scholarly journals Analysis of Determinants of the Impact and the Grid Capability to Evaluate and Improve Grid Resilience from Extreme Weather Event

Energies ◽  
2017 ◽  
Vol 10 (11) ◽  
pp. 1779 ◽  
Author(s):  
Fauzan Hanif Jufri ◽  
Jun-Sung Kim ◽  
Jaesung Jung
Keyword(s):  
Extreme Weather ◽  
Extreme Weather Event ◽  
Weather Event ◽  
The Impact

The Impact of an Extreme Weather Event on Business Performance

2021 ◽  
Author(s):  
Sumit Agarwal ◽  
Mingxuan Fan ◽  
Leora F. Klapper ◽  
Edward Lee
Keyword(s):  
Business Performance ◽  
Extreme Weather ◽  
Extreme Weather Event ◽  
Weather Event ◽  
The Impact

scholarly journals Analysis of an Extreme Weather Event in a Hyper Arid Region Using WRF-Hydro Coupling, Station, and Satellite data

2018 ◽  
Author(s):  
Youssef Wehbe ◽  
Marouane Temimi ◽  
Michael Weston ◽  
Naira Chaouch ◽  
Oliver Branch ◽  
...  
Keyword(s):  
Soil Moisture ◽  
United Arab Emirates ◽  
Hydrological Modeling ◽  
Flash Flood ◽  
Pearson Correlation ◽  
Global Radiation ◽  
Wrf Model ◽  
Extreme Weather ◽  
Extreme Weather Event ◽  
Weather Event

Abstract. This study investigates an extreme weather event that impacted the United Arab Emirates (UAE) in March 2016 using the Weather Research and Forecasting (WRF) model version 3.7.1 coupled with its hydrological modeling extension package (Hydro). Six-hourly forecasted forcing records at 0.5o spatial resolution, obtained from the NCEP Global Forecast System (GFS), are used to drive the three nested downscaling domains of both standalone WRF and coupled WRF/WRF-Hydro configurations for the recent flood-triggering storm. Ground and satellite observations over the UAE are employed to validate the model results. Precipitation, soil moisture, and cloud fraction retrievals from GPM (30-minute, 0.1o product), AMSR2 (daily, 0.1o product), and MODIS (daily, 5 km product), respectively, are used to assess the model output. The Pearson correlation coefficient (PCC), relative bias (rBIAS) and root-mean-square error (RMSE) are used as performance measures. Results show reductions of 24 % and 13 % in RMSE and rBIAS measures, respectively, in precipitation forecasts from the coupled WRF/WRF-Hydro model configuration, when compared to standalone WRF. The coupled system also shows improvements in global radiation forecasts, with reductions of 45 % and 12 % for RMSE and rBIAS, respectively. Moreover, WRF-Hydro was able to simulate the spatial distribution of soil moisture reasonably well across the study domain when compared to AMSR2 satellite soil moisture estimates, despite a noticeable dry/wet bias in areas where soil moisture is high/low. The demonstrated improvement, at the local scale, implies that WRF-Hydro coupling may enhance hydrologic forecasts and flash flood guidance systems in the region.

scholarly journals Climate effects on the onset of flowering in the United Kingdom

2019 ◽  
Vol 31 (1) ◽  
Author(s):  
Nigel Fox ◽  
Anna Maria Jönsson
Keyword(s):  
Climate Change ◽  
Time Series ◽  
United Kingdom ◽  
Response Rates ◽  
Extreme Weather ◽  
Extreme Weather Event ◽  
Negative Response ◽  
Wild Plant ◽  
Weather Event ◽  
The United Kingdom

Abstract Background A warmer climate has consequences for the timing of phenological events, as temperature is a key factor controlling plant development and flowering. In this study, we analyse the effects of the long-term climate change and an extreme weather event on the first flowering day (FFD) of five spring-flowering wild plant species in the United Kingdom. Citizen science data from the UK Woodland Trust were obtained for five species: Tussilago farfara (coltsfoot), Anemone nemorosa (wood anemone), Hyacinthoides non-scripta (bluebell), Cardamine pratensis (cuckooflower) and Alliaria petiolate (garlic mustard). Results Out of the 351 site-specific time series (≥ 15-years of FFD records), 74.6% showed significant negative response rates, i.e. earlier flowering in warmer years, ranging from − 5.6 to − 7.7 days °C−1. 23.7% of the series had non-significant negative response rates, and 1.7% had non-significant positive response rates. For cuckooflower, the response rate was increasingly more negative with decreasing latitudes. The winter of 2007 reflects an extreme weather event, about 2 °C warmer compared to 2006, where the 2006 winter temperatures were similar to the 1961–1990 baseline average. The FFD of each species was compared between 2006 and 2007. The results showed that the mean FFD of all species significantly advanced between 13 and 18 days during the extreme warmer winter of 2007, confirming that FFD is affected by temperature. Conclusion Given that all species in the study significantly respond to ambient near-surface temperatures, they are suitable as climate-change indicators. However, the responses to a + 2 °C warmer winter were both more and less pronounced than expected from an analysis of ≥ 15-year time series. This may reflect non-linear responses, species-specific thresholds and cumulative temperature effects. It also indicates that knowledge on extreme weather events is needed for detailed projections of potential climate change effects.

scholarly journals GIS-based quantitative landslide hazard prediction modelling in natural hillslope, Agra Khola watershed, central Nepal

1970 ◽  
Vol 10 ◽  
pp. 63-70 ◽  
Author(s):  
Prem Bahadur Thapa ◽  
Tetsuro Esaki
Keyword(s):  
Multivariate Analysis ◽  
Prediction Model ◽  
Extreme Weather ◽  
Landslide Hazard ◽  
Extreme Weather Event ◽  
Hazard Mapping ◽  
Weather Event ◽  
Quantitative Technique ◽  
Central Nepal ◽  
Hazard Levels

The influence of geological and geomorphological variables were spatially integrated to develop landslide hazard prediction model in the Agra Khola watershed of central Nepal where a large number of landslides triggered off due to extreme weather event of July 19-21, 1993. A quantitative technique of multivariate analysis was performed to predict elements or observations of landslides successfully into different hazard levels in the area. The predicted landslide hazard was validated and spatially relevancy of the prediction is established. The GIS-based prediction model possessed objectivity and reproducibility, and also improved the landslide hazard mapping in the natural hillslope. doi: 10.3126/bdg.v10i0.1421   Bulletin of the Department of Geology, Tribhuvan University, Kathmandu, Nepal, Vol. 10, 2007, pp. 63-70  

scholarly journals Warmer and wetter winters: characteristics and implications of an extreme weather event in the High Arctic

2014 ◽  
Vol 9 (11) ◽  
pp. 114021 ◽  
Author(s):  
Brage B Hansen ◽  
Ketil Isaksen ◽  
Rasmus E Benestad ◽  
Jack Kohler ◽  
Åshild Ø Pedersen ◽  
...  
Keyword(s):  
High Arctic ◽  
Extreme Weather ◽  
Extreme Weather Event ◽  
Weather Event

Campylobacteriosis Risk Of Hospital Admission Related To Extreme Weather Event Frequency In Maryland

2015 ◽  
Vol 2015 (1) ◽  
pp. 2267
Author(s):  
Sutyajeet Soneja ◽  
Chengsheng Jiang ◽  
Clifford Mitchell ◽  
Amy Sapkota ◽  
Amir Sapkota
Keyword(s):  
Hospital Admission ◽  
Extreme Weather ◽  
Extreme Weather Event ◽  
Weather Event ◽  
Event Frequency
Sign in / Sign up

Export Citation Format

Share Document