The development of stream temperature regression models at regional scales has regained some popularity over the past years. These models are used to predict stream temperature in ungauged catchments ...to assess the impact of human activities or climate change on riverine fauna over large spatial areas. A comprehensive literature review presented in this study shows that the temperature metrics predicted by the majority of models correspond to yearly aggregates, such as the popular annual maximum weekly mean temperature (MWMT). As a consequence, current models are often unable to predict the annual cycle of stream temperature, nor can the majority of them forecast the inter-annual variation of stream temperature. This study presents a new statistical model to estimate the monthly mean stream temperature of ungauged rivers over multiple years in an Alpine country (Switzerland). Contrary to similar models developed to date, which are mostly based on standard regression approaches, this one attempts to incorporate physical aspects into its structure. It is based on the analytical solution to a simplified version of the energy-balance equation over an entire stream network. Some terms of this solution cannot be readily evaluated at the regional scale due to the lack of appropriate data, and are therefore approximated using classical statistical techniques. This physics-inspired approach presents some advantages: (1) the main model structure is directly obtained from first principles, (2) the spatial extent over which the predictor variables are averaged naturally arises during model development, and (3) most of the regression coefficients can be interpreted from a physical point of view – their values can therefore be constrained to remain within plausible bounds. The evaluation of the model over a new freely available data set shows that the monthly mean stream temperature curve can be reproduced with a root-mean-square error (RMSE) of ±1.3 °C, which is similar in precision to the predictions obtained with a multi-linear regression model. We illustrate through a simple example how the physical aspects contained in the model structure can be used to gain more insight into the stream temperature dynamics at regional scales.
Observations from the Surface Heat Budget of the Arctic Ocean (SHEBA) are analyzed to develop a consistent data set suitable for the validation of snow and sea ice components used in climate models. ...Since the snow depth is a crucial variable to properly determine the ice thickness evolution, several methods are tested to estimate the actual snow depth at the exact location of the measured internal temperatures. Snow and ice thickness gauge measurements show high spatial variability at small spatial scales. Consequently, individual measurements of snow/ice thickness are not representative of the thickness at the locations where temperature profiles were measured. Observed skin temperatures and snow internal temperature profiles suggest that the mean winter snow cover at the reference mass balance site was thicker by 11 cm when compared with gauge observations at a small distance from that reference site. The mean winter snow cover thickness measured at the SHEBA mass balance site, Pittsburgh, is larger by a factor of 2.3 when compared to the snow depth derived from precipitation measurements. Assuming continuity of heat fluxes at the snow‐ice interface, an effective snow thermal conductivity of 0.50 Wm−1 K−1 is calculated. This is significantly higher than values generally used in climate models (0.31 Wm−1 K−1) or derived from in situ measurements (0.14 Wm−1 K−1) at SHEBA. Ocean heat fluxes, inferred from ice thickness and internal temperature measurements at various sites, are very consistent and match reasonably well those derived from turbulence measurements and a bulk formulation. A heat budget of surface fluxes shows a mean annual net imbalance of 1.5 Wm−2, with a mean energy deficit of 3.5 Wm−2 during winter and a mean surplus of 6.4 Wm−2 during summer.
Thermal diffusivity of snow is an important thermodynamic property associated with key hydrological phenomena such as snow melt and heat and water vapor exchange with the atmosphere. Direct ...determination of snow thermal diffusivity requires coupled point measurements of thermal conductivity and density, which continually change due to snow metamorphism. Traditional methods for determining these two quantities are generally limited by temporal resolution. In this study we present a method to determine the thermal diffusivity of snow with high temporal resolution using snow temperature profile measurements. High resolution (between 2.5 and 10cm at 1min) temperature measurements from the seasonal snow pack at the Plaine-Morte glacier in Switzerland are used as initial conditions and Neumann (heat flux) boundary conditions to numerically solve the one-dimensional heat equation and iteratively optimize for thermal diffusivity. The implementation of Neumann boundary conditions and a t-test, ensuring statistical significance between solutions of varied thermal diffusivity, are important to help constrain thermal diffusivity such that spurious high and low values as seen with Dirichlet (temperature) boundary conditions are reduced. The results show that time resolved thermal diffusivity can be determined from temperature measurements of seasonal snow and support density-based empirical parameterizations for thermal conductivity.
Elevated in-stream temperature has led to a surge in the occurrence of parasitic intrusion proliferative kidney disease and has resulted in fish kills throughout Switzerland’s waterways. Data from ...distributed temperature sensing (DTS) in-stream measurements for three cloud-free days in August 2007 over a 1260 m stretch of the Boiron de Morges River in southwest Switzerland were used to calibrate and validate a physically based one-dimensional stream temperature model. Stream temperature response to three distinct riparian conditions were then modeled: open, in-stream reeds, and forest cover. Simulation predicted a mean peak stream temperature increase of 0.7 °C if current vegetation was removed, an increase of 0.1 °C if dense reeds covered the entire stream reach, and a decrease of 1.2 °C if a mature riparian forest covered the entire reach. Understanding that full vegetation canopy cover is the optimal riparian management option for limiting stream temperature, in-stream reeds, which require no riparian set-aside and grow very quickly, appear to provide substantial thermal control, potentially useful for land-use management.
