Mapping Climate under Varying Emission Scenarios (from NCAR)

Four tiers or RCPs were developed, and each is named according to the level of radiative forcing (enhanced greenhouse effect or warming) anticipated by the year 2100.

The four RCPs include one peak pathway in which radiative forcing reaches 8.5 Watts per square meter (Wm-2) by the year 2100; two intermediate “stabilization pathways” in which radiative forcing stabilizes at 6 Wm-2 and 4.5 Wm-2 after the year 2100, and one low pathway in which radiative forcing peaks around 3 Wm- 2 before 2100 and then declines. This low scenario describes GHG emissions that drop below zero around 2070 and continue to decrease (carbon-negative) into the future.

For more information http://sedac.ipcc-data.org/ddc/ar5_scenario_process/index.html

Radiative forcing: cumulative measure of human emissions of GHGs from all sources expressed in Watts per square meter.

1. Working with multidimensional data (netCDF)

NetCDF is a true multidimensional data format very commonly used to represent atmospheric data. The data that we will use for this exercise contains information on air temperature anomalies. A climate anomaly is the difference between a future modeled climate when compared to the present climate.

Anomalies are useful to determine the magnitude of change. The variables in this netCDF file are:

-tas: Air Temperature Anomaly (change).

-lat, long, and time: are the dimensions

-atas20ymin: ensemble minimum

-atas20ymax: ensemble maximum

An ensemble is the average of several runs in which each run is assigned slightly different initial conditions resulting in different future outcomes.

In this netCDF file, each year is actually a 20-year average centered on the year displayed.

1.1 Add netCDF data through Multidimension Toolbox

Open ArcMap, browse to the map document D:\GISClimatedata\exercise4\maps\rcp.mxd

This map displays the continental US and contains four layers. The layer RCP 4.5 is the most carbon-neutral emissions scenario and the layer RCP 2.6 is a carbon-negative emissions scenario. These data display air temperature anomalies. A temperature anomaly is the difference between a plausible future temperature when compared to present day climate. Anomalies show change and are a good way to display how temperature change varies in space and time.

Turn on the layer RCP 4.5. Notice the difference in these two layers.

The RCP 4.5 layer uses warmer colors to display a warmer future than the RCP 2.6 layer.

Turn off the layer RCP 4.5 Annual Average Temperature Anomaly.

Open the Properties window for layer RCP 2.6 Annual Average Temperature Anomaly and click on the NetCDF tab.

Notice that the time is 4/19/2091.

These maps show the annual air temperature anomaly for 2091 (2081-2100). The RCP 4.5 map indicates hotter temperatures than the RCP 2.6 map. This is due to the different greenhouse gas concentrations used by each scenario. RCPs should not be viewed as forecasts or absolute bonds. They are representations of plausible alternative scenarios of the future, but are not predictions or forecasts. No single RCP is intended as a best guess or most likely outcome. In this exercise, you will look at three scenarios: A high emissions scenario - RCP 8.5; a neutral emissions scenario - RCP 4.5 and a low emissions scenario - RCP 2.6. By looking at the range of possible future climates, one can better understand and prepare for future climate change.

Close the Layer Property window.

Notice that we are missing the high emissions scenario (RCP 8.5) and RCP 6.0 for comparison. In the next few steps you will add a netCDF file of RCP 8.5 and RCP 6.0 that contain 70 years of future temperature projections.

For this exercise, you will add these as a raster dataset.