scholarly journals The Swiss Alpine zero degree line: methods, past evolution, sensitivities

2021 ◽  
Author(s):  
Simon C. Scherrer ◽  
Stefanie Gubler ◽  
Kathrin Wehrli ◽  
Andreas M. Fischer ◽  
Sven Kotlarski

<p>The near-surface zero degree line (ZDL) is a key isotherm in mountain regions worldwide, but a detailed analysis of methods for the ZDL determination, their properties and applicability in a changing climate is missing. We here test different approaches to determine the near-surface ZDL on a monthly scale in the Swiss Alps. A non-linear profile yields more robust and more realistic ZDLs than a linear profile throughout the year and especially in the winter-half year when frequent inversions disqualify a linear assumption. In the period 1871-2019, the Swiss ZDL has risen significantly in every calendar month: In northern Switzerland, the monthly ZDL increases generally amount to 300-400 m with smaller values in April and September (200-250 m) and a larger value in October (almost 500 m). The largest increases of 600-700 m but also very large uncertainties (±400 m, 95% confidence interval) are found in December and January. The trends have accelerated in the last decades especially in spring and summer. The ZDL has increased by ~160 m per °C warming in the summer-half year and up to 340±45 m/°C in winter months. In southern Switzerland, ZDL trends and temperature scalings are somewhat smaller, especially in winter. Sensitivity analyses using a simple shift of the non-linear temperature profile suggest that the winter ZDL-temperature scalings are at a record high today or will reach it in the near future, and are expected to decrease with a strong future warming. Nevertheless, the cumulative ZDL increase for strong warming is considerably larger in winter than in summer. Based on a few key criteria, we also present best practises to determine the ZDL in mountain regions worldwide. The outlined methods lay a foundation for the analysis of further isotherms and to study the future ZDL evolution based on climate scenario data.</p>

2020 ◽  
Author(s):  
Simon C. Scherrer ◽  
Sven Kotlarski

<p>The monitoring of near-surface temperature is a fundamental task of climatology that remains especially challenging in mountain regions. Here we assess the regional monitoring capabilities of modern reanalysis products in the well-monitored northern Swiss Alps during the last 20 to almost 60 years. Monthly and seasonal 2 m air temperature (T2m) anomalies of the global ERA5 and the three regional reanalysis products HARMONIE, MESCAN-SURFEX and COSMO-REA6 are evaluated against high quality in situ observational data for a low elevation (foothills) mean, and a high elevation (Alpine) mean. All reanalysis products show a good year-round performance for the foothills with the global reanalysis ERA5 showing the best overall performance. The high-resolution regional reanalysis COSMO-REA6 clearly performs best for the Alpine mean, especially in winter. Most reanalysis data sets show deficiencies at high elevations in winter and considerably overestimate recent T2m trends in winter. This stresses the fact that even in the most recent decades utmost care is required when using reanalysis data for near-surface temperature trend assessments in mountain regions. Our results indicate that a high-resolution model topography is an important prerequisite for an adequate monitoring of winter T2m using reanalysis data at high elevations in the Alps. Assimilating T2m remains challenging in highly complex terrain. The remaining shortcomings of modern reanalyses also highlight the continued need for a reliable and dense in situ observational monitoring network in mountain regions.</p><p> </p>


2017 ◽  
Vol 11 (1) ◽  
pp. 585-607 ◽  
Author(s):  
Anna Haberkorn ◽  
Nander Wever ◽  
Martin Hoelzle ◽  
Marcia Phillips ◽  
Robert Kenner ◽  
...  

