Snow Scheme Research Articles

Correcting first‐order errors in snow water equivalent estimates using a multifrequency, multiscale radiometric data assimilation scheme

A season‐long, multiscale, multifrequency radiometric data assimilation experiment is performed to test the feasibility of snow water equivalent (SWE) estimation. Synthetic passive microwave (PM) observations at Advanced Microwave Scanning Radiometer‐Earth Observing System frequencies and 25 km resolution and synthetic near infrared (NIR) narrowband albedo observations corresponding to Moderate Resolution Imaging Spectroradiometer band 5 (1230–1250 μm) and 1 km resolution are assimilated into a land surface model snow scheme using the ensemble Kalman filter. First‐order sources of model uncertainty, including error in precipitation quantity, grain size evolution, precipitation spatial distribution, and vegetation leaf area index are modeled. SWE remote sensing retrieval schemes would be of limited value for these scenarios where snow depth ranged between 1.0 and 2.0 m, grain size varied in space, significant vegetation was present, and the snowpack sometimes contained liquid water. Nevertheless, the true basinwide SWE is recovered, in general, within a root‐mean‐square error (RMSE) of approximately 2 cm. Synergy is observed between the PM and NIR measurements because of the complementary nature of the multiscale, multifrequency measurements. Results from the assimilation are compared to those from a pure modeling approach and from a remote sensing retrieval approach. The effects of model uncertainty, measurement error, and ensemble size are investigated.

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

Abstract The performance of a modified version of the snow scheme included in the Interactions between Surface–Biosphere–Atmosphere (ISBA) land surface scheme, which was operationally implemented into the regional weather forecast system at the Canadian Meteorological Centre, is examined in this study. Stand-alone verification tests conducted prior to the operational implementation showed that ISBA's new snow package was able to realistically reproduce the main characteristics of a snow cover, such as snow water equivalent and density, for five winter datasets taken at Col de Porte, France, and at Goose Bay, Newfoundland, Canada. A number of modifications to ISBA's snow model (i.e., new liquid water reservoir in the snowpack, new formulation of snow density, and melting effect of incident rainfall on the snowpack) were found to improve the numerical representation of snow characteristics. Objective scores for the fully interactive preimplementation tests carried out with the Canadian regional weather fore...

Refinements to SSiB with an Emphasis on Snow Physics: Evaluation and Validation Using GSWP and Valdai Data

Refinements to the snow-physics scheme of SSiB (Simplified Simple Biosphere Model) are described and evaluated. The upgrades include a partial redesign of the conceptual architecture to better simulate the diurnal temperature of the snow surface. For a deep snowpack, there are two separate prognostic temperature snow layers - the top layer responds to diurnal fluctuations in the surface forcing, while the deep layer exhibits a slowly varying response. In addition, the use of a very deep soil temperature and a treatment of snow aging with its influence on snow density is parameterized and evaluated. The upgraded snow scheme produces better timing of snow melt in GSWP-style simulations using ISLSCP Initiative I data for 1987-1988 in the Russian Wheat Belt region. To simulate more realistic runoff in regions with high orographic variability, additional improvements are made to SSiB's soil hydrology. These improvements include an orography-based surface runoff scheme as well as interaction with a water table below SSiB's three soil layers. The addition of these parameterizations further help to simulate more realistic runoff and accompanying prognostic soil moisture fields in the GSWP-style simulations. In intercomparisons of the performance of the new snow-physics SSiB with its earlier versions using an 18-year single-site dataset from Valdai Russia, the version of SSiB described in this paper again produces the earliest onset of snow melt. Soil moisture and deep soil temperatures also compare favorably with observations.

Test of a simple two-layer parameterisation to simulate the energy balance and temperature of a snow pack

Reasonably simple yet realistic modelling schemes simulating the heat and mass balance within a snow pack are required to provide the necessary boundary conditions for meteorological and hydrological models. An improvement to a one-layer snow energy balance model (UEB, Tarboton etal., 1995) is proposed to better simulate snow surface and snow pack temperatures and, as a result, snowmelt. The modified scheme is assessed against measured snow data from the WINTEX field campaign during spring 1997 in northern Finland, and compared with results from a complex multi-layer snow energy balance scheme. The results show that separation of a one-layer representation into two snow layers and a soil layer enables a more realistic simulation of soil and snow temperatures as well as of the snow surface temperature. The two-layer and the multi-layer snow schemes yielded comparable results for internal processes in the snow whenever the simulation was carried out under similar boundary forcing. The modified scheme is proposed for use as a sub-scheme in meteorological or hydrological models, or as a tool for simulating spatially-variable snowmelt and the surface energy balance during seasonal snow cover.

