Response of vegetation NDVI to climatic extremes in the arid region of Central Asia: a case study in Xinjiang,China

Theoretical and Applied Climatology - Observed data showed the climatic transition from warm-dry to warm-wet in Xinjiang during the past 30 years and will probably affect vegetation...     

Regional analysis of wind climatic erosivity factor: a case study in fars province, southwest Iran

Wind erosion climatic erosivity is a measure of the climatic tendency to produce conditions conducive to wind erosion. This research develops a method to determine the regional climate’s tendency to cause wind erosion on the basis of a physically based climatic factor (CE) and linear moment analysis (L-moments) in Fars province, southwest Iran. CE is calculable from wind speed quantiles and other available meteorological data. The wind quantiles can be estimated by a frequency analysis of the available wind data. Wind speed data are often either not available or are of short record length, and thus, CE estimates from such data have large standard errors. In such a situation, data from several sites can be used to estimate wind speed quantiles at each site based on a regional frequency analysis. Monthly averages of maximum daily wind speed of 19 meteorological stations in Fars province were used for regional analysis. Based on L-moment analysis, two homogeneous regions were determined. Regional wind speed quantiles were calculated, and the results were used to calculate CE values for two 6-month wet and dry periods for each homogeneous region. Furthermore, CE values were estimated for each station in the study area using a Weibull distribution, and the results were compared with the regional-based CE values. It showed that CE values estimated using the regional-based approach have smaller sampling variance compared to those obtained from the Weibull method. The proposed method can be used to evaluate the regional risk of wind erosion in arid and semi-arid environments.     

Spatiotemporal analysis of precipitation and temperature concentration using PCI and TCI: a case study of Khuzestan Province,Iran

Theoretical and Applied Climatology - Temperature and precipitation are the basic elements of climate, and their variation can change the water demands of different uses. In this study, the trend...     

大气对红外窗区遥感的影响

本文简述大气对红外窗区遥感的影响。给出处理遥感资料的辐射传输方程。用简化的辐射传输方程处理一次海空试验的资料,将遥感测量与常规测量作了比较,结果较为满意。     

基于GIS气候资源评价及区划研究——以陕西省苹果气候区划为例

应用模糊综合评判的理论和方法,通过陕西省优质苹果气候区划实例,探索了运用GIS技术进行气候资源评价及区划的方法:即在分析选择影响苹果品质气候因子的基础上,确定优质苹果气候资源评价指标模型;根据要素权重和隶属度,建立单因子评价栅格图层;利用GIS空间叠置功能,综合评价图按适宜度分级并与夏季水热状况矢量图叠加,得到陕西省苹果种植气候生态区划图。结果表明,渭北黄土高原海拔80 0～1 2 0 0 m冷凉半干旱、半湿润区,是陕西省优质苹果气候生态区。     

Spatial patterns of vegetation phenology metrics and related climatic controls of eight contrasting forest types in India – analysis from remote sensing datasets

Summary Leaf phenology describes the seasonal cycle of leaf functioning and is essential for understanding the interactions between the biosphere, the climate and the atmosphere. In this study, we characterized the spatial patterns in phenological variations in eight contrasting forest types in an Indian region using coarse resolution NOAA AVHRR satellite data. The onset, offset and growing season length for different forest types has been estimated using normalized difference vegetation index (NDVI). Further, the relationship between NDVI and climatic parameters has been assessed to determine which climatic variable (temperature or precipitation) best explain variation in NDVI. In addition, we also assessed how quickly and over what time periods does NDVI respond to different precipitation events. Our results suggested strong spatial variability in NDVI metrics for different forest types. Among the eight forest types, tropical dry deciduous forests showed lowest values for summed NDVI (SNDVI), averaged NDVI (ANDVI) and integrated NDVI (I-NDVI), while the tropical wet evergreen forests of Arunachal Pradesh had highest values. Within the different evergreen forest types, SNDVI, ANDVI and INDVI were highest for tropical wet evergreen forests, followed by tropical evergreen forests, tropical semi-evergreen forests and were least for tropical dry evergreen forests. Differences in the amplitude of NDVI were quite distinct for evergreen forests compared to deciduous ones and mixed deciduous forests. Although, all the evergreen forests studied had a similar growing season length of 270 days, the onset and offset dates were quite different. Response of vegetative greenness to climatic variability appeared to vary with vegetation characteristics and forest types. Linear correlations between mean monthly NDVI and temperature were found to yield negative relationships in contrast to precipitation, which showed a significant positive response to vegetation greenness. The correlations improved much for different forest types when the log of cumulative rainfall was correlated against mean monthly NDVI. Of the eight forest types, the NDVI for six forest types was positively correlated with the logarithm of cumulative rainfall that was summed for 3–4 months. Overall, this study identifies precipitation as a major control for vegetation greenness in tropical forests, more so than temperature.     

