Showing posts with label Snow. Show all posts
Showing posts with label Snow. Show all posts

Tuesday, September 10, 2024

30-years (1991-2021) Snow Water Equivalent Dataset in the Po River District, Italy

This paper presents a long-term snow water equivalent dataset in the Po River District, Italy, spanning from 1991 to 2021 at daily time step and 500 m spatial resolution partially covering the mountain ranges of Alps and Apennines. The data has been generated using a hybrid modelling approach integrating the hydrological modelling conducted with the physically- based GEOtop model, preprocessing of the meteorological data, and assimilation of in-situ snow measurements and Earth Observation snow products to enhance the quality of the model estimates. 
A rigorous quality assessment of the dataset has been performed at different control points selected based on reliability, quality, and territorial distribution. The point validation between simulated and observed snow depth across control points shows the accuracy of the dataset in simulating the normal and relatively high snow conditions, respectively. Additionally, satellite snow cover maps have been compared with simulated snow depth maps, as a function of elevation and aspect. 2D Validation shows accurate values over time and space, expressed in terms of snowline along the cardinal directions. This paper hase been submitted to Scientific Data.  The preprint and all the indications to get the data is obtained by clicking on the Figure above. 

Thursday, July 4, 2024

A Ph.D. position on snow modelling and the related runoff production

 APPLY TODAY ! There is an opening until July 10 (<---Here it is the link) for a Ph.D. position on the SpaceItUP and SUPER project(Snow and glacier rUnoff Production in alpine RivER basins 1990-2050)


Due to climate change, the Alpine region is experiencing a reduction in snow quantity (snow droughts) and an increase in evapotranspiration losses (green water), with significant consequences for sustainable water resource management and ecosystem preservation. This project aims to develop new models to quantify snowmelt and evapotranspiration losses, providing practitioners with calculation tools that are different from traditional lumped parameter models but simpler than 3D process-based models. The project also intends to study the water content obtained from snow and glaciers, from the present to 2050, in the Po and Adige river basins, assessing both quantitative and temporal variations in contributions. The primary tools for the analyses will be the open-source models of the GEOframe system, integrated, modified, and improved by the new models. The modeling will be supported by the acquisition of Earth observation products derived from the MODIS and Sentinel platforms, and potentially other platforms as data becomes available. The final product of the research, concerning snow forecasts, will be developed on a regular grid of 250 meters, while flow rates will be produced for each section of interest. The analyses for the control period from 1990 to 2022 will be conducted on both daily and hourly scales, providing a valuable "reference data cube." Future projections will be produced on a monthly scale. As part of enhancing the current state of the art, which is typical for a doctoral project, reliability criteria and error estimation methods will be developed for each produced dataset. The work will be done in collaboration with dr. John Mohd Wani as co-advisor. Collaborations can include working and exchanging ideas with dr. Christian Massari (GS), Professor Manuela Girotto (GS), Prof. Stefan Gruber (GS), Giacomo Bertoldi (GS)Kelly Gleason (GS), Marco Borga (GS) and Stefano Ferraris (GS).
Old work on snow and permafrost of the group can be found here (to be updated soon).
 The deadline is approachinf very fast, therefore APPLY! To better understand the policies of the group, please give a reading here 

Thursday, June 27, 2024

How much snow is in the mountains and what is its fate? by Manuela Girotto

Water resources such as snow or groundwater can be estimated using satellite remote sensing observations and numerical models. Both models and observations have inherent uncertainties and limitations related to observation errors, model parameterization, and input uncertainties. A promising method to alleviate shortcomings in models and observations is data assimilation because it combines existing and emerging observations with model estimates, thus bridging scale and limitation gaps between observations and models. 


Using these tools, we can address the following science questions: How much water is stored as seasonal snow? How much is in the groundwater aquifers? Can we quantify hydrological changes due to human induced processes (e.g., irrigation)? This presentation will focus on the estimation of snow seasonal amounts in mountainous regions, the water towers of the world. They supply a substantial part of both natural and anthropogenic water demands and they are also highly sensitive and prone to climate change. Slides of the talk can be found by clicking on the above figure. 

 
The presentation was followed by an interesting discussion that you can see here below:

Saturday, October 28, 2023

CARITRO Project: Snow droughts e green water: how climate change modifies the hydrological cycle in the Alpine Region.

Due to the impact of climate change, the Alpine region is experiencing a dual effect: a decrease in snowfall leading to snow droughts, and an increase in water losses through evapotranspiration, also known as green water. These changes have significant implications for the sustainable management of water resources and the preservation of ecosystems. This project, funded by the CARITRO foundation, aims to address these challenges by developing innovative models to accurately quantify snow melt and evapotranspiration losses. The ultimate goal is to provide practitioners with user-friendly calculation tools that are more advanced than traditional lumped models but less complex than intricate "process-based" 3D models. Initially proposed by Niccolò Tubini, the project has been taken up by John Mohd Wani with minimal modifications.  


The complete project plan can be found here

Friday, October 20, 2023

Identifying Snowfall Elevation Patterns by Assimilating Satellite- Based Snow Depth Retrievals

Precipitation in mountain regions is highly variable and poorly measured, posing important challenges to water resource management. Traditional methods to estimate precipitation include in-situ gauges, doppler weather radars, satellite radars and radiometers, numerical modeling and reanalysis products. Each of these methods is unable to adequately capture complex orographic precipitation. Here, we propose a novel approach to characterize orographic snowfall over mountain regions. We use a particle batch smoother to leverage satellite information from Sentinel-1 derived snow depth retrievals and to correct various gridded precipitation products. This novel approach is tested using a simple snow model for an alpine basin located in Trentino Alto Adige, Italy. We quantify the precipitation biases across the basin and found that the assimilation method (i) corrects for snowfall biases and uncertainties, (ii) leads to cumulative snowfall elevation patterns that are consistent across precipitation products, and (iii) results in overall improved basin-wide snow variables (snow depth and snow cover area) and basin streamflow estimates.



The analysis of the snowfall elevation patterns' spatial characteristics indicates that the proposed assimilation scheme results in more accurate spatial patterns in the snowfall distribution across the entire basin. The derived snowfall orographic patterns contribute to a comprehensive improvement of mountain hydrologic variables such as snow depth, snow cover area, and streamflow. The most significant enhancements in streamflow are observed during the spring and summer months when peak flow observations align more accurately with the posterior cases than the prior ones. These results primarily stem from the fact that the assimilation of Sentinel-1 assigns less snowfall to the lower-elevation regions of the basin, while higher rates are assigned to the higher elevation. As summer approaches, water is released more slowly from the higher elevation via snow-melt than in the prior case, which aligns better with observations. The assimilation of Sentinel-1 effectively downscales coarser-resolution precipitation products. While the prior snowfall cumulative elevation pattern has a small gradient across elevation bands, these patterns are consistent across elevations and precipitation products after the assimilation of snow depth retrievals. In conclusion, this study provides a framework for correcting snowfall orographic patterns across other seasonally-snow dominated mountain areas of the world, especially where in-situ data are scarce. The full paper can be found by clicking on the Figure above.
Reference


Girotto, Manuela, Giuseppe Formetta, Shima Azimi, Claire Bachand, Marianne Cowherd, Gabrielle De Lannoy, Hans Lievens, et al. 2023. “Identifying Snowfall Elevation Patterns by Assimilating Satellite-Based Snow Depth Retrievals.” The Science of the Total Environment, September, 167312. https://doi.org/10.1016/j.scitotenv.2023.167312.

