scholarly journals Present and future changes in winter climate indices relevant for access disruptions in Troms, northern Norway

2020 ◽  
Vol 20 (6) ◽  
pp. 1847-1865
Author(s):  
Anita Verpe Dyrrdal ◽  
Ketil Isaksen ◽  
Jens Kristian Steen Jacobsen ◽  
Irene Brox Nilsen
Keyword(s):  
Heavy Rain ◽  
Climate Indices ◽  
Snow Avalanches ◽  
Heavy Snowfall ◽  
Strong Decrease ◽  
Winter Climate ◽  
Northern Norway ◽  
Snow Drift ◽  
The Future ◽  
High Impact Weather

Abstract. A number of seaside communities in Troms, northern Norway, are vulnerable to sudden weather-induced access disruptions due to high-impact weather and dependency on one or few roads. In this paper we study changes in winter weather known to potentially cause access disruptions in Troms, for the present climate (1958–2017) and two future periods (2041–2070; 2071–2100). We focus on climate indices associated with snow avalanches and weather that may lead to for example slippery road conditions. In two focus areas, the most important results show larger snow amounts now compared to 50 years ago, and heavy snowfall has become more intense and frequent. This trend is expected to turn in the future, particularly at low elevations where snow cover during winter might become a rarity by 2100. Strong snow drift, due to a combination of snowfall and wind speed, has slightly increased in the two focus areas, but a strong decrease is expected in the future due to less snow. Events of heavy rain during winter are rather infrequent in the present winter climate of Troms, but we show that these events are likely to occur much more often in all regions in the future.

scholarly journals Present and future changes in winter climate indices relevant for access disruptions in Troms, northern Norway

2019 ◽  
Author(s):  
Anita Verpe Dyrrdal ◽  
Ketil Isaksen ◽  
Jens Kristian Steen Jacobsen ◽  
Irene Brox Nilsen
Keyword(s):  
Water Supply ◽  
Climate Model ◽  
Climate Adaptation ◽  
Climate Indices ◽  
Present Climate ◽  
Winter Climate ◽  
Northern Norway ◽  
Zero Crossings ◽  
Freeze Thaw ◽  
The Future

Abstract. In some seaside communities in northern Norway the vulnerability to weather induced access disruptions is high, due to frequent high impact weather in the region and the dependency on one or few roads particularly exposed to avalanches, wind and rockfall. In this paper we study changes in typical winter weather indices known to potentially cause such access disruptions in the region. A gridded observation-based dataset is used to analyse changes in present climate (1958–2017), while an ensemble of 10 EURO-CORDEX climate model simulations are used to assess expected future changes in the same indices, towards the end of this century. We focus on weather indices associated with snow avalanches, such as maximum snow amount and snowfall intensity and frequency, but also freeze-thaw cycles in terms of temperatures crossing zero degrees Celsius (zero-crossings), total water supply and the frequency of high wind speed are studied. Our results show that there are large climate gradients in Troms county and also in detected changes. In both focus areas, however, we find an increase in studied snow indices in present climate, while a strong decrease is expected in near and far future, particularly in low elevations where snow during winter might become a rarity by 2100. Heavy water supply is rather infrequent in the present climate of Troms, but we show that these events are likely to occur more often in all inland areas in the future. Although the risk of dry snow-related access disruptions might decrease, a warmer and wetter winter climate may increase the risk of wet-snow avalaches and slushflows. We find that zero-crossings, known to destabilize the snow pack and cause rockfall, have increased in most parts of Troms during the last decades, and a further increase is expected for inland regions in the future, while coastal regions can expect less zero-crossings. The higher risk of water and rainfall-induced hazards and more frequent freeze-thaw conditions calls for careful coordination of climate adaptation, cooperation between different sectors, as well as guidance and training of local authorities, especially in exposed and remote regions.

scholarly journals Assessing the Response of Snow Avalanche Runout Altitudes to Climate Fluctuations Using Hierarchical Modeling: Application to 61 Winters of Data in France

2010 ◽  
Vol 23 (12) ◽  
pp. 3157-3180 ◽  
Author(s):  
N. Eckert ◽  
H. Baya ◽  
M. Deschatres
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Hierarchical Modeling ◽  
Control Measures ◽  
Level Shift ◽  
Snow Avalanches ◽  
Winter Climate ◽  
Climate Fluctuations ◽  
High Magnitude ◽  
Proposed Model

