scholarly journals Evaluating Predictor Strategies for Regression-Based Downscaling with a Focus on Glacierized Mountain Environments

2017 ◽  
Vol 56 (6) ◽  
pp. 1707-1729 ◽  
Author(s):  
Marlis Hofer ◽  
Johanna Nemec ◽  
Nicolas J. Cullen ◽  
Markus Weber
Keyword(s):  
Large Scale ◽  
Global Radiation ◽  
Local Scale ◽  
Forecast Skill ◽  
Model Complexity ◽  
High Mountain ◽  
European Alps ◽  
Limited Information ◽  
Mountain Environments ◽  
Measuring Site

AbstractThis study explores the potential of different predictor strategies for improving the performance of regression-based downscaling approaches. The investigated local-scale target variables are precipitation, air temperature, wind speed, relative humidity, and global radiation, all at a daily time scale. Observations of these target variables are assessed from three sites in close proximity to mountain glaciers: 1) the Vernagtbach station in the European Alps, 2) the Artesonraju measuring site in the tropical South American Andes, and 3) the Mount Brewster measuring site in the Southern Alps of New Zealand. The large-scale dataset being evaluated is the ERA-Interim dataset. In the downscaling procedure, particular emphasis is put on developing efficient yet not overfit models from the limited information in the temporally short (typically a few years) observational records of the high mountain sites. For direct (univariate) predictors, optimum scale analysis turns out to be a powerful means to improve the forecast skill without the need to increase the downscaling model complexity. Yet the traditional (multivariate) predictor sets show generally higher skill than the direct predictors for all variables, sites, and days of the year. Only in the case of large sampling uncertainty (identified here to particularly affect observed precipitation) is the use of univariate predictor options justified. Overall, the authors find a range in forecast skill among the different predictor options applied in the literature up to 0.5 (where 0 indicates no skill, and 1 represents perfect skill). This highlights that a sophisticated predictor selection (as presented in this study) is essential in the development of realistic, local-scale scenarios by means of downscaling.

scholarly journals Large-scale atmospheric forcing and topographic modification of precipitation rates over High Asia – a neural-network-based approach

2015 ◽  
Vol 6 (1) ◽  
pp. 61-81 ◽  
Author(s):  
L. Gerlitz ◽  
O. Conrad ◽  
J. Böhner
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Spatial Resolution ◽  
Large Scale ◽  
Local Scale ◽  
Predictor Variables ◽  
High Mountain ◽  
Target Area ◽  
Monthly Precipitation ◽  
Highly Nonlinear

Abstract. The heterogeneity of precipitation rates in high-mountain regions is not sufficiently captured by state-of-the-art climate reanalysis products due to their limited spatial resolution. Thus there exists a large gap between the available data sets and the demands of climate impact studies. The presented approach aims to generate spatially high resolution precipitation fields for a target area in central Asia, covering the Tibetan Plateau and the adjacent mountain ranges and lowlands. Based on the assumption that observed local-scale precipitation amounts are triggered by varying large-scale atmospheric situations and modified by local-scale topographic characteristics, the statistical downscaling approach estimates local-scale precipitation rates as a function of large-scale atmospheric conditions, derived from the ERA-Interim reanalysis and high-resolution terrain parameters. Since the relationships of the predictor variables with local-scale observations are rather unknown and highly nonlinear, an artificial neural network (ANN) was utilized for the development of adequate transfer functions. Different ANN architectures were evaluated with regard to their predictive performance. The final downscaling model was used for the cellwise estimation of monthly precipitation sums, the number of rainy days and the maximum daily precipitation amount with a spatial resolution of 1 km2. The model was found to sufficiently capture the temporal and spatial variations in precipitation rates in the highly structured target area and allows for a detailed analysis of the precipitation distribution. A concluding sensitivity analysis of the ANN model reveals the effect of the atmospheric and topographic predictor variables on the precipitation estimations in the climatically diverse subregions.

scholarly journals Large scale atmospheric forcing and topographic modification of precipitation rates over High Asia – a neural network based approach

2014 ◽  
Vol 5 (2) ◽  
pp. 1275-1317 ◽  
Author(s):  
L. Gerlitz ◽  
O. Conrad ◽  
J. Böhner
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Spatial Resolution ◽  
Large Scale ◽  
Local Scale ◽  
Predictor Variables ◽  
High Mountain ◽  
Target Area ◽  
Monthly Precipitation ◽  
The Tibetan Plateau

