scholarly journals Explicitly modelling microtopography in permafrost landscapes in a land-surface model (JULES vn5.4_microtopography)

2021 ◽  
Author(s):  
Noah D. Smith ◽  
Sarah E. Chadburn ◽  
Eleanor J. Burke ◽  
Kjetil Schanke Aas ◽  
Inge H. J. Althuizen ◽  
...  
Keyword(s):  
Land Surface ◽  
Land Surface Model ◽  
Hydrological Regime ◽  
Surface Model ◽  
Large Variability ◽  
Spatially Resolved ◽  
Degradation Rates ◽  
Methane Fluxes ◽  
Soil Temperatures ◽  
The Difference

Abstract. Microtopography can be a key driver of heterogeneity in the ground thermal and hydrological regime of permafrost landscapes. In turn, this heterogeneity can influence plant communities, methane fluxes and the initiation of abrupt thaw processes. Here we have implemented a two-tile representation of microtopography in JULES (the Joint UK Land Environment Simulator), where tiles are representative of repeating patterns of elevation difference. We evaluate the model against available spatially resolved observations at four sites, gauge the importance of explicitly representing microtopography for modelling methane emissions and quantify the relative importance of model processes and the model’s sensitivity its parameters. Tiles are coupled by lateral flows of water, heat and redistribution of snow. A surface water store is added to represent ponding. The model is parametrised using characteristic dimensions of landscape features at sites. Simulations are performed of two Siberian polygon sites, Samoylov and Kytalyk, and two Scandinavian palsa sites, Stordalen and Iškoras. The model represents the observed differences between greater snow depth in hollows vs raised areas well. The model also improves soil moisture for hollows vs the non-tiled configuration (‘standard JULES’) though the raised tile remains drier than observed. For the two palsa sites, it is found that drainage needs to be impeded from the lower tile, representing the non-permafrost mire, to achieve the observed soil saturation. This demonstrates the need for the landscape-scale drainage to be correctly modelled. Causes of moisture heterogeneity between tiles are decreased runoff from the low tile, differences in snowmelt, and high to low-tile water flow. Unsaturated flows between tiles are negligible, suggesting the adequacy of simpler water-table based models of lateral flow in wetland environments. The modelled differences in snow depths and soil moistures between tiles result in the lower tile soil temperatures being warmer for palsa sites. When comparing the soil temperatures for July at 20 cm depth, the difference in temperature between tiles, or ‘temperature splitting’, is smaller than observed (3.2 vs 5.5 °C). The mean temperature of the two tiles remains approximately unchanged (+0.4 °C) vs standard JULES, and lower than observations. Polygons display small (0.2 °C) to zero temperature splitting, in agreement with observations. Consequently, methane fluxes are near identical (+0 to 9 %) to those for standard JULES for polygons, though can be greater than standard JULES for palsa sites (+10 to 49 %). Through a sensitivity analysis we identify the parameters resulting in the greatest uncertainty in modelled temperature. We find that at the sites tested, varying the parameters can result in the modelled July temperature splitting being at most 0.9 or 3 °C larger than observed for palsa or polygon sites respectively. Varying the palsa elevation between 0.5 and 3 m has little effect on modelled soil temperatures, showing that having only two tiles can still be a valid representation of sites with a large variability of palsa elevations. Lateral conductive fluxes, while small, reduce the temperature splitting by ~1 °C, and correspond to the order of observed lateral degradation rates in peat plateau regions, indicating possible application in an area-based thaw model.

scholarly journals Simulation of semi-arid biomass plantations and irrigation using the WRF-NOAH model – a comparison with observations from Israel

2014 ◽  
Vol 18 (5) ◽  
pp. 1761-1783 ◽  
Author(s):  
O. Branch ◽  
K. Warrach-Sagi ◽  
V. Wulfmeyer ◽  
S. Cohen
Keyword(s):  
Land Surface ◽  
High Surface ◽  
Land Surface Model ◽  
Vapour Pressure Deficit ◽  
Soil Heat Flux ◽  
Heat Fluxes ◽  
Surface Radiation ◽  
Surface Model ◽  
Maximum Deviation ◽  
Soil Temperatures

