bluuebunny/crossref_metadata_2025 huggingface dataset:
Intraseasonal modulation of Sudden Stratospheric Warmings by ENSO
Authors: Palmeiro Froila M. , García-Serrano Javier , Ruggieri Paolo , Batté Lauriane , Gualdi Silvio
Published: June 2021

Using the complete ERA-Interim reanalysis and three state-of-the-art models, this study explores how El Niño-Southern Oscillation (ENSO) can influence the frequency and seasonal cycle of sudden stratospheric warmings (SSWs) by modulating the background upward wave propagation. Reanalysis data shows that in the last four decades, winters with SSWs were significantly more common than inactive winters, particularly under La Niña (LN) conditions but not during El Niño (EN), regardless of the ENSO/SSW definitions considered herein. In agreement with previous studies, our models tend to simulate a linear ENSO-SSW relationship, with more SSWs for EN, that show a peak of occurrence around January — as occurs in reanalysis —, and less SSWs for LN when compared to neutral conditions. Independently of ENSO, the main tropospheric precursor of SSWs appears to be an anomalous wave-like pattern over Eurasia, but it is dominated by wavenumber 1 (WN1) for EN and shows an enhanced wavenumber 2 (WN2) for LN. The differences in this Eurasian wave pattern, which is largely internally generated (ENSO-unforced), emerge from the distinct configuration of the background, stationary wave pattern induced by ENSO, favouring a relative stronger WN1 (WN2) component during EN (LN). Our results suggest that the ENSO-forced signal relies on preconditioning the seasonal-mean polar vortex, becoming weaker and displaced (stronger and more stable) for EN (LN), while ENSO-unforced wave activity represents the ultimate trigger of SSWs. This supports the view that ENSO and SSWs are different sources of variability of the winter atmospheric circulation and may reconcile previous findings in this context.
Introduction of a simple formula for estimating approximate intensity-duration-frequency curves from daily rain gauge data
Authors: Benestad Rasmus , Lutz Julia , Verpe Dyrrdal Anita , Haugen Jan Erik , Parding Kajsa M. , Dobler Andreas
Published: June 2021

A simple formula for estimating approximate values of return levels for sub-daily rainfall is presented. It was derived from a combination of simple mathematical principles, approximations and fitted to 10-year return levels taken from intensity-duration-frequency (IDF) curves representing 14 sites in Oslo. The formula has subsequently been evaluated against IDF curves from independent sites elsewhere in Norway. Since it only needs 24 h rain gauge data as input, it can provide approximate estimates for the IDF curves used to describe sub-daily rainfall return levels. In this respect, it can be considered as a means of downscaling regarding the timescale, given an approximate power-law dependency between temporal scales. One clear benefit of this framework is that observational data is far more abundant for 24 hr rain gauge records than for sub-daily measurements. Furthermore, it does not assume stationarity and is well-suited for projecting IDF curves for a future climate. This method also provides a framework that strengthens the connection between climatology and meteorology to hydrology, and can be applied to risk management in terms of flash flooding. The proposed formula can also serve as a 'yardstick' to study how different meteorological phenomena with different timescales influence the local precipitation, such as convection, weather fronts, cyclones, atmospheric rivers, or orographic rainfall. An interesting question is whether the slopes of the IDF curves change as a consequence of climate change and if it is possible to predict how they change. One way to address this question is to apply the framework to simulations by convective-permitting regional climate models that offer a complete representation of both sub-daily and daily precipitation over time and space. 
Synthetically generated low-pressure systems to support studies of sea level extremes
Authors: Rantanen Mika , Särkkä Jani , Räihä Jani , Kämäräinen Matti , Jylhä Kirsti
Published: June 2021

Extremely high sea levels on the Finnish coast are typically caused by close passages of extratropical cyclones (ETCs), which raise the sea level with their associated extreme winds and lower air pressure. For coastal infrastructure, such as nuclear power plants, it is crucial to study physically possible sea level heights associated with ETCs. Such sea levels are not straightforward to determine from observational datasets only, because tide gauge records  cover about 100 years and do not necessarily capture the most extreme cases having return periods longer than 100 years.

In this study, a method for generating an ensemble of synthetic low-pressure systems is being developed to investigate the extreme sea level heights on the Finnish coast of Baltic sea. As input parameters for the method, the point of origin, velocity of the center of the cyclone and depth of the pressure anomaly need to be given. Based on the input parameters, the method forms an idealized low-pressure system using a two-dimensional Gaussian function. In order to find extreme, but still reasonable values for the input parameters, cyclone tracks from ERA5 reanalysis data will be analysed.

The ensemble of synthetic low pressure systems (i.e. the wind and pressure data) is used as an input to a numerical sea level model. As a result, we have an ensemble of simulated sea levels, from which we can determine the properties of the ETCs that induce the highest sea levels on a given location on the coast. The preliminary simulation results show that this method works well, forming a basis for studies on extreme sea levels. 

