黄河源区植被变化趋势及其对气候变化的响应过程研究

利用1982～2001年NOAA/AVHRR(美国大气海洋局卫星/甚高分辨率辐射计)NDVI(归一化植被指数)资料、2000～2008年EOS/MODIS(地球观测系统卫星/中等分辨率成像光谱仪)NDVI资料以及1982～2008年黄河源区的玛多、玛曲和兴海气象台站逐月气温和降水资料,分析了黄河源区玛多、玛曲和兴海地区...     

Characterizing the urban temperature trend using seasonal unit root analysis: Hong Kong from 1970 to 2015

This paper explores urban temperature in Hong Kong using long-term time series. In particular, the characterization of the urban temperature trend was investigated using the seasonal unit root analysis of monthly mean air temperature data over the period January 1970 to December 2013. The seasonal unit root test makes it possible to determine the stochastic trend of monthly temperatures using an autoregressive model. The test results showed that mean air temperature has increased by0.169?C(10 yr)~(-1)over the past four decades. The model of monthly temperature obtained from the seasonal unit root analysis was able to explain 95.9% of the variance in the measured monthly data — much higher than the variance explained by the ordinary least-squares model using annual mean air temperature data and other studies alike. The model accurately predicted monthly mean air temperatures between January 2014 and December 2015 with a root-mean-square percentage error of 4.2%.The correlation between the predicted and the measured monthly mean air temperatures was 0.989. By analyzing the monthly air temperatures recorded at an urban site and a rural site, it was found that the urban heat island effect led to the urban site being on average 0.865?C warmer than the rural site over the past two decades. Besides, the results of correlation analysis showed that the increase in annual mean air temperature was significantly associated with the increase in population, gross domestic product, urban land use, and energy use, with the R~2 values ranging from 0.37 to 0.43.     

西南地区植被变化与气温及降水关系的初步分析

利用卫星遥感植被归一化指数（NDVI）资料和西南地区96个实测台站的月平均气温以及降水资料,初步分析了西南地区植被变化与气温及降水的关系。结果表明：近20年来西南地区植被覆盖状况较好,其中夏季植被覆盖最好,冬季植被分布空间差异最大;西南地区植被整体呈增加趋势,同时也存在较明显的季节和区域差异：春季西南大部分地区植被以增加为主,夏季、秋季全区以减少为主,冬季则以增加为主且存在明显的东西反向特征,东部减少西部增加。时滞互相关分析表明：西南地区11～2月份的植被对超前其1～2个月的气温以及夏季的植被对春季气温的敏感性比较大,3～4月的植被生长对上年夏季的降水敏感性比较大;同期时,1～3月植被和气温为正相关关系,6～9月的植被生长和降水为明显的负相关关系;在植被超前气候的条件下,1～2月的植被和滞后1～2个月的气温呈正相关关系,与滞后1个月的降水有明显的负相关关系。     

我国东部地区NDVI与气温、降水的关系研究

利用东部地区的1982—2001年归一化植被指数(NDVI)资料以及131个标准气象台站的气温、降水资料,用相关分析、奇异值分析(SVD)方法研究了该地区的植被与气温、降水的相互作用,得到以下几点认识：NDVI的最大值滞后于气温最高值的时间尺度在一个月左右。前期气温与后期NDVI的相关系数在春夏为负值,在秋冬却以正值为主。前期植被与后期气温的相关系数以负值为主。NDVI最大值滞后于降水最大值的时间尺度在两个月左右,同期NDVI与降水的相关系数为负值,而无论降水超前于NDVI或者NDVI超前于降水的时间尺度大于1个月时,二者的相关系数转为正值。由SVD方法得到东部地区7月份的NDVI与8月份的气温、降水有较好的相关关系。河南西南部及东北部区域NDVI与大部分地区的气温为正相关;长江流域NDVI与32 °N以南地区的降水有较好的负相关。因此,前期植被的变化特征可以作为后期气温、降水的预报的一种参考因子。     

Further-Adjusted Long-Term Temperature Series in China Based on MASH

A set of homogenized monthly mean surface air temperature(SAT) series at 32 stations in China back to the 19 th century had previously been developed based on the RHtest method by Cao et al.,but some inhomogeneities remained in the dataset.The present study produces a further-adjusted and updated dataset based on the Multiple Analysis of Series for Homogenization(MASH) method.The MASH procedure detects 33 monthly temperature records as erroneous outliers and152 meaningful break points in the monthly SAT series since 1924 at 28 stations.The inhomogeneous parts are then adjusted relative to the latest homogeneous part of the series.The new data show significant warming trends during 1924–2016 at all the stations,ranging from 0.48 to 3.57?C(100 yr)~(-1),with a regional mean trend of 1.65?C(100 yr)~(-1);whereas,the previous results ranged from a slight cooling at two stations to considerable warming,up to 4.5?C(100 yr)~(-1).It is suggested that the further-adjusted data are a better representation of the large-scale pattern of climate change in the region for the past century.     

