Abstract
The accuracy of weather forecasts has experienced remarkable improvements over the recent decades and is now considered important tools for developing the climate resilience of smallholder farmers, particularly as climate change upends traditional farming calendars. However, the effect of observations of climate change on the use of weather forecasts has not been studied. In an analysis of smallholder farming in Zambia, Kenya, and Jamaica, we document low weather forecast use, showing that perceptions of changes in the climate relate to views on forecast accuracy. Drawing on detailed data from Zambia, we show that weather forecast use (or not) is associated with perceptions of the accuracy (or inaccuracy) of the forecast, with rates of weather forecast use far lower among those who believe climate change impacts forecast accuracy. The results suggest a novel feedback whereby climate change erodes confidence in weather forecasts. Thus, in a changing climate where improvements in weather forecasts have been made, farmers thus experience a double disadvantage whereby climate change disrupts confidence in traditional ways of knowing the weather and lowers trust in supplementary technical forecasting tools.
Similar content being viewed by others
Data availability
Data will be made available upon request to the lead author.
Materials availability
Not applicable.
Code availability
Not applicable.
References
Alley RB, Emanuel KA, Zhang F (2019) Weather: advances in weather prediction. Science 363:342–344
Arbuckle JG, Prokopy LS, Haigh T, et al (2013) Climate change beliefs, concerns, and attitudes toward adaptation and mitigation among farmers in the Midwestern United States. Clim Change 2013 117:4 117:943–950. https://doi.org/10.1007/S10584-013-0707-6
Barr S, Woodley E (2019) Enabling communities for a changing climate: re-configuring spaces of hazard governance. Geoforum 100:116–127. https://doi.org/10.1016/j.geoforum.2019.02.007
Bauer P, Thorpe A, Brunet G (2015) The quiet revolution of numerical weather prediction. Nature 525:47–55
Benjamin SG, Brown JM, Brunet G et al (2018) 100 years of progress in forecasting and NWP applications. Meteorol Monogr 59:13.1–13.67. https://doi.org/10.1175/amsmonographs-d-18-0020.1
Bothe O (2019) When Does Weather Become Climate? Eos 100:. https://doi.org/10.1029/2019eo131019
Burgeno JN, Joslyn SL (2020) The impact of weather forecast inconsistency on user trust. Weather Clim Soc 12:679–694. https://doi.org/10.1175/WCAS-D-19-0074.1
Capstick SB, Pidgeon NF (2014) Public perception of cold weather events as evidence for and against climate change. Clim Chang 122:695–708. https://doi.org/10.1007/s10584-013-1003-1
Challinor AJ, Watson J, Lobell DB et al (2014) A meta-analysis of crop yield under climate change and adaptation. Nat Clim Chang 4:287–291. https://doi.org/10.1038/nclimate2153
Dayamba DS, Ky-Dembele C, Bayala J et al (2018) Assessment of the use of Participatory Integrated Climate Services for Agriculture (PICSA) approach by farmers to manage climate risk in Mali and Senegal. Clim Serv. https://doi.org/10.1016/j.cliser.2018.07.003
Dilling L, Lemos MC (2011) Creating usable science: opportunities and constraints for climate knowledge use and their implications for science policy. Glob Environ Chang 21:680–689. https://doi.org/10.1016/j.gloenvcha.2010.11.006
Eakin H (2005) Institutional change, climate risk, and rural vulnerability: cases from Central Mexico. World Dev 33:1923–1938. https://doi.org/10.1016/j.worlddev.2005.06.005
Eakin HC, Lemos MC, Nelson DR (2014) Differentiating capacities as a means to sustainable climate change adaptation. Glob Environ Chang 27:1–8. https://doi.org/10.1016/J.GLOENVCHA.2014.04.013
Funk C, Raghavan Sathyan A, Winker P, Breuer L (2019) Changing climate - changing livelihood: smallholder’s perceptions and adaption strategies. J Environ Manag 259:109702. https://doi.org/10.1016/j.jenvman.2019.109702
Gareau BJ, Huang X, Gareau TP, DiDonato S (2020) The strength of green ties: Massachusetts cranberry grower social networks and effects on climate change attitudes and action. Clim Chang 2020 162:3 162:1613–1636. https://doi.org/10.1007/S10584-020-02808-0
Garnett T, Appleby MC, Balmford A et al (2013) Sustainable intensification in agriculture: premises and policies. Science 341:33–34. https://doi.org/10.1126/science.1234485
Georgeson L, Maslin M, Poessinouw M (2017) Global disparity in the supply of commercial weather and climate information services. Sci Adv 3:e1602632. https://doi.org/10.1126/sciadv.1602632
GFDRR (2012) Back to our common future: Sustainable Development in the 21st Century (SD21) project—summary for policymakers. Washington D.C.
