scholarly journals Spatial and temporal patterns of snowmelt refreezing in a Himalayan catchment

2021 ◽  
pp. 1-21
Author(s):  
Sanne B. M. Veldhuijsen ◽  
Remco J. de Kok ◽  
Emmy E. Stigter ◽  
Jakob F. Steiner ◽  
Tuomo M. Saloranta ◽  
...  
Keyword(s):  
Air Temperature ◽  
Snow Depth ◽  
Spatial And Temporal Patterns ◽  
Complete Understanding ◽  
Meteorological Forcing ◽  
Highly Sensitive ◽  
Snow Model ◽  
The Himalaya ◽  
Daily Time ◽  
Made In

Abstract Recent progress has been made in quantifying snowmelt in the Himalaya. Although the conditions are favorable for refreezing, little is known about the spatial variability of meltwater refreezing, hindering a complete understanding of seasonal snowmelt dynamics. This study aims to improve our understanding about how refreezing varies in space and time. We simulated refreezing with the seNorge (v2.0) snow model for the Langtang catchment, Nepalese Himalaya, covering a 5-year period. Meteorological forcing data were derived from a unique elaborate network of meteorological stations and high-resolution meteorological simulations. The results show that the annual catchment average refreezing amounts to 122 mm w.e. (21% of the melt), and varies strongly in space depending on elevation and aspect. In addition, there is a seasonal altitudinal variability related to air temperature and snow depth, with most refreezing during the early melt season. Substantial intra-annual variability resulted from fluctuations in snowfall. Daily refreezing simulations decreased by 84% (annual catchment average of 19 mm w.e.) compared to hourly simulations, emphasizing the importance of using sub-daily time steps to capture melt–refreeze cycles. Climate sensitivity experiments revealed that refreezing is highly sensitive to changes in air temperature as a 2°C increase leads to a refreezing decrease of 35%.

Spatial and temporal patterns of snowmelt refreezing in a Himalayan catchment

2021 ◽  
Author(s):  
Sanne Veldhuijsen ◽  
Remco De Kok ◽  
Emmy Stigter ◽  
Jakob Steiner ◽  
Tuomo Saloranta ◽  
...  
Keyword(s):  
Air Temperature ◽  
Annual Runoff ◽  
Polar Regions ◽  
Spatial And Temporal Patterns ◽  
Meteorological Forcing ◽  
Snow Modeling ◽  
Highly Sensitive ◽  
Snow Model ◽  
The Himalaya

<p>Seasonal snow contributes significantly to the annual runoff in the Himalaya and both timing and volume are important for downstream users.  In  polar regions, meltwater refreezing within snowpacks has been well-studied. While the conditions in the Himalaya are considered favorable for refreezing,<strong> </strong>little is known about refreezing in this region, hindering a complete understanding of seasonal snowmelt dynamics. In this study, we simulated refreezing with the seNorge (v2.0) snow model for the Langtang catchment in the Nepalese Himalaya covering a 5-year period. Thereby, we aim to improve our understanding about how refreezing varies in space and time and to provide a framework for future snow modeling studies. The first part of this study focuses extensively on developing meteorological forcing data, which were derived from an unique elaborate network of meteorological stations and high-resolution meteorological simulations. The snow model was validated against in-situ snow observations and snow cover satellite data. In the second part of this study, we analyze the spatial and temporal refreezing patterns, and attempt to identify possible driving factors. The results show that the annual average refreezing amounts to 122 mm (21% of the total melt). We found that the magnitude of refreezing varies strongly in space depending on elevation and aspect. In addition, there is a strong seasonal altitudinal variability related to air temperature and snow depth, with most refreezing during the early melt season. We also found a substantial intra-annual variability, which mainly results from fluctuations of snowfall, highlighting the importance of using multi-year time series in refreezing assessments. Daily refreezing simulations decreased by 84% (to an average 19 mm year<sup>-1</sup>) compared to hourly simulations, emphasizing the importance of using sub-daily time steps to capture diurnal melt-refreeze cycles. Climate sensitivity experiments revealed that refreezing is highly sensitive to future changes in air temperature, as a temperature increase of 2°C leads to a refreezing decrease of 35%. We conclude that including refreezing with a sub-daily temporal resolution is highly relevant for understanding snow dynamics in the current and future climate of the Himalaya.</p><p> </p>

