利用天气数值预报产品建立贵州黔西南州分县温度预报方程的方法及应用

利用2002～2004年1～12月EC、T213天气数值产品的温度格点实时分析资料、预报资料以及贵州省黔西南州8个测站观测资料,从160个样本中筛选出相关较好的因子,利用多元回归统计模型,以及根据地理环境,天气形势分型造成的温度差值(ΔT)为逐步订正值,建立黔西南州分县温度预报方程。在2005年11月～2006年2月应用中取得较好效果,预报误差小于±3.0℃,平均误差1.3℃。     

喀斯特地区地表温度空间降尺度方法初探

喀斯特地区地形起伏大,常规的降尺度方法及所选择的因子对其不适用。该文根据喀斯特地区的特点,选取反射率、遥感指数及高程因子为尺度因子,通过随机森林模型建立MODIS第31、32波段辐射亮度数据和尺度因子之间的非线性关系,构建适合喀斯特地区的随机森林(Karst Random Forest,KRF)模型,成功将空间分辨率为1 km的热红外辐射亮度降至100 m,最后利用劈窗算法反演得到空间分辨率为100 m的地表温度。将KRF方法与仅考虑常规因子的多因子随机森林回归模型(MTVRF)和热锐化算法(TsHARP)对比,结果表明:1)在不同高差的喀斯特地区,KRF方法可较大程度提高地表温度降尺度精度,均方根误差(RMSE)在遵义市西北部和贵阳市以南地区分别为2.46 K和1.45 K,较MTVRF模型分别降低了0.1419 K和0.2928 K,较TsHARP算法分别降低了0.6204 K和0.6953 K,且在地形起伏度较低的喀斯特山区城市(贵阳市以南)表现更好;2)在喀斯特地区不同地类上,KRF方法效果也较好,其中植被区域最优,RMSE为1.41 K,破碎的裸土区域RMSE为1.84 K。研究显示,考虑特殊尺度因子的KRF方法可提高喀斯特地区地表温度的降尺度精度,为该地区以地表温度为基础的研究提供更精细可靠的地表温度产品。     

Agricultural land use dynamics in the Brazilian Amazon based on remote sensing and census data

The potential impact of deforestation in the Brazilian Amazon on greenhouse gas emissions to the atmosphere calls for policies that take account of changes in forest cover. Although much research has focused on the location and effects of deforestation, little is known about the distribution and reasons for the agricultural uses that replace forest cover. We used Landsat TM-based deforestation and agricultural census data to generate maps of the distribution and proportion of four major agricultural land uses throughout the Brazilian Amazon in 1997 and 2007. We built linear and spatial regression models to assess the determinant factors of deforestation and those major agricultural land uses - pasture, temporary agriculture and permanent agriculture - for the states of Pará, Rondônia, and Mato Grosso. The data include 30 determinant factors that were grouped into two years (1996 and 2006) and in four categories: accessibility to markets, public policies, agrarian structure, and environment. We found an overall expansion of the total agricultural area between 1997 and 2007, and notable differences between the states of Pará, Rondônia, and Mato Grosso in land use changes during this period. Regression models for deforestation and pasture indicated that determinant factors such as distance to roads were more influential in 1997 than in 2007. The number of settled families played an important role in the deforestation and pasture, the effect was stronger in 2007 than 1997. Indigenous lands were significant in preventing deforestation in high-pressure areas in 2007. For temporary and permanent agricultures, our results show that in 1997 the effect of small farms was stronger than in 2007. The mapped land use time series and the models explain empirically the effects of land use changes across the region over one decade.     

变暖背景下陕西极端气候事件变化分析

利用1961-2010年陕西省78个气象观测站的逐日最高温度、最低温度、平均温度以及日降水量资料,采用趋势分析方法对该地区极端气候事件的变化进行了分析。结果表明:①近50 a来陕西降水极端事件没有显著的增减变化趋势,但存在明显的阶段性。②近50 a来区域严重干燥事件在显著增加而严重湿润事件趋于减少,2000年以后严重干湿事件均偏多,区域降水有向不均衡、极端化发展的趋势。③区域年极端高（低）温事件在近50 a来呈现显著的增加（减少）趋势,其空间分布具有较好的一致性。极端温度事件的变化在各季节存在差异,冬、春季变暖的趋势比较显著。在显著变暖的20世纪90年代以后,相对于降水极端事件,温度极端事件显现地更为突出。     

基于GIS的宜昌市近50年来气温与降水时空演变规律研究

基于ArcGIS的Spatial Analyst Tools反距离加权平均方法,对宜昌市7个站点1960-2009年气温和降水日数据进行时空演变规律分析和空间化展示,结果表明:(1)宜昌市近50年年均气温为16.26℃,1977-2009年变化较为剧烈,各区均呈增温态势;代际变化与总体变化趋势相同,自20世纪80年代后...     

评估滨海湿地应对海平面上升的脆弱性的研究范式

滨海湿地是海陆交界的生态过渡带,也是对气候变化极为敏感的、脆弱的生态系统,海平面上升对全球滨海湿地构成了严重威胁.为了精确预测未来海平面加速上升背景下滨海湿地的变化趋势,有必要深入开展滨海湿地应对海平面上升的脆弱性评估研究.概述了评估滨海湿地应对海平面上升的脆弱性的研究范式,评估过程包括4个步骤:确定滨海湿地的高程资本...     

甘肃河西地区土地资源农业开发利用程度评价及持续利用对策研究

土地资源是区域社会经济发展的基本资源之一,土地资源开发利用程度评价将为人们了解掌握区域土地开发利用合理与否提供科学信息。作为重要商品粮基地的甘肃河西地区,土地农业开发利用历史悠久,文章通过土地资源农业开发利用程度评价研究,初步分析研究了区域土地开发利用特点,旨在为区域可持续发展战略的制定提供科学依据。     

FHD-1矢量质子磁力仪与温度相关性分析

通过矢量质子磁力仪FHD-1各分量北京时21点数据、日均值数据和室内记录的温度值作相关性分析,探讨温度对线圈和产出的数据是否有影响。     

基于空间散乱点插值的曲面重构

采用最近邻点法、距离反比加权法和克里格法等空间插值方法,基于IDL语言实现插值算法,对我国西部某金属矿山坑道内,利用大功率充电法测得的163个电位数据进行曲面重构,结果表明,克里格插值方法更能够真实地反映空间数据变量(场)的分布特性,具有广泛的实用价值。     

The effects of elevation on thermal bioclimatic conditions in Uludağ (Turkey)

This study compares the thermal bioclimatic conditions recorded at Bursa (100 m) and Uluda? (1878 m) meteorological stations at 7:00, 14:00 and 21:00 LST (local standard time) between 1975 and 2006, by using the physiologically equivalent temperature (PET), which is calculated from meteorological parameters. The effects of elevation-dependent environmental and atmospheric conditions on thermal perception (i.e., PET) values were analyzed and assessed. The analysis showed that the mean annual difference between PET values in Bursa and Uluda? was 12 ºC. The difference was lower in winter (9 ºC PET) and higher in summer (15 ºC PET). The highest difference between PET values occurred in the afternoon (16 ºC PET) and the lowest difference occurred in the morning (8.4 ºC PET). The differences occur as a result of high altitude and higher surface albedo due to snowfall, which leads to lower PET values and thus to less comfortable thermal conditions. The mean PET values of Bursa and Uluda? decrease 0.67 ºC every 100 m.