6. Coupling CLM and CISM

6.1. Modes of coupling CLM and CISM

6.1.1. Non-evolving ice sheet

In typical CESM runs, CISM is not evolving; CLM computes the ice sheet surface mass balance and sends it to CISM, but CISM’s ice sheet geometry remains fixed over the course of the run, and CISM does not send any fluxes to other CESM components. These configurations use compsets with CISM2%XXX-NOEVOLVE in their long name (for some ice sheet XXX). In these runs, CISM serves two roles in the system:

  1. Over the CISM domain(s) (typically Greenland in CESM2), CISM dictates glacier areas and topographic elevations, overriding the values on CLM’s surface dataset. CISM also dictates the elevation of non-glacier land units in its domain, and only in this domain are atmospheric fields downscaled to non-glacier land units.

  2. CISM provides the grid onto which SMB is downscaled.

6.1.2. Evolving ice sheet with two-way (interactive) coupling

Dynamic ice sheet evolution can be turned on by using a compset with CISM2%XXX-EVOLVE in its long name (for some ice sheet XXX), or by setting the xml variables CISM_EVOLVE_ICESHEET (for one or more instances of ICESHEET) and the overall CISM_EVOLVE after setting up a case. In this configuration, CISM sends updated glacier areas and topographic elevations to CLM at the end of each year. In addition, CISM sends fluxes of ice and liquid water to the ocean. CLM responds to these changes by adjusting the areas of the glacier land unit and each elevation class within this land unit, as well as the mean topographic heights of each elevation class. Thus, CLM’s glacier areas and elevations remain in sync with CISM’s.

When running with two-way coupling, conservation of water and energy in the CLM-CISM coupling becomes important. There are still some unhandled edge cases in this regard (one significant case being when CLM dictates an amount of glacial melt that exceeds the available ice in a CISM grid cell), but we do take pains to achieve conservation in most cases. An important mechanism to achieve this conservation is via a global renormalization step done when mapping SMB from CLM to CISM, as described in Section 6.5.1. By default, this renormalization is done when running with a two-way-coupled ice sheet that sends fluxes to other components (which is typically true in this case of an evolving ice sheet), but is turned off in other cases. This leads to small differences in the remapped SMB field in runs with an evolving vs. non-evolving ice sheet. This default can be overridden via the driver namelist variable, glc_renormalize_smb, keeping in mind that setting this to off will break conservation for a configuration with an evolving, two-way-coupled ice sheet.

6.1.3. Evolving ice sheet with one-way (diagnostic) coupling

A hybrid mode is also possible, in which CISM evolves dynamically but does not feed back to the rest of the system. This configuration is enabled by turning on CISM evolution (by using a CISM2%XXX-EVOLVE compset or changing the relevant CISM_EVOLVE_ICESHEET and overall CISM_EVOLVE xml variables to TRUE), but then changing the xml variable GLC_TWO_WAY_COUPLING to FALSE. This change results in changes to CLM and CISM:

  • CLM will not respond to changes in CISM’s glacier areas and topographic elevations. In addition, even at initialization, CLM is not affected by CISM’s glacier areas and topographic elevations, instead specifying these from its initial conditions file, or from its surface dataset in a cold start or interpolated-start run (as would be the case when running with a stub GLC model, as described below). (In the future, we may want to allow the option that CLM synchronizes its glacier areas and topographic elevations at initialization, but then does not respond to any changes throughout the run.)

  • CISM does not send fluxes of ice or liquid water to the ocean. Instead, fluxes from CLM are treated the same as in the non-evolving ice sheet case. Note that this behavior of whether or not CISM sends fluxes to the ocean can also be controlled independently from GLC_TWO_WAY_COUPLING, via the CISM namelist variable, zero_gcm_fluxes.

6.1.4. Stub GLC model (CISM absent)

It is also possible to run CESM with a stub glacier model rather than CISM by using compsets with SGLC in place of CISM2%XXX-NOEVOLVE. These configurations are similar to those with a non-evolving ice sheet, with the following differences:

  1. CLM’s glacier areas and elevations will be taken entirely from CLM’s initial conditions file, or from its surface dataset in a cold start or interpolated-start run.

  2. In CLM, no downscaling of atmospheric forcings is done over non-glacier land units (but atmospheric forcings are still downscaled over glacier land units in areas with multiple glacier elevation classes).

