scholarly journals Introducing CRYOWRF v1.0: Multiscale atmospheric flow simulations with advanced snow cover modelling

2021 ◽  
Author(s):  
Varun Sharma ◽  
Franziska Gerber ◽  
Michael Lehning
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Climate Change Impacts ◽  
Atmospheric Model ◽  
Blowing Snow ◽  
Atmospheric Flow ◽  
Flow Simulations ◽  
Modelling Framework ◽  
Road Map ◽  
And Performance

Abstract. Accurately simulating snow-cover dynamics and the snow-atmosphere coupling is of major importance for topics as wide-ranging as water resources, natural hazards and climate change impacts with consequences for sea-level rise. We present a new modelling framework for atmospheric flow simulations for cryospheric regions called CRYOWRF. CRYOWRF couples the state-of-the-art and widely used atmospheric model WRF, with the detailed snow-cover model SNOWPACK. CRYOWRF makes it feasible to simulate dynamics of a large number of snow layers governed by grain-scale prognostic variables with online coupling to the atmosphere for multiscale simulations from the synoptic to the turbulent scales. Additionally, a new blowing snow scheme is introduced in CRYOWRF and is discussed in detail. CRYOWRF's technical design goals and model capabilities are described and performance costs are shown to compare favourably with existing land surface schemes. Three case studies showcasing envisaged use-cases for CRYOWRF for polar ice sheets and alpine snowpacks are provided to equip potential users with templates for their research. Finally, the future road-map for CRYOWRF's development and usage is discussed.

scholarly journals Simulation of wind-induced snow transport in alpine terrain using a fully coupled snowpack/atmosphere model

2013 ◽  
Vol 7 (3) ◽  
pp. 2191-2245 ◽  
Author(s):  
V. Vionnet ◽  
E. Martin ◽  
V. Masson ◽  
G. Guyomarc'h ◽  
F. Naaim-Bouvet ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Winter Season ◽  
Coupled Model ◽  
Deposition Process ◽  
Atmospheric Model ◽  
Horizontal Resolution ◽  
Blowing Snow ◽  
Erosion And Deposition ◽  
Atmospheric Flow ◽  
Snow Transport

Abstract. In alpine regions, wind-induced snow transport strongly influences the spatio-temporal evolution of the snow cover throughout the winter season. To gain understanding on the complex processes that drive the redistribution of snow, a new numerical model is developed. It couples directly the detailed snowpack model Crocus with the atmospheric model Meso-NH. Meso-NH/Crocus simulates snow transport in saltation and in turbulent suspension and includes the sublimation of suspended snow particles. A detailed representation of the first meters of the atmosphere allows a fine reproduction of the erosion and deposition process. The coupled model is evaluated against data collected around the experimental site of Col du Lac Blanc (2720 m a.s.l., French Alps). For this purpose, a blowing snow event without concurrent snowfall has been selected and simulated. Results show that the model captures the main structures of atmospheric flow in alpine terrain, the vertical profile of wind speed and the snow particles fluxes near the surface. However, the horizontal resolution of 50 m is found to be insufficient to simulate the location of areas of snow erosion and deposition observed by terrestrial laser scanning. When activated, the sublimation of suspended snow particles causes a reduction in deposition of 5.3%. Total sublimation (surface + blowing snow) is three times higher than surface sublimation in a simulation neglecting blowing snow sublimation.

scholarly journals Simulation of Northern Eurasian Local Snow Depth, Mass, and Density Using a Detailed Snowpack Model and Meteorological Reanalyses

2013 ◽  
Vol 14 (1) ◽  
pp. 203-219 ◽  
Author(s):  
Eric Brun ◽  
Vincent Vionnet ◽  
Aaron Boone ◽  
Bertrand Decharme ◽  
Yannick Peings ◽  
...  
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Land Surface Model ◽  
Northern Eurasia ◽  
Surface Model ◽  
Monthly Precipitation ◽  
Blowing Snow ◽  
Snow Water

