Why are agricultural impacts of climate change so uncertain? The importance of temperature relative to precipitation

By David B. Lobell, Marshall Burke. Environmental Research Letters, 2008

464 citations recorded by the source corpus.

Estimates of climate change impacts are often characterized by large uncertainties that reflect ignorance of many physical, biological, and socio-economic processes, and which hamper efforts to anticipate and adapt to climate change. A key to reducing these uncertainties is improved understanding of the relative contributions of individual factors. We evaluated uncertainties for projections of climate change impacts on crop production for 94 crop–region combinations that account for the bulk of calories consumed by malnourished populations. Specifically, we focused on the relative contributions of four factors: climate model projections of future temperature and precipitation, and the sensitivities of crops to temperature and precipitation changes. Surprisingly, uncertainties related to temperature represented a greater contribution to climate change impact uncertainty than those related to precipitation for most crops and regions, and in particular the sensitivity of crop yields to temperature was a critical source of uncertainty. These findings occurred despite rainfall’s important contribution to year-to-year variability in crop yields and large disagreements among global climate models over the direction of future regional rainfall changes, and reflect the large magnitude of future warming relative to historical variability. We conclude that progress in understanding crop responses to temperature and the magnitude of regional temperature changes are two of the most important needs for climate change impact assessments and adaptation efforts for agriculture.

Subfields: Ecology, Evolution, Behavior and Systematics, Global and Planetary Change, Plant Science

View Paper: https://www.semanticscholar.org/paper/a98252cfdf7093de1f7090ddaacefb3b56d175fd

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In Ecology, Evolution, Behavior and Systematics

In Global and Planetary Change

In Plant Science

Citations in the corpus

Climate change and variability in Sub-Saharan Africa: a review of current and future trends and impacts on agriculture and food security (2011, background): “Of particular concern are some of the limitations of the general circulation models used to simulate climate changes, and the way those limitations may affect the predicted impacts of climate change on agriculture ( Lobell and Burke 2008; Lobell et al. 2008; Parry et al. 1999; Thornton et al. 2008)”
Agriculture and climate change in global scenarios: why don't the models agree (2014, background): “See Lobell and Burke (2008) and Lobell et al. (2013) for more recent statistical approaches to the effects of climate change on agriculture.”
Random Forests for Global and Regional Crop Yield Predictions (2016, methodology): “Four methods were used to evaluate and compare the model performances: 1) root mean square error (RMSE, Eq [1]), 2) Nash-Sutcliffe model efficiency (EF, Eq [2]), 3) index of agreement known as Willmott’s d (d, Eq [3]) [36], and 4) observed vs.”
The impact of climate extremes and irrigation on US crop yields (2015, background): “…understand crop yield responses to climate conditions, it was found that both temperature and precipitation are key factors for predicting yields (Lobell and Burke 2008), with growing season precipitation and temperature explaining over 30% of year-to-year yield variations (Lobell and Field…”
Implications of climate change for agricultural productivity in the early twenty-first century (2010, background): “Lobell & Burke (2008) report that a change in growing season precipitation by one standard deviation can be associated with as much as a 10 per cent change in production (e.g. millet in South Asia).”