Climate modelling on regional and
local scale
Edoardo Bucchignani (e.bucchignani@cira.it)
CMCC, Euromediterranean Center on Climate Change,s Impacts on Soil and Coasts
CIRA, Italian Aerospace Research Center, Meteo System and Instrumentation
0
Outlook
• Introduction
• Climate Change: an Integrated framework
• Global Models and Regional Climate Models
• The IPCC scenarios
• Dynamical Downscaling
• The COSMO – CLM model
• Example of climate projections over Africa
• Concluding remarks and Discussion
Slide 1
CMCC Euro-Mediterranean Centre on Climate Change
• CMCC is a non-profit research Institution;
• Established in 2005, with the financial support of the Italian Ministry of Education,
University and Research and the Ministry of the Environment, Land and Sea;
• CMCC manages and promotes scientific and applied activities in the field of
international climate change research;
• CMCC involves and links private and public institutions jointly investigating
multidisciplinary topics related to climate science research;
• CMCC offices: Lecce, Bologna, Capua, Milan, Sassari, Venice, Viterbo, Benevento;
• CMCC’s mission is to investigate and model our climate system and its interactions with
society to provide reliable, rigorous, and timely scientific results to stimulate sustainable
growth, protect the environment and to develop science driven adaptation and mitigation
policies in a changing climate.
Impacts on Soil and Coast (ISC) of CMCC
This division has 2 units:
• The first Unit focuses on the hydrogeological risks connected with climate change and
integrates climate models at the regional scale with the analysis of risks related to
extreme events and their impacts (such as landslides, floods and hydrological drought).
• The second Unit aims to develop and apply methodologies to analyze environmental
impacts and risks correlated with climate change and natural hazards. The team also
focuses on the impact of climate change regarding pollution at the regional and global
scale in order to identify its potential effects in modifying the bioavailability to toxic
chemicals.
• ISC Division is also responsible for the development of the regional climate model
COSMO CLM. The first unit, in particular, is involved from 2008 in the activities of the
CLM Community.
• We are currently performing numerical simulations at 0.44o resolution over MENACORDEX domain, driven by ERA-Interim reanalysis for the period 1979-1984, in order
to find an optimal configuration of the model.
Climate Change – an integrated framework
Adaptation
Mitigation
To Manage the unavoidable
To Avoid the unmanageable
Slide 4
How can we understand better the Earth system?
Observations
A numerical laboratory
•Experimentation with Earth is not practical
•Numerical models of the Earth system
allow systematic experimentation
•Experimental design making optimal use
of the flexibility of the model system under
the practical limitations
• Easy possibility to run experiments and
store data
•Diagnostic tools to evaluate the model
data
Slide 5
The global effort to predict the climate
It is possible to predict the
climate if we represent the
climate system as a set of
mathematical equations: the
equations of climate.
The equations of climate are
very complex, but they can be
solved in approximate way by
numerical techniques:
the numerical models of
climate.
6
Computational
cells:
Temperature,
Wind,
Pressure
…
Slide 6
Approximations and Assumptions
Physical errors: the mathematical model is just a simplified representation of
the real world!
Numerical errors: governing equations cannot be solved in analytical way, but
only through approximate numerical procedures!
Moreover, due to the high computational costs for the evaluation of some
physical phenomena, the equations “introduced” in the supercomputer must be
further simplified (e.g. processes inside clouds, radiative interaction processes,
soil-atmosphere interaction processes).
7
Slide 7
The Earth System Models
Earth System Model (ESM) comprises several models representing the coupled
dynamics, physics and chemistry of the global atmosphere and world oceans
ESM Modules
•Atmosphere: atmospheric fluid dynamics and thermodynamics, moist
processes, radiative transfer, transport and chemistry of trace
constituents
•Ocean World: ocean circulation, ocean biogeochemistry
•Land surface: Surface processes, ecosystems, hydrology
•Ocean surface: Sea ice, wave processes.
