bluuebunny/crossref_metadata_2025 huggingface dataset:
A preliminary study of storage and transport processes in an idealized valley
Authors: Bašić Ivan , Schmidli Juerg , Singh Shweta
Published: June 2022

An accurate representation of atmospheric boundary layer (ABL) processes is critical for trace gas simulations and inverse modelling on the regional scale. This is particularly challenging over complex terrain such as the Swiss Midlands. Thus, it is not surprising that current operational numerical weather prediction models still provided limited accuracy for the simulation of vertical mixing processes over such regions. Vertical mixing in the ABL induced by local circulations directly impacts the vertical profiles of trace gases emitted at the surface. A bias in these processes may introduce significant errors in the estimate of trace gas concentrations. For example, the accumulation of greenhouse gases (GHG) during nighttime stable boundary layers (SBLs) is significantly underestimated compared to GHG observation sites such as Payerne or tall tower site Beromünster. Therefore, in the present work, high-resolution simulations using Cloud Model 1 (CM1) with idealized topography, representative of the Swiss Midlands, are performed, with the aim to contribute to an improved understanding of the relevant storage and transport processes, e.g. accumulation of passive tracer in nocturnal cold pools, separation of turbulence and local circulation effects, morning depletion and export of tracers to higher levels, entrainment of free-tropospheric air into the boundary layer, and their sensitivity to different environmental conditions, such as  atmospheric stratification, upper-level winds, surface forcings and to the properties of underlying topography. The model setup also includes virtual towers located at valley floor, over the slope and the mountain ridge. First results will be presented, and the current state of the research will be discussed.
Surface air temperature bias in meteorological models due to misrepresentation of the atmospheric boundary layer thickness
Authors: Esau Igor , Kähnert Marvin
Published: June 2022

Meteorological models are still imperfect. They often reveal a certain bias in the prediction of atmospheric variables near the surface. Among them, the surface air temperature bias is well known. Model developers usually relate this bias to problems with the surface energy balance caused by clouds, horizontal heterogeneity, and imprecise knowledge of land surface types. Indeed, fluxes in the surface balance are prone to misrepresentations. However, strong attention to physical imperfections in models diverts efforts from the investigation of plausible dynamical causes of the temperature bias.

In this study, we focus on almost overlooked effects coming from misrepresentation of the atmospheric boundary layer depth, Habl. We compare diurnal variations of the temperature biases in several meteorological models. The study discloses that the predicted temperature is frequently changing much less agile than the observed one. Narrowing our analysis to nocturnal temperature drops, the largest bias is almost exclusively found at the end of the cooling period. In order to explain this universal behavior in so different models, we look at the energy balance model with turbulent fluxes parametrized non-locally, i.e., through Habl. This approach was motivated by a strong but implicit link between Habl and fluxes incorporated in all turbulence closures through mixing length scale and stability correction functions.

We argue that coupling between Habl and fluxes must be relaxed if the surface air temperature bias is to be reduced, particularly in nocturnal conditions with strong surface cooling. We suggest that attempts to increase turbulent surface fluxes, as follows from the total turbulent energy theory by S. Zilitinkevich, would not lead to satisfactory results without such a decoupling in the turbulence closures. Finally, we extend our analysis to the fully operational numerical weather prediction model AROME-Arctic and demonstrate the effects of the boundary layer dynamics in a four-year case study over the Sodankylä supersite. 
Analysis of the dynamic of extreme rainfall events based on rain gauge measurement networks in Berlin, Germany in the context of wireless communication performance
Authors: Bart Frederik , Meier Fred , Scherer Dieter , Hellmann David
Published: June 2022

With the effects of the advancing climate change the intensity and frequency of extreme rainfall events in many regions of the world is likely to increase. Heavy rainfall has a significant impact on the propagation of electromagnetic waves during wireless data transmission, especially for higher frequency ranges above 10 GHz. For the development of future wireless communication technologies like Terahertz (THz) links, precise information about the development and characteristics of extreme rainfall events is essential, especially in urban regions where these new technologies are likely to be implemented. In this study we investigate the dynamic of heavy rainfall events in the city of Berlin and surrounding areas for the timeframe between 2011 and 2020. Stationary measurements and crowdsourcing data of the urban climate observatory network as well as the measurement network of the German Meteorological Service (Deutscher Wetterdienst, DWD) is statistically evaluated to characterize the intensity, duration, and spatiotemporal variability of extreme rainfall events. Furthermore, possible connections between rainfall and factors like land cover and topography are analyzed. The influence of the distance between individual measurement stations on these results is examined using auto correlations. The rainfall data will also be used for attenuation models based on recommendations of the International Telecommunications Union to evaluate the rain specific impact on wireless signal propagation. For this investigation several common frequency ranges for the 5th wireless communication standard (5G), as well as frequencies in the THz ranges (100 GHz to 10 THz), are used to allow for an assessment of the vulnerability of wireless communication networks in the area of Berlin. Furthermore, these results are used as a reference for similar evaluations with spatially and temporally resolved meteorological datasets including the Central Europe refined analysis generated with the weather research and forecasting model and the radar-based precipitation climatology data set by the DWD.
One- and Three-Dimensional radiative effects in shallow cumulus cloud fields: Large-Eddy Simulations and Observations
Authors: Wiltink Job , Veerman Menno , Maier Richard , van Heerwaarden Chiel , Jakub Fabian , Mayer Bernhard
Published: June 2022