Abstract Snow avalanches are natural hazards strongly controlled by the mountain winter climate, but their recent response to climate change has thus far been poorly documented. In this paper, hierarchical modeling is used to obtain robust indexes of the annual fluctuations of runout altitudes. The proposed model includes a possible level shift, and distinguishes common large-scale signals in both mean- and high-magnitude events from the interannual variability. Application to the data available in France over the last 61 winters shows that the mean runout altitude is not different now than it was 60 yr ago, but that snow avalanches have been retreating since 1977. This trend is of particular note for high-magnitude events, which have seen their probability rates halved, a crucial result in terms of hazard assessment. Avalanche control measures, observation errors, and model limitations are insufficient explanations for these trends. On the other hand, strong similarities in the pattern of behavior of the proposed runout indexes and several climate datasets are shown, as well as a consistent evolution of the preferred flow regime. The proposed runout indexes may therefore be usable as indicators of climate change at high altitudes.

Future Extreme Climates Projection over Huang-Huai-Hai Region of China

2014 ◽  
Vol 955-959 ◽  
pp. 3887-3892 ◽  
Author(s):  
Huang He Gu ◽  
Zhong Bo Yu ◽  
Ji Gan Wang
Keyword(s):  
Climate Changes ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Daily Rainfall ◽  
Heavy Rain ◽  
Near Surface ◽  
Temperature And Precipitation ◽  
Huai River ◽  
The Future

This study projects the future extreme climate changes over Huang-Huai-Hai (3H) region in China using a regional climate model (RegCM4). The RegCM4 performs well in “current” climate (1970-1999) simulations by compared with the available surface station data, focusing on near-surface air temperature and precipitation. Future climate changes are evaluated based on experiments driven by European-Hamburg general climate model (ECHAM5) in A1B future scenario (2070-2099). The results show that the annual temperature increase about 3.4 °C-4.2 °C and the annual precipitation increase about 5-15% in most of 3H region at the end of 21st century. The model predicts a generally less frost days, longer growing season, more hot days, no obvious change in heat wave duration index, larger maximum five-day rainfall, more heavy rain days, and larger daily rainfall intensity. The results indicate a higher risk of floods in the future warmer climate. In addition, the consecutive dry days in Huai River Basin will increase, indicating more serve drought and floods conditions in this region.

Winter-Season Climate Prediction for the U.K. Health Sector

2006 ◽  
Vol 45 (12) ◽  
pp. 1782-1792 ◽  
Author(s):  
G. R. McGregor ◽  
M. Cox ◽  
Y. Cui ◽  
Z. Cui ◽  
M. K. Davey ◽  
...  
Keyword(s):  
Health Sector ◽  
Climate Prediction ◽  
Maximum Temperature ◽  
General Level ◽  
Climate Indices ◽  
Temperature Threshold ◽  
Winter Mortality ◽  
Winter Climate ◽  
Seasonal Climate ◽  
Study Results

Abstract The winter climate of the British Isles is characterized by considerable interannual variability, which, because of the general climate sensitivity of a number of health outcomes, places at times considerable pressure on the provision of health services. Seasonal climate forecasts potentially could improve management within the health sector and assist in hedging against the vagaries of climatic variability. For this reason, an exploratory analysis of the potential utility of seasonal climate forecasting for the health sector in the United Kingdom is presented here. Study results revealed that the general level of winter mortality at the monthly to seasonal time scale possesses a strong association with simple descriptors of winter climate such as maximum temperature and the number of days below a given temperature threshold. Because such climate indices can be derived from the output of coupled seasonal climate prediction models, predictions of general levels of mortality may be possible using simple transfer functions that describe winter climate and health associations. Despite the potential one-month-ahead and one-season-ahead predictability of winter mortality levels, the predictability of the key climate indices by coupled climate models is shown to be somewhat limited, which compromises the ability to predict general levels of winter mortality for all months except February.

scholarly journals Estimating Future Peak Water Demand with a Regression Model Considering Climate Indices

