An intercomparison of stratospheric gravity wave potential energy densities from METOP GPS radio occultation measurements and ECMWF model data

Abstract. Temperature profiles based on radio occultation (RO) measurements with the operational European METOP satellites are used to derive monthly mean global distributions of stratospheric (20–40 km) gravity wave (GW) potential energy densities (E_P) for the period July 2014–December 2016. In order to test whether the sampling and data quality of this data set is sufficient for scientific analysis, we investigate to what degree the METOP observations agree quantitatively with ECMWF operational analysis (IFS data) and reanalysis (ERA-Interim) data. A systematic comparison between corresponding monthly mean temperature fields determined for a latitude–longitude–altitude grid of 5° by 10° by 1 km is carried out. This yields very low systematic differences between RO and model data below 30 km (i.e., median temperature differences is between −0.2 and +0.3 K), which increases with height to yield median differences of +1.0 K at 34 km and +2.2 K at 40 km. Comparing E_P values for three selected locations at which also ground-based lidar measurements are available yields excellent agreement between RO and IFS data below 35 km. ERA-Interim underestimates E_P under conditions of strong local mountain wave forcing over northern Scandinavia which is apparently not resolved by the model. Above 35 km, RO values are consistently much larger than model values, which is likely caused by the model sponge layer, which damps small-scale fluctuations above  ∼ 32 km altitude. Another reason is the well-known significant increase of noise in RO measurements above 35 km. The comparison between RO and lidar data reveals very good qualitative agreement in terms of the seasonal variation of E_P, but RO values are consistently smaller than lidar values by about a factor of 2. This discrepancy is likely caused by the very different sampling characteristics of RO and lidar observations. Direct comparison of the global data set of RO and model E_P fields shows large correlation coefficients (0.4–1.0) with a general degradation with increasing altitude. Concerning absolute differences between observed and modeled E_P values, the median difference is relatively small at all altitudes (but increasing with altitude) with an exception between 20 and 25 km, where the median difference between RO and model data is increased and the corresponding variability is also found to be very large. The reason for this is identified as an artifact of the E_P algorithm: this erroneously interprets the pronounced climatological feature of the tropical tropopause inversion layer (TTIL) as GW activity, hence yielding very large E_P values in this area and also large differences between model and observations. This is because the RO data show a more pronounced TTIL than IFS and ERA-Interim. We suggest a correction for this effect based on an estimate of this artificial E_P using monthly mean zonal mean temperature profiles. This correction may be recommended for application to data sets that can only be analyzed using a vertical background determination method such as the METOP data with relatively scarce sampling statistics. However, if the sampling statistics allows, our analysis also shows that in general a horizontal background determination is advantageous in that it better avoids contributions to E_P that are not caused by gravity waves.