bluuebunny/crossref_metadata_2025 huggingface dataset:
Artificial Neural Network Approach in Rain Rate Estimation by Using AMSU-B and MHS Data
Authors: Akın Melek , Öztopal Ahmet
Published: June 2022

Low-Earth Orbit (LEO) satellites provide passive microwave (PMW) information about the hydrometeors. PMW data, which can be obtained from Advanced Microwave Sounding Unit-B (AMSU-B) and Microwave Humidity Sounder (MHS), has a direct interaction with precipitation. The methods developed using PMW data are sensitive to the concentration of ice particles or water droplets associated with precipitation. Therefore, this data is more appropriate to estimate the rain rate.

Artificial Neural Network (ANN) is one of the techniques of Machine Learning (ML). It has been developed by imitating the stimulation and information received by the sense organs through the neurons in the computer environment. Today it is one of the technics of being used in almost all computational science fields. ANN can also be thought of as a black box that processes given inputs and generates outputs. This system process data in parallel, and it also learn coefficients among neurons with the principle of minimalizing and renewing mistake. In other words, ANN uses the method of trial and error.

The aim of this study is to develop an estimation model based on ANN by using brightness temperature data from five different channels (89, 150, 184, 186, and 190 GHz) of the AMSU-B and MHS mounted on NOAA 15-18 and METOP-A satellites. Brightness temperatures obtained by different channel frequencies are used as an input for the ANN model, and the rain rate values are tried to be estimated. In addition, the model results are compared with the rain gauge data and rain rate values of the 183 WSL Fast Rain Rate Retrieval Algorithm.

Keywords: Artificial Neural Networks, Precipitation, Rain rate, Turkey.
Composite monthly mean temperature time series for Iceland reaching back to the late 18th century.
Authors: Ólafsdóttir Kristín Björg , Jónsson Trausti
Published: June 2022

Composite record of monthly mean temperatures is presented for Iceland. It is based on over ten series of temperature observations, covering a time interval from 1779 to present. It represents the major temperature variations in Iceland during the last centuries. The longest continuous temperature record in Iceland comes from Stykkishólmur. The observations started in November 1845, by Árni Thorlacius, a merchant in the village of Stykkishólmur. It marks a watershed in the history of meteorological observations in Iceland, with observations at the site continuing to the present. The composite Icelandic time series prior to 1845 is reconstructed using observations from several other locations in the country. Observations of relatively good quality exist from Reykjavík, from 1820 to 1854, made by Jón Thorsteinsson in cooperation with the Danish Scientific Society. There is a strong relationship between the temperature observations at Stykkishólmur and Reykjavík during the overlapping period. Before that time comes the least reliable part of the series. Several short discontinuous series of measurements exist from the late eighteenth century to early nineteenth century from various locations in the country. The observations were in the hands of enthusiastic individuals during this time and the quality of them is very variable. Although the confidence in the reconstruction in the oldest part of the series is low, it gives valuable estimate of the yearly and seasonal temperature variations during this time. Overall, the data show a warming trend, but with significant multi-decadal variability. The temperatures in the 19th century are lower and the variations are much greater than in the 20th century. It corresponds to years when sea ice was observed at the coast and the temperature variations are larger when there a is more irregular sea-ice influence.
Spatial structures in atmospheric boundary-layer flow – wind tunnel modeling
Authors: Jurcakova Klara , Kellnerova Radka
Published: June 2022

Coherent structures play a dominant role in momentum and mass transfer in turbulent boundary layers. It is very difficult to directly monitor those structures in an atmospheric boundary layer because their detection from point measurements is very uncertain and continuous spatial atmospheric measurements are seldom. Wind tunnel modeling of ABL flows offers a well-controlled environment and allows the utilization of state-of-the-art experimental methods such as Particle Image Velocimetry with a high temporal and spatial resolution. We have analyzed flow measurements from the meteorological observatory Kopisty (Czech Republic) where an 80m tall meteorological tower equipped with 3D sonic anemometers at four levels is installed. We have built a wind-tunnel scaled model of the observatory and its vicinity to study spatial coherent structures and their characteristics in neutrally stratified ABL flows. The wind-tunnel measurement revealed large organized structures as low- and high-momentum regions or clusters of correlated longitudinal and vertical velocity fluctuations (e.g., sweep and ejection events). Those structures are not eddies, they are in the shape of irregular waves. They can be a few hundred meters long and up to a hundred meters wide. The structures’ size is increasing with the height above ground and in the lowest 100 m, the majority of them are attached to the ground. Both measurements and model results showed the dependence of the flow structure on the upwind terrain conditions. The coherent structures are smaller and stronger in the flow coming from the hilly forested terrain (southwest wind direction) compared to the flow coming from the lakeside (northeast wind direction).
“Pseudo-deterministic” precipitation products, a clustering-based approach to combine and reduce ensemble information
Authors: Schmidt Malte , Bondy Jan , Fundel Vanessa , Blahak Ulrich
Published: June 2022

Ensemble prediction systems have evolved as a standard in modern weather prediction. At the same time, with an increasing number of members and higher spatiotemporal resolution, the amount of data produced is growing fast. However, not all operational users are able to process the increasing amount of data, which calls for methods to reduce ensemble information.