Clouds strongly regulate how much radiation reaches the earth’s surface. Due to scattering and absorption processes within clouds, surface radiation can be highly variable both in space and time. Accurately capturing the high surface heterogeneity of solar radiation is important, for example for grid operators who need to ensure the safe ingestion of solar energy into the energy grid. In Numerical Weather Predictions and Large-Eddy-Simulations, radiation is often computed using one-dimensional radiative transfer, even though this can produce unrealistic surface irradiance fields. Applying three-dimensional radiative transfer is much more accurate because of the possibility of the horizontal transfer of radiation. However, applying three-dimensional radiative transfer in simulations is for most applications still too expensive.

In this study we investigated cloud-radiation interactions by applying either one-dimensional or three-dimensional radiative transfer using Large-Eddy-Simulations. The performance of the respective simulations were weighted against high quality surface observations from the Baseline Surface Radiation Network at Cabauw. We simulated/ observed a case representing a summer’s day in the Netherlands where shallow cumulus developed late in the morning and dissipated again later in the afternoon.

Simulations where one-dimensional radiative transfer was applied did not reproduce the observations well. Although being over a factor ten slower, simulations with three-dimensional radiative transfer applied did resemble observations much better. Still, for the simulations with three-dimensional radiative transfer the underestimation of diffuse radiation was considerable.   

To speed up the three-dimensional radiative transfer simulations we investigated an option that allowed the radiative transfer calculations to not fully converge. Using this incomplete solve option we found that biases in global radiation, sensible and latent heat remained smaller than for one-dimensional radiative transfer simulations, when we compared both to a fully solved three-dimensional radiative transfer run.   

With this work, we aimed to provide an insight into the relevance of three-dimensional radiative transfer application in shallow cumulus cloud fields emphasizing the need for further development of computationally efficient three-dimensional radiative transfer solvers in LES.
A comparison of the PurpleAir PA-II sensor to both regulatory particulate matter monitors and meteorological instrumentation in Asheville, North Carolina
Authors: Couzo Evan , Godfrey Christopher
Published: June 2022

Routine ambient air quality monitoring is mandated by U.S. federal law, but many regions of the U.S. are sparsely monitored due in part to the high cost of regulatory monitors.  Low-cost sensors can fill data gaps when it is neither feasible nor cost-effective to expand regulatory monitoring networks.  Initial comparisons of ambient measurements from the PurpleAir PA-II sensor – a low-cost (<$300 USD) and commercially available sensor that measures fine particulate matter (PM2.5) using a laser particle counter – with nearby (~2 km) regulatory PM2.5 monitors maintained by the Asheville Buncombe Air Quality Agency in Asheville, North Carolina, indicate general agreement.  Continuous data collection began in January 2022, thus capturing a range of atmospheric conditions and seasonal changes in PM2.5 concentrations.  High water vapor content is known to affect the performance of optical particle counters such as the PA-II, so additional summertime measurements may reveal persistent biases in air quality measurements in these conditions.

The PA-II sensor also measures temperature, relative humidity, and barometric pressure.  Preliminary analyses compare the sensor’s measurements of these environmental variables to co-located research-grade meteorological instrumentation, including Campbell Scientific, Inc. 107 and 109 temperature probes, a Vaisala HMP45C temperature and relative humidity probe, and a Vaisala PTB101B barometer. Results reveal an expected high temperature bias of several degrees Fahrenheit caused by the small amount of heat generated by the electronics contained in the PA-II’s housing. A low relative humidity bias is a consequence of the temperature performance. Barometric pressure measurements from the PA-II sensor are consistently high by about 2-3 hPa.
Preliminary results of a physical model for extrapolating the wind field over complex terrain
Authors: Michos Dimitrios , Kazantzidis Andreas , Catthoor Francky , Foussekis Dimitris
Published: June 2022

In complex terrain, wind power production depends not only on wind velocity but on wind direction too. Estimating such volatile variables is a difficult but essential task for the installation of a Wind Turbine (WT) and the operation of Wind Farm (WF). Our goal is to create a short term (5-15min) forecasting physical model when terrain complexity excludes measurements using long-range scanning lidars. In this study we will try to extrapolate the wind field over a wind farm with the use of steady state CFD simulations. Steady state RANS CFD simulations are extremely faster than time dependent ones (LES), which makes them fast enough for operational use, as well as for estimating wind flow over a wanted location for many different scenarios.

