• Aldrian, E. C., and et al. , 2010: Regional climate information for risk management. Procedia Environ. Sci., 1, 369383, https://doi.org/10.1016/j.proenv.2010.09.024.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Alexander, M., and S. Dessai, 2019: What can climate services learn from the broader services literature? Climatic Change, 157, 133149, https://doi.org/10.1007/s10584-019-02388-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Barnston, A. G., and S. J. Mason, 2011: Evaluation of IRI’s seasonal climate forecasts for the extreme 15% tails. Wea. Forecasting, 26, 545554, https://doi.org/10.1175/WAF-D-10-05009.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Barnston, A. G., S. Li, S. J. Mason, D. G. DeWitt, L. Goddard, and X. Gong, 2010: Verification of the first 11 years of IRI’s seasonal climate forecasts. J. Appl. Meteor. Climatol., 49, 493520, https://doi.org/10.1175/2009JAMC2325.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Berri, G. J., P. L. Antico, and L. Goddard, 2005: Evaluation of the Climate Outlook Forums’ seasonal precipitation forecasts of southeast South America during 1998–2002. Int. J. Climatol., 25, 365377, https://doi.org/10.1002/joc.1129.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bours, D., C. McGinn, and P. Pringle, 2014: Guidance note 2: Selecting indicators for climate change adaptation programming. SEA Change Community of Practice and UKCIP, 10 pp., https://ukcip.ouce.ox.ac.uk/wp-content/PDFs/MandE-Guidance-Note2.pdf.

  • Brasseur, G. P., and L. Gallardo, 2016: Climate services: Lessons learned and future prospects. Earth’s Future, 4, 7989, https://doi.org/10.1002/2015EF000338.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Broecker, J., 2012: Probability forecasts. Forecast Verification: A Practitioner’s Guide in Atmospheric Science, 2nd ed. I. T. Jolliffe and D. B. Stephenson, Eds., Wiley-Blackwell, 119139.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bruno Soares, M., 2017: Assessing the usability and potential value of seasonal climate forecasts in land management decisions in the southwest UK: Challenges and reflections. Adv. Sci. Res., 14, 175180, https://doi.org/10.5194/asr-14-175-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bruno Soares, M., M. Daly, and S. Dessai, 2018: Assessing the value of seasonal climate forecasts for decision-making. Wiley Interdiscip. Rev.: Climate Change, 9, e523, https://doi.org/10.1002/wcc.523.

    • Search Google Scholar
    • Export Citation
  • Buizer, J., J. Foster, and D. Lund, 2000: Global impacts and regional actions: Preparing for the 1997/98 El Niño. Bull. Amer. Meteor. Soc., 81, 21212139, https://doi.org/10.1175/1520-0477(2000)081<2121:GIARAP>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Carr, E. R., and K. N. Owusu-Daaku, 2016: The shifting epistemologies of vulnerability in climate services for development: The case of Mali’s agrometeorological advisory programme. Area, 48, 717, https://doi.org/10.1111/area.12179.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cash, D. W., W. C. Clark, F. Alcock, N. M. Dickson, N. Eckley, D. H. Guston, J. Jäger, and R. B. Mitchell, 2003: Knowledge systems for sustainable development. Proc. Natl. Acad. Sci. USA, 100, 80868091, https://doi.org/10.1073/pnas.1231332100.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cash, D. W., J. C. Borck, and A. G. Patt, 2006: Countering the loading-dock approach to linking science and decision making: Comparative analysis of El Niño/Southern Oscillation (ENSO) forecasting systems. Sci. Technol. Hum. Values, 31, 465494, https://doi.org/10.1177/0162243906287547.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Clifford, N., M. Cope, T. Gillespie, and S. French, 2016: Key Methods in Geography .Sage, 752 pp.