The SINFONY project at Deutscher Wetterdienst (DWD) focuses on the probabilistic forecasting and Nowcasting-NWP combination of precipitation, with the aim of better representing convective heavy rainfall events. Ensemble reduction of SINFONY output data is based on two concepts. Firstly, it aims to compact the information of an ensemble into a new, combined member (the “pseudo-deterministic” member). The second approach is to retain most of the information in a member-reduced ensemble that also contains the newly created pseudo-deterministic member. This postprocessing of an ensemble can be helpful to users that have limited computational power at their disposal but still want to benefit from the probabilistic information of the ensemble. Another application of the pseudo-deterministic product could be its visualisation as a map with locally the most probable precipitation scenario.

The pseudo-deterministic member is defined as the locally most probable forecast of the ensemble identified by a k-means-based clustering of the members in limited areas and blending the resulting best local forecasts back together. This leads to a mixed forecast that is supposed to have higher statistical skill averaged over the model domain (here, Germany) compared to the weather model’s deterministic member. In addition, the clustering can also be used for the identification of precipitation scenarios that differ significantly from the locally most probable precipitation. As a result, a reduced ensemble can be derived that contains a large part of the forecast distribution. In this poster, we present and evaluate the developed algorithm for the ensemble reduction and explore how skill depends on the number of reduced ensemble members in convective weather situations. 
From radar-based heavy rainfall event monitoring to impact assessment (an example from Germany)
Authors: Walawender Ewelina , Lengfeld Katharina , Winterrath Tanja , Weigl Elmar
Published: June 2022

Extreme rainfall events, due to its dynamic and still not always predictable character, continue to be a subject of social concern even in a highly-developed country such as Germany. They can lead to numerous hazards, like flash-floods, landslides and soil erosion, causing damages and huge economic costs, as well as direct risk to human life. 

Thus, not only the real-time monitoring but also a deep analysis of past extreme precipitation events has a crucial meaning in understanding their possible impact. The investigation of past losses and risk factors can help to estimate the potential danger and shape human sensitivity to weather extremes.

With this objective, the Deutscher Wetterdienst (DWD) performs a radar-based object-oriented identification and classification of extreme rainfall. For the past events that occurred over the area of Germany in 2001-2021, the Catalogue of Radar-based Heavy Rainfall Events (CatRaRE) is available. It is derived from high-resolution climatological data (1h, 1km - RADKLIM). For the current cases of heavy rainfall, quasi real-time monitoring based on hourly operational hourly RADOLAN data is performed.

For all detected events a wide range of indices and extremity attributes (e.g. return period, heavy precipitation and weather extremity indices) were determined. The geospatial character of the dataset has allowed also for an enrichment with e.g. socioeconomic and geophysical variables, building the substantial basis for a risk analysis. In addition, combining meteorological and non-meteorological characteristics of each event with available data on corresponding insurance losses, fire-brigades’ operations or crowdsourcing reports served for an impact quantification. Through those steps, we obtained a rich basis that can be also used operationally as a lookup table when estimating a possible impact of current or forecasted events that show similar characteristics.

We will present results of a heavy rainfall hazard mapping for the area of Germany together with an impact analysis of all classified heavy precipitation events. In addition, we will give examples for using the extended version of the CatRaRE Catalogue as a basis for assessing the impact of operationally detected and/or predicted precipitation events.
Object-based Nowcasting at DWD using KONRAD3D, HYMEC, and Lightning Data
Authors: Josipovic Lukas , Werner Manuel , Feger Robert , Wapler Kathrin , Schultze Markus , Blahak Ulrich
Published: June 2022

In recent years, a new nowcasting algorithm has been developed at DWD (Deutscher Wetterdienst), called KONRAD3D. It aims to automatically detect, track, and nowcast convective cells in order to support DWD’s warning decisions. The deterministic core of KONRAD3D consists of state of the art techniques, e.g. adaptive thresholding for the cell detection and Kalman filtering of cell centroids and velocities during the tracking step.

Originally, KONRAD3D made use of three-dimensional radar reflectivity data only. Currently, work is in progress to include lightning data and information on hydrometeor types that is based on polarimetric radar data. In this context, we will introduce a new polarimetric hail flag—a parameter that assesses a cell’s threat of hail—that rests upon the hydrometeor data and should roughly estimate the expectable near-ground hail size.

Studies about relationships of lightning and the hail amount of KONRAD3D cells showed strong correlations. A lightning jump detection within KONRAD3D turned out to be a promising approach for hail nowcasting. Statistics on 800 hailstorms over Germany between April and September 2019 revealed that lightning jumps occur 15 to 20 minutes before the maximum near-ground hail intensity on average.

