Tobias Jonas

Evaluation of forest snow processes models (SnowMIP2)

Thirty-three snowpack models of varying complexity and purpose were evaluated across a wide range of hydrometeorological and forest canopy conditions at five Northern Hemisphere locations, for up t ...

Estimating Snow Water Equivalent Using Snow Depth Data and Climate Classes

Abstract In many practical applications snow depth is known, but snow water equivalent (SWE) is needed as well. Measuring SWE takes ∼20 times as long as measuring depth, which in part is why depth measurements outnumber SWE measurements worldwide. Here a method of estimating snow bulk density is presented and then used to convert snow depth to SWE. The method is grounded in the fact that depth varies over a range that is many times greater than that of bulk density. Consequently, estimates derived from measured depths and modeled densities generally fall close to measured values of SWE. Knowledge of snow climate classes is used to improve the accuracy of the estimation procedure. A statistical model based on a Bayesian analysis of a set of 25 688 depth–density–SWE data collected in the United States, Canada, and Switzerland takes snow depth, day of the year, and the climate class of snow at a selected location from which it produces a local bulk density estimate. When converted to SWE and tested against t...

CO2 exchange between air and water in an Arctic Alaskan and midlatitude Swiss lake: Importance of convective mixing

[1] CO2 exchange between lake water and the atmosphere was investigated at Toolik Lake (Alaska) and Soppensee (Switzerland) employing the eddy covariance (EC) method. The results obtained from three field campaigns at the two sites indicate the importance of convection in the lake in driving gas flux across the water-air interface. Measurements were performed during short (1-3 day) periods with observed diurnal changes between stratified and convective conditions in the lakes. Over Toolik Lake the EC net CO2 efflux was 114 +/- 33 mg C m(-2) d(-1), which compares well with the 131 +/- 2 mg C m(-2) d(-1) estimated by a boundary layer model (BLM) and the 153 +/- 3 mg C m(-2) d(-1) obtained with a surface renewal model (SRM). Floating chamber measurements, however, indicated a net efflux of 365 +/- 61 mg C m(-2) d(-1), which is more than double the EC fluxes measured at the corresponding times (150 +/- 78 mg C m(-2) d(-1)). The differences between continous (EC, SRM, and BLM) and episodic (chamber) flux determination indicate that the chamber measurements might be biased depending on the chosen sampling interval. Significantly smaller fluxes (p < 0.06) were found during stratified periods (51 +/- 42 mg C m(-2) d(-1)) than were found during convective periods (150 +/- 45 mg C m(-2) d(-1)) by the EC method, but not by the BLM. However, the congruence between average values obtained by the models and EC supports the use of both methods, but EC measurements and the SRM provide more insight into the physical-biological processes affecting gas flux. Over Soppensee, the daily net efflux from the lake was 289 +/- 153 mg C m(-2) d(-1) during the measuring period. Flux differences were significant (p < 0.002) between stratified periods (240 +/- 82 mg C m(-2) d(-1)) and periods with penetrative convection (1117 +/- 236 mg C m(-2) d(-1)) but insignificant if convection in the lake was weak and nonpenetrative. Our data indicate the importance of periods of heat loss and convective mixing to the process of gas exchange across the water surface, and calculations of gas transfer velocity using the surface renewal model support our observations. Future studies should employ the EC method in order to obtain essential data for process-scale investigations. Measurements should be extended to cover the full season from thaw to freeze, thereby integrating data over stratified and convective periods. Thus the statistical confidence in the seasonal budgets of CO2 and other trace gases that are exchanged across lake surfaces could be increased considerably.

How alpine plant growth is linked to snow cover and climate variability

[1] Recent climate models predict future changes in temperature and precipitation in the Alps. To assess the potential response of alpine plant communities to climate change, we analyzed specific and combined effects of temperature, precipitation, and snow season timing on the growth of plants. This analysis is based on data from 17 snow meteorological stations and includes plant growth records from the same sites over 10 years. Using multiple regression and path analysis, we found that plant growth was primarily driven by climatic factors controlled by the timing of the snow season. Air temperature and precipitation before snow-up and after melt-out yielded the greatest direct impact on maximum plant height as well as growth rates. The variability of environmental drivers between sites versus between years had different effects on plant growth: e.g., sites with early melt-out dates hosted plant communities with tall, slow-growing vegetation. But interannual variations in melt-out dates at a given site did not produce measurable differences in plant growth performance. However, high temperatures after melt-out invariably resulted in a shortened growth period. We speculate that the plant growth patterns we observed in response to climate variation between sites are indicative of the long-term responses of alpine plant communities to persistent climate changes. With most climate models indicating shorter winters, we thus expect alpine grasslands in the Alps to display an enhanced biomass production in the future.