 

The computer used for the simulations has 24-cores and 128gb ram installed. The software used for the simulations is COMSOL Multiphysics. In this study, each steady state simulation represents 10 min averages and the computational time needed is below 2 min. The simulations were run for an area 2.5x2x0.6 km3 large with a non-uniform mesh and the distance between computational nodes ranging from 22,5 to 75.5m in the area of interest.

 

Wind measurements from a vertical Wind Profile LIDAR installed at CRES WF located at Lavrio (Greece), were used for the validation of the model. The terrain location is complex with a RIX index of 10%. Lidar measurements at 6 different heights (54 m, 78 m, 100 m, 120 m, 140 m, 160 m) were used as inlet conditions after being vertically extrapolated and interpolated, acknowledging the factors that govern lidar accuracy in complex. The inlet plane was positioned 1.3 km away from the LIDAR location. Horizontal homogeneity was assumed at inlet plane. The simulations were run at an expanded area to capture the effects of the terrain on wind movement, because of lack of more measurement locations.

 

Results from 291 simulations that were corrected with linear regression, were compared with data from the three WTs and the LIDAR. Extreme errors were detected when sudden changes in wind speed or direction were observed. The maximum mean absolute error (MAE) of wind velocity with respect to LIDAR measurements at all available heights is 0.28 m/s and the minimum is 0.17 m/s.  In addition, absolute errors are smaller than 0.7 m/s and maximum absolute percentage error is 11% for 95% of the estimations. The accuracy of the model increases with height because of the terrain anomalies and turbulence effects.
Sub-Hourly Precipitation Extremes in Mainland Portugal and downburst events
Authors: Belo-Pereira Margarida , Santos João , Pinto Paulo
Published: June 2022

Sub-hourly heavy precipitation events (SHHPs) frequently underlie major meteorological hazards. This study uses a 71-weather-station dataset for 2000–2020 to diagnose SHHPs corresponding to 10-minute precipitation events of at least 5.0 mm (above the 99th percentile of the precipitation days) and identify their associated synoptic-scale conditions, using a meridional pressure gradient (MPG index) defined on an hourly timescale. This index revealed two main synoptic-scale weather types: remote and regional low-pressure systems (RemL and RegL, respectively). RegL events show two pronounced maxima in spring and autumn, whereas RemL events have a single maximum in autumn. Moreover, RegL events are largely concentrated in the afternoon and evening, while RemL events are much more uniformly distributed during the day, despite some bias toward mid-day and early afternoon. These features suggest that RegL events tend to be thermally driven, whereas RemL events are associated with frontal systems.

Moreover, a preliminary linkage between the SHHPs and mesoscale convective systems is established by detecting sudden surface pressure surges, which are manifestations of mesohighs associated with downbursts. Finally, two case studies of downburst events are presented. The first event occurred on 23 December 2009 when a rapidly deepening extra-tropical cyclone crossed Mainland Portugal. During this event, several power towers were destroyed by downburst winds associated with a mesovortex, observed in a bow echo line triggered by an upper cold front.

The second event occurred on 17 June 2017 and contributed to the rapid spreading and intensification of unprecedented forest fires in Portugal, with the loss of many human lives. On 17 June, the distinctive markers of mesohighs, cold pools and the associated downbursts, were identified by weather stations and these signatures were also present in the AROME forecasts. These downbursts were caused by an MCS (visible in satellite images and radar reflectivity), which developed in an environment characterized by weak synoptic forcing, accompanied by moderate CAPE and an inverted V-profile, with a very warm and dry layer from the surface to 650 hPa, which is typical of hybrid downbursts.
Verification and updates of the ESA-CCI land cover product
Authors: Oswald Sandro , Samuelsson Patrick , Kurzeneva Ekaterina , Palmason Bolli
Published: June 2022

This talk introduces the initial actions within the EUMETNET/C-SRNWP project ‘Evaluation and updates of ESA-CCI global land cover map for NWP needs’. We present the coordination activities of the working group and the first steps verifying and updating the latest ESA-CCI land cover map of 2020. Hereby, we started a survey in June 2021 with all members of the C-SRNWP Surface Expert team to evaluate their needs and possible future plans related to the usage of the ESA-CCI land cover product. The results show a clear need for accurate water information and the distinction between fresh and salt water. In addition, the distinction between lakes and rivers would be a benefit. Hence, we tried to find an up-to-date and accurate global water mask as reference to replace existing water bodies in the ESA-CCI land cover with new classes for fresh and salt water. In this manner, we use the Open Street Map (OSM), which is open source with a high level of detail and is updated continually by a community of more than eight million members. In a second step, we tried to find an adequate platform where scientists can report their founded issues on the ESA-CCI land cover map. We consider the open source end-to-end software development platform Gitlab as a suitable environment where scientists can interact also through programming codes. As an outlook regarding the other outcome of the survey, the level of detail of the urban class requires improvements and has to be divided in more subclasses using as e.g. Local Climate Zones.
On the role of Ocean Mixed Layer and Sea Surface Temperature Anomaly in the genesis, intensification and evolution of the Mediterranean Tropical-Like cyclones “IANOS”.
Authors: Ricchi Antonio , Liguori Giovanni , Cavicchia Leone , Miglietta Mario Marcello , Bonaldo Davide , Carniel Sandro , Ferretti Rossella
Published: June 2022

