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Earth Institute Research Projects

Climate Decision Support in the Gulf States: Assessing the Impacts of Key Uncertainties in End-to-End Assessments

Lead PI: Alexander Ruane

Unit Affiliation: Center for Climate Systems Research (CCSR)

August 2010 - July 2013
Inactive
Global ; New York ; Florida ; Alabama
Project Type: Research

DESCRIPTION: The overall objective of this project is to evaluate the impacts of uncertainty throughout the climate impacts assessment process to identify the most crucial options and provide more robust analysis for climate change decision support, thereby improving risk management and the development of sustainable adaptation strategies in the agricultural sector. We investigate the assessment uncertainties associated with peanut modeling in the Gulf Coast regions of Florida and Alabama. NASA remote sensing tools (including several high-resolution precipitation products and surface insolation estimates) and modeling systems (including the Modern Era Retrospective Analysis; MERRA) are also introduced into the impacts assessment process and their impacts on final decision support estimated.

OUTCOMES: Experiments have been completed for a series of locations in Southern Alabama and Northwestern Florida, allowing for a full investigation of propagating uncertainties involving more than a dozen historical climate datasets, more than 30 future climate models, and a variety of climate scenario methods. Project activities led to a paper in Global Change Biology and work has led directly to several major global initiatives within the the Agricultural Model Intercomparison and Improvement Project (AgMIP). These include the Coordinated Climate-Crop Modeling Project (C3MP), which aligned 100+ researchers to follow similar protocols for temperature, precipitation, and CO2 sensitivity tests enabling crop model emulation to understand core climate factor responses. In the end there were 1000+ sites evaluated including 50+ countries, 20+ crop models, and 15+ crop species. A similar approach was also applied to the AgMIP Global Gridded Crop Model Intercomparison (GGCMI), which produced global climate factor responses (adding nitrogen and application dimensions) enabling global emulators and impacts response surfaces. A similar approach was also applied by AgMIP's European partners at sites across Europe in their MACSUR project. This work also led to the development of two climate forcing datasets (AgMERRA and AgCFSR) that combines satellite remote sensing, gridded station datasets, and NASA MERRA to create a bias-adjusted historical climate dataset designed for agricultural model applications. AgMERRA and AgCFSR play an integral role in many agricultural impact studies within AgMIP and beyond, as they dramatically increase the consistency and accuracy of climate information in regions where local observations are not reliable.

SPONSOR:

National Aeronautics & Space Administration

FUNDED AMOUNT:

$395,256

PUBLICATIONS:

Ruane, A.C., R. Goldberg, and J. Chryssanthacopoulos, 2015: Climate forcing datasets for agricultural modeling: Merged products for gap-filling and historical climate series estimation. Agric. Forest Meteorol., 200, 233-248, doi:10.1016/j.agrformet.2014.09.016.

Ruane, A.C., J.M. Winter, S.P. McDermid, and N.I. Hudson, 2015: AgMIP climate datasets and scenarios for integrated assessment. In Handbook of Climate Change and Agroecosystems: The Agricultural Model Intercomparison and Improvement Project (AgMIP) Integrated Crop and Economic Assessments, Part 1. C. Rosenzweig and D. Hillel, Eds., ICP Series on Climate Change Impacts, Adaptation, and Mitigation Vol. 3. Imperial College Press, pp. 45-78, doi:10.1142/9781783265640_0003.

Ruane, A.C., S. McDermid, C. Rosenzweig, G.A. Baigorria, J.W. Jones, C.C. Romero, and L.D. Cecil, 2014: Carbon-temperature-water change analysis for peanut production under climate change: A prototype for the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). Glob. Change Biol., 20, no. 2, 394-407, doi:10.1111/gcb.12412.

This work paved the way for additional high-profile publications beyond the end of the grant period:

Fronzek, S., N. Pirttioja, T.R. Carter, M. Bindi, H. Hoffmann, T. Palosuo, M. Ruiz-Ramos, F. Tao, M. Trnka, M. Acutis, S. Asseng, P. Baranowski, B. Basso, P. Bodin, S. Buis, D. Cammarano, P. Deligios, M.-F. Destain, B. Dumont, R. Ewert, R. Ferrise, K. François, T. Gaiser, P. Hlavinka, I. Jacquemin, K.C. Kersebaum, C. Kollas, J. Krzyszczak, I.J. Lorite, J. Minet, M.I. Minguez, M. Montesino, M. Moriondo, C. Müller, C. Nendel, I. Öztürk, A. Perego, A. Rodríguez, A.C. Ruane, F. Ruget, M. Sanna, M.A. Semenov, C. Slawinski, P. Stratonovitch, I. Supit, K. Waha, E. Wang, L. Wu, Z. Zhao, and R.P. Rötter, 2018: Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change. Agric. Syst., 159, 209-224, doi:10.1016/j.agsy.2017.08.004.

