This article has been possible because of the cooperation between Television of Catalonia and the Applied Physics Department of the University of Barcelona, via the work of an intern student who was working from home because of the lockdown during the COVID19 pandemic.
The mood of people we have studied in this article was similar to the one experimented by researchers. Weeks and months at home, with the only outside contact through the window, and social media.
To obtain reliable snowfall estimates in high mountain remains a challenge. This study uses daily snow water equivalent (SWE) estimates by a cosmic ray sensor on two Swiss glaciers to assess three
readily-available high-quality precipitation products. We find a large bias between in situ SWE and snowfall, which differs among the precipitation products, the two sites, the winter seasons and in situ meteorological conditions. All products have great potential for various applications in the Alps.
In this work, machine learning techniques, satellite data and land-cover data were used to produce a land-cover map for Ireland that shows greater accuracy and resolution than an altered version of the standard land-cover map (ECOCLIMAP-SG) used for numerical weather prediction. This method offers a way to universally improve meteorological land-cover maps across jurisdictions, while also offering a method of updating the map regularly to account for seasonal changes in surface land-covers.
Agricultural production is largely determined by weather conditions during the crop growing season. Weather events such as frosts, droughts or heat stress during crop growth and development helps explain yield variability of common arable crops. We developed a methodology and visualisation tool for risk assessment, and tested the workflow for drought and frost risk. The methodology can be extended to other extreme weather events and their impacts on crop growth in different regions of the world.
The Norwegian Meteorological Institute initiated the project TV meteorologists as climate communicators in 2019. Our goal was to make it easier for people to understand climate change and how it relates to local weather. The TV meteorologists have received extended training in climate issues, and in the last two years they have had 40 TV-appearances focusing on different local climate issues on the NRK Evening news. The majority of the stories have also been shared through social media.
Fall velocities of rain drops are reported for 2–3 mm drop diameters for several different turbulent intensities. The fall velocities are measured by 2D video disdrometers and the turbulence intensities by 100 Hz sonic anemometer. The findings are, (i) the mean fall speed decreases with increasing turbulent intensity, and (ii) the standard deviation increases with increase in the rms of the air velocity fluctuations.
Persistent warm urban temperature anomalies – urban heat islands – significantly enhance already amplified climate warming in the Arctic. This study presents the surface urban heat islands in all circum-Arctic settlements with more than 3000 inhabitants. It reveals strong and persistent urban temperature anomalies during both summer and winter seasons that vary in different cities from 0.5 °C to more than 6.0 °C.
We have developed a tool to visualize rainfall observations, based on a combination of meteorological stations and weather radars, over Sweden in near real-time. By accumulating the rainfall in time (1–12 h) and space (hydrological basins), the tool is designed mainly for hydrological applications, e.g. to support flood forecasters and to facilitate post-event analyses. Despite evident uncertainties, different users have confirmed an added value of the tool in case studies.
Based on the LES model data, a very strong correlation was found not only between the condensation, but also evaporation rate and upward mass flux. While good correlation between the upward mass flux and condensation is not surprising, the very high correlation coefficient (R = 0.99), as well as the role of the upward mass flux in determining the evaporation rate, is remarkable and may be important for future latent heat parameterization development.
The Pūre orchard is one of the biggest and oldest apple orchards in the Baltic. We have digitized the full flowering phenological data of apple trees over the period of 1959 to 2019. Described changes in full-flowering time: apple trees all 17 varieties have begun to flower earlier. We tested three sets of meteorological data in phenological model to develop better-quality phenological predictions. As ongoing and predicted climate change has had and will have a significant impact on agriculture
This study presents estimates of the maximum temperature in Bangladesh for the 21st century for the pre-monsoon season (March–May), the hottest season in Bangladesh. The maximum temperature is important as indicator of the frequency and severity of heatwaves. Several emission scenarios were considered assuming different developments in the emission of greenhouse gases. Results show that there will likely be a heating of at least 1 to 2 degrees Celsius.
Correct estimates of wind speed between 60 and 200 m above ground are of great interest for the renewable energy sector. Observed wind speeds are compared to three different reanalyses. ERA5 and COSMO-REA6 outperform MERRA-2 at offshore, flat and hilly sites. Over land, ERA5 models nighttime wind speed better than COSMO-REA6 due to better representation of the low level jet through higher vertical resolution, a more comprehensive data assimilation scheme, and/or the more recent model version.
Wind speed forecasts have many potential users that could benefit from skilful forecasts. We validated weekly mean speed forecasts for Finland using
forecasts from the ECMWF (European Centre for Medium-Range Weather Forecasts). We concentrate on winter (November, December and January) forecasts.
The forecasts proved to be skilful until the third week, but the longest skilful lead time depends on how the skill is calculated and what is used as the reference.
Each building has to withstand a certain mass of snow. In the Alps, snow load standards are coarse, and inconsistencies at national borders are common. A new methodology to derive a snow load map for Austria is presented. It consists of modeling and spatially interpolating snow loads with modern extreme value statistics. The new approach is much more accurate than the currently used Austrian snow load map and provides a reproducible base for other countries.
Convection-permitting models allow for prediction of rainfall events with increasing levels of detail. However, this increased resolution can create problems such as the so-called double penalty problem when attempting to verify model forecast accuracy. This problem is amplified when trying to maximise the value of a convection-permitting ensemble prediction system (EPS). Post-processing of the EPS can help to overcome these issues. In this spirit, two new up-scaling algorithms based on Machine
10-year long sensitivity study on domain size was perform with REMO regional climate model. We can conclude, that the selection of domain size has larger impact on the simulation of precipitation, and in case of the seasonal mean of the precipitation indices, the differences amongst the results obtained on each model domain exceed 10%. In general, the smallest biases were obtained on the largest domain, therefore further long term simulations are being achieved on this.