基于MODIS数据的青藏高原气温与增温效应估算

利用2001-2007 年MODIS地表温度数据、137 个气象观测台站数据和ASTERGDEM数据, 采用普通线性回归分析方法(OLS)及地理加权回归分析方法(GWR), 研究了高原月均地表温度与气温的相关关系, 最终选择精度较高的GWR分析方法, 建立了高原气温与地表温度、海拔高度的回归模型。各月气温GWR回归模型的决定系数(Adjusted R²) 都达到了0.91 以上(0.91~0.95), 标准误差(RMSE) 介于1.16~1.58℃;约70%以上的台站各月残差介于-1.5~1.5℃之间, 80%以上的台站的残差介于-2~2℃之间。根据该模型, 估算了青藏高原气温, 并在此基础上, 将高原及周边地区7 月份月均气温转换到4500 m和5000 m海拔高度上, 对比分析高原内部相对于外围地区的增温效应。研究结果表明:(1) 利用GWR方法, 结合地面台站的观测数据和MODIS Ts、DEM等, 对高原气温估算的精度高于以往普通回归分析模型估算的精度(RMSE=2~3℃), 精度可以提高到1.58℃;(2) 高原夏半年海拔5000 m左右的高山区气温能达到0℃以上, 尤其是7 月份, 海拔4000~5500 m的高山区的气温仍能达到10℃左右, 为山地森林的发育提供了温度条件, 使高原成为北半球林线分布最高的地方;(3) 高原的增温效应非常突出, 初步估算, 在相同的海拔高度上高原内部气温要比外围地区高6~10℃。     

基于Modis地表温度的青藏高原东部及其邻近地区气温估算(英文)

Climatic conditions are difficult to obtain in high mountain regions due to few meteorological stations and, if any, their poorly representative location designed for convenient operation. Fortunately, it has been shown that remote sensing data could be used to estimate near-surface air temperature (Ta) and other climatic conditions. This paper makes use of recorded meteorological data and MODIS data on land surface temperature (Ts) to estimate monthly mean air temperatures in the southeastern Tibetan Plateau and its neighboring areas. A total of 72 weather stations and 84 MODIS images for seven years (2001 to 2007) are used for analysis. Regression analysis and spatio-temporal analysis of monthly mean Ts vs. monthly mean Ta are carried out, showing that recorded Ta is closely related to MODIS Ts in the study region. The regression analysis of monthly mean Ts vs. Ta for every month of all stations shows that monthly mean Ts can be rather accurately used to estimate monthly mean Ta (R2 ranging from 0.62 to 0.90 and standard error between 2.25℃ and 3.23℃). Thirdly, the retrieved monthly mean Ta for the whole study area varies between 1.62℃ (in January, the coldest month) and 17.29℃ (in July, the warmest month), and for the warm season (May-September), it is from 13.1℃ to 17.29℃. Finally, the elevation of isotherms is higher in the central mountain ranges than in the outer margins; the 0℃ isotherm occurs at elevation of about 4500±500 m in October, dropping to 3500±500 m in January, and ascending back to 4500±500 m in May next year. This clearly shows that MODIS Ts data combining with observed data could be used to rather accurately estimate air temperature in mountain regions.     

MODIS-based air temperature estimation in the southeastern Tibetan Plateau and neighboring areas

Climatic conditions are difficult to obtain in high mountain regions due to few meteorological stations and, if any, their poorly representative location designed for convenient operation. Fortunately, it has been shown that remote sensing data could be used to estimate near-surface air temperature (Ta) and other climatic conditions. This paper makes use of recorded meteorological data and MODIS data on land surface temperature (Ts) to estimate monthly mean air temperatures in the southeastern Tibetan Plateau and its neighboring areas. A total of 72 weather stations and 84 MODIS images for seven years (2001 to 2007) are used for analysis. Regression analysis and spatio-temporal analysis of monthly mean Ts vs. monthly mean Ta are carried out, showing that recorded Ta is closely related to MODIS Ts in the study region. The regression analysis of monthly mean Ts vs. Ta for every month of all stations shows that monthly mean Ts can be rather accurately used to estimate monthly mean Ta (R2 ranging from 0.62 to 0.90 and standard error between 2.25℃ and 3.23℃). Thirdly, the retrieved monthly mean Ta for the whole study area varies between 1.62℃ (in January, the coldest month) and 17.29 ℃ (in July, the warmest month), and for the warm season (May-September), it is from 13.1℃ to 17.29℃. Finally, the elevation of isotherms is higher in the central mountain ranges than in the outer margins; the 0℃ isotherm occurs at elevation of about 4500±500 m in October, dropping to 3500±500 m in January, and ascending back to 4500±500 m in May next year. This clearly shows that MODIS Ts data combining with observed data could be used to rather accurately estimate air temperature in mountain regions.     

