Does it always rain in Belgium? In some weeks that may seem to be the case, but in the last decade Belgium actually counted between 180 and 212 rain days a year. And in none of these years, the annual rainfall surpassed the thousand millimeters. Rainfall peaked in 2016, at roughly 940 millimeters. In 2015 however, rainfall had only been 737 millimeters – the lowest rainfall in the period considered here.

 Belgium’s maritime climate   

Belgium has a temperate maritime climate, with cool summers and moderate winters. In the 2006-2016 period, the average temperature in the country was between 9.7 and 11.9 degrees Celsius. 2014 was the warmest year in the past decade, with an average temperature of nearly 12 degrees.

The Belgian winter  

Next to a large number of rain days, Belgium’s average winter usually counts a number of frost days as well, when temperatures drop below zero. In 2010, there were nearly 75 such days. By comparison, 2014 had just ten frost days. That year, there was just one ice day, defined as a day in which the maximum temperature during the day is below the freezing point as well. In 2016, there were two ice days in Belgium.

Precipitation in Belgium increased to 1063.26 mm in 2023 from 749.60 mm in 2022. This dataset includes a chart with historical data for Belgium Average Precipitation.

Does it always rain in Belgium? Well, there is some truth in each stereotype! Although it certainly does not rain every day, there is a lot of rainfall in Belgium. In 2016, it rained 190 out of 366 days, or over half of the days. And this was by no means a record: in 2012, it rained 212 days, or nearly 60 percent of all days. That year, the rainfall was nearly 1,000 millimeters. In 2016, although there were fewer rain days, rainfall was still over 940 millimeters.

 Fortunately the sun sometimes shines too  

Having read this, one might be forgiven for thinking the climate in Belgium is rather bad. Fortunately, Belgians have ample time to enjoy the sun as well. In 2016 for example, there were nearly 1,600 hours of sunshine. This was significantly more than in 2007 and 2008 for instance, when there were less than 1,500 hours. In recent years, 2011 was the sunniest year, with almost 1,800 hours of sunshine.

Average temperature around 10 degrees Celsius  

All year round, the average temperature in Belgium is around 10 degrees Celsius in the last decade. In 2016, the average reached 10.7 degrees, a slight decrease compared to the two previous years, when the average temperature was 11.9 (2014) and 11.3 (2015) respectively.

Belgium: Precipitation, mm per year: The latest value from 2021 is 847 mm per year, unchanged from 847 mm per year in 2020. In comparison, the world average is 1168 mm per year, based on data from 178 countries. Historically, the average for Belgium from 1961 to 2021 is 847 mm per year. The minimum value, 847 mm per year, was reached in 1961 while the maximum of 847 mm per year was recorded in 1961.

Belgium BE: Average Precipitation in Depth data was reported at 847.000 mm/Year in 2020. This stayed constant from the previous number of 847.000 mm/Year for 2019. Belgium BE: Average Precipitation in Depth data is updated yearly, averaging 847.000 mm/Year from Dec 1961 (Median) to 2020, with 60 observations. The data reached an all-time high of 847.000 mm/Year in 2020 and a record low of 847.000 mm/Year in 2020. Belgium BE: Average Precipitation in Depth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Belgium – Table BE.World Bank.WDI: Environmental: Land Use, Protected Areas and National Wealth. Average precipitation is the long-term average in depth (over space and time) of annual precipitation in the country. Precipitation is defined as any kind of water that falls from clouds as a liquid or a solid.;Food and Agriculture Organization, electronic files and web site.;;

In 2019, Belgium’s weather institute registered approximately 1,760 hours of sunshine. During the decade covering 2008 to 2019, 2018 turned out to be the sunniest year of them all. On average, 1,600 hours of sunshine per year were measured in Belgium over this period. However, the number of sunshine hours varied each year. For instance, Belgium reached its lowest level of sunshine in 2008 with less than 1,500 hours. On the other hand, the country experienced an average of 200 days of rainfall per year, during this period.

Europe comparison

Although the Netherlands and Germany neighbor Belgium and share the same climate, hours of sunshine were higher in both countries. For instance, in 2018, over two thousand hours of sunshine were measured in the Netherlands and Germany. Although these differences are not outstanding, sunshine measures were continually higher from 2008 to 2018. Belgium was, therefore, not the sunniest destination in Europe. However, the country was not the least sunny either. Fewer hours of sunshine were, for example, reported in the United Kingdom.

Vitamin D

Vitamin D, also referred to as the sun vitamin, is created from our body when exposed to the sun’s UVB radiations. These rays are mostly found during the summer months and, therefore, insufficient exposure to the sun can create a Vitamin D deficiency. This vitamin is linked to various health benefits and its deficiency to diverse health implications. A day-light deficit can favor seasonal depression, characterized by tiredness; especially in Belgium, which reported an irregular number of summer days from 2008 to 2018. In 2014, around 20 percent of the Belgians were consuming Vitamin D supplements.

This dataset contains both the raw data and the generated synthetic weather years used in the paper submitted to Progress in Energy. The data covers 11 regions analyzed in this study: Austria (AT), Belgium (BE), Denmark (DK), the Czech Republic (CZ), France (FR), Germany (DE), Italy (IT), Luxembourg (LU), the Netherlands (NL), Poland (PL), and Switzerland (CH).

