长江中游城市群水资源承载力时空格局及耦合协调性

长江中游城市群是实施生态优先绿色发展战略的重点区域,从水资源承载系统内的水资源、社会、经济、生态环境4个子系统中选取24项指标构建水资源承载力评价体系,综合运用改进熵权TOPSIS模型、空间自相关分析和耦合协调发展模型定量评价2012-2018年长江中游城市群水资源承载力时空变化过程及子系统间的耦合协调性.结果表明,（1）长江中游城市群整体水资源承载力水平表现为：缓慢上升（2012-2015年）、下降（2015-2017年）、再上升的趋势（2017-2018年）;（2）水资源承载力的空间差异不明显（仅2016年差异显著）,武汉城市圈水资源承载力的空间差异相对较大且呈现低值包围高值的空间分布特征;（3）各城市生态环境子系统承载力得分较为均衡,但其他子系统的承载力均差异较大;（4）影响水资源承载力的主要因素依次为城市污水处理厂日处理能力、人均GDP、城镇化率、第三产业比重和人均水资源量;（5）长江中游城市群水资源承载系统的耦合协调度总体处于中等水平,且水资源承载力与耦合协调度有极强的正相关关系.研究结果可为长江中游城市群水资源承载力改善及水资源优化配置提供依据.     

Influences of meteorological conditions on interannual variations of particulate matter pollution during winter in the Beijing–Tianjin–Hebei area

To investigate the interannual variations of particulate matter (PM) pollution in winter, this paper examines the pollution characteristics of PM with aerodynamic diameters of less than 2.5 and 10 μm (i.e., PM_2.5 and PM₁₀), and their relationship to meteorological conditions over the Beijing municipality, Tianjin municipality, and Hebei Province—an area called Jing–Jin–Ji (JJJ, hereinafter)—in December 2013–16. The meteorological conditions during this period are also analyzed. The regional average concentrations of PM_2.5 (PM₁₀) over the JJJ area during this period were 148.6 (236.4), 100.1 (166.4), 140.5 (204.5), and 141.7 (203.1) μg m^–3, respectively. The high occurrence frequencies of cold air outbreaks, a strong Siberian high, high wind speeds and boundary layer height, and low temperature and relative humidity, were direct meteorological causes of the low PM concentration in December 2014. A combined analysis of PM pollution and meteorological conditions implied that control measures have resulted in an effective improvement in air quality. Using the same emissions inventory in December 2013–16, a modeling analysis showed emissions of PM_2.5 to decrease by 12.7%, 8.6%, and 8.3% in December 2014, 2015, and 2016, respectively, each compared with the previous year, over the JJJ area.     

Relationship between atmospheric heat source over the Tibetan Plateau and precipitation in the Sichuan–Chongqing region during summer

NCEP–NCAR reanalysis data and a 47-yr daily precipitation dataset from a network of 42 rain gauges are used to analyze the atmospheric heat source (<Q₁>) anomaly over the Tibetan Plateau (TP) and its influence on the summer precipitation anomaly in the Sichuan–Chongqing region. Results show that the vertical advection of <Q₁> over the central TP is a major factor affecting summer precipitation in the Sichuan–Chongqing region. When the vertical advection of <Q₁> over the central TP is strengthened, the South Asian high shifts further than normal to the south and east, the western Pacific subtropical high shifts further than normal to the south and west, and the Indian low weakens. This benefits the transport of warm moist air from the low latitude oceans to the Sichuan–Chongqing region. Correspondingly, in the high latitudes, two ridges and one trough form, which lead to cool air moving southward. These two air masses converge over the Sichuan–Chongqing region, leading to significant precipitation. In contrast, when the vertical advection of <Q₁> over the central TP is weakened, the South Asian high moves to the north and west, the subtropical high moves eastward and northward, and the Indian low strengthens. This circulation pattern is unfavorable for warm air advection from the south to the Sichuan–Chongqing region, and the cool air further north cannot move southward because of the presence of two troughs and one ridge at high latitude. Thus, ascent over the Sichuan–Chongqing region is weakened, resulting in less precipitation.     

