van Hooidonk Ruben, Maynard Jeffrey Allen, Liu Yanyun, Lee Sang-Ki
NOAA Atlantic Oceanographic and Meteorological Laboratory, 4301 Rickenbacker Causeway, Miami, FL, 33149, USA.
Cooperative Institute of Marine and Atmospheric Sciences, Rosenstiel School of Marine & Atmospheric Science, University of Miami, 4600 Rickenbacker Causeway, Miami, FL, 33149, USA.
Glob Chang Biol. 2015 Sep;21(9):3389-401. doi: 10.1111/gcb.12901. Epub 2015 Apr 1.
Projections of climate change impacts on coral reefs produced at the coarse resolution (1°) of Global Climate Models (GCMs) have informed debate but have not helped target local management actions. Here, projections of the onset of annual coral bleaching conditions in the Caribbean under Representative Concentration Pathway (RCP) 8.5 are produced using an ensemble of 33 Coupled Model Intercomparison Project phase-5 models and via dynamical and statistical downscaling. A high-resolution (11 km) regional ocean model (MOM4.1) is used for the dynamical downscaling. For statistical downscaling, sea surface temperature (SST) means and annual cycles in all the GCMs are replaced with observed data from the ~4-km NOAA Pathfinder SST dataset. Spatial patterns in all three projections are broadly similar; the average year for the onset of annual severe bleaching is 2040-2043 for all projections. However, downscaled projections show many locations where the onset of annual severe bleaching (ASB) varies 10 or more years within a single GCM grid cell. Managers in locations where this applies (e.g., Florida, Turks and Caicos, Puerto Rico, and the Dominican Republic, among others) can identify locations that represent relative albeit temporary refugia. Both downscaled projections are different for the Bahamas compared to the GCM projections. The dynamically downscaled projections suggest an earlier onset of ASB linked to projected changes in regional currents, a feature not resolved in GCMs. This result demonstrates the value of dynamical downscaling for this application and means statistically downscaled projections have to be interpreted with caution. However, aside from west of Andros Island, the projections for the two types of downscaling are mostly aligned; projected onset of ASB is within ±10 years for 72% of the reef locations.
全球气候模型(GCMs)在约1°的粗分辨率下得出的气候变化对珊瑚礁影响的预测,为相关辩论提供了参考,但无助于确定当地的管理行动目标。在此,利用33个耦合模式比较计划第5阶段模式的集合,并通过动力降尺度和统计降尺度,得出了在代表性浓度路径(RCP)8.5情景下加勒比地区年度珊瑚白化状况开始时间的预测。动力降尺度使用了一个高分辨率(约11公里)的区域海洋模型(MOM4.1)。对于统计降尺度,所有GCMs中的海表面温度(SST)均值和年循环被来自约4公里分辨率的美国国家海洋和大气管理局探路者SST数据集的观测数据所取代。所有三种预测的空间模式大致相似;所有预测中年度严重白化开始的平均年份为2040 - 2043年。然而,降尺度预测显示,在单个GCM网格单元内,许多地方年度严重白化(ASB)开始的时间相差10年或更多。在适用这种情况的地区(例如佛罗里达、特克斯和凯科斯群岛、波多黎各以及多米尼加共和国等)的管理人员可以确定那些相对而言虽属暂时但却是避难所的地点。与GCM预测相比,巴哈马群岛的两种降尺度预测有所不同。动力降尺度预测表明,ASB开始时间更早,这与区域洋流预计的变化有关,而这一特征在GCMs中未得到体现。这一结果证明了动力降尺度在此应用中的价值,也意味着对统计降尺度预测必须谨慎解读。然而,除了安德罗斯岛以西,两种降尺度预测大多是一致的;72%的珊瑚礁地点ASB预计开始时间在±10年之内。