Guido Z, Knudson C, Campbell D, Tomlinson J (2019) Climate information services for adaptation: what does it mean to know the context? Clim Dev:1–13. https://doi.org/10.1080/17565529.2019.1630352
Guido Z, Knudson C, Finan T, et al (2020a) Shocks and cherries: The production of vulnerability among smallholder coffee farmers in Jamaica. World Development 132:104979. https://doi.org/10.1016/j.worlddev.2020.104979
Guido Z, Zimmer A, Lopus S et al (2020b) Farmer forecast: impacts of seasonal rainfall expectations on agricultural decision-making in sub-Saharan Africa. Elsevier
Hansen JW, Mason SJ, Sun L, Tall A (2011) Review of seasonal climate forecasting for agriculture in sub-Saharan Africa. Exp Agric 47:205–240. https://doi.org/10.1017/S0014479710000876
Hornsey MJ, Harris EA, Bain PG, Fielding KS (2016) Meta-analyses of the determinants and outcomes of belief in climate change. Nat Clim Chang 6:622–626. https://doi.org/10.1038/nclimate2943
Hoskins B (2013) The potential for skill across the range of the seamless weather-climate prediction problem: a stimulus for our science. Q J R Meteorol Soc 139:573–584. https://doi.org/10.1002/qj.1991
Ingram KT, Roncoli MC, Kirshen PH (2002) Opportunities and constraints for farmers of west Africa to use seasonal precipitation forecasts with Burkina Faso as a case study. Agric Syst 74:331–349. https://doi.org/10.1016/S0308-521X(02)00044-6
Jain M, Naeem S, Orlove B et al (2015) Understanding the causes and consequences of differential decision-making in adaptation research: adapting to a delayed monsoon onset in Gujarat, India. Glob Environ Chang 31:98–109. https://doi.org/10.1016/j.gloenvcha.2014.12.008
Jensen AD, Akperov MG, Mokhov II et al (2018) The dynamic character of Northern Hemisphere flow regimes in a near-term climate change projection. Atmosphere 2018 9:27. https://doi.org/10.3390/ATMOS9010027
Kalanda-Joshua M, Ngongondo C, Chipeta L, Mpembeka F (2011) Integrating indigenous knowledge with conventional science: enhancing localised climate and weather forecasts in Nessa, Mulanje, Malawi. Phys Chem Earth 36:996–1003. https://doi.org/10.1016/j.pce.2011.08.001
Khatri-Chhetri A, Aggarwal PK, Joshi PK, Vyas S (2017) Farmers’ prioritization of climate-smart agriculture (CSA) technologies. Agric Syst 151:184–191. https://doi.org/10.1016/j.agsy.2016.10.005
Lazo JK, Morss RE, Demuth JL (2009) 300 billion served. Bull Am Meteorol Soc 90:785–798. https://doi.org/10.1175/2008BAMS2604.1
Lee TM, Markowitz EM, Howe PD et al (2015) Predictors of public climate change awareness and risk perception around the world. Nat Clim Chang 5:1014–1020. https://doi.org/10.1038/nclimate2728
Lemos MC, Kirchhoff CJ, Ramprasad V (2012) Narrowing the climate information usability gap. Nat Clim Chang 2:789–794
Letson D, Llovet I, Podestá G et al (2001) User perspectives of climate forecasts: crop producers in Pergamino, Argentina. Clim Res 19:57–67. https://doi.org/10.3354/cr019057
Lowder SK, Skoet J, Raney T (2016) The number, size, and distribution of farms, smallholder farms, and family farms worldwide. World Dev 87:16–29. https://doi.org/10.1016/j.worlddev.2015.10.041
Magnusson L, Källén E (2013) Factors influencing skill improvements in the ECMWF forecasting system. Mon Weather Rev 141:3142–3153. https://doi.org/10.1175/MWR-D-12-00318.1
Mase AS, Gramig BM, Prokopy LS (2017) Climate change beliefs, risk perceptions, and adaptation behavior among Midwestern U.S. crop farmers. Clim Risk Manag 15:8–17. https://doi.org/10.1016/J.CRM.2016.11.004
Mase AS, Prokopy LS (2014) Unrealized potential: a review of perceptions and use of weather and climate information in agricultural decision making. Weather Clim Soc 6:47–61. https://doi.org/10.1175/WCAS-D-12-00062.1
Meadow A, Ferguson D, Guido Z et al (2015) Moving toward the deliberate coproduction of climate science knowledge. Weather Clim Soc 7:179–191. https://doi.org/10.1175/WCAS-D-14-00050.1
Menapace L, Colson G, Raffaelli R (2013) Risk aversion, subjective beliefs, and farmer risk management strategies. Am J Agric Econ 95:384–389. https://doi.org/10.1093/AJAE/AAS107
