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Innovative Web Based Applications of High Resolution Climate Modeling
and Projections Techniques
CCRC, Columbia, SCOctober 31, 2018
Jenny Dissen, Engagement and PartnershipsNOAA Cooperative Institute for Climate and Satellites - NC
North Carolina State University
Contributors/Acknowledgements:Dr. Katharine Hayhoe (Texas Tech University); Dr. David Easterling (NOAA NCEI); Dr. Kenneth Kunkel
(NOAA CICS-NC); Andrew Ballinger, Ph.D., Research Scholar; Dr. Farhan Akhtar (US Department of State)
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Agenda
Indo-U.S. Partnership for Climate Resilience
Engagement Activities
Climate Analysis Tool
Looking Ahead…
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U.S.-India Partnership for Climate Resilience (US PCR)
• PCR initiated in September 2014 between President Obama and Prime Minister Modi
• Goals:• Advance our bilateral climate change relationship• Enable technical expertise and information exchange• Support strengthening of adaptation and resilience
planning and capabilities in regions of India
India Partners Involved:
• Officials in the Ministry of Earth Sciences
(MoES); Ministry of Environment, Forest &
Climate Change (MoEF&CC);
• Pune-based Indian Institute for Tropical
Meteorology (IITM);
• NGOs: EPTRI and TERI
• Private sector: Value Labs
U.S. Partners:
• Interagency Agreement (IAA) between
Department of State and NOAA
• NOAA National Centers for Environmental
Information
• NOAA Cooperative Institute for Climate and
Satellites – NC / NC State University
• Several university partners (Texas Tech
University)
• World Resources Institute
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India’s Policy – National and State Action Plans
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Workshops on Development and Applications of Climate Projections
• Downscaling Techniques and Applications• March, 2017 | IITM, Pune• Technical discussions, exercise, select applications
• High Resolution Climate Modeling Overview and Exercise• February 9, 2018 | The Energy and Resources Institute (TERI)
• High Resolution Climate Modeling Overview and Exercise• February 12 - 13, 2018 | EPTRI• Targeted for State Action Planners
• Climate and Health Workshop• October 23-24, 2018 | New Delhi• Vector-Borne Disease, Malaria, Predictive Capabilities
• Proposed: World Sustainable Development Summit (To be finalized)
• February 11 - 13, 2019 | New Delhi and Northern India• Technical workshop on climate modeling and projections
• Workshop focused on the India Himalayan Range
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Technical Sessions
Theories and methods of climate modeling, projections
and downscaling
Explorations of specific downscaled data sets—including
the World Climate Research Program’s CORDEX data
on South Asia
GFDL-NCPP “Perfect Model” Model Approach to
Comparing Downscaling Methods
Introduction to Asynchronous Regional Regression
Model (ARRM) and NASA Earth Exchange Global Daily
Downscaled Projections (NEX-GDDP) Outputs
Uses and Applications for Decision Making
• Case Study in Uttarakhand
• India State Action Plans and Vulnerability Risk
Assessments ... cases from several Indian states
• Sectoral examples: agriculture, infrastructure and
urban planning, water resources management
Discussion on downscaled climate information and its
application potentials in various sectors
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Workshop Experience
• Overall, a tremendous success – but:
• Participants challenged with:
• R (a programming language and IDE)
• Panoply (a simple graphical tool for
viewing climate data maps)
• Exercise used open-source resources
• Installation challenges
• Had to learn R code and various
libraries
• Code and Data (unwieldy)
• Download ~21 GB of data time
consuming
• Dr. Hayhoe’s code and data are on a
few thumb drives being passed
around…
• Biggest stumbling block: finding the code
and the data in R
• Second Biggest Stumbling Block:
misreading (or not reading) the instructions.
• Oops. I forgot the parentheses!
• Let’s try that again
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As a Result…
• EPTRI partnered with Value Labs to address
user experience and usability concerns
• Creating a web-based platform to visualize
downscaled data Climate Analysis Tool
(work in progress)
• Key Features:
• User not required to code in R
• Graphs and charts populated in the tool
• Improved user interaction with simple
drop down selection options
• Stakeholder no longer burdened with
issues with data and programming and
• Participants spending more time
discussing outcomes, results and
implications of changing climatic
conditions
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1. Analyze climate model
output at a location:• Observe and compare
trends by station data
• You will have the ability to
select various parameters
and indicators
• Download charts to
embed in presentations
• Download the data files
2. … and over the entire
region (or sub-region):• Observe spatial patterns
• Explore different future
climate periods
Tool Capabilities
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How often will temperature exceed a threshold?
