Climate Explorer—Visualize Climate Data in Maps and Graphs
About the Tool and Data
Climate Explorer is a research application built to support the U.S. Climate Resilience Toolkit. The tool offers interactive visualizations for exploring maps and data related to the toolkit's Taking Action case studies.
Base maps (imagery, street maps) come from ESRI Web services. Map layers in the tool represent geographic information available through climate.data.gov. Each layer's source and metadata can be accessed through its information icon.
Climate Explorer graphs available via the tools Historical Data tab display 1981-2010 U.S. Climate Normals for temperature and precipitation, overlain with daily observations from the Global Historical Climatology Network-Daily (GHCN-D) database. Please note that GHCN-D data have been checked for obvious inaccuracies, but they have not been adjusted to account for the influences of historical changes in instrumentation and observing practices. GHCN-D data are useful for comparing weather and climate, but for long-term climate change analyses, we recommend the National Climatic Data Center's Climate at a Glance.
Navigating the map
- Zoom in or out using your mouse wheel or the plus and minus icons at top left.
- To pan—or move around on the map—click and drag.
- Toggle between a street map and satellite imagery using the button at the bottom left.
Exploring map layers
Find and display available data layers from the LAYERS tab at top right.
- Select any Topic from the top drop-down menu to see the list of layers associated with that theme.
Available layers appear in two groups, Climate Stressors and People and Assets Impacted.
- The interface shows only three layers at a time in each group.
- To reveal additional map layers, place your cursor over either of the lists and scroll down.
- Turn any layer on or off by checking its box.
- View the legend and a link to its source by clicking the layer's "i" icon .
- Adjust the opacity / transparency of any layer by sliding the blue bar beneath the layer's name to the left or right.
Sharing the map
To share the location, zoom level, and data layers you've displayed for any map, click the permalink icon at top left to generate a URL (web address) for your view. Copying and pasting this URL into email or another application will give others direct access to the same map you were viewing when you clicked the permalink button.
Exploring graphs of temperature and precipitation
Produce and interact with graphs showing daily observations and long-term averages from the HISTORICAL DATA tab at top right.
Generate graphs by zooming in to an area of interest on the map and clicking any red pin.
- For help interpreting the graphs, see the next 2 sections on this page.
Customize the display by zooming and/or panning on the x or y axis in either graph.
- To squeeze or stretch the graph in either direction, use your mouse wheel, or hold your shift key down while clicking and dragging either axis.
- To display earlier or later data in the graph, click and drag to the right or left.
- Compare graphs from multiple stations by clicking additional red pins on the map. Each station you select turns blue and shows a number so you can match graphs to their locations.
- Click the TEMPERATURE and PRECIPITATION buttons above the graph area to toggle their associated graphs on and off.
Interpreting Climate Explorer's temperature graphs
Long-term average temperatures
The green curve displayed as the base layer of each temperature graph shows the long-term average maximum and minimum temperatures (in degrees Fahrenheit) through the year. For every day of the year, the top edge of the green range represents the average of maximum temperatures measured on that date at the station from 1981 to 2010. Similarly, for each day of the year, the bottom edge of the green range represents the average of all minimum temperatures measured on that date from 1981 to 2010. The example on the right shows several years of temperature data for Mobile, Alabama. The green portion of the curve shows the long-term average pattern of cool winters and warm summers.
Daily temperature observations
The top of each blue bar shows the observed maximum temperature recorded by the station on the date indicated by the x axis. Similarly, the bottom of each blue bar shows the day's observed minimum temperature. Wherever the blue bars extend above or below the green curve, observed temperatures were warmer or cooler than the long-term average for that date. The example on the right shows a zoomed in view of the image above it. On December 21, 2013, observed maximum and minimum temperatures were both higher than the long-term average maximum temperature. On January 7, observed minimum and maximum temperatures were both cooler than the long-term average of the date's minimum temperature.
Interpreting Climate Explorer's precipitation graphs
Long-term average annual precipitation accumulation
The single red line in each precipitation graph shows long-term average annual precipitation (in inches) as a cumulative total. The height of the curve represents the average of cumulative precipitation totals received through each day of the year from 1981 to 2010. Examining the shape of the line can reveal information about the location's rainy versus dry seasons. The example on the right shows several years of observations at Ralston Reservoir, near Denver, Colorado. Through 2012, the location received lower-than-average precipitation. In 2013, a single rain event pushed the location's annual total far above the long-term average.
