Projections of high resolution climate changes for South Korea using multiple-regional climate models based on four RCP scenarios. Part 1: surface air temperature

We projected surface air temperature changes over South Korea during the mid (2026-2050) and late (2076-2100) 21st century against the current climate (1981-2005) using the simulation results from five regional climate models (RCMs) driven by Hadley Centre Global Environmental Model, version 2, coupled with the Atmosphere- Ocean (HadGEM2-AO), and two ensemble methods (equal weighted averaging, weighted averaging based on Taylor’s skill score) under four Representative Concentration Pathways (RCP) scenarios. In general, the five RCM ensembles captured the spatial and seasonal variations, and probability distribution of temperature over South Korea reasonably compared to observation. They particularly showed a good performance in simulating annual temperature range compared to HadGEM2-AO. In future simulation, the temperature over South Korea will increase significantly for all scenarios and seasons. Stronger warming trends are projected in the late 21st century than in the mid-21st century, in particular under RCP8.5. The five RCM ensembles projected that temperature changes for the mid/late 21st century relative to the current climate are +1.54°C/+1.92°C for RCP2.6, +1.68°C/+2.91°C for RCP4.5, +1.17°C/+3.11°C for RCP6.0, and +1.75°C/+4.73°C for RCP8.5. Compared to the temperature projection of HadGEM2-AO, the five RCM ensembles projected smaller increases in temperature for all RCP scenarios and seasons. The inter-RCM spread is proportional to the simulation period (i.e., larger in the late-21st than mid-21st century) and significantly greater (about four times) in winter than summer for all RCP scenarios. Therefore, the modeled predictions of temperature increases during the late 21st century, particularly for winter temperatures, should be used with caution.     

Ocean–atmosphere coupling and the boreal winter MJO

The influence of ocean–atmosphere coupling on the simulation and prediction of the boreal winter Madden–Julian Oscillation (MJO) is examined using the Seoul National University coupled general circulation model (CGCM) and atmospheric—only model (AGCM). The AGCM is forced with daily SSTs interpolated from pentad mean CGCM SSTs. Forecast skill is examined using serial extended simulations spanning 26 different winter seasons with 30-day forecasts commencing every 5 days providing a total of 598 30-day simulations. By comparing both sets of experiments, which share the same atmospheric components, the influence of coupled ocean–atmosphere processes on the simulation and prediction of MJO can be studied. The mean MJO intensity possesses more realistic amplitude in the CGCM than in AGCM. In general, the ocean–atmosphere coupling acts to improve the simulation of the spatio-temporal evolution of the eastward propagating MJO and the phase relationship between convection (OLR) and SST over the equatorial Indian Ocean and the western Pacific. Both the CGCM and observations exhibit a near-quadrature relationship between OLR and SST, with the former lagging by about two pentads. However, the AGCM shows a less realistic phase relationship. As the initial conditions are the same in both models, the additional forcing by SST anomalies in the CGCM extends the prediction skill beyond that of the AGCM. To test the applicability of the CGCM to real-time prediction, we compute the Real-time Multivariate MJO (RMM) index and compared it with the index computed from observations. RMM1 (RMM2) falls away rapidly to 0.5 after 17–18 (15–16) days in the AGCM and 18–19 (16–17) days in the CGCM. The prediction skill is phase dependent in both the CGCM and AGCM.     

From brightening to dimming in sunshine duration over the eastern and central Tibetan Plateau (1961–2005)

The Tibetan Plateau (TP) with an average elevation of over 4,000 m asl is the highest and most extensive highland in the world. We used monthly mean sunshine duration from the Chinese Meteorological Administration to examine the spatial and temporal variability of sunshine duration at 71 stations with elevations above 2,000 m asl in the eastern and central TP during the 1961–2005 period. The temporal evolution of the mean annual sunshine duration series shows a significant increase from 1961 to 1982 at a rate of 49.8 h/decade, followed by a decrease from 1983 to 2005 at a rate of ?65.1 h/decade, with an overall significant decrease at a rate of ?20.6 h/decade during the whole 1961–2005 period, which is mainly due to the summer and spring seasons. This confirms the evidence that sunshine duration in the TP ranges from brightening to dimming in accordance with sunshine duration trends in the rest of China. The surface solar radiation downwards from ERA-40 reanalysis data in the same region confirms the brightening/dimming phenomenon shown by the sunshine duration before/after the 1980s. Otherwise, additional climatic variables such as low cloud amount, total cloud amount, precipitation, relative humidity and water vapor pressure, in most cases, exhibit significant negative correlation with sunshine duration in the TP on an annual and seasonal basis before and after 1982, respectively. The trends of these variables suggest that changes in some of them might be related to the brightening and dimming detected with the use of sunshine duration measurements over the TP. We also hypothesize that the impact of anthropogenic aerosols upon the climatic variables analyzed cannot be rejected, especially in the significant increase in low cloud cover since approximately 1980.     

