Local land–atmosphere feedbacks limit irrigation demand

Decker, Mark; Ma, S.; Pitman, A. J.

doi:10.1088/1748-9326/aa65a6

Cited by 15 publications

(22 citation statements)

References 38 publications

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“…A limitation of the work presented here is therefore the lack of the atmospheric feedback in the uncoupled configuration. However, the Decker et al (2017) results indicate that a coupled configuration would likely reduce irrigation amounts simulated by the model. As the irrigation demand was greater in the model than in the humanpractice observations, the coupled atmosphere has the potential to reduce irrigation amounts to be more in line with those observed.…”

Section: Discussionmentioning

confidence: 94%

“…Recent work by Decker et al (2017) shows that atmospheric feedbacks can reduce the irrigation demand simulated by a land surface model. That is, a coupled model configuration allows the atmosphere to respond to the irrigation application, moistening the near-surface area, and reducing the need for additional irrigation as compared to the same model run uncoupled.…”

Section: Discussionmentioning

confidence: 99%

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Assessment of irrigation physics in a land surface modeling framework using non-traditional and human-practice datasets

Lawston

Santanello

Franz

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. Irrigation increases soil moisture, which in turn controls water and energy fluxes from the land surface to the planetary boundary layer and determines plant stress and productivity. Therefore, developing a realistic representation of irrigation is critical to understanding land-atmosphere interactions in agricultural areas. Irrigation parameterizations are becoming more common in land surface models and are growing in sophistication, but there is difficulty in assessing the realism of these schemes, due to limited observations (e.g., soil moisture, evapotranspiration) and scant reporting of irrigation timing and quantity. This study uses the Noah land surface model run at high resolution within NASA's Land Information System to assess the physics of a sprinkler irrigation simulation scheme and model sensitivity to choice of irrigation intensity and greenness fraction datasets over a small, high-resolution domain in Nebraska. Differences between experiments are small at the interannual scale but become more apparent at seasonal and daily timescales. In addition, this study uses point and gridded soil moisture observations from fixed and roving cosmic-ray neutron probes and co-located human-practice data to evaluate the realism of irrigation amounts and soil moisture impacts simulated by the model. Results show that field-scale heterogeneity resulting from the individual actions of farmers is not captured by the model and the amount of irrigation applied by the model exceeds that applied at the two irrigated fields. However, the seasonal timing of irrigation and soil moisture contrasts between irrigated and non-irrigated areas are simulated well by the model. Overall, the results underscore the necessity of both high-quality meteorological forcing data and proper representation of irrigation for accurate simulation of water and energy states and fluxes over cropland.

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Section: Discussionmentioning

confidence: 94%

Section: Discussionmentioning

confidence: 99%

Assessment of irrigation physics in a land surface modeling framework using non-traditional and human-practice datasets

Lawston

Santanello

Franz

et al. 2017

Hydrol. Earth Syst. Sci.

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“…We note that we do not test these new developments against the older version 1.4b in this manuscript as these new developments are the new default settings for CABLE. Furthermore, the new stomatal conductance scheme has been tested offline (De Kauwe et al, ) and in ACCESS (Kala, De Kauwe, et al, ), and the groundwater model and subgrid‐scale runoff parameterization and new pore‐scale formulation for soil evaporation has been tested offline (Decker ; Decker, Or, et al, ) and in WRF (Decker, Ma, et al, ). The focus of this work is to test the sensitivity of WRF‐LIS‐CABLE to a collection of available atmospheric physics options in WRF.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of the CABLEv2.3.4 Land Surface Model Coupled to NU‐WRFv3.9.1.1 in Simulating Temperature and Precipitation Means and Extremes Over CORDEX AustralAsia Within a WRF Physics Ensemble

Hirsch

Kala

Carouge

et al. 2019

J Adv Model Earth Syst

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The Community Atmosphere Biosphere Land Exchange (CABLE) model is a third-generation land surface model (LSM). CABLE is commonly used as a stand-alone LSM, coupled to the Australian Community Climate and Earth Systems Simulator global climate model and coupled to the Weather Research and Forecasting (WRF) model for regional applications. Here, we evaluate an updated version of CABLE within a WRF physics ensemble over the COordinated Regional Downscaling EXperiment (CORDEX) AustralAsia domain. The ensemble consists of different cumulus, radiation and planetary boundary layer (PBL) schemes. Simulations are carried out within the NASA Unified WRF modeling framework, NU-WRF. Our analysis did not identify one configuration that consistently performed the best for all diagnostics and regions. Of the cumulus parameterizations the Grell-Freitas cumulus scheme consistently overpredicted precipitation, while the new Tiedtke scheme was the best in simulating the timing of precipitation events. For the radiation schemes, the RRTMG radiation scheme had a general warm bias. For the PBL schemes, the YSU scheme had a warm bias, and the MYJ PBL scheme a cool bias. Results are strongly dependent on the region of interest, with the northern tropics and southwest Western Australia being more sensitive to the choice of physics options compared to southeastern Australia which showed less overall variation and overall better performance across the ensemble. Comparisons with simulations using the Unified Noah LSM showed that CABLE in NU-WRF has a more realistic simulation of evapotranspiration when compared to GLEAM estimates.

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“…This includes the parameterization of irrigation (e.g. Cook, Shukla, Puma, & Nazarenko, ; De Vrese, Hagemann, & Claussen, ; Decker, Ma, & Pitman, ; Guimberteau, Laval, Perrier, & Polcher, ; Harding & Snyder, ; Lawston, Santanello, Zaitchik, & Rodell, ; Qian, Huang, Yang, & Berg, ; Sacks, Cook, Buenning, Levis, & Helkowski, ; Thiery et al., ) to fully interactive crop modules that incorporate different crop varieties with defined growing seasons and fallow periods (e.g. Levis et al., ).…”

Section: Introductionmentioning

confidence: 99%

“…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 This includes the parameterization of irrigation (e.g. Cook, Shukla, Puma, & Nazarenko, 2014;De Vrese, Hagemann, & Claussen, 2016;Decker, Ma, & Pitman, 2017;Guimberteau, Laval, Perrier, & Polcher, 2012;Harding & Snyder, 2012;Lawston, Santanello, Zaitchik, & Rodell, 2015;Qian, Huang, Yang, & Berg, 2013;Sacks, Cook, Buenning, Levis, & Helkowski, 2008;Thiery et al, 2017) to fully interactive crop modules that incorporate different crop varieties with defined growing seasons and fallow periods (e.g. Levis et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Modelled biophysical impacts of conservation agriculture on local climates

Hirsch

Prestele

Davin

et al. 2018

Global Change Biology

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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.

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Local land–atmosphere feedbacks limit irrigation demand

Cited by 15 publications

References 38 publications

Assessment of irrigation physics in a land surface modeling framework using non-traditional and human-practice datasets

Assessment of irrigation physics in a land surface modeling framework using non-traditional and human-practice datasets

Evaluation of the CABLEv2.3.4 Land Surface Model Coupled to NU‐WRFv3.9.1.1 in Simulating Temperature and Precipitation Means and Extremes Over CORDEX AustralAsia Within a WRF Physics Ensemble

Modelled biophysical impacts of conservation agriculture on local climates

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