bluuebunny/crossref_metadata_2025 huggingface dataset:
Real World Emissions of Aerosol And Its Climate Relevant Properties from Light and Heavy-Duty Commercial Vehicles Operated On Road
Authors: Khan Mohd Shahzar , Habib Gazala , Kumari Jyoti , Kumar Niraj , Kumar Rahul
Published: February 2023

Emissions from road transport plays key role in local air pollution, climate change and human health risk. Diesel exhaust emissions are the primary source of carbonaceous aerosol including particulate matter (PM) and light absorbing carbon. Emissions of fine aerosol and gaseous pollutants from automobiles depend on technology, fuel type, road type and driving behavior which are expected to be different in India. Presents study reports the real-world tailpipe emission factors of pollutants from light-duty (goods) and heavy-duty vehicles during on-road operation for the first time in India. A sampler for mobile sources has been designed and evaluated and was used to collect the PM mass on filters and to measure aerosol absorption and scattering coefficients. The sampler comprises of an inlet system, portable dilution tunnel (PDT) with ejector, zero air generator, PM sampler with cyclone and filter holders, aethalometer, nephelometer and DC power unit. The particle losses inside PDT were found insignificant at 40 and 60 dilution ratios. The on-road emission measurements of trucks, tractors and light motor vehicle-goods (LMV-Goods) were conducted in Rajgir in Bihar, India. The PM2.5 mass collected on filters were utilized for gravimetric analysis, EC-OC analysis, and others chemical constituents. PM emission factors obtained in present study were 1.1 ± 3.1 and 1.7 ± 4.1 g/kg for LMV-goods and HDV-trucks which were found to be considerably different from those measured in the laboratory using standard driving cycle. These new on-road emission factors would be helpful in emission inventories improvement which has implications on climate change assessment. In present work particle loss and formation, emission factors (g/kg) and city-wise emissions of climate relevant aerosol constituents will be discussed.
Controlling colloid transport through porous media via local gradients of solute concentration
Authors: Jotkar Mamta , Ben-Noah Ilan , Hidalgo Juan J. , Dentz Marco , Cueto-Felgueroso Luis
Published: February 2023

Diffusiophoresis referring to the colloidal particle migration triggered by gradients of local salt concentration, has been established in the recent years as an efficient particle manipulation tool in relatively simple microfluidic setups such as plane channels, dead-end pores, Y-shaped channels, vertical diverging pores, etc. Owing to the fact that the particle velocities depend logarithmically on the solute concentration gradients, small variations in the concentration fields can result in significantly large diffusiophoretic particle motion. However, despite the recent investigations hardly anything is known about its effects in the field of flow and transport in porous media. Spatial heterogeneities and complex fluid-phase distributions are quite ubiquitously found across spatial scales ranging from pore-scale to field-scale. These have a strong impact on the flow and transport of dissolved solutes through porous media giving rise to rich heterogeneous solute landscapes that provide local gradients of solute concentration, a prerequisite for diffusiophoretic motion. Following this motivation, we perform pore-scale simulations to understand the effects of diffusiophoresis at pore-scale in partially saturated media for varying degrees of fluid saturation and quantify their impact on the macroscopic particle transport. We envision that by exploiting the heterogeneous solute landscapes, particle motion can be controlled in an efficient manner. Depending on the sign of the diffusiophoretic mobility, determined by the size and surface charge of the colloidal particle, localized particle entrapment or removal can be achieved systematically. Our results that are pioneer in the field of diffusiophoretic transport through porous media, will pave the way to attaining controlled particle manipulation through porous media. 
Garnet microstructures suggest ultra-fast decompression of ultrahigh-pressure rocks
Authors: Duretz Thibault , Luisier Cindy , Tajčmanová Lucie , Yamato Philippe
Published: February 2023

Radial microcracks surrounding retrogressed SiO2 inclusions in UHP garnets are key microstructural observations allowing to constrain the mechanisms of exhumation of ultra-high-pressure (UHP) rocks. The major challenge lies in identifying whether the microstructures formed during their ascent from mantle depths, or as a consequence of transient variations in the tectonic regime. By combining petrographic observations, petrochronological data and numerical thermo-mechanical modelling, we show that radial cracks around SiO2 inclusions in ultrahigh-pressure garnets from Dora Maira are caused by ultrafast decompression during the early stage of exhumation (< 0.5 Ma). Decompression rates higher than 10-14 s-1 are, for the first time, inferred from natural microstructures independently of current petrochronological estimates1. We demonstrate that the SiO2 phase transition generates shear stresses sufficiently large to trigger plastic yielding, resulting in the generation and propagation of radial and bent shear bands, mimicking the fractures observed in UHP garnet. Our results question the traditional interpretation of the exhumation from great depth of ultrahigh-pressure tectonic. Instead, we propose that such ultrafast decompression rates are related to transient changes in the stress state of the buried continental lithosphere, favoring an exhumation mechanism involving nappe stacking. 1 Rubatto, D. & Hermann, J. Exhumation as fast as subduction? Geology 29, 3–6 (2001).
Improving Cross-Track Scanning Radiometers’ Precipitation Retrieval over Ocean by Morphing
Authors: You Yalei , Huffman George , Peters-Lidard Christa , Munchak Joseph , Tan Jackson , Braun Scott , Kidd Chris , Ringerud Sarah , Blackwell William , Xun Yang John , Nelkin Eric , Dong Jun
Published: February 2023

