Downscaling reveals diverse effects of anthropogenic climate warming on the potential for local environments to support malaria transmission

被引：10

作者：

Paaijmans, Krijn P. ^{[1
,2
,3
]}

Blanford, Justine I. ^{[4
]}

Crane, Robert G. ^{[5
]}

Mann, Michael E. ^{[6
,7
]}

Ning, Liang ^{[6
,7
,8
]}

Schreiber, Kathleen V. ^{[9
]}

Thomas, Matthew B. ^{[1
,2
]}

机构：

[1] Penn State Univ, Ctr Infect Dis Dynam, University Pk, PA 16802 USA

[2] Penn State Univ, Dept Entomol, University Pk, PA 16802 USA

[3] Univ Barcelona, Hosp Clin, Barcelona Ctr Int Hlth Res CRESIB, Barcelona, Spain

[4] Penn State Univ, GeoVISTA Ctr, Dept Geog, University Pk, PA 16802 USA

[5] Penn State Univ, Dept Geog, AESEDA, University Pk, PA 16802 USA

[6] Penn State Univ, Dept Meteorol, University Pk, PA 16802 USA

[7] Penn State Univ, Earth & Environm Syst Inst, University Pk, PA 16802 USA

[8] Univ Massachusetts, Northeast Climate Sci Ctr, Dept Geosci, Amherst, MA 01003 USA

[9] Millersville Univ Pennsylvania, Dept Geog, Millersville, PA 17551 USA

来源：

CLIMATIC CHANGE | 2014年 / 125卷 / 3-4期

关键词：

EAST-AFRICAN HIGHLANDS; TEMPERATURE; DYNAMICS; FUTURE; PROJECTIONS; RESURGENCE; MOSQUITOS; RISK; AIR;

D O I：

10.1007/s10584-014-1172-6

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

The potential impact of climate warming on patterns of malaria transmission has been the subject of keen scientific and policy debate. Standard climate models (GCMs) characterize climate change at relatively coarse spatial and temporal scales. However, malaria parasites and the mosquito vectors respond to diurnal variations in conditions at very local scales. Here we bridge this gap by downscaling a series of GCMs to provide high-resolution temperature data for four different sites and show that although outputs from both the GCM and the downscaled models predict diverse but qualitatively similar effects of warming on the potential for adult mosquitoes to transmit malaria, the predicted magnitude of change differs markedly between the different model approaches. Raw GCM model outputs underestimate the effects of climate warming at both hot (3-fold) and cold (8-12 fold) extremes, and overestimate (3-fold) the change under intermediate conditions. Thus, downscaling could add important insights to the standard application of coarse-scale GCMs for biophysical processes driven strongly by local microclimatic conditions.

引用

页码：479 / 488

页数：10

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