First results about evaluation of forecasted numerical weather model data set in view of neutral atmosphere delay

The neutral atmosphere that extending from the surface of earth to about 80 km overhead is the electrically neutral part (within a certain frequency band which GNSS signals fall) of the atmosphere. There is no doubt that neutral atmosphere has a delaying effect on transmitted radio waves. Spilker (1996) noted that the more precise term of this delaying effect is neutral atmosphere delay, even though this delaying effect has been traditionally referred to as just troposphere delay. At all events, the delaying effect has propagated into satellite observations, and we must deal with it appropriately in order to achieve precise satellite positioning results. There are many geodesists have been making their contributions to treatment of neutral atmosphere delay, and how to get satisfactory supports from numerical weather model data set is one of the efforts making to calibrate this delaying effect more precisely up-to-date. Currently, both Earth observation network and technology have great improvement, which results in wonderful increase of Earth observational data as well as the subsequent numerical weather model data set. Briefly speaking, numerical weather model data set which generally provided by different organizations and/or institutions is a global and/or regional gridded meteorological data set with specific temporal-spatial resolution. Generally, reanalysis data set and forecast data set are usually considered to be the two main data set representations, and they both provide two types of data level, i.e., three-dimensional pressure levels and two-dimensional surface level. The data set contains some usually used meteorological parameters, such as height, temperature, pressure, humidity. With these meteorological parameters, some main terms related to neutral atmosphere delay, such as hydrostatic/wet delay, gradient factors and mapping factors can all be calculated without any difficulty by using computing techniques like raytracing and interpolation. Undoubtedly, the performance of different types of data set that mentioned above in representing neutral atmosphere delay are not all the same. Definitely, some interesting and meaningful comparison results have found and widely propagated by many scholars. In this work, we put more emphasis on evaluation of the forecast data set from neutral atmosphere delay point of view, considering there is an objective fact that satellite positioning industry especially the (near) real-time positioning has vigorous development, in which the calibration of neutral atmosphere delay is required more and more accurate and timely-supported. Besides time-delayed reanalysis data set and time-advanced forecast data set, microwave radiometer data set and radiosonde data set are also employed. The first results show that empirical model such as UNB3 can only state the normal level of delaying effect and the obtained delay values are either larger or smaller; the pressure levels data set performs better than the surface level data set with very high proportion in time domain; even though reanalysis data set generally has good performance, forecast data set can work for the neutral atmosphere delay calibration with relatively satisfactory support in term of accuracy.

This work is supported by the National Natural Science Foundation of China (42304010), the Youth Foundation of Changzhou Institute of Technology (E3-6207-21-060, 31020222007).