated Retrieval System(MiRS)products,the National Center for Environmental Prediction(NCEP)Global Forecast System(GFS)analysis data,and the European Centre for Medium-Range Weather Forecasts(ECMWF)ERA5 reanalysis data from January 1,2016 to October 1,2020.Biases and impacts of error correlations between any two of the above datasets on RO observation error estimate are considered and results are analyzed.Firstly,the mathematical details for estimating the RO observation error standard deviation are described.Then,the RO observation error standard deviations of both refractivity and bending angle near 471 radiosonde stations that are distributed around the globe are estimated.In past studies,RO observation errors are estimated based on RO observations,radiosonde observations,the GFS analysis data and the ERA5 reanalysis data.However,the three-cornered hat method assumes the four data sources involved in the calculation are independent,but the GFS analysis data and ERA5 reanalysis data are very likely correlated.In this study,we replaced the ERA5 reanalysis data by the MiRS data,which is independent of the GFS analysis data.The newly estimate RO observation errors are greater than those estimated by RO observations,radiosonde observations,GFS analysis data and ERA5 reanalysis data.The RO observation errors decrease toward high latitudes.Finally,the data distribution of the occultation observation data of GNOS,GNOS-Ⅱ,GRAS and TGRS in August 2022 in the Tibetan Plateau and the equatorial Middle East Pacific(115 ° W-70 ° W,40 ° S-0 °)region and the size of the lowest detection height are calculated.China is planning to build a global RO small-satellite constellation.This study is of great significance to the proper applications of the upcoming RO data. |
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