. SURFEX is a new externalized land and ocean surface platform that describes the surface fluxes and the evolution of four types of surfaces: nature, town, inland water and ocean. It is mostly based on pre-existing, well-validated scientific models that are continuously improved. The motivation for the building of SURFEX is to use strictly identical scientific models in a high range of applications in order to mutualise the research and development efforts. SURFEX can be run in offline mode (0-D or 2-D runs) or in coupled mode (from mesoscale models to numerical weather prediction and climate models). An assimilation mode is included for numerical weather prediction and monitoring. In addition to momentum, heat and water fluxes, SURFEX is able to simulate fluxes of carbon dioxide, chemical species, continental aerosols, sea salt and snow particles. The main principles of the organisation of the surface are described first. Then, a survey is made of the scientific module (including the coupling strategy). Finally, the main applications of the code are summarised. The validation work undertaken shows that replacing the pre-existing surface models by SURFEX in these applications is usually associated with improved skill, as the numerous scientific developments contained in this community code are used to good advantage.

/pdf/the-surfexv7-2-land-and-ocean-surface-platform-for-coupled-261aoq10jv.pdf

The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes

This paper reviews the current state of knowledge pertaining to the interactions of lake ice and climate. Lake ice has been shown to be sensitive to climate variability through observations and modelling, and both longterm and short-term trends have been identified from ice records. Ice phenology trends have typically been associated with variations in air temperatures while ice thickness trends tend to be associated more to changes in snow cover. The role of ice cover in the regional climate is less documented and with longer ice-free seasons possible as a result of changing climate conditions, especially at higher latitudes, the effects of lakes on their surrounding climate (such as increased evaporation, lake-effect snow and thermal moderation of surrounding areas, for example) can be expected to become more prominent. The inclusion of lakes and lake ice in climate modelling is an area of increased attention in recent studies. An important step in improving predictions of ice conditions in models is the assimilation of remote sensing data in areas where in-situ data is lacking, or non-representative of the lake conditions. The ability to accurately represent ice cover on lakes will be an important step in the improvement of global circulation models, regional climate models and numerical weather forecasting.

The response and role of ice cover in lake-climate interactions

An improved lake model for climate simulations: Model structure, evaluation, and sensitivity analyses in CESM1 Zachary M. Subin 1,2 , William J. Riley 2 and Dmitrii Mironov 3 Lakes can influence regional climate, yet most general circulation models have, at best, simple and largely untested representations of lakes. We developed the Lake, Ice, Snow, and Sediment Simulator (LISSS) for inclusion in the land-surface component (CLM4) of an earth system model (CESM1). The existing CLM4 lake model performed poorly at all sites tested; for temperate lakes, summer surface water temperature predictions were 10–25uC lower than observations. CLM4-LISSS modifies the existing model by including (1) a treatment of snow; (2) freezing, melting, and ice physics; (3) a sediment thermal submodel; (4) spatially variable prescribed lake depth; (5) improved parameterizations of lake surface properties; (6) increased mixing under ice and in deep lakes; and (7) correction of previous errors. We evaluated the lake model predictions of water temperature and surface fluxes at three small temperate and boreal lakes where extensive observational data was available. We also evaluated the predicted water temperature and/or ice and snow thicknesses for ten other lakes where less comprehensive forcing observations were available. CLM4- LISSS performed very well compared to observations for shallow to medium-depth small lakes. For large, deep lakes, the under-prediction of mixing was improved by increasing the lake eddy diffusivity by a factor of 10, consistent with previous published analyses. Surface temperature and surface flux predictions were improved when the aerodynamic roughness lengths were calculated as a function of friction velocity, rather than using a constant value of 1 mm or greater. We evaluated the sensitivity of surface energy fluxes to modeled lake processes and parameters. Large changes in monthly-averaged surface fluxes (up to 30 W m 22 ) were found when excluding snow insulation or phase change physics and when varying the opacity, depth, albedo of melting lake ice, and mixing strength across ranges commonly found in real lakes. Typical variation among model parameterization choices can therefore cause persistent local surface flux changes much larger than expected changes in greenhouse forcing. We conclude that CLM4-LISSS adequately simulates lake water temperature and surface energy fluxes, with errors comparable in magnitude to those resulting from uncertainty in global lake properties, and is suitable for inclusion in global and regional climate studies. prediction of climate at the regional scale in regions with large lake area [Dutra et al., 2010; Krinner, 2003; Lakes typically have different albedo, greater sub- Lofgren, 1997; Long et al., 2007; Rouse et al., 2005; surface heat conductance and effective heat capacity, Samuelsson et al., 2010], and are important in regional and much lower surface roughness than surrounding energy budgets [Jeffries et al., 1999]. Several modeling land area. These properties are important for accurate studies [Bonan, 1995; Dutra et al., 2010; Krinner, 2003; Samuelsson et al., 2010] have found significant changes Energy and Resources Group, University of California, Berkeley, in regional temperature with prognostic 1-dimensional (1D) lake models integrated in climate models. California, USA Earth Sciences Division, Lawrence Berkeley National Laboratory, The impacts of lakes on regional climate vary with Berkeley, California, USA location and season. In general, unfrozen lakes tend to German Weather Service, Offenbach, Germany suppress diurnal temperature variation as compared to surrounding land [Samuelsson et al., 2010]. Some tem- perate and high-latitude lakes tend to be cooler than 1. Introduction

