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1.
A computational framework to generate daily temperature maps using time-series of publicly available MODIS MOD11A2 product Land Surface Temperature (LST) images (1 km resolution; 8-day composites) is illustrated using temperature measurements from the national network of meteorological stations (159) in Croatia. The input data set contains 57,282 ground measurements of daily temperature for the year 2008. Temperature was modeled as a function of latitude, longitude, distance from the sea, elevation, time, insolation, and the MODIS LST images. The original rasters were first converted to principal components to reduce noise and filter missing pixels in the LST images. The residual were next analyzed for spatio-temporal auto-correlation; sum-metric separable variograms were fitted to account for zonal and geometric space-time anisotropy. The final predictions were generated for time-slices of a 3D space-time cube, constructed in the R environment for statistical computing. The results show that the space-time regression model can explain a significant part of the variation in station-data (84%). MODIS LST 8-day (cloud-free) images are unbiased estimator of the daily temperature, but with relatively low precision (±4.1°C); however their added value is that they systematically improve detection of local changes in land surface temperature due to local meteorological conditions and/or active heat sources (urban areas, land cover classes). The results of 10–fold cross-validation show that use of spatio-temporal regression-kriging and incorporation of time-series of remote sensing images leads to significantly more accurate maps of temperature than if plain spatial techniques were used. The average (global) accuracy of mapping temperature was ±2.4°C. The regression-kriging explained 91% of variability in daily temperatures, compared to 44% for ordinary kriging. Further software advancement—interactive space-time variogram exploration and automated retrieval, resampling and filtering of MODIS images—are anticipated.  相似文献   

2.
选取QIN和SOB两种代表性劈窗算法对辽宁地区地表温度进行反演,并分析二者的精度和误差分布。结果表明:QIN和SOB算法反演的地表温度(TS)与地面气象台站准同步观测的气温和地温的线性拟合显著,SOB算法线性拟合更好;从误差分布直方图上看,两种算法的反演结果与地温更接近,SOB算法与同步气温和地温在±2 ℃之间的误差比例略高于QIN算法;在野外开展与卫星遥感空间尺度一致的地表温度观测试验,QIN和SOB算法与实测值的平均绝对误差均为1.5 ℃;与NASA官网发布的地表温度产品对比发现,QIN和SOB算法的平均绝对误差分别为1.75 ℃、1.70 ℃;因此QIN、SOB算法在辽宁地区均适用,SOB算法误差更小。  相似文献   

3.
FY-3A陆表温度反演及高温天气过程动态监测   总被引:1,自引:0,他引:1       下载免费PDF全文
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。  相似文献   

4.
The public health implications of a warming urban environment mean that appropriate action by planners, designers and health workers will be necessary to minimise risk under future climate scenarios. Data at an appropriate spatial scale are required by user groups in order to identify key areas of vulnerability. Thermal mapping of a UK urban conurbation was carried out during the summers of 2007 and 2008 with the aim of providing high spatial resolution temperature data. The air temperature results showed an average daytime (night time) urban?Crural thermal contrast of 3°C (5°C) on summer days (nights) with ideal urban heat island (UHI) conditions. The intensity of the daytime surface temperature heat island was found to exceed 10°C. The measured data were used to derive an empirical model of spatial temperature patterns based upon characteristics of land use, distance from urban centre and building geometry. This model can be used to provide sub-kilometre resolution temperature data which are required by decision makers and can provide a mechanism for downscaling climate model output.  相似文献   

5.
This study demonstrates that urban heat island (UHI) intensity can be estimated by comparing observational data and the outputs of a well-developed high-resolution regional climate model. Such an estimate is possible because the observations include the effects of UHI, whereas the model used does not include urban effects. Therefore, the errors in the simulated surface air temperature, defined as the difference between simulated and observed temperatures (simulated minus observed), are negative in urban areas but 0 in rural areas. UHI intensity is estimated by calculating the difference in temperature error between urban and rural areas. Our results indicate that overall UHI intensity in Japan is 1.5 K and that the intensity is greater in nighttime than in daytime, consistent with the previous studies. This study also shows that root mean square error and the magnitude of systematic error for the annual mean temperature are small (within 1.0 K).  相似文献   

