Interactions Between Soil-Biosphere-Atmosphere Research Articles

A new approach for drought index adjustment to clay-shrinkage-induced subsidence over France: advantages of the interactive leaf area index

Abstract. Clay shrinkage, which consists of a reduction in the volume of clay soils during dry periods, can affect buildings and cause subsidence damage. In France, losses due to subsidence are estimated at more than EUR 16 billion for the period 1989–2021 (CCR, 2021) and are expected to increase under the effect of climate warming. This work aims to improve the current understanding of the conditions triggering subsidence by proposing an innovative drought index. We use a daily soil wetness index (SWI) to develop a new annual drought index that can be related to subsidence damage. The SWI is derived from simulations of soil moisture profiles from the interactions between soil–biosphere–atmosphere (ISBA) land surface model developed by Météo-France. The ability of the drought index to correlate with insurance claim data is assessed by calculating the Kendall rank correlation over 20 municipalities in France. The insurance data, aggregated by year and municipality, are provided by the Caisse Centrale de Réassurance (CCR). A total of 1200 configurations of the drought index are considered. They are generated by combining different calculation methods, ISBA simulation settings, soil model layers, and drought percentile thresholds. The analysis includes a comparison with the independent claim data of six additional municipalities and with a record of official “CatNat” (the French national natural disaster compensation scheme) decrees, useful for the analysis. The best results are obtained for drought magnitudes based on SWI values of the 0.8-to-1.0 m deep soil layer, an ISBA simulation with interactive leaf area index (LAI), and consideration of low drought SWI percentile thresholds. Comparison with claim data shows that drought magnitude is able to identify subsidence events while being spatially consistent. This drought magnitude index provides more insight into subsidence triggers while benefiting from advanced land surface modeling schemes (interactive LAI, multilayer soil). This work paves the way for more reliable damage estimates.

Assessment of the interactions between soil–biosphere–atmosphere (ISBA) land surface model soil hydrology, using four closed-form soil water relationships and several lysimeters

Abstract. Soil water drainage is the main source of groundwater recharge and river flow. It is therefore a key process for water resource management. In this study, we evaluate the soil hydrology and the soil water drainage, simulated by the interactions between soil–biosphere–atmosphere (ISBA) land surface model currently used for hydrological applications from the watershed scale to the global scale, where parameters are generally not calibrated. This evaluation is done using seven lysimeters from two long-term model approach sites measuring hourly water dynamics between 2009 and 2019 in northeastern France. These 2 m depth lysimeters are filled with different soil types and are either maintained as bare soil or covered with vegetation. Four closed-form equations describing soil water retention and hydraulic conductivity functions are tested, namely the commonly used equations from Brooks and Corey (1966) and van Genuchten (1980), a combination of the van Genuchten (1980) soil water retention function with the Brooks and Corey (1966) unsaturated hydraulic conductivity function, and, for the very first time in a land surface model (LSM), a modified version of the van Genuchten (1980) equations, with a new hydraulic conductivity curve proposed by Iden et al. (2015). The results indicate good performance by ISBA with the different closure equations in terms of soil volumetric water content and water mass. The drained flow at the bottom of the lysimeter is well simulated, using Brooks and Corey (1966), while some weaknesses appear with van Genuchten (1980) due to the abrupt shape near the saturation of its hydraulic conductivity function. The mixed form or the new van Genuchten (1980) hydraulic conductivity function from Iden et al. (2015) allows the solving of this problem and even improves the simulation of the drainage dynamic, especially for intense drainage events. The study also highlights the importance of the vertical heterogeneity of the soil hydrodynamic parameters to correctly simulate the drainage dynamic, in addition to the primary influence of the parameters characterizing the shape of the soil water retention function.

