Exploring the ability of the variable-resolution CESM to simulate cryospheric-hydrological variables in High Mountain Asia
Abstract. Earth System Models (ESMs) can help to improve the understanding of climate-induced cryospheric-hydrological impacts in complex mountain regions, such as High Mountain Asia (HMA). Coarse ESM grids, however, have difficulties in representing cryospheric-hydrological processes that vary over short distances in complex mountainous environments. Variable-resolution (VR) ESMs could help to overcome these limitations. This study investigates the ability of the VR-Community Earth System Model (VR-CESM) to simulate cryospheric-hydrological variables such as glacier surface mass balance (SMB) over HMA. To this end, a new VR grid is generated with regional grid refinement up to 7 km over HMA. Two coupled atmosphere-land simulations are run for the period 1979–1998. The second simulation is performed with an updated glacier-cover dataset and includes snow and glacier model modifications. To evaluate the outcomes, comparisons are made to gridded outputs derived from a globally uniform 1degree CESM grid, observation-, reanalysis-, and satellite-based datasets, and a glacier model forced by a regional climate model (RCM). In general, climatological biases are reduced compared to the coarse-resolution CESM grid, but glacier SMB is too negative relative to observation-based glaciological and geodetic mass balances as well as RCM-forced glacier model output. In the second simulation, the SMB is improved but still underestimated due to cloud-cover and temperature biases, missing model physics, and incomplete land-atmosphere coupling. The outcomes suggest that VR-CESM could be a useful tool to simulate cryospheric-hydrological variables and to study climate change in mountainous environments, but further developments are needed to better simulate the SMB of mountain glaciers.
René R. Wijngaard et al.
Status: final response (author comments only)
- RC1: 'Comment on tc-2022-256', Anonymous Referee #1, 06 Feb 2023
- RC2: 'Comment on tc-2022-256', Anonymous Referee #2, 13 Feb 2023
René R. Wijngaard et al.
René R. Wijngaard et al.
Viewed (geographical distribution)
The authors evaluate the performance of a variable-resolution (VR) configuration of the Community Earth System version 2 over the High Mountain Asia (HMA) region, focusing on the cryospheric-hydrological variables. A new VR mesh is produced for this study with its grid spacing refined to ~ 7 km over the HMA region from ~ 1° in the coarse-resolution domain. A new glacier-cover input data is also produced for the VR grid.
The performance of VR configuration is compared to a globally uniform ~1° grid (NE30) through 20-year long simulations (1979-1998) and also evaluated against a variety of observational dataset. While the regionally refined mesh improves some aspects of the simulation quality, such as the circulation patterns forced by the topography, other aspects are degraded from the NE30 simulation. One reason for the degradation is model sensitivity to spatial resolution and time step length, i.e., less optimal tuning. Another VR simulation with several tuning to alleviate such sensitivities showed improved performance, but model biases still remain. They also suggest several future directions to reduce the VR model bias and improve physical representations in both the atmosphere and land models, as well as their coupling method.
The study addresses questions relevant to the scope of TC. The target region (HMA) is an important natural resource for the population in the broad Asia region. The model they evaluate (CESM) is a widely used community model. The grid resolution within the regional refinement is higher than a previous study focusing on the same region using CESM, and the new glacier input data is a original product from this study. The text is well written, and figures are overall high quality, altough I have several minor suggetions. All together, I think this study can be an important contribution to the community.
However, I have one major concern about their atmospheric model configuration and one suggestion of additional experiment that could strengthen the scientific quality and impact of the manuscript. Please consider the following major comments before publication.
1) I believe the spectral element dynamical core used in this study is the hydrostatic version, which is not expected to be appropriate for the 7-km grid spacing. Several previous studies found that hydrostatic and non-hydrostatic schems produce Significantly different solutions in sub-10km grid spacings, or even larger gridcell sizes over steep topography like HMA (Wedi and Smolarkiewicz 2009, Prein et al., 2015, Yang et al., 2017). Errors would appear in vertical acceleration or unphysical propagations of gravitiy waves, which certainly affect moist physics behavior over HMA. No assessment of those aspects were provided in the manuscript.
