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Rust, William, John P. Bloomfield, Mark Cuthbert, Ron Corstanje, and Ian Holman. "The importance of non-stationary multiannual periodicities in the North Atlantic Oscillation index for forecasting water resource drought." Hydrology and Earth System Sciences 26, no. 9 (May 11, 2022): 2449–67. http://dx.doi.org/10.5194/hess-26-2449-2022.
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Abstract. Drought forecasting and early warning systems for water resource extremes are increasingly important tools in water resource management in Europe where increased population density and climate change are expected to place greater pressures on water supply. In this context, the North Atlantic Oscillation (NAO) is often used to indicate future water resource behaviours (including droughts) over Europe, given its dominant control on winter rainfall totals in the North Atlantic region. Recent hydroclimate research has focused on the role of multiannual periodicities in the NAO in driving low frequency behaviours in some water resources, suggesting that notable improvements to lead-times in forecasting may be possible by incorporating these multiannual relationships. However, the importance of multiannual NAO periodicities for driving water resource behaviour, and the feasibility of this relationship for indicating future droughts, has yet to be assessed in the context of known non-stationarities that are internal to the NAO and its influence on European meteorological processes. Here we quantify the time–frequency relationship between the NAO and a large dataset of water resources records to identify key non-stationarities that have dominated multiannual behaviour of water resource extremes over recent decades. The most dominant of these is a 7.5-year periodicity in water resource extremes since approximately 1970 but which has been diminishing since 2005. Furthermore, we show that the non-stationary relationship between the NAO and European rainfall is clearly expressed at multiannual periodicities in the water resource records assessed. These multiannual behaviours are found to have modulated historical water resource anomalies to an extent that is comparable to the projected effects of a worst-case climate change scenario. Furthermore, there is limited systematic understanding in existing atmospheric research for non-stationarities in these periodic behaviours which poses considerable implications to existing water resource forecasting and projection systems, as well as the use of these periodic behaviours as an indicator of future water resource drought.
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Guðmundsson, Kristinn, Mike R. Heath, and Elizabeth D. Clarke. "Average seasonal changes in chlorophyll a in Icelandic waters." ICES Journal of Marine Science 66, no. 10 (August 13, 2009): 2133–40. http://dx.doi.org/10.1093/icesjms/fsp208.
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Abstract Guðmundsson, K., Heath, M. R., and Clarke, E. D. 2009. Average seasonal changes in chlorophyll a in Icelandic waters. – ICES Journal of Marine Science, 66: 2133–2140. The standard algorithms used to derive sea surface chlorophyll a concentration from remotely sensed ocean colour data are based almost entirely on the measurements of surface water samples collected in open sea (case 1) waters which cover ∼60% of the worlds oceans, where strong correlations between reflectance and chlorophyll concentration have been found. However, satellite chlorophyll data for waters outside the defined case 1 areas, but derived using standard calibrations, are frequently used without reference to local in situ measurements and despite well-known factors likely to lead to inaccuracy. In Icelandic waters, multiannual averages of 8-d composites of SeaWiFS chlorophyll concentration accounted for just 20% of the variance in a multiannual dataset of in situ chlorophyll a measurements. Nevertheless, applying penalized regression spline methodology to model the spatial and temporal patterns of in situ measurements, using satellite chlorophyll as one of the predictor variables, improved the correlation considerably. Day number, representing seasonal variation, accounted for substantial deviation between SeaWiFS and in situ estimates of surface chlorophyll. The final model, using bottom depth and bearing to the sampling location as well as the two variables mentioned above, explained 49% of the variance in the fitting dataset.
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Saviano, Simona, Anastasia Angela Biancardi, Marco Uttieri, Enrico Zambianchi, Luis Alberto Cusati, Andrea Pedroncini, Giorgio Contento, and Daniela Cianelli. "Sea Storm Analysis: Evaluation of Multiannual Wave Parameters Retrieved from HF Radar and Wave Model." Remote Sensing 14, no. 7 (March 31, 2022): 1696. http://dx.doi.org/10.3390/rs14071696.
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Intense atmospheric disturbances, which impact directly on the sea surface causing a significant increase in wave height and sometimes strong storm surges, have become increasingly frequent in recent years in the Mediterranean Sea, producing extreme concern in highly populated coastal areas, such as the Gulf of Naples (Western Mediterranean Sea, Central Tyrrhenian Sea). In this work, fifty-six months of wave parameters retrieved by an HF radar network are integrated with numerical outputs to analyze the seasonality of extreme events in the study area and to investigate the performance of HF radars while increasing their distances from the coast. The model employed is the MWM (Mediterranean Wind-Wave Model), providing a wind-wave dataset based on numerical models (the hindcast approach) and implemented in the study area with a 0.03° spatial resolution. The integration and comparison with the MWM dataset, carried out using wave parameters and spectral information, allowed us to analyze the availability and accuracy of HF sampling during the investigated period. The statistical comparisons highlight agreement between the model and the HF radars during episodes of sea storms. The results confirm the potential of HF radar systems as long-term monitoring observation platforms, and allow us to give further indications on the seasonality of sea storms under different meteorological conditions and on their energy content in semi-enclosed coastal areas, such as the Gulf of Naples.
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Saviano, Simona, Anastasia Angela Biancardi, Florian Kokoszka, Marco Uttieri, Enrico Zambianchi, Luis Alberto Cusati, Andrea Pedroncini, and Daniela Cianelli. "HF Radar Wind Direction: Multiannual Analysis Using Model and HF Network." Remote Sensing 15, no. 12 (June 8, 2023): 2991. http://dx.doi.org/10.3390/rs15122991.