One part of DWD’s project SINFONY (Seamless INtegrated FOrecastiNg sYstem) focuses on extending KONRAD3D towards an object-based ensemble nowcasting algorithm called KONRAD3D-EPS. It enables a suitable way of including cell life-cycle models in order to better predict intensification and weakening tendencies..

We give an overview of our deterministic cell detection and tracking algorithm KONRAD3D and present statistics of cell attributes. Moreover, we demonstrate the concept of our probabilistic nowcasting system. We also illustrate the basic functionalities of our algorithms for prominent example cases with focus on hail threat assessment.
Probabilistic short-term to seasonal soil moisture forecasts over Germany and surrounds using the hydrologic model ParFlow/CLM
Authors: Belleflamme Alexandre , Wagner Niklas , Goergen Klaus , Kollet Stefan
Published: June 2022

The repeated droughts that have affected Europe in 2018, 2019, and 2020, as well as increasing environmental and legal constraints that demand for a more sustainable management of soil water resources, stress the needs for terrestrial water budget forecasts at stakeholder-relevant high spatial resolutions, e.g., for the agricultural sector. In this context, we have established and operate a new quasi-operational forecasting experiment with the integrated hydrologic model ParFlow (www.parflow.org) which forecasts all relevant states and fluxes of the terrestrial water cycle over Germany and its neighbouring regions at 600m horizontal resolution. ParFlow simulates the complete 2D/3D surface and subsurface water budget, including the unsaturated and the saturated (groundwater) zones, as well as the energy and water fluxes at the atmosphere-surface-subsurface interface through its surface module CLM (Common Land Model). The simulations are driven by surface and near-surface atmospheric variables from different weather forecasting products from ECMWF (European Centre for Medium-Range Weather Forecasts). The 10-day hydrologic forecast, driven by the deterministic high-resolution weather forecast HRES, is complemented by a 50-member ensemble of ParFlow/CLM simulations forced by ECMWF’s ENS probabilistic forecast ensemble. This short-term ensemble approach allows for evaluating the impact of the uncertainties of the weather forecast, and especially of precipitation, on the different components of the terrestrial water budget. At the beginning of each season, we additionally run a 4-month seasonal prediction ensemble of the terrestrial water cycle using ECMWF’s SEAS long-term probabilistic 50-member ensemble forecast. Since soil moisture has a high inertia, especially for deeper soil layers, compared to, e.g., atmospheric variables, the spread of the ensemble remains acceptable over the prediction period. To provide the most useful information products on the evolution of water resources over the upcoming months to stakeholders, we derive diagnostics from the probabilistic seasonal forecasts that allow for a risk assessment. For example, for each 10-day period of the forecast, we calculate the probability (or risk) for the plant available water to reach values below a critical threshold for water stress, e.g., 30%. A prototypical application of these experiments is the ADAPTER project (www.adapter-projekt.de). In this framework, the monitoring and forecasting of relevant soil moisture-related diagnostics is meant to provide support for agricultural and water resources management, e.g., against droughts.
End-to-end learning of representative PV capacity factors from aggregated PV feed-ins
Authors: Zech Matthias , von Bremen Lueder
Published: June 2022

Energy system models rely on accurate weather information to capture spatio-temporal characteristics of renewable energy generation. Whereas energy system models are often solved with high abstraction of the actual energy system, meteorological data from reanalysis or satellites provides rich gridded information of the weather. The mapping from meteorological data to renewable energy generation usually relies on major assumptions as for solar photovoltaic energy the photovoltaic module parameters. In this study, we show that these assumptions lead to large deviations between reported and estimated energy as shown in case of photovoltaic energy feed-ins in Germany. To decrease these deviations, we propose a novel gradient-based end-to-end framework which is able to learn local representative photovoltaic capacity factors from aggregated reported transmission system operator feed-ins. As part of the end-to-end framework, we compare physical and neural network model formulations to obtain a functional mapping from meteorological data to photovoltaic capacity factors. We show that all developed methods have better performance than commonly used reference methods. The neural network shows remarkable success to predict the aggregated Transmission System Operator photovoltaic energy feed-ins leading to an accurate, unbiased prediction model. However, choosing the neural network model is not always the strictly preferred choice as it depends on the use case: Operational use cases may decide for the neural network implementation due to its higher accuracy whereas academic settings prefer the physical model due to its high interpretability and transferability. In this talk, we discuss the development of the end-to-end framework which we believe is highly relevant due to its energy-meteorological and methodological contributions. 
Advances enabled by a Regional Environmental Prediction system developed in the UK
Authors: Berthou Segolene , Arnold Alex , Castillo Juan Manuel , Lewis Huw , Mahmood Sana , Sanchez Claudio
Published: June 2022