Metcalfe SE, Schmook B, Boyd DS et al (2020) Community perception, adaptation and resilience to extreme weather in the Yucatan Peninsula, Mexico. Reg Environ Chang 20:1–15. https://doi.org/10.1007/s10113-020-01586-w
Moser SC (2010) Communicating climate change: history, challenges, process and future directions. Wiley Interdiscip Rev Clim Chang 1:31–53
Mulenga BP, Wineman A, Sitko NJ (2017) Climate trends and farmers’ perceptions of climate change in Zambia. Environ Manag 59:291–306. https://doi.org/10.1007/s00267-016-0780-5
Nissan H, Goddard L, de Perez EC et al (2019) On the use and misuse of climate change projections in international development. Wiley Interdiscip Rev Clim Chang 10:e579. https://doi.org/10.1002/wcc.579
Orlove BS, Chiang JCH, Cane MA (2000) Forecasting Andean rainfall and crop yield from the influence of El Nino on Pleiades visibility. Nature 403:68–71. https://doi.org/10.1038/47456
Rijks D (1992) WMO Agricultural Meteorology Programme. Agric For Meteorol 59:319–324. https://doi.org/10.1016/0168-1923(92)90100-I
Rogers D, Tsirkunov V (2013) Weather and climate resilience: effective preparedness through national meteorological and hydrological services. World Bank Publications
Roncoli C (2006) Ethnographic and participatory approaches to research on farmers’ responses to climate predictions. Climate Research 33:81–99. https://doi.org/10.3354/cr033081
Roncoli C, Ingram K, Kirshen P (2002) Reading the rains: local knowledge and rainfall forecasting in Burkina Faso. Soc Nat Resour 15:409–427. https://doi.org/10.1080/08941920252866774
Roncoli C, Kirshen P, Ingram K, Jost C (2001) Burkina Faso - integrating indigenous and scientific rainfall forecasting. Washington, D.C.
Rose B, Floehr E (2017) Analysis of high temperature forecast accuracy of consumer weather forecasts from 2005-2016. Dublin, OH
Rosegrant MW, Ringler C, Zhu T (2009) Water for Agriculture: maintaining food security under growing scarcity. Annu Rev Environ Resour 34:205–222. https://doi.org/10.1146/annurev.environ.030308.090351
Roxburgh N, Guan D, Shin KJ et al (2019) Characterising climate change discourse on social media during extreme weather events. Glob Environ Chang 54:50–60. https://doi.org/10.1016/j.gloenvcha.2018.11.004
Scher S, Messori G (2019) How global warming changes the difficulty of synoptic weather forecasting. Geophys Res Lett 46:2931–2939. https://doi.org/10.1029/2018GL081856
Singh AS, Eanes F, Prokopy LS (2020) Climate change uncertainty among American farmers: an examination of multi-dimensional uncertainty and attitudes towards agricultural adaptation to climate change. Clim Chang 162:1047–1064. https://doi.org/10.1007/s10584-020-02860-w
Stern PC, Easterling WE (eds) (1999) Making climate forecasts matter, panel on the human dimensions of seasonal-to-interannual climate variability. Committee on the Human Dimensions of Global Change, National Research Council, Washington, D.C.: National Academies Press
Stone RC, Meinke H, Stone RC, Meinke H (2006) Weather, climate, and farmers: an overview. Meteorol Appl 13:7–20. https://doi.org/10.1017/S1350482706002519
Suh S, Johnson JA, Tambjerg L et al (2020) Closing yield gap is crucial to avoid potential surge in global carbon emissions. Glob Environ Chang 63:102100. https://doi.org/10.1016/j.gloenvcha.2020.102100
Tall A, Coulibaly JY, Diop M (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 Services
Thorpe A, Rogers D (2018) The future of the global weather enterprise : opportunities and risks. Bull Am Meteorol Soc 99:2003–2008
UN (2016) Transforming our world: the 2030 agenda for Sustainable Development United Nations United Nations
UNESCO (2019) Indigenous knowledge and climate change. https://en.unesco.org/links. Accessed 12 Jul 2019
van der Linden S (2015) The social-psychological determinants of climate change risk perceptions: towards a comprehensive model. J Environ Psychol 41:112–124. https://doi.org/10.1016/j.jenvp.2014.11.012