  • Coughlan de Perez, E., E. Stephens, K. Bischiniotis, M. van Aalst, B. van den Hurk, S. Mason, H. Nissan, and F. Pappenberger, 2017: Should seasonal rainfall forecasts be used for flood preparedness? Hydrol. Earth Syst. Sci., 21, 45174524, https://doi.org/10.5194/hess-21-4517-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Daly, M., and S. Dessai, 2018: Examining the role of user engagement in the Regional Climate Outlook Forums: Implications for co-production of climate services. Sustainability Research Institute Paper No. 113, Centre for Climate Change Economics and Policy Working Paper No. 329, University of Leeds, 30 pp., www.cccep.ac.uk/wp-content/uploads/2018/03/Working-Paper-329-Daly-Dessai.pdf.

    • Search Google Scholar
    • Export Citation
  • Daly, M., J. West, and P. Yanda, 2016: Establishing a baseline for monitoring and evaluating user satisfaction with climate services in Tanzania. CICERO Rep. 2016:02, 54 pp., https://pub.cicero.oslo.no/cicero-xmlui/handle/11250/2382516.

    • Search Google Scholar
    • Export Citation
  • Desai, V., and R. Potter, 2016: Doing Development Research .Sage, 324 pp.

  • Feder, G., R. Murgai, and J. B. Quizon, 2004: Sending farmers back to school: The impact of farmer field schools in Indonesia. Rev. Agric. Econ., 26, 4562. https://doi.org/10.1111/j.1467-9353.2003.00161.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Garfin, G., T. J. Brown, T. Wordell, and E. Delgado, 2016: The making of national seasonal wildfire outlooks. Climate in Context: Science and Society Partnering for Adaptation, A. S. Parris et al., Eds., Amer. Geophys. Union, 143172.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Georgeson, L., M. Maslin, and M. Poessinouw, 2017: Global disparity in the supply of commercial weather and climate information services. Sci. Adv., 3, e1602632, https://doi.org/10.1126/SCIADV.1602632.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gerlak, A. K., and C. Greene, 2019: Interrogating vulnerability in the global framework for climate services. Climatic Change, 157, 99114, https://doi.org/10.1007/s10584-019-02384-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gerlak, A. K., and et al. , 2018: Building a framework for process-oriented evaluation of Regional Climate Outlook Forums. Wea. Climate Soc., 10, 225239, https://doi.org/10.1175/WCAS-D-17-0029.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Graham, R. J., and et al. , 2011: Long-range forecasting and the Global Framework for Climate Services. Climate Res ., 47, 4755, https://doi.org/10.3354/cr00963.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guido, Z., V. Rountree, C. Greene, A. Gerlak, and A. Trotman, 2016: Connecting climate information producers and users: Boundary organization, knowledge networks, and information brokers at Caribbean Climate Outlook Forums. Wea. Climate Soc., 8, 285298, https://doi.org/10.1175/WCAS-D-15-0076.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Haines, S., 2019: Managing expectations: Articulating expertise in climate services for agriculture in Belize. Climatic Change, 157, 4359, https://doi.org/10.1007/s10584-018-2357-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hansen, J., S. J. Mason, L. Sun, and A. Tall, 2011: Review of seasonal climate forecasting for agriculture in sub-Saharan Africa. Exp. Agric., 47, 205240, https://doi.org/10.1017/S0014479710000876.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hegger, D., M. Lamers, A. van Zeijl-Rozema, and C. Dieperink, 2012: Conceptualising joint knowledge production in regional climate change adaptation projects: Success conditions and levers for action. Environ. Sci. Policy, 18, 5265, https://doi.org/10.1016/j.envsci.2012.01.002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hewitt, C., S. J. Mason, and D. Walland, 2012: The global framework for climate services. Nat. Climate Change, 2, 831832, https://doi.org/10.1038/nclimate1745.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hinkel, J., and A. Bisaro, 2015: A review and classification of analytical methods for climate change adaptation. Wiley Interdiscip. Rev.: Climate Change, 6, 171188, https://doi.org/10.1002/wcc.322.

    • Search Google Scholar
    • Export Citation
  • Hyvärinen, O., L. Mtilatila, K. Pilli-Sihvola, A. Venäläinen, and H. Gregow, 2015: The verification of seasonal precipitation forecasts for early warning in Zambia and Malawi. Adv. Sci. Res., 12, 3136, https://doi.org/10.5194/asr-12-31-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • IDRC, 2012: Identifying the intended user(s) and use(s) of an evaluation. International Development Research Centre, 4 pp., www.betterevaluation.org/sites/default/files/idrc.pdf.

