Very high resolution interpolated climate surfaces for global land areas
Very high resolution interpolated climate surfaces for global land areas
复制标题
DOI：
10.1002/joc.1276
复制
发表时间：
2005-12-01
期刊：
影响因子：
--
通讯作者：
Jarvis, A
中科院分区：
文献类型：
--
作者：
Hijmans, RJ;Cameron, SE;Jarvis, A
我们开发了全球陆地区域（不包括南极洲）的插值气候表面，空间分辨率为30弧秒（通常称为1公里的空间分辨率）。考虑的气候要素是月降水量和平均、最低和最高温度。输入数据是从各种来源收集的，并在可能的情况下，仅限于1950-2000年期间的记录。我们使用ANUSPLIN软件包中实现的薄板平滑样条算法进行插值，使用纬度、经度和海拔作为自变量。我们量化的不确定性所产生的输入数据和插值映射气象站的密度，海拔偏差的气象站，海拔变化的网格单元格内，并通过数据分区和交叉验证。海拔偏差在高纬度地区往往是负的（台站低于预期），但在热带地区是正的。在山区和采样率低的地区，不确定性最高。数据划分显示，孤立岛屿（如太平洋岛屿）的表面高度不确定。将海拔和气候数据汇总到10弧分分辨率显示网格单元内存在巨大变化，说明了高分辨率表面的价值。与现有的数据集在10弧分分辨率的比较表明，总体协议，但在某些地区的显着变化。通过与美国的两套高分辨率数据集进行比较，还发现了地方差异很大的地区，特别是山区。与以前的全球气候学相比，我们的数据具有以下优点：数据的空间分辨率更高（400倍或更高）;使用了更多的气象站记录;使用了改进的高程数据;可以获得更多关于数据中不确定性空间模式的信息。由于现有气候站的总体密度较低，我们的表面无法捕捉到分辨率为1公里的所有可能发生的变化，特别是山区的降水量。在今后的工作中，可通过基于知识的方法和纳入额外的协变量，特别是通过遥感获得的层来捕捉这种变化。版权所有（c）2005皇家气象学会。
We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1-km spatial resolution). The climate elements considered were monthly precipitation and mean, minimum, and maximum temperature. Input data were gathered from a variety of sources and, where possible, were restricted to records from the 1950-2000 period. We used the thin-plate smoothing spline algorithm implemented in the ANUSPLIN package for interpolation, using latitude, longitude, and elevation as independent variables. We quantified uncertainty arising from the input data and the interpolation by mapping weather station density, elevation bias in the weather stations, and elevation variation within grid cells and through data partitioning and cross validation. Elevation bias tended to be negative (stations lower than expected) at high latitudes but positive in the tropics. Uncertainty is highest in mountainous and in poorly sampled areas. Data partitioning showed high uncertainty of the surfaces on isolated islands, e.g. in the Pacific. Aggregating the elevation and climate data to 10 arc min resolution showed an enormous variation within grid cells, illustrating the value of high-resolution surfaces. A comparison with an existing data set at 10 arc min resolution showed overall agreement, but with significant variation in some regions. A comparison with two high-resolution data sets for the United States also identified areas with large local differences, particularly in mountainous areas. Compared to previous global climatologies, ours has the following advantages: the data are at a higher spatial resolution (400 times greater or more); more weather station records were used; improved elevation data were used; and more information about spatial patterns of uncertainty in the data is available. Owing to the overall low density of available climate stations, our surfaces do not capture of all variation that may occur at a resolution of 1 km, particularly of precipitation in mountainous areas. In future work, such variation might be captured through knowledge-based methods and inclusion of additional co-variates, particularly layers obtained through remote sensing. Copyright (c) 2005 Royal Meteorological Society.