A new method for measuring air temperature profiles in the atmospheric boundary layer at high spatial and temporal resolution is presented. The measurements are based on Raman scattering distributed ...temperature sensing (DTS) with a fiber optic cable attached to a tethered balloon. These data were used to estimate the height of the stable nocturnal boundary layer. The experiment was successfully deployed during a two-day campaign in September 2009, providing evidence that DTS is well suited for this atmospheric application. Observed stable temperature profiles exhibit an exponential shape confirming similarity concepts of the temperature inversion close to the surface. The atmospheric mixing height (MH) was estimated to vary between 5 m and 50 m as a result of the nocturnal boundary layer evolution. This value is in good agreement with the MH derived from concurrent Radon-222 (222Rn) measurements and in previous studies.
Stream temperature and discharge are key hydrological variables for ecosystem and water resource management and are particularly sensitive to climate warming. Despite the wealth of meteorological and ...hydrological data, few studies have quantified observed stream temperature trends in the Alps. This study presents a detailed analysis of stream temperature and discharge in 52 catchments in Switzerland, a country covering a wide range of alpine and lowland hydrological regimes. The influence of discharge, precipitation, air temperature, and upstream lakes on stream temperatures and their temporal trends is analysed from multi-decadal to seasonal timescales. Stream temperature has significantly increased over the past 5 decades, with positive trends for all four seasons. The mean trends for the last 20 years are +0.37±0.11 ∘C per decade for water temperature, resulting from the joint effects of trends in air temperature (+0.39±0.14 ∘C per decade), discharge (-10.1±4.6 % per decade), and precipitation (-9.3±3.4 % per decade). For a longer time period (1979–2018), the trends are +0.33±0.03 ∘C per decade for water temperature, +0.46±0.03°C per decade for air temperature, -3.0±0.5 % per decade for discharge, and -1.3±0.5 % per decade for precipitation. Furthermore, we show that snow and glacier melt compensates for air temperature warming trends in a transient way in alpine streams. Lakes, on the contrary, have a strengthening effect on downstream water temperature trends at all elevations. Moreover, the identified stream temperature trends are shown to have critical impacts on ecological and economical temperature thresholds (the spread of fish diseases and the usage of water for industrial cooling), especially in lowland rivers, suggesting that these waterways are becoming more vulnerable to the increasing air temperature forcing. Resilient alpine rivers are expected to become more vulnerable to warming in the near future due to the expected reductions in snow- and glacier-melt inputs. A detailed mathematical framework along with the necessary source code are provided with this paper.
A new multilayer sigma‐coordinate thermodynamic sea ice model is presented. The model employs a coordinate transformation which maps the thickness of the snow and ice slabs onto unity intervals and ...thus enables automatic relayering when the snow or ice thickness changes. This is done through an advection term which naturally appears in the transformed energy equation. Unlike previous approaches, the model conserves the total energy per layer (Jm−2 as opposed to Jm−3), which takes into account the changes in internal energy associated with thickness changes. This model was then tested against observational data from the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment in the context of the Sea Ice Model Intercomparison Project, Part 2, Thermodynamics (SIMIP2). In general, the model reproduces the observed internal snow‐ice temperature and the ice thickness evolution very well. Results show that the ice thickness evolution is very sensitive to the ocean heat flux (Focn) and the thickness of the snow cover in winter. Given that the spatial variability in snow depth at small scale is large, the specification of the snow depth temporal evolution is crucial for an intercomparison project. Since Focn in SIMIP2 is calculated as a residual of the observed basal growth rates and heat conduction, the salinity of newly formed ice used in the simulations must be consistent with that used to derive Focn. Simulated and observed snow surface and snow‐ice interface temperatures suggest that not enough heat is conducted through the snow layer even when using a snow thermal conductivity as large as 0.50 Wm−1 K−1 (value derived from observed snow and ice internal temperature profiles). A surface energy budget of simulated and observed energy fluxes confirms this finding.
