bluuebunny/crossref_metadata_2025 huggingface dataset:
A deep CNN model for medium-range spatio-temporal wind speed prediction for wind energy applications
Authors: Scheepens Daan , Hlavackova-Schindler Katerina , Plant Claudia , Schicker Irene
Published: June 2021

The amount of wind farms and wind power production in Europe, on-shore and off-shore, increased rapidly in the past years. To ensure grid stability, omit fees in energy trading, and on-time (re)scheduling of maintenance tasks accurate predictions of wind speed and wind energy is needed. Especially for the prediction range of +48 hours up to 2 weeks ahead at least hourly predictions are envisioned by the users. However, these are either not covered by the high-resolution models or are on a spatial and temporal course scale. 

To address this as a first step we therefore propose a deep CNN based model for wind speed prediction  using the ECMWF ERA5 to train our model using at least seven wind-related temporal variables, i.e. divergence, geopotential, potential vorticity, temperature, relative vorticity, vertical wind velocity and horizontal wind velocity.

The input of the CNN is represented by  the 3-dim tensor (size of the 2-dim figures x time shots), one for each variable. The CNN  outputs the most probable of the six categories in which the wind speed will be during the following 96 hours, in 6h intervals. Different combinations of input data are investigated in terms of temporal input.

We analyse the influence of prediction range on the predicted category as well as the relevance of each of the wind-related variables in the prediction of this category.  The model will be tested and applied to the ECMWF IFS forecasts over Austria. The ensure a higher spatial and temporal resolution an additional step will be used for downscaling the CNN directly to a 1 km grid.

This work is performed as part of the MEDEA project, which is funded by the Austrian Climate Research Program.
The two-energies turbulence scheme coupled to the assumed PDF method
Authors: Bastak Duran Ivan , Sakradzija Mirjana , Schmidli Juerg
Published: June 2021

An update of the two-energy turbulence scheme is presented. The two-energy scheme is an extension of a Turbulence Kinetic Energy (TKE) scheme following the ideas of Zilitinkevich et al. (2013), but valid for the whole stability range and including the influence of moisture. The additional turbulence prognostic energy is used for the calculation of the stability parameter. The stability parameter is thus not anymore strictly local and has a prognostic character. These characteristics enable the two-energy scheme to model both turbulence and clouds in the atmospheric boundary layer. The original implementation of the two-energy scheme is able to successfully model shallow convection without the need of an additional parameterization for non-local fluxes. However, the performance of the two-energy scheme is worse in stratocumulus cases, where it tends to overestimate the erosion of the stable layers due to over-mixing. We have identified the causes of the over-mixing in the stable layers.  First, the non-local stability parameter does not consider local stratification, which leads to its underestimation and subsequent over-mixing.  Second, the scheme lacks an internal parameter that could distinguish between a shallow convection regime and a stratocumulus regime, thus the scheme can not be calibrated in this respect.  And third, the turbulence length scale formulation is not flexible enough to adjust to all possible regimes in the ABL. To alleviate this problem, we propose several modifications: an update of the stability parameter, a modified computation of the turbulence length scale, and introduction of the influence of entropy potential temperature into the scheme. In addition, the two-energy scheme is coupled to a simplified assumed PDF method in order to achieve a more universal representation of the cloudy regimes. The updated turbulence scheme is evaluated for selected idealized and real cases in the ICON modeling framework.
Fog formation, smog situations and air quality in high school physics education
Authors: Molnár Beáta , Weidinger Tamás , Tasnádi Péter
Published: June 2021

 It has become a requirement worldwide that physics syllabus should contain everyday knowledge as well. One important field that can make the curriculum more colourful and exciting is the field of meteorology. In our presentation a three-lesson-long curriculum for grammar schools will be introduced on how to teach the connection between fog formation and air quality. Mist (visibility between 1 and 5 km) and fog (visibility below 1 km) are frequent weather events in the Carpathian Basin in the winter half year and during mostly anticyclonic weather situations with durations of 500-1000 and 150-300 hours respectively. In these cases often occurs the temperature inversions, the cold air pool events thus the high concentration of pollutants. The international educational experience of this particular topic will be surveyed, mainly in the countries of the Carpathian Basin; moreover the measurement processes and education methods used in the GLOBE programme will also be presented. The curriculum was tried within the framework of physics among 14 to 16-year-old Slovakian secondary school students partially in long-distance education on the Internet. Students’ knowledge on the given subject was tested both before and after the experiment.