Tuesday, July 12, 2022

Modelling the Thermodynamics of Glaciers

 Is it possible to predict the ice temperature and its thermodynamic properties?  In principle it would not seem difficult.  The heat propagation equation has long been known.  It therefore seems that it is enough to know the incoming solar radiation, have a simple model of heat propagation, a digital model of elevation of the glacier and the terrain, and that's it.  There are some difficulties though.  Assuming the physics works as described, we can understand fairly quickly that the heat capacity of the ice is enormous and if the mass of the glacier is large, this requires that the heat balance model must be run for hundreds of years to obtain reliable results.  This is impractical because we would need to know the (forcing) meteorological conditions starting from a distant past (everyone knows that the future is unknown, fewer are those who reflect on the fact that not even the past and the present are perfectly known).  In fact, as any mathematician knows, glacier modeling requires you to set the temperature and heat flow conditions around the glacier at any time (the boundary conditions).  We do not have them but we can invent plausible ones, making use of a little art and a lot of artisan’s experience.  This, to be honest, introduces some uncertainty into what is being built, but it would be enough to be clear about this and people could perhaps understand.


    Obviously, as you can imagine, the thermodynamics of glaciers is not as trivial as we assumed at the beginning.  It is a fact that knowledge of ice physics hasn't evolved much in the last twenty years or so.  How does snow compact into ice?  And how does ice behave under great pressure?  How does the heat capacity of ice vary during these metamorphisms?  And how the thermal conductivity?  (The first factor tells how much energy it takes to make the temperature of a kilogram of ice vary by one degree, the second how fast, the energy changes redistribute through the ice pack).  And, furthermore, what is the thermal variability of ice in space?  The action that determines these quantities is called the characterization of the thermal properties of ice.  This can be done by monitoring glaciers and making some assumptions, but it cannot be obtained without careful application.

  In reality we should not only solve the thermal balance but the whole energy balance, which includes the possible phase transitions that generate the transformation of ice into water and water vapor and, of course, vice versa.  If we make these necessary refinements, the equations become more difficult to be solved (well, some colleagues have said that for certain reasons the energy budget models are often wrong - not ours actually - due to the numerical consequences introduced by these aspects).  When liquid water is added to ice, percolation and runoff are obviously obtained, which change the nature of the phenomena and of the descriptive equations, to which the advection-dispersion terms must be added.
  Perhaps I also forgot to mention that snow is different from ice and the properties of the ground beneath the glacier are important in determining the general state of a glacier itself.
Going to the problem of the failure of the Marmolada glaciers, the failure itself is a different business because it has to deal with the formation of cracking and geo-mechanics of solids. They certainly depend on the thermodynamics but this connection itself is not easy to obtain since both the geometry of cracks and the mechanics are two further differentiated issues.

 So do we have to conclude that the hope of modeling the thermodynamics of a glacier is a lost battle?  Not at all!  We must conclude that with the investigators patient, a lot of evidence can be gathered and some results can be obtained to get a decently approximate thermal state of the glacier.  We can realize that above all it is an accumulation of information that is necessary and that this derives from the possibility of continuing research over time. Only patient application (and some intuition) eliminates the gray area in our knowledge of these problems and improves the models.  Maybe we are year zero, but next year we could be year one, and so on.

For who wants to go a little deeper on the topic they can find a little of literature below.

References

Aschwanden, Andy, Ed Bueler, Constantine Khroulev, and Heinz Blatter. 2012. “An Enthalpy Formulation for Glaciers and Ice Sheets.” Journal of Glaciology 58 (209): 441–57. https://doi.org/10.3189/2012JoG11J088.

Beniston, Martin, Daniel Farinotti, Markus Stoffel, Liss M. Andreassen, Erika Coppola, Nicolas Eckert, Adriano Fantini, et al. 2018. “The European Mountain Cryosphere: A Review of Its Current State, Trends, and Future Challenges.” The Cryosphere 12 (2): 759–94. https://doi.org/10.5194/tc-12-759-2018.

Carletti, Francesca, Adrien Michel, Francesca Casale, Alice Burri, Daniele Bocchiola, Mathias Bavay, and Michael Lehning. 2022. “A Comparison of Hydrological Models with Different Level of Complexity in Alpine Regions in the Context of Climate Change.” Hydrology and Earth System Sciences 26 (13): 3447–75. https://doi.org/10.5194/hess-26-3447-2022.

Corripio, Javier González. 2002. “Modelling the Energy Balance of High Altitude Glacierised Basins in the Central Andes.” University of Edinburgh.

Dall’Amico, M., S. Endrizzi, S. Gruber, and R. Rigon. 2011. “A Robust and Energy-Conserving Model of Freezing Variably-Saturated Soil.” The Cryosphere. https://tc.copernicus.org/articles/5/469/2011/.

Endrizzi, S., S. Gruber, M. Dall’Amico, and R. Rigon. 2014. “GEOtop 2.0: Simulating the Combined Energy and Water Balance at and below the Land Surface Accounting for Soil Freezing, Snow Cover and Terrain Effects.” Geoscientific Model Development 7 (6): 2831–57. https://doi.org/10.5194/gmd-7-2831-2014.

Gouttevin, I., M. Lehning, T. Jonas, D. Gustafsson, and M. Mölder. 2015. “A Two-Layer Canopy Model with Thermal Inertia for an Improved Snowpack Energy Balance below Needleleaf Forest (model SNOWPACK, Version 3.2.1, Revision 741).” Geoscientific Model Development 8 (8): 2379–98. https://doi.org/10.5194/gmd-8-2379-2015.

Greve, R. and Blatter, H.: Comparison of thermodynamics solvers in the polythermal ice sheet model SICOPOLIS, Polar Science, 10, 11–23, 2016

Hewitt, I. and Schoof, C.: A model for polythermal ice incorporating gravity-driven moisture transport, Journal of fluid mechanics, 797, 2016

Hanzer, Florian, Kristian Förster, Johanna Nemec, and Ulrich Strasser. 2017. “Projected Cryospheric and Hydrological Impacts of 21st Century Climate Change in the Ötztal Alps (Austria) Simulated Using a Physically Based Approach.” Hydrology and Earth System Sciences Discussions, August, 1–34. https://doi.org/10.5194/hess-2017-309.

Hock, Regine. 2005. “Glacier Melt: A Review of Processes and Their Modelling.” Progress in Physical Geography 29 (3): 362–91.

Lehning, Michael, Perry Bartelt, Bob Brown, Charles Fierz, and Pramod Satyawali. 2002. “A Physical SNOWPACK Model for the Swiss Avalanche Warning.” Cold Regions Science and Technology 35 (3): 147–67. https://doi.org/10.1016/s0165-232x(02)00073-3.