基于Modis地表温度的横断山区气温估算及其时空规律分析

横断山区气象观测站稀少且多分布在河谷之中,气温资料极度匮乏,严重影响山区地理与生态研究。随着遥感技术的发展,热红外遥感数据,结合地面观测数据,可以用来推测山区气温。本文通过对横断山区2001 年-2007 年间64 个气象台站的多年月平均气温数据(Ta) 与Modis地表温度多年月平均值(Ts) 进行了时序分析和回归分析,并取得如下研究结果：(1) Ts 与Ta 具有非常好的线性相关关系,89%的台站的决定系数高于0.5;95%的台站的标准误差都低于3 oC,84.4%的台站标准误差低于2.5 oC;12 个月份的Ts 与Ta 的决定系数R²在0.63~0.90 之间,标准误差在2.22~3.05 oC之间。(2) 研究区内月均气温的变化范围在-2.25~15.64 oC之间;生长季(5-9 月份) 的月均气温变化范围为：10.44~15.64 oC。(3) 等温线的海拔高度自山体外围向内部逐渐升高,与山体效应的增温效应相吻合;0 oC等温线自10 月份从海拔4700±500 m左右逐渐降低,至1月份降至最低点,约在3500±500 m左右,此后,逐渐回升,至次年5 月份再次达到4700±500 m左右,也就是说横断山区5200 m以下的广大山区全年至少有6~12 个月的气温在0 oC以上。研究表明：可以利用Modis月均地表温度结合地面观测台站的数据较精确的估算山区月均气温。     

基于MODIS的秦巴山地气温估算与山体效应分析

秦巴山地作为横亘在中国南北过渡带的巨大山脉,其山体效应对中国中部植被和气候的非地带性分布产生了重要的影响,山体内外同海拔的温差是表征山体效应大小较为理想的指标。本研究结合MODIS地表温度（LST）数据、STRM-1 DEM数据和秦巴山地的118个气象站点的观测数据,分别采用普通线性回归（OLS）和地理加权回归（GWR）两种分析方法对秦巴山地的气温进行估算,在此基础上将秦巴山地各月气温转换为同海拔（1500 m,秦巴山地平均海拔）气温,对比分析秦巴山地的山体效应。结果表明：① 相比OLS分析,GWR分析方法的精度更高,各月回归模型的R ²均在0.89以上,均方根误差（RMSE）在0.68~0.98 ℃之间。② 利用GWR估算得到的同海拔气温,从东向西随海拔升高呈现了明显的升高的趋势,秦岭西部山地比东段升高约6 ℃和4.5 ℃;大巴山西部山地年均和7月份同海拔的气温较东段升高约8 ℃和5 ℃。③ 从南向北,以汉江为分界,秦岭与大巴山的同海拔的气温均呈现出由山体边缘向内部升高的趋势。④ 秦巴山地西部大起伏高山,秦岭大起伏高中山和大巴山大起伏中山,相比豫西汉中中山谷地,各月均同海拔气温分别升高了约3.85~9.28 ℃、1.49~3.34 ℃和0.43~3.05 ℃,平均温差约为3.50 ℃,说明秦巴山地大起伏中高山的山体效应十分明显。     