Implementation of a new crop phenology and irrigation scheme in the ISBA land surface model using SURFEX_v8.1

Abstract. With an increase in the number of natural processes represented, global land surface models (LSMs) have become more and more accurate in representing natural terrestrial ecosystems. However, they are still limited with respect to the impact of agriculture on land surface variables. This is particularly true for agro-hydrological processes related to a strong human control on freshwater. While many LSMs consider natural processes only, the development of human-related processes, e.g. crop phenology and irrigation in LSMs, is key. In this study, we present the implementation of a new crop phenology and irrigation scheme in the ISBA (interactions between soil–biosphere–atmosphere) LSM. This highly flexible scheme is designed to account for various configurations and can be applied at different spatial scales. For each vegetation type within a model grid cell, three irrigation systems can be used at the same time. A limited number of parameters are used to control (1) the amount of water used for irrigation, (2) irrigation triggering (based on the soil moisture stress), and (3) crop seasonality (emergence and harvesting). A case study is presented over Nebraska (USA). This region is chosen for its high irrigation density and because independent observations of irrigation practices can be used to verify the simulated irrigation amounts. The ISBA simulations with and without the new crop phenology and irrigation scheme are compared to different satellite-based observations. The comparison shows that the irrigation scheme improves the simulated vegetation variables such as leaf area index, gross primary productivity, and land surface temperature. In addition to a better representation of land surface processes, the results point to potential applications of this new version of the ISBA model for water resource monitoring and climate change impact studies.

Assimilation of passive microwave vegetation optical depth in LDAS-Monde: a case study over the continental USA

Abstract. The land data assimilation system, LDAS-Monde, developed by the research department of the French meteorological service (Centre National de Recherches Météorologiques – CNRM) is capable of well representing land surface variables (LSVs) from regional to global scales. It jointly assimilates satellite-derived observations of leaf area index (LAI) and surface soil moisture (SSM) into the interactions between soil–biosphere–atmosphere (ISBA) land surface model (LSM), increasing the accuracy of the model simulations of the LSVs. The assimilation of vegetation variables directly impacts root zone soil moisture (RZSM) through seven control variables consisting in soil moisture of seven soil layers from the soil surface to 1 m depth. This positive impact is particularly useful in dry conditions, where SSM and RZSM are decoupled to a large extent. However, this positive impact does not reach its full potential due to the low temporal availability of optical-based LAI observations, which is, at best, every 10 d, and can suffer from months of missing data over regions and seasons with heavy cloud cover such as winter or in monsoon conditions. In that context, this study investigates the assimilation of low-frequency passive microwave vegetation optical depth (VOD), available in almost all weather conditions, as a proxy for LAI. The Vegetation Optical Depth Climate Archive (VODCA) dataset provides near-daily observations of vegetation conditions, which is far more frequent than optical-based products such as LAI. This study's goal is to convert the more frequent X-band VOD observations into proxy-LAI observations through linear seasonal re-scaling and to assimilate them in place of direct LAI observations. Seven assimilation experiments are run from 2003 to 2018 over the contiguous United States (CONUS), with (1) no assimilation and the assimilation of (2) SSM, (3) LAI, (4) re-scaled X-band VOD (VODX), (5) re-scaled VODX only when LAI observations are available, (6) LAI + SSM, and (7) re-scaled VODX + SSM. This study analyzes these assimilation experiments by comparing them to satellite-derived observations and in situ measurements and is focused on the variables of LAI, SSM, gross primary production (GPP), and evapotranspiration (ET). Each experiment is driven by atmospheric forcing reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5. Results show improved representation of GPP and ET by assimilating re-scaled VOD in place of LAI. Additionally, the joint assimilation of vegetation-related variables (i.e., LAI or re-scaled VOD) and SSM demonstrates a small improvement in the representation of soil moisture over the assimilation of any dataset by itself.

