Map the effects of climate change on the ocean

Oceans play a vital role in regulating global climates. Ocean currents circulate warm and cold water, connecting distant regions of the planet, determining regional climates, creating biodiverse ecology, and influencing weather. The ocean has a much higher heat capacity than the land or atmosphere, which means that it heats and cools slowly, moderating the climates of coastal areas. Oceans absorb much of the sun's heat and much of the carbon dioxide created by burning fossil fuels.

However, the oceans are experiencing dramatic changes due to climate change. In addition to rising temperatures, the oceans are suffering from acidification and deoxygenation that threaten marine ecosystems. These effects extend to humans through severe weather, sea level rise, and depleted fisheries. In addition, the warmer the ocean gets, the less ability it has to moderate the effects of climate change on land. In this tutorial, you'll download, visualize, and compare data for three of the most important climate change stressors on the oceans: rising temperatures, acidification, and deoxygenation.

This tutorial was last tested on August 21, 2023, with ArcGIS Pro 3.1. If you're using a different version of ArcGIS Pro, you may encounter different functionality and results.

Requirements

• User, Publisher, or Administrator role in an ArcGIS organization (see options for software access)
• ArcGIS Pro (see options for software access)

Map change to ocean temperatures

In this tutorial, you'll map climate change projections from the Coupled Model Intercomparison Project version 6 (CMIP6). Climate models simulate earth systems to help scientists understand how climate has changed and how it will change in the future. CMIP combines the results of many climate models and is used in the assessment reports published by the Intergovernmental Panel on Climate Change (IPCC).

To start, you'll download and explore CMIP6 maps for sea surface temperatures. In ArcGIS Pro, you'll use this data to map temperatures from the recent past (1985–2014), projected temperatures for the future (2070–2099), and the temperature differences between these two time periods.

Download CMIP6 data

CMIP6 data is shared by the National Oceanic and Atmospheric Administration (NOAA) on their Climate Change Web Portal. The portal contains many datasets, so you'll configure the site's parameters to download maps specific to sea surface temperatures.

Note:

If you are unable to download the data following these steps, you can continue reading. Copies of the data will be provided later when they are required.

1. Go to NOAA's Climate Change Web Portal for CMIP6.
2. Under Select Data, for Experiment, choose SSP3-7.0.

   The Shared Socioeconomic Pathways (SSPs) are a set of scenarios used to model climate change. SSP3-7.0 models a future characterized by regional rivalry with high greenhouse gas emissions.

   

3. Under Select Data, for Shading and Contour or vector, choose Sea Surface Temperature.
4. Leave Model set to Average Of All Models and Statistic set to Anomaly.

   The data that you download will be in a multidimensional format, meaning that it can store multiple variables at once. One of the variables will be the anomaly: the difference between temperatures in the future and temperatures in the past.

5. Ensure that Future Climate is set to No.

   

   Next, you'll choose the time periods to compare.

6. Under Time Period, choose the following parameters:
   • Ensure that Season is set to Entire Year.
   • For Historical Period, choose 1985-2014.
   • For 21st Century Period, choose 2070-2099.
7. For Region, choose Global.

   

   You'll preview the data before you download it.

8. Near the top of the page, click Make Slideshow.

   The maps update. The map in the upper left corner represents mean sea surface temperatures from 1985 to 2014 in degrees Celsius.

   

   The map in the upper right corner shows the difference in mean sea surface temperature between the past (1985–2014) and the future (2070–2099), as projected by the CMIP6 model using the SSP3-7.0 scenario.

   

   Question 1: Which latitudes are projected to see the greatest change in sea surface temperature? How much temperature change is projected?

   Note:

   Answers are provided at the end of the tutorial.

9. Near the top of the page, click Download Data.
10. When the data is ready, click Click here to download the netCDF file.

    

11. Locate the downloaded .nc file on your computer.

    Note:

    Depending on your web browser, you may be prompted to choose where the file will be downloaded. Most browsers download to your computer's Downloads folder by default.

    

12. Rename the file temperature_1985_2014.nc.

    The data that you downloaded includes a map of sea surface temperatures in the past. You'll change the parameters and download another dataset that maps projected sea surface temperatures for the future.

13. On the climate change web portal site, for Future Climate, choose Yes.
14. Click Download Data and click Click here to download the netCDF file.
15. Rename the downloaded file temperature_2070_2099.nc.