 
The new Italian regional reanalysis SPHERA: benefits of the convection-permitting resolution in detecting severe-weather events
Authors: Giordani Antonio , Cerenzia Ines , Paccagnella Tiziana , Di Sabatino Silvana
Published: June 2021

In recent years the interest towards the development of limited-area atmospheric reanalysis datasets has been growing more and more. Regional reanalyses in fact, as a consequence of the restricted domain that they cover, provide a data distribution displaced on a much finer grid compared to a coarser global dataset. This permits to better resolve those patterns related to rapid and high-impact weather events, first and foremost convection. Furthermore, with a finer horizontal resolution, a consistent increase in the level of detail in the description of the orography is also gained, that is a crucial point to achieve especially in a very complex territory such as Italy. This study presents the first application of the novel regional reanalysis dataset developed at ARPAE-SIMC: the High rEsolution ReAnalysis over Italy (SPHERA). SPHERA is a high-resolution convection-permitting reanalysis over the Italian domain and the surrounding seas covering 25 years, from 1995 to 2020, at hourly temporal frequency. SPHERA is based on the non-hydrostatic limited-area model COSMO, and produced by a dynamical downscaling of the global reanalysis ERA5, developed at ECMWF. A nudging data assimilation scheme is applied in order to steer the model outcomes towards the surface and upper-air observations. All the available conventional observations have been used.

The added value of SPHERA in representing severe-weather and convective events is evident from its preliminar validation, which was performed on the multidecadal period against various datasets of surface observations, joined with the comparison against the global reanalysis ERA5. In fact, a clear advantage of SPHERA on its driver ERA5 is found for the detection of events with moderate to intense daily and sub-daily rainfalls, which are characterized by a strong seasonal and geographical component, that is further investigated. We report also the preliminary sensitivity analysis on the dimension of the box used to operate the upscaling for the validation of SPHERA, a process necessary to reduce the errors caused by geographical mismatches between observed and simulated events localizations, which are particularly frequent in case of strongly-localized and rapid processes. Furthermore, in order to give a quantitative evaluation of the performance of the new reanalysis in particular conditions, the results of the simulations for specific case studies involving the occurrence of severe-precipitation events in recent years was performed, focusing on events having different dynamical genesis, but interrelated by the important damages they caused. From this analysis, for which also a comparison with other regional reanalyses is performed, the advantage of SPHERA in representing the most intense rainfall occurrences, in terms of location, intensity and timing, clearly emerges.
Regional winds over the Iberian Peninsula with COSMO-REA6 high resolution regional reanalysis: cierzo, levante and poniente
Authors: Ortega María , Sánchez Enrique , Gutiérrez Claudia , Molina María Ofelia
Published: June 2021

Regional winds are caused by small-scale pressure differences in a way that important air flows can arise in a very small and specific region. Sometimes an orographic feature, such as a channel like the Ebro Valley or the Strait of Gibraltar, lead the wind, due to mass conservation, to acquire a certain specific range of directions and considerable speed. In the regions where they are observed, the wind is of great importance not only for the climatology and meteorology of these areas but also for their culture and identity. However, it is difficult to analyze them using the most common reanalysis products, since their spatial resolutions are not high enough to properly describe the orographic characteristics that lead to the regional winds in specific locations. Here, we will explore the application of the COSMO-REA6 high resolution reanalysis system for the assessment of the main regional winds in the Iberian Peninsula: the cierzo wind in the Ebro Valley and the levante and poniente winds in the Strait of Gibraltar, for the 2000-2018 period. COSMO-REA6 uses a spatial resolution of 6 km (0.055º), which is much larger than previous reanalysis and regional modelling databases, so it can better capture the orography of the areas and therefore the regional winds we intend to study. The cierzo, levante and poniente winds are very relevant in the Iberian Peninsula due to their intensity and their frequency. Defined with a 5 m/s threshold for each hour, and their specific direction range, around 95, 150 and 110 wind days per year are obtained, respectively. Their study may also be important for other reasons, such as the production of renewable energy in these areas. First, we conduct a preliminary assessment of wind speed and direction with hourly data from weather stations, which have been obtained from the HadISD global sub-daily dataset. Then, we compare data from stations with COSMO-REA6 reanalysis in each location and produce a spatial description of the reanalysis in the Peninsula. We also study the atmospheric patterns associated with the regional winds characterized above. Due to the few studies that have been carried out on regional winds in the Iberian Peninsula, these results can be of great interest for various fields, such as meteorology, climatology and the generation of renewable energy.
Future Projections of heat and cold stress based on two RCP Scenarios over Greece
Authors: Politi Nadia , Vlachogiannis Diamando , Sfetsos Athanasios , Markantonis Iason
Published: June 2021

