Weather
Estibaliz Gascon presents the IFS ensemble forecasts from ECMWF that provides an instantaneous precipitation type output variable.
Length: 37 minutes.
One of the greatest difficulties facing forecasters during the cool season is the correct determination of precipitation type, especially with temperatures close to freezing point. There are numerous sources of uncertainty in precipitation type forecasts which is why mixed phases are not well predicted. These uncertainties are difficult to reduce but can potentially be quantified by the use of ensembles.
The Integrated Forecast System (IFS) ensemble forecasts (ENS) from ECMWF provide an instantaneous precipitation type (ptype) output variable that describes 6 types of precipitation at the surface: rain, freezing rain, snow, wet snow, sleet or ice pellets (plus dry). As part of ECMWF's contribution to the ANYWHERE European project, two new products were developed. These are the most probable precipitation type, shown on map format, and the instantaneous probabilities of different types, shown for a given site. The first of these shows which type is most probable whenever the probability of some precipitation is >50%. The second product depicts the temporal evolution of probabilities for a specific location in bar chart format, classified also according to three categories of instantaneous precipitation rate. These new instantaneous probabilistic products will be shown through an experiment reproducing the freezing rain case study in Slovenia in 2014.
Jean Marc Moisselin presents methods to detect IWC from satellite data.
Length: 45 min
Author: Jean-Marc Moisselin (Météo-France)
Large amount of ice particle may cause erroneous aircraft probe measurement and damage aircraft engines. The ice crystals are generally located near cores of deep convection and associated cirrus anvils, at high altitude and in tropical areas. The understanding of the phenomena and its forecast are a key issue for aviation. There are several methods to detect clouds associated with ice crystal icing: MSG-CPP High IWC Mask, DARDAR, PHIWC, Alpha, RDT(detects and tracks convective systems).
A series of fields experiment in tropical regions have been conducted separately or conjointly by HAIC and HIWC projects. During HAIC campaigns, RDT has been provided on an operational basis through dedicated MétéoFrance processing chains. Qualitative and quantitative studies provided reasonably good results, especially in terms of probability of detection.
A new day-time attribute (adapted from MSG-CPP High IWC Mask algorithm) has been implemented in RDT v2016. Now RDT is produced globally by using five geostationary satellites, which in turn increased operational applications. New generation of satellites and the feedback on products performance will help to improve retrieval of the hazard and to define future research fields.
Andreas Frank gives a short overview about ZAMG special products for winter road conditions.
Length: 26 minutes.
During winter season we have a lot of additional products dealing with road weather, especially road conditions (snow, ice, hoarfrost,...). The talk will give a short overview about our special products, what are the differences to a normal forecast and point out some problems in forecasting special parameters in the alpine region. Additionally you will get some information about our special training services for road maintainance workers and also you will get a short overview about our internet portal, which we provide for our customers.
Virve Karsisto describes the currently used road weather model in Finland.
Length: 25 minutes.
Finnish Meteorological Institute’s (FMI) road weather model has been in operational use for almost 20 years. The main outputs of the model are road surface temperature and amounts of water, snow and ice on the road. Based on these values, the model determines also the road condition (e.g. wet, icy or snowy), calculates friction and gives index for overall driving conditions (normal, difficult, very difficult). The forecasts help in the road maintenance decision making and give useful information to the road users about the driving conditions. In the actual forecast phase, the input is obtained from forecast edited by duty meteorologist.
There are several things that know about the model behavior. For example, the model is very dependent of the driving forecast. The typical errors in the input data will also present themselves in the road weather forecast. In addition, the present model assumes open sky conditions and doesn't take into account the openness of the surroundings. This can cause error to the forecasts for example in forested areas. The model aims to improve the first forecast hours by utilizing a method called coupling. This correction is used during the forecast phase so that its effect reduces as the forecast advances. Although coupling improves the forecast in average, in some situations it might not work as intended.
Elina Tuhkalainen treats the formation and dissipation of fog at airports in Finland.
Length: 35 min
Author: Elina Tuhkalainen (FMI)
In this presentation formation and dissipation of fog and stratus will be treated. The presenters will also address how these phenomena occur around the year and how they affect the services at the airports in Finland.
Ralf Schmitz gives a short overview about how the German weather service supports land transport service.
Length: 19 minutes.
The lecture will give a short overview about how the German weather service support land transport service. Main focus is to show results of the new backend containing MOS trained weather forecasts at the 1500 German Street Weather Stations (SWS) and forecasts of the street model METRo at this stations. Results will be presented at a Frontend system which will be replaced by a new modern system as well as the new Backend System.
The presentation shows a possibility of turbulence diagnostics with aid of the Turbulence Kinetic Energy (TKE).
