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17th Annual Climate Prediction Application Science Workshop

Co-Authors: Dr. David Easterling1, Dr. Ken Kunkel2, Andrew Ballinger2 Dr. Katharine Hayhoe3, Dr. Farhan Akhtar4

Acknowledgements: Dr. Ashwini Kulkarni4

Presenter: Jenny Dissen2

Author Affiliation:1. NOAA National Centers for Environmental Information, Center for Weather and Climate, Asheville, NC2. NOAA Cooperative Institute for Climate and Satellites - North Carolina / NC State University, Asheville, North Carolina3. Texas Tech University4. US Department of State5. Indian Institute of Tropical Meteorology

Climate Projections for Informing Sectors and Climate Action Plans

In India

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Agenda

Ø Indo-U.S. Partnership for Climate Resilience

Ø Engagement Activities

Ø Climate Analysis Tool

Ø 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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Conducting Workshops on Development and Applications of Climate Projections

• Downscaling Techniques and Applications• March, 2017 | IITM, Pune

• 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

• Climate and Health Workshop• October 23-24, 2018 | New Delhi

• World Sustainable Development Summit (Under Development)• February 11 - 13, 2019 | New Delhi and Northern India• Technical workshop on climate modeling and projections• Workshop focused on the India Himalayan Range

• Regional Climate Modeling and Impacts Discussion (In Development)

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Workshop Focus Areas

Ø Theories and methods of climate modeling, projections and downscaling

Ø Explorations of specific downscaled data sets, includingØ the World Climate Research Program’s CORDEX

data on South AsiaØ NASA Earth Exchange Global Daily Downscaled

Projections (NEX-GDDP) Outputs

Ø GFDL-NCPP “Perfect Model” Model Approach to Comparing Downscaling Methods

Ø Introduction to Asynchronous Regional Regression Model (ARRM)

Ø 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

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Workshop Experience

• Oops. I forgot the parentheses!

• Let’s try that again• Web-based platform to visualize

downscaled data à Climate Analysis Tool (work in progress)

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1. Analyse climate model output at a location• Observe and compare

trends by station data• Select various parameters

and indicators

2. … Or over the entire region (or sub-region):• Observe spatial patterns• Explore different future

climate periods

Tool Features

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Key OutcomesInnovation for Climate Services

• Translate climate projections into relevant impacts information using state-of-the-art, well-documented climate models and well-evaluated climate downscaling approaches

• Enables extensive interaction extensively with various stakeholders and policy-makers

• Tool development currently a work in progress…with opportunity for more data and information

The collaboration to build Climate Analysis Tool supports in climate assessments:

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Looking Ahead…

Ø Continue working with decision-makers and State Action Planners to obtain, incorporate and analyze state or regional data

Ø Build engagement capacity and discussions to Ø Assist decision-makers with understanding and using outputs

Ø Assist science community with needs and information

Ø Assess application potential for regional climate modeling and in the area of sustainable landscapes

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More Information

Indo-U.S. Team

• David Easterling1

• Kenneth Kunkel2• Jenny Dissen2

• Andrew Ballinger2

• Katharine Hayhoe3

• Farhan Akhtar4

• Anne Stoner5

• Bridget Thrasher6

Author Affiliation:1. NOAA National Centers for Environmental

Information, Center for Weather and Climate, Asheville, NC

2. Cooperative Institute for Climate and Satellites - North Carolina / NC State University, Asheville, North Carolina

3. Texas Tech University4. U.S. Department of State, Washington D.C.5. Stanford University

• Dr. Ashwini Kulkarni6• Kalyan Chakraborthy7

• Dr. Sesha Srinivas7

• Praveen Chakravarthula8

• Sai Krishna Nooka8

• Kiran Jangeti8• Satyla Styavarapu8

US Team India Team

Author Affiliation:6. Indian Institute for Tropical Meteorology – Pune7. Environmental Protection and Training Research

Institute – Hyderabad, India8. Value Labs

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Back Up Slides

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India’s Policy – National and State Action Plans

• Dr. S. D. Attri, Sc-F, DGM• India Meteorological Department

• Dr. B. Siva Prasad, Scientist• Environment Protection Training and Research Institute

• Mr. Abhishek Goyal, DGM• Environment Services, Tata Sustainability Group

• Mr. Mihir Mathur, System Dynamics Modeller• The Energy Resources Institute

Moderator: Jenny Dissen, NOAA CICS-NC / NC State University

Climate Services in India – Moving the Needle

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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 projectionsØ Projections for individual weather stations, downscaled using

ARRMv2 (for temperature) and ARRMv1 (for precipitation)Ø 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 AwaysDownscaling 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.phpIf the spatial and/or temporal resolution of these observations meet your needs, you do not need to do any further downscaling.