Climate change will exert a considerable influence across the area of Greece with temperature and precipitation extreme events becoming more frequent creating significant impacts on many societal and economic sectors. Future projections based on a range of anthropogenic scenarios show that decreases of annual rainfall amounts associated with increases of heat-waves and droughts are anticipated in several regions of Greece. Τhe Weather Research and Forecasting (WRF) model has appropriately been set-up and parameterized with a high spatial resolution of 5 km for the area of Greece. Previous research has revealed the capability of the configured WRF high resolution model to reproduce the main climatological variables in this region, which is dominated by highly variable topographic characteristics. The scope of this study is to investigate climate change projections for indices that express human‐perceived temperature extremes such as the Humidity index (Humidex), Wind Chill index (WCI) and Heat stress index (HI) in order to evaluate the potential impact on human health. These indices use different meteorological variables or a combination of them such as temperature, relative humidity and wind speed. The computation of these indices is based on daily simulated data, under two different scenarios (RCP4.5 and RCP 8.5) and periods (2025-2049 and 2075-2099) compared to present climate conditions (1980-2004). Downscaled results are derived from the global EC-EARTH model dataset, used for initial and boundary conditions. Our findings contribute to the quantification of future changes as well as on the identification of potential areas that might become prone to different degrees of heat/cold stress over the area of Greece.
AI for short term forecasts (nowcasting) at DWD, status and perspectives.
Authors: Müller Richard
Published: June 2021

Artificial Intelligence (AI) is nowadays a central key for the improvement of methods in many modern applications and research areas, e.g. autonomous driving, image / face recognition as well as system simulation and optimization. The AI success stories are increasing quite rapidly. However, AI is still largely underrepresented in weather services.

DWD was among the first European weather services who used modern AI methods within the scope of short term weather forecast. The respective research activities and applications are currently performed in close cooperation with the University of Saarbrücken and Mainz as well as the German Aerospace Center, whereby DWD acts mainly on implementation and steering of the research. Further, on an international level, DWD agreed recently on a closer cooperation with the new AI section of the South-Korean Meteorological Agency as well.

This presentation will provide an overview about the AI applications at DWD covering the following topics:

- The application of computer vision for the short term forecasting (nowcasting) of radiation, fronts, thunderstorms and precipitation based on satellite data.

- The development and application of machine learning for the early detection of thunderstorms as well as for the improvement of short term forecasts of mature Cbs.

- The operational usage of neuronal networks for the detection of volcanic ash (satellite data).

- AI concepts for a seamless integrated forecasting system.

However, AI, in particular machine learning, is also linked with handicaps. Thus the pros and cons of AI, will be discussed in comparison to classical methods. Within this scope, recent validation results will be considered as well.

 
Road siting effect metrological evaluation on near-surface air temperatures
Authors: Coppa Graziano , Quarello Annarosa , Steeneveld Gert-Jan , Jandric Nebojsa , Merlone Andrea
Published: June 2021

With the purpose of revising World Meteorological Organization’s Commission for Instruments and Methods of Observation (WMO/CIMO) Guide #8 on weather stations siting, and in the framework of EMPIR project ENV58 MeteoMet 2, an experiment to evaluate metrologically the maximum influence of a paved road on 2-m air temperature measurements (“road siting effect”) has been designed, installed and run in Italy. It consists of a 100-m long array of seven measurement stations, at increasing distances from a local road, equipped with shielded Pt100 thermometers and ancillary sensors (hygrometers, anemometers, solar radiation meters). Data coming from 1 year of observations, has been analysed for daily climatological metrics, finding that the road mostly effects minimum temperatures, with average values of ~ 0.30±0.18 °C at a distance of 1 m; then, in order to quantify the instrumental effect on the measurement, data was filtered by applying a Generalized Additive Model, selecting only times when the effect is more intense (during nights, in presence of low winds coming from the road), and the road siting effect has been calculated by modelling the maximum temperature differences by using Extreme Values Analysis. The 1-year return value on 10-min measurements is 1.22±0.30 °C at 1 m from the road, with a gradual decline (~ 0.1 °C/m), while an extrapolation to 100-year return level gives a value of 1.71±0.79 °C. Analysis also show the possibility of calculating an asymptotic upper limit to these values, providing there are enough data to lower the associated uncertainties. These results, published in the International Journal of Climatology (Coppa et al 2021, https://doi.org/10.1002/joc.7044) is a first step towards a redefinition of the weather station classification scheme of WMO/CIMO Guide #8, together with building and tree effects experiments which have been run in parallel with the road siting experiment here presented and which will be presented elsewhere. Raw data is also available at Zenodo.org (Coppa et al 2020, https://doi.org/10.5281/ZENODO.4300299)
Internal boundary layer development over lake surface in case of very young waves
Authors: Lükő Gabriella , Torma Péter , Weidinger Tamás , Krámer Tamás , Vecenaj Zeljko , Grisogono Branko , Lázár István
Published: June 2021

