Temperature and water vapor profiles from the Korea Meteorological Administration (KMA) and the United Kingdom Met Office (UKMO) Unified Model (UM) data assimilation systems and from reanalysis fields from the European Centre for Medium-Range Weather Forecasts (ECMWF) were assessed using collocated radiosonde observations from the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) for January-December 2012. The motivation was to examine the overall performance of data assimilation outputs. The difference statistics of the collocated model outputs versus the radiosonde observations indicated a good agreement for the temperature, amongst datasets, while less agreement was found for the relative humidity. A comparison of the UM outputs from the UKMO and KMA revealed that they are similar to each other. The introduction of the new version of UM into the KMA in May 2012 resulted in an improved analysis performance, particularly for the moisture field. On the other hand, ECMWF reanalysis data showed slightly reduced performance for relative humidity compared with the UM, with a significant humid bias in the upper troposphere. ECMWF reanalysis temperature fields showed nearly the same performance as the two UM analyses. The root mean square differences (RMSDs) of the relative humidity for the three models were larger for more humid conditions, suggesting that humidity forecasts are less reliable under these conditions.
A new set of Infrared Atmospheric Sounding Interferometer (IASI) channels was re-selected from 314 EUMETSAT channels. In selecting channels, we calculated the impact of the individually added channel on the improvement in the analysis outputs from a one-dimensional variational analysis (1D-Var) for the Unified Model (UM) data assimilation system at the Met Office, using the channel score index (CSI) as a figure of merit. Then, 200 channels were selected in order by counting each individual channel's CSI contribution. Compared with the operationally used 183 channels for the UM at the Met Office, the new set shares 149 channels, while the other 51 channels are new. Also examined is the selection from the entropy reduction method with the same 1D-Var approach. Results suggest that channel selection can be made in a more objective fashion using the proposed CSI method. This is because the most important channels can be selected across the whole IASI observation spectrum.In the experimental trial runs using the UM global assimilation system, the new channels had an overall neutral impact in terms of improvement in forecasts, as compared with results from the operational channels. However, upper-tropospheric moist biases shown in the control run with operational channels were significantly reduced in the experimental trial with the newly selected channels. The reduction of moist biases was mainly due to the additional water vapor channels, which are sensitive to the upper-tropospheric water vapor.
Optical properties of aerosols associated with haze events over Seoul were examined using ground-based skyradiometer and satellite-borne CALIOP and MODIS measurements over the 2009~2010 period. It is shown that aerosol optical thickness (AOT), Ångström exponents (α), and fine-mode particles increase during the haze events. The CALIOP-measured vertical profiles of aerosol during the haze events revealed that most of aerosols are loaded within layers below 4 km altitude. A large portion of these events appear to be related to the long-range transport of aerosols from China; about 35% and 18% of the haze events observed over Seoul were traced back to northern China and southern China, respectively. Compared with optical properties for locally-induced haze events (25%), these long-range transported aerosols are found to have relatively higher AOTs.
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.
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