bluuebunny/crossref_metadata_2025 huggingface dataset:
ML-based prediction of storm properties using KONRAD3D cell objects, lightning data, and environment conditions from NWP
Authors: Berndt Christian , Schultze Markus
Published: July 2023

Object-based cell detection and tracking algorithms provide a useful tool for analyzing current and past storm properties and movement. KONRAD3D, an algorithm which recently became operational at DWD, uses radar scans of different elevation angles to derive 3-dimensional cell objects with specific properties.  Nowcasting of storm position by displacing it using the current cell movement seems to be straightforward, however, predicting the life cycle or specific storm properties such as lifetime, maximum future severity, and hail occurrence and size is difficult. We aim at analyzing the potential of machine learning techniques (ML), in particular random forest and gradient boosting, to provide these predictions using KONRAD3D cell properties in combination with NWP and lightning activity data.
We perform a recalculation of KONRAD3D for a 6-year time period, where we considered several other data sources to compute specific storm environment and attributes. For instance, NWP data from the ICON-EU model is used to characterize the convective environment, while lightning data is used quantify electrical activity. Next, we filter resulting storm detections regarding our three prediction tasks using ML:
(1) Maximum expected future cell severity: all storms are considered.
(2) Longevity of quasi-stationary cells: only storms with a minimum speed below a threshold are considered.
(3) Hail size: all storms are considered.
For tasks 1 and 2, we analyze the prediction performance for different storm ages, i.e. cell attributes at initial detection, after 15 min, and 30 min during the life cycle are used as predictors for ML. Maximum hail size (task 3) is estimated using individual cell detections. In order to achieve a final comparison of methods, we perform a 10-fold cross validation
Longevity of quasi-stationary storm events is difficult to predict since there many events with a short duration and only very few with a long duration. The distribution of maximum expected severity is less skew and therefore prediction scores are better. Random forest and gradient boosting are preferred over artificial neural networks, since decision tree methods are easier and faster to train and also provide better cross validation scores. In case of maximum future severity, a substantial improvement compared to a simple persistence forecast is achieved. ML-based prediction of maximum hail size delivers reasonable results and is able to outperform classical methods, such as MESH. However, prediction uncertainty remains high in most cases and needs to be quantified in order to generate meaningful predictions.
Simulating wind turbine interactions with low-level jet using a meso-to-micro downscaling approach
Authors: Bui Hai , Bakhoday-Paskyabi Mostafa
Published: July 2023

This study presents a high-resolution simulation of a low-level jet (LLJ) with explicit representation of wind turbines using the Weather Research and Forecast (WRF) model and the newly-developed Simple Actuator Disk model for Large Eddy Simulation (SADLES). LLJs are low-level wind maxima that can impact the power output and structural loads of turbines. Therefore, accurate prediction of the LLJ is essential for wind energy planning and management. The meso-to-micro downscaling approach is used to capture the LLJ dynamics, which involves nested domains with increasing spatial resolution from the mesoscale to the microscale. The WRF model is configured with five nested domains: mesoscale domains with grid spacing of 9 km, 3 km, and 1 km to capture the general dynamics structure of the LLJ, and two micro domains with grid spacing of 200 m and 40 m with large eddy simulation (LES) configuration. The SADLES model is used in the 40-m domain to enable the interaction between the LLJ and the wind turbines of the Alpha Ventus wind farm located in the North Sea. The simulation results are verified against observations at the FINO1 mast stations, including cup anemometers at various heights and LiDAR wind profiles. The WRF-SADLES system captures the LLJ dynamics and the interactions of turbines on the LLJ. The LLJ is well-reproduced in terms of its intensity, depth, and spatial extent, and the wakes of individual turbines are explicitly captured, significantly impacting the LLJ. The study provides insights into the LLJ dynamics and turbine-wake interactions, which can inform wind energy planning and management.
Probabilisitic road temperature forecasting using machine learning techniques – comparison of a multi-model approach in the Austrian Alps
Authors: Schicker Irene , Dabernig Markus , Kann Alexander , Meingast Maria
Published: July 2023

