Performance evaluation of gridded climate data in snow-melt models calibrated by spatial snow-cover observations from MODIS

2021 ◽  
Author(s):  
Dhiraj Raj Gyawali ◽  
András Bárdossy
Keyword(s):  
Temporal Stability ◽  
High Sensitivity ◽  
Delta Method ◽  
Snow Melt ◽  
Climate Data ◽  
Data Intensive ◽  
Mountainous Regions ◽  
Physically Based ◽  
Snow Distribution ◽  
Wide Scale

<p>Considering the snow effect on land and atmospheric processes, accurate representation of seasonal snow evolution including the distribution and melt volume, is highly imperative to strengthen water resources development trajectories in mountainous regions. However, along with the high sensitivity to climate change, the limitation of reliable snow-melt estimation in these regions is further exacerbated with data scarcity. This study thus attempts to develop relatively simpler degree-day snow-models driven by freely available gridded datasets for data scarce snow-fed regions. The methodology uses readily available MODIS imageries to calibrate the snow-melt models on snow-distribution instead of snow-amount. In addition, freely available cloud masks from geostationary satellites are also used to complement the snow-melt models. The major advantage of this approach is the possibility of regional calibration using freely available reasonably accurate climate data, without the need of direct snow depth measurements. These models offer relative simplicity and plausible alternatives to data intensive physically based model as well as in-situ measurements and have a wide scale applicability allowing immediate verification with point measurements.</p><p>Bavaria region in Germany is selected for this study.  E-OBS (European Observations) gridded precipitation and temperature datasets (0.25 degrees) are considered here instead of the ground measured data to replicate “a data scarce scenario” as in most of the mountainous regions around the globe. The coarser meteorological inputs are downscaled applying the delta method using WorldClim monthly climate surfaces to 0.0833 degrees (~1km) grids. MODIS images are also resampled and upscaled to 1km resolution for uniformity. The qualitative pixel-to-pixel comparison suggest a very good agreement with MODIS data and the calibrated parameter sets depict plausible temporal stability.</p><p>The snow-melt volume will be further used in HBV hydrological model as standalone input to simulate the streamflow in one of the snow-fed catchments in Bavaria and to evaluate the performance of this approach in streamflow. The abstract will the updated as soon as the results are available.</p>

scholarly journals Development and parameter estimation of snowmelt models using spatial snow-cover observations from MODIS

2021 ◽  
Author(s):  
Dhiraj Raj Gyawali ◽  
András Bárdossy
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Mean Squared Error ◽  
Snow Melt ◽  
Data Intensive ◽  
Degree Day ◽  
Snow Water ◽  
Snow Distribution ◽  
Wide Scale ◽  
The Time Domain

Abstract. Given the importance of snow on different land and atmospheric processes, accurate representation of seasonal snow evolution including distribution and melt volume, is highly imperative to any water resources development trajectories. The limitation of reliable snow-melt estimation in these regions is however, further exacerbated with data scarcity. This study attempts to develop relatively simpler extended degree-day snow-models driven by freely available snow cover images in snow-dominated regions. This approach offers relative simplicity and plausible alternative to data intensive models as well as in-situ measurements and have a wide scale applicability, allowing immediate verification with point measurements. The methodology employs readily available MODIS composite images to calibrate the snow-melt models on snow-distribution in contrast to the traditional snow-water equivalent based calibration. The spatial distribution of snow cover is simulated using different extended degree-day models calibrated against MODIS snow-cover images for cloud-free days or a set of images representing a period within the snow season. The study was carried out in Baden-Württemberg in Germany, and in Switzerland. The simulated snow cover show very good agreement with MODIS snow cover distribution and the calibrated parameters exhibit relative stability across the time domain. The snow-melt from these calibrated models were further used as standalone inputs to a “truncated” HBV without the snow component in Reuss (Switzerland), and Horb and Neckar (Baden-Wuerttemberg) catchments, to assess the performance of the melt outputs in comparison to a calibrated standard HBV model. The results show slight increase in overall NSE performance and a better NSE performance during the winter. Furthermore, 3–15 % decrease in mean squared error was observed for the catchments in comparison to the results from standard HBV. The increased NSE performance, albeit less, can be attributed to the added reliability of snow-distribution coming from the MODIS calibrated outputs. This paper highlights that the calibration using readily available images used in this method allows a flexible regional calibration of snow cover distribution in mountainous areas across a wide geographical extent with reasonably accurate precipitation and temperature data. Likewise, the study concludes that simpler specific alterations to processes contributing to snow-melt can contribute to identifying the snow-distribution and to some extent the flows in snow-dominated regimes.

