Identify and interpret fields and derived products
Georg Pistotnik covers the topic of drylines, shows it's relevance in severe weather development.
Drylines are boundaries separating warmer and drier from cooler and moister air, usually resulting from differential diurnal heating and therefore vertical mixing. The most common and distinct dryline in the Alpine region is the boundary between Foehn winds (dynamically driven) and upvalley/upslope circulations (thermally driven). Thunderstorms often form along drylines and intensify when they move onto their moist side, where CAPE and vertical wind shear are systematically enhanced and favor convective organization. This presentation highlights how station and readiosonde data, high-resolution satellite imagery and even webcam images can be integrated into the nowcasting of drylines and resulting thunderstorms, using some prominent cases of the past few years in the eastern Alpine region.
Lecture slides
Katarina Katušić talks about Croatian Met Service work principles and schedules, case study and satellite products used during operational shift work.
The Weather and Marine Analysis and Forecasting Sector is a part of the Croatian Meteorological and Hydrological Service (DHMZ), and it is in charge of weather forecasts and warnings for the public and numerous companies. Over the years, we have gone through many challenges. Quite recently, during the lockdown, the earthquake severely damaged our headquarters, and even with those difficulties the work did not stop. We also prepare and present weather forecasts for national television. Furthermore, this presentation will cover the usage of weather satellite products in daily operational work.
Lecture slides
Jorge Ponte shows the challenges of being a forecaster, issuing warnings and discusses extreme precipitation event that affected Lisbon.
Extreme rainfall events in December 2022 caused significant losses in Lisbon, Portugal. This presentation examines these events to discuss whether it was possible (or not) to make a better forecast and issue earlier warnings. By analyzing various numerical model products from the preceding days alongside real-time monitoring data (satellite, radar, stations), the presentation will explore the operational forecaster's decision-making process during extreme weather situations.
Lecture slides
A conceptual model on DIBS: A special kind of Cirrus clouds formed by dust
The strongest influence of DIBS, and especially of dusty cirrus, on surface weather is mainly the reduced solar radiation reaching the ground as dust particles act as condensation nuclei and form clouds where otherwise no clouds would have been present. As current numerical weather prediction models do not accurately account for microphysical cloud formation processes caused by the additional dust at higher atmospheric levels, predicted maximum temperatures often have a considerable bias towards higher values.
Case Study of the pre-convective environment of 19th May 2021 using IASI sounder data.
This Case Study of the pre-convective environment of 19th May 2021 using IASI sounder data focuses on exploring how the use of IASI retrievals added additional value to the forecast of the incoming storm over Hungary.
Ana Russo and Rita Durão talk about heatwave impact on air quality, pollutants and evaluation of air quality.
Heatwaves often lead to low air quality levels. Very high to extreme temperatures combined with stagnant air conditions increase air pollutants concentrations, such as tropospheric ozone. This effect might be emphasized when drought conditions also occur, which contributes to increasing fire danger and decreasing air quality levels too. Air pollution impacts on health are consequently an important issue, together with the drawbacks on ecosystems. This lecture will provide insights into the detection, monitoring, and evaluation of air quality impacts, using among others, remote sensing products.
Bostjan Muri talks about using LSA SAF data and vegetation anomalies for drought monitoring.
In this presentation, we explore numerous real world applications of the use of LSA SAF data. Our focus is identifying heatwaves and droughts based on satellite data. Vegetation anomalies can be particularly helpful for drought monitoring. These show cases are selected in order to highlight the benefits of specific applications using LSA SAF data and its added-value when compared with other existing sources of observations (either satellite or meteorological stations) as well as model output.
Anke Duguay-Tetzlaff and Vincent Humphrey present about the recent Swiss drought monitoring project and use of EUMETSAT satellite data for drought monitoring.
The Swiss government has started a drought monitoring project in 2023. The goal is to set an operational drought monitoring and warning system in the upcoming years. In a pre-study we have analyzed the potential of EUMETSAT satellite data for climatological drought monitoring in Switzerland. We will present possibilities and shortcomings of the different analyzed soil moisture, land surface temperature and evaporation data and provide an outlook on how we plan to integrate EUMETSAT data in the system.
Luca Brocca shows how to combine multiple satellite derived variables to monitor drought.
How do we monitor drought? Is it enough to use only precipitation data and calculate the SPI (Standardized Precipitation Index)? New satellite-derived products (precipitation, evaporation, soil moisture and snow) offer additional ways to monitor drought in space and time, to assess WHERE the water is (surface soil, root zone soil, snowpack), and thus to know WHEN the water will be available. Real-world case studies will be analyzed together with the participants, also using an interactive platform (https://explorer.dte-hydro.adamplatform.eu/). The objectives of the lecture are: (1) to assess drought risk based on (new) satellite observations, and (2) to translate drought risk information into real-world decisions for water resources management (e.g., reservoir management, irrigation, hydropower generation).
João Martins talks about using Land Surface Temperature (LST) in heatwave monitoring using LSA SAF datasets.
Heat and water stress leave clear signatures on land surface variables that can be monitored from space. The LSA SAF has been providing satellite datasets and products that allow the characterization of the surface energy budget and the monitoring of vegetation growth and stress. We will show that combining information on the surface temperature diurnal cycle and on vegetation state provides a different perspective on the spatial extent and time evolution of droughts and heatwaves, and reveals underlying soil vegetation-atmosphere feedbacks.
Vesa Nietosvaara showcases how the MTG's FCI instrument will improve the quality of satellite data, especially for users in high latitudes.
The first Meteosat Third Generation (MTG-I) satellite with Flexible Combined Instrument (FCI) was launched at the end of 2022. It will be followed later in 2024 by MTG-S Satellite with Infrared Sounder onboard. MTG will carry novelty instruments – Infrared Sounder, Lightning Imager and Ultraviolet Visible Near-infrared (UVN) Spectrometer - in the GEO orbit. Meteosat Third Generation aims to secure continuity and to increase the capabilities of the Meteosat satellites in response to requirements of the future forecast/nowcast systems. Altogether, the new and enhanced capabilities will allow us to make a huge step in better monitoring of our environment, and allowing development of new applications.
Marjo Hippi explains how FMI deals with slipperiness during winter.
Icy and snowy sidewalks are very typical phenomena in Finland during winter. Near zero temperatures and slipperiness due to ice and snow on sidewalks increases the pedestrians' slip risk. Almost every second person slips annually in Finland and around 50 000 persons (1 % of Finnish population) are injured needing medical attention. Slip injuries cause huge economic losses, long sick leaves, and human suffering. The Finnish Meteorological Institute (FMI) has developed a numerical weather model that predicts the sidewalk slipperiness from pedestrians' point of view. The model classifies the sidewalk slipperiness into three classes: normal, slippery, and very slippery. Very slippery sidewalk condition mean that the slip risk is increased. Typical situations for very difficult sidewalk situations are packed snow, freezing or ice layer covered by water or snow. The model is a tool for duty meteorologists when issuing warning about slippery sidewalk condition.