Abstract. A 10 × 10 km irrigated biomass plantation was simulated in an arid region of Israel to simulate diurnal energy balances during the summer of 2012 (JJA). The goal is to examine daytime horizontal flux gradients between plantation and desert. Simulations were carried out within the coupled WRF-NOAH atmosphere/land surface model. MODIS land surface data was adjusted by prescribing tailored land surface and soil/plant parameters, and by adding a controllable sub-surface irrigation scheme to NOAH. Two model cases studies were compared – Impact and Control. Impact simulates the irrigated plantation. Control simulates the existing land surface, where the predominant land surface is bare desert soil. Central to the study is parameter validation against land surface observations from a desert site and from a 400 ha Simmondsia chinensis (jojoba) plantation. Control was validated with desert observations, and Impact with Jojoba observations. Model evapotranspiration was validated with two Penman–Monteith estimates based on the observations. Control simulates daytime desert conditions with a maximum deviation for surface 2 m air temperatures (T2) of 0.2 °C, vapour pressure deficit (VPD) of 0.25 hPa, wind speed (U) of 0.5 m s−1, surface radiation (Rn) of 25 W m−2, soil heat flux (G) of 30 W m−2 and 5 cm soil temperatures (ST5) of 1.5 °C. Impact simulates irrigated vegetation conditions with a maximum deviation for T2 of 1–1.5 °C, VPD of 0.5 hPa, U of 0.5 m s−1, Rn of 50 W m−5, G of 40 W m−2 and ST5 of 2 °C. Latent heat curves in Impact correspond closely with Penman–Monteith estimates, and magnitudes of 160 W m−2 over the plantation are usual. Sensible heat fluxes, are around 450 W m−2 and are at least 100–110 W m−2 higher than the surrounding desert. This surplus is driven by reduced albedo and high surface resistance, and demonstrates that high evaporation rates may not occur over Jojoba if irrigation is optimized. Furthermore, increased daytime T2 over plantations highlight the need for hourly as well as daily mean statistics. Daily mean statistics alone may imply an overall cooling effect due to surplus nocturnal cooling, when in fact a daytime warming effect is observed.

scholarly journals Introducing Hysteresis in Snow Depletion Curves to Improve the Water Budget of a Land Surface Model in an Alpine Catchment

2014 ◽  
Vol 15 (2) ◽  
pp. 631-649 ◽  
Author(s):  
Claire Magand ◽  
Agnès Ducharne ◽  
Nicolas Le Moine ◽  
Simon Gascoin
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Water Budget ◽  
Land Surface Model ◽  
Surface Model ◽  
Depletion Curve ◽  
Physically Based ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference ◽  
Snow Model

Abstract The Durance watershed (14 000 km2), located in the French Alps, generates 10% of French hydropower and provides drinking water to 3 million people. The Catchment land surface model (CLSM), a distributed land surface model (LSM) with a multilayer, physically based snow model, has been applied in the upstream part of this watershed, where snowfall accounts for 50% of the precipitation. The CLSM subdivides the upper Durance watershed, where elevations range from 800 to 4000 m within 3580 km2, into elementary catchments with an average area of 500 km2. The authors first show the difference between the dynamics of the accumulation and ablation of the snow cover using Moderate Resolution Imaging Spectroradiometer (MODIS) images and snow-depth measurements. The extent of snow cover increases faster during accumulation than during ablation because melting occurs at preferential locations. This difference corresponds to the presence of a hysteresis in the snow-cover depletion curve of these catchments, and the CLSM was adapted by implementing such a hysteresis in the snow-cover depletion curve of the model. Different simulations were performed to assess the influence of the parameterizations on the water budget and the evolution of the extent of the snow cover. Using six gauging stations, the authors demonstrate that introducing a hysteresis in the snow-cover depletion curve improves melting dynamics. They conclude that their adaptation of the CLSM contributes to a better representation of snowpack dynamics in an LSM that enables mountainous catchments to be modeled for impact studies such as those of climate change.

