Error analysis of upper tropospheric water vapor in CMIP5 models using “A-Train” satellite observations and reanalysis data

Upper tropospheric water vapor (UTWV) plays a critical role in amplifying global warming caused by increasing greenhouse gases, yet it is one of the most poorly simulated quantities in climate models. It is not clear what physical processes play a central role in controlling the model errors in UTWV. We diagnose the UTWV simulation errors from AMIP models submitted to the CMIP5 project by using “A-Train” satellite observation and reanalysis data. We identify the relative contributions of errors in relative humidity (RH), temperature, and large-scale circulation (represented by vertical pressure velocity at 500 hPa, ω500) to the modeled UTWV errors over the tropics (30°N–30°S). It is found that models generally have positive biases in UTWV, except over the continental convective regions where negative biases predominate. The errors in the patterns and amplitudes of climatological UTWV are highly correlated with those in RH and ω500. The fractional UTWV errors show large positive errors over the large-scale descending regimes (0 < ω500 < 40 hPa/day) where large model spreads also exist. The seasonal cycle of hemispherically averaged UTWV closely resembles that of ω500. The errors for UTWV interannual anomalies are abundant over the climatologically deep convective regions (SST > 300 K or ω500 < −30 hPa/day) and these errors are positive (negative) where anomalous descent (ascent) occurs during El Niño. We find that the water vapor errors are dominated by the errors in RH rather than in temperature throughout the troposphere, while temperature errors play an important role for water vapor errors near the tropopause.