Lehning, Michael, Ingo Völksch, David Gustafsson, Tuan Anh Nguyen, Manfred Stähli, and Massimiliano Zappa. 2006. “ALPINE3D: A Detailed Model of Mountain Surface Processes and Its Application to Snow Hydrology.” Hydrological Processes, IAHS Publica, 20 (10): 2111–28. https://doi.org/10.1002/hyp.6204.

Machguth, Horst, Frank Paul, Martin Hoelzle, and Wilfried Haeberli. 2006. “Distributed Glacier Mass-Balance Modelling as an Important Component of Modern Multi-Level Glacier Monitoring.” Annals of Glaciology 43: 335–43. https://doi.org/10.3189/172756406781812285.

Pellicciotti, Francesca, Marco Carenzo, Jakob Helbing, Stefan Rimkus, and Paolo Burlando. 2009. “On the Role of Subsurface Heat Conduction in Glacier Energy-Balance Modelling.” Annals of Glaciology 50 (50): 16–24. https://doi.org/10.3189/172756409787769555.

Perona, P., and P. Burlando. 2008. “Mechanistic Interpretation of Alpine Glacierized Environments: Part 1. Model Formulation and Related Dynamical Properties.” Advances in Water Resources 31 (June): 937–47.

Tiel, Marit, Kerstin Stahl, Daphné Freudiger, and Jan Seibert. 2020. “Glaciohydrological Model Calibration and Evaluation.” WIREs Water 66 (September): 249. https://doi.org/10.1002/wat2.1483.

Tubini, Niccolò, Stephan Gruber, and Riccardo Rigon. 2021. “A Method for Solving Heat Transfer with Phase Change in Ice or Soil That Allows for Large Time Steps While Guaranteeing Energy Conservation.” The Cryosphere 15 (6): 2541–68. https://doi.org/10.5194/tc-15-2541-2021.

Vionnet, V., E. Brun, S. Morin, A. Boone, S. Faroux, P. Le Moigne, E. Martin, and J-M Willemet. 2012. “The Detailed Snowpack Scheme Crocus and Its Implementation in SURFEX v7.2.” Geoscientific Model Development 5 (3): 773–91. https://doi.org/10.5194/gmd-5-773-2012.

Weiler, Markus, Jan Seibert, and Kerstin Stahl. 2018. “Magic Components-Why Quantifying Rain, Snowmelt, and Icemelt in River Discharge Is Not Easy.” Hydrological Processes 32 (1): 160–66. https://doi.org/10.1002/hyp.11361.

Wever, N., C. Fierz, C. Mitterer, H. Hirashima, and M. Lehning. 2014. “Solving Richards Equation for Snow Improves Snowpack Meltwater Runoff Estimations in Detailed Multi-Layer Snowpack Model.” The Cryosphere 8 (1): 257–74. https://doi.org/10.5194/tc-8-257-2014.

Zemp, Michael, Wilfried Haeberli, Martin Hoelzle, and Frank Paul. 2006. “Alpine Glaciers to Disappear within Decades?” Geophysical Research Letters 33 (13): 303. https://doi.org/10.1029/2006GL026319.

Monday, April 11, 2022

Snow droUghts predictioN in the Alps: a changing climate assessmEnT: SUNSET PRIN Project

Reduced mountain snowpack, i.e. a “snow drought”, due to rising temperatures or changes in precipitation amount has critical implications on water resources availability. Ongoing climate change may influence the frequency and severity of snow droughts. SUNSET aims to develop an integrated methodology to assess the impact of climatic variations and changes on snow droughts and on the seasonal low flows in the Italian Alps. To meet this objective, SUNSET develops based on two main scientific advances. The first advance are the Convection-Permitting Models (CPM) for climate simulations, with improved topographical features, physical representation of mountain‐precipitation interactions, and avoided errors from convective parameterizations. A second recent advance is the availability of improved multi-objective calibration strategies for hydrological-snowpack models which permit reliable simulations of both snow pack evolution and runoff variability. With SUNSET, a modelling chain linking bias-corrected Convective Precipitation Modelling (CPM) and Regional Climate Models (RCM) outputs as well as state-of-the art hydrological models will be developed and exploited to quantify changes in the frequency and severity of snow droughts through the end of the current century. The project focuses on two broad study areas in the Western and Eastern Italian Alps, where a set of catchments with detailed process observations are available.
                    

SUNSET is based on two types of data: i) 20-to-30 years time series of validated catchment precipitation-temperature-discharge data from the network of twelve project study basins; ii) process data, collected in previous projects which will help improving the hydrological model validation. The past dataset includes observations from MODIS and Sentinel-1 that are functional to provide correct snow cover areas and snow water equivalent data.

Climate simulations will be based on 12-member CPM and RCM ensembles from the FPS-CORDEX project available for 3 time slices (historical, 1996-2005; near future, 2041-2050; far future, 2090-2099) for the extreme climate change scenario, i.e. RCP8.5. RCM outputs from CORDEX will also be considered to evaluate the added value of CPM compared to coarser resolution models and to investigate the climate change signal under different scenarios which are not available in CMP simulations, i.e. RCP4.5 (six-member RCM ensembles) versus RCP8.5 (six-member RCM ensembles. Hydrological models are part of an expandable system called GEOframe developed along the last 15 years and have already a setup for most of the study basin network.

SUNSET will communicate and disseminate the project results to a wide audience of residents in the two study areas and beyond through collaborations with Local Authorities. SUNSET will test, archive, document, and keep track of versions of the research code and software using open-source software and data protocols and accessible documentation.

By clicking on the above Figure you can access the full proposal. 
 
Finally we've got the project!
 

Thursday, October 15, 2020

How snowy are the Alps ?

 A recent preprint was submitted to The Cryosphere were a large group of colleagues scientists analyzed the snow precipitation in more than 2000 gauges all over the Alps. This research is not only important for assessing the effects of climate change but also will be a benchmark to other more local studies on snowfall. 

I think it could be a good reading for many, therefore I am sharing its information here. By clicking on the Figure you download the paper.

Tuesday, July 16, 2019

Snow, Ice and Permafrost

On Friday 19, 2019, there will be an event the event "climb for climate". I will be representing the University of Trento and give a short divulgative talk. The result can be found here below.
There I briefly summarise three of the topics related on the cryosphere on which I and my colleague Alberto Bellin (GS) and our group did something.  Snow, glaciers and permafrost, not only are hydrological topics, they are certainly among the most fascinating ones.

Thursday, April 4, 2019

EGU Wien 2019: Snow Water Equivalent modeling: comparing GEOtop physically based approach with temperature-index-based models in GEOframe-NewAge

In the work for a new version of GEOtop snow modelling, we are comparing here the results given by the GEOtop 2.0 snow model with those by the GEOframe components. Comparison is made in one point and, in both cases, requires calibration which is, however, made on different quantities for the different context. To get the results give a look to the poster.
The work uses the data given by ARPA Val d'Aosta retrieved at Torgnon site
Please find the high resolution poster by clicking on the figure above.

