Earth Sciences Division (ESD) Department of Energy (DOE) Lawrence Berkeley National Laboratory (LBNL)

Climate Analog Tracker: Where will the world's climates go with global warming?

Click around anywhere on the map to explore.

Direction: Where will the climate be

Future greenhouse gas emissions:




One way of visualizing how climate change will effect ecosystems is to ask where those ecosystems would have to move to stay in the most similar climate possible.  This is shown in these dynamic maps above, which calculate the similarity of different climates, called climate analogs1, and show how they move around in different global warming scenarios.

This method shows where a place's current climate will be going to in the future, or where a place's future climate will be coming from. The map colors show how similar the climate of a place and time is to that of the reference location (the place where you click), with darker meaning more similar. The way this is calculated here is to take each of twelve average monthly values of temperature and precipitation at each point in space and time (from a climate model), compare these to the values at the reference location and time, and normalize them by their intrinsic variability to calculate a metric representing the relative overall differences in climate (the Standard Euclidean Distance, or SED). To find where the climate is “going to,” the reference time is fixed at the first 20-year period, and all the differences for each subsequent period are calculated relative to that; for finding where it is “coming from” the reference time shifts to be each period shown, and the differences are all taken from the first period relative to that moving reference.

The arrows connect the reference climate to its most similar analog, and so shows the direction and distance that ecosystems would have to move to best maintain their current climate. The two directions can be useful for answering different questions—for example, if you are interested in finding the most similar spot in today's climate for a given ecosystem may move to, then you should follow where the climate is going to; if you want to know what ecosystems will be moving in to occupy a specific place, then you should follow the path of where the climate is coming from.  Where no dark areas appear, there are no good climate analogs.  In the "going to" sense, this means that there are no places for that climate to go to, so that particular climate will disappear; in the "coming from" sense, it means that there are no places where the climate can come from, so what will be there will be a novel climate1. The arrows themselves can be used to ask how ecosystem properties, such as carbon storage, may shift as a result of climate change2.

The climate projections here are based on simlations performed by the CESM1 model, with greenhouse gas concentrations following the historical record through 2005, and three possible scenarios used for the upcoming IPCC Fifth Assessment Report, from 2006-2099. The model simulations used here have a resolution of about 1 degree latitude and longitude (about 70 miles, or 110 km), so finer-scale changes than that cannot be seen here. In the low "RCP2.6" scenario, CO2 concentrations reach 421 ppm by 2100; in the moderate "RCP4.5" scenario CO2 reaches 538 ppm by 2100; and in the high "RCP8.5" scenario CO2 reaches 936 ppm. Current (2013) CO2 concentrations are about 400 ppm.

References

1. Williams JW, Jackson ST, Kutzbach JE. (2007) Projected distributions of novel and disappearing climates by 2100 AD. Proceedings of the National Academy of Sciences. doi:10.1073/pnas.0606292104

2. Koven, C. (2013) Boreal carbon loss due to poleward shift in low-carbon ecosystems. Nature Geoscience. doi: 
10.1038/ngeo1801

 

Ackowledgements

This research was supported by the Director, Office of Science, Office of Biological and Environmental Research of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 as part of their Climate and Earth System Modeling Program.

 

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Web page by Charlie Koven and Mike Godwin. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 United States License.