Previous studies showed that conical scanning radiometers greatly outperform cross-track scanning radiometers for precipitation retrieval over ocean. This study demonstrates a novel approach to improve precipitation rates at the cross-track scanning radiometers’ observation time by propagating the conical scanning radiometers’ retrievals to the cross-track scanning radiometers’ observation time. The improved precipitation rate is a weighted average of original cross-track radiometers’ retrievals and retrievals propagated from a conical scanning radiometer. Results show that the morphed precipitation rates agree much better with the reference. The degree of improvement depends on several factors, including the propagated precipitation source, the time interval between the cross-track scanning radiometer and the conical scanning radiometer, the precipitation type (convective versus stratiform), the precipitation events’ size, and the geolocation. The study has potential to greatly improve high-impact weather systems monitoring (e.g., hurricanes) and multisatellite precipitation products. It may also enhance the usefulness of future satellite missions with cross-track scanning radiometers on board.
ectron Aurora and polar rain dependencies on Solar Wind Drivers
Authors: Bouriat Simon , Wing Simon , Barthélémy Mathieu
Published: February 2023

Data analysis was performed using 17 years of DMSP SSJ/4/5 data to characterize the relations between the solar wind drivers and the electron low-energy fluxes measured on both magnetic poles (magnetic latitude above 55°). Inputs are solar wind velocity, density, dynamic pressure and Bz of the interplanetary magnetic field. Median of electron energy flux for each MLAT-MLT pair have been computed for given values of solar wind drivers. Results highlight that high velocity, density or pressure implies higher energy flux overall, higher polar rain energy fluxes, and wider nightside oval. There seems to be a positive correlation between polar rain and solar wind density as opposed to what Riehl & Hardy (1986) found. As a function of Bz, the oval width as a “U” shape and the polar cap activity a “V” shape, with their minimum at Bz around zero. Riehl, K. B., & Hardy, D. A. (1986). Average characteristics of the polar rain and their relationship to the solar wind and the interplanetary magnetic field. Journal of Geophysical Research: Space Physics, 91 (A2), 1557-1571. Retrieved from https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/JA091iA02p01557 doi: https://doi.org/10.1029/JA091iA02p01557
Evolution of soil structure at field-scale on a silt loam in Northern Germany
Authors: Eden Marie , Brunotte Joachim , Lorenz Marco
Published: February 2023

Compaction is considered as one of the major threats to soil quality and health. The use of heavy farm machinery may compact the soil, reducing the pore volume and simultaneously increasing soil bulk density. In this context, a multitude of internal (soil-related) and external factors are at play and influence soil physical properties like bulk density, which is a widely used indicator of compaction.Undisturbed soil samples were collected on a North German farm from six individual fields, all located within the same area of ~1.2 km². All fields display loess-derived soils, similar in soil type, texture and management (same farmer).  Since 1995, samples were extracted from ~20 and ~40 cm (~35 cm as of 2016) representing top- and subsoil.For one of the fields, there are approximately 15 observations within a timeframe of roughly 20 years. For the topsoil, a trend of decreasing bulk density was observed, whereas the subsoil showed a trend for the opposite behaviour, with bulk density increasing over time. Soil compaction and thus increased bulk densities are expectable on agricultural fields managed with heavy machinery. However, for the topsoil, regular tillage accompanied by soil loosening might have caused the decrease in bulk density over time. From a soil structural and stability point of view, this might nonetheless not be beneficial.
Assessing long-term ZTD trends for climate
Authors: C. Santos Marcelo , Rees Jordan , Balidakis, Kyriakos , Klos Anna , Pacione Rosa
Published: February 2023

In this presentation we showcase results of an ongoing effort to assess long-term ZTD trends for eventual use in climate models, either for assimilation or validation. We have been analyzing the ZTD time series estimated from six REPRO3 IGS Analysis Centers (ACs), namely, COD, ESA, GFZ, GRG, JPL, TUG, to compare their long-term trends. Long-term here means 20 years or longer. About thirty stations have been selected globally for this purpose. The estimated ZTD time series have gone through a process of homogenization using ERA-5 derived ZTDs as reference. The homogenized data is then averaged to daily values to minimize potential influences coming from different estimation strategies used by individual ACs. As mentioned, our interest is with the long-term signal. Similar averaging is applied to the ERA-5 ZTDs. Two combinations, using weighted mean and (a robust) least median of squares, are being generated from the six homogenized ACs. The combinations serve as quality control to each ACs. Analysis of the trends generated from each one of the seven ZTD times series is performed looking at their similarities in both time and frequency domains. Results obviously vary depending on the geographical location. For example, for station ALBH, in Canada, inter-AC scatter is 0.47 mm/decade for the trends, 0.11 mm for the annual amplitudes, and 0.29 degrees for the annual phase. 
Using Earth’s free oscillations to assess mantle circulation models
Authors: Schneider Anna , Schuberth Bernhard , Koelemeijer Paula , Restelli Federica , Zaroli Christophe
Published: February 2023

