bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamic Anthropogenic actiVities and feedback to Emissions (DAVE): – An agent based model for heat and exposure to other anthropogenic emissions
Authors: McGrory Megan , Hertwig Denise , Lo Piano Samuele , Ramirez-Mendiola Jose Luis , Smith Stefán Thor , Paskin Matthew , Liu Yiqing , Grimmond Sue
Published: July 2023

Two thirds of global energy consumption, and over 70% of CO2 emissions came from urban areas in 2020, when 56% of the global population lived in towns and cities. It is predicted that further rapid urbanization will lead to almost 70% of the world’s population living in urban areas by 2050 (https://www.iea.org/reports/world-energy-outlook-2021). Therefore, for future energy and climate predictions it is key to model urban climates accurately. Modelling urban climates creates several challenges and considerations, including the additional term in the surface energy balance of anthropogenic heat flux (QF). These heat emissions linked to people’s activities vary with human/animal metabolism, transport, and energy consumption within buildings.  

Here, a bottom-up approach is taken to model QF accounting for both urban form and function allowing a dynamic response to a wide range of factors. The model DAVE (Dynamic Anthropogenic actiVities and feedback to Emissions), informed by a predecessor (DASH, https://doi.org/10.5194/gmd-13-4891-2020), is coupled to a surface energy balance model (e.g., SUEWS, https://doi.org/10.1016/j.jhydrol.2011.10.001), a building energy model (STEBBS, https://doi.org/10.5194/gmd-13-4891-2020) and a transport model (MATSDA).  Extensive data mining provides the inputs for the building and transport modules (Hertwig et al. 2023 – this meeting), for the cities simulated. People’s dynamic behaviour is informed by probabilities derived from time use surveys (https://doi.org/10.5255/UKDA-SN-8128-1). Combined, the impacts of energy use and exposure in different environments are simulated for both places and people as daily activities occur.  

Examples of applications of how the coupled modelling system can be used are to:  

model the exposure of people to air pollution and heat, for example those from different age or neighbourhood cohorts 
model dynamics of energy demand across urban regions. 

simulate feedbacks between weather and climate on intra-neighbourhood QF  emissions 

Funding supported this work includes: ERC urbisphere, NERC APEx, and EPRSC CREDS. 
Effects of urban areas on the diurnal cycle of temperature and precipitation as found in global climate simulations
Authors: Katzfey Jack , Schlünzen K. Heinke , Hoffmann Peter , Thatcher Marcus
Published: July 2023

Urban areas with their high population density, industrial facilities and traffic account for about 70% of the world’s CO2 emissions and thereby contribute to global climate change. In addition, the urban fabric and its qualities (albedo, heat storage, vertical extension) influence atmospheric parameters, resulting in the well-known urban heat island (UHI) effect that may influence precipitation as well as temperature. Although both effects are found worldwide, analyses of global climate model results for urban impacts on temperature and precipitation are rare.
Previous analyses of global climate model CCAM simulations for 1985-2010 have revealed UHI effects and influences of urban areas on minimum and maximum temperatures [1]. Using the same data set to derive time-zone corrected 3-hourly data, climate average global diurnal cycles of temperature and precipitation were calculated. The  UHI intensity depends on season and climate region (northern extra-tropics (NET), southern extra-tropics (SET), or tropics (TR)). The largest statistically significant UHI influences are consistently found in the evening and at night-time, in agreement with many previous studies. Signs of urban cool islands were found for a few hours per season and climate region. Influences of urban areas on precipitation varied, with increases and decreases in all climate regions and seasons. For NET (274 cities), two out of three cities show significantly increased precipitation, while for SET (39 cities) and TR (26 cities) more decreases than increases were noted. Exceptions to these general influences of urban areas on precipitation were found at several hours for all seasons. The geographic settings of the large urban areas used for these analyses might be one explanation of the different precipitation changes induced by UHI, since urban areas are not distributed evenly around the globe. The increase in precipitation seen for NET might be because these urban areas are in less warm climate regions compared to SET and TR.
[1] Katzfey J.; Schlünzen K.H.; Hoffmann P.; Thatcher M. (2020): How an Urban Parameterization Affects a High-resolution Global Climate Simulation. QJRMS, 146 (733), 3808–3829. https://doi.org/10.1002/qj.3874.
Wind-wave-wake interactions in offshore wind farms
Authors: Fischereit Jana , Imberger Marc , Müller Sara , Hahmann Andrea N. , Larsén Xiaoli Guo
Published: July 2023