Conditions for the Compost Bomb Instability

2020 ◽  
Author(s):  
Joe Clarke ◽  
Paul Ritchie ◽  
Peter Cox
Keyword(s):  
Global Warming ◽  
Positive Feedback ◽  
Land Surface ◽  
Microbial Respiration ◽  
Land Surface Model ◽  
Surface Model ◽  
Specific Rate ◽  
Feedback Process ◽  
Moss Layer ◽  
Soil Temperatures

<p>Under global warming, soil temperatures are expected to rise. This increases the specific rate of microbial respiration in the soils which in turn warms the soil, creating a positive feedback process. This leads to the possibility of an instability, known as the compost bomb, in which rapidly warming soils release their soil carbon as CO2 to the atmosphere, accelerating global warming. Models of the compost bomb have exhibited interesting dynamical phenomena: excitability, rate induced tipping and bifurcation induced tipping. We examine models with increasing degrees of sophistication, to help understand the conditions that give rise to the compost bomb. We clarify the role an insulating moss layer plays and demonstrate that it has a 'most dangerous' thickness. We also use JULES, a land surface model, to examine where a compost bomb might occur and what affect other processes such as hydrology might have on the compost bomb.</p>

Impacts of Soil Heating Condition on Precipitation Simulations in the Weather Research and Forecasting Model

2009 ◽  
Vol 137 (7) ◽  
pp. 2263-2285 ◽  
Author(s):  
Xingang Fan
Keyword(s):  
Soil Temperature ◽  
Air Temperature ◽  
Land Surface ◽  
Lower Boundary ◽  
Land Surface Model ◽  
Surface Model ◽  
Heating Condition ◽  
Near Surface ◽  
Thermal Fields ◽  
Soil Temperatures

Soil temperature is a major variable in land surface models, representing soil energy status, storage, and transfer. It serves as an important factor indicating the underlying surface heating condition for weather and climate forecasts. This study utilizes the Weather Research and Forecasting (WRF) model to study the impacts of changes to the surface heating condition, derived from soil temperature observations, on regional weather simulations. Large cold biases are found in the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis project (ERA-40) soil temperatures as compared to observations. At the same time, a warm bias is found in the lower boundary assumption adopted by the Noah land surface model. In six heavy rain cases studied herein, observed soil temperatures are used to initialize the land surface model and to provide a lower boundary condition at the bottom of the model soil layer. By analyzing the impacts from the incorporation of observed soil temperatures, the following major conclusions are drawn: 1) A consistent increase in the ground heat flux is found during the day, when the observed soil temperatures are used to correct the cold bias present in ERA-40. Soil temperature changes introduced at the initial time maintain positive values but gradually decrease in magnitude with time. Sensible and latent heat fluxes and the moisture flux experience an increase during the first 6 h. 2) An increase in soil temperature impacts the air temperature through surface exchange, and near-surface moisture through evaporation. During the first two days, an increase in air temperature is seen across the region from the surface up to about 800 hPa (∼1450 m). The maximum near-surface air temperature increase is found to be, averaged over all cases, 0.5 K on the first day and 0.3 K on the second day. 3) The strength of the low-level jet is affected by the changes described above and also by the consequent changes in horizontal gradients of pressure and thermal fields. Thus, the three-dimensional circulation is affected, in addition to changes seen in the humidity and thermal fields and the locations and intensities of precipitating systems. 4) Overall results indicate that the incorporation of observed soil temperatures introduces a persistent soil heating condition that is favorable to convective development and, consequently, improves the simulation of precipitation.

scholarly journals Simulating the thermal regime and thaw processes of ice-rich permafrost ground with the land-surface model CryoGrid 3

2016 ◽  
Vol 9 (2) ◽  
pp. 523-546 ◽  
Author(s):  
S. Westermann ◽  
M. Langer ◽  
J. Boike ◽  
M. Heikenfeld ◽  
M. Peter ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Thermal Regime ◽  
Land Surface ◽  
Climate Model ◽  
Late Quaternary ◽  
Land Surface Model ◽  
Hydrological Regime ◽  
Surface Model ◽  
Conductive Heat ◽  
Permafrost Thaw