scholarly journals Numerical modeling of blowing and drifting snow in Alpine terrain

2001 ◽  
Vol 47 (156) ◽  
pp. 97-110 ◽  
Author(s):  
Peter Gauer
Keyword(s):  
Field Measurements ◽  
Erosion And Deposition ◽  
Mountainous Regions ◽  
Boundary Layer Equations ◽  
Trajectory Calculations ◽  
Drifting Snow ◽  
Physically Based ◽  
Turbulent Closure ◽  
Snow Distribution ◽  
Two Layer Model

AbstractIn mountainous regions, snow transport due to wind significantly influences snow distribution and, as a result, avalanche danger. A physically based numerical two-layer model is developed to simulate blowing and drifting snow in Alpine terrain. One layer describes the driving-wind field and the transport in suspension. The description is based on the atmospheric boundary-layer equations, using ane−∊model for the turbulent closure. The second layer describes the transport due to saltation, including erosion and deposition of snow. Here, conservation equations for mass and momentum are formulated for the mixture of snow and air. Particle trajectory calculations are used to parameterize quantities characterizing the saltation layer. Both layers are mutually coupled by boundary conditions. A two-way coupling between particles and airflow is taken into account. Comparisons between simulation results and field measurements around an Alpine crest show encouraging results.

Problems in Developing a Physically Based Snowmelt Model

1975 ◽  
Vol 2 (4) ◽  
pp. 474-488 ◽  
Author(s):  
D. H. Male ◽  
Don M. Gray
Keyword(s):  
Simulation Models ◽  
Distribution Patterns ◽  
Streamflow Forecasting ◽  
Mountainous Regions ◽  
Thaw Cycle ◽  
Exchange Processes ◽  
Mass Transfer Processes ◽  
Physically Based ◽  
Freeze Thaw Cycle ◽  
Snow Distribution

Over the past few years several snowmelt simulation models have been developed as an aid to streamflow forecasting in mountainous regions. This paper describes the major difficulties encountered when simulation of Prairie snowmelt conditions is attempted, not only for the purpose of forecasting streamflow, but also soil moisture, evaporation, and snow distribution patterns. Simulation is discussed in terms of the energy equation for the snowpack and it is shown that the improvement of the model depends on the following factors: (i) the adjustment of the radiation flux at the snow surface for slope and aspect, (ii) the development of procedures which will allow estimates of the areal distribution of sensible heat, (iii) successful modelling of the diurnal freeze–thaw cycle common to Prairie snowpacks, (iv) an investigation of the energy exchange processes during the period when the snow cover is discontinuous or patchy, (v) knowledge of the coupling of heat and mass transfer processes in frozen soils, and (vi) the extrapolation of point estimates of significant parameters to an areal basis.

Modeling spatial snow-cover distribution using snow-melt models and MODIS images

2020 ◽  
Author(s):  
Dhiraj Raj Gyawali ◽  
András Bárdossy
Keyword(s):  
Spatial Distribution ◽  
Snow Cover ◽  
Snow Depth ◽  
Region Of Interest ◽  
High Sensitivity ◽  
Distribution Data ◽  
Depth Information ◽  
Snow Melt ◽  
Snow Hydrology ◽  
Snow Distribution

