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Optimized split-window coefficients for deriving surface temperatures from inland water bodies

机译:优化的分割窗口系数,可从内陆水体得出地表温度

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Large inland water bodies constituting lakes, reservoirs and inland-seas are excellent proxy indicators for climate change. Using thermal infrared satellite data, a recent study found that a global set of inland water bodies showed significant warming in seasonal nighttime Lake Surface Water Temperatures (LSWTs) between 1985 and 2009. Split-window land surface temperature (LST) retrievals are typically tuned for a broad range of land surface emissivities and global atmospheric conditions, and are not optimized for inland water body surfaces, whereas split-window sea-surface temperatures (SSTs) are only tuned for a single emissivity (water), but over ocean atmospheres. Over inland water bodies, these two approaches can lead to region dependent errors in LSWTs, spurious trends, and inconsistencies between sensors in the long-term temperature record of inland water bodies. To address this issue, the primary goal of this paper was to develop a methodology for deriving a set of optimized split-window coefficients, individually tuned for the regional atmospheric conditions of 169 globally distributed, saline and freshwater inland water bodies from multiple satellite sensors including the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua; Along Track Scanning Radiometer (ATSR) including ATSR-1, ATSR-2, AATSR; and Advanced Very High Resolution Radiometer (AVHRR-3). The new Inland Water-body Surface Temperature (IWbST) v1.0 algorithm was applied to Terra MODIS and Advanced Along Track Scanning Radiometer (AATSR) data and validated with in situ water temperature data from sites with widely contrasting atmospheric conditions: Lake Tahoe in California/Nevada, a high-elevation cool and dry site, and the Salton Sea in California, a low-elevation warm and humid site. Analysis showed improved accuracy in LSWTs in terms of bias and RMSE when compared to the standard MODIS LST and AATSR SST products. For example, the IWbST RMSE at Salton Sea was reduced by 0.4. K when compared to the operational MODIS product. For the AATSR data, the IWbST RMSE was reduced by 0.36. K at Tahoe and 0.29. K at Salton Sea when compared to results obtained using the operational AATSR split-window coefficients. The IWbST improvements are significant in relation to the current accuracy of water temperature retrievals from space (< 0.5. K), and will enable the derivation of long-term, accurate LSWTs consistently across multiple sensors for climate studies.
机译:构成湖泊,水库和内陆海域的大型内陆水体是气候变化的优秀替代指标。利用热红外卫星数据,最近的一项研究发现,一组全球内陆水体在1985年至2009年之间的季节性夜间湖面水温(LSWT)方面出现了明显的变暖。通常对分窗式地表温度(LST)进行调整范围广泛的陆地表面发射率和全球大气条件,并且未针对内陆水体表面进行优化,而分窗海表温度(SST)仅针对单个发射率(水)进行了调整,但针对海洋大气进行了调整。在内陆水体上,这两种方法可能导致内河水体长期温度记录中的小波WT的区域相关误差,伪趋势和传感器之间的不一致。为了解决这个问题,本文的主要目的是开发一种方法,用于从一组卫星传感器(包括169个全球分布的盐和淡水内陆水体)中,针对一组169个区域分布的大气条件,分别对一组优化的分窗系数进行优化。 Terra和Aqua上的中分辨率成像光谱仪(MODIS);沿轨道扫描辐射计(ATSR),包括ATSR-1,ATSR-2,AATSR;和先进的超高分辨率辐射计(AVHRR-3)。新的内陆水体表面温度(IWbST)v1.0算法已应用于Terra MODIS和先进的沿航迹扫描辐射计(AATSR)数据,并使用来自大气条件差异较大的地点的原位水温数据进行了验证:加利福尼亚的太浩湖/内华达州是高海拔的凉爽干燥地区,而加利福尼亚州的萨尔顿海则是低海拔的温暖潮湿地区。分析显示,与标准MODIS LST和AATSR SST产品相比,LSWT的偏差和RMSE精度更高。例如,萨尔顿海的IWbST RMSE降低了0.4。与可操作的MODIS产品相比为K。对于AATSR数据,IWbST RMSE降低了0.36。 Tahoe处的K和0.29。与使用AATSR分割窗口系数获得的结果相比较时,索尔顿海的K。 IWbST的改进与当前从太空取回水温的精确度(<0.5。K)相比具有重要意义,并将能够在用于气候研究的多个传感器上一致地得出长期,准确的LSWT。

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