Simulation of the internal temperature in the Passol Laboratory, University of Debrecen

2012 ◽  
Vol 3 (1) ◽  
pp. 63-73 ◽  
Author(s):  
I. Csáky ◽  
F. Kalmár
Keyword(s):  
Temperature Variation ◽  
Air Temperature ◽  
Indoor Air ◽  
Storage Capacity ◽  
Building Structures ◽  
Internal Temperature ◽  
The One ◽  
Heavy Structure ◽  
East West ◽  
Made In

Abstract Nowadays the facades of newly built buildings have significant glazed surfaces. The solar gains in these buildings can produce discomfort caused by direct solar radiation on the one hand and by the higher indoor air temperature on the other hand. The amplitude of the indoor air temperature variation depends on the glazed area, orientation of the facade and heat storage capacity of the building. This paper presents the results of a simulation, which were made in the Passol Laboratory of University of Debrecen in order to define the internal temperature variation. The simulation proved that the highest amplitudes of the internal temperature are obtained for East orientation of the facade. The upper acceptable limit of the internal air temperature is exceeded for each analyzed orientation: North, South, East, West. Comparing different building structures, according to the obtained results, in case of the heavy structure more cooling hours are obtained, but the energy consumption for cooling is lower.

Micro-climatological influences on temperature condition in an old people’s home in Helsinki, Finland, caused by extended heat-waves 

2021 ◽  
Author(s):  
Achim Drebs ◽  
Tim Sinsel ◽  
Kirsti Jylhä
Keyword(s):  
Air Temperature ◽  
Heat Waves ◽  
Daily Maximum ◽  
Old People ◽  
Concrete Walls ◽  
Meteorological Forcing ◽  
Clear Sky ◽  
Wave Event ◽  
Construction Type ◽  
Maximum Air Temperature

<p>In our research we describe the micro-climatological influences of two heat-waves around and the air temperature development in a certain old people’s home in Helsinki, Finland. The stand-alone six-storey concrete building was erected in the late 1970’s and represents the prevailing construction type of this area. The building is located on a slightly southwards declining slope.</p><p>The first simulation used real meteorological forcing-data from the heat-wave event in summer 2018, which lasted from July, 13<sup>th</sup> until August, 5<sup>th</sup>. In this period the daily maximum air temperature reached almost every day 25 °C and more, sometimes even more than 30 °C. All air temperature, wind, humidity, and solar radiation (cloudiness) measurements were conducted at a near-by synoptical weather station.</p><p>The second simulation used fourteen-day constructed meteorological forcing-data, based on a clear-sky, slowly increasing air temperature, higher than normal humidity, and low wind conditions assumption starting on July, 13<sup>th</sup> (day 194 of the year).</p><p>We used the holistic ENVI-met simulation soft-ware to simulate the physical environment around the old people’s home and especially the energy fluxes inside the concrete walls to explain the needs for cooling demands.</p><p>The research is part of the HEATCLIM-project financed by the Academy of Finland Science Program CLIHE (2020-2023).</p>

scholarly journals Simulation of Snow on Arctic Sea Ice Using a Coupled Snow–Ice Model

2010 ◽  
Vol 11 (1) ◽  
pp. 199-210 ◽  
Author(s):  
Yi-Ching Chung ◽  
Stéphane Bélair ◽  
Jocelyn Mailhot
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Snow Depth ◽  
Single Layer ◽  
Coupled System ◽  
The Arctic ◽  
Ice Thickness ◽  
The Arctic Ocean ◽  
Snow Model ◽  
Ice Model