Monday, March 18, 2019

Snow for GEOtop 4.0

We are going to  change GEOtop snow, we are struggling with the change since three years but beginning is always difficult. Today we are presenting some of the road we did and are goig to take.  At the fifth intercomparison meeting on SWE (modelling, measurements, remote sensing).
Get the presentation by clicking on the Figure above. The title is in Italian (Elements for the development of a new snow model for GEOtop 4.0), but the contents in English.
On similar topic were also the seminar by

Tuesday, November 13, 2018

Crocus and Snowpack in a nutshell

There is not an enormous choice of process based models that treat snow Among them, two that are a reference for us are Snowpack and Crocus. Here it is their essential references.

SNOWPACK

CROCUS

Sunday, February 28, 2016

Nevi/Snows

This text is from Mario Rigoni Stern.  English translation by Joseph E. Tomasi. When translating he wrote to me from Ulaabaatoar, Mongolia, where he lives, that it was snowing, and all was covered by ten-twenty centimetres of white. He wrote: "According to Rigoni-Stern's calendar, it would be a bàchtalasneea, but according to the local season, it is more probable a swalbasneea. They were the right days to translate Nevi. "


Snows/Sneea

There are many snows in my memory: the snows of avalanches, the snows of high altitudes, the snows of Albanian mountains, of Russian steppes, of Polish moors. But it is not of these that I wish to speak; I will speak instead of how snows were once called where I come from: snows with many names, snows of yesteryear, ignored by the weather reports of winter sports resorts.
Brüskalan is what Old Auntie Marietta, my grandfather’s aunt, would say to me; that was the first snow of winter, the real stuff. It could snow and snow even in October and November, but autumn snow is weak snow, limp snow, which hinders the grazing of cattle in meadows mowed in September and the work of the woodsmen when the ground is not yet frozen in the woods. I remember the nuisance it would cause on All Souls’ Day, when tin garlands and real ferns from the woods would drip snow on newly cleaned graves; and how in the woods not yet completely bare we would go to cut beech trees: how grudgingly we worked with hands a-freezing, and how the snow stuck to our boots. There I learned that wet snow chills more than powdery snow. 
But when the brüskalan came it was different. After the Indian Summer, after Martinmas, the earth was well frozen, noisy under our hobnailed boots with studs and spikes. The smell of the first snow filled the air:  a clean and light smell; better and more welcome than the smell of fog. The healthy fog, I mean, the one that would come one or twice a year about the time of the migration of the skylarks.
Raising your gaze to the north, you would see a faint greyness that from the peaks reached low to the woods and then came down towards the town. And the top of the bell tower and its bells were soon within the grey milkiness and then the whole church, the roofs of the highest houses too. On the dusty streets, on the log piles, in the courtyards, and onto our ruffled heads the first flakes fell. We would open our mouth skywards to feel them melt on our tongue.
Very soon the snow would cover the dusty streets, the dry grass in the meadows, the sawdust in the courtyards from the beeches, the graves in the cemetery.
The voices and sounds of the town, the calls of sparrows and wrens became muffled, and at this point the brüskalan became real sneea: snow abundant and light coming down from the mill in the sky. Then, with trepidation, we would go up to the attic to find skis and lame (blades), our one-man sleds: in Scandinavia I have found identical objects with an identical name that, however, has no relation to the Italian word lama.  
We skied and sledded on the road  leading down to the main square, defying the local policeman and the scoldings of mothers and grandmothers, who, on their way to Mass, were slipping on hardened snow, bound  to become bare ice that not even the snow plow pulled by twelve horses would be able to scrape away.
This is more than seventy years ago. I must have been about five years old when an uncle of mine, who had been with the Alpini troops from 1913 till 1920, tied two curved lengths of wood to my boots, which he called skj, and I hurtled myself down the piste, which was then no more than the snow piled in front of the house by the snowplow and from the clearing of the courtyards: a nice big pile that covered the fences and gate pillars and that to us children seemed very high indeed. With spades and cinder shovels we smoothed its descent to the road; to climb up it, we dug steps right into it: - Make waaay!
But then the winter would wear on; the wood stocks would thin because the fireplace ate and ate; as did the stove in the kitchen. My grandfather's chair was near the stove, and it was there that he loved to smoke his pipe and, when I would come home all wet and cold, I would go between his chair and the stove to put my back against the warmth. Auntie would grumble, saying that I would cook my blood.
As winter wore on towards its end, the sneea became haapar. On the riverbanks in the sun it would trickle away over the earth in thousands and thousands of drops, and the brown of the soil would appear. It was at this time of year that we would hear the first skylarks: suddenly one morning a shiver would run over your skin and it would be their song, high in the sky above the haapar
With the haapar came the haarnust. That is the old snow that in springtime, during the warm hours, the sun softens at the surface and then the cold of the night hardens again. Excellent snow for off-track excursions, to be done from the very first light of dawn until about eleven in the morning, in every terrain and with cross-country or mountaineering skis, with good klister grip wax or skins. But even on foot, when because of our age we were not to take risks. Then we would walk with comfortable lightweight boots upon the haarnust, which bore the weight of our steps without giving way: we would walk "high", as if suspended over rocks and dips, level with the tops of young firs that sprout from the snow with the spring, which always started with the smell of tree resin, and on we marched effortlessly in mid-air. Then, when all the snow had melted, returning to those places, we would say: "I walked up there, at the height of those branches."
After the haapar and after the haarnust came the swalbasneea: the snow of the swallows, the snow of March that has always been on time through the centuries. It falls after the swallows have come back: sometimes soft, sometimes wet, sometimes as a blizzard, or even calmly into swollen banks. In one night it can fall up to a metre thick, and then the swallows that arrived up here to announce the spring will return to the plains for a few days, until the damp air or the rain or the pregnant soil melts the swalbasneea away. 
The kuksneea is the snow of April; it does not always come but it is not rare either. On meadows that are beginning to show green again and where the crocuses are blooming it does not last long, as the living earth melts it even before the sun can. Just as the swalbasneea is the snow of the swallow, the kuksneea is the snow of the cuckoo because it is he, the joyous awakener of the woods, who sometimes calls it, to have fun when it falls away from the branches of the conifers: for him, who comes from Africa, this thing soft and white and cold is both rare and curious.
When the meadows are covered with the solar yellow of dandelions and the blue of forget-me-nots, and the bees are busy from dawn till dusk collecting pollen and nectar, then might come the bàchtalasneea: the snow of the quail. A cloud bearing down from the north, a gust of wind, a sudden drop in temperature and in May can come the bàchtalasneea. It lasts only a few short hours, but long enough to scare the birds in the nest, to bring death to the bees surprised outside the hive, and to worry the does about to give birth.
I do not remember when exactly, I did not write it down; perhaps the last summer snow fell about fifteen years ago. I do not know the old name for this snow, I would need to ask those who now are a hundred years old or more. Perhaps they called it kuasneea: the snow of the cows, because in summer they can be found high in mountain pastures. Probably when it falls the cows come down bellowing to the woods and it becomes difficult to herd them. And making cheese becomes a problem too. The memory of this snow and when it fell lives on in the names of those born on those days: Nives, Nevino, Bianca, Nevio ...