Venäläinen A, Pilli-Sihvola K, Tuomenvirta H et al (2016) Analysis of the meteorological capacity for early warnings in Malawi and Zambia. Clim Dev 8:190–196. https://doi.org/10.1080/17565529.2015.1034229
Waldman KB, Attari SZ, Gower DB, et al (2019a) The salience of climate change in farmer decision-making within smallholder semi-arid agroecosystems. Clim Chang 2019 156:4 156:527–543. https://doi.org/10.1007/S10584-019-02498-3
Waldman KB, Blekking JP, Attari SZ, Evans TP (2017) Maize seed choice and perceptions of climate variability among smallholder farmers. Glob Environ Chang 47:51–63. https://doi.org/10.1016/j.gloenvcha.2017.09.007
Waldman KB, Todd PM, Omar S et al (2020) Agricultural decision making and climate uncertainty in developing countries. Environ Res Lett 15:113004. https://doi.org/10.1088/1748-9326/ABB909
Waldman KB, Vergopolan N, Attari SZ et al (2019b) Cognitive biases about climate variability in smallholder farming systems in Zambia. Weather Clim Soc 11:369–383. https://doi.org/10.1175/wcas-d-18-0050.1
Webber S (2019) Putting climate services in contexts: advancing multi-disciplinary understandings: introduction to the special issue. Clim Chang. https://doi.org/10.1007/s10584-019-02600-9
Weber EU (2016) What shapes perceptions of climate change? New research since 2010. Wiley Interdiscip Rev Clim Chang 7:125–134. https://doi.org/10.1002/wcc.377
Wise RM, Fazey I, Stafford Smith M et al (2014) Reconceptualising adaptation to climate change as part of pathways of change and response. Glob Environ Chang 28:325–336. https://doi.org/10.1016/J.GLOENVCHA.2013.12.002
Wood SA, Jina AS, Jain M et al (2014) Smallholder farmer cropping decisions related to climate variability across multiple regions. Glob Environ Chang 25:163–172. https://doi.org/10.1016/j.gloenvcha.2013.12.011
World Bank (2015) Creating an atmosphere of cooperation in sub-Saharan Africa by strengthening weather, climate and hydrological services. Washington D.C.
World Bank (2017) Improving weather forecasts can reduce losses to development in Africa. https://www.worldbank.org/en/news/feature/2017/09/12/improving-weather-forecasts-can-reduce-losses-to-development-in-africa. Accessed 17 Sep 2019
Zabini F, Grasso V, Magno R et al (2015) Communication and interpretation of regional weather forecasts: a survey of the Italian public. Meteorol Appl 22:495–504. https://doi.org/10.1002/met.1480
Zhang F, Qiang Sun Y, Magnusson L et al (2019) What is the predictability limit of midlatitude weather? J Atmos Sci 76:1077–1091. https://doi.org/10.1175/JAS-D-18-0269.1
Acknowledgements
We are indebted to the many farmers who shared their ideas and time, often in lieu of tending their farms. We especially thank Allan Chilenga from the Zambian Agriculture Research Institute (ZARI) within the Zambian Ministry of Agriculture for his help in organizing field work.
Funding
The research in Zambia and Kenya was funded by the US National Science Foundation, grant numbers SES-1360463, DEB-1924309, and SES-1832393. Research in Jamaica was funded by the NOAA (grant NA13OAR4310184) for the International Research and Applications Project (IRAP), with contributions from USAID.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Ethics approval
All procedures performed in studies involving humans were in accordance with the ethical standards of the University of Arizona (UA), and approval was obtained from the UA Institutional Review Board.
Consent to participate
All the farmers surveyed were provided information about the project goals and survey, and they were allowed to freely consent or withdraw.
Consent for publication
We give consent for publication.
Conflict of interest
The authors declare no competing interests.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
ESM 1
(PDF 651 kb)
Rights and permissions
About this article
Cite this article
Guido, Z., Lopus, S., Waldman, K. et al. Perceived links between climate change and weather forecast accuracy: new barriers to tools for agricultural decision-making. Climatic Change 168, 9 (2021). https://doi.org/10.1007/s10584-021-03207-9
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10584-021-03207-9