For a thorough understanding of the impact of mantle convection on vertical motions of the lithosphere, computational modeling plays a crucial role. Mantle circulation can be modeled by solving the equations of motion of a fluid using Earth-like input parameters assimilating plate motions at the surface in discrete steps through time. Thus, a realistic Earth model relies on the robustness of the inserted information. However, apart from the general difficulty of inferring deep Earth’s properties, also the plate tectonic model introduces uncertainty. Especially the linking of relative plate motions to absolute position relies on controversial assumptions such as fixity of structures in the mantle (e.g., plumes or Large-Low-Shear-Velocity Provinces) or the association between subducted plates at depth and high velocity regions in tomographic images. The latter specifically are restricted by non-uniqueness and the need to regularize the inversions, distorting structures and damping heterogeneity amplitudes.In order to infer secondary results from an MCM, it is thus important to validate the model against independent observations. Here, we employ Earth’s free oscillations that feature global sensitivity to 3-D structure for model assessment, complementing our earlier work using seismic body wave data. To this end, the temperature field of a published MCM is converted to seismic velocity with the help of a thermodynamic model of mantle mineralogy. An effective forward approach for the computation of normal mode data from synthetic Earth models is the calculation of splitting functions, describing the distortion of characteristic frequency peaks in the spectrum induced by even degree structural heterogeneity. A general problem is that the sensitivity of normal modes with depth often shows oscillatory behaviour preventing a straight forward relation of frequency shifts to structure in a certain depth range. This can be mitigated by combining kernels of several modes via a Backus-Gilbert approach to obtain focused sensitivity in pre-specified depth ranges of the mantle. For testing the significance of relevant model differences in splitting function data, geometrical alterations mimicking changes in the absolute reference frame and viscosity were applied to a pre-computed MCM. Current results indeed indicate that normal mode data are sensitive to such model changes within their respective uncertainty ranges.
Connecting COVID-19 and climate change in the anthropocene: evidence from urban vulnerability in São Paulo
Authors: Pereira Santos Alexandre , Lopez Miguel Rodriguez , Scheffran Jürgen
Published: February 2023

Global crises such as climate change and the COVID-19 pandemic do not affect cities uniformly. These crises converge in urban areas and often interact through their primary and secondary impacts with the vulnerability of urban populations. This paper investigates urban development dynamics and socio-environmental vulnerability in a megalopolis in the Global South, São Paulo (Brasil). Our goal is to assess the connections between urbanisation and risk exposure, a gap in vulnerability research when considering climate and health hazards. We implement an innovative mixed methods research design using thematic, hot spots, and survival analysis techniques. Two focus groups at the central and peripheral regions of the city provide qualitative data, while open data sets and COVID-19 case microdata (n= 1,948,601) support the quantitative methods. We find a complex system of relationships between urbanisation and risk exposure. Socioeconomic vulnerability characteristics of the population do not explain exposure entirely but significantly contribute to risk-prone location choices. Additionally, social vulnerability factors such as low income and social segregation are highly concentrated in São Paulo, coinciding with substantial COVID-19 fatality rates during 25 months of the pandemic. Finally, qualitative analysis helps us overcome the limitations of quantitative methods on the intraurban scale, indicating contrasting experiences of resilience and resistance during the health crisis. While the low-income group faced mental health and food security issues, the upper-middle-income sample took advantage of opportunities arising during the pandemic to improve work and well-being. We argue that these results demonstrate potential synergies for climate adaptation and health policies in combating socio-environmental vulnerability at the community scale. Environmental justice is thus paramount for global development agendas such as the Sustainable Development Goals, Sendai Framework, and the Paris Agreement.
Discrimination of sea ice leads and floes using Deep Learning applied to Sentinel-3 Ocean and Land Colour Instrument (OLCI) imaging spectrometer
Authors: Chen Weibin , Tsamados Michel , Willatt Rosie , Takao So , Nelson Connor , Lawrence Isobel , Lee Sanggyun , Brockley David , Landy Jack , De Rijke-Thomas Claude , Shirazi Dorsa , Stroeve Julienne , Francis Alistair
Published: February 2023

