Heavy rainfall in Paraguay during the 2015-2016 austral summer: causes and sub-seasonal-to-seasonal predictive skill
Heavy rainfall in Paraguay during the 2015-2016 austral summer: causes and sub-seasonal-to-seasonal predictive skill
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DOI：
10.1175/jcli-d-17-0805.1
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发表时间：
2018-07
影响因子：
4.9
通讯作者：
James Doss‐Gollin;Á. Muñoz;S. Mason;M. Pasten
中科院分区：
文献类型：
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作者：
James Doss‐Gollin;Á. Muñoz;S. Mason;M. Pasten
在2015/16年夏季，巴拉圭、阿根廷和巴西南部的巴拉圭河流域发生严重洪灾，造成17万多人流离失所。这些洪水是由巴拉圭河下游流域反复出现的暴雨造成的。来自南美低空急流的增强的湿气流入和与斜压系统相关的局部辐合的交替序列有利于中尺度对流活动和增强的降水。这些环流模式受到非常强的厄尔尼诺事件的跨时间尺度相互作用的支持，在第4和第5阶段异常持续的Madden-Julian振荡，以及在中南部大西洋存在偶极子SST异常。同时使用季节性和次季节性强降雨预测，可以提前两至四周为决策者提供有关这些洪水事件开始的有用信息。11月初的季节性预报成功地表明，12月至2月巴拉圭南部和巴西的强降雨概率（第90百分位）增加。原始次季节性强降雨预测表现出有限的技能，在领先的时间超过前两个预测周，但模型输出统计方法，涉及主成分回归大幅提高了空间分布的技能，第3周相对于其他方法进行测试，包括扩展逻辑回归。持续监测影响该地区降雨的气候驱动因素，并使用经统计校正的强降水季节性和次季节性预报，可能有助于改善该地区和其他地区的防洪工作。
During the austral summer 2015/16, severe flooding displaced over 170 000 people on the Paraguay River system in Paraguay, Argentina, and southern Brazil. These floods were driven by repeated heavy rainfall events in the lower Paraguay River basin. Alternating sequences of enhanced moisture inflow from the South American low-level jet and local convergence associated with baroclinic systems were conducive to mesoscale convective activity and enhanced precipitation. These circulation patterns were favored by cross-time-scale interactions of a very strong El Niño event, an unusually persistent Madden–Julian oscillation in phases 4 and 5, and the presence of a dipole SST anomaly in the central southern Atlantic Ocean. The simultaneous use of seasonal and subseasonal heavy rainfall predictions could have provided decision-makers with useful information about the start of these flooding events from two to four weeks in advance. Probabilistic seasonal forecasts available at the beginning of November successfully indicated heightened probability of heavy rainfall (90th percentile) over southern Paraguay and Brazil for December–February. Raw subseasonal forecasts of heavy rainfall exhibited limited skill at lead times beyond the first two predicted weeks, but a model output statistics approach involving principal component regression substantially improved the spatial distribution of skill for week 3 relative to other methods tested, including extended logistic regressions. A continuous monitoring of climate drivers impacting rainfall in the region, and the use of statistically corrected heavy precipitation seasonal and subseasonal forecasts, may help improve flood preparedness in this and other regions.