ISBA-MEB (SURFEX v8.1): model snow evaluation for local-scale forest sites

Abstract. Accurate modeling of the effect of snow cover on the surface energy and mass fluxes is required from land surface models. The Interactions between Soil–Biosphere–Atmosphere (ISBA) model uses a composite soil–vegetation approach that has limitations when representing snow and soil phase change processes in areas of high vegetation cover since it does not explicitly represent the snowpack lying on the ground below the canopy. In particular, previous studies using ISBA have pointed out that the snowpack ablation tends to occur to early in the season in forest regions in the Northern Hemisphere. The multi-energy balance (MEB) version of ISBA has been developed recently, to a large degree, to address this issue. A vegetation layer, which is distinct from the soil, has been added to ISBA and new processes are now explicitly represented, such as snow interception and an understory litter layer. To evaluate the behavior of this new scheme in a cold forested region, long-term offline simulations have been performed for the three BERMS forest sites located in Saskatchewan, Canada. It is shown that the new scheme leads to an improved energy budget representation, especially in terms of the ground and sensible heat fluxes, with decreases in root-mean-square error (RMSE) of 77 % and 18 %, respectively. A positive impact for soil temperatures, consistent with the improvement of the ground heat flux, is obtained, particularly in terms of bias, which is reduced from −6.2 to −0.1 K at a 10 cm soil depth on average for the three sites and 12 studied years. The impact of using MEB on the snowpack simulation is a better agreement with observations during the snow season, especially concerning the last day of snow in the season: errors are on the order of 1 d averaged over the three sites and all of the years using MEB, which represents a reduction in error of 20 d compared to the composite scheme. The analysis shows that this improvement is mostly caused by the ability of MEB to represent a snowpack that nearly completely covers the soil below the canopy and that decouples the soil from the atmosphere, while keeping a close coupling between the vegetation and the atmosphere.

The interactions between soil–biosphere–atmosphere (ISBA) land surface model multi-energy balance (MEB) option in SURFEXv8 – Part 2: Introduction of a litter formulation and model evaluation for local-scale forest sites

Abstract. Land surface models (LSMs) need to balance a complicated trade-off between computational cost and complexity in order to adequately represent the exchanges of energy, water and matter with the atmosphere and the ocean. Some current generation LSMs use a simplified or composite canopy approach that generates recurrent errors in simulated soil temperature and turbulent fluxes. In response to these issues, a new version of the interactions between soil–biosphere–atmosphere (ISBA) land surface model has recently been developed that explicitly solves the transfer of energy and water from the upper canopy and the forest floor, which is characterized as a litter layer. The multi-energy balance (MEB) version of ISBA is first evaluated for three well-instrumented contrasting local-scale sites, and sensitivity tests are performed to explore the behavior of new model parameters. Second, ISBA-MEB is benchmarked against observations from 42 forested sites from the global micro-meteorological network (FLUXNET) for multiple annual cycles.It is shown that ISBA-MEB outperforms the composite version of ISBA in improving the representation of soil temperature, ground, sensible and, to a lesser extent, latent heat fluxes. Both versions of ISBA give comparable results in terms of simulated latent heat flux because of the similar formulations of the water uptake and the stomatal resistance. However, MEB produces a better agreement with the observations of sensible heat flux than the previous version of ISBA for 87.5 % of the simulated years across the 42 forested FLUXNET sites. Most of this improvement arises owing to the improved simulation of the ground conduction flux, which is greatly improved using MEB, especially owing to the forest litter parameterization. It is also shown that certain processes are also modeled more realistically (such as the partitioning of evapotranspiration into transpiration and ground evaporation), even if certain statistical performances are neutral. The analyses demonstrate that the shading effect of the vegetation, the explicit treatment of turbulent transfer for the canopy and ground, and the insulating thermal and hydrological effects of the forest floor litter turn out to be essential for simulating the exchange of energy, water and matter across a large range of forest types and climates.

The growth of shrubs on high Arctic tundra at Bylot Island: impact on snow physical properties and permafrost thermal regime

