Test run with CFORCE DATM

[wwieder]

Members of the Ocean group (Rita, Gokhan and Fred) are bias correcting ERA5 for running G-cases as part of the CFORCE project. It would be good to see if we can leverage some of this work for CLM simulations so we can develop our own 'in house' DATM pipeline that can be updated more regularly.

Rita has done global bias correcting for incoming solar and has methods for correcting other biases over oceans (temperature, humidity, & winds). This may be challenging over land, as the higher resolution of the dataset (quarter degree) introduces greater topographic heterogeneity than many of our datasets. CFORCE is not changing precip over the ocean, but acknowledges there are precip biases over land (rain bombs in Africa).

@olyson, to start with I wonder if you can take a stab at doing a relatively short SP run on with the current CFORCE data?
@swensosc may have some experience here that's helpful (see also #3010)
@megandevlan is interested in helping to evaluate the forcing (and eventually simulations), as ESPAT is interested in using this.

There are some interesting questions to consider here, especially related to:

• Performance (hourly data at quarter degree).
• Potentially removing multiple streams in the DATM field, as temporal interpolation may not be needed)
• Ability to get direct and diffuse incoming shortwave radiation?
• Mesh file generation (Remove ERA5 forcing option as it isn't functional #3010 mentions challenges running at the poles)?
• Methods for bias correcting this higher spatial resolution fields.

Rita stressed this is a work in progress, but her current files are here /glade/campaign/cgd/oce/people/rita/ERA5/ and said she'd help navigate what files to use

[dlawrenncar]

Note that as we start to consider how to update the CFORCE dataset to be improved over land, here is a paper that describes the WFDEI dataset, which is a bias-corrected ERA-Interim dataset produced a few years ago. https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2014WR015638

[olyson]

I've incorporated the CFORCE dataset into the datm for testing. And done a one month SP test run. The forcing fields look provisionally ok in a gross sense, except for surface pressure (PBOT in the history file), which has spatial patterns that aren't consistent with the forcing files (SP in the forcing file). I think it is because the "lat" variable in the SP_*.nc forcing files is oriented north to south, which isn't consistent with the mesh file, which is oriented south to north.

[ekluzek]

I've incorporated the CFORCE dataset into the datm for testing. And done a one month SP test run. The forcing fields look provisionally ok in a gross sense, except for surface pressure (PBOT in the history file), which has spatial patterns that aren't consistent with the forcing files (SP in the forcing file). I think it is because the "lat" variable in the SP_*.nc forcing files is oriented north to south, which isn't consistent with the mesh file, which is oriented south to north.

@olyson we could either have a mesh file that reverses latitudes, or reverse the dataset. It seems to me that we should reverse the dataset as S to N is the standard in CESM. Isn't this also a problem for the Ocean people as well?

[olyson]

I'm using the same mesh for other streams, solar and precip for example, so I think it would be best to reverse the dataset. We think the Ocean people use SLP.

[dlawrenncar]

I expect that the ocean folks use SLP. It's probably worth flagging to them that we saw an issue with SP so that they can double check that there isn't a problem.

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On Tue, Nov 11, 2025 at 12:05 PM Keith Oleson ***@***.***> wrote: *olyson* left a comment (ESCOMP/CTSM#3588) <#3588 (comment)> I'm using the same mesh for other streams, solar and precip for example, so I think it would be best to reverse the dataset. I'm not sure if the Ocean people use SP or if they use SLP, I haven't checked SLP. — Reply to this email directly, view it on GitHub <#3588 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AFABYVDMGB5UFW765RRIVLL34IXQBAVCNFSM6AAAAACLMKZ4I6VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZTKMJYGM3TIOBRGI> . You are receiving this because you commented.Message ID: ***@***.***>

[olyson]

@margarita-markina has processed the SP files, thanks. PBOT now looks like I would expect. I'm continuing the 1-month run for several years (1980-1989) to compare to a CRUJRA2024 control.