MODIS大气廓线产品在青海省空气温度遥感估算中的应用研究

气温是反映生态环境的重要参数之一,准确估算气温的时空分布对于气候变化研究具有重要意义。论文基于2011—2019年青海省气温实测数据、MODIS产品和SRTM DEM数据,在像元尺度分别开展了晴天条件和有云条件下瞬时空气温度的遥感估算研究,并评价了不同气温估算方法的精度差异,进而通过多元回归模型生成研究区高精度月空气温度产品,对青海省气温的时空分布格局进行分析。研究结果表明,在未使用气温实测数据进行校准的情况下,通过将MOD07_L2大气廓线产品反演的空气温度与MOD06_L2地表温度平均的方法,能够显著提高气温的估算精度。晴天条件下相关系数(r)为0.93,均方根误差(RMSE)为4.71 ℃;有云条件下r为0.89,RMSE为5.16 ℃。在使用气温观测值进行校准的情况下,通过引入高程参数,多元回归模型月尺度空气温度估算的决定系数(R²)和RMSE总体分别保持在0.8以上和2.5 ℃以下。将上述回归模型应用到栅格尺度,从而生成整个青海省高精度卫星过境时刻的逐月气温产品,进而分析其时空分布格局。具体来说,青海省月最高气温出现在7月,全省平均气温为13.59 ℃,最低气温出现在1月,全省平均气温为-9.44 ℃;气温的空间分布主要受海拔控制,全省平均气温直减率为4 ℃/km。上述研究表明MODIS大气廓线产品在全天气气温估算方面具有独特优势,特别是在地面气温实测数据的支持下能够有效降低遥感估算的系统性误差,实现大尺度复杂地形条件下气温的高精度估算。     

念青唐古拉山南坡气温分布及其垂直梯度

利用架设在念青唐古拉山南坡9个海拔高度(4 300~5 500 m)的自动气象站1 a(2006年8月1日至2007年7月31日)的实测数据,对山坡1.5 m高度的近地面气温随海拔梯度和时间的分布进行了分析。表明念青南坡4 300~4 950 m冷季(10~4月)存在逆温。利用高山各观测高度的温度与当雄气象站气温具有良好相关,推算出多年平均情况下念青唐古拉山南坡各观测高度的年平均气温和各月平均气温。并由此推测念青唐古拉山南坡海拔5 100 m以上存在高山多年冻土,此多年冻土下界高度比《中国冻土》指出的高度高约200 m。     

新疆北部夏季降水与海温异常的关系

利用1960—2004年新疆北部36个气象站月降水资料和美国国家气候数据中心重建的1960—2004年全球2°×2°月平均海洋表面温度资料,研究了新疆北部夏季降水与海温异常的关系。研究表明,新疆北部夏季降水变化与ENSO事件关系不密切,而与前期冬末—春季的5个海温敏感区密切联系,这5个海温敏感区分别为北印度洋、西太平洋暖池及黑潮区、热带中东太平洋、北大西洋和热带大西洋。前期春季海温异常与新疆北部夏季降水变化联系最显著,表现为显著正相关关系。研究为预测新疆北部夏季降水提供了有益的因子。     

基于MODIS数据的青藏高原旱情监测研究

本文利用温度植被旱情指数（TVDI）和植被供水指数（VSWI）分别对2009、2010年3—10月青藏高原土壤湿度状况进行监测分析,同时利用气象台站实测地面降水资料进行了验证。利用MODIS资料提取的归一化植被指数（NDVI）和地表温度（T_S）,构建NDVI-T_S特征空间,依据该特征空间计算出的反映青藏高原土壤湿度的TVDI与同期累积降水相关性显著;VSWI计算过程简单,但所反映的土壤湿度与同期累积降水的相关性较差。因此,对青藏高原这种范围广、下垫面多变复杂区域而言,TVDI能够更好地反映土壤湿度状况,对干旱监测具有一定的科学意义。     

Mapping Air Temperature in the Lancang River Basin Using the Reconstructed MODIS LST Data

Air temperature is an important climatological variable and is usually measured in meteorological stations. Accurate mapping of its spatial and temporal distribution is of great interest for various scientific disciplines, but low station density and complexity of the terrain usually lead to significant errors and unrepresentative spatial patterns over large areas. Fortunately the current studies have shown that the regression models can help overcome the problem with the help of time series remote sensing data. However, noise induced by cloud contamination and other atmospheric disturbances variability impedes the application of LST data. An improved Savizky-Golay (SG) algorithm based on the LST background library is used in this paper to reconstruct MODIS LST product. Data statistical analysis included 12 meteorological stations and 120 reconstructed MODIS LST images of the period from 2001 to 2010. The coeffificient of correlations (R²) for 80% of the stations was higher than 0.5 (below 0.5 for only 2 stations) which illustrated that there is a considerably close agreement between monthly mean TA (air temperature) and the reconstructed LST in the Lancang River basin. Comparing to the regression model for every month with only LST data, the regression model with LST and NDVI had higher R² and RMSE. Finally, the LST-NDVI regression method was applied as an estimate model to produce distributed maps of air temperature with month intervals and 1 km spatial in the Lancang River basin of 2010.     