全球风云三号D星MERSI/NDVI产品质量评估

MERSI/NDVI是风云三号D星的一个关键业务产品,深入了解其质量状况对推广产品应用、改进产品算法都具有重要意义.文中针对业务化运行后的全球MERSI/NDVI产品(2019年5月至2020年12月),以同期Terra MODIS/NDVI产品(MOD13A2)为参考,通过空间格局和时间序列的对比、APU(准确度Ac...     

基于MODIS白天地温产品的青藏高原海拔依赖型变暖特征分析

基于2001～2018年中分辨率成像光谱仪（MODIS）探测的白天地面温度（简称MODIS 白天地温）资料,与青藏高原（简称高原）122个气象站点观测的最高气温资料,在年尺度上评估了MODIS 白天地温在高原的适用性,研究了高原五个干湿分区下MODIS 白天地温的海拔依赖型变暖特征,得到以下主要结论:（1）MODIS白天地温能够基本再现观测的最高气温的时空以及海拔依赖型变暖特征;（2）高原整体上,MODIS白天地温存在显著的海拔依赖型变暖特征,平均海拔每增加100 m,其趋势增加0.02°C (10a)?1,且受积雪—反照率反馈主导;（3）干湿分区下,海拔依赖型变暖特征在高原表现为偏湿润地区强于偏干旱地区;季风区强于西风区。海拔依赖型特征强弱:半湿润地区＞湿润半湿润地区＞半干旱地区＞湿润地区＞干旱地区。平均海拔每增加100 m,以上区域的地温趋势分别增加0.06,0.03,0.03,0.01,0.01°C (10a)?1。半湿润和湿润半湿润地区年均温在0°C左右,在气候变暖背景下积雪—反照率反馈作用最为强烈,是其海拔依赖型变暖的主导因素;干旱与半干旱地区年均温相对更低,气候变暖程度对积雪影响相对较小,积雪—反照率反馈作用被限制,但仍对上述地区的海拔依赖型变暖起主导作用;而湿润地区的积雪覆盖率的上升可能是由于降雪（固态降水）增加抵消了积雪融化损耗,云辐射、水汽等其他因素主导了其海拔依赖型变暖。     

青藏高原冬季NDVI与西南地区夏季气温的滞后关系

该文利用EOF分解得到的1982—2001年西南地区夏季平均、最高和最低气温的时空特征显示, 西南地区夏季平均、最高气温的时空变化具有很好的一致性, 尤其是川渝地区20世纪80年代为气温负距平, 90年代开始有明显升温。利用GIMMS NDVI和西南4省市96个台站的气温资料进行了相关分析、合成分析以及SVD分析, 得到前期冬季青藏高原植被影响该区夏季气温的滞后关系以及影响较大的区域。结果表明:西南地区夏季平均气温、最高气温对青藏高原冬季植被变化较敏感, 其中青藏高原西部NDVI与西南地区夏季气温的相关强于东部; 青藏高原NDVI异常偏高对应西南地区夏季气温偏高, 其中最高气温升高较明显, 增温最大值出现在7月, 位于西南地区北部; 青藏高原冬季植被变化与西南地区平均气温、最高气温和最低气温的最佳耦合模态中影响程度及关键区域略有差异, 青藏高原冬季NDVI与夏季平均气温关系最密切, 其中青藏高原东北大部分地区和南部 (包括拉萨及林芝东部地区) 的影响最大, 气温对前期青藏高原NDVI变化反应的敏感区主要位于四川盆地及其附近地区。     