/pdf/an-improved-lake-model-for-climate-simulations-model-znyrehytf7.pdf

An improved lake model for climate simulations: Model structure, evaluation, and sensitivity analyses in CESM1

Department of the Interior Northeast Climate Adaptation Science Center; Midwest Glacial Lakes Fish Habitat Partnership grant through FWS; NSF Expedition in Computing Grant [1029711]; NSFNational Science Foundation (NSF) [EAR-PF-1725386]; Digital Technology Center at the University of MinnesotaUniversity of Minnesota System; Department of the Interior North Central Climate Adaptation Science Center; North Temperate Lakes Long-Term Ecological Research [NSF DEB-1440297]; Global Lake Ecological Observatory Network [NSF 1702991]

https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2019WR024922

Process-Guided Deep Learning Predictions of Lake Water Temperature

Warming-induced changes in lake thermal and mixing regimes present risks to water quality and ecosystem services provided by U.S. lakes and reservoirs. Modulation of responses by different physical and hydroclimatic settings are not well understood. We explore the potential effects of climate change on 27 lake “archetypes” representative of a range of lakes and reservoirs occurring throughout the U.S. Archetypes are based on different combinations of depth, surface area, and water clarity. LISSS, a one-dimensional dynamic thermal simulation model, is applied to assess lake response to multiple mid-21st century change scenarios applied to nine baseline climate series from different hydroclimatic regions of the U.S. Results show surface water temperature increases of about 77 % of increase in average air temperature change. Bottom temperature changes are less (around 30 %) for deep lakes and in regions that maintain mid-winter air temperatures below freezing. Significant decreases in length of ice cover are projected, and the extent and strength of stratification will increase throughout the U.S., with systematic differences associated with depth, surface area, and clarity. These projected responses suggest a range of future challenges that lake managers are likely to face. Changes in thermal and mixing dynamics suggest increased risk of summer hypoxic conditions and cyanobacterial blooms. Increased water temperatures above the summer thermocline could be a problem for cold water fisheries management in many lakes. Climate-induced changes in water balance and mass inputs of nutrients may further exacerbate the vulnerability of lakes to climate change.

/pdf/sensitivity-of-lake-thermal-and-mixing-dynamics-to-climate-462uurqp38.pdf

Sensitivity of lake thermal and mixing dynamics to climate change

In this study, we report on the ability of four one-dimensional lake models to simulate the water temperature profiles of Lake Geneva, the largest water body in Western Europe, over a 10-yr period from 1996 to 2005, using lake models driven by a common atmospheric forcing. These lake models have already demonstrated their capability of reproducing the temperature distribution in smaller lakes and include one eddy-diffusive lake model, the Hostetler model; a Lagrangian model, the one-dimensional Dynamic Reservoir Simulation Model "DYRESM" a к - e turbulence model, "SIMSTRAT"; and one based on the concept of self-similarity (assumed shape) of the temperature-depth curve, the Freshwater Lake model "FLake." Only DYRESM and SIMSTRAT reproduce the variability of the water temperature profiles and seasonal thermocline satisfactorily. In layers in which thermocline variability is greatest, the temperature root mean square error is ≪2°C and 3°C (at the time of highest stratification) for these models, respectively. It is possible to apply certain one-dimensional lake models that simulate the behavior of temperature to investigate the potential future warming of the water column in Lake Geneva. Importantly, the metalimnion boundary is successfully modeled, which represents an encouraging step toward demonstrating the feasibility of coupling biogeochemical modules, such as, for example, a phytoplanktonic model, to assess the possible biological responses within lakes to climate change.

/pdf/simulation-of-multiannual-thermal-profiles-in-deep-lake-2lbrojq9ya.pdf

Orlane Annevillec

Papers

Simulation of multiannual thermal profiles in deep Lake Geneva: a comparison of one-dimensional lake models.