Abstract. With climate warming, shrubs have been observed to grow on Arctic tundra. Their presence is known to increase snow height and is expected to increase the thermal insulating effect of the snowpack. An important consequence would be the warming of the ground, which will accelerate permafrost thaw, providing an important positive feedback to warming. At Bylot Island (73° N, 80° W) in the Canadian high Arctic where bushes of willows (Salix richardsonii Hook) are growing, we have observed the snow stratigraphy and measured the vertical profiles of snow density, thermal conductivity and specific surface area (SSA) in over 20 sites of high Arctic tundra and in willow bushes 20 to 40 cm high. We find that shrubs increase snow height, but only up to their own height. In shrubs, snow density, thermal conductivity and SSA are all significantly lower than on herb tundra. In shrubs, depth hoar which has a low thermal conductivity was observed to grow up to shrub height, while on herb tundra, depth hoar only developed to 5 to 10 cm high. The thermal resistance of the snowpack was in general higher in shrubs than on herb tundra. More signs of melting were observed in shrubs, presumably because stems absorb radiation and provide hotspots that initiate melting. When melting was extensive, thermal conductivity was increased and thermal resistance was reduced, counteracting the observed effect of shrubs in the absence of melting. Simulations of the effect of shrubs on snow properties and on the ground thermal regime were made with the Crocus snow physics model and the ISBA (Interactions between Soil–Biosphere–Atmosphere) land surface scheme, driven by in situ and reanalysis meteorological data. These simulations did not take into account the summer impact of shrubs. They predict that the ground at 5 cm depth at Bylot Island during the 2014–2015 winter would be up to 13 °C warmer in the presence of shrubs. Such warming may however be mitigated by summer effects.

Impact of Surface Parameter Uncertainties within the Canadian Regional Ensemble Prediction System

Abstract The aim of this study is to assess the impact of uncertainties in surface parameter and initial conditions on numerical prediction with the Canadian Regional Ensemble Prediction System (REPS). As part of this study, the Canadian version of the Interactions between Soil–Biosphere–Atmosphere (ISBA) land surface scheme has been coupled to Environment Canada’s numerical weather prediction model within the REPS. For 20 summer periods in 2009, stochastic perturbations of surface parameters have been generated in several experiments. Each experiment corresponds to 20 simulations differing by the perturbations at the initial time of one or several surface parameters or prognostic variables. The sensitivity to these perturbations is quantified especially for 2-m temperature, 10-m wind speed, cloud fraction, and precipitation up to 48-h lead time. Spatial variability of these sensitivities over the North American continent shows that soil moisture, albedo, leaf area index, and SST have the largest impacts on the screen-level variables. The temporal evolution of these sensitivities appears to be closely linked to the diurnal cycle of the boundary layer. The surface perturbations are shown to increase the ensemble spread of the REPS for all screen-level variables especially for 2-m temperature and 10-m wind speed during daytime. A preliminary study of the impact on the ensemble forecast has shown that the inclusion of the surface perturbations tends to significantly increase the 2-m temperature and 10-m wind speed skill.

Simulation of Northern Eurasian Local Snow Depth, Mass, and Density Using a Detailed Snowpack Model and Meteorological Reanalyses

Abstract The Crocus snowpack model within the Interactions between Soil–Biosphere–Atmosphere (ISBA) land surface model was run over northern Eurasia from 1979 to 1993, using forcing data extracted from hydrometeorological datasets and meteorological reanalyses. Simulated snow depth, snow water equivalent, and density over open fields were compared with local observations from over 1000 monitoring sites, available either once a day or three times per month. The best performance is obtained with European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim). Provided blowing snow sublimation is taken into account, the simulations show a small bias and high correlations in terms of snow depth, snow water equivalent, and density. Local snow cover durations as well as the onset and vanishing dates of continuous snow cover are also well reproduced. A major result is that the overall performance of the simulations is very similar to the performance of existing gridded snow products, which, in contrast, assimilate local snow depth observations. Soil temperature at 20-cm depth is reasonably well simulated. The methodology developed in this study is an efficient way to evaluate different meteorological datasets, especially in terms of snow precipitation. It reveals that the temporal disaggregation of monthly precipitation in the hydrometeorological dataset from Princeton University significantly impacts the rain–snow partitioning, deteriorating the simulation of the onset of snow cover as well as snow depth throughout the cold season.

The Hydrological Modeling and Analysis Platform (HyMAP): Evaluation in the Amazon Basin

