Developing a Snow Algae Model to Reconstruct Blooming at the Global Scale Using a Land Surface Model

<p>Lakes play a major role on local climate and boundary layer stratification. At global scale, they have been shown to have an impact on the energy budget, (see for example Le Moigne et al., 2016 or Bonan, 1995 ) . To represent the energy budget of lakes at a global scale, the FLake (Mironov et al, 2008) lake model has been coupled to the ORCHIDEE land surface model - the continental part of the IPSL earth system model. By including Flake in ORCHIDEE, we aim to improve the representation of land surface temperature and heat fluxes. Using the standard CMIP6 configuration of ORCHIDEE,&#160; two 40-year simulations were generated (one coupled with FLake and one without) using the CRUJRA meteorological forcing data at a spatial resolution of 0.5&#176;. We compare land surface temperatures and heat fluxes from the two ORCHIDEE simulations and assess the impacts of lakes on surface energy budgets. MODIS satellite land surface temperature products will be used to validate the simulations. We expect a better fit between the simulated land surface temperature and the MODIS data when the FLake configuration is used. The preliminary results of the comparison will be presented.</p>

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Carbonyl sulfide: comparing a mechanistic representation of the vegetation uptake in a land surface model and the leaf relative uptake approach

Biogeosciences ◽

10.5194/bg-18-2917-2021 ◽

2021 ◽

Vol 18 (9) ◽

pp. 2917-2955

Author(s):

Fabienne Maignan ◽

Camille Abadie ◽

Marine Remaud ◽

Linda M. J. Kooijmans ◽

Kukka-Maaria Kohonen ◽

...

Keyword(s):

Land Surface ◽

Carbonyl Sulfide ◽

Land Surface Model ◽

Global Scale ◽

C3 Plants ◽

Surface Model ◽

High Temporal Resolution ◽

Co2 Uptake ◽

Mechanistic Approach ◽

Relative Uptake

Abstract. Land surface modellers need measurable proxies to constrain the quantity of carbon dioxide (CO2) assimilated by continental plants through photosynthesis, known as gross primary production (GPP). Carbonyl sulfide (COS), which is taken up by leaves through their stomates and then hydrolysed by photosynthetic enzymes, is a candidate GPP proxy. A former study with the ORCHIDEE land surface model used a fixed ratio of COS uptake to CO2 uptake normalised to respective ambient concentrations for each vegetation type (leaf relative uptake, LRU) to compute vegetation COS fluxes from GPP. The LRU approach is known to have limited accuracy since the LRU ratio changes with variables such as photosynthetically active radiation (PAR): while CO2 uptake slows under low light, COS uptake is not light limited. However, the LRU approach has been popular for COS–GPP proxy studies because of its ease of application and apparent low contribution to uncertainty for regional-scale applications. In this study we refined the COS–GPP relationship and implemented in ORCHIDEE a mechanistic model that describes COS uptake by continental vegetation. We compared the simulated COS fluxes against measured hourly COS fluxes at two sites and studied the model behaviour and links with environmental drivers. We performed simulations at a global scale, and we estimated the global COS uptake by vegetation to be −756 Gg S yr−1, in the middle range of former studies (−490 to −1335 Gg S yr−1). Based on monthly mean fluxes simulated by the mechanistic approach in ORCHIDEE, we derived new LRU values for the different vegetation types, ranging between 0.92 and 1.72, close to recently published averages for observed values of 1.21 for C4 and 1.68 for C3 plants. We transported the COS using the monthly vegetation COS fluxes derived from both the mechanistic and the LRU approaches, and we evaluated the simulated COS concentrations at NOAA sites. Although the mechanistic approach was more appropriate when comparing to high-temporal-resolution COS flux measurements, both approaches gave similar results when transporting with monthly COS fluxes and evaluating COS concentrations at stations. In our study, uncertainties between these two approaches are of secondary importance compared to the uncertainties in the COS global budget, which are currently a limiting factor to the potential of COS concentrations to constrain GPP simulated by land surface models on the global scale.

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A high resolution global scale groundwater model

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-11-5217-2014 ◽

2014 ◽

Vol 11 (5) ◽

pp. 5217-5250 ◽

Cited By ~ 9

Author(s):

I. E. M. de Graaf ◽

E. H. Sutanudjaja ◽

L. P. H. van Beek ◽

M. F. P. Bierkens

Keyword(s):