Changes in extreme daily mean temperatures in summer in eastern China during 1955–2000

Summary Statistical characteristics of extremely low and high daily mean temperatures in summer (June, July and August) in eastern China have been investigated. The extremely low temperatures are defined as those days with temperatures not exceeding the 10th percentile with respect to the reference period of 1961–90; similarly the extremely high temperatures are defined as those exceeding the 90th percentile. There are well-defined spatial structures in trends of the frequency of extremely low temperatures as well as of high temperature extremes. In the north region (i.e. northern and northeastern China) the linear trends of frequency of low and high temperature extremes are –1.09 and +1.23 days/10yr, respectively. For the southern portion of the study area, the trends are –1.32 and –2.32 days/10yr. Taking the study area as a whole, the linear trends are –0.76 days/10yr and +1.08 days/10yr, respectively. The changes of frequency of extreme temperatures are mainly related to the shift in the temperature means. There is a dominant anticyclonic pattern in the lower- to middle troposphere over East Asia in association with warmer conditions in the north region. For the south region there is a jump-like change in the summer mean temperature and the extreme temperature events in around 1976. The large-scale northwestern Pacific subtropical high plays an important role in the jump-like changes of the temperature extremes.     

The Siberian High and climate change over middle to high latitude Asia

Summary The Siberian High is the most important atmospheric centre of action in Eurasia during the winter months. Here its variability and relationship with temperature and precipitation is investigated for the period 1922 to 2000. The pronounced weakening of the Siberian High during the last ∼ 20 years is its most remarkable feature. Mean temperature, averaged over middle to high latitude Asia (30° E–140° E, 30° N–70° N), is correlated with the Siberian High central intensity (SHCI) with correlation coefficient of − 0.58 (1922–1999), and for precipitation, the correlation coefficient is − 0.44 (1922–1998). Taking the Arctic Oscillation (AO), the SHCI, the Eurasian teleconnection pattern (EU), and the Southern Oscillation (SO) index into account, 72 percent of the variance in temperature can be explained for the period 1949–1997 (for precipitation the variance is 26 percent), with the AO alone explaining 30 percent of the variance, and the Siberian High contributing 24 percent. The precipitation variance explained by the Siberian High is only 9.8 percent of the total. Received January 2, 2001 Revised November 24, 2001     

基于WRF的高原低涡内波动特征及空心结构的初步研究

本文采用美国新一代非静力中尺度数值模式WRFV3.1.1版本对2006年8月14日的1次高原低涡过程进行了3重嵌套的数值模拟,分析模拟输出的高时空分辨率资料,发现涡度散度在各层次上均存在着正负值区域的相临交替分布,体现出一定的波动性,并随时间的变化而旋转,由此对高原低涡中的涡旋波的产生和发展进行详细分析,发现高原低涡中同时具有产生涡旋Rossby波与惯性重力波的条件,进一步粗略计算了涡旋波切向的移速介于涡旋Rossby波与惯性重力波的理论移速之间。由分析结果得出结论认为,在低涡中心区域,由于较高的涡度径向梯度,同时有较强的辐合辐散,波动表现出以涡旋Rossby波与惯性重力波混合的特性为主;低涡外围区域中涡度径向梯度大大减弱,失去了产生涡旋Rossby的条件,显现为惯性重力波的特性。同时高原低涡生命期相对较短,波动在圆周上的传播条件不均匀,这说明可能大多高原低涡螺旋形态的发展并不均匀或并不完整,较难形成如同海上热带气旋般比较均匀和完整的螺旋云带。另外,模拟也发现,在低涡成熟阶段,低涡呈现暖心结构,中心区域垂直运动较弱,表现为相对平静的眼区域。      

地面大气电场资料在强对流天气预报中的应用

利用大气电场仪对2008年6～10月天津地面大气电场变化进行连续监测。讨论晴空、稳定型降水、飑线和暴雨天气下地面大气电场强度特点,结合新一代多普勒天气雷达资料和闪电定位资料,对2008年9月4日飑线过程和2008年7月14日暴雨过程进行分析。结果发现:大气电场仪曲线在雷暴发生前15～50min剧烈变化,在强对流天气的雷电监测中有明显的指示作用。结合雷达资料和闪电定位仪资料能够提高雷电预警和短时临近预报的准确率,多站点的大气电场仪数据能够扩大雷暴监测范围并且判断雷暴云移动路径。     

油蒿在高浓度CO2条件下对干旱胁迫的反应

采用人工模拟试验方法研究毛乌素沙地沙生植物群落的优势种－－油蒿在高浓度CO2条件下对土壤干旱胁迫的反应。结果表明，不同程度的土壤干旱胁迫使油蒿生长与生物量下降，随着干旱程度的加重而增加负面影响；大气中CO2浓度升高对油蒿的生长发育起到“施肥作用”；虽然在高浓度CO2条件下发生土壤干旱胁迫对油蒿的影响也是负效应，但CO2的“施肥效应”依然存在，“施肥效应”的生理机理是CO2浓度升高提高了光合作用速率。     

亚洲季风区大气热源汇的气候特征

用1950-2005 a共56年NCEP/NCAR再分析资料和倒算法计算了全球的大气热源、热汇,分析了亚洲季风区的大气热源、热汇的基本气候特征和年变化气候特征,主要结论包括:(1)从气候平均看,亚洲季风区的南亚-热带印度洋-热带西太平洋地区是全球范围最大的大气热源区,西太平洋暖池区是最强的热源中心.(2)在亚洲季风区,大气热源、热汇的季节差异明显.从青藏高原南侧和孟加拉湾北部到中国东部和南海地区,冬季是较强的热汇区,夏季则是强的热源区;而在北太平洋中纬度和澳大利亚北部洋面上,冬季是强热源区,夏季是弱的热源或热汇.(3)亚洲季风区中,青藏高原、东亚大陆、西太平洋地区三个经度带内热源、热汇的年变化明显不同.     

抚仙湖历史水位反演与未来30年水位变化预测

在极端气候事件频发和人类活动加剧的背景下,抚仙湖水位波动显著,尤其是2009—2012年极端干旱事件的发生,使抚仙湖平均水位（1721.31 m）低于法定最低水位（1721.65 m）,给生态环境安全带来严重威胁.因此,找到合适有效的湖泊水位模拟方法,对气候变化影响下的未来水位进行预测,并做好相应的应对准备,对湖泊生态系统的保护至关重要.本文运用DYRESM水动力模型对抚仙湖1959—2050年水位进行了模拟.因抚仙湖流域尚无长时间序列的历史水文观测数据,故利用模型和水量补偿法对抚仙湖入湖水量进行反推,构建了降水量-入湖水量的回归方程,并通过有效的实测入湖水量和水位数据,对回归方程的精度进行了检验.利用全球气候模式BCC-CSM2-MR中SSP245和SSP585两种情景提供的未来气候预估数据,运用DYRESM预测了抚仙湖2021—2050年水位变化趋势.结果表明：（1）构建的DYRESM水动力模型和降水-入湖水量回归方程精度较高,模型结果能很好地反映抚仙湖水位的年际和年内变化趋势,且能有效捕捉到抚仙湖的水位峰值.（2）在SSP245和SSP585两种情景下,抚仙湖2021—2050年多年平均水位分别为1722.98和1723.93 m,较1959—2017年平均水位1721.77 m分别升高1.21和2.16 m.两种情景下抚仙湖未来水位均有部分时段超过法定最高蓄水位（1723.35 m）,但均高于法定最低水位.因此,未来气候变化对抚仙湖水量的影响有限,并不会导致水位过低,当水位超过法定最高蓄水位时,可通过控制出流闸门将水位调节在合理范围内.