Irrigation is an essential practice for sustaining global food production and many regional economies. Emerging scientific evidence indicates that irrigation substantially affects mean climate ...conditions in different regions of the world. Yet how this practice influences climate extremes is currently unknown. Here we use ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. An evaluation of the model performance reveals that irrigation has a small yet overall beneficial effect on the representation of present-day near-surface climate. While the influence of irrigation on annual mean temperatures is limited, we find a large impact on temperature extremes, with a particularly strong cooling during the hottest day of the year (-0.78 K averaged over irrigated land). The strong influence on extremes stems from the timing of irrigation and its influence on land-atmosphere coupling strength. Together these effects result in asymmetric temperature responses, with a more pronounced cooling during hot and/or dry periods. The influence of irrigation is even more pronounced when considering subgrid-scale model output, suggesting that local effects of land management are far more important than previously thought. In conclusion, our results underline that irrigation has substantially reduced our exposure to hot temperature extremes in the past and highlight the need to account for irrigation in future climate projections.
Changes in forest cover have a strong effect on climate through the alteration of surface biogeophysical and biogeochemical properties that affect energy, water and carbon exchange with the ...atmosphere. To quantify biogeophysical and biogeochemical effects of deforestation in a consistent setup, nine Earth system models (ESMs) carried out an idealized experiment in the framework of the Coupled Model Intercomparison Project, phase 6 (CMIP6). Starting from their pre-industrial state, models linearly replace 20×106 km2 of forest area in densely forested regions with grasslands over a period of 50 years followed by a stabilization period of 30 years. Most of the deforested area is in the tropics, with a secondary peak in the boreal region. The effect on global annual near-surface temperature ranges from no significant change to a cooling by 0.55 ∘C, with a multi-model mean of −0.22±0.21 ∘C. Five models simulate a temperature increase over deforested land in the tropics and a cooling over deforested boreal land. In these models, the latitude at which the temperature response changes sign ranges from 11 to 43∘ N, with a multi-model mean of 23∘ N. A multi-ensemble analysis reveals that the detection of near-surface temperature changes even under such a strong deforestation scenario may take decades and thus longer than current policy horizons. The observed changes emerge first in the centre of deforestation in tropical regions and propagate edges, indicating the influence of non-local effects. The biogeochemical effect of deforestation are land carbon losses of 259±80 PgC that emerge already within the first decade. Based on the transient climate response to cumulative emissions (TCRE) this would yield a warming by 0.46 ± 0.22 ∘C, suggesting a net warming effect of deforestation. Lastly, this study introduces the “forest sensitivity” (as a measure of climate or carbon change per fraction or area of deforestation), which has the potential to provide lookup tables for deforestation–climate emulators in the absence of strong non-local climate feedbacks. While there is general agreement across models in their response to deforestation in terms of change in global temperatures and land carbon pools, the underlying changes in energy and carbon fluxes diverge substantially across models and geographical regions. Future analyses of the global deforestation experiments could further explore the effect on changes in seasonality of the climate response as well as large-scale circulation changes to advance our understanding and quantification of deforestation effects in the ESM frameworks.
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