RCM workshop, Meteo Rwanda, Kigali Climpact2 and RCMs RCM workshop, Meteo Rwanda, Kigali 17th – 20th July 2017 This presentation is intended to provide an overall introduction. It won’t go into huge amounts of detail but should act as a signposting session to other talks later in the week.

Resolution is important (example) A Regional Climate Model (RCM) is a high resolution climate model that covers a limited area of the globe, typically 5,000 km x 5,000 km. RCMs are based on physical laws represented by mathematical equations that are solved using a three-dimensional grid. The typical horizontal resolution of an RCM is 50 km. Hence RCMs are comprehensive physical models, usually including the atmosphere and land surface components of the climate system, and containing representations of the important processes within the climate system (e.g., cloud, radiation, rainfall, soil hydrology). Many of these physical processes take place on much smaller spatial scales than the model grid and cannot be modelled and resolved explicitly. Their effects are taken into account using parametrizations by which the process is represented by relationships between the area or time averaged effect of such sub-grid scale process and the large scale flow. © Crown copyright Met Office 2

Resolution is important (example) A Regional Climate Model (RCM) is a high resolution climate model that covers a limited area of the globe, typically 5,000 km x 5,000 km. RCMs are based on physical laws represented by mathematical equations that are solved using a three-dimensional grid. The typical horizontal resolution of an RCM is 50 km. Hence RCMs are comprehensive physical models, usually including the atmosphere and land surface components of the climate system, and containing representations of the important processes within the climate system (e.g., cloud, radiation, rainfall, soil hydrology). Many of these physical processes take place on much smaller spatial scales than the model grid and cannot be modelled and resolved explicitly. Their effects are taken into account using parametrizations by which the process is represented by relationships between the area or time averaged effect of such sub-grid scale process and the large scale flow. © Crown copyright Met Office 3

Resolution is important (example) A Regional Climate Model (RCM) is a high resolution climate model that covers a limited area of the globe, typically 5,000 km x 5,000 km. RCMs are based on physical laws represented by mathematical equations that are solved using a three-dimensional grid. The typical horizontal resolution of an RCM is 50 km. Hence RCMs are comprehensive physical models, usually including the atmosphere and land surface components of the climate system, and containing representations of the important processes within the climate system (e.g., cloud, radiation, rainfall, soil hydrology). Many of these physical processes take place on much smaller spatial scales than the model grid and cannot be modelled and resolved explicitly. Their effects are taken into account using parametrizations by which the process is represented by relationships between the area or time averaged effect of such sub-grid scale process and the large scale flow. © Crown copyright Met Office 4

Weather vs. Climate “Climate is what we expect, weather is what we get” (1887) Climate = Average weather and its variability over a period of time, ranging from months to millions of years. WMO Quantifies climate over a 30-year average period. Observations create the 30 year climate baseline, which new observations and climatic trends are measured against. Climate refers to the state of the climate system as a whole, including a statistical description of its variations. Before we can understand the problem and climate change we need to understand what climate is and how it is different to the weather. This is Mark Twain a famous American author in the 19th century – he famously sais: “the climate is what we expect, weather is what we get” So if weather is different to the climate Q: How would you define climate? The weather is the day-to-day variable conditions, whereas climate is defined by the WMO as the average weather and its variability over a period of time. The World Meteorological Organisation quantifies climate over a 30 year period. Therefore, weather observations over the 30 years are averaged out to generate a global climate average.

Describe daily extremes more accurately Changes in extremes of weather, for example heavy rainfall events, are likely to have more of an impact than changes in annual or seasonal means. RCMs are much better than GCMs at simulating extremes. The diagram shows the probability of daily rainfall over the Alps being greater than a number of thresholds up to 50 mm. It is clear that the GCM-simulated probability does not agree well with observations, whereas the RCM simulation is much more realistic. For this reason, RCM predictions of changes in extremes in the future are likely to be very different to, and much more credible than, those from GCMs. Frequency of winter days over the Alps with different daily rainfall thresholds. RCM and Observations aggregated at GCM scale

A chain of separate models Regional Climate Model Global Climate Model Impacts Models

ClimPACT2 An R software package for calculating climate extremes indices, authored by a team led by Assoc. Prof. Lisa Alexander and Nicholas Herold at the University of New South Wales. https://github.com/ARCCSS-extremes/climpact2

ClimPACT2 Nick’s intro ...

Installation tutorials Install R in (Ubuntu) Linux https://www.youtube.com/watch?v=T_0LbTxvs5s Run Climpact2 GUI in Linux https://www.youtube.com/watch?v=1sSCqsRMCZI

Proof of concept: ClimPACT2 analysing RCM output data David ran two PRECIS experiments for the case study over a 25km Eastern Caribbean region. One experiment downscaled 1980-1990 from the HadGEM2-ES GCM (a CMIP5 model) using historical GHG values and a second 2080-2090 from HadGEM2-ES RCP 8.5.

Proof of Concept: Climpact2 analysing RCM output data The raw output data from the experiments has to be processed to be “Climpact2 ready”. That means regridding, changing the units (to Celsius / millimetres per day), conversion to NetCDF data format, and more. To do this, NCO tools and CF-Python are needed. http://nco.sourceforge.net/ http://cfpython.bitbucket.org/

Proof of Concept: Climpact2 analysing RCM output data When the PRECIS RCM data was in the right format, David edited a file in the climpact2-master directory: climpact2.wrapper.r David made changes to this file to the names of the variables (e.g. Air_temperature instead of Tmax) and to the input file names.

Proof of Concept: Climpact2 analysing RCM output data David then ran Climpact2.wrapper.r inputting the baseline data and writing out a quantiles file. Next David ran Climpact2.wrapper.r inputting the future projections data and the quantiles file. Climpact2 ran and produced output NetCDF files.

Next Steps If you want to use Climpact2 to analyse regional climate data, you can either generate data yourself with an RCM (including PRECIS) or download data from online repositories, e.g. the Coordinated Regional Downscaling Experiments project: http://www.cordex.org

Case Study : Climpact2 analysing RCM output data The CMIP5 GCM HadGEM2-ES has been downscaled by the PRECIS RCM over the CORDEX Southeast Asia domain

Case Study : Climpact2 analysing RCM output data Resolution: 25km Baseline: 1960-1989 Future: 2060-2089 RCP8.5

© Crown copyright Met Office Panoply The main window A quick look at the main Panoply window. Note that Panoply does *not* read PP files! © Crown copyright Met Office

Interpreting Climpact2 Activity You will be put into a team Team 1: Drought Team 2: Rain Team 3: HEAT

Questions?