Selecting climate change scenarios using impact‐relevant sensitivities

Abstract

Climate impact studies often require the selection of a small number of climate scenarios. Ideally, a subset would have simulations that both (1) appropriately represent the range of possible futures for the variable/s most important to the impact under investigation and (2) come from global climate models (GCMs) that provide plausible results for future climate in the region of interest. We demonstrate an approach to select a subset of GCMs that incorporates both concepts and provides insights into the range of climate impacts. To represent how an ecosystem process responds to projected future changes, we methodically sample, using a simple sensitivity analysis, how an ecosystem variable responds locally to projected regional temperature and precipitation changes. We illustrate our approach in the Pacific Northwest, focusing on (a) changes in streamflow magnitudes in critical seasons for water management and (b) changes in annual vegetation carbon.

Projected changes in future climate over the Midwest and Great Lakes region using downscaled CMIP5 ensembles

“…Regardless of downscaling approach, the selection of GCM scenarios to be used for regional impact analysis can be crucial because the overall quality of products deriving from the downscaling process is ultimately determined by these primary inputs (Brekke et al, 2008;Mote and Salathé, 2010;Gu et al, 2015;McSweeney et al, 2015;Vano et al, 2015).…”

Incorporating Multidimensional Probabilistic Information Into Robustness‐Based Water Systems Planning

“…Water Resources Research possible (Gao & Bryan, 2015;Kasprzyk et al, 2013;Vano et al 2015). In addition, the relative importance of the uncertain factors on unacceptable or vulnerable outcomes can be identified using a regional sensitivity analysis, sometimes called Monte Carlo filtering (Pianosi et al, 2016).…”

Using cumulative potential recharge for selection of GCM projections to force regional groundwater models: A Nebraska Sand Hills example

“…For modeling purposes, research institutions and management agencies rely on already available studies of GR derived from of Global Circulation Model (GCM) projections. In such cases, development of GR projections is just a stage of a larger project that must consider other drivers of change, such as land use and resource demands (Snover et al, 2013;Vano et al, 2015). Thus, sets of various projections are constrained by the capacity to assess and incorporate available climate change scenarios into the planning, or modeling, process.…”

“…Then, the characterization of the sensitivity of the regional groundwater systems to GR changes, and analyses of the modeling uncertainty, becomes more efficient. Despite this need to rationalize the number of climate scenarios in impact-modeling assessments, there is a limited focus toward methods of effectively using GCM-derived information (e.g., Vano et al, 2015). Starting from pioneering work by Rosenberg et al (1999), groundwater recharge and groundwater modeling studies vary by the numbers of GCM projections used (Table 1).…”