From Sentieri sotto la neve (Paths Beneath the Snow), 1998, Mario Rigoni Stern



Nevi/Sneea

Ho tante nevi nella memoria: nevi di slavine, nevi di alte quote, nevi di montagne albanesi, di steppe russe, di lande polacche. Ma non di queste intendo parlare; dirò di come le nevi  un tempo venivano indicate dalle mie parti: nevi dai più nomi, nevi d’antan, non considerate nei bollettini delle stazioni degli sport invernali.
Brüskalan, mi diceva l’Amia Marietta, la zia del nonno; ed era questa era la prima neve dell’inverno, quella vera. Nevicava, nevicava, anche a ottobre e a novembre, ma la neve autunnale è una neve fiacca, flaccida, che interrompe il pascolo alle vacche sui prati falciati a settembre e il lavoro del bosco quando il terreno non è ancora gelato.  Ricordo il fastidio che dava, il giorno dei Morti, quando le ghirlande di latta e le felci vere del bosco sgocciolavano neve sulle tombe ripulite; e quando nel bosco non ancora del tutto spoglio si andava al taglio del faggio: come malvolentieri si lavorava con le mani che gelavano, e come la neve si attaccava agli scarponi. E’ così che ho imparato che la neve fradicia raggela più di quella farinosa.

Ma quando brüskalanava era diverso. Il terreno dopo l’estate di San Martino era ben gelato e risuonava sotto le scarpe chiodate con le brocche e giazzini. Lo si sentiva nell’aria l’odore della prima neve: un odore pulito, leggero; più buono e grato di quello della nebbia. Di quella nebbia sana, intendo, che veniva una o due volte all’anno al tempo del passo delle allodole.
Alzando lo sguardo verso nord vedevi un tenue grigiore che dalle cime raggiungeva i boschi e che si abbassava verso il paese. E la punta del campanile e le campane erano già dentro il grigiore lattiginoso e poi anche la chiesa, i tetti delle case più alte. Sulle strade polverose, sulle cataste di legna, sui cortili e sopra le nostre teste arruffate cadevano le prime stille. Aprivamo la bocca verso il cielo per sentirle sciogliersi sulla lingua.
In breve la neve copriva la polvere delle strade, l’erba secca sui pascoli, la segatura di faggio nei cortili, le tombe del cimitero.
Le voci, i rumori del paese, i richiami dei passeri e degli scriccioli si facevano lievi, e a questo punto la brüskalan diventava vera sneea: neve abbondante e leggera giù dal molino del cielo.
E noi si andava trepidanti in soffitta a prendere gli sci e le lame, i nostri slittini monoposto: oggetto e nome che ho trovato identici in Scandinavia e che non hanno nulla a che fare con l’italiano lama.
Si sciava e si slittava  sulla strada che scendeva verso la piazza, sfidando la guardia comunale  e le sgridate delle mamme e delle nonne, che andavano a messa e scivolavano sulla neve indurita destinata a diventare ghiaccio vivo, che nemmeno lo spazzaneve tirato da dodici cavalli sarebbe riuscito a intaccare.
Questo più di settant’anni fa. Forse avevo cinque anni quando uno zio, che era stato alpino dal 1913 al 1920, mi legò agli scarponi due tavole arcuate che si chiamavano skj e io mi buttai giù per la pista, che era poi la neve ammucchiata davanti a casa dallo spazzaneve e dalla spazzatura dei cortili: un bel mucchio che superava i recinti e i pilastri del cancello e che a noi bambini sembrava altissimo. Con i badili e le palette del focolare lo lisciavamo verso la discesa della strada; per salirci sopra avevamo scavato dei gradini: - Pistaaa!
Ma poi l’inverno diventava lungo; le scorte di legna si assottigliavano perché il focolare mangiava, mangiava; come pure mangiava la stufa nella stua. La sedia del nonno era vicina alla stufa, ed era lì che amava fumare la pipa e io, quando rientravo bagnato e infreddolito, mi mettevo tra la sedia e la stufa per appoggiare la schiena al caldo della parete. L’aria mi brontolava perché diceva che mi cucinavo il sangue.
Quando l’inverno stava per finire la sneea diventatava hapar. Sulle rive al sole andava via per la terra in mille e mille gocce, e appariva il bruno del suolo. Era in questo periodo che sentivamo le prime allodole: una mattina ti correva il brivido per la pelle ed era il loro canto alto nel cielo sopra l’haapar.
Con l’haapar veniva l’haarnust. è questa la neve vecchia che verso primavera, nelle ore calde, il sole ammorbidisce in superficie e che poi il freddo della notte indurisce. Neve ottima per escursioni fuori pista, da farsi nelle primissime luci dell’alba e fino alle undici del mattino, in ogni terreno e con gli sci da fondo o da alpinismo, con buona sciolina klister o pelli di foca. Ma anche a piedi quando pe l’età non si deve spericolare. Allora si va con comodi scarponi leggeri sopra l’haarnust che sopporta il peso del passo senza cedere: cammini in “alto” , come sospeso, sopra pietre e buche, a livello degli apici degli alberi giorni che spuntano dalla neve verso la primavera che incomincia con l’odore della resina, e vai senza fatica, a mezz’aria. Poi, quando tutta la neve sarà sciolta, ritornando su quei passi verrà da dire:”Ho camminato lassù, all’altezza di quei rami!”.
Dopo l’haapar e dopo l’haarnust veniva la swalbasneea: la neve delle rondini, la neve di marzo che è sempre puntuale nei secoli. Cade dopo che sono arrivate le rondini: a volte soffice, a volte bagnata, a volte come tormenta, o anche calma in dilatate falde. In una notte può caderne fino ad un metro e allora le rondini arrivate quassù ad annunciare la primavera se ne ritornano in pianura per qualche giorno finché l’aria umida o la pioggia o il terreno in amore non avranno sciolto la swalbasneea.
La kuksneea è la neve d’aprile; non sempre presente, ma non è nemmeno rara. Sui prati che incominciano a rinverdire e dove sono fioriti i crochi non si ferma molto, perché  prima ancora del sole la terra in amore la fa sciogliere. Come la  swalbasneea è la neve della rondine, la kuksneea è la neve del cuculo perché è lui, il gioioso uccello risvegliatole del bosco, che qualche volta la chiama per divertirsi quando di sfalda dai rami delle conifere: per lui che viene dall’Africa, questa bianca e soffice e fredda è rara e curiosa. 
Quando i prati si coprono del giallo solare dei fiori del tarassaco e dell’azzurro dei miosotidi, e le api sono indaffarate dall’alba al tramonto nella raccolta di pollini e nettari, allora può arrivare la bàchtalasneea: la neve della quaglia. Una nube che scende da nord, una ventata, un rapido abbassamento della temperatura ed ecco a maggio, la bàchtalasneea.  Dura solo poco ore, ma sufficiente per fare paura agli uccelli nel nido, dare morte alle api sorprese fuori dall’arnia e preoccupazione alle femmine di capriolo in attesa del parto. 
Non ricordo con precisione, non me lo sono annotato; forse l’ultima neve estiva è caduta una quindicina di anni fa. Non so il nome antico di questa neve, dovrei chiederlo a chi ora ha cent’anni. Forse di chiamava kuasneea: la neve delle vacche, perché d’estate si trovano sui pascoli delle malghe. Probabilmente quando viene giù le vacche scendono urlando nei boschi e diventa difficile tenerle in mandria. Come un problema diventa fare il formaggio. Di questa neve rimane memoria e data nei nati in quei giorni: Nives, Nevino, Bianca, Nevio …


Da Sentieri sotto la neve, 1998, Mario Rigoni Stern

Thursday, May 29, 2014

Snow (Neve)

As I did for the other "theoretical" part of my classes, I split here the old slides, in Italian indeed, in parts. Questo per un più semplice accoppiamento delle slides con l'audio delle lezioni.