  3. There is no downscaling of CLM’s surface mass balance and temperature fields to a higher-resolution glacier grid.

This configuration is useful for single-point or regional CLM simulations, or for configurations not supported by CISM (such as runs with a Gregorian, rather than no-leap, calendar), or simply to avoid needing to make CLM-CISM mapping files when running with a new land/atmosphere grid.

6.2. Brief overview of CLM-CISM coupling

This section provides a brief overview of the two-way coupling between CLM and CISM. Details on the coupling fields and their remapping are given in the following sections.

CLM passes two fields to CISM: surface temperature and surface mass balance (SMB). Surface temperature is provided only for glacier land units, whereas SMB is provided for both glacier and vegetated land units. Over the CISM domain, CLM runs with “virtual” vegetated and glacier land units, so that it is able to provide forcing fields even for grid cells where a given land unit has zero area. SMB over glacier land units can be positive (ice accumulation), negative (ice melt) or zero; SMB over vegetated land units can only be positive or zero. A positive SMB over vegetated land units will trigger glacial inception in any underlying CISM cell that is currently unglaciated.

These forcing fields are sent from CLM to the CESM coupler every time step (typically 1/2 hour). The coupler creates annual averages, remaps and downscales these annual averages to the CISM grid, then calls CISM at the end of the year. CISM then uses these forcings to drive its dynamics for the year, likely resulting in changes to glacier area and topographic elevations. These new areas and elevations are sent back to CLM (via the coupler); CLM updates its own areas and elevations over the CISM domain to match these for the following year’s computations.

There is an important but subtle point here: Although CLM is responsible for computing SMB, including glacial inception, its glacier areas and elevations do not change until it receives a signal to do so from CISM.

6.3. Resetting CLM’s baseline states for dynamic landunits


The information in this section is subtle, but it is important for a fully-coupled run with an evolving ice sheet. In particular, it is important that you give some thought to CLM’s reset_dynbal_baselines namelist flag in order to minimize the fictitious sensible heat fluxes generated by CLM’s dynamic landunits code while still conserving water and energy. So please read this section carefully and ask for clarifications if you are still unsure when to set this flag.

The information presented here applies to CLM development tags starting with ctsm1.0.dev031 and to the CLM tag used for the ISMIP6 runs (ismip6.n01_release-clm5.0.15). It does not apply to other CLM versions used in CESM2.1.z releases. You should strive to use a version of CLM where this applies (which can be determined based on the availability of the reset_dynbal_baselines namelist flag) in order to avoid very large dynbal ice and energy fluxes.

6.3.1. Overview of CLM’s dynbal fluxes

When subgrid column or landunit areas change in CLM — as occurs with transient glaciers — the water and energy states of each column remain constant on a per-area basis. In general, this results in a change in the grid cell-integrated water and energy. In order to conserve water and energy in the coupled system, CLM generates adjustment fluxes. Runoff fluxes (either positive or negative) are generated to conserve liquid water and ice, and sensible heat fluxes are generated to conserve energy. Although needed for conservation, these “dynbal” fluxes do not have a physical meaning. (See also the “Transient Land Use and Land Cover Change” chapter of the CLM Technical Note, and in particular the “Mass and Energy Conservation” section in that chapter.)

CLM’s glacier columns have a different state representation from soil columns: glacier columns include nearly 50 m of ice that is (in some sense) “virtual”, yet they do not represent the soil under this ice. These two differences work in opposite directions, but the first dominates because there is much more mass in the 50 m of glacial ice than there is in a typical 50 m soil column. A naïve accounting would therefore generate large dynbal fluxes in the transition between glacier and bare soil.

To reduce these fictitious dynbal fluxes, we subtract baseline values from glacier columns, accounting for the two issues mentioned above: (1) we subtract the water and energy in the glacier ice, because this is a virtual state in CLM, and (2) we add the water and energy from the vegetated column, to account for the fact that we don’t have an explicit representation of soil-under-glacier. (This carries the assumption that the soil-under-glacier has the same state as the initial vegetated state in that grid cell.) We set these baselines in initialization, so they begin equal to the cold start state. Water and ice in the glacial ice stay fixed over the course of a simulation, so the cold start values should be the same as the current values at any point in time. The heat content of the glacial ice does change over time, however, so these default baselines do not sufficiently reduce the dynbal sensible heat fluxes. (In addition, the water and ice contents in the soil column change over time, although this is a secondary concern.) The resolution of this issue is discussed in the following sub-section.

