An Empirical Study of Geographic and Seasonal Variations in Diurnal Temperature Range
An Empirical Study of Geographic and Seasonal Variations in Diurnal Temperature Range
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DOI：
10.1175/2010jcli3215.1
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发表时间：
2010-06-15
影响因子：
4.9
通讯作者：
Forster, Piers M.
中科院分区：
文献类型：
--
作者：
Jackson, Lawrence S.;Forster, Piers M.
陆地表面气温日较差（DTR）随地理和季节变化而变化。作者使用广义加性模型（GAM），一种非线性回归方法研究了这些变化。以DTR为响应变量，气象和陆面参数作为解释变量。回归曲线相关的DTR偏离其平均值的气象和陆地表面变量的值。云量，土壤湿度，距离内陆，太阳辐射和海拔高度相结合的解释变量，在合奏的84 GAM模型，使用的数据分为7种植被类型和12个月。该集合解释了DTR的80%的地理和季节变化。植被类型和云量表现出最强的DTR的关系。短波辐射，距离内陆，海拔与DTR呈正相关，而云量和土壤湿度呈负相关。对地表能量收支的单独分析表明，净长波辐射的变化代表了太阳和水文变化对DTR的影响。研究发现，植被及其相关的气候是重要的DTR变化除了气候的影响，云量，土壤水分，太阳辐射。地面净长波辐射是DTR变化的一个强有力的诊断因子，可以解释热带地区DTR季节变化的95%以上。
The diurnal temperature range (DTR) of surface air over land varies geographically and seasonally. The authors have investigated these variations using generalized additive models (GAMs), a nonlinear regression methodology. With DTR as the response variable, meteorological and land surface parameters were treated as explanatory variables. Regression curves related the deviation of DTR from its mean value to values of the meteorological and land surface variables. Cloud cover, soil moisture, distance inland, solar radiation, and elevation were combined as explanatory variables in an ensemble of 84 GAM models that used data grouped into seven vegetation types and 12 months. The ensemble explained 80% of the geographical and seasonal variation in DTR. Vegetation type and cloud cover exhibited the strongest relationships with DTR. Shortwave radiation, distance inland, and elevation were positively correlated with DTR, whereas cloud cover and soil moisture were negatively correlated. A separate analysis of the surface energy budget showed that changes in net longwave radiation represented the effects of solar and hydrological variation on DTR. It is found that vegetation and its associated climate is important for DTR variation in addition to the climatic influence of cloud cover, soil moisture, and solar radiation. It is also found that surface net longwave radiation is a powerful diagnostic of DTR variation, explaining over 95% of the seasonal variation of DTR in tropical regions.