The experimental curriculum consists of three parts. In the first part air humidity and the notion of absolute and relative humidity are discussed. Through a few specific exercises the students learn to specify relative humidity and become acquainted with fog formation. It is shown via an experiment that air cooling at a constant humidity is not enough to form fog because condensational cores are needed for the formation of tiny water drops. In the 2nd lesson the concept of temperature inversion and its connection to fog and air pollution are discussed. With the use of Internet websites the students collect information about the formation of smog, its types, occurrence and the conditions announcing smog alert. In the 3rd lesson the methods of analysing air pollution and different air polluting materials are discussed. Websites, where the students can follow the air pollution data of their area, are used. On the grounds of this tasks about interpretation of the data are solved. Pieces of information which are available on the website of the European Environment Agency are also touched on. It was a new realization for them that the inhabitants of poverty-stricken valleys were more vulnerable to the formation of smog.

Other than helping the students better understand the concept of humidity, the experiment helped them better understand changes in consistency. Based on our experience, the experimental curriculum motivated the students to understand processes which take place in their environment regarding environmental protection and to make suggestions about solving these problems. 
How to determine the current state of the climate?
Authors: Scherrer Simon C. , Begert Michael , Stöckli Reto , Gubler Stefanie , Kotlarski Sven , Croci-Maspoli Mischa
Published: June 2021

Determining the current state of the climate is a core task of climate monitoring and climate information in every climate service department. Traditionally, averages over a recent 30-year period, so called climate normals, are used for this purpose. However, the classic concept of climate normals is based on the assumption of a stationary climate. Due to climate change, this stationarity assumption is violated for some variables such as temperature and climate normals can deviate considerably from the true current state of the climate. Since 2012, the World Meteorological Organization recommends updating climate normals more frequently, every 10 years instead of every 30 years. The scientific literature however shows that further alternative approaches are desirable and can potentially help users make better informed decisions. MeteoSwiss is currently examining the possibilities of introducing supplementary estimates that better describe the current state of the climate. In this presentation we discuss statistical properties of a series of alternative estimates such as shorter averaging periods, different linear trend fits and applying smoothed curve fitting (e.g. cubic splines, kernel regression). The analysis is applied for the testbed of Switzerland using a perfect model framework for combined observational/climate scenario temperature series. The results allow to determine if supplementary estimates are superior to the classical normal or not and are a central component for deciding whether alternative to the classical normals should be introduced. Another important goal of this presentation is to initiate a discussion among climate service providers about their thoughts, experiences and approaches in defining the current climate state.
Borderless Heat Stress
Authors: Brimicombe Chloe , Di Napoli Claudia , Cornforth Rosalind , Pappenberger Florian , Petty Celia , Cloke Hannah
Published: June 2021

Heatwaves have been increasing in frequency, duration, and intensity. They have been the deadliest hydro-meteorology hazard globally for the last 5 years according to the world meteorological organisation. In addition, they are not constrained by geography in the same sense as many other hazards and as such they are borderless. They however receive less attention, research, and funding internationally than other hazards such as floods and storms, effecting how we perceive their risk and their reporting. Here we consider the impact of heatwaves by making use of the Universal Thermal Climate Index (UTCI) for indicating heat stress. The UTCI is a biometeorological index that computes thermal stress using the parameters of 2m temperature, wind speed, mean radiant temperature and relative humidity and a body model, making it a human-centric approach to assessing thermal stress and is skilful for both indicating and forecasting heat hazards. Further a comparison to how heat impacts are reported in EM-DAT (an international disasters database) and international meteorological organisation reports, supplemented by English news media reports is made to assess whether heat impacts are sufficiently reported. In addition, we refer to specific case studies of the United Kingdom, Ghana, and Uganda to further explore impacts, risk perception and policy at a country level, because although heat is borderless impacts occur on a local scale. All this together, will provide the evidence for the development a potentially global early warning system and the implementation of climate change adaptation on a local level to build adaptive capacity and resilience to the growing risk of heat stress internationally. 
The new MeteoSwiss postprocessing scheme for medium-range surface weather forecasts: multi-model, probabilistic, seamless, and at any arbitrary location
Authors: Spirig Christoph , Bhend Jonas , Hemri Stephan , Rajczak Jan , Nerini Daniele , Keller Regula , Cattani Daniel , Schaer Mathieu , Moret Lionel , Liniger Mark
Published: June 2021

MeteoSwiss has developed and is currently implementing a NWP postprocessing suite for providing  automated weather forecasts at any location in Switzerland. The aim is a combined postprocessing of high resolution limited area and global model ensembles with different forecast horizons to enable seamless probabilistic forecasts over two weeks leadtime. Further, the output should be coherent in space and provide predictions at any location of interest, including sites without observations. We use the full archive of MeteoSwiss’ operational local area models (COSMO-1 and COSMO-E) over the past four years and the corresponding IFS-ENS medium range predictions of ECMWF to develop postprocessing routines for temperature, precipitation, cloud cover and wind. Here we present selected key results on the performance of various postprocessing methods we applied but also on practical aspects of their implementation into operational production.