In partnership with other UK institutions, the UK Met Office has developed a regional environmental prediction system at km scale, over two domains: the Northwest European shelf and the Indian region. This provides a flexible research capability with which to study the interactions between atmosphere, land, river, ocean, wave and biogeochemistry processes resolved at km-scale, and the effect of environmental feedbacks on the evolution and impacts of multi-hazard weather events. The UKC3 coupled system incorporates models of the atmosphere (Met Office Unified Model), land surface with river routing (JULES), shelf-sea ocean (NEMO), ocean surface waves (WAVEWATCH III) and biogeochemistry (ERSEM) coupled together using OASIS3-MCT libraries and the FabM coupler. This research framework has enabled to uncover interesting scientific results and to improve to both atmospheric and marine weather prediction. Recent developments have further enabled to run the system in ensemble forecast mode and in climate mode. We present advances allowed by this system, such as:

benefits of ocean/wave coupled system for marine forecasting

Improvements of summer temperature forecasts by using SST prediction from the marine prediction system

improvements to winter storm wind forecasting when coupling the atmosphere with the wave models, resulting in changes to the atmospheric drag scheme

changes to tropical cyclone prediction from atmosphere-ocean coupling mostly, coupled system enabling a more rigorous treatment of the near-surface energy budget

Benefits and challenges of integrated hydrology

dampening of UK heatwaves by tidal processes over the northwest European shelf

effects of representing marine diurnal cycle on the diurnal cycle of convection over the maritime continent

impacts of an SST perturbation scheme in ensemble forecasting system

first atmosphere/ocean climate runs at km-scale over the Northwest European self.

 
To what extent does the diagnosis of multiple grid-box weather types add value in post-processing ensemble rainfall forecasts?
Authors: Pillosu Fatima , Hewson Timothy
Published: June 2022

"ecPoint" is a statistical post-processing technique that anticipates sub-grid variability and estimates biases in numerical weather prediction (NWP) model outputs, de facto downscaling such outputs from grid-box to point-scale. Forecasts are post-processed based on the distribution of errors in short-range forecasts versus rain gauge observations in the calibration period. This talk will focus on the branch of the ecPoint family products that post-processes ECMWF ensemble (ENS) rainfall forecasts. ecPoint applies the "remote calibration" approach, whose concept is based on the fact that the physics of rainfall generation is the same around the globe. The "remote calibration" approach then allows the post-processing of forecasts in location X using past observations in different regions, countries, or continents as far as the rainfall-generating weather type (WT) between location X and the remote locations is similar. "Weather types" are identified at grid-box scale and can be defined with different degrees of precision. For example, one can have a single-WT scenario where every grid-box is post-processed with the same error distribution. Or one can have a multiple-WT scenario where n significantly different error distributions are defined using predictors calculated from NWP variables (e.g. the fraction of convective rainfall in the total precipitation forecasts, the speed of steering winds, CAPE, etc.) or location-related variables (e.g. solar radiation, orography, etc.). Each grid-box forecast is then post-processed with the corresponding error distribution. In spite of verification having shown that multi-WT ecPoint-Rainfall (214 WTs derived from five predictors) provides more reliable and skilful rainfall forecasts than raw ENS (for point-verification, especially in case of extremes, e.g. rainfall greater than 50 mm/12h), such a product requires the investment of resources to manually re-calibrate ecPoint-Rainfall for new model cycles. Although a multiple-WT ecPoint-Rainfall delivers better forecasts, a single-WT product would be cheaper to re-calibrate. So, is it worth maintaining a multiple-WT ecPoint-Rainfall? This talk aims to answer this question. 
Impact of radiation on the formation of potential vorticity anomalies
Authors: Schäfer Sophia , Attinger Roman , Joos Hanna , Zardi Noè
Published: June 2022

Radiation in the atmosphere drives atmospheric dynamics on all scales from locally in a cloud via weather systems to global weather and climate and also interacts strongly with physical processes. Radiative heating and cooling can have a significant effect on the dynamics of extratropical cyclones (Schäfer and Voigt 2018), but the impact has been less extensively studied than for other sources of diabatic heating. Attinger et al. (2019) found that radiative heating and cooling can both increase and decrease cyclone strength measured by potential vorticity (PV) in different regions of a marine pacific cyclone, while Attinger et al. (2021) analysed cyclone composites and found that radiation can have a comparable impact on potential vorticity generation along the cold front as convection and condensation for cyclones in a cold environment.

We investigate the local and global effects of radiation-dynamics interaction by analysing accumulated heating rates and potential vorticity both locally in the grid-boxes and accumulated along trajectories. We find a significant effect of longwave radiation on both potential temperature and potential vorticity in the Northern Hemisphere, particularly in the lower troposphere. There is a pronounced land-sea contrast and impact of orography. The impact is concentrated at the top of cloud layers, particularly low clouds, showing the importance of cloud-radiation-dynamics interaction for dynamic development. We investigate in which regions and parts of cyclones radiative effects are particularly important.