The Sentinel-3A and Sentinel-3B satellites, launched in February 2016 and April 2018 respectively, build on the legacy of CryoSat-2 by providing high-resolution radar altimetry data over the polar regions up to 81 degrees North. The combination of synthetic aperture radar (SAR) mode altimetry from Sentinel-3A and Sentinel-3B, and the Ocean and Land Colour Instrument (OLCI) imaging spectrometer, results in the creation of the first satellite platform that offers coincident optical imagery and SAR radar altimetry. We utilise these datasets to validate existing surface classification algorithms, in addition to investigating novel applications of deep learning to classify sea-ice from leads. This is important for estimating sea-ice thickness and to predict future changes in the Arctic and Antarctic regions. In particular, we propose the use of Vision Transformers (ViT) for this task and demonstrate their effectiveness, with accuracy reaching above 92%. We compare our automated results with human classification using the software IRIS. 
Estimation of road vulnerability criteria for vehicle overturning hazard impact assessment
Authors: Choo KyungSu , Choi JungRyel , Kang DongHo , Kim ByungSik
Published: February 2023

Impact forecasting means providing information on potential socioeconomic risks according to weather conditions, away from the existing weather factor-oriented forecast. The importance of impact information-based forecasting services that can support decision-making to reduce damage from weather disasters is being emphasized by the World Meteorological Organization. In countries such as the United States and the United Kingdom are investing manpower and finance in technology development to provide and spread impact information, but awareness of impact forecasts has not spread in Korea. In addition, the focus is on disasters such as floods and typhoons, which cause a lot of damage to the impact forecast, and research on vehicle risk impact assessment due to strong winds in the transportation sector, which is relatively less damaged, is insufficient. In Korea, there are not many cases of damage to vehicle conduction due to strong winds, but there are cases of damage, the need for research is increasing, and it is insufficient compared to advanced countries. In order to assessment the risk of a vehicle due to strong winds, road vulnerability, high wind strength, and vehicle exposure are required, and the purpose of this study is to calculate the criteria for road vulnerability, which is a risk assessment factor of a vehicle. Road vulnerabilities were presented by dividing them into minimal, minor, significant, and severe through density analysis, and verification was conducted by substituting them for past damage cases. It is judged that the results of this study can be used as a criterion for preparing an objective evaluation of potential risks for vehicle drivers.Acknowledgments This research was support by a (2022-MOIS63-002) of Cooperative Research Method and Safety Management Technology in National Disaster funded by Ministry of Interior and Safety(MOIS, Korea).
Long-term effects on soil forest unmanaged after a wildfire at different fire severities: historical fire at Cadiretes Massif, Catalonia, Spain
Authors: Peñalver-Alcalá Antonio , Garcia-Braga Eduardo A. , Farguell Joaquim , Francos Marcos , Úbeda Xavier
Published: February 2023

Wildfire is a common disturbance in Mediterranean forests ecosystems. However, during the last decades wildfire frequency and burned surface area have been increasing. The abandon of forest areas by the population, the change of soil uses and climate change are causing wildfires of higher magnitude and difficult to control. The affected ecosystems have several difficulties to recover due to the high temperature reached during those great fires. The effects of fire on burnt soil forests depend on many different factors, such as the intensity of fire, duration, quantity of combustible or recurrence among others. However, the understanding of wildfire effects on soil forests at long-term is still needed to improve.The aim of this study is to monitor the long-term effects (28 years) of a wildfire (55 ha) in Cadiretes Massif on soil properties in two areas affected at different fire severities (low severity: LS; high severity: HS). An unburnt Control area (C) adjacent to the burnt area was selected to compare with LS and HS. Prior the wildfire, the area was a plantation of Pinus pinaster ssp. with some individuals of Quercus suber L. No management has been applied in the area after the wildfire. The soil properties studied were hydrophobicity, pH, salinity, extractable calcium (Ca2+), magnesium (Mg2+), sodium (Na+), potassium (K+), Total Nitrogen (TN), Total Organic Carbon (TOC) and Soil Organic Carbon stock (SOCstock). Moreover, non-tree biomass accumulation on soil forests was collected in three different layers: freshly fallen, dry litter and humus.In all studied areas (C, LS, HS) a hydrophilic behavior was observed. Moreover, in both burnt areas (LS and HS) and in C area were found similar pH values and Mg2+, Na+, K+ concentrations (~5.3, ~591 mg kg-1, ~142 mg kg-1, ~244 mg kg-1; respectively). However, significant differences (p<0.05) were found in soil salinity, Ca2+, TN, TOC and SOCstock between C area (~115µS cm-1, ~2955 mg kg-1, ~0.26%, ~6.9%, ~113 kg C m-2) and burnt areas (LS: ~87µS cm-1, ~2681 mg kg-1, ~0.22%, ~5.0%, ~72 kg C m-2; HS: ~80µS cm-1, ~2337 mg kg-1, ~0.19%, ~4.5%, ~57 kg C m-2). Related to the non-tree biomass accumulation, significant difference was found in the accumulation in humus between C (~232g m-2) and burnt areas (LS: ~116g m-2; HS: ~100g m-2). No significant differences were found in the accumulation of freshly fallen (~275g m-2) and dry litter (~111g m-2).These results could indicate that at long-term, soil properties of burnt areas are partially able to recover and reach similar values to those of unburnt areas. However, it also seems that some soil parameters need more time to reach similar values than unburnt areas, especially after high severity fire episodes
Formalization of experimental protocols for automated data processing and uncertainty estimation
Authors: Vasilyeva Nadezda , Vladimirov Artem , Vasiliev Taras
Published: February 2023

