bluuebunny/crossref_metadata_2025 huggingface dataset:
1D Radiative Transfer Model Calculations of Solar Actinic Flux Densities with Satellite Cloud Products – Comparison with Airborne Measurements on HALO
Authors: Kremer Arthur , Bohn Birger , Palikonda Rabindra , Smith Jr. William L.
Published: June 2022

Clouds are highly variable in their structure as well as phase, resulting in a potentially large influence on actinic flux densities. Chemistry-transport models rely on accurate simulations of actinic flux densities to reproduce the essential impact of photolysis processes, thus the need for accurate radiative transfer calculations in the presence of clouds arises. Current studies show that under clear sky conditions simulated and measured UV/VIS actinic flux densities are typically within 10%, independent of wavelength. On the other hand, the impact of clouds on actinic radiation is more difficult to reproduce correctly when dependent on cloud structure, phase and position, flux densities can be significantly smaller or greater compared to clear sky conditions.

Following a similar approach by Ryu et al., 2016, UV/VIS spectral actinic flux densities were calculated utilizing cloud products from geostationary satellites (NASA SatCORPS). In this work, the latest version of the libRadtran model has been used, as well as aerosol properties (MODIS, MOD08_D3), surface albedos (MODIS) and total ozone columns (TEMIS, MSR-2) from polar-orbiting satellites as key input to simulate actinic flux densities in a range 280-650 nm. The evaluation of the model results is made by comparison with measured data from several campaigns with the research aircraft HALO (High Altitude and Long Range Research Aircraft) with a total of around 90 flights.

Using the NASA SatCORPS products (cloud phase, cloud optical depth, cloud top height, cloud liquid or ice water content and cloud particle size) 1-D radiative transfer calculations were conducted. Radiative properties of water clouds are reliably reproduced using look-up tables based on pre-conducted radiative transfer calculations using Mie theory. On the other hand, ice clouds and their correct parametrizations are challenging because of the wide range of possible ice crystal variations. Moreover, small-scale variations captured by the highly resolved aircraft measurements cannot be reproduced completely, due to the lower spatial and temporal resolution of satellite observations. The final intent of this study is to assess the quality of the radiative transfer modelled actinic flux densities and their potential to improve chemistry-transport models.
High resolution simulations using ICON-LEM to study convective storms in an urban environment around Paris
Authors: Bruder Lena , Kiszler Theresa , Schemann Vera , Löhnert Ulrich
Published: June 2022

The population in cities is steadily increasing, requiring more sustainable and secure urban environments. This includes the adaptability and resilience towards natural disasters. Floods and storms can have a large negative impact on livelihoods and infrastructure. At the same time, we are increasing our ability to predict such events. Numerical weather prediction models nowadays can perform on large regions with convection resolving grid resolution. 

 

A current research question is to what extent forecasting improvements can be obtained by running locally nested large-eddy simulations in advance of convective storms. To investigate this, we use a setup with the atmospheric model ICON in the numerical weather prediction mode (ICON-NWP, 2.5 km resolution) as well as in the large eddy simulation mode (ICON-LEM). The study is embedded into the WMO-WWRP endorsed Paris Research Demonstration Project (RDP) focussing on the Olympic Games of Paris in 2024 with the objective to advance meteorological research for future weather forecasting systems in urban areas.

 

The ICON-LEM is set-up and run for Paris and its urban surroundings using a circular domain applying different horizontal resolutions (100 - 600m). We use a two-moment cloud microphysics parameterization scheme and the Smagorinsky scheme for the subgrid scale turbulence. For the evaluation on the observational side, we use the super site SIRTA. There, for instance, we can use the ground-based remote sensing profilers (e.g. microwave radiometer, Doppler lidar) as well as radiosondes and surface measurements. We ran the model for single cases with convective storms and high temperatures.

 

We analyzed the boundary layer growth in the simulations using ICON-NWP during the day, which showed good agreement between model and observations. The vertical profiles of the radiosondes showed that the height of the inversions was not accurately met and there is less humidity in the model. We plan to further extend our analysis to evaluate the precipitation and establish if and what refinements to certain parameters such as the roughness length can improve the simulations.
Statistically downscaled decadal predictions for summer precipitation forecast in Colombia
Authors: Toro Ortiz Yenny Marcela , Rosa Cánovas Juan José , Solano Farías Feliciano , García-Valdecasas Ojeda Matilde , Romero Jiménez Emilio , Gámiz Fortis Sonia , Castro Díez Yolanda , Palomino Lemus Reiner , Esteban Parra María Jesús
Published: June 2022

The impacts on the environment due to climate change are substantial for the future and could markedly affect the hydrology of tropical regions, as evidenced in the latest reports of The Invergovermental Panel on Climate (IPCC). This research studies the potential use of decadal predictions from the MIROC6 (National Institute for Environmental Studies Model of the University of Tokyo Japan) model to predict boreal summer (from June to August) precipitation in Colombia for the first year of each simulated decade. Colombia is a country with areas with large annual precipitation records but also with dry regions, where the precipitation variability has marked socioeconomic and biodiversity impacts. The choice of this model is based on its ability to reproduce the main atmospheric circulation patterns affecting to the study area. The analysis is based on a statistical downscaling (DS) of an ensemble of 10 decadal hindcasts from this model to obtain regionalized predictions of precipitation. The added value of these high precipitation simulations is addressed comparing them with those directly computed from MIROC6 outputs.