Mediterranean basin could be occasionally it can be affected by tropical-like cyclonic phenomena. These are called out Mediterranean Tropical-Like Cyclones (TLC) or Medicanes. Their frequency is about 1.5 per year and they can reach category 1 intensities. Previous studies focusing could beon past TLCs events have found that SST play a fundamental role in modulating the intense air-sea exchange of latent and sensible heat fluxes, hence controlling both development and evolution of TLCs. However, given the connection between ocean mixed layer, ocean heat content and temperature, it is important to explore also the role of the mixed layer depth (MLD). In this study we investigated the role of both SST and MLD on genesis, intensification and evolution of a recent record-breaking TLC “IANOS”.  IANOS cyclone it originated over the southern Ionian Sea around 14 Sept 2020, moved over the Central Ionian Sea from south-west to North-East, and made landfall around 19 Sept 2020 over Greece mainland coast, reaching atmospheric pressure values of 984 hpa and wind intensity of over 120-130 km/h. It developed over a basin where a positive SST anomaly up to 4 °C was detected, which coincided with the sea area where it reached the maximum intensity. We conducted a series of experiments using an atmospheric model (WRF - Weather Research and Forecasting system) driven by underlying SST (standalone configuration) with daily update or coupled to a simple mixed-layer ocean model (SLAB ocean), with SST calculated at every time step using the SLAB ocean for a given value of the MLD. WRF was implemented with 3 km grid spacing, IFS Analysis (at 9km resolution), while SST or MLD initialization, for standalone or coupled runs, respectively, are provided by the MFS-CMEMs Copernicus dataset at 4 km of horizontal resolution. For the studied TLC, the mean MLD is modified by increasing or decreasing its depth by 10 m, 30 m, 50 m, 70 m, 100 m. At first the MLD thickness was characterized  for the days in which the cyclone developed using ocean modeling data. Then we identified possible past and future climatological scenarios of MLD thickness. Starting from these data, we simulated the impact of the MLD, and consequently of the Ocean Heat Content, on the TLC. The preliminary results show that the MLD influences not only the intensity of the cyclone but also the structure of the precipitation field both in terms of magnitude and location. The results deserve further investigation in particular in the content of climate change scenarios.
Climatological Heat Waves in Norway -  a base for Operational Warning System
Authors: Tilley Tajet Helga Therese , Sagen Stine , Agersten Solfrid , Hygen Hans Olav , Gangstø Skaland Reidun , Lussana Cristian , Brox Nilsen Irene , Smits John
Published: June 2022

With increasing temperatures in Norway, the possibility of heat waves are assumed to increase. The Norwegian Meteorological Institute (MET Norway) is testing ways to monitor heat waves  and possibly implement an operational warning system for heat waves in the future. For this work, it was necessary to assess the development of observed heat waves in Norway.

Heat waves were computed from daily minimum and maximum temperatures for the period 1961-2020, for three example stations and maps. For the stations, time series were assessed. For the maps, an observation-based dataset on a 1×1 km grid was used. The two different normal periods 1961-1990 and 1991-2020 were also compared.

The method to qualify a heat wave determines the number of heat waves in a given summer. There are different methods used internationally. MET Norway wants to find a method that works for Norway, and maybe in cooperation with surrounding countries. The last couple of years we have had the same criterias as used in Denmark; the mean value of maximum temperature of three consecutive days ≥ 28 degrees. In this study we have looked at different methods to qualify a heat wave in Norway, since the Danish method indicated heat waves too frequently, also during the spring. The method for heat waves is based on the maximum and minimum temperature combined. We have looked at different temperature limits and different number of days. For other weather warnings, a 2 years return period is used for a yellow warning. When testing different methods, we found that the mean value of maximum temperature for 5 days ≥ 28 degrees combined with the mean value of minimum temperature for 5 days ≥ 16 degrees were likely to occur seldom enough and also give some heat stress to people and nature.