Application of remote sensing and multivariate analysis to the agroclimatic characterization of a Mediterranean region

Summary This paper presents a climatological application of the combination of remote sensing data and multivariate analysis. It proposes a methodology to perform an agroclimatic characterization of a region with the aim of determining homogeneous areas. This methodology is applied to Catalonia, in the northwest of the Mediterranean Sea, in the Iberian Peninsula. To this end various multivariate analysis techniques have been applied to data from 107 meteorological stations and to digitally processed AVHRR images from a NOAA satellite (ground surface temperature and thermal inertia). Values of emissivity and albedo for different land uses and phenomenological states, in addition to the most suitable algorithms for the soil surface temperature, have been obtained. Combining this information with orographic characteristics and the Papadakis classification, a final map is obtained with 68 homogeneous zones for the period between April and October, the most important for the agriculture of the area studied.With 5 Figures     

New climatic zones in Iran: a comparative study of different empirical methods and clustering technique

Theoretical and Applied Climatology - Recently in agricultural and industrial sectors, researchers have started to classify the climate of a region using empirical methods and clustering. This...     

伊犁地区不同草地类型植被指数与气候因子的关系

基于2006—2012年主要生长季(5—9月)MODIS旬最大值合成NDVI数据,结合同期气温、降水插值栅格资料,采用均值法、线性回归法、相关系数法分析了伊犁河谷地区七大不同草地类型NDVI的时空变化规律及其对气象因子响应的敏感性及滞后性。结果表明:(1)伊犁河谷草地植被NDVI整体呈微弱增加趋势,其中,温性荒漠类草地的增加趋势略高于其他几种类型。(2)温性草甸草原、温性草原、温性荒漠草原、高寒草原、低平地草甸的NDVI主要受降水影响,即NDVI与生长季平均降水量呈极显著正相关,且平均降水量每增加1 mm,其NDVI分别增加0.005、0.006、0.007、0.004、0.003。(3)不同草地类型与气温、降水存在不同的滞后响应,多数草地类型5月气温、降水与7月NDVI表现出显著相关性。其中,温性草甸草原、温性草原、温性荒漠草原NDVI受气温和降水共同影响,气温每升高1℃,NDVI分别减少0.020、0.028、0.027,降水每增加1 mm,NDVI分别增加0.002、0.003、0.003;高寒草原主要受降水影响,降水每增加1 mm,NDVI增加0.003;低平地草甸主要受气温影响,气温每升高1℃,NDVI减少0.016;温性荒漠、沼泽与气温、降水没有明显相关性。不同草地类型对水热因子的需求不同,是产生这种结果的主要原因。     

Airborne measurements of turbulent fluxes during LITFASS-98: Comparison with ground measurements and remote sensing in a case study

Summary ?Simultaneous flight measurements with the research aircraft Do 128 and the helicopter-borne turbulence probe Helipod were performed on 18 June 1998 during the LITFASS-98 field experiment. The area-averaged turbulent vertical fluxes of momentum, sensible, and latent heat were determined on a 15 km × 15 km and a 10 km × 10 km flight pattern, respectively. The flights were carried out over heterogeneous terrain at different altitudes within a moderately convective boundary layer with Cumulus clouds. Co-spectra-analysis demonstrated that the small scale turbulent transport was completely sampled, while the comparatively small flight patterns were possibly of critical size regarding the large-scale turbulence. The phygoide of the airplane was identified as a significant peak in some co-spectra. The turbulent fluxes of momentum and sensible heat at 80 m above the ground showed systematic dependence on the location of the flight legs above the heterogeneous terrain. This was not observed for the latent heat flux, probably due to the vertical distribution of humidity in the boundary layer. Statistical error analysis of the fluxes F showed that the systematic statistical error ΔF was one order of magnitude smaller than the standard deviation σ _F . The difference between area-averaged fluxes derived from simultaneous Helipod and Do 128 measurements was much smaller than σ _F , indicating that the systematic statistical error was possibly over-estimated by the usual method. In the upper half of the boundary layer the airborne-measured sensible heat flux agreed well with windprofiler/RASS data. A linear fit was the best approximation for the height dependence of all three fluxes. The linear extrapolations of the latent and sensible heat fluxes to the ground were in good agreement with tower, scintillometer, and averaged ground-station measurements on various surface types. Systematic discrepancies between airborne and ground-based measurements were not found. Received June 18, 2001; revised December 21, 2001; accepted June 3, 2002     

Compounding effects of human activities and climatic changes on surface water availability in Iran

Climatic Change - By combining long-term ground-based data on water withdrawal with climate model projections, this study quantifies the compounding effects of human activities and climate change...     

Correction to: New climatic zones in Iran: a comparative study of different empirical methods and clustering technique

Theoretical and Applied Climatology -     

基于GWR模型的典型区域GPM数据降尺度研究——以浙江省为例

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。     

Agricultural drought survey using MODIS-based image indices at the regional scale: case study of the Urmia Lake Basin,Iran

Theoretical and Applied Climatology - Drought is a natural, global and recurring phenomenon caused by climatic anomalies and inevitable meteorological changes. Lake Urmia in northwestern Iran has...     