池州地区冬半年固态降水及其环流背景统计特征

基于2003－2018年池州冬半年观测资料,采用T-mode主成分客观分析法（TPCA）等方法进行固态降水与环流背景的统计分析。结果表明：池州172个固态降水日中,固态降水的主要月份占比分别是1月的44.8%、2月的27.9%和12月的16.3%;其中雨雪转换、纯雪和冻雨3类占比分别为55.2%、41.3%和3.5%。环流形势可划分为一槽一脊型（Ⅰ型）,纬向波动型（Ⅱ型）和两槽一脊型（Ⅲ型）,Ⅰ型占比最多,Ⅱ型次之,Ⅲ型较少。Ⅰ～Ⅲ型分别代表北方冷空气从中路、西路和东路南下,池州固态降水过程主要受中路冷空气影响。Ⅰ型气温最低,出现固态降水概率最高,是其它形势3倍以上;Ⅱ型气温最高,出现固态降水概率最低。除Ⅲ型外,纯雪过程中低层温度均较雨雪转换过程低2.0 ℃左右;雨雪转换过程中925 hPa温度与850 hPa基本相同,一般在-4.0～-5.0 ℃之间,而纯雪过程则较850 hPa偏高1.0 ℃左右;雨雪转换过程1000 hPa温度基本在0 ℃附近,纯雪则在0 ℃以下。925 hPa盛行东北风,850 hPa存在气旋性环流,配合700 hPa上12.0 m/s左右急流、水汽通量及水汽通量散度大值中心,有利于池州固态降水的产生。它一般属于大尺度降水,层结稳定,锋区位于700 hPa以下,低层有冷平流,切变线一般位于850～800 hPa之间。     

TREC算法在人工影响天气作业指挥系统中的应用

雷达回波外推是解决人工影响天气指挥炮点作业时间选取的有效途径。文章介绍了雷达回波外推的相关性跟踪方法（TREC）,由TREC矢量得到的回波移向移速,以6 min为间隔,线性外推4次回波,根据外推回波是否落在炮点的有效射程范围内,得到回波到达炮点射程范围的时间,为炮点作业时间的选取提供参考。个例分析表明,外推回波落在炮点有效射程范围的外推时间与回波实际落在炮点的有效射程范围内时间点基本吻合。     

Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004)

We assessed current status of multi-model ensemble (MME) deterministic and probabilistic seasonal prediction based on 25-year (1980–2004) retrospective forecasts performed by 14 climate model systems (7 one-tier and 7 two-tier systems) that participate in the Climate Prediction and its Application to Society (CliPAS) project sponsored by the Asian-Pacific Economic Cooperation Climate Center (APCC). We also evaluated seven DEMETER models’ MME for the period of 1981–2001 for comparison. Based on the assessment, future direction for improvement of seasonal prediction is discussed. We found that two measures of probabilistic forecast skill, the Brier Skill Score (BSS) and Area under the Relative Operating Characteristic curve (AROC), display similar spatial patterns as those represented by temporal correlation coefficient (TCC) score of deterministic MME forecast. A TCC score of 0.6 corresponds approximately to a BSS of 0.1 and an AROC of 0.7 and beyond these critical threshold values, they are almost linearly correlated. The MME method is demonstrated to be a valuable approach for reducing errors and quantifying forecast uncertainty due to model formulation. The MME prediction skill is substantially better than the averaged skill of all individual models. For instance, the TCC score of CliPAS one-tier MME forecast of Niño 3.4 index at a 6-month lead initiated from 1 May is 0.77, which is significantly higher than the corresponding averaged skill of seven individual coupled models (0.63). The MME made by using 14 coupled models from both DEMETER and CliPAS shows an even higher TCC score of 0.87. Effectiveness of MME depends on the averaged skill of individual models and their mutual independency. For probabilistic forecast the CliPAS MME gains considerable skill from increased forecast reliability as the number of model being used increases; the forecast resolution also increases for 2 m temperature but slightly decreases for precipitation. Equatorial Sea Surface Temperature (SST) anomalies are primary sources of atmospheric climate variability worldwide. The MME 1-month lead hindcast can predict, with high fidelity, the spatial–temporal structures of the first two leading empirical orthogonal modes of the equatorial SST anomalies for both boreal summer (JJA) and winter (DJF), which account for about 80–90% of the total variance. The major bias is a westward shift of SST anomaly between the dateline and 120°E, which may potentially degrade global teleconnection associated with it. The TCC score for SST predictions over the equatorial eastern Indian Ocean reaches about 0.68 with a 6-month lead forecast. However, the TCC score for Indian Ocean Dipole (IOD) index drops below 0.40 at a 3-month lead for both the May and November initial conditions due to the prediction barriers across July, and January, respectively. The MME prediction skills are well correlated with the amplitude of Niño 3.4 SST variation. The forecasts for 2 m air temperature are better in El Niño years than in La Niña years. The precipitation and circulation are predicted better in ENSO-decaying JJA than in ENSO-developing JJA. There is virtually no skill in ENSO-neutral years. Continuing improvement of the one-tier climate model’s slow coupled dynamics in reproducing realistic amplitude, spatial patterns, and temporal evolution of ENSO cycle is a key for long-lead seasonal forecast. Forecast of monsoon precipitation remains a major challenge. The seasonal rainfall predictions over land and during local summer have little skill, especially over tropical Africa. The differences in forecast skills over land areas between the CliPAS and DEMETER MMEs indicate potentials for further improvement of prediction over land. There is an urgent need to assess impacts of land surface initialization on the skill of seasonal and monthly forecast using a multi-model framework.     