Keywords: precipitation, Colombia, decadal predictions, statistical downscaling.

ACKNOWLEDGMENTS: Y.M.T.O. thank the Colombian Ministry of Science, Technology, and Innovation for the predoctoral fellowship (grant code: 860). This research has been carried out in the framework of the project CGL2017-89836-R, funded by the Spanish Ministry of Economy and Competitiveness with additional FEDER funds, project P20_00035, funded by FEDER/Junta de Andalucía-Consejería de Transformación Económica, Industria, Conocimiento y Universidades, the Spanish Ministry of Science and Innovation (LifeWatch-2019-10-UGR-01), and the project B-RNM-336-UGR18, funded by FEDER / Junta de Andalucía - Consejería de Economía y Conocimiento.
Increasing the resilience of the German transport system to climate change and extreme weather events 
Authors: Hänsel Stephanie , Klippel Lara , Brendel Christoph , Nilson Enno , Schade Nils , Meine Lennnart , Herrmann Carina , Hache Ingo
Published: June 2022

Humankind is currently experiencing changes in the climate system and more changes are projected to occur in the next decades. For the transport sector, it is not only important to contribute to the mitigation of climate change in order to limit climatic changes to a manageable level, but also to manage unavoidable changes and related impacts on infrastructure and mobility by adapting transport infrastructure assets and services to the new conditions in which they will operate. The challenge of providing a climate resilient transport system is taken up by the BMDV Network of Experts – a research network of seven Federal Agencies under the German Federal Ministry of Digital and Transportation (BMDV).

Transport infrastructures and traffic flows along the federal roads, railways and inland waterways vulnerable to climate changes today and in future are to be identified. This is done using specific impact models as well as climate indices that serve as proxies for expected damages. These climate change impact analyses are done based on common data sets, scenario assumptions and assessment methods that allow for a comparable assessment over all modes of transport. Climate impacts that are studied within the BMDV Network of Experts are storms―windthrow, heavy precipitation―flash floods, erosion and landslides, enduring precipitation―flooding, drought―low flows and embankment fires, and sea level rise―tidal dynamics. Exemplarily, adaptation measures are developed in order to increase the climate resilience of the transport modes.

The research network has a strong practical orientation; the demands and questions of the infrastructure operators are integrated in the conception of research questions. The data, methods and results obtained by the research program BMDV Network of Experts are included in the operational services within the DAS core service “climate and water” (https://www.das-basisdienst.de/) that was established in 2020. These services support the climate change adaptation of transport and mobility in Germany, while many of the specific data, methods and analysis tools are also relevant for other fields of action like water management, coastal protection, construction engineering or the energy sector. The ongoing close dialogue between science, policy and practice is thereby of great importance in order to provide useful and targeted services.
Investigating the representation of microphysical processes in Arctic mixed-phase clouds in ICON-LEM
Authors: Kiszler Theresa , Ebell Kerstin , Chellini Giovanni , Kneifel Stefan , Schemann Vera
Published: June 2022

The Arctic shows an increased climate warming rate. There still exist uncertainties around the role that cloud feedback mechanisms play in this. In our study, we want to address these uncertainties. For that, we created a semi operational setup with daily cloud-resolving simulations over Svalbard. For these simulations with 600 m resolution, we use the ICOsahedral Non-hydrostatic model in the large eddy mode (ICON-LEM). The setup uses a two-moment microphysical parameterization and can handle heterogeneous surfaces. We apply the operational forecasts from the global ICON model as lateral boundary conditions. The advantage of this setup is that we can step away from focussing on single cases and instead look at many different types of large scale and local conditions.

We created and evaluated several months of these simulations using observations from Ny-Ålesund (Svalbard) for comparison. The supersite “AWIPEV” is located there. It includes a microwave radiometer, daily radiosondes, a rain gauge and other remote sensing instruments. In addition, we were able to use the Cloudnet data set that provides a classification of the hydrometeors. We found that the model captures general features such as the wind flow, integrated water vapour, temperature and relative humidity profiles very well. The cloud occurrence was overestimated by the model but still lies in a climatologically realistic range.

