skip to main content

Title: Improving lake mixing process simulations in the Community Land Model by using <i>K</i> profile parameterization
Abstract. We improved lake mixing process simulations by applying a vertical mixing scheme, K profile parameterization (KPP), in the Community Land Model (CLM) version 4.5, developed by the National Center for Atmospheric Research. Vertical mixing of the lake water column can significantly affect heat transfer and vertical temperature profiles. However, the current vertical mixing scheme in CLM requires an arbitrarily enlarged eddy diffusivity to enhance water mixing. The coupled CLM-KPP considers a boundary layer for eddy development, and in the lake interior water mixing is associated with internal wave activity and shear instability. We chose a lake in Arctic Alaska and a lake on the Tibetan Plateau to evaluate this improved lake model. Results demonstrated that CLM-KPP reproduced the observed lake mixing and significantly improved lake temperature simulations when compared to the original CLM. Our newly improved model better represents the transition between stratification and turnover. This improved lake model has great potential for reliable physical lake process predictions and better ecosystem services.
; ; ; ; ;
Award ID(s):
Publication Date:
Journal Name:
Hydrology and Earth System Sciences
Page Range or eLocation-ID:
4969 to 4982
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract. Concerns about food security under climate change motivate efforts to better understand future changes in crop yields.Process-based crop models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing future climate and management conditions not sampled in the historical record and new locations to which cultivation may shift.However, process-based crop models differ in many critical details, and their responses to different interacting factors remain only poorly understood.The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, an activity of the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to provide a systematic parameter sweep focused on climate change factors and their interaction with overall soil fertility, to allow both evaluating model behavior and emulating model responses in impact assessment tools.In this paper we describe the GGCMI Phase 2 experimental protocol and its simulation data archive.A total of 12 crop models simulate five crops with systematic uniform perturbations of historical climate, varying CO2, temperature, water supply, and applied nitrogen (“CTWN”) for rainfed and irrigated agriculture, and a second set of simulations represents a type of adaptation by allowing the adjustment of growing season length.We present some crop yield results to illustrate generalmore »characteristics of the simulations and potential uses of the GGCMI Phase 2 archive.For example, in cases without adaptation, modeled yields show robust decreases to warmer temperatures in almost all regions, with a nonlinear dependence that means yields in warmer baseline locations have greater temperature sensitivity.Inter-model uncertainty is qualitatively similar across all the four input dimensions but is largest in high-latitude regions where crops may be grown in the future.« less
  2. Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 =  0.76; Nash–Sutcliffe modeling efficiency, MEF  =  0.76) and ecosystem respiration (ER, r2 =  0.78, MEF  =  0.75), with lesser accuracy for latent heat fluxes (LE, r2 =  0.42, MEF  =  0.14) and and net ecosystem CO2 exchange (NEE, r2 =  0.38, MEF  =  0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57–0.86). For spatial across-site gradients of annual meanmore »GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2 &lt; 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value.« less
  3. Abstract. Reconstructions of global hydroclimate during the Common Era (CE; the past ∼2000 years) are important for providing context for current and future global environmental change. Stable isotope ratios in water are quantitative indicators of hydroclimate on regional to global scales, and these signals are encoded in a wide range of natural geologic archives. Here we present the Iso2k database, a global compilation of previously published datasets from a variety of natural archives that record the stable oxygen (δ18O) or hydrogen (δ2H) isotopic compositions of environmental waters, which reflect hydroclimate changes over the CE. The Iso2k database contains 759 isotope records from the terrestrial and marine realms, including glacier and ground ice (210); speleothems (68); corals, sclerosponges, and mollusks (143); wood (81); lake sediments and other terrestrial sediments (e.g., loess) (158); and marine sediments (99). Individual datasets have temporal resolutions ranging from sub-annual to centennial and include chronological data where available. A fundamental feature of the database is its comprehensive metadata, which will assist both experts and nonexperts in the interpretation of each record and in data synthesis. Key metadata fields have standardized vocabularies to facilitate comparisons across diversearchives and with climate-model-simulated fields. This is the firstglobal-scale collection of water isotope proxy records from multiple typesof geological and biological archives. Itmore »is suitable for evaluatinghydroclimate processes through time and space using large-scale synthesis,model–data intercomparison and (paleo)data assimilation. The Iso2k databaseis available for download at (Konecky and McKay, 2020) and is also accessible via the NOAA/WDS Paleo Datalanding page: (last access: 30 July 2020).« less
