MODIS MOD16蒸散发产品在中国流域的质量评估

利用地面观测降水数据、流量数据,以及重力卫星(GRACE)观测的与全球陆面数据同化系统(GLDAS)模拟的流域蓄水量变化数据,基于流域水量平衡原理,从年与月两个时间尺度分析了MODIS全球蒸散发产品(MOD16)在中国不同流域的一致性及其时空特征。结果表明:1)年尺度上,MOD16/ET在中国流域(除松花江流域)与基于水量平衡估算的流域实际ET(WBET)相比呈现高估,且在不同集水区高估程度不同,与流域实际ET的差异从北方的松花江流域、黄河流域到南方的长江流域有从小到大的特点;2)月尺度上,MOD16/ET与WBET相比,存在低值区(20 mm/月)高估、高值区(20 mm/月)低估的特点;在蒸散发过程较弱的11月到次年3月,MOD16/ET产品在中国流域存在普遍性高估;而在其他月份,MOD16/ET与WBET的一致性因流域而异;3)MOD16/ET与WBET的一致性在中国不同流域存在地域性差异,总体上在外流区的一致性优于内流区,在北方松花江流域的一致性优于南方的长江流域。     

Case study of dust event sources from the Gobi and Taklamakan deserts: An investigation of the horizontal evolution and topographical effect using numerical modeling and remote sensing

A severe dust event occurred from April 23 to April 27, 2014, in East Asia. A state-of-the-art online atmospheric chemistry model, WRF/Chem, was combined with a dust model, GOCART, to better understand the entire process of this event. The natural color images and aerosol optical depth (AOD) over the dust source region are derived from datasets of moderate resolution imaging spectroradiometer (MODIS) loaded on a NASA Aqua satellite to trace the dust variation and to verify the model results. Several meteorological conditions, such as pressure, temperature, wind vectors and relative humidity, are used to analyze meteorological dynamic. The results suggest that the dust emission occurred only on April 23 and 24, although this event lasted for 5 days. The Gobi Desert was the main source for this event, and the Taklamakan Desert played no important role. This study also suggested that the landform of the source region could remarkably interfere with a dust event. The Tarim Basin has a topographical effect as a “dust reservoir” and can store unsettled dust, which can be released again as a second source, making a dust event longer and heavier.     

亚洲地区MODIS和Himawari-8细模态气溶胶产品验证及其时空分布分析

利用AERONET观测网数据,结合MODIS(中分辨率成像光谱仪)及Himawari-8(新一代地球同步气象卫星)的气溶胶产品分析了亚洲41个站点2015—2016年细模态气溶胶光学特性.结果表明,MODIS和Himawari-8反演气溶胶细模态比例(FMF)及细模态气溶胶光学厚度(fAOD)落在误差区间EE(期望误差)内的比例均不超过80%,其中8个典型站点则不超过50%,总体上MODIS要优于Himawari-8,但与AERONET地基观测资料相比还存在一定的误差.因此,需要进一步研究反演方法,提升地表反射率的确定精度,从而提高卫星遥感反演精度.通过季节平均的比较,发现春、夏、秋、冬四季MODIS和Himawari-8的反演值均有所低估,MODIS fAOD各季节平均偏差相对较小.Himawari-8 FMF秋季在Dhaka_University站的平均偏差较大,MODIS FMF春、冬季的平均偏差最大值相对较大,夏、秋季则相对较小;对于同一站点在相同季节均为Himawari-8 fAOD偏差较大,并且MODIS fAOD各季节的平均偏差最大值均小于Himawari-8 fAOD的偏差值.同时,利用卫星观测分析了亚洲地区FMF和fAOD年均及季节平均分布特征,发现MODIS和Himawari-8 FMF年均分布高值区主要位于华北平原、东北平原、四川盆地和中南半岛,MODIS fAOD年均分布高值区主要位于中南半岛,Himawari-8 fAOD年均值则普遍较低.MODIS FMF和fAOD季节平均分布呈现出夏秋高、春冬低的趋势,Himawari-8 FMF和fAOD季节平均分布则呈现出春秋高、夏冬低的特征,高值区的位置和量值均有明显的季节变化.     

Scale-dependent relations in land cover biophysical dynamics

The exploration of the relationships between plant biotic dynamics and scale can reveal important information on ecosystem spatial organization by addressing preservation of information integrity in upscaling/downscaling procedures of land-surface parameterization for environmental modeling applications. Scale-dependent relations of vegetation dynamics are investigated in this study by using emergent biophysical characteristics obtained through a predictive multidimensional model of vegetation anomalies derived from remote-sensing observations. In particular, the analysis is focused on the spatial organization of some phenological parameters including deterministic variations (seasonal range, interannual variability, jump discontinuities) and stochastic components (plant memory, spatial correlations). The analysis is performed using MODIS-based Normalized Difference Vegetation Index (NDVI) 16-day composites for the period from March 2000 to December 2006 over Italy at different levels of spatial aggregation (1-8 km). Scale-dependences of the statistical moments of the phenological parameters are quantified through simple power laws for five distinct vegetated land covers. Results suggest that some biophysical characteristics, especially deterministic components, show no preferential spatial scale for important coverage. In particular, broad-leaved forests and natural grasslands are characterized by deterministic and low-distance spatial components well explained by scale relationships, which are modulated by possible spatiotemporal dynamics of climatic drivers. Agricultural lands show high scale-dependent relations on short-term biophysical memory sources and low-distance spatial components of phenology likely related to hierarchical interactions of anthropogenic and ecological processes; whereas mixed patterns of croplands and natural areas generally present no consistent scaling relations.     