An internal boundary layer (IBL) may develop above lakes due to surface roughness change. The water surface has significantly less resistance to wind flow compared to the aerodynamically rough land surface. As a result, the wind speed increases along the fetch in the IBL over the lake surface. Consequently, the wind shear stress, which is the main driving force of waves and currents in lakes, also varies along the fetch. Measurements were carried out for six weeks in 2018 within a Croatian-Hungarian observational campaign in Lake Balaton in order to explore the IBL characteristics and establish a simple but reliable IBL model that can reproduce wind shear stress variability over the lake. One wind measurement station was installed on land and three over the lake along the fetch of the prevailing wind direction. On the landside, the wind profile was observed by a sodar from which characteristic land surface roughness lengths were derived by logarithmic profile fitting. On the waterside, momentum fluxes were measured with eddy-covariance (EC) technique at fetches of ~0.1, ~3.5, and ~6 km. To describe the water surface roughness dynamics, waves were simultaneously recorded with an underwater acoustic surface tracking at the middle station. An analytic IBL model is fitted to the measured wind speed and stress data employing wind speed classes. In the model, the wind stress development is dynamically coupled with the wave state by a wave age dependent roughness length function which is valid for highly fetch limited conditions and very young wave ages of ~2-15. The model is able to quantitatively reproduce wind speed, wind stress, and wave state development over the lake surface based on land observation of wind speed if the land roughness length is also known. Based on our model and measurements, we found a considerable spatial variability of momentum flux due to the change of wave state and wind speed along the fetch. The variation of momentum flux also influences the evolving sensible heat flux, which was also compared to the EC measurements.
Evaluation of the the wind farm wake parametrization with large-eddy simulations of wakes in WRF
Authors: Peña Alfredo , Mirocha Jeffrey
Published: June 2021

Mesoscale models, such as the Weather Research and Forecasting (WRF) model, are now commonly used to predict wind resources, and in recent years their outputs are being used as inputs to wake models for the prediction of the production of wind farms. Also, wind farm parametrizations have been implemented in the mesoscale models but their accuracy to reproduce wind speeds and turbulent kinetic energy fields within and around wind farms is yet unknown. This is partly because they have been evaluated against wind farm power measurements directly and, generally, a lack of high-quality observations of the wind field around large wind farms. Here, we evaluate the in-built wind farm parametrization of the WRF model, the so-called Fitch scheme that works together with the MYNN2 planetary boundary layer (PBL) scheme against large-eddy simulations (LES) of wakes using a generalized actuator disk model, which was also implemented within the same WRF version. After setting both types of simulations as similar as possible so that the inflow conditions are nearly identical, preliminary results show that the velocity deficits can differ up to 50% within the same area (determined by the resolution of the mesoscale run) where the turbine is placed. In contrast, within that same area, the turbine-generated TKE is nearly identical in both simulations. We also prepare an analysis of the sensitivity of the results to the inflow wind conditions, horizontal grid resolution of both the LES and the PBL run, number of turbines within the mesoscale grid cells, surface roughness, inversion strength, and boundary-layer height.
New digital formats for communicating CO2 savings potential for Germany
Authors: Blome Tanja , Dold Christian , El Zohbi Juliane , Goerl Knut , Koehnke Fiona , Preuschmann Swantje , Steuri Bettina , Sun Jianing , Rechid Diana , Schultz Martin , Jacob Daniela
Published: June 2021

Human-induced climate change is one of the most pressing challenges of our time. The Helmholtz Association is making essential contributions to curbing the causes of climate change and finding ways to adapt. With the Helmholtz Climate Initiative, research is concentrated on the two focal points, "reduction of net emissions" and "adaptation to climate impacts". In Net-Zero-2050, Cluster I of the Helmholtz Climate Initiative, strategies and ways to reduce carbon emissions are scientifically investigated and evaluated. Furthermore, two digital communication formats are being developed to comprehensively show the research's complex results. Firstly, the web-based National Net-Zero-2050 Atlas informs the user about different methods and technologies for CO2 reduction and possible reduction paths. Secondly, the Soil Carbon App enables actors of the agricultural sector to assess climate mitigation potentials that arise from using different land management methods. A land surface model is used to simulate future scenarios presented in the app via cloud-based, model-driven workflows.

Both formats aim to support users in making decisions and developing strategies. The work on the products follows the principles of comprehensibility, transparency and appropriate information presentation. During the work on the products, we identified challenges such as:

How to deal with multi-dimensional data sets and uncertainties?

How to present scientific results in a user-friendly manner for varied target groups?

How to guide the users of varied target groups through the communication formats?

With the aid of a critical internal reflection, approaches to overcome these challenges were developed and applied. For example, the atlas introduces different complexity levels to enable users to gain understanding, despite very diverse backgrounds, prior knowledge and information needs. The app, for its part, offers two main sectors that address the users’ different demands and prior knowledge: (1) it features options to choose from the data and subsequently delivers graphical analyses, and (2) it provides respective interpretation, texts, and web links.