Abstract Recent advances in global flow routing schemes have shown the importance of using high-resolution topography for representing floodplain inundation dynamics more reliably. This study presents and evaluates the Hydrological Modeling and Analysis Platform (HyMAP), which is a global flow routing scheme specifically designed to bridge the gap between current state-of-the-art global flow routing schemes by combining their main features and introducing new features to better capture floodplain dynamics. The ultimate goals of HyMAP are to provide the scientific community with a novel scheme suited to the assimilation of satellite altimetry data for global water discharge forecasts and a model that can be potentially coupled with atmospheric models. In this first model evaluation, HyMAP is coupled with the Interactions between Soil–Biosphere–Atmosphere (ISBA) land surface model in order to simulate the surface water dynamics in the Amazon basin. The model is evaluated over the 1986–2006 period against an unprecedented source of information, including in situ and satellite-based datasets of water discharge and level, flow velocity, and floodplain extent. Results show that the model can satisfactorily simulate the large-scale features of the water surface dynamics of the Amazon River basin. Among all stream gauges considered, 23% have Nash–Sutcliffe coefficients (NS) higher than 0.50 and 68% above zero. About 28% of the stations have volume errors lower than 15%. Simulated discharges at Óbidos had NS = 0.89. Time series of simulated floodplains at the basin scale agrees well with satellite-based estimates, with a relative error of 7% and correlation of 0.89. These results indicate nonnegligible improvements in comparison to previous studies for the same region.

A simple groundwater scheme in the TRIP river routing model: global off-line evaluation against GRACE terrestrial water storage estimates and observed river discharges

Abstract. Groundwater is a non-negligible component of the global hydrological cycle, and its interaction with overlying unsaturated zones can influence water and energy fluxes between the land surface and the atmosphere. Despite its importance, groundwater is not yet represented in most climate models. In this paper, the simple groundwater scheme implemented in the Total Runoff Integrating Pathways (TRIP) river routing model is applied in off-line mode at global scale using a 0.5° model resolution. The simulated river discharges are evaluated against a large dataset of about 3500 gauging stations compiled from the Global Data Runoff Center (GRDC) and other sources, while the terrestrial water storage (TWS) variations derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission help to evaluate the simulated TWS. The forcing fields (surface runoff and deep drainage) come from an independent simulation of the Interactions between Soil-Biosphere-Atmosphere (ISBA) land surface model covering the period from 1950 to 2008. Results show that groundwater improves the efficiency scores for about 70% of the gauging stations and deteriorates them for 15%. The simulated TWS are also in better agreement with the GRACE estimates. These results are mainly explained by the lag introduced by the low-frequency variations of groundwater, which tend to shift and smooth the simulated river discharges and TWS. A sensitivity study on the global precipitation forcing used in ISBA to produce the forcing fields is also proposed. It shows that the groundwater scheme is not influenced by the uncertainties in precipitation data.

Soil moisture modelling of a SMOS pixel: interest of using the PERSIANN database over the Valencia Anchor Station

Abstract. In the framework of Soil Moisture and Ocean Salinity (SMOS) Calibration/Validation (Cal/Val) activities, this study addresses the use of the PERSIANN-CCS1database in hydrological applications to accurately simulate a whole SMOS pixel by representing the spatial and temporal heterogeneity of the soil moisture fields over a wide area (50×50 km2). The study focuses on the Valencia Anchor Station (VAS) experimental site, in Spain, which is one of the main SMOS Cal/Val sites in Europe. A faithful representation of the soil moisture distribution at SMOS pixel scale (50×50 km2) requires an accurate estimation of the amount and temporal/spatial distribution of precipitation. To quantify the gain of using the comprehensive PERSIANN database instead of sparsely distributed rain gauge measurements, comparisons between in situ observations and satellite rainfall data are done both at point and areal scale. An overestimation of the satellite rainfall amounts is observed in most of the cases (about 66%) but the precipitation occurrences are in general retrieved (about 67%). To simulate the high variability in space and time of surface soil moisture, a Soil Vegetation Atmosphere Transfer (SVAT) model – ISBA (Interactions between Soil Biosphere Atmosphere) is used. The interest of using satellite rainfall estimates as well as the influence that the precipitation events can induce on the modelling of the water content in the soil is depicted by a comparison between different soil moisture data. Point-like and spatialized simulated data using rain gauge observations or PERSIANN – CCS database as well as ground measurements are used. It is shown that a good adequacy is reached in most part of the year, the precipitation differences having less impact upon the simulated soil moisture. The behaviour of simulated surface soil moisture at SMOS scale is verified by the use of remote sensing data from the Advanced Microwave Scanning Radiometer on Earth observing System (AMSR-E). We show that the PERSIANN database provides useful information at temporal and spatial scales in the context of soil moisture retrieval. 1Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System – http://chrs.web.uci.edu/persiann