Abstract. The heterogeneity of precipitation rates in high mountain regions is not sufficiently captured by state of the art climate reanalysis products due to their limited spatial resolution. Thus there exists a large gap between the available data sets and the demands of climate impact studies. The presented approach aims to generate spatially high resolution precipitation fields for a target area in Central Asia, covering the Tibetan Plateau, the adjacent mountain ranges and lowlands. Based on the assumption, that observed local scale precipitation amounts are triggered by varying large scale atmospheric situations and modified by local scale topographic characteristics, the statistical downscaling approach estimates local scale precipitation rates as a function of large scale atmospheric conditions, derived from the ERA-Interim reanalysis, and high resolution terrain parameters. Since the relationships of the predictor variables with local scale observations are rather unknown and highly non-linear, an Artificial Neural Network (ANN) was utilized for the development of adequate transfer functions. Different ANN-architectures were evaluated with regard to their predictive performance. The final downscaling model was used for the cellwise estimation of monthly precipitation sums, the number of rainy days and the maximum daily precipitation amount with a spatial resolution of 1 km2. The model was found to sufficiently capture the temporal and spatial variations of precipitation rates in the highly structured target area and allows a detailed analysis of the precipitation distribution. A concluding sensitivity analysis of the ANN model reveals the effect of the atmospheric and topographic predictor variables on the precipitation estimations in the climatically diverse subregions.

scholarly journals Geodiversity of proglacial areas and implications on abiotic ecosystem services

2021 ◽  
Author(s):  
Irene Maria Bollati ◽  
Cristina Viani ◽  
Anna Masseroli ◽  
Giovanni Mortara ◽  
Bruno Testa ◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Building Materials ◽  
Holistic Approach ◽  
Ice Age ◽  
High Mountain ◽  
European Alps ◽  
Mountain Environments ◽  
Successional Species ◽  
Living Organisms ◽  
Different Response

<p>Proglacial areas, defined as the areas left free from glaciers since the Little Ice Age, are open-air laboratories to study the effects of climate change on high mountain environments. Their different abiotic features (i.e. geodiversity) depend mainly on the bedrock characteristics, the type of glaciers acting in the areas and the morphometry of their hydrographic basins, which influence the geomorphic dynamics (i.e., geomorphodiversity). From this, it could derive a different response of glacier forefields to deglaciation and particular evolutionary trends. Hydrological elements and dynamics are particularly variable (i.e. hydrogeodiversity), especially in terms of proglacial lakes diversification, having effects down-valley, even far from the strict proglacial area, and also in term of potential natural hazards. Moreover, geodiversity of proglacial areas may have implications on other types of “diversity”. After the glacier retreat, glacier forefields are, in fact, characterized by soils development and vegetation settlement. In particular, soils characterized by different ages and by different degree of development coexist over short distances (i.e. pedodiversity), functioning also as a support for living organisms. Biotic components gradually colonize such areas, from the pioneer to the late-successional species, bringing varied species along the proglacial plains (i.e. biodiversity). All these aspects can be discussed in the perspective of the abiotic ecosystem services (i.e. regulating, supporting, provisioning, and cultural) provided by glacier forefields. Regulating services are related to both atmospheric and terrestrial processes, including natural hazard regulation. Supporting services deal mainly with habitat provision and soils development. Provisioning services include both material (freshwater, building materials) and immaterial (i.e. tourism) resources. Finally, cultural services, that are the most numerous, take into account, among the others, the spiritual and historical meaning, the geohistorical importance for the Earth Sciences development, the educational and geotourism-related opportunities, and the landscape benefit effects. Considering all these aspects, and the intense dynamics proglacial areas are affected by, which will be illustrated through examples mainly from the European Alps, it emerges the importance of a careful monitoring and management of such areas, hopefully through an even more holistic approach.</p>

scholarly journals Assessing reliability of hydrological simulations through model intercomparison at the local scale in the Everest region

2017 ◽  
Author(s):  
Judith Eeckman ◽  
Santosh Nepal ◽  
Pierre Chevallier ◽  
Gauthier Camensuli ◽  
Francois Delclaux ◽  
...  
Keyword(s):  
Water Storage ◽  
Local Scale ◽  
High Mountain ◽  
Physical Processes ◽  
Central Himalayas ◽  
Mountain Environments ◽  
Mountain Catchment ◽  
Spatio Temporal ◽  
Surface Scheme ◽  
Downstream Communities

