An ensemble of 48 physically perturbed model estimates of the 1/8° terrestrial water budget over the conterminous United States, 1980–2015
Abstract. Terrestrial water budget (TWB) data over large domains are of high interest for various hydrological applications. Spatiotemporally continuous and physically consistent estimations of TWB rely on land surface models (LSMs). As an augmentation of the operational North American Land Data Assimilation System Phase 2 (NLDAS‑2) four-LSM ensemble, this study presents a 48-member perturbed-physics ensemble configured from the Noah LSM with multi-physics options (Noah‑MP). The 48 Noah‑MP physics configurations are selected to give a representative cross-section of commonly used LSMs for parameterizing runoff, atmospheric surface layer turbulence, soil moisture limitation on photosynthesis, and stomatal conductance.
The ensemble simulated the 1980–2015 monthly TWB over the conterminous United States (CONUS) at a 1/8° spatial resolution. Simulation outputs include total evapotranspiration and its constituents (canopy evaporation, soil evaporation, and transpiration), runoff (the surface and subsurface components), as well as terrestrial water storage (snow water equivalent, four-layer soil water content from the surface down to 2 m, and the groundwater storage anomaly). This dataset is available at https://doi.org/10.5281/zenodo.7109816 (Zheng et al., 2022). Evaluations carried out in this study and previous investigations show that the ensemble performs well in reproducing the observed terrestrial water storage, snow water equivalent, soil moisture, and runoff. Noah-MP complements the NLDAS models well, and adding Noah-MP consistently improves the NLDAS estimations of the above variables in most areas of CONUS. Besides, the perturbed-physics ensemble facilities the identification of model deficiencies. The parameterizations of shallow snow, lakes, and near-surface atmospheric turbulence should be improved in future model versions.
Hui Zheng et al.
Status: final response (author comments only)
RC1: 'Comment on essd-2022-133', Anonymous Referee #1, 29 Dec 2022
- AC1: 'Reply on RC1', Hui Zheng, 19 Feb 2023
RC2: 'Review Comment on essd-2022-133', Anonymous Referee #2, 17 Jan 2023
- AC2: 'Reply on RC2', Hui Zheng, 19 Feb 2023
Hui Zheng et al.
An ensemble of 48 physically perturbed model estimates of the 1/8° terrestrial water budget over the conterminous United States, 1980–2015 https://doi.org/10.5281/zenodo.7109816
Hui Zheng et al.
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The manuscript presents the 48-member Noah-MP simulations in CONUS and the evaluation results. Common terrestrial water budget variables are provided. Comprehensive evaluation is performed based on multi-source reference dataset. The manuscript is well written. The dataset will be useful for diverse applications. I think the manuscript is suitable for publication on ESSD. Below are some comments which could be useful to the authors.
The dataset is not developed by this paper according to the description in the manuscript. For example, Fei et al. (2021), which is a publication of the same authors, already evaluated part of the 48-member Noah-MP model outputs. However, the description in the manuscript is kind of misleading (e.g., the abstract and line 79), making the readers have an impression that this manuscript runs the ensemble simulation. I recommend that the authors re-organize relevant contents, clearly stating the development and evaluation history of the 48-member simulations, and the role of this manuscript (e.g., evaluation and data release?) in the introduction part.
Line 104: Can you talk more about the “pitfalls”?
Section 2.2: Why these parameterizations are chosen? Can they represent the full range of uncertainty? Besides, I think the introduction to parameterizations can be moved the appendix. As a dataset description paper, these technical details could weaken the readability of the paper for most readers.
Line 279: Is this recursive spin up in a single year?
I have some doubts about Sections 3.1 and 3.2. I think there is a mistake. In Eq 34, you should not subtract r_clim (see Eq 8 in Dirmeyer et al., 2006). Otherwise, r_clim is subtracted twice in Eq 37. For the subscript t in Section 3.2, I did not find any explanation (please correct me if I made a mistake). To be honest, the two sections use more equations and symbols than Dirmeyer et al., (2006) but make the same concept much less straightforward and harder to understand. Probably the authors want to use more symbols to make the definition clearer, but it turned out making things worse from my opinion. I suggest that the authors reorganize these sections.
Section 3.5: I understand that the reference datasets are important. But this section is too long for a dataset description dataset on ESSD. This can be a distraction from your core dataset. I am wondering whether you can remove some contents or move some contents to the appendix.
Line 492: Can you explain it more clearly?
Figures 5 and 6: According to the second column, Noah-MP EM not is not notably better than NLDAS EM. Can you explain how this affects the results in the third column? Besides, the statement “four estimates’ arithmetic average outperforms the three-model NLDAS ensemble mean at almost every NASMD site” is not always true (e.g., Fig. 6c and 6f). I suggest adding some quantitative statistics in the figures (e.g., the median value, or the ratio of positive values). This will make comparison more straightforward.
Figure 7: The figure caption is unclear. Besides, I think you mean “difference” (Line 524) instead of “relative bias” in the figure caption.
Line 530-532: Any explanation?