A Modified Becker''s Split-Window Approach for Retrieving Land Surface Temperature from AVHRR and VIRR

In order to provide a long time-series, high spatial resolution, and high accuracy dataset of land surface temperature (LST) for climatic change research, a modified Becker and Li's split-window approach is pro- posed in this paper to retrieve LST from the measurements of Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration (NOAA)-7 to -18 and the Visible and InfraRed Radiometer (VIRR) onboard FY-3A. For this purpose, the Moderate Resolution Transmittance Model (MODTRAN) 4.1 was first employed to compute the spectral radiance at the top of atmosphere (TOA) under a variety of surface and atmosphere conditions. Then, a temperature dataset consists of boundary temperature Ts (which is one of the input parameters to MODTRAN), and channels 4 and 5 brightness temperatures (T4 and T5) were constructed. Note that channels 4 and 5 brightness tempera- tures were simulated from the MODTRAN output spectral radiance by convolving them with the spectral response functions (SRFs) of channels 4 and 5 of AVHRRs and VIRR. The coefficients of modified Becker and Li's split-window approach for various AVHRRs and VIRR were subsequently regressed based on this temperature dataset using the least square method. As an example of validation, one AVHRR satellite image over Beijing acquired at 0312 UTC 27 April 2008 by AVHRR onboard NOAA-17 was selected to retrieve the LST image using the modified Becker and Li's approach. The comparison between this LST image and that from the MODIS level-2 LST product provided by the University of Tokyo in Japan indicates that the correlation coefficient is 0.88, the bias is 0.6 K, and the root mean square deviation (RMSD) is 2.1 K. Furthermore, about 70% and 37% pixels in the LST difference image, which is the result of retrieved LST image from AVHRR minus the corresponding MODIS LST image, have the values within ±2 and ±1 K, respectively.     

FY-3A陆表温度反演及高温天气过程动态监测

采用FY-3A/VIRR数据,利用Becker局地分裂窗改进算法反演得到逐日陆表温度 (LST), 对2009年一次高温天气过程进行动态监测, 并分析不同下垫面的热环境变化。结果显示:此过程中可见光红外扫描辐射计 (VIRR) 陆表温度产品在敦煌辐射校正场地两次验证的误差为-0.17 K和1.77 K,与同时间过境的MODIS产品均方根误差为2.64 K,直方图对比陆表温度的频数分布基本一致;对高温天气过程监测发现,此次出现以华北的石家庄、郑州、北京等地和西北地区东部的西安等地为中心的两个陆表温度高值区, 部分地区达到了320.2 K以上;城市剖面资料证实城市热岛现象存在,并发现工矿用地的热岛效应不容忽视,主要是大面积的工矿用地周围植被破坏严重,地表增温更为显著。     

Spatio-temporal regression kriging model of mean daily temperature for Croatia

High resolution gridded mean daily temperature datasets are valuable for research and applications in agronomy, meteorology, hydrology, ecology, and many other disciplines depending on weather or climate. The gridded datasets and the models used for their estimation are being constantly improved as there is always a need for more accurate datasets as well as for datasets with a higher spatial and temporal resolution. We developed a spatio-temporal regression kriging model for Croatia at 1 km spatial resolution by adapting the spatio-temporal regression kriging model developed for global land areas. A geometrical temperature trend, digital elevation model, and topographic wetness index were used as covariates together with measurements from the Croatian national meteorological network for the year 2008. This model performed better than the global model and previously developed models for Croatia, based on MODIS land surface temperature images. The R2 was 97.8% and RMSE was 1.2 °C for leave-one-out and 5-fold cross-validation. The proposed national model still has a high level of uncertainty at higher altitudes leaving it suitable for agricultural areas that are dominant in lower and medium altitudes.     

西藏林芝地区混合像元MODIS地表温度产品验证

西藏林芝地区地形复杂、土地覆盖类型多样,MODIS地表温度 (land surface temperature,LST) 产品验证面临处理混合像元的难题,为获得与像元尺度 (1 km) 相匹配的地表温度数据,该文提出采用多点同时观测结合面积加权的方法,将该方法应用于验证林芝地区2013年6月10日夜间晴空MODIS/LST产品。结果显示:单点观测对像元的代表性不足,容易低估产品精度 (10个样本均方根误差为2.2 K),面积加权法可获得综合性更好的地面LST信息,对MODIS/LST产品的精度给出更高的评价 (30个样本均方根误差为1.40 K)。对于地表类型混杂程度高且地势较为平坦的像元,面积加权法的优势更为明显,可将卫星LST产品与地面LST之间的差异由3 K降至1 K以内。     

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。     

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.     