Slide 8
ESM in Europe
Center
Country
Atmosphere
Atm-Strat
ocean
sea ice
coupler
land sfc
atmos
ocean
chem
biogeochem
PISCES
IPSL
France
LMD
NEMO
NEMO/LIM
OASIS3
ORCHIDEE
INCA
CNRM
France
ARPEGE
NEMO
GELATO
OASIS
ISBA-A-gs
MOCAGE
Hadley (GEM2)
UK
UM
NEMO
CICE
OASIS
Hadley (GEM3)
UK
UM
NEMO
CICE
OASIS
JULES
UKCA
ECHAM5
MPI-OM
EcBilt
CLIO
CLIO
ECHAM5
NEMO
LIM
OASIS3
NEMO/LIM
OASIS
Cerfacs
NERC
UK
COSMOS
Germany
OASIS
MESSy
HAMMOZ
Finland
Sweden
LOVECLIM
Belgium
CMCC
Italy
DMI
Danemark IFS/ARP/ECHAM
NEMO
NL
IFS
NEMO
NCAR
MICOM
NCAR/CICE
GISS
GISS
VECODE
LOCH
SILVA
PELAGOS
OASIS4
NCAR
HAMOCC
GISS
GISS
EC-EARTH
KNMI
OASIS
ECMWF
SMHI
Sweden
Ireland
Switzerland
Danemark
Portugal
Bjerknes
Norway
NERSC
Norway
BSC
Spain
CAPC
Greece
NCAR/GISS
GISS
developed
under devt
GISS
GISS
Slide 9
The CMCC coupled atmosphere-ocean G C M
ATMOSPHERE (dynamics, physics, prescribed
gases and aerosols)
Global
Atmosphere
ECHAM5 T159 (~ 80Km ) - L31
Roeckner et al. (2006)
Heat Flux
Mass Flux
Momentum Flux
SST
SS vel.
Global Ocean
& Sea-Ice
COUPLER Oasis 3
Valcke et al. (2004)
OCEAN (dynamics and physics)
OPA (Barnier et al. 2006)
SEA-ICE: LIM (Timmermann et al. 2005)
Slide 10
The IPCC Scenarios
A plausible description of how the future may develop, based on a coherent and
internally consistent set of assumptions about key relationships and driving forces (e.g.,
rate of technology changes, prices). Note that scenarios are neither predictions nor
forecasts.
These scenarios describe several factors associated with climate change in the XXI
century.
These factors include emission levels for 10 greenhouse gases, regions’ economic
viability, energy technology in use, resources in use, land use, and carbon
sequestration rates.
Marmolada, begin of XIX century
Marmolada today
Slide 11
Radiative forcing
It is a measure of the influence of
these factors in altering the balance of
incoming and outgoing energy in the
Earth - atmosphere system and is an
index of the importance of the factors
as a potential climate change
mechanism.
IPCC 5th Coupled Model Intercomparison project (CMIP5)
Slide 12
CMPI5: Representative Concentration Pathways (RCP)
RCP8.5: high emissions scenario, high population growth, slow per capita
income growth, little convergence by high and low countries; coal intensive
energy scenario
RCP4.5: high income growth, low population growth, gains in clean energy and
efficiency resulting from aggressive carbon pricing ($85/ton CO2 by 2100)
Carbon Dioxide and Methane concentration time series used to force the atmospheric component
of the CMCC CGCM model according to the different scenarios.
Slide 13
CMCC IPCC Experiments: Global mean surface temperature anomaly.
Slide 14
The CMCC global simulations: T2M changes
RCP8.5: T2m at the end of the 21st century might be larger than 3.5 °C with respect to the Slide 15
reference period.
The CMCC global simulations: Total Precipitation changes
Projected
changes
in
precipitation are less linear.
The projected increase in the central part of Africa (up to 60%,) is more pronounced
and extended northward in A1B scenario if compared to the other ones.
Slide 16
Precipitation Projections: consistency with other global models
CMCC
Slide 17
Global changes, local changes:
the problems of downscaling
Slide 18
Reasons why downscaling of GCM output is useful
• There are important differences between the real world
and its model representation;
• small-scale effects (such as topography) important to
local climate could be poorly represented in the GCM;
• variables such as streamflow may not be represented
explicitly by the GCM;
• GCMs are not perfect and their forecasts are subject to
error (i.e., parameterization schemes are not perfect);
• Impact models need high resolution data.
19 Slide 19
Downscaling Definitions
Simulation of climate sub-grid-scale based on output from global climate
models. It can be performed:
by
developing
a
statistical
relationship between local climate
variables and model predictors
(large scale variables).
Statistical downscaling
by explicit solving of processbased physical dynamics of
the regional climate system.
Dynamical downscaling
20 Slide 20
The simulation cascade
Cascade
Forecasts
•
Global Models (GCM)
– Require initial conditions
– Low horizontal and vertical resolution
•
Regional Climate Models (RCM)
– Require Boundary conditions (by GCM)
– High resolution and nesting
•
Specific high resolution models
Example: specific models for the
reconstruction of a wind field on complex
orographic areas
21 Slide 21
Global Circulation Model vs Limited Area Model
Orography
22 Slide 22
The COSMO CLM REGIONAL MODEL
The regional model used for the simulations is COSMO-CLM (1-50 km of
horizontal resolution)
23 Slide 23
Overview
• The COSMO-CLM is the Climate Mode of the COSMO model system:
• It is a non hydrostatic regional climate model atmospheric prediction system, developed by
the CLM-Community.