Alcuni webinar (seminari via web) in inglese, sulla neve sono indicizzati qui.

Wednesday, March 19, 2014

Ubiquitous Diffusion

These are the slides for the lecture I gave to Michael Dumbser' class on Environmental Modelling. I tried to show the non linear diffusion equations that can be found in analysing the water and energy budget of the soil-snow (with freezing soil) continuum. In practice I used the material from my class in hydrology (the whole stuff here) and other material from GEOtop's talks, and the presentation is, at the moment, in Italian and English.
Incidentally two of these equations present  discontinuities due to phase transitions and the three of them require special numerical methods to be integrated. Here I suggest that a good method could be the Nested Newton one, introduced recently by Casulli and Zanolli (for integrating Richards), and before by  Brugnano and Casulli (for integrating Boussinesq equation).
Below you can find also the audio (in Italian) of the lecture: Richards equation (21.9 Mb); Frozen Soil (18.4 Mb); Snow (7.1 Mb). I gave longer presentations on Richards equation, in Todini Symposium (here), and at the summer School on Landslide Modelling in Praia a Mare (here).
An update. A new treatment of part of this matter is given by Niccolo Tubini in his Master Thesis. The slides he used in the 2017 lecture are here.

Essential References

L. Brugnano and V. Casulli, Iterative solution of piecewise linear systems and applications
to flows in porous media, SIAM J. Sci. Comput., 31 (2009), pp. 1858–1873.

Casulli, V., and Zanolli, P., A Nested Newton-Type Algorithm for Finite Volume Methods Solving Richards' Equation in Mixed Form, SIAM J. Sci. Comput., 32(4), 2255–2273,  Volume 32, Issue 4, 2010.

Cordano E., and Rigon R., A mass-conservative method for the integration of the two-dimensional groundwater (Boussinesq) equation,  Water Resour. Res., 49, doi:10.1002/wrcr.20072, 2013.


Dall’Amico, M.; Endrizzi, S., Gruber, S; and Rigon, R. (2011), An energy-conserving model of freezing variably-saturated soil, The Cryosphere.

Endrizzi S., Gruber S., Dall’Amico M., Rigon R., GEOtop 2.0.: Simulating the combined energy and water balance at and below the land surface accounting for soil freezing, snow cover and terrain effects, Geosci. Model Dev., 2015

Monday, March 10, 2014

Snow cyberseminars at CUASHI

In this early 2014 CUASHI sponsored three cyberseminars on snow modelling.  Here they are below.


Presenter: Dr. Jeff Dozier - University of California, Santa Barbara, Bren School of Environmental Science & Management
in conjunction with Dr. Anne Nolin - Oregon State University, Department of Geosciences

Title: Assessing Snow and Snowmelt Runoff in Remote Mountain Ranges
Abstract:
Our objective is to estimate seasonal snow volumes, relative to historical trends and extremes, in snow-dominated mountains that have austere infrastructure, sparse gauging, challenges of accessibility, and emerging or enduring insecurity related to water resources. The world's mountains accumulate substantial snow and, in some areas, produce the bulk of the runoff. In ranges like Afghanistan's Hindu Kush, availability of water resources affects US policy, military and humanitarian operations, and national security. The rugged terrain makes surface measurements difficult and also affects the analysis of remotely sensed data. To judge feasibility, we consider two regions, a validation case and a case representing inaccessible mountains. For the validation case, we use the Sierra Nevada of California, a mountain range of extensive historical study, emerging scientific innovation, and conflicting priorities in managing water for agriculture, urban areas, hydropower, recreation, habitat, and flood control. For the austere regional focus, we use the Hindu Kush, where some of the most persistent drought in the world causes food insecurity and combines with political instability, and occasional flooding. Our approach uses a mix of satellite data and spare modeling to present information essential for planning and decision making, ranging from optimization of proposed infrastructure projects to assessment of water resources stored as snow for seasonal forecasts. We combine optical imagery (MODIS on Terra/Aqua), passive microwave data (SSM/I and AMSR-E), retrospective reconstruction with energy balance calculations, and a snowmelt model to establish the retrospective context. With the passive microwave data we bracket the historical range in snow cover volume.


Presenter: Dr. Michael Durand, Assistant Professor, Ohio State University

Title: Microwaves and snow grains: Monitoring the changing mountain snowpack
Abstract:  Snow is a vital water resource for over a sixth of the world's population. There are concerns about the impact of changing timing of snowmelt runoff in a warming climate. Microwave radiation has been measured from space and exploited to estimate snow water equivalent (SWE) for decades. Current algorithms struggle to successfully estimate SWE in mountainous areas. Use of microwave data for snowpack characterization for hydrologic studies has been stymied by the complex role of snow microstructure and layering on snow microwave emission, the large spatial scale of the passive microwave (PM) measurements compared with dominant montane landscape spatial scales, and vegetation attenuation of PM measurements.  Here, we summarize recent advances in these three areas, and assess the prospect of large-scale SWE estimation in mountainous areas.


Presenter: Dr. David Robinson, Rutgers University, Department of Geography

Title: Large-scale Snow Extent over Northern Hemisphere Lands
Abstract: 
Annual snow cover extent (SCE) over Northern Hemisphere (NH) lands averages 25.8 million square kilometers.  It ranges from an average of 47.1 million sq. km. in January to 3.0 million sq. km. (mostly atop the Greenland Ice Sheet) in August. SCE is calculated at the Rutgers Global Snow Lab from daily SCE maps produced by meteorologists at the National Ice Center, who rely primarily on visible satellite imagery to construct the maps.

Annual SCE over NH lands has averaged lower since the late 1980s than earlier in the satellite era that began in the late 1960s.  This is most evident from late winter through spring, and in the past decade has been exceedingly pronounced at high latitudes in May and June. The most recent four Mays have had four of the five lowest NH SCEs on record, with Eurasian (Eur) SCE at a record low in 2013. North American (NA) SCE achieved a record minimum in May 2010, but of late has not been as consistently low as over Eur. The past six Junes have seen record minimum SCEs over the NH and Eur, with five of these six Junes the lowest over NA.  The recent early timing of arctic snowmelt appears to be occurring at an equivalent if not greater pace than the loss of summer Arctic sea ice extent.

While when projecting snow melt discharge it is much preferable to know the water equivalent of a snowpack (SWE) rather than its extent, the response of streamflow to seasonal SCE changes has been found to be significant within large basins in Siberia and the North American arctic.  Along with an overview of continental SCE kinematic, this hydrological relationship will be examined in this presentation, along with results looking at satellite microwave derived SWE and discharge, which also show promising results on a large scale. 


