The Effects of Climate Change on Seasonal Snowpack and the Hydrology of the Northeastern and Upper Midwest United States

The potential effects of climate change on the snowpack of the northeastern and upper Midwest United States are assessed using statistically downscaled climate projections from an ensemble of 10 climate models and a macroscale hydrological model. Climate simulations for the region indicate warmer-th...

Full description

Saved in:
Bibliographic Details
Published in:Journal of climate 2016-09, Vol.29 (18), p.6527-6541
Main Authors: Demaria, Eleonora M. C., Roundy, Joshua K., Wi, Sungwook, Palmer, Richard N.
Format: Article
Language:English
Subjects:
20th century
21st century
Air temperature
Archives & records
Basins
Climate change
Climate effects
Climate models
Climate science
Datasets
Ecosystems
General circulation models
Hydrologic models
Hydrology
Precipitation
River ecology
Seasonal precipitation
Seasons
Simulation
Snow
Snow cover
Snow-water equivalent
Snowpack
Spring
Spring (season)
Statistical analysis
Stream discharge
Stream flow
Temperature
Trends
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The potential effects of climate change on the snowpack of the northeastern and upper Midwest United States are assessed using statistically downscaled climate projections from an ensemble of 10 climate models and a macroscale hydrological model. Climate simulations for the region indicate warmer-than-normal temperatures and wetter conditions for the snow season (November–April) during the twenty-first century. However, despite projected increases in seasonal precipitation, statistically significant negative trends in snow water equivalent (SWE) are found for the region. Snow cover is likely to migrate northward in the future as a result of warmer-than-present air temperatures, with higher loss rates in northern latitudes and at high elevation. Decreases in future (2041–95) snow cover in early spring will likely affect the timing of maximum spring peak streamflow, with earlier peaks predicted in more than 80% of the 124 basins studied.
ISSN:0894-8755
1520-0442
DOI:10.1175/JCLI-D-15-0632.1