Road weather conditions, especially road temperature, have a major impact on road safety even more so in case of unusual early/late snow events leading to damages to logistic infrastructure, road infrastructure, and fatalities. Road maintenance services use meteorological forecasts as well as targeted road temperature and precipitation forecast to estimate when, where, and how often they have to treat roads before and during such events happen and rely, thus, on accurate and targeted predictions.
Numerical weather prediction models are able to provide a good guesstimate but still lack the detail, temporal and spatial resolution, which is needed especially in regions with rugged terrain. Here, we take a two-fold approach in (i) implementing different post-processing methods, deterministic and probabilistic, and (ii) evaluate the skills of the separate models and a combined multi-model ensemble approach. Furthermore, simplistic transfer learning approaches are implemented to test the models’ skills in unobserved areas. For step (i) the following methods are used: (a) multilinear regression, (b) Kalman filtering, (c) random forest, (d) a feed forward neural network, (e) a transformer neural network, (f) the EMOS model, and (g) the Metro model.
Two Austrian regions are considered here, namely Tyrol and the state of Salzburg. Results for these regions show that the simplistic transfer learning approaches are only in a few cases better than a temperature height correction approach. The Kalman filter results show that a careful parameter selection is needed to achieve good results. They rely, too, on onsite measurements and cannot be applied to regions with no measurements. All other methods are able to improve the raw NWP forecasts indicating that overall a mix of method is better suitable than relying on one single method (deterministic/probabilistic).
eWaterCycle as a modelling interface between meteorology and hydrology
Authors: Kalverla Peter C. , Verhoeven Stefan , Schilperoort Bart , Alidoost Sarah , Liu Yang , Drost Niels , Aerts Jerom , Hut Rolf
Published: July 2023

In our digital age, connecting models and data from various components of the earth system becomes more and more important. To this end, it is important to define standards and interfaces facilitate such integration. Here, we present the approach we took for eWaterCycle [1].
eWaterCycle is a fully Open Source system designed explicitly to advance the state of Open and FAIR hydrological modelling. It gives users access to a centralized platform where they can perform hydrological experiments. Complete with data, a suite of models, an interactive scripting environment, and a graphical explorer to quickly setup an experiment.
Hydrological models vary in programming language, their setup and configuration. They require differently defined inputs, and do not have a standard form of output. This makes it challenging to compare and exchange models and their inputs and output. eWaterCycle aims to solve this, so scientists can build upon each other’s work and focus on scientific questions instead of technical details.
Inside eWaterCycle, models are wrapped in a Basic Model Interface and live in their own isolated containers. We developed grpc4bmi  to enable communication with models inside their containers. This means that you can talk to different models, written in a range of programming languages, in a standardized way. ESMValTool is used to generate the meteorological forcing data with reproducible recipes. Discharge observations from the USGS and GRDC are available to validate the models.
The platform comes with comprehensive documentation, including a suite of example notebooks. It also includes setup instructions for system administrators and guidance for incorporating new models. The interface between meteorology and hydrology is most prominent in the forcing generation module. Beyond that, the standards and technology used for the hydrological models in eWaterCycle can be extended to other components of the land-atmosphere continuum.
[1] https://doi.org/10.5194/gmd-15-5371-2022
Measurement uncertainties of scanning microwave radiometers and their influence on temperature profiling
Authors: Böck Tobias , Pospichal Bernhard , Löhnert Ulrich
Published: July 2023

Ground-based microwave radiometers (MWRs) operating in the K-band and V-band frequency ranges (22 – 32 GHz and 51 – 58 GHz) are increasingly used for acquiring temperature profiles (T) and coarse humidity profiles (H) of the troposphere. These instruments measure microwave radiances, expressed as brightness temperatures (TB), in zenith and other angles over a region with a radius of approximately 10 km. Those measured TBs are used to derive profiles. Ground-based MWRs are also highly reliable instruments for measuring integrated water vapor (IWV) and liquid water path (LWP), with uncertainties below 0.5 kg/m2 and 20 g/m2, respectively. Zenith observations provide these variables with high temporal resolution (up to 1 second), while elevation scans offer the capability to obtain more precise temperature profiles close to the surface and evaluate horizontal water vapor and cloud inhomogeneities.Two years ago, the E-PROFILE program has initiated a business case proposal that was accepted by EUMETNET to offer continuous MWR data to the European meteorological services for boundary layer monitoring and assimilation in numerical weather prediction (NWP) models. Additionally, the European Research Infrastructure for the observation of Aerosol, Clouds, and Trace gases ACTRIS and the European COST action PROBE (PROfiling the atmospheric Boundary layer at European scale) are presently committed to establishing continent-wide quality and observation standards for MWR networks for research and NWP applications.For all that it is important to provide an estimate of all the uncertainties of scanning MWR measurements. When installing a MWR, it has to be kept in mind that measurement uncertainties due to the instrument setup and originating from external sources can have an impact on observations and the quality of the obtained atmospheric profiles. Therefore, identifying and coping with these kinds of errors is one important part of the quality control, especially while searching for a suitable measurement location with minimum disturbances. We will present the impact of the following measurement uncertainties – namely (1) physical obstacles in line of sight of the instrument, (2) pointing errors or a tilt of the instrument, (3) horizontal inhomogeneities of the atmosphere, and (4) radio frequency interference (RFI) – and give recommendations on how to set-up a MWR accordingly.
Characterisation and temporal evolution (1915-2022) of drought and pluvial periods in Catalonia
Authors: Altava-Ortiz Vicent , Barnolas Mercè , Barrera-Escoda Antoni
Published: July 2023

