CEG8526: Hydrosystems modelling and management

Practical 1: Using climate model information

Aim and learning outcomes

The purpose of this practical is to use some simple online tools to understand how information from GCMs is commonly presented and how this output may be interpreted to understand future climate change. The practical also encourages you to think about the limitations of these tools and the information they provide in terms of assessing and responding to the impacts of climate change.

After completing this practical you should be able to:

•   Interpret climate data (observations and model output) using standard methods of climate model data visualisation.

•   Summarise regional changes in key climate variables from CMIP6 models quantitatively.

•   Understand and explain the sources of uncertainty in climate model projections of future climate.

•   Identify the limitations of climate model output for decision-making.

The understanding of climate model outputs gained in this practical will be essential in preparing to use the UKCP18 projections in your assessed coursework.

Practical summary

General circulation models (GCMs) area fundamental tool in deriving global-scale projections of future climate while regional climate models (RCMs) provide more local scale information at higher resolutions. GCMs thus provide information that underlies global action to mitigate climate change and also provide the boundary conditions for RCMS that are used to understand the potential regional and local impacts of climate change on society and how we might adapt in the future.  In this practical you will use a freely available web tool to explore the latest climate projections to produce a summary of regional climate change.

The IPCC WGI Interactive Atlas is a tool providing spatial and temporal analyses of much of the observed and projected climate change information underpinning the Working Group I contribution to the Sixth Assessment Report.  The IPCC Atlas homepage allows you to access its different features.

The first time you access the homepage you will have the option of a quick tour of the functionality - please take a few moments to take the tour as this will help familiarise you with the location of the various tools.

The atlas provides three main products accompanied by documentation and user guidance:

Simple: allows you to view annual and seasonal climate and climate change under 1.5°C, 2°C, 3°C and 4°C of global warming.

Advanced: allows you to view annual and seasonal climate and climate change for different scenarios using a range of different model experiments (CMIP5, CMIP6, CORDEX).  You can also examine model simulations over different historical periods as well as observations from different global and regional datasets.

Regional synthesis: allows you to examine mapped or tabulated summaries of projections (with confidence information) and past trends (with attribution information)

Documentation: provides access to user guidance, videos and tutorials.

The user guidance page provides information to help you understand the different forms of output provided, including the time series, annual cycle, global warming level (GWL) and climate stripe plots.

You should work through this worksheet in order, and answer the questions 1A, 2A-C, 3A-C, and 4A.

Activity 1 - deriving projections using the simple tool

Complete the following tasks and where you see a           symbol, note down your answers for discussion later. To get used to navigating the atlas and to the type of information it provides the  first task uses the simple option (option ).

Once in the simple atlas, use the menuselections for variable, quantity & scenario and season:

1A. Derive projections of the change in maximum (daily) temperature (TX) for the South Asia region (centred on India) in summer (June to August) under 1.5°C and 4°C of global warming, including estimates of the uncertainty in the projections.  To do this you will need to select the region from the map and then select the relevant options from the menu bar.  You can then use the range of options at the bottom of the display to view the regionally aggregated information in different formats. The ‘Table Summary’ will be most useful for  completing the table below. Here you should derive the average change and the P10|P90 ranges.  What do the ranges e.g. P10|P90 represent here?

You can check your answers, including comparing maps on the Canvas page for this practical.

The default setting is for the regionally aggregated information to be presented in small plots under the map.  You can enlarge these by dragging the symbol up to cover the map.

When you have finished, you can drag it back down again to revert to the map view.

Activity 2 - comparing the performance of models against observed data

Next use the advanced option (option ). You can do this by clicking on Home in the top right or selecting the advanced option from the dropdown menu. You will now see that you have an extra option - a choice of different datasets which provides the option to look at model projections (future), model historical (simulations of past climate) and observations (datasets of historical weather observations).

Using the menuselections for variable, quantity & scenario and season, this time we will explore some of the observational datasets in the atlas. Select the GPCC (Global

Precipitation Climatology Centre) dataset from the list of observations to look at Total precipitation (PR).  For a given observational dataset the available variables are highlighted in white - you will note that each dataset only provides certain variables. First, using the period 1961-2015 look at the value (mm/day) for this variable (for observations you can also examine the trend).  Use the zoom  tool to focus in on Australia and examine the data for the December-February season.  You should get amap like the figure below:

Note that we don’t have complete coverage of rain gauges as the map would suggest but researchers can produce datasets of our observations on a grid through statistical techniques of spatial interpolation. This allows us to better compare observations with models but be aware of the fact that this creates uncertainty in the estimated gridded observations.

