Translating Process Understanding to Improve Climate Models Workshop Products
One of the outcomes from the workshop was a white paper, released August 2016, summarizing questionnaire responses, workshop presentations, discussions, and recommendations to inform the broad research community and agency considerations.
Another product that stemmed from workshop discussions was examples of some of the types of processes that participants thought were in a reasonable state of readiness for translation into climate model improvements, including information on the motivation for addressing them. In addition to improving specific processes within the model, there was a stated need to incorporate new model capabilities for missing processes and components. The workshop identified many different opportunities for model improvement by incorporating new process understanding. Some of these opportunities are summarized in Table 1, but any future activities should not be limited to the topics discussed in this document or at the workshop given that the interests of only a subset of the community have been considered thus far.
Table 1. Selected set of examples of the type of processes/phenomena identified at the workshop that participants felt were in a reasonable state of readiness for translation into climate model improvements.
| Process / Phenomenon | Potential Bias Improvement | Motivation | References |
Estuarine/fjord – ocean interactions | Salinity near estuaries and rivers; coastal ocean stratification | Allows for riverine nutrient & heat transport; impacts coastal biogeochemistry | Geyer and MacCready (2014), Horner-Devine et al. (2015) |
Atmospheric boundary layer and land surface interaction | Forecast biases on sub-seasonal timescales | Improvements in soil moisture coupling to atmospheric boundary layer | Kumar et al. (2014) |
Equatorial mixing | Cold tongue bias | Can influence simulated variability (ENSO), surface coupling | Sasaki et al. (2013) |
Eddy life cycle and energetics | Mixed layer depth; primary production | Controls on vertical ocean exchange, upper ocean stratification, non-Newtonian mixing parameterization | Mana and Zanna (2014), Jansen et al. (2015b) |
Eastern boundary upwelling | Warm regional SST bias | Improve coupled interactions and feedbacks; impacts on BGC | Small et al. (2015) |
Western boundary currents | SST, surface heat fluxes, and oceanic heat transport | Potential links to AMOC, decadal variability | Carton et al. (2014), Hu et al. (2015) |
Swell and Langmuir turbulence | Southern ocean mixed layer bias | Potentially influence ocean transient response | Fan and Griffies (2014) |
Shelf-open ocean exchange | Ocean water mass and density structure | Potential influence on shelf biogeochemical processes including upwelling driven primary production, hypoxia, and low pH events | Bryan et al. (2015) |
Gravity wave drag | Large-scale atmospheric circulation | Improved wind stress and coupling | Geller et al. (2013) |
Topographic wave drag | Internal wave representation and large-scale ocean circulation | Improved energy balance representation in ocean interior | Trossman et al. (2016) |
Atmospheric moist convection | Diurnal cycle of precipitation, MJO | Improvements to tropical climate and variability | Pearson et al. (2014) |
Mixed-phase clouds | Radiation biases, precipitation biases | Potential influence on cloud feedbacks | Pithan et al. (2014) |
Glacier/ice shelf - ocean interaction | Ocean influence on glacial and ice-sheet retreat
| Potential impact of increased glacial meltwater discharge on ocean circulation including AMOC and of ocean dynamics on variable submarine melting of glaciers/ice shelves | Straneo and Heimbach 2013
|
Snow on sea ice | Snow and albedo biases | Influences polar feedbacks | Hezel et al. (2012) |
References:
Bryan, F., J. Dennis, P. MacCready, and M. Whitney, 2015: Final report collaborative project. Improving the representation of coastal and estuarine processes in Earth system models. NCAR Technical Report 1226494, doi:10.2172/1226494.
Carton, J. A., S. A. Cunningham, E. Frajka-Williams, Y.-O. Kwon, D. P. Marshall, and R. Msadek, 2014: The Atlantic overturning circulation: More evidence of variability and links to climate. Bull. Amer. Meteorol. Soc., 95, 163, doi:10.1175/BAMS-D-13-00234.1.
Clement, A. C., R. Burgman, and J. R. Norris, 2009: Observational and model for positive low-level cloud feedback. Science, 325, 460-464, doi:10.1126/science.1171255.