Groundwater Flow ◽

Land Surface ◽

Regional Scale ◽

Land Surface Model ◽

Global Scale ◽

Water Levels ◽

Natural State ◽

Surface Model ◽

Groundwater Model ◽

Aquifer Systems

Abstract. Groundwater is the world's largest accessible source of fresh water. It plays a vital role in satisfying needs for drinking water, agriculture and industrial activities. During times of drought groundwater sustains baseflow to rivers and wetlands, thereby supporting ecosystems. Most global scale hydrological models (GHMs) do not include a groundwater flow component, mainly due to lack of geohydrological data at the global scale. For the simulation of lateral flow and groundwater head dynamics a realistic physical representation of the groundwater system is needed, especially for GHMs that run at finer resolution. In this study we present a global scale groundwater model (run at 6' as dynamic steady state) using MODFLOW to construct an equilibrium water table at its natural state as the result of long-term climatic forcing. The aquifer schematization and properties were based on available global datasets of lithology and transmissivities combined with estimated aquifer thickness of an upper unconfined aquifer. The model is forced with outputs from the land-surface model PCR-GLOBWB, specifically with net recharge and surface water levels. A sensitivity analysis, in which the model was run with various parameter settings, showed variation in saturated conductivity causes most of the groundwater level variations. Simulated groundwater heads were validated against reported piezometer observations. The validation showed that groundwater depths are reasonably well simulated for many regions of the world, especially for sediment basins (R2 = 0.95). The simulated regional scale groundwater patterns and flowpaths confirm the relevance of taking lateral groundwater flow into account in GHMs. Flowpaths show inter-basin groundwater flow that can be a significant part of a basins water budget and helps to sustain river baseflow, explicitly during times of droughts. Also important aquifer systems are recharged by inter-basin groundwater flows that positively affect water availability.

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La représentation des surfaces continentales dans la modélisation du climat à Météo-France

La Météorologie ◽

10.37053/lameteorologie-2020-0018 ◽

2020 ◽

pp. 067

Author(s):

Bertrand Decharme ◽

Christine Delire ◽

Aaron Boone

Keyword(s):

Land Surface ◽

Climate Models ◽

Land Surface Model ◽

Global Scale ◽

Surface Model ◽

Climate Modelling ◽

History Of ◽

International Climate ◽

Land Surfaces ◽

Computational Resources

Les surfaces continentales jouent un rôle non négligeable dans le système climatique de la Terre. Elles occupent d'ailleurs une place majeure dans les cycles globaux de l'eau et du carbone. Elles ont été prises en compte dès les premiers modèles numériques de climat et, avec l'évolution des connaissances, des capacités de calcul et de la demande sociétale, leur représentation s'est aujourd'hui considérablement complexifiée. Nous présentons ici une brève histoire de l'évolution du modèle de surfaces Isba (Interactions sol-biosphère-atmosphère) de Météo-France dans son utilisation à l'échelle du globe en la replaçant dans le contexte international de la modélisation climatique. Land surfaces play a significant role in the Earth climate system, and they are a major component of the global carbon and water cycles. The first numerical climate models took them into account in very simple ways. Through time the complexity of their representation has increased a lot owing to improved knowledge, larger computational resources and changing societal demands. We present here a brief history of the ISBA (Interactions Soil-Biosphere-Atmosphere) land surface model developed at Météo-France when used at the global scale and how it evolved in the context of international climate modelling.

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Investigating vegetation role on UHI with mechanistic modelling worldwide

10.5194/egusphere-egu21-4198 ◽

2021 ◽

Author(s):

Ziyan Zhang ◽

Athanasios Paschalis ◽

Ana Mijic ◽

Naika Meili ◽

Simone Fatichi

Keyword(s):

Land Surface ◽

Urban Areas ◽

Energy Demand ◽

Land Surface Model ◽

Remote Sensing Data ◽

Global Scale ◽

Surface Model ◽

Urban Fabric ◽

Urban Energy ◽

Set Up

<p>The urban heat island effect (UHI), defined as the temperature difference between urban areas and their surroundings, has been widely observed in many cities worldwide, impacting urban energy demand, citizen&#8217;s comfort and health. UHI intensities have been found to depend on background climate, and the urban fabric, including built (building thermal properties, heights, reflectance) and natural characteristics (vegetation cover, species composition, vegetation management). In this study, we focus on developing a global scale mechanistic understanding of how each of those properties alters the urban energy budget and leads to UHI development. To achieve this goal, we use the state-of-art urban ecohydrological and land-surface model (urban Tethys-Chloris) to perform a set of detailed UHI simulations for multiple large urban clusters across America, Europe and China in a 10-year time period (2009-2019), spanning a gradient of aridity, vegetation amount, and different compositions of the urban fabric. Model simulations were set up using the latest generation remote sensing data and climate reanalysis (ERA5). Using the simulations, we develop a paradigm of how UHIs develop worldwide, and propose viable solutions for sustainable UHI mitigation.</p>

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Multimodel Analysis of Energy and Water Fluxes: Intercomparisons between Operational Analyses, a Land Surface Model, and Remote Sensing

