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>

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%.

scholarly journals Spatial expression pattern of serine proteases in the blood fluke Schistosoma mansoni determined by fluorescence RNA in situ hybridization

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Lenka Ulrychová ◽  
Pavel Ostašov ◽  
Marta Chanová ◽  
Michael Mareš ◽  
Martin Horn ◽  
...  
Keyword(s):  
In Situ Hybridization ◽  
Schistosoma Mansoni ◽  
Rna Sequencing ◽  
Serine Proteases ◽  
Expression Patterns ◽  
High Sensitivity ◽  
Host Parasite Interactions ◽  
Highly Sensitive ◽  
Host Parasite

Abstract Background The blood flukes of genus Schistosoma are the causative agent of schistosomiasis, a parasitic disease that infects more than 200 million people worldwide. Proteases of schistosomes are involved in critical steps of host–parasite interactions and are promising therapeutic targets. We recently identified and characterized a group of S1 family Schistosoma mansoni serine proteases, including SmSP1 to SmSP5. Expression levels of some SmSPs in S. mansoni are low, and by standard genome sequencing technologies they are marginally detectable at the method threshold levels. Here, we report their spatial gene expression patterns in adult S. mansoni by the high-sensitivity localization assay. Methodology Highly sensitive fluorescence in situ RNA hybridization (FISH) was modified and used for the localization of mRNAs encoding individual SmSP proteases (including low-expressed SmSPs) in tissues of adult worms. High sensitivity was obtained due to specifically prepared tissue and probes in combination with the employment of a signal amplification approach. The assay method was validated by detecting the expression patterns of a set of relevant reference genes including SmCB1, SmPOP, SmTSP-2, and Sm29 with localization formerly determined by other techniques. Results FISH analysis revealed interesting expression patterns of SmSPs distributed in multiple tissues of S. mansoni adults. The expression patterns of individual SmSPs were distinct but in part overlapping and were consistent with existing transcriptome sequencing data. The exception were genes with significantly low expression, which were also localized in tissues where they had not previously been detected by RNA sequencing methods. In general, SmSPs were found in various tissues including reproductive organs, parenchymal cells, esophagus, and the tegumental surface. Conclusions The FISH-based assay provided spatial information about the expression of five SmSPs in adult S. mansoni females and males. This highly sensitive method allowed visualization of low-abundantly expressed genes that are below the detection limits of standard in situ hybridization or by RNA sequencing. Thus, this technical approach turned out to be suitable for sensitive localization studies and may also be applicable for other trematodes. The results suggest that SmSPs may play roles in diverse processes of the parasite. Certain SmSPs expressed at the surface may be involved in host–parasite interactions. Graphic abstract

A highly sensitive chlorine gas sensor and enhanced thermal DC electrical conductivity from polypyrrole/silicon carbide nanocomposites

RSC Advances ◽  
2016 ◽  
Vol 6 (87) ◽  
pp. 84200-84208 ◽  
Author(s):  
Adil Sultan ◽  
Sharique Ahmad ◽  
Faiz Mohammad
Keyword(s):  
Electrical Conductivity ◽  
Silicon Carbide ◽  
Gas Sensor ◽  
Dodecylbenzenesulfonic Acid ◽  
Chemical Polymerization ◽  
Dc Electrical Conductivity ◽  
Highly Sensitive ◽  
Chlorine Gas

We report the synthesis of polypyrrole (PPy) and polypyrrole/silicon carbide nanocomposites (PPy/SiC) and PPy/SiC/dodecylbenzenesulfonic acid (DBSA) by in situ chemical polymerization and their application as sensors for the detection of highly toxic chlorine gas.

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