Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Marika Koukoula"'
Autor:
Herminia Torelló‐Sentelles, Francesco Marra, Marika Koukoula, Gabriele Villarini, Nadav Peleg
Publikováno v:
Earth's Future, Vol 12, Iss 9, Pp n/a-n/a (2024)
Abstract Urban areas have been shown to impact rainfall by altering both its intensity and spatial structure at sub‐hourly and sub‐kilometer scales. However, there is currently no clear understanding of the precise pattern of change and the mecha
Externí odkaz:
https://doaj.org/article/d78a8a49403144fda67ee3e0de94298a
Publikováno v:
Energy Reports, Vol 10, Iss , Pp 4148-4169 (2023)
In the United States, weather-related power outages cost the economy tens of billions annually, and there has been an upward trend in billion-dollar disasters over the last two decades. Thus, it is of growing importance to be able to predict outages
Externí odkaz:
https://doaj.org/article/4d8df144a8284a54bf2fa87aa80a6959
Publikováno v:
Environmental Research Letters, Vol 19, Iss 10, p 104020 (2024)
In light of the rapid growth in cities, there is a pressing need to explore how urbanization affects extreme weather, especially short-duration convective storms that can potentially trigger urban floods. Here we use a high-resolution Weather Researc
Externí odkaz:
https://doaj.org/article/23055192bdfd4c1ca840a30156f85a42
Autor:
Christina Kalogeri, Christos Spyrou, Marika Koukoula, Pantelis M. Saviolakis, Aikaterini Pappa, Michael Loupis, Charis Masouras, Petros Katsafados
Publikováno v:
Environmental Sciences Proceedings, Vol 26, Iss 1, p 174 (2023)
The main aim of this study is to model the Nature-based solution of Green Roofs (GRs) in order to assess their efficiency as a mitigation strategy for UHI effects and extreme summertime temperatures over Attica in Greece. The area of study is a regio
Externí odkaz:
https://doaj.org/article/49908c3859fc4873a4c8fee456855ad2
Publikováno v:
Weather and Climate Extremes, Vol 37, Iss , Pp 100487- (2022)
Power outages caused by extreme weather events cost the economy of the United States billions of dollars every year and endanger the lives of the people affected by them. These types of events could be better managed if accurate predictions of storm
Externí odkaz:
https://doaj.org/article/25a5c3c5c84a4a46b26a366f280b9c28
Publikováno v:
Forecasting, Vol 3, Iss 3, Pp 541-560 (2021)
Thunderstorms are one of the most damaging weather phenomena in the United States, but they are also one of the least predictable. This unpredictable nature can make it especially challenging for emergency responders, infrastructure managers, and pow
Externí odkaz:
https://doaj.org/article/676da921935b4b449b4115df0369edb3
Publikováno v:
IEEE Access, Vol 8, Pp 60029-60042 (2020)
The accuracy of machine learning-based power outage prediction models (OPMs) is sensitive to how well event severity is represented in their training datasets. Unbalanced or overly dispersed event severity can result in random errors in outage predic
Externí odkaz:
https://doaj.org/article/09f41892f0c24696b0454e21fced639b
Publikováno v:
The Journal of Engineering (2020)
The outage prediction model (OPM) is a weather-related machine learning-based power outage model, which has been developed at the University of Connecticut for many years and has recently grown to cover three states and five utility service territori
Externí odkaz:
https://doaj.org/article/52aede51e5bd4ca18bcd7e8a33da780d
More than half of the world’s population now resides in cities and the amount of urban population is expected to further increase during the coming decades. Urbanization and the associated changes in land use/land cover can have a notable impact on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d0671a1efe8920c618e234d8c9b72a9b
https://doi.org/10.5194/egusphere-egu23-1239
https://doi.org/10.5194/egusphere-egu23-1239
Autor:
Meijian Yang, Guiling Wang, Shu Wu, Paul Block, Rehenuma Lazin, Sarah Alexander, Jonathan Lala, Muhammad Rezaul Haider, Zoi Dokou, Ezana Amdework Atsbeha, Marika Koukoula, Xinyi Shen, Malaquias Peña, Efthymios Nikolopoulos, Amvrossios Bagtzoglou, Emmanouil Anagnostou
Publikováno v:
Agricultural and Forest Meteorology. 331:109347
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::95624123ec594e8f6ed421560e054fd4
https://doi.org/10.1016/j.agrformet.2023.109347
https://doi.org/10.1016/j.agrformet.2023.109347