 References:

Attinger, R., Spreitzer, E., Boettcher, M., Wernli, H., & Joos, H. (2021). Systematic assessment of the diabatic processes that modify low-level potential vorticity in extratropical cyclones. Weather and Climate Dynamics, 2(4), 1073-1091. https://doi.org/10.5194/wcd-2-1073-2021

Attinger, R, Spreitzer, E, Boettcher, M, Forbes, R, Wernli, H, Joos, H. (2019), Quantifying the role of individual diabatic processes for the formation of PV anomalies in a North Pacific cyclone. Q J R Meteorol Soc.; 145: 2454– 2476. https://doi.org/10.1002/qj.3573

Schäfer, S. A. K., & Voigt, A. (2018). Radiation weakens idealized midlatitude cyclones. Geophysical Research Letters, 45, 2833– 2841. https://doi.org/10.1002/2017GL076726
Identifying and enhancing socioeconomic value of Integrated Urban Services
Authors: Perrels Adriaan , Millls Gerald
Published: June 2022

All over the World large and medium-sized cities formulate ambitions and implement plans to create smart, sustainable, and climate resilient urban environments. These plans are needed to manage risks in urban areas where hazardous events can cause a series of interlocking systems to fail. To support these plans Integrated Urban Services (IUS) are being developed. IUS is driven both by the growing capabilities of NHMSs to develop and provide such services and by the growing needs of urban decision makers to adequately anticipate these hazards and their impacts on cities and to improve short-term and long-term resilience. To implement IUS cities must invest in diverse observation and modelling options to monitor and evaluate their response to changes in the climate (including extreme events) and urban landscape.

Notwithstanding the large potential to contribute to sustainability goals of cities the realization of broad scoped truly integrated urban services could be faster than its current pace of development. In this context it is expected that the ability to better demonstrate the value potential of IUS and the extra benefits of further developing and coordinating different services would help to precipitate uptake and expansion of IUS. To this end, the WMO Study Group on Integrated Urban Services has produced several guidelines to help NHMSs to create IUS in cooperation city authorities. This Study Group also received expert support to better describe the benefit potential, mechanisms behind benefit generation, and ways to assess the net benefits of IUS. The approach hinges on the value chain concept.

The presentation will show how the value chain can explain and analyse the diversity in organizational and service structure of IUS. The presentation will also illustrate how the value chain can be used to quantify value generation and how that approach can also be used to review what segments in current service practice seem to offer the prospect for the most notable improvements. Assessed service cases are as such hypothetical yet based on real world information and on indications from the literature on key parameters.
Characterizing the influence of obstacles on scanning microwave profilers
Authors: Böck Tobias , Pospichal Bernhard , Löhnert Ulrich
Published: June 2022

Ground-based microwave radiometers (MWRs) which operate within the K-band and V-band (22 – 32 GHz and 51 – 58 GHz) are used to obtain temperature profiles (T) and rather coarse humidity profiles (H) of the troposphere. MWRs measure microwave radiances, expressed as brightness temperatures (TB), in zenith and other angles over an area of ~10 km radius. The brightness temperatures can be used to retrieve the T-profiles and H-profiles. Ground-based MWRs are also among the best instruments to measure path integrated values like IWV (Integrated Water Vapor) and LWP (Liquid Water Path), with excellent uncertainties below 0.5 kg/m2 and 20 g/m2, respectively. Besides zenith observations which provide these variables with a high temporal resolution (up to 1 second), elevation scans are used to retrieve more precise temperature profiles close to the ground, as well as to assess horizontal water vapor and cloud inhomogeneities.

Driven by the E-PROFILE program, a business case proposal was accepted by EUMETNET last year to continuously provide MWR data to the European meteorological services for boundary layer monitoring and assimilation to numerical weather prediction (NWP) models. Also, the European Research Infrastructure for the observation of Aerosol, Clouds, and Trace gases ACTRIS and the European COST action PROBE (PROfiling the atmospheric Boundary layer at European scale) currently focus on establishing continent-wide quality and observation standards for MWR networks for research as well as for NWP applications.

When installing a MWR, it has to be kept in mind that external error sources like physical obstacles and radio frequency interference (RFI) can have an impact on observations and the quality of the obtained atmospheric profiles when they are within the range of the MWR. Therefore, identifying and coping with these kinds of errors is one important part of the quality control, especially while searching for a suitable measurement location with low disturbances. If physical obstacles like trees, towers, masts and walls are too close to the MWR they can have significant repercussions in elevation scans which are necessary for deriving accurate T-profiles. That is why it is crucial to pinpoint the exact location of these obstacles and to determine a minimum distance at which they do not interfere with the MWR anymore. We will present a sensitivity study which uses a line-by-line (LBL) radiative transfer (RT) model and in which obstacles at any distance from the profiler can be simulated. Output comparisons with and without these simulated obstacles provide a theoretical atmospheric penetration depth per frequency channel and elevation.
Predicting flash floods in Ecuador and beyond
Authors: Pillosu Fatima ,   Flash Flood Team
Published: June 2022

"ecPoint" is a statistical post-processing technique that anticipates sub-grid variability and biases in numerical weather prediction (NWP) model outputs, de facto downscaling them from grid-box to point-scale. ecPoint-Rainfall is the branch of the ecPoint family of products that post-processes ECMWF ensemble (ENS) rainfall forecasts. Global verification over a 1-year period has shown that, versus rain gauge observations, ecPoint-Rainfall provides more reliable and skilful rainfall forecasts than raw ENS (up to 10-day lead times and especially in case of extremes, e.g. rainfall >= 50 mm/12h). 