西安市日最大电力负荷率与气象因子相关关系分析预报模型的建立

基于西安市2010—2013年逐日最大电力负荷和同期的气象资料,分析了日最大电力负荷的变化规律,利用最小二乘法,除去日最大负荷的节假日效应和周末效应后,将气象负荷从日最大电力负荷中分离出来,建立西安气象负荷率与气温、相对湿度、总云量、降水量、风速的相关关系,并基于2010—2012年的11月—次年2月和6—8月的资料,分别采用逐步回归、多元线性回归和BP神经网络方法建立最大气象负荷和主要气象影响因子之间的预报模型,将2013年对应时间的日最大气象负荷率作为预报效果的独立样本检验。结果显示:2010—2013年西安的日最大电荷存在明显的增长趋势,且存在明显的周末效应和节假日效应;气温是影响气象负荷率的最显著因子,引入温湿指数(THI)的BP神经网络算法对气象负荷率的拟合和预测效果最优。     

A modified Becker’s split-window approach for retrieving land surface temperature from AVHRR and VIRR

In order to provide a long time-series,high spatial resolution,and high accuracy dataset of land surface temperature(LST) for climatic change research,a modified Becker and Li’s split-window approach is proposed in this paper to retrieve LST from the measurements of Advanced Very High Resolution Radiometer(AVHRR) onboard National Oceanic and Atmospheric Administration(NOAA)-7 to-18 and the Visible and InfraRed Radiometer(VIRR) onboard FY-3A.For this purpose,the Moderate Resolution Transmittance Model(MODTRAN) 4.1 was first employed to compute the spectral radiance at the top of atmosphere(TOA) under a variety of surface and atmosphere conditions.Then,a temperature dataset consists of boundary temperature T s(which is one of the input parameters to MODTRAN),and channels 4 and 5 brightness temperatures(T 4 and T 5) were constructed.Note that channels 4 and 5 brightness temperatures were simulated from the MODTRAN output spectral radiance by convolving them with the spectral response functions(SRFs) of channels 4 and 5 of AVHRRs and VIRR.The coefficients of modified Becker and Li’s split-window approach for various AVHRRs and VIRR were subsequently regressed based on this temperature dataset using the least square method.As an example of validation,one AVHRR satellite image over Beijing acquired at 0312 UTC 27 April 2008 by AVHRR onboard NOAA-17 was selected to retrieve the LST image using the modified Becker and Li’s approach.The comparison between this LST image and that from the MODIS level-2 LST product provided by the University of Tokyo in Japan indicates that the correlation coefficient is 0.88,the bias is 0.6 K,and the root mean square deviation(RMSD) is 2.1 K.Furthermore,about 70% and 37% pixels in the LST difference image,which is the result of retrieved LST image from AVHRR minus the corresponding MODIS LST image,have the values within ± 2 and ± 1 K,respectively.     

风云三号C星微波全球地表温度产品精度评估

地表温度是衡量地表水热平衡的关键参数,微波地表温度因其范围大、全天候等独特的优势,在气候、农业和环境等领域得到广泛应用。基于经质量控制的MODIS地表温度产品对风云三号卫星C星的微波地表温度日产品和月平均产品进行验证评估,结果显示:FY-3C卫星升轨(夜晚)和降轨(白天)微波地表温度日产品平均分别高估8. 7 K、低估13. 2 K,月平均产品平均分别高估7. 9 K、低估12. 0 K,日产品和月平均产品的反演误差都在15K以内。在全球空间分布上,升轨(夜晚)和降轨(白天)月产品误差分别呈现高估和低估,热带雨林区和沙漠、荒漠区域在夜晚分别高估5 K以内和30 K以内,白天则分别低估10 K以内和10～30 K。不同土地覆盖类型间FY-3C微波地表温度反演精度存在差异,总体上升轨(夜晚)比降轨(白天)的精度高,反演精度最高和最低的土地类型分别是常绿阔叶林和荒漠、稀疏植被,不同土地覆盖类型间的地表温度反演精度在季节上存在明显差异。根据分析结果,改进FY-3C微波地表温度的反演算法,可进一步提高微波地表温度的反演精度。     