  • Jolliffe, I. T., 2007: Uncertainty and inference for verification measures. Wea. Forecasting, 22, 637650, https://doi.org/10.1175/WAF989.1.

  • Jolliffe, I. T., and D. B. Stephenson, 2012: Introduction. Forecast Verification: A Practitioner’s Guide in Atmospheric Science, 2nd ed. I. T. Jolliffe and D. B. Stephenson, Eds., Wiley-Blackwell, 112.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Korecha, D., and A. Sorteberg, 2013: Validation of operational seasonal rainfall forecast in Ethiopia. Water Resour. Res., 49, 76817697, https://doi.org/10.1002/2013WR013760.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumar, A., 2010: On the assessment of the value of the seasonal forecast information. Meteor. Appl., 17, 385392, https://doi.org/10.1002/met.167.

  • Lemos, M. C., 2015: Usable climate knowledge for adaptive and co-managed water governance. Curr. Opin. Environ. Sustain., 12, 4852, https://doi.org/10.1016/j.cosust.2014.09.005.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lemos, M. C., C. J. Kirchhoff, and V. Ramprasad, 2012: Narrowing the climate information usability gap. Nat. Climate Change, 2, 789794, https://doi.org/10.1038/nclimate1614.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Livezey, R. E., and M. M. Timofeyeva, 2008: The first decade of long-lead U.S. seasonal forecasts: Insights from a skill analysis. Bull. Amer. Meteor. Soc., 89, 843854, https://doi.org/10.1175/2008BAMS2488.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lourenço, T. C., R. Swart, H. Goosen, and R. Street, 2016: The rise of demand-driven climate services. Nat. Climate Change, 6, 1314, https://doi.org/10.1038/nclimate2836.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mahon, R., and et al. , 2019: Fit for purpose? Transforming National Meteorological and Hydrological Services into National Climate Service Centers. Climate Serv ., 13, 1423, https://doi.org/10.1016/j.cliser.2019.01.002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Martinez, R., B. J. Garanganga, A. Kamga, Y. Luo, S. Mason, J. Pahalad, and M. Rummukainen, 2010: Regional climate information for risk management: Capabilities. Procedia Environ. Sci., 1, 354368, https://doi.org/10.1016/j.proenv.2010.09.023.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mason, S. J., 2004: On using “climatology” as a reference strategy in the Brier and ranked probability skill scores. Mon. Wea. Rev., 132, 18911895, https://doi.org/10.1175/1520-0493(2004)132<1891:OUCAAR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mason, S. J., 2008: Understanding forecast verification statistics. Meteor. Appl ., 15, 3140, https://doi.org/10.1002/met.51.

  • Mason, S. J., 2012: Seasonal and longer-range forecasts. Forecast Verification: A Practitioner’s Guide in Atmospheric Science, 2nd ed. I. T. Jolliffe and D. B. Stephenson, Eds., Wiley-Blackwell, 203220.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mason, S. J., and S. Chidzambwa, 2008: Position paper: Verification of African RCOF forecasts. RCOF Review 2008, IRI Tech. Rep. 09-02, 26 pp., https://core.ac.uk/download/pdf/161435162.pdf.