This study aims to present the structure of research activities as a directed graph, connecting objects, properties, experimental conditions, actions, measurements and models, where individual experimental protocols and, for example, data harmonization schemes are its subgraphs. This gives a natural way for composition and decomposition of experimental protocols and allows to seamlessly increase level of detail for any protocol step. This representation also gives criteria of similarity between protocols. As a practical advantage for protocols, represented in such a way, it is possible to implement automated data processing with error propagation through a network of properties and generation of user interfaces for data input and validation. Data processing system based on this concept allows to relate and link different existing standards and a possibility to add any measured property. As a proof of concept, using examples from soil science experimental field, we created a prototype system, including tools for constructing and editing protocols, visualization of protocols collection as a graph, search engine for choosing the best path for estimating the property of interest with desired precision. The formalized protocols can be operated in a prototype ELN with automatically generated UI and automated data processing.
Climate-related education for the healthcare industry in Ukraine
Authors: Shablii Tetiana , Stepanenko Sergiy , Shablii Oleh , Khomenko Inna
Published: February 2023

In the frameworks of the European educational project Erasmus+ ClimEd (Multilevel Local, Nation- and Regionwide Education and Training in Climate Services, Climate Change Adaptation and Mitigation), further climate-related education is provided for professionals in the healthcare industry, as one of the climate-associated industries in Ukraine.A trans-disciplinary approach in developing distance and blended advanced training courses for medical doctors constitutes knowledge transfer in basics of Climatology and Economics of Climate Change at the pre-course and post-course stages. The main course includes modules on climate-associated pathology in Pulmonology, Cardiology, Neurology, Infectious Diseases and Epidemiology, Obstetrics and Gynecology, and Psychiatry. In view of the climate change an increase in occurrence of floods, wildfires, droughts and other natural disasters alongside extreme weather events is observed thus crucially setting down a requirement for development of a module on emergency primary healthcare.All the modules are to be developed and taught by high-level professionals, who hold at least a PhD degree. It is under the ClimEd project that blended courses on climate change and climate adaptation are to be designed and delivered for the target audiences of decision-makers in the healthcare industry and the wider public. This will bring in stabilization to the industry-specific aspects of nationwide economy through introduction of the aggregate of all settings, the online, onsite, and hybrid, to be applied in the educational process to ensure maximum efficiency in accordance with the stakeholders’ needs.
Emulating the regional temperature responses (RTPs) of short-lived climate forcers
Authors: Dewey Maura , Hansson Hans Christen , Ekman Annica M. L.
Published: February 2023

Here we develop a statistical model emulating the surface temperature response to changes in emissions of short-lived climate forcers as simulated by an Earth system model. Short-lived climate forcers (SLCFs) are chemical components in the atmosphere that interact with radiation and have both an immediate effect on local air quality, and regional and global effects on the climate in terms of changes in temperature and precipitation distributions. The short atmospheric residence times of SLCFs lead to high atmospheric concentrations in emission regions and a highly variable radiative forcing pattern. Regional Temperature Potentials (RTPs) are metrics which quantify the impact of emission changes in a given region on the temperature or forcing response of another, accounting for spatial inhomogeneities in both forcing and the temperature response, while being easy to compare across models and to use in integrated assessment studies or policy briefs. We have developed a Gaussian-process emulator using output from the Norwegian Earth System Model (NorESM) to predict the temperature responses to regional emission changes in SLCFs (specifically back carbon, organic carbon, sulfur dioxide, and methane) and use this model to calculate regional RTPs and study the sensitivity of surface temperature in a certain region, e.g. the Arctic, to anthropogenic emission changes in key policy regions. The main challenge in developing the emulator was creating the training data set such that we included maximal SLCF variability in a realistic and policy relevant range compared to future emission scenarios, while also getting a significant temperature response. We also had to account for the confounding influence of greenhouse gases (GHG), which may not follow the same future emission trajectories as SLCFs and can overwhelm the more subtle temperature response that comes from the direct and indirect effects of SLCF emissions. The emulator can potentially provide accurate and customizable predictions for policy makers to proposed emission changes with minimized climate impact.
Lessons learned from the demonstrator 5G RuralDorset project: a pilot landslide monitoring system using Internet of Things, Machine Learning and 5G/NB-IoT mobile networks
Authors: Pennington Catherine , Angelopoulos Marios , Arnhardt Christian , Dray Matthew , Banks Vanessa , Holyoake Simon , Christopher John
Published: February 2023