As the large scale dynamics are accurately simulated, this gives us the foundation to scrutinize the details of the cloud microphysical parameterization. As the next step, we investigate the shortcomings we could see in greater detail. One example is the more efficient production of cloud ice in the model than what was observed. For the analysis of specific microphysical processes, we are working on a software package which should enable the independent running of certain microphysical processes. This will make entangling the contributions of each process simpler and clearer while saving computational resources. Further, we show that for the Arctic, we must consider that standard nuclei concentrations, as used in models developed for the mid-latitudes do not represent the Arctic state. The goal in the long term is to improve the microphysical parameterization so that the model can better represent Arctic mixed-phase clouds.
Finnish Meteorological Institute’s Climate Bulletin Research Letters
Authors: Karhu Juha A. , Ajosenpää Hada , Luomaranta Anna , Ervasti Tiina , Gregow Hilppa
Published: June 2022

Finnish Meteorological Institute’s Climate Bulletin Research Letters is a recently established research-based publication that features short and easy-to-read research articles on climate and climate services. The issues are published as a supplement to the Climate Bulletin journal by the Finnish Meteorological Institute. Even though the articles may be short, each one is peer-reviewed and citeable with a unique DOI. Research Letters is published in English once or twice a year. All issues and articles are open access. No publication fees are charged either.

The editorial and publication processes have been designed to facilitate swift publication. Couple of weeks review and revision times are imposed. Once approved for publication, an article is instantly published as online and preprint versions. After 7-8 articles have been published this way, they will be collected to a single issue and published online at ISSUU digital publication platform.

Research Letters is a publication channel for short reports, results of projects or case studies that may not be suitable for a full-scale peer reviewed publication. It was established to satisfy a clear need for short research publications. The themes of the series revolve around climate, climate services, climate change, marine research and results of research projects. From time to time, theme issues present extreme weather phenomena or maritime themes, among other topics. Special emphasis of the publication is in introducing new climate services and tools for different target groups, such as cities and agricultural, forestry, tourism and energy sectors.

Since the first issue in spring 2019, four regular issues and one special issue have been published with 39 articles in total. The first issue has now over 400 reads. It is possible to subscribe to receive email reminders when new issues of the Climate Bulletin (in Finnish with a short summary in English) or Research Letters are published. Subscribers will only receive reminders when new issues are published. Subscription data is not used for advertising or other purposes. Research Letters is available on the Climate Bulletin website: https://www.ilmastokatsaus.fi/category/research-letters/. Climate Bulletin editorial team can be reached via email: ilmastokatsaus@fmi.fi. The editor-in-chief of the Climate Bulletin is Hilppa Gregow, Head of Unit, Finnish Meteorological Institute, hilppa.gregow@fmi.fi.
Air temperature and humidity records-based indices as signals of seasonal changes
Authors: Lalić Branislava , Firanj Sremac Ana
Published: June 2022

The astronomical and meteorological definitions of spring, summer, autumn, and winter are unique and quantitative. Nevertheless, in everyday life, season transition is more related to human perception of seasons than astronomical parameters (like the timing of equinox or solstice) or calendar. If any kind of vegetation is present, human perception of seasons strongly relays on changes in plant development: spring – the start of the growing season and intensive leaf appearance; summer – the intensive leaf development and flowering of gardens/yield formation in the field/crop harvest; autumn – a slowdown of development, and harvesting; winter – dormancy. If there is no vegetation whatsoever, human perception of seasons is probably based on one of the thermal comfort indices. For example, ten values of the universal thermal climate index (UTCI) that describe thermal stress categories corresponding to specific human physiological responses to the thermal environment can be associated with seasons and their transition.

Fitzjarrald et al. (2001) found the onset of spring in Eastern USA using springtime minimum in the afternoon relative humidity and first date when tendency Bowen ratio falls below one. Adopting an alternate approach, Lalic et al. (2022) linked changes in extreme values and inflection points of afternoon relative humidity and normalized daily temperature range (DTR/Td) with the growing stages of plants.

This study intends to offer indices based on daily air temperature and humidity records, which can be used as unique and quantitative descriptors of the timing of season transitions. As a case study, the timing of extreme values and inflection points of selected indices calculated using climate station data will be compared with phenology dynamics of dominant plants.

Literature

Fitzjarrald, D. R., Acevedo, O. C., Moore, K. E., 2001: Climatic Consequences of Leaf Presence in the Eastern United States. J. Climate, 14 (4), 598–614. https://doi.org/10.1175/1520-0442(2001)014<0598:CCOLPI>2.0.CO;2

Lalic, B., Fitzjarrald, D. R., Firanj Sremac, A., Marcic, M., Petric, M., 2022: Identifying Crop and Orchard Growing Stages Using Conventional Temperature and Humidity Reports, Atmosphere (Accepted for publication).
Storylines of Maritime Continent dry season precipitation changes under global warming
Authors: Ghosh Rohit , Shepherd Ted
Published: June 2022