Daily precipitation observations
Red shading shows accumulated precipitation observed through each year. Increases in the shaded area indicate days when the location received precipitation; flat segments of the shaded portion indicate days without precipitation. Dates for which the shaded portion is below the line indicate the annual accumulation was below average. When the shading extends above the line, the station's annual accumulated precipitation was above average. The example on the right is a zoomed in view of the graph above it. The steep increase in cumulative precipitation in late August of 2013 indicates a heavy rain event. The smaller stair-step pattern of increases in 2014 shows a number of smaller rain events.
Tutorial 1: Using topic layers to identify potential climate impacts
This map shows the city of Tybee Island, Georgia. Click this permalink to launch Climate Explorer showing the same map so you can follow these steps. Take a look at the island and the road that connects it to the mainland.
Under Climate Stressors, turn on the Inundation from Sea Level Rise (2 ft) layer. Click the “i” icon to the right of the layer name to display the legend. Examine the legend and the map to see where shallow (light blue) and deep (dark blue) water is likely to cover land and parts of the roadway if sea level rises by two feet. As the map shows, the only road leading to the island would be inundated by this amount of sea level rise. Click the source link in the legend if you want to learn more about the data layer and how it was produced.
To examine the geography of the island, adjust the transparency slider (the blue bar below the layer's name) to reduce the visibility of the Inundation layer. In the image at right, the layer is shown at 30 percent visibility. This adjustment makes it easier to explore the extent of inundation across features of the landscape.
Under the People and Assets Impacted section, turn on the Land Cover (2011) layer and adjust its transparency level. Here, we've displayed the Land Cover layer at 35 percent opacity. Click the "i" icon to display the legend for this layer and examine the legend and map to explore how land is used on Tybee Island. Turn the Inundation from Sea Level Rise (2 ft) layer on and off to visualize areas expected to experience flooding if sea level rises two feet. Interact with Climate Explorer to identify areas vulnerable to flooding from two feet of storm surge or sea level rise.
Tutorial 2: Interaction with climate data to identify impacts
In this example, you'll visualize the impacts a rising sea level may have on a coastal community and explore historical precipitation data to better understand the impact of Hurricane Sandy in 2012.
This map shows communities along the New Jersey coast. Click this permalink to launch Climate Explorer showing the same map so you can follow these steps.
Turn on the Inundation from Sea Level Rise (3ft) layer. Though sea level is not expected to rise by three feet in the near future, this layer can be used to visualize the effect of a three-foot storm surge on these communities. Based on the visualization, list some of the features likely to be inundated by a three-foot storm surge. (Note that the Inundation from Sea Level Rise layers will not show up if you've zoomed in too closely).
Hurricane Sandy made landfall in this region in October of 2012. The storm brought a large amount of precipitation to the area. Click the Historical Data tab at top and click the red pin on the map at Hammonton, New Jersey, to display weather data from the station. As we're only interested in precipitation for this example, toggle the temperature graph off by clicking TEMPERATURE above the graphs.
Zoom and pan on the x axis to display data for October 2012. Use your mouse wheel or hold the shift key down and click and drag in a horizontal direction to adjust the graph display. You can also scale the y axis. Notice the red pin at Hammonton has turned blue, indicating the location of the data in the graph.
The red line in the graph represents the long-term average cumulative precipitation received at Hammonton through the year. The shaded portion of the graph represents observed precipitation at Hammonton. The year 2011 had above-average rainfall, but 2012's observed precipitation total was below average.
Take a look at the steep increase in observed precipitation during October 2012 (circled); this represents the rainfall brought by Hurricane Sandy. Compare this increase to the even larger precipitation event that occurred in August of 2011 from Tropical Storm Irene. Though Irene brought more precipitation than Sandy to Hammonton, the area did not experience widespread flooding and damage to buildings and infrastructure. Based on these observations, storm surge associated with Hurricane Sandy likely caused more damage than the heavy precipitation associated with the storm.