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Features to Analyze Climate Questions
• Analyze different variables• Maximum daytime temperature• Minimum nighttime temperature• Average daily temperature• Precipitation• Degree-days
• Assess different indicators • Annual or seasonal average • Annual or season maximum or
minimum • The number of days above or below
a given threshold• Seasonal variations
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Annual Average Daily Maximum Temperature
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Average Total Rainfall from July to September
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Policy Innovation Support in Climate Assessments
• Translate climate projections into
relevant impacts information using
state-of-the-art, well-documented
climate models and well-evaluated
climate downscaling approaches
• Interact extensively with the
stakeholders
• Communicate findings to the
intended audience in a relevant,
accessible manner
The collaboration to build Climate Analysis Tool supports in climate assessments:
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Looking Ahead…
Further review, validate and develop additional features in the tool
Work with decision-makers and State Action Planners to incorporate their state information for use and analysis
Build engagement capacity discussions to assist decision-makers with understanding and using outputs
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More Information
Indo-U.S. Team
• David Easterling2
• Kenneth Kunkel1
• Jenny Dissen1
• Andrew Ballinger1
• Farhan Akhtar4
• Katharine Hayhoe5
• Anne Stoner5
• Bridget Thrasher6
Author Affiliation:1. Cooperative Institute for Climate and Satellites -
North Carolina / NC State University, Asheville, North Carolina
2. NOAA National Centers for Environmental Information, Center for Weather and Climate, Asheville, NC
3. U.S. Department of State, Washington D.C.4. Texas Tech University5. Stanford University
• Kalyan Chakraborthy
• Dr. Sesha Srinivas
• Dr. Ramesh
• Shaily Maloo• Dr. Ashwini Kulkarni (IITM Pune)
• Praveen Chakravarthula
• Sai Krishna Nooka
• Kiran Jangeti• Satyla Styavarapu
US Team India Team Value Labs
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Back Up Slides
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Overview of the station-based dataset:• Asynchronous Regional Regression Model (ARRMv1,2)
– Uses the ARRM downscaling technique, developed by Dr. Katharine Hayhoe, Dr. Anne Stoner, Ian Scott-Fleming and colleagues at Texas Tech University.
• Includes 6 global climate models from the CMIP5 suite:– CCSM4, GFDL-ESM2G, IPSL-CM5A-LR, MIROC5, MPI-ESM-LR,
and MRI-CGCM3 (more are available for expansion).
• Downscales 2 future climate scenarios: – Lower emissions (RCP4.5) / Higher emissions (RCP8.5)
• Three daily fields are currently available for analysis: – Maximum Temperature (°C)– Minimum Temperature (°C)– Precipitation (mm)
Station-based downscaling with ARRM
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The NASA NEX-GDDP Dataset
Overview of this gridded dataset:
• 21 global climate models from the CMIP5 suite
• 1 Historical and 2 Future scenarios:
– Lower emissions (RCP4.5) / Higher emissions (RCP8.5)
• BCSD downscaling to 0.25° x 0.25° (globally gridded)
• Three daily fields:
– Maximum Temperature (°C)
– Minimum Temperature (°C)
– Precipitation (mm)
• More info: https://cds.nccs.nasa.gov/nex-gddp/
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Climate Data Exercise
• 6 CMIP5 Global Climate Models (GCMs), selected for their
ability to reproduce the Indian Monsoon and their long
development history
• 2 future Representative Concentration Pathways (RCPs)
• 3 variables: daily maximum and minimum temperature, 24
hour cumulative precipitation
• 64 out of 79 weather stations
• 2 sets of downscaled projections
Projections for individual weather stations, downscaled using
ARRMv2 (for temperature) and ARRMv1 (for precipitation)
Gridded projections covering all of India, downscaled using
NASA NEX
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Two Future Scenarios: Higher and Lower
Continued reliance on fossil fuels, but with much greater efficiency than today.
Developed nations’ emissions peak, then decline, while developing nations’ emissions growth continues.
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Two Future Scenarios: Higher and Lower
Transition to alternative energy sources.Developed nations reduce emissions ~80% by 2050Developing nations participate in emission reductions.
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90° E
90° E
80° E
80° E
70° E
70° E
30° N 30° N
20° N 20° N
10° N 10° N
64 out of 79 long-term weather stations that have sufficient daily maximum and minimum temperature and 24 hour cumulative precipitation to be downscaled
Climate Data Exercise
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SAMPLE.PLOTS -> 3 TYPES OF EXCEL PLOTS
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SAMPLE.PLOTS -> 3 TYPES OF EXCEL PLOTS
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Key Take Aways
Downscaling Methods
• The “perfect model” framework for evaluating downscaling methods consistently identifies geographic locations and quantiles at which the stationarity assumption is violated.
• For temperature, all ESDMs show reasonable stationarity in the middle of the distribution in most regions but degrade toward the tails and at high latitudes, especially for simpler methods.
• For precipitation, methods show sharp differences depending on the quantile of the distribution. This has important implications for application of ESDM output to impact assessment.
• Using the “perfect model” framework as a development tool has created an ESDM with biases at least equal to, and generally lower than, its predecessor; upcoming research will test ARRMv2 biases in precipitation and relative humidity.
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I’d like to do my own downscaling
The downscaling we have provided uses:
(1) GHCN weather station data, available here: https://www.ncdc.noaa.gov/oa/climate/ghcn-daily/
(2) 0.25 degree gridded data from the Global Meteorological Forcing Dataset, available here: http://hydrology.princeton.edu/data.pgf.php
If the spatial and/or temporal resolution of these observations meet your needs, you do not need to do any further downscaling.
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SUMMARY
Climate is changing; incorporating future projections into planning can help cities prepare for a different future.
We scientists obsess over uncertainty, but on the ground even qualitative information (direction of trend) and awareness of vulnerabilities can be useful.
The key to success is integrating climate preparedness into existing planning frameworks and mechanisms, not treating it like something new.
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