6.
Wu  Yang  Huang  Anning  Lazhu  Yang  Xianyu  Qiu  Bo  Wen  Lijuan  Zhang  Zhiqi  Fu  Zhipeng  Zhu  Xueyan  Zhang  Xindan  Cai  Shuxin  Tang  Yong 《Climate Dynamics》2020,55(9-10):2703-2724

A series of model sensitivity simulations are carried out to calibrate and improve the Weather Research and Forecasting Model coupled with a one-dimensional lake model (WRF-Lake) based on observations over Lake Nam Co. Using the default lake model parameters, the solution of WRF-Lake exhibits significant biases in both the lake thermodynamics and regional climatology, i.e., higher lake surface temperature (LST), earlier onset of summer thermal stratification, and overestimated near-surface air temperature and precipitation induced by the lake’s excessive warming and moistening impacts. The performance of WRF-Lake is improved through adjusting the initial lake temperature profile, the temperature of maximum water density (Tdmax), the surface roughness length, and the light extinction coefficient. Results show that initializing the water temperature with spring observation mitigates the LST overestimation and reduces the timing error of the onset of thermal stratification. By further adjusting Tdmax from 4 °C to the observed value of 3.5 °C, the LST increase from June to mid-July is enhanced and the buildup of thermal stratification is more accurately predicted. Through incorporating the parameterized surface roughness length and decreasing the light extinction coefficient, the model better reproduces the observed daily evolution of LST and vertical lake temperature profile. The calibrated WRF-Lake effectively mitigates the overestimation of over-lake air temperature at 2 m height and precipitation over regions downwind the lake. This suggests that an improved lake scheme within the coupled WRF-Lake is essential for realistically simulating the lake–air interactions and the regional climate over the lake-rich Tibetan Plateau.

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7.
Zhangjiakou is an important wind power base in Hebei Province, China. The impact of its wind farms on the local climate is controversial. Based on long-term meteorological data from 1981 to 2018, we investigated the effects of the Shangyi Wind Farm (SWF) in Zhangjiakou on air temperature, wind speed, relative humidity, and precipitation using the anomaly or ratio method between the impacted weather station and the non-impacted background weather station. The influence of the SWF on land surface temperature (LST) and evapotranspiration (ET) using MODIS satellite data from 2003 to 2018 was also explored. The results showed that the SWF had an atmospheric warming effect at night especially in summer and autumn (up to 0.95°C). The daytime air temperature changes were marginal, and their signs were varying depending on the season. The annual mean wind speed decreased by 6%, mainly noted in spring and winter (up to 14%). The precipitation and relative humidity were not affected by the SWF. There was no increase in LST in the SWF perhaps due to the increased vegetation coverage unrelated to the wind farms, which canceled out the wind farm-induced land surface warming and also resulted in an increase in ET. The results showed that the impact of wind farms on the local climate was significant, while their impact on the regional climate was slight.  相似文献   

8.
The Yangtze River Delta Economic Belt is one of the most active and developed areas in China and has experienced quick urbanization with fast economic development. The weather research and forecasting model (WRF), with a single-layer urban canopy parameterization scheme, is used to simulate the influence of urbanization on climate at local and regional scales in this area. The months January and July, over a 5-year period (2003–2007), were selected to represent the winter and summer climate. Two simulation scenarios were designed to investigate the impacts of urbanization: (1) no urban areas and (2) urban land cover determined by MODIS satellite observations in 2005. Simulated near-surface temperature, wind speed and specific humidity agree well with the corresponding measurements. By comparing the simulations of the two scenarios, differences in near-surface temperature, wind speed and precipitation were quantified. The conversion of rural land (mostly irrigation cropland) to urban land cover results in significant changes to near-surface temperature, humidity, wind speed and precipitation. The mean near-surface temperature in urbanized areas increases on average by 0.45?±?0.43°C in winter and 1.9?±?0.55°C in summer; the diurnal temperature range in urbanized areas decreases on average by 0.13?±?0.73°C in winter and 0.55?±?0.84°C in summer. Precipitation increases about 15% over urban or leeward areas in summer and changes slightly in winter. The urbanization impact in summer is stronger and covers a larger area than that in winter due to the regional east-Asian monsoon climate characterized by warm, wet summers and cool, dry winters.  相似文献   

