An inter-comparison of zenith tropospheric delays derived from DORIS and GPS data

Doppler Orbitography Radiopositioning Integrated by Satellite (DORIS) and Global Positioning System (GPS) techniques are similarly affected by propagation delays in the neutral atmosphere (troposphere) and hence make use of similar data processing strategies for reducing this effect. We compare Zenith Tropospheric Delays (ZTDs) estimated from 52 DORIS and GPS station pairs co-located at 35 sites over the 2005–2008 period. We find an overall systematic negative mean bias of −4 mm and a median bias of −2 mm, with a large site-to-site scatter and especially stronger biases over South America, potentially linked to remaining problems related to the South Atlantic Anomaly (SAA) in the current DORIS data processing. The standard deviation of ZTD differences is in the range 4–12 mm over the globe (8 mm on average), with larger values located in the southern hemisphere. The spatial variability of differences is consistent with previous work but remains largely unexplained. DORIS is shown to be much less sensitive to instrumental changes than GPS (only the switch from Alcatel to Starec antenna at Toulouse is detected as an offset of −4 mm in the ZTD time series). On the opposite, discontinuities and spurious annual signals are found in the GPS ZTD solutions. A discontinuity of +5 mm is found on 5 November 2006, linked to the switch from relative to absolute GPS antenna models used in the data processing. The use of modified GPS antennas (e.g. at GODE) or improved antenna models is shown to reduce the spurious annual signal (e.g. from 5 mm to 2 mm at METS). Overall, the agreement between both techniques is good, though DORIS shows a significantly larger random scatter. The high stability and good spatial and temporal coverage make DORIS a potential candidate technique for meteorology and climate studies as long as reasonable time averaging can be applied (e.g. differences are reduced from 8.6 to 2.4 mm with 5-day averages) and no real-time application is considered. This technique could be considered as a potential contributor to Global Geodetic Observing System (GGOS) for climatology.     

Improving the estimation of zenith dry tropospheric delays using regional surface meteorological data

Global Navigation Satellite Systems (GNSS) are emerging as possible tools for remote sensing high-resolution atmospheric water vapour that improves weather forecasting through numerical weather prediction models. Nowadays, the GNSS-derived tropospheric zenith total delay (ZTD), comprising zenith dry delay (ZDD) and zenith wet delay (ZWD), is achievable with sub-centimetre accuracy. However, if no representative near-site meteorological information is available, the quality of the ZDD derived from tropospheric models is degraded, leading to inaccurate estimation of the water vapour component ZWD as difference between ZTD and ZDD. On the basis of freely accessible regional surface meteorological data, this paper proposes a height-dependent linear correction model for a priori ZDD. By applying the ordinary least-squares estimation (OLSE), bootstrapping (BOOT), and leave-one-out cross-validation (CROS) methods, the model parameters are estimated and analysed with respect to outlier detection. The model validation is carried out using GNSS stations with near-site meteorological measurements. The results verify the efficiency of the proposed ZDD correction model, showing a significant reduction in the mean bias from several centimetres to about 5 mm. The OLSE method enables a fast computation, while the CROS procedure allows for outlier detection. All the three methods produce consistent results after outlier elimination, which improves the regression quality by about 20% and the model accuracy by up to 30%.     

An estimation of tropospheric corrections using GPS and synoptic data: Improving Urmia Lake water level time series from Jason-2 and SARAL/AltiKa satellite altimetry

Tropospheric correction is one of the most important corrections in satellite altimetry measurements. Tropospheric wet and dry path delays have strong dependence on temperature, pressure and humidity. Tropospheric layer has particularly high variability over coastal regions due to humidity, wind and temperature gradients. Depending on the extent of water body and wind conditions over an inland water, Wet Tropospheric Correction (WTC) is within the ranges from a few centimeters to tens of centimeters. Therefore, an extra care is needed to estimate tropospheric corrections on the altimetric measurements over inland waters. This study assesses the role of tropospheric correction on the altimetric measurements over the Urmia Lake in Iran. For this purpose, four types of tropospheric corrections have been used: (i) microwave radiometer (MWR) observations, (ii) tropospheric corrections computed from meteorological models, (iii) GPS observations and (iv) synoptic station data. They have been applied to Jason-2 track no. 133 and SARAL/AltiKa track no. 741 and 356 corresponding to 117–153 and the 23–34 cycles, respectively. In addition, the corresponding measurements of PISTACH and PEACHI, include new retracking method and an innovative wet tropospheric correction, have also been used. Our results show that GPS observation leads to the most accurate tropospheric correction. The results obtained from the PISTACH and PEACHI projects confirm those obtained with the standard SGDR, i.e., the role of GPS in improving the tropospheric corrections. It is inferred that the MWR data from Jason-2 mission is appropriate for the tropospheric corrections, however the SARAL/AltiKa one is not proper because Jason-2 possesses an enhanced WTC near the coast. Furthermore, virtual stations are defined for assessment of the results in terms of time series of Water Level Height (WLH). The results show that GPS tropospheric corrections lead to the most accurate WLH estimation for the selected virtual stations, which improves the accuracy of the obtained WLH time series by about 5%.