Flash flood forecasting could be a natural downstream application for ecPoint-Rainfall. One of this field's challenges is indeed finding reliable and skilful forecasts for localized rainfall extremes, which tend to be the primary cause of flash flood events. Radar-derived rainfall estimates can feed into nowcasting systems (which provide forecasts with lead times up to a few hours), whilst km-scale NWP models can provide reasonable guidance for localized extreme rainfall for slightly longer leads (e.g. up to 24 hours). However, such small lead times limit the mitigating actions that end-users can take. ecPoint-Rainfall targets longer leads.

ecPoint-Rainfall forecasts have been verified against flash flood observations in Ecuador to understand whether they can better predict flash floods compared to other medium-range rainfall forecasts (e.g. raw ECMWF ENS). It will be shown that, in the context of flash flood reports, in regions dominated by small scale convective systems (e.g. Ecuador's Andean region), ecPoint-Rainfall outperforms ENS. In contrast, in areas dominated by large-scale convective systems (e.g. coastal areas of Ecuador), the performance of the two forecasting systems is comparable. This talk will discuss these findings and how they are helping with the creation of global medium-range, ecPoint-Rainfall-based flash flood warnings.
Seasonal Forecasts of Winter Temperature Improved by Higher-Order Modes of Mean Sea Level Pressure Variability in the North Atlantic Sector
Authors: Dalelane Clementine
Published: June 2022

The variability of the sea level pressure in the North Atlantic sector is the most important driver of weather and climate in Europe. The main mode of this variability, the North Atlantic Oscillation (NAO), explains up to 50% of the total variance. Other modes, known as the Scandinavian index, East Atlantic and East Atlantic/West Russian pattern, complement the variability of the sea level pressure, thereby influencing the European climate.

Current seasonal forecasts of European winter climate, though highly desirable for society and economy, are as yet not fully reliable. There exist a number of autumn predictors, such as sea surface and stratospheric temperature, Eurasian snow depth, and Arctic sea ice extension, that impact on the upcoming pressure regimes in a predictable way. The present dynamical seasonal forecast systems respond still too weakly to these known seasonal predictors. But the relationship is reproduced quite well by means of statistics.

In combination, statistical and dynamical forecasts have the potential to improve forecasts of the North Atlantic pressure conditions and thereby affected variables like temperature and precipitation in Europe considerably. A seasonal prediction system with enhanced winter NAO skill due to ensemble subsampling w.r.t. a statistical estimate of the NAO index entails an improved prediction of the surface climate variables as well. Here, we show that a refined subselection procedure that accounts both for the NAO index and for the three additional modes of sea level pressure variability, is able to further increase the prediction skill of the operational seasonal forecast model of the German Meteorological Service GCFS of wintertime mean sea level pressure, near-surface temperature and precipitation across Europe.     

 
Modelling the dispersion of a passive tracer from a continuous poit source in a steady thermally-driven slope wind
Authors: Farina Sofia , Zardi Dino , Bisignano Andrea
Published: June 2022

Thermally-driven slope winds regularly occur over simple inclines and mountain valley sidewalls under clear-sky, calm-wind synoptic situations. As typical features of mountainous terrains these flows contribute to the transport of momentum, heat, and mass, including pollutants and other passive tracers.

A simple model for the dispersion of a passive tracer in a thermally driven wind over a slope is presented. The source of the tracer is pointwise and the emission continuous. Dispersion results from the combination of along-slope advection by a pure anabatic/katabatic flow and slope-normal turbulent diffusion. The mean wind is modeled following Prandtl’s (1942) steady state solution assuming a K-closure for momentum and heat fluxes, where the eddy viscosity and diffusivity are constant. The advection-diffusion equation for the passive tracer is solved with a constant eddy diffusivity as well. Results are compared with those that are obtained neglecting the dynamical structure of the wind, i. e.  adopting a classical Gaussian model with uniform wind velocity. A sensitivity analysis of resulting concentrations on the height of the source above ground and on the wind strenght is proposed. Two different regimes are identified, depending on the relative position of the source and the velocity maximum. Moreover, mathematical relationships between the position and the intensity of the ground concentration field, and their dependence on environmental parameters are outlined.

