CJCZO -- GIS/Map Data -- EEMT -- Santa Catalina Mountains -- (2010-2010)

Yearly effective energy and mass transfer (EEMT) (MJ m−2 yr−1) was calculated for the Catalina Mountains by summing the 12 monthly values. Effective energy and mass flux varies seasonally, especially in the desert southwestern United States where contemporary climate includes a bimodal precipitation distribution that concentrates in winter (rain or snow depending on elevation) and summer monsoon periods. This seasonality of EEMT flux into the upper soil surface can be estimated by calculating EEMT on a monthly basis as constrained by solar radiation (Rs), temperature (T), precipitation (PPT), and the vapor pressure deficit (VPD): EEMT = f(Rs,T,PPT,VPD). Here we used a multiple linear regression model to calculate the monthly EEMT that accounts for VPD, PPT, and locally modified T across the terrain surface. These EEMT calculations were made using data from the PRISM Climate Group at Oregon State University (www.prismclimate.org). Climate data are provided at an 800-m spatial resolution for input precipitation and minimum and maximum temperature normals and at a 4000-m spatial resolution for dew-point temperature (Daly et al., 2002). The PRISM climate data, however, do not account for localized variation in EEMT that results from smaller spatial scale changes in slope and aspect as occurs within catchments. To address this issue, these data were then combined with 10-m digital elevation maps to compute the effects of local slope and aspect on incoming solar radiation and hence locally modified temperature (Yang et al., 2007). Monthly average dew-point temperatures were computed using 10 yr of monthly data (2000–2009) and converted to vapor pressure. Precipitation, temperature, and dew-point data were resampled on a 10-m grid using spline interpolation. Monthly solar radiation data (direct and diffuse) were computed using ArcGIS Solar Analyst extension (ESRI, Redlands, CA) and 10-m elevation data (USGS National Elevation Dataset [NED] 1/3 Arc-Second downloaded from the National Map Seamless Server at seamless.usgs.gov). Locally modified temperature was used to compute the saturated vapor pressure, and the local VPD was estimated as the difference between the saturated and actual vapor pressures. The regression model was derived using the ISOHYS climate data set comprised of approximately 30-yr average monthly means for more than 300 weather stations spanning all latitudes and longitudes (IAEA).

年度有效能量与物质转移（EEMT）(MJ m−2 yr−1）通过累加12个月的数值计算得出，以Catalina山脉为例。有效能量与物质通量呈现季节性变化，尤其在沙漠西南部美国地区，该地区的当代气候包括双峰降水分布，降水集中在冬季（雨或雪，取决于海拔）和夏季季风时期。这种EEMT通量对土壤上层表面的季节性影响可以通过基于太阳辐射（Rs）、温度（T）、降水量（PPT）和蒸汽压亏缺（VPD）的月度EEMT计算进行估算：EEMT = f(Rs,T,PPT,VPD)。在此，我们采用多重线性回归模型计算考虑了VPD、PPT和地形表面局部修正温度的月度EEMT。这些EEMT计算是基于俄勒冈州立大学PRISM气候组（www.prismclimate.org）提供的数据进行的。气候数据以800米空间分辨率提供，用于输入降水量、平均最低温度和最高温度；以4000米空间分辨率提供露点温度（Daly等人，2002年）。然而，PRISM气候数据并未考虑由较小空间尺度上坡度和方位变化导致的局部EEMT变化，这种变化通常发生在流域内。为了解决这一问题，这些数据随后与10米数字高程图相结合，以计算局部坡度和方位对入射太阳辐射的影响，从而计算局部修正温度（Yang等人，2007年）。利用2000年至2009年10年的月度数据计算了月平均露点温度，并将其转换为蒸汽压。降水量、温度和露点数据使用10米网格进行样条插值重采样。月度太阳辐射数据（直接辐射和散射辐射）使用ArcGIS Solar Analyst扩展（ESRI，Redlands，CA）和10米高程数据（从国家地图无缝服务器seamless.usgs.gov下载的USGS国家高程数据集[NED] 1/3弧秒）进行计算。局部修正温度用于计算饱和蒸汽压，而局部VPD被估计为饱和蒸汽压与实际蒸汽压之差。回归模型是基于包含超过300个气象站、覆盖所有经纬度的约30年平均月平均值的ISOHYS气候数据集得出的（IAEA）。