Another related concern is the vertical resolution. The small horizontal grid spacing is probably not balanced by the rather coarse 32 vertical levels (Lindzen and Fox-Rabinovitz 1989, Skamarock et al., 2019). Any testing was done with diffrent vertical levels?
Because I believe that the model is used with the resolution outside of its intended use, I strongly suggest the authors providing justifications and caveats to the readers about their results. The atmospheric model configuration used here should not be recommended as the standard for future modeling studies on the 7km VR grid.
2) First, I appreciate the authors for not only identifying model biases but also suggesting certain model components/characteristics that contribute to the biases, e.g., tropospheric warming due to stronger vertical motion and additional heating from CLUBB at higher resolution and with a shorter time step. But some of bias attribution remain speculative/qualitative or too general (section 3.7), which I feel is limiting the impact of the manuscript.
Noting that enough materials are presented in the current draft, I'd still like to suggest conducting off-line CLM5 simulations on the same two grids, NE30 and HMA_VR, forced by observed meteorology. Off-line land simulations are much cheaper than the coupled atmosphere-land simulation and would help partition model biases in the surface/near-surface variables, espesically SEB and SMB, into those from the land model alone or those from errornous forcing from the atmosphere (or from problems arising from coupling or feedback). It is also worth asking if finer grid resolution and/or the new glacier data improve the off-line CLM5 performance. Having more accurate knowledge of CLM5 performance will help strengthen the logical basis for the discussion in section 3.7.
Lindzen, R. S., & Fox-Rabinovitz, M. (1989). Consistent vertical and horizontal resolution. Monthly Weather Review, 117, 2575–2583.
Lu, J., Chen, G., Leung, L. R., Burrows, D. A., Yang, Q., Sakaguchi, K., & Hagos, S. (2015). Toward the Dynamical Convergence on the Jet Stream in Aquaplanet AGCMs. Journal of Climate, 28(17), 6763–6782. https://doi.org/10.1175/JCLI-D-14-00761.1
Pope, V. D., & Stratton, R. A. (2002). The processes governing horizontal resolution sensitivity in a climate model. Climate Dynamics, 19(3–4), 211–236. https://doi.org/10.1007/s00382-001-0222-8
Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K., et al. (2015). A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges. Reviews of Geophysics, 53, 1–39. https://doi.org/10.1002/2014RG000475.Received
Rauscher, S. a., & Ringler, T. D. (2014). Impact of variable-resolution meshes on midlatitude baroclinic eddies using CAM-MPAS-A. Monthly Weather Review, 142(11), 4256–4268. https://doi.org/10.1175/MWR-D-13-00366.1
Skamarock, W. C., Snyder, C., Klemp, J. B., & Park, S.-H. (2019). Vertical Resolution Requirements in Atmospheric Simulation. Monthly Weather Review, 147(7), 2641–2656. https://doi.org/10.1175/mwr-d-19-0043.1
Wedi, N. P., & Smolarkiewicz, P. K. (2009). A framework for testing global non-hydrostatic models. Quarterly Journal of the Royal Meteorological Society, 135, 469–484. https://doi.org/10.1002/qj.377
Yang, Q., Leung, L. R., Lu, J., Lin, Y. L., Hagos, S., Sakaguchi, K., & Gao, Y. (2017). Exploring the effects of a nonhydrostatic dynamical core in high‐resolution aquaplanet simulations. Journal of Geophysical Research: Atmospheres, 122(6), 3245–3265. https://doi.org/10.1002/2016JD025287
"In the western USA and the Chilean Andes, it has been used with regional refinements up to 7 km to simulate regional climate and snowpack (Huang et al., 2016; Rhoades et al., 2016; Bambach et al., 2021; Xu et al., 2021).Also, over the Tibetan Plateau, South Asia, and East Asia, it has been applied to study the regional climate and snow characteristics (Rahimi et al., 2019; Xu et al., 2021). The application of VR-CESM to simulate glacier SMB has been limited, this far, to the Greenland Ice Sheet (van Kampenhout et al., 2019; Herrington et al., 2022)."