The dry half of the year from May to October over the Maritime continent is a crucial period. Because a severely dry year could lead to unprecedented damages due to forest fires. The amount of rainfall during this period is closely tied to the sea surface temperature (SST) evolution over the tropical Pacific Ocean. The future change in the tropical Pacific SST has uncertainty with majority of the climate models showing a higher warming over eastern tropical Pacific. However multiple climate models show a higher warming rate over the western tropical Pacific, known as the warm pool region. This feature can also be seen in observations over the last 120 years. The effect of this differing tropical Pacific SST evolution can have contrasting influence over the maritime continent precipitation. Therefore, this study provides a risk-based estimate of the future dry season maritime continent precipitation, which is based on the possible evolution of tropical Pacific SST through physical climate storyline approach. We provide storylines of future dry period precipitation using the outputs of 38 climate models from Coupled Model Intercomparison Project version 6 (CMIP6). Our results suggest that a higher basin wide tropical Pacific warming with higher warming in the eastern tropical Pacific than the west would lead to a drier condition over the Islands of Sumatra and Java. Whereas lower increase in basin wide tropical Pacific SST with a warmer western tropical Pacific, which we saw in observations, would lead to wetter condition over the Islands of Borneo and Neu Guinea.

 
Unified parameterization of turbulence and boundary layer clouds using the updated two-energies turbulence scheme 
Authors: Schmidli Juerg , Bašták Ďurán Ivan , Sakradzija Mirjana
Published: June 2022

The unified parameterization of turbulence and clouds in the atmospheric boundary layer is one of the challenges in current weather prediction and climate models. An update of the two-energy turbulence scheme is presented, the 2TE+APDF scheme. The original version 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. To alleviate this problem, we propose several modifications: an update of the stability parameter to consider local stratification, a more flexible computation of the turbulence length scale, and the introduction of the entropy potential temperature to distinguish between a shallow convection and a stratocumulus regime. In addition, the two-energy scheme is coupled to a simplified assumed PDF (probability density function) method in order to achieve a more universal representation of the cloudy regimes. The updated turbulence scheme is evaluated for several idealized cases and one selected real case in the ICON modeling framework. The results show that the updated scheme corrects the overmixing problem in the stratocumulus cases. The performance of the updated scheme is comparable to the operational setup, and could be thus used instead of the operational turbulence and shallow convection scheme in ICON. Additionally, the updated scheme improves the coupling with dynamics, which is beneficial for the modeling of coherent flow structures in the ABL, such as, for example, cloud streets.
Assimilation of atmospheric wind vectors retrieved via Optical flow algorithm and a thermal all-sky imager
Authors: Acevedo Valencia Walter , Kurzrock Frederik , Reinhardt Maria , Potthast Roland
Published: June 2022

Ground-based remote sensing of wind is currently dominated by radar profilers and wind lidars, which deliver profiles of excellent quality and high update rates. Unfortunately, the relative high costs of these devices have so far strongly limited their geographical coverage. On the other hand, infrared all-sky imagers are more affordable instruments, that can provide valuable information at day and night time, not only about cloud cover, but also about wind via computer vision techniques. In this work we investigate for the first time, whether this kind of derived wind observations can be used for data assimilation. A Reuniwatt’s thermal-infrared all-sky imager “Sky InSight”©, installed at the Lindenberg Meteorological Observatory – Richard-Assmann-Observatory (MOL-RAO) in Germany, a ceilometer in the same location and the computer vision algorithm “Optical Flow” (OF) were used to retrieve atmospheric wind vectors at cloud base height: subsequent brightness temperature photographs delivered by our imager were geometry-corrected and afterwards analysed by the OF-procedure, obtaining a set of atmospheric wind vectors in the surroundings of the camera. These vectors were finally rescaled and averaged to generate one overall wind observation, valid at the cloud base height retrieved by the ceilometer, for the time period when the photographs were taken. Afterwards, these derived wind observations were assimilated into the German regional weather prediction system, which uses the limited area version of the ICON (ICOsahedral Nonhydrostatic) model and the Local Ensemble Transform Kalman Filter (LETKF). In this work we evaluate the quality of these observations as well as their data assimilation impact for a set of monitoring experiments.
Benchmarking different approaches to convert surface solar irradiance into PV power production : a case study with an operational forecast system for a roof-top PV farm
Authors: Cros Sylvain , Briand Swann , Badosa Jordi
Published: June 2022

Photovoltaic production of a given solar power plant is mainly correlated with solar irradiance reaching the solar panel and to a lesser extent with air temperature and wind speed. Therefore, available energy in a building with roof-top photovoltaic (PV) panels in self-consumption can be highly variable due to cloud cover stochastic behaviour. Accurate irradiance forecast within the next hours are useful to help the energy management system of the building to cope with this variability and thus to maximize the consumption of the locally generated electricity at the expense of grid energy, then reducing financial and environmental costs of the overall building energy consumption.