    • Search Google Scholar
    • Export Citation
  • Mason, S. J., and A. P. Weigel, 2009: A generic forecast verification framework for administrative purposes. Mon. Wea. Rev., 137, 331349, https://doi.org/10.1175/2008MWR2553.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McNie, E., 2013: Delivering climate services: Organizational strategies and approaches for producing useful climate-science information. Wea. Climate Soc., 5, 1426, https://doi.org/10.1175/WCAS-D-11-00034.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Meadow, A. M., D. B. Ferguson, Z. Guido, A. Horangic, G. Owen, and T. Wall, 2015: Moving toward the deliberate coproduction of climate science knowledge. Wea. Climate Soc., 7, 179191, https://doi.org/10.1175/WCAS-D-14-00050.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Meinke, H., R. Nelson, P. Kokic, R. Stone, R. Selvaraju, and W. Baethgen, 2006: Actionable climate knowledge: From analysis to synthesis. Climate Res ., 33, 101110, https://doi.org/10.3354/cr033101.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Min, Y.-M., V. N. Kryjov, S. M. Oh, and H.-J. Lee, 2017: Skill of real-time operational forecasts with the APCC multi-model ensemble prediction system during the period 2008–2015. Climate Dyn ., 49, 41414156, https://doi.org/10.1007/s00382-017-3576-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murphy, A. H., 1991: Forecast verification: Its complexity and dimensionality. Mon. Wea. Rev., 119, 15901601, https://doi.org/10.1175/1520-0493(1991)119<1590:FVICAD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murphy, A. H., 1993: What is a good forecast? An essay on the nature of goodness in weather forecasting. Wea. Forecasting, 8, 281293, https://doi.org/10.1175/1520-0434(1993)008<0281:WIAGFA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • NOAA, 1998: An Experiment in the Application of Climate Forecasts: NOAA-OGP Activities Related to the 1997-98 El Niño Event .NOAA Office of Global Programs, 142 pp.

    • Search Google Scholar
    • Export Citation
  • Njau, L. N., 2010: Seasonal-to-interannual climate variability in the context of development and delivery of science-based climate prediction and information services worldwide for the benefit of society. Procedia Environ. Sci., 1, 411420, https://doi.org/10.1016/j.proenv.2010.09.029.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • O’Brien, K., S. Eriksen, L. P. O. Nygaard, and A. Schjolden, 2007: Why different interpretations of vulnerability matter in climate change discourses. Climate Policy, 7, 7388, https://doi.org/10.1080/14693062.2007.9685639.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ogallo, L., 2010: The mainstreaming of climate change and variability information into planning and policy development for Africa. Procedia Environ. Sci., 1, 405410, https://doi.org/10.1016/j.proenv.2010.09.028.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ogallo, L., P. Bessemoulin, J.-P. Ceron, S. J. Mason, and S. J. Connor, 2008: Adapting to climate variability and change: The Climate Outlook Forum process. WMO Bull ., 57, 93102. https://public.wmo.int/en/bulletin/adapting-climate-variability-and-change-climate-outlook-forum-process.

    • Search Google Scholar
    • Export Citation
  • Peng, P., A. Kumar, M. S. Halpert, and A. G. Barnston, 2012: An analysis of CPC’s operational 0.5-month lead seasonal outlooks. Wea. Forecasting, 27, 898917, https://doi.org/10.1175/WAF-D-11-00143.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Perrels, A., T. H. Frei, F. Espejo, L. Jamin, and A. Thomalla, 2013: Socio-economic benefits of weather and climate services in Europe. Adv. Sci. Res, 10, 6570, https://doi.org/10.5194/asr-10-65-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Siregar, P. R., and T. A. Crane, 2011: Climate information and agricultural practice in adaptation to climate variability: The case of climate field schools in Indramayu, Indonesia. Cult. Agric. Food Environ., 33, 5569, https://doi.org/10.1111/j.2153-9561.2011.01050.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Steynor, A., J. Padgham, C. Jack, B. Hewitson, and C. Lennard, 2016: Co-exploratory climate risk workshops: Experiences from urban Africa. Climate Risk Manage ., 13, 95102, https://doi.org/10.1016/j.crm.2016.03.001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tall, A., 2010: Climate forecasting to serve communities in West Africa. Procedia Environ. Sci., 1, 421431, https://doi.org/10.1016/j.proenv.2010.09.030.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tall, A., J. Y. Couilbaly, and M. Diop, 2018: Do climate services make a difference? A review of evaluation methodologies and practices to assess the value of climate information services for farmers: Implications for Africa. Climate Serv ., 11, 112, https://doi.org/10.1016/j.cliser.2018.06.001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tang, S., and S. Dessai, 2012: Usable science? The U.K. Climate Projections 2009 and decision support for adaptation planning. Wea. Climate Soc., 4, 300313, https://doi.org/10.1175/WCAS-D-12-00028.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vaughan, C., and S. Dessai, 2014: Climate services for society: Origins, institutional arrangements, and design elements for an evaluation framework. Wiley Interdiscip. Rev.: Climate Change, 5, 587603, https://doi.org/10.1002/wcc.290.