Note that these baseline values do not include aboveground mass and energy — that is, any mass and energy in the snow pack or associated with surface water or vegetation.

6.3.2. Further reducing dynbal fluxes via reset_dynbal_baselines

As mentioned above, the use of baselines set based on the cold start state is not sufficient to reduce the dynbal sensible heat fluxes. For a grid cell that undergoes full glaciation or deglaciation in a single year (the first of which can often happen in practice in the model), CLM can generate dynbal sensible heat fluxes on the order of 10s of W m-2 every time step for the following year. To reduce these dynbal sensible heat fluxes, CLM provides the namelist flag, reset_dynbal_baselines. Use of this flag can also further reduce the runoff fluxes, since water and ice contents in the soil column can change over time.

Setting reset_dynbal_baselines = .true. in user_nl_clm at the start of a simulation resets the baselines for glacier columns to values based on the states in CLM’s initial conditions file for that simulation. This can be done, for example, when transitioning from an offline spinup to a fully-coupled run. The baseline values are saved to CLM’s restart file, so the same baselines will then persist for the remainder of this simulation, as well as for any new cases branched off of this one. (This setting only impacts startup and hybrid runs. It has no effect in a continue run, so it is safe to keep this flag set to .true. for resubmissions of the case. It is an error for this to be set in a branch run. Furthermore, this setting has no effect in a cold start run.) If the states haven’t changed much from the reset point to the point when glacier dynamics occur (because the system was close to equilibrium when you reset baselines), then the dynbal fluxes arising from glacier dynamics should be very small.

Setting reset_dynbal_baselines to true in the midst of a series of simulations has the potential to break water and energy conservation, so care is needed regarding exactly when to set this flag. Specifically, any water and energy that has previously been added to or removed from states that contribute to these baselines (currently, (a) glacier ice and (b) soil water and energy in the vegetated landunit in the same grid cell as glaciers) will effectively be ignored when computing conservation corrections due to land cover change. Instead, only the change in states from this point forward will be considered.

Here are guidelines for when this flag should and should not be set:

  1. If you are starting a fully-coupled (B compset) case with an evolving, two-way-coupled ice sheet, using initial conditions from a case without a full ocean (I or F compset): You should set reset_dynbal_baselines = .true. at the start of this fully-coupled case.

  2. If you are transitioning from one coupled run with an evolving ice sheet to another (e.g., from a historical to a future transient run): Do not set reset_dynbal_baselines, as this will break conservation.

  3. What about the situation where you are starting a fully-coupled case with an evolving, two-way-coupled ice sheet, using initial conditions from a fully-coupled case with a non-evolving ice sheet? For example, you may be doing a series of (a) offline spinup (via an I compset), (b) further coupled spinup with a non-evolving ice sheet, (c) coupled run with an evolving ice sheet; should you reset the baselines at the start of (b) or at the start of (c)? Doing so at the start of (b) is safe (as for case (1), above), but what about doing so at the start of (c)? It’s unclear whether resetting the dynbal baselines at this time is the “right” thing to do. Doing so would likely result in smaller dynbal fluxes, but may result in some loss of conservation. Referencing the two ways to think about the dynbal fluxes (in section Section If we think of the baselines as being arbitrary, then it seems safe to reset them at this time, because the dynbal baselines aren’t invoked until the onset of transient glacier areas, so it seems safe to reset them up until that transient behavior begins. However, if we think of the baselines as being more physically-based, then it seems wrong to reset them at this time, because there may (for example) have truly been some energy absorbed by CLM’s glacier ice since the start of the coupled run, and this energy should be released back to the system when the ice sheet retreats.

Note that the value of this flag has no significant impact on cases with a non-evolving ice sheet.

6.3.3. Confirming that the dynbal fluxes are small in your simulation

When running a coupled simulation with an evolving ice sheet, it is a good idea to periodically check CLM’s dynbal fluxes to ensure that they remain relatively small. The three relevant fluxes are EFLX_DYNBAL, QFLX_LIQ_DYNBAL, and QFLX_ICE_DYNBAL. It is a good idea to check these fluxes for the first few years of your simulation, and then periodically spot-check them at various other points throughout the run.

The point of this is to ensure that CLM’s fluxes to the ocean and atmosphere aren’t being dominated by these fictitious, conservation-correction fluxes. These fluxes remain constant throughout a given year, so it is sufficient to check a single monthly average for a given year, or to only output annual averages of these fields.