Abstract The Crocus snowpack model within the Interactions between Soil–Biosphere–Atmosphere (ISBA) land surface model was run over northern Eurasia from 1979 to 1993, using forcing data extracted from hydrometeorological datasets and meteorological reanalyses. Simulated snow depth, snow water equivalent, and density over open fields were compared with local observations from over 1000 monitoring sites, available either once a day or three times per month. The best performance is obtained with European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim). Provided blowing snow sublimation is taken into account, the simulations show a small bias and high correlations in terms of snow depth, snow water equivalent, and density. Local snow cover durations as well as the onset and vanishing dates of continuous snow cover are also well reproduced. A major result is that the overall performance of the simulations is very similar to the performance of existing gridded snow products, which, in contrast, assimilate local snow depth observations. Soil temperature at 20-cm depth is reasonably well simulated. The methodology developed in this study is an efficient way to evaluate different meteorological datasets, especially in terms of snow precipitation. It reveals that the temporal disaggregation of monthly precipitation in the hydrometeorological dataset from Princeton University significantly impacts the rain–snow partitioning, deteriorating the simulation of the onset of snow cover as well as snow depth throughout the cold season.

Heterogenous snow cover derived uncertainty in Arctic carbon budget

2020 ◽  
Author(s):  
Hotaek Park ◽  
Youngwook Kim
Keyword(s):  
Greenhouse Gases ◽  
Snow Cover ◽  
Land Surface ◽  
Snow Depth ◽  
Environmental Changes ◽  
Moisture Stress ◽  
Surface Model ◽  
Active Layer Thickness ◽  
Blowing Snow ◽  
Permafrost Temperature

<p>The winter of northern Arctic regions is characterized by strong winds that lead to frequent blowing snow and thus heterogeneous snow cover, which critically affects permafrost hydrothermal processes and the associated feedbacks across the northern regions. However until now, observations and models have not documented the blowing snow impacts. The blowing snow process has coupled into a land surface model CHANGE, and the improved model was applied to observational sites in the northeastern Siberia for 1979–2016. The simulated snow depth and soil temperature showed general agreements with the observations. To quantify the impacts of blowing snow on permafrost temperatures and the associated greenhouse gases, two decadal experiments that included or excluded blowing snow, were conducted for the observational sites and over the pan-Arctic scale. The differences between the two experiments represent impacts of the blowing snow on the analytical components. The blowing snow-induced thinner snow depth resulted in cooler permafrost temperature and lower active layer thickness; this lower temperature limited the vegetation photosynthetic activity due to the increased soil moisture stress in terms of larger soil ice portion and hence lower ecosystem productivity. The cooler permafrost temperature is also linked to less decomposition of soil organic matter and lower releases of CO2 and CH4 to the atmosphere. These results suggest that the most land models without a blowing snow component likely overestimate the release of greenhouse gases from the tundra regions. There is a strong need to improve land surface models for better simulations and future projections of the northern environmental changes.</p>

scholarly journals Simulation of wind-induced snow transport and sublimation in alpine terrain using a fully coupled snowpack/atmosphere model

2014 ◽  
Vol 8 (2) ◽  
pp. 395-415 ◽  
Author(s):  
V. Vionnet ◽  
E. Martin ◽  
V. Masson ◽  
G. Guyomarc'h ◽  
F. Naaim-Bouvet ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Winter Season ◽  
Coupled Model ◽  
Atmospheric Model ◽  
Blowing Snow ◽  
Atmospheric Flow ◽  
Complex Processes ◽  
Alpine Regions ◽  
Spatio Temporal ◽  
Snow Transport