<p>Reliable representations of spatial distribution of snow and subsequent snow-melt are critical challenges for hydrological estimations, given their crucial relevance in mountainous regimes especially because of the high sensitivity to climate change. Relatively accurate physically based models are data intensive while in-situ measurements of snow-depth are prone to be non-representative due to local influences. Likewise, lack of snow-depth information and to some extent, cloud cover in the mountains limit the usage of Remote-sensing images in snow estimation. Against this backdrop, this work presents a methodology incorporating available remotely-sensed images (MODIS Snow-cover products) and simple distributed snow-melt models to estimate a time-continuous spatial snow extent in snow dominated regimes. </p><p>The methodology employs relatively cloud-free MODIS composite images to calibrate the spatial distribution of snow simulated by different distributed degree-day models. These variants of models are run in a domain of 500m x 500m grids, and incorporate daily precipitation, daily min-, max- and mean temperatures, and daily radiation data interpolated onto the aforementioned grids. Variations in the models include a simple degree model followed by incorporation of different aspects governing snow hydrology such as precipitation induced melt, radiation, topography, and land use.  The modeled snow depths in each grid are reclassified to ‘1’ (snow depths above a threshold) and ‘0’ (no snow), and calibrated against MODIS snow-cover for cloud-free days with snow. Snow-melt parameters are then estimated for the region of interest. The result is a spatial snow-cover distribution time-series. This approach is replicated in different regions viz. Baden-Württemberg and Bavaria in Germany, and in Switzerland. Results suggest good agreement with MODIS data and the parameters show relative stability across the time domain at the same sites and are transferrable to other regions. Calibration using readily available images used in this method offers adequate flexibility, albeit the simplicity, to calibrate snow distribution in mountainous areas across a wide geographical extent with reasonably accurate precipitation and temperature data. The final validated spatial snow-distribution data can be, as a stand-alone input, coupled with distributed hydrological models to reliably estimate streamflow in data-scarce mountainous catchments.</p>

scholarly journals Climate change and freshwater ecosystems in Oceania: an assessment of vulnerability and adaptation opportunities.

2011 ◽  
Vol 17 (3) ◽  
pp. 201 ◽  
Author(s):  
K M Jenkins ◽  
R T Kingsford ◽  
G P Closs ◽  
B J Wolfenden ◽  
C D Matthaei ◽  
...  
Keyword(s):  
Climate Change ◽  
New Zealand ◽  
Sea Level ◽  
Pacific Islands ◽  
Environmental Flows ◽  
Freshwater Ecosystems ◽  
Freshwater Wetlands ◽  
Snow Melt ◽  
Mountainous Regions ◽  
Elevated Salinity

Human-forced climate change significantly threatens the world’s freshwater ecosystems, through projected changes to rainfall, temperature and sea level. We examined the threats and adaptation opportunities to climate change in a diverse selection of rivers and wetlands from Oceania (Australia, New Zealand and Pacific Islands). We found common themes, but also important regional differences. In regulated floodplain rivers in dry regions (i.e. Australia), reduced flooding projected with climate change is a veneer on current losses, but impacts ramp up by 2070. Increasing drought threatens biota as the time between floods extends. Current measures addressing water allocations and dam management can be extended to adapt to climate change, with water buy-back and environmental flows critical. Freshwater wetlands along coastal Oceania are threatened by elevated salinity as sea level rises, potentially mitigated by levee banks. In mountainous regions of New Zealand, the biodiversity of largely pristine glacial and snow melt rivers is threatened by temperature increases, particularly endemic species. Australian snow melt rivers face similar problems, compounding impacts of hydro-electric schemes. Translocation of species and control of invasive species are the main adaptations. Changes to flow regime and rising water temperatures and sea levels are the main threats of climate change on freshwater ecosystems. Besides lowering emissions, reducing impacts of water consumption and protecting or restoring connectivity and refugia are key adaptations for conservation of freshwater ecosystems. Despite these clear imperatives, policy and management has been slow to respond, even in developed regions with significant resources to tackle such complex issues.

scholarly journals Strong Snow-Storms, their Effect on Snow Cover and Snow Accumulation

1977 ◽  
Vol 19 (81) ◽  
pp. 441-449
Author(s):  
A.K. Dyunin ◽  
B.A. Anfilofiyev ◽  
M. G. Istrapilovich ◽  
N.T. Mamayeva ◽  
YA. D. Kvon
Keyword(s):  
Decisive Role ◽  
Snow Accumulation ◽  
Glacier Mass Balance ◽  
Mountainous Regions ◽  
Wind Speeds ◽  
Snow Distribution ◽  
Snow Storm ◽  
Field And Laboratory Conditions ◽  
Snow Storms