Both ensemble model output statistics (EMOS) and machine learning (ML) approaches are able to improve the forecasts in terms of CRPS by up to 30% as compared to the direct output of the local area model. The skill increase obtained by postprocessing varies depending on the parameter, region and season, with best results for temperature and wind in areas of complex orography and only marginal improvements for precipitation during seasons with a high fraction of convective situations. Particularly for temperature, the combined postprocessing of COSMO and IFS-ENS resulted in a skill benefit over postprocessing the COSMO models alone. Locally optimized postprocessing would allow further skill improvements, but only at sites where observations are available. However, the ability of non-local postprocessing approaches to provide calibrated forecast at any point in space is a key advantage for providing automated forecasts to the general public via the internet and smartphone app. Furthermore, the computational efficiency of these non-local approaches makes them attractive for operationalization in a realtime context. 
Cost efficient energy scenarios to meet climate targets: does a hedging approach change economic policy recommendations?
Authors: Held Hermann
Published: June 2021

The last assessment report by the IPCC (AR5, WGIII, 2014) shows that the 2° target is compatible with continued economic growth and that the globally averaged short-term loss of consumption to finance an energy transition is 1%. Furthermore, initial work on the 1.5°C target shows that the economic expenditures are significantly higher, but are likely to be of the same order of magnitude.

This complex of results on the costs of an energy transition was generated with the help of integrated energy and climate economic models, as a result of which hundreds of energy scenarios were evaluated. Most of these scenarios were generated without an explicit representation of uncertainty about essential input parameters such as the learning rates of individual energy technologies or climate sensitivity.

This article examines the mechanisms through which explicit consideration of uncertainty has changed or could change policy recommendations. In particular, it is pointed out that the economic paradigm implicitly used in the above, asking for cost-minimal solutions under climate targets, needs to be generalized if one does not want to turn a blind eye to the possibility of future learning about uncertain parameters in today's investment planning.

In this context, a separate approach (Held, 2019) is presented and discussed for which class of issues the energy scenarios summarized in the most recent IPCC report are robust under uncertainty and for which qualitatively different policy recommendations would result.

Reference

Held, Cost Risk Analysis – Dynamically Consistent Decision-Making under Climate Targets, Environmental and Resource Economics, 72 (1), 247-261, DOI 10.1007/s10640-018-0288-y, http://link.springer.com/article/10.1007/s10640-018-0288-y (2019).
The combination use of microclimate measurement network, urban type classification and mesoscale climate prediction model to estimate the thermal condition distribution
Authors: Chen Yu Cheng , Cheng Fang Yi , Yang Cheng Pei , Lin Tzu Ping
Published: June 2021

The climate in Taiwan is hot and humid, and urban show high-density development. The dense urban development has increased the heat storage of the ground and buildings. The compact arrangement of tall buildings causes the narrowness of the urban space to block the sky's view and hinders the relatively smooth airflow, which will cause problems such as poor ventilation in the city and cause high thermal risk in the city. In the past, when obtaining climate data, if only the climate stations set by the Central Meteorological Bureau were used, the distance between the stations was too far, and the coverage of the ground around the distribution area was almost the same, resulting in significant differences between the predicted results and the actual climate conditions. Therefore, this research established a microclimate measurement network to obtain climate data. For the urban environment information, the urban built environment data, such as digital surface model, and building information, were regulated data or required to purchase. Therefore, this study uses the Local Climate Zone (LCZ) which can consider land use and land cover simultaneously and can be freely produced by satellite images. The typology classification method can be used to view the city by the height and density of obstacles. LCZ can solve the inaccuracy of estimation caused by the mixed land-use in Taiwan and assign various types of related data from the scheme such as heat capacity, albedo, and roughness through classification results. This study herein applies LCZ combined with a mesoscale climate prediction model Weather Research and Forecasting (WRF) to predict the climate conditions within the study's scope and compare them with actual measured values. It can be used for urban climate assessment. The research results preliminarily show that by applying the LCZ classification and its corresponding factors to WRF with Multi-layer urban canopy model which can consider vertical surfaces such as building volume facades horizontal surfaces such as streets and roofs. The predicted temperature and actual temperature will be slightly underestimated, and it can be approximately between 1.5°C to 2.5°C in the urban area at night and 0.5°C to 1°C during the day. This phenomenon may be due to the relative ratio of buildings and road width in Taiwan, making the actual night. The heat dissipation effect is poor, and it is easy to cause heat accumulation in the urban area.
Exploring the coastal effects relevant for offshore wind farming using the space borne synthetic aperture radar data in the German Bight
Authors: Djath Bughsin , Schulz-Stellenfleth Johannes
Published: June 2021

In the coastal zone complex atmospheric processes such as momentum and heat fluxes are  caused by large differences between the land and the sea. The smoother sea surface leads to wind speeds, which are usually higher over the ocean than over land. In addition, there are complicated effects caused by temperature gradients in the ocean due to water depth variations.  This study focuses on the investigation of the change in the horizontal wind field and the atmospheric stability between the coast and up to 200 km offshore.