The article presents the two dissemination products as well as the challenges and solutions from the development work.
Causal relationships between particulate matter and COVID-19 cases in USA cities
Authors: Kamigauti Leonardo Yoshiaki , Martins Palma Perez Gabriel , Andrade Maria de Fatima
Published: June 2021

Recent studies have shown that increased outdoor concentrations of particulate matter (PM) enhances the transmission of the novel Coronavirus (COVID-19). Although the viability of this causal relationship has been established indoors, outdoor correlations are contested based on potential confounding effects, such as urban mobility. Testing the hypothesis of PM-assisted airborne viral transmission is important to support the decision-making process and mitigation of future airborne epidemics. In a recent study we have shown that Granger causality analysis supports a causal relationship between outdoor PM concentrations and COVID-19 new cases. In this study, we aim to further explore this causal link by considering urban mobility as a common driver and a mediator in a set of causal networks based on lagged multivariate linear regressions. Causal networks are graphical models designed to help distinguishing and quantifying correlation and causation relationships. We quantify the strength at which PM increases COVID-19 new cases directly and the strength of urban mobility as a driver of both PM and COVID-19 new cases. We also quantify the effect of COVID-19 new cases in urban mobility that causes the PM concentration. We employ a dataset of daily air quality measurements in 52 cities in the United States of America (USA) considering PM concentrations in two particle size ranges, smaller than 2.5 μm (PM2.5), and between 10 and 2.5 μm (PMC). PMC is related to soil dust resuspension in most cities. So, we used the PMC as an urban mobility proxy. We also employ carbon monoxide (CO) along with the Apple dataset of IPhone users mobility which shows the relative volume of satellite navigation requests by city in the USA.
Snow depth monitoring with GNSS reflectometry: Results from Antarctica and selected geodetic ground stations
Authors: Simeonov Tzvetan , Ramatschi Markus , Vey Sibylle , Wickert Jens
Published: June 2021

The permanent and seasonal snow covers are an important element of the global hydrological cycle and have substantial influence on global climate. Currently around 10% of the Earth’s land surface is covered by glaciers, ice caps and snow cover. Snow and ice cover play important role in the Earth’s climate by reflecting solar radiation and thus decreasing the average Earth temperature. Glaciers and ice caps participate in a positive feedback loop in the Earth’s climate. By contracting due to increasing temperatures, they reflect less solar radiation, further contributing to the global temperatures increase.

Using the single antenna ground-based GNSS Reflectometry (GNSS-R) method for snow depth estimation is an emerging application. A new technique for snow depth measurement using the phase changes in the observed SNR data, rather than the height estimates, is validated in a GNSS-R setup in Antarctic station Neumayer III. The new technique shows improved characteristics to the classical single antenna ground-based GNSS-R snow depth determination method. The validation is done in an environment of constant snow accumulation. The results from new technique show high correlation of the de-trended datasets between the GNSS-R and in-situ snow buoy measurements of 0.85. The de-trended classical height estimations of the SNR show lower correlation to the snow buoys of 0.60.

A screening of the International GNSS Service (IGS) global network shows, that snow depth observations are possible in only 7 of the 506 available stations. The main limitations on the stations are the local topography and climate. The snow depth observations from these seven stations are compared with the ERA5 snow depth estimations, local measurements and climate normals. The analysis of the data for station Visby, following the new GNSS-R analysis technique, shows very high correlation of 0.91 and low RMSE of 2.26cm, while the classical GNSS-R estimation has RMSE of 2.48cm and ERA5 shows RMSE of 4.2cm when compared to local meteorological observations.
An Investigation of cold-wet Compound Events in Greece
Authors: Markantonis Iason , Vlachogiannis Diamando , Sfetsos Thanasis , Kioutsioukis Ioannis , Politi Nadia
Published: June 2021

Climate change is set to affect extreme climate and meteorological events. The combination of interacting physical processes (climate drivers) across various spatial and temporal scales resulting to an extreme event is referred to as compound event. So far, climate change impacts on compound events in Greece such as daily cold-wet events have not been explored. The complex geography and topography of Greece forms a variety of regions with different local climate and a great range in daily minimum temperature and precipitation distributions. This leads to the assumption that there we will also observe a variety in the distribution of cold-wet events depending on the region. Aim of our study in this work is first to identify the cold-wet events based on observational data and then to examine the predictive capability of regional different climate models and ERA-Interim against observations from the Hellenic National Meteorological Service (HNMS) stations for the occurrence of cold-wet compound events in the present climate. The study will focus on the colder and wetter period of the year (November-April) to determine the extremes for this period. Specifically, the datasets employed are from two EURO-CORDEX Regional Climate Models (RCMs) with 0.11° horizontal resolution and validated ERA-Interim Reanalysis downscaled with the Weather Research and Forecasting (WRF) model at 5km horizontal resolution, for the historical period 1980-2004. In particular, the RCM datasets analyses have been produced from SMHI-RCA4 driven by MPI-M-MPI-ESM-LR Global Climate Model (GCM) and CLMcom-CLM-CCLM4-8-17 driven by MOHC-HadGEM2-ES GCM. After the comparison with the observations, the gridded data from the models will give us the ability to observe the spatial distribution of the compound events.
Managed infrastructure and services to empower meteorological services in developing countries
Authors: Smith Tom
Published: June 2021