利用MODIS/LST产品分析基准气候站环境代表性

该文基于2001—2007年地表温度遥感反演产品 (MOD11A2),以基准气候站对其周围不同大小窗口内地表温度距平序列的解释方差作为度量,评估了我国142个基准气候站的环境代表性,并将代表性与土地覆盖和高程状况进行相关研究。结果显示:以解释方差大于0.75作为区分是否具有代表性的阈值,约41%的站点代表性较好,代表区域范围可超过51×51 km2,多分布于北方地区;约21%的站点代表性较差,代表区域范围不足7×7 km2,多分布于南方地区;其他代表区域范围居中的站点在南、北方均有分布;站点周围的土地覆盖多样性和地形起伏度与站点代表性存在负相关,且相关性随窗口的增大而加强。文中还评估了基准气候站对所属气候区的代表性,发现在气候特征复杂的西南地区和新疆部分地区,站点对气候区的代表性较差。     

Estimation of Land Surface Temperature over the Tibetan Plateau Using AVHRR and MODIS Data

Estimation of large-scale land surface temperature from satellite images is of great importance for the study of climate change. This is especially true for the most challenging areas, such as the Tibetan Plateau (TP). In this paper, two split window algorithms (SWAs), one for the NOAA’s Advanced Very High Resolu-tion Radiometer (AVHRR), and the other for the Moderate Resolution Imaging Spectroradiometer (MODIS), were applied to retrieve land surface temperature (LST) over the TP simultaneously. AVHRR and M...     

The effect of air temperature and human thermal indices on mortality in Athens, Greece

This paper investigates whether there is any association between the daily mortality for the wider region of Athens, Greece and the thermal conditions, for the 10-year period 1992–2001. The daily mortality datasets were acquired from the Hellenic Statistical Service and the daily meteorological datasets, concerning daily maximum and minimum air temperature, from the Hellinikon/Athens meteorological station, established at the headquarters of the Greek Meteorological Service. Besides, the daily values of the thermal indices Physiologically Equivalent Temperature (PET) and Universal Thermal Climate Index (UTCI) were evaluated in order to interpret the grade of physiological stress. The first step was the application of Pearson’s χ ² test to the compiled contingency tables, resulting in that the probability of independence is zero (p?=?0.000); namely, mortality is in close relation to the air temperature and PET/UTCI. Furthermore, the findings extracted by the generalized linear models showed that, statistically significant relationships (p?<?0.01) between air temperature, PET, UTCI and mortality exist on the same day. More concretely, on one hand during the cold period (October–March), a 10°C decrease in daily maximum air temperature, minimum air temperature, temperature range, PET and UTCI is related with an increase 13%, 15%, 2%, 7% and 6% of the probability having a death, respectively. On the other hand, during the warm period (April–September), a 10°C increase in daily maximum air temperature, minimum air temperature, temperature range, PET and UTCI is related with an increase 3%, 1%, 10%, 3% and 5% of the probability having a death, respectively. Taking into consideration the time lag effect of the examined parameters on mortality, it was found that significant effects of 3-day lag during the cold period appears against 1-day lag during the warm period. In spite of the general aspect that cold conditions seem to be favourable factors for daily mortality, the air temperature and PET/UTCI exceedances over specific thresholds depending on the distribution reveal that, very hot conditions are risk factors for the daily mortality.     

The urban heat island of Bucharest during the extreme high temperatures of July 2007

This paper explores the characteristics of the air (T_air) and land surface temperature (LST) from the city of Bucharest (Romania) during the extreme high temperatures that affected the region in July 2007. The behavior of Bucharest’s Urban Heat Island (UHI) is quantitatively described following similar methodological approaches to previous studies. The analysis integrates thermal data supplied by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors aboard the NASA satellites and meteorological data provided by the ground-based weather stations. Based on the T_air, one may claim that during extreme high summer temperatures, the UHI preserves its spatial and temporal pattern regarding the differences between the central urban perimeter and the suburban area. The investigation of the LST from July 2007 reveals that the nocturnal changes refer mainly to the magnitude and the limits of the UHI, while the shape is not changed. However, the extreme temperatures induce significant modifications of the features of the diurnal UHI, obliterating and dissipating it in certain spots, enlarging it and creating shifted heat islands in some other spots. The main explanation is the outstanding duration and intensity of the hot mass of air impacting the area. The correlations between the T_air measured at the weather stations in Bucharest and the corresponding LST retrieved significant values both under “normal” conditions and extreme temperature persistence, and offer good premises for robust validation studies. The MODIS products performed like an extremely useful instrument for analyzing the UHI.     

