The effect of aerosol representation on cloud microphysical properties in Northeast Asia

This study performed a three-dimensional regional-scale simulation of aerosol and cloud fields using a meso-scale non-hydrostatic model with a bin-based cloud microphysics. The representation of aerosols in the model has been improved to account for more realistic multi-modal size distribution and multiple chemical compositions. Two case studies for shallow stratocumulus over Northeast Asia in March 2005 were conducted with different aerosol conditions to evaluate model performance. Improved condensation nuclei (CN) and cloud condensation nuclei (CCN) are attributable to the newly constructed aerosol size distribution. The simulated results of cloud microphysical properties (cloud droplet effective radius, liquid water path, and optical thickness) with improved CN/CCN number are close to the retrievals from satellite-based observation. The effects of aerosol on the microphysical properties of shallow stratocumulus are investigated by model simulation, in terms of columnar aerosol number concentration. Enhanced aerosol number concentration results in increased liquid water path in humid case, but invariant liquid water path in dry case primarily due to precipitation occurrence. The changes of cloud microphysical properties are more predominant for small aerosol burden than for large aerosol burden with the retarded changes in cloud mass and size due to inactive condensation and collision-coalescence processes. Quantitative evaluation of sensitivity factor between aerosol and cloud microphysical properties indicates a strong aerosol-cloud interaction in Northeast Asian region.     

Retrieval of outgoing longwave radiation from COMS narrowband infrared imagery

Hourly outgoing longwave radiation(OLR) from the geostationary satellite Communication Oceanography Meteorological Satellite(COMS) has been retrieved since June 2010. The COMS OLR retrieval algorithms are based on regression analyses of radiative transfer simulations for spectral functions of COMS infrared channels. This study documents the accuracies of OLRs for future climate applications by making an intercomparison of four OLRs from one single-channel algorithm(OLR12.0using the 12.0 μm channel) and three multiple-channel algorithms(OLR10.8+12.0using the 10.8 and 12.0 μm channels; OLR6.7+10.8using the 6.7 and 10.8 μm channels; and OLR All using the 6.7, 10.8, and 12.0 μm channels). The COMS OLRs from these algorithms were validated with direct measurements of OLR from a broadband radiometer of the Clouds and Earth's Radiant Energy System(CERES) over the full COMS field of view [roughly(50°S–50°N, 70°–170°E)] during April 2011.Validation results show that the root-mean-square errors of COMS OLRs are 5–7 W m-2, which indicates good agreement with CERES OLR over the vast domain. OLR6.7+10.8and OLR All have much smaller errors(～ 6 W m-2) than OLR12.0and OLR10.8+12.0(～ 8 W m-2). Moreover, the small errors of OLR6.7+10.8and OLR All are systematic and can be readily reduced through additional mean bias correction and/or radiance calibration. These results indicate a noteworthy role of the6.7 μm water vapor absorption channel in improving the accuracy of the OLRs. The dependence of the accuracy of COMS OLRs on various surface, atmospheric, and observational conditions is also discussed.     

Analysis of solar radiation on the surface estimated from GWNU solar radiation model with temporal resolution of satellite cloud fraction

Preliminary analysis with a solar radiation model is generally performed for photovoltaic power generation projects. Therefore, model accuracy is extremely important. The temporal and spatial resolutions used in previous studies of the Korean Peninsula were 1 km × 1 km and 1-h, respectively. However, calculating surface solar radiation at 1-h intervals does not ensure the accuracy of the geographical effects, and this parameter changes owing to atmospheric elements (clouds, aerosol, ozone, etc.). Thus, a change in temporal resolution is required. In this study, one-year (2013) analysis was conducted using Chollian geostationary meteorological satellite data from observations recorded at 15-min intervals. Observation data from the intensive solar site at Gangneung-Wonju National University (GWNU) showed that the coefficient of determination (R²), which was estimated for each month and season, increased, whereas the standard error (SE) decreased when estimated in 15-min intervals over those obtained in 1-h intervals in 2013. When compared with observational data from 22 solar sites of the Korean Meteorological Administration (KMA), R² was 0.9 or higher on average, and over- or under-simulated sites did not exceed 3 sites. The model and 22 solar sites showed similar values of annual accumulated solar irradiation, and their annual mean was similar at 4,998 MJ m^?2 (3.87 kWh m^?2). These results show a difference of approximately ± 70 MJ m^?2 (± 0.05 kWh m^?2) from the distribution of the Korean Peninsula estimated in 1-h intervals and a higher correlation at higher temporal resolution.     