基于GWR模型的典型区域GPM数据降尺度研究——以浙江省为例北大核心

为提高研究区域的降尺度效果,基于地理加权回归法(Geographically Weighted Regression,GWR),选取全球降水计划(Global Precipitation Measurement,GPM)3IMERGM产品,以数字高程模型(Digital Elevation Model,DEM)作为控制解释变量,将其分别与解释变量水汽通量散度、气温构建两个降尺度模型、与解释变量归一化植被指数(Normalized Difference Vegetation Index,NDVI)构建对照降尺度模型,对浙江省进行降尺度研究。利用研究区域内气象站点的实测数据,对由不同解释变量构建的3个降尺度模型的降尺度结果进行对比分析及精度验证。结果表明:构建的3个降尺度模型中,引入解释变量水汽通量散度构建的降尺度模型的综合效果优于其余两种模型,水汽通量散度较NDVI、气温更适合作为解释变量。构建的降尺度模型有效地提高了GPM数据的空间分辨率(由0.1°提升至1 km),降尺度数据维持了精度且能够更真实反映研究区域内的降水量分布情况。     

Modeling and mapping temperature and precipitation climate data in Greece using topographical and geographical parameters

This study presents a methodology for modeling and mapping the seasonal and annual air temperature and precipitation climate normals over Greece using several topographical and geographical parameters. Data series of air temperature and precipitation from 84 weather stations distributed evenly over Greece are used along with a set of topographical and geographical parameters extracted with Geographic Information System methods from a digital elevation model (DEM). Normalized difference vegetation index (NDVI) obtained from MODIS Aqua satellite data is also used as a geographical parameter. First, the relation of the two climate elements to the topographical and geographical parameters was investigated based on the Pearson’s correlation coefficient to identify the parameters that mostly affect the spatial variability of air temperature and precipitation over Greece. Then a backward stepwise multiple regression was applied to add topographical and geographical parameters as independent variables into a regression equation and develop linear estimation models for both climate parameters. These models are subjected to residual correction using different local interpolation methods, in an attempt to refine the estimated values. The validity of these models is checked through cross-validation error statistics against an independent test subset of station data. The topographical and geographical parameters used as independent variables in the multiple regression models are mostly those found to be strongly correlated with both climatic variables. Models perform best for annual and spring temperatures and effectively for winter and autumn temperatures. Summer temperature spatial variability is rather poorly simulated by the multiple regression model. On the contrary, best performance is obtained for summer and autumn precipitation while the multiple regression model is not able to simulate effectively the spatial distribution of spring precipitation. Results revealed also a relatively weaker model performance for precipitation than that for air temperature probably due to the highly variable nature of precipitation compared to the relatively low spatial variability of air temperature field. The correction of the developed regression models using residuals improved though not significantly the interpolation accuracy.     

赤道太平洋对流活动异常对我国夏季降水和气温的影响

利用月平均ＯＬＲ、降水和气温资料,研究了ＥＮＳＯ期间赤道太平洋对流活动与我国夏季降水和气温的关系。结果表明：春季、夏季中、西太平洋对流活动异常与我国夏季江淮地区的降水有密切关系;春季和前一年冬季西太平洋对流活动异常与东北地区夏季降水有显著相关。前一年冬季中、西太平洋对流活动异常与我国降水的显著相关区是不同的,前者为华南、西南地区,后者为东北至内蒙古一带。气温与同期中、西太平洋对流活动的相关不显著。     

赤道太平洋对流活动异常对我国夏季降水和气温的影响

利用月平均ＯＬＲ、降水和气温资料,研究了ＥＮＳＯ期间赤道太平洋对流活动与我国夏季降水和气温的关系。结果表明：春季、夏季中、西太平洋对流活动异常与我国夏季江淮地区的降水有密切关系;春季和前一年冬季西太平洋对流活动异常与东北地区夏季降水有显著相关。前一年冬季中、西太平洋对流活动异常与我国降水的显著相关区是不同的,前者为华南、西南地区,后者为东北至内蒙古一带。气温与同期中、西太平洋对流活动的相关不显著。     

