全国大部降水偏少 分布不均 冷空气过程强度弱 气温偏高——2005年1月

1月份，全国大部地区降水接近常年同期或偏少，其中华南东部部分地区降水较常年偏少8成以上；长江以南出现大范围雨雪天气；月平均气温较常年同期偏高，但地区分布差异显著，江南以及华南等地出现较为严重的冰(霜)冻灾害。     

西北地区降水偏多大雾天气发生频繁——2006年12月——

2006年12月，我国大部分地区降水偏少或接近常年同期，西北地区东南部出现明显降水过程，旱情有所缓解，但东北大部、江南北部、华南西部以及新疆中南部、云南南部、西藏南部等地降水偏少，干旱维持或发展；全国大部地区月平均气温接近常年同期或偏高。中东部地区大雾天气比较频繁。     

部分地区发生暴雨洪涝灾害两个台风登陆浙江和福建——2004年8月

8月份，全国大部地区降水接近常年同期或偏少，气温接近常年同期或偏低，日照时数接近常年同期或偏少。本月出现的主要气候事件有：两个台风登陆我国，浙江、福建等省部分地区受灾严重；20多个省市区局部发生暴雨洪涝或泥石流、滑坡等灾害；内蒙古东北部、黑龙江西南部和吉林西部等地大部旱情缓解；江南东部、华南大部等地出现长时间高温天气；四川、宁夏等省区局地遭受冰雹或雷暴袭击。     

江西、湖南深秋暴雨 西北、华北干旱严重——2005年11月——

11月份，全国平均降水量为25．4mm，接近常年同期（26．3mm）。全国平均气温为6．8℃，比常年同期（5．2℃）偏高1．6℃，为1951年以来的历史同期第四高值。月内，江西、湖南部分地区降水明显偏多，造成暴雨洪涝灾害；南方部分地区旱情月内出现缓解；华北大部、西北地区东北部等地由于降水偏少，旱情持续或发展；中东部地区出现大雾天气；青海南部雪灾较为严重，内蒙古中东部等地出现沙尘天气；江南、西南东部、华南北部等地出现持续阴雨寡照天气。     

南方普降大雪 华南持续干旱——2005年1月

1月份 ,全国大部地区降水接近常年同期或偏少 ,其中华南东部部分地区降水较常年偏少 8成至 1倍 ,旱情趋于严重 ;云南西南部旱情有所抬头。长江以南出现大范围雨雪天气 ,湘、赣、鄂、贵等地遭受雪灾。月平均气温较常年同期偏高 ,但地区分布差异显著 ,江南以及华南等地出现较为严重的冰 (霜 )冻灾害 ,农作物生产受到一定影响。我国中东部地区雾日频繁 ,给交通运输带来很大影响 ,全国因雾引发交通事故较上月有大幅度的上升。1　长江以南出现大范围雨雪天气 ,湘、赣、鄂、贵等地遭受雪灾1 0～ 1 3日 ,受西南暖湿气流和南下冷空气影响 ,西南地区…     

长江中下游华南持续秋旱 西南局地发生暴雨洪涝--2004年10月--

10月份,全国大部地区降水量较常年同期偏少,华南和长江中下游地区由于持续少雨发生大面积秋旱,其中广西、广东、安徽等地旱情严重。月平均气温,全国大部地区接近常年同期,内蒙古东部、东北较常年同期明显偏高。月内,华南部分地区出现寒露风天气;甘肃、宁夏等地的部分地区遭受霜冻灾害;     

台风登陆浙江福建南方出现高温天气——2004年8月

8月份，全国大部地区降水接近常年同期或偏少，上中旬内蒙古东部、黑龙江西南部、吉林西部、四川东部、重庆等地旱情持续或发展，下旬上述大部地区旱情缓解；全国大部地区气温接近常年同期或偏低；江南、华南等地出现持续高温天气。有8个热带气旋活动，其中有两个在我国华南沿海登陆。受登陆台风云娜、艾莉的影响，浙江、福建等省部分地区发生严重的暴雨洪涝或泥石流等灾害。     

南方高温酷热台风活动频繁——2001年7月——

7月份,全国大部气温偏高或接近常年,南方大部出现持续高温酷热天气.月内有6个热带气旋活动,5个在华南沿海登陆.全国大部降水偏少或接近常年.中、下旬,北方旱区出现较明显降雨,大部旱情得到缓解;长江中下游部分地区及四川盆地、重庆等地降水偏少,部分地区伏旱严重,华南大部及西南南部降水明显偏多,部分地区出现暴雨洪涝灾害.     