AbstractSnow-drifts have been studied by many researchers both in field and laboratory conditions, however these investigations have been carried out mostly at wind speeds up to 20 m/s whereas in many areas of our planet snow-storms occur at winds up to 40 m/s and more. During the winter seasons of 1972-76 the authors carried out a great number of experiments with an artificial snow-storm in a special wind tunnel 27 m long. The wind speeds reached 40 m/s (60-65 m/s at the 10 m anemometer height). The existing theories and hypotheses of snow-drifting, and in particular the “diffusion" model, were tested in a series of the experiments. These have not confirmed the assumption of the Australian scientists on the decisive role of diffusion in drift mechanism at large wind speeds. The problem of strong snow-storm effect on snow accumulation on avalanche-danger slopes, in particular, wind redistribution of snow is no less important.The results obtained may be used for the determination of snow accumulation in avalanche starting zones due to deflation. This is especially important for forecasting very dangerous and frequently-occurring avalanches due to snow-storms. The investigations performed enable us to estimate the snow deposition produced by strong and superstrong snow-storms, to account for the peculiarities of such snow-storms and the means of protection, to forecast snow distribution in mountainous regions, and to define the role of snow-storms in glacier mass balance.

scholarly journals Practices and Strategies for Adaptation to Climate Variability in Family Farming. An Analysis of Cases of Rural Communities in the Andes Mountains of Colombia and Chile

Agriculture ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1096
Author(s):  
Carla Marchant Santiago ◽  
Paulina Rodríguez Díaz ◽  
Luis Morales-Salinas ◽  
Liliana Paz Betancourt ◽  
Luis Ortega Fernández
Keyword(s):  
Rural Communities ◽  
Climate Variability ◽  
Methodological Approach ◽  
Climate Data ◽  
Family Farming ◽  
Mountainous Regions ◽  
The Andes ◽  
Adaptation Practices ◽  
Self Production

Climate variability imposes greater challenges on family farming and especially on rural communities in vulnerable mountainous regions such as the Andes in Latin America. Changes in rainfall patterns and fluctuations in temperatures cause a greater frequency of extreme events, increased pests, and crop diseases, which even lead to food insecurity in communities that depend on self-production for survival. This is why strategies need to be developed to face this new scenario. Two cases of adaptation experiences to the effects of climate variability in rural communities in Chile (Araucanía Region) and Colombia (Cauca Department) were analyzed on this paper. For this, a mixed methodological approach was adopted that included the analysis of climate data, socioeconomic, and productive characterization of the communities, and a characterization of adaptation practices for both cases. The results show various ways of adapting mainly to changes in the availability and access of water for the development of agriculture and for domestic use. Likewise, it is shown that in order to be successful, the measures for facing climate variability must be part of coordinated strategies under a community-based adaptation approach and not developed in isolation.

scholarly journals Temperature and rainfall estimates for past 18 000 years in Owens Valley, California with a coupled catchment–lake model

2015 ◽  
Vol 12 (7) ◽  
pp. 6505-6539 ◽  
Author(s):  
Z. Yu ◽  
W. Dong ◽  
P. Jiang
Keyword(s):  
General Circulation ◽  
Regional Climate ◽  
Circulation Model ◽  
Climate Data ◽  
Owens Valley ◽  
Climatic Fluctuations ◽  
Closed Basin ◽  
The Past ◽  
Lake Model ◽  
Physically Based

Abstract. Closed-basin lakes are intricately linked to the hydrological systems and are very sensitive recorders of local hydro-climatic fluctuations. Lake records in closed-basins are usually used to investigate the paleoclimate condition which is critical for understanding the past and predicting the future. In this study, a physically based catchment–lake model was developed to extract quantitative paleoclimate information including temperature and rainfall over the past 18 000 years (ka) from lake records in a hydrologically closed basin in the Owens River Valley, California, US. The initial model inputs were prepared based on current regional climate data, boundary conditions from the General Circulation Model, and fossil proxy data. The inputs subsequently were systematically varied in order to produce the observed lake levels. In this way, a large number of possible paleoclimatic combinations can quickly narrow the possible range of paleoclimatic combinations that could have produced the paleolake level and extension. Finally, a quantitative time-series of paleoclimate information for those key times was obtained.

scholarly journals Strong Snow-Storms, their Effect on Snow Cover and Snow Accumulation

