Orrego R, Abarca-Del-Río R, Ávila A, Morales L
Departamento de Suelos y Recursos Naturales, Facultad de Agronomía, Universidad de Concepción, Concepción, Chile ; Scientific and Technological Bioresource Nucleus, Universidad de La Frontera, Temuco, Chile.
Departamento de Geofísica, Universidad de Concepción, Concepción, Chile.
Springerplus. 2016 Sep 28;5(1):1669. doi: 10.1186/s40064-016-3157-6. eCollection 2016.
Climate change scenarios are computed on a large scale, not accounting for local variations presented in historical data and related to human scale. Based on historical records, we validate a baseline (1962-1990) and correct the bias of A2 and B2 regional projections for the end of twenty-first century (2070-2100) issued from a high resolution dynamical downscaled (using PRECIS mesoscale model, hereinafter DGF-PRECIS) of Hadley GCM from the IPCC 3rd Assessment Report (TAR). This is performed for the Araucanía Region (Chile; 37°-40°S and 71°-74°W) using two different bias correction methodologies. Next, we study high-resolution precipitations to find monthly patterns such as seasonal variations, rainfall months, and the geographical effect on these two scenarios. Finally, we compare the TAR projections with those from the recent Assessment Report 5 (AR5) to find regional precipitation patterns and update the Chilean `projection. To show the effects of climate change projections, we compute the rainfall climatology for the Araucanía Region, including the impact of ENSO cycles (El Niño and La Niña events). The corrected climate projection from the high-resolution dynamical downscaled model of the TAR database (DGF-PRECIS) show annual precipitation decreases: B2 (-19.19 %, -287 ± 42 mm) and A2 (-43.38 %, -655 ± 27.4 mm per year. Furthermore, both projections increase the probability of lower rainfall months (lower than 100 mm per month) to 64.2 and 72.5 % for B2 and A2, respectively.
气候变化情景是在大尺度上计算的，没有考虑历史数据中呈现的与人类尺度相关的局部变化。基于历史记录，我们验证了一个基线（1962 - 1990年），并校正了来自政府间气候变化专门委员会第三次评估报告（TAR）的哈德利全球气候模式（Hadley GCM）的高分辨率动力降尺度（使用PRECIS中尺度模式，以下简称DGF - PRECIS）得出的21世纪末（2070 - 2100年）A2和B2区域预测的偏差。这是针对阿劳卡尼亚地区（智利；南纬37° - 40°，西经71° - 74°）使用两种不同的偏差校正方法进行的。接下来，我们研究高分辨率降水以找到月度模式，如季节变化、降雨月份以及这两种情景下的地理效应。最后，我们将TAR预测与最近的第五次评估报告（AR5）中的预测进行比较，以找到区域降水模式并更新智利的“预测”。为了展示气候变化预测的影响，我们计算了阿劳卡尼亚地区的降雨气候学，包括厄尔尼诺 - 南方涛动（ENSO）周期（厄尔尼诺和拉尼娜事件）的影响。来自TAR数据库的高分辨率动力降尺度模型（DGF - PRECIS）校正后的气候预测显示年降水量减少：B2情景下为（-19.19%，-287 ± 42毫米），A2情景下为（-43.38%，-655 ± 27.4毫米/年）。此外，两种预测都将低降雨月份（每月低于100毫米）的概率分别提高到B2情景下的64.2%和A2情景下的72.5%。