利用温度植被干旱指数反演伊犁博州地区土壤湿度

利用MODIS合成产品数据MOD11A2和MOD13A2获取的归一化植被指数（NDVI）和陆地表面温度（LST）构建Ts—NDVI特征空间,并把该特征空间计算的温度植被干旱指数（TVDI）作为土壤湿度指标。利用该指标反演伊犁博州地区6～8月3个月份每8d的土壤湿度。然后将土壤湿度分为5级,进而得到该时段伊犁博州地区土壤湿度空间分布特征。     

Modeling land surface phenology in a mixed temperate forest using MODIS measurements of leaf area index and land surface temperature

The development of satellite-derived vegetation indices and metrics has enabled researchers to monitor land surface phenology (LSP). While the use of satellite data to monitor LSP is prevalent, there has been minimal effort to model LSP in temperate climates using satellite observations of the land surface. Satellite-derived LSP models are beneficial for studying past and future changes in phenology and related ecosystem processes (e.g., water, energy, and carbon fluxes). The purpose of this study was to model LSP during the spring in a mixed temperate forest using satellite-derived measurements of leaf area index (LAI) and land surface temperature (LST). As part of the model validation process, the use of LST as a proxy for air temperature to model LSP was also investigated. The results indicate that LST derived from the MODIS Terra sensor at 10:30?a.m. (local solar time) can be used to develop a LSP model that predicts the full profile of LAI from winter dormancy to maturity and the date when LAI reaches half of the annual maximum (LAI_50%) with relatively low error. In addition, the modeled LAI values closely tracked in situ observations of the phenological development of the dominant deciduous tree species located in the study area where the model was developed. A comparison of LST and daily maximum air temperature at two levels above the ground surface revealed distinct differences and nonlinearities in the relationship between these two variables. However, accumulated growing degree-days calculated from each of these variables were similar because the largest differences between LST and daily maximum air temperature occurred prior to the beginning of heat accumulation. Consequently, the model predictions of LAI_50% derived from the use of LST and daily maximum air temperature were similar. When the developed model was applied in two other mixed forests, the errors were larger due to substantial interannual variability in the relationship between LAI and heat accumulation and systematic differences in this relationship between sites. Although the model cannot be successfully applied in these other mixed forests, the ability of the model to capture a consistent relationship between satellite estimates of LAI and LST in the study area where it was developed demonstrates that satellite observations of the land surface can be used in certain locations to create LSP phenology models. When validated, the models can be used to examine past and future changes in phenology and related ecosystem processes.     

Trends of urban surface temperature and heat island characteristics in the Mediterranean

Urban air temperature studies usually focus on the urban canopy heat island phenomenon, whereby the city center experiences higher near surface air temperatures compared to its surrounding non-urban areas. The Land Surface Temperature (LST) is used instead of urban air temperature to identify the Surface Urban Heat Island (SUHI). In this study, the nighttime LST and SUHI characteristics and trends in the seventeen largest Mediterranean cities were investigated, by analyzing satellite observations for the period 2001–2012. SUHI averages and trends were based on an innovative approach of comparing urban pixels to randomly selected non-urban pixels, which carries the potential to better standardize satellite-derived SUHI estimations. A positive trend for both LST and SUHI for the majority of the examined cities was documented. Furthermore, a 0.1 °C decade^?1 increase in urban LST corresponded to an increase in SUHI by about 0.04 °C decade^?1. A longitudinal differentiation was found in the urban LST trends, with higher positive values appearing in the eastern Mediterranean. Examination of urban infrastructure and development factors during the same period revealed correlations with SUHI trends, which can be used to explain differences among cities. However, the majority of the cities examined show considerably increased trends in terms of the enhancement of SUHI. These findings are considered important so as to promote sustainable urbanization, as well as to support the development of heat island adaptation and mitigation plans in the Mediterranean.     

