Product Users | Explore the simulations

TIPS | Climate projections describe a range of possible climate outcomes and are based on different climate models with different set-ups. How should I use this information? It is important to evaluate the climate models’ ability to simulate changes, and one way to do so is to examine how they reproduce the mean seasonal cycle in temperature and precipitation. We examine model output collected from the Climate Model Intercomparison Project - Phase5 (CMIP5), the Coordinated Regional Climate Downscaling Experiment over Europe (EURO-CORDEX), and the Empirical-Statistical Downscaling project (ESD) at the Norwegian Meteorological Institute to provide the best estimates of global/regional/local climate signal that in turn can be used in impact studies. Click on the dashboard to navigate between other items.

Glossary

Filter by

Climate Model Simulations

Product Users | Models' biases

TIPS | One way to assess the skill of climate models is to examine the models' biases in reproducing the seasonal cycle. Here, you can navigate between (CMIP5, A) global and (EURO-CORDEX, B) regional climate models, modify the settings so that they fit your needs, and explore how the models reproduce the monthly mean air temperature and precipitation totals over a number of pre-defined regions. You can additionally click on the dashboard menu to navigate between other evaluations of climate model simulations.

1. Select a region : Explore and navigate through various regions (AR5 predefined regions)

The regions used the AR5 Reference Regions which include 26 regions defined in SREX. In addition to these regions, the Arctic, Antarctic, South Asia and South-East Asia) and three global analysis domains: land only, sea only and all points. Read more
Demo video
You can navigate between the various predefined regions.

2. Settings & Outputs : Modify the default settings and select the output type and values.


You can navigate between one control and two (near and far) future time horizons.

You can modify the layout of the chart to display individual simulations or the envelope-based on all simulations.

You can display values for various statistics such as the mean and the spatial standard deviation. The spatial correlation are only computed between historical simulations and the reference data for the present (1981-2010).

You can filter the simulations and keep only identical simulations for all climate variables such as preciptiation and temperaure.

3. Bias in monthly mean air Temperature

4. Bias in monthly precipitation totals

1. Select a region : Explore and navigate through various regions (EURO-CORDEX, PRUDENCE, European countries)

You can navigate between the various predefined regions such as Europe (EURO-CORDEX domain, PRUDENCE regions, and national regions

2. Settings & Outputs : Modify the default settings and select the output type and values.


You can navigate between one control and two (near and far) future time horizons.

You can modify the layout of the chart to display individual simulations or the envelope-based on all simulations.

You can display values for various statistics such as the mean and the spatial standard deviation. The spatial correlations are computed only between historical simulations and the reference data for the present (1981-2010).

You can filter the simulations and keep only identical simulations for all climate variables such as preciptiation and temperaure.

3. Bias in monthly mean air Temperature

4. Bias in monthly precipitation totals

Product Users | Seasonal Cycle

TIPS | One way to assess the skill of climate models is to examine how they reproduce the seasonal cycle. Here, you can navigate between (CMIP5, A) global and (Euro-CORDEX, B) regional climate models, modify the settings so that they fit your needs, and explore how the models reproduce the monthly mean air temperature and precipitation totals over a number of pre-defined regions. Click on the dashboard to navigate between other evaluation items.

1. Select a region : Explore and navigate through various regions (AR5 predefined regions)

The regions used the AR5 Reference Regions which include 26 regions defined in SREX. In addition to these regions, the Arctic, Antarctic, South Asia and South-East Asia) and three global analysis domains: land only, sea only and all points. Read more
Demo video
You can navigate between the various predefined regions.

2. Settings & Outputs : Modify the default settings and select the output type and values.


You can navigate between one control and two (near and far) future time horizons.

You can modify the layout of the chart to display individual simulations or the envelope-based on all simulations.

You can display values for various statistics such as the mean and the spatial standard deviation. The spatial correlations are computed only between historical simulations and the reference data for the present (1981-2010).

You can filter the simulations and keep only identical simulations for all climate variables such as preciptiation and temperaure.

3. Seasonal Cycle of monthly mean air Temperature

4. Seasonal Cycle of monthly precipitation totals

1. Select a region : Explore and navigate through various predefined regions (EURO-CORDEX, PRUDENCE, European countries)

You can navigate between the various predefined regions.

2. Settings & Outputs : Modify the default settings and select the output type and values.


You can navigate between one control and two (near and far) future time horizons.

You can modify the layout of the chart to display individual simulations or the envelope-based on all simulations.

You can display values for various statistics such as the mean and the spatial standard deviation. The spatial correlations are computed only between historical simulations and the reference data for the present (1981-2010).

You can filter the simulations and keep only identical simulations for all climate variables such as preciptiation and temperaure.