9.
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。  相似文献   

10.
西藏林芝地区混合像元MODIS地表温度产品验证   总被引:1,自引:1,他引:0       下载免费PDF全文
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。  相似文献   

11.
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...  相似文献   

12.
CoLM模式地表温度变分同化研究   总被引:2,自引:1,他引:1  
本文采用变分方法对通用陆面模式 (CoLM) 中的地表温度进行同化.同化伴随约束条件采用CoLM模式中的地表及植被能量平衡方程,调节因子采用裸土及植被蒸发比.采用美国通量网 (AmeriFlux) 中的Bonville站数据对同化方法进行了单点验证,验证结果表明同化后地表温度以及蒸散结果更加接近于实测值.选取中国华北地区对同化方法进行区域验证,结果显示每天仅采用白天一次观测值对地表温度进行同化的方法是有效的.通过对同化前后地表温度误差直方图比较可以发现,在有MODIS观测值的区域,同化后白天地表温度误差大大降低,同时,同化后地表蒸散空间分布图也发生了变化.单点验证以及区域验证结果都表明了变分同化方法是可靠的.变分同化方法可以改进陆面模式模拟结果,对于地表过程研究中的植被生态、水文等研究具有重要意义,同时,陆面模式可以与数值预报模式进行耦合,改进数值预报结果.  相似文献   

13.
The climate of the last glacial maximum (LGM) is simulated with a high-resolution atmospheric general circulation model, the NCAR CCM3 at spectral truncation of T170, corresponding to a grid cell size of roughly 75 km. The purpose of the study is to assess whether there are significant benefits from the higher resolution simulation compared to the lower resolution simulation associated with the role of topography. The LGM simulations were forced with modified CLIMAP sea ice distribution and sea surface temperatures (SST) reduced by 1°C, ice sheet topography, reduced CO2, and 21,000 BP orbital parameters. The high-resolution model captures modern climate reasonably well, in particular the distribution of heavy precipitation in the tropical Pacific. For the ice age case, surface temperature simulated by the high-resolution model agrees better with those of proxy estimates than does the low-resolution model. Despite the fact that tropical SSTs were only 2.1°C less than the control run, there are many lowland tropical land areas 4–6°C colder than present. Comparison of T170 model results with the best constrained proxy temperature estimates (noble gas concentrations in groundwater) now yield no significant differences between model and observations. There are also significant upland temperature changes in the best resolved tropical mountain belt (the Andes). We provisionally attribute this result in part as resulting from decreased lateral mixing between ocean and land in a model with more model grid cells. A longstanding model-data discrepancy therefore appears to be resolved without invoking any unusual model physics. The response of the Asian summer monsoon can also be more clearly linked to local geography in the high-resolution model than in the low-resolution model; this distinction should enable more confident validation of climate proxy data with the high-resolution model. Elsewhere, an inferred salinity increase in the subtropical North Atlantic may have significant implications for ocean circulation changes during the LGM. A large part of the Amazon and Congo Basins are simulated to be substantially drier in the ice age—consistent with many (but not all) paleo data. These results suggest that there are considerable benefits derived from high-resolution model regarding regional climate responses, and that observationalists can now compare their results with models that resolve geography at a resolution comparable to that which the proxy data represent.  相似文献   

14.
中国区域陆面覆盖变化的气候效应模拟研究   总被引:3,自引:0,他引:3  
基于MODIS和CLCV陆面覆盖资料,利用区域气候模式RegCM4分别进行两组24年(1978-2001年)的数值模拟试验,研究中国区域陆面覆盖变化对区域气候的影响。结果表明,以荒漠化和植被退化为主要特征的陆面覆盖变化通过改变陆面能量、水分平衡与大尺度环流进而对气候要素产生重要影响。夏季,中国南方地区普遍降温,季风边缘区及藏北高原气温升高,降水减少;季风边缘区与西北地区气温年际波动加剧;内蒙古中东部地区西南风增强,进而水汽输送增强,一定程度上增加了该地区降水。冬季,中国东部地区偏北气流增强,更多干燥冷空气南下,使得黄河以南地区降水减少、气温降低。  相似文献   