Offshore wind farms are exposed to a dynamic environment where the interactions between wind and waves modify wind resources. By extracting energy from the flow, wind farms alter these interactions and traditional wind resource assessment usually simplifies or ignores the interactions between wind and waves. However, in recent years some progress has been made in properly considering these interactions. In this presentation, we will highlight the relevance of these wind-wave-wake interactions for wind energy applications by summarizing the findings of two studies.
First, we show which role these interactions play in tropical cyclone development. For that, we use Typhoon Megi, a category 5 cyclone that hit Taiwan in late September 2016, as an example. Second, we demonstrate the relevance of wind-wave-wake interactions for resource assessment. We use a statistical-dynamical downscaling approach to represent the 30-year climate in the German Bight and assess the impact of waves and wakes on wind resources (Fischereit et al. 2022).
For both studies, we use the Coupled-Ocean-Atmosphere-Wave-Sediment Transport Modeling System (COAWST; Warner et al. 2008, 2010). In this modelling system, we activate the atmospheric model WRF (Weather, Research and Forecasting model) and the wave model SWAN (Simulating WAves Nearshore model) . We apply the Wave Boundary Layer Model (WBLM; Du et al. 2017, 2019) to ensure that the exchange of flux and energy between these two models are consistent. To derive the range of possible wind farm effects, we use two different wind farm parameterizations (WFP) in the simulation, namely the WFP by Fitch et al. (2012) and the Explicit Wake Parameterization (EWP) by Volker et al. (2015).
The studies show that wind-wave-wake interactions influence wind resources, and that they also affect the intensity and track of a typhoon. This highlights that these interactions should be considered in wind energy applications.
Extreme rainfall of short duration at local scale: case study of Shkodra
Authors: Porja Tanja , Kafexhiu Ervin , Peqini Klaudio
Published: July 2023

Abstract: Local storms can often generate extreme rainfall of short duration that causes immediate and serious flooding in the local scale. The genesis and rapid development of such storms are a result of complex processes that occur in the dynamics of the storm. In this study are examined the Automatic Weather Station's rainfall data and reanalyses from NWP fields for Shkodra city to search the causes of such extreme rainfall in such a short time. The extreme precipitation generally is created as a result of high vertical instability of a air mass very rich in moisture. While the extreme rainfall of short duration at local scale is mainly related to the convective cells and local thermodynamic factors like the vertical profile of temperature and humidity, depending to the local atmospheric circulation. A retrospective analyses regarding the extreme rainfall of short duration at the local scale may provide a detailed picture of the extreme rainfall behaviour occuring in that area for short time intervals of 1, 3 , 6 up to 24 hours. The analyses of the events of short duration extreme rainfall at a local scale for a long term period may provide good results regarding the estimation of the future risk of the sudden local scale floods for the urban areas. Pairing the incidence of local flash floods with the triggers of these events can serve as an additional tool in forecasting local storms that produce short-term extreme rainfall and flash flooding. This study shows that the increased frequency of events with extreme rainfall and the increasing of the rainfall quantities for short time duration intervals is likely to become a prominent feature of the local storms that bring flash floods in the populated and urbanised areas.
Keywords: Extreme rainfall, local flood, vertical profile, convective rainfall
Spatial patterns and seasonality of drought in Switzerland under present and future climatic conditions, and irrigation water requirements
Authors: Calanca Pierluigi , Toschini Thomas , Wüst-Galley Chloé
Published: July 2023

In Switzerland, as elsewhere in Europe, recurrent drought has been one of the main concerns of the agricultural sector during the last few decades. The dry years of 2003, 2006, 2015, 2018 and again 2022 had serious impacts on forage production. As a result, additional imports were necessary to support in particular the dairy sector. Another consequence of the drought was an increase in the need for irrigation, which, however, could not always be met. Eventually, farmers had to accept restrictions on water withdrawals on several occasions. Climate change projection indicate that such situations could become more common in future.
To increase preparedness and help the agricultural sector, as a whole, better cope with drought under future climatic conditions, quantitative information on drought occurrence at regional to national scale is required. In this contribution, we present a drought assessment for Switzerland that addresses the following questions: (i) Spatial patterns of drought. What was the geography of drought events in the recent pat? Can we expect similar geographic patterns in the future? (ii) Seasonality and persistence of drought. Has there been a shift the temporal characteristics of drought because of climate warming? Are further shifts likely to occur in future? (iii) Irrigation requirements: Has the need for irrigation already increased in the recent past? If yes, where and by how much? What can be expected in this respect for the coming decades?
We base our analysis on high-resolution, gridded meteorological data and climate change projections, and use drought indices to characterize drought events in time and space. We further show how a simple model that relates irrigation requirements to a drought index can be employed to estimate current and future needs across Switzerland. Finally, we discuss how these results can be integrated in initiatives aiming at supporting farmers in the process of adaptation.
Optimization of urban form classification and the impact on the urban thermal condition
Authors: Chen Yu Cheng , Chen Jue Ru
Published: July 2023