长江三角洲城市带扩展对区域温度变化的影响

Based on non-radiance-calibrated DMSP/OLS nighttime light imagery from 1992 to 2003, urban land area statistical data, meteorological data and land surface temperature data retrieved by MODIS and NOAA/AVHRR data, the influence of urbanization on regional cli- matic trend of temperature in the Yangtze River Delta (YRD) was analyzed. Conclusions are as follows: 1) There is a significant urbanization process from 1992 to 2003 in the YRD. Four city clusters of Nanjing–Zhenjiang–Yangzhou, Suzhou–Wuxi–Changzhou, Shanghai and Hangzhou Bay form a zigzag city belt. The increase rate of annual mean air temperature in city-belt is 0.28–0.44℃/10a from 1991 to 2005, which is far larger than that of non-city-belt. 2) The urban heat island (UHI) effect on regional mean air temperature in different seasons is summer>autumn>spring>winter. 3) The UHI intensity and the urban total population logarithm are creditably correlated. 4) The UHI effect made the regional annual mean air temperature increased 0.072℃ from 1961 to 2005, of which 0.047℃ from 1991 to 2005, and the annual maximum air temperature increased 0.162℃, of which 0.083℃ from 1991 to 2005. All these indicating that the urban expansion in the YRD from 1991 to 2005 may be regarded as a serious climate signal.     

近50年来中国冬季风寒温度的变化

风寒温度是冬季表征人体热舒适度常用的参数,也是气候变化影响研究中关注的要素。本文利用中国地面国际交换站气候资料月值数据集的气温和风速,分析1956-2005年中国冬季风寒温度的时间和空间变化特征。结果表明,近50年来中国冬季风寒温度普遍呈上升趋势,全国平均升高3.2 ^oC,变化速率达0.64 ^oC/10a;西北、华北、东北和青藏地区的上升速率分别为0.79 ^oC/10a、0.84 ^oC/10a、0.81 ^oC/10a、0.80 ^oC/10a,其中华北北部农牧交错带地区上升趋势最为强烈,超过1 ^oC/10a;35^oN以南的我国南方地区上升速率较低,为0.39 ^oC/10a。风寒温度的这种变化特征是近50年来气温升高和风速下降综合作用的结果。其中气温变化造成的风寒温度上升是2.4 ^oC,而地表风速下降对风寒温度的贡献为0.8 ^oC。东亚气温和风速的变化受诸多大气环流系统的影响,分析表明影响东亚气候的几个主要环流因子中,西伯利亚高压、北极涛动、西太平洋遥相关型和欧亚遥相关型等与风寒温度有显著相关。这四个环流因子一起能解释50年来全国平均风寒温度方差的46.7%。全国平均气温与这四个环流因子的相关分别达到-0.65,+0.49,+0.31和-0.32;而平均风速与北极涛动的相关最显著,达-0.51。     

青藏高原东北部与南部地区树木径向生长对气候要素的响应——以祁丰和林周树轮为例

了解树木径向生长对气候响应的区域特征是模拟或预测未来全球变化如何对森林生态系统产生影响的基础。对青藏高原东北部(祁丰)干旱气候条件下与南部(林周)高寒半干旱气候条件下的两条标准化年表分析发现,两年表敏感度均较高,样芯间一致性均较强,为分析树木径向生长对气候要素的响应关系提供了保障。对祁丰和林周树轮宽度序列与其附近酒泉(1951-2009年)和当雄(1963-2009年)气象站上年5月到当年9月的气候因子(月平均气温、月最高气温、月平均最低温和月降水量)进行相关和响应分析发现,祁丰和林周树木的径向生长与当年5-6月平均气温存在负相关关系,相关系数分别为-0.360和-0.466;而与当年5-6月降水量显著正相关,相关系数分别为0.499和0.623。祁丰和林周树轮宽度序列与帕尔默干旱指数(PDSI,1951-2005年)的格网数据在每个月份均呈正相关关系,与5-6月的相关值分别为0.581和0.719。上年7月到当年6月的降水量与祁丰(r=0.529)和林周(r=0.667)树轮宽度序列的相关值也较高,推断干旱状况是限制高原东北部与南部树木径向生长的主要因素。     