Distribution of seasonal rainfall in the East Asian monsoon region

Summary ?This study deals with the climatological aspect of seasonal rainfall distribution in the East Asian monsoon region, which includes China, Korea and Japan. Rainfall patterns in these three countries have been investigated, but little attention has been paid to the linkages between them. This paper has contributed to the understanding of the inter-linkage of various sub-regions. Three datasets are used. One consists of several hundred gauges from China and South Korea. The second is based on the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP). The two sources of precipitation information are found to be consistent. The third dataset is the NCEP/NCAR reanalysis 850-hPa winds. The CMAP precipitation shows that the seasonal transition over East Asia from the boreal winter to the boreal summer monsoon component occurs abruptly in mid-May. From late March to early May, the spring rainy season usually appears over South China and the East China Sea, but it is not so pronounced in Japan. The summer monsoon rainy season over East Asia commonly begins from mid-May to late May along longitudes of eastern China, the Korean Peninsula, and Japan. A strong quasi-20-day sub-seasonal oscillation in the precipitation appears to be dominant during this rainy season. The end date of the summer monsoon rainy season in eastern China and Japan occurs in late July, while the end date in the Korean Peninsula is around early August. The autumn rainy season in the Korean Peninsula has a major range from mid-August to mid-September. In southern China, the autumn rainy season prevails from late August to mid-October but a short autumn rainy season from late August to early September is noted in the lower part of the Yangtze River. In Japan, the autumn rainy season is relatively longer from mid-September to late October. The sub-seasonal rainfall oscillation in Korea, eastern China and Japan are explained by, and comparable to, the 850-hPa circulation. The strong westerly frontal zone can control the location of the Meiyu, the Changma, and the Baiu in East Asia. The reason that the seasonal sea surface temperature change in the northwestern Pacific plays a critical role in the northward advance of the onset of the summer monsoon rainfall over East Asia is also discussed. Received October 5, 2001; revised April 23, 2002; accepted May 11, 2002     

飓风中的涡旋罗斯贝波

文中从柱坐标系下的正压无辐散涡度方程出发,用WKBJ方法求解方程,发现在飓风中存在类似于行星罗斯贝波的涡旋罗斯贝波,这种波的形成主要是由于飓风中基态涡度垂直分量的径向梯度所决定。利用一次飓风过程的精确数值模拟所输出高分辨的资料,计算了飓风中径向涡度梯度的分布,指出这类波动主要存在于眼墙和眼心中。波动结构分析表明,波动能量具有径向频散,这有可能是飓风暖心结构的一种形成机制。最后用波射线法讨论了定常涡旋罗斯贝波的径向频散     

南极伊利莎白公主地250年来雪芯累积、氧同位素与化学研究

1Introduction In the ongoing discussion of climate change,the mass balance of Antarctica has received increasing attention during recent decades,since its reaction to global warming will strongly influence sea-level change(Schlosser and Oerter,2002).Many …