    • Search Google Scholar
    • Export Citation
  • Vaughan, C., S. Dessai, and C. Hewitt, 2018: Surveying climate services: What can we learn from a bird’s eye view? Wea. Climate Soc., 10, 373395, https://doi.org/10.1175/WCAS-D-17-0030.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vizard, A. L., G. A. Anderson, and D. J. Buckley, 2005: Verification and value of the Australian Bureau of Meteorology township seasonal rainfall forecasts in Australia, 1997–2005. Meteor. Appl., 12, 343355, https://doi.org/10.1017/S135048270500191X.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wall, T. U., A. M. Meadow, and A. Horganic, 2017: Developing evaluation indicators to improve the process of coproducing usable climate science. Wea. Climate Soc., 9, 95107, https://doi.org/10.1175/WCAS-D-16-0008.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • West, J., M. Daly, and P. Yanda, 2018: Evaluating user satisfaction with climate services in Tanzania 2014-2016: A summary report to the Global Framework for Climate Services Adaptation Programme in Africa. CICERO Rep. 2018:07, 65 pp., https://pub.cicero.oslo.no/cicero-xmlui/handle/11250/2500793.

    • Search Google Scholar
    • Export Citation
  • Wilks, D. S., 2000: Diagnostic verification of the Climate Prediction Center long-lead outlooks, 1995–98. J. Climate, 13, 23892403, https://doi.org/10.1175/1520-0442(2000)013<2389:DVOTCP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wilks, D. S., and A. H. Murphy, 1998: A case study of the use of statistical models in forecast verification: Precipitation probability forecasts. Wea. Forecasting, 13, 795810, https://doi.org/10.1175/1520-0434(1998)013<0795:ACSOTU>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wilks, D. S., and C. M. Godfrey, 2002: Diagnostic verification of the IRI net assessment forecasts, 1997–2000. J. Climate, 15, 13691377, https://doi.org/10.1175/1520-0442(2002)015<1369:DVOTIN>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • WMO, 2000: Coping with the climate: A way forward—Summary and proposals for action. IRI Pub. IRI-CW/01/2, 31 pp., www.wmo.int/pages/prog/wcp/wcasp/documents/PretoriaSumRpt2.pdf.

  • WMO, 2008: Part II: User liaison in RCOFs. WMO Doc., 7 pp., www.wmo.int/pages/prog/wcp/ccl/opace/documents/RCOF-PP-partII.pdf.

  • WMO, 2009: Regional climate outlook forums. WMO Pamphlet, 2 pp., www.wmo.int/pages/prog/wcp/wcasp/documents/RCOF_Flyer1.4_July2009_EN.pdf.

  • WMO, 2011: Climate knowledge for action: A global framework for climate services—Empowering the most vulnerable. WMO Rep., 20 pp., www.wmo.int/gfcs/sites/default/files/FAQ/HLT/HLT_FAQ_en.pdf.

    • Search Google Scholar
    • Export Citation
  • WMO, 2014a: Implementation plan of the global framework for climate services. WMO Rep., 81 pp., https://library.wmo.int/doc_num.php?explnum_id=4028.

    • Search Google Scholar
    • Export Citation
  • WMO, 2014b: Annex to the implementation plan of the global framework for climate services–User interface platform component. WMO Rep., 49 pp., https://gfcs.wmo.int/sites/default/files/Components/User%20Interface%20Platform//GFCS-ANNEXES-UIP-FINAL-14210_en.pdf.

    • Search Google Scholar
    • Export Citation
  • WMO, 2017: Global RCOF review meeting report. WMO Workshop Rep., 56 pp., www.wmo.int/pages/prog/wcp/wcasp/meetings/documents/rcofs2017/Report_RCOF_Review_2017_final.pdf.

    • Search Google Scholar
    • Export Citation
  • WMO, 2018: Guidance on verification of operational seasonal climate forecasts. WMO- 1220, 66 pp., https://library.wmo.int/doc_num.php?explnum_id=4886.