Catalonia is currently affected by a severe drought episode which is reporting unrecorded impacts in most part of the country. It is well known that precipitation presents a high temporal variability in the Mediterranean climate. Consequently, drought episodes are frequent, and they are an intrinsic characteristic of this type of climate. However, drought events are showing a higher frequency during the last few decades.
In this work we have studied drought and pluvial episodes derived from the calculation of the Standardized Precipitation Index (SPI) in Catalonia during the instrumental period 1915-2022. Series of precipitation aggregated at 12 and 72 months, lead to a first approximation for temporal variability of drought and pluvial events at high and low frequency, respectively. From the temporal evolution of the SPI-12, it is derived that the frequency of dry(wet) episodes has increased(decreased) in recent decades (statistically significant). This behaviour is observed in all Catalan hydrological catchments. The increase in the drought frequency is also corroborated when analysing the SPI-72 dry/wet area time series. The SPI-72 signal also reveals that the natural transition between pluvial and drought periods (and vice versa) has been broken since the 1980s, with domination of droughts since then. From the total number of drought episodes, two of them emerge: the 2004-2008 event and the current 2021-2023 drought episode. Depending on the analysed basin, one of these events can be considered the most severe one ever recorded in Catalonia since 1915.
In fact, the severity of the current event has motivated the creation of a new drought severity index (DSI), which considers the pick, mean intensity, duration and extension of the drought area. In the context of climate change, this index is called to be useful to rank future drought episodes when compared with historical ones.      
Katabatic winds and polynya activity in Terra Nova Bay during winter seasons in the period 1995-2022
Authors: Fusco Giannetta , Aulicino Giuseppe , Capozzi Vincenzo , Cotroneo Yuri , Esposito Massimiliano , Budillon Giorgio
Published: July 2023

Terra Nova Bay (TNB), in the Ross Sea, is characterized by the presence of persistent ice-free areas during the austral winter, known as polynyas. TNB polynya markedly influences air-sea dynamics and physical oceanography in that region as a major sea ice and salt “factories”, maintained by strong persistent katabatic winds. The role of TNB polynya is important in the formation of High Salinity Shelf Water (HSSW), the densest water mass of the Southern Ocean, occurring during sea ice production that increases the salinity of the subsurface water. The aim of this study is to investigate the processes that occur in the TNB coastal polynya and the role of the air-sea interactions in the determination of its opening and activity. First of all, we analysed the role of the katabatic winds, that are widely recognized to be one of the most relevant meteorological features of Antarctica continental margins. The genesis of these winds can be ascribed to the cooling of the near-surface air on the Antarctic Plateau, which determines a strong pressure gradient force downslope. The topographic forcing provides a strong direction consistency to such winds and can cause strengthening in wind speed near steep-sloped coasts. The impact of katabatic winds has been evaluated analyzing the in-situ meteorological data collected in Terra Nova Bay in the framework of the MeteoClimatological Observatory of Italian National Research Antarctic Program (PNRA). We studied the polynya response to the wind forcing and the katabatic regime, establishing subjective criteria to distinguish these strong and persistent winds from a normal wind’s intensification, and find the moments of distribution of katabatic events over the years from 1995 to 2022 examined during the austral winter season (April to October). The characterization of the detected event has been performed through the following indicators, the duration (DUR), the Severity (SEV) and Intensity (INT). Subsequently, we have computed the frequency (FRE, which is the number of events) and the average DUR, SEV and INT of the events belonging to every single year of the 1995-2022 period. In the second step the open water fractions, detected by the Ice Surface Temperature (IST) imagery derived from the MODIS data, were used to estimate the opening and the activity of the polynya during the winter seasons. Then, we estimated the surface heat budget between ocean and atmosphere, which can be assumed to result directly in ice production considering that ocean column is at its freezing point. Assuming that ice production rate depends on the net heat flux and on the polynya extension, it is possible to calculate the total production of salt released during sea ice formation and HSSW volume.
Rain, sleet and snow under global warming at Norwegian tourist destinations
Authors: Heiberg Hanne , Kuya Elinah Khasandi , Hanssen-Bauer Inger , Mayer Stephanie
Published: July 2023