夏季白天中国中东部不同类型云分布特征及其对近地表气温的影响

本文利用2001～2017年ERA5再分析资料以及CERES卫星资料,探究夏季白天中国中东部不同类型云的云量及其光学厚度的时空变化特征,并利用一维辐射对流模式定量分析不同类型云对近地表气温的影响。观测结果表明:夏季白天中国中东部总云量及其光学厚度整体呈由南向北逐渐减小的分布特征,且中高云量占主导地位。总云量整体呈?0.3% a?1显著减少趋势,其中低云的贡献（?0.27% a?1）最大;总云光学厚度为0～0.1 a?1增加趋势,其中低云光学厚度（0.06 a?1）和中低云光学厚度（0.03 a?1）呈增加趋势,而中高云光学厚度（?0.08 a?1）和高云光学厚度（?0.03 a?1）呈减少趋势。模式结果表明:四种不同类型云的温度效应（Cloud Effect Temperature, CET）均为负值,表现为降温效应。低云、中低云、中高云和高云的年均CET值分别为?2.9°C、?2.7°C、?2.2°C和?1.7°C。其中,低云在华北平原降温可达?5°C;中低云和中高云在四川盆地和云贵高原降温可达?7.8°C。不同类型云温度效应与近地表气温的年际变化具有较好的一致性,具体表现为:2004年前（后）近地表气温呈现下降（上升）趋势,不同类型云的CET在此期间呈下降（上升）趋势,表现为云的降温效应增强（减弱）与近地表气温下降（上升）相对应,体现了夏季白天中国中东部4种不同类型云温度效应与近地表气温都呈正相关关系。特别地,夏季白天中国中东部中高云量占主导地位,其CET与近地表气温的相关系数高达0.63。综上,夏季白天中国中东部不同类型云温度效应对近地表气温的影响不同,但均呈正相关关系。定量分析不同类型云对近地表气温的影响可以为定量研究云反馈对区域增暖的作用以及合理预估未来区域增暖情景提供必要的科学参考。     

Integrating remote sensing data with WRF model for improved 2-m temperature and humidity simulations in China

The default green vegetation fraction (GVF) in the Weather Research and Forecasting (WRF) Model version 3.7.1 was derived between 1985 and 1990 from the 1990s Normalized Difference Vegetation Index (NDVI) achieved from the NOAA Advanced Very High Resolution Radiometer (AVHRR), and its representation is deteriorating when used to simulate recent weather and climate events. In this study, we applied in WRF v3.7.1 the updated GVF estimated by the real-time NDVI of the Moderate Resolution Imaging Spectroradiometer (MODIS) data to provide a better representation of the prescribed surface GVF condition. A one-year simulation was carried out in China, and the simulated 2-m air temperature and specific humidity were compared between the WRF model control experiment that employs the default GVF data (WRF-CTL), the WRF simulations with updated GVF (WRF-MODIS), and the observations from 824 weather stations in China. Results are significantly improved for both the 2-m air temperature and the specific humidity by WRF-MODIS, which has effectively reproduced the observed pattern and increased the correlation coefficient between the model simulations and observations. The RMSE and bias of specific humidity are also reduced in WRF-MODIS. In general, the real-time MODIS-NDVI based GVF reflected the realistic increase of vegetation cover in China when comparing to the WRF default GVF, and also provided a more accurate seasonal variation for the simulated year of 2009. As a result, the WRF-MODIS simulation significantly improves its representation in the simulated 2-m air temperature and specific humidity, both in spatial distributions and seasonal variations, due to the GVF’s great contribution in modulating the coupled land-atmosphere interactions.     

农田灌溉过程与土壤参数更新对中亚费尔干纳盆地WRF/Noah模拟精度的提升

通过中亚费尔干纳盆地2007～2011年气候的模拟试验,揭示了新增农田灌溉过程与更新土壤参数对WRF（Weather Research and Forecasting）/Noah模式模拟精度的提升作用。通过对比标准版本与嵌入灌溉过程参数化方案后的WRF/Noah模式的模拟结果,研究发现农业灌溉提升了土壤含水量,导致地表蒸发增强,潜热增加,感热减少,致使近地层大气降温、增湿,这一效应降低了WRF/Noah模拟的暖、干偏差,模拟2 m气温和大气比湿均方根误差分别由6.52°C降低至5.81°C,由1.66 g/kg降低至1.13 g/kg。进而针对WRF默认配置的费尔干纳盆地内土壤数据精度欠佳的问题,再利用国际土壤参比与信息中心（ISRIC）数据（主要是粉砂粘壤土和粉砂壤土）替换了WRF默认的数据（主要是粘土和壤土）,降低了土壤凋萎系数,使得有效土壤水增多,缩小了灌溉需水量的模拟误差,并使得蒸散发进一步增强,潜热增多,感热减少,导致近地层降温、增湿,进一步降低了WRF/Noah模拟的暖、干偏差,模拟温度、湿度的均方根误差分别由5.81°C降低至5.46°C,由1.13 g/kg降低至1.08 g/kg。上述结果表明:充分农业灌溉对陆面过程产生影响,以及采用高精度的土壤数据能够显著提高WRF/Noah模式在中亚费尔干纳盆地的模拟精度。     