Reference

Prandtl L. 1942. Führer durch die Strömungslehre, Chapter 5. Vieweg und Sohn: Braunschweig, Germany. [English translation: Prandtl L. 1952. Mountain and valley winds in stratified air, in Essentials of Fluid Dynamics: 422–425. Hafner Publishing Company: New York, NY]

 
PERUN/Reanalys – the high resolution reanalysis for central Europe driven by ERA 5
Authors: Pokorna Lucie , Sokol Zbynek , Belda Michal , Brozkova Radmila , Trojakova Alena , Bobotova Gabriela
Published: June 2022

PERUN/Reanalysis (PERRea) is a product based on the ALADIN system, which shares its model code with the global NWP systems ARPEGE/IFS. It is the first step towards the regional climate simulations within the CMIP6 framework.   

PERRea is being calculated for the period 1989–2019 on the domain covering Central Europe and its surroundings, with the horizontal mesh size 2.3km and 87 vertical levels. It provides not only the consistent 3D information about regional weather and climate on hourly footing, but its verification against the measurements and the driving ERA5 reanalysis quantifies accuracy of underlying ALADIN configuration, intended for simulations of future climate.

In order to guarantee reliable operation at convection permitting scales, PERRea employs ALADIN non-hydrostatic dynamical kernel combined with the so-called ALARO-1 physics. Its main highlights are: 1) self-switching-off convection parameterization with microphysical calculations sandwiched between updraft and downdraft computation, seeing joint output from subgrid and resolved condensation, 2) turbulence scheme incorporating the moist effects and using two prognostic energies, and 3) broadband radiation scheme enabling full cloud-radiation interaction. As for data assimilation component, PERRea analyses the soil properties using the optimal interpolation of SYNOP screen level temperature and humidity measurements. The upper air analysis combines the large scales from driving ERA5 reanalysis with the small scales from the previous high-resolution short range forecast. Their optimal combination is ensured via digital filter blending technique.

In this contribution, comparison of the PERRea with different reference datasets is presented for the period 1990–1999 over the full domain. Daily, monthly and seasonal precipitation, 2m temperature, 10m wind speed and surface solar radiation were selected for the comparison. Validation sets include ERA5 (the driving reanalysis of PERRea), station data from ECA&D dataset and E-OBS v23.0 (gridded station data over Europe) in 0.1° resolution.

The preliminary results show generally good agreement between PERRea and the two reference datasets, ERA5 and E-OBS. A weak systematic overestimation of precipitation in PERRea in selected regions with respect to ERA5 may indicate a difficulties in simulation of dry spells. The comparison of 2m temperature in PERRea against E-OBS shows insufficient diurnal amplitude especially in summer; whilst maximum daily temperature is underestimated in Central Europe, the minimum temperature is overestimated by more than 3 °C.

This research is supported by the Technology Agency of the Czech Republic Czech Technology Agency, under the SS02030040 project.
Transdisciplinary, interdisciplinary, and interinstitutional work as the building blocks for effective service delivery
Authors: Saulo Celeste
Published: June 2022

Service delivery is at the heart of our mission as National Meteorological Services (NMS) and one of my main concerns since I became the Director of Argentina's NMS. Meeting societal needs under an everchanging context and limited resources demands partnerships and collaborations. My former career as a researcher at the University of Buenos Aires allowed me to build bridges between the operational and the academic sectors, which historically have had barriers to setting up constructive teamwork. Developing a common language, understanding different expectations, and respecting diversity has been critical to establishing effective collaborations towards achieving goals that could not be undertaken by the operational or the academic communities in isolation. In particular, I will focus on the impact of our relatively new Meteorology and Society department. This unit co-led the development of a new early warning system, our first fully co-designed product, with the participation of decision-makers, social and natural scientists, and an international private company.
The Needs of Re-users of Authoritative Hydromet Warnings - Lessons Learned from Meteoalarm
Authors: Kaltenberger Rainer
Published: June 2022

EUMETNET Meteoalarm acts as a one-stop-shop for bringing together in one place the authoritative hydromet warnings of 37 National Meteorological and Hydrological Services (NMHSs) in Europe. Global enterprises such as Google, Apple, IBM/The Weather Channel and AccuWeather, who aim to provide a high-quality information service to their users, ingest warnings from European NMHSs, which have been submitted to Meteoalarm via the XML-based Common Alerting Protocol (CAP) format and the Meteoalarm CAP Profile, into their systems. This allows the warning products and services of the relevant NMHSs to reach hundreds of millions end-users 24/7, helping to contribute to public safety in Europe and to offer a seamless transboundary warning service to citizens. Well known products and services of these companies include the standard weather apps for Android and iPhone, weather widgets for Windows 10 and 11 and many others. The engagement of these major re-users allows NMHSs to successfully bridge the often-quoted "last mile" delivery to end-users, which NMHSs by themselves can struggle to achieve. Based on a recent workshop, a survey, and more than ten years of hand-on experience in cooperating with these and other partners, this contribution will give an overview of the needs of re-users in the private sector, both technically and content-wise, with respect to hydromet warnings and connected meta-data. Finally the presentation will discuss future possibilities in deepening cooperation between the public and private sectors, including possible ways and means through which this successful cooperation could, based on user-profiling at the re-users side, in future potentially lead to tailor-made and user-specific impact warnings.
Meteorological cooperation in Ibero-America. Lessons learned and challenges
Authors: Tamayo Jorge
Published: June 2022

Cooperation between the NMHSs of the Ibero-American Community has been carried out since 2003 through the Conference of Directors of Ibero-American NMHSs (CIMHET), which develops, by means of the Ibero-American Meteorological Cooperation Program (PCMI), several action plans approved at its annual meetings on three strategic lines: Institutional strengthening and resource mobilization, provision of meteorological, climatic and hydrological services and training. During these years, different activities have been carried out within the strategic lines indicated.