利用ASTER数据反演南京城市地表温度

利用针对ASTER数据的分裂窗算法,反演了南京城市地表温度,并用实际观测资料和同步的MODIS数据对反演结果进行了验证,结果表明：基于ASTER数据的地表温度反演结果与实际观测资料相差0.9℃,与MODIS数据的反演结果具有较好的空间一致性;基于ASTER数据反演的当日南京地表温度在23～56℃范围内,城市地表温度普遍高于35℃,市内公园地表温度略低,多位于30～35℃,长江水体温度低于30℃,地表温度存在明显的空间差异;南京城市夏季白天存在明显＂热岛效应＂,热岛强度的空间差异与南京城市发展、规划有关。     

Mapping of Land-Atmosphere Heat Fluxes and Surface Parameters with Remote Sensing Data

A variational data assimilation scheme is used to infer two key parameters ofthe surface energy balance that control the partitioning of available energy intolatent, sensible, and ground heat fluxes (LE, H, and G). Remotely sensedland surface temperature (LST) is the principal data source. Maps ofdiurnal energy balance components are presented for a basin with varied landcover (Arno Basin, Italy) for a 18-day period in July 1996.Given available energy, the major unknown (dimensionless) parameters requiredfor partitioning among fluxes are: (1) Landscape effects on near-surfaceturbulence as captured by the bulk heat transfer coefficient C_BN underneutral conditions and (2) surface control of the relative magnitudes of LEand H as represented by the evaporative fraction E_F. The data assimilationscheme merges 1.1-km resolution remotely sensed LST images (based onoptical, thermal and microwave measurements from two different satelliteplatforms) into a parsimonious model of heat diffusion. Both the measurementsand the model predictions are considered uncertain. Posterior error statisticsthat represent uncertainty of the estimated parameters are also derived.Maps of C_BN show spatial patterns consistent with the dominant land useand basin physiography. Daily maps of E_F exhibit spatial variationscorresponding to land cover and land use – the day-to-day variations inE_F show fluctuations consistent with rain events and drydowns experiencedduring the period. Based on these parameters and available environmentalvariables, maps of diurnal LE and H may be produced (in this paper daytimeLE maps are reported).The application demonstrates that remotely sensed land surface temperaturesequences contain significant amount of information of the partitioning ofavailable energy among the fluxes. The variational data assimilation frameworkis shown to be an efficient and parsimonious approach without reliance onempirical relationships such as those based on vegetation indices.     

2005年7月珠三角地表温度场的遥感监测分析

城市热环境及其热效应是当前城市气候与环境中最为重要的研究内容之一。分析地表温度（LST）是研究热环境的一个有效手段。选取2005年7月中旬高温期间MODIS数据，利用推广分裂窗算法反演LST，采用最大值合成方法制作珠江三角洲地区热场分布序列图。结果发现：珠三角地区增温初期的高温区主要分布在珠三角外围的城市，呈由外向内的增温过程；珠三角地区沿河道区域的增温幅度最高最快，增温盛期的地表最高温度主要分布在河网密集地区；城市化和工业化程度高的市区热岛效应明显。研究结果符合目前珠三角经济区的发展状况，对城市区域布局和规划有积极意义。     

THE INTRASEASONAL VARIABILITY OF SURFACE WIND AND UPPER LAYER THERMAL STRUCTURE IN THE WESTERN TROPICAL PACIFIC WARM POOL REGION DURING THE WINTER OF 1992～1993

In this paper, the hydrographical and meteorological data observed by the R/Vs "Xiang Yang Hong No. 5", "Experiment No. 3"and "Ke Xue No. 1 "during TOGA-COARE IOP are used to analyze the variability of surface wind and upper layer thermal structure, and to reveal the periods of intraseasonal oscillation of surface wind components and certain layers of sea temperature from November 6, 1992 to February 18, 1993 in the western tropical Pacific warm pool region. It is shown that the variation of the sea surface temperature (SST) was inversely correlated to that of surface wind components. It is also indicated from spectral analysis that the significant periods of intraseasonal oscillation of daily mean zonal wind (MZW) were 30-to 60-day and 8-to 9-day long, and that of mean meridional wind (MMW)was 6-to 7-day long. The fluctuation of daily mean sea temperature (MST) in certain layers from surface to the 250 m layer also had the 30-to 60-day low frequency oscillation except for the 150 m layer,and the fluctuations of the daily MST in 100, 150, 200 and 250 m layers had the same 3-day period,their coherence and phase differences were over 0. 90 and between 319° and 353° respectively, which implies the fluctuations of daily MST from 100 to 250 m layers were in phase with each other in the same 3-day period. The analysis of in situ observations revealed a physical evidence of the westerly wind bursts (WWBs) which trigger off the eastward movement of warm water through intraseasonal oscillation and induce the onset of E1 Nino event.