Abstract. Understanding hydrological processes of high-altitude areas is vital because downstream communities depend on water resources for their livelihood. This paper compares the hydrological responses at the local scale of two models using different degrees of refinement to represent physical processes in sparsely instrumented mountainous Himalayan catchments. Two small catchments located in mid- and high- mountain environments were chosen to represent the very different climatic and physiographic characteristics of the Central Himalayas in the Everest region of eastern Nepal. This work presents the novelty of applying, at a small spatio-temporal scale and under the same forcing conditions, a fully distributed surface scheme based on mass and energy balance equations (ISBA surface scheme), and a semi-distributed calibrated model (J2000 hydrological model). A new conceptual module coupled to the ISBA surface scheme for flow routing is presented. The results show that both models describe the evapotranspiration, quick runoff and discharge processes in a similar way. The reliability of the simulations for these variables can therefore be considered as satisfactory. The differences in the structure and results of the two models mainly concern the water storage and flows in the soil, in particular for the high-mountain catchment. This conclusion suggests that the uncertainty associated with model structure is significant for water storage and flow in the soil.

scholarly journals Webcams as a Remote Tool for Eco-ethological Research: A Study on the Alpine Chough

2021 ◽  
Vol 9 ◽  
Author(s):  
Cristina Vallino ◽  
Nigel Gilles Yoccoz ◽  
Antonio Rolando ◽  
Anne Delestrade
Keyword(s):  
Weather Conditions ◽  
High Elevation ◽  
Environmental Drivers ◽  
Daily Maximum ◽  
High Mountain ◽  
European Alps ◽  
Flock Size ◽  
Ski Resorts ◽  
Mountain Environments ◽  
Study Sites

Methods and devices specifically created for remote animal surveys and monitoring are becoming increasingly popular and effective. However, remote devices are also widely used in our societies for different, not scientific, goals. Ski resorts in the European Alps, for instance, use webcams to share panoramic views and promote themselves in the industry of winter recreational activities. We tested preinstalled webcam effectiveness as a remote tool for eco-ethological studies. Our target species was the Alpine Chough Pyrrhocorax graculus, a social and opportunistic corvid species of high mountain environments that attends ski resorts to feed on scraps discarded by high elevation bars and restaurants. We studied the effect of the winter presence of tourists and weather conditions on flocking behaviour at ski resorts. We used flock size and time spent at the ski resort as response variables, and assessed how strongly they were related to the number of tourists and weather conditions. We analysed about 13,500 pictures taken at 10 min intervals at three ski resorts sites in the European Alps in France, Italy and Switzerland. The number of birds was very different among the three study sites. Flock size and time spent were related to the same environmental drivers, but with different effect sizes in the three areas. The daily maximum flock size and the time spent at ski resorts increased with the number of tourists and decreased with temperature at two sites out of three. We also found that the presence of fresh snow caused a decrease in the maximum flock size in all ski resorts. In conclusion, Alpine Choughs modulated their presence at the ski resorts according to human presence and weather conditions, but these responses were context-dependent. Preinstalled webcams, despite a few caveats, can therefore be successfully employed in eco-ethological research. Webcams around the world are increasing in number and represent therefore a large potential resource. If webcam companies could be engaged to make some slight adjustments, without compromising their goals, then this could offer a new way to collect eco-ethological data.

scholarly journals Subseasonal Forecasts of the Northern Queensland Floods of February 2019: Causes and Forecast Evaluation

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 758
Author(s):  
Wayne Yuan-Huai Tsai ◽  
Mong-Ming Lu ◽  
Chung-Hsiung Sui ◽  
Yin-Min Cho
Keyword(s):  
Large Scale ◽  
Deep Convection ◽  
Austral Summer ◽  
Rainfall Event ◽  
Monsoon Depression ◽  
Forecast Skill ◽  
Sea Surface ◽  
Central Pacific ◽  
Percentile Rank ◽  
Extended Range

During the austral summer 2018/19, devastating floods occurred over northeast Australia that killed approximately 625,000 head of cattle and inundated over 3000 homes in Townsville. In this paper, the disastrous event was identified as a record-breaking subseasonal peak rainfall event (SPRE). The SPRE was mainly induced by an anomalously strong monsoon depression that was modulated by the convective phases of an MJO and an equatorial Rossby (ER) wave. The ER wave originated from an active equatorial deep convection associated with the El Niño warm sea surface temperatures near the dateline over the central Pacific. Based on the S2S Project Database, we analyzed the extended-range forecast skill of the SPRE from two different perspectives, the monsoon depression represented by an 850-hPa wind shear index and the 15-day accumulated precipitation characterized by the percentile rank (PR) and the ratio to the three-month seasonal (DJF) totals. The results of four S2S models of this study suggest that the monsoon depression can maintain the same level of skill as the short-range (3 days) forecast up to 8–10 days. For precipitation parameters, the conclusions are similar to the monsoon depression. For the 2019 northern Queensland SPRE, the model forecast was, in general, worse than the expectation derived from the hindcast analysis. The clear modulation of the ER wave that enhanced the SPRE monsoon depression circulation and precipitation is suspected as the main cause for the lower forecast skill. The analysis procedure proposed in this study can be applied to analyze the SPREs and their associated large-scale drivers in other regions.