Abstract. Thawing of permafrost in a warming climate is governed by a complex interplay of different processes of which only conductive heat transfer is taken into account in most model studies. However, observations in many permafrost landscapes demonstrate that lateral and vertical movement of water can have a pronounced influence on the thaw trajectories, creating distinct landforms, such as thermokarst ponds and lakes, even in areas where permafrost is otherwise thermally stable. Novel process parameterizations are required to include such phenomena in future projections of permafrost thaw and subsequent climatic-triggered feedbacks. In this study, we present a new land-surface scheme designed for permafrost applications, CryoGrid 3, which constitutes a flexible platform to explore new parameterizations for a range of permafrost processes. We document the model physics and employed parameterizations for the basis module CryoGrid 3, and compare model results with in situ observations of surface energy balance, surface temperatures, and ground thermal regime from the Samoylov permafrost observatory in NE Siberia. The comparison suggests that CryoGrid 3 can not only model the evolution of the ground thermal regime in the last decade, but also consistently reproduce the chain of energy transfer processes from the atmosphere to the ground. In addition, we demonstrate a simple 1-D parameterization for thaw processes in permafrost areas rich in ground ice, which can phenomenologically reproduce both formation of thermokarst ponds and subsidence of the ground following thawing of ice-rich subsurface layers. Long-term simulation from 1901 to 2100 driven by reanalysis data and climate model output demonstrate that the hydrological regime can both accelerate and delay permafrost thawing. If meltwater from thawed ice-rich layers can drain, the ground subsides, as well as the formation of a talik, are delayed. If the meltwater pools at the surface, a pond is formed that enhances heat transfer in the ground and leads to the formation of a talik. The model results suggest that the trajectories of future permafrost thaw are strongly influenced by the cryostratigraphy, as determined by the late Quaternary history of a site.

scholarly journals Simulating carbon exchange using a regional atmospheric model coupled to an advanced land-surface model

2010 ◽  
Vol 7 (8) ◽  
pp. 2397-2417 ◽  
Author(s):  
H. W. Ter Maat ◽  
R. W. A. Hutjes ◽  
F. Miglietta ◽  
B. Gioli ◽  
F. C. Bosveld ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Land Surface ◽  
Land Surface Model ◽  
Atmospheric Model ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Shortwave Radiation ◽  
Surface Model ◽  
Large Variability ◽  
Regional Atmospheric Modelling System

Abstract. This paper is a case study to investigate what the main controlling factors are that determine atmospheric carbon dioxide content for a region in the centre of The Netherlands. We use the Regional Atmospheric Modelling System (RAMS), coupled with a land surface scheme simulating carbon, heat and momentum fluxes (SWAPS-C), and including also submodels for urban and marine fluxes, which in principle should include the dominant mechanisms and should be able to capture the relevant dynamics of the system. To validate the model, observations are used that were taken during an intensive observational campaign in central Netherlands in summer 2002. These include flux-tower observations and aircraft observations of vertical profiles and spatial fluxes of various variables. The simulations performed with the coupled regional model (RAMS-SWAPS-C) are in good qualitative agreement with the observations. The station validation of the model demonstrates that the incoming shortwave radiation and surface fluxes of water and CO2 are well simulated. The comparison against aircraft data shows that the regional meteorology (i.e. wind, temperature) is captured well by the model. Comparing spatially explicitly simulated fluxes with aircraft observed fluxes we conclude that in general latent heat fluxes are underestimated by the model compared to the observations but that the latter exhibit large variability within all flights. Sensitivity experiments demonstrate the relevance of the urban emissions of carbon dioxide for the carbon balance in this particular region. The same tests also show the relation between uncertainties in surface fluxes and those in atmospheric concentrations.

scholarly journals Interpretation of ASCAT Radar Scatterometer Observations Over Land: A Case Study Over Southwestern France

