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Data assimilation of satellite microwave measurements is one of the important keys to improving weather forecasting over the Arctic region. However, the use of surface‐sensitive microwave‐sounding channel measurements for data assimilation or retrieval has been limited, especially during winter, due to the poorly constrained sea ice emissivity. In this study, aiming at more use of those channel measurements in the data assimilation, we propose an explicit method for specifying the surface radiative boundary conditions (namely emissivity and emitting layer temperature of snow and ice). These were explicitly determined with a radiative transfer model for snow and ice and with snow/ice physical parameters (i.e. snow/ice depths and vertical distributions of temperature, density, salinity, and grain size) simulated from the thermodynamically driven snow/ice growth model. We conducted 1D‐Var experiments in order to examine whether this approach can help to use the surface‐sensitive microwave temperature channel measurements over the Arctic sea ice region for data assimilation. Results show that (1) the surface‐sensitive microwave channels can be used in the 1D‐Var retrieval, and (2) the specification of the radiative boundary condition at the surface using the snow/sea ice emission model can significantly improve the atmospheric temperature retrieval, especially in the lower troposphere (500 hPa to surface). The successful retrieval suggests that useful information can be extracted from surface‐sensitive microwave‐sounding channel radiances over sea ice surfaces through the explicit determination of snow/ice emissivity and emitting layer temperature. [ABSTRACT FROM AUTHOR]

In this work it is shown that the prediction of individual midlatitude waves in a global forecast framework may benefit from the assimilation of cloud-cleared radiances (CCRs) from the Atmospheric Infrared Sounder (AIRS). The assimilation of CCRs, relative to clear-sky radiances, provides more information in high-latitude areas affected by broken low-level stratus clouds, which are common over north polar latitudes during the summer and autumn seasons. This added information in cloudy regions produces slightly lower low-level temperatures and lower mid-tropospheric heights (through hydrostatic adjustment) over the Arctic and part of northeastern Siberia. In areas that are both dynamically unstable (with the potential for rapid error growth) and data void (as observed by clear-sky radiances), the assimilation of CCRs provides valuable information that can improve the representation of individual baroclinic waves and their subsequent forecasts. The assimilation of AIRS CCRs slightly modifies the geopotential height gradients between the Arctic and the midlatitudes, leading to improvements in the forecast of individual baroclinic waves, as is shown through three case-studies. The set of observing system experiments (OSEs) is performedwith theNASAGoddard EarthObserving System (GEOS) data assimilation and forecast system during boreal autumn 2014. AIRS CCRs are thinned to approximately one quarter the density of operationally assimilated AIRS radiances, consistent with their higher information content. Global 6-hourly analyses are produced from 01 September to 10 November 2014 and seven-day forecasts are initialized at 0000 UTC daily. Since the CCR methodology is widely applicable, these findings are also relevant to other infrared sensors. [ABSTRACT FROM AUTHOR]