Snow is an essential aspect of skiing-based tourism, making it crucial for practitioners within the tourist industry to understand future snow conditions at different altitudes within their regions. However, despite an increase in the availability of climate change information on websites, such as the IPCC WGI Interactive Atlas, the spatial resolution and systematic errors in these products can limit their usefulness for practitioners.
To address these limitations, the ClimTour project has utilized post-processed data from Euro cordex to create maps showing projected future rain-, sleet-, and snowfall for the entire Norwegian mainland. These maps also show the distributions of rain, sleet, and snow at different altitudes in areas around selected tourist destinations. The project examined changes in the number of precipitation days and the average precipitation amount per precipitation day, as well as a combination of both factors, to determine changes in precipitation. The calculations were done on an annual basis as well as for winter (DJF) and spring (MAM).
By comparing coastal and inland areas at high and low altitudes, the project aimed to determine where and when snow will disappear. The results showed that the largest changes in the number of days with snow will occur along the coast in the north, while changes will be smaller along the coast in the south, where there are already quite a few snow days, and in mountainous areas, where temperatures remain below zero in winter. The percentage of snow will decrease the most along the coast, where it will become rare in some areas, and least in inner Finnmark and generally in mountainous areas.
Understanding these projections can help practitioners within the tourist industry plan for the future and adapt their businesses to changing snow conditions. Overall, the ClimTour project provides valuable information for the skiing-based tourism industry in Norway.
Freshwater paradox: will saving of water help in mitigating climate change or increase the instability of the hydrological cycle?
Authors: Báder László , Szilágyi József , Négyesi Klaudia
Published: July 2023

The series of severe droughts in Europe from the beginning of this century may have a root cause to which we do not pay enough attention. The key function of the water cycle - energy, and water distribution - is directly influenced by climate change. Analyzing the trends of ERA5-Land gridded meteorological data for Central-Europe confirms significant trends with p=0.05 for temperature, relative humidity, and net radiation. Average increase of net radiation energy in Hungary is about 80mm in water equivalent during the last four decades. This increased load has an impact on the energy transfer processes where evapotranspiration has the largest share.
Trends of actual evaporation and Penman reference evaporation were analyzed in the study region. Evapotranspiration was estimated by the complementary relationship method of evaporation. Both parameters show significantly increasing trend. The warning signal, however, is that the gap between them is increasing, too. Demand (represented here by reference evaporation) is increasing faster than supply (evapotranspiration). Considering that water is the dominant energy transfer medium of climatic energy, an opening gap can be interpreted as the stability of the energy distribution system is decreasing. This change can trigger a growing risk of droughts, where drought is a symptom of system underperformance.
The common interpretation of evaporation as a loss factor in the hydrological cycle should be urgently changed to a functional view: energy distribution via evaporation is a vital environmental service. Atmospheric circulation and the water cycle are inherently connected. Saving water may not be the correct approach to mitigate climate change, as it only amplifies the deficiencies of the energy exchange process. One cannot stop desertification by chasing water use efficiency and using less water, but the other way around: scarcity of water can only be eliminated by ensuring that a wealth of water resources is available for evapotranspiration, thus for smooth distribution of climatic energy.
Decrease of the global precipitation area in CMIP6 projections
Authors: Dobler Andreas , Benestad Rasmus , Lussana Cristian , Lutz Julia , Landgren Oskar , Haugen Jan Erik , Mezghani Abdelkader , Parding Kajsa M.
Published: July 2023

Reanalysis as well as satellite data from TRMM show a decreasing trend in the daily precipitation area between 50°S and 50°N throughout the past decades. The trend is highly correlated to global mean temperatures and indicates the change in the hydrological cycle may be connected to the warming climate, resulting in increased drought frequencies and more intense rainfall. However, changes in the satellite networks provide inhomogeneous data sets and have possibly affected the precipitation area in the satellite and reanalysis dataset. Global climate and Earth system models, although suffering from biases in precipitation amounts and frequencies, are not influenced by changing observation systems. Thus, they provide a possibility to test the hypothesis of a decreasing precipitation area in a warming climate.
Here, we have used simulations from CMIP6 and CMIP5 to test this hypothesis. The models following the high-emission scenarios SSP5-8.5, SSP3-7.0 and RCP8.5 showed a clear decrease in the precipitation area towards the end of the 21st century. Compared to changes in the satellite and reanalysis data, the magnitude in the CMIP models was smaller. The decrease was apparent globally but most pronounced between 50°S and 50°N. Zonal averages of the daily precipitation area showed a general decrease from 5° to 50° on both hemispheres and an increase from 55° towards the poles, indicating a poleward shift of precipitation. In the Arctic region, the daily precipitation area was increasing from 20% to 30% on average.
Along with the precipitation area changes, the precipitation frequency decreased between 5° and 50 °S and increased in the polar regions. In the Northern Hemisphere, the precipitation frequency decreased over the North Atlantic, the Mediterranean region and Middle America. At the same time, precipitation intensity increased mostly everywhere.
Our analysis supports that in a warming climate, the daily precipitation area may indeed shrink, as found in reanalysis and satellite data. The results also showed that an increase in precipitation is coupled with an increase in precipitation intensity, while a decrease in precipitation is coupled with a decrease in frequency. However, the latter was generally coupled with an increase in precipitation intensity, suggesting increased drought frequencies and more intense rainfall at the same time.
A contextualization of heavy rainfall events in climate forecasts: A case study for Amman in Jordan
Authors: Hoffmann Peter
Published: July 2023