The wind resources at 10 m height are assessed from synthetic aperture radar (SAR) data acquired by the satellites Sentinel1A/B over the German Bight within the period of 2017-2020 with a focus on offshore wind directions. The satellite data provide information on sea surface roughness, which can be linked to near surface wind speed.  Information on the air-sea thermal components is  provided by model data from the German weather service (DWD).

The SAR data  show a significant increase of wind speed offshore in most cases. Increasing wind speeds between land and sea over fetch distances of 70 km and more are often detected. The increase δu in horizontal wind speed between offshore and the coast exceeds 2.5 m/s in average. Furthermore, the estimated atmospheric stability shows an impact on the wind speed gradients. The thermal stability appears to dictate the distance over which the wind increases. Strong thermal stability tends to influence the horizontal wind gradient by increasing the fetch distance over more than 100 km. In the context of offshore wind farming, the potential effects of these horizontal wind gradients on the wind power will be discussed.
Providing a long-term hydroclimatic perspective for the recent extreme decline of Lake Prespa (SW Balkans) through quantitative reconstruction of lake water-balance changes over the past 5000 years
Authors: van der Schriek Tim , Giannakopoulos Christos
Published: June 2021

Ancient lakes throughout the Mediterranean are at risk of disappearing due to a combination of climate change and human impacts. The growing imbalance between water availability and demand is creating unprecedented ecological problems. There is an urgent need for better understanding the patterns of natural lake water variability to improve water resource management and conservation. The incorporation of long-term cycles is particularly important for assessing low frequency – high magnitude trends in lake water levels.

The Ohrid-Prespa Lake system is amongst the oldest permanent lake systems in Europe, with an age of >1 million years, and hosts a globally significant biodiversity. The closed-basin Prespa Lakes are particularly sensitive to climatic variability with long-term water level changes informing on the dynamic balance between [1] runoff and precipitation supplying water to the lakes, and [2] water loss from the lakes by evaporation and underground karst outflow.

The large, ongoing, fall of the Prespa Lakes that started in 1987 threatens the biodiversity and water resources of the interconnected lake system. This decline is caused by climate change, specifically by decreases of 10% in precipitation and 25% in runoff, amplified by water abstraction. There is no precedent for this water level fall in the observational record (1951-present), although geological archives indicate equally low water levels at least twice over the past five millennia. 

Here we present the first quantified estimates of changes in the lake water balance over time that are based on the strong relationship between open water surface area and water loss. This quantification allows direct comparison of lake low- and highstand events across time and assessing magnitudes of regional hydro-climatic changes. This study uses a novel approach that reconstructs absolute lake levels and related open water surface areas for different past periods, using the landform-sediment record.

The hydro-climate of the Prespa catchment shows a drying trend of since the mid Holocene. The recent (2001-2018) lake lowstand is the most significant over the past 700 years in terms of water loss changes. A lake lowstand period of a similar magnitude occurred about 2000 years ago. The most extreme lowstand period over the past 5000 years occurred between 1100-800 years ago during the Medieval Climate Anomaly, when water loss changes were >50% higher compared to the present lowstand. However, the renewed decline in lake level and surface area since 2019 requires close monitoring; if lake level falls a further 2m to 840m.a.s.l. it would become the largest recorded fall over the entire Holocene, with unknown impacts for the wider system.

 
Evaluation of thermally driven local winds in a deep Alpine valley in a high-resolution numerical weather prediction model
Authors: Schmidli Juerg , Quimbayo-Duarte Julian
Published: June 2021

In fair weather conditions, thermally driven local winds are dominant feature of the atmospheric boundary layer over complex terrain. They may dominate the wind climatology in deep Alpine valleys resulting in a unique wind climatology for any given valley. The accurate forecasting of these local wind systems is challenging, as they are the result of complex and multi-scale interactions. Even more so, if the aim is the accurate forecasting of the winds from the near-surface to the free atmosphere, which can be considered a prerequisite for the accurate prediction of mountain weather.  This study investigates the skill of the COSMO model at 1.1 km grid spacing in simulating the thermally driven local winds in the Swiss Alps for a month-long period in September 2016. The study combines the evaluation of the surface winds in several Alpine valleys with a more detailed evaluation of the wind evolution throughout the depth of the valley atmosphere for a particular location in the Swiss Rhone valley, the town of Sion. The former is based on a comparison with observations from the operational measurement network of MeteoSwiss, while the latter uses data from a wind profiler stationed at Sion airport. It is found that the near-surface valley wind is generally well represented for the larger Alpine valleys, except for the Rhone valley at Sion. The reasons for the poor skill at Sion are investigated and shown to be attributable to several factors. One of which is a too strong cross-valley flow reaching down to the valley floor and displacing the daytime up-valley wind. A second factor is the particular local valley geometry. It is shown that an increase of the initial soil moisture and the use a finer horizontal grid spacing results in an improved simulation of the diurnal valley wind at Sion.
Impact of drought conditions on urban climate of Zagreb (Croatia)
Authors: Nimac Irena , Herceg-Bulić Ivana , Žuvela-Aloise Maja , Žgela Matej
Published: June 2021