15.
We simulated the impact of anthropogenic heat release (AHR) on the regional climate in three vast city agglomerations in China using the Weather Research and Forecasting model with nested high-resolution modeling.Based on energy consumption and high-quality land use data,we designed two scenarios to represent no-AHR and current-AHR conditions.By comparing the results of the two numerical experiments,changes of surface air temperature and precipitation due to AHR were quantified and analyzed.We concluded that AHR increases the temperature in these urbanized areas by about 0.5℃-1℃,and this increase is more pronounced in winter than in other seasons.The inclusion of AHR enhances the convergence of water vapor over urbanized areas.Together with the warming of the lower troposphere and the enhancement of ascending motions caused by AHR,the average convective available potential energy in urbanized areas is increased.Rainfall amounts in summer over urbanized areas are likely to increase and regional precipitation patterns to be altered to some extent.  相似文献   

16.
不同分辨率CCSM4对东亚和中国气候模拟能力分析   总被引:9,自引:4,他引:5  
田芝平  姜大膀 《大气科学》2013,37(1):171-186
本文利用通用气候系统模式CCSM4在三种水平分辨率下的工业化革命前期气候模拟试验,结合观测和再分析资料,比较了各分辨率下模式对中国温度和降水、东亚海平面气压和850 hPa风场的模拟能力,综合评价了模式分辨率对东亚和中国气候模拟的影响.结果表明,三种分辨率对中国温度均具有很好的模拟能力,除春季外,低分辨率(T31,约3.75°×3.75°)对全年温度的模拟能力均要稍好于中(f19,约1.9°×2.5°)、高(f09,约0.9°×1.25°)分辨率;各分辨率对中国降水的模拟能力远不如温度,除冬季外全年都出现的中部地区虚假降水并未因为模式分辨率提高而得到本质改善;对于东亚海平面气压场,低分辨率在冬季模拟能力相对最好,中等分辨率在夏季相对较好,而高分辨率的模拟能力均表现最差;低分辨率对850 hPa东亚冬季风和夏季风的模拟能力均要好于中、高分辨率,而两种较高分辨率的模拟能力则比较接近.总的来说,低分辨率CCSM4在东亚和中国气候模拟中表现出了较大优势,加之其计算代价小,适合进行需要较长时间积分的气候模拟研究.  相似文献   

17.
The aim of this study was to develop an advanced parameterization of the snow-free land surface albedo for climate modelling describing the temporal variation of surface albedo as a function of vegetation phenology on a monthly time scale. To estimate the effect of vegetation phenology on snow-free land surface albedo, remotely sensed data products from the Moderate-Resolution Imaging Spectroradiometer (MODIS) on board the NASA Terra platform measured during 2001 to 2004 are used. The snow-free surface albedo variability is determined by the optical contrast between the vegetation canopy and the underlying soil surface. The MODIS products of the white-sky albedo for total shortwave broad bands and the fraction of absorbed photosynthetically active radiation (FPAR) are analysed to separate the vegetation canopy albedo from the underlying soil albedo. Global maps of pure soil albedo and pure vegetation albedo are derived on a 0.5° regular latitude/longitude grid, re-sampling the high-resolution information from remote sensing-measured pixel level to the model grid scale and filling up gaps from the satellite data. These global maps show that in the northern and mid-latitudes soils are mostly darker than vegetation, whereas in the lower latitudes, especially in semi-deserts, soil albedo is mostly higher than vegetation albedo. The separated soil and vegetation albedo can be applied to compute the annual surface albedo cycle from monthly varying leaf area index. This parameterization is especially designed for the land surface scheme of the regional climate model REMO and the global climate model ECHAM5, but can easily be integrated into the land surface schemes of other regional and global climate models.  相似文献   

18.
The spatial resolution gap between global or regional climate models and the requirements for local impact studies motivates the need for climate downscaling. For impact studies that involve glacier modelling, the sparsity or complete absence of climate monitoring activities within the regions of interest presents a substantial additional challenge. Downscaling methods for this application must be independent of climate observations and cannot rely on tuning to station data. We present new, computationally-efficient methods for downscaling precipitation and temperature to the high spatial resolutions required to force mountain glacier models. Our precipitation downscaling is based on an existing linear theory for orographic precipitation, which we modify for large study regions by including moist air tracking. Temperature is downscaled using an interpolation scheme that reconstructs the vertical temperature structure to estimate surface temperatures from upper air data. Both methods are able to produce output on km to sub-km spatial resolution, yet do not require tuning to station measurements. By comparing our downscaled precipitation (1 km resolution) and temperature (200 m resolution) fields to station measurements in southern British Columbia, we evaluate their performance regionally and through the annual cycle. Precipitation is improved by as much as 30% (median relative error) over the input reanalysis data and temperature is reconstructed with a mean bias of 0.5°C at locations with high vertical relief. Both methods perform best in mountainous terrain, where glaciers tend to be concentrated.  相似文献   