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HF radar systems have the potential to measure the wind direction, in addition to surface currents and wave fields. However, studies on HF radar for wind direction determination are rare in the scientific literature. Starting with the results presented in Saviano et al. (2021), we here expand on the reliability of the multiannual wind direction data retrieved over two periods, from May 2008 to December 2010 and from January to December 2012, by a network of three SeaSonde high-frequency (HF) radars operating in the Gulf of Naples (Central Tyrrhenian Sea, Western Mediterranean Sea). This study focuses on the measurements obtained by each antenna over three range cells along a coast–offshore transect, pointing to any potential geographically dependent measurement. The scarcity of offshore wind measurements requires the use of model-generated data for comparative purposes. The data here used are obtained from the Mediterranean Wind–Wave Model, which provides indications for both wave and wind parameters, and the ERA5@2km wind dataset obtained by dynamically downscaling ERA5 reanalysis. These data are first compared with in situ data and subsequently with HF-retrieved wind direction measurements. The analysis of the overall performance of the HF radar network in the Gulf of Naples confirms that the HF radar wind data show the best agreement when the wind speed exceeds a 5 m/s threshold, ensuring a sufficiently energetic surface wave field to be measured. The results obtained in the study suggest the necessity of wind measurements in offshore areas to validate the HF radar wind measurements and to improve the extraction algorithms. The present work opens up further investigations on the applications of wind data from SeaSonde HF radars as potential monitoring platforms, both in coastal and offshore areas.
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Pommier, C., C. Michotey, G. Cornut, P. Roumet, E. Duchêne, R. Flores, A. Lebreton, et al. "Applying FAIR Principles to Plant Phenotypic Data Management in GnpIS." Plant Phenomics 2019 (April 30, 2019): 1–15. http://dx.doi.org/10.34133/2019/1671403.
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GnpIS is a data repository for plant phenomics that stores whole field and greenhouse experimental data including environment measures. It allows long-term access to datasets following the FAIR principles: Findable, Accessible, Interoperable, and Reusable, by using a flexible and original approach. It is based on a generic and ontology driven data model and an innovative software architecture that uncouples data integration, storage, and querying. It takes advantage of international standards including the Crop Ontology, MIAPPE, and the Breeding API. GnpIS allows handling data for a wide range of species and experiment types, including multiannual perennial plants experimental network or annual plant trials with either raw data, i.e., direct measures, or computed traits. It also ensures the integration and the interoperability among phenotyping datasets and with genotyping data. This is achieved through a careful curation and annotation of the key resources conducted in close collaboration with the communities providing data. Our repository follows the Open Science data publication principles by ensuring citability of each dataset. Finally, GnpIS compliance with international standards enables its interoperability with other data repositories hence allowing data links between phenotype and other data types. GnpIS can therefore contribute to emerging international federations of information systems.
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Wu, Tonghua, Changwei Xie, Xiaofan Zhu, Jie Chen, Wu Wang, Ren Li, Amin Wen, et al. "Permafrost, active layer, and meteorological data (2010–2020) at the Mahan Mountain relict permafrost site of northeastern Qinghai–Tibet Plateau." Earth System Science Data 14, no. 3 (March 21, 2022): 1257–69. http://dx.doi.org/10.5194/essd-14-1257-2022.
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Abstract. Relict permafrost presents an ideal opportunity to understand the impacts of climatic warming on the ground thermal regime since it is characterized by a mean annual ground temperature close to 0 ∘C and relatively thin permafrost. The long-term and continuous observations of permafrost thermal state and climate background are of great importance to reveal the links between the energy balance on hourly to annual timescales, to evaluate the variations in permafrost thermal state over multiannual periods and to validate the remote sensing dataset. We present 11 years of meteorological and soil data from the Mahan Mountain relict permafrost site of northeastern Qinghai–Tibet Plateau. The meteorological data comprise air and land surface temperature, relative humidity, wind speed and direction, shortwave and longwave downwards and upwards radiation, water vapor pressure, and precipitation on a half-hour timescale. The active layer data include daily soil temperature and soil volumetric water content at five different depths. The permafrost data consist of the ground temperature at 20 different depths up to 28.4 m. The high-quality and long-term datasets are expected to serve as accurate forcing data in land surface models and evaluate remote-sensing products for a broader geoscientific community. The datasets are available from the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/Cryos.tpdc.271838, Wu and Xie, 2021).
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Shahi, Sonika, Jakob Abermann, Georg Heinrich, Rainer Prinz, and Wolfgang Schöner. "Regional Variability and Trends of Temperature Inversions in Greenland." Journal of Climate 33, no. 21 (November 1, 2020): 9391–407. http://dx.doi.org/10.1175/jcli-d-19-0962.1.
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AbstractStrong and thick temperature inversions are key components of the Arctic climate system and it is important to study and better understand them. The present study quantifies the temporal and spatial variability of surface-based inversions (SBIs) and elevated inversions (EIs) over Greenland, as derived from the ERA-Interim (ERA-I) dataset for the period 1979–2017. The seasonal and multiannual variability of inversion strength, thickness, and frequency are examined. Our results clearly show regional as well as seasonal patterns of both SBIs and EIs. SBIs are more frequent and stronger than EIs, and the spatial variability of inversions is larger during winter and smaller during summer. Furthermore, during summer, there has been a trend toward stronger (0.3 K decade−1), thicker (12 m decade−1), and more frequent (3% decade−1) SBIs in the southern part of Greenland, especially in the past two decades. Evidently, the strengthening of the anticyclone over Greenland causes a reduction of cloud cover, which manifests in an increase in SBI strength and thickness, particularly in the southern part of Greenland.
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DIMITROV, B. D., and E. S. BABAYEV. "Cyclic variations in the dynamics of flu incidence in Azerbaijan, 1976–2000." Epidemiology and Infection 143, no. 1 (March 18, 2014): 13–22. http://dx.doi.org/10.1017/s095026881400048x.