Dry periods and heat waves are becoming more frequent and intense in changing climate. Effect and impact of such specific events on local climate and ecosystems may vary spatially. One of the critical spots regarding extreme warm events are urban areas due to increased heat load. Here, we examine impact of drought conditions on characteristics of summertime urban heat island (UHI) for Zagreb, Croatia. For these purposes daily air temperature, precipitation, relative humidity, wind speed and wind direction data from the station Zagreb-Maksimir in a period 1928–2019 are used in the analysis. To define dry and wet conditions, standardized precipitation evapotranspiration index (SPEI) is used. The effect of drought conditions on summer UHI is analyzed from the perspective of preceding (i.e. wintertime and springtime) as well as concurrent (i.e. summertime) drought conditions. To estimate urban heat load in the city, urban climate model MUKLIMO_3 combined with cuboid method is used. Urban heat load is here represented as a number of summer days, i.e. days with maximum air temperature above 25°C. Landsat-8 satellite data were employed to analyze land surface temperature for specific situations. Results indicated substantial increase in heat load for situations when dry summer was preceded by dry late winter-spring period. However, when late winter-spring period was wet and followed with dry summer, much weaker increase in heat load is obtained. On the other hand, decrease in heat load is found for wet summer preceded by wet late winter-spring season. It is also showed that intensity of UHI is affected with drought conditions.

 
A network of meteorological stations for monitoring climate change impacts and adaptation on urban and rural environments
Authors: Lemesios Giannis , Kitsara Gianna , Varotsos Konstantinos V. , Psiloglou Basil , Giannakopoulos Christos
Published: June 2021

Ιn the framework of two European Projects, the LIFE URBANPROOF and LIFE TERRACESCAPE, a network of 24 meteorological stations has been installed for recording meteorological parameters and climate indices for the monitoring of impacts of climate change on urban and agricultural areas as well as for the assessment of respective adaptation measures.

Regarding the urban environment, the study aims to estimate the Urban Heat Island (UHI) effect in the Greater Athens’ Municipality of Peristeri, Greece, by analysing data from the meteorological stations installed (since January 2020) in different urban surroundings and investigating relative changes in surface temperatures and perceived thermal discomfort (HUMIDEX) thus identifying hot and cool spots at the local scale. The UHI mapping in the Municipality of Peristeri was designed and implemented in such a way, as to provide accurate information about heat stress conditions across different parts of the city. Fully automated sensors of air temperature and relative humidity were installed at eleven (11) sites throughout the municipality, covering a wide range of urban characteristics, such as densely populated areas, open spaces, municipal parks etc., where local climatic conditions were expected to show a degree of variation.

As regards the rural environment, the study intends to estimate the anticipated changes of the micro-climate in the Aegean island of Andros, Greece after land-use interventions, which are considering the use of drystone terraces as green infrastructures resilient to climate change impacts. To that end, a network of 13 meteorological stations has been installed in selected rural areas of Andros since June 2018 for monitoring purposes. The thirteen meteorological stations, 12 small autonomous stations and 1 automated, currently operating on Andros Island continue (till now days) to generate baseline (micro-) climatic data, providing basic meteorological parameters such as air temperature and relative humidity. In addition, the valuable information, based on observational data from installed network of the meteorological stations, located either at currently abandoned terrace sites (project plots) or cultivated sites of Andros will be used to provide a solid basis for comparisons with changes projected for the future climate, combined with climatic indices which directly or indirectly affect agriculture in the monitoring areas.

 
Turbulence characteristics and coherent structures in the convective boundary layer analyzed using Doppler wind lidars during FESSTVaL@MOL 2020
Authors: Dewani Noviana , Sakradzija Mirjana , Schlemmer Linda , Schmidli Jürg
Published: June 2021

Doppler wind lidars are used to measure boundary layer turbulence, which is an important process to transfer heat and moisture within the boundary layer. Turbulence measurements using Doppler wind lidars were conducted during FESSTVaL@MOL field experiment from June to August 2020. The FESSTVaL@MOL 2020 is a part of the FESSTVaL (Field Experiment on sub-mesoscale spatio-temporal variability in Lindenberg) measurement campaign conducted at the boundary layer site Falkenberg, a part of the Lindenberg Meteorological Observatory – Richard-Aßmann-Observatorium (MOL-RAO). One Doppler wind lidar has been operated in vertical stare mode to characterize turbulence in the convective boundary layer during the summer. Two other Doppler wind lidars have been operated in low elevation angle PPI scan mode and one Doppler wind lidar has been operated in RHI scan mode. These three scanning configurations are used to investigate the dominant coherent structures near the surface.