西北地区降水偏多 大雾天气发生频繁

2006年12月, 我国大部分地区降水偏少或接近常年同期.西北地区东南部出现明显降水过程, 旱情有所缓解, 但东北大部、江南北部、华南西部以及新疆中南部、云南南部、西藏南部等地降水偏少, 干旱维持或发展; 全国大部地区月平均气温接近常年同期或偏高. 中东部地区大雾天气比较频繁.     

北方大部旱情缓解 南方出现高温伏旱 华南连遭台风袭击 广西广东损失严重

7月份 ,全国大部降水偏少或接近常年。中、下旬 ,北方旱区出现较明显降雨 ,大部旱情得到不同程度的缓解 ;南方降雨不均 ,长江中下游部分地区及四川盆地、重庆等地伏旱严重 ,华南大部降水偏多 ,部分地区出现洪涝。全国大部地区月平均气温偏高或接近常年 ;南方大部出现持续高温酷热天气。有 5个台风在华南沿海登陆 ,两广等地损失严重。1　北方旱区普降喜雨 ,大部旱情缓解 ;长江中下游等地伏旱明显7月份 ,北方大部降水偏少或接近常年。西北大部、华北中北部月降水量在 1 0 0ｍｍ以下 ,其中新疆南部和东部、青海北部及甘肃西部等地不足 1 0ｍｍ…     

Performance of a multi-RCM ensemble for South Eastern South America

The ability of four regional climate models to reproduce the present-day South American climate is examined with emphasis on La Plata Basin. Models were integrated for the period 1991–2000 with initial and lateral boundary conditions from ERA-40 Reanalysis. The ensemble sea level pressure, maximum and minimum temperatures and precipitation are evaluated in terms of seasonal means and extreme indices based on a percentile approach. Dispersion among the individual models and uncertainties when comparing the ensemble mean with different climatologies are also discussed. The ensemble mean is warmer than the observations in South Eastern South America (SESA), especially for minimum winter temperatures with errors increasing in magnitude towards the tails of the distributions. The ensemble mean reproduces the broad spatial pattern of precipitation, but overestimates the convective precipitation in the tropics and the orographic precipitation along the Andes and over the Brazilian Highlands, and underestimates the precipitation near the monsoon core region. The models overestimate the number of wet days and underestimate the daily intensity of rainfall for both seasons suggesting a premature triggering of convection. The skill of models to simulate the intensity of convective precipitation in summer in SESA and the variability associated with heavy precipitation events (the upper quartile daily precipitation) is far from satisfactory. Owing to the sparseness of the observing network, ensemble and observations uncertainties in seasonal means are comparable for some regions and seasons.     

Variability of rainfall characteristics over the South Coast region of South Africa

Thirty years of daily rainfall data are analysed for the South Coast region of South Africa, a region which experiences substantial rainfall variability and frequent severe drought and flood events, but whose climate variability has not been much researched. It is found that El Niño–Southern Oscillation (ENSO) exerts an influence since most wet years correspond to mature phase La Niña years. ENSO also influences South Coast rainfall via increases in the number of cut-off lows in southern South Africa during mature phase La Niña years. A statistically significant correlation between the Niño 3.4 index and monthly rainfall totals, and between this index and the frequency of wet days, exists for two summer months and also for June. There are also changes in the heavy rainfall day frequencies from one decade to another. Examination of NCEP re-analyses indicates that wet (dry) years result from an equatorward (poleward) shift in the subtropical jet, cyclonic (anticyclonic) pressure anomalies over the South Atlantic and South Africa, and increased (decreased) density of mid-latitude cyclonic systems.     

南海季风试验研究

介绍了"九五"国家攀登项目"南海季风试验"外场观测系统和主要结果.该试验是一次旨在了解南海季风爆发,维持和变化主要物理过程的大气与海洋联合试验,是由十几个国家与地区参加的一次大型国际合作项目.通过1998年5～8月的外场观测试验,取得了大量和多种大气与海洋的加密观测资料,为南海和东亚季风及其与海洋的相互作用研究提供了比较完善的资料集.目前研究正在深入阶段.作者只是对这个试验的一般情况作了说明.     