The trend on runoff variations in the Lhasa River Basin

Taking the Lhasa River Basin above Lhasa hydrological station in Tibetan Plateau as a study area, the characteristics of the annual and monthly mean runoff during 1956?2003 were analyzed, based on the hydro-data of the two hydrological stations (Lhasa and Tanggya) and the meteorological data of the three meteorological stations (Damxung, Lhasa and Tanggya). The trends and the change points of runoff and climate from 1956 to 2003 were detected using the nonparametric Mann-Kendall test and Pettitt-Mann-Whitney change-point statistics. The correlations between runoff and climate change were analyzed using multiple linear regression. The major results could be summarized as follows: (1) The annual mean runoff during the last 50 years is characterized by a great fluctuation and a positive trend with two change points (around 1970 and the early 1980s), after which the runoff tended to in-crease and was increasing intensively in the last 20 years. Besides, the monthly mean runoff with a positive trend is centralized in winter half-year (November to April) and some other months (May, July and September). (2) The trends of the climate change in the study area are generally consistent with the trend of the runoff, but the leading climate factors which aroused the runoff variation are distinct. Precipitation is the dominant factor influencing the annual and monthly mean runoff in summer half year, while temperature is the primary factor in winter season.     

近45 年青藏高原土壤温度的变化特征分析

利用青藏高原60 个气象站1960-2005 年的土壤温度观测资料, 采用Mann-Kendall 法和功率谱方法对不同深度土壤温度的时间变化进行趋势突变和周期检验, 并以主成分方法考察 其空间分布特征。分析结果发现青藏高原浅层土壤温度自1970 年以来升高趋势明显, 1969-1970 年为明显的突变点; 40~320 cm 的深层土壤温度存在3.25 年的显著周期变化; 浅 层土壤温度空间特征则主要体现为全区一致型和南北反向变化型。同时以浅层土壤温度梯度 (10~20 cm) 的变化特征讨论了青藏高原地气间能量的交换关系以及浅层土壤温度梯度对高原 多年冻土的响应, 认为高原地气温差和浅层土壤温度梯度之间存在一种涨落机制, 体现的是 高原地气间的耗散结构关系; 而浅层土壤温度梯度分布特征对高原多年冻土有明显的响应。     

青藏高原夏季上空水汽含量演变特征及其与降水的关系

利用青藏高原(以下简称高原) 近30 年(1979-2008 年) 14 个探空站的温度和湿度观测资料以及83 个地面台站的月平均降水资料,分析了高原夏季上空水汽含量与地面降水的联系以及高原地区的降水转化率问题。结果表明：1) 高原夏季水汽含量在空间分布上表现出随海拔高度增高而减少的特征,其中东北部为最大值,东南部为次大值,而西北部为最小值。夏季降水整体上由东南向西北递减;2) EOF分解表明,高原夏季水汽含量存在两种主要的空间分布型：即全区一致变化型和南北反向变化型,其中以唐古拉山脉北侧为界呈现出的水汽含量南北反向型与降水的第一特征向量场表现出的南北反向型在空间分布上十分相似;3) 在年际变化上,高原夏季水汽含量的南北反向型与降水的南北反向型之间存在较一致的对应关系：即水汽含量出现南多北少时,高原南部降水普遍偏多而北部降水普遍偏少,反之亦然;4) 高原夏季平均降水转化率在3%~38%之间,其空间差异非常明显,高原南部降水转化率明显大于北部地区。     