  4. Abstract. Dry deposition is a key process for surface ozone(O3) removal. Stomatal uptake is a major component of O3 drydeposition, which is parameterized differently in current land surfacemodels and chemical transport models. We developed and used a standaloneterrestrial biosphere model, driven by a unified set of prescribedmeteorology, to evaluate two widely used dry deposition modeling frameworks,Wesely (1989) and Zhang et al. (2003), with different configurations ofstomatal resistance: (1) the default multiplicative method in the Weselyscheme (W89) and Zhang et al. (2003) scheme (Z03), (2) the traditionalphotosynthesis-based Farquhar–Ball–Berry (FBB) stomatal algorithm, and (3) theMedlyn stomatal algorithm (MED) based on optimization theory. We found thatusing the FBB stomatal approach that captures ecophysiological responses toenvironmental factors, especially to water stress, can generally improve thesimulated dry deposition velocities compared with multiplicative schemes.The MED stomatal approach produces higher stomatal conductance than FBB andis likely to overestimate dry deposition velocities for major vegetationtypes, but its performance is greatly improved when spatially varying slopeparameters based on annual mean precipitation are used. Large discrepancieswere also found in stomatal responses to rising CO2 levels from 390to 550 ppm: the multiplicative stomatal method with an empirical CO2response function produces reduction (−35 %) in global stomatalconductance on average much larger than that with the photosynthesis-basedstomatal method (−14 %–19 %). Ourmore »results show the potential biases inO3 sink caused by errors in model structure especially in the Weselydry deposition scheme and the importance of using photosynthesis-basedrepresentation of stomatal resistance in dry deposition schemes under achanging climate and rising CO2 concentration.« less
  5. Abstract. Current peatland models generally treat vegetation as static, although plant community structure is known to alter as a response to environmental change. Because the vegetation structure and ecosystem functioning are tightly linked, realistic projections of peatland response to climate change require the inclusion of vegetation dynamics in ecosystem models. In peatlands, Sphagnum mosses are key engineers. Moss community composition primarily follows habitat moisture conditions. The known species habitat preference along the prevailing moisture gradient might not directly serve as a reliable predictor for future species compositions, as water table fluctuation is likely to increase. Hence, modelling the mechanisms that control the habitat preference of Sphagna is a good first step for modelling community dynamics in peatlands. In this study, we developed the Peatland Moss Simulator (PMS), which simulates the community dynamics of the peatland moss layer. PMS is a process-based model that employs a stochastic, individual-based approach for simulating competition within the peatland moss layer based on species differences in functional traits. At the shoot-level, growth and competition were driven by net photosynthesis, which was regulated by hydrological processes via the capitulum water content. The model was tested by predicting the habitat preferences of Sphagnum magellanicum and Sphagnum fallax – twomore »key species representing dry (hummock) and wet (lawn) habitats in a poor fen peatland (Lakkasuo, Finland). PMS successfully captured the habitat preferences of the two Sphagnum species based on observed variations in trait properties. Our model simulation further showed that the validity of PMS depended on the interspecific differences in the capitulum water content being correctly specified. Neglecting the water content differences led to the failure of PMS to predict the habitat preferences of the species in stochastic simulations. Our work highlights the importance of the capitulum water content with respect to the dynamics and carbon functioning of Sphagnum communities in peatland ecosystems. Thus, studies of peatland responses to changing environmental conditions need to include capitulum water processes as a control on moss community dynamics. Our PMS model could be used as an elemental design for the future development of dynamic vegetation models for peatland ecosystems.« less