- CCCR - Indian Institute of Tropical Meteorology

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Transcript - CCCR - Indian Institute of Tropical Meteorology

Introduction of CCCR-IITM
R. Krishnan
Centre for Climate Change Research
Indian Institute of Tropical Meteorology, Pune
Objectives
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Harness the strengths in science to better understand global and regional climate change
with particular focus on the South Asian monsoon
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Understand impacts of global warming on planetary scale phenomena like monsoons and
El Niño
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Understand the nature of biogeochemical interactions and their response to climate
change
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Create and update information reservoirs for better assessment of climatic changes and
their impacts
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Identify and explore new areas of research that will contribute to the fundamental
understanding of the Earth’s climate system
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Build linkages with national and international research groups to optimally leverage
scientific capabilities for climate change research
CCCR
Administration
Scientific Research
Modeling Program
Outreach
Observational Program
Objectives
 To understand Past Changes in Monsoon Climate
To build a Global Earth System Model to address
the Attribution & Projection of regional climate
change – (Long-term)
To develop regional climate change scenarios over
South Asia using High-resolution Regional
Climate Models ; quantify uncertainties for
providing reliable inputs for impact assessments.
Contribute to IPCC AR5 – (Short-term)
using Multiple Proxy Records. Reconstruction of
monsoon indices going back to a few thousand
years
 Co-ordinate the MoES flux network program to
measure GHG flux variations across diverse
ecosystems and vegetation types over India
 To promote Outreach and Training for Capacity
Building in Climate Change Research and
Dissemination of Information
Increase in Surface Temperature
Observations
Predictions with Anthropogenic/Natural forcings
Predictions with Natural forcings
1.0º C
Attribution: Are increases in greenhouse gases responsible for global warming?
IPCC 2007
Primary synoptic and smaller-scale circulation features that affect cloudiness and precipitation
in Summer monsoon region. Locations of June to September rainfall exceeding 100 cm over
the land West of 100oE associated with the southwest monsoon are indicated (Rao, 1981).
Those over water areas and east of 100oE are omitted.
Challenges in assessment of future changes in South Asian
monsoon rainfall
Source: Kripalani
et al. 2010
•Wide variations and uncertainties among the IPCC AR4 models in capturing the
mean monsoon rainfall over South Asia (eg., Kripalani et al. 2007, Annamalai et
al. 2007).
•Realism of present-day climate simulation is an essential requirement for
reliable assessment of future changes in monsoon
Questions : On Attribution?
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How much of the observed variability of the mean Indian Summer
Monsoon rainfall due to Climate Change?
How much of the observed increase in temperature over India been
decreased by increasing presence of aerosols?
Questions : On Projections of Monsoon
• What will happen to the monsoon hydrological cycle 50-100 years from
now under different scenarios? In particular, will the quantum of seasonal
mean rainfall increase or decrease and if so by how much?
• What is the uncertainty in these projections? Can we quantify this
uncertainty?
• How can we reduce this uncertainty?
