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Journal Article

Examining current bias and future projection consistency of globally downscaled climate projections commonly used in climate impact studies

Lucas Berio Fortini; Lauren R. Kaiser; Abby G. Frazier; Thomas W. Giambelluca
Climatic Change · Vol. 176, Issue 12 · 2023

Abstract

The associated uncertainties of future climate projections are one of the biggest obstacles to overcome in studies exploring the potential regional impacts of future climate shifts. In remote and climatically complex regions, the limited number of available downscaled projections may not provide an accurate representation of the underlying uncertainty in future climate or the possible range of potential scenarios. Consequently, global downscaled projections are now some of the most widely used climate datasets in the world. However, they are rarely examined for representativeness of local climate or the plausibility of their projected changes. Here we explore the utility of two such global datasets (CHELSA and WorldClim2) in providing plausible future climate scenarios for regional climate change impact studies. Our analysis was based on three steps: (1) standardizing a baseline period to compare available global downscaled projections with regional observation-based datasets and regional downscaled datasets; (2) bias correcting projections using a single observation-based baseline; and (3) having controlled differences in baselines between datasets, exploring the patterns and magnitude of projected climate shifts from these datasets to determine their plausibility as future climate scenarios, using Hawaiʻi as an example region. Focusing on mean annual temperature and precipitation, we show projected climate shifts from these commonly used global datasets not only may vary significantly from one another but may also fall well outside the range of future scenarios derived from regional downscaling efforts. As species distribution models are commonly created from these datasets, we further illustrate how a substantial portion of variability in future species distribution shifts can arise from the choice of global dataset used. Hence, projected shifts between baseline and future scenarios from these global downscaled projections warrant careful evaluation before use in climate impact studies, something rarely done in the existing literature.

Bibliographic Information

JournalClimatic Change
PublisherSpringer
Publication Date2023-12-01
Publication Year2023
Volume176
Issue12
Document TypeJournal Article
Print ISSN0165-0009
eISSN1573-1480
DOI10.1007/s10584-023-03623-z

Access Information

NARA Access Coverage1977-01-01~Current
Journal Homepagehttps://www.springer.com/journal/10584
Publisher PageOpen Publisher Page
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