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SUMMARYMulticomponent cyclicity in influenza (flu) incidence had been observed in various countries (e.g. periods T = 1, 2–3, 5–6, 8·0, 10·6–11·3, 13, 18–19 years) and its close similarity with cycles in natural environmental phenomena as meteorological factors and heliogeophysical activity (HGA) suggested. This report aimed at verifying previous results on cyclic patterns of flu incidence by exploring whether flu annual cyclicity (seasonality) and trans-year (13 to <24 months) and/or multiannual (long-term, ⩾24 months) cycles might be present. For this purpose, a relatively long monthly flu incidence dataset consisting of absolute numbers of new cases from the Grand Baku area, Azerbaijan, for the years 1976–2000 (300 months) was analysed. The exploration of underlying chronomes or, time structures, was done by linear and nonlinear parametric regression models, autocorrelation, spectral analysis and periodogram regression analysis. We analysed temporal dynamics and described multicomponent cyclicity, determining its statistical significance. The analysis, considering the flu data specifically stratified in three distinct intervals (1976–1990, 1991–1995, 1996–2000), and also combinations thereof, indicated that the main cyclic pattern was a seasonal one, with a period of T = 12 months. Further, a number of multiannual cycles with periods T in the ranges of 26–36, 62–85 or 113–162 months were observed, i.e. average periods of 2·5, 6·1 and 11·5 years, respectively. Indeed, most of these cycles correspond to similar cyclic parameters of HGA and further analyses are warranted to investigate such relationships. In conclusion, our study revealed the presence of multicomponent cyclic dynamics in influenza incidence by using relatively long time-series of monthly data. The specific cyclic patterns of flu incidence in Azerbaijan allows further, more specific modelling and correlations with environmental factors of similar cyclicity, e.g. HGA, to be explored. These results might contribute more widely to a better understanding of influenza dynamics and its aetiology as well as to the derivation of more precise forecasted estimates for planning and prevention purposes.
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Chiriaco, Marjolaine, Jean-Charles Dupont, Sophie Bastin, Jordi Badosa, Julio Lopez, Martial Haeffelin, Helene Chepfer, and Rodrigo Guzman. "ReOBS: a new approach to synthesize long-term multi-variable dataset and application to the SIRTA supersite." Earth System Science Data 10, no. 2 (May 23, 2018): 919–40. http://dx.doi.org/10.5194/essd-10-919-2018.
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Abstract. A scientific approach is presented to aggregate and harmonize a set of 60 geophysical variables at hourly timescale over a decade, and to allow multiannual and multi-variable studies combining atmospheric dynamics and thermodynamics, radiation, clouds and aerosols from ground-based observations. Many datasets from ground-based observations are currently in use worldwide. They are very valuable because they contain complete and precise information due to their spatio-temporal co-localization over more than a decade. These datasets, in particular the synergy between different type of observations, are under-used because of their complexity and diversity due to calibration, quality control, treatment, format, temporal averaging, metadata, etc. Two main results are presented in this article: (1) a set of methods available for the community to robustly and reliably process ground-based data at an hourly timescale over a decade is described and (2) a single netCDF file is provided based on the SIRTA supersite observations. This file contains approximately 60 geophysical variables (atmospheric and in ground) hourly averaged over a decade for the longest variables. The netCDF file is available and easy to use for the community. In this article, observations are “re-analyzed”. The prefix “re” refers to six main steps: calibration, quality control, treatment, hourly averaging, homogenization of the formats and associated metadata, as well as expertise on more than a decade of observations. In contrast, previous studies (i) took only some of these six steps into account for each variable, (ii) did not aggregate all variables together in a single file and (iii) did not offer an hourly resolution for about 60 variables over a decade (for the longest variables). The approach described in this article can be applied to different supersites and to additional variables. The main implication of this work is that complex atmospheric observations are made readily available for scientists who are non-experts in measurements. The dataset from SIRTA observations can be downloaded at http://sirta.ipsl.fr/reobs.html (last access: April 2017) (Downloads tab, no password required) under https://doi.org/10.14768/4F63BAD4-E6AF-4101-AD5A-61D4A34620DE.
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Latchmore, Tessa, Paul D. Hynds, R. Stephen Brown, Kevin McDermott, and Anna Majury. "Estimating the duration and overlap of Escherichia coli contamination events in private groundwater supplies for quantitative risk assessment using a multiannual (2010–2017) provincial dataset." Environmental Pollution 309 (September 2022): 119784. http://dx.doi.org/10.1016/j.envpol.2022.119784.
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Groos, Alexander R., Janik Niederhauser, Bruk Lemma, Mekbib Fekadu, Wolfgang Zech, Falk Hänsel, Luise Wraase, Naki Akçar, and Heinz Veit. "An hourly ground temperature dataset for 16 high-elevation sites (3493–4377 m a.s.l.) in the Bale Mountains, Ethiopia (2017–2020)." Earth System Science Data 14, no. 3 (March 9, 2022): 1043–62. http://dx.doi.org/10.5194/essd-14-1043-2022.