6.3.4. More details and thoughts on these dynbal fluxes

It is not necessary that you read this sub-section, but we provide it in case you would like more details and thoughts on these dynbal fluxes. Two ways to think about the subtraction of baselines

It seems that there are two ways to think about this subtraction of baselines for the sake of computing dynbal fluxes:

  1. More physically-based: we choose which states to subtract and add via baselines in order to have a state representation that more closely matches reality. For glaciers, we subtract the virtual ice column, and add the missing soil-under-glacier.

  2. Choose baselines in order to minimize dynbal fluxes. We are free to choose whatever baselines we want in order to minimize fluxes (as long as these baselines are constant in time — though I think it is fine for them to vary for different columns within or between grid cells). We can think of counting the water and energy contents relative to some arbitrary “zero” state (where the baseline values give this “zero” state), or roughly equivalently, counting the change in water and energy contents over time relative to some starting point. One way to think about this is that we have some unknown states (e.g., the soil under glacier); we are free to keep these values in an “unknown” state (rather than assigning them some arbitrary value) until the last possible moment.

I’m not sure if (2) is always acceptable. For glaciers, it turns out that the two methods lead us to the same place for mass, though not necessarily for energy. For cases where the two ways of thinking lead us to different places, I’m not sure if (2) is an acceptable way to think about these baselines, in terms of conservation. Other resources

See also the “Transient Land Use and Land Cover Change” chapter of the CLM Technical Note, and in particular the “Mass and Energy Conservation” section in that chapter.

For more details and diagrams of water and energy conservation with dynamic landunits, see the Dynamic landunits water and energy conservation presentation.

6.4. Fields exchanged between CLM and CISM

6.4.1. CLM to CISM Overview

CLM passes three fields to the coupler for the sake of CLM-CISM coupling: surface mass balance (SMB), surface temperature, and surface topographic height. The first two are remapped/downscaled and sent to CISM, whereas surface topographic height is just used by the coupler itself in the downscaling routine. Each CLM grid cell sends \(N+1\) copies of each of these fields, where \(N\) is the number of elevation classes, and the additional \(1\) is for the bare/vegetated portion of the grid cell. (However, surface temperature and topographic height are irrelevant for the bare/vegetated portion.) CLM sends values of these fields every time step (typically 1/2 hour). The coupler creates annual averages of the fields before remapping and downscaling them to the CISM grid.

Details of CLM’s glacier treatment, including the surface mass balance calculation, are given in the “Glaciers” chapter of the CLM Technical Note.

Note that the CLM-CISM coupling does not currently have the capability to couple using a positive degree day (PDD) scheme. Surface mass balance (SMB)

The SMB calculation is described in detail in the “Glaciers” chapter of the CLM Technical Note. Here we just summarize a few important points.

CLM’s SMB currently only considers changes in the ice column, not changes in the snow pack. A positive SMB (ice accumulation) is generated when the snow pack grows beyond its prescribed limit (snow capping). A negative SMB (ice melt) is generated when CLM’s ice column experiences melt. A positive (but not negative) SMB can be generated over CLM’s vegetated land unit; this condition triggers glacial inception in CISM. Surface temperature

CLM sends surface temperature to provide an upper boundary condition for CISM’s temperature calculations. In CLM, this is the temperature of the top ice layer. Surface topographic height

The average topographic height of each glacier elevation class is needed for the downscaling, as described below. When running two-way-coupled, CLM’s topographic heights are obtained via averages of the underlying CISM grid cells. However, CLM sends these heights back to the coupler so that the downscaling routine has access to these values regardless of whether we are running one-way or two-way coupled.

6.4.2. CISM to CLM Mask of ice-covered vs. ice-free points

Each grid cell in CISM is classified as either ice-covered or ice-free (there are no partially-ice-covered cells). CISM uses different definitions of ice-covered for different purposes; for the purposes of this coupling, any cell with ice thickness greater than zero is considered to be ice-covered. This field is used in conjunction with surface height to determine the total glacier fraction in each CLM grid cell, as well as the fractional cover of each CLM glacier elevation class.

This field is needed even when running one-way-coupled, because it is used in the CLM-to-CISM downscaling (to determine which CISM grid cells should receive SMB from glacier land units vs. vegetated land units). Surface height

CISM sends the surface height of each grid cell. For glaciers, this is the height of the ice surface. For ice-free points, this is the topographic height. This field is used to determine the fractional cover and mean elevation of each CLM glacier elevation class, as well as the mean elevation of the vegetated land unit in each CLM grid cell within the CISM domain.