Radiatively driven convection in ice-covered lakes: Observations, scaling, and a mixed layer model

Penetrative convection is discussed where the instability is driven by radiative heating of water below the temperature of maximum density. Convection of this type occurs in ice-covered freshwater lakes in late spring, when the snow cover vanishes and solar radiation is absorbed beneath the ice cover. The vertical temperature structure, bulk mixed layer scaling, and mixed layer deepening are examined for a number of temperate and polar lakes. A bulk mixed layer scaling for this type of convection is based on energy arguments underlying the classical Deardorff convective scaling. The depth of the convective layer serves as an appropriate length scale. However, a modified scale that takes account of the energetics of a distributed radiation source term replaces the surface buoyancy flux velocity scale used by Deardorff. The scaling compares favorably with large-eddy simulations of turbulence kinetic energy (TKE) and with both observations and large-eddy simulations of the TKE dissipation rate. Mixed layer deepening is simulated with a model of convection beneath lake ice. The model describes the structure of the stably stratified layer just beneath the ice with a stationary solution to the heat transfer equation; the structure of the entrainment layer is parameterized with a zero-order jump approach. The entrainment equation is derived from the mixed layer TKE budget and bulk mixed layer scaling. Entrainment regimes characteristic of convection beneath ice are analyzed. It is shown that if the Deardorff convective velocity scale is replaced with a scale incorporating the distributed buoyancy flux, the entrainment equation describing atmospheric and oceanic convective boundary layers also applies beneath the ice. Model predictions compare well with data from observations in a number of lakes. We propose and compare with observations an extension of the mixed layer model that allows for the inclusion of salinity. Although the salt concentration is low in most temperate and polar lakes, its dynamical effect can be significant close to the temperature of maximum density. (Less)

Observations of a quasi shear-free lacustrine convective boundary layer: Stratification and its implications on turbulence

[1] Convection due to surface cooling has been investigated in the surface boundary layer of a small lake under near-ideal conditions undisturbed by wind, large-scale currents, and differential cooling. Successive temperature microstructure profiles revealed a stable stratification in the lower bulk of the convective boundary layer despite strong cooling over the entire layer. Lateral heat fluxes as well as heat exchange with the thermocline could be excluded as driving mechanism of the observed stratification. Acoustic Doppler current profiler (ADCP) measurements indicated an asymmetric pattern of vertical velocities: strong downward plumes were observed upon a background of slow upflow. We suggest that this asymmetry allows cold water from the super-adiabatic surface layer to intrude at the base of the convective layer, thus causing the observed stratification. This in particular involves downward plumes that feature a relatively low entrainment rate in the center bulk of the convective layer. Corresponding large-eddy simulation studies, as well as thermistor string and ADCP data, were found consistent with this scenario. The dissipation rate of turbulent kinetic energy (TKE) was estimated on the basis of the temperature microstructure profiles and from the ADCP data. Mean dissipation rates of only about 20% of the surface buoyancy flux were typically identified. This finding is attributed to respectively low buoyant production rates of TKE, attenuated by strong convective plumes penetrating through the stable stratification in the lower bulk of the convective layer into the thermocline. INDEX TERMS: 4568 Oceanography: Physical: Turbulence, diffusion, and mixing processes; 4524 Oceanography: Physical: Fine structure and microstructure; 4572 Oceanography: Physical: Upper ocean processes; 4239 Oceanography: General: Limnology; KEYWORDS: convection, temperature microstructure, ADCP, stratification, turbulent kinetic energy, convective boundary layer

Radiatively driven convection in an ice-covered lake investigated by using temperature microstructure technique