Climate services has worked together with the forecasting group at MET Norway to propose a method to use for both forecasting and climatology. This summer (2022) the heat wave monitoring system will be tested operationally, and an evaluation is due in the autumn.
Conditioned Forecasting Model based on Self-Supervised Learning
Authors: An Sojung , Oh Tae-Jin , Na Inchae , Jang Jiyeon , Park Wooyeon , Kim Sang-Wook , Noh Ilseok , Kim Junghan
Published: June 2022

In order to capture spatio-temporal characteristics of precipitation process in machine learning context, many studies applied convolutional and recurrent neural networks. Many state-of-the-art approaches focused on learning a single latent representation of the quantitative precipitation forecast (QPF). To describe reflectivity echoes with a single latent variable may be an overly restrictive assumption, impeding effective learning of the precipitation features. Therefore, we propose a conditioned forecasting model based on self-supervised learning (SSL), that generalizes diverse precipitation types which would enable various latent representations. Our method trains each latent variables according to a condition that is approximated with a generative adversarial network (GAN). Specifically, the model is pre-trained by the same condition for retaining consistency of latent space while training the generator features. The feature matrix of the generator is clustered every 100 epoch based on Principal Component Analysis (PCA) and k-means clustering. Korean summer (JJA) precipitation with 4km resolution from 2012 to 2021 is used as the dataset which is converted from radar reflectivity of Constant Altitude Plan Position Indicator (CAPPI) to rainfall intensity. A sample consists of 18 time series of 10 minute intervals. The dataset is splitted into 2012 to 2020 as training set and 2021 as test set. Overall, it contains 9,048 sequences for training and 729 sequences for testing. Results show that our method improved generalization of precipitation features as it showed comparable or better performance compared to previous studies in terms of critical success index (CSI) score up to 2 hours prediction. Our SSL method can train useful representations from unlabeled precipitation data and effectively predicts complicated echo patterns. We also found that training GANs by clustering the generator features more than sixteen condition types is much easier to solve mode collapse where many GAN models suffer from.
Digitizing observations of precipitation and temperature extremes from the meteorological reports of the Royal Meteorological Institute (1881-1900)  by volunteer citizen scientists.
Authors: Ingels Romain , Journée Michel
Published: June 2022

Data repositories and archives play a critical role as source for observational data used in the study of past weather events and climate. Therefore, data storage is the first and essential step in the process of making the data usable. The Royal Meteorological Institute (RMI) has been digitizing its archives in image scan format for several years now, thanks to BELSPO's national DIGIT programme, in order to save them. This represents a significant amount of data that can be made available as soon as it has been encoded in a way that can be easily used by everyone. In terms of human resources, it would take a lot of time and people to carry out such a task. This is why RMI is going to launch a first campaign of keying by volunteers of its archives of climate bulletins from 1881 to 1900 via the Zooniverse platform. For this campaign, volunteers will be asked to encode daily precipitation and extreme temperature data. Zooniverse provides a popular way of developing citizen science projects. Using their Project Builder interface, a custom website was created to enable volunteers to transcribe the data from the images.

This first campaign will assess the usefulness and reliability of the results collected through volunteer participation. The focus will be on the design of the encoding page, the feedback from volunteers on the tool provided, the quality of the results but also the popularity of such a process. An analysis of the results will be carried out to assess whether RMI will carry out other campaigns in the future on a wider range of climate parameters.
Impact of climate change on wintertime persistent inversions in the Grenoble valley during the 21st century
Authors: Bacer Sara , Beaumet Julien , Le Bouëdec Enzo , Ménégoz Martin , Gallée Hubert , Staquet Chantal
Published: June 2022

When anticyclonic conditions persist over mountainous regions, inversion layers can develop in the valleys and persist from a few days to a few weeks, especially in winter. During inversion episodes, the atmosphere inside the valley is stable and vertical mixing is prevented, promoting the accumulation of pollutants below the inversion layer and affecting the air quality of the valley.

Mountainous areas are experiencing a warming rate twice stronger than the global atmospheric temperature, thus, they are particularly sensitive to climate change. In the 21st century, the valley circulation will undergo unknown modifications due to climate change, and this concerns also the fate of wintertime persistent inversions, which could be reinforced or weakened with consequences on pollutant trapping.

This work addresses the issue of climate change impact on persistent inversions in the Grenoble valley, which is the most populated city in the Alps. The long-term projections of the regional climate model MAR (Modéle Atmosphérique Régional) forced by the global climate model MPI (developed by the Max Planck Institute) are first used to perform a statistical study of the inversions over the 21st century. The main characteristics of the inversions, e.g. duration, frequency, intensity, and their trends, are investigated for two different scenarios (SSP2-4.5 and SSP5-8.5). The intensity and the frequency of the inversions show a statistically significant decreasing trend in the 21st century for the worst-case scenario.

The detailed structure of the inversion (atmospheric circulation, vertical temperature profiles, and inversion top) is next investigated by comparing two persistent episodes in the past and around 2050. For this purpose, the WRF (Weather Research and Forecasting) model, forced by MAR, is used at high resolution (111 m). In order to perform a fair comparison of the episodes, and given the influence of the orography on the valley circulation, the episodes are selected in such a way to satisfy common large-scale characteristics of a wintertime anticyclonic regime over Grenoble.
Assessment of extreme winds over Europe in Regional Climate Models
Authors: Outten Stephen , Sobolowski Stefan
Published: June 2022

Every year, extreme wind events cause a great deal of financial losses across Europe. As such, the accurate projection of the changes in extreme winds will be invaluable for many industries, including insurance, construction, energy, and afforestation. Adaptation planning requires the estimation of how the magnitude and frequency of extreme events, such as extreme winds, will vary in the future.