Days, when local heavy rainfall occur are often associated with characteristic large scale circulation patterns as a small part of the entire spectrum of the weather variability. To better understand the essence of the synoptical weather variability in observations and simulations, reanalyses, seasonal forecasts and climate projections have been explored in order to identify critical patterns, existing rules and long-term changes. As a study region serves Jordan located in the Eastern Mediterranean region, where heavy rainfall in the winter-half year can trigger flash floods in urban areas (Amman) or wadi systems (Petra). There is a urgent need to better estimate such weather related risks under climate change beyond the mean temperature rise. For this purpose we calculated composite patterns of the synoptical conditions for dates where the local amount of rainfall exceeded the 99th percentile.  The results of this study show probably only one side the medal. And this regards a rather intensification of extreme rainfall events associated with critical circulation patterns dependent on the global warming level across models. However, the recurring frequency of such patterns is widely regressive in the scenario simulations of the CMIP6 ensemble against our first expectation. According to the results, such extreme events at that location becoming rarer and stronger. Whether models overestimate the decline in frequency cannot be fully answered. However, retrospective analyses of ERA5 renalysis data indicate possible discrepancies and limitations of climate model scenarios beyond long-term trends in temperature indicators. A shift in the seasonality of extreme rainfall patterns are highly effected by the prevailing circulation patterns and thus need to be assessed with care.
D3D: Deep 3D scattering of solar radiation in the atmosphere due to clouds
Authors: Giannaklis Christos , Logothetis Stavros Andreas , Salamalikis Vasileios , Tzoumanikas Panagiotis , Kazantzidis Andreas
Published: July 2023

The cloud radiative effect, the strong interaction between cloud and radiation, is a leading physical mechanism in climate. However, due to the uncertainties of this effect, caused by three dimensional (3D) structures of clouds, it is difficult to simulate the cloud system and its effects in climate models. For this reason, 3D radiative transfer models have been developed for the simulation of radiation absorption/scattering and considering the complex dependencies of the amount, shapes and microphysical properties of cloud field. During the last decade, technological improvements resulted in the use of all-sky imaging (ASI) systems for the detection/characterization of clouds as well as to have observational information of the 3D cloud structure.  Moreover, deep learning neural networks, the new and very promising generation of neural models that can achieve state-of-the-art accuracy, are proved, very recently, to be able to accurately predict the distribution of radiance in artificial clouds.
Under this framework, the D3D project aims to conduct innovative research in the study of interactions between clouds and solar radiation by combining a) 3D reconstructed cloud from ASIs, b) full 3D radiative transfer simulations and c) deep learning neural networks. ASIs will provide the necessary observations of the 3D cloud structure to quantify the 3D radiation effects and the linkages to aerosol and cloud optical properties. A 3D radiative transfer model will be used for simulations and the reconstruction of the radiance field for a variety of atmospheric conditions, including different types of aerosols and clouds. The 3D cloud information from the ASIs for selected atmospheric conditions will be the principal input parameter in the 3D model. The derived polar radiances will be validated against the estimated ones by a radiometer installed proximal to the ASIs. The deep-learning neural networks will be trained, validated, and tested against model-derived datasets for various artificial atmospheric conditions. At the final stage, the model outputs and measured 3D radiances for cloudy conditions will be used as model input to render radiances at fast rates.
User-oriented evaluation framework for regional reanalyses
Authors: Spangehl Thomas , Borsche Michael , Niermann Deborah , Bär Franziska
Published: July 2023