South Indian Ocean Rossby Waves

ABSTRACT

South Indian Ocean Rossby waves (SIO-RW) are identified in the Global Ocean Data Assimilation System (GODAS) 1.5–7?yr filtered sea surface height (SSH) time series. There is a persistent three-year oscillation in the 5°–15°S latitude band from 55° to 85°E. Field correlations show little coupling at 90°E, but as the SIO-RW undulates westward at approximately 0.19?m?s^?1 across the mid-basin, a northwest–southeast axis of warm sea surface temperatures (SSTs) and deep convection forms. Many teleconnections in earlier work are confirmed: interannual pulses of zonal wind in the eastern basin trigger the SIO-RW via anticyclonic wind stress curl. New insights derive from an understanding of links with the upper troposphere. As the SIO-RWs move westward with the onset of an El Niño in the Pacific, increased convection over the north Indian Ocean corresponds to reduced evaporation and SST warming. Mid-tropospheric heating T′?>?2°C over the northwest Indian Ocean accelerates the southern sub-tropical jet to greater than 10?m?s^?1 over the southeast Indian Ocean, reinforcing the anticyclonic vorticity. The downstream acceleration of the jet generates upper-level divergence and moist convection over the western basin, anchoring an atmospheric Rossby wave in a northwest–southeast alignment underpinned by differential propagation of the SIO-RW. As the ocean Rossby wave reaches Africa, the coupling fades and transitions. What distinguishes Indian Ocean from Pacific Ocean Rossby waves are their southern latitude and higher frequency. The tropical mid-tropospheric heating that accelerates the southern sub-tropical jet shifts westward in tandem with the SIO-RW.     

Influence of South China Sea SST and the ENSO on Winter Rainfall over South China

The present study investigates the influence of South China Sea (SCS) SST and ENSO on winter (January--February--March; JFM) rainfall over South China and its dynamic processes by using station observations for the period 1951--2003, Met Office Hadley Center SST data for the period 1900--2008, and ERA-40 reanalysis data for the period 1958--2002. It is found that JFM rainfall over South China has a significant correlation with Nino-3 and SCS SST. Analyses show that in El Nino or positive SCS SST anomaly years, southwesterly anomalies at 700 hPa dominate over the South China Sea, which in turn transports more moisture into South China and favors increased rainfall. A partial regression analysis indicates that the independent ENSO influence on winter rainfall occurs mainly over South China, whereas SCS SST has a larger independent influence on winter rainfall in northern part of South China. The temperature over South China shows an obvious decrease at 300 hPa and an increase near the surface, with the former induced by Nino-3 and the latter SCS SST anomalies. This enhances the convective instability and weakens the potential vorticity (PV), which explains the strengthening of ascending motion and the increase of JFM rainfall over South China.     

华南南部前汛期气温异常的时空变化特征

利用国家气候中心整编的1951—2000年中国160个站的月平均气温资料，根据“九五”重中之重项目执行组指出的华南地区代表站，选出华南南部地区12个代表站。侧重分析了华南南部前汛期气温异常的季节、年际和年代际变化的时空特征。发现在年代际变化方面，20世纪60年代中期到80年代末为相对低温期，90年代以后温度有明显升高的趋势，而且50a温度变化的总趋势是增加的。华南南部前汛期气温异常存在2a、4a、5a的年际周期和12a和19a的年代际周期；在空间上，华南南部前汛期气温增暖的幅度相对较弱，华南南部的前汛期气温与全国大部分地区呈现同位相的变化特征，与个别地区呈反位相。     

Influence of ENSO and the South Atlantic Ocean on climate predictability over Southeastern South America

We perform a systematic study of the predictability of surface air temperature and precipitation in Southeastern South America (SESA) using ensembles of AGCM simulations, focusing on the role of the South Atlantic and its interaction with the El Niño-Southern Oscillation (ENSO). It is found that the interannual predictability of climate over SESA is strongly tied to ENSO showing high predictability during the seasons and periods when there is ENSO influence. The most robust ENSO signal during the whole period of study (1949–2006) is during spring when warm events tend to increase the precipitation over Southeastern South America. Moreover, the predictability shows large inter-decadal changes: for the period 1949–1977, the surface temperature shows high predictability during late fall and early winter. On the other hand, for the period 1978–2006, the temperature shows (low) predictability only during winter, while the precipitation shows not only high predictability in spring but also in fall. Furthermore, it is found that the Atlantic does not directly affect the climate over SESA. However, the experiments where air–sea coupling is allowed in the south Atlantic suggest that this ocean can act as a moderator of the ENSO influence. During warm ENSO events the ocean off Brazil and Uruguay tends to warm up through changes in the atmospheric heat fluxes, altering the atmospheric anomalies and the predictability of climate over SESA. The main effect of the air–sea coupling is to strengthen the surface temperature anomalies over SESA; changes in precipitation are more subtle. We further found that the thermodynamic coupling can increase or decrease the predictability. For example, the air–sea coupling significantly increases the skill of the model in simulating the surface air temperature anomalies for most seasons during period 1949–1977, but tends to decrease the skill in late fall during period 1978–2006. This decrease in skill during late fall in 1978–2006 is found to be due to a wrong simulation of the remote ENSO signal that is further intensified by the local air–sea coupling in the south Atlantic. Thus, our results suggest that climate models used for seasonal prediction should simulate correctly not only the remote ENSO signal, but also the local air–sea thermodynamic coupling.