Abstract. In alpine regions, wind-induced snow transport strongly influences the spatio-temporal evolution of the snow cover throughout the winter season. To gain understanding on the complex processes that drive the redistribution of snow, a new numerical model is developed. It directly couples the detailed snowpack model Crocus with the atmospheric model Meso-NH. Meso-NH/Crocus simulates snow transport in saltation and in turbulent suspension and includes the sublimation of suspended snow particles. The coupled model is evaluated against data collected around the experimental site of Col du Lac Blanc (2720 m a.s.l., French Alps). First, 1-D simulations show that a detailed representation of the first metres of the atmosphere is required to reproduce strong gradients of blowing snow concentration and compute mass exchange between the snowpack and the atmosphere. Secondly, 3-D simulations of a blowing snow event without concurrent snowfall have been carried out. Results show that the model captures the main structures of atmospheric flow in alpine terrain. However, at 50 m grid spacing, the model reproduces only the patterns of snow erosion and deposition at the ridge scale and misses smaller scale patterns observed by terrestrial laser scanning. When activated, the sublimation of suspended snow particles causes a reduction of deposited snow mass of 5.3% over the calculation domain. Total sublimation (surface + blowing snow) is three times higher than surface sublimation in a simulation neglecting blowing snow sublimation.

scholarly journals A Response of Snow Cover to the Climate in the Northwest Himalaya (NWH) Using Satellite Products

2021 ◽  
Vol 13 (4) ◽  
pp. 655
Author(s):  
Animesh Choudhury ◽  
Avinash Chand Yadav ◽  
Stefania Bonafoni
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Significant Negative Correlation ◽  
Shuttle Radar Topography Mission ◽  
Vital Role ◽  
Snow Cover Area ◽  
Study Region ◽  
Northwest Himalaya ◽  
The Past ◽  
Average Annual Temperature

The Himalayan region is one of the most crucial mountain systems across the globe, which has significant importance in terms of the largest depository of snow and glaciers for fresh water supply, river runoff, hydropower, rich biodiversity, climate, and many more socioeconomic developments. This region directly or indirectly affects millions of lives and their livelihoods but has been considered one of the most climatically sensitive parts of the world. This study investigates the spatiotemporal variation in maximum extent of snow cover area (SCA) and its response to temperature, precipitation, and elevation over the northwest Himalaya (NWH) during 2000–2019. The analysis uses Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra 8-day composite snow Cover product (MOD10A2), MODIS/Terra/V6 daily land surface temperature product (MOD11A1), Climate Hazards Infrared Precipitation with Station data (CHIRPS) precipitation product, and Shuttle Radar Topography Mission (SRTM) DEM product for the investigation. Modified Mann-Kendall (mMK) test and Spearman’s correlation methods were employed to examine the trends and the interrelationships between SCA and climatic parameters. Results indicate a significant increasing trend in annual mean SCA (663.88 km2/year) between 2000 and 2019. The seasonal and monthly analyses were also carried out for the study region. The Zone-wise analysis showed that the lower Himalaya (184.5 km2/year) and the middle Himalaya (232.1 km2/year) revealed significant increasing mean annual SCA trends. In contrast, the upper Himalaya showed no trend during the study period over the NWH region. Statistically significant negative correlation (−0.81) was observed between annual SCA and temperature, whereas a nonsignificant positive correlation (0.47) existed between annual SCA and precipitation in the past 20 years. It was also noticed that the SCA variability over the past 20 years has mainly been driven by temperature, whereas the influence of precipitation has been limited. A decline in average annual temperature (−0.039 °C/year) and a rise in precipitation (24.56 mm/year) was detected over the region. The results indicate that climate plays a vital role in controlling the SCA over the NWH region. The maximum and minimum snow cover frequency (SCF) was observed during the winter (74.42%) and monsoon (46.01%) season, respectively, while the average SCF was recorded to be 59.11% during the study period. Of the SCA, 54.81% had a SCF above 60% and could be considered as the perennial snow. The elevation-based analysis showed that 84% of the upper Himalaya (UH) experienced perennial snow, while the seasonal snow mostly dominated over the lower Himalaya (LH) and the middle Himalaya (MH).

scholarly journals Assessing biophysical and socio-economic impacts of climate change on regional avian biodiversity

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Simon Kapitza ◽  
Pham Van Ha ◽  
Tom Kompas ◽  
Nick Golding ◽  
Natasha C. R. Cadenhead ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
Integrated Modelling ◽  
Land Use Patterns ◽  
Economic Changes ◽  
Use Patterns ◽  
Modelling Framework ◽  
Avian Biodiversity ◽  
Biodiversity Change ◽  
Impacts Of Climate Change