Global reanalyses are known for more than 25 years and are widely used for monitoring climate variability and change, for academic purposes and commercial applications. Meanwhile, they are a fundamental part of operational climate services such as the Copernicus Climate Change Service (C3S). Recently, also regional reanalyses that provide higher spatial and temporal resolution became popular. Examples of exploitation of regional reanalyses include applications in the energy sector. Of special interest are variables such as wind speed at hub heights of modern wind turbines (offshore and onshore), near surface temperature and surface solar irradiance. Moreover, regional reanalyses are potentially useful for climate applications dealing with extremes such as wind storms, regional temperature anomalies including heat waves and droughts.
Here we show results from an evaluation approach that is used for monitoring the production process of the regional reanalysis COSMO-REA6 Generation 2 (R6G2), currently produced by Germany’s national meteorological Service (Deutscher Wetterdienst, DWD). Numerous datasets are used as observational reference, based either on in-situ measurements from stations and towers or satellite-borne remote sensing technology. Different products such as ERA5, COSMO-REA6 and HoKliSim-De are used as benchmark. The technical infrastructure for the standardised evaluation and monitoring is provided by the MAVIS system which builds on Freva (Free Evaluation System Framework, https://doi.org/10.5334/jors.253).
One user requirement is the availability of uncertainty information. There has been evidence that ensemble information is required for the representation of individual extreme events such as wind storms. The capability of the MAVIS system and requirements for application of the evaluation framework to ensemble-based regional reanalyses will be discussed.
 
Digitization and reconstruction of typhoon along the southern coastal regions in Qing China
Authors: Pei Qing
Published: July 2023

During the Qing Dynasty (1644–1911AD), there were more migrants toward southern coastal China, which contributed to the enough records for empirical analysis. In the meantime, the Qing period of China overlapped with Little Ice Age (LIA, 1400–1900AD), a period of abnormal climate with prolonged cooling and persistent hydroclimatic anomalies. Therefore, under this climatic background, the work to reconstruct the typhoon in southern coastal China will help to understand the linkage between natural disasters and abnormal climatic conditions, which has been insufficiently examined so far. 
To reconstruct the typhoon along the southern coastal regions in Qing China, both narrative and quantitative methods will be used. Based on the content of records, the typhoon occurrence will be identified. Furthermore, the consequence of typhoon event will be used to identify the strength of typhoon. Then, the occurrence and strength of past typhoon will be digitized and reconstructed based on the historical records. According to the digitized information, statistical methods and Geographic Information System (GIS) will enable spatiotemporal analysis on those numerical datasets.  
I will finally discuss the possibility to adopt a digitization approach for typhoon reconstruction. Current methods usually make use of natural archives/proxies and thus cannot fully consider the special features of archives of societies, although environmental studies should be guided by humanities. Therefore, I would like to develop some new digitization methods, such as text recognition methods to digitize the descriptive content of historical records into numerical data. It is thus a promising and innovative attempt to adopt a Machine Learning approach to recognize, digitize, and quantify the historical records, including the occurrence, duration, and severity of typhoon. 
Improvements in infrared gas analyzers for measuring atmospheric gases on moving platforms
Authors: Bogoev Ivan , Vandemark Doug , Miller Scott , Emond Marc , Covert Jason , Shellito Shawn
Published: July 2023

Accurate observations of atmospheric composition and exchange of greenhouse gases between the ecosystems and the atmosphere are critical for constraining climate models. Infrared gas analyzers (IRGA) using either broad band non-dispersive or narrow band tunable laser technologies are widely used for this purpose. Typically, such analyzers are installed on stationary meteorological towers over land; but an increasing number of systems are being deployed on mobile platforms and buoys to extend the spatial coverage and include measurements over water.  One technological challenge is that the motion of the platform influences the gas concentration measurements. Empirical correction methods have been proposed, but their universality is limited because the source of these sensor-related effects and their underlining mechanisms have not been understood. In this study we identified the dominant source of the error: orientation-dependent temperature stabilization of the thermoelectrically cooled infrared detector. To further investigate this hypothesis and gain insights to a solution, a new prototype closed-path IRGA with an improved infrared detector was developed. In the study, we compared the performance of the prototype to standard models of commercially available IRGA measuring CO2 and H2O.  Tilt experiments with side-by-side mounted IRGAs were first conducted on a controlled laboratory platform with independent pitch and roll axes. Over the ±30° range of angular position, the orientation-correlated errors were reduced by a factor of 4 to 10 on CO2 and a factor of 2 to 8 on H2O. Subsequent testing was performed duplicating realistic buoy motion in a deep-water tank with typical at-sea combined pitch and roll motion. In these tests, improvements in the measurement errors were similar to the laboratory experiments. Implications for the correction of past field measurements and insights for further sensor optimization and system improvements are discussed.
Short-time forecast on heavy rainfall in Eastern China using the deep generative models
Authors: Xu Jun , Dai Kan
Published: July 2023