The experience accumulated during all these years shows several important factors for the success of the different projects carried out, among others that all priorities and activities have been approved within the framework of the annual meetings of the CIMHET, the intense horizontal cooperation among NMHSs, the adoption of common positions and coordinated actions in regional and global forums, the great involvement of WMO, with active participation in the meetings of the Conference and development of activities, the promotion of dialogue with users, so that many of the activities planned in the Program are focused on contributing to the socio-economic development of the countries, or also the coordination with other Ibero-American networks, like CODIA and RIOCC, with proposal for common projects, which makes it easier to access financing mechanisms.

The main problems to achieve the stated goals include the lack of personnel in the NMHS, both technical to carry out their objectives and managerial to propose and implement development projects, the lack of continuity in the implementation of the projects, especially due to the change in management levels, the lack of political relevance and institutional representation of many NMHSs or the lack of sustainability of some of the systems implemented as a result of the lack of human and budgetary resources.

As challenges to be addressed to ensure a better use of the cooperation and projects developed, it is worth highlighting the increase in coordination between the different cooperation initiatives in the region, designing projects with other sectoral networks, having teams that allow monitoring the projects and carrying out the necessary actions for their implementation and ensuring their sustainability, increase the presence of NMHSs in national climate change policies, increase visibility in financing institutions and contribute significantly to the development of the Ibero-American Environmental Agenda approved by the Summit of Heads of State and Government of the Ibero-American Community.
How EUMETSAT connects communities to deliver products and services seamlessly
Authors: Evans Phil , Counet Paul
Published: June 2022

Increasing society’s resilience to high-impact natural events and climate change requires coordinated research and new investments in earth observation and prediction. EUMETSAT (The European Organisation for the Exploitation of Meteorological Satellites), together with its international partners provides the backbone of the global meteorological space based observing system.

In the next five years, EUMETSAT will launch the new generation of its main geostationary and polar systems as well as several new missions of the Copernicus Programme on behalf of the European Union, meeting the requirements for a vast set of applications, including global and regional numerical weather prediction, nowcasting, atmospheric composition and ocean monitoring as well as climate.

Those systems will bring an unprecedented observational capacity benefiting the full weather/climate value chain. We would present an overview of the main applications to key sectors, ranging from nowcasting to long term climate record and CO2 monitoring. 

In the near future, additional polar missions could complement the mandatory programs with specific focus on wind measurements and microwave soundings. Socio-economic impact assessment could be presented as a guidance for future studies and programmes.

With the objective to get these new observations made available as widely as possible, and to generate maximum impact on economies and societies, EUMETSAT is also embarked in the development of a set of innovative big data services, making use of latest IT, AI and ML technologies. These efforts are developed in close coordination with European National Meteorological Services, EUMETNET and ECMWF.
A new quality Control procedure for ECA&D
Authors: Stepanek Petr , Van der Schrier Gerard , Zahradníček Pavel
Published: June 2022

The ECA&D data-set collects over  81000 series of observations for the Essential Climate Variables more than 22400 stations from all countries in Europe.  Large number of these series are affected by outliers, repeated values and other issues in the measurements. These quality issues need to be identified  prior to further processing of the data into e.g. the production of the gridded E-OBS datasets as  these issues may lead to erroneous estimates of climate impact indices and trends. In the context of the  Copernicus contract C3S2_311 Lot3, the MetQC method developed at GCRI has been implemented for operational use at ECA&D. This new method combines checks on  duplicate series, repetitive values and outliers with an inter-stations comparison.  Earlier work compared five different quality check methods (MetQC, MASH, ACMANT, NOAA, C3QC) on four benchmark data-sets covered by ECA&D. This work indicated  that the MetQC approach performed well in comparison against the  other methods and the new method replaces the more primitive approach at ECA&D in which straightforward stand-alone tests were conducted.  A strong aspect of the MetQC method is that it provides an estimate for  an alternative value of a suspect value based on values of surrounding stations, with a quantification of the reliability of this alternative.  The MetQC method has been further refined and tailored to the application at ECA&D to be capable of handling the vast dataset in a reasonable time.  The presentation will focus on the improvement in quality for ECA&D and comparisons in terms of numbers of flagged data and given between the new approach and the approach it replaces.