Persistent high concentration of ozone during windstorm conditions in southern Korea

Summary Prior to and following the development of a windstorm in the mountainous coastal area of southern Korea, ground level ozone (O₃)-concentrations near Kangnung city, on the lee side of the mountains, show a maximum value at approximately 1300 LST, owing to a photolytic cycle of NO₂–NO–O₃ during the day and a minimum in concentrations at night as a result of the reverse cycle. During the development period of the windstorm, ozone concentrations are generally high all day, and slightly higher during the night. This distribution pattern of ozone is very different from the typical distribution of ozone in the absence of windstorms. High daytime concentrations of ozone during the windstorm are due to both the increase in the amount of ozone from photochemical reactions involving NO_x and the increase in O₃-concentration due to a decrease in the convective boundary layer thickness under the influence of downslope windstorm conditions on the lee-side of the mountains. At night, the windstorm increases in intensity as the westerly winds combine with a katabatic wind blowing downslope toward the surface at the coast. This causes momentum transport of air parcels in the upper levels toward the surface at the coast and the development of internal gravity waves, which generate a hydraulic jump directed upward over the coast and the East sea, thereby reducing to very thin the thickness of the nocturnal surface inversion layer (NSIL). The higher O₃-concentration at night depends mainly upon the shallow NSIL and on some O₃ being transported by the momentum transfer from the upper troposphere toward the ground in windstorm conditions.     

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.     

A copula-based multivariate analysis of Canadian RCM projected changes to flood characteristics for northeastern Canada

In the present work, climate change impacts on three spring (March–June) flood characteristics, i.e. peak, volume and duration, for 21 northeast Canadian basins are evaluated, based on Canadian regional climate model (CRCM) simulations. Conventional univariate frequency analysis for each flood characteristic and copula based bivariate frequency analysis for mutually correlated pairs of flood characteristics (i.e. peak–volume, peak–duration and volume–duration) are carried out. While univariate analysis is focused on return levels of selected return periods (5-, 20- and 50-year), the bivariate analysis is focused on the joint occurrence probabilities P1 and P2 of the three pairs of flood characteristics, where P1 is the probability of any one characteristic in a pair exceeding its threshold and P2 is the probability of both characteristics in a pair exceeding their respective thresholds at the same time. The performance of CRCM is assessed by comparing ERA40 (the European Centre for Medium-Range Weather Forecasts 40-year reanalysis) driven CRCM simulated flood statistics and univariate and bivariate frequency analysis results for the current 1970–1999 period with those observed at selected 16 gauging stations for the same time period. The Generalized Extreme Value distribution is selected as the marginal distribution for flood characteristics and the Clayton copula for developing bivariate distribution functions. The CRCM performs well in simulating mean, standard deviation, and 5-, 20- and 50-year return levels of flood characteristics. The joint occurrence probabilities are also simulated well by the CRCM. A five-member ensemble of the CRCM simulated streamflow for the current (1970–1999) and future (2041–2070) periods, driven by five different members of a Canadian Global Climate Model ensemble, are used in the assessment of projected changes, where future simulations correspond to A2 scenario. The results of projected changes, in general, indicate increases in the marginal values, i.e. return levels of flood characteristics, and the joint occurrence probabilities P1 and P2. It is found that the future marginal values of flood characteristics and P1 and P2 values corresponding to longer return periods will be affected more by anthropogenic climate change than those corresponding to shorter return periods but the former ones are subjected to higher uncertainties.     

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.     

Contrast in Fluid M etallogeny between the Tianmashan Au-S Deposit and the Datuanshan Cu Deposit in Tongling, Anhui Province

A comprehensive contrast of ore-forming geological background and ore-forming fluid features, especially fluid ore-forming processes, has been performed between the Tianmashan and the Datuanshan ore deposits in Tongling, Anhui Province. The major reasons for the formation of the stratabound skarn Au-S ore deposit in Tianmashan and the stratabound skarn Cu ore deposit in Datuanshan are analyzed in accordance with this contrast. The magmatic pluton in Tianmashan is rich in Au and poor in Cu, but that in Datuanshan is rich in Cu and Au. The wallrock strata in Tianmashan contain Au-bearing pyrite layers with some organic substance but those in Datuanshan contain no such layers. Moreover, the ore-forming fluids in Tianmashan are dominantly magmatic ones at the oxide and sulfide stages, but those with high content of Cu in Datuanshan are mainly groundwater fluids. In addition, differences in compositional evolution and physicochemical condition variation of the ore-forming fluids result in gradual dispersion     

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.     

Effect of Data Assimilation Parameters on The Optimized Surface CO<Subscript>2</Subscript> Flux in Asia

In this study, CarbonTracker, an inverse modeling system based on the ensemble Kalman filter, was used to evaluate the effects of data assimilation parameters (assimilation window length and ensemble size) on the estimation of surface CO₂ fluxes in Asia. Several experiments with different parameters were conducted, and the results were verified using CO₂ concentration observations. The assimilation window lengths tested were 3, 5, 7, and 10 weeks, and the ensemble sizes were 100, 150, and 300. Therefore, a total of 12 experiments using combinations of these parameters were conducted. The experimental period was from January 2006 to December 2009. Differences between the optimized surface CO₂ fluxes of the experiments were largest in the Eurasian Boreal (EB) area, followed by Eurasian Temperate (ET) and Tropical Asia (TA), and were larger in boreal summer than in boreal winter. The effect of ensemble size on the optimized biosphere flux is larger than the effect of the assimilation window length in Asia, but the importance of them varies in specific regions in Asia. The optimized biosphere flux was more sensitive to the assimilation window length in EB, whereas it was sensitive to the ensemble size as well as the assimilation window length in ET. The larger the ensemble size and the shorter the assimilation window length, the larger the uncertainty (i.e., spread of ensemble) of optimized surface CO₂ fluxes. The 10-week assimilation window and 300 ensemble size were the optimal configuration for CarbonTracker in the Asian region based on several verifications using CO₂ concentration measurements.