River ecosystems are highly sensitive to climate change and projected future increase in air temperature is expected to increase the stress for these ecosystems. Rivers are also an important ...socio-economic factor impacting, amongst others, agriculture, tourism, electricity production, and drinking water supply and quality. In addition to changes in water availability, climate change will impact river temperature. This study presents a detailed analysis of river temperature and discharge evolution over the 21st century in Switzerland. In total, 12 catchments are studied, situated both on the lowland Swiss Plateau and in the Alpine regions. The impact of climate change is assessed using a chain of physics-based models forced with the most recent climate change scenarios for Switzerland including low-, mid-, and high-emission pathways. The suitability of such models is discussed in detail and recommendations for future improvements are provided. The model chain is shown to provide robust results, while remaining limitations are identified. These are mechanisms missing in the model to correctly simulate water temperature in Alpine catchments during the summer season. A clear warming of river water is modelled during the 21st century. At the end of the century (2080–2090), the median annual river temperature increase ranges between +0.9 ∘C for low-emission and +3.5 ∘C for high-emission scenarios for both lowland and Alpine catchments. At the seasonal scale, the warming on the lowland and in the Alpine regions exhibits different patterns. For the lowland the summer warming is stronger than the one in winter but is still moderate. In Alpine catchments, only a very limited warming is expected in winter. The period of maximum discharge in Alpine catchments, currently occurring during mid-summer, will shift to earlier in the year by a few weeks (low emission) or almost 2 months (high emission) by the end of the century. In addition, a noticeable soil warming is expected in Alpine regions due to glacier and snow cover decrease. All results of this study are provided with the corresponding source code used for this paper.
The mountain cryosphere of mainland Europe is recognized to have important impacts on a range of environmental processes. In this paper, we provide an overview on the current knowledge on snow, ...glacier, and permafrost processes, as well as their past, current, and future evolution. We additionally provide an assessment of current cryosphere research in Europe and point to the different domains requiring further research. Emphasis is given to our understanding of climate–cryosphere interactions, cryosphere controls on physical and biological mountain systems, and related impacts. By the end of the century, Europe's mountain cryosphere will have changed to an extent that will impact the landscape, the hydrological regimes, the water resources, and the infrastructure. The impacts will not remain confined to the mountain area but also affect the downstream lowlands, entailing a wide range of socioeconomical consequences. European mountains will have a completely different visual appearance, in which low- and mid-range-altitude glaciers will have disappeared and even large valley glaciers will have experienced significant retreat and mass loss. Due to increased air temperatures and related shifts from solid to liquid precipitation, seasonal snow lines will be found at much higher altitudes, and the snow season will be much shorter than today. These changes in snow and ice melt will cause a shift in the timing of discharge maxima, as well as a transition of runoff regimes from glacial to nival and from nival to pluvial. This will entail significant impacts on the seasonality of high-altitude water availability, with consequences for water storage and management in reservoirs for drinking water, irrigation, and hydropower production. Whereas an upward shift of the tree line and expansion of vegetation can be expected into current periglacial areas, the disappearance of permafrost at lower altitudes and its warming at higher elevations will likely result in mass movements and process chains beyond historical experience. Future cryospheric research has the responsibility not only to foster awareness of these expected changes and to develop targeted strategies to precisely quantify their magnitude and rate of occurrence but also to help in the development of approaches to adapt to these changes and to mitigate their consequences. Major joint efforts are required in the domain of cryospheric monitoring, which will require coordination in terms of data availability and quality. In particular, we recognize the quantification of high-altitude precipitation as a key source of uncertainty in projections of future changes. Improvements in numerical modeling and a better understanding of process chains affecting high-altitude mass movements are the two further fields that – in our view – future cryospheric research should focus on.
Modelling and forecasting wind-driven redistribution of
snow in mountainous regions with its implications on avalanche danger,
mountain hydrology or flood hazard is still a challenging task often ...lacking
in essential details. Measurements of drifting and blowing snow for
improving process understanding and model validation are typically limited
to point measurements at meteorological stations, providing no information
on the spatial variability of horizontal mass fluxes or even the vertically
integrated mass flux. We present a promising application of a compact and
low-cost radar system for measuring and characterizing larger-scale
(hundreds of metres) snow redistribution processes, specifically blowing
snow off a mountain ridge. These measurements provide valuable information
of blowing snow velocities, frequency of occurrence, travel distances and
turbulence characteristics. Three blowing snow events are investigated, two
in the absence of precipitation and one with concurrent precipitation.
Blowing snow velocities measured with the radar are validated by comparison
against wind velocities measured with a 3D ultra-sonic anemometer. A minimal
blowing snow travel distance of 60–120 m is reached 10–20 % of the
time during a snow storm, depending on the strength of the storm event. The
relative frequency of transport distances decreases exponentially above the
minimal travel distance, with a maximum measured distance of 280 m. In a
first-order approximation, the travel distance increases linearly with the
wind velocity, allowing for an estimate of a threshold wind velocity for
snow particle entrainment and transport of 7.5–8.8 m s−1, most
likely depending on the prevailing snow cover properties. Turbulence
statistics did not allow a conclusion to be drawn on whether low-level,
low-turbulence jets or highly turbulent gusts are more effective in
transporting blowing snow over longer distances, but highly turbulent flows
are more likely to bring particles to greater heights and thus influence
cloud processes. Drone-based photogrammetry measurements of the spatial snow
height distribution revealed that increased snow accumulation in the lee of the
ridge is the result of the measured local blowing snow conditions.
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