Heavy rainfall, generated by multi-scale processes and characterized by small spatial scale, sudden occurrence, low predictability and strong disaster-causing, is the bottleneck of short-time forecast in China. At present, the grid resolution of quantitative forecast on precipitation in national quantitative precipitation forecast operation is only 5km, which could not meet the requirements of fine forecast for disaster prevention and reduction. Recent study in Europe and the United States shows that the high resolution short-time probabilistic forecast with advantages in heavy rainfall forecast could be generated by using the deep generative models to correct the error and improve the resolution of the low resolution numerical model forecast. In view of the above facts, based on the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (IFS) forecast data and China Meteorological Administration Land Surface Data Assimilation System (CLDAS) observed precipitation gridded data in 1km resolution, the short-time probabilistic precipitation forecast was studied in 1km resolution forecast by using the deep generative model in Eastern China. Results show that the short-time probabilistic forecast could be effectively generated by the deep generative model with the forecast feature inputs associated to the formation of heavy rainfall. Meanwhile, the critical success index and fractions skill score of 3 hours accumulation precipitation above 20mm could be greater than the model forecast. Case studies showed that the forecast generated by the deep generative model could effectively improve the forecast of the location and intensity of heavy rainfall, which showed promising application in the future in forecast operation in China.
Worldwide seasonal drought forecasts with local relevance
Authors: Sperna Weiland Frederiek , Trambauer Patricia , Verkade Jan
Published: July 2023

Worldwide drought frequencies and intensities are changing, and many countries and river basins are confronted with the impacts of severe droughts leading to food insecurity and drinking water shortage.  Hydrological drought forecasts with long lead-times can be of great value to help reduce societal impacts, especially when they include local sector-specific information.To provide high-resolution hydrological forecasts with sufficient local detail we enable the automized implementation of high-resolution basin scale hydrological models anywhere in the world instead of implementing one often lower resolution global hydrological model. The underlying distributed hydrological model – wflow_sbm – relies on so-called pedo-transfer functions that translate input base maps such as land use, digital elevation model, river network and soil type to estimate model parameter values. Herewith the model requires little calibration and can be easily implemented for additional river basins. So far, hydrological models have been included for the Paraná, Lempa,  Vardar, Rhine and Niger river basins and drought forecasts are set-up using the ECMWF seasonal forecasts (SEAS5). All has been integrated in the operational forecasting platform Delft-FEWS that facilitates the data handling, hydrological model simulations and statistical analysis.The forecasting platform facilitates research analysis and developments on amongst others (1) spatial explicit drought forecasting skill, (2) the value of different meteorological and hydrological drought indicators such as the Standardized Precipitation Index (SPI), Standardized Precipitation and Evaporation Index (SPEI), discharge anomalies, soil moisture deficit (SMDI) and evaporation deficit indices (ETDI) and (3) the development of dedicated indicators for specific user groups defined based on their needs.
Project FOCI - Non-CO2 Forcers and Their Climate, Weather, Air Quality, and Health Impacts
Authors: Halenka Tomas , Sokhi Ranjeet S.
Published: July 2023

While overall global warming with the causes and global processes connected to well-mixed CO2, and its impacts on global to continental scales are well understood with a high level of confidence, there are knowledge gaps concerning the impact of many other non-CO2 radiative forcers leading to low confidence in the conclusions. This relates mainly to specific anthropogenic and natural precursor emissions of short-lived GHGs and aerosols and their precursors. The anthropogenic origin is connected to a large extent with the urban environment. These gaps and uncertainties also exist in their subsequent effects on atmospheric chemistry and climate, through direct emissions dependent on changes in e.g., agriculture production and technologies based on scenarios for future development as well as feedback of global warming on emissions, e.g., permafrost thaw.
The main goal of the EC Horizon Europe project FOCI is to assess the impact of key radiative forcers, where and how they arise, the processes of their impact on the climate system, to find and test an efficient implementation of these processes into global Earth System Models and into Regional Climate Models, eventually coupled with CTMs, and finally to use the tools developed to investigate mitigation and/or adaptation policies incorporated in selected scenarios of future development targeted at Europe and other regions of the world, with final emphasis to selected cities environment. We will develop new regionally tuned scenarios based on improved emissions to assess the effects of non-CO2 forcers. Mutual interactions of the results and climate services producers and other end-users will provide feedback for the specific scenarios optimization and potential application to support the decision-making, including climate policy. First preliminary outputs and strategies will be mentioned in addition to the general overview of the project.
Climate Change Scenarios and Prediction Localization for City of Prague
Authors: Halenka Tomas , Belda Michal , Huszar Peter , Karlicky Jan , Dhib Saoussen
Published: July 2023