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Abstract. Tropical mountains and highlands in Africa are under pressure because of anthropogenic climate and land-use change. To determine the impacts on the afro-alpine environment and to assess the potential socio-economic consequences, the monitoring of essential climate and environmental variables at high elevation is fundamental. However, long-term temperature observations on the African continent above 3000 m are very rare. Here we present a consistent multiannual dataset of hourly ground temperatures for the Bale Mountains in the southern Ethiopian Highlands, which comprise Africa's largest tropical alpine area. The dataset covers the period from January 2017 to January 2020. To characterise and continuously monitor the mountain climate and ecosystem of the Bale Mountains along an elevation gradient from 3493 to 4377 m, ground temperature data loggers have been installed at seven sites at 2 cm depth; at four sites at 10 cm depth; and at five sites at 2, 10, and 50 cm depth. The statistical analysis of the generated time series reveals that ground temperatures in the Bale Mountains are subject to large daily fluctuations of up to 40 ∘C and minor seasonal variations on the order of 5 to 10 ∘C. Besides incoming short-wave radiation, ground moisture, and clouds at night, slope orientation and the type of vegetation coverage seem to be the main factors controlling daily and seasonal ground temperature variations. On the central Sanetti Plateau above 3800–4000 m, the mean annual ground temperature ranges from 9 to 11 ∘C. However, nocturnal ground frost down to a depth of 5 cm occurs frequently during the dry season from November to February. At the five sites where ground temperature is measured at three depths, the monitoring will be continued to trace long-term changes. To promote the further use of the ground temperature dataset by the wider research community dealing with the climate and geo-ecology of tropical mountains in eastern Africa, it is made freely available via the open-access repository Zenodo: https://doi.org/10.5281/zenodo.6047457 (Groos et al., 2022).
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Zowam, Fabian J., Adam M. Milewski, and David F. Richards IV. "A Satellite-Based Approach for Quantifying Terrestrial Water Cycle Intensity." Remote Sensing 15, no. 14 (July 21, 2023): 3632. http://dx.doi.org/10.3390/rs15143632.
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The terrestrial water cycle intensity (WCI) is a widely used tool to quantify the impact of climate change on the distribution of global water resources. In this study, a satellite-based WCI was tested by comparing the parameter-elevation regressions on independent slopes model (PRISM) precipitation estimates with those of the Global Precipitation Measurement (GPM) satellite mission across the contiguous United States (CONUS), based on an existing Köppen–Geiger climate classification for the CONUS. Both precipitation products were not statistically different across all climate classes. Consequently, satellite-based WCI changes between two multiannual periods (2001 to 2009 and 2010 to 2019) were calculated at a 0.1-degree spatial resolution using the GPM and a validated global evapotranspiration dataset. This study showed that: (1) The water cycle is speeding up in many parts of the CONUS, particularly the West, driven by recent increases in both precipitation and evapotranspiration through much of the region. (2) The El Niño-Southern Oscillation (ENSO) may be influencing the WCI of the CONUS by driving precipitation in the west, southeast, and parts of the north, and dryness in the northeast regions. The hydrological impacts of these results cannot be generalized. However, flood and drought risks, water availability and quality issues remain key primary concerns.
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Bauer-Marschallinger, Bernhard, Wouter A. Dorigo, Wolfgang Wagner, and Albert I. J. M. van Dijk. "How Oceanic Oscillation Drives Soil Moisture Variations over Mainland Australia: An Analysis of 32 Years of Satellite Observations*." Journal of Climate 26, no. 24 (December 2, 2013): 10159–73. http://dx.doi.org/10.1175/jcli-d-13-00149.1.
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Abstract Australia is frequently subject to droughts and floods. Its hydrology is strongly connected to oceanic and atmospheric oscillations (climate modes) such as the El Niño–Southern Oscillation (ENSO), Indian Ocean dipole (IOD), and southern annular mode (SAM). A global 32-yr dataset of remotely sensed surface soil moisture (SSM) was used to examine hydrological variations in mainland Australia for the period 1978–2010. Complex empirical orthogonal function (CEOF) analysis was applied to extract independent signals and to investigate their relationships to climate modes. The annual cycle signal represented 46.3% of the total variance and a low but highly significant connection with SAM was found. Two multiannual signals with a lesser share in total variance (6.3% and 4.2%) were identified. The first one had an unstable period of 2–5 yr and reflected an east–west pattern that can be associated with ENSO and SAM but not with IOD. The second one, a 1- to 5-yr oscillation, formed a dipole pattern between the west and north and can be linked to ENSO and IOD. As expected, relationships with ENSO were found throughout the year and are especially strong during southern spring and summer in the east and north. Somewhat unexpectedly, SAM impacts strongest in the north and east during summer and is proposed as the key driver of the annual SSM signal. The IOD explains SSM variations in the north, east, and southeast during spring and also in the west during winter.
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Cusack, Stephen. "A long record of European windstorm losses and its comparison to standard climate indices." Natural Hazards and Earth System Sciences 23, no. 8 (August 24, 2023): 2841–56. http://dx.doi.org/10.5194/nhess-23-2841-2023.
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Abstract. Traditional insurance has both a great exposure to decadal variations in European storm activity and the ability to adjust its business strategy over these timescales. Hence, the recent development of skilful predictions of multiannual mean European winter climate seems a very welcome addition to the long list of ways that researchers have improved management of windstorm risk. Yet companies do not use these forecasts of mean winter climate to adjust their view of risk. The main reason is the lack of a long, reliable record of losses to understand how forecasted time-mean circulation anomalies relate to the damage from a few, intense storms. This study fills that gap with a European windstorm loss record from 1950 to 2022, based on ERA5 peak near-surface winds per event which were converted to losses using an established damage function. The resulting dataset successfully identifies major storms over the past 70 years and simulates the multidecadal variations from low values in the 1960s up to high levels in the 1980s and 1990s then down to the 2010s. However, it underestimated the steepness of the observed loss decline from the stormy end of the 20th century to the lull over the past 20 years. This was caused by a quite flat trend in ERA5 extreme winds over the period, in contrast to the significant decline in observed peak gusts. Imposing these gust trends on ERA5 peak winds reconciled modelled losses with industry experience over the past few decades. Indices of European winter climate used in long-range forecasting were compared to the new modelled loss dataset. They had correlations of around 0.4 at interannual timescales, rising to about 0.7 for decadal and longer variations. Notably, the climate indices have a similar multidecadal trend as ERA5 extreme winds in modern times, including a less steep decline than found in observed gusts and losses. Further investigation of the modern-day divergence between climate indices and losses may help connect decadal forecasting to insurance.