AbstractClimate change threatens biodiversity directly by influencing biophysical variables that drive species’ geographic distributions and indirectly through socio-economic changes that influence land use patterns, driven by global consumption, production and climate. To date, no detailed analyses have been produced that assess the relative importance of, or interaction between, these direct and indirect climate change impacts on biodiversity at large scales. Here, we apply a new integrated modelling framework to quantify the relative influence of biophysical and socio-economically mediated impacts on avian species in Vietnam and Australia and we find that socio-economically mediated impacts on suitable ranges are largely outweighed by biophysical impacts. However, by translating economic futures and shocks into spatially explicit predictions of biodiversity change, we now have the power to analyse in a consistent way outcomes for nature and people of any change to policy, regulation, trading conditions or consumption trend at any scale from sub-national to global.

Conditions controlling atmospheric pollutant deposition via snowpack

2010 ◽  
Vol 18 (NA) ◽  
pp. 87-114 ◽  
Author(s):  
Marek Błaś ◽  
Katarzyna Cichała-Kamrowska ◽  
Mieczysław Sobik ◽  
Żaneta Polkowska ◽  
Jacek Namieśnik
Keyword(s):  
Snow Cover ◽  
Atmospheric Precipitation ◽  
Accurate Estimate ◽  
Buffering Capacity ◽  
Blowing Snow ◽  
Atmospheric Pollutant ◽  
Solid Precipitation ◽  
Pollutant Deposition ◽  
Important Addition ◽  
Flow Through

Solid precipitation represents a potentially important addition to other measures of deposition. However, an accurate estimate of snowfall amount and pollutant loading is not a trivial matter. There are obvious distinctions between regular precipitation collection and snowpack sampling that represent the cumulative chemistry of bulk deposition. The main goal is to show the most important processes and factors that may influence the rate and magnitude of pollutants deposition affected by the snowfall and snow cover: atmospheric pollutant enhancement of snowfall, pollutants deposition at snow cover surface, drifting and blowing snow, formation of the snow cover and its internal changes, as well as pollutants flow through the snowpack. These phenomena lead to continuous changes in the chemistry of the snow cover and the deposition calculated on the basis of pollutants concentrations in daily portions of atmospheric precipitation. The real deposition released from snowpack is strictly related to the number and depth of thaw episodes. If the amount of stored pollutants is large, first portions of ablation water flushing from the snowpack can carry the load of pollutants, and potentially affecting the environment in a detrimental way. Igneous bedrock is especially sensitive to acidic ions because of its low buffering capacity.

Management System Competency Model and Development Program

2018 ◽  
Author(s):  
Mark S. Jean ◽  
Lynn A. Sikorski ◽  
Laura P. Zaleschuk
Keyword(s):  
Performance Management ◽  
Management System ◽  
Development Program ◽  
Competency Model ◽  
Management Systems ◽  
Success Rates ◽  
Road Map ◽  
Person Perspective ◽  
And Performance ◽  
Measurement And Evaluation

The pipeline industry continues to look for ways to improve its compliance and performance. Management systems have increased prevalence in the pipeline industry, with recognition that carefully designed and well-implemented management systems are the fundamental method that should be used to keep people safe, protect the environment and align organizational activities. Experience has shown significantly better success rates with management system implementation, both in terms of the quality and speed, when the person responsible for the design, implementation and sustainment of the management system has an integrated set of technical and enabling competencies. However, there is currently no standardized competency model that can be used to support a Management Systems Professional’s specialized knowledge and skills. The paper outlines the competencies needed by individuals to be effective in the design, implementation, measurement and evaluation of management systems. Applying a ‘whole-person’ perspective, the model includes business, relational and technical competencies that contribute to performance excellence for management system practitioners, including outlining example behaviours at target level performance and proficiency, and supported by a defined body of knowledge. This paper describes the Management System Competency Model, including how it can be used to create a position-specific development program for application within various organizations. This research establishes a basis for the creation of a practical, systematic and easy to use development road map for individuals and organizations who use or leverage a management system.

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