[olyson]

Land diagnostics for a SP CFORCE run compared to CRUJRA2024 are here.
Maybe most useful to look at the set2 contour plots for these forcing variables:

PREC, RAIN, SNOW, TBOT, WIND, THBOT, QBOT, PBOT, ZBOT, FLDS, FSDS (and the partitioning into visible, near-infrared, direct, and diffuse).
Some interesting model responses in LHEAT, FSH, and FPSN (annual mean). Significant increases in LHEAT (and decreases in FSH) almost everywhere, particularly in the tropics. Some of this increase in LHEAT in the tropics seems to be due to increased canopy evaporation due to more precip. The Amazon also has higher transpiration. Lower photosynthesis in the tropics.

A note about the streams. The forcing data is hourly and the model time-step is 1/2 hourly. I've left the time interpolation for solar, precip, and the rest of the variables at "coszen", "nearest", and "linear", respectively. I think those are still the right choices for precip and the "linear" variables. I'm not sure how well "coszen" works for hourly data interpolated to 1/2 hourly. Needs to be investigated. And probably the diurnal cycle of all these variables needs to be looked at in more detail also.

[dlawrenncar]

If it would be easy, an ILAMB comparison would be interesting to see, not so much necessarily to look at the model output, but to see what the climate forcing scores look like. Even better would be a three way comparison between a CRUJRA run, a GSWP3 run, and a CFORCE run. I think we had previously seen a degradation in the forcing scores for CRUJRA.

…

On Thu, Nov 13, 2025 at 12:21 PM Keith Oleson ***@***.***> wrote: *olyson* left a comment (ESCOMP/CTSM#3588) <#3588 (comment)> Land diagnostics for a SP CFORCE run compared to CRUJRA2024 are here <https://webext.cgd.ucar.edu/I2000/Clm60SP_ctsm53084_1deg_ERA5CFORCE_2000/lnd/Clm60SP_ctsm53084_1deg_ERA5CFORCE_2000_1981_1989-Clm60SP_ctsm53084_1deg_CRUJRA2024_2000_1981_1989/setsIndex.html> . Maybe most useful to look at the set2 contour plots for these forcing variables: PREC, RAIN, SNOW, TBOT, WIND, THBOT, QBOT, PBOT, ZBOT, FLDS, FSDS (and the partitioning into visible, near-infrared, direct, and diffuse). Some interesting model responses in LHEAT, FSH, and FPSN (annual mean). Significant increases in LHEAT (and decreases in FSH) almost everywhere, particularly in the tropics. Some of this increase in LHEAT in the tropics seems to be due to increased canopy evaporation due to more precip. The Amazon also has higher transpiration. Lower photosynthesis in the tropics. A note about the streams. The forcing data is hourly and the model time-step is 1/2 hourly. I've left the time interpolation for solar, precip, and the rest of the variables at "coszen", "nearest", and "linear", respectively. I think those are still the right choices for precip and the "linear" variables. I'm not sure how well "coszen" works for hourly data interpolated to 1/2 hourly. Needs to be investigated. And probably the diurnal cycle of all these variables needs to be looked at in more detail also. — Reply to this email directly, view it on GitHub <#3588 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AFABYVHBO5GOB67QG7EJLB334TK37AVCNFSM6AAAAACLMKZ4I6VHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZTKMRZGM2TANJRGA> . You are receiving this because you commented.Message ID: ***@***.***>

[olyson]

I like that idea. Currently, the CFORCE data is only available for 1980-1989. I think it would be desirable to extend that through 2014, which is when the GSWP3 data ends. The ILAMB datasets that evaluate forcing extend out that far as well. @margarita-markina , would it be possible to process data out through 2014? I see some directories corresponding to those years, but don't have permissions to look at them to see if they have what we would need.
In the meantime though, I could do a GSWP3 run for 1980-1989 and run ILAMB on the three simulations for that time period...if we want to proceed quickly.

[margarita-markina]

Will do! One more note: in my A-compset runs I set tintalgo = linear and offset = 0 for SWDN, because the coszen option was giving weird results (not sure yet if that’s related to the hourly forcing or something else). So you might want to double-check this on your side as well.