Modelling soil moisture at SMOS scale by use of a SVAT model over the Valencia Anchor Station

Abstract. The main goal of the SMOS (Soil Moisture and Ocean Salinity) mission is to deliver global fields of surface soil moisture and sea surface salinity using L-band (1.4 GHz) radiometry. Within the context of the Science preparation for SMOS, the Valencia Anchor Station (VAS) experimental site, in Spain, was chosen to be one of the main test sites in Europe for Calibration/Validation (Cal/Val) activities. In this framework, the paper presents an approach consisting in accurately simulating a whole SMOS pixel by representing the spatial and temporal heterogeneity of the soil moisture fields over the wide VAS surface (50×50 km2). Ground and meteorological measurements over the area are used as the input of a Soil-Vegetation-Atmosphere-Transfer (SVAT) model, SURFEX (Externalized Surface) - module ISBA (Interactions between Soil-Biosphere-Atmosphere) to simulate the spatial and temporal distribution of surface soil moisture. The calibration as well as the validation of the ISBA model are performed using in situ soil moisture measurements. It is shown that a good consistency is reached when point comparisons between simulated and in situ soil moisture measurements are made. Actually, an important challenge in remote sensing approaches concerns product validation. In order to obtain an representative soil moisture mapping over the Valencia Anchor Station (50×50 km2 area), a spatialization method is applied. For verification, a comparison between the simulated spatialized soil moisture and remote sensing data from the Advanced Microwave Scanning Radiometer on Earth observing System (AMSR-E) and from the European Remote Sensing Satellites (ERS-SCAT) is performed. Despite the fact that AMSR-E surface soil moisture product is not reproducing accurately the absolute values, it provides trustworthy information on surface soil moisture temporal variability. However, during the vegetation growing season the signal is perturbed. By using the polarization ratio a better agreement is obtained. ERS-SCAT soil moisture products are also used to be compared with the simulated spatialized soil moisture. However, the lack of soil moisture data from the ERS-SCAT sensor over the area (45 observations for one year) prevented capturing the soil moisture variability.

Large-scale coupled hydrologic and hydraulic modelling of the Ob river in Siberia

The Ob river in Western Siberia is one of the largest rivers in the Arctic and has a complex hydrological cycle mainly driven by snow melting in spring and rainfall and evapotranspiration in summer/autumn. The Ob is a source of fresh water for the Arctic Ocean and a change in its regime could affect the ocean thermohaline circulation. Due to the scarcity of in situ measurements in the Arctic and the size of the region, the hydrological modelling of large Arctic rivers is difficult to perform. To model the northern part of the Ob river basin, the land surface scheme ISBA (Interactions between Soil-Biosphere-Atmosphere) has been coupled with the flood inundation model LISFLOOD-FP. Different sensitivity tests on input data and parameters have been performed and the results have been compared with in-situ measurements and remotely sensed observations of water level. The best modelling is obtained with a river depth of 10 meters and a Manning coefficient of 0.015: correlation and Nash-Sutcliffe coefficients with in-situ measurement are equal or even slightly above (depending on the precipitation dataset used) 0.99 and 0.95 respectively. The sensitivity tests show that modelling errors are mainly linked with atmospheric input (snow and rain precipitation), snow cover and drainage parameterization for ISBA and Manning coefficient, river depth and floodplain topography for LISFLOOD-FP.

