Simulated 50% rain-snow air temperature thresholds (linear regression)

Map of simulated 50% rain-snow air temperature thresholds based on a bivariate binary logistic regression phase prediction model applied to 27 years of MERRA-2 reanalysis data. The probability of snowfall was predicted for each precipitation event in the record as a function of air temperature and relative humidity. For each MERRA-2 grid cell, the probabilities were binned by 1°C air temperature bins to produce a snow frequency curve. The 50% rain-snow air temperature threshold was then calculated using a linear regression on snow frequency between 0.5°C and 6.5°C. This approach was used for grid cells without enough snow and rain events to compute the threshold using a hyperbolic tangent.基于应用于27年MERRA-2再分析数据的双变量二元逻辑回归相变预测模型，构建得到50%雨-雪转换气温阈值的模拟分布图。本研究以气温与相对湿度为影响因子，对数据集记录中的每一次降水事件的降雪概率开展预测。针对每个MERRA-2网格单元，将各网格内的降雪概率以1℃为间隔进行分箱统计，以此生成降雪频率曲线。随后通过对0.5℃至6.5℃区间内的降雪频率序列进行线性回归分析，计算得到50%雨-雪转换气温阈值。对于降雪与降雨事件样本量不足、无法通过上述线性回归方法计算阈值的网格单元，则采用双曲正切函数完成阈值求解。