2019 ◽  
Vol 11 (23) ◽  
pp. 2842 ◽  
Author(s):  
Daniel Shamambo ◽  
Bertrand Bonan ◽  
Jean-Christophe Calvet ◽  
Clément Albergel ◽  
Sebastian Hahn
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Extreme Event ◽  
Cloud Model ◽  
Large Fraction ◽  
Land Surface Model ◽  
Surface Model ◽  
Area Index ◽  
The Difference ◽  
The Impact

This paper investigates to what extent soil moisture and vegetation density information can be extracted from the Advanced Scatterometer (ASCAT) satellite-derived radar backscatter (σ°) in a data assimilation context. The impact of independent estimates of the surface soil moisture (SSM) and leaf area index (LAI) of diverse vegetation types on ASCAT σ° observations is simulated over southwestern France using the water cloud model (WCM). The LAI and SSM variables used by the WCM are derived from satellite observations and from the Interactions between Soil, Biosphere, and Atmosphere (ISBA) land surface model, respectively. They permit the calibration of the four parameters of the WCM describing static soil and vegetation characteristics. A seasonal analysis of the model scores shows that the WCM has shortcomings over karstic areas and wheat croplands. In the studied area, the Klaus windstorm in January 2009 damaged a large fraction of the Landes forest. The ability of the WCM to represent the impact of Klaus and to simulate ASCAT σ° observations in contrasting land-cover conditions is explored. The difference in σ° observations between the forest zone affected by the storm and the bordering agricultural areas presents a marked seasonality before the storm. The difference is small in the springtime (from March to May) and large in the autumn (September to November) and wintertime (December to February). After the storm, hardly any seasonality was observed over four years. This study shows that the WCM is able to simulate this extreme event. It is concluded that the WCM could be used as an observation operator for the assimilation of ASCAT σ° observations into the ISBA land surface model.

Diagnosing Present and Future Permafrost from Climate Models

2013 ◽  
Vol 26 (15) ◽  
pp. 5608-5623 ◽  
Author(s):  
Andrew G. Slater ◽  
David M. Lawrence
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Land Surface Model ◽  
Coupled Model ◽  
Temporal Distribution ◽  
Surface Model ◽  
Permafrost Region ◽  
Near Surface ◽  
Surface Climate ◽  
Soil Temperatures

Abstract Permafrost is a characteristic aspect of the terrestrial Arctic and the fate of near-surface permafrost over the next century is likely to exert strong controls on Arctic hydrology and biogeochemistry. Using output from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), the authors assess its ability to simulate present-day and future permafrost. Permafrost extent diagnosed directly from each climate model's soil temperature is a function of the modeled surface climate as well as the ability of the land surface model to represent permafrost physics. For each CMIP5 model these two effects are separated by using indirect estimators of permafrost driven by climatic indices and compared to permafrost extent directly diagnosed via soil temperatures. Several robust conclusions can be drawn from this analysis. Significant air temperature and snow depth biases exist in some model's climates, which degrade both directly and indirectly diagnosed permafrost conditions. The range of directly calculated present-day (1986–2005) permafrost area is extremely large (~4–25 × 106 km2). Several land models contain structural weaknesses that limit their skill in simulating cold region subsurface processes. The sensitivity of future permafrost extent to temperature change over the present-day observed permafrost region averages (1.67 ± 0.7) × 106 km2 °C−1 but is a function of the spatial and temporal distribution of climate change. Because of sizable differences in future climates for the representative concentration pathway (RCP) emission scenarios, a wide variety of future permafrost states is predicted by 2100. Conservatively, the models suggest that for RCP4.5, permafrost will retreat from the present-day discontinuous zone. Under RCP8.5, sustainable permafrost will be most probable only in the Canadian Archipelago, Russian Arctic coast, and east Siberian uplands.

scholarly journals Land surface model parameter optimisation using in-situ flux data: comparison of gradient-based versus random search algorithms

2018 ◽  
Author(s):  
Vladislav Bastrikov ◽  
Natasha MacBean ◽  
Cédric Bacour ◽  
Diego Santaren ◽  
Sylvain Kuppel ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Cost Function ◽  
Land Surface ◽  
Random Search ◽  
Land Surface Model ◽  
Surface Model ◽  
Model Data ◽  
Gradient Based ◽  
The Difference ◽  
The Cost