The high intensity of urban development in recent years has replaced many natural surfaces with artificial objects. Buildings and roads have increased heat storage, which has become one of the leading causes of urban hyperthermia. In the past, studies on urban form and the thermal environment mainly used surface coverage analysis. However, surface classification cannot effectively consider three-dimensional urban information such as building height and density. Therefore, this study will use Local Climate Zone (LCZ) as a classification method to investigate urban form and temperature. LCZ is a classification method that explores the association between urban form and temperature. Since the classification process of LCZ is a supervised classification using satellite images, the results are subjectively influenced. Therefore, this project selects several representative zones, combines the LCZ classification with the types defined by each category, and conducts a questionnaire survey on 50 students with architecture and landscape planning backgrounds to compile the classification results of most people in each representative zone. The survey results were used for training, and the types of LCZs in the study site were summarized. The results showed that the accuracy of the objective classification results was 5.5% higher than that of the subjective classification. Increasing the number of training areas from 3 to 8 for each type also improved the accuracy by about 4.5%. In addition, this study analyzed the LCZ classification of buildings and landscapes in each region and the influence of temperature through the temperature data of the Meteorological Bureau in 2022. It was found that the average LCZ temperature in built-up areas could reach 32°C, while the average LCZ temperature in non-built-up areas was about 30.5°C in summer daytime. This study will serve as a reference for urban design to reduce the temperature for the potential of sustainable urban development.
Reconstruction of solar radiation in Tokyo since 1720 based on daily weather records in historical documents
Authors: Ichino Mika , Masuda Kooiti , Mikami Takehiko
Published: July 2023

The impact of climate change on human society has been a significant issue in historical studies and is also vital for future adaptation to climate change. To understand climate change before the start of meteorological observations and its devastating impact on societies in the past, the spatial patterns of climate variations must be reconstructed with a higher temporal resolution than those provided by the annual data. Japan has a large volume of records, including those related to daily weather conditions from the 17th to 19th centuries, which can help with this reconstruction.
This study applied the method previously developed by Ichino et al. (2001) for estimating solar radiation from the weather records of the Japan Meteorological Agency (JMA) to those collected from historical diaries. Adjusting the classification of descriptions from historical diaries, which are recorded in various expressions, allowed for their application in the method constructed from the current JMA weather descriptions. We estimated solar radiation for 1720–1912 in Japan based on the weather descriptions recorded in historical diaries from Tokyo, pertaining to the Little Ice Age. We validated the estimation compared to solar radiation estimated from the JMA-observed sunshine duration. The reconstruction was combined with the estimation from sunshine duration and the observed solar radiation to create the solar radiation time series data for 1720–2022.
The method used in this study successfully reconstructed solar radiation data in an adequate manner for all seasons with a higher temporal resolution, compared to other methods, including the use of proxy data for assessing historical climate variation. In addition, solar radiation is a fundamental factor for not only the energy balance of the Earth but also the hydrological cycle and agricultural productivity. Therefore, this extended reconstruction of time series data could contribute towards discussing climate change and its effects on historical societies. Herein, we discuss the long-term variations of the reconstructed solar radiation data since the 18th century, focusing on its particular effects on famine.
Reference
Ichino M, Sakamoto N, Masuda K, Mikami T (2001) The method for estimating global solar radiation based on weather records－toward the climatic reconstruction in the historical period－. Tenki 48:823–830. (in Japanese)
Keywords
Solar radiation, Historical weather descriptions, Historical diaries, Little Ice Age, Climate change, Japan
An attempt to reconstruct winter temperatures over the past 300 years from snowfall ratios based on diary weather records
Authors: Mikami Takehiko
Published: July 2023

In Japan, diaries that record daily weather conditions since the 18th century have been kept in various parts of the country. The winter weather distribution in the Japanese archipelago is characterized by a north-south extension of the mountain ranges, with the Sea of Japan side having more snow days and the Pacific side having more sunny days. On the other hand, when temperatures are higher in winter, precipitation is more likely to be rain, and when temperatures are lower, it is more likely to be snow. Therefore, by obtaining a linear regression equation based on the correlation between the ratio of the number of snowfall days to the total number of precipitation days in winter and the average temperature for the period when meteorological observation records are available (since 1879), it is possible to reconstruct long-term temperature variations from the snowfall ratio obtained from diary weather records in historical periods. Based on this principle, we attempted to reconstruct winter temperatures in Nagasaki since 1700. Fortunately, Nagasaki has records of early meteorological observations by Dutch medical doctors from 1840 to 1860, before the start of official meteorological observations, which can be used to verify the reconstructed temperatures. The results show that winter temperatures in Nagasaki tended to be lower in the period from about 1700 to 1840, but warmed temporarily in the 1850s and 1860s, and then remained lower again until about 1950. The temperature reconstructions for 1840-1860, when the reconstructed and observed temperatures overlap, are almost coincident, demonstrating that the winter temperature reconstructions based on snowfall ratios are mostly accurate.
Change in the relationship between daily mean precipitation and temperature over the East Asia summer monsoon region
Authors: Hwang Seung-On , Yeh Sang-Wook , Lee Johan
Published: July 2023

