首页> 外文OA文献 >Analysis of the linkages between rainfall and land surface conditions in the West African monsoon through CMAP, ERS-WSC, and NOAA-AVHRR data - art. no. D24115
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Analysis of the linkages between rainfall and land surface conditions in the West African monsoon through CMAP, ERS-WSC, and NOAA-AVHRR data - art. no. D24115

机译:通过CMAP,ERS-WSC和NOAA-AVHRR数据分析西非季风中降雨与地面条件之间的联系-艺术。没有。 D24115

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摘要

[1] The European Remote Sensing Wind Scatterometer (ERS-WSC) backscattering coefficient, NOAA Advanced Very High Resolution Radiometer (NOAA-AVHRR) Normalized Difference Vegetation Index (NDVI), and Climate Prediction Center Merged Analysis Precipitation ( CMAP) precipitation data sets are studied over the period August 1991 to December 2000 to document ( 1) the interannual and intra-annual evolutions of vegetation photosynthetic activity and soil-vegetation water content over West Africa and ( 2) their two-way links with precipitation. Over the Sahel, at interannual timescales the strongest relationships between vegetation, soil moisture, and precipitation are observed from July to October and when 1-month lag is considered between the parameters. This delay reflects the vegetation response time to the moisture pulses that follow precipitation events. The high correlation between NDVI and sigma_0 at interannual timescales confirms the importance of vegetation in the backscattering coefficient. However, sigma_0 shows stronger statistical links with precipitation, suggesting that this product contains additional useful information related in particular to upper soil moisture. Over Guinea, large differences are observed between the two remote sensing products, and their relationship with precipitation at interannual timescales is weaker. Sigma_ 0 is significantly linked to precipitation from July to November, whereas NDVI does not show any significant relationship with precipitation. NDVI and sigma_0 serial correlations over the Sahel and Guinea suggest that a 2-month memory usually characterizes vegetation photosynthetic activity and soil-vegetation water content anomalies. However, anomalies disappearance in winter then reappearance in the following spring also suggests an interseason memory held by deep soil moisture reservoirs and deep-rooted plants. A composite analysis reveals that the wettest Sahelian rainy seasons were preceded by positive anomalies of soil-vegetation water content over Guinea from winter to spring. Cross correlations and Granger causality analyses partly relate these winter to spring land surface anomalies to those recorded in precipitation during the previous autumn. Spring soil-vegetation water content anomalies strengthen the meridional gradient of soil-vegetation water content over the subcontinent. This gradient is thought to contribute to the gradient of entropy that drives the West African monsoon.
机译:[1]欧洲遥感风散射仪(ERS-WSC)的后向散射系数,NOAA高级超高分辨率辐射仪(NOAA-AVHRR)归一化植被指数(NDVI)和气候预测中心合并分析降水(CMAP)降水数据集是在1991年8月至2000年12月期间进行了研究,以记录(1)西非植被光合作用和土壤-植被含水量的年际和年际演变,以及(2)它们与降水的双向联系。在萨赫勒地区,在每年的时间尺度上,从7月到10月观察到植被,土壤水分和降水之间的最强关系,并且在两个参数之间考虑了1个月的滞后。该延迟反映了植被对降水事件之后的水分脉冲的响应时间。 NDVI和sigma_0在年际时标之间的高度相关性确认了植被在后向散射系数中的重要性。但是,sigma_0与降水之间的统计联系更强,这表明该产品还包含其他有用信息,特别是与上部土壤湿度有关的信息。在几内亚上空,观测到两种遥感产品之间的差异很大,而且它们与年际时间尺度上的降水之间的关系较弱。 Sigma_0与7月至11月的降水显着相关,而NDVI与降水没有显着关系。萨赫勒地区和几内亚地区的NDVI和sigma_0序列相关性表明,通常需要2个月的记忆才能表征植被的光合活动和土壤-植被含水量异常。然而,冬季异常消失,然后在第二年春天再次出现,这也暗示了由深层土壤水分储集层和根深蒂固的植物所保持的季节间记忆。一项综合分析显示,从冬季到春季,几内亚上的土壤-植被含水量呈正异常,随后是萨赫勒最湿润的雨季。互相关和格兰杰因果关系分析部分将这些冬季与春季土地表面异常与上一秋季降水记录中的异常相关。春季土壤-植物水分含量异常增强了次大陆上土壤-植物水分含量的子午梯度。人们认为该梯度有助于驱动西非季风的熵梯度。

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