An Intercomparison of Three Snow Schemes of Varying Complexity Coupled to the Same Land Surface Model: Local-Scale Evaluation at an Alpine Site

The Interactions between Soil, Biosphere, and Atmosphere land surface scheme is currently used coupled both to atmospheric models and to a distributed hydrological model. There are two snow-scheme options available for hydrological modeling: the baseline force-restore approach, which uses a composite snow-soil-vegetation energy budget and a single snow layer; and a multilayer detailed internal-process snow model. Only the force-restore method is routinely used in atmospheric modeling applications. Recent studies have shown that hydrological simulations for mountainous catchments within the Rhone basin, France, are significantly improved using the detailed snow scheme. The main drawback is that the scheme is computationally expensive, and it is not currently feasible for routine application in atmospheric models. For these reasons, a third new intermediate-complexity scheme has been developed that includes certain key physical processes from the complex model for improved snowpack realism and hydrological depiction while attemping to keep computational requirements similar to those of the simple default scheme. In the current study, the new scheme is described, evaluated, and compared with the results from the two other schemes at a local scale at an alpine site located within the Rhone basin for two contrasting (weather) years. All schemes are able to model the basic features of the snow cover with similar errors averaged over the 2-yr period; however, there are important differences on shorter timescales. When compared with the more complex scheme, it was found that differing surface energy budget parameter-izations (turbulent transfer, albedo) were the cause for the largest differences in total snowpack snow water equivalent (SWE) simulated by the models. When compared with the simple scheme, the ability for the intermediate model to simulate snow ripening resulted in the largest differences in simulated SWE and snow temperature during melt and runoff.

Implementing a new snow scheme in Simplified Simple Biosphere Model

This paper describes a modified version of SSIB through implementing a new snow model (SAST) in Simplified Simple Biosphere Model SSIB for climate study and presents the evaluation results by testing the scheme based on the field data from Russia and France. The relevant equations in the scheme are given, which describe complicated interactive processes among air-vegetation-snow-soil continuum through mass and heat exchange. An efficient numerical scheme is developed to solve the nonlinear equations successfully. By using the field data from Russia and France, the function of the new scheme is evaluated. The numerical results from the scheme show good agreement with field data. It indicates that the scheme developed here is workable and can be extended for climate study.

Comparison of two hydrological simulations of the Rhone basin

The objective of the GEWEX/Rhone project is to develop a regional model of the surface energy and water cycles, coupled with a macroscale hydrological model within the Rhone basin. Two methods have been used: the Standard MODCOU model (SM) and CIRSE. SM computes the water balance with a daily time step using production functions consisting of 3 reservoirs. CIRSE is comprised of the ISBA surface scheme and the detailed CROCUS snow scheme. It solves the energy and water balances with a 5-minute time step. Both methods use the same model for the runoff routing and the water table evolution. This article presents the application of the 2 methods over the French part of the Rhone basin (86500 km2), for the 14-year period August 1981 to July 1995. Both models give satisfying results. SM, which was calibrated over a 3-year period, obtains the best results in terms of daily efficiency. However, the simulated total annual discharge is closer to the observations with CIRSE than with SM. This is due to the representation of the vegetation cycle and probably to a more realistic description of the soil moisture and evaporation in CIRSE.

Simulation of snow mass and extent in general circulation models

An evaluation of the Biosphere Atmosphere Transfer Scheme (BATS) snow submodel was conducted, both in a stand-alone mode and within the National Center for Atmospheric Research (NCAR) Community Climate Model version 3 (CCM3). We evaluated, in the stand-alone mode, the performance of BATS parameterizations at local scales using ground-based observations from the former Soviet Union and from Mammoth Mountain, California. The BATS snow scheme reproduces well the seasonal evolution of snow water equivalent in both sites, and the results for the Mammoth Mountain site compare well with those from a more complex, physically based model (SNTHERM), In the coupled mode, we evaluated the modelled snow cover extent, snow mass, precipitation and temperature from BATS as linked to the NCAR CCM3 using available observations. The coupled models capture the broad pattern of seasonal and geographical distribution of snow cover, with better overall performance than the passive microwave snow data derived from the Nimbus-7 Scanning Multi-channel Microwave Radiometer (SMMR) which generally underestimates snow depth. In terms of continents, the snow mass is better simulated during the accumulation period than during the melt period, which is the case for both North America and Eurasia, The simulation of snow mass, precipitation and air temperature for North America is slightly better than that for Eurasia. A rigorous evaluation of snow simulations in coupled land-atmosphere models requires high quality global datasets of snow cover extent, snow depth and snow water equivalent. The available datasets and model outputs are not yet ready to fulfil this objective.