    • Search Google Scholar
    • Export Citation
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The Gnat and the Bull Do Climate Outlook Forums Make a Difference?

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  • 1 School of Geography and Development, and Udall Center for Studies in Public Policy, The University of Arizona, Tucson, Arizona
  • | 2 International Research Institute for Climate and Society, The Earth Institute, Columbia University, Palisades, New York
  • | 3 Department of Environmental Studies, University of New England, Biddeford, Maine
  • | 4 School of Geography and Development, The University of Arizona, Tucson, Arizona
  • | 5 Institute for the Environment, and School of Natural Resources and Environment, The University of Arizona, Tucson, Arizona
  • | 6 Centre for Climate Change Economics and Policy, and Sustainability Research Institute, University of Leeds, Leeds, United Kingdom
  • | 7 International Research Institute for Climate and Society, The Earth Institute, Columbia University, Palisades, New York
  • | 8 University of Hawai‘i at Hilo, Hilo, Hawai‘i
  • | 9 Institute for the Environment, The University of Arizona, Tucson, Arizona
  • | 10 School of Natural Resources and the Environment, The University of Arizona, Tucson, Arizona
  • | 11 Center for Climate Adaptation Science and Solutions, The University of Arizona, Tucson, Arizona
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Abstract

Little has been documented about the benefits and impacts of the recent growth in climate services, despite a growing call to justify their value and stimulate investment. Regional Climate Outlook Forums (RCOFs), an integral part of the public and private enterprise of climate services, have been implemented over the last 20 years with the objectives of producing and disseminating seasonal climate forecasts to inform improved climate risk management and adaptation. In proposing guidance on how to measure the success of RCOFs, we offer three broad evaluative categories that are based on the primary stated goals of the RCOFs: 1) quality of the climate information used and developed at RCOFs; 2) legitimacy of RCOF processes focused on consensus forecasts, broad user engagement, and capacity building; and 3) usability of the climate information produced at RCOFs. Evaluating the quality of information relies largely on quantitative measures and statistical techniques that are standardized and transferrable, but assessing the RCOF processes and perceived usability of RCOF products will necessitate a combination of quantitative and qualitative social science methods that are sensitive to highly variable regional contexts. As RCOFs have taken up different formats and procedures to adapt to diverse institutional and political settings and varied technical and scientific capacities, objective evaluation methods adopted should align with the goals and intent of the evaluation and be performed in a participatory, coproduction manner where producers and users of climate services together design the evaluation metrics and processes. To fully capture the potential benefits of the RCOFs, it may be necessary to adjust or recalibrate the goals of these forums to better fit the evolving landscape of climate services development, needs, and provision.

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Andrea K. Gerlak, agerlak@email.arizona.edu

Abstract

Little has been documented about the benefits and impacts of the recent growth in climate services, despite a growing call to justify their value and stimulate investment. Regional Climate Outlook Forums (RCOFs), an integral part of the public and private enterprise of climate services, have been implemented over the last 20 years with the objectives of producing and disseminating seasonal climate forecasts to inform improved climate risk management and adaptation. In proposing guidance on how to measure the success of RCOFs, we offer three broad evaluative categories that are based on the primary stated goals of the RCOFs: 1) quality of the climate information used and developed at RCOFs; 2) legitimacy of RCOF processes focused on consensus forecasts, broad user engagement, and capacity building; and 3) usability of the climate information produced at RCOFs. Evaluating the quality of information relies largely on quantitative measures and statistical techniques that are standardized and transferrable, but assessing the RCOF processes and perceived usability of RCOF products will necessitate a combination of quantitative and qualitative social science methods that are sensitive to highly variable regional contexts. As RCOFs have taken up different formats and procedures to adapt to diverse institutional and political settings and varied technical and scientific capacities, objective evaluation methods adopted should align with the goals and intent of the evaluation and be performed in a participatory, coproduction manner where producers and users of climate services together design the evaluation metrics and processes. To fully capture the potential benefits of the RCOFs, it may be necessary to adjust or recalibrate the goals of these forums to better fit the evolving landscape of climate services development, needs, and provision.

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Corresponding author: Andrea K. Gerlak, agerlak@email.arizona.edu
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