This field is needed even when running one-way-coupled, because it is used in the CLM-to-CISM downscaling. Ice sheet grid mask

CLM needs a way to know where CISM is sending valid data, and thus knowing where it should update its glacier areas and elevations. This is provided via the “ice sheet grid mask”. CISM sets this field to 1 for all points that are either bare land or ice-covered (including floating ice), and 0 for open ocean (this is determined based on the criterion, usrf > 0; in principle, this criterion could cause problems if there were a grid cell with usrf <= 0 despite having non-zero ice thickness). This mask is important so that CLM maintains the values specified by its surface dataset outside the CISM domain, as well as in areas that CISM considers to be open ocean but CLM considers to be at least partially land-covered.

This mask is also used in the coupler to determine the ice sheet region over which SMB must be conserved in the SMB remapping process (see Section 6.5.1). We assume that we can use the same mask for these two purposes (i.e., both for defining where CISM is sending valid data and for defining where CISM can receive SMB). (This use of the ice sheet grid mask more closely aligns with the use of the mask where we are potentially sending non-zero fluxes, described in Section However, we can’t use that mask for the remapping, because we then could only perform renormalization if we were running with two-way coupling. For this reason, it is important that these two masks are defined in the same way.)

One subtlety regards the treatment of land points that fall within CISM’s rectangular grid but are outside of Greenland - chiefly, Ellesmere Island. We do not want CISM to handle these points, and we want CLM to maintain the glacier cover from its surface dataset there. To accomplish this, all land points outside of Greenland are artificially submerged to below sea level in a preprocessing step applied to CISM’s input file. Thus, these points are not included in the ice sheet grid mask.

This mask is (slightly) dynamic in time, both because of its inclusion of ice shelves and because (with isostasy) CISM’s land-ocean boundary can change in time.

This mask is regridded to the CLM grid using simple area-conservative remapping. (Elevation classes are irrelevant here.) Ice sheet mask where we are potentially sending non-zero fluxes

CLM also needs to know where CISM is a fully-coupled part of the climate system - i.e., where it is potentially sending non-zero runoff fluxes to the ocean. CLM uses this information to determine how to route its positive and negative SMB terms in order to conserve water. This is described in detail in the “Glaciers” chapter of the CLM Technical Note. In particular, see the discussion of the dependence on glc_dyn_runoff_routing in that chapter: CLM’s glc_dyn_runoff_routing is true within this mask and false outside of it.

This mask is currently a subset of the ice sheet grid mask. Currently, it is identical to the ice sheet grid mask if we are running with an evolving, two-way-coupled ice sheet, and otherwise is zero everywhere (and, as described in Section, this relationship should remain true, because the ice sheet grid mask is used in the coupler in a way that closely matches the use of this second mask). One reason this is sent as a separate field is to handle the scenario where there are multiple ice sheets (e.g., Greenland and Antarctica), with one ice sheet operating two-way-coupled while another is one-way-coupled. In this case, this mask matches the ice sheet grid mask for the two-way-coupled ice sheet and is zero for the other.

Note that, like the ice sheet grid mask, this mask excludes CISM’s open ocean grid cells. CISM does not currently have code in place to handle inputs of SMB over open ocean (e.g., routing this SMB directly to the ocean), so CLM needs to treat these open ocean areas the same as points completely outside CISM’s domain for conservation reasons.

This mask, like the ice sheet grid mask, is regridded to the CLM grid using simple area-conservative remapping. (Elevation classes are irrelevant here.) Heat flux

Hooks are in place for CISM to send the heat flux from the ice interior to the surface to each CLM elevation class. However, this is not yet fully implemented, leading to a small loss of energy conservation.

This flux is only applicable when running with an evolving, two-way-coupled ice sheet.

6.4.3. Other fields sent from CISM Ice runoff (calving)

CISM sends an ice runoff - i.e., calving - flux directly to the ocean (POP). When this flux reaches the ocean, POP immediately melts the ice, so this ice flux is equivalent to a negative salinity flux together with a negative heat flux. Hooks are in place to instead direct this flux to the sea ice model, but CESM’s sea ice model is not yet capable of simulating icebergs.

