the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Investigating the Response of Land-Atmosphere Interactions and Feedbacks to Spatial Representation of Irrigation in a Coupled Modeling Framework
Abstract. The characteristics of the land surface play a critical role in determining the transfer of water, heat, and momentum to the atmosphere. Together with the model physics, parameterization schemes, and parameters employed, land datasets determine the spatial variability in land surface states (i.e., soil moisture and temperature) and fluxes. Despite the importance of these datasets, they are often chosen out of convenience or regional limitations without due assessment of their impacts on model results. Irrigation is an anthropogenic form of land heterogeneity that has been shown to alter the land surface energy balance, ambient weather, and local circulations. As such, irrigation schemes are becoming more prevalent in weather and climate models with rapid developments in dataset availability and parameterization scheme complexity. Thus, to address pragmatic issues related to modeling irrigation, this study uses a high-resolution, regional coupled modeling system to investigate the impacts of irrigation dataset selection on land-atmosphere (L-A) coupling using a case study from the Great Plains Irrigation Experiment (GRAINEX) field campaign. The simulations are assessed in the context of irrigated versus non-irrigated regions, subregions across the irrigation gradient, and sub-grid scale process representation in coarser scale models. The results show that L-A coupling is sensitive to the choice of irrigation dataset and resolution and that the irrigation impact on surface fluxes and near surface meteorology can be dominant, conditioned on the details of the irrigation map (i.e., boundaries, heterogeneity, etc), or minimal. A consistent finding across several analyses was that even a low percentage of irrigation fraction can have significant local and downstream atmospheric impacts, suggesting that representation of boundaries and heterogeneous areas within irrigated regions is particularly important for the modeling of irrigation impacts on the atmosphere in this model. When viewing the simulations presented here as a proxy for ‘ideal’ tiling in a Earth System Model scale gridbox, the results show that some ‘tiles’ will reach critical nonlinear moisture and PBL thresholds that could be important for clouds and convection, implying that heterogeneity resulting from irrigation should be taken into consideration in new sub-grid land-atmosphere exchange parameterizations.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(28822 KB) - Metadata XML
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Supplement
(7037 KB) - BibTeX
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-91', Anonymous Referee #1, 02 Mar 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-91/egusphere-2023-91-RC1-supplement.pdf
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AC1: 'Reply on RC1', Patricia Lawston-Parker, 03 May 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-91/egusphere-2023-91-AC1-supplement.pdf
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AC1: 'Reply on RC1', Patricia Lawston-Parker, 03 May 2023
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RC2: 'Comment on egusphere-2023-91', Anonymous Referee #2, 06 Apr 2023
This paper comprehensively investigates the impact of irrigation on land-atmosphere coupling using the Noah LSM, which has great scientific significance. It focuses specifically on the impact of various satellite-based irrigation products on LA coupling, and the influence of different spatial resolutions on these effects. This paper also explored the “scale effect” across multiple spatial resolutions through ground-based observations and model simulations. However, in the current version, major revisions still need to be made to the structure of the paper, and the quality of the figures also needs improvement. Here are my suggestions:
1. “Irrigation threshold” is a critical parameter that affects the irrigation timing and amount in the model simulations. However, it seems that there is no detailed discussion of this threshold in the paper. I suggest that the author provide a detailed explanation of this threshold and supplement some sensitivity analyses of the threshold selection on the results.
2. The second section (Background) and Introduction contain duplicated information. I suggest merging them to streamline this section. The current version makes it difficult for readers to capture the key messages. In addition, the description of the observation data in the paper is too brief. Due to the ground-based observations are crucial for the validation of the simulations, the authors should strengthen this part.
3. The definition of “transition region” needs to be highlighted in the Method section.
Minor comments:
Line 24-26: Please provide specific quantitative information instead of qualitative expressions.
Line 28: Please provide the full name when PBL first appears.
Line 33-34: This sentence is exactly the same as the abstract, please rephrase.
Line 60: More references.
Line 68: “L-A” has already been abbreviated before, so it is not necessary to provide the full name here.
Line 72: What does “Irrigation Dataset” specifically refer to? Is it the irrigation fraction map or the irrigation water use map?
Line 159: Why not use satellite-based LAI?
Line 165: When considering irrigation as a special form of precipitation in the model, have the effects of canopy interception been taken into account? Large and lush leaves often result in more actual water consumption for irrigation, and has the cooling effect caused by the interception evaporation been calculated in the model?