I do not find any of the cited studies carrying out 7-km resolution refinement with the CESM-SE or a comparable model; the finest grid spacing seems to be ~ 12km.
Deep convection parameterization is not mentioned. Was it turned off for the simulations in this study?
"including a new glacier region over HMA with a 36-EC scheme in CLM. The new glacier region makes it possible to simulate SMB in multiple (including virtual) ECs in HMA, while retaining the computationally cheaper default behavior of one EC per grid cell in other mountain glacier regions. "
To clarify, in the default CESM/CLM, can a user set different number of ECs for each grid column? Or is this region-dependent EC numbers is a special configuration prepared for this study?
Why the difference in spinup procedure for each VR run? I suppose spin-up procedure affect the model bias against observations, especially those of cryospheric-hydrological variables. So signals from the spin-up difference are likely to be mixed with those from the configuration/resolution differences. The authors can look at model biases of the HMA_VR7b spinup run and compare them to those after spinup to get some ideas of the spinup impact on the analyzed variables.
"The monsoonal circulation in the NE30 run has two centers, a broad region of ascent in the southern HMA region, primarily over the Indian Ocean, and a narrower region of ascent over the front range of the Himalayas.
Please specify which sub-figures or rows are being discussed (e.g., "Figure 6, second row") to help readers follow the text. Maybe it's useful to add indices (a,b,c,...) to each row.
"While the warming and drying patterns are largely the result of greater vertical velocities due to the enhanced spatial resolution in the HMA VR runs, the shorter physics timestep also contributes to this warming and drying (not shown), which is a common response to reducing the physics timestep (Williamson, 2008; Herrington et al., 2022)."
Williamson (2008) does not specifically discuss warming and drying as seen in this work.
He illustrated model sensitivities to both the timeestep and spatial resolution.
According to Herrington et al. (2022), shorter time step contributes only to the warming of the lower troposphere.
Pope and Straten (2002) found a similar warming of the mid-latitude troposphere because of eddy flux and its convergence are enhanced with higher resolution. Although large-scale feature, mid-latitude waves simulated at different resolutions converge only at 50 km or finer grid spacing according to Lu et al.(2015). An enhanced mid-latitude eddies inside regional refinement is reported by Rauscher and Ringler (2014) in their VR simulations as well, so the same processes may be occuring in the simulations here.
Section 3.3 & 3.4
Please clarify what "absolute monthly mean xxxx (e.g., precipitation) differences" means.
Precipitation, snow cover, and snow depth are positive quantities, so no need to use their absolute values.
Why is the NE30 result not included in this section?
"Figure 15 shows the relation between grid-cell-mean SMB and glacier fraction (GCF)"
->"Figure 14 shows..."
The minimum and maximum biases are not good to be used as whiskers for this figure because they
push the y-axis limits so wide that we cannot see the differences in the quantile boxes.
It's probably better to use 95th percentile, 3 standard deviations, or any other quantities that only moderately widens the y-axis range compared to the quantile range.
typo in the caption
"for rainfall (mm month-1) (a-b) and snowfall (mm month-1) (c-d)"
"for rainfall (mm month-1) (a,c) and snowfall (mm month-1) (b,d)"
Figure 11, typo in the caption
-> Obs, black
Figure 12, typo in the caption
"The black box in Figure 14a denote"
-> "The black box in Figure 12a denotes"
Code and Data Availability.
"Data will be available before publication in Zenodo."
What data are you referring to? Will the codes that produced the input data be publicly available?
Section S1 describes the workflow to produce the new glacier data in great detail.
A critical information missing is the codes and/or applications used. Please consider sharing those information as well. Without, it is difficult for other researchers to reproduce the data or apply the same procedure to other regions.
Not sure how the redbox in the inset of Figure S1b represents the outline of HMA.
Do the two insets cover the same area?