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Gonçalves Ageitos, María, Vincenzo Obiso, Ron L. Miller, Oriol Jorba, Martina Klose, Matt Dawson, Yves Balkanski, et al. "Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts." Atmospheric Chemistry and Physics 23, no. 15 (August 4, 2023): 8623–57. http://dx.doi.org/10.5194/acp-23-8623-2023.
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Abstract. Soil dust aerosols are a key component of the climate system, as they interact with short- and long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play a role in biogeochemical cycles by providing nutrient inputs such as iron and phosphorus. The influence of dust on these processes depends on its physicochemical properties, which, far from being homogeneous, are shaped by its regionally varying mineral composition. The relative amount of minerals in dust depends on the source region and shows a large geographical variability. However, many state-of-the-art Earth system models (ESMs), upon which climate analyses and projections rely, still consider dust mineralogy to be invariant. The explicit representation of minerals in ESMs is more hindered by our limited knowledge of the global soil composition along with the resulting size-resolved airborne mineralogy than by computational constraints. In this work we introduce an explicit mineralogy representation within the state-of-the-art Multiscale Online Nonhydrostatic AtmospheRe CHemistry (MONARCH) model. We review and compare two existing soil mineralogy datasets, which remain a source of uncertainty for dust mineralogy modeling and provide an evaluation of multiannual simulations against available mineralogy observations. Soil mineralogy datasets are based on measurements performed after wet sieving, which breaks the aggregates found in the parent soil. Our model predicts the emitted particle size distribution (PSD) in terms of its constituent minerals based on brittle fragmentation theory (BFT), which reconstructs the emitted mineral aggregates destroyed by wet sieving. Our simulations broadly reproduce the most abundant mineral fractions independently of the soil composition data used. Feldspars and calcite are highly sensitive to the soil mineralogy map, mainly due to the different assumptions made in each soil dataset to extrapolate a handful of soil measurements to arid and semi-arid regions worldwide. For the least abundant or more difficult-to-determine minerals, such as iron oxides, uncertainties in soil mineralogy yield differences in annual mean aerosol mass fractions of up to ∼ 100 %. Although BFT restores coarse aggregates including phyllosilicates that usually break during soil analysis, we still identify an overestimation of coarse quartz mass fractions (above 2 µm in diameter). In a dedicated experiment, we estimate the fraction of dust with undetermined composition as given by a soil map, which makes up ∼ 10 % of the emitted dust mass at the global scale and can be regionally larger. Changes in the underlying soil mineralogy impact our estimates of climate-relevant variables, particularly affecting the regional variability of the single-scattering albedo at solar wavelengths or the total iron deposited over oceans. All in all, this assessment represents a baseline for future model experiments including new mineralogical maps constrained by high-quality spaceborne hyperspectral measurements, such as those arising from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) mission.
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Sanda, Mia, Daniel Dunea, Stefania Iordache, Alin Pohoata, Ana-Maria Glod-Lendvai, and Ion Onutu. "A Three-Year Analysis of Toxic Benzene Levels and Associated Impact in Ploieşti City, Romania." Toxics 11, no. 9 (September 2, 2023): 748. http://dx.doi.org/10.3390/toxics11090748.
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This study examines the levels of benzene and the potential health impact during three years of continuous monitoring (2019–2021), including the COVID-lockdown period from 2020 in a city that is an important Romanian center for petroleum refining and associated product manufacturing. The dataset contains benzene, toluene, NOx, PM10 concentrations, and meteorological factors monitored by six automatic stations from the national network of which four are in the city and two outside. Special attention was given to the benzene dynamics to establish patterns related to the health impact and leukemia. An assessment of the exposure was performed using EPA’s ExpoFIRST v. 2.0 for computing the inhalation Average Daily Dose (ADD) and Lifetime Average Daily Dose (LADD). The health impact was estimated based on several indicators such as lifetime cancer risk (LCR), Hazard Quotient (HQ), Disability-Adjusted Life Years (DALY), and Environmental burden of disease (EBD). Overall, the annual average of all stations was almost similar between years i.e., 3.46 in 2019, 3.41 in 2020, and 3.63 µg/m3 in 2021, respectively. The average of all stations during the lockdown period was 2.67 µg/m3, which was lower than the multiannual average of the 2019–2021 period, i.e., 3.5 µg/m3. Significant correlations were present between benzene and other pollutants such as NOx (r = 0.57), PM10 fraction (r = 0.70), and toluene (r = 0.69), and benzene and temperature (r = −0.46), humidity (r = 0.28), and wind speed (r = −0.34). Regarding the ADD, in all scenarios, the most affected age categories are small children, despite a lower outdoor exposure time. From birth to <70 years, the ADD varied depending on the exposure scenario resulting in 3.27 × 10−4, 5.6 × 10−4, and 4.04 × 104 mg/kg-day, and 3.95 × 10−4, 10.6 × 10−4, and 6.76 × 10−4 mg/kg-day for the LADD, respectively. The Integrated Lifetime Cancer Risk (ILTCR) values were 14.1 × 10−5 in winter, 9.04 × 10−5 in spring, 8.74 × 10−5 in summer, and 10.6 × 10−4 in autumn. The ILTCR annual averages were 1.08 × 10−4 (2019), 1.07 × 10−4 (2020), 1.04 × 10−4 (2021), and 1.06 × 10−4 for the entire period. The resulting ILTCR values point out very risky conditions, with the annual averages reaching the definite cancer risk category. The corresponding burden based on the DALY’s loss due to leukemia in Ploieşti was estimated at 0.291 (2 μg/m3 benzene), 0.509 (3.5 μg/m3 benzene), 0.582 (4 μg/m3 benzene), and 0.873 DALYs per 100,000 inhabitants (6 μg/m3 benzene), respectively. The current study provides useful insights for a better understanding of the exposure levels to benzene and associated health impact in Ploieşti despite the limitations determined by the data hiatus and incomplete or missing information regarding the health impact.