Seasonal prediction for tropical cyclone frequency around Taiwan using teleconnection patterns

In this study, a statistical model is developed to predict the frequency of tropical cyclones (TCs) that influence Taiwan in boreal summer. Predictors are derived from large-scale environments from February to May in six regions, including four atmospheric circulation predictors over the western sea and eastern sea of Australia, the subtropical western North Pacific (SWNP), and the eastern sea of North America, and two sea surface temperature predictors in the Southeast Indian Ocean and the North Atlantic. The statistical model is verified based on statistical cross-validation tests and by contrasting the differences in the large-scale environments between high and low TC frequency years hindcasted by the model. The results show the relationships of two atmospheric circulation predictors and one SST predictor around Australia with Antarctic Oscillation (AAO) pattern, as well as the relationships of those in the SWNP and around eastern sea of North America with Pacific/North American teleconnection (PNA) pattern. When the anomalous anticyclone around Australia (positive AAO pattern) and the one over the region from eastern sea of North America and the Aleutian Islands to the SWNP (negative PNA pattern) are both strengthened from February, the trade wind in the equatorial Pacific is intensified and consequently plays an important role in steering TCs towards Taiwan during boreal summer.     

Development of statistical seasonal prediction models of Arctic Sea Ice concentration using CERES absorbed solar radiation

Statistical seasonal prediction models for the Arctic sea ice concentration (SIC) were developed for the late summer (August-October) when the downward trend is dramatic. The absorbed solar radiation (ASR) at the top of the atmosphere in June has a significant seasonal leading role on the SIC. Based on the lagged ASR-SIC relationship, two simple statistical models were established: the Markovian stochastic and the linear regression models. Crossvalidated hindcasts of SIC from 1979 to 2014 by the two models were compared with each other and observation. The hindcasts showed general agreement between the models as they share a common predictor, ASR in June and the observed SIC was well reproduced, especially over the relatively thin-ice regions (of one- or multi-year sea ice). The robust predictability confirms the functional role of ASR in the prediction of SIC. In particular, the SIC prediction in October was quite promising probably due to the pronounced icealbedo feedback. The temporal correlation coefficients between the predicted SIC and the observed SIC were 0.79 and 0.82 by the Markovian and regression models, respectively. Small differences were observed between the two models; the regression model performed slightly better in August and September in terms of temporal correlation coefficients. Meanwhile, the prediction skills of the Markovian model in October were higher in the north of Chukchi, the East Siberian, and the Laptev Seas. A strong non-linear relationship between ASR in June and SIC in October in these areas would have increased the predictability of the Markovian model.     

Analytical solution for transient groundwater flow during slug test in vertical cutoff walls

An analysis method for transient groundwater flow during slug tests performed in vertical cutoff walls is presented. The analytical solution for evaluating hydraulic conductivity of vertical cutoff walls is derived by applying the method of images to the previously developed analytical solution that is exclusively applicable to an infinite aquifer. Two distinct boundary conditions are considered to account for the configuration of the vertical cutoff wall: the wall‐soil formation interfaces with or without the existence of filter cakes, that is, constant‐head boundary and no‐flux boundary conditions. A series of type curves is constructed from the analytical solution and compared with those of a partially penetrated well within an aquifer. The constant‐head boundary condition provides faster hydraulic head recovery than the aquifer case. On the other hand, the no‐flux boundary condition leads to a delayed hydraulic head recovery. The greater the shape factor and well offset from the center of the cutoff wall, and the smaller the width of the cutoff wall, the greater the effect of the boundary condition observed in the type curves. This result shows the significance of considering proper boundary conditions at the vertical cutoff wall in analyzing slug tests. Copyright © 2014 John Wiley & Sons, Ltd.     

