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Retrievals of cloud ice mass and humidity from the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) and the  Odin-SMR (Sub-Millimetre Radiometer)  limb sounder are presented and example applications of the  data are given. SMILES data give an unprecedented view of the diurnal  variation of cloud ice mass. Mean regional diurnal cycles are reported and  compared to some global climate models. Some improvements in the models  regarding diurnal timing and relative amplitude were noted, but the models'  mean ice mass around 250 hPa is still low compared to the observations.  The influence of the ENSO (El Niño–Southern Oscillation) state on the upper troposphere is demonstrated  using 12 years of Odin-SMR data.    The same retrieval scheme is applied for both sensors, and gives low  systematic differences between the two data sets. A special feature of this  Bayesian retrieval scheme, of Monte Carlo integration type, is that values  are produced for all measurements but for some atmospheric states retrieved  values only reflect a priori assumptions. However, this "all-weather"  capability allows a direct statistical comparison to model data, in contrast  to many other satellite data sets. Another strength of the retrievals is the  detailed treatment of "beam filling" that otherwise would cause large  systematic biases for these passive cloud ice mass retrievals.    The main retrieval inputs are spectra around 635/525 GHz from tangent  altitudes below 8/9 km for SMILES/Odin-SMR, respectively. For both  sensors, the data cover the upper troposphere between 30° S and  30° N. Humidity is reported as both relative humidity and volume mixing  ratio. The vertical coverage of SMILES is restricted to a single layer, while  Odin-SMR gives some profiling capability between 300 and 150 hPa. Ice mass  is given as the partial ice water path above 260 hPa, but for Odin-SMR ice  water content, estimates are also provided. Besides a smaller contrast between  most dry and wet cases, the agreement with Aura MLS (Microwave Limb Sounder) humidity data is good. In  terms of tropical mean humidity, all three data sets agree within 3.5 %RHi.  Mean ice mass is about a factor of 2 lower compared to CloudSat. This deviation  is caused by the fact that different particle size distributions are assumed,  combined with saturation and a priori influences in the SMILES and Odin-SMR  data

Overview and sample applications of SMILES and Odin-SMR retrievals of upper tropospheric humidity and cloud ice mass