Evaluating the performance of remote sensing precipitation products CMORPH,PERSIANN, and TMPA,in the arid region of northwest China

The arid region of northwest China is a large area with complex topography. Hydrological research is limited by scarcity and uneven distribution of rain gauges. Satellite precipitation products provide wide coverage and high spatial–temporal resolutions, but the accuracy needs to be evaluated before application. In this paper, the reliability of four satellite precipitation products (CMORPH [Climate Prediction Center’s morphing technique], PERSIANN [Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks], TRMM [Tropical Rainfall Measuring Mission] 3B42, and TRMM 3B43) were evaluated through comparison with ground data or reported values on daily, monthly, and annual scales from 2003 to 2010. Indices including frequency bias index, probability of detection, and false alarm ratio were used to evaluate recorded precipitation occurrences; relative mean bias, the correlation coefficient, and the Nash coefficient were used to assess precipitation amount. Satellite precipitation products were more accurate in the warm than in the cold season, and performed better in northern Xinjiang than in other regions during the cold season. CMORPH and PERSIANN tended to overestimate precipitation. TRMM 3B42 and TRMM 3B43 performed best because the former most accurately detected precipitation occurrences on a daily scale, and both produced accurate space–time distribution of precipitation and the best consistency with rain gauge observations. Only a few monthly precipitation values for TRMM 3B42 and TRMM 3B43, and annual precipitation values for TRMM 3B42 were with satisfactory precision. TRMM3B42 and TRMM 3B43 are therefore recommended, but correction will be needed before application. Factors including elevation, relative relief, longitude, and latitude had significant effects on the performance of satellite precipitation products, and these factors may be helpful in correcting satellite precipitation.     

4D tomographic reconstruction of the tropospheric wet refractivity using the concept of virtual reference station,case study: northwest of Iran

Iran enjoys a variety of climatological conditions. Moreover, numerical weather prediction (NWP) models are not assimilated with the meteorological data in Iran, the country suffering from poor spatial and temporal resolution of radiosonde measurements. These facts make modeling of troposphere impossible using the measurements and NWP. On the other hand, the global positioning system (GPS) has been emerged as a valuable tool for modeling and remote sensing of Earth’s atmosphere. This research is the first attempt to address the tropospheric wet refractivity modeling by GPS measurements in Iran. Changes of topography in the study area are taken into account. As a leading work, virtual reference stations (VRS) are used to fix the rank deficiency of the problem. The model space resolution matrix is used to achieve the optimum spatial resolution of the tomographic model and the optimum number of VRS stations. The accuracy of the developed model (KNTU1) is investigated by deploying radiosonde measurements.     

Precipitation extremes in a karst region: a case study in the Guizhou province, southwest China

The topography of hilly landscapes modifies crop environment changing the fluxes of water and energy, increasing risk in these vulnerable agriculture systems, which could become more accentuated under climate change (drought, increased variability of rainfall). In order to quantify how wheat production in hilly terrain will be affected by future climate, a newly developed and calibrated micro-meteorological model for hilly terrain was linked to a crop growth simulation model to analyse impact scenarios for different European regions. Distributions of yield and growing length of rainfed winter wheat and durum wheat were generated as probabilistic indices from baseline and low (B2) and high (A2) emission climate scenarios provided from the Hadley Centre Regional Climate Model (HadRM3). We used site-specific terrain parameters for two sample catchments in Europe, ranging from humid temperate (southeast UK) to semi-arid Mediterranean (southern Italy). Results for baseline scenario show that UK winter wheat is mainly affected by annual differences in precipitation and yield distributions do not change with terrain, whilst in the southern Mediterranean climate yield variability is significantly related to a slope × elevation index. For future climate, our simulations confirm earlier predictions of yield increase in the UK, even under the high emission scenario. In the southern Mediterranean, yield reduction is significantly related to slope × elevation index increasing crop failure in drier elevated spots but not in wet years under baseline weather. In scenarios for the future, the likelihood of crop failure rises sharply to more than 60%, and even in wet years, yields are likely to decrease in elevated spots.     

植被地表反照率动态模拟方法比较-以玉米农田为例

利用2007年锦州玉米农田生态系统野外观测站玉米生长季辐射资料,对地表反照率综合模型、半经验双层模型和简化双层模型模拟精度进行比较。结果表明：简化双层模型在玉米生育初期模拟能力较差,其他时段模拟能力都较强,尤其在玉米生育后期更为明显;半经验双层模型除在玉米叶面积指数处于最大时期模拟误差较小外,其他时段基本无法模拟。综合模型大部分时段模拟能力都较强,仅在玉米生育后期模拟能力稍差,该模型对实现玉米农田地表反照率动态参数化更为理想,可为改进陆面过程模型提供参考。