Comparison of Statistical Post-Processing Methods for Probabilistic Wind Speed Forecasting

In this study, the statistical post-processing methods that include bias-corrected and probabilistic forecasts of wind speed measured in PyeongChang, which is scheduled to host the 2018 Winter Olympics, are compared and analyzed to provide more accurate weather information. The six post-processing methods used in this study are as follows: mean bias-corrected forecast, mean and variance bias-corrected forecast, decaying averaging forecast, mean absolute bias-corrected forecast, and the alternative implementations of ensemble model output statistics (EMOS) and Bayesian model averaging (BMA) models, which are EMOS and BMA exchangeable models by assuming exchangeable ensemble members and simplified version of EMOS and BMA models. Observations for wind speed were obtained from the 26 stations in PyeongChang and 51 ensemble member forecasts derived from the European Centre for Medium-Range Weather Forecasts (ECMWF Directorate, 2012) that were obtained between 1 May 2013 and 18 March 2016. Prior to applying the post-processing methods, reliability analysis was conducted by using rank histograms to identify the statistical consistency of ensemble forecast and corresponding observations. Based on the results of our study, we found that the prediction skills of probabilistic forecasts of EMOS and BMA models were superior to the biascorrected forecasts in terms of deterministic prediction, whereas in probabilistic prediction, BMA models showed better prediction skill than EMOS. Even though the simplified version of BMA model exhibited best prediction skill among the mentioned six methods, the results showed that the differences of prediction skills between the versions of EMOS and BMA were negligible.     

The Korean Integrated Model (KIM) System for Global Weather Forecasting

The Korea Institute of Atmospheric Prediction Systems (KIAPS) began a national project to develop a new global atmospheric model system in 2011. The ultimate goal of this 9-year project is to replace the current operational model at the Korea Meteorological Administration (KMA), which was adopted from the United Kingdom’s Meteorological Office’s unified model (UM) in 2010. The 12-km Korean Integrated Model (KIM) system, consisting of a spectral-element non-hydrostatic dynamical core on a cubed sphere grid and a state-of-the-art physics parameterization package, has been launched in a real-time forecast framework, with initial conditions obtained via the advanced hybrid four-dimensional ensemble variational data assimilation (4DEnVar) over its native grid. A development strategy for KIM and the evolution of its performance in medium-range forecasts toward a world-class global forecast system are described. Outstanding issues in KIM 3.1 as of February 2018 are discussed, along with a future plan for operational deployment in 2020.     

Numerical simulation of groundwater flow in the Peshawar intermontane basin, northwest Himalayas

The hypothesis that abnormal fluid pressure is generated in basins under tectonic compression is tested. The study site, between the Main Karakoram Thrust (MKT), Main Mantle Thrust (MMT), Main Central Thrust (MCT), Main Boundary Thrust (MBT) and Salt Range Thrust (SRT) in northwest Pakistan, is experiencing a tectonic compression of 90 MPa. The Peshawar basin is a broad, oval depression comprising a thick sequence of lacustrine, deltaic and fluvial sediments overlain by loess and alluvial deposits dated at 2.8–0.6 Ma. It is surrounded by the Precambrian and Tertiary intrusive and metamorphic rocks on the north and sedimentary rocks of Paleogene and Neogene to the south. The basin was divided into four hydrostratigraphic units for numerical simulations using the three-dimensional finite-element model FEMWATER within groundwater modeling system (GMS) ver. 5.1. Simulated pressure head data have been compared with the field measurements of hydraulic heads. Transient simulations indicate that topography alone is not sufficient to induce the pressure heads observed in the field, generating consistently positive residuals 0.98–2.90 m over the topography-driven flow. The residuals disappeared after inclusion of the elastic properties of the four hydrostratigraphic units in the model, suggesting the effect of tectonic compression.