Noah‐MP‐Crop: Introducing dynamic crop growth in the Noah‐MP land surface model

Liu, Xing; Chen, Fei; Barlage, Michael; Zhou, Guangsheng; Niyogi, Dev

doi:10.1002/2016jd025597

Cited by 86 publications

(121 citation statements)

References 52 publications

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“…Principle to this is the simulation of plant carbon assimilation, respiration, and transpiration of water. Many current LSMs use adaptations of the Faquhar-Ball-Berry model of coupled leaf-level photosynthesis and stomatal conductance-the solutions to which have proven robust for a range of environmental conditions-and a variety of scaling techniques to canopy level [Farquhar and von Caemmerer, 1982;Ball et al, 1987;Collatz et al, 1991;Cox et al, 1998;Lawrence and Slingo, 2004;Lokupitiya et al, 2009;Oleson et al, 2013;Kim et al, 2015;Liu et al, 2016]. Solving for photosynthesis and conductance requires numerous PFT-specific parameters, examples of which are shown in Kim et al [2015] for four PFTs in the Ent Terrestrial Biosphere Model, Table D1 [ Farquhar and von Caemmerer, 1982;Ball et al, 1987;Collatz et al, 1991;Luo et al, 2012;Oleson et al, 2013;Kim et al, 2015].…”

Section: Representing Agriculture Through Dynamic Coupled Climate-crmentioning

confidence: 99%

Representing agriculture in Earth System Models: Approaches and priorities for development

McDermid

Mearns

Ruane

2017

J Adv Model Earth Syst

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Earth System Model (ESM) advances now enable improved representations of spatially and temporally varying anthropogenic climate forcings. One critical forcing is global agriculture, which is now extensive in land‐use and intensive in management, owing to 20th century development trends. Agriculture and food systems now contribute nearly 30% of global greenhouse gas emissions and require copious inputs and resources, such as fertilizer, water, and land. Much uncertainty remains in quantifying important agriculture‐climate interactions, including surface moisture and energy balances and biogeochemical cycling. Despite these externalities and uncertainties, agriculture is increasingly being leveraged to function as a net sink of anthropogenic carbon, and there is much emphasis on future sustainable intensification. Given its significance as a major environmental and climate forcing, there now exist a variety of approaches to represent agriculture in ESMs. These approaches are reviewed herein, and range from idealized representations of agricultural extent to the development of coupled climate‐crop models that capture dynamic feedbacks. We highlight the robust agriculture‐climate interactions and responses identified by these modeling efforts, as well as existing uncertainties and model limitations. To this end, coordinated and benchmarking assessments of land‐use‐climate feedbacks can be leveraged for further improvements in ESM's agricultural representations. We suggest key areas for continued model development, including incorporating irrigation and biogeochemical cycling in particular. Last, we pose several critical research questions to guide future work. Our review focuses on ESM representations of climate‐surface interactions over managed agricultural lands, rather than on ESMs as an estimation tool for crop yields and productivity.

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Section: Representing Agriculture Through Dynamic Coupled Climate-crmentioning

confidence: 99%

Representing agriculture in Earth System Models: Approaches and priorities for development

McDermid

Mearns

Ruane

2017

J Adv Model Earth Syst

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“…The parameterizations of Noah‐MP‐Crop in this study use the default values from Liu et al () to allow direct comparison with prior results. Simulations conducted with the control or the constant rooting depth are referred to as fixed_root , while those with the new dynamic rooting depth are referred to as dynamic_root .…”

Section: Methodsmentioning

confidence: 99%

“…To study the impacts of land use/land change on hydroclimatic systems, a better understanding of the interactions between soil‐crops‐atmosphere is necessary. Recently, the Noah‐MP model was enhanced to include crops, and a new version, Noah‐MP‐Crop (Liu et al, ), was introduced to the community. The model development follows a series of recent studies that seek to link crops in weather studies (e.g., Harding et al, ; Levis et al, ; Liu et al, ; Lu et al, ; Song et al, ).…”

Section: Introductionmentioning

confidence: 99%

“…This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. and a new version, Noah-MP-Crop (Liu et al, 2016), was introduced to the community. The model development follows a series of recent studies that seek to link crops in weather studies (e.g., Harding et al, 2015;Levis et al, 2012;Liu et al, 2016;Lu et al, 2015;Song et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