基于MODIS数据反演江浙皖地区气溶胶光学厚度

气溶胶是气候变化和大气污染的重要影响因素。人们发现卫星遥感为大面积获取气溶胶光学厚度提供了手段,同时卫星遥感的气溶胶光学厚度弥补了地面观测空间覆盖不足的缺陷。文章首先介绍了使用暗像元法反演气溶胶光学厚度的算法和计算流程,利用传统的暗像元法和改进的暗像元法(即V5.2算法)反演江浙皖地区(29～33°N;116～120°E)气溶胶光学厚度的空间分布,并对两种算法所得结果进行比较与分析。结果表明:暗像元法基本可以反映出该区域气溶胶光学厚度的空间分布特点,尤其是在浓密植被区卫星反演得到的结果与(AERONET)太阳光度计的观测值基本相近。但是在城市地区,该算法得到的结果与观测值存在一定的偏差,有待于进一步改善。     

基于MODIS数据的地表组分温度反演研究

组分温度的反演是当前定量遥感的一个难点。与众多的陆面温度遥感模型相比,成熟的组分温度遥感模型相对较少。通过对近地面热红外辐射能量的线性展开,建立了MODIS多波段植被、土壤组分温度反演模型。该模型将组分温度与地表温度定量联系起来,模型中所涉及到的参数充分考虑到研究区湿地环境的特点。在计算组分温度时,首先利用单窗算法得到的MODIS陆面温度反演模型计算地表温度,然后由所建立的组分温度模型计算植被、土壤温度。选用2005年10月31日的鄱阳湖地区MODIS数据试验,与实测的植被、土壤温度相比,反演的组分温度的误差在15~21℃;通过对模型参数的敏感性分析,表明该模型具有一定的稳定性。实践证明,该方法能够有效实现组分温度的分离,是一种组分温度反演的较好方法。     

2008年冬—2009年春辽宁省干旱的遥感监测与大气结构分析

MODIS的多波段及高时空分辨率特征有利于对大面积干旱区域的动态监测。2008年10月下旬至2009年2月中旬我国中东部和北方地区十多个省市遭遇了严重干旱。论文选取2009年初干旱较严重的辽宁省作为研究区域,使用热惯量法提取MODIS数据的干旱信息,识别出干旱区域和干旱程度。为了深入分析导致此次干旱的大气结构特征和机理,从天气形势、斜温图(Skew-T)两方面揭示了干旱发生期间影响旱区的大气风向风速、温度、湿度及大气能量的结构特征。研究表明东北冷涡强大稳定而导致的干冷空气路径维持,整层大气的温度-露点差较大,西北风使来源地水汽稀少,稳定的大气层结及干下沉气流等大气结构特征是引起辽宁省严重干旱的重要原因。     

青藏高原短波辐射分布式模拟及其时空分布

论文基于太阳辐射参数化传输模型,结合MODIS每日两次的大气产品和DEM,构建了太阳短波辐射分布式模型,对青藏高原2007年的太阳直接辐射、散射辐射与总辐射分布状况进行了模拟,并利用研究区站点实测值对模型精度进行了验证,其中日值数据直接辐射的相关性分别为0.72(拉萨)和0.82(格尔木),散射辐射分别为0.71(拉萨)和0.70(格尔木),总辐射相关性大都在0.70以上;旬值数据实测值与模拟值的相关性大都在0.90以上。模拟结果表明:实际天气情形下青藏高原年平均直接辐射量为4 244 MJ/m2,年平均散射辐射量为2 348 MJ/m2,年平均总辐射量为6 592 MJ/m2。直接辐射与总辐射的空间分布主要受纬度地带性与垂直地带性的影响,且地形对地表短波辐射的影响大于纬度的影响;散射辐射的空间分布主要取决于当地的地形起伏与大气状况。     

应用MODIS进行赤潮影响因子分析的研究与探讨

遥感技术已经成为赤潮监测的重要手段之一,目前,国内外已有多项应用遥感技术对赤潮成功监测的实例。然而,关于对赤湖的成因进行分析和研究的报道,在国内外学术文献中仍十分稀少。本文总结了赤潮监测的常见方法及引起赤潮发生的可能因素,对MODIS应用于赤潮探测技术的优势进行了分析,并在此基础上提出一种基于MODIS数据的综合海水水色、叶绿素a浓度、海水表面温度、悬浮泥沙含量多种因素的赤潮影响因子分析方法。对赤潮成因的分析将有利于实现赤潮的预测,从而尽可能减少赤潮暴发所造成的损失。     

Spatiotemporal Evaluation of Simulated Evapotranspiration and Streamflow over Texas Using the WRF‐Hydro‐RAPID Modeling Framework

This study assesses a large‐scale hydrologic modeling framework (WRF‐Hydro‐RAPID) in terms of its high‐resolution simulation of evapotranspiration (ET) and streamflow over Texas (drainage area: 464,135 km²). The reference observations used include eight‐day ET data from MODIS and FLUXNET, and daily river discharge data from 271 U.S. Geological Survey gauges located across a climate gradient. A recursive digital filter is applied to decompose the river discharge into surface runoff and base flow for comparison with the model counterparts. While the routing component of the model is pre‐calibrated, the land component is uncalibrated. Results show the model performance for ET and runoff is aridity‐dependent. ET is better predicted in a wet year than in a dry year. Streamflow is better predicted in wet regions with the highest efficiency ~0.7. In comparison, streamflow is most poorly predicted in dry regions with a large positive bias. Modeled ET bias is more strongly correlated with the base flow bias than surface runoff bias. These results complement previous evaluations by incorporating more spatial details. They also help identify potential processes for future model improvements. Indeed, improving the dry region streamflow simulation would require synergistic enhancements of ET, soil moisture and groundwater parameterizations in the current model configuration. Our assessments are important preliminary steps towards accurate large‐scale hydrologic forecasts.