The retrieved wind data from vertical stare mode are categorized into cloud-topped boundary layer and cloud-free boundary layer days. We will analyze the intensity of the turbulence using vertical velocity variance and dissipation rate of the turbulent kinetic energy and the source of turbulence using a skewness profile for both categories. These profiles will be combined with low elevation angle PPI scan mode to categorize the coherent structures near the surface by their intensity and origin. Besides, we will present the overview of the preliminary study about the evolution of mixing layer height before and after cold-pool passage from several cases during FESSTVaL@MOL 2020 using vertical stare and RHI scan data.
Nowcasting of surface wind speed using probabilistic, explainable Deep Learning
Authors: Zanetta Francesco , Nerini Daniele
Published: June 2021

Surface wind is an extremely difficult parameter to predict, particularly in the complex topography of the Alps. Due to several important processes happening at sub-kilometer scale, even high resolution Numerical Weather Prediction models such as COSMO-1 still present substantial biases. To address this, a wide range of statistical post-processing methods are used. Recently, methods based on Deep Learning have emerged as a new solution and are now actively developed at many weather services, including MeteoSwiss. At the same time, efforts are made to obtain accurate representations of surface wind speed up to a few hours ahead by integrating all available information in real-time, an approach known as nowcasting.

With the aim of seamlessly combining nowcasting and post-processing approaches for surface wind speed predictions, we developed a Deep Learning probabilistic post-processing model that is also able to integrate real time observations, and developed a new metric, the Similarity Index, for this purpose. The Similarity Index is a way to estimate the correlation of surface wind speed between two locations, based on their position and geomorphological setting, and can be used to choose the best available observation to be used at any point in space at any given time, and weigh that observation in a way that mimics geostatistical interpolation methods. The proposed methodology yields improved forecasts of wind speed where both systematic and random errors are reduced, thanks to the post-processing and nowcasting components respectively. In a second phase, we implemented a state- of-the-art explainability framework for machine learning, SHAP, and presented how it can be used to get insights into the model and build trust in the results.
Wind profile correction algorithm based on Atmospheric Boundary Layer stability profile
Authors: Albuquerque Neto Francisco , Almeida Vinicius , Carelli Julia
Published: June 2021

In recent years, the use of radar wind profilers (RWP) at airports has grown significantly with the aim of supporting decision makers to maintain the safety of aircraft landings and takeoffs.

The RWP provide vertical profiles of averaged horizontal wind speed and direction and vertical wind velocity for the entire Atmospheric Boundary Layer (ABL) and beyond. In addition, RWP with Radio-Acoustic Sounding System (RASS) are able to retrieve virtual temperature profiles in the ABL.

RWP data evaluation is usually based on the so-called Doppler Beam Swinging method (DBS) which assumes homogeneity and stationarity of the wind field. Often, transient eddies violate this homogeneity and stationarity requirement. Hence, incorrect wind profiles can relate to transient eddies and present a problem for the forecast of high-impact weather phenomena in airports. This work intends to provide a method for removing outliers in such profiles based on historical data and other variables related to the Atmospheric Boundary Layer stability profile in the study region.

For this study, a dataset of almost one year retrieved from a RWP LAP3000 with RASS Extension is used for a wind profile correction algorithm development.

The algorithm consists of the detection of outliers in the wind profiles based on the thermodynamic structure of the ABL and the generation of the corrected profiles.

Results show that the algorithm is capable of identifying and correcting unrealistic variations in speed caused by transient eddies. The method can be applied as a complement to the RWP data processing for better data reliability.

 

Keywords: atmospheric boundary layer; stability profile; wind profile
Upstream of hydroclimate extremes : maxima of moisture transport
Authors: Dufour Ambroise , Gulev Sergey , Zolina Olga
Published: June 2021

The prevailing westerly winds provide Europe with an average flow of moisture from the North Atlantic. We document the climatological transport of water vapour across Europe's western border, from the south of the Iberic Peninsula to Northern Scandinavia. Four state-of-the-art reanalyses (NCEP CFSR, JRA 55, MERRA 2 and ERA 5) are confronted to satellite observations (QUIKSCAT and ASCAT) and to radiosoundings (IGRA) from six coastal sites.  Over the datasets' common time range (2000-2011), the agreement is generally good in terms of yearly and monthly fluxes. The satellite products have generally lower values than the rest of the ensemble. Some disparities appear on the vertical. A longer time range (1980-2020) excludes satellite data but allows to detect local increases in moisture transport in the later years.