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González-Álvarez, Álvaro, Orlando Viloria-Marimón, Óscar Coronado-Hernández, Andrés Vélez-Pereira, Kibrewossen Tesfagiorgis, and Jairo Coronado-Hernández. "Isohyetal Maps of Daily Maximum Rainfall for Different Return Periods for the Colombian Caribbean Region." Water 11, no. 2 (February 20, 2019): 358. http://dx.doi.org/10.3390/w11020358.
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In Colombia, daily maximum multiannual series are one of the main inputs for design streamflow calculation, which requires performing a rainfall frequency analysis that involves several prior steps: (a) requesting the datasets, (b) waiting for the information, (c) reviewing the datasets received for missing or data different from the requested variable, and (d) requesting the information once again if it is not correct. To tackle these setbacks, 318 rain gauges located in the Colombian Caribbean region were used to first evaluate whether or not the Gumbel distribution was indeed the most suitable by performing frequency analyses using three different distributions (Gumbel, Generalized Extreme Value (GEV), and Log-Pearson 3 (LP3)); secondly, to generate daily maximum isohyetal maps for return periods of 2, 5, 10, 20, 25, 50, and 100 years; and, lastly, to evaluate which interpolation method (IDW, spline, and ordinary kriging) works best in areas with a varying density of data points. GEV was most suitable in 47.2% of the rain gauges, while Gumbel, in spite of being widely used in Colombia, was only suitable in 34.3% of the cases. Regarding the interpolation method, better isohyetals were obtained with the IDW method. In general, the areal maximum daily rainfall estimated showed good agreement when compared to the true values.
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Shimabukuro, Yosio E., Egidio Arai, Gabriel M. da Silva, Andeise C. Dutra, Guilherme Mataveli, Valdete Duarte, Paulo R. Martini, Henrique L. G. Cassol, Danilo S. Ferreira, and Luís R. Junqueira. "Mapping and Monitoring Forest Plantations in São Paulo State, Southeast Brazil, Using Fraction Images Derived from Multiannual Landsat Sensor Images." Forests 13, no. 10 (October 18, 2022): 1716. http://dx.doi.org/10.3390/f13101716.
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This article presents a method, based on orbital remote sensing, to map the extent of forest plantations in São Paulo State (Southeast Brazil). The proposed method uses the random forest machine learning algorithm available on the Google Earth Engine (GEE) cloud computing platform. We used 30 m annual mosaics derived from Landsat-5 Thematic Mapper (TM) images and from Landsat-8 Operational Land Imager (OLI) images for the 1985 to 1995 and 2013 to 2021 time periods, respectively. These time periods were selected based on the planted areas’ rotation, especially the eucalypt’s short rotation. To classify the forest plantations, green, red, NIR, and MIR spectral bands, NDVI, GNDVI, NDWI, and NBR spectral indices, and vegetation, shade, and soil fractions were used for both sensors. These indices and the fraction images have the advantage of reducing the volume of data to be analyzed and highlighting the forest plantations’ characteristics. In addition, we also generated one mosaic for each fraction image for the TM and OLI datasets by computing the maximum value through the period analyzed, facilitating the classification of areas occupied by forest plantations in the study area. The proposed method allowed us to classify the areas occupied by two forest plantation classes: eucalypt and pine. The results of the proposed method compared with the forest plantation areas extracted from the land use and land cover maps, provided by the MapBiomas product, presented the Kappa values of 0.54 and 0.69 for 1995 and 2020, respectively. In addition, two pilot areas were used to evaluate the classification maps and to monitor the phenological stages of eucalypt and pine plantations, showing the rotation cycle of these plantations. The results are very useful for planning and managing planted forests by commercial companies and can contribute to developing an automatic method to map forest plantations on regional and global scales.
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Galiforni-Silva, Filipe, Kathelijne M. Wijnberg, and Suzanne J. M. H. Hulscher. "Storm-induced sediment supply to coastal dunes on sand flats." Earth Surface Dynamics 8, no. 2 (May 8, 2020): 335–50. http://dx.doi.org/10.5194/esurf-8-335-2020.
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Abstract. Growth of coastal dunes requires a marine supply of sediment. Processes that control the sediment transfer between the subtidal and the supratidal zone are not fully understood, especially in sand flats close to inlets. It is hypothesised that storm surge events induce sediment deposition on sand flats, providing fresh material for aeolian transport and dune growth. The objective of this study is to identify which processes cause deposition on the sand flat during storm surge conditions and discuss the relationship between the supratidal deposition and sediment supply to the dunes. We use the island of Texel (NL) as a case study, of which multiannual topographic and hydrographic datasets are available. Additionally, we use the numerical model XBeach to simulate the most frequent storm surge events for the area. Results show that supratidal shore-parallel deposition of sand occurs in both the numerical model and the topographic data. The amount of sand deposited is directly proportional to surge level and can account for more than a quarter of the volume deposited at the dunes yearly. Furthermore, storm surges are also capable of remobilising the top layer of sediment of the sand flat, making fresh sediment available for aeolian transport. Therefore, in a sand flat setting, storm surges have the potential of reworking significant amounts of sand for aeolian transport in periods after the storm and as such can also play a constructive role in coastal dune development.
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Cabrera César, José, Jean Caratt Ortiz, Guillermo Valencia Ochoa, Rafael Ramírez Restrepo, and José R. Nuñez Alvarez. "A New Computational Tool for the Development of Advanced Exergy Analysis and LCA on Single Effect LiBr–H2O Solar Absorption Refrigeration System." Lubricants 9, no. 8 (August 5, 2021): 76. http://dx.doi.org/10.3390/lubricants9080076.
