[1] Simultaneous nadir overpasses (SNOs) of polar-orbiting satellites are most frequent in polar areas but can occur at any latitude when the equatorial crossing times of the satellites become close owing to orbital drift. We use global SNOs of polar orbiting satellites to evaluate the intercalibration of microwave humidity sounders from the more frequent high-latitude SNOs. We have found based on sensitivity analyses that optimal distance and time thresholds for defining collocations are pixel centers less than 5 km apart and time differences less than 300 s. These stringent collocation criteria reduce the impact of highly variable surface or atmospheric conditions on the estimated biases. Uncertainties in the estimated biases are dominated by the combined radiometric noise of the instrument pair. The effects of frequency changes between different versions of the humidity sounders depend on the amount of water vapor in the atmosphere. There are significant scene radiance and thus latitude dependencies in the estimated biases and this has to taken into account while intercalibrating microwave humidity sounders. Therefore the results obtained using polar SNOs will not be representative for moist regions, necessitating the use of global collocations for reliable intercalibration.

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One of the main avenues to improve the skill of a numerical weather prediction system is to increase the accuracy of the initial conditions for prediction through the assimilation of a larger number of observations. This article discusses our work on assimilating cloud-affected radiances from microwave temperature sounding channels of the Advanced Microwave Sounding Unit A (AMSU-A) satellite sensor, which are currently underused by the Met Office operational data assimilation system. Despite their importance, as measured by impact indicators such as the Forecast Sensitivity to Observations Impact (FSOI), most cloud-affected microwave data are discarded so as to avoid detrimental effects, as they are much more difficult to predict than clear-sky radiances. This is due to shortcomings in parametrization schemes (for example, large-scale cloud and precipitation, convection) in both nonlinear and linearized prognostic models, as well as radiative transfer models. As first demonstrated at the European Centre for Medium-Range Weather Forecasts (ECMWF), these difficulties can be eased when observation uncertainties for cloud-affected radiances are inflated prior to assimilation as a function of cloud amount present in a given observed or predicted scene. Our results show that cloud-dependent observation uncertainty inflation for cloud-affected radiances provides beneficial effects on forecast skill over two three-month-long "all-sky" (nonprecipitating) data assimilation trials. In particular, root-mean-square error (RMSE) reductions in 500-hPa geopotential height forecasts of about 1% up to day 2 and in 10-m wind and 2-m temperature forecasts up to day 6 have been demonstrated. Also, our experiments show evidence of significant improvements in the fit between observations and short-range forecasts for lower-peaking humidity-and temperature-sensitive channels. KEYWORDSall-sky, assimilation, cloud, microwave, satellite 1The assimilation of all-sky microwave radiances in 4D-Var was pioneered at the European Centre for Medium-Range Weather Forecasts (ECMWF), where cloudand precipitation-affected radiances from the Special Sensor Microwave/Imager (SSM/I) and the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR/E) were assimilated operationally starting from March 2009. Currently, all microwave humidity sounders (over oceans, land, snow-covered land, and sea ice) and microwave imagers (over oceans) are assimilated at ECMWF in all-sky conditions This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland.

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Radiances measured by satellite radiometers are often subject to biases due to limitations in their radiometric calibration. In support of the Global Space-based Inter-Calibration System project, to improve the quality of calibrated radiances from atmospheric sounders and imaging radiometers, an activity is underway to compare routinely measured radiances with those simulated from operational global numerical weather prediction (NWP) fields. This paper describes the results obtained from the first three years of these comparisons. Data from the Highresolution Infrared Radiation Sounder, Spinning Enhanced Visible and Infrared Imager, Advanced Along-Track Scanning Radiometer, Advanced Microwave Sounding Unit, and Microwave Humidity Sounder radiometers, together with the Atmospheric Infrared Sounder, a spectrometer, and the Infrared Atmospheric Sounding Interferometer, an interferometer, were included in the analysis. Changes in mean biases and their standard deviations were used to investigate the temporal stability of the bias and radiometric noise of the instruments. A double difference technique can be employed to remove the effect of changes or deficiencies in the NWP model which can contribute to the biases. The variation of the biases with other variables is also investigated, such as scene temperature, scan angle, location, and time of day. Many of the instruments were shown to be stable in time, with a few exceptions, but measurements from the same instrument on different platforms are often biased with respect to each other. The limitations of the polar simultaneous nadir overpasses often used to monitor biases between polar-orbiting sensors are shown with these results due to the apparent strong dependence of some radiance biases on scene temperature.