• demand_generation_all.csv: This file includes the raw data, adjusted data, and residual load used in the study. The adjusted demand and renewable generation time series have been specifically designed to align with our system setup. These adjustments are based on renewable capacity values and demand values derived from the FlexMex scenario 2D. A detailed description of FlexMex is available at https://zenodo.org/records/5802178">https://zenodo.org/records/5802178. The dataset includes the following columns:
  • Timestamps: Defined by the columns 'year', 'month', 'day', and 'hour'.
  • Raw demand time series: 'country code+ _demand'
  • Raw renewable generation time series:
    • Solar PV: 'country code + _solar'.
    • Wind onshore: 'country code + _wind_onshore'.
    • Wind offshore: 'country code + _wind_offshore'.
  • Adjusted demand time series: 'country code + _demand_aj'
  • Adjusted renewable generation time series:
    • Solar PV: 'country code + _solar_aj'.
    • Wind onshore: 'country code + _wind_onshore_aj'.
    • Wind offshore: 'country code + _wind_offshore_aj'.
  • Residual Load time series: 'country code + _r_load_aj'.
• 'TMY.csv': Time series of the typical meteorological year.
• 'ELY.csv': Time series of the extreme low residual load year.
• 'EHY.csv': Time series of the extreme high residual load year.
• 'TMY_1D.csv': Time series of the typical meteorological year with a one-day extreme event.
• 'TMY_1W.csv': Time series of the typical meteorological year with a one-week extreme event.
• 'TMY_2W.csv': Time series of the typical meteorological year wth a two-week extreme event.
• 'EHY_1D.csv': Time series of the extreme high residual load year with a one-day extreme event.
• 'EHY_2W.csv': Time series of the extreme high residual load year with a two-week extreme event..

Context

Experimental data used to create regression models of appliances energy use in a low energy building.

Content

Data Set Characteristics:

Multivariate, Time-Series, Regression

Number of Instances(Rows):

19735

Number of Attributes(Columns):

29

Associated Tasks:

Regression

Source:

Luis Candanedo, luismiguel.candanedoibarra '@' umons.ac.be, University of Mons (UMONS).

Data Set Information: Given in Metadata tab about the sources and collection methodology.

Attribute Information:

date time year-month-day hour:minute:second

Appliances, energy use in Wh (target variable for prediction)

lights, energy use of light fixtures in the house in Wh

T1, Temperature in kitchen area, in Celsius

RH_1, Humidity in kitchen area, in %

T2, Temperature in living room area, in Celsius

RH_2, Humidity in living room area, in %

T3, Temperature in laundry room area

RH_3, Humidity in laundry room area, in %

T4, Temperature in office room, in Celsius

RH_4, Humidity in office room, in %

T5, Temperature in bathroom, in Celsius

RH_5, Humidity in bathroom, in %

T6, Temperature outside the building (north side), in Celsius

RH_6, Humidity outside the building (north side), in %

T7, Temperature in ironing room , in Celsius

RH_7, Humidity in ironing room, in %

T8, Temperature in teenager room 2, in Celsius

RH_8, Humidity in teenager room 2, in %

T9, Temperature in parents room, in Celsius

RH_9, Humidity in parents room, in %

To, Temperature outside (from Chievres weather station), in Celsius

Pressure (from Chievres weather station), in mm Hg

RH_out, Humidity outside (from Chievres weather station), in %

Wind speed (from Chievres weather station), in m/s

Visibility (from Chievres weather station), in km

Tdewpoint (from Chievres weather station), °C

rv1, Random variable 1, nondimensional

rv2, Random variable 2, nondimensional

Where indicated, hourly data (then interpolated) from the nearest airport weather station (Chievres Airport, Belgium) was downloaded from a public data set from Reliable Prognosis, rp5.ru. Permission was obtained from Reliable Prognosis for the distribution of the 4.5 months of weather data.

Acknowledgements

Luis M. Candanedo, Veronique Feldheim, Dominique Deramaix, Data driven prediction models of energy use of appliances in a low-energy house, Energy and Buildings, Volume 140, 1 April 2017, Pages 81-97, ISSN 0378-7788, Web Link.

Citation

Dua, D. and Graff, C. (2019). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.

Inspiration

1) This is a regression task, You should predict the "appliances" column. Column descriptions are given above. Please read them before proceeding. 2) Appropriate time series analysis with regression is preferred more. 3) Exploratory data analysis with charts and plots.

Have fun!

In mid-July 2021, a quasi-stationary extratropical cyclone over parts of western Germany and eastern Belgium led to unprecedented sustained widespread precipitation, nearly doubling climatological monthly rainfall amounts in less than 72 h. This resulted in extreme flooding in many of the Eifel-Ardennes low mountain range river catchments with loss of lives, and substantial damage and destruction. Despite many reconstructions of the event, open issues on the underlying physical mechanisms remain. In a numerical laboratory approach based on a 52-member spatially and temporally consistent high-resolution hindcast reconstruction of the event with the integrated hydrological surface-subsurface model ParFlow, this study shows the prognostic capabilities of ParFlow and further explores the physical mechanisms of the event. Within the range of the ensemble, ParFlow simulations can reproduce the timing and the order of magnitude of the flood event without additional calibration or tuning. What stands out is the large and effective buffer capacity of the soil. In the simulations, the upper soil in the highly affected Ahr, Erft, and Kyll river catchments are able to buffer between about one third to half of the precipitation that does not contribute immediately to the streamflow response and leading eventually to widespread, very high soil moisture saturation levels. In case of the Vesdre river catchment, due to its initially higher soil water saturation levels, the buffering capacity is lower; hence more precipitation is transferred into discharge.

平均降水量在12-01-2020达847.000mm/Year，相较于12-01-2019的847.000mm/Year保持不变。平均降水量数据按年更新，12-01-1961至12-01-2020期间平均值为847.000mm/Year，共60份观测结果。该数据的历史最高值出现于12-01-2020，达847.000mm/Year，而历史最低值则出现于12-01-2020，为847.000mm/Year。CEIC提供的平均降水量数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的比利时 – Table BE.World Bank.WDI: Environmental: Land Use, Protected Areas and National Wealth。