Melting of Snow Cover in a Tropical Mountain Environment in Bolivia: Processes and Modeling

Abstract To determine the physical processes involved in the melting and disappearance of transient snow cover in nonglacierized tropical areas, the CROCUS snow model, interactions between Soil–Biosphere–Atmosphere (ISBA) land surface model, and coupled ISBA/CROCUS model have been applied to a full set of meteorological data recorded at 4795 m MSL on a moraine area in Bolivia (16°17′S, 68°32′W) between 14 May 2002 and 15 July 2003. The models have been adapted to tropical conditions, in particular the high level of incident solar radiation throughout the year. As long as a suitable function is included to represent the mosaic partitioning of the surface between snow cover and bare ground and local fresh snow grain type (as graupel) is adapted, the ISBA and ISBA/CROCUS models can accurately simulate snow behavior over nonglacierized natural surfaces in the Tropics. Incident solar radiation is responsible for efficient melting of the snow surface (favored by fresh snow albedo values usually not exceeding 0.8) and also for the energy stored in snow-free areas (albedo = 0.18) and transferred horizontally to adjacent snow patches. These horizontal energy transfers (by conduction within the upper soil layers and by turbulent advection) explain most of the snowmelt and prevent the snow cover from lasting more than a few days during the wet season in this high-altitude tropical environment.

Operational Implementation of the ISBA Land Surface Scheme in the Canadian Regional Weather Forecast Model. Part I: Warm Season Results

The summertime improvement resulting from the operational implementation of a new surface modeling and assimilation strategy into the Canadian regional weather forecasting system is described in this study. The surface processes over land are represented in this system using the Interactions between Soil–Biosphere–Atmosphere (ISBA) land surface scheme. Surface variables, including soil moisture, are initialized using a sequential assimilation technique in which model errors of low-level air temperature and relative humidity are used to determine analysis increments of surface variables. It was found that the magnitude and nature of the analysis increments applied to the surface variables depended on the surface and meteorological conditions observed in each region. In regions characterized by weak meteorological activity (i.e., no clouds or precipitation), model errors of low-level air characteristics are more likely to be related to an incorrect representation of surface processes due to either erroneous initial conditions or inaccurate parameterizations in the land surface scheme. In other regions characterized by more frequent and more intense precipitation events, surface corrections are mainly associated with inaccurate atmospheric forcing. Objective evaluation against observations from radiosondes and surface stations showed that the amplitude of the diurnal cycle of near-surface air temperature and humidity is larger with the new surface system, in better agreement with observations. This type of improvement was found to extend higher up in the boundary layer (up to 700 hPa) where cold and humid biases were significantly reduced by introducing the new surface system. The model precipitation was also found to be significantly influenced by the new representation of surface fluxes. The problematic increase of a positive bias in precipitation with integration time was found to be significantly reduced with the new system, due to the warmer and drier boundary layer.

Robust simulation of root zone soil moisture with assimilation of surface soil moisture data

An operational framework is presented for assimilating surface soil moisture remote sensing measurements into a soil‐vegetation‐atmosphere‐transfer (SVAT) model for the robust prediction of root zone moisture time series. The proposed approach is based on analytical treatment of the dynamical equations coupling surface and deeper soil reservoirs. The resulting framework uses biases between observed and modeled time rates of change of surface soil moisture to quantify biases between modeled and actual root zone average soil moisture contents. The approach is based on the popular interactions between soil‐biosphere‐atmosphere (ISBA) force‐restore SVAT model. An experimental data set, collected near Cork, Ireland, is analyzed both for a long data series of 183 days and four short periods that were selected to focus on different hydrometeorological conditions. The results demonstrated that the proposed framework performs uniformly robust over 3 orders of magnitude of misspecification of saturated hydraulic conductivity. In the presence of uncertain initial conditions, the results demonstrated a marked increase in model skill (over the original ISBA model) for periods when average precipitation was less than average potential evaporation.

The Land Surface Scheme ISBA within the Météo-France Climate Model ARPEGE. Part I. Implementation and Preliminary Results

Abstract This paper describes recent developments in climate modeling at Meteo-France related to land surface processes. The implementation of a simple land surface parameterization, Interactions between Soil Biosphere Atmosphere (ISBA), has gained from previous validations and calibrations at local scale against field datasets and from aggregation procedures devised to define effective land surface properties. Specific improvements for climate purposes are introduced: spatial variability of convective rainfall in canopy drainage estimation and subsurface gravitational percolation. The methodology used to derive climatological maps of land surface parameters at the grid-scale resolution of the model from existing database for soil and vegetation types at global scale is described. A 3-yr integration for the present day climate with a T42L30 version of the climate model has been performed. Results obtained compare favorably with available observed climatologies related to the various components of the cont...