3. Seasonal Cycle of monthly mean air Temperature

4. Bias in monthly precipitation totals

How to read the chart The chart shows the evolution as a function of years.
Remember ! some text here

How to read ! Monhtly Summary statistics

Data Users | Global Climate Models

TIPS | the global climate models constitute powerful tools for climate projection to provide the best representation of the projected climate signal over a region of interest. The climate simulations evaluated here are based on the Coordinated Regional Climate Downscaling Experiment over Europe (EURO-CORDEX) to produce the best estimates of regional/local climate signal that in turn can be used in impact studies. You can click on the dashboard to navigate between other items.

1. Select a region : Explore and navigate through various regions (AR5 predefined regions)

The regions used the AR5 Reference Regions which include 26 regions defined in SREX. In addition to these regions, the Arctic, Antarctic, South Asia and South-East Asia) and three global analysis domains: land only, sea only and all points. Read more
Demo video

2. Settings & Outputs : Modify the default settings and select the output type and values.


You can navigate between one control and two (near and far) future time horizons.

You can modify the layout of the chart to display individual simulations or the envelope-based on all simulations.

You can filter the output to selected simulations in the meta data table or display all simulations (default).

You can display or hide the legend in the different charts

You can group the simulations by values in the meta data table, for instance, by global climate model ID, i.e. all simulations sharing the same global climate model belong to the same group but different colors are applied for simulations within each group.

You can apply the same color within groupped simulations by values in the meta data table such as the global climate model ID. In this case, all simulations within each group will have same colored lines

You can transform the values into anomalies by substracting the mean, compute the bias or the root mean square errors as devitations with regards to the reference data, or compute the climate change with regards to the base period 1981-2010

You can display values for various statistics such as the mean and the spatial standard deviation. The spatial correlations are computed only between historical simulations and the reference data for the present (1981-2010).

You can filter the simulations and keep only identical simulations for all climate variables such as preciptiation and temperaure.

3. Evaluate the seasonal cycle in simulated Mean Air Temperature

4. Evaluate the seasonal cycle in Simulated Monthly Precipitation totals

5. Scatter Plots of Simulated Climate Variables

Data Users | Regional Climate Models

TIPS | The regional climate model simulations constitute a better representation of regional climate outcomes than global climate outputs as they are run on higher spatial resolution, and include more local processes to provide the best representation of the climate signal over a region of interest. The climate simulations evaluated here are based on the Coordinated Regional Climate Downscaling Experiment over Europe (EURO-CORDEX) to produce the best estimates of regional/local climate signal that in turn can be used in impact studies. You can click on the dashboard to navigate between other items.

1. Display the region (EURO-CORDEX, PRUDENCE, European countries)

2. Settings & Outputs : Modify the default settings and select the output type and values.


You can navigate between one control and two (near and far) future time horizons.

You can modify the layout of the chart to display individual simulations or the envelope-based on all simulations.

You can filter the output to selected simulations in the meta data table or display all simulations (default).

You can display or hide the legend in the different charts

You can group the simulations by values in the meta data table, for instance, by global climate model ID, i.e. all simulations sharing the same global climate model belong to the same group but different colors are applied for simulations within each group.

You can apply the same color within groupped simulations by values in the meta data table such as the global climate model ID. In this case, all simulations within each group will have same colored lines

You can apply the same color within groupped simulations by values in the meta data table such as the global climate model ID. In this case, all simulations within each group will have same colored lines

You can display values for various statistics such as the mean and the spatial standard deviation. The spatial correlations are computed only between historical simulations and the reference data for the present (1981-2010).

You can filter the simulations and keep only identical simulations for all climate variables such as preciptiation and temperaure.

3. Evaluate the seasonal cycle in simulated Mean Air Temperature

4. Evaluate the seasonal cycle in Simulated Monthly Precipitation totals

5. Scatter Plots of Simulated Climate Variables

Product Users | Changes in Climate

TIPS | Changes in Climate can be obtained using various climate models such as global climate models, regional climate models, and empirical statistical climate models which constitute powerful tools to provide the best representation of the projected climate signal over a region of interest. The climate simulations evaluated here are based on the CMIP5 global climate models, these are in turn used to force regional climate models (Coordinated Regional Climate Downscaling Experiment) and Empirical-Statistical Models (ESD) to produce the best estimates of regional/local climate signal that in turn can be used in impact studies. You can click on the dashboard to navigate between other items.

CMIP5 Global Climate Model Simulations


You can navigate between various AR5 predefined regions.

You can navigate between one control and two (near and far) future time horizons.

You can modify the layout of the chart to display individual simulations or the envelope-based on all simulations.

You can display values for various statistics such as the mean and the spatial standard deviation. The spatial correlations are computed only between historical simulations and the reference data for the present (1981-2010).

You can filter the simulations and keep only identical simulations for all climate variables such as preciptiation and temperaure.

EURO-CORDEX Regional Climate model Simulations (Implemented over the whole Europe!)


