globalchange  > 气候变化事实与影响
DOI: 10.1016/j.scitotenv.2019.01.167
WOS记录号: WOS:000458408200033
论文题名:
Future precipitation variability during the early rainfall season in the El Yunque National Forest
作者: Ramseyer, Craig A.1; Miller, Paul W.2; Mote, Thomas L.3
通讯作者: Ramseyer, Craig A.
刊名: SCIENCE OF THE TOTAL ENVIRONMENT
ISSN: 0048-9697
EISSN: 1879-1026
出版年: 2019
卷: 661, 页码:326-336
语种: 英语
英文关键词: Hydroclimatology ; Puerto Rico ; Climate change ; Climate modeling ; Artificial neural networks
WOS关键词: CLIMATE-CHANGE IMPACT ; PUERTO-RICO ; CARIBBEAN RAINFALL ; LUQUILLO MOUNTAINS ; TROPICAL ATLANTIC ; TEMPERATURE ; REANALYSIS ; SATELLITE ; PACIFIC ; DROUGHT
WOS学科分类: Environmental Sciences
WOS研究方向: Environmental Sciences & Ecology
英文摘要:

El Yunque National Forest, situated in the Luquillo Mountains of northeast Puerto Rico, is home to a wide range of climate-sensitive ecosystems and forest types. In particular, these ecosystems are highly sensitive to changes in the hydroclimate, even on short time scales. Current global climate models (GCMs) predict coarse-scale reductions in precipitation across the Caribbean prompting the need to investigate future fine-scale hydroclimate variability in the Luquillo Mountains. This research downscales coarse-resolution GCM RCP8.5 predictions from the IPCC CMIP5 project to the local scale to better assess future rainfall variability during the most critical period of the annual hydroclimate cycle, the early rainfall season (ERS). An artificial neural network (ANN) is developed using five field variables (1000-, 850-, 700-, and 500-hPa specific humidity and 1000-700-hPa bulk wind shear) and four derived precipitation forecasting parameters from the ERA-Interim reanalysis. During the historical period (1985-2016), the ANN predicts a binary dry (<5 mm) versus wet (>= 5 mm) day outcome with 92% percent accuracy.


When the historical inputs are replaced with bias-corrected data from four CMIP5 GCMs, the downscaled ensemble mean indicates a 7.2% increase in ERS dry-day frequency by mid-century (2041-2060), yielding an ERS dry-day percentage of 70% by mid-century. The results presented here show that the decrease in precipitation and wet-days is, at least in part, due to an increase in 1000-700-hPa bulk wind shear and a less favorable thermodynamic environment driven by increased mid-tropospheric warming and a stronger trade wind inversion. By regressing ERS total precipitation against dry-day frequency (R-2 = 0.95), the predicted mid-century dry-day proportion corresponds to a similar to 200-mm decrease in seasonal precipitation. In contrast, the ensemble predicts a dry-day frequency recovery back towards the historical climatological mean by end-century (2081-2100). (C) 2019 Elsevier B.V. All rights reserved.


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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/134339
Appears in Collections:气候变化事实与影响

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作者单位: 1.Salisbury Univ, Dept Geog & Geosci, Salisbury, MD USA
2.Louisiana State Univ, Dept Oceanog & Coastal Sci, Baton Rouge, LA 70803 USA
3.Univ Georgia, Dept Geog, Athens, GA 30602 USA

Recommended Citation:
Ramseyer, Craig A.,Miller, Paul W.,Mote, Thomas L.. Future precipitation variability during the early rainfall season in the El Yunque National Forest[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2019-01-01,661:326-336
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