Fan, Y., and S. M. Griffies, 2014: Impacts of parameterized Langmuir turbulence and nonbreaking wave mixing in global climate simulations. J. Climate, 27, 4752-4775, doi:10.1175/JCLI-D-13-00583.1.
Geller, M. A., and Coauthors, 2013: A comparison between gravity wave momentum fluxes in observations and climate models. J. Climate, 26, 6383-6405, doi:10.1175/JCLI-D-12-00545.1.
Geyer, W. R., and P. MacCready, 2014: The estuarine circulation. Ann. Rev. Fluid Mech., 46, 175–197, doi:10.1146/annurev-fluid-010313-141302.
Hezel, P. J., X. Zhang, C. M. Bitz, B. P. Kelly, and F. Massonnet, 2012: Projected decline in spring snow depth on Arctic sea ice caused by progressively later autumn open ocean freeze-up this century. Geophys. Res. Lett., 39, L17505, doi:10.1029/2012GL052794.
Horner-Devine, A. R., R. D. Hetland, and D. G. MacDonald, 2015. Mixing and transport in coastal river plumes. Ann. Rev. Fluid Mech., 47, 569-594, doi:10.1146/annurev-fluid-010313-141408.
Hu, D., and Coauthors, 2015: Pacific western boundary currents and their roles in climate. Nature, 522, 299-308, doi:10.1038/nature14504.
Jansen, M., A. Adcroft, R. Hallberg, and I. M. Held, 2015b: Parameterization of eddy fluxes based on a mesoscale energy budget. Ocean Modell., 92, 28-41, doi:10.1016/j.ocemod.2015.05.007.
Junker, T., M. Schmidt, and V. Mohrholz, 2015: The relation of wind stress curl and meridional transport in the Benguela upwelling system. J. Mar. Syst., 143, 1-6, doi:10.1016/j.jmarsys.2014.10.006.
Kumar, S., and Coauthors 2014: Effects of realistic land surface initializations on subseasonal to seasonal soil moisture and temperature predictability in North America and in changing climate simulated by CCSM4. J. Geophys. Res.: Atmos., 119, 13,250-12,270, doi:10.1002/2014JD022110.
Kemppinen, O., T. Nousiainen, and G. Y. Jeong, 2015: Effects of dust particle internal on light scattering. Atmos. Chem. Phys., 15, 12011-12027, doi:10.5194/acp-15-12011-2015.
Mana, P. G. L, and L. Zanna, 2014: Toward a stochastic parametrization of ocean mesoscale eddies. Ocean Modell., 79, 1-20, doi:10.1016/j.ocemod.2014.04.002.
Pearson, K. J., G. M. S. Lister, C. E. Birch, R. P. Allan, R. J. Hogan, and S. J. Woolnough, 2014: Modelling the diurnal cycle of tropical convection across the ‘grey zone’. Quart. J. Roy. Meteorol. Soc., 140, 491-499, doi:10.1002/qj.2145.
Pithan, F., B. Medeiros, and T. Mauritsen, 2014: Mixed-phase clouds cause climate model biases in Arctic wintertime temperature inversions. Climate Dyn., 43, 289-303, doi:10.1007/s00382-013-1964-9.
Sasaki, W., K. J. Richards, and J. J. Luo, 2013: Impact of vertical mixing induced by small vertical scale structures above and within the equatorial thermocline on the tropical Pacific in a CGCM. Climate Dyn., 41, 443-453, doi:10.1007/s00382-012-1593-8.
Straneo, F. and Heimbach, P., 2013. North Atlantic warming and the retreat of Greenland's outlet glaciers. Nature, 504, 36-43, doi:10.1038/nature12854.
Trossman, D. S., B. K. Arbic, S. T. Garner, J. A. Goff, S. R. Jayne, E. J. Metzger, and A. J. Wallcraft, 2013: Impact of parameterized lee wave drag on the energy budget of an eddying global ocean model. Ocean Modell., 72, 119-142, doi:10.1016/j.ocemod.2013.08.006.