Strategy on Regional Climate Change Research at IITM
Centre for Climate Change Research (CCCR)
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To build capacity in the country in high resolution coupled
ocean-atmosphere modelling to address issues on Attribution
and Projection of regional Climate Change
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To provide reliable input for Impact Assessment studies
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Earth System Model (ESM)
Dynamic downscaling of regional monsoon climate using high
resolution models; quantification of uncertainties
Observational monitoring: Network with other Institutions
Roadmap towards Earth System
Model (ESM) development
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Start with an atmosphere-ocean coupled model with
realistic mean climate
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Fidelity in capturing the global and monsoon climate
Realistic representation of monsoon interannual variability
Features of ocean-atmosphere coupled interactions
Same modeling framework for seasonal monsoon prediction
…
Include components of the ESM
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Biogeochemistry Module (Terrestrial and Marine)
Aerosol and Chemistry Transport Module
…
Basic framework for global climate modeling
NCEP Coupled Forecast System (CFS-2) T126L64
• The NCEP CFS Components
• Atmospheric GFS (Global Forecast System) model
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–
–
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–
–
–
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– T126 ~ 110 km; vertical: 64 sigma – pressure hybrid levels
– Model top 0.2 mb
– Simplified Arakawa-Schubert convection (Pan)
– Non-local PBL (Pan & Hong)
– SW radiation (Chou, modifications by Y. Hou)
– Prognostic cloud water (Moorthi, Hou & Zhao)
– LW radiation (GFDL, AER in operational wx model)
- Land surface processes (Noah land model)
• Interactive Ocean: GFDL MOM4 (Modular Ocean Model, ver.4)
– – 0.5 deg poleward of 10oN and 10oS; and 0.25 deg near equator (10oS – 10oN)
– – 40 levels
– – Interactive sea-ice
PRITHVI (High Performance Computing System) , IITM, Pune
Configuration of PRITHVI, HPC at IITM:
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IBM P6 575 nodes totaling 117 numbers including the 2 nodes for GPFS quorum
and one Login node. Each node is populated with 32 cores of IBM P 6 CPU
running at 4.7 G Hz. Total of 3744 cores with Peak Performance of 70 Tflops.
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High end Servers P570’s, P550’s, 20 Visual Workstations.
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Interconnectivity using Infiniband Switches and Ethernet
Management purposes
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Total of 3 Peta Bytes of Storage including Online, Near-line and Archival
Storage
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GPFS, Tivoli and other Management Softwares
switches for
CFSv2 precipitation (JJAS): 100-yr mean
CFSv1 precipitation (JJAS): 100-yr mean
TRMM precipitation (JJAS): 10-yr mean
CMAP precipitation (JJAS): 30-yr mean
CFSv2 runs from CCCR on PRITHVI
Results from the CFS2 validation runs
cold bias
CFS2 Bias
(Model minus Obs)
Sea Surface Temperatures
(Annual Mean)
Preethi et al. (2013): Under preparation
CFS2 Bias
(Model minus Obs)
Precipitation
(Annual Mean)
Basic structure of ESM
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Include ESM components in the CFS-2 coupled ocean-atmosphere model
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Incorporation of Ocean Biogeochemistry Component (MOM4P1) - Completed
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Incorporation of Aerosol Transport Module - Partially completed and ongoing
Centre for Climate Change Research (CCCR), IITM, Pune
Research Highlights
Earth System Model (ESM) development: . The first version of the Earth System Model
(ESM 1.0) has been successfully developed at CCCR-IITM by incorporating a Marine
Biogeochemistry and Ecosystem component known as TOPAZ (Tracers of Phytoplankton
with Allometric Zooplankton, GFDL, Princeton) in the CFS global coupled GCM at IITM.
The ESM development activity is a
significant progress in climate modeling
towards understanding the global and
regional climate response to biogeochemical processes & the mechanisms
that control the ocean carbon cycle
Detailed testing and validation of ESM1.0 is
in progress
Team: Swapna, Roxy, Aparna, Ketan, Ashok, Krishnan
Preliminary results from a 36-yr run of the CFSv2 and ESM1.0 starting from Dec 2009 IC
The ESM 1.0 run shows significant improvement of reduction of cold SST bias
The CFSv2 run shows a systematic SST cooling bias (blue line) during the model spin up
Global Mean Monthly Temperature (oC)
Months
Global Mean Annual Temperature (oC)
ESM
CFSv2
Year
Comparison of ESM and CFSv2 simulations ~ 80 years free run from 2010 onward
Air temp (2 m)
SST
Tropical SST
Tropical SST
Ht cont
Courtesy: Swapna, CCCR
Annual mean SST difference (Model minus WOA)
ESM1.0
CFSv2
Zonal mean annual mean temperature
Courtesy: Swapna, CCCR
Precipitation (mm day-1): JJAS mean
CFSv2
ESM1.0
TRMM
Leading pattern of SST variability in the tropical Pacific from EOF/PC analysis
Observations
(HadiSST)
ESM1.0
CFSv2
Courtesy: Swapna, CCCR
Wavelet power spectra of Nino3 SST
Observations (HadiSST)
ENSO
PDO
ESM 1.0
ENSO
PDO
CFSv2
ENSO
Precipitation
(10N-30N; 70E-100E)
Indian (land +Ocean)
Courtesy: Preethi, CCCR
Lag/lead correlation between ISMR and Nino3 SST
Courtesy: Preethi, CCCR
Nino3 SST
Incorporation of Aerosol Transport Module in CFSv2
IITM ESM
Framework superstructure
Gridded
components
Max Planck Institute
MPI-ESM
Coupler
components
GFS
MoM4
Initialization
•initialize atmosphere
•read spectral fields
•tracers frozen (=3)
•read surface files
Run
•Clim. aerosol
•radiation call
output
Earth System Modeling
Framework infrastructure
MPI-OM
SUBMODELS
HAM, MOZ ,..