The relationship between daily mean precipitation and surface air temperature (mean P-T) over the East Asia summer monsoon land region for 1979–2022 and its decadal change are investigated using binned scaling analysis and the Clausius–Clapeyron equation. Mean P-T scaling analysis produces a peak-shaped scaling curve that roughly follows the Clausius–Clapeyron constraint below a threshold temperature at which precipitation reaches its peak and shows negative scaling due to a saturation deficit above the threshold temperature. This feature is similar to the scaling behavior for extreme P-T relationships observed in many previous studies for mid-latitudes, execpt for a different magnitude of precipitation and the C-C scaling rate. It is found that there is distinct regime shift of mean P-T relationship before and after 2000, which is clearly seen in all the parameters such as the threshold temperature, mean precipitation, and scaling rate. The threshold temperature has increased after 2000, indicating that the hydrological response to warming can be explained by C-C scaling prediction at further high temperature. However, the precipitation peak has decreased after 2000, which contradicts well-established increasing and linked tendencies for temperature and precipitation in a warmer world. We therefore conclude that the dependency of daily mean precipitation on daily mean surface temperature may be influenced by hydrological changes in the East Asian monsoon in summer. This poses a concern for the spatio-temporal variability of regional monsoon systems and suggests that localized responses to global warming need to be considered to understand the mean P-T relationship over the East Asia summer monsoon region. 
An experiment in Climate Service portability: implementing a Danish Climate Atlas in Ghana
Authors: Payne Mark R. , Ahiataku Maureen Abla , Ansah Samuel Owusu , Asuman Eric , Lamptey Benjamin , Johansen Christian Robdrup , Sarup Kim
Published: July 2023

Climate services provide tailored information to support climate adaptation at the local level. However, the highly specific local needs of each setting also means that they are difficult to generalise and transport from one setting to another. In this presentation we describe a collaboration between Denmark and Ghana to establish climate services in Ghana. The template for this Ghanaian climate service is Klimaatlas, the Danish National Climate Atlas, a well-established tool used by actors throughout Denmark as one of the primary tools underpinning local climate adaptation planning. Klimaatlas presents projections from the EURO-CORDEX regional climate model ensemble, bias-corrected against local observations, in the form of an interactive web-interface and tailored reports. Our initial efforts show that some parts of the Klimaatlas approach to developing a climate service can be reused directly in Ghana, particularly around user engagement and some aspects of the presentation of information: other parts however need to be rethought from scratch.  In particular, the large data volumes associated with CORDEX ensembles present a major bottleneck for applications in Ghana, where both bandwidth and storage are limited. Ensuring the robustness and durability of the service will also be critical to its success and have received particular attention. Furthermore, while there is a wealth of observational data, much of it cannot be used for bias correction in its current form. We will describe our efforts to solve these problems and the lessons learned, and present recommendations for how the climate service community can aid the development of climate services in developing countries.
Sensitivity of the winter North Atlantic-European atmospheric circulation to Tropical North Atlantic SST anomalies
Authors: Gil-Reyes Laura , García-Serrano Javier , Kucharski Fred
Published: July 2023

One of the leading modes of sea surface temperature (SST) variability in the Tropical Atlantic consists of a meridional pattern dominated by anomalies in the Tropical North Atlantic (TNA). It is strongly coupled with the North Atlantic Oscillation (NAO); in addition to be one of the lobes of the NAO-induced SST tripole, it is thought to be an integral part of the positive ocean feedback onto the atmosphere (i.e. NAO-like response). This study aims at exploring the contribution of two SST areas on the atmospheric response to TNA: the Subtropical North Atlantic (SNA) in the eastern basin, and the Caribbean region (CBBN) in the western basin. A set of sensitivity experiments has been performed with the intermediate-complexity atmosphere model SPEEDY (T30L8), keeping fixed the radiative forcing at present-day climate conditions. Atmosphere-only simulations comprise a control run with observed climatological SSTs over 1980-2010 (CTRL), a first sensitivity run prescribing the whole observed TNA pattern with climatology elsewhere (FULL), and two additional sensitivity runs similar to FULL but splitting the observed TNA pattern into its eastern (SNA) and western (CBBN) components, namely east and west of 60ºW. Two-hundred members have been completed for each simulation, covering the extended winter season from November to March. Further, a twin set of experiments has been performed coupling SPEEDY to a slab ocean model (SPEEDY-SOM) in order to assess the impact of extratropical air-sea interaction on the atmospheric response to TNA, SNA and CBBN. Preliminary results suggest that the Caribbean region plays an important role in the tropical-extratropical teleconnection.
Next generation warning production system at MeteoSwiss
Authors: Mahlstein Irina , Beusch Lea , Moret Lionel , Willemse Saskia , Liniger Mark
Published: July 2023