Add multidimensional data to a map

You have downloaded two .nc files with global sea surface temperature data. Next, you'll add them to a map in ArcGIS Pro. One layer will map temperatures in the past, and the other will map temperatures in the future.

1. Download the OceanClimate .zip file and unzip it to a location on your computer, for example, drive C.
2. Locate and unzip the downloaded file on your computer. Inside the OceanClimate folder, double-click OceanClimate.aprx to open it in ArcGIS Pro.

   

3. If prompted, sign in with your ArcGIS account.

   Note:

   If you don't have access to ArcGIS Pro or an ArcGIS organizational account, see options for software access.

   A map appears, showing ocean currents in the Equal Earth projection.

   You may have many panes open in ArcGIS Pro. You'll reset the workspace so you are able to find the tools you need during this tutorial.

4. On the ribbon, click the View tab. In the Windows group, click Reset Panes and click Reset Panes for Mapping (Default).

   

   You'll add the temperature data you downloaded to this map. The temperature data is in a netCDF file, which is a multidimensional file format. When you add it to a map, you need to choose which variable (or dimension) to display. One way to do that is with the Subset Multidimensional Raster tool.

5. Above the ribbon, click Command Search.
6. Type subset. In the search results, click Subset Multidimensional Raster.

   

   The Geoprocessing pane appears.

7. For Input Multidimensional Raster, click the Browse button.

   

8. Browse to and choose the temperature_1985_2014.nc file that you downloaded earlier.

   Note:

   If you were unable to download the file, you can find a copy of it in the unzipped OceanClimate folder.

9. For Output Multidimensional Raster, type temperature_1985_2014 and press Tab.

   The file extension .crf is added to the output name. The output will be stored in the cloud raster format.

10. For Variables, uncheck anomaly. Check histclim.

    This variable will map the temperatures from the chosen time period, rather than the change in temperatures.

11. For Dimension Definition, choose All.

    

12. Click Run.

    A layer is added to the map. It represents mean sea surface temperatures between 1985 and 2014. The coldest waters are shown in blue and the warmest in red. In the Contents pane, the legend shows that mean temperatures ranged from -1.9 to 31.3 degrees Celsius.

    

    The map shows an expected pattern of cooler waters at higher latitudes and warmer waters at the equator. However, the currents also have a role to play.

13. On the map, compare the Ocean surface currents layer to the temperature_1985_2014.crf layer.

    

    Question 2: Describe how some of the temperature patterns visible on the map relate to ocean currents.

14. In the Contents pane, uncheck the Ocean surface currents layer to turn it off.

    

    Next, you'll map sea surface temperatures projected for the future.

15. In the Geoprocessing pane, update the following parameters:
    • For Input Multidimensional Raster, browse to and choose the temperature_2070_2099.nc file.
    • For Output Multidimensional Raster, type temperature_2070_2099 and press Tab.
    • For Variables, ensure histclim is checked.

    

16. Click Run.

    A new layer named temperature_2070_2099.crf is added to the map. It looks very similar to temperature_1985_2014.crf.

    

Compare sea surface temperatures for the past and future

Your map now has two layers representing sea surface temperatures, one that records mean values from the past, and one that projects mean values for the future, based on the SSP3.0-7 scenario. You'll compare these two layers visually and with charts to learn how climate change will affect sea surface temperatures.

1. In the Contents pane, turn the temperature_2070_2099.crf layer off and on to observe differences between it and the temperature_1985_2014.crf layer underneath.

   

   The changes are subtle, but visible. The map shows slightly more orange and less blue in the future.

2. In the Contents pane, compare the legends for the two layers.

   The minimum and maximum values are both higher in the 2070–2099 layer than in the 1985–2014 layer. This difference in values confirms that sea surface temperatures are rising, even if the difference is not clearly visible on the map.

   

   More meaningful differences might be visible on a chart.

3. In the Contents pane, right-click temperature_1985_2014.crf. Point to Create chart and click Histogram.

   

4. In the Chart Properties pane, for Number, choose Band 1. Under Statistics, check the Mean and Median check boxes.

   

5. Make another chart with the same settings for the temperature_2070_2099.crf layer.

   The two histograms look similar, both showing a bimodal distribution.

