Worldwide alteration of lake mixing regimes in response to climate change View Full Text


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Article Info

DATE

2019-04

AUTHORS

R. Iestyn Woolway, Christopher J. Merchant

ABSTRACT

Lakes hold much of Earth’s accessible liquid freshwater, support biodiversity and provide key ecosystem services to people around the world. However, they are vulnerable to climate change, for example through shorter durations of ice cover, or through rising lake surface temperatures. Here we use a one-dimensional numerical lake model to assess climate change impacts on mixing regimes in 635 lakes worldwide. We run the lake model with input data from four state-of-the-art model projections of twenty-first-century climate under two emissions scenarios. Under the scenario with higher emissions (Representative Concentration Pathway 6.0), many lakes are projected to have reduced ice cover; about one-quarter of seasonally ice-covered lakes are projected to be permanently ice-free by 2080–2100. Surface waters are projected to warm, with a median warming across lakes of about 2.5 °C, and the most extreme warming about 5.5 °C. Our simulations suggest that around 100 of the studied lakes are projected to undergo changes in their mixing regimes. About one-quarter of these 100 lakes are currently classified as monomictic—undergoing one mixing event in most years— and will become permanently stratified systems. About one-sixth of these are currently dimictic—mixing twice per year—and will become monomictic. We conclude that many lakes will mix less frequently in response to climate change. Many lakes that currently mix once or twice a year may become permanently stratified or mix only once in a warming climate, suggest numerical simulations of lake mixing regimes. Mixing regimes are most affected by ice-cover duration and surface temperatures. More... »

PAGES

271-276

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41561-019-0322-x

DOI

http://dx.doi.org/10.1038/s41561-019-0322-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112850922


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41561-019-0322-x'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41561-019-0322-x'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41561-019-0322-x'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41561-019-0322-x'


 

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