In the framework of the renewal of the warning system at MeteoSwiss, we use the possibility to redesign the software as well as the scientific approach of generating warnings. The production chain is designed such that the data is guided and refined along the pathway. Here, we present the operational production process currently in development for the next generation warning system. The first step is the combination of all available data into one data stream (seamless weather). The second stage prepares warning proposals for the forecasters. The only human interaction with the system (third step) is the one of the forecaster in case of extreme weather. However, the automatically generated warning proposals aim to minimize the time needed by the forecaster to issue a warning. In a last step at the end of the chain, the warning products are customized and distributed to our customers. Furthermore, the warnings will also be verified automatically to monitor the quality of the system.
Along the chain, we run into a number of challenges, which ask for clever solutions: How do we group grid cells with similar extreme weather information into meaningful warning polygons? How do we facilitate the interaction of the system with the forecaster? Which aspects of the warning do we verify? How do we judge the quality of the warning? Finally yet importantly, what does the warning that we issue actually mean? If we do not have a common understanding about what we are expecting to happen within a warning polygon a clear communication of uncertainties and measuring the quality of our warnings is impossible.
Hence, the system involves new applications based on specific developments aiming at generating the greatest value for public warnings. Most of the warning chain is purely machine driven; nonetheless, the human interaction remains a key aspect of the new warning system.
Changes in the occurrence of the persistent seasonal snow cover in Slovakia in the period 1921/1922 - 2022/2023
Authors: Markovič Ladislav , Faško Pavel
Published: July 2023

Snow cover and its characteristics are among the meteorological indicators that are usually the most affected by the changing climate. In the complex natural conditions of Slovakia, this can mean the emergence of conflicting tendencies even within small regions. In connection with the geographical location of Slovakia, the influence of the greater continentality of the climate of eastern Slovakia, or more pronounced manifestations of the oceanic climate of the western and south-western regions of Slovakia, can also influence formation and durability of the seasonal snow cover (SC). Persistent seasonal snow cover is methodically defined as a period of continuous snow cover that can be interrupted for a maximum of 3 days during the given season. Time series of the daily snow cover depth used in this paper already reached a length of more than a hundred years, which can be a sufficient guarantee of an objective expression of detected changes in the occurrence of persistent seasonal snow cover. In connection with the general decrease of days with the persistent seasonal snow cover, which has not avoided the Central European region, the aim of this paper is to draw attention to the reduction in the occurrence of the persistent seasonal snow cover in Slovakia. It manifests itself in the form of a decrease in the number of days with snow coverat the beginning and at the end of the winter season and its instability during the main part of the season, in which the fluctuation of temperature conditions is accentuated. In the historical context, the shortening of the period with persistent seasonal snow cover in Slovakia began to manifest itself significantly in the second decade of the 21st century.
Creating skillful and reliable probabilistic forecasts using machine learning
Authors: Clare Mariana , Haiden Thomas
Published: July 2023

Machine learning techniques are increasingly used in weather forecasting, to either improve results from numerical weather prediction (NWP) models or emulate some aspects of the forward integration part of NWP models using a purely data-driven approach. So far most of the techniques presented have focused on producing deterministic forecasts, as many standard machine learning techniques lack the ability to express uncertainty.  

Whilst methods that attempt to fully emulate NWP models are both very complex and computationally expensive, in this talk I will show how much simpler and computationally cheaper techniques can be used to create a probabilistic forecast from a single global high-resolution forecast by post-processing. Specifically, I will focus on the relatively novel technique of a Bayesian Neural Network and show how it can predict the distribution of the forecast error relative to its own analysis. By adding these error distributions to the original forecast, we can create a probabilistic forecast. Time permitting, I will discuss how more advanced techniques can be applied to take these distributions and generate spatially consistent ensemble members. 

This methodology is particularly useful for NWP models at very high resolutions where running an ensemble is too computationally expensive and for machine learning approaches where no uncertainty information is available. In this talk, I will show how this methodology can be successfully applied to both ECMWF’s high-resolution forecast and a purely data-driven weather forecast model being run at ECMWF, for both the surface variable of 2m temperature and the atmospheric variable of Z500. These probabilistic forecasts have been verified using standard metrics and, in the case of the high-resolution numerical forecast, have as good as or better CRPS scores than the ECMWF ensemble forecast for the lead times tested. Moreover, these probabilistic forecasts are reliable with spread-skill ratios close to one. Hence, this novel machine learning post-processing technique has the potential to produce probabilistic forecasts that are valuable and useful to forecasters. 
Representative impact scenarios from weather and climate ensembles
Authors: Messori Gabriele , Jewson Stephen , Scher Sebastian
Published: July 2023