Any solar energy forecast solution presents several sources of uncertainty at each main steps of the process: cloud forecast, radiative transfer of cloud and aerosols, irradiance conversion into power. Reducing the uncertainty of PV power modelled from irradiance forecast is a specific issue because it depends on certain conditions of the forecast application. PV performance models convert irradiance into PV power if PV cells characteristics are known and correctly specified by manufacturer, which is not always the case. Moreover, unexpected shadowing, panel surface soiling or aging of materials cannot be easily taken into account. If a consistent historical record of PV power data is available, a model output statistics (MOS) helps to decrease these induced uncertainties. If only real-time data are available, adaptive calibration using Kalman filter can improve the accuracy. If both historical and real-time data access are available, various machine learning approaches can set up more accurate MOS.

The start-up incubator of Institut Polytechnique de Paris is a building equipped with a roof-top PV farm with a total capacity of 17 kWp, made up with 53 using 8 different technologies with several tilted angle and some panels are equipped with reflectors. Minute PV power data have been continuously recorded from July 2020 onwards, collocated with the irradiance measurements of the Palaiseau BSRN station. This exceptional testbed enabled us to benchmark the several approaches for PV power modelling. We implement reference algorithms (linear regression, Kalman filter and autoregression) simulating respectively the availability data conditions (historical, real-time, both) and compared them with more complex machine-learning approaches. Results according to data availability, season, solar zenith angle, air temperature and irradiance variability are discussed. One of the outcome is that availability of real-time power measurements improves significantly forecasting results in most weather situations.
Measuring the social impact of weather warnings with event-based surveys
Authors: Popovic Nathalie , Willemse Saskia
Published: June 2022

At the Swiss Federal Office of Meteorology and Climatology MeteoSwiss, the main goal of our warning system is to support the affected population and organizations in the best possible way to take the necessary measures to reduce the impact of extreme weather events. How can we measure whether our warnings achieve this goal and create societal value? A classical way of assessing the success of a warning system is to calculate the hit rate and false alarm rate. While this is very important, it is just a first step in measuring the value of the warning. Even the most perfect warning is not a guarantee for a reduction of the impact of the warned extreme event. A next step would be to assess how many individuals of the target group were reached and whether they were satisfied with the warnings and understood the information. However, the number of people reached and their average satisfaction alone still do not indicate how successful our warnings are. What we ultimately would like to know is whether our warnings lead to improved risk assessment, behavioural change and finally, to reduced costs and damages through extreme weather.

This contribution presents a concept for a standardized population survey that aims to provide quantifiable measures on the social impact of the warning. By drawing from methods of impact assessment in the non-profit sector, we differentiate between output, outcome and impact of our warnings and derive indicators for each of these levels. Data for these indicators will be collected through representative population surveys in the affected regions a few days after an extreme weather event occurred. During a pilot phase to be launched in fall of this year, we will assess the potential of these indicators and of different data collection methods (representative online survey vs. representative telephone interviews vs. online survey with users of our channels). Although data will not be available yet at the time of the conference, the presentation aims to present our approach and discuss opportunities as well as challenges and limits of measuring the value of our warnings by using event-based surveys.
Public responses to heat health alerts in the United Kingdom
Authors: Taylor Andrea , Summers Barbara , Barnard Jenna , Domingos Samuel
Published: June 2022

INTRODUCTION

With climate change projected to lead to an increase in the frequency and severity of heatwaves in the United Kingdom, effectively communicating with the public about the need for heat protection behaviours during these events is becoming increasingly important. In this study we investigated public responses to a severe heat event on 25th July 2019, where forecast temperatures had triggered a Level 3 heat health warning (“heatwave action”) in multiple regions.

METHODOLOGY

Between 7th-8th August 2019 a sample of 520 UK residents in Greater London and Yorkshire and Humberside were recruited through Qualtrics Panels to complete an online survey on their experience of high temperatures on July 25th. They were asked to indicate 1) whether they recalled receiving a heat health alert; 2) trust in the alert (if recalled); 3) perceived normality of the temperature; 4) perceived pleasantness of the temperature; and 5) engagement in heat protective (e.g. sunscreen, drinking water, opening windows at night) and heat avoidant (e.g. staying in the shade, avoiding midday sun, avoiding physical exertion) behaviours.

RESULTS

Of the participants, 293 (56.3%) reporting seeing or hearing a heat health warning. Using regression analyses we find that heat protective behaviours are associated with recalled exposure to heat health alerts as well as perceiving temperature to be less pleasant and warmer than usual. However, recalled exposure to heat health alerts was not a significant predictor of heat avoidant behaviours. Where heat health messaging was recalled, trust was a consistent predictor of both heat protective and heat avoidant behaviours.