McDermid, S.P., A.C. Ruane, C. Rosenzweig, N.I. Hudson, M.D. Morales, P. Agalawatte, S. Ahmad, L.R. Ahuja, I. Amien, S.S. Anapalli, J. Anothai, S. Asseng, J. Biggs, F. Bert, P. Bertuzzi, V. Bhatia, M. Bindi, I. Broad, D. Cammarano, R. Carretero, A.A. Chattha, U. Chung, S. Debats, P. Deligios, G. De Sanctis, T. Dhliwayo, B. Dumont, L. Estes, F. Ewert, R. Ferrise, T. Gaiser, G. Garcia, S. Gbegbelegbe, V. Geethalakshmi, E. Gerardeaux, R. Goldberg, B. Grant, E. Guevara, J. Hickman, H. Hoffmann, H. Huang, J. Hussain, F.B. Justino, A.S. Karunaratne, A.-K. Koehler, P.K. Kouakou, S.N. Kumar, A. Lakshmanan, M. Lieffering, X. Lin, Q. Luo, G. Magrin, M. Mancini, F.R. Marin, A.D. Marta, Y. Masutomi, T. Mavromatis, G. McLean, S. Meira, M. Mohanty, M. Moriondo, W. Nasim, N. Negm, F. Orlando, S. Orlandini, I. Ozturk, H.M.S. Pinto, G. Podesta, Z. Qi, J. Ramarohetra, H.H. Rahman, H. Raynal, G. Rodriguez, R. Rötter, V. Sharda, L. Shuo, W. Smith, V. Snow, A. Soltani, K. Srinivas, B. Sultan, D.K. Swain, F. Tao, K. Tesfaye, M.I. Travasso, G. Trombi, A. Topaj, E. Vanuytrecht, F.E. Viscarra, S.A. Wajid, E. Wang, H. Wang, J. Wang, E. Wijekoon, L. Byun-Woo, Y. Xiaoguang, B.H. Young, J.I. Yun, Z. Zhao, and L. Zubair, 2015: The AgMIP Coordinated Climate-Crop Modeling Project (C3MP): Methods and protocols. In Handbook of Climate Change and Agroecosystems: The Agricultural Model Intercomparison and Improvement Project (AgMIP) Integrated Crop and Economic Assessments, Part 1. C. Rosenzweig and D. Hillel, Eds., ICP Series on Climate Change Impacts, Adaptation, and Mitigation Vol. 3. Imperial College Press, pp. 191-220, doi:10.1142/9781783265640_0008.

Pirttioja, N., T. Carter, S. Fronzek, M. Bindi, H. Hoffmann, T. Palosuo, M. Ruiz-Ramos, F. Tao, M. Acutis, S. Asseng, P. Baranowski, B. Basso, P. Bodin, S. Buis, D. Cammarano, P. Deligios, M.-F. Destain, B. Dumont, R. Ewert, R. Ferrise, L. François, T. Gaiser, P. Hlavinka, I. Jacquemin, K.C. Kersebaum, C. Kollas, J. Krzyszczak, I.J. Lorite, J. Minet, M.I. Minguez, M. Montesino, M. Moriondo, C. Müller, C. Nendel, I. Öztürk, A. Perego, A. Rodríguez, A.C. Ruane, F. Ruget, M. Sanna, M.A. Semenov, C. Slawinski, P. Stratonovitch, I. Supit, K. Waha, E. Wang, L. Wu, Z. Zhao, and R.P. Rötter, 2015: A crop model ensemble analysis of temperature and precipitation effects on wheat yield across a European transect using impact response surfaces. Clim. Res., 65, 87-105, doi:10.3354/cr01322.

DATASETS: AgMERRA - available at https://data.giss.nasa.gov/impacts/agmipcf/

Simulation outputs from Gulf Coast peanut simulations is available from the PI upon request. Inputs are available from public archives, including reanalyses and satellite products.

KEYWORDS

peanuts crop models climate and society climate change decision support agmip c3mp climate decisions modeling systems remote sensing climate stress tests

THEMES

Modeling and Adapting to Future Climate