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A single effect LiBr–H2O absorption refrigeration system coupled with a solar collector and a storage tank was studied to develop an assessment tool using the built-in App Designer in MATLAB®. The model is developed using balances of mass, energy, and species conservation in the components of the absorption cooling system, taking into account the effect of external streams through temperature and pressure drop. The whole system, coupled with the solar energy harvesting arrangement, is modeled for 24 h of operation with changes on an hourly basis based on ambient temperature, cooling system load demand, and hourly solar irradiation, which is measured and recorded by national weather institutes sources. Test through simulations and validation procedures are carried out with acknowledged scientific articles. These show 2.65% of maximum relative error on the energy analysis with respect to cited authors. The environmental conditions used in the study were evaluated in Barranquilla, Colombia, with datasets of the Institute of Hydrology, Meteorology and Environmental Studies (IDEAM), considering multiannual average hourly basis solar irradiation. This allowed the authors to obtain the behavior of the surface temperature of the water in the tank, COP, and exergy efficiency of the system. The simulations also stated the generator as the biggest source of irreversibility with around 45.53% of total exergy destruction in the inner cycle without considering the solar array, in which case the solar array would present the most exergy destruction.
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Mueller, Marlin M., Clémence Dubois, Thomas Jagdhuber, Florian M. Hellwig, Carsten Pathe, Christiane Schmullius, and Susan Steele-Dunne. "Sentinel-1 Backscatter Time Series for Characterization of Evapotranspiration Dynamics over Temperate Coniferous Forests." Remote Sensing 14, no. 24 (December 16, 2022): 6384. http://dx.doi.org/10.3390/rs14246384.
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Forests’ ecosystems are an essential part of the global carbon cycle with vast carbon storage potential. These systems are currently under external pressures showing increasing change due to climate change. A better understanding of the biophysical properties of forests is, therefore, of paramount importance for research and monitoring purposes. While there are many biophysical properties, the focus of this study is on the in-depth analysis of the connection between the C-band Copernicus Sentinel-1 SAR backscatter and evapotranspiration (ET) estimates based on in situ meteorological data and the FAO-based Penman–Monteith equation as well as the well-established global terrestrial ET product from the Terra and Aqua MODIS sensors. The analysis was performed in the Free State of Thuringia, central Germany, over coniferous forests within an area of 2452 km2, considering a 5-year time series (June 2016–July 2021) of 6- to 12-day Sentinel-1 backscatter acquisitions/observations, daily in situ meteorological measurements of four weather stations as well as an 8-day composite of ET products of the MODIS sensors. Correlation analyses of the three datasets were implemented independently for each of the microwave sensor’s acquisition parameters, ascending and descending overpass direction and co- or cross-polarization, investigating different time series seasonality filters. The Sentinel-1 backscatter and both ET time series datasets show a similar multiannual seasonally fluctuating behavior with increasing values in the spring, peaks in the summer, decreases in the autumn and troughs in the winter months. The backscatter difference between summer and winter reaches over 1.5 dB, while the evapotranspiration difference reaches 8 mm/day for the in situ measurements and 300 kg/m2/8-day for the MODIS product. The best correlation between the Sentinel-1 backscatter and both ET products is achieved in the ascending overpass direction, with datasets acquired in the late afternoon, and reaches an R2-value of over 0.8. The correlation for the descending overpass direction reaches values of up to 0.6. These results suggest that the SAR backscatter signal of coniferous forests is sensitive to the biophysical property evapotranspiration under some scenarios.
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Taszarek, Mateusz, John Allen, Tomáš Púčik, Pieter Groenemeijer, Bartosz Czernecki, Leszek Kolendowicz, Kostas Lagouvardos, Vasiliki Kotroni, and Wolfgang Schulz. "A Climatology of Thunderstorms across Europe from a Synthesis of Multiple Data Sources." Journal of Climate 32, no. 6 (March 8, 2019): 1813–37. http://dx.doi.org/10.1175/jcli-d-18-0372.1.
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Abstract The climatology of (severe) thunderstorm days is investigated on a pan-European scale for the period of 1979–2017. For this purpose, sounding measurements, surface observations, lightning data from ZEUS (a European-wide lightning detection system) and European Cooperation for Lightning Detection (EUCLID), ERA-Interim, and severe weather reports are compared and their respective strengths and weaknesses are discussed. The research focuses on the annual cycles in thunderstorm activity and their spatial variability. According to all datasets thunderstorms are the most frequent in the central Mediterranean, the Alps, the Balkan Peninsula, and the Carpathians. Proxies for severe thunderstorm environments show similar patterns, but severe weather reports instead have their highest frequency over central Europe. Annual peak thunderstorm activity is in July and August over northern, eastern, and central Europe, contrasting with peaks in May and June over western and southeastern Europe. The Mediterranean, driven by the warm waters, has predominant activity in the fall (western part) and winter (eastern part) while the nearby Iberian Peninsula and eastern Turkey have peaks in April and May. Trend analysis of the mean annual number of days with thunderstorms since 1979 indicates an increase over the Alps and central, southeastern, and eastern Europe with a decrease over the southwest. Multiannual changes refer also to changes in the pattern of the annual cycle. Comparison of different data sources revealed that although lightning data provide the most objective sampling of thunderstorm activity, short operating periods and areas devoid of sensors limit their utility. In contrast, reanalysis complements these disadvantages to provide a longer climatology, but is prone to errors related to modeling thunderstorm occurrence and the numerical simulation itself.
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Scotti, Alberto, and Roberta Bottarin. "Fine-scale multiannual survey of benthic invertebrates in a glacier-fed stream used for hydropower generation." Scientific Data 8, no. 1 (April 13, 2021). http://dx.doi.org/10.1038/s41597-021-00887-x.