CONCLUSIONS

While our findings suggest that while heat health messaging is associated with greater uptake of some heat protective behaviours, this may be contingent on trust in heat health messaging. Moreover, having positive feelings towards warm weather may attenuate willingness to engage in heat protective and avoidant behaviours. We discuss the implications of this for the communication of heat alerts and warnings by national meteorological services.
Meteorological analysis of "Morning dips" in wind power production across Germany in 2021
Authors: Schielicke Lisa , Gatzen Christoph , Gruhlke Daniel
Published: June 2022

Wind power is highly dependent on the large scale weather situation, but additionally, small-scale variations of the boundary layer can have significant effects on the wind power production. In a joint collaboration with Statkraft, the authors analysed the influence of diurnal variations of the boundary layer on the amount of wind power produced across Germany.

Statkraft maintains wind power plants across the country and monitors the power production. A high-resolution data set of wind power production, broken down to the locations of the power plants, has been analysed with respect to small-scale variations of the wind power production. These sudden and often unexpected drops in wind power production are known to occur during daytime, especially in the morning (“morning dip”).

This work uses the data of 2021 to give the frequency of these morning dips across Germany. Their diurnal and seasonal occurrence is analysed as well as the regional occurrence. The occurrence of morning is analysed with respect to different pattern of meteorological conditions.

We found that morning dips are frequent in the warm season, whereas they are almost missing in the winter. Their average diurnal occurrence is dependent on the time of sun rise, and the relative frequency of days with morning dips was largest in the southern and eastern parts of Germany. Sunny conditions were most likely to be associated with morning dips, even when the large-scale flow was only modest. Cloudy and rainy conditions were not favorable for morning dips, even when the large-scale flow was strong. We suppose that morning dips are associated with sharp changes of the wind speed within the boundary layer, and that the change of boundary-layer depth during the morning causes the rapid drop of wind power production in particular on sunny days in the warm season.
Assessing the weather conditions for urban cyclists by spatially dense measurements
Authors: Ament Felix , Schmitt Amelie , Burgemeister Finn , Dorff Henning , Finn Tobias , Hansen Akio , Kirsch Bastian , Lange Ingo , Radtke Jule
Published: June 2022

Convincing commuters to use a bike for their daily trips is a timely contribution to reach sustainable development goals. In public discussions, bad weather is frequently raised as argument limiting the usability of cycling on an everyday basis. Looking at objective meteorological observations, how often does a typical commuter in an urban environment experiences bad weather while cycling? And can smart cyclists being informed by nowcasting and day-ahead forecasts effectively reduce the number of bad weather rides?

To answer these two key questions of this study, we analyze a huge ensemble of randomly drawn routes and assess the meteorological comfort of each ride by a threshold-based traffic light scheme. We chose temperature, wind, and precipitation as meteorological parameters indicating bad weather for cyclist. Observations are derived both from classical weather stations and from experimental novel urban observation systems: We explore the potential of a high-resolution X-band precipitation radar and of the dense station network (103 stations) during the FESST@HH campaign, which are both available at our study region, the city of Hamburg in northern Germany.

Most frequently we observe discomfort caused by temperature with a probability of 33%. Wind and precipitation discomfort occur only at 6% and 7% of the rides. Being slightly flexible in terms of riding times and being informed by a perfect nowcasting forecast is a very effective approach to reduce the risk to experience rain by a factor of two. Day ahead forecasts by operational ensemble systems provides an almost perfect guidance concerning temperature but the limited predictability of precipitation and wind renders these forecasts only useful for riders with a high risk awareness and small sensitivity to false alarms. In conclusions, this presentation indicates that weather is not severely limiting biking commuters and highlights the potential of guidance from weather observations and forecasts to reduce the risk experiencing bad weather during a ride.   
Recent Updates to the National Solar Radiation Database (NSRDB)  
Authors: Sengupta Manajit , Habte Aron , Xie Yu , Buster Grant , Benton Brandon , Bannister Mike
Published: June 2022

For over 20 years, the National Solar Radiation Database (NSRDB), covering most of the western hemisphere, has been a source of public data for many solar energy applications. Recent improvements in satellite technology and machine-learning-based remote sensing methods have added tremendous value to the NSRDB in terms of both the quantity and quality of the data. 

For example, the historical NSRDB data that is available from 1998 to present with one year lag is processed on a nominal 4x4 km grid spacing at a 30min frequency. Beginning in 2018, the NSRDB has additional datasets at 2x2 km 5min resolution available for the Continental United States, Hawaii, Mexico, and the Caribbean Islands, and at a 2x2 km 10min resolution available for North and South America from +60 to -60 degrees latitude. The improved spatiotemporal resolution should be a great asset to our stakeholders, especially for the analysis of utility scale solar installations which typically desire a higher resolution than the previously available 4x4 km 30min data. 