   

6. Switch between the two charts to compare their mean and median values.

   	Mean	Median
   1985–2014	12.8	12.3
   2070–2099	14.7	14.7

   Tip:

   You can read the Mean and Median values in both the chart view and the Chart Properties pane.

   Both values show an increase of about 2 degrees between the two time frames. While 2 degrees Celsius may not seem like a large number, this difference is enough to change ocean chemistry and affect biodiversity. Warming oceans also contribute to rising sea levels, shifts in weather patterns on land, and extreme weather events.

   Note:

   Read more about ocean warming on the Woods Hole Oceanographic institution (WHOI) website.

7. Close both charts and the Chart Properties pane.

Visualize change in sea surface temperatures

The ocean is not warming evenly. Some parts are experiencing more dramatic temperature increases than others. Next, you'll add a third layer that maps the differences between ocean temperatures in the past and the future.

1. In the Geoprocessing pane, update the following parameters:
   • For Output Multidimensional Raster, type temperature_change and press Tab.
   • For Variables, uncheck histclim and check anomaly.

   Note:

   You can choose either .nc file for the Input Multidimensional Raster parameter. Both contain the same anomaly data.

2. Click Run.

   A new layer appears on the map. Areas that are expected to see the most change (up to 4.8 degrees warmer) are shown in red. Areas that are expected to see the least change (1.3 degrees colder) are shown in blue. The polar regions have both the highest and the lowest change values.

   

   The color scheme of the temperature_change.crf layer is not applied evenly. The values range between -1.3 and 4.8. This means that the middle value is 1.73, not zero, so some areas on the map that are shown in blue and green colors give the impression of cooling when they are actually warming. You'll adjust the symbology so areas with no change (a value of 0) are shown in white, areas that are warming are shown in red, and areas that are cooling are shown in blue.

3. Close the Geoprocessing pane.
4. In the Contents pane, right-click temperature_change.crf and click Symbology.

   The Symbology pane appears.

   First, you'll choose a diverging color scheme to match the diverging nature of the data. Diverging color schemes have two contrasting colors on either end with a neutral color in the middle.

5. In the Symbology pane, click the Color scheme menu. Check the Show names check box.

   

6. Scroll to near the bottom of the list and click the Red-Blue (Continuous) color scheme.

   

7. Ensure that the Invert check box is checked.

   The map and the legend show higher values in red and lower values in blue.

   

   Next, you'll ensure that the white middle color is aligned with zero.

8. In the Symbology pane, ensure that Stretch type is set to Minimum Maximum.

   

   This setting ensures that the full range of the data maps to the full range of the color scheme.

9. In the lower half of the Symbology pane, for Statistics, choose Custom.

   You'll ensure that the Min and Max values are equally distanced from zero. Zero is the desired middle value because it represents a change in temperature of 0 degrees Celsius.

10. Copy the Max value, 4.80763292.

    

11. For Min, erase everything after the minus symbol and paste 4.80763292.

    

    The map updates. Now all values greater than 0 (areas that are warming) are shown in red and all values less than 0 (areas that are cooling) are shown in blue. Darker colors represent more intense change.

    

    The map is almost entirely red, indicating that almost all parts of the ocean are projected to warm over the next century. There are only a few areas along the coasts of Antarctica and in the fjords of Greenland that are a pale blue.

    The temperature_1985_2014.crf and temperature_2070_2099.crf layers could be compared to learn where the ocean was warming, but the temperature_change.crf layer visualizes the change more clearly.

12. In the Contents pane, turn on the Ocean surface currents layer.

    The maps you made earlier showed that ocean temperatures were mostly determined by latitude, but this map shows that how quickly temperatures are rising is greatly affected by ocean currents.

    

13. Turn off the Ocean surface currents layer.
14. Click the arrow next to Reference data to collapse the group layer.
15. On the Quick Access Toolbar, click Save to save the project.

    

So far in this tutorial, you have visually compared maps of sea surface temperatures for the past and future with each other, and with ocean currents. You learned how to preview and download CMIP6 climate model data, add netCDF data to a map, create charts, and configure raster symbology with a diverging color scheme centered on zero.

Map changes to ocean pH and dissolved oxygen

You have mapped projected changes to sea surface temperatures. Next, you'll map projected changes to two other ocean variables that are under stress due to climate change: dissolved oxygen and acidity. The data has already been provided in the ArcGIS Pro project, so you don't need to download more netCDF files, but you do need to apply a consistent symbology to the layers so all three variables can be compared fairly.

