A Visualization Approach for Projecting Future Climate Distributions in North America
Conservation and natural resource managers require information about potential future climate changes for the areas they manage, in terms that are relevant for the specific biotic and environmental resources likely to be affected by climate change. We produced a suite of data sets that provide managers with climate and climate-derived data and a visualization approach that allows managers to map where 1) a managed area's potential future climate is located on today's landscape (i.e., the locations of the modern analogues of future climate) and 2) the areas to which the present climate (and habitat) of managed areas are projected to move. We produced downscaled climate data from historical (1901-2000) data sets and from future (2001-2100) climate simulations, generated by both coupled atmosphere-ocean general circulation models (AOGCMs) and regional climate models (e.g., RegCM3). Data were downscaled at a relatively coarse resolution (e.g., ~10-km) for North America, and at a finer resolution (e.g., ~1-km) for the contiguous US and Alaska.
Based on discussions with land managers, we used the climate data as input to existing environmental models to derive additional variables, such as bioclimate variables (e.g., moisture indices), that are required for management of specific resources (e.g., vegetation and habitat). These data can be incorporated into an online web interface that allows managers to download the underlying climate data and to produce maps of future climate analogues. This research addresses the USGS Science Strategy science directions “Understanding Ecosystems and Predicting Ecosystem Change” and “Climate Variability and Change” (USGS Circular 1309). It also supports USGS responsibilities under the U.S. Climate Change Science Program (CCSP) Strategic Plan (2003) Question 8.3 (Product 3) and Goal 3 of the CCSP 2008-2010 Revised Research Plan, by enhancing our understanding of potential climate change effects on important ecological systems.
- Source: USGS Sciencebase (id: 4f834286e4b0e84f608680e7)
Conservation and natural resource managers require information about potential future climate changes for the areas they manage, in terms that are relevant for the specific biotic and environmental resources likely to be affected by climate change. We produced a suite of data sets that provide managers with climate and climate-derived data and a visualization approach that allows managers to map where 1) a managed area's potential future climate is located on today's landscape (i.e., the locations of the modern analogues of future climate) and 2) the areas to which the present climate (and habitat) of managed areas are projected to move. We produced downscaled climate data from historical (1901-2000) data sets and from future (2001-2100) climate simulations, generated by both coupled atmosphere-ocean general circulation models (AOGCMs) and regional climate models (e.g., RegCM3). Data were downscaled at a relatively coarse resolution (e.g., ~10-km) for North America, and at a finer resolution (e.g., ~1-km) for the contiguous US and Alaska.
Based on discussions with land managers, we used the climate data as input to existing environmental models to derive additional variables, such as bioclimate variables (e.g., moisture indices), that are required for management of specific resources (e.g., vegetation and habitat). These data can be incorporated into an online web interface that allows managers to download the underlying climate data and to produce maps of future climate analogues. This research addresses the USGS Science Strategy science directions “Understanding Ecosystems and Predicting Ecosystem Change” and “Climate Variability and Change” (USGS Circular 1309). It also supports USGS responsibilities under the U.S. Climate Change Science Program (CCSP) Strategic Plan (2003) Question 8.3 (Product 3) and Goal 3 of the CCSP 2008-2010 Revised Research Plan, by enhancing our understanding of potential climate change effects on important ecological systems.
- Source: USGS Sciencebase (id: 4f834286e4b0e84f608680e7)