Estimating Confidence Intervals around Relative Humidity Profiles from Satellite Observations: Application to the SAPHIR Sounder

Abstract

AbstractA novel scheme for the estimation of layer-averaged relative humidity (RH) profiles from spaceborne observations in the 183.31-GHz line is presented. Named atmospheric relative humidity profiles including analysis of confidence intervals (ARPIA), it provides for each vector of observations the parameters of the distribution of the RH instead of its expectation, as is usually done by the current methods. The profiles are composed of six layers distributed between 100 and 950 hPa. The approach combines the six channels of the Sondeur Atmosphérique du Profil d’Humidité Intertropical par Radiométrie (SAPHIR) instrument on board the Megha-Tropiques satellite and the generalized additive model for location, scale and shape (GAMLSS) method to infer the parametric distributions, assuming that they follow a Gaussian law. The knowledge of the conditional uncertainty is an asset in the evaluation using radiosounding profiles of RH with a dedicated Bayesian method. Taking the uncertainties into account in both the ARPIA estimates and the in situ measurements yields biases, root-mean-square, and correlation coefficients in the range of −0.56% to 9.79%, 1.58% to 13.32%, and 0.55 to 0.98, respectively, with the largest biases being obtained over the continent, in the midtropospheric layers.