The Suomi National Polar‐orbiting Partnership (NPP) satellite was successfully launched on 28 October 2011. On board the Suomi NPP, the Advanced Technology Microwave Sounder (ATMS) is a cross‐track scanning instrument and has 22 channels at frequencies ranging from 23 to 183 GHz which allows for probing the atmospheric temperature and moisture under clear and cloudy conditions. ATMS inherited most of the sounding channels from its predecessors: Advanced Microwave Sounding Unit‐A (AMSU‐A) and Microwave Humidity Sounder (MHS) onboard NOAA and MetOp satellites. However, ATMS has a wider scan swath and has no gaps between two consecutive orbits. It includes one new temperature sounding channel and two water vapor sounding channels and provides more details of thermal structures in lower troposphere, especially for the storm conditions such as tropical cyclones. While ATMS temperature sounding channels have shorter integration time and therefore higher noise than AMSU‐A, the ATMS observations from their overlapping field of views are resampled to produce AMSU‐A‐like measurements.

[1] Global cloud parameters including cloud liquid water, cloud base height, cloud top height, and cloud type are observed from the cloud profiling radar onboard CloudSat. Global Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation (RO) data during a 3 year period from 2007 to 2009 are collocated in space and time with CloudSat data. The collocated data set is then classified into seven groups: one clear-sky condition and six different cloud types with liquid water content (LWC) measurements. For each group, atmospheric refractivity, temperature, and water vapor derived from COSMIC GPS ROs are compared with those of the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses. It is found that the COSMIC GPS RO refractivity observations are systematically greater than the refractivity calculated from ECMWF analyses, which is to be referred as a positive N bias in clouds. The fractional N bias is as high as 1.2% depending on cloud types. Using CloudSat LWC, it is demonstrated that LWC can contribute 0.8% of the total refractivity by individual clouds and 0.16% of the positive N bias. The 0.16% positive N bias is comparable in magnitude to the retrieval uncertainty quantified by the mean difference (DN O-R ) between the observed refractivity with LWC contribution subtracted and the refractivity calculated using GPS retrieved profiles of temperature, pressure, and humidity. The values of DN O-R increase linearly with LWC as anticipated theoretically. Positive N biases are spatially correlated with positive water vapor biases, negative temperature biases, and large liquid water contents.Citation: Yang, S., and X. Zou (2012), Assessments of cloud liquid water contributions to GPS radio occultation refractivity using measurements from COSMIC and CloudSat,

Mathematical solutions accounting for the effects of liquid and ice clouds on the propagation of the GPS radio signals are first derived. The percentage contribution of ice water content (IWC) to the total refractivity increases linearly with the amount of IWC at arate of 0.6 (g m^"')^'. Measurements of coincident profiles of IWC from CloudSat in deep convection during 2007-10 are then used for estimating the ice-scattering effects on GPS radio occultation (RO) measurements from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC). The percentage contribution of IWC to the total refractivity from CloudSat measurements is consistent with the theoretical model, reaching about 0.6% at 1 g m •' IWC.The GPS RO refractivity observations in deep convective clouds are found to be systematically greater than the refractivity calculated from the ECMWF analysis. The fractional N bias (GPS minus ECMWF) can be as high as 1.8% within deep convective clouds. Compared with ECMWF analysis, the GPS RO retrievals have a negative temperature bias and a positive water vapor bias, which is consistent with a positive bias in refractivity. The relative humidity calculated from GPS retrievals is usually as high as 80%-90% right above the 0°C temperature level in deep convection and is about 15%-30% higher than the ECMWF analysis. The majority of the data points in deep convection are located on the negative side of temperature differences and the positive side of relative humidity differences between GPS RO retrievals and ECMWF analysis.

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