•It is designed for simulations on time scales up to centuries and spatial resolutions down to 1
km.
• It is the only limited area numerical model system in Europe which has a range of
applicability encompassing:
1.
2.
3.
4.
operational numerical weather prediction (COSMO)
regional climate modelling of past, present and future (CLM),
the dispersion of trace gases and aerosol (ART) and
idealized studies (ITC)
• It is applicable for downscaling in all regions of the world and of most of the Global Climate
simulations available
• It is fully documented.
• it is freely available for scientific purposes
Slide 24
COSMO-CLM: Overview
A huge variety of applications of the model system exists within more than 300
scientific projects in the field of regional climate modelling covering:
• high resolution simulations of mega-cities
• medium resolution simulations of continents
• tropical to arctic latitudes
• paleo studies, the recent past and climate scenarios for the 21st century.
This makes it highly relevant for climate science and for climate mitigation and
adaptation politics.
However, the development of a fully dynamical reliable regional earth system model is
still ongoing.
Slide 25
Why a non-hydrostatic model for weather and climate ?
Better description of convective phenomena with respect to hydrostatic models (the convective rain is
characterized by localized and intense rainstorm)
•Challenges of NWP
- Local accuracy for agriculture, industry and
society
-Prediction of extreme weather events
•Challenges of RCM
- Climate and climate change of vulnerable
regions for climate application studies
- Climate Change of extreme event statistics
Slide 26
Climate models need to be further developed
Snow or Rain? Winter-sport regions need reliable
predictions Salzburg, 2011
Parameterizations
The governing equations are not sufficient in order to give a complete
description of the phenomena that take place in the atmosphere.
Some phenomena, take place on unresolved motion scales, but they have
significant impact also on the scale of meteorological impact.
Examples: turbulent diffusion in the atmosphere, interaction with the orography,
convection.
In order to improve the quality of the previsions of model, the effects of these
phenomena are taken into account by means of PARAMETERIZATIONS.
Slide 27
The CMCC work plan
Study of the climate of Lebanon
Collection and analysis of the available data
Set up of the regional climate model on the region of interest
Climate simulation related to a past period (e.g. 1979-2011) (1994)
Validation with available observations (e.g. CRU dataset)
Execution of the climate projections for the period 2006 - 2100, employing the
IPCC RCP4.5 and RCP8.5 emission scenarios
Evaluation of : rainfall probability curves (format utilizable by
hydrologist), seasonal cycle of surface temperature and extreme climate
indices.
Bias correction (if needed)
Slide 28
IBM Power6 supercomputer
Architecture:
Cluster of 30 IBM P575 nodes
Configuration: 30 Nodes
Each node has 32 (4.7 GHz) cores
and 128 GB of memory
18 Tflops computing power
Infiniband 4x DDR interconnection
Operating system: AIX 5.3
Compilers:
Fortran90, C/C++
Slide 29
IBM High Performance Computing system
Architecture: Cluster of INTEL Sandy Bridge processors
Xeon E5-2670 2,6 GHz
Configuration:
482 bi-processor iDataplex dx360 M4 computing nodes
FDR InfiniBand network (56Gb/sec) interconnection
The theoretical peak performance of the system
(7712 cores in total) is about 160Tflops
Operating system: CentOS v.6.2 ( Linux kernel )
Compilers:
Fortran90, C/C++
Slide 30
Climate projections over over SubSaharian Africa
2021-2050 vs. last thirty years of the XX century.
Simulations performed at 8 km resolution, driven by CMCC-MED (80 km
resolution).
Slide 31
T2m : future (2021-2050) vs past (1971-2000)
RCP4.5
DJF
Less evident increase of
temperature, especially in
JJA.
In
DJF,
significant
increase in the northern
part.
JJA
Slide 32
T2m : future (2021-2050) vs past (1971-2000)
RCP8.5
DJF
Larger
increase
of
temperature in JJA with
respect to the other
scenario.
In DJF, the increase is
evident
only
in
the
northern part.
JJA
Slide 33
Precipitation: future (2021-2050) vs past (1971-2000)
RCP4.5
There are differences
between
the
two
seasons.
In DJF, there is a
general increase of
precipitation, while in
JJA there is a summer
there is a general
increase with some
exceptions.
Slide 34
DJF
JJA
Precipitation: future (2021-2050) vs past (1971-2000)
RCP8.5
In DJF, there is a
general increase of
precipitation, similar to
RCP4.5
DJF
In JJA there is a
behavior similar to
RCP4.5
JJA
Slide 35
T2m and precipitation Trend (A1B vs RCP 4.5)
Ouagadougou
St.Louis
Slide 36
Thank you for your attention
e.bucchignani@cira.it