Journal of Hydrometeorology ◽

10.1175/2011jhm1372.1 ◽

2012 ◽

Vol 13 (1) ◽

pp. 3-26 ◽

Cited By ~ 23

Author(s):

Raghuveer K. Vinukollu ◽

Justin Sheffield ◽

Eric F Wood ◽

Michael G. Bosilovich ◽

David Mocko

Keyword(s):

Remote Sensing ◽

Land Surface ◽

Land Surface Model ◽

Global Scale ◽

Heat Fluxes ◽

Surface Model ◽

Water Fluxes ◽

Net Radiation ◽

Energy Fluxes ◽

Ensemble Mean

Abstract Using data from seven global model operational analyses (OA), one land surface model, and various remote sensing retrievals, the energy and water fluxes over global land areas are intercompared for 2003/04. Remote sensing estimates of evapotranspiration (ET) are obtained from three process-based models that use input forcings from multisensor satellites. An ensemble mean (linear average) of the seven operational (mean-OA) models is used primarily to intercompare the fluxes with comparisons performed at both global and basin scales. At the global scale, it is found that all components of the energy budget represented by the ensemble mean of the OA models have a significant bias. Net radiation estimates had a positive bias (global mean) of 234 MJ m−2 yr−1 (7.4 W m−2) as compared to the remote sensing estimates, with the latent and sensible heat fluxes biased by 470 MJ m−2 yr−1 (13.3 W m−2) and −367 MJ m−2 yr−1 (11.7 W m−2), respectively. The bias in the latent heat flux is affected by the bias in the net radiation, which is primarily due to the biases in the incoming shortwave and outgoing longwave radiation and to the nudging process of the operational models. The OA models also suffer from improper partitioning of the surface heat fluxes. Comparison of precipitation (P) analyses from the various OA models, gauge analysis, and remote sensing retrievals showed better agreement than the energy fluxes. Basin-scale comparisons were consistent with the global-scale results, with the results for the Amazon in particular showing disparities between OA and remote sensing estimates of energy fluxes. The biases in the fluxes are attributable to a combination of errors in the forcing from the OA atmospheric models and the flux calculation methods in their land surface schemes. The atmospheric forcing errors are mainly attributable to high shortwave radiation likely due to the underestimation of clouds, but also precipitation errors, especially in water-limited regions.

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On the Nature of Soil Moisture in Land Surface Models

Journal of Climate ◽

10.1175/2009jcli2832.1 ◽

2009 ◽

Vol 22 (16) ◽

pp. 4322-4335 ◽

Cited By ~ 308

Author(s):

Randal D. Koster ◽

Zhichang Guo ◽

Rongqian Yang ◽

Paul A. Dirmeyer ◽

Kenneth Mitchell ◽

...

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Land Surface Model ◽

Global Scale ◽

Surface Model ◽

Land Surface Models ◽

Common Information ◽

Surface Models ◽

Moisture State ◽

Environmental Prediction

Abstract The soil moisture state simulated by a land surface model is a highly model-dependent quantity, meaning that the direct transfer of one model’s soil moisture into another can lead to a fundamental, and potentially detrimental, inconsistency. This is first illustrated with two recent examples, one from the National Centers for Environmental Prediction (NCEP) involving seasonal precipitation forecasting and another from the realm of ecological modeling. The issue is then further addressed through a quantitative analysis of soil moisture contents produced as part of a global offline simulation experiment in which a number of land surface models were driven with the same atmospheric forcing fields. These latter comparisons clearly demonstrate, on a global scale, the degree to which model-simulated soil moisture variables differ from each other and that these differences extend beyond those associated with model-specific layer thicknesses or soil texture. The offline comparisons also show, however, that once the climatological statistics of each model’s soil moisture variable are accounted for (here, through a simple scaling using the first two moments), the different land models tend to produce very similar information on temporal soil moisture variability in most parts of the world. This common information can perhaps be used as the basis for successful mappings between the soil moisture variables in different land models.

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Hydrological recurrence as a measure for large river basin classification and process understanding

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-11-8191-2014 ◽

2014 ◽

Vol 11 (7) ◽

pp. 8191-8238 ◽

Cited By ~ 1

Author(s):

R. Fernandez ◽

T. Sayama

Keyword(s):