Moreover, we have developed new methods for the prediction of cloud properties from satellite data using physics-guided machine learning. These methods were originally developed to compensate for the limitations of traditional cloud property retrieval algorithms, but they have proven to be generally more accurate than the traditional algorithms. The results demonstrate higher accuracy in the modeled irradiance that is expected to be helpful for a wide variety of solar energy applications. 

In summary, the goal of the NSRDB is to provide the public with the highest-quality freely-available solar irradiance data possible. In this context, the NSRDB continues to evolve and push the envelope of what a public solar dataset can be. We think these recent advancements are important contributions to the solar energy community, and we hope that they will be fully taken advantage of.
EUMETNET's E-PROFILE network for thermodynamic profiling and the detection of airborne hazards
Authors: Haefele Alexander , Bircher-Adrot Simone , Rüfenacht Rolf , Lehmann Volker , Mattis Ina , Mortier Augustin , Cimini Domenico , Turp Myles
Published: June 2022

EUMETNET's E-PROFILE programme aims to gather, centrally process and deliver profiles of wind, temperature, humidity and aerosols including volcanic ash in near real-time. It consists of a data hub to collect process and distribute data while the instruments are owned and operated by EUMETNET members as well as partners from academia and industry. As of today, E-PROFILE integrates operationally 30 radar wind profilers and more than 400 automatic lidars and ceilometers (ALC) producing profiles of wind speed and direction and attenuated backscatter coefficient, respectively. Most radar wind profilers are assimilated into ECMWF's Integrated Forecasting System (IFS) and an extensive analysis of Forecast Sensitivity to Observation (FSO) data from ECMWF confirms the positive impact of those data on the forecast quality.  ALC data are calibrated centrally by E-PROFILE using natural atmospheric targets and provide a basic yet quantitative information of aerosols including volcanic ash and durst, which are considered airborne hazards for aviation. With more than 400 operational sites, E-PROFILE's ALC network is a valuable complement to satellite observations and surface based research lidar networks. In the current programme phase (2019 - 2023) we are working on an advanced processing chain to retrieve aerosol extinction coefficients and aerosol mass concentration from ALCs to better meet the user requirements. Finally, E-PROFILE has been tasked to integrate microwave radiometers and Doppler lidars and to collect, process and distribute temperature, humidity and wind measurements from these instruments. This new component of the E-PROFILE programme aims at filling the observational gap in the atmospheric boundary layer.  We present briefly the operational components of E-PROFILE, give a detailed update on the ongoing developments and highlight how E-PROFILE serves NWP and informs about airborne hazards.
How to communicate uncertainty in weather warnings to the public? Put it into perspective!
Authors: Schulze Katja , Popovic Nathalie , Fleischhhut Nadine
Published: June 2022

Communicating the uncertainty underlying weather warnings appears promising. Information about uncertainty can increase confidence in the forecast and support the decision-making process (Joslyn and LeClerc, 2013; LeClerc and Joslyn, 2015; Fundel et al., 2019). However, probabilities can be misunderstood if they are not appropriately communicated (Murphy, 1980; Gigerenzer et al., 2005; Budescu et al., 2014). Uncertainty information in weather warnings might also reduce threat perception and intention to act (Taylor 2021; Schulze & Voss, in prep.).

As part of the WEXICOM project (Weather warnings: from EXtreme event Information to COMunication and action), we conducted a representative experimental online survey in Germany (n=1 721). In close collaboration with Nathalie Popovic (MeteoSwiss), we investigated how the public perceives weather warnings with different formats of uncertainty information. The study tested three combinations of numerical and verbal uncertainty information in weather warnings (numerical probability & verbal probability vs. numerical probability & verbal frequency vs. numerical frequency & verbal frequency). Moreover, we tested all three conditions with and without additional explanation about the probability level at which the weather service typically issues a warning. All combinations were tested for three probability levels (20%; 40%; 60%) in two weather scenarios (hurricane force gale; thunderstorm with extremely heavy rainfall).

We find that low probabilities decreased the perceived risk and warning response – in line with numerous findings in other domains that low probability events are often not taken seriously. Interestingly, the format in which probabilities were communicated did not make a difference: The warning response was independent of whether probability information was given in numerical or verbal form. What was striking, however, was that providing information about the low probability level at which weather services typically issue a warning improved the perception of the warning — especially at low probability levels. Thus, the main problem for the public might not be understanding the uncertainty information but interpreting its magnitude in the context of weather warnings. Here, a simple reference point can help to put low probabilities into perspective.
The impact of the dust transport events over Europe in March 2022 on the weather forecast with the ECMWF model
Authors: Flemming Johannes , Remy Samuel , Inness Antje , Ades Melanie , Parrington Mark , Garrigues Sebastien , Hogan Robin , Haiden Thomas , Engelen Richard
Published: June 2022