Cities play a fundamental role in climate at local to regional scales through modification of heat and moisture fluxes, as well as affecting local atmospheric chemistry and composition, alongside air-pollution dispersion. Vice versa, regional climate change impacts urban areas and is expected to increasingly affect cities and their citizens in the upcoming decades. To assess the impact of cities and urban structures on weather, climate, and air quality, a modeling approach is commonly used and the inclusion of urban parameterization in land-surface interactions is of primary importance to capture the urban effects properly. This is especially important when going to higher resolution, which is a common trend in the operational weather forecast, air-quality prediction as well as regional climate modeling. As the most of population is living in the cities and the share is increasing, we need a proper description of urban processes to assess impacts within the cities and the effectiveness of adaptation and mitigation options applied in cities in connection with climate change as well as the urban heat island itself. This is critical in connection to extreme events, for instance, heat waves with extremely high temperatures exacerbated by the urban heat island effect, in particular during night-time, with significant consequences for human health. In the City of Prague, this can achieve about 4-5°C.
This is studied in the local project PERUN in very high resolution (convection-permitting) to localize climate change scenarios for the City of Prague. The potential of such simulations for urban heat island adaptation and/or mitigation options assessment and planning is studied within the project IMPETUS4CHANGE, where the City of Prague is one of the so-called Demonstrator City, where proof of concept will be evaluated. Connection to the air quality interaction is considered as well.
From Aerosols to Greenhouse Gases: evaluating the concentrations
Authors: Andrade Maria de Fatima , Leonardo Noele , Castelo Daniel , Souto-Oliveira Carlos , Medeiros José Agostinho Gonçalves , Domingues Lucas Gatti
Published: July 2023

Since the 1980s, the atmospheric aerosol in Sao Paulo, the most populous and economically active region of Southeast Brazil, has been extensively studied to determine its composition, concentration, and health impacts. The city of São Paulo is characterized by a multi-centric urban landscape, with people usually commuting from the periphery to downtown where there are most of the jobs and opportunities. This results in congestion, large emissions from the transport sector and as a consequence, more pollutant exposure. The transport sector is responsible for 60% of the CO2 emission. PM2.5, an important climate pollutant is composed mainly of carbonaceous compounds, associated with the emissions by the vehicular fleet which uses biofuels (gasohol and bio-diesel). Starting in 2020, the aerosol network in Sao Paulo underwent updates to include measurements of greenhouse gases (GHGs) at five sites as part of the METROCLIMA project (www.metroclima.iag.usp.br). The primary objectives of this project are to determine the megacity's contribution to CO2 and CH4 emissions. Measurements of stable carbon isotopes (12C and 13C) of CO2 and CH4 in the atmosphere provide valuable information for identifying and quantifying the predominant sources and sinks of these gases. Continuous monitoring of d13C-CO in Sao Paulo has revealed changes in the contributions of significant CO2 sources, including fossil fuels (including biofuels) and wildfires. CO2 background concentrations were estimated for the period from 2019 to 2021, resulting in an annual increase rate of 2.5 ppm/year, which is consistent with the estimated values provided by NOAA-USA. The concentrations in the background station varied from 416.94 (9.25) to 421.82 (7.47), from 2019 to 2022. The highest concentrations were found in the morning and evening hours associated with vehicular emissions, but during the day it was possible to observe the effect of local vegetation photosynthesis in the reduction of the CO2 concentrations. 
Do severe storms across Australia, Europe and the United States share similarities? A comparison of atmospheric profiles and environmental predictors
Authors: Taszarek Mateusz , Allen John , Nixon Cameron , Dowdy Andrew , Battaglioli Francesco
Published: July 2023

It is well known that atmospheric environments across Australia, Europe and the United States are conducive to the occurrence of convective storms resulting in significant tornadoes, giant hail and damaging winds. However, while many studies have focused on evaluating convective environments over specific regions, only a limited number of elaborations compared different parts of the world. Therefore, in this work we use severe weather reports, ground lightning detection data and ERA5 reanalysis over the last 20 years to address the following research question: do severe storms across Australia, Europe and the United States share environmental similarities? A comparison of composite vertical profiles of temperature, moisture and wind highlighted several consistent features that are common for specific hazards among all three continents. For example, near-ground relative humidity and storm-relative helicity are important for tornadoes while buoyancy in below freezing temperatures and weak near-ground winds are important for large hail. Low-level moisture flux turned out to be the best discriminator between tornadoes and large hail events. However, despite these similarities, statistical analysis indicated that a predictive value for some ingredients can be markedly different among continents. A prime reason for that are different underlying climatological conditions. For example, a strong low-level wind shear combined with sufficient buoyancy is rare over Europe and Australia but when it occurs, it is often associated with tornado reports. On the other hand, a strong low-level wind shear is common over the United States, but is not always associated with proper convective organization to produce a tornado. For this reason, we believe that developing environmental models intended to work universally across the entire world can be extremely difficult as it is challenging to disentangle signals that are associated with physical processes from those that result from a local climatology.