1977 ◽  
Vol 19 (81) ◽  
pp. 441-449 ◽  
Author(s):  
A.K. Dyunin ◽  
B.A. Anfilofiyev ◽  
M. G. Istrapilovich ◽  
N.T. Mamayeva ◽  
YA. D. Kvon
Keyword(s):  
Decisive Role ◽  
Snow Accumulation ◽  
Glacier Mass Balance ◽  
Mountainous Regions ◽  
Wind Speeds ◽  
Snow Distribution ◽  
Snow Storm ◽  
Field And Laboratory Conditions ◽  
Snow Storms

Abstract Snow-drifts have been studied by many researchers both in field and laboratory conditions, however these investigations have been carried out mostly at wind speeds up to 20 m/s whereas in many areas of our planet snow-storms occur at winds up to 40 m/s and more. During the winter seasons of 1972-76 the authors carried out a great number of experiments with an artificial snow-storm in a special wind tunnel 27 m long. The wind speeds reached 40 m/s (60-65 m/s at the 10 m anemometer height). The existing theories and hypotheses of snow-drifting, and in particular the “diffusion" model, were tested in a series of the experiments. These have not confirmed the assumption of the Australian scientists on the decisive role of diffusion in drift mechanism at large wind speeds. The problem of strong snow-storm effect on snow accumulation on avalanche-danger slopes, in particular, wind redistribution of snow is no less important. The results obtained may be used for the determination of snow accumulation in avalanche starting zones due to deflation. This is especially important for forecasting very dangerous and frequently-occurring avalanches due to snow-storms. The investigations performed enable us to estimate the snow deposition produced by strong and superstrong snow-storms, to account for the peculiarities of such snow-storms and the means of protection, to forecast snow distribution in mountainous regions, and to define the role of snow-storms in glacier mass balance.

scholarly journals Reconciling Flagging Strategies for Multi-Sensor Satellite Soil Moisture Climate Data Records

2020 ◽  
Vol 12 (20) ◽  
pp. 3439
Author(s):  
Mendy van der Vliet ◽  
Robin van der Schalie ◽  
Nemesio Rodriguez-Fernandez ◽  
Andreas Colliander ◽  
Richard de Jeu ◽  
...  
Keyword(s):  
Soil Moisture ◽  
European Space Agency ◽  
Data Availability ◽  
Climate Data ◽  
Mountainous Regions ◽  
Soil Moisture Data ◽  
Climate Records ◽  
The Individual ◽  
The Impact

Reliable soil moisture retrievals from passive microwave satellite sensors are limited during certain conditions, e.g., snow coverage, radio-frequency interference, and dense vegetation. In these cases, the retrievals can be masked using flagging algorithms. Currently available single- and multi-sensor soil moisture products utilize different flagging approaches. However, a clear overview and comparison of these approaches and their impact on soil moisture data are still lacking. For long-term climate records such as the soil moisture products of the European Space Agency (ESA) Climate Change Initiative (CCI), the effect of any flagging inconsistency resulting from combining multiple sensor datasets is not yet understood. Therefore, the first objective of this study is to review the data flagging system that is used within multi-sensor ESA CCI soil moisture products as well as the flagging systems of two other soil moisture datasets from sensors that are also used for the ESA CCI soil moisture products: The level 3 Soil Moisture and Ocean Salinity (SMOS) and the Soil Moisture Active/Passive (SMAP). The SMOS and SMAP soil moisture flagging systems differ substantially in number and type of conditions considered, critical flags, and data source dependencies. The impact on the data availability of the different flagging systems were compared for the SMOS and SMAP soil moisture datasets. Major differences in data availability were observed globally, especially for northern high latitudes, mountainous regions, and equatorial latitudes (up to 37%, 33%, and 32% respectively) with large seasonal variability. These results highlight the importance of a consistent and well-performing approach that is applicable to all individual products used in long-term soil moisture data records. Consequently, the second objective of the present study is to design a consistent and model-independent flagging strategy to improve soil moisture climate records such as the ESA CCI products. As snow cover, ice, and frozen conditions were demonstrated to have the biggest impact on data availability, a uniform satellite driven flagging strategy was designed for these conditions and evaluated against two ground observation networks. The new flagging strategy demonstrated to be a robust flagging alternative when compared to the individual flagging strategies adopted by the SMOS and SMAP soil moisture datasets with a similar performance, but with the applicability to the entire ESA CCI time record without the use of modelled approximations.

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