A simple snow‐atmosphere‐soil transfer model

This paper presents a simple snow model for climate studies. There are three prognostic variables in the model: specific enthalpy, snow water equivalent, and snow depth. This model is developed on the basis of up‐to‐date comprehensive and complex snow schemes but with substantial simplification and improvement. The effects of vapor on snow processes have been analyzed in the paper. On the basis of the analysis, vapor's contribution in the mass equation is eliminated, and an effective conductivity coefficient, which includes a simple parameterization for vapor diffusion effect, is used to describe its contribution in the energy equation to simplify the computation. Specific enthalpy is used in the energy balance equation. Using enthalpy rather than temperature greatly simplifies the computational procedure for the phase change calculation in the snow process. This approach, along with a one‐step test scheme that avoids iterations, saves computational time, which is important for general circulation model (GCM) simulations. The layering scheme is a critical part in the model. After many tests, it is found that three layers with an appropriate layering scheme are adequate for most cases. Preliminary testing using Russian and French snow data shows that the three‐layer model is able to produce reasonable and consistent results.

Treatment of soil, vegetation and snow in land surface models: a test of the Biosphere–Atmosphere Transfer Scheme with the HAPEX-MOBILHY, ABRACOS and Russian data

Various components of the land surface, their individual hydrological processes and the process-oriented models are reviewed in this paper, with the focus on their application in global climate models (GCMs). The Biosphere–Atmosphere Transfer Scheme (BATS) is examined regarding its performance for three different surfaces (crop, forest and grass), with available data from HAPEX-MOBILHY, ABRACOS and Russian data sets. The simulations of the key land surface prognostic variables, such as soil moisture and snow cover, are examined in detail because such validation has been lacking. Using the HAPEX-MOBILHY data, the impact of errors in the forcing variables on the uncertainties in the partitioning of total run-off and evapotranspiration is investigated, and the influence of the periodic forcing on soil moisture simulations is examined. Furthermore, an alternative empirically based approach for the soil evaporation efficiency is tested. The current framework of BATS soil hydrology, vegetation and snow schemes adequately reproduces observed soil moisture profiles for the three surfaces considered, and captures the seasonal evolution of snow mass. The simulations can be enhanced when site-specific information on surface parameters is available. Because of the realism of the overall framework of BATS, its inclusion in a GCM [the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM)] leads to reasonably realistic simulations of surface hydroclimatological variables. Further improving surface hydrology in global climate models is dependent on thorough tests of the available models using the available data, on the collection of long-term, seasonal, high-quality data, both at point and on larger spatial scales, and on the effective representation of the surface types on GCM scales.

The validation of a snow parameterization designed for use in general circulation models

A snow model designed for use in general circulation models is tested using atmospheric forcing derived from observations. Using data for four sites from the former Soviet Union, simulations of snow mass, snow density, snow depth, albedo and net radiation are validated. While we find the model works well in capturing the general patterns of the seasonal cycles and interannual variability in these quantities, there are systematic problems in the modelling of snow density and snow albedo towards the end of each snow season. An analysis of the snow densification parameterization shows that the model is very sensitive to the value of a poorly known parameter describing the temperature dependence of the snow compactive viscosity. Many problems in the simulation of snow stem from the simplification of complex processes occurring over time, such as layering and ripening, by a single bulk snow layer which prevents the model responding dynamically to changes in the forcing. In the simulation of the four sites, we used various methods for downward longwave radiation, and we find that the simulation of snow by the model is very sensitive to this quantity. Climate models do not provide this flux accurately in transitional seasons at high latitudes which suggests that it is probably premature to include very complex snow schemes into climate models. In this paper, we were able to obtain far better simulations by choosing the ‘right’ method for downward longwave radiation than by tuning parameters or increasing the complexity of the snow parameterization. However, the ability of the model to capture seasonal and interannual variability irrespective of which downward longwave radiation was used is important, and provides some support for the inclusion of complex snow schemes into climate models. © 1998 Royal Meteorological Society

The validation of a snow parameterization designed for use in general circulation models