Abstract. In this study we modelled the influence of the spatially and temporally heterogeneous snow cover on the surface energy balance and thus on rock temperatures in two rugged, steep rock walls on the Gemsstock ridge in the central Swiss Alps. The heterogeneous snow depth distribution in the rock walls was introduced to the distributed, process-based energy balance model Alpine3D with a precipitation scaling method based on snow depth data measured by terrestrial laser scanning. The influence of the snow cover on rock temperatures was investigated by comparing a snow-covered model scenario (precipitation input provided by precipitation scaling) with a snow-free (zero precipitation input) one. Model uncertainties are discussed and evaluated at both the point and spatial scales against 22 near-surface rock temperature measurements and high-resolution snow depth data from winter terrestrial laser scans.In the rough rock walls, the heterogeneously distributed snow cover was moderately well reproduced by Alpine3D with mean absolute errors ranging between 0.31 and 0.81 m. However, snow cover duration was reproduced well and, consequently, near-surface rock temperatures were modelled convincingly. Uncertainties in rock temperature modelling were found to be around 1.6 °C. Errors in snow cover modelling and hence in rock temperature simulations are explained by inadequate snow settlement due to linear precipitation scaling, missing lateral heat fluxes in the rock, and by errors caused by interpolation of shortwave radiation, wind and air temperature into the rock walls.Mean annual near-surface rock temperature increases were both measured and modelled in the steep rock walls as a consequence of a thick, long-lasting snow cover. Rock temperatures were 1.3–2.5 °C higher in the shaded and sunny rock walls, while comparing snow-covered to snow-free simulations. This helps to assess the potential error made in ground temperature modelling when neglecting snow in steep bedrock.


2021 ◽  
Vol 32 ◽  
pp. 45-62
Author(s):  
Mohamed Khodjet Kesba ◽  
Noureddine El Meiche ◽  
A. Benkhedda

The influence of linear and non-linear temperature and moisture concentration distribution on the stress distribution was studied for metal/ceramic sandwich plate with transverse cracks. An interlaminar adhesive layer between two different layers is taken into account which transferring the normal stress and the interlaminar shear stress. The validation of the used model was done with the comparison of the stiffness reduction as a function of crack density and the experimental data. A comparison showed that a satisfactory qualitative and quantitative agreement was obtained. The temperature and moisture concentration variation are studied using the linear and non-linear distribution around the cracks to predict the stress distributions along the axis x. Finally, it observed through this study that the variations of the thermal and moisture concentration distribution largely impact the stress distribution for a sandwich plate with transverse cracks in the central layer and also with different mechanical properties of each layers.


1981 ◽  
Vol 93 ◽  
pp. 191-206
Author(s):  
Daiichiro Sugimoto ◽  
Shigeki Miyaji

Shell flashes take place both in deep interior of red giant stars and near surface of accreting white dwarfs. Theories of shell flashes have been thus far presented piece by piece in different papers. It is the purpose of the present review to construct and generalize them in order to reach better understanding. A non-linear yet almost analytical theory is presented which treats the development of the shell flash in finite amplitude. Recurrence of the shell flashes is also shown to be well understood as a non-linear oscillation in dissipative system which tends to be its limit cycle. As a result strength of the peak energy-generation and recurrence time of the shell flashes are related with mass of the accreting white dwarfs, accretion rate, etc.


2007 ◽  
Vol 8 (4) ◽  
pp. 910-921 ◽  
Author(s):  
Nicola Montaldo ◽  
John D. Albertson ◽  
Marco Mancini

Abstract In the presence of uncertain initial conditions and soil hydraulic properties, land surface model (LSM) performance can be significantly improved by the assimilation of periodic observations of certain state variables, such as the near-surface soil moisture (θg), as observed from a remote platform. In this paper the possibility of merging observations and the model optimally for providing robust predictions of root-zone soil moisture (θ2) is demonstrated. An assimilation approach that assimilates θg through the ensemble Kalman filter (EnKF) and provides a physics-based update of θ2 is developed. This approach, as with other common soil moisture assimilation approaches, may fail when a key LSM parameter, for example, the saturated hydraulic conductivity (ks), is estimated poorly. This leads to biased model errors producing a violation of a main assumption (model errors with zero mean) of the EnKF. For overcoming this model bias an innovative assimilation approach is developed that accepts this violation in the early model run times and dynamically calibrates all the components of the ks ensemble as a function of the persistent bias in root-zone soil moisture, allowing one to remove the model bias, restore the fidelity to the EnKF requirements, and reduce the model uncertainty. The robustness of the proposed approach is also examined in sensitivity analyses.


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