Impact of Ground Based GPS Data on Numerical Weather Prediction

Abstract

A study on the impact of zenith total delays (ZTD's) obtained from observations by ground based Global Positioning System (GPS) receivers in Europe on the skill of numerical weather prediction (NWP) is presented. The ZTD depends mainly on the local pressure at the GPS site and the integrated water vapour in the column above. Both pressure and humidity information are vital to NWP models, but it is mainly as a source of humidity information the ZTD's are expected to be significant to NWP models. Given the currently meagre amount of humidity observations the inclusion of ZTD's in the data assimilation, determining the starting states for NWP forecasts, is expected to improve forecast skill. Groups in Europe, the US, and Japan are carrying out impact and other studies to assess whether such expectations can be fulfilled.
We here present results from parallel runs, with and without ZTD data in the data assimilation, for the period of February 2002, using European ZTD data from the COST Action 716 data sample. Data from 117 GPS stations are included in the assimilations. The runs are performed using the spectral version of the HIRLAM local area NWP model and its variational data assimilation system, HIRVDA, in 3DVar mode. The simulations have been carried out at both 0.45 and 0.15 degree resolution. It is found that statistical verification against observations (heights, winds, temperatures, humidities) from stations on the EWGLAM list indicates mainly neutral impact of GPS ZTD's in this period, with the exception that systematic improvements are seen in the geopotential heights. A detailed comparison of NWP forecasts of precipitation is performed against 12 hour rain gauge observations. Both contingency tables and in particular detailed comparisons (by eye) of precipitation maps show that for this period inclusion of ground based GPS ZTD observations improve the prediction of strong precipitation.
In combination with our previous results, (Vedel and Huang 2003), and those reported by other groups, this solidifies the conclusion that GPS ZTD data will improve NWP forecast skill of precipitation. Questions remain to be solved before ground based GPS data can be used in an optimal way in NWP models. These include better knowledge of the errors and error correlations of both the ZTD observations and of the NWP first guess field, as well as better ways of comparing model and observed precipitation. The new European project TOUGH (Targeting Optimal Use of GPS Humidity Observations in Meteorology) will address some of these issues.