River Basin ◽

Land Surface ◽

Fourier Transforms ◽

Land Surface Model ◽

Arctic Region ◽

River Basins ◽

Large River ◽

Global Scale ◽

Surface Model ◽

Monsoon Area

Abstract. Hydrologic functions of river basins are summarized as water collection, storage and discharge, which can be characterized by the dynamics of hydrological variables including precipitation, evaporation, storage and runoff. In some situations these four variables behave more in a recurrent manner by repeating in a similar range year after year or in other situations they exhibit more randomness with higher variations year by year. The degree of recurrence in runoff is important not only for water resources management but also for hydrologic process understandings, especially in terms of how the other three variables determine the degree of recurrence in runoff. The main objective of this paper is to propose a simple hydrologic classification framework applicable to global scale and large basins based on the combinations of recurrence in the four variables. We evaluate it by Lagged Autocorrelation, Fast Fourier Transforms and Colwell's Indices of variables obtained from EU-WATCH dataset composed by eight hydrologic and land surface model outputs. By setting a threshold to define high or low recurrence in the four variables, we classify each river basin into 16 possible classes. The overview of recurrence patterns at global scale suggested that precipitation is recurrent mainly in the humid tropics, Asian Monsoon area and part of higher latitudes with oceanic influence. Recurrence in evaporation was mainly dependent on the seasonality of energy availability, typically high in the tropics, temperate and subarctic regions. Recurrence in storage at higher latitudes depends on energy/water balances and snow, while that in runoff is mostly affected by the different combinations of these three variables. According to the river basin classification 10 out of the 16 possible classes were present in the 35 largest river basins in the world. In humid tropic region, the basins belong to a class with high recurrence in all the variables, while in subtropical region many of the river basins have low recurrence. In temperate region, the energy limited or water limited in summer characterizes the recurrence in storage, but runoff exhibits generally low recurrence due to the low recurrence in precipitation. In the subarctic and arctic region, the amount of snow also influences the classes; more snow yields higher recurrence in storage and runoff. Our proposed framework follows a simple methodology that can aid in grouping river basins with similar characteristics of water, energy and storage cycles. The framework is applicable at different scales with different datasets to provide useful insights into the understanding of hydrologic regimes based on the classification.

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Carbonyl Sulfide: Comparing a Mechanistic Representation of the Vegetation Uptake in a Land Surface Model and the Leaf Relative Uptake Approach

10.5194/bg-2020-381 ◽

2020 ◽

Author(s):

Fabienne Maignan ◽

Camille Abadie ◽

Marine Remaud ◽

Linda M. J. Kooiijmans ◽

Kukka-Maaria Kohonen ◽

...

Keyword(s):

Land Surface ◽

Carbonyl Sulfide ◽

Land Surface Model ◽

Global Scale ◽

C3 Plants ◽

Surface Model ◽

High Temporal Resolution ◽

Co2 Uptake ◽

Mechanistic Approach ◽

Relative Uptake

Abstract. Land surface modelers need measurable proxies to constrain the quantity of carbon dioxide (CO2) assimilated by continental plants through photosynthesis, known as Gross Primary Production (GPP). Carbonyl sulfide (COS), which is taken up by leaves through their stomates and then hydrolysed by photosynthetic enzymes, is a candidate GPP proxy. A former study with the ORCHIDEE land surface model used a fixed ratio of COS uptake to CO2 uptake normalized to respective ambient concentrations for each vegetation type (Leaf Relative Uptake, LRU). COS leaf fluxes were then computed from GPP, and the resulting concentrations were transported with an atmospheric model which included all other known COS fluxes as inputs. Modelled COS concentrations could then be compared to COS measurements from the NOAA air sampling tower network. The LRU approach is known to have limited accuracy since the LRU ratio changes with variables such as Photosynthetically Active Radiation (PAR): while CO2 uptake slows under low light, COS uptake is not light limited. However, the LRU approach has been popular for COS-GPP proxy studies because of its ease of application and apparent low contribution to uncertainty for regional scale applications. In this study we refined the COS-GPP relationship and implemented in ORCHIDEE a mechanistic model that describes COS uptake by continental vegetation. We compared the simulated COS fluxes against measured hourly COS fluxes at two sites, and studied the model behaviour and links with environmental drivers. We performed simulations at global scale, and estimated the global COS uptake by vegetation to be −756 Gg S yr−1, in the middle range of former studies (−490 to −1335 Gg S yr−1). Based on the mechanistic approach in ORCHIDEE, we derived new LRU values for the different vegetation types, ranging between 0.92 and 1.72, close to recently published averages for observed values of 1.21 for C4 and 1.68 for C3 plants. We transported the COS using the monthly vegetation COS fluxes derived from both the mechanistic and the LRU approaches, and evaluated the simulated COS concentrations at NOAA sites. Although the mechanistic approach was more appropriate when comparing to high-temporal-resolution COS flux measurements, both approaches gave similar results when transporting with monthly COS fluxes and evaluating COS concentrations at stations. In our study, uncertainties between these two approaches are of second importance as compared to the uncertainties in the COS global budget, which are currently a limiting factor to the potential of COS concentrations to constrain GPP simulated by land surface models on the global scale.

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