A snow model designed for use in general circulation models is tested using atmospheric forcing derived from observations. Using data for four sites from the former Soviet Union, simulations of snow mass, snow density, snow depth, albedo and net radiation are validated. While we find the model works well in capturing the general patterns of the seasonal cycles and interannual variability in these quantities, there are systematic problems in the modelling of snow density and snow albedo towards the end of each snow season. An analysis of the snow densification parameterization shows that the model is very sensitive to the value of a poorly known parameter describing the temperature dependence of the snow compactive viscosity. Many problems in the simulation of snow stem from the simplification of complex processes occurring over time, such as layering and ripening, by a single bulk snow layer which prevents the model responding dynamically to changes in the forcing. In the simulation of the four sites, we used various methods for downward longwave radiation, and we find that the simulation of snow by the model is very sensitive to this quantity. Climate models do not provide this flux accurately in transitional seasons at high latitudes which suggests that it is probably premature to include very complex snow schemes into climate models. In this paper, we were able to obtain far better simulations by choosing the 'right' method for downward longwave radiation than by tuning parameters or increasing the complexity of the snow parameterization. However, the ability of the model to capture seasonal and interannual variability irrespective of which downward longwave radiation was used is important, and provides some support for the inclusion of complex snow schemes into climate models.

Validation of the Snow Submodel of the Biosphere–Atmosphere Transfer Scheme with Russian Snow Cover and Meteorological Observational Data

Snow cover is one of the most important variables affecting agriculture, hydrology, and climate, but detailed measurements are not widely available. Therefore, the effectiveness and validity of snow schemes in general circulation models have been difficult to assess. Using long-term snow cover data from the former Soviet Union, this paper focuses on the validation of the snow submodel in the Biosphere‐Atmosphere Transfer Scheme (BATS) using 6 years of data (1978‐83) at six stations. Fundamental uncertainties in the datasets limit the accuracy of our assessment of the model’s performance. In the absence of a wind correction for the gauge-measured precipitation and with the standard rain‐snow transition criterion (2.28C), the model gives reasonable simulations of snow water equivalent and surface temperature for all of the six stations and the six winters examined. In particular, the time of accumulation and the end of ablation and the alteration due to aging are well captured. With some simple modifications of the code, the model can also reproduce snow depth, snow cover fraction, and surface albedo. In view of the scheme’s simplicity and efficiency, these results are encouraging. However, if a wind correction is applied to the gauge-measured precipitation, the model shows increased rootmean-square errors in snow water equivalent for all six stations except Tulun. Perhaps, the better agreement without wind correction means that the snow has blown beyond the area of snow measurement, as might be accounted for only by a detailed regional snow‐wind distribution model. This study underlines four aspects that warrant special attention: (i) estimation of the downward longwave radiation, (ii) separation of the aging processes for snowpack density and snow surface albedo, (iii) parameterization of snow cover fraction, and (iv) choice of critical temperature for rain‐snow transition.

The Milankovitch theory and climate sensitivity: 1. Equilibrium climate model solutions for the present surface conditions

An examination of the results of climate models testing the Milankovitch theory suggests that this theory may be closely linked to the broader and as yet unresolved question of the evaluation of climate sensitivity. With this point in mind, a climate model intended to test climate sensitivity in general and the Milankovitch theory in particular is described, and its equilibrium solutions for the present surface boundary conditions are analyzed. The statistical‐dynamical hemispheric climate model is zonally averaged, with expanded longitudinal separation at the surface level, and includes topography, and detailed sea ice/snow and land snow schemes capable of simulating nonlinear effects of heat transfer through the layers of ice and snow, a modified long‐wave scheme, a provision for a variable cloud top temperature (VCT) model, and an eddy exchange parameterization connecting the eddy coefficients to the n th power of the meridional temperature gradient. The value of n in the latter relation is varied between the traditional value of 2 associated with the Green theory and a value of 4, which we believe to be more suitable for seasonal climate models of the present type. Four climate model versions are implemented with the aim of investigating three basic feedback mechanisms associated with the ice/snow albedos, the long‐wave radiation, and the meridional eddy transport, and estimating the upper bound of climate sensitivity due to their effect. The differences between the results of the four versions are rather small for the simulation of the present climate but are more than tripled for a 1% decrease in the solar constant. It is therefore concluded that an agreement with the observed fields does not automatically guarantee a correct simulation of climate sensitivity. The approach suggested by the present study is to explore a range of variability of some tunable parameters, rather than to tune these parameters to a single optimal set of values. The resulting sensitivity to a 1% decrease in the solar constant varies between 1° and 4°C in these four versions. The equilibrium response to a change between extreme high and low summer insolation orbits is a shift in the region of positive annual snow budgets, varying between 6° and 10° of latitude according to the sensitivity of the particular model version. The experiments presented in Part 1 of this study offer an estimate of the range of response of the equilibrium climate solution, leaving the investigation of the feedback effects that the building of ice sheets has on the climate system to Part 2.