The 5G RuralDorset project (https://5gruraldorset.org/) was a large (£9M; 2020-2022), multi-disciplinary project funded by the UK Department for Culture, Media and Sport that aimed to understand how 5G mobile network technologies could address some specific challenges in rural communities in Dorset, UK: public safety, economic growth, food production and environmental.  Work Package X aimed to develop and trial a novel landslide monitoring system for coastal cliffs using 5G/NB-IoT (Narrow Band - Internet of Things) technologies.  The system comprised a set of small, fully autonomous, highly integrated and power efficient sensing devices that were able to collect sensory data to identify landslide activity and landslide movement. These data were transmitted wirelessly using 5G/NB-IoT to a cloud-based Data Management Platform, where they were presented to the end user over a web interface for processing by Machine Learning algorithms. It is important to note that the term ‘Internet of Things’ has been used widely in recent years in application to landslide monitoring to in fact describe real-time telemetry of data. However, the true added value of IoT-enabled systems lies in their ability to extract knowledge from collected data, make decisions and take actions based on ambient conditions and evolution of physical processes.  This talk will describe the lessons learned from this work and highlight some of the obstacles to overcome when attempting to develop and commission such a system.
Postprocessing of ensemble precipitation forecasts over India using weather types
Authors: Widmann Martin , Gonczol Noemi , Angus Michael , Neal Robert
Published: February 2023

Accurate predictions of heavy precipitation in India are vital for impact-orientated forecasting, and an essential requirement for mitigating the impact of damaging flood events. Operational forecasts from non-convection-permitting models can have large biases in the intensities of heavy precipitation, and while convection-permitting models can perform better, their operational use over large areas is not yet feasible. Statistical postprocessing can reduce these biases for relatively little computational cost, but few studies have focused on postprocessing forecasts of monsoonal rainfall.We present a postprocessing method for operational precipitation forecasts based on local precipitation distributions for 30 Indian weather types. It is applied to ensemble forecasts for daily precipitation with 12km spatial resolution and lead times of up to 10 days from the Indian National Centre for Medium Range Weather Forecasting (NCMRWF) Ensemble Prediction System (NEPS). The method yields local probabilistic forecasts that are the weighted mean of the observed local precipitation distributions for each weather type, with weights given by the relative frequency of the weather types in the forecast ensemble.The general forecast skill is determined through the Continuous Ranked Probability Skill Score (CRPSS) and the skill for predicting the exceedance of the local 90th percentile is quantified through the Brier Skill Score (BSS). The CRPSS shows moderate improvement over most of India for forecasts with one day lead time, and substantial improvements almost everywhere for longer lead times. The BSS for one day forecasts indicates a spatially complex pattern of higher and lower performance, while for longer lead times the forecasts for heavy precipitation are improved almost everywhere. The improvements with respect to both measures are particularly high over mountainous or wet regions. We will also present reliability diagrams for the raw and postprocessed forecasts of threshold exceedances.  
The spatio-temporal dynamics of the peak of the growing season and its responses to climatic driving factors in Africa
Authors: Shi Siqi , Yang Peiqi , van der Tol Christiaan
Published: February 2023

Vegetation phenology characterizes the periodic plant life cycle events across a growing season. It is sensitive to climate change and thus important for the understanding of vegetation-climate interactions. Previous studies have revealed the importance of the start and end of the growing season, and investigated their dynamics with climate change. However, the spatio-temporal dynamics of the peak of the growing season (POS), which is also important to understand the response of plants to climate change, has not been well documented. Here, we applied three methods (Savitzky-Golay filtering, SG; Asymmetric Gaussian function, AG; and Double Logistic function, DL) in TIMESAT to estimate the latitudinal and longitudinal gradients and temporal trends of the peak of the growing season (POS) in Africa based on normalized difference vegetation index (NDVI) during 1982-2015. We investigated the relationships of POS with mean temperature, accumulative precipitation, and accumulative insolation over the preseason periods by computing temporal partial correlation coefficients. The results showed similar patterns and minor differences in POS based on the three methods. The averaged differences overall less than 0.4 days (MEANSG-AG = -0.1427 days, MEANSG-DL = 0.307 days, MEANAG-DL = 0.1983 days). For the spatio-temporal dynamics of POS, the latitudinal variations in POS were not very obvious but significant in both northern and southern Africa. In northern Africa, there was no clear longitudinal gradient in POS, while a significant west-east gradient in the temporal trends of POS was exhibited with POS change rate from 0.48 days/year to 0.19 days/year. From the temporal trends, we found an overall delayed trend of POS with 0.28 days/year on average in northern Africa and 0.25 days/year on average in southern Africa. In northern Africa, preseason precipitation was the most important factor controlling POS with a positive correlation, followed by temperature with a positive correlation. The correlations between preseason temperature and POS exhibited spatial heterogeneity, with more areas showing positive relationship than negative relationship. Compared to northern Africa, the response of POS to climatic factors is more complex in southern Africa. The three climate factors all showed significant correlations to POS for most areas. Both decreased accumulative precipitation and radiation over preseason overall delayed POS for most areas. The temperature was also significantly associated with POS changes, while had different effects on POS, i.e., POS can be resulted from lower temperature and higher temperature (depending on the location), implying the complicated interactions between POS changes and temperature in southern Africa. Our study deepens the understanding between phenology and climate change in Africa.
Using expired weather forecasts to supply up to 10 000 years of weather data
Authors: Dolezal Petr , Keshav Srinivasan , Shuckburgh Emily
Published: February 2023