Statistical estimation of high-resolution surface air temperature from MODIS over the Yangtze River Delta,China

High-resolution surface air temperature data are critical to regional climate modeling in terms of energy balance, urban climate change, and so on. This study demonstrates the feasibility of using Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) to estimate air temperature at a high resolution over the Yangtze River Delta region, China. It is found that daytime LST is highly correlated with maximum air temperature, and the linear regression coefficients vary with the type of land surface. The air temperature at a resolution of 1 km is estimated from the MODIS LST with linear regression models. The estimated air temperature shows a clear spatial structure of urban heat islands. Spatial patterns of LST and air temperature differences are detected, indicating maximum differences over urban and forest regions during summer. Validations are performed with independent data samples, demonstrating that the mean absolute error of the estimated air temperature is approximately 2.5°C, and the uncertainty is about 3.1°C, if using all valid LST data. The error is reduced by 0.4°C (15%) if using best-quality LST with errors of less than 1 K. The estimated high-resolution air temperature data have great potential to be used in validating high-resolution climate models and other regional applications.     

西南地区植被变化与气温及降水关系的初步分析

利用卫星遥感植被归一化指数(NDVI)资料和西南地区96个实测台站的月平均气温以及降水资料,初步分析了西南地区植被变化与气温及降水的关系。结果表明:近20年来西南地区植被覆盖状况较好,其中夏季植被覆盖最好,冬季植被分布空间差异最大;西南地区植被整体呈增加趋势,同时也存在较明显的季节和区域差异:春季西南大部分地区植被以增加为主,夏季、秋季全区以减少为主,冬季则以增加为主且存在明显的东西反向特征,东部减少西部增加。时滞互相关分析表明:西南地区11~2月份的植被对超前其1~2个月的气温以及夏季的植被对春季气温的敏感性比较大,3~4月的植被生长对上年夏季的降水敏感性比较大;同期时,1~3月植被和气温为正相关关系,6~9月的植被生长和降水为明显的负相关关系;在植被超前气候的条件下,1~2月的植被和滞后1~2个月的气温呈正相关关系,与滞后1个月的降水有明显的负相关关系。      

基于MODIS资料的贵州植被叶面积指数的时空变化及其对气候的响应

利用2000～2006年MODIS(Moderate Resolution Imaging Spectroradiometer)卫星遥感观测的植被叶面积指数月平均资料以及相应时段的月平均气温、降水的观测资料对贵州植被的时空变化进行了分析.结果表明贵州2000～2006年植被分布受水热条件控制表现出对气候因子不同的响应关系,其中对降水的响应关系比气温明显,特别是冬季和春季,而植被在夏季和秋季的分布主要受气温的制约,与降水的关系并不明显.从季节和年际尺度的时间变化角度而言,植被对气温的响应比对降水明显,季节变化和年际变化的相关系数分别为0.89和0.73(分别通过99.9%和95%信度检验).     

南海OLR异常与2007年广东省高温天气的关系

利用NCEP／NCAR提供的位势高度场、温度场资料和NOAA提供的OLR资料,应用EOF分析和相关分析等方法,分析南海区域（107．5°-120°E、12．5°-22．5°N）OLR的异常特征及其与2007年广东省高温天气的关系。结果表明,南海区域对100°-120°E、0°-35°N区域内OLR异常分布的主要时空型贡献最大,即该区域OLR的变率最大。OLR的分布基本可以反映出副热带高压的位置和强度,OLR值偏大、中心偏西,则副热带高压偏强、偏西。上空对流偏弱,下沉增温是造成2007年7月广东省长时间、大范围高温天气的主要原因之一。     

河北地区气温内插模型及检验方

以1965—1999年河北省逐月平均气温为研究对象,采用一元线性回归法和IDW(Inverse Distance Weighted)相结合的方法,将温度插值到河北省整个区域,绘制河北省温度空间分布图,实现河北省年内各月平均气温空间填图;同时,分析了河北省冬季和夏季各月的月平均温度的误差精度。结果表明：插值的结果与观测值的相关系数(R)在12个月均大于0.82,显示插值方法具有较好的模拟精度,可用于气温的空间插值和特征分析。