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1912
Author(s):  
Anika Stelzl ◽  
Michael Pointl ◽  
Daniela Fuchs-Hanusch
Keyword(s):  
Climate Change ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Water Demand ◽  
Support Vector ◽  
Climate Indices ◽  
Climate Projections ◽  
Worst Case ◽  
Modeling Approaches ◽  
The Future

Although Austria is a water-rich country, impacts of climate change on water supply are already noticeable. Some regions were affected by water scarcity in recent years. Due to climate change, an increase in peak water demand is expected in the future. Therefore, water demand prediction models that include climate indices are of interest. In this paper, we present a general multiple linear regression (GMLR) model that can be applied to selected study sites. We compared the performance of the GMLR model with different modeling approaches, i.e., stepwise multiple linear regression, support vector regression, random forest regression and a neural network approach. All models were trained with water demand and weather data reaching back several years and tested with the last available observation year. The applied modeling approaches achieved a similar performance. As a second step, the GMLR model was used to estimate the peak water demands for the time period 2025–2050. For the future water demand estimate, 16 different climate projections were used. These climate projections represent the worst-case climate change scenario (RCP 8.5). The expected increase in peak water demand could be confirmed with the modeling approach. An increase in peak water demand by 3.5% compared to the reference period was estimated.

scholarly journals Analysis of Flood Damage in the Seoul Metropolitan Government Using Climate Change Scenarios and Mitigation Technologies

2020 ◽  
Vol 13 (1) ◽  
pp. 105
Author(s):  
Jaekyoung Kim ◽  
Junsuk Kang
Keyword(s):  
Climate Change ◽  
Extreme Rainfall ◽  
Heavy Rain ◽  
Flood Damage ◽  
Climate Change Scenarios ◽  
Permeable Pavement ◽  
Metropolitan Government ◽  
Run Off ◽  
The Future ◽  
One Year

The social and economic damages caused by climate change have increased rapidly over the last several decades, with increasing instances of heatwaves, floods, and extreme rainfall. In 2011, heavy rain of 110.5 mm/hr caused great damage to the Seoul Metropolitan Government. Most of the causes of flooding in modern cities include a sharp increase in non-permeable pavement and a lack of water circulation facilities. It is predicted that heavy rainfalls will occur in the future, causing large amounts of local damage. In this study, possible future flood damages were analyzed using climate change scenarios based on the Korean Peninsula. ArcGIS was adopted to perform analyses, and Huff curves were employed for precipitation analysis. Water tanks, permeable pavement, and ecological waterways were installed as mitigation technologies. These three technologies can contribute to flooding mitigation by increasing the rainwater storage capacity. This study suggests that all floods can be reduced by RCP 8.5 by 2050 and 2060. Although there will be run-off after 2050, it is believed that technology will significantly reduce the volume and possibility of floods. It is recommended that a one-year analysis should be conducted in consideration of the maintenance aspects that will arise in the future.

scholarly journals Heavy rain events in the Western Mediterranean: an atmospheric pattern classification

2008 ◽  
Vol 2 (1) ◽  
pp. 61-64 ◽  
Author(s):  
C. Martínez ◽  
J. Campins ◽  
A. Jansà ◽  
A. Genovés
Keyword(s):  
Heavy Rain ◽  
Western Mediterranean ◽  
High Impact ◽  
Good Relationship ◽  
Operational Analysis ◽  
Mediterranean Regions ◽  
High Impact Weather ◽  
Components Analysis ◽  
Rain Events

Abstract. Heavy rain is one of the most important high-impact weather phenomena that occasionally affect Mediterranean areas. The aim of this study is to achieve a classification of atmospheric patterns related to heavy rain events in both French and Spanish Mediterranean regions. The classification is made on some atmospheric fields (geopotential at 1000 hPa and at 500 hPa and temperature at 850 hPa) of HIRLAM-INM-0.5° operational analysis, for heavy rain events included in the High Impact Weather MEDEX database. It covers a period of roughly 7 and a half years, from January 1997 to May 2004. A Principal Components Analysis was conducted to reduce the number of variables. After that, by means of a Cluster Analysis, the heavy rain events are classified into 8 atmospheric patterns. The results show a good relationship between regions affected by heavy rain and atmospheric patterns, in the sense that the same atmospheric patterns usually produce heavy rain in different regions, and heavy rain in different regions is usually due to specific atmospheric patterns.

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