Now click on the Duplicate map icon on       the right. This will split the screen in two,       with a duplicate of the map.  Each side of the map will now have its own set of menus to the left or right.  Using one of the maps change the datasetselection to Model Historical|CMIP6 (at the bottom of the menu). In the quantity & scenario menu select a time period that closely match – 1980-2015 for the observations and 1981-2010 for the CMIP6 historical  simulations. This is atypical model performance approach for validating climate models.

You can again check your maps on Canvas.

2A. Write a short description of how well the climate models reproduce the observed patterns of PR. Include some quantitative information - you can use the point information tool o to compare the data at specific locations. For example, do the models simulate the magnitude (values) and spatial patterns of mean precipitation well?

2B. List any other features of precipitation you might want to validate against the observations in addition to the seasonal average if you were interested in using the models to assess future impacts of the climate on society.

Now, using the map that currently shows the historical observations, using the dataset menu, change the dataset from observations/GPCC to model historical/CORDEX

Australasia for 1981-2010.

2C. Write down your observations about the difference in the resolution of the data

compared with that from the GCMs. What type of model has been used in the CORDEX  experiments? What features of the climate might be better represented by these models and why?

Activity 3 - exploring projections of climate change using scenarios

Finally, we will look at some projections using CMIP6 and scenarios.   Revert back to a single map view using the symbol. Select CMIP6 from the dataset menu and from the variable list we will look at one of the precipitation extremes indices, maximum 1-day precipitation  (RX1day) for December-February.   Look at the long-term percentage change (2081-2100)  for scenarioSSP5-8.5 relative to the baseline of 1981-2010 for Northern Europe.

RX1day is an example of aclimate index. An index is a simple diagnostic quantity that is used to characterize an aspect of the climate system such as extreme temperature or precipitation. A common set of indices used in climate analyses are those defined by the

Expert Team on Climate Change Detection and Indices (ETCCDI) and these have been

calculated for visualisation in the climate change atlas. Look at the other indices that are available.

3A. Write down abrief summary of the projected changes for the region (you can also use any regional summary plots in the lower panel), commenting on how confident you would be in applying these changes in practice to assess future flood risk.  To do this, use your knowledge of the limitations of these models, and also the uncertainty information provided in the atlas. Werecommend you use the simple visualisation of uncertainty:

Remember, the maps show the mean of a collection/ensemble of models. The number of     models used is shown in the title of each map. For this simple method, no overlay indicates the different models in the ensemble are in agreement in that at least 80% of the models    agree in the sign of change in individual grid cells. An overlay of diagonal lines (/) indicates  low model agreement, where fewer than 80% of models agree on the sign of the change.

Next, examine the Global Warming Level (GWL) plot for this region showing the relationship  between warming and RX1day (see below).  To do this make sure you select value (mm) and not change (%) in the quantity selection option.

3B. Write down your observations of what this tells us about the relationship between temperature and extreme precipitation? What is the physical basis for this relationship?

Finally, compare the CMIP6 projections with those for the CORDEX Europe experiment.

3C. If you were interested in applying climate change uplifts for extreme precipitation for flash flooding in urbanareas how confident would you be in applying the output from each product?

Activity 4 - applying climate model information

Finally, let’s put all this information together with a plausible working scenario where you might use a range of information available in the atlas.

You are required to produce a climate change assessment for a conference of regional city leaders.

You need to produce a summary providing evidence for why they need to develop climate change

plans in their administration – both in terms of mitigation of climate change and adaptation to

future climatic (and hydrological) hazards.  You should use the IPCC Atlas to provide evidence

making the case for action and declare a Climate Emergency (see statement onNewcastle’s Climate Emergencyas an example).  This might include evidence from the Atlas of:

•    already observed climate change using the option to visualise trends in observed data;

•    projections of future change.

You should look at a range of scenarios or global warming levels to demonstrate the effect of

potential emissions reductions and also examine a range of variables, indices and indicators that demonstrate the potential impacts that they may need to plan for across different sectors to underpin the declaration of an emergency.

4A. Select one region of interest to you and for that region use appropriate model output to write down at least three pieces of data you would provide to the leaders

(where appropriate you should relate it to specific types of hazards that might affect the region).

You should also reflect on the degree to which the information available tells you what you/city leaders need to know.

a.    Write down the limitations of the information you have provided and ideas for how you might go about providing a more robust estimate of regional climate change.

b.    Make alist of what other information/data and tools might you need to

translate this into an assessment of local climate change and the impacts of that change (remember higher temperatures or more intense rainfall are changes in  climate but are not impacts on human or natural systems).

Once complete post your summary in theclimate change discussion boardand you may compare your analyses with theregional fact sheetspublished by the IPCC.