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