Ensembles have revolutionized weather forecasts, by providing a probabilistic view of future weather. However, ensembles contain a large amount of information, and using this to understand the potential impacts of the forecasted weather requires a skilled user with extensive computational resources. This challenge is particularly acute for users considering the weather conditions over a geographical region, rather than at a single location. In these cases, considering every single ensemble member and its impacts may be practically unfeasible. Many such users thus simply consider the ensemble mean and some measure of ensemble spread, such as the ensemble’s standard deviation. While this facilitates the use of ensemble forecasts, it does not explore the range of possible impacts of the forecasted weather. Here, we propose a framework facilitating the use of ensemble forecasts for weather impacts. We specifically represent the ensemble by the mean and a single deviation from the mean. This deviation is defined so as to both be representative of the variability in the ensemble, and have a significant impact according to some impact metric. We determine such a deviation using a statistical method known as Directional Component Analysis, which is based on linearizing an impact metric around the ensemble mean. We provide a concrete example using 2-m temperature forecasts for continental Europe from ECMWF, and show that this approach is more robust than considering the single worst (in terms of impacts) ensemble member. This same approach can be applied to ensembles of projections of future climates. We illustrate this by deriving representative deviations for the UKCP18 and EURO-CORDEX projections of future precipitation in Europe. We conclude that the mean and representative deviation method we propose may both contribute to automated early warnings for weather impacts and support users who wish to explore the implications of longer-term climate impacts in a resource-effective fashion.
Incoming photosynthetically active radiation (PAR) in the Biebrza National Park, north-eastern Poland (Kopytkowo case study)
Authors: Górowski Jan , Fortuniak Krzysztof , Siedlecki Mariusz , Pawlak Włodzimierz
Published: July 2023

Photosynthetically active radiation (PAR) is one of the most important ecosystem steering factors. Here we present the results of 9-year (2013-2021) continuous measurements of incoming PAR made at the Kopytkowo site (53°35′30.8′′ N, 22°53′32.4′′ E, 109 m a.s.l.) in the Biebrza National Park in north-eastern Poland.  The area is a unique marsh ecosystem on a European scale. The PQS1 Quantum Sensor mounted at a height of 2.7 m a.g.l. was used to measure PAR with a time step of ten seconds. The data were then averaged into a 5-minute time step used in the study. The results were expressed in terms of photosynthetically active photon flux density (PPFD in µmol·m⁻²-·s⁻¹-). The results show that two seasons, corresponding to different PAR regimes in the Biebrza Basin can be distinguished. The first season (the warm part of the year) starts in the second half of March and lasts until the beginning of October. During this period, the development of convective cloudiness influences photosynthetically active radiation values. The winter season, which lasts for the remainder of the year, is characterised by a higher proportion of cloudy days, influencing the reduced values of surveyed radiation. In general, the annual and diurnal PAR course reflects the incoming radiation on the top of the atmosphere and its attenuation in the atmosphere.For this reason, in addition to the standard climatological PAR characteristics, we have determined the clearness index in the PAR range. We found that this index can be expressed as a hyperbolic function of the Sun's height for the clear sky. Due to the limited availability of PAR measurement data, we have proposed simple parameterization of this element. Three types of models were taken into account: parameterizations based on the values of total solar radiation, parameterizations for a cloudless sky with the height of the Sun as an input parameter, and their development for parameterization of daily sums in any weather conditions using the daily air temperature amplitude as an input variable.
Acknowledgements: Funding for this research was provided by the National Science Centre, Poland under project UMO-2020/37/B/ST10/01219 and the University of Lodz under project 4/IDUB/DOS/2021. The authors thank the authorities of the Biebrza National Park for allowing continuous measurements in the area of the Park.
Provision of design temperatures
Authors: Hygen Hans Olav , Grinde Lars , Tajet Helga Therese Tilley , Dokka Tor Helge
Published: July 2023

To design a building adapted to local climate requires a number of different climate indicators, one of them is design temperatures (DUT) for summer and winter. 
The classic definition of summer design temperature was the maximum temperature exceeded 50 hours a typical year, and for winter the coldest three day average temperature. Looking into different descriptions of the DUT, there are distinct discrepancies. One example is for DUT-winter, where some instances describe the three coldest consecutive days and others the DUT-winter as a return period (e.g. 30 year) based on observations, similar for DUT-summer where some define it as 50 consecutive hours, others as individual hours summed together.
The above uncertainty of definition is combined with the uncertainty of representation. The classic construction of DUT is based on observations from a representative station, interpolated to e.g. the municipality of interest. This method opens for the uncertainty of representation of the observational site and correctness for the interpolation. 
Standards Norway contacted MET Norway to update the values of the DUT summer and winter in Norway to be calculated for the latest normal period, 1991 - 2020. In this work a new method to calculate DUT summer and winter was proposed and accepted:

Instead of using single observational sites as a base, national climate grids calculated on a daily basis at MET Norway covering the entire country with a 1x1 km resolution is used as a basis
Instead of a single temperature representing e.g. a single day is a statistical based approach applied. The method that was selected was a Bayesian-GEV approach where the output was calculated for 1 to 5 days average for highest and lowest mean temperature, with return values for 2-200 years. 

This new approach resolves partly the challenge of representativity and interpolation by using robust and well documented spatial interpolation. The statistical approach also provides more well documented and robust statistics than the older approach. This approach creates a challenge since the new datasets represent something different than the older approach, and thus challenges the standard built on these datasets. 
The distribution of the datasets will be renewed. Previously one had to buy the datasets from e.g. Standards Norway or other commercial vendors, the new dataset will be distributed openly from MET Norway, and implemented in e.g. the API frost.met.no 
Besides the DUT, an extended information package containing daily temperature range and absolute humidity is calculated based on representative stations.
Drought monitoring in Slovakia
Authors: Krčová Ivana , Turňa Maroš , Labudová Lívia , Ivaňáková Gabriela , Ridzoň Jakub , Holec Juraj
Published: July 2023

The drought is much discussed phenomena in the latest years, because of its more frequent occurrence and the stronger intensity. For this reason, the monitoring of dry conditions is very important. The Slovak Hydrometeorological Institute (SHMI) monitors the meteorological and soil drought since 2015, and then in 2017, the monitoring of the surface water level and monitoring of the water resources with the drought impacts on the agriculture and forestry was added in 2017. The products are public and freely available on the SHMI webpage. The monitoring aims on the evolution of climatic conditions regarding to the beginning, the development and intensity of drought. The monitoring of meteorological drought is updating on weekly basis and the additional product is the forecast of drought for following 10 days. The used indices are SPEI and SPI. Both indices are calculated using flowing window with accumulation period of 30 days. Nowadays, the monitoring is only for selected 41 meteorological stations, but it is planned to convert it to grid resolution 1 km and on daily basis. The monitoring of soil drought is produced on weekly basis in the cooperation with CzechGlobe, from Brno, Czech Republic. The soil data are computed by SoilClim model in 0.5x0.5 km grid. The one part of soil drought monitoring is the characterisation of drought impacts on local scale. Drought impacts are evaluated in forestry and agriculture by experts. The model results and the answers from questionnaire are annually summarized and compared themselves. In this case the cooperation among experts from various departments is inevitable.
Weather and climate and their human impacts during the Thirty Years’ War in Central Europe
Authors: Brázdil Rudolf , Dobrovolný Petr , Pfister Christian , Kleemann Katrin , Olinski Piotr , Szabó Péter , Chromá Kateřina
Published: July 2023

The Thirty Years’ War in 1618–1648 CE was an armed military conflict in Europe resulting from culminating contradictions between advocates of Roman Catholic and Protestant Churches during reformation time of the 17th century on the one hand and power fight for European political hegemony on the other. This war meant for Europe a time of its great wide-ranging devastation. Based on documentary evidence, the paper characterises climate, weather extremes, economic and socio-political events of that time in Central Europe (nowadays Germany, Poland, Czech Republic, Slovakia, Switzerland, Austria and Hungary). Natural climate forcing indicates a gradual climate deterioration during the first half of the 17th century, related to a decrease in solar activity towards the Maunder Minimum and increased volcanic activity starting in the early 1640s. More variable temperature, precipitation and drought patterns (with respect to the 1961–1990 reference period) were typical for 1618–1648 in Central Europe. Seasonal and annual temperatures experienced cooler patterns (except summer), while spring and annual precipitation totals indicated rather drier conditions. These climatic patterns were characterised by the occurrence of many weather extremes, from which particularly late spring and early autumn frosts, heavy rain spells, followed by floods, and intense droughts were reflected in failure of grain, fruit and vine grape harvests as well as low yields of other crops. The years 1627 and 1628 are discussed as possible “years without summer”. Weather extremes caused different human impacts and responses as food shortages (reflecting harvests and prices of grain), famines and epidemics, decline in population etc. Results are discussed in a broader European context with respect to climate, weather extremes and socio-economic impacts.
Downscaling of convection-permitting simulated precipitation for future projection
Authors: Nguyen Thi Quynh Trang , Cook Lauren
Published: July 2023

Convection-permitting regional climate models (CPRCMs) have emerged as a promising approach to produce high-resolution climate simulations as they are able to better represent sub-daily temperature and precipitation patterns and extreme values compared with coarser- resolution convection parameterizing simulations.  However, to bridge the gap between the grid scale (1-4 km) of CPRCMs and local spatial scale (ground station), bias-correction is still needed. The objective of our work is to test a statistical downscaling technique on CPRCMs to produce bias-corrected precipitation for a future period at the station level. Quantile mapping (QM) was chosen because this empirical method is among the most reliable and straightforward bias correction techniques. The quantile mapping process was implemented between CPRCM outputs for the historical period (1998 – 2009) and the point-scale observations and then applied to sub-hourly precipitation for the future period (2078 – 2089) in Zurich, Switzerland. Kloten station in Zurich was chosen to implement the experiment. At the same time, a simple nonparametric quantile mapping approach was used for other hourly climate variables such as temperature, relative humidity, air pressure, global radiation, and wind speed. The climate extremes indices for temperature and precipitation were also calculated to analyze the long-term climate trends in the study site. According to our results, the climate change signals of both precipitation and temperature were not altered during bias adjustment and the inter-variable dependencies were also preserved. Nevertheless, limitations of our approach still remain and future work is needed to determine whether more advanced techniques can improve sub-daily predictions for multiple climate variables. 
A climate modelling analysis of the Plan-B region in Vorarlberg, Austria
Authors: Goler Robert , Hollósi Brigitta , Kainz Astrid , Vergeiner Johannes , Ender Gerold
Published: July 2023

In order to plan and implement appropriate adaptation measures to protect settlements, the economy and other assets from natural hazards, it is important to know the potential consequences of climate change. Accordingly, the Plan-B model region within the Rhine Valley of the west-Austrian state of Vorarlberg is supported by the KLAR! program of the Austria Climate and Energy Fund to assist with this endeavour. The region encompasses some 91,000 inhabitants, making it one of the most densely populated regions in Austria. 
The focus of this work was on a detailed climate modelling study of the Plan-B region using the microscale urban climate model MUKLIMO_3. An accurate representation within the model involved processing input data from the Copernicus high-resolution datasets such as the digital elevation model, CORINE land cover, imperviousness and tree cover density supplemented by locally available building, land cover and vegetation data. The availability of measurements from a dense network of weather stations during July 2022 allowed the model accuracy to be evaluated for two case studies, and showed good results in representing the spatial variations of the region at a resolution of 50 m.
The modelling results from MUKLIMO_3 for the historical and current climate periods show hot-spots concentrated within the built-up urban areas. In such locations, annual averages of up to 70 summer days and 27 hot days are simulated for the period 1991-2020, consistent with the observations. Conversely, in the vicinity of water bodies such as Lake Constance, within parks or areas outside the urban fabric, annual averages of about 20-30 summer days and 2-8 hot days are more typical. From 1961 to 2020 the annual numbers of summer days, hot days and tropical nights are shown to increase across the entire domain reflecting the warming trend due to climate change. 
Climate model projection data from an ensemble of EURO-CORDEX models under the emissions scenarios RCP4.5 and RCP8.5 are input to show the expected heat load changes across the region for two future time periods. When compared with the 1991-2020 period, 2041-2070 can expect local increases of up to 20 summer days and 4 hot days for RCP4.5, and 28 summer days and 9 hot days for RCP8.5. A larger disparity in the results between the scenarios is shown for the period 2071-2100, with local increases of up to 56 summer days and 35 hot days for the extreme RCP8.5 scenario simulated relative to the 1991-2020 period. These results provide important information for decision makers and urban planners on where climate change adaptation measures to reduce heat load should be planned.
A Framework to Evaluate the Climate Models
Authors: Samantaray Alok , Mooney Priscilla , Vivacqua Carla
Published: July 2023

Many studies in climate change research rely on error metrics to evaluate the performance of climate models. However, the majority of these studies use only one or two metrics, which can limit the insights obtained from the analysis. This is because each metric evaluates only a specific aspect of the model-data relationship, and important information may be missed if not considered. To gain a more comprehensive understanding of model performance, it is necessary to use multiple error metrics. Doing so can reveal model strengths and weaknesses and provide insights for improving the model. Nevertheless, the choice of metrics should be based on the study's specific objectives and research questions, as different metrics may be more relevant or meaningful in different contexts. This study presents the Bergen Metric, a composite error metric that evaluates climate models' overall performance based on the p-norm framework. This approach utilizes a non-parametric clustering technique to reduce the number of error metrics without losing any relevant information. The research emphasizes the importance of using multiple error metrics to gain a thorough understanding of the model behavior. This study has evaluated 89 regional climate simulations of precipitation and temperature over Europe using 38 different error metrics for eight sub-regions in Europe, providing useful information about the metrics' performance in different regions. Furthermore, the study highlights the possibility of observing conflicting behavior among error metrics while examining a single model, underscoring the need for using multiple error metrics tailored to specific use cases. Overall, the Bergen Metric framework provides a useful tool to assess climate model performance and simplify the interpretation of results from multiple error metrics.