Several transport events of Saharan dust to Europe and the Mediterranean took place in Spring 2022. The most severe one during 13-17 of March led to an unprecedented increase in aerosol optical depth, surface particulate matter concentrations and dust deposition in Western Europe.  The dust outbreak was well predicted with the regional and global atmospheric composition forecasting systems of the Copernicus Atmosphere Monitoring Service (CAMS). The global CAMS forecasting system is a specific configuration of the Integrated Forecasting System of the European Centre for Medium Range Weather Forecasts. It uses the prognostic aerosol and ozone fields in the radiation scheme to account for the interaction of these tracers with the short and long wave radiative transfer.  The impact of the prognostic dust on the meteorological forecasts, in particular on the 2m temperature predictions, is quantified by a comparison with a meteorological control forecast which uses an aerosol climatology derived from the CAMS re-analysis. This aerosol climatology is also used in the operational high-resolution forecast (9km) of ECMWF. We show that the dust plume led to a cooling of the 2m temperature forecast by up to 4 K. This cooling can be confirmed to be an improvement of the forecast by a comparison with synop and other observations.  In the presentation, we will discuss in more detail the impact of the quality of the aerosol forecast on its meteorological impact by considering different aspect of the aerosol modelling and the aerosol data assimilation to initialise the global aerosol forecasts. 
How can data assimilation of visible satellite data assist seamless prediction?
Authors: Bach Liselotte , Deppisch Thomas , Scheck Leonhard , Schomburg Annika , Ulbrich Sven , Blahak Ulrich , Schraff Christoph , Faulwetter Robin , Stephan Klaus , Köpken-Watts Christina , Potthast Roland
Published: June 2022

In the framework of the project SINFONY at Deutscher Wetterdienst, we work towards seamless prediction at the very-short range blending over from observation-based nowcasting to numerical weather prediction. The key goals that we pursue in this context are:
1.    To deliver forecasts earlier to be displayed in the meteorological workstation NinJo of our forecasters, which is realized by hourly forecast initialization in our newly-developed Rapid Update Cycle (RUC) and shorter latency for observation arrival ahead of data assimilation. 
2.    To provide seamlessly combined products integrating nowcasted and forecasted radar reflectivities as well as precipitation from both forecasting systems.
3.    To achieve a better representation of precipitation processes and convective cells in our NWP model to allow for the seamless blending with nowcasts. For this purpose, we use a two-moment microphysics scheme that predicts not only mixing ratios of hydrometeor species, but also their particle size distribution. This is also of great importance for the data assimilation of geostationary all-sky satellite data assimilation, for data assimilation of lightning data and essentially radar reflectivities.

In this presentation, we explain how data assimilation of cloudy visible satellite data can help to improve the accuracy of clouds and precipitation processes in NWP forecasts to assist a seamless blending of nowcasting and NWP in terms of radar reflectivities mentioned in 2) and 3). 

Visible satellite data are directly sensitive to liquid water path, ice water path and specific humidity  which are integral quantities related to precipitation processes. Moreover, cloud positioning can be improved by deleting false alarm clouds and convective cells and introducing missing ones to the forecast. A key advantage is that visible data are particularly sensitive to water clouds, which allows to constrain convective cells already at their state of initiation in the initial conditions of our RUC forecasts.

We elaborate on the basic principles of satellite data assimilation in our ICON-D2-KENDA system making use of an ensemble Kalman filter. Case studies will be shown to demonstrate how data assimilation of all-sky satellite data reduces analysis and forecast error of clouds and precipitation. Finally, we show the impact in our rapid update pre-operational system over longer periods of time. 
A Doppler Lidar technique for monitoring the „whole“ boundary layer
Authors: Kirtzel Hans-Juergen , Peters Gerhard
Published: June 2022

Doppler Lidar is a powerful measuring technique for observing particularly vertical wind profiles in the atmospheric boundary layer. It is well known that the performance of such long-range wind lidars depends to some extent on the atmospheric conditions, which causes a variable upper limit of the accessible measuring heights. Another, more fundamental constraint of long-range lidars refers to the lower height limit which is typically > 50 m. Furthermore, useful profiling in these height ranges requires range resolution much finer than the height range itself. An adequate range resolution causes broad Doppler spectra which result for typical Lidar wavelengths (1 – 1.5 um) in an unacceptable poor velocity resolution.

The height range below 50 m plays a key role for the interaction between surface and atmosphere and can show sharp and sometimes complex gradients as for example in nocturnal stable layers. The diurnal evolution of the profile of mean wind and turbulence close to the surface can be quite different from higher layers and cannot be inferred from upper height observations.

 A combination of Lidar techniques has been developed to overcome the above-mentioned lower range limitation and to extend the lower height range down to < 10 m while preserving the long-range capability.

Field data from such recently developed Lidar system will be presented in comparison with composite profiles from simultaneous measurements with a conventional long-range pulsed Doppler Lidar, a short-range FM-CW-Lidar and a 15 m mast with sonic instrumentation. The analysis will include profiles of mean wind as well as of turbulence parameters.