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AbstractThe present dataset contains information about aquatic macroinvertebrates and environmental variables collected before and after the implementation of a small “run-of-river” hydropower plant on the Saldur stream, a glacier-fed stream located in the Italian Central-Eastern Alps. Between 2015 and 2019, with two sampling events per year, we collected and identified 34,836 organisms in 6 sampling sites located within a 6 km stretch of the stream. Given the current boom of the hydropower sector worldwide, and the growing contribution of small hydropower plants to energy production, data here included may represent an important – and long advocated – baseline to assess the effects that these kinds of powerplants have on the riverine ecosystem. Moreover, since the Saldur stream is part of the International Long Term Ecological Research network, this dataset also constitutes part of the data gathered within this research programme. All samples are preserved at Eurac Research facilities.
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Kosak, Ferdinand, and Sven Hilbert. "The Passage of Years: Not a Matter of Covert Retrieval of Autobiographical Memories." Frontiers in Psychology 12 (October 14, 2021). http://dx.doi.org/10.3389/fpsyg.2021.744551.
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In current research, variations in retrospective passage of time judgments for long intervals are commonly attributed to differences regarding the number of experiences in these intervals or the accessibility of the respective memories. This seems to imply the assumption of a covert retrieval, where authors presume that memories from the respective interval influence the experience of time without these memories being explicitly activated when judging. However, no studies have systematically investigated the relation between the experience of time and the respective experiences and memories. To this end, we analyzed data from three studies in which participants judged the passage of the last 5 years either before being asked to select outstanding life events from a list (Studies 1a and b; N = 293 and 263) or before recalling as many meaningful personal memories as were spontaneously accessible (Study 2; N = 262). Despite applying a statistically powerful trial-by-trial mixed-effects modeling approach, neither in the separate datasets nor in the combined dataset, passage of time judgments were predicted by the number of reported events or memories. This suggests that people's spontaneous judgments of the passage of multiannual intervals are not necessarily affected by a covert retrieval of memories from the respective period.
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Kosak, Ferdinand, and Sven Hilbert. "The Passage of Years: Not a Matter of Covert Retrieval of Autobiographical Memories." Frontiers in Psychology 12 (October 14, 2021). http://dx.doi.org/10.3389/fpsyg.2021.744551.
Full textAbstract:
In current research, variations in retrospective passage of time judgments for long intervals are commonly attributed to differences regarding the number of experiences in these intervals or the accessibility of the respective memories. This seems to imply the assumption of a covert retrieval, where authors presume that memories from the respective interval influence the experience of time without these memories being explicitly activated when judging. However, no studies have systematically investigated the relation between the experience of time and the respective experiences and memories. To this end, we analyzed data from three studies in which participants judged the passage of the last 5 years either before being asked to select outstanding life events from a list (Studies 1a and b; N = 293 and 263) or before recalling as many meaningful personal memories as were spontaneously accessible (Study 2; N = 262). Despite applying a statistically powerful trial-by-trial mixed-effects modeling approach, neither in the separate datasets nor in the combined dataset, passage of time judgments were predicted by the number of reported events or memories. This suggests that people's spontaneous judgments of the passage of multiannual intervals are not necessarily affected by a covert retrieval of memories from the respective period.
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Brönnimann, Stefan. "Evolution of total column ozone prior to the era of ozone depletion." Frontiers in Earth Science 11 (February 6, 2023). http://dx.doi.org/10.3389/feart.2023.1079510.
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Total column ozone has been monitored for almost a century. The focus of most research studies over the last 40 years was on the era of ozone depletion and the detection of signs of recovery. However, the question also arises to what extent total column ozone has changed prior to this era. Possible causes could be changes in ozone production (both in the troposphere and stratosphere) due to changing atmospheric composition, changes in solar activity, or climatic changes. In this contribution, I discuss the evolution of total column ozone in the 40 years from 1924, when ozone monitoring started, to 1963, which is approximately the time when ozone depletion started to affect the ozone layer. Using long historical measurements, as well as an assimilated zonal mean total column ozone dataset, I show that variability was characterized by strong interannual-to-multiannual anomalies, with a small positive trend at the northern mid-to high-latitudes of ca. 6 DU over the 40-year period. The latitudinal pattern of the trend matches that found in CMIP6 models, but the trend at mid-latitudes is weaker than that in the models.
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Voutilainen, Liina, Eva R. Kallio, Jukka Niemimaa, Olli Vapalahti, and Heikki Henttonen. "Temporal dynamics of Puumala hantavirus infection in cyclic populations of bank voles." Scientific Reports 6, no. 1 (February 18, 2016). http://dx.doi.org/10.1038/srep21323.
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Abstract Understanding the dynamics of zoonotic pathogens in their reservoir host populations is a prerequisite for predicting and preventing human disease epidemics. The human infection risk of Puumala hantavirus (PUUV) is highest in northern Europe, where populations of the rodent host (bank vole, Myodes glareolus) undergo cyclic fluctuations. We conducted a 7-year capture-mark-recapture study to monitor seasonal and multiannual patterns of the PUUV infection rate in bank vole populations exhibiting a 3-year density cycle. Infected bank voles were most abundant in mid-winter months during years of increasing or peak host density. Prevalence of PUUV infection in bank voles exhibited a regular, seasonal pattern reflecting the annual population turnover and accumulation of infections within each year cohort. In autumn, the PUUV transmission rate tracked increasing host abundance, suggesting a density-dependent transmission. However, prevalence of PUUV infection was similar during the increase and peak years of the density cycle despite a twofold difference in host density. This may result from the high proportion of individuals carrying maternal antibodies constraining transmission during the cycle peak years. Our exceptionally intensive and long-term dataset provides a solid basis on which to develop models to predict the dynamic public health threat posed by PUUV in northern Europe.