Length: 50 min
Author: André Simon, Péter Salavec (OMSZ)
Turbulence is a hazardous weather phenomenon for aviation and a challenge for a forecaster. It is typically a small-scale phenomenon and its direct observations and measurements are relatively sparse, except of the surface layer of the atmosphere. The presentation shows a possibility of turbulence diagnostics with aid of the Turbulence Kinetic Energy (TKE) calculated from a high-resolution non-hydrostatic model AROME. This parameter is calculated from a prognostic equation and it is only rarely applied as an end-product in operational forecasting. We studied the distribution of TKE in various meteorological situations, with focus on the Visual Flight Rules (VFR) conditions. Both advantages and limits of the TKE diagnostics are discussed. High attention is also given to forecasting of mountain waves, which can have both positive and negative impact on the flight. A development work based on this theory is in progress at the Unit of Aviation Meteorology resulting in new products for the mountain wave gliding branch of sport aviation.
Geir Ottar Fagerlid presents the upgraded Norwegian road weather warning system, focussing on precipitation and wind.
Length: 28 minutes.
Driving and road weather in Norway can be demanding all year around, not just because of the subarctic location, but also because of the complex terrain, from deep fjords to high mountains. The Norwegian Meteorological Institute have recently upgraded its road weather warning system, focusing on precipitation and wind.
Kris Bedka talks about methods helping to detect hazardous weather situations for aviation.
Length: 30 min
Author: Kris Bedka (NASA)
Current generation geostationary satellites are observing convection that is hazardous to aviation at increasingly high spatio-temporal detail. In recent years, commercial and research aircraft have collected automated turbulence and cloud ice water content observations that can be used to better understand exactly where within deep convection the turbulence and icing conditions are typically occurring. Ground-based weather radar and severe weather reports also identify locations of hail, downburst wind, and tornadoes. Research conducted at NASA Langley Research Center (LaRC), in collaboration with a number of U.S. and international partners, has resulted in geostationary-based analyses and automated detection algorithms that can denote where turbulence, icing, and severe weather conditions are likely. These methods are applicable to any geostationary visible and IR imager across the globe and therefore can be used to map these weather hazards in nearreal time, a capability that is especially valuable over regions without weather radars and other conventional observations of aviation hazards.
Alexander Jann and Andreas Wirth present the new aviation products of ASII-NG (Next Generation).
Length: 30 min
Author: Alexander Jann, Andreas Wirth (ZAMG)
Two new satellite-derived products related to turbulence analysis have been developed recently in the frame of the Nowcasting-SAF. The first product (ASII-GW”Automatic Satellite Image Interpretation – Gravity Waves”) objectively detects grating patterns in the water vapor 7.3 imagery which point to the presence of gravity waves. The second product (ASII-TF “Automatic Satellite Image Interpretation – Tropopause Folding”) identifies the location of tropopause folds from satellite and NWP data. The algorithm is based on the logistic regression method.
In this presentation, we will talk about the selected algorithms and present cases from the official Nowcasting-SAF validation reports (to be released shortly) to illustrate the product performance.
Marjo Hippi presents a numerical model developed at FMI that simulates the level of slipperiness on the side-walks.
Length: 30 minutes.
The Finnish Meteorological Institute (FMI) has developed a numerical weather model that simulates the level of slipperiness on the sidewalks. The model classifies the expected sidewalk slipperiness into three classes; normal, slippery and very slippery. Normal means that there is not ice or snow on the surface. FMI is giving warnings if very slippery sidewalk condition is expected. During very slippery sidewalk condition normal walking is difficult for everyone and extra attention must be paid off when walking.
Icy and snowy sidewalks are very typical phenomena in Finland during winter. Slipperiness due to ice and snow on sidewalks increases the risk of pedestrians' injuries. Almost every second person slips annually in Finland and around 50 000 persons (1 % of Finnish population) are injured and need medical attention. Slip injuries are a big problem causing economic losses and long sick leaves. Emergency departments are crowded during the most slippery days. FMI's warnings for slippery pedestrians' sidewalk condition is one way to improve the safety among the pedestrians and add awareness of slipperiness. Pedestrians may reserve more time for travelling, choose the way of travelling or use anti-slip devices if very slippery pavement condition is forecasted.
Peter Schmitt analyses the different aspects of CAT and presents a CAT forecasting method.
Length: 40 min
Author: Peter Schmitt (DWD)
Clear air turbulence (CAT) is the term for medium- or high-level turbulence in regions with significant wind shear. CAT is an important factor for the aviation safety.
In the first part of the presentation, I will show you typical parts of CAT in relation with the 300 hPa geopotential analysis. Furthermore you get an overview to the correlation between CAT and characteristic cloud patterns in satellite images. In many cases satellite images provide the first clue or a confirmation for the presence auf CAT.
The second part is dedicated the forecast of CAT in Deutscher Wetterdienst (DWD) with the ICON model. DWD has been applying a forecast method based on Eddy Dissipation Rate (EDR). This real property of atmospheric turbulence is the main sink term of Turbulent Kinetic Energy. In a case study you will see the typical working process in practice with consideration of the model output, typical cloud pattern in satellite image and the use of the conceptual model and the structure of geopotential field.