Observing the Water Vapor Feedback With GPS Radio Occultation Measurements

Abstract:

Recent studies show that the distribution of projected climate sensitivity (CS) is highly asymmetric with large tails towards higher temperatures, leaving open an uncomfortably large possibility of CS > 4.5^oC. Central to the estimation of CS is the distribution of water vapor in the atmosphere, which directly affects the water vapor feedback and indirectly drives the cloud feedback. Yet, a plethora of studies report large discrepancies between models and observations of the tropical humidity climatology and its vertical distribution. Our preliminary results indicate that the tropical humidity climatology derived from Global Positioning System (GPS) radio occultation (GPSRO) observations are in excellent agreement with NASA’s Modern Era Retrospective Analysis for Research and Applications (MERRA). We will present the time series of tropospheric water vapor using GPSRO data sets from 2006 onwards, and will compare our results with different sources such as the European Center for Medium Range Weather Forecasts (ECMWF) and the Atmospheric Infrared Sounder (AIRS). We will carefully quantify the statistical differences among the series to identify and document biases among the data sets. Finally, we will correlate the aforementioned humidity series with surface temperature climatologies in order to estimate the variability of water vapor in response to temperature fluctuations, dq/dT_s, which is directly related to the water vapor feedback. Current research indicates that GPSRO data sets can capture the amount of water vapor in very dry and very moist air more efficiently than other observing platforms, possibly suggesting larger water vapor feedback than previously known. Inter–comparing the dq/dT_s among the different data sets will provide us with an additional constraint on the water vapor feedback. The critical role of the up–coming Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC–2) mission in late 2016, in characterizing the tropical humidity climatology and the associated climate feedbacks, will be discussed.