This flux is only applicable when running with an evolving, two-way-coupled ice sheet. Liquid runoff (basal melting)

CISM sends a liquid runoff flux directly to the ocean; this is generated from basal melting. Note that this term does not include surface melting: the surface melt term is sent from CLM to the ocean via the runoff routing model.

This flux is only applicable when running with an evolving, two-way-coupled ice sheet.

6.5. Remapping fields sent from CLM to CISM

6.5.1. Remapping surface mass balance from CLM to CISM

As described above, the surface mass balance (SMB) of ice sheets is computed by CLM for each column (i.e., elevation class) of each glaciated landunit in each grid cell on the land grid. The SMB is then remapped by the coupler to the finer ice sheet grid and passed to CISM. When CESM is run with two-way, interactive coupling between glaciers and ice sheets, we want to conserve the total amount of water in the system, while also mapping SMB smoothly and accurately between grids.

Specifically, we would like the SMB remapping to satisfy the following requirements:

  1. Conservation: For any ice sheet defined by a CISM domain, the sum over CLM grid cells of the SMB sent to the coupler is equal (within machine roundoff) to the sum over CISM grid cells of the SMB received from the coupler. Note that this is a global (i.e., whole-ice-sheet) rather than a local requirement.

  2. Smoothness: The remapping is smooth and continuous on the CISM grid, without obvious imprinting of the coarser CLM grid.

  3. Accuracy: The SMB applied in CISM at a given location is close to the value computed by CLM at that location and elevation.

  4. Sign preservation: Any positive SMB in CLM maps to a positive SMB in CISM, and likewise for negative SMB.

Here we describe the algorithm used by the coupler to satisfy these requirements. First we introduce some notation:

  • lfrac is the fraction of a CLM grid cell that does not overlap the ocean grid and is treated as land. Since the ocean and land grids are non-conforming, we can have 0 < lfrac < 1 in CLM cells near the ocean boundary.

  • Sg_icemask_g is a binary mask on the CISM grid that identifies cells which are ice-covered and/or land-covered, and therefore are eligible to apply a nonzero SMB from CLM. (Ice-free land cells can have a positive SMB, and ice-covered cells can have an SMB of either sign.) CISM cells that are ice- and/or land-covered have Sg_icemask_g = 1, and ice-free ocean cells have Sg_icemask_g = 0.

  • Sg_icemask_l is obtained by mapping Sg_icemask_g from the CISM grid to the CLM grid. Since the grids are different, this mask is not binary; we can have 0 < Sg_icemask_l < 1.

  • g = min(lfrac, Sg_icemask_l) is the fraction of CLM-computed SMB that is sent to CISM via the coupler. The remaining SMB is not sent to CISM. A fraction lfrac - g is sent by the coupler to the runoff model; this is the fraction of the cell that is land-covered but does not overlap the CISM grid. The remaining fraction, 1 - lfrac, is not sent to either CISM or the runoff model, because any precipitation in the non-land part of a CLM cell has already fallen into the ocean.

  • \(A_i\) is the area of a CLM grid cell. CLM and the coupler agree on the grid cell area.

  • \(A_j\) is the area of a CISM grid cell according to CISM, and \(A_j^c\) is the area according to the coupler. These two areas differ because CISM’s stereographic projection does not conserve area.

  • \(f_{ik}\) is the fraction of CLM grid cell i occupied by glacier ice in elevation class k.

  • \(q_{ik}\) is the SMB of CLM grid cell i in elevation class k.

  • \(q_j\) is the SMB remapped to CISM grid cell j.

Using this notation, we can express the conservation requirement (1):

(1)\[\sum_i{g_i A_i \sum_k{f_{ik} q_{ik}}} = \sum_j{A_j q_j},\]

where the sum on the LHS is taken over grid cells i and columns k on the CLM grid, and the sum on the RHS is taken over grid cells j on the CISM grid.

To additionally satisfy sign preservation (4), Eq. (1) is replaced by two equations: one for the accumulation zone (limited to cells and columns with \(q > 0\)), and one for the ablation zone (limited to cells and columns with \(q < 0\)).

Requirements (2) and (3) are ensured by bilinear remapping in the horizontal plane combined with linear interpolation in the vertical. These operations are smooth but not conservative. Thus, in order to satisfy all four requirements, bilinear remapping and vertical interpolation are followed by a normalization step that guarantees conservation in both the accumulation and ablation zones.

