Climate modelling on regional and local scale - PowerPoint PPT Presentation

1 / 38
About This Presentation
Title:

Climate modelling on regional and local scale

Description:

Climate modelling on regional and local scale Edoardo Bucchignani (e.bucchignani_at_cira.it) CMCC, Euromediterranean Center on Climate Change,s Impacts on Soil and Coasts – PowerPoint PPT presentation

Number of Views:160
Avg rating:3.0/5.0
Slides: 39
Provided by: Ciro89
Category:

less

Transcript and Presenter's Notes

Title: Climate modelling on regional and local scale


1
  • Climate modelling on regional and local scale

Edoardo Bucchignani (e.bucchignani_at_cira.i
t) CMCC, Euromediterranean Center on Climate
Change,s Impacts on Soil and Coasts CIRA, Italian
Aerospace Research Center, Meteo System and
Instrumentation
2
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
3
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
  • CMCCs 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.

4
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 MENA-CORDEX domain,
    driven by ERA-Interim reanalysis for the period
    1979-1984, in order to find an optimal
    configuration of the model.

5
Climate Change an integrated framework
To Manage the unavoidable
Adaptation
Mitigation
To Avoid the unmanageable
Slide 4
6
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
7
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.
Computational cells Temperature, Wind,
Pressure
Slide 6
8
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
9
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
10
ESM in Europe
Slide 9
11
The CMCC coupled atmosphere-ocean G C M
Heat Flux Mass Flux Momentum Flux
SST SS vel.
Slide 10
12
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
13
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
14
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
15
CMCC IPCC Experiments Global mean surface
temperature anomaly.
Slide 14
16
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
reference period.
Slide 15
17
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
18
Precipitation Projections consistency with other
global models
CMCC
Slide 17
19
Global changes, local changes the problems
of  downscaling
Slide 18
20
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
21
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).
by explicit solving of process-based physical
dynamics of the regional climate system.
Statistical downscaling
Dynamical downscaling
20
Slide 20
22
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
23
Global Circulation Model vs Limited Area Model
Orography
22
Slide 22
24
The COSMO CLM REGIONAL MODEL
The regional model used for the simulations is
COSMO-CLM (1-50 km of horizontal resolution)
23
Slide 23
25
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. operational numerical weather prediction (COSMO)
  2. regional climate modelling of past, present and
    future (CLM),
  3. the dispersion of trace gases and aerosol (ART)
    and
  4. 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
26
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
27
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

Climate models need to be further developed Snow
or Rain? Winter-sport regions need reliable
predictions Salzburg, 2011
Slide 26
28
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
29
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
30
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
31
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
32
Climate projections over over Sub-Saharian
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
33
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
34
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
35
Precipitation future (2021-2050) vs past
(1971-2000)
RCP4.5

DJF
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.
JJA
Slide 34
36
Precipitation future (2021-2050) vs past
(1971-2000)
RCP8.5

DJF
In DJF, there is a general increase of
precipitation, similar to RCP4.5 In JJA there is
a behavior similar to RCP4.5
JJA
Slide 35
37
T2m and precipitation Trend (A1B vs RCP 4.5)
Ouagadougou
St.Louis
Slide 36
38
Thank you for your attention e.bucchignani_at_cira.i
t
Write a Comment
User Comments (0)
About PowerShow.com