青藏高原气温空间分布规律及其生态意义

作为世界第三极的青藏高原,其巨大的块体产生了显著的夏季增温作用,对亚洲乃至全球气候都具有重大影响。但由于高原自然条件严酷,山区气象观测台站很少,气象资料极度匮乏;如果依靠台站数据进行空间插值获得高原气温的空间分布数据,会由于插值点过少而产生较大误差并可能掩盖一些空间信息,因而难以全面反映高原气温的空间分布规律。利用基于MODIS地表温度数据估算的青藏高原气温数据,详细分析各月气温及重要等温线的空间分布格局,并结合林线和雪线数据,初步探讨了高原气温空间分布格局对高原地理生态格局的重要影响。研究表明：① 等温线的海拔高度自高原东北部、东部边缘向内部逐渐升高,等温线在高原内部比东部边缘高500~2000 m,表明相同海拔高度上气温自边缘向高原内部逐渐升高。② 高原西北部的羌塘高原、可可西里为高原的寒冷区,全年有7个月的气温低于0 ℃,3~4个月的气温低于-10 ℃;青藏高原南部（喜马拉雅山北坡—冈底斯山南坡）和中部（冈底斯山北坡—唐古拉山南坡）是高原的温暖区,全年有5个月的气温能达到5~10 ℃,有3个月的气温能超过10 ℃,尤其是拉萨—林芝—左贡一带在3500~4000 m以下的地区最冷月均温也能高于0 ℃。③ 北半球最高雪线和林线分别分布于高原的西南部和东南部,表明高原气温空间分布特征对本地的地理生态格局具有重要影响。     

类型变更的相邻气象观测站的日气温资料整合

利用日气温资料,分析了因气象观测站类型变更而致的气候资料连续性和均一性问题及其影响,提出了订正相邻观测站日气温并将因观测站类型变更而致的相邻站不连续日气温资料整合的方法。主要结论有:(1)气象观测站类型变更而致的气候数据不连续既影响资料的均一性,也影响气候变化研究的结果。在考虑或不考虑测站类型变更(仅1980年以后)时,对我国过去60年1月气温趋势变化的估计结果差别达6.0%。(2)虽然海拔差异明显影响相邻站气温,但城乡差别等下垫面及其周边环境差异因素的作用极为显著;可导致两个地理位置相近的测站最大月气温差别超过0.50℃。(3)利用相邻测站的月气温差异进行各月的日气温订正可以消除海拔、台站下垫面及其周边环境差异对观测资料的均一性影响;使订正后的序列能更好地反映出气候的年际变化特征;从而可为我国正在开展的气候区划新方案、气候变化对区划影响及冷暖期环境格局变化等研究工作提供更均一的气候观测基础资料。     

近48年来城市化对昆明地区气温的影响

以低纬高原城市昆明及邻近的安宁和太华山站分别代表大城市、小城市和无城市化影响的对比站,利用1960-2007年气象资料,分析不同规模城市发展对气温的影响。结果表明：①昆明及邻近地区近48年来平均气温显著升高,具有一致性。②城市化加剧了平均气温上升的幅度,大城市和小城市的城市效应分别达到0.31 ℃/10a和0.09 ℃/10a,急剧的变化出现在20世纪80年代后期城市高速发展期。③城市化加剧了平均最低气温的显著升高,但对平均最高气温影响不明显。由此导致气温日较差的显著减小,大城市和小城市气温日较差的城市效应分别达到-0.49 ℃/10a和-0.27 ℃/10a。④城市化还导致了极端最低气温显著升高,相对湿度显著降低,霜日数显著减少。但对极端最高气温的影响并不显著。     

1956-2003年拉萨河流域径流变化趋势

Taking the Lhasa River Basin above Lhasa hydrological station in Tibetan Plateau as a study area, the characteristics of the annual and monthly mean runoff during 1956-2003 were analyzed, based on the hydro-data of the two hydrological stations （Lhasa and Tanggya） and the meteorological data of the three meteorological stations （Damxung, Lhasa and Tanggya）. The trends and the change points of runoff and climate from 1956 to 2003 were detected using the nonparametric Mann-Kendall test and Pettitt-Mann-Whitney change-point statistics. The correlations between runoff and climate change were analyzed using multiple linear regression. The major results could be summarized as follows： （1） The annual mean runoff during the last 50 years is characterized by a great fluctuation and a positive trend with two change points （around 1970 and the early 1980s）, after which the runoff tended to increase and was increasing intensively in the last 20 years. Besides, the monthly mean runoff with a positive trend is centralized in winter half-year （November to April） and some other months （May, July and September）. （2） The trends of the climate change in the study area are generally consistent with the trend of the runoff, but the leading climate factors which aroused the runoff variation are distinct. Precipitation is the dominant factor influencing the annual and monthly mean runoff in summer half year, while temperature is the primary factor in winter season.