The algorithm proceeds as follows:

  1. In CLM, compute the SMB for each grid cell and elevation class (EC) that has nonzero overlap (\(g > 0\)) with the CISM domain, and send to the coupler.

  2. Accumulate and average the SMB for each EC over the CLM-CISM coupling interval (typically 1 year).

  3. At the end of the coupling interval, compute the total SMB in the accumulation and ablation zones of CLM.

  4. For each EC, do a bilinear remapping of SMB from the CLM grid to the CISM grid.

  5. For each CISM grid cell, do a linear interpolation in elevation space between adjacent ECs, to compute the SMB at the CISM cell elevation. If a cell lies above or below the range of elevations in the various ECs, values from the highest and lowest ECs are extrapolated. Note: State whether this is a linear extrapolation from the two highest and lowest ECs, or simply an extension of the highest and lowest values.

  6. Compute the total (uncorrected) SMB in the accumulation and ablation zones of CISM.

  7. Apply a normalization correction for conservation. For example, suppose \(Q_{\text{acc}}^{\text{clm}} = 1.05 \, Q_{\text{acc}}^{\text{cism}}\), where \(Q_{\text{acc}}\) is the total SMB in the accumulation zone of a given model. Then in every CISM cell that lies in the accumulation zone, we would multiply the SMB by \(Q_{\text{acc}}^{\text{clm}}\, / \, Q_{\text{acc}}^{\text{cism}} = 1.05\) (and similarly for the ablation zone).

  8. Send the normalized SMB on the CISM grid to CISM.

Step 1 is done in CLM at every time step. The other steps are done in the coupler, with steps 3-8 carried out at the end of the coupling interval.

In practice, normalization factors usually fall between 0.9 and 1.1 at typical CESM global grid resolutions of \(\sim 1^\circ\). Thus, if an SMB of 1 m/yr is computed in CLM, the downscaled SMB in CISM might differ by up to 10%. If we used conservative rather than bilinear remapping, differences also would be up to about 10%, because of area distortions on CISM’s polar stereographic grid. Thus the local errors for bilinear remapping and renormalization are similar to the local errors for conservative remapping. Bilinear remapping, however, is far smoother; smoothness is obtained at the cost of local conservation.

When running with multiple ice sheets, the conservation correction is applied independently for each ice sheet. This means that the SMB over one ice sheet does not impact the renormalized SMB over another ice sheet.

6.5.2. Remapping surface temperature from CLM to CISM

Surface temperature is remapped similarly to surface mass balance (see Section 6.5.1), but without the renormalization and without separation into accumulation vs. ablation zones:

  1. CLM computes surface temperature for each grid cell and elevation class (EC).

  2. The coupler accumulates and averages surface temperature for each EC over the CLM-CISM coupling interval (typically 1 year).

  3. For each EC, the coupler does a bilinear remapping of surface temperature from the CLM grid to the CISM grid.

  4. For each CISM grid cell, the coupler does a linear interpolation in elevation space between adjacent ECs, to compute the surface temperature at the CISM cell elevation.

6.6. CLM’s glacier regions and their behaviors

CLM divides the world’s glaciers and ice sheets into multiple regions that differ in various respects. For a detailed description of these different glacier behaviors, see the “Glaciers” chapter of the CLM Technical Note. Here we focus on the user interface for controlling these behaviors.

Two sets of CLM inputs work together to determine glacier physics in each grid cell: the GLACIER_REGION field on the surface dataset and a set of namelist options (whose names begin with glacier_region; see the CLM Namelist Definitions for details). The GLACIER_REGION field is an integer from 1 through the number of glacier regions, as well as 0 for all grid cells that are not part of a distinct other region. The various glacier_region namelist options then specify the behavior for each of these regions. The first element in each namelist array specifies the behavior of GLACIER_REGION 0, the second element specifies the behavior of GLACIER_REGION 1, etc.

(We rely on CLM’s surface dataset rather than making behaviors dependent on CISM’s ice sheet grid mask because we don’t want CLM physics to change just because CISM is using a different grid.)


If you want ice sheet forcings (SMB and surface temperature) for regions other than the standard Greenland CISM domain, it is critical that you give some thought to this GLACIER_REGION field and the associated namelist options: You will need to ensure that your glacier regions are set up to have virtual elevation classes (glacier_region_behavior = 'virtual'), and that glaciers produce a valid SMB field (glacier_region_melt_behavior = 'replaced_by_ice') wherever you want forcings for CISM.