5 Species: sulfate,
seasalt, blackcarbon, organic
matter & dust
Emission inventory
Aerosol transport,
dry & wet
deposition/
sedimentation
Nucleation,
condensation,
coagulation and
thermodynamics
extinction cross
section, single
scattering albedo,
asymmetry
parameter
OASIS
Coupler
ECHAM6
Initialization
•initialize atmosphere
•read emissions
•register submodels
•allocate memory
•read aerosol emission
Run
•read boundary cond
•physics calculations
•diffusion
•cloud & surface calc
•diagnostics
output
Distinct features
GFS & ECHAM have
different grid
structure
Parallelization &
redistribution
scheme differ
submodels are not
standalone - derives
time, date, memory
structure from
ECHAM
HAM variables are
grouped in streams
for calculations and
for outputs
ECHAM handles
HAM outputs
Team: Ayantika, Jayant, Ramesh, Ingo Kirchner, Krishnan, Ashok
WCRP CORDEX South Asia – led by CCCR, IITM
Co-ordinated Regional Downscaling Experiment – CORDEX South Asia
South Asia
•Better understand regional climate processes and improve climate models
•Develop reliable high-resolution regional climate change scenarios globally, thereby contributing to the IPCC AR5 and to the climate
community beyond the AR5
•Evaluate regional climate model performance through a set of experiments aiming at producing regional climate projections
•Quantify and understand the uncertainties in regional climate projections
•Develop regional capacity for assessment of regional climate change with higher level of confidence of model-based projections and
judgment of regional experts
•Link climate modeling better with regional impact, adaptation and vulnerability assessment
•Integrate the regional downscaling activities, facilitate cross-fertilization of scientific expertise and engage the community of regional
scientists for further capacity building in the region
Paleoclimate research
Approach
1. Palaeoclimate reconstruction along N-S and E-W transact.
2. Proxies:
- Tree-ring
- Speleothems
- Corals
Courtesy: Hemant Borgaonkar
W. Himalaya
Srinagar
Simla
Nepal
Tibe
t
New Delhi
Central India
Bhopal
Peninsular
India
B’lore
Th’puram
Tree-Ring Network over India
Dendro-climatic Studies
Highlights
0.6
0.4
0.2
0
-0.2
-0.4
Year
• Tree-ring Drought Records of Indian
Monsoon rainfall since past five centuries.
2001
1981
1961
1941
1921
1901
1881
1861
1841
1821
1801
1781
1761
1741
1721
1701
1681
1661
1641
1621
1601
-0.6
1581
• Teak tree-ring chronologies from central
& south India indicate positive relationship
with monsoon and annual rainfall and PDSI
suggests the important role of moisture in
tree growth climate relationship.
0.8
1561
Longest tree-ring chronology of Tectona
grandis (Teak) from Kerala (AD 1481 -2003
523 Years).
1541
•
1521
Higher growth in recent years observed in
high altitude near glacier tree-ring
chronologies
of
western
Himalaya
associated with increasing temperature
trend.