Abstract The new Recherche Prévision Numérique (NEW-RPN) model, a coupled system including a multilayer snow thermal model (SNTHERM) and the sea ice model currently used in the Meteorological Service of Canada (MSC) operational forecasting system, was evaluated in a one-dimensional mode using meteorological observations from the Surface Heat Budget of the Arctic Ocean (SHEBA)’s Pittsburgh site in the Arctic Ocean collected during 1997/98. Two parameters simulated by NEW-RPN (i.e., snow depth and ice thickness) are compared with SHEBA’s observations and with simulations from RPN, MSC’s current coupled system (the same sea ice model and a single-layer snow model). Results show that NEW-RPN exhibits better agreement for the timing of snow depletion and for ice thickness. The profiles of snow thermal conductivity in NEW-RPN show considerable variability across the snow layers, but the mean value (0.39 W m−1 K−1) is within the range of reported observations for SHEBA. This value is larger than 0.31 W m−1 K−1, which is commonly used in single-layer snow models. Of particular interest in NEW-RPN’s simulation is the strong temperature stratification of the snowpack, which indicates that a multilayer snow model is needed in the SHEBA scenario. A sensitivity analysis indicates that snow compaction is also a crucial process for a realistic representation of the snowpack within the snow/sea ice system. NEW-RPN’s overestimation of snow depth may be related to other processes not included in the study, such as small-scale horizontal variability of snow depth and blowing snow processes.

scholarly journals Assimilation of snow cover and snow depth into a snow model to estimate snow water equivalent and snowmelt runoff in a Himalayan catchment

2017 ◽  
Vol 11 (4) ◽  
pp. 1647-1664 ◽  
Author(s):  
Emmy E. Stigter ◽  
Niko Wanders ◽  
Tuomo M. Saloranta ◽  
Joseph M. Shea ◽  
Marc F. P. Bierkens ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Snow Cover ◽  
Climate Sensitivity ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Snowmelt Runoff ◽  
Snow Water ◽  
Snow Model

Abstract. Snow is an important component of water storage in the Himalayas. Previous snowmelt studies in the Himalayas have predominantly relied on remotely sensed snow cover. However, snow cover data provide no direct information on the actual amount of water stored in a snowpack, i.e., the snow water equivalent (SWE). Therefore, in this study remotely sensed snow cover was combined with in situ observations and a modified version of the seNorge snow model to estimate (climate sensitivity of) SWE and snowmelt runoff in the Langtang catchment in Nepal. Snow cover data from Landsat 8 and the MOD10A2 snow cover product were validated with in situ snow cover observations provided by surface temperature and snow depth measurements resulting in classification accuracies of 85.7 and 83.1 % respectively. Optimal model parameter values were obtained through data assimilation of MOD10A2 snow maps and snow depth measurements using an ensemble Kalman filter (EnKF). Independent validations of simulated snow depth and snow cover with observations show improvement after data assimilation compared to simulations without data assimilation. The approach of modeling snow depth in a Kalman filter framework allows for data-constrained estimation of snow depth rather than snow cover alone, and this has great potential for future studies in complex terrain, especially in the Himalayas. Climate sensitivity tests with the optimized snow model revealed that snowmelt runoff increases in winter and the early melt season (December to May) and decreases during the late melt season (June to September) as a result of the earlier onset of snowmelt due to increasing temperature. At high elevation a decrease in SWE due to higher air temperature is (partly) compensated by an increase in precipitation, which emphasizes the need for accurate predictions on the changes in the spatial distribution of precipitation along with changes in temperature.

scholarly journals Toxicity testing: Non-animal approaches and safety science

2014 ◽  
Vol 36 (3) ◽  
pp. 19-25 ◽  
Author(s):  
Fiona Reynolds ◽  
Carl Westmoreland ◽  
Julia Fentem
Keyword(s):  
Safety Assessment ◽  
Toxicity Testing ◽  
Chemical Safety ◽  
Research Investment ◽  
Highly Sensitive ◽  
Safety Science ◽  
Modelling Techniques ◽  
Animal Tests ◽  
Made In

