Presentation at ARRCC-CARISSA workshop 29 Jan 2019 to 31 Jan 2019

1. An overview of available climate
projections for South Asia
Cathryn Fox
Met Office
Future Climate Projections and their Applications in South Asia
29th – 31st January 2019, ICIMOD, Kathmandu, Nepal
www.metoffice.gov.uk © Crown Copyright 2018, Met Office

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The ARRCC programme will target four focal countries
in the South Asia region, namely Bangladesh, Pakistan,
Nepal and Afghanistan.
As part of our initial baselining activity we reviewed
available climate projections in the region
This talk will give a brief introduction to the different
types of projections available
The report is also available to those interested –
contact me for a copy!

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GCMs
- Global Climate or General Circulation Models
- Have resolution typically 100-300km
- Many different GCMs are run by modelling centres all
over the world
- These are compared during the different stages of the
Coupled Model Intercomparison Project (CMIP) to
support national and international climate change
assessments

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Maps of temperature changes in 2016–2035, 2046–2065 and
2081–2100 with respect to 1986–2005 in the RCP4.5 scenario
GCMs: CMIP5
• CMIP5 is the latest completed phase of the
Coupled Model Intercomparison Project
(2010-2014)
• It consists of 49 models and four
Representative Concentration Pathways,
which allow a range of future climate
projections
• Used for the IPCC AR5 (2013)
• The data is freely available for anyone to
access and use for their own climate
research

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GCMs: QUMPGCMs: QUMP
• In addition to using a multi-model ensemble, research
centres run Perturbed Physics Ensembles to assess
climate model uncertainties
• These are the same climate model run many times with
different plausible starting variants
• QUMP (Quantifying Uncertainties in Model Projections) is
the Met Office Hadley Centre’s PPE.
• It has 17 members which are formulated to systematically
sample parameter uncertainties under the A1B emissions
scenario
• QUMP has been used for the UK’s own national climate
projections, including the recently completed UKCP18

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RCMs: downscaling methods
• RCMs downscale GCMs to a resolution of 50km or less to
provide fine scale representation of a region’s climate
• These finer resolution results can be used in impact
models
• The two main downscaling methods are dynamical and
statistical
• Statistical downscaling uses relationships between large-
scale and regional processes to estimate regional climate
• Dynamical downscaling directly models physical
processes at regional scales, but require large
computational power
• Both techniques will pass on any biases in the driving
GCM to the RCM results

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RCMs: CORDEX South Asia
• CORDEX (Co-Ordinated Regional Downscaling
Experiment) is a framework to evaluate the performance of
RCMs produced by modelling centres around the world.
• Various RCMs are used to downscale CMIP5 GCM data
over regional domains
• CORDEX South Asia consists of 13 RCMs covering the
SA region, and has a resolution of 0.44 degrees
• Raw data is available from the Earth System Grid
Federation data nodes and processed data is provided by
the Center for Climate Change Research (CCCR), Indian
Institute of Tropical Meteorology (IITM) who are the
regional lead

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• PRECIS (Providing Regional Climates for Impacts
Studies) is a regional climate modelling system
developed at the Met Office Hadley Centre
• It allows users to easily produce detailed climate
projections for any region of the world without
requiring large computing power.
• PRECIS is based on the atmospheric component
of the Met Office Hadley Centre's coupled climate
model, HadCM3, which was used in CMIP3
• PRECIS has been utilised in a wide range of
climate-related studies and impacts research
projects across the world, including in the ARRCC
region of South Asia
RCMs: PRECIS

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The challenge
Multiple models:
• GCMs: CMIP3,
CMIP5, QUMP
• RCMs: CORDEX,
PRECIS
Multiple scenarios:
• RCPs
• SRES
Multiple methods:
• Dynamical
• Statistical
How do we make sense of all this information?
How can we make the best use of this information to inform decision makers?

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Our goal is to understand the user’s requirements so that producers can extract relevant messages
and communicate them in an appropriate format
Distillation means:
‘A process of comparing, understanding and combining multiple sources of climate
information to create a coherent and scientifically robust audience appropriate output”
It involves an iterative process between users and producers of the climate information:
Distillation of climate information
Users of climate information Producers of climate information
Knowledge and requirements define
what’s required from the climate
information to inform decision-making
Technical knowledge and expertise to
conduct appropriate scientifically robust
analysis to meet the users requirements

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Co-production iterative process: user engagement
Technical process: MO and local scientists
Development of clear, concise, scientifically robust, audience-appropriate messages
Decisionstobemade
Visualisation CommunicationModel/data selection Combining output
from multiple
sources
Identify appropriate
analysis
Identify users and
their vulnerabilities
to weather and
climate through:
• Questionnaires
• Interviews
• Workshops
Agree appropriate
analysis:
• Variables,
• Timescales,
• Spatial scales,
• Scenarios
Multiple models:
• MMEs, PPEs
Multiple scales:
• GCMs, RCMs
Multiple methods:
• Dynamical
• Statistical
Multiple scenarios:
• RCPs, SRES
Model democracy:
• All models
equally weighted
• Sub-selection or
weighting of
models
Model selection:
• Verification
• Representation of
processes
• Span range of
plausible futures
• Selection of
content to visualise
• Development of
visualisations that
show important
aspects
• Conversations
• Transparency
• Narratives
• Scenarios
The ‘distillation funnel’

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Thank you
Any questions?
cathryn.fox@metoffice.gov.uk