Often in developing countries the spatial coverage with surface weather observations is sparse and the reliability of existing systems is lower than in other parts of the world. These gaps in the availability of observation data have significant negative consequences, locally and globally. For decades international funds have been used to acquire meteorological infrastructure with little to no focus on life-cycle management. Furthermore, improvements in one part of the value chain are often not connected with further downstream services meaning local benefits are generated with substantial delay, if at all.

DTN is one of the few organizations offering comprehensive solutions across the value chain from deployment and operation of observation systems through to weather analytics creating valuable insights for business, consumers and governments across the globe. DTN not only project manages the setup of weather observation systems but also maintains and operates measurement networks on different continents. The sensor agnostic approach enables us to offer the right sensor solution for each situation.

We see an opportunity to correct the mistakes of the past, changing the focus from acquiring observation systems to life cycle management to ensure the systems are maintained and leveraged effectively to provide forecasts and warnings for protection of life and property and enabling NMSs to focus on fulfilling their mission.

Funding organizations such as the World Bank must change the focus from hardware procurement to a performance-based PPE/P model that ensures the value of investments in infrastructure are realized. This sustainable approach will; ensure long lasting partnerships, harness the innovation in the private sector, create local jobs maintaining infrastructure and enable economic development through improved ability to manage the impact of weather and climate events.
Characterization of the morning transition from downslope to upslope winds and its connection with the nocturnal inversion breakup at the foot of a gentle slope.
Authors: Farina Sofia , Barbano Francesco , Di Sabatino Silvana , Marchio Mattia , Zardi Dino
Published: June 2021

Thermally driven winds observed in complex terrain are characterized by a daily cycle dominated by two main phases: a diurnal phase in which winds blow upslope (anabatic), and a nocturnal one in which they revert their direction and blow downslope (katabatic). This alternating pattern also implies two transition phases, following sunrise and sunset respectively. 

Here we study the upslope component of the slope wind with a focus on the morning transition from the katabatic to the anabatic flow based on data from the MATERHORN experiment, performed in Salt Lake Desert (Utah) between Fall 2012 and Spring 2013 (Fernando et al, 2015). 

First of all, a criterion for the selection of purely thermally driven slope wind days is proposed and adopted to select five case studies, taken from both the spring and the autumn periods. Then, the analysis allowed the investigation of the driving mechanisms through the connection with the patterns of erosion of the nocturnal inversion in the valley bed at the foot of the slope under analysis. Three main patterns of erosion of the inversion in the particular topography of a gentle and isolated slope are identified: a) erosion due to upward growth of a convective boundary layer, b) erosion due to descent of the inversion top, and c) erosion due to a mix of the two previous mechanisms. The three patterns are then linked to the initiation of the transition by two different and competing mechanisms: mixing from above (top-down dilution) and surface heating from below. Finally, an analytical model for the description of slope circulation (Zardi and Serafin, 2015) has been used to diagnose the time of the transition.

Zardi, D. and S. Serafin, 2015: An analytic solution for daily-periodic thermally-driven slope flow. Quart. J. Roy. Meteor. Soc., 141, 1968–1974. 

Fernando, H. J. S., Pardyjak, E. R., Di Sabatino, S., Chow, F. K., De Wekker, S. F. J., Hoch, S. W, Zsedrovits, T., 2015, The MATERHORN: Unraveling the intricacies of mountain weather. Bulletin Of The American Meteorological Society, 96, 1945-1967. 
Explaining recent trends in extreme precipitation in the Southwestern Alps by changes in atmospheric influences
Authors: Blanchet Juliette , Blanc Antoine , Creutin Jean-Dominique
Published: June 2021