Sunday, December 29, 2013

Snowflakes (is Christmas time after all, and I live in a boreal place)

Christmas time remembered me to give a look to snow crystal formation literature and models. To my surprise, a definitive (thermodynamic) theory of their formation does not exist. This is what can be deduced form the review paper by the K.G. Libbrecht (2005).  Even if in two subsequent papers (2012 and 2013) he tries to delineate a possible path towards a comprehensive theory. Actually the attention to Libbrecht paper was brought to me by a paper on a three-dimensional model of snow-fakes (fakes ;-), not flakes) by Gravner and Griffeath. For a classification of snow crystal, Magono paper, would be fine. I am looking forward to read them all (starting from the Libbrecht review and his two most recent papers, which seem to add something) and complete this post more appropriately eventually. For the moment, be happy with the bibliography.

Some of the  references could look strange (e.g. Fu et al., 2006). In that case, I was looking for literature in the area of fractal surfaces. Something else should be available.  In particular, I was looking for a papers by J. Nittman and  Eugene Stanley (a "star" among the "fractalists"). In any case, growth of this type of forms is pretty general and ubiquitous (as shown in many papers, and in particular, in Ben Jacob's ones).

I also indulged in adding some papers about snow crystal methamorphism. This is not the topic of the post, but for the moment I keep trace of them in here. Other papers were just added for getting some general reference to crystal growth (e.g. the Krug's one, and those looking to micro-meteorological aspects of the growth).

Interesting readings are also addressed in this older post.



References

Ben Jacob, E. (1993). From snowflake formation to growth of bacterial colonies: Part I. Diffusive patterning in azoic systems. Contemporary Physics, 34(5), 247–273. doi:10.1080/00107519308222085

Ben-Jacob, E. (1997). From snowflake formation to growth of bacterial colonies II: Cooperative formation of complex colonial patterns. Contemporary Physics, 38(3), 205–241. doi:10.1080/001075197182405

Chen, J. P., & Lamb, D. (1994). Simulation of Cloud Microphisical and Chemical Processes using a Multicomponent Framework. Part I: Description of the Microphysical Model. Journal of the Atmospheric Sciences, 51(18), 2613–2630.

Chen, S., & Baker, I. (2010). Evolution of individual snowflakes during metamorphism. Journal of Geophysical Research, 115(D21), D21114. doi:10.1029/2010JD014132

Fu, F., Liu, L., Yang, K., & Wang, L. (2006). The structure of the self-organized blogosphere. arXiv:Physics, 1–5.

Fukuta, N., & Takahashi, T. (1999). The Growth of Atmospheric Ice Crystals: A Summary of Findings in Vertical Supercooled Cloud Tunnel Studies. Journal of the Atmospheric Sciences, 56(12), 1963–1979. doi:10.1175/1520-0469(1999)056<1963:TGOAIC>2.0.CO;2

Gravner, J., & Griffeath, D. (2007). Modeling snow crystal growth III: three dimensional  snow fakes. arXiv:Physics, 1–39.

Gravner, J., & Griffeath, D. (2009a). Modeling snow-crystal growth: A three-dimensional mesoscopic approach. Physical Review E, 79(1), 011601. doi:10.1103/PhysRevE.79.011601

Krug, J. (2002). Four Lectures on the Physics of Crystal GrowtharXivcond-Math, 1–43.

Libbrecht, K. G. (2005). The physics of snow crystals. Reports on Progress in Physics. doi:10.1088/0034-4885/68/4/R03
Libbrecht, K. G. (2013a). Aerodynamical Effects in Snow Cristal Growthth. arXiv:Physics, 1–23.

Libbrecht, K. G. (2013b). Toward a Comprehensive Model of Snow Crystal Growth Dynamics: 2. Structure Dependent Attachment Kinetics near -5 C. arXivcond-Math, 1–13.

Magono, C., & Lee, C. W. (1966). Meterological Classification of Natural Snow Crystals. Journal Of the Faculty of Sciences, Hokkaido University, Japan, 2(4), 312–345.

Nelson, J. (2005). Branch Growth and Sidebranching in Snow Crystals. Crystal Growth & Design, 5(4), 1509–1525. doi:10.1021/cg049685v

Nittmann, J., & Stanley, H. E. (1987). Non-deterministic approach to anisotropic growth patterns with continuously tunable morphology: the fractal properties of some real snowflakes. Journal of Physics a: Mathematical Genereral

Nelson, J., & Knight, C. (1998). Snow Crystal Habit Changes Explained by Layer Nucleation. Journal of the Atmospheric Sciences, 55(8), 1452–1465. doi:10.1175/1520-0469(1998)055<1452:schceb>2.0.co;2

Rango, A., P, W. W., & Erbe, E. F. (1996). Snow crystal imaging using scanning electron microscopy: I. Precipitated snow. Hydrological Sciences–Journal–Des Sciences Hydrologiques, 41(2), 219–233.

Rango, A., P, W. W., & Erbe, E. F. (1996b), Snow crystal imaging using scanning  electron microscopy: II. Metamorphosed snowHydrological Sciences–Journal–Des Sciences Hydrologiques41(2), 235–250.

Reiter, C. A. (2005). A local cellular model for snow crystal growth. Chaos Solitons & Fractals, 23(4), 1111–1119. doi:10.1016/j.chaos.2004.06.071

Friday, May 24, 2013

The Snow Water Equivalent (NewAGE-SWE) model component in JGrass-NewAGE

This is, at the moment, a stub prepared to contain the material related to the paper provisionally entitled: The Cache La Poudre snow water equivalent modelling with JGrass-NewAGE.

The paper has been finally submitted to GMD, and the Discussion Manuscript is therefore visible to everybody on GMDD. The revised version of the paper can be seen instead here.


Here the abstract of the revised paper: "The paper presents a package of a modified temperature index based snow water equivalent model as part of the hydrological modeling system NewAge-JGrass. 35 Three temperature-based snow models are integrated in the
NewAge-JGrass modeling system and use many of its com- ponents such as those for radiation balance (SWRB), kriging (KRIGING), automatic calibration algorithms (particle swarm optimization), and tests of goodness of fit (NewAge-V), to build suitable modelling solutions (MS). Similarly to all the NewAge-JGrass components, the models can be exe- cuted both in raster and in vector mode. The simulation time step can be daily, hourly or sub-hourly, depending on user needs and availability of input data. The MS are applied on the Cache la Poudre river basin (CO, USA) using three test applications. First, daily snow water equivalent is simulated for three different measurement stations for two snow model formulations. Second, hourly snow water equivalent is sim- ulated using all the three different snow model formulations. Finally a raster mode application is performed to compute snow water equivalent maps for the whole Cache la Poudre basin. In all the applications the model performance is satis- factory in terms of goodness of fit relative to measured snow water equivalent time series and the results, and the differences in performances of the different modelling solutions are discussed."


The model, the data, and the simulations' scripts used in the paper will be made available through the appropriate links from this page in order to let people reproduce our results. In fact, we call it Reproducible Research. It is certainly a challenging strategy for any researcher, and sometimes data cannot be disclosed. However, I said what I said, and this is a couple of old posts which fully explain my position (About Scientific Software, No code - No paper).

