Evaluating the capability of soil enthalpy, soil moisture and soil temperature in predicting seasonal precipitation
Evaluating the capability of soil enthalpy, soil moisture and soil temperature in predicting seasonal precipitation
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评价土壤焓、土壤湿度和土壤温度预测季节降水的能力
DOI：
10.1007/s00376-017-7006-5
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发表时间：
2018
影响因子：
5.8
通讯作者：
Shanlei Sun
中科院分区：
文献类型：
--
作者：
Changyu Zhang;Haishan Chen;Shanlei Sun
土壤热能(H)包含了地表水热过程中土壤水分(W)和土壤温度(T)的综合作用。在本研究中，使用多元线性回归方法研究了HTO和T的敏感性。结果表明，由于土壤冰的影响，T对H的贡献总体上是正的，而W则表现出不同的(正或负)影响。例如，如果土壤中含有更多的冰，则W对土壤的贡献是负的；然而，在土壤冰融化后，W对土壤的贡献是正的。特别是，由于深层土壤(即第五层)的冬季年际变化较低，他对TOW比TOW更敏感。此外，为了比较H、WAND和TIN降水(P)预报的潜力，选择了对H、WAND和TIN具有相似敏感性的黄淮流域(HHB)和东南中国(SEC)。分析表明，尽管h-Pad和T-P相关系数的空间分布相似，但前者的值始终高于后者。此外，H为HHB和SEC上的预测提供了最有效的信号，即5月初夏(6月)P之间的显著领先相关。综上所述，H综合了TH的影响，是一个自变量，相对于单个陆面因素(如TANW)，H在监测地表加热和改进季节性预测方面具有更强的能力。
Soil enthalpy (H) contains the combined effects of both soil moisture (w) and soil temperature (T) in the land surface hydrothermal process. In this study, the sensitivities ofHtowandTare investigated using the multi-linear regression method. Results indicate thatTgenerally makes positive contributions toH, while w exhibits different (positive or negative) impacts due to soil ice effects. For example,wnegatively contributes toHif soil contains more ice; however, after soil ice melts,wexerts positive contributions. In particular, due to lowerwinterannual variabilities in the deep soil layer (i.e., the fifth layer),His more sensitive toTthan tow. Moreover, to compare the potential capabilities ofH,wandTin precipitation (P) prediction, the Huanghe–Huaihe Basin (HHB) and Southeast China (SEC), with similar sensitivities ofHtowandT, are selected. Analyses show that, despite similar spatial distributions ofH–PandT–Pcorrelation coefficients, the former values are always higher than the latter ones. Furthermore,Hprovides the most effective signals forPprediction over HHB and SEC, i.e., a significant leading correlation between MayHand early summer (June)P. In summary,H, which integrates the effects ofTandwas an independent variable, has greater capabilities in monitoring land surface heating and improving seasonalPprediction relative to individual land surface factors (e.g.,Tandw).