Visualize change in dissolved oxygen

Fish and other marine animals require dissolved oxygen to live, and even slight reductions in oxygen supply cause severe stress to ecosystems. Climate change has caused a decline in the oxygen content of the oceans. You'll visualize projected changes to dissolved oxygen from 1985–2014 to 2070–2099.

1. In the Contents pane, turn off all three temperature layers.
2. Click the arrow next to oxygen_change to expand the layer and view its legend. Turn the layer on.

   

   Note:

   Dissolved oxygen concentration in this map is measured in 0.001 molecules per cubic meter of water.

   The oxygen_change layer has some negative values (indicating decreased dissolved oxygen concentrations) and some positive values (indicating increased oxygen). You'll use a diverging color scheme for this layer so values of zero (indicating no change) are shown in white.

3. Open the Symbology pane for the oxygen_change layer.

   Tip:

   If the Symbology pane is already open, click the oxygen_change layer in the Contents pane. The Symbology pane updates to show properties for the selected layer.

4. For Color scheme, choose Red-Blue (Continuous).
5. Uncheck the Invert check box.

   

   Now, the areas where oxygen will increase are blue (suggesting a healthy ocean) and the areas where oxygen will decrease are red (suggesting an unhealthy one).

   

   This color scheme aligns with the one you chose for the temperature_change.crf layer, since areas of greater concern are both shown in red. Next, you'll center the color scheme on the white color.

6. In the Symbology pane, ensure that Stretch type is set to Minimum Maximum.
7. For Statistics, choose Custom. Change the Max value to 42.09399414.

   

   The map does not change dramatically in appearance, since the Min and Max values were already similar distances from zero.

   

   Question 3: Which parts of the ocean are projected to see the most deoxygenation? Which parts are projected to see the least?

   Note:

   Read more about ocean deoxygenation on the International Union for Conservation of Nature (IUCN) website.

Visualize change in pH

The pH scale ranges from 0 to 14 and measures the acidity or basicity of water. A pH of 7 is neutral, higher values are basic, and lower values are acidic. Seawater has a natural pH of about 8.1, but as the ocean absorbs more carbon dioxide, its pH is decreasing, making the ocean more acidic. The acidification of the ocean is already killing shellfish and corals.

You'll visualize projected changes to pH in the ocean from 1985–2014 to 2070–2099.

1. In the Contents pane, turn off the oxygen_change layer.
2. Expand the pH_change layer and turn it on.

   

   The symbology of the pH_change layer is difficult to read. The entire map appears orange because outliers in the data range are using most of the color scheme range. You'll adjust the symbology to show color variation and to match the color scheme of the other two change layers.

3. Open the Symbology pane for the pH_change layer.
4. For Color scheme, choose Red-Blue (Continuous).

   You'll use red to map lower values, since they represent higher acidification, and more danger to the health of the oceans. You'll use blue to represent higher values, or less change in acidity.

5. Uncheck the Invert check box.

   

   The map appears mostly blue. Next, you'll remove the influence of outliers on the color scheme.

6. For Stretch type, choose Percent Clip.

   

   This stretch type stretches the color scheme over a smaller part of the data range. The Min and Max numbers (both set to 2.000) indicate how much of the data range will be clipped. In this case, any values within 2 percent of the top or bottom of the data range will be considered outliers. They will draw with the darkest red or darkest blue, reserving most of the color scheme range for most of the data.

   The map updates to show a more dramatic pattern of dark reds in the arctic and dark blues at the equator.

   

7. Compare the map to its legend to confirm that the symbology makes sense.

   

   The diverging color scheme suggests that red areas will become more acidic, blue areas will become less acidic, and white areas will stay the same. However, the legend shows that all pixels have negative values. This means that all parts of the ocean will have a lower pH by the end of the century. Using any blue in this map will be misleading. You'll update the map so it only contains shades of red.

8. In the Symbology pane, click Color scheme and click Format color scheme.

   

   The Color Scheme Editor window appears.

9. In the Color Scheme Editor window, click the darkest blue color stop to select it. Click the Remove color button.

   

10. Click the Remove color button four more times to remove all of the blue color stops.

    The color scheme now ranges from dark red to white.

    

11. Click OK.

    The map now more accurately reflects projections for acidification of the oceans.