1501
•
1481
Longest tree-ring chronology of Cedrus
deodara from Gangotri (A.D. 1450-2003;
554 Years)
R.W. Index Anomaly
•
Tree-ring width index chronology of Cedrus deodara from
Western Himalaya
2
X̄ + 2σ
Ring width Index
1.5
1
0.5
0
1650
X̄ - 2σ
1700
1750
1800
Reconstructed
Year1850
1900
1950
2000
Observed
Reconstructed Extreme pre-monsoon years prior to A.D.1879 over western Himalaya
1691, 1717, 1721, 1729, 1738, 1749, 1759, 1769, 1782, 1815, 1830, 1839, 1847, 1850, 1851, 1860
The strong relationship between extreme pre-monsoon climate and pointer years (narrow rings) might
have been held good for past several centuries. About 16 regional pointer years were observed prior to
A.D 1879., which would most probably be due to the extreme pre-monsoon summer. Such long proxy
records of extreme climate information would be important to understand the long term climate change in
the context of recent warming scenario.
Fluxnet Project: quantifying the ecosystem fluxes
Mahabaleswar: Flux tower measurement over a forest canopy representatives
of Western Ghats to quantify forest atmosphere exchange of CO2, water vapor
and energy.
Kaziranga National Park Soil plant atmosphere study in relation to net CO2 flux
from terrestrial ecosystem of Assam
Darjeeling: Study of biosphere-atmosphere exchange of GHG in a tropical high
altitude forest canopy at Eastern Himalaya (Darjeeling, W.B.)
Lakshwadeep: Study on flux of GHG governed by bio-physical processes in the
Lakshadweep Island.
Pichavaram: Studies on green house gas fluxes in Pichavaram Mangrove ecosystem.
Port Blair: Studies of carbon sequestration off Port Blair and surrounding group of
islands, Andamans.
Courtesy: Supriyo Chakraborty
Darjeeling, W.B
Mahabaleswar, Maharashtra
Lakshadweep Island
Kaziranga
National Park
Assam
Pichavaram mangrove
ecosystem
Port Blair
Andaman Islands
CO2 and GHG monitoring and inverse modeling for source / sink estimation
Sinhagad observational site
Source: Yogesh Tiwari, CCCR, IITM
CO2 and GHG monitoring and inverse modeling for source / sink estimation
Figure : Measured concentrations of CO2 (top) in air samples collected at CRI (symbol) along with fitted curve to the data
points using a digital filter (black line). Smoothed fits to the Mauna Loa (blue line) and SEY data (red line) obtained by CSIRO
and ESRL programs respectively, are shown for comparisons. Comparisons of inter-seasonal and inter-annual variability in
CO2 (bottom) at CRI site
Current Science, 2009
Source: Yogesh Tiwari, CCCR, IITM
CO2 (ppm)
CO2, Sinhagad (SNG) – Mauna Loa (MLO)
Running mean
smoothing using
adjacent averaging
9-points
Ongoing and near-future plans
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Basic research and developmental work (ie., publications, ESM, CORDEX, Fluxnet etc)
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ESM2.0: Complete incorporation of aerosol transport module in CFSv2 -- Timeline 1 yr
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CORDEX Data Portal: Archival, management, sharing , distribution and publication of
CORDEX data from multiple models – Time line 1 year
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Paleoclimate studies:
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Expand the Indian tree-ring data network by using tree-ring data from South and Southeast Asia viz.,
Nepal, Myanmar, Thailand, Indonesia, etc to develop large-scale proxy climate for Monsoon Asia
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Reconstruct monsoon rainfall variations covering more than 20000 years from Speleothem records
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Precipitation isotope analysis across the east-west transect across the Western Ghats to identify
moisture sources during the monsoon and estimation of recycled moisture over the region
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Characterize amount effect in precipitation of different places in India
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MoES GHG fluxnet program: Complete procurement of equipments, instruments and
sensors. Setting up of fluxnet towers and GHG measurement system at six locations of
India. Link fluxnet activity and background CO2 concentration measurements from
Sinhagad together with climate model experiments to estimate sources and sinks;
validate model estimates with fluxnet data
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Macroscale hydrological modeling: Assessment of hydrological impacts of climate
change on river basins of India and quantification of uncertainties - based on macroscale
hydrological model simulations driven by regional climate projections
Thank you