You can navigate between various PRUDENCE predefined regions (! not yet implemented).

You can navigate between one control and two (near and far) future time horizons.

You can modify the layout of the chart to display individual simulations or the envelope-based on all simulations.

You can display values for various statistics such as the mean and the spatial standard deviation. The spatial correlations are computed only between historical simulations and the reference data for the present (1981-2010).

You can filter the simulations and keep only identical simulations for all climate variables such as preciptiation and temperaure.

ESD simulations on station level (Loading ...!)


You can navigate between three emission scenarios pre-defined by the IPCC.

You can modify the time horizon.

You can modify the base period at your convenience.

You can display the multi-model ensemble mean or navigate between the various driven global climate models.

You can navigate between various climate parameters or indices.

You can navigate between various locations.

You can navigate between various seasons

1. Select a region (e.g. EURO-CORDEX definition)

The EURO-CORDEX domain Read more
Demo video

2. Settings & Outputs : Modify the default settings and select the output type and values.

3. Water Resources

4. River Runoff

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

1. Select your region of interest

2. Settings & Outputs : Modify the default settings and select the output type and values.

3. Growing season

The interactive figure shows the Intensity-Duration-Frequency curve simulated by the selected set of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

4. Frost

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

5. Rain during harvest

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

6. Drought

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

7. Hail

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

8. Flood

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

9. Sunlight

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

1. Select your region of interest

2. Settings & Outputs : Modify the default settings and select the output type and values.

3. Temperature

The interactive figure shows the Intensity-Duration-Frequency curve simulated by the selected set of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

4. Precipitation

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

5. Snow

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

6. Wind

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

1. Select your region of interest

2. Settings & Outputs : Modify the default settings and select the output type and values.

3. Floods

The interactive figure shows the Intensity-Duration-Frequency curve simulated by the selected set of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

4. Storms

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and correlations instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

About KPI's for the Health Sector

Meteorological elements such as temperature, wind, precipitation, and humidity may have some health issues (Epstein and Ferber, 2011), affecting conditions such as heat waves, pollution, pollen, flooding, storm surge, wind, snow, ice, or droughts. Heat waves pose a health hazards for an aging population in southern Europe, whereas higher temperatures in general can increase the spread of diseases and their vectors (eg. ticks and lyme disease). Changing temperatures also affect spread pollen affecting people with allergies, and temperature inversions can trap pollution (warmer winters may potentially reduce the frequency of inversions). Flooding and storm surge can lead to drowning, while strong winds can result in dangerous situations with flying debris. The presence of snow and ice can also lead to accidents, the former through shifting snow (causing cardiac arrest in older people) or avalanches, while icy condition can result in higher number of broken limbs. Droughts can lead to dangerous conditions with higher risks of wildfires. A typical user from the health sector may include planners within health authorities (ministry of health) and hospitals. To prepare outlooks for future demands, they need to look at various factors, and climate change may not necessarily be the most important one. Furthermore, the time horizon for their planning is usually shorter than a decade, unless there is a need to start a research project to develop new treatments or build new hospitals. Reliable seasonal to decadal predictions can benefit annual budgeting and planning, typically the time frame for society.

Read more
Demo video

1. Settings & Outputs : Modify the default settings and select the output type and values.

2. Heat waves and temperature changes

The interactive figure shows the Intensity-Duration-Frequency curve simulated by the selected set of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and spatial correlation (only works on present (1981-2010) climate) instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

3. Pollution

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and spatial correlation (only works on present (1981-2010) climate) instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and spatial correlation (only works on present (1981-2010) climate) instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

4. Floods and Droughts

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and spatial correlation (only works on present (1981-2010) climate) instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and spatial correlation (only works on present (1981-2010) climate) instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

5. Storms and Storm Surge

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and spatial correlation (only works on present (1981-2010) climate) instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and spatial correlation (only works on present (1981-2010) climate) instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

6. Snow and Ice

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and spatial correlation (only works on present (1981-2010) climate) instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.

The interactive figure shows the seasonal cycle of pseudo-observed (dashed) and modeled precipitation by the multi-model ensemble of simulations assuming the intermediate emission scenario (RCP4.5). You can modify the type of the output from the "Settings & Outputs" tab box into, for example, individual simulations, envelope of the ensemble model simulations, box plots of both, transform the values into anomalies, group the models by attributes, etc. You can additionally double click on specific climate models from the legend (once displayed) or the meta data table to isolate one or a group of simulations or modified the displyed statistic to, for example, spatial standard deviation and spatial correlation (only works on present (1981-2010) climate) instead of the mean. Other options are also included such as zoom in/out, show closest data by pointing with the mouse on the simulations, compare data between simulations, and download the plot as png by taking a snapshot. You can also check and download both the data and meta data tabs for furhter details about the simulations.