Beyond the climatological picture, day to day moisture fluxes present significant fluctuations, both in the dry and wet directions. The variability is consistent between reanalyses and radiosondes but slightly weaker in the satellite data. The fluxes on pressure levels are strongly correlated to their vertically integrated counterpart. We take advantage of the vertical coherence to stratify humidity and wind profiles according to quantiles of integrated moisture transport. The respective role of humidity and wind changes becomes apparent. Wind speed and direction determines the moisture transport more than the humidity field on a short term basis. On the scale of decades, there was no discernable change of circulation. It was moistening that drove the increase in water vapour transport. The effect was disproportionate for higher quantiles as a consequence of the non-linear Clausius-Clapeyron equation.
Recent weakening in the winter ENSO teleconnection over the North Atlantic-European region
Authors: Ivasić Sara , Herceg Bulić Ivana , King Martin P.
Published: June 2021

New observational evidence for variability of the atmospheric response to wintertime El Niño-Southern Oscillation (ENSO) is found. A weakening in the recent ENSO teleconnection over the North Atlantic-European (NAE) region is demonstrated by using various methods (e.g. composite analysis, running correlation, regression maps) applied onto different observational datasets and reanalyses (HadSLP, NOAA 20th Century reanalysis). Changes in both the spatial pattern and strength of the ENSO teleconnection indicate a turning point in the 1970s, with a shift from a response resembling the North Atlantic Oscillation (NAO) in late winter to an anomaly pattern with very weak or statistically non-significant values; and to nearly non-existent teleconnection in the most recent decades. Weakening of the ENSO signal is found at the surface (sea level pressure), but also at higher levels for different variables (geopotential height, temperature, zonal wind). To offer a possible reason behind the observed change, we have investigated the potential role of sea-ice and SST climatology in modulating the ENSO-NAE teleconnection. Sensitivity experiments made with a GCM of indermediate complexity (ICTP AGCM) using different combinations of sea-ice and sea surface temperature (SST) climatology conditions enabled the investigation of their respective roles. As indicated by the targeted simulations, recent change in the SST climatology in the Atlantic and Arctic has contributed to the weakening of the ENSO effect. Results highlight the importance of the background SST state and sea-ice climatology having opposite effects in modulating the ENSO-NAE teleconnection over the area of interest. The findings of this study could further our understanding of modulations of ENSO teleconnections and the role of ENSO as a source of predictability in the NAE sector.
Analysis of the environment of a severe hailstorm in Mendoza, Argentina during the RELAMPAGO-CACTI field campaign
Authors: Bechis Hernán , Alvarez Imaz Milagros , Simone Inés , Galligani Victoria , Cancelada Maite , Piscitelli Franco , Paula Maldonado , Salio Paola
Published: June 2021

Storms in the Mendoza province, Argentina are known for frequently producing large and severe hail. The environmental conditions and strong interaction with topography there provide unique conditions for the initiation and intensification of severe storms. The RELAMPAGO (Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations) and CACTI (Clouds, Aerosols, and Complex Terrain Interactions) field campaigns were deployed between October 2018 to April 2019 over west-central Argentina, and have collected unprecedented Intensive Observation Periods (IOPs) in the region. During the IOP number 10 on November 26, 2018, a severe hailstorm developed and moved across the observational network in the Mendoza domain. 4-cm diameter hail was reported over multiple hailpad sites and with in-situ measurements. Several soundings, mobile and fixed radar observations, and surface observations are available for this case, along with 1-min GOES-16 ABI Mesoscale Domain Sector (MDS) data coverage.

High-temporal frequency soundings and surface observations collected prior to the convection initiation are analyzed, allowing a detailed description of the storm environment. Processes leading to convective initiation over the higher terrain include the development of the upslope flow associated with a mountain-plains circulation, the weakening and ascent of the nocturnal inversion owing to diurnal heating and mixed-layer growth, and upper-level cooling related to the advance of a shortwave trough. Once the storm initiates, it moves eastward towards the lower terrain, where the higher CAPE and deep-layer shear environment support the transition into a supercell. It is after this transition that the most severe hail at the surface is observed.
Comparison between the 2D wind fields retrieved by a scanning Doppler lidar and anemometric measurements
Authors: Benavent-Oltra José Antonio , Romanic Djordje , Lompar Milos , Burlando Massimiliano
Published: June 2021

In this work, two-dimensional (2D) wind fields retrieved by SingleDop software using scanning Doppler lidar data are compared with anemometric measurements in Genoa (Italy). SingleDop is a software module based on the theoretical work described in Xu et al. (2006), which is intended to retrieve 2D low-level winds from either real or simulated Doppler radar data. The lidar used in this work is a three-dimensional (3D) scanning WindCube 400S lidar, developed by Leosphere (France), which scans the azimuthal range of 100º –250º, up to a maximum distance of 14 km in the radial direction, for 4 elevations corresponding to 2.5º, 5°, 7.5° and 10º from the horizontal. The anemometer used for comparison is located about 1.3 km (horizontally) from the Doppler lidar and provides the wind velocity with a sampling rate of 1 Hz.