scholarly journals School Choice During a Period of Radical School Reform. Evidence from Academy Conversion in England

2020 ◽  
Author(s):  
Marco Bertoni ◽  
Stephen Gibbons ◽  
Olmo Silva
Keyword(s):  
School Choice ◽  
Large Scale ◽  
English Education ◽  
Limited Information ◽  
State Control ◽  
High Performing ◽  
Opt Out ◽  
Improved Performance ◽  
Expected Benefits ◽  
State Schools

Abstract We study how demand responds to the rebranding of existing state schools as autonomous ‘academies’ in the context of a radical and large-scale reform to the English education system. The academy programme encouraged schools to opt out of local state control and funding, but provided parents and students with limited information on the expected benefits. We use administrative data on school applications for three cohorts of students to estimate whether this rebranding changes schools’ relative popularity. We find that families – particularly higher-income, White British – are more likely to rank converted schools above non-converted schools on their applications. We also find that it is mainly schools that are high-performing, popular and proximate to families’ homes that attract extra demand after conversion. Overall, the patterns we document suggest that families read academy conversion as a signal of future quality gains – although this signal is in part misleading as we find limited evidence that conversion causes improved performance.

scholarly journals Statistical Downscaling of Daily Wind Speed Variations

2014 ◽  
Vol 53 (3) ◽  
pp. 660-675 ◽  
Author(s):  
Megan C. Kirchmeier ◽  
David J. Lorenz ◽  
Daniel J. Vimont
Keyword(s):  
Wind Speed ◽  
Gamma Distribution ◽  
Large Scale ◽  
Probabilistic Method ◽  
Probabilistic Approach ◽  
Local Scale ◽  
Scale Parameters ◽  
Wind Speeds ◽  
Distribution Shape ◽  
Realistic Information

AbstractThis study presents the development of a method to statistically downscale daily wind speed variations in an extended Great Lakes region. A probabilistic approach is used, predicting a daily-varying probability density function (PDF) of local-scale daily wind speed conditioned on large-scale daily wind speed predictors. Advantages of a probabilistic method are that it provides realistic information on the variance and extremes in addition to information on the mean, it allows the autocorrelation of downscaled realizations to be tuned to match the autocorrelation of local-scale observations, and it allows flexibility in the use of the final downscaled product. Much attention is given to fitting the proper functional form of the PDF by investigating the observed local-scale wind speed distribution (predictand) as a function of the decile of the large-scale wind (predictor). It is found that the local-scale standard deviation and the local-scale shape parameter (from a gamma distribution) are nonconstant functions of the large-scale predictor. As such, a vector generalized linear model is developed to relate the large-scale and local-scale wind speeds. Maximum likelihood and cross validation are used to fit local-scale gamma distribution shape and scale parameters to the large-scale wind speed. The result is a daily-varying probability distribution of local-scale wind speed, conditioned on the large-scale wind speed.

scholarly journals Temperature distribution in a permafrost-affected rock ridge from conductivity and induced polarization tomography

2020 ◽  
Author(s):  
P-A Duvillard ◽  
F Magnin ◽  
A Revil ◽  
A Legay ◽  
L Ravanel ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Temperature Distribution ◽  
Thermal State ◽  
Low Cost ◽  
Freezing Temperature ◽  
Induced Polarization ◽  
Rock Surface ◽  
European Alps ◽  
Limited Information ◽  
Polarization Tomography

Summary Knowledge of the thermal state of steep alpine rock faces is crucial to assess potential geohazards associated with the degradation of permafrost. Temperature measurements at the rock surface or in boreholes are however expensive, invasive, and provide spatially-limited information. Electrical conductivity and induced polarization tomography can detect permafrost. We test here a recently developed petrophysical model based on the use of an exponential freezing curve applied to both electrical conductivity and normalized chargeability to infer the distribution of temperature below the freezing temperature. We then apply this approach to obtain the temperature distribution from electrical conductivity and normalized chargeability field data obtained across a profile extending from the SE to NW faces of the lower Cosmiques ridge (Mont Blanc massif, Western European Alps, 3613 m a.s.l., France). The geophysical datasets were acquired both in 2016 and 2019. The results indicate that the only NW face of the rock ridge is frozen. To evaluate our results, we model the bedrock temperature across this rock ridge using CryoGRID2, a 1D MATLAB diffusive transient thermal model and surface temperature time series. The modelled temperature profile confirms the presence of permafrost in a way that is consistent with that obtained from the geophysical data. Our study offers a promising low-cost approach to monitor temperature distribution in Alpine rock walls and ridges in response to climate change.

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