[1] Convection in an ice-covered lake, driven by the absorption of solar radiation, is investigated by means of temperature microstructure technique. This type of convection typically occurs in spring, when melting snow on the ice cover enables solar radiation to penetrate into the water body. The diurnal dynamics of the stratification system of five distinct layers is analyzed by means of consecutive CTD profiles and with the aid of a one-dimensional model. The model solves the transfer equation of heat and salinity and includes convective procedures to react on density instabilities. This study is focused on the turbulent kinetic energy (TKE) balance. The stratification analysis reveals the importance of several processes for the TKE balance, namely: (1) the entrainment into the top layer from the convective layer below, (2) the inflow of water from melted ice, and (3) the volumetric solar heating. Enabled by the analysis of the temperature microstructure profiles, two TKE budgets are presented. The temporally averaged budget reveals a vertical distribution of generation and dissipation rate similar to the case of cooling-induced convection in a surface boundary layer. But contrary to this reference regime, a transition layer was found in the upper convective layer, where both rates drop back to zero toward the layer above. The second TKE budget is spatially averaged over the convective layer but resolves the diurnal dynamics. The generation rate and dissipation rate feature similar diurnal dynamics, where the dissipation lags on average by 1.5 hours. The temporal change rate of TKE was found to be on the same order of magnitude as the generation rate and the dissipation rate, while the export rate of TKE out of the convective layer was found to be less significant.

Assimilation of point SWE data into a distributed snow cover model comparing two contrasting methods

In alpine and high-latitude regions, water resource decision making often requires large-scale estimates of snow amounts and melt rates. Such estimates are available through distributed snow models which in some situations can be improved by assimilation of remote sensing observations. However, in regions with frequent cloud cover, complex topography, or large snow amounts satellite observations may feature information of limited quality. In this study, we examine whether assimilation of snow water equivalent (SWE) data from ground observations can improve model simulations in a region largely lacking reliable remote sensing observations. We combine the model output with the point data using three-dimensional sequential data assimilation methods, the ensemble Kalman filter, and statistical interpolation. The filter performance was assessed by comparing the simulation results against observed SWE and snow-covered fraction. We find that a method which assimilates fluxes (snowfall and melt rates computed from SWE) showed higher model performance than a control simulation not utilizing the filter algorithms. However, an alternative approach for updating the model results using the SWE data directly did not show a significantly higher performance than the control simulation. The results show that three-dimensional data assimilation methods can be useful for transferring information from point snow observations to the distributed snow model. Key Points Evaluating methods for assimilating snow observations into distributed models Assimilation can improve model skill also at locations without observations Assimilation of fluxes appears more successful than assimilation of states (Less)

Evaluating snow models with varying process representations for hydrological applications

Much effort has been invested in developing snow models over several decades, resulting in a wide variety of empirical and physically based snow models. For the most part, these models are built on similar principles. The greatest differences are found in how each model parameterizes individual processes (e.g., surface albedo and snow compaction). Parameterization choices naturally span a wide range of complexities. In this study, we evaluate the performance of different snow model parameterizations for hydrological applications using an existing multimodel energy-balance framework and data from two well-instrumented alpine sites with seasonal snow cover. We also include two temperature-index snow models and an intensive, physically based multilayer snow model in our analyses. Our results show that snow mass observations provide useful information for evaluating the ability of a model to predict snowpack runoff, whereas snow depth data alone are not. For snow mass and runoff, the energy-balance models appear transferable between our two study sites, a behavior which is not observed for snow surface temperature predictions due to site-specificity of turbulent heat transfer formulations. Errors in the input and validation data, rather than model formulation, seem to be the greatest factor affecting model performance. The three model types provide similar ability to reproduce daily observed snowpack runoff when appropriate model structures are chosen. Model complexity was not a determinant for predicting daily snowpack mass and runoff reliably. Our study shows the usefulness of the multimodel framework for identifying appropriate models under given constraints such as data availability, properties of interest and computational cost.

Influence of Initial Snowpack Properties on Runoff Formation during Rain-on-Snow Events

AbstractRain-on-snow (ROS) events have caused severe floods in mountainous areas in the recent past. Because of the complex interactions of physical processes, it is still difficult to accurately predict the effect of snow cover on runoff formation for an upcoming ROS event. In this study, a detailed physics-based energy balance snow cover model (SNOWPACK) was used to assess snow cover processes during more than 1000 historical ROS events at 116 locations in the Swiss Alps. The simulations of the mass and energy balance, liquid water flow, and the temporal evolution of structural properties of the snowpack were used to analyze runoff formation characteristics during ROS events. Initial liquid water content and snow depth at the onset of rainfall were found to influence the temporal dynamics, intensities, and cumulative amount of runoff. The meteorological forcing is modulated by processes within the snowpack, leading to an attenuation of runoff intensities for intense and short rain events and an amplifyi...