the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
“Pochva”: a new hydro-thermal process model in soil, snow, vegetation for application in atmosphere numerical models
Abstract. This work presents the land model “Pochva”. “Pochva” is a model of hydro-thermal processes at the Earth surface and in the underlying medium. The model simulates the main hydro-thermal parameters of the surface, soil layer, vegetation and snow layer. Its soil process scheme allows to use physical parameters having vertical variations along the soil profile. Its snow processes scheme is a multiple layer scheme and has a numerical algorithm allowing to solve both cases of extremely thin and extremely thick layer. The model is marked by a particular accuracy in simulating the water phase transitions in soil and snow, and by the autonomy in the determination of the lower boundary condition in the soil column. The model can be used as a stand-alone land-surface model driven by observed or analytical forcing data, or coupled to an atmospheric model, either global or limited-area, either in forecast regime or climatic (hindcast) regime. The results of coupling “Pochva” to the numerical weather prediction limited-area model “Bolam” are presented in this article.
- Preprint
(2610 KB) - Metadata XML
- BibTeX
- EndNote
Status: open (until 26 Oct 2024)
-
RC1: 'Comment on gmd-2024-138', Anonymous Referee #1, 19 Sep 2024
reply
This article presents a comprehensive model of hydro-thermal processes in vegetated soil and snow cover, emphasizing the vertical variations of physical parameters along the soil profile. The model features a sophisticated snow processes scheme capable of handling extremely thin and thick snow layers, ensuring accurate simulation of water phase transitions in soil and snow. The interaction between the atmosphere and land surface is simulated, incorporating vegetation and snow cover as independent thermodynamic entities. The model's verification in the NWP model Bolam demonstrates its performance across various climatic zones, revealing biases and RMSEs for temperature and humidity, with particular attention to seasonal variations and geographical differences. The model is based on the idea of describing the thermal state of soil environment using entropy, and pays attention to the soil water phase transition, making it novel and potentially applicable in atmospheric and climate research. However, the article still needs some revisions before it is suitable for publication.
1. The colors in Figure 1 seem to be inconsistent with the colors in the legend (color for "Liquid water on the plant leaf surface"). Please check if there is a problem.
2. The meaning of β veg in equation 11 does not seem to be given in the article.
3. In Figure 2, it mentions k=nlev_soil, where nlev_soil refers to the maximum number of soil layers?Can this maximum number of layers vary, or is it a fixed value? Also, is the vertical stratification of soil layers in the model uniform, or does it vary across different spatial locations?
4. Why were the simulation results from 2013 to 2015 over the European region selected for validating the Pochva model, instead of selecting periods from the routine operational weather prediction results of CNR-ISAC, where Pochva has already been applied?
5. In the evaluation of land surface models, offline mode is commonly used. Can the Pochva model perform offline simulations? If so, it is suggested to use offline simulations for evaluation to more effectively avoid the uncertainty in atmospheric models from influencing the evaluation results.
Minor modifications:
1. It is recommended to remove the phrase 'of National Center of Atmospheric Research (USA)' after the Common Land model in lines 26-27, as the later development and application of this model were mostly carried out in China.
2. line 316 then shuld be than?
3. line 385 does the equation in this line need a number?
4. line 559 snow us should be snow was?Finally, the reviewer would like to express his respect for the author of the article. As we all know, developing a new land surface model all by oneself is extremely difficult and may face various challenges.
Citation: https://doi.org/10.5194/gmd-2024-138-RC1
Viewed
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
151 | 73 | 62 | 286 | 6 | 4 |
- HTML: 151
- PDF: 73
- XML: 62
- Total: 286
- BibTeX: 6
- EndNote: 4
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1