The dataset analyzed is from November 2019 to June 2020. The total number of available lidar scans per day is ~420 for each elevation (2.5º, 5º, 7.5º and 10º). The 2D wind fields are retrieved by SingleDop for different de-correlated lengths (L= 10, 5 and 1 km). The overall number of measurements available for the comparison is therefore approximately 420 scans per day × 180 days × 4 heights × 3 L, which results in nearly 106 wind velocity values. The wind direction retrieved by SingleDop properly corresponds to the anemometric data with a  BIAS ~13º, RMSE ~40º and a circular correlation of 0.8. Concerning the wind intensity, the results obtained for L = 5 km show the best agreement with the anemometric measurements with a BIAS of 0.8 m/s, RMSE around 1.8 m/s and a correlation coefficient higher than 0.9. Both for wind direction and velocity, the BIAS and RMSE slightly increase with the elevation whereas the circular and linear correlations decrease, as expected due to the increasing distance between lidar and anemometric measurements.
Pathways for climate change adaptation in urban areas - first results from field measurements and ENVI-met modeling
Authors: Eingrüber Nils , Korres Wolfgang , Schneider Karl
Published: June 2021

In the context of climate change, more frequent and intensive exposure to heat stress is observed and predicted for many cities worldwide. Urban climatological studies in recent decades have shown significant positive trends in the number of hot days. As heat stress poses a considerable health risk, adaptation measures need to be developed. Against this background, the research study aims to measure and model the urban microclimate of a 15 ha study area in Cologne. A network of IButtons and Netatmo weather stations with ultrasonic anemometers is used to measure temperature, humidity and wind speed/direction for assessing the climate character of the study area. The low cost sensors are calibrated against built up research grade meteorological stations. Utilizing low cost sensors also provides opportunities to activate citizens in microclimate research and to foster participation in mitigating climate change effects. The measurement network is set up as transects along street corridors and is used to a) identify the local climatic impacts of different surface types, vegetation areas and building structures, and b) to later calibrate and validate the ENVI-met model. Processes affecting the urban energy balance and microclimate are identified focussing particularly on source areas of excessive heat. Effects of urban green infrastructures are analysed with regard to their mitigation potential for heat stress, water demand for evapotranspiration, and their potential to modify the partitioning of the radiation balance into sensible heat and latent heat flux. We will use the validated ENVI-met model to simulate various adaptation scenarios and climate change scenarios. Adaptation measures will comprise changes in surface (e.g. urban water bodies and vegetation areas), facade/roof greenings or cooling materials. Climate projections until 2099 will be used with ENVI-met by downscaling meteorological data using the Statistical DownScaling Model (SDSM) and assuming the HadCM3 future emission scenarios.
Spin-up time from switching the microphysics scheme in the assimilation cycle and impacts on the precipitation forecast quality
Authors: Ulbrich Sven , Welzbacher Christian , Khosravianghadikolaei Kobra , Hoff Michael , de Lozar Alberto , Bach Liselotte , Stephan Klaus , Schraff Christoph , Blahak Ulrich , Potthast Roland
Published: June 2021

The SINFONY project at Deutscher Wetterdienst (DWD) aims to produce seamless precipitation forecast products from minutes up to 12 hours, with particular focus on convective events. While the near future predictions are typically from nowcasting procedures using radar data, the numerical weather prediction (NWP) aims at longer time scales. The lead-time in the latest available forecast is usually too long for merging both the nowcasting and NWP output to produce reliable seamless predictions.

At DWD, the current forecasts are produced by the short range numerical weather prediction (SRNWP) making use of a continuous assimilation cycle with relatively long cutoff times and using 1-moment microphysics. In order to reduce the differences in the precipitation to the nowcasting on the NWP side, we use two different approaches. First, we reduce the lead-time from the model start by running 1-hourly forecasts based on an assimilation cycle with shorter data cutoff. Secondly, we use new observational systems in the assimilation cycle, such as radar or satellite data to capture and represent strong convective activity. This procedure is called Rapid Update Cycle (RUC). As an additional measure, we introduce a 2-Moment microphysics scheme into the numerical model, resulting in a better representation of the radar reflectivities. In order to keep the model state similar to that of the SRNWP, the RUC is a time limited assimilation cycle starting from forecasts of the SRNWP at pre-defined times.

The introduction of the 2-Moment scheme leads to a spin-up affecting both the assimilation cycle and the short forecasts. The resulting effects are analysed by comparison with the corresponding assimilation cycle using the 1-Moment scheme. As a complementary approach for the analysis, the routine cycle is run with the 2-Moment scheme. The forecast quality is used as a measure to compare the results with respect to precipitation and additional observed parameters. It is shown in how far the resulting improvements are related to the assimilation and momentum scheme, or to the higher frequency of forecasts.