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Implementing Dynamic Rooting Depth for Improved Simulation of Soil Moisture and Land Surface Feedbacks in Noah‐MP‐Crop

Liu

Chen

Barlage

et al. 2020

J Adv Model Earth Syst

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The study postulates that crop rooting depth representation plays a vital role in simulating soil‐crop‐atmospheric interactions. Rooting depth determines the water access for plants and alters the surface energy participation and soil moisture profile. The aboveground crop growth representation in land surface models continues to evolve and improve, but the root processes are still poorly represented. This limitation likely contributes to the bias in simulating soil‐crop‐related variables such as soil moisture and associated water and energy exchanges between the surface and the atmosphere. In Noah‐MP‐Crop, the rooting depth of crops is assumed as 1 m regardless of crop types and the length of growing seasons. In this study, a simple dynamic rooting depth formulation was integrated into Noah‐MP‐Crop. On comparing with soil moisture observations from the in situ Ameriflux, USDA Soil Climate Analysis Network, and the remote‐sensed Soil Moisture Active Passive data set, the results highlight the improved performance of Noah‐MP‐Crop due to modified rooting depth. The improvements were noted in terms of soil moisture and more prominently in terms of the energy flux simulations at both field scale and regional scale. The enhancements in soil moisture profiles reduce the biases in surface heat flux simulations. The impact of rooting depth representation appears to be particularly significant for improving model performance under drought‐like situations. Although it was not possible to validate the simulated rooting depth due to lack of observations, the overall performance of the model helps emphasize the importance of enhancing the representation of crop rooting depth in Noah‐MP‐Crop.

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“…The LETKF technique requires both localization in time and space (Dai et al, 2019; Hunt, Kostelich, et al, 2007; Liu, Bowman, et al, 2016; Liu, Chen, et al, 2016), which means that the posteriori is independently estimated in each model grid cell at a given time within a defined radius. We determine the spatial localization ( E ) using the normalized cumulative semiovariogram of observations (Şen, 1997), which strongly fit ( R 2 = 0.97) the Cressman formula:

E = \frac{((), D^{2} - d^{2})}{(D^{2} + d^{2})}

.…”

Section: Measurements Modeling and Methodsmentioning

confidence: 99%

Quantifying the Impact of Excess Moisture From Transpiration From Crops on an Extreme Heat Wave Event in the Midwestern U.S.: A Top‐Down Constraint From Moderate Resolution Imaging Spectroradiometer Water Vapor Retrieval

et al. 2020

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The primary focus of this study is to understand the contribution from excess moisture from crop transpiration to the severity of a heat wave episode that hit the Midwestern U.S. from 16 to 20 July 2011. To elucidate this, we first provide an optimal estimate of the transpiration water vapor flux using satellite total column water vapor retrievals whose accuracy and precision are characterized using independent observations. The posterior transpiration flux is estimated using a local ensemble transform Kalman filter that employs a mesoscale weather model as the forward model. The new estimation suggests that the prior values of transpiration flux from crops are biased high by 15%. We further use the constrained flux to examine the sensitivity of meteorology to the contributions from crops. Over the agricultural areas during daytime, elevated moisture (up to 40%) from crops not only increases humidity (thus the heat index) but also provides a positive radiative forcing by increasing downward longwave radiation (13 ± 4 W m−2) that results in even higher surface air temperature (+0.4 °C). Consequently, we find that the elevated moisture generally provides positive feedback to aggravate the heat wave, with daytime enhancements of heat index by as large as 3.3 ± 0.8 °C. Due to a strong diurnal cycle in the transpiration, the feedback tends to be stronger in the afternoon (up to 5 °C) and weaker at night. Results offer a potential basis for designing mitigation strategies for the effect of transpiration from agriculture in the future, in addition to improving the estimation of canopy transpiration.

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Noah‐MP‐Crop: Introducing dynamic crop growth in the Noah‐MP land surface model

Cited by 86 publications

References 52 publications

Representing agriculture in Earth System Models: Approaches and priorities for development

Representing agriculture in Earth System Models: Approaches and priorities for development

Implementing Dynamic Rooting Depth for Improved Simulation of Soil Moisture and Land Surface Feedbacks in Noah‐MP‐Crop

Quantifying the Impact of Excess Moisture From Transpiration From Crops on an Extreme Heat Wave Event in the Midwestern U.S.: A Top‐Down Constraint From Moderate Resolution Imaging Spectroradiometer Water Vapor Retrieval

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