A semi‐objective circulation pattern classification scheme for the semi‐arid Northeast Brazil,International Journal of Climatology

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A semi‐objective circulation pattern classification scheme for the semi‐arid Northeast Brazil
International Journal of Climatology ( IF 3.5 ) Pub Date : 2020-05-04 , DOI: 10.1002/joc.6608
Patrick Laux _{1,

2} , Brian Böker ₂ , Eduardo Sávio Martins ₃ , Francisco Vasconcelos Junior ₃ , Vincent Moron ₄ , Tanja Portele ₁ , Christof Lorenz ₁ , Andreas Philipp ₂ , Harald Kunstmann _{1,

2}

Affiliation

Funding information Seasonal water re-sources management in semi-arid regions: Transfer of regionalized global information to practice (SaWaM), Grant/Award Number: 02WGR1421A Abstract The semi-arid Northeast Brazil (NEB) is just recovering from a very severe water crisis induced by a multiyear drought. With this crisis, the question of water resources management has entered the national political agenda, creating an opportunity to better prepare the country to deal with future droughts. In order to improve climate predictions, and thus preparedness in NEB, a circulation pattern (CP) classification algorithm offers various options. Therefore, the main objective of this study was to develop a computer aided CP classification based on the Simulated ANnealing and Diversified RAndomization clustering (SANDRA) algorithm. First, suitable predictor variables and cluster domain setting are evaluated using ERA-Interim reanalyses. It is found that near surface variables such as geopotential at 1,000 hPa (GP1,000) or mean sea level pressure (MSLP) should be combined with horizontal wind speed at the upper 700 hPa level (UWND700). A 11-cluster solution is favoured due to the trade-offs between interpretability of the cluster centroids and the explained variances of the predictors. Second, occurrence and transition probabilities of this 11-cluster solution of GP1,000 andUWND700 are analysed, and typical CPs, which are linked to dry and wet conditions in the region are identified. The suitability of the new classification to be potentially applied for statistical downscaling or CPconditional bias correction approach is analysed. The CP-conditional cumulative density functions (CDFs) exhibit discriminative power to separate between wet and dry conditions, indicating a good performance of the CP approach.

中文翻译：

巴西东北部半干旱区半客观环流模式分类方案

资金信息半干旱地区的季节性水资源管理：将区域化全球信息转化为实践 (SaWaM)，赠款/奖励编号：02WGR1421A 摘要半干旱的巴西东北部 (NEB) 刚刚从非常严重的水危机中恢复过来多年干旱造成的。随着这场危机，水资源管理问题已进入国家政治议程，为该国更好地应对未来干旱创造了机会。为了改进气候预测，从而改进 NEB 的准备工作，环流模式 (CP) 分类算法提供了多种选择。因此，本研究的主要目标是开发一种基于模拟退火和多样化随机化聚类 (SANDRA) 算法的计算机辅助 CP 分类。第一的，使用 ERA-Interim 再分析评估合适的预测变量和聚类域设置。研究发现，近地表变量，例如 1,000 hPa (GP1,000) 的位势或平均海平面压力 (MSLP) 应与 700 hPa 高位 (UWND700) 的水平风速相结合。由于集群质心的可解释性和预测变量的解释方差之间的权衡，11 集群解决方案受到青睐。其次，分析了 GP1,000 和 UWND700 的 11 星团解的发生和转变概率，并确定了与该地区干湿条件相关的典型 CP。分析了可能应用于统计降尺度或 CP 条件偏差校正方法的新分类的适用性。

更新日期：2020-05-04

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