Quadtree aggregations of WHEEL forecast model

World Hybrid Earthquake Estimates based on Likelihood scores (WHEEL) is a model obtained from a multiplicative log-linear combination of TEAM with the Smoothed Seismicity (KJSS) model of Kagan and Jackson (2011). The forecast model is proposed and described in the following publication: Bayona, J.A., Savran, W., Strader, A., Hainzl, S., Cotton, F. and Schorlemmer, D., 2021. Two global ensemble seismicity models obtained from the combination of interseismic strain measurements and earthquake-catalogue information. <em>Geophysical Journal International</em>, <em>224</em>(3), pp.1945-1955. Multi-resolution grids are generated using Quadtree. The grids are generated based on earthquake catalog data and strain data points. Each file in the repository represents a forecast aggregated on a particular grid. The forecast files are naming is derived from the criteria used to generate the grid. For example, 'N' stands for number earthquakes, 'SN' stands for Strain data points, and 'L' stands for maximum zoom-level allowed for the grid. The forecast is represented in the following format: Tile depth_min depth_max 5.95 6.05 6.15 6.25 ... '000' 0.0 70.0 0.00715 0.00693 0.00628 0.00573 ...基于似然得分的全球混合地震估计（World Hybrid Earthquake Estimates based on Likelihood scores, WHEEL）是通过将TEAM模型与Kagan和Jackson（2011）提出的平滑地震活动性模型（Smoothed Seismicity, KJSS）进行乘性对数线性组合得到的模型。该预测模型的详细说明与提出见于以下学术论文：Bayona, J.A.、Savran, W.、Strader, A.、Hainzl, S.、Cotton, F. 与 Schorlemmer, D.，2021年。《两种基于震间应变测量与地震目录信息融合的全球集合地震活动性模型》，《国际地球物理期刊》（*Geophysical Journal International*），第224卷第3期，第1945-1955页。 多分辨率网格采用四叉树（Quadtree）算法生成，网格构建依托地震目录数据与应变数据点完成。该数据集仓库中的每个文件均对应特定网格上聚合得到的地震预测结果。预测文件的命名规则由生成网格时所采用的参数决定，例如：'N'代表地震数量，'SN'代表应变数据点数量，'L'代表网格允许的最大缩放层级。 预测结果采用如下格式存储： Tile 深度最小值 深度最大值 5.95 6.05 6.15 6.25 … 示例行：'000' 0.0 70.0 0.00715 0.00693 0.00628 0.00573 …