Comparison of global observations and trends of total precipitable water derived from microwave radiometers and COSMIC radio occultation from 2006 to 2013

Abstract

Abstract. We compare atmospheric total precipitable water (TPW) derived from the SSM/I (Special Sensor Microwave Imager) and SSMIS (Special Sensor Microwave Imager/Sounder) radiometers and WindSat to collocated TPW estimates derived from COSMIC (Constellation System for Meteorology, Ionosphere, and Climate) radio occultation (RO) under clear and cloudy conditions over the oceans from June 2006 to December 2013. Results show that the mean microwave (MW) radiometer -COSMIC TPW differences range from 0.06 to 0.18 mm for clear skies, from 0.79 to 0.96 mm for cloudy skies, from 0.46 to 0.49 mm for cloudy but non-precipitating conditions, and from 1.64 to 1.88 mm for precipitating conditions. Because RO measurements are not significantly affected by clouds and precipitation, the biases mainly result from MW retrieval uncertainties under cloudy and precipitating conditions. All COSMIC and MW radiometers detect a positive TPW trend over these 8 years. The trend using all COSMIC observations collocated with MW pixels for this data set is 1.79 mm decade −1 , with a 95 % confidence interval of (0.96, 2.63), which is in close agreement with the trend estimated by the collocated MW observations (1.78 mm decade −1 with a 95 % confidence interval of 0.94, 2.62). The sample of MW and RO pairs used in this study is highly biased toward middle latitudes (40-60 • N and 40-65 • S), and thus these trends are not representative of global average trends. However, they are representative of the latitudes of extratropical storm tracks and the trend values are approximately 4 to 6 times the global average trends, which are approximately 0.3 mm decade −1 . In addition, the close agreement of these two trends from independent observations, which represent an increase in TPW in our data set of about 6.9 %, are a strong indication of the positive water vapor-temperature feedback on a warming planet in regions where precipitation from extratropical storms is already large.

Global Water Vapor Estimates from Measurements from Active GPS RO Sensors and Passive Infrared and Microwave Sounders

“…Being an active limb-sounding measurement, GPS RO technique is capable of retrieving profiles of microwave refractivity at very high vertical resolution [23]. The root mean square (RMS) error was estimated to be less than 1 K based on a detailed theoretical study [23], and this estimate was found to be consistent with numerous cross-validation studies between RO, radiosonde observation (RAOB), and other satellite measurements (e.g., [20,21,[24][25][26][27][28]).…”

Spatial and Temporal Variation of Aerosol and Water Vapour Effects on Solar Radiation in the Mediterranean Basin during the Last Two Decades

“…In fact, the study period extends along 19 years (from 2000 to 2018), using one of the longest remote sensing derived climate data sets in the region, with the advantage of covering a wide area that is also considered one of the regions in the world most sensitive to climate change. Other authors have used shorter time series to evaluate AOD and PWV trends [26,27]. It is also the first study to apply a new methodology (which has been successfully tested on nine specific stations previously [23]) to a wide area, taking advantage of the extensive coverage provided by satellites.…”

Characteristics of Satellite Sampling Errors in Total Precipitable Water from SSMIS, HIRS, and COSMIC Observations

“…While microwave imagers can provide data under cloudy conditions, they can only retrieve accurate data over ocean due to the complexity of land surface emissivity. And for the GPS‐RO data, although it has all weather observations both over land and ocean, its horizontal resolution is very coarse, which is about 200 km (Ho et al, ; Teng et al, ). Actually, no single sensing technique can completely provide homogeneous data products across the whole globe and under all weather conditions with high frequency and accuracy (Ho et al, ; Ho & Peng, ).…”

“…Other studies also show that sampling errors may cause the estimates of climate variables to be uncertain. For example, Ho et al () validated the accuracy of Constellation System for Meteorology, Ionosphere, and Climate (COSMIC) data with collocated microwave radiometer measurements. But finally, a much higher global TPW trend was got with this validated data set.…”