When modelling possible future renewable electricity systems, a strong focus needs to be directed to the input weather variables driving any such system. Since we cannot know the exact weather in any slightly distant future, a probabilistic approach is usually chosen, modelling the system over many possible scenarios, typically all of the past recorded weather data available. However, this narrows the range of situations considered to about 40 years, placing fundamental limits on the analysis, e.g. of rare, extreme scenarios.In our work, we explore the possibility of using past expired ensemble forecasts from the ECMWF [1] to drastically increase the number of scenarios considered to up to 10 000 years of data. These ensemble forecasts are physical models that are regularly initialized from the same slightly perturbed snapshot, but due to the chaotic nature of weather, their predictions diverge from each other. The later stages of their predictions are thus entirely independent predictions of what the weather could have been, including the correct spatial correlations. We analyze the data from the operational archive of ECMWF to assess their suitability for modelling renewable systems of the future and demonstrate how this wealth of additional weather scenarios can enable the utilization of otherwise heavily data-dependent machine learning techniques in energy modelling.  [1] European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Model Ensemble extended forecast https://www.ecmwf.int/en/forecasts/datasets/set-vi
“ARCTIC SCIENCE COLLABORATIONS” - A HOLISTIC SYSTEM UNDERSTANDING OF THE ARCTIC ENVIRONMENTAL SYSTEM FOR WELL-TARGETED POLICY ACTIONS- Future perspectives
Authors: Lappalainen Hanna , Petäjä Tuukka , Baklanov Alexander
Published: February 2023

An improved understanding of the land - atmosphere - ocean feedbacks and interactions is needed for the future strategies for sustainable development of the Arctic region. An understading of the Arctic climate system and  the implementation of the related processes in climate models are required to provide advice for policy actions.  In this presenation, we highlight key areas for Arctic research from the atmospheric, oceanic, cryospheric, and social perspectives, and summarize recent developments in a holistic understanding of the Arctic climate system carried out in in a frame of AASCO Arctic Science Collaboration project in 2020-2022. We also provide an outlook of the links between research and its societal impacts.
Modeling the impact of land-use and climate change on water quality of a deep dam reservoir
Authors: Lin Yu-I , Yu Mei-Siang , Chang Hue-Shien , Pan Shu-Yuan
Published: February 2023

Te-Chi Reservoir is an multipurpose reservoir, which supplies drinking water for a population of ~2,800,000 and generate hydroelectric power in the Taichung city, Taiwan. In the past 10 years, this reservoir experienced several events of algal blooms and extreme drought. According to the historical water quality data, the frenauency of the trophic state for the reservoir has increased in the recent years. The N/P ratios of the reservoir are generally greater than 15, indicating that the limited nutrient of eutrophication is phosphorous. In this study, we developed an integrated model to predict the water quality of the reservoir using an input of 10-year observational data. A hydrological stream flow model (i.e., SWAT) was integrated with the simple phosphorous (P) input-output models (i.e., the Vollenweider model) to simulate the change of the trophic state and the concentration of P in the reservoir. We first investigated the hydrological variability impact on the P load in past three year when the extreme weather (drought) happened.The results showed that the concentraion of total phosphorous (TP) was significantly influenced by the inflow of the river to the reservoir and the precipitation (rainfall). The simulated concentrations of TP in dry seasons were typically higher than that in the wet seasons. During the drought, the internal loading, such as resuspension, played a significant source of P for the reservoir. We also investigated the sources and loads of key water pollutants, especially nitrogen and phosphorous, from the spatial aspect in the watershed of the reservoir. The results indicated that the TP loads of each sub-catchment area ranged from 2.76 to 4.12 kg/h. Furthermore, in order to understant the feasibility of establishment of riparian buffer strip, the effect of the land use change on water quality was simulated. This study demonstrated the application of the integrated SWAT-Vollenweider model for a reservior to identify the drivers of pollutants for managing its watershed to mitigate the potential of eutrophication.
Drought characterization across Peru and Ecuador and its relationship with ocean-atmospheric indices
Authors: Vega-Jácome Fiorella , Bronstert Axel , Fernandez-Palomino Carlos Antonio , Lavado-Casimiro Waldo
Published: February 2023