Abstract. Land surface models (LSMs), used within earth system models, rely on numerous processes for describing carbon, water and energy budgets, often associated with highly uncertain parameters. Data assimilation (DA) is a useful approach for optimising the most critical parameters in order to improve model accuracy and refine future climate predictions. In this study, we compare two different DA methods for optimising the parameters of seven plant functional types (PFTs) of the ORCHIDEE land surface model using daily averaged eddy-covariance observations of net ecosystem exchange and latent heat flux at 78 sites across the globe. We perform a technical investigation of two classes of minimisation methods – local gradient-based (the L-BFGS-B algorithm) and global random search (the genetic algorithm) – by evaluating their relative performance in terms of the model–data fit and the difference in retrieved parameter values. We examine the performance of each method for two cases: when optimising parameters at each site independently (single-site approach) and when simultaneously optimising the model at all sites for a given PFT using a common set of parameters (multi-site approach). We find that for the single site case the random search algorithm results in lower values of the cost function (i.e. lower model – data root mean square differences) than the gradient-based method; the difference between the two methods is smaller for the multi-site optimisation due to a smoothing of the cost function shape with a greater number of observations. The spread of the cost function, when performing the same tests with 16 random first guess parameters, is much larger with the gradient based method, due to the higher likelihood of being trap in local minima. When using pseudo-observations tests the genetic algorithm results in a closer approximation of the true posterior parameter value in the L-BFGS-B algorithm. We demonstrate the advantages and challenges of different DA techniques and provide some advice on using it for the LSM parameters optimisation.

scholarly journals Simulating the thermal regime and thaw processes of ice-rich permafrost ground with the land-surface model CryoGrid 3

2015 ◽  
Vol 8 (8) ◽  
pp. 6931-6986 ◽  
Author(s):  
S. Westermann ◽  
M. Langer ◽  
J. Boike ◽  
M. Heikenfeld ◽  
M. Peter ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Thermal Regime ◽  
Land Surface ◽  
Climate Model ◽  
Late Quaternary ◽  
Land Surface Model ◽  
Hydrological Regime ◽  
Surface Model ◽  
Conductive Heat ◽  
Permafrost Thaw

Abstract. Thawing of permafrost in a warming climate is governed by a complex interplay of different processes, of which only conductive heat transfer is taken into account in most model studies. However, observations in many permafrost landscapes demonstrate that lateral and vertical movement of water can have a pronounced influence on the thaw trajectories, creating distinct landforms like thermokarst ponds and lakes even in areas where permafrost is otherwise thermally stable. Novel process parameterizations are required to include such phenomena in future projections of permafrost thaw and hereby triggered climatic feedbacks. In this study, we present a new land-surface scheme designed for permafrost applications, CryoGrid 3, which constitutes a flexible platform to explore new parameterizations for a range of permafrost processes. We document the model physics and employed parameterizations for the basis module CryoGrid 3, and compare model results with in-situ observations of surface energy balance, surface temperatures, and ground thermal regime from the Samoylov permafrost observatory in NE Siberia. The comparison suggests that CryoGrid 3 can not only model the evolution of the ground thermal regime in the last decade, but also consistently reproduce the chain of energy transfer processes from the atmosphere to the ground. In addition, we demonstrate a simple 1-D parameterization for thaw process in permafrost areas rich in ground ice, which can phenomenologically reproduce both formation of thermokarst ponds and subsidence of the ground following thawing of ice-rich subsurface layers. Long-term simulation from 1901–2100 driven by reanalysis data and climate model output demonstrate that the hydrological regime can both accelerate and delay permafrost thawing. If meltwater from thawed ice-rich layers can drain, the ground subsides while at the same time the formation of a talik is delayed. If the meltwater pools at the surface, a pond is formed which enhances heat transfer in the ground and leads to the formation of a talik. The model results suggest that the trajectories of future permafrost thaw are strongly influenced by the cryostratigraphy, as determined by the late quaternary history of a site.

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