We analyze recent trends in extreme daily precipitation in the Southwestern Alps. We consider a high-resolution precipitation dataset of 1 x1 km2 for the period 1958-2017. A robust method of trend estimation is considered, based on nonstationary extreme value distribution and a homogeneous neighborhood approach. The results show contrasting trends in extreme daily precipitation depending on the season. In autumn, the trends are significantly increasing in most of the Southwestern Greater Alpine Region, with an increase up to 100% the average maxima for the 20-year return level between 1958 and 2017, while the French Alps show mainly decreasing extremes. Knowing that autumn experiences most of the largest maxima, the increase in the Mediterranean area is of concern for risk protection.  In winter, the valleys and medium mountain areas surrounding the Northern French Alps show significant increasing extremes, while the inner French Alps, the Swiss Valais and the Aosta Valley show significant decreasing trends. In the other seasons, the significant trends are mostly negative in the Mediterranean area, while the French Alps show less organized and contrasting trends.  For all seasons, part of the significant changes in extremes can be related to changes in the dominant atmospheric influences generating the maxima, particularly in the Mediterranean influenced region that shows the most organized trends. In particular, the strong positive trends in autumn in Southern France are concomitant with an increase in Mediterranean influence generating the maxima. However some exceptions are notable with counter-intuitive trends in extremes given the trends in dominant influences. 
An upcoming European network of microwave radiometers for operational temperature profiling and humidity observations
Authors: Rüfenacht Rolf , Bircher-Ardot Simone , Pospichal Bernhard , Cimini Domenico , Knist Christine , Martinet Pauline , Orlandi Emiliano , Czekala Harald , Loehnert Ulrich , Sugier Jacqueline , Turp Myles , Haefele Alexander
Published: June 2021

From the perspective of numerical weather prediction and nowcasting, the atmospheric boundary layer (ABL) is one of the most undersampled regions of the atmosphere due to difficulties of spaceborne remote sensing at these altitudes. Ground-based microwave radiometers (MWR) have the potential to contribute to the closing of this gap. Indeed, commercial K- and V-band (20-60 GHz) radiometers provide observations of temperature profile, water vapour and liquid water and are most sensitive to the ABL due to their choice of spectral channels and observation geometry.
EUMETNET's E-PROFILE observation programme has thus evaluated the potential for a European network of ground-based microwave radiometers. The stakeholder needs were inferred from WMO and EUMETNET Statements of Guidance, OSCAR and a dedicated user survey. The maturity and effectivity of the technology was assessed through a literature review and experts judgements comprising recent large-scale campaigns, experiences with long-term usage and assimilation trials and outcomes of the recent COST action TOPROF. Last but not least, the availability of existing instrumentation from which a European network could be built up was investigated. 
Based on this study, EUMETNET decided to establish an operational MWR network by 2023 with continuous near real-time provision of brightness temperatures, humidity and temperature information from a centralised retrieval as well as forecast indices for fore- and nowcasting. The products will come along with different monitoring quality control stages at timescales from near real-time to monthly. Special care will be dedicated to ensure reliable absolute calibration results by accounting for the recent developments and recommendations from TOPROF. In the setting up and operation of the network as well as in the implementation of retrievals and monitoring, important synergies with the ACTRIS programme and the scientific community gathered in the COST action PROBE are expected.
The presentation will briefly outline the reasoning for setting up the network but mainly focusses on the operational aspects and services that E-PROFILE MWR will provide. Moreover, the first steps taken towards an operational network will be discussed and the general roadmap outlined.
Synoptic and local characteristics of severe wind episodes in the Basque Country.
Authors: Egaña Joseba , Gaztelumendi Santiago , Hernandez Roberto , Otxoa de Alda Kepa
Published: June 2021

Episodes of very strong winds can occur in the Basque Country for different reasons. On the one hand, in the winter season (October-April) due to deep depressions that move from west to east within the intense zonal circulation, often passing through the British Isles. In the summer season (May-September) strong winds may be due to severe storms or "galernas" (coastal trapped disturbances). The most relevant and widespread damage occurs in the cold season, usually due to deep depressions or other configurations that generate a strong local pressure gradient. In fact, the most damaging situations affecting the Basque Country during the 21st century are related to deep low passages considered as explosive cyclogenesis events, the Klaus and Xynthia episodes.

This work analyses some of the most relevant wind events during the 21st century, in terms of synoptic configuration and local behaviour, using reanalysis data and observations from the Automatic Meteorological Stations (AWS) network of the Basque Country.  The final objective is to identify and classify the common behaviour among high impact weather episodes, understanding the main synoptic features and drawing general conclusions on how synoptic features condition relevant aspects at lower scales, where complex orographic effects are relevant.