    

    Note:

    You can find more color schemes designed specifically for scientific ocean mapping at Oceanography Color Schemes. Learn how to add a style to ArcGIS Pro in this One Minute Map Hack video.

    Question 4: Which parts of the ocean are projected to see the most acidification? Which parts are projected to see the least?

    Note:

    Read more about ocean acidification at the NOAA website.

Compare results

Your work so far has determined that the oceans are projected to grow warmer and more acidic, and to contain less oxygen in the future. To finish the tutorial, you'll compare all three change layers to find areas where risk from all three climate change stressors is high.

1. In the Contents pane, collapse the temperature_2070_2099.crf and temperature_1985_2014.crf layers.

   

2. Turn the temperature_change.crf layer on and off to compare it to the pH_change layer.

   

3. Compare the temperature_change.crf layer to the oxygen_change layer.

   

4. Compare the oxygen_change layer to the pH_change layer.

   

   The three change layers have some similarities and some differences. The most dramatic changes are at either pole, areas of the map that are difficult to see on this projection. You'll convert the map to a global scene to view the polar regions more clearly.

5. On the ribbon, click the View tab.
6. In the View group, click Convert and click To Global Scene.

   

   In ArcGIS, maps are 2D and scenes are 3D. Global scenes represent the earth as a sphere and are more appropriate for visualizing the entire globe. Local scenes are necessary when you want to use a projected coordinate system.

   A new scene appears.

7. Click and drag on the globe to center your view over the north pole.

   

8. Turn the change layers on and off to compare them on the globe.

   The temperature_change.crf and oxygen_change layers show a similar pattern of dark reds rimming the Arctic Ocean, while only the pH_change layer shows dark reds over the north pole and along the east coast of Greenland.

   

   Change in dissolved oxygen (left), temperature (center), and pH (right).

   Question 5: What areas of the ocean are most at risk from all three climate change stressors?

9. Save the project.

Climate change is producing severe effects on the oceans, which are projected to continue into the future. However, these changes are not as simple as rising temperatures: global warming effects all ocean properties, including dissolved oxygen and pH level, and these effects are distributed unevenly over the earth. Mapping and comparing these ocean changes allows them to be better understood.

Note:

This tutorial only explores measurements on the surface of the ocean. Temperature, pH, and dissolved oxygen also vary by ocean depth. Try the tutorial Visualize and explore coral reef habitats with voxels to learn how to visualize three-dimensional ocean data.

In this tutorial, you learned the following skills:

• How to download CMIP6 climate model data
• How to add netCDF data to a map in ArcGIS Pro using the Subset Multidimensional Raster tool
• How to create charts and compare mean and median values across layers
• How to configure raster symbology with a diverging color scheme
• How to convert a map to a global scene

Question answers

1. Which latitudes are projected to see the greatest change in sea surface temperature? How much of a temperature change is projected?

   Northern waters, especially those between 35 and 80 degrees north, are projected to see the greatest change, with temperatures rising more than 2.8 degrees Celsius.

2. Describe how some of the temperature patterns visible on the map relate to ocean currents.

   Warm waters from the Atlantic Ocean enter the Arctic via the currents between Europe and Greenland. Similar currents don't exist for the North Pacific, which is blocked by land, or for the Southern Ocean, which is surrounded by strong cold currents.

3. Which parts of the ocean are projected to see the most deoxygenation? Which parts are projected to see the least?

   The map shows that high latitudes, especially the seas north of the Aleutian Islands, Scandinavia, and western Russia, will see the greatest depletion of oxygen in the coming years. The Antarctic and the region southeast of Greenland will see increases in dissolved oxygen.

4. Which parts of the ocean are projected to see the most acidification? Which parts are projected to see the least?

   The Arctic Ocean is projected to experience the most severe acidification in the coming years, along with the northwest coasts of North America and Asia. The west coast of South America and the equatorial region of the Pacific Ocean will experience the least acidification.

5. What areas of the ocean are most at risk from all three climate change stressors?

   Northern waters are most at risk from warming temperatures, acidification, and deoxygenation. The Barents Sea (between Svalbard and Novaya Zemlya) is under particular stress from these three climate change factors.

Acknowledgements

• Coupled Model Intercomparison Project (CMIP6), accessed via the National Oceanic and Atmospheric Administration (NOAA) Physical Sciences Laboratory, Climate Change Web Portal).
• We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF.