The Preferred Structure of the Interannual Indian Monsoon Variability

The leading empirical orthogonal function (EOF) of the June-Sept. mean, rotational horizontal wind at 850 hPa and 200 hPa (over the region 12.5°S–42.5°N, 50°E–100°E) from 56 years (1948–2003) of reanalysis (from the National Centers for Environmental Prediction) shows strong anti-cyclonic circulation at upper levels, strong Indian Ocean cross-equatorial flow and on-shore flow over western India at lower levels . The associated principal component (PC) is correlated at the 0.75 level with the seasonal mean observed Indian Monsoon rainfall (IMR). Composite differences of vertically integrated divergence (surface to 800 hPa) and vorticity (surface to 500 hPa) between ``strong' years (PC-1 exceeds one standard deviation σ) and ``weak' years (PC-1 less than − σ) suggest increased rising motion and storminess over the Bay of Bengal and central India. Composite difference maps of station rainfall from the India Meteorological Department (IMD) between strong years and normal years (weak years and normal years) are statistically significant over central India, with strong (weak) years associated with increased (decreased) precipitation. In both cases the maps of rainfall anomalies are of one sign throughout India. The correlation of PC-1 with global seasonal mean SST is strong and negative over the eastern equatorial Pacific, but positive in a surrounding horse-shoe like region. Significant negative correlation occurs in the northwestern Indian Ocean. The lag/lead correlation between the NINO3 SST index and PC-1 is similar to but stronger than the NINO3/IMR correlation. Modest (but significant) negative correlation is seen when NINO3 leads PC-1 (or IMR) by one-two months. Strong negative correlation is seen when PC-1 (or IMR) leads NINO3. The projections of running five-day means of horizontal rotational winds at 850 and 200 hPa onto EOF-1 (after removing the seasonal mean for each year) were pooled for strong, normal and weak years. The strong and normal year probability distribution functions (pdfs) are nearly indistinguishable, but the weak year pdf has more weight for moderate negative values and in both extreme tails and shows some hint of bi-modality.     

SEASONAL AND INTER-ANNUAL VARIABILITY OF THE SOUTH CHINA SEA WARM POOL AND ITS RELATION TO THE SOUTH CHINA SEA MONSOON ONSET

The South China Sea warm pool interacts vigorously with the summer monsoon which is active in the region. However, there has not been a definition concerning the former warm pool which is as specific as that for the latter. The seasonal and inter-annual variability of the South China Sea warm pool and its relations to the South China Sea monsoon onset were analyzed using Levitus and NCEP/NCAR OISST data. The results show that, the seasonal variability of the South China Sea warm pool is obvious, which is weak in winter, develops rapidly in spring, becomes strong and extensive in summer and early autumn, and quickly decays from mid-autumn. The South China Sea warm pool is 55 m in thickness in the strongest period and its axis is oriented from southwest to northeast with the main section locating along the western offshore steep slope of northern Kalimantan-Palawan Island. For the warm pools in the South China Sea, west Pacific and Indian Ocean, the oscillation, which is within the same large scale air-sea coupling system, is periodic around 5 years. There are additional oscillations of about 2.5 years and simultaneous inter-annual variations for the latter two warm pools. The intensity of the South China Sea warm pool varies by a lag of about 5 months as compared to the west Pacific one. The result also indicates that the inter-annual variation of the intensity index is closely related with the onset time of the South China Sea monsoon. When the former is persistently warmer (colder) in preceding winter and spring, the monsoon in the South China Sea usually sets in on a later (earlier) date in early summer. The relation is associated with the activity of the high pressure over the sea in early summer. An oceanic background is given for the prediction of the South China Sea summer monsoon, though the mechanism through which the warm pool and eventually the monsoon are affected remains unclear.     

青藏高原臭氧的准两年振荡

通过对臭氧卫星观测资料及大气环流资料的分析,研究了青藏高原上空臭氧的季节和年际变化.通过分析青藏高原地区臭氧准两年振荡(QBO),并与同纬度无山区及赤道地区臭氧QBO进行比较,指出:青藏高原臭氧QBO的平均周期为29个月,平均振幅为8DU.青藏高原臭氧QBO变化位相与热带平流层纬向风场QBO相反,即热带平流层纬向西风时,青藏高原上空臭氧总量偏小,东风时臭氧总量偏大.还讨论了与青藏高原臭氧QBO相关的大气环流物质输送理论.     

Trends in land surface evapotranspiration across China with remotely sensed NDVI and climatological data for 1981–2010

Abstract

Using satellite observations of Normalized Difference Vegetation Index (NDVI) from NOAA-AVHRR and Terra-MODIS, together with climatic data in a physical evapotranspiration (ET) model, the spatio-temporal variability of ET is investigated in terrestrial China from 1981 to 2010. The model predictions of actual ET (ET_a) are validated with ET values from in situ eddy covariance flux measurements and from basin water balance calculations. The national averaged crop reference ET (ET_p) and ET_a values are 916 ± 21 and 415 ± 12 mm year^-1, respectively. The annual ET_a pattern is closely associated with vegetation conditions in the eastern part of China, whereas ET_a is low in the sparsely-vegetated areas and deserts in the northwestern region, corresponding to scarce rainfall events and amounts. The trends of ET_p and ET_a are remarkably different over the country, and the complementary relationship between ET_p and ET_a is revealed for the study period. Averaged over the whole country, ET_a showed an increasing trend from the 1980s to the mid-1990s, followed by a decreasing trend, consistent with the precipitation anomaly. Across the main vegetation types, annual ET_a amounts are found to correspond clearly with the bands of precipitation and ET_p.     

三沙市海域海平面变化

使用1993-2011年的台站和卫星高度计资料详细分析了三沙市海域近19 a的海平面变化特征及规律。结果表明:三沙市周边海域海平面存在明显的季节变化,且区域特征明显。海平面变化除了明显的年和半年周期,2~3 a、4~7 a和准9 a的周期也较显著。海平面长期变化呈现明显的波动上升趋势,且空间分布上区域特征显著,西沙群岛南部海域海平面上升趋势最强,西沙群岛北部与中沙群岛西部次之,南沙群岛东部海平面上升速率较快,南沙群岛西部上升趋势最弱。受大气环流等异常气候事件的影响,1998年和2010年海平面的年际变化波动较大,年变化振幅显著偏高。未来三沙市海平面将继续上升,预计2030年、2050年、2070年和2100年海平面将比常年分别升高约11 cm、20 cm、30 cm和45 cm。     

西北西风区与东部季风区年气温变化特征对比分析

利用我国西北西风区138站、东部季风区375站1964\_2006年43 a的年平均气温资料,对其时空变化特征及气温变化倾向率进行了对比分析。结果表明,西风区与季风区的时间变化规律基本一致,总体是在波动中呈一致的上升趋势,上升的趋势均是随着时间的推移而增加的,但西风区的年际变化更为剧烈,年际变化幅度大;除西风区1站和季风区4站具有负温度变率外,其余各站均为正温度变率,西风区≥0.4 ℃/10a变率区位于新疆西北部、新疆东部至青海西部的带状分布区及内蒙中部地区,而季风区≥0.4 ℃/10a位于受季风影响相对弱的北部地区,主要是西安-天津以西、以北的华北、东北地区。     

1971-2005年西藏主要农区农田蒸散量变化特征及其与环境因子的关系

利用1971—2005年西藏"一江两河"主要农区4个气象站点月平均最高气温、最低气温、降水量、风速、相对湿度、日照时数等资料,应用Penman-Monteith模型计算了农田蒸散量,分析其空间分布、年际和年代际变化特征,并讨论了影响蒸散量变化的气象因子.研究表明:近35a西藏主要农区年蒸散量表现为不同程度的减小趋势,为-16.5～-71.6mm.(10a)-1,以泽当减幅最大;四季蒸散量均呈现为减小趋势,以冬季减幅最明显.土壤水分年亏缺量呈明显的减少趋势,平均每10a减小59.6mm,特别是近25a(1981—2005年)减幅更明显.20世纪70年代至90年代年、季蒸散量均为逐年代减小趋势.90年代与80年代比较,主要农区各季土壤水分亏缺量都有不同程度的减小,尤其是夏季由亏缺转为盈余.日照时数和平均风速的显著下降,以及平均相对湿度的明显增加可能是蒸散量显著下降的主要原因,平均气温日较差的显著减小和降水量的增加在蒸散量减少趋势中也起着重要作用.     

乌鲁木齐河流域气候变化的区域差异特征及突变分析

利用乌鲁木齐河流域气象站的气温和降水资料,运用一元回归分析法和5年趋势滑动,进行了气候变化的趋势分析。结果表明:乌鲁木齐河流域的年平均气温在20世纪60-80年代偏低,90年代以后偏高,即80年代前呈下降趋势,90年代后呈上升趋势,并且秋、冬季升温幅度较大;60年代降水量最少,之后逐渐增多,2000年以来迅速增多;气温变化在空间上表现出上游气温低于下游,秋、冬季气候变暖明显早于春、夏季;降水变化的空间差异也明显。在此基础上,利用滑动T检验法、YAMAMOTO检验信噪比(SNR)、Mann-Kendall法、Cramer法和Pettitt法进行气候突变分析。结果表明:乌鲁木齐河流域气温降水突变不明显,不同方法检验的结果不太一致;春、夏季气温可能在1997年发生突变,而秋、冬季在80年代末90年代初发生突变。     

青海高原太阳辐射时空分布特征

对西宁莫家泉湾和玉树辐射观测站的资料分别进行了订正和插补,对青海省太阳辐射的空间分布、年际变化进行了系统研究。结果表明：青海省年总辐射量高,总的分布趋势西高东低;20世纪70年代是总辐射高值时期,而80年代处于明显的低值时期,80年代末期至90年代初期有所回升,但90年代中期后处于下降状态。70年代的高值期和80年代低值期的出现与该时段青海省云雨状况和全球重大火山喷发事件密切相关,火山喷发是导致80年代总辐射量减少的重要原因。     

基于Google Earth Engine的红树林年际变化监测研究

遥感技术已广泛应用于红树林资源调查与动态监测中,但仍然存在遥感数据获取困难、数据预处理工作量大、监测时间长而周期过大等问题,影响了学者对红树林演变过程的精细刻画与理解。本文基于Google Earth Engine（GEE）云遥感数据处理平台,选取Landsat系列卫星数据,生成长时间序列年际极少云影像集（云量少于5%）,利用3个红外波段反射率（NIR、SWIR1、SWIR2）和3个特征指数（NDVI、NDWI、NDMI）建立阈值规则集,实现对实验区越南玉显县红树林、红树林-虾塘、不透水面-裸地、水体4种目标地物的专家知识决策树分类和土地覆盖的制图,并基于分类结果监测该区域1993-2017年的红树林年际动态变化。结果表明：GEE平台可满足多云多雨地区红树林的长时间序列年际变化监测需求;本文阈值分类方法可以有效提取红树林及红树林-虾塘,实验区有86%年份的影像分类精度达到80%以上;年际变化监测可精细刻画实验区红树林面积先增后减再增的变化过程,也能准确反映红树林与红树林-虾塘养殖系统面积之间的负相关关系。红树林年际动态监测结果可以降低红树林演变分析的不确定性,并能更精细地量化红树林与其他土地覆盖类型的转化过程,从而评估经济发展、政策等因素对红树林演变的影响。