New informatics capabilities and computational and mathematical modelling techniques, used in combination with highly sensitive molecular biology and mechanistic chemistry approaches, are transforming the way in which we assess the safety of chemicals and products. In recent years, good progress has been made in replacing some of the animal tests required for regulatory purposes with methods using cells and tissues in vitro. Nevertheless, big scientific challenges remain in developing relevant non-animal models able to predict the effects of chemicals which are absorbed systemically. The greatest breakthroughs in non-animal approaches for chemical safety assessment will most likely result from continued multi-disciplinary research investment in predictive (integrative and systems) biology. Some of our current research in this area is described in the present article.

scholarly journals Recognized and Emerging Features of Erythropoietic and X-Linked Protoporphyria

Diagnostics ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 151
Author(s):  
Elena Di Pierro ◽  
Francesca Granata ◽  
Michele De Canio ◽  
Mariateresa Rossi ◽  
Andrea Ricci ◽  
...  
Keyword(s):  
Biosynthetic Pathway ◽  
Aminolevulinic Acid ◽  
Protoporphyrin Ix ◽  
Limiting Factor ◽  
Zinc Protoporphyrin ◽  
Complete Understanding ◽  
Inherited Disorders ◽  
Rate Limiting ◽  
Systemic Accumulation ◽  
Made In

Erythropoietic protoporphyria (EPP) and X-linked protoporphyria (XLP) are inherited disorders resulting from defects in two different enzymes of the heme biosynthetic pathway, i.e., ferrochelatase (FECH) and delta-aminolevulinic acid synthase-2 (ALAS2), respectively. The ubiquitous FECH catalyzes the insertion of iron into the protoporphyrin ring to generate the final product, heme. After hemoglobinization, FECH can utilize other metals like zinc to bind the remainder of the protoporphyrin molecules, leading to the formation of zinc protoporphyrin. Therefore, FECH deficiency in EPP limits the formation of both heme and zinc protoporphyrin molecules. The erythroid-specific ALAS2 catalyses the synthesis of delta-aminolevulinic acid (ALA), from the union of glycine and succinyl-coenzyme A, in the first step of the pathway in the erythron. In XLP, ALAS2 activity increases, resulting in the amplified formation of ALA, and iron becomes the rate-limiting factor for heme synthesis in the erythroid tissue. Both EPP and XLP lead to the systemic accumulation of protoporphyrin IX (PPIX) in blood, erythrocytes, and tissues causing the major symptom of cutaneous photosensitivity and several other less recognized signs that need to be considered. Although significant advances have been made in our understanding of EPP and XLP in recent years, a complete understanding of the factors governing the variability in clinical expression and the severity (progression) of the disease remains elusive. The present review provides an overview of both well-established facts and the latest findings regarding these rare diseases.

scholarly journals The Rise of the OM-LoC: Opto-Microfluidic Enabled Lab-on-Chip

Micromachines ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1467
Author(s):  
Harry Dawson ◽  
Jinane Elias ◽  
Pascal Etienne ◽  
Sylvie Calas-Etienne
Keyword(s):  
Low Cost ◽  
Optical Components ◽  
New Era ◽  
Lab On Chip ◽  
Highly Sensitive ◽  
Multiple Challenges ◽  
On Chip ◽  
Optical Circuits ◽  
Made In

The integration of optical circuits with microfluidic lab-on-chip (LoC) devices has resulted in a new era of potential in terms of both sample manipulation and detection at the micro-scale. On-chip optical components increase both control and analytical capabilities while reducing reliance on expensive laboratory photonic equipment that has limited microfluidic development. Notably, in-situ LoC devices for bio-chemical applications such as diagnostics and environmental monitoring could provide great value as low-cost, portable and highly sensitive systems. Multiple challenges remain however due to the complexity involved with combining photonics with micro-fabricated systems. Here, we aim to highlight the progress that optical on-chip systems have made in recent years regarding the main LoC applications: (1) sample manipulation and (2) detection. At the same time, we aim to address the constraints that limit industrial scaling of this technology. Through evaluating various fabrication methods, material choices and novel approaches of optic and fluidic integration, we aim to illustrate how optic-enabled LoC approaches are providing new possibilities for both sample analysis and manipulation.

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