19.
Time series of MODIS land surface temperature(T_s) and normalized difference vegetation index(NDVI) products,combined with digital elevation model(DEM) and meteorological data from 2001 to 2012,were used to map the spatial distribution of monthly mean air temperature over the Northern Tibetan Plateau(NTP). A time series analysis and a regression analysis of monthly mean land surface temperature(T_s) and air temperature(T_a) were conducted using ordinary linear regression(OLR) and geographical weighted regression(GWR). The analyses showed that GWR,which considers MODIS T_s,NDVI and elevation as independent variables,yielded much better results [R_(Adj)~2 0.79; root-mean-square error(RMSE) =0.51℃–1.12℃] associated with estimating T_a compared to those from OLR(R_(Adj)~2= 0.40-0.78; RMSE = 1.60℃–4.38℃).In addition,some characteristics of the spatial distribution of monthly T_a and the difference between the surface and air temperature(T_d) are as follows. According to the analysis of the 0℃ and 10℃ isothermals,T_a values over the NTP at elevations of 4000–5000 m were greater than 10℃ in the summer(from May to October),and T_a values at an elevation of3200 m dropped below 0℃ in the winter(from November to April). T_a exhibited an increasing trend from northwest to southeast. Except in the southeastern area of the NTP,T d values in other areas were all larger than 0℃ in the winter.  相似文献   

20.
Impact of ocean model resolution on CCSM climate simulations   总被引:1,自引:1,他引:0  
The current literature provides compelling evidence suggesting that an eddy-resolving (as opposed to eddy-permitting or eddy-parameterized) ocean component model will significantly impact the simulation of the large-scale climate, although this has not been fully tested to date in multi-decadal global coupled climate simulations. The purpose of this paper is to examine how resolved ocean fronts and eddies impact the simulation of large-scale climate. The model used for this study is the NCAR Community Climate System Model version 3.5 (CCSM3.5)—the forerunner to CCSM4. Two experiments are reported here. The control experiment is a 155-year present-day climate simulation using a 0.5° atmosphere component (zonal resolution 0.625 meridional resolution 0.5°; land surface component at the same resolution) coupled to ocean and sea-ice components with zonal resolution of 1.2° and meridional resolution varying from 0.27° at the equator to 0.54° in the mid-latitudes. The second simulation uses the same atmospheric and land-surface models coupled to eddy-resolving 0.1° ocean and sea-ice component models. The simulations are compared in terms of how the representation of smaller scale features in the time mean ocean circulation and ocean eddies impact the mean and variable climate. In terms of the global mean surface temperature, the enhanced ocean resolution leads to a ubiquitous surface warming with a global mean surface temperature increase of about 0.2?°C relative to the control. The warming is largest in the Arctic and regions of strong ocean fronts and ocean eddy activity (i.e., Southern Ocean, western boundary currents). The Arctic warming is associated with significant losses of sea-ice in the high-resolution simulation. The sea surface temperature gradients in the North Atlantic, in particular, are better resolved in the high-resolution model leading to significantly sharper temperature gradients and associated large-scale shifts in the rainfall. In the extra-tropics, the interannual temperature variability is increased with the resolved eddies, and a notable increases in the amplitude of the El Ni?o and the Southern Oscillation is also detected. Changes in global temperature anomaly teleconnections and local air-sea feedbacks are also documented and show large changes in ocean–atmosphere coupling. In particular, local air-sea feedbacks are significantly modified by the increased ocean resolution. In the high-resolution simulation in the extra-tropics there is compelling evidence of stronger forcing of the atmosphere by SST variability arising from ocean dynamics. This coupling is very weak or absent in the low-resolution model.  相似文献   

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