Pregled bibliografske jedinice broj: 1252943
Towards climate services for European cities: Lessons learnt from the Copernicus project Urban SIS
Towards climate services for European cities: Lessons learnt from the Copernicus project Urban SIS // Urban Climate, 31 (2020), 100549, 20 doi:10.1016/j.uclim.2019.100549 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1252943 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Towards climate services for European cities:
Lessons learnt from the Copernicus project Urban SIS
Autori
Gidhagen, Lars ; Olsson, Jonas ; Amorim, Jorge H. ; Asker, Christian ; Belusic, Danijel ; Carvalho, Ana C. ; Engardt, Magnuz ; Hundecha, Yeshewatesfa ; Körnich, Heiner ; Lind, Petter ; Lindstedt, David ; Olsson, Esbjörn ; Rosberg, Jörgen ; Segersson, David ; Strömbäck, Lena
Izvornik
Urban Climate (2212-0955) 31
(2020);
100549, 20
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Climate impacts ; Climate adaptation ; Cities ; Meteorology ; Air quality ; Hydrology
Sažetak
The growing share of Europe's population living in cities makes urban climate change impact assessment and adaptation a critical issue. The urban environment is characterized by its sensitivity to small-scale meteorological, hydrological and environmental processes. These are generally not fully described in climate models, largely because of the models' insufficient spatial resolution. The Urban SIS climate service offers historical and future simulated data downscaled to 1 km × 1 km resolution over selected European metropolitan areas. The downscaled data are subsequently used as input to air quality and hydrological impact models, all made available to users as Essential Climate Variables and Sectoral Impact Indicators through a web portal. This paper presents the Urban SIS climate service and demonstrates its functionality in a case study in Stockholm city, Sweden. Good model performance was attained for intra-city temperature gradients and small-scale precipitation extremes. Less positive results were obtained for large-scale precipitation and hydrology, mainly due to an insufficient domain size in the meteorological and climate modelling, in turn related to the substantial computational requirements. An uncertainty classification approach was developed to aid the interpretation and user application of the data. We hope our lessons learnt will support future efforts in this direction.
Izvorni jezik
Engleski
Znanstvena područja
Geofizika
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus