bluuebunny/crossref_metadata_2025 huggingface dataset:
Promotion of e-cigarettes by providers and users’ feedback in some social networks in Vietnam in 2019
Authors: Trang Nguyen Thi Thu , Ly Le Thi Huong , Toan Do Thi Thanh , Mai Vu Nhat , Thao Nguyen Thi Huong , Trang Vu Thu , Thao Nguyen Thi , Thai Pham Quang , Hoat Luu Ngoc , Son Dinh Thai , Nhan Nguyen Thi , Minh Luu Ngoc
Published: June 2021

E-cigarettes (e-cigarettes) have been using social media as an informative platform to promote e-cigarettes for their users. The most popular social media in Vietnam were YouTube and Facebook. The information and knowledge could affect e-cigarette user’s belief and the way they make a decision. Despite this, there is a gap in our knowledge of policy maker’s in user’s perceptions about how they feel with promotion on social media platform in Vietnam. This study aimed to describe the promotion of e-cigarettes by providers on some social networks and to describe electronic cigarette users’ feedback about videos/posts of providers on some social networks in Vietnam in 2019. Searches in major electronic databases, including Facebook and YouTube, were conducted using the following search terms: “electronic cigarette,” “electronic vaporizer,” “electronic pod,”. The video/post was selected if they’re from providers and include advertising content on the social media platform during 2019. Of the 104 e-cigarette related videos/posts retrieved, there were 27% on Facebook and 28% on YouTube. The three most common advertising contents were beneft of using e-cigarette, negative health consequences and entertainment effects.
Textos mínimos
Authors:   Facultad de Artes y Humanidades, Universidad de los Andes, Camacho Guizado Eduardo
Published: June 2021

Textos mínimos es una colección de 54 poemas breves en los que la voz poética reflexiona sobre el lenguaje y su conexión con el momento vital de la madurez y la cercanía de la muerte. Los poemas evocan el género de haiku pero no son exactamente haikus, son “falsos haikus”, según el poeta, pues no cumplen las normas de versificación, de por sí complejas en el momento de la adaptación a lenguas diferentes del japonés. Sin embargo, los poemas hacen algo muy similar a lo que hace un haiku: captura, o intenta capturar, la esencia del instante, su riqueza evocadora y a veces nostálgica pero siempre reveladora, en conexión con un asunto vital para la experiencia del poeta.
SO2 and BrO emissions of Masaya volcano from 2014 to 2020
Authors: Dinger Florian , Kleinbek Timo , Dörner Steffen , Bobrowski Nicole , Platt Ulrich , Wagner Thomas , Ibarra Martha , Espinoza Eveling
Published: June 2021

Abstract. Masaya (Nicaragua, 12.0∘ N, 86.2∘ W; 635 m a.s.l.) is one of the few volcanoes hosting a lava lake, today. This study has two foci: (1) discussing the state of the art of long-term SO2 emission flux monitoring with the example of Masaya and (2) the provision and discussion of a continuous data set on volcanic gas data with a large temporal coverage, which is a major extension of the empirical database for studies in volcanology as well as atmospheric bromine chemistry. We present time series of SO2 emission fluxes and BrO/SO2 molar ratios in the gas plume of Masaya from March 2014 to March 2020 – covering the three time periods (1) before the lava lake appearance, (2) a period of high lava lake activity (November 2015 to May 2018), and (3) after the period of high lava lake activity. For these three time periods, we report average SO2 emission fluxes of (1000±200), (1000±300), and (700±200) t d−1 and average BrO/SO2 molar ratios of (2.9±1.5)×10-5, (4.8±1.9)×10-5, and (5.5±2.6)×10-5. Our SO2 emission flux retrieval is based on a comprehensive investigation of various aspects of spectroscopic retrievals, the wind conditions, and the plume height. We observed a correlation between the SO2 emission fluxes and the wind speed in the raw data. We present a partial correction of this artefact by applying dynamic estimates for the plume height as a function of the wind speed. Our retrieved SO2 emission fluxes are on average a factor of 1.4 larger than former estimates based on the same data. Further, we observed different patterns in the BrO/SO2 time series: (1) an annual cyclicity with amplitudes between 1.4 and 2.5×10-5 and a weak semi-annual modulation, (2) a step increase by 0.7×10-5 in late 2015, (3) a linear trend of 1.4×10-5 per year from November 2015 to March 2018, and (4) a linear trend of -0.8×10-5 per year from June 2018 to March 2020. The step increase in 2015 coincided with the lava lake appearance and was thus most likely caused by a change in the magmatic system. We suggest that the cyclicity might be a manifestation of meteorological cycles. We found an anti-correlation between the BrO/SO2 molar ratios and the atmospheric water concentration (correlation coefficient of −0.47) but, in contrast to that, neither a correlation with the ozone mixing ratio (+0.21) nor systematic dependencies between the BrO/SO2 molar ratios and the atmospheric plume age for an age range of 2–20 min after the release from the volcanic edifice. The two latter observations indicate an early stop of the autocatalytic transformation of bromide Br− solved in aerosol particles to atmospheric BrO.
Identification of snowfall microphysical processes from Eulerian vertical gradients of polarimetric radar variables
Authors: Planat Noémie , Gehring Josué , Vignon Étienne , Berne Alexis
Published: June 2021

Abstract. Polarimetric radar systems are commonly used to study the microphysics of precipitation. While they offer continuous measurements with a large spatial coverage, retrieving information about the microphysical processes that govern the evolution of snowfall from the polarimetric signal is challenging. The present study develops a new method, called process identification based on vertical gradient signs (PIVSs), to spatially identify the occurrence of the main microphysical processes (aggregation and riming, crystal growth by vapor deposition and sublimation) in snowfall from dual-polarization Doppler radar scans. We first derive an analytical framework to assess in which meteorological conditions the local vertical gradients of radar variables reliably inform about microphysical processes. In such conditions, we then identify regions dominated by (i) vapor deposition, (ii) aggregation and riming and (iii) snowflake sublimation and possibly snowflake breakup, based on the sign of the local vertical gradients of the reflectivity ZH and the differential reflectivity ZDR. The method is then applied to data from two frontal snowfall events, namely one in coastal Adélie Land, Antarctica, and one in the Taebaek Mountains in South Korea. The validity of the method is assessed by comparing its outcome with snowflake observations, using a multi-angle snowflake camera, and with the output of a hydrometeor classification, based on polarimetric radar signal. The application of the method further makes it possible to better characterize and understand how snowfall forms, grows and decays in two different geographical and meteorological contexts. In particular, we are able to automatically derive and discuss the altitude and thickness of the layers where each process prevails for both case studies. We infer some microphysical characteristics in terms of radar variables from statistical analysis of the method output (e.g., ZH and ZDR distribution for each process). We, finally, highlight the potential for extensive application to cold precipitation events in different meteorological contexts.
Committed and projected future changes in global peatlands – continued transient model simulations since the Last Glacial Maximum
Authors: Müller Jurek , Joos Fortunat
Published: June 2021

Abstract. Peatlands are diverse wetland ecosystems distributed mostly over the northern latitudes and tropics. Globally they store a large portion of the global soil organic carbon and provide important ecosystem services. The future of these systems under continued anthropogenic warming and direct human disturbance has potentially large impacts on atmospheric CO2 and climate. We performed global long-term projections of peatland area and carbon over the next 5000 years using a dynamic global vegetation model forced with climate anomalies from 10 models of the Coupled Model Intercomparison Project (CMIP6) and three standard future scenarios. These projections are seamlessly continued from a transient simulation from the Last Glacial Maximum to the present to account for the full transient history and are continued beyond 2100 with constant boundary conditions. Our results suggest short to long-term net losses of global peatland area and carbon, with higher losses under higher-emission scenarios. Large parts of today's active northern peatlands are at risk, whereas peatlands in the tropics and, in case of mitigation, eastern Asia and western North America can increase their area and carbon stocks. Factorial simulations reveal committed historical changes and future rising temperature as the main driver of future peatland loss and increasing precipitations as the driver for regional peatland expansion. Additional simulations forced with climate anomalies from a subset of climate models which follow the extended CMIP6 scenarios, transient until 2300, show qualitatively similar results to the standard scenarios but highlight the importance of extended transient future scenarios for long-term carbon cycle projections. The spread between simulations forced with different climate model anomalies suggests a large uncertainty in projected peatland changes due to uncertain climate forcing. Our study highlights the importance of quantifying the future peatland feedback to the climate system and its inclusion into future earth system model projections.
Simulating glacial dust changes in the Southern Hemisphere using ECHAM6.3-HAM2.3
Authors: Krätschmer Stephan , van der Does Michelle , Lamy Frank , Lohmann Gerrit , Völker Christoph , Werner Martin
Published: June 2021

Abstract. Mineral dust aerosol constitutes an important component of the Earth’s climate system, not only on short timescales due to direct and indirect influences on the radiation budget, but also on long timescales by acting as a fertilizer for the biosphere and thus affecting the global carbon cycle. For a quantitative assessment of its impact on the global climate, state-of-the-art atmospheric and aerosol models can be utilized. In this study, we use the ECHAM6.3-HAM2.3 model to perform global simulations of the mineral dust cycle for present-day (PD), pre-industrial (PI) and Last Glacial Maximum (LGM) climate conditions. The intercomparison with marine sediment and ice core data as well as other modeling studies shows that the obtained annual dust emissions of 1221, 923 and 5159 Tg for PD, PI and LGM, respectively, generally agree well with previous findings. Our analyses focussing on the Southern Hemisphere suggest that over 90 % of the mineral dust deposited over Antarctica are of Australian or South American origin during both PI and LGM. However, contrary to previous studies, we find that Australia contributes a higher proportion during the LGM, which is mainly caused by changes in the precipitation patterns. Obtained increased particle radii during the LGM can be traced back to increased sulphate condensation on the particle surfaces as a consequence of longer particle lifetimes. The meridional transport of mineral dust from its source regions to the South Pole takes place at different altitudes, depending on the grain size of the dust particles. We find a trend of generally lower transport heights during the LGM compared to PI as a consequence of reduced convection due to colder surfaces, indicating a vertically less extensive Polar Cell.
Local-scale wind speed features captured by seasonal forecasts
Authors: Ramon Jaume , Lledó Llorenç , Bretonnière Pierre-Antoine , Samsó Margarida , Doblas-Reyes Francisco J.
Published: June 2021

Thanks to the recent advances in climate modelling, seasonal predictions are becoming more skilful at anticipating the future state of near-surface climate variables over extratropics. Nevertheless, such predictions are delivered on too coarse grids with horizontal resolutions of hundreds of kilometres so that local events happening at much finer scales cannot be reproduced. This is particularly noted for variables with high spatial variability like wind or precipitation: wind speeds can vary substantially over a few kilometres, from the top of a mountain to a valley floor. The differences in magnitude might be relevant for the deriving sectoral indicators, for example, within the wind industry and at a wind farm level.

This work presents and applies a downscaling methodology to generate fine-scale seasonal forecasts ---up to station scale--- for near-surface wind speeds in Europe. The hybrid forecasts are based on a statistical downscaling with a perfect prognosis approach, fitting a multi-linear regression with the four main Euro-Atlantic Teleconnections (EATC) indices as predictors. Seasonal predictions of EATC indices, which are predictable with relatively good skill levels, are later inserted into the multi-linear model. This results in skilful seasonal predictions of surface wind speeds. Indeed, the comparison of the hybrid forecasts against the dynamical forecasts of wind speed shows that the skill of such forecasts is not only maintained but also increased over most of Europe. The hybrid forecasts are generated at 17 locations where tall tower wind speed data are available and at a pan-European scale using the 100-metre wind speeds from the ERA5 reanalysis. Improving the accuracy of seasonal predictions is an essential step to inform weather-and-climate-vulnerable socio-economic sectors of seasonal anomalies a few months ahead.
Spatial structure of the Surface Urban Heat Island in summer based on Landsat 8 imagery in the Górnośląsko – Zagłębiowska Metropolis, Southern Poland 
Authors: Renc Aleksandra , Łupikasza Ewa , Błaszczyk Małgorzata
Published: June 2021

Urbanization results in the increase of impervious surfaces build of materials with high heat capacity and low albedo. Therefore, urban areas heat up more than the surroundings, leading to the development of the urban heat island (UHI). The UHI intensifies the effect of global warming by increased intensity and frequency of heatwaves in the city. In summer, the UHI is considered a phenomenon hazardous for the life and health of city inhabitants. The problem of UHI has not been studied in the Górnośląska-Zagłębiowska Metropolis (GZM), which is the most populated area in Poland. This study aims to determine the spatial structure and intensity of the surface urban heat island (SUHI) in GZM and identify the areas exposed to the most intense heat island. The relationship between the type of land use and the SUHI occurrence was also studied. Four LANDSAT 8 images were converted to the form of land surface temperature (LST). Based on the mean and standard deviation of the LST the extent of the overall SUHI was determined without considering the type of land use. Based on the same method, three classes of SUHI intensity (standard, strong and extreme) were defined and distinguished within anthropogenic areas determined based on the Corine Land Cover 2018 classification of land use. The intensity of SUHI was defined as a difference between urban and non-urban areas. The relationships between various types of land use and LST were also examined. In GZM, SUHI has a structure of 'archipelago' rather than an 'island'. In each image, the highest LSTs were identified for industrial areas represented by Katowice Smeltery. The standard SUHI, defined as average LST +1 standard deviation (only within an anthropogenic area) accounted for 12.7% to 14.4% of the GZM area in individual years, which indicates a small temporal variability of its extent. The extreme SUHI was identified mainly for shopping and logistic centers, industrial facilities, or coal dumps. The intensity of SUHI ranged from 5 to 9 °C depending on the image and method of urban and non-urban areas delineating. The highest average LST was characteristic of the discontinuous urban fabric and industrial or commercial units. Water and forest areas had the lowest average LST. The discontinuous urban fabric and industrial or commercial units constituted more than 70% of the overall SUHI area.
The European Climate Data Explorer - a new web portal providing interactive access to climate change information for Europe 
Authors: Füssel Hans-Martin , Almond Samuel
Published: June 2021

The Copernicus Climate Change Service’s (C3S) Climate Data Store (CDS) contains a wealth of information about the Earth's recent past, present and future climate. The CDS catalogue contains both general climate datasets, such as climate observations, seasonal forecasts, global and regional reanalyses and global and regional climate projections datasets, and in addition derived Climate Impact Indices (CII). CIIs are processed data which was developed to respond to specific sectoral needs. Most CII datasets were developed as part of the C3S Sectoral Information System (SIS) activities, which develops user-oriented products for various climate-sensitive sectors (e.g., water management, energy, biodiversity, human health and tourism).

The European Climate Data Explorer (ECDE) is a new web portal providing interactive access to selected climate variables and indices included in the CDS. It is hosted on the European Climate Adaptation Platform (Climate-ADAPT), a publicly accessible web portal managed by the European Environment Agency (EEA) in collaboration with the European Commission. The ECDE aims to facilitate access to a wide range of data on observed and projected climate change in Europe. Such data are relevant, among others, for developing and implementing national and subnational climate adaptation strategies and plans, including sectoral strategies.

The variables and indices currently included in the ECDE reflect user needs expressed through an EEA-led stakeholder consultation as well as data availability from C3S-led SIS contracts. The interactive access allows users to zoom in on maps in order to focus on regions of interest, show time series for specific countries and subnational regions (to NUTS level 3), and export images and data. The ECDE will be expanded further in response to user needs and increasing data availability in the CDS. This expansion will include additional sectoral indices as well as new data sources (e.g. from CMIP6).

The ECDE is complemented by the online EEA Report Changing climate hazards in Europe and a Technical Paper. These products provide further information on the underlying indices and datasets. The report also presents past and projected trends for key climate hazards across Europe.

The ECDE lowers the technical hurdles that limit access to CDS data for a large part of EEA’s target audience. Doing so, the ECDE supports the European Green Deal, including the new EU Strategy on Adaptation to Climate Change, and the EU Mission on Adaptation to climate change including societal transformation.
Modeling phenology of the Central European apple: The seasonal forecast application perspective
Authors: Firanj Sremac Ana , Lalic Branislava , Eitzinger Josef , Schneider Stefan
Published: June 2021

Tree phenology dynamic is the direct response of the plant to seasonal environmental conditions. Therefore, most trees have been strongly impacted by the increasing frequency of extreme weather events caused by global warming. In the past decade, fruit production in Europe has suffered a catastrophic failure of the yield because of the extreme and adverse weather events occurring (mostly frost) during winter dormancy and tree flowering. Therefore, forecasting the phenological development on the seasonal time scale can help in the organization of the prevention measures in the upcoming production season.

The Central European apple orchards' phenology dynamics are analyzed using the first bloom data and meteorological measurements collected during the COMBIRISK project. Projection to Latent Structures regression analysis (PLSR) from the ChillR package (https://cran.r-project.org/web/packages/chillR/index.html) is used to analyze two dormancy stages in the phonological development: endodormancy (chilling period) and ecodormancy (forcing period) in order to determine the changes in the phenological development patterns. Flowering is modeled considering chilling and forcing plant requirements and focusing on the temperature stresses impact through the stress factor calibration.

ECMWFs seasonal forecasts (SEAS5) are statistically downscaled by the Austrian national weather service (ZAMG) to a 1 km horizontal grid. These seasonal forecasts are used as input meteorological data for the apple phenology dynamic model in the AGROFORECAST project. Obtained results are compared with the observed timing of flowering to test the efficacy of available seasonal forecast for this application. This study is supported by the Ministry of education, science and technological development of the Republic of Serbia (agreement 451-03-9/2021-14/200117). 
Multi-model assessment of the late-winter stratospheric response to El Niño and La Niña
Authors: Mezzina Bianca , Palmeiro Froila M. , García-Serrano Javier , Bladé Ileana , Batté Lauriane , Benassi Marianna
Published: June 2021

The impact of El Niño-Southern Oscillation (ENSO) on the late-winter extra-tropical stratosphere (January-March) is assessed in a multi-model framework. Three state-of-the-art atmospheric models are run with prescribed SST anomalies representative of a strong ENSO event, with symmetric patterns for El Niño and La Niña. The well-known temperature perturbation in the lower stratosphere during El Niño is captured by two models, in which the anomalous warming at polar latitudes is accompanied by a positive geopotential height anomaly that extends over the polar cap. In the third model, which shows a lack of temperature anomalies over the pole, the anomalous anticyclone is confined over Canada and does not expand to the polar cap. This anomalous center of action emerges from the large-scale tropospheric Rossby wave train forced by ENSO, and conservation of potential vorticity around the polar vortex is invoked to link it to the temperature response. No disagreement across models is found in the lower stratosphere for La Niña, whose teleconnection is opposite in sign but weaker. In the middle-upper stratosphere (above 50 hPa) the geopotential height anomalies project on a wavenumber-1 (WN1) pattern for both El Niño and, more weakly, La Niña, and show a westward tilt with height up to the stratopause. It is suggested that this WN1 pattern arises from the high-latitude lower-stratospheric anomalies, and that the ENSO teleconnection to the polar stratosphere can be interpreted in terms of upward propagation of the stationary Rossby wave train and quasi-geostrophic balance, instead of wave breaking.
The multi-model assessment, with 50 members for each experiment, contributes to the ERA4CS-funded MEDSCOPE project and includes: EC-EARTH/IFS (L91, 0.01hPa), CNRM/ARPEGE (L91, 0.01hPa), CMCC/CAM (L46, 0.3hPa).
Upgrade of a climate service tailored to water reservoirs management 
Authors: Sánchez-García Eroteida , Abia Inmaculada , Domínguez Marta , Voces José , Sánchez-Perrino Juan Carlos , Navascués Beatriz , Rodríguez-Camino Ernesto , Garrido Mª Nieves , Pastor Fernando , García-Gómez Mª Concepción , Dimas Mirta , Barranco Luis , Ruíz Carlos
Published: June 2021

In this paper we present the upgrade  of  a web tool designed to help in the decision making process for water reservoirs management in Spain. The tool, called S-ClimWaRe (Seasonal Climate predictions in support of Water Reservoirs management) is organized in two main displaying panels. The first one -diagnostic panel- allows the user to explore, for any water reservoir or grid point over continental Spain, the existing hydrological variability and risk linked to climate variability.  The second one -forecasting panel- provides probabilistic seasonal predictions for some variables of interest. Following users’ need the tool initially covers the extended winter season (from November to March), when the North Atlantic Oscillation pattern strongly influences the hydrological interannual variability in South-Western Europe. This climate service is fully user driven with a strong commitment of users and stakeholders that has allowed  continuous improvement of this tool, meeting users requirements and incorporating latest scientific progress.
The latest S-ClimWaRe version -developed in the framework of the MEDSCOPE project within the European Research Area for Climate Services (ERA4CS) initiative- includes some technical enhancements requested by customers and new seasonal predictions obtained through application of two post-processing steps to ECMWF System-5 forecasts. These two steps consist of a  downscaling statistical procedure and a new methodology that combines different skilful NAO forecasts to create an optimal NAO pdf that is then used to weight the ensemble members forecasts of hydrological variables. The new upgraded S-ClimWaRe web tool enriches the forecasting panel with precipitation and water inflow forecast skill, and provides additional forecasts for accumulated snowfall and temperature. A prototype based on two different hydrological models to produce the seasonal forecasts of water inflow has also been tested over a pilot dam. These hydrological models are driven by the  downscaled precipitation and temperature forecasts also introduced in the web viewer. The assessment of this downscaling procedure shows promising results with respect to the existing seasonal forecasts based on a statistical approach.
The climate impact of the Drake Passage opening from a fluid dynamics point of view: the role of Antarctic glaciation
Authors: Herein Matyas , Vinzce Miklos , Bozoki Tamas , Dan Borcia Ion , Harlander Uwe , Horicsanyi Attila , Nyerges Anita , Rodda Constanza , Pal Andras , Palfy Jozsef
Published: June 2021

Pronounced global cooling around the Eocene-Oligocene transition (EOT) was a pivotal event in Earth’s climate history, controversially associated with the opening of the Drake Passage.  Using a physical laboratory model we revisit the fluid dynamics of this marked reorganization of ocean circulation. Our differentially heated rotating annulus is a widely studied experimental set-up designed to model mid-latitude circulation in the atmosphere and the ocean, as well. Here we show, seemingly contradicting paleoclimate records that in our experiments opening the pathway yields higher values of mean water surface temperature than the “closed” configuration. This mismatch points to the importance of the crucial role ice albedo feedback plays in the investigated EOT-like transition, a component that is not captured in the laboratory model. Our conclusion is supported by numerical simulations performed in a global climate model (GCM) of intermediate complexity, where both “closed” and “open” configurations were explored, with and without active ice-albedo feedback. The GCM results indicate that sea surface temperatures would change in the opposite direction following an opening event in the two ice dynamics settings, and the results are therefore consistent both with the laboratory experiment (slight warming after opening) and the paleoclimatic data (pronounced cooling after opening). It follows that in the hypothetical case of an initially ice-free Antarctica the continent could have become even warmer after the opening, a scenario not indicated by paleotemperature reconstruction. These results provide circumstantial evidence supporting a particular EOT scenario in which Antarctica had already been – at least partially – covered with ice when the Drake Passage fully opened.
Forecasting of Meteorologically Driven “Extremes” in Wind and Solar Power: Can We Tackle and Improve Selected Cases of Non-forecasted Extreme Events using Deep Learning?
Authors: Papazek Petrina , Schicker Irene , de Wit Rosmarie
Published: June 2021

With the rapid transition towards an increased usage of renewable energy accurate predictions of the expected power production are needed to ensure grid stability, energy trading, and (re)scheduling of maintenance and energy transfer. In the last decades, both numerical weather prediction models as well as post-processing methods have significantly improved their prediction skills when applied to renewable energy. There are, however, events in renewable energy production which can be considered as extreme events but are not necessarily extremes in terms of meteorological conditions. The MEDEA project, funded by the Austrian Climate Research Program, aims at improving the definition and detection of extreme events relevant for renewable energies and to use these findings to improve both weather and climate predictions of such extreme events. In this MEDEA case study, we investigate selected (extremes) cases in renewable energy which were not properly reproduced by the models. We will have a deeper dive into two Saharan dust events in 2021 where none of the models was able to properly reproduce the amount of aerosols in Central Europe and solar power production was off by more than 5 GW in contrast to the predictions.  Here, several NWP models have failed to properly recognize its impact and, thus, impaired results based on raw model output. To tackle such events and improve the predictability, a deep learning framework consisting of an auto-encoder LSTM (long short-term memory; type of an artificial neural network) and random forest will be used and adopted for day-ahead predictions of these events. Relevant features for the learning algorithms are extracted from different NWP models, satellite data, and observations. Similarly, for wind energy production we demonstrate the methods in two selected case studies of extreme events. Results obtained by the deep learning framework yield, in general, high forecast-skills where we elaborate on interesting cases studies from a meteorological point of view. Different combinations of inputs and processing-steps are part of the analysis. We compare results to traditional forecast methods in order to validate the performance of our methods.
Assessment of seasonal forecast skills of temperature and precipitation: a comparison of 5 different models over the Mediterranean region
Authors: Calì Quaglia Filippo , Terzago Silvia , von Hardenberg Jost
Published: June 2021

Seasonal forecasts are increasingly employed as sources of information on the expected evolution of climate in the few months ahead by various end-users. This study provides an overall assessment of the skills of the main seasonal forecast systems available in the Copernicus Climate Data Store (C3S) in representing temperature and precipitation anomalies at the monthly time scale. The focus area is the Mediterranean, a densely populated region identified as a hotspot for climate change, where seasonal forecasts could be useful to a variety of economic sectors, including water management, hydropower production, agriculture.

In this study, seasonal forecast systems issued by 5 European institutions (ECMWF, Météo-France, UKMO, DWD, CMCC), together with two different Multi-Model Ensembles (MME) derived from them, have been analysed. The added value of these forecast systems with respect to simpler forecast approaches based on climatology and persistence has been investigated.

Different deterministic (Anomaly Correlation Coefficient) and probabilistic scores (Ranked Probability Score, Continuous Ranked Probability Score and Receiver Operating Characteristic Curve) have been employed to obtain an overall assessment of the quality of the forecasts (as of Murphy, 1993 and WMO, 2018), using ERA5 dataset as a reference. We performed the analysis using 6-month forecasts starting in May and November to reproduce the following summer and the winter seasons.

In general, temperature patterns and respective skill scores are better reproduced than those regarding precipitation. The anomaly correlation coefficients for MME reach the best agreement values for each season and variable except for winter temperature. Different behaviours are found for the different skill scores; their high spatial variability suggests that smaller regions could perform better for a single variable or starting date. Seasonal forecast systems, despite some limitations, show an added value with respect to simple forecast approaches based on the climatology or persistence.
Seasonal forecasting of mountain snow resources: evaluation of a climate service prototype
Authors: Terzago Silvia , Bongiovanni Giulio , von Hardenberg Jost
Published: June 2021

Warming trends in the past decades in mountain regions have resulted in glacier shrinking, seasonal snow cover reduction, changes in the amount and seasonality of meltwater runoff (IPCC, 2019), and we expect droughts to become more severe in the future (Haslinger et al., 2014) with consequences for both mountain and downstream economies. Effective adaptation strategies to address and reduce negative climate change impacts involve multiple time scales, from the long-term support of mountain water resource management and the diversification of mountain tourism activities, to the seasonal scale, for the optimization of the available snow resources. 

In the frame of the MEDSCOPE project we developed a prototype to generate seasonal forecasts of mountain snow resources, in order to estimate the temporal evolution of the depth and the water content of the snowpack with lead times of several months. The prototype has been tailored on the needs of water and hydropower plant managers and of mountain ski resorts managers. We present the modelling chain, based on the seasonal forecasts of ECMWF and Météo-France seasonal prediction systems, made available through the Copernicus Climate Change Service (C3S). Seasonal forecasts of precipitation, near-surface air temperature, radiative fluxes, wind and humidity are bias-corrected and downscaled to the site of Bocchetta delle Pisse 2410 m a.s.l. in the North-Western Italian Alps, and finally used as input for a physically-based multi-layer snow model (SNOWPACK, Bartelt and Lehning, 2002). The RainFARM stochastic downscaling procedure (Terzago et al., 2018) is used for precipitation data in order to allow an estimate of uncertainties linked to small-scale variability in the forcing.

The skills of the prototype in predicting the snow depth evolution from November 1st to May 31st in each season of the hindcast period 1995-2015 are demonstrated using station measurements as a reference. We show the correlation between forecast and observed snow depth anomalies and we quantify the forecast quality in terms of reliability, resolution, discrimination and sharpness using a set of probabilistic measures (Brier Skill Score, the Area Under the ROC Curve Skill Score and the Continuous Ranked Probability Skill Score). Implications of the forecast quality at different lead times on climate services are discussed. 

Real-time snow forecasts for the current season (2020-2021) are available at this link: http://wilma.to.isac.cnr.it/diss/snowpack/snowseas-eng.html
On the role of Eurasian autumn snow cover in dynamical seasonal predictions 
Authors: Ruggieri Paolo , Benassi Marianna , Materia Stefano , Peano Daniele , Ardilouze Constantin , Batté Lauriane , Gualdi Silvio
Published: June 2021

Seasonal climate predictions leverage on many predictable or persistent components of the Earth system that can modify the state of the atmosphere and of relant weather related variable such as temprature and precipitation. With a dominant role of the ocean, the land surface provides predictability through various mechanisms, including snow cover, with particular reference to Autumn snow cover over the Eurasian continent. The snow cover alters the energy exchange between land surface and atmosphere and induces a diabatic cooling that in turn can affect the atmosphere both locally and remotely. Lagged relationships between snow cover in Eurasia and atmospheric modes of variability in the Northern Hemisphere have been investigated and documented but are deemed to be non-stationary and climate models typically do not reproduce observed relationships with consensus. The role of Autumn Eurasian snow in recent dynamical seasonal forecasts is therefore unclear. In this study we assess the role of Eurasian snow cover in a set of 5 operational seasonal forecast system characterized by a large ensemble size and a high atmospheric and oceanic resolution. Results are compemented with a set of targeted idealised simulations with atmospheric general circulation models forced by different snow cover conditions. Forecast systems reproduce realistically regional changes of the surface energy balance associated with snow cover variability. Retrospective forecasts and idealised sensitivity experiments converge in identifying a coherent change of the circulation in the Northern Hemisphere. This is compatible with a lagged but fast feedback from the snow to the Arctic Oscillation trough a tropospheric pathway.
A Study on the Severe Precipitation Induced by the Meiyu Front in Taiwan
Authors: Hou Jou Ping , Su Li-Zhen
Published: June 2021

Along the coast of northwestern Taiwan, when the Meiyu front passed, there were occasional rapids caused by the terrain, and after convergence with the prevailing wind field, it caused severe precipitation. In 1987, some studies conducted by Taiwan mesoscale experiment (TAMEX) found that low-level jet (about 1 km high) under certain conditions, known as barrier jet, strongly affected the heavy rainfall in northern Taiwan. On the morning of June 2, according to the results of the study in the Meiyu frontal contact north Taiwan, in just 12 hours later to Keelung and north coast down to the super heavy rain of reason, may be related to frontal subject in northern Taiwan snowy mountains, the enhancement of barrier jets occurring near the surface height is related to the increase in barrier jets during the movement of the frontal body. The results of this study show that when the Meiyu front moves southeast, the enhancement of the convective system on the front may cause by a larger inclination angle with its front, with appropriate movement speed, through the southwest airflow in front of the Meiyu front, especially a barrier of about 1 km in height. The warm and humid air introduced by the jet is related. Strong convection will develop in a forced convergence zone off the northwestern part of Taiwan, and the convergence zone is mainly caused by a combination of sub-synoptic forcing such as low-level wind shear convergence, barrier jets, and convective feedback of non-adiabatic terms. In addition, due to the existence of the barrier jet and the frontal wind shear zone, cyclonic circulation around the jet area was generated. With the instability of the temperature gradient and the enhancement of the abnormal zone of the positive potential vorticity, it is speculated that it should be the cause of the severe precipitation in this case. Because the biggest difference between the first and the second strong precipitation may come from the complicated topographic effect and limited space, this research focuses on the reasons for the development of the first severe weather development and heavy precipitation.
About simulated influence of roof- and wall-greening on an old people’s home in Helsinki, Finland, during the 2018 heatwave event - Drebs, Achim, …
Authors: Drebs Achim , Sinsel Tim , Jylhä Kirsti
Published: June 2021

Due to geographical location extended heat-waves occurs in coastal high-latitude areas or cities rather seldom.

In our research we describe influences of roof- and wall-greening on micro-meteorological conditions around (and in?) a moderate insulated stand-alone six-storey concrete building in Helsinki, Finland. The block of flats serves as an old people's home and being built in the late 1970’s, it represents the prevailing construction type of that era. The building is located on a slightly southwards declining slope, and the neighbouring buildings are 30 meters away.

We applied the holistic ENVI-met simulation soft-ware and used real meteorological forcing-data as input for the simulations.  The study focused on a 24-day heat-wave event in summer 2018. During the period from July, 13th until August, 5th, the daily maximum air temperature reached almost every day 25 °C and more, sometimes even more than 30 °C. All one-hour air temperature, wind, humidity, and solar radiation (cloudiness) measurements were conducted at a near-by synoptic weather station.

 The ENVI-met soft-ware has standard set-ups for green roof and green wall properties for simulations of their impacts on the thermal condition. We simulated different levels of insulation (poor, moderate, and good) and used the roof- and wall-greening separately or together in order to find the optimal combination of different greening options. Furthermore, we analysed the physical environment around the old people’s home from the aspect of human comfort, especially the influences of the simulated green infrastructures in front of the building.

The research is part of the HEATCLIM-project financed by the Academy of Finland Science Program CLIHE (2020-2023).
Changes in African extreme precipitation and storm structure since 1981 revealed by satellite observations
Authors: Marra Francesco , Cattani Elsa
Published: June 2021

Quantifying past changes in extreme precipitation is crucial to understand the climate response and improve our projections. Due to the limited data availability, information about Africa is of particular interest. We combine high-resolution satellite estimates (CHIRPSv2) with an innovative approach for the detection and attribution of trends in extremes (both annual maxima and rarer events, such as the 100-year return levels) to investigate changes in daily precipitation extremes and storm structure occurred over Africa since 1981. Scale-dependence is explored by comparing trends detected at the local (0.05° resolution) and meso- (1°) scales. The statistical model was validated using a gauge-based dataset (GPCC) before application to satellite estimates. 

Roughly ~20% of the continent experienced significant (p=0.05) changes in annual maxima at both scales. Decreasing trends are observed in the central portion of the continent, and increasing trends in the Sahel and some districts in southern and eastern Africa. Storms tended to become spatially smoother, with faster decreases at the local scales (median=13% faster for annual maxima, 14% for 100-year return levels) and faster increases at the mesoscales (17% for annual maxima, 16% for 100-year return levels). The 100-year return levels increased 33% (25% at the mesoscale) faster than annual maxima and decreased 43% (45%) faster.

The model explains 89% (91% at the mesoscale) of the variance in the observed significant trends. Changing proportions between heavy and mild events explain 25% (38%) of this variance, changes in the overall intensities 13% (21%), and changes in the number of wet days 4% (12%). About ~25% of the area experienced significant trends in at least one model parameter, although no significant trend could be detected in the maxima. Censoring annual maxima, the model still explains 77% of the variance in their trends, suggesting it could be effectively used in situations in which observed/modelled extremes are not trusted.
Hail detection from high-frequency radiometers on the GPM constellation. A new prospect for a global hailstorm climatology
Authors: Laviola Sante , Monte Giulio , Levizzani Vincenzo , Ferraro Ralph R. , Beauchamp James
Published: June 2021

Hail detection is an open issue from the remote sensing point of view both from the ground and from space. Hail is extremely difficult to observe using passive and active sensing due to signal attenuation and the relatively scarce knowledge of the cloud structure in hailstorms. Several approaches have been recently proposed mainly using radar data from the ground in connection with observations in the visible and infrared from geostationary satellites. High frequency MWs aboard to airborne and satellite were also used to infer hail patterns. The potential of the 90–190 GHz frequency range when employed in the classification of cloud types and in the detection of signals from different hail sizes was recently proved by Laviola et al. 2020 and Ferraro et al. (2020) extending previous approaches to these frequencies that are now available on several platforms. MW high frequencies offer the advantage of very high sensitivity to the scattering signature from different ice particles with diameters from a few millimeters to 10s of centimeters. Thus, we are able to classify the region of convective clouds where different hail sizes are generated by identifying severity areas characterized by small ice aggregates potentially forming hail, large hail and super hail. In this work, a probability-based model originally designed for AMSU-B/MHS (Laviola et al, 2020) has been fitted to the observations of all MHS-like radiometers onboard the satellites of the GPM constellation. All MHS-like frequency channels in the 150-170 GHz frequency range were adjusted on the MHS channel at 157 GHz in order to account for the instrumental differences and tune the original model on the MHS-like technical characteristics. The novelty of this approach offers the potential of retrieving a uniform and homogeneous hail dataset on the global scale. Currently running on 10 MHS-like radiometers orbiting on the GPM constellation, the application of the hail detection model demonstrates the high potential of this generalized model to map the evolution of hail-bearing systems at very high temporal rate. The results on the global scale also demonstrate the high performances of the hail model in detecting the differences of hailstorm structure across the two hemispheres by means of a thorough reconstruction of the seasonality of the events particularly in South America where the largest hailstones are typically observed.