Question about abnormal GST simulation
Jiaxin Lei
Dear everyone, I encountered some issues with the simulated daily ground surface temperature (GST).
I used meteorological forcing data from a full hydrological year (October 2018 to October 2019) to run ParFlow-CLM. Taking one representative station as an example (as Figure 1), the results appear reasonable for the first 1.5 months, but afterward, the GST becomes abnormally flat, staying around 273.16 K for an extended period (in some cases, 3–5 months), as indicated by points a and b in the figure. Moreover, even the GST output during the spin-up phase seems problematic (as Figure 2). I repeated the spin-up process and run the case for several times, but the results remained nearly the same as shown in Figure 1 and 2.
I have carefully checked the eight meteorological input files and confirmed that their time series are correct. The CLM input files also appear to be in order. I tried adjusting the initial temperature value in drv_clmin.dat (from 300 K to 290 K), but the issue persisted. Since this abnormal pattern was observed across all 9 ground temperature monitoring stations in the region, each located in different land cover types, I assume the land type is not the direct cause of this issue.
Therefore, I would like to ask if anyone has experienced similar GST simulation problems with ParFlow-CLM. Could you please share your thoughts on potential causes or solutions?
Thank you very much in advance for your help.
Best wishes,
Jiaxin Lei
Master's student, Beijing Normal University
Reed M. Maxwell
This is very likely a snowpack or frozen ground temperature and you are freezing and thawing. Until the heat of fusion is overcome the temperature has to stay at zero C. Are you using the land surface temperature (which is a skin temperature) or one of the soil layer temperatures as comparison? They are very different quantities and you are probably seeing the top layer temp of the snowpack in your simulations, not a temperature in the soil.
From:
par...@googlegroups.com <par...@googlegroups.com> on behalf of Jiaxin Lei <leiji...@gmail.com>
Date: Tuesday, July 22, 2025 at 9:52 AM
To: ParFlow <par...@googlegroups.com>
Subject: Question about abnormal GST simulation
Dear everyone, I encountered some issues with the simulated daily ground surface temperature (GST).
I used meteorological forcing data from a full hydrological year (October 2018 to October 2019) to run ParFlow-CLM. Taking one representative station as an example (as Figure 1), the results appear reasonable for the first 1.5 months, but afterward, the GST becomes abnormally flat, staying around 273.16 K for an extended period (in some cases, 3–5 months), as indicated by points a and b in the figure. Moreover, even the GST output during the spin-up phase seems problematic (as Figure 2). I repeated the spin-up process and run the case for several times, but the results remained nearly the same as shown in Figure 1 and 2.
I have carefully checked the eight meteorological input files and confirmed that their time series are correct. The CLM input files also appear to be in order. I tried adjusting the initial temperature value in drv_clmin.dat (from 300 K to 290 K), but the issue persisted. Since this abnormal pattern was observed across all 9 ground temperature monitoring stations in the region, each located in different land cover types, I assume the land type is not the direct cause of this issue.
Therefore, I would like to ask if anyone has experienced similar GST simulation problems with ParFlow-CLM. Could you please share your thoughts on potential causes or solutions?
Thank you very much in advance for your help.
Best wishes,
Jiaxin Lei
Master's student, Beijing Normal University
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Jiaxin Lei
Thank you very much for your reply and explanation.
Sorry I didn’t mention it clearly in my original post — I’m using the ParFlow-CLM model, and the variable I used for comparison is t_grnd, which I understood to represent ground surface temperature (GST). I compared this output with the observed ground surface temperature from meteorological stations.
I just checked the WTD (water table depth) at the same meteorological station locations, and I suspect that the shallow WTD simulated (8/9 of the stations own a WTD under 0.05m) by the model may be contributing to the unusual ground temperature behavior. In the drv_clmin.dat file, I noticed a parameter called capr (if I understand correctly, this coefficient regulates the coupling between the surface temperature and the first soil layer). So I wonder if the surface ground temperature might be influenced by the shallowest soil layer temperature. May I ask if it is necessary to adjust the WTD output first and then compare the ground temperature at this time? Or are there some other reasons causing abnormal ground temperature?
Several keys setting of the part of CLM are as followed：
model.Solver.CLM.EvapBeta = "Linear"
model.Solver.CLM.VegWaterStress = "Saturation"
model.Solver.CLM.ResSat = 0.1
model.Solver.CLM.WiltingPoint = 0.12
model.Solver.CLM.FieldCapacity = 0.98
model.Solver.CLM.IrrigationType = "none"
model.Solver.CLM.RootZoneNZ = 6 ？
model.Solver.CLM.SoiLayer = 6 ？
Also, I observed that at many of the WTD monitoring sites, the model significantly underestimates WTD — for example, observed values are typically 2–3 meters, while the model outputs are often less than 0.5 meters. I would really appreciate any suggestions on how to improve the WTD simulation under such circumstances.
The last small question is that. When is the restart step mentioned in the manual needed? Is it only necessary to use it when continuing the operation of the previous steps? Sorry for that after learning I didn't quite understand the meaning of "restart" of CLM.
Thank you again for your time and help!
Best regards,
Jiaxin Lei
Master’s student