In the Basque Country area, most extreme episodes correspond to intense zonal circulations where deep depressions are generated, often explosive cyclogenesis. If we look at the surface configuration, the most frequent case is that of the British low, also secondary lows to the primary one, which is located around the British Isles. Wind events generated by depressions passing through the Bay of Biscay are also frequent. In general, these situations generate southerly wind events that can sometimes turn to the west. Other less frequent situations that can generate intense winds are Atlantic lows to the west of the Iberian Peninsula, which generate southerly winds, or situations of high pressure in the Atlantic with low pressure in Europe, sometimes in France, which generate intense winds from the north and northwest. Locally, due to the complex orography and the configuration of the valleys in the Basque Country, the wind is channelled in different ways, affecting different areas depending on the direction and strength of the wind.
Benefit of microwave radiometer and cloud radar observations for data assimilation and fog process studies during the SOFOG3D experiment
Authors: Martinet Pauline , Burnet Frédéric , Bell Alistair , Kremer Arthur , Letillois Matthias , Löhnert Ulrich , Antoine Salomé , Caumont Olivier , Cimini Domenico , Delanöe Julien , Hervo Maxime , Huet Thierry , Georgis Jean-François , Orlandi Emiliano , Price Jeremy , Raynaud Laure , Rottner Lucie , Seity Yann , Unger Vinciane
Published: June 2021

Fog forecasts still remain quite inaccurate due to the complexity, non linearities and fine scale of the main physical processes driving the fog lifecycle. Additionally to the complex modelling of fog processes, current numerical weather prediction models are known to suffer from a lack of operational observations in the atmospheric boundary layer and more generally during cloudy-sky conditions. Continuous observations of both thermodynamics and microphysics during the fog lifecycle are thus essential to develop future operational networks with the aim of validating current physical parameterizations and improving the model initial state through data assimilation techniques. In this context, an international network of 8 ground-based microwave radiometers (MWRs) has been deployed at a regional-scale on a 300 x 300 km domain during the SOFOG3D (SOuth FOGs 3D experiment for fog processes study) that has been conducted from October 2019 to April 2020. The MWR network has been extended with ceilometers at all MWR sites and additional microphysical observations from the 95 GHz cloud radar BASTA at two major sites as well as wind measurements from a Doppler lidar deployed at the super-site. After an overview of the SOFOG3D objectives and experimental set-up, preliminary results exploiting mainly the MWR network and cloud radar observations will be presented. Firstly, the capability of MWRs to provide temperature and humidity retrievals within fog and stratus clouds will be evaluated and discussed against radiosoundings launched during intensive observation periods (IOPs). Secondly, first retrievals of liquid water content profiles within fog and stratus clouds derived from the synergy between MWRs and the BASTA cloud radar will be presented. To that end, a one dimensional variational approach (1D-Var) directly assimilating MWR brightness temperatures and cloud-radar reflectivities has been developed. 1D-Var retrievals will be validated through a dataset of simulated observations and real fog cases of the SOFOG3D experiment. The capability of MWR and cloud radar observations to improve the initial state of the AROME model during fog conditions will be discussed with a focus on selected case studies. Finally, the usefulness of ground-based remote sensing networks to improve our understanding of fog processes and to validate physical parameterizations will be illustrated using the operational AROME model and the AROME Ensemble Prediction System
Using probabilistic forecasts to effectively enhance operational marine industry decision-making
Authors: Mylne Ken , Steele Edward , Brown Hannah , Bunney Christopher , Gill Philip , Saulter Andrew , Standen Jessica
Published: June 2021

Ensemble Prediction Systems (EPSs) are now run routinely by many global weather centres but, despite the enormous potential these forecasts offer, their perceived complexity has long presented a barrier to effective adoption by many users; limiting the opportunity for early decision-making by industry. To facilitate the interpretation of a set of (potentially seemingly contradictory) forecasts, a sensible approach is to turn the prediction into a binary (yes/no) forecast by applying a user-relevant operational weather limit – with the decision to proceed with or postpone an operation based on whether a certain proportion of the members predict un-/favourable conditions. However, the question then remains as to how the appropriate probability threshold to achieve an optimum decision can be objectively defined. Here, we present two approaches for simplifying the interpretation of ensemble (probabilistic) ocean wave forecasts out to 15 days ahead, as pioneered – in operation – in Summer 2020 to support the recent weather sensitive installation of the first phase of a 36 km subsea pipeline in the North Sea. Categorical verification information was constructed from 1460 archive wave forecasts, issued for the two-year period 2017 to 2018, and used to characterise the past performance of the European Centre for Medium-Range Weather Forecasts (ECMWF) EPS in the form of Receiver Operating Characteristic and Relative Economic Value analysis. These data were then combined with a bespoke parameterization of the impact of adverse weather on the planned operation, allowing the relevant go/no-go ensemble probability threshold for the interpretation of future forecasts to be determined. Trials on an unseen nine-month period of data from the same site (Spring to Autumn 2019) confirm the approaches facilitate a simple technique for processing/interpreting the ensemble forecast, able to be readily tailored to the particular decision being made. The use of these methods achieves a considerably greater value (benefit) than equivalent deterministic (single) forecasts or traditional climate-based options at all lead times up to 15 days ahead, promising a more robust basis for effective planning than typically considered by the offshore industry. This is particularly important for tasks requiring early identification of long weather windows (e.g. offshore pipeline installation), but similarly relevant for maximising the exploitation of any ensemble forecast –  by any sector – providing a practical approach for how such data are handled and used to promote safe, efficient and successful operations.