Line 258-260: Can the changes in EF be quantified specifically? This can help compare the changes in EF caused by different irrigation fraction products and the results caused by different resolutions.
Line 308: It is necessary to emphasize why similar data analysis needs to be conducted on individual stations.
Figure 2: A legend should be provided to explain the meaning of different colors and numbers, rather than just describe them in the figure caption.
Figure 6: The proportion of text and numbers in Figure 6 and subsequent figures doesn’t look very good, and the font size is too small to read clearly. Also, the unit of the Y-axis can be converted to MJ or displayed using scientific notation.
Figure 7: The two sub-figures in Figure 7 need to be rearranged horizontally instead of vertically.
Citation: https://doi.org/10.5194/egusphere-2023-91-RC2 -
AC2: 'Reply on RC2', Patricia Lawston-Parker, 03 May 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-91/egusphere-2023-91-AC2-supplement.pdf
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AC2: 'Reply on RC2', Patricia Lawston-Parker, 03 May 2023
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-91', Anonymous Referee #1, 02 Mar 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-91/egusphere-2023-91-RC1-supplement.pdf
-
AC1: 'Reply on RC1', Patricia Lawston-Parker, 03 May 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-91/egusphere-2023-91-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Patricia Lawston-Parker, 03 May 2023
-
RC2: 'Comment on egusphere-2023-91', Anonymous Referee #2, 06 Apr 2023
This paper comprehensively investigates the impact of irrigation on land-atmosphere coupling using the Noah LSM, which has great scientific significance. It focuses specifically on the impact of various satellite-based irrigation products on LA coupling, and the influence of different spatial resolutions on these effects. This paper also explored the “scale effect” across multiple spatial resolutions through ground-based observations and model simulations. However, in the current version, major revisions still need to be made to the structure of the paper, and the quality of the figures also needs improvement. Here are my suggestions:
1. “Irrigation threshold” is a critical parameter that affects the irrigation timing and amount in the model simulations. However, it seems that there is no detailed discussion of this threshold in the paper. I suggest that the author provide a detailed explanation of this threshold and supplement some sensitivity analyses of the threshold selection on the results.
2. The second section (Background) and Introduction contain duplicated information. I suggest merging them to streamline this section. The current version makes it difficult for readers to capture the key messages. In addition, the description of the observation data in the paper is too brief. Due to the ground-based observations are crucial for the validation of the simulations, the authors should strengthen this part.
3. The definition of “transition region” needs to be highlighted in the Method section.
Minor comments:
Line 24-26: Please provide specific quantitative information instead of qualitative expressions.
Line 28: Please provide the full name when PBL first appears.
Line 33-34: This sentence is exactly the same as the abstract, please rephrase.
Line 60: More references.
Line 68: “L-A” has already been abbreviated before, so it is not necessary to provide the full name here.
Line 72: What does “Irrigation Dataset” specifically refer to? Is it the irrigation fraction map or the irrigation water use map?
Line 159: Why not use satellite-based LAI?
Line 165: When considering irrigation as a special form of precipitation in the model, have the effects of canopy interception been taken into account? Large and lush leaves often result in more actual water consumption for irrigation, and has the cooling effect caused by the interception evaporation been calculated in the model?
Line 258-260: Can the changes in EF be quantified specifically? This can help compare the changes in EF caused by different irrigation fraction products and the results caused by different resolutions.
Line 308: It is necessary to emphasize why similar data analysis needs to be conducted on individual stations.
Figure 2: A legend should be provided to explain the meaning of different colors and numbers, rather than just describe them in the figure caption.
Figure 6: The proportion of text and numbers in Figure 6 and subsequent figures doesn’t look very good, and the font size is too small to read clearly. Also, the unit of the Y-axis can be converted to MJ or displayed using scientific notation.
Figure 7: The two sub-figures in Figure 7 need to be rearranged horizontally instead of vertically.
Citation: https://doi.org/10.5194/egusphere-2023-91-RC2 -
AC2: 'Reply on RC2', Patricia Lawston-Parker, 03 May 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-91/egusphere-2023-91-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Patricia Lawston-Parker, 03 May 2023
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Cited
Patricia Lawston-Parker
Joseph A. Santanello Jr.
Nathaniel W. Chaney
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(28822 KB) - Metadata XML
-
Supplement
(7037 KB) - BibTeX
- EndNote
- Final revised paper