Saturday, September 29, 2012

My Past Research on Cryopheric Hydrology


In [J22] it was demonstrated that a single-layer snowpack model can be sufficiently accurate in describing the evolution of the water equivalent of the snow, as long as the incident radiation is calculated accurately taking care of shadows and the complexity of mountain topography.


Subsequently, the single-layer model was replaced with a multilayer model in order to forecast the evolution of density and of metamorphism of the snow as well as the percolation phenomena within the snowpack, during the thesis of Stefano Endrizzi. Among the various studies carried out, one validates the snow model satellite data derived from MODIS [A41].  Furthermore, the same model was used to study the hydrological evolution of glaciers in Trentino (Alpine) and South America (Equatorial) [A39, A47].  Eventually, the modeling of the cryosphere moved towards considering evolutive processes of permafrost [thesis of Matteo Dall'Amico, and J30], that is the layer of soil subject to temperatures below zero centigrades for more than two consecutive years.  All of these research projects, as well as allowing the aforementioned studies, are necessary to modeling the entire yearly hydrological cycle in mountain environments such as Trentino.

[J30], drawing from an accurate work of reanalysis of process thermodynamics, implements a robust method for the integration of the freezing-soil equation.  The numeric algorithm used is globally convergent Newtonian method that is appropriate for the equations under study.  [J36] is a geomorphological survey of rock glaciers in Trentino, to be subsequently modelled with GEOtop.

References in English


[ J22] - Zanotti, F., Endrizzi, S, Bertoldi, G. e R. Rigon, The GEOTOP snow module, Hydrol. Proc., 18, 3667-3679 (2004), DOI 10.1002/hyp.5794

[j30]- M. Dall’Amico, S. Endrizzi, S. Gruber, and R. Rigon, An energy-conserving model of freezing variably-saturated soil, The Cryosphere, 5, 469-484, 2011, doi:10.5194/tc-5-469-2011

[J36] - R. Seppi, A. Carton, M. Zumiani, M. Dall’Amico, G. Zampedri, R. Rigon, "Inventory, distribution and topographic features of rock glaciers in the southern region of the Eastern Italian Alps (Trentino)" in Geografia Fisica e Dinamica Quaternaria, v. 2012, n. 35(2) (In press)

[A41] Endrizzi S., Bertoldi G., Neteler M., and Rigon R., Snow Cover Patterns and Evolution at Basin Scale: GEOtop Model Simulations and Remote Sensing Observations, Proceedings of the 63th Eastern Snow Conference,


References in Italian

[A47] Noldin I., Endrizzi S., Rigon R., Dall’Amico M, Sistema di drenaggio di un ghiacciaio alpino, Neve e Valanghe, n. 69, 48-52, 2010



Friday, May 25, 2012

Remote Sensing of Snow

Preparing the slides for my hydrological class, and aiming to overview (just a little indeed) measurements methods, I discovered prof Hongjie Xie page, from which I withdraw some information. This was for me the excuse to copy and download some reference on passive microwaves and optical sensor dedicated to snow. Below it is a report of the page (with the bibliography a little edited to cope with available papers).

"Since the middle of the 1960’s, a number of satellite-derived snow products have been available, with a few available in near-real time through Internet (Bitner et al, 2002).
Space-board passive microwave radiometer, such as SMMR (Scanning Multichannel Microwave Radiometer), SSM/I (Special Sensor Microwave/Imager), and AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System), can penetrate clouds to detect microwave energy emitted by snow and ice and provide information on SWE or snow depth and thus estimating runoff (Pulliainen, 2006; Wulder et al., 2007). Since the 1970s, SWE retrieval from space-borne passive microwave has been investigated Space-borne passive microwave data are well suited to snow cover monitoring because of characteristics such as all weather imaging, a wide swath width with frequent overpass times, and a long available time series (Derksen et al., 2004). But the coarse spatial resolution (25 km of AMSR-E is the best available now) hinders their application in operational hydrological modeling and snow-caused disasters monitoring (Foster et al., 2003; Dressler, et al. 2006; Pulliainen,2006). Optical sensors such as AVHRR (Advanced Very High Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectraradiometer), SPOT and Landsat have been well developed to produce snow cover maps with high spatial resolution (Salonmonson & Appel, 2004; Brown et al., 2007; Dozier&Painter, 2004). But due to the inherent limitation, optical sensors cannot see the earth surface when cloud is present. High cloud blockage becomes the biggest problem in applying snow products from optical sensor (Klein & Barnett, 2003; Zhou et al., 2005; Tekeli et al., 2005; Ault et al., 2006; Liang et al. 2008 a, b; Wang et al., 2008a, b; Wang and Xie 2009)"

Bibliography

Ault T.W.,⁎, Czajkowski K.P., Benko T., Coss J., Struble J., Spongberg A., Templin M.,  Gross C., Validation of the MODIS snow product and cloud mask using student and NWS cooperative station observations in the Lower Great Lakes Region, Remote Sensing of Environment 105 (2006) 341–353

Bitner D., T. Carroll, D. Cline and P. Romanov, 2002: An assessment of the differences between 
three satellite snow cover mapping techniques, Hydrological Processes 16:3723–3733.

Brown R., Derksen C., Wang L, Assessment of spring snow cover duration variability over northern Canada from satellite datasets,  Remote Sensing of Environment 111 (2007) 367–381

C. Derksen C.,Brown, R., Walker A., Merging Conventional (1915–92) and Passive Microwave (1978–2002) Estimates of Snow Extent and Water Equivalent over Central North America, Journal of Hydromet, 5,  2004, 850-861

Dozier J,  Painter T.H, Multispectral and hyperspectral remote sensing of alpine snow, Annu. Rev. Earth Planet. Sci. 2004. 32:465–94 doi: 10.1146/annurev.earth.32.101802.120404

Dressler,K. A., Leavesley,G. H.,  Bales R. C. and Fassnacht S. R., Evaluation of gridded snow water equivalent and satellite snow cover products for mountain basins in a hydrologic model, Hydrol. Process. 20, 673–688 (2006)

Foster, J.L.,  Sunb C., Walkerd J.P.,  Kelly R., Changa A., Dong J.,  Powell U, Quantifying the uncertainty in passive microwave snow water equivalent observations, Remote Sensing of Environment 94 (2005) 187–203

Klein A, Barnett A.C., Validation of daily MODIS snow cover maps of the Upper Rio Grande River Basin for the 2000–2001 snow year, Remote Sensing of Environment 86 (2003) 162–176

Liang T., Zhang X., Xie X, Wu C., Feng Q, Huang X, Chen Q., Toward improved daily snow cover mapping with advanced combination of MODIS and AMSR-E measurements, Remote Sensing of Environment xxx (2008) xxx-xxx

Pulliainen J., Mapping of snow water equivalent and snow depth in boreal and sub-arctic zones by assimilating space-borne microwave radiometer data and ground-based observations, Remote Sensing of Environment, Volume 101, Issue 2, 30 March 2006, Pages 257-269, ISSN 0034-4257, 10.1016/j.rse.2006.01.002.

Salomonson V.V, Appel, I., Estimating fractional snow cover from MODIS using the normalized difference snow index, Remote Sensing of Environment 89 (2004) 351 – 360

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