Extreme winds are examined in a selection of Euro-CORDEX downscalings. Since these include multiple downscalings of the same global climate models by different regional climate models, it is possible to intercompare how different models represent extreme winds. The peaks-over-threshold approach is used identify the extreme events based on the fitted Generalized Pareto Distributions (GPD), and maps of 30-year return winds for all locations over Europe are presented. Future changes in the frequency of extreme winds are assessed for Northern, Central, and Sothern Europe for three future periods, being the near, mid, and end of this century. The results show that the frequency of extreme wind events will increase from one period to the next over the 21st century in all three regions of Europe.

The results of the recently published study will be presented in detail along with a brief overview of the statistical methods employed. Our ongoing work to create a comprehensive dataset of assessed extreme winds and precipitation will also be addressed. Time permitting, we will present evidence of the benefits of downscaling, an assessment of how the base period length affects the uncertainties, and a brief comparison of the different methods commonly employed to assess uncertainties.
The effect of the CORINE land cover class application at mid-resolution WRF simulations on urban heat island
Authors: Zempléni Zsuzsanna , Varga Ákos János , Breuer Hajnalka
Published: June 2022

The CORINE land cover dataset provides a more realistic dataset for various scientific applications. In this study we incorporated almost all (38 instead of the original 44 classes, as water classes are not dividable in the WRF routines) CORINE classes to the WRF model and created 1-year long 5 km resolution simulations to check its effects. The simulated area covers the Central European region.

On a closer look, compared to the USGS dataset the first observable differences are the decreased number of non-irrigated croplands that are described as forests. The secondary difference comes in the coverage of urban areas. In some cases, a city previously covered by 2 grid points are now covered by 20, which causes a more pronounced urban heat island (UHI) effect.

Our goal is to analyse the effect of land cover differences on urban heat island intensity by only relying on the NoahMP provided heat flux calculations. For regional climate simulations the application of urban parameterisation could be more computationally demanding. Therefore, we try to assess the feasibility of UHI analysis at such a scale without urban parameterisation.

Urban areas are selected similarly to radar cell tracking, fitting a circle around the urban land cover classes and the rural regions are selected from a double size circle radius if there are no large altitude differences between the urban average altitude and the rural grid point. According to the preliminary results an annual average 1.5 °C UHI can be simulated without urban parameterisation. Principal component analysis shows that the main driver of the UHI is the annual variation of leaf area index in the rural regions. The secondary driver is either the precipitation or the snow cover, depending on the spring and wintertime weather.
Detecting changes in the Western Mediterranean cyclones
Authors: Dolgos Emília , Pongrácz Rita , Bartholy Judit
Published: June 2022

Mid-latitude cyclones form an essential part of large-scale atmospheric circulation pattern, and their evolution, intensity, trajectory, and associated weather events (e.g., extreme precipitation, consequent floods, etc.) are all important from a local/regional point of view. In this study, we focus on the Mediterranean region where mid-latitude cyclones are fundamental factors in the weather and climate conditions in the region. Since the Mediterranean region is considered as one of the most vulnerable areas to climate change, this region calls for special attention. To mitigate the effects of future climate change and to develop suitable adaptation strategies it is necessary to have a clear and detailed understanding of Mediterranean cyclones and their characteristics. For this purpose, we selected the western part of the Mediterranean region as our study area. For this target area, we use ECMWF reanalysis data and the historical simulations of global climate models from the CMIP6 project. We started the statistical climatological analysis with locating the potential areas of low pressure systems in the region. Validation is carried out by the comparison between the results of reanalysis and CMIP6-simulation data. Frequency, intensity, and duration changes are assessed. For the analysis, mean sea level pressure and precipitation are considered from 1901 to 2020, with 6-hour temporal resolution and as daily amounts, respectively, in the western Mediterranean region and its vicinity. The study continues with the evaluation of future trends based on different climate scenarios (RCP and/or SSP scenarios upon availability), which represent different anthropogenic impacts and mitigation efforts. The results can serve as valuable input for impact modelers to further detailed analysis, and for decision makers and stakeholders to consider future projected climatic conditions when building the long-term strategies of their specific sectors.
Enhancement of quality in climate services – development of a formative evaluation scheme for co-creation processes
Authors: Keup-Thiel Elke , Bathiany Sebastian , Dressel Markus , El Zohbi Juliane , Rechid Diana , Schuck-Zöller Susanne , Suhari Mirko , Timm Esther
Published: June 2022

National and international climate services support adaptation to climate change. Climate services should aim to deliver climate service products, which are useable, useful, accurate and suitable for users. Good practices for the design of climate services include transdisciplinary approaches and co-creation of climate service products.

