Abstract

Including the parameterization of land management practices into Earth System Models has been shown to influence the simulation of regional climates, particularly for temperature extremes. However, recent model development has focused on implementing irrigation where other land management practices such as conservation agriculture (CA) has been limited due to the lack of global spatially explicit datasets describing where this form of management is practiced. Here, we implement a representation of CA into the Community Earth System Model and show that the quality of simulated surface energy fluxes improves when including more information on how agricultural land is managed. We also compare the climate response at the subgrid scale where CA is applied. We find that CA generally contributes to local cooling (~1°C) of hot temperature extremes in mid‐latitude regions where it is practiced, while over tropical locations CA contributes to local warming (~1°C) due to changes in evapotranspiration dominating the effects of enhanced surface albedo. In particular, changes in the partitioning of evapotranspiration between soil evaporation and transpiration are critical for the sign of the temperature change: a cooling occurs only when the soil moisture retention and associated enhanced transpiration is sufficient to offset the warming from reduced soil evaporation. Finally, we examine the climate change mitigation potential of CA by comparing a simulation with present‐day CA extent to a simulation where CA is expanded to all suitable crop areas. Here, our results indicate that while the local temperature response to CA is considerable cooling (>2°C), the grid‐scale changes in climate are counteractive due to negative atmospheric feedbacks. Overall, our results underline that CA has a nonnegligible impact on the local climate and that it should therefore be considered in future climate projections.

Highlights

  • Agricultural land management has a substantial impact on regional climate (e.g. Davin, Seneviratne, Ciais, Olioso, & Wang, 2014; Hirsch, Wilhelm, Davin, Thiery, & Seneviratne, 2017; Luyssaert et al, 2014; Thiery et al, 2017), and influences local responses to projected climate change (Hirsch et al, 2017)

  • In this study we present the first results of implementing a new spatially explicit global dataset of conservation agriculture (CA) within an Earth System Model (ESM) in order to more realistically assess the influence of CA on the climate

  • We find that including the biophysical characteristics of CA does add value to the simulation of the surface energy fluxes, where the changes are prominent at the subgrid scale

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Summary

| INTRODUCTION

Agricultural land management has a substantial impact on regional climate (e.g. Davin, Seneviratne, Ciais, Olioso, & Wang, 2014; Hirsch, Wilhelm, Davin, Thiery, & Seneviratne, 2017; Luyssaert et al, 2014; Thiery et al, 2017), and influences local responses to projected climate change (Hirsch et al, 2017). Davin et al (2014) apply more conservative changes over Europe in a regional climate model by increasing surface albedo over croplands by 0.1 and increasing the soil resistance by a factor of 4 to represent the effects of crop residue on evaporation They found that the cooling potential of no‐till farming was greater for temperature extremes than mean temperature. Davin et al, 2014; Hirsch et al, 2017; Lobell et al, 2006; Wilhelm et al, 2015) use an idealized approach to examine the cooling potential of various land management practices, they all demonstrate that changes in albedo and evapotranspiration associated with no‐till farming have implications for climate, temperature extremes, and that investment in further developing parameterizations to represent this land management practice, and conservation agriculture, within ESMs is worth pursuing. We aim to assess whether applying a more conservative approach of the biophysical effects of conservation agriculture within an ESM can improve the simulation of present‐day climate and we explore the possible climate sensitivity to different conservation agriculture estimates

| MATERIALS AND METHODS
| Evaluation datasets
| RESULTS
| DISCUSSION
| Discussion of CESM results
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