Peru and Ecuador have suffered high economic losses because of extreme events (Floods and Droughts). The analysis of the meteorological droughts and their drivers is of paramount importance for water resources management and risk assessment in these countries. This study aims to characterize the spatiotemporal variability of droughts across Peru and Ecuador over the last four decades (1981-2020) and evaluate the relationship with the ocean-atmospheric circulation patterns. The Rain for Peru and Ecuador (RAIN4PE) gridded precipitation dataset was used to estimate the Standardized Precipitation Index (SPI) at time scales of 3 and 12 months to assess short and long-term droughts, respectively. Droughts were characterized by the number of events, duration, intensity, and severity, and the relationship was evaluated by computing the Pearson correlation to identify the leading oceanic-atmospheric indices: E (Eastern Pacific SST anomalies), C (Central Pacific SST anomalies), PDO (Pacific Decadal Oscillation), SOI (Southern Oscillation Index), MEI2 (Multivariate Enso Index), TPI (Tripole Index for the Interdecadal Pacific Oscillation), TNA (Tropical North Atlantic index), and TSA (Tropical Southern Atlantic Index).The results show high spatiotemporal variability of drought characteristics with the high frequency of extreme droughts over the southern Peruvian Andes in Peru and the eastward of the Andes in Ecuador. The ranking of the extremeness of drought events based on the areal extent, duration, and intensity identified that three of the four more extreme events match ENSO conditions in Peru (1992/02, 1988/08, 1990/01) and Ecuador (1985/04, 1990/01, 1995/04). Finally, strong relationships between ocean-atmospheric indices and droughts in Peru and Ecuador were identified. Droughts in Peru evidence significant correlations with E, C, and TNA indices. Similarly, droughts in Ecuador show high correlations with E, C, PDO, TPI, and SOI indices. These results provide more insights into the characteristics of droughts and the possible drivers, information that is useful for water resource management decisions and can help as the basis for developing drought forecasts.
Retrieving cloud properties based on MTG/IRS (Meteosat Third Generation/InfraRed Sounder)
Authors: Chen Xuemei , Kerdraon Gaëlle , Péré Sonia , Vidot Jérôme , Fontaine Emmanuel
Published: February 2023

The next generation Meteosat Third Generation sounding satellite (MTG-S) is expected to be launched at the end of 2024. MTG-S will carry a hyperspectral interferometer, namely InfraRed Sounder (IRS), to provide a four-dimensional look at the atmosphere from a geostationary orbit. IRS will measure the radiance emission from the earth at 1960 infrared spectral channels at two bands (2250 ~ 1600 cm-1 and 1210 ~ 680 cm-1), with a spectral resolution of around 0.60 cm-1.Satellite-based cloud information is essential for the subsequent retrievals of atmospheric and surface products or for data assimilation in numerical weather prediction (NWP) models. Our project aims at studying the feasibility of retrieving cloud properties from MTG/IRS simulated data, notably cloud mask, cloud classification, and cloud top pressure/temperature/height following NWC SAF threshold methodologies. In this poster, the radiative transfer modelling by RTTOV is carried out at various atmospheric and cloud conditions to study the IRS spectral behaviours, especially at window channels. We will also discuss our preliminary retrieval of a cloud mask by brightness temperature thresholds using the selected IRS channels.
Shallow-water hydrothermal venting at the Paleocene-Eocene Thermal Maximum onset
Authors: Jones Morgan , Berndt Christian , Planke Sverre , Zarikian Carlos Alvarez , Frieling Joost , Millett John M. , Nelissen Mei , Brinkhuis Henk
Published: February 2023

The Paleocene-Eocene Thermal Maximum (PETM) around 56 Ma was associated with 5-6 °C global warming, resulting from massive carbon release into the ocean–atmosphere system. One potential driver of hyperthermal conditions was the North Atlantic Igneous Province (NAIP), as both volcanic degassing and thermogenic volatile release during contact metamorphism during its emplacement were large potential emitters of carbon. Despite a broad temporal correlation between NAIP activity and the PETM, the exact relationship is obscured by multiple climate forcings, imprecise geochronological data, uncertainties in the timing and magnitude of volatile fluxes from volcanic and thermogenic sources, and limited availability from crucial NAIP localities that could constrain these unknowns. Here we present new seismic and borehole data for the Modgunn hydrothermal vent complex in the Northeast Atlantic (IODP Sites U1567-U1568). Stable carbon isotope stratigraphy and dinoflagellate cyst biostratigraphy reveal a negative carbon isotope excursion coincident with the appearance of Apectodinium augustum in the vent crater infill. Modern examples of submarine explosion craters suggest they have filled in within decades to centuries, so the preservation of the PETM onset within the Modgunn vent suggests an extremely close temporal correlation between the crate formation and the onset of hyperthermal conditions. Furthermore, the majority of the craters across the entire NAIP are likely to have vented in very shallow water, implying that the vast majority of emitted CO2 and CH4 gases directly entered the atmosphere during eruptions. These findings add considerable weight to the hypothesis that thermogenic degassing aided the initiation of the PETM. 