Upper tropospheric water vapor and clouds play an important role in Earth's climate, but knowledge of them, in particular diurnal variation in deep convective clouds, is limited. An essential variable to understand them is cloud ice water content. The Japanese Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) on board the International Space Station (ISS) samples the atmosphere at different local times allowing the study of diurnal variability of atmospheric parameters. We describe a new ice cloud data set consisting of partial Ice Water Path and Ice Water Content. Preliminary comparisons with EOS-MLS, CloudSat-CPR and CALIOP-CALIPSO are presented. Then, the diurnal variation over land and over open ocean for partial ice water path is reported. Over land, a pronounced diurnal variation peaking strongly in the afternoon/early evening was found. Over the open ocean, little temporal dependence was encountered. This data set is publicly available for download in HDF5 format.
Research Containing: climate
Evaluating the Diurnal Cycle of Upper-Tropospheric Ice Clouds in Climate Models Using SMILES Observations
Upper-tropospheric ice cloud measurements from the Superconducting Submillimeter Limb Emission Sounder (SMILES) on the International Space Station (ISS) are used to study the diurnal cycle of upper-tropospheric ice cloud in the tropics and midlatitudes (40°S?40°N) and to quantitatively evaluate ice cloud diurnal variability simulated by 10 climate models. Over land, the SMILES-observed diurnal cycle has a maximum around 1800 local solar time (LST), while the model-simulated diurnal cycles have phases differing from the observed cycle by ?4 to 12 h. Over ocean, the observations show much smaller diurnal cycle amplitudes than over land with a peak at 1200 LST, while the modeled diurnal cycle phases are widely distributed throughout the 24-h period. Most models show smaller diurnal cycle amplitudes over ocean than over land, which is in agreement with the observations. However, there is a large spread of modeled diurnal cycle amplitudes ranging from 20% to more than 300% of the observed over both land and ocean. Empirical orthogonal function (EOF) analysis on the observed and model-simulated variations of ice clouds finds that the first EOF modes over land from both observation and model simulations explain more than 70% of the ice cloud diurnal variations and they have similar spatial and temporal patterns. Over ocean, the first EOF from observation explains 26.4% of the variance, while the first EOF from most models explains more than 70%. The modeled spatial and temporal patterns of the leading EOFs over ocean show large differences from observations, indicating that the physical mechanisms governing the diurnal cycle of oceanic ice clouds are more complicated and not well simulated by the current climate models.