Weather and Climate for Tourism (WeCTOU) is a free service for the public providing climate and environmental information for tourism in Romania.
WeCTOU is an independent service developed and operated by Meteo Romania, being funded by European Commission and the European Centre for Medium-Range Weather Forecasts (ECMWF) through C3S (Copernicus Climate Change Service) under the contract C3S_428I_METEORO.
The products available on WeCTOU at climatic scale are derived from regional and global reanalysis datasets produced by ECMWF and available through Climate Data Store. For more information, see 'Climate and Environmental Information – Description of indices’..
The recently observed data comes from the satellite-based products using observations in the last 1-10 days. The satellite-based data is available from Copernicus Land Monitoring Service (CLMS) and Copernicus Marine Environment Monitoring Service (CMEMS). For more information, see 'Climate and Environmental Information – Description of indices'.
The forecast data for the next day is available from Copernicus Atmosphere Monitoring Service (CAMS) and it is produced using numerical models at regional or global scale. Copernicus Atmosphere Monitoring Service.
WeCTOU provides free climate and environmental information tailored for tourism for 160 locations in Romania. Payed products are also available.
The information presented through WECTOU is associated with a degree of uncertainty and its accuracy is not guaranteed.
Meteo Romania accepts no liability for your business or health nor for any action you take based on the products presented through WeCTOU or the consequences of your actions. The information provided on the website is purely indicative.
Meteo Romania will not be responsible or liable to pay compensations, directly or indirectly, for any damage or loss caused or presumed to be caused by the interpretation and / or use of the information presented through WeCTOU.
Meteo Romania will not be liable for damages resulting from inability to access or problems with the services of the site.
Reproduction of the publicly available content of this website is authorized if the the source is acknowledged.
For all enquiries about the service, including subscribe and unsubscribe questions, please contact the WeCTOU team at email@example.com.
The climate-based indices were derived based on data for the period 2000-2018 available from the following datasets:
Snow depth (SD) it is one of the indices used to derive touristic information for locations with dominantly mountain and rural touristic character. SDT is derived from ERA5-Land dataset, which has a spatial resolution of 10km, using data at 12:00 UTC. The SDT index was analyzed at monthly scale for 7 months (January, February, March, April, October, November, December).
Snow Cover (SCE) is based on the index ‘Snow Cover Extent’, it is provided for locations with dominantly mountain and rural touristic character and it is derived from the ERA5-Land dataset, using data at 12:00 UTC. It was analyzed at monthly scale for 7 months (January, February, March, April, October, November, December).
Sea Water Temperature is based on the Sea Surface Temperature (SST) data and it is provided for the localities with predominantly beach tourism. The information is derived from ‘Sea surface temperature daily data from 1981 to present from satellite-derived data‘, it has a spatial resolution of 5 km and it has been processed for every 10 days in a month for May-September.
Frostbite risk information is based on the Wind Chill Temperature (WCT) and it is provided for locations with mountain tourism. The index is derived using UERRA-HARMONIE dataset which has a spatial resolution of 9km. WCT index is based on two parameters – wind speed at 10m and air temperature at 2m – and it is a biometeorological index relevant mainly for cold season. The classes of risk are those used operationally for weather forecast in Canada.
Respiratory comfort is based on Pulmonary stress (PS) index, which is a bioclimatic index (Becancenot, 1974) based on the respiratory exchanges between lungs and the environment, in the conditions of a certain amount of water vapor in the air. It is used in Romania in studies regarding the therapeutic role of climate (e.g. positive/adverse effects in relation to some morbidities, climate characteristics of balneary resorts), along with other bioclimatic indices (e.g. Teodoreanu and Mihaila, 2012). The PS index was derived using data from UERRA-HARMONIE. In WeCTOU application, this information is provided for localities with mountain, rural and beach tourism.
Thermal stress is based on UTCI (Universal Thermal Climate Index) and it is provided through WeCTOU web platform for all localities and tourism types. UTCI is based on human heat balance models and it is designed to be applicable in all seasons and climates and for all spatial and temporal scales (Bröde et al. 2012). The index is based on several meteorological parameters – air temperature a 2m, relative humidity, wind speed at 10m and radiation. The data used is provided by UERRA-HARMONIE.