The advancement of effective adaptation measures to climate change requires continuous interactions between climate service providers and users of the products. To assess the effectiveness of this co-creation endeavours evaluation is crucial. At present, output and outcome assessments are conducted occasionally in the climate services research field but they are performed ex-post and do not help to adjust the ongoing process of co-creation.

Thus, the focus of the presented work is on the formative evaluation of the co-creative development of science-based climate service products. It is done during the run-time of a project with the intention to reflect and readjust the processes. To find the related evaluation criteria, we analysed in detail the process of co-creation of climate service products in the knowledge transfer project ADAPTER (ADAPT tERrestrial systems, https://adapter-projekt.org/). In ADAPTER, simulation-based climate service products have been developed together with key partners and practitioners from the agricultural sector, to support decision-making in the context of climate change adaptation.

Starting with the empirical identification of the main characteristics of the product development process, six sub-processes were determined. Then, questions for a formative evaluation were assigned to the different steps and sub-processes. Finally, a literature review on quality criteria in transdisciplinary research delivered additional qualitative aspects and served as theoretical basis. As a result, a scheme of quality criteria and related assessment questions for the different sub-processes in climate service development was created, based on both empirical and theoretical work. Of course, this formative evaluation scheme needs validation and testing but, at least, will be particularly helpful to reflect on and to improve the co-creation processes in climate services and enhance their quality.
Evaluation and Improvement of Arctic Forecast: Data Assimilation of MOSAiC Expedition Data for SynopSys Project
Authors: Paschalidi Zoi , Cress Alexander , Jaiser Ralf , Rinke Annette , You Cheng , Handorf Dörthe , Monsees Falco , Weber Mark , Rozanov Alexey
Published: June 2022

The accurate and precise weather information in polar region have proved to be essential for the global weather and climate research. However, even though we leave in the ‘golden age’ of earth observations, there is a lack of in-situ observation coverage in the polar regions. Additionally, the use of radiances measured from polar-orbiting satellites is of limited use due to the difficulties using those kind of data over ice and snow. The major research expedition in Arctic, MOSAiC (Multidisciplinary drifting Observatory of Arctic Climate), managed to shed light on polar conditions with the collection of a huge variety of highly resolved data.

The SynopSys Project (Synoptic events during MOSAiC and their Forecast Reliability in the Troposhere-Stratosphere System) is a collaboration of the German Weather Service (DWD) with the Alfred-Wegener Institute (AWI) and the University of Bremen. The project aims to combine the state-of-the-art weather observations from the MOSAiC Expedition together with remote sensing products and meteorological forecast in order to identify and study synoptic events in the Arctic.

The current work focuses on the evaluation and improvement of the weather forecasting capabilities of ICON-NWP model in Arctic. In this frame, the latest version of the global model ICON is employed to assimilate the different kind MOSAiC data – from synoptic station data to ascending and descending radiosondes. On the one hand, a series of sensitivity studies has taken place to evaluate the different observation systems and identify the ones with the highest influence on the arctic model forecast. The improvement of the weather forecast itself and the weather analysis because of the assimilation of the project data is studied on the other hand, as well as their influence on the weather forecast of the mid-latitudes. The experiment period covers March and April 2020, which is of high meteorological interest, due to the observed day-to-day variability – a cold period at the beginning of the month was followed by strong warm air intrusion, challenging the model forecast and analysis performance.
Data Assimilation of visible and infrared cloud observations from pictures
Authors: Reinhardt Maria , Kurzrock Frederik , Acevedo Walter , Potthast Roland
Published: June 2022

We present an innovational way of assimilating visible and infrared observations of clouds into the weather forecasting model for regional scale: ICON-D2 (ICOsahedral Nonhydrostatic), which is operated by the German Weather Service (Deutscher Wetterdienst, DWD). For the visible camera photographs, a convolutional neural network is trained to detect clouds in pictures. The result is a greyscale picture, in which each pixel has a value between 0 and 1, describing the probability of the pixel belonging to a cloud. By averaging over a certain section of the picture one gets a value for the cloud cover of that region. To build the forward operator, which maps an ICON model state into the observation space, a three dimensional grid in space from the camera point of view had to be constructed and the ICON model variables were interpolated onto this grid. The pixels of the picture are modeled as rays, originating at the camera location and the maximum interpolated cloud cover (CLC) along each ray is taken as a model equivalent for each pixel. CLC is a diagnostic variable of an ICON model state describing the probability of the cloud coverage within the respective grid box. After superobbing, monitoring experiments have been conducted to compare the observations and model equivalents over time. The results of these experiments look promising with RMSE values below 0.32 and we continued by performing single assimilation steps as well longer experiments. 
For assimilating the infrared camera pictures we use a forward operator created by Leonhard Scheck at LMU Munich which provides a fast solution for the radiative transfer equations. Monitoring experiments as well as Data Assimilation experiments were conducted and will be presented. 
The transition from practical to intrinsic predictability of midlatitude weather
Authors: Selz Tobias , Riemer Michael , Craig George
Published: June 2022

This study investigates the transition from current practical predictability of midlatitude weather to its intrinsic limit. For this purpose, estimates of the current initial condition uncertainty of 12 real cases taken from ECMWF's ensemble of data assimilations system are reduced in several steps from 100% to 0.1%. They are propagated in time with a global numerical weather prediction model (ICON at 40 km resolution) that is extended by a stochastic convection scheme to better represent error growth from unresolved motions. With the provision that the perfect model assumption is sufficiently valid, it is found that the potential forecast improvement that could be obtained by perfecting the initial conditions is 4-5 days. This improvement is essentially achieved with an initial condition uncertainty reduction by 90% relative to current conditions, at which point the dominant error growth mechanism changes: With respect to physical processes, a transition occurs from rotationally-driven initial error growth to error growth dominated by latent heat release in convection and due to the divergent component of the flow. With respect to spatial scales, a transition from large-scale up-amplitude error growth to a very rapid initial error growth on small scales is found. Reference experiments with a deterministic convection scheme show a 5-10% longer predictability, but only if the initial condition uncertainty is small. These results confirm that planetary-scale predictability is intrinsically limited by rapid error growth due to latent heat release in clouds through an upscale-interaction process, while this interaction process is unimportant on average for current levels of initial condition uncertainty.
The role of the stratosphere in teleconnections arising from slow and fast MJO episodes
Authors: Yadav Priyanka , Domeisen Daniela , Garfinkel Chaim
Published: June 2022

The Madden-Julian Oscillation (MJO) influences the North Atlantic region on timescales of days to weeks. The extratropical response has been found to depend on the propagation speed of the MJO in the region of the Indian to the Pacific ocean: Here, we define slow (fast) MJO events as events that take more (less) than 16 (10) days to propagate from the Indian Ocean (phase 3) to the Pacific Ocean (phase 6), and the MJO amplitude has to be greater than 1 for at least 3 consecutive days in phase 3 and phase 6. Slowly propagating MJO events lead to a stronger North Atlantic Oscillation (NAO) response than fast MJO events, and the positive (negative) NAO response for slow events occurs after a lag of 10 days following phase 4 (phases 7-8). The increased persistence of the tropical thermal forcing in slow events may contribute to a stronger extratropical response.

Furthermore, the MJO can influence the strength of the stratospheric polar vortex, which in turn can impact the NAO via downward coupling. While the tropospheric pathway for teleconnections from MJO events with varying phase speed is well understood, the stratospheric pathways for MJO events of different propagation speeds has not yet been explored.

In this study, we discuss the stratospheric pathways during fast and slow MJO episodes using reanalysis data with respect to the strength of the Northern Hemisphere stratospheric polar vortex and subsequent downward coupling to the troposphere. The results suggest that the stratosphere plays an important role in generating a strong NAO response during slowly propagating MJO episodes.
Climate change-induced jet variability over the North Atlantic: Trends and drivers
Authors: Hermoso Alejandro , Schemm Sebastian
Published: June 2022

Extreme weather in midlatitudes is strongly associated with extratropical cyclones, which propagate within preferred latitudinal bands known as the storm tracks. The position, orientation and intensity of storm tracks make a key contribution to regional climate variability and change. Therefore, understanding changes in storm track location and dynamics under the influence of anthropogenic climate change is crucial for quantifying the socioeconomic risks posed by their associated extreme events.

Deep tropospheric jets, which affect the entire depth of the troposphere are typically present over storm tracks and understanding their interactions and symbiotic life cycle is essential for quantifying trends and variability in regional climate in all regions affected by storm tracks. In this work, we analyse modifications in deep jet characteristics forced by anthropogenic climate change over the North Atlantic sector during the winter season (December-February) by using ERA5 reanalysis data and Community Earth System Model (CESM) simulations for historical and future periods.

Firstly, deep jets are separated into three regimes (southern, medium and northern) defined by different latitudinal positions and life cycle characteristics, such as Rossby wave breaking (RWB) type. Next, forced changes in regime frequency and life cycles are identified by applying machine learning techniques aimed at distinguishing anthropogenic forcing from natural variability. Further, the goal is to quantify the role of additional drivers, such as the Artic amplification, tropical amplification, polar stratospheric vortex or variations in El Niño Southern Oscillation for the observed change in jet regimes.

Preliminary analyses based on ERA5 indicate an increasing preference for cyclonic RWB and southern jet regimes, which favour the development of explosive cyclones. In contrast, anticyclonic RWBs, which are favoured in the northern regime and are linked to the presence of potential vorticity streamers and heavy precipitation over western Europe, tend to become less frequent.