Weather for staying outdoor is based on the Holiday Climate Index (HCI) (Scott et al, 2016). This index targets the general outdoor leisure activities (e.g. city tours, sightseeing etc.), aiming to characterize how suitable is the local climate for such activities. HCI takes into account several aspects of climate (i.e. thermal comfort, cloudiness, precipitation and wind), employing 5 meteorological parameters (air temperature at 2m, relative humidity, wind speed at 10m, total cloud cover and total precipitation). The data is provided by UERRA-HARMONIE dataset. The index comprises 7 classes of climate conditions suitability –from unfavorable to ideal - for this type of touristic activities and it is optimized for urban areas. In the context of WECTOU application, HCI is provided for all localities, as the comparison with sectoral (tourism) data indicated that the index is relevant for other tourism types too.
Green cover is based on Green Cover Index (GCI) which is a newly developed index within WECTOU contract aiming to provide environmental information for rural area. It is derived using two satellite-based products: (1) Leaf Area Index (LAI)- defined as one half of the total green leaf area per unit horizontal ground surface area, and thus it corresponds to the green elements of the vegetation. LAI values vary from 0 to 10, with values below 1 representing sparse vegetation, while values higher than 5 represent dense vegetation. LAI data is available from C3S platform, having a spatial resolution of 1km; (2) Normalized Difference Vegetation Index (NDVI)- is an indicator of the greenness of the biomes. The NDVI values vary from -1 to +1. The values below 0.2 correspond to water, clouds, artificial surfaces, snow etc., while the values above 0.2 correspond to vegetation (from sparse vegetation to dense vegetation). NDVI data is available from CLMS (Copernicus Land Monitoring Service), having a spatial resolution of 1km. GCI takes into consideration only natural vegetation in the area surrounding localities with rural tourism (i.e. cultivated areas are not considered).
The information in this category is derived from satellite products based on observations in the last 1-10 days. The data is available from CLMS (Copernicus Climate Monitoring Service) for Snow Cover and Green Cover and from CLMEMS (Copernicus Marine Environment Monitoring Service) from Sea Water Temperature.
This information is provided by forecasts available from CAMS (Copernicus Atmosphere Monitoring Service) and it refers to three indices:
Traffic pollution alerts (PM10) – is based on the forecast of PM10 and it is provided in WECTOU for urban areas. The PM10 forecast is produced by an ensemble of nine state-of-the-art numerical air quality models developed in Europe from all nine models. They are combined via an ensemble approach, consisting in calculating the median value of the individual outputs. The models have a 0.1 degree spatial resolution, so outputs may not be correlated enough with real concentrations.
Pollen allergy risk is based on the forecast of birch and grass pollen, produced with the same ensemble of numerical models as PM10 and available from CAMS.
Sun burn risk is based on the forecast of UV index available from CAMS/ECMWF and obtained with numerical models at global scale. The information is provided for all rural, sea-side and mountain locations.
Becancenot, J.P.(1974): Premieres donnees sur les stress bioclimatiques moyens en France, Annales de Geogr., no.459, LXXXIII, sept.-oct.14
Bröde, P Bröde, P., Fiala, D., Błażejczyk, K., Holmér, I., Jendritzky, G., Kampmann, B., Tinz, B., Havenith, G (2012): Deriving the operational procedure for the Universal Thermal Climate Index (UTCI). Int.J.Biomet., 56:3, 481-494
Scott, D., Rutty, M., Amelung, B. and Tang, M. (2016): An inter-comparison of the Holiday Climate Index (HCI) and the Tourism Climate Index (TCI), Atmosphere, 7, 80, doi:10.3390/atmos7060080
Teodeoreanu, E. and Mihaila, D. (2012): Is the bioclimate of Suceava Plateau comfortable or uncomfortable? Analysis based on TEE and THI, Present Present Environment And Sustainable Development, vol. 6, no. 1, 2012