Climatological Conditions Research Articles

Effects of foliar applications of methyl jasmonate alone or with urea on anthocyanins content during grape ripening

Anthocyanins, the main phenolic compounds responsible for the color of red grapes and wines, exhibit antioxidant and antimicrobial properties and offer various health benefits for humans. Currently, climate change can affect grape quality by causing a decoupling between the technological and phenolic maturities of the grapes. Foliar application of methyl jasmonate (MeJ) and urea (Ur) can be a tool to mitigate the global warming effects in the vineyard. The aim of this work was to study i) the development of anthocyanin content in ‘Tempranillo’ grapes along the ripening process, and ii) the effect of foliar application of MeJ and MeJ+Ur on these phenolic compounds over two vintages (2019 and 2020). Overall, in the first vintage, anthocyanins peaked in their concentrations in the pre-harvest or harvest moments; whereas in the second vintage, the highest contents of these phenolic compounds were reached at harvest time, after that, a maintenance or decreased of their concentrations was observed. In both vintages, non-acylated anthocyanins was the most abundant family of anthocyanins. Foliar application of MeJ+Ur was more effective in enhancing anthocyanin biosynthesis than MeJ treatment, which also increased anthocyanin content compared to control grapes. Therefore, MeJ and Ur foliar treatment could present a synergy in anthocyanin biosynthesis by the plant. Moreover, the impact of these applications varied across vintages, and also the content of anthocyanins in grapes, probably due to different climatological conditions. Consequently, the two foliar treatments, MeJ and MeJ+Ur, could be a suitable tool to increase anthocyanins biosynthesis in grapes, and thus improve grape quality.

Geographical variability in hygrothermal simulation results of historical building envelopes with interior insulation in Belgium

Thermal retrofits of existing buildings offer a great potential to reduce Europe’s energy use and CO2 emissions. The impact of these retrofitting strategies on the risk for degradation in building envelopes is assessed through hygrothermal simulations. Due to the lack of long term climate data, hygrothermal simulations are performed for a certain location, and the results are generalised over a large region. However, this generalisation may not be valid, since the hygrothermal performance of building envelopes is highly influenced by local climate conditions. Therefore, we assessed the geographical variability on degradation risks in building envelopes. This paper presents the results of 34560 hygrothermal simulations of solid masonry walls, with and without interior insulation, and including a range of other parameter variations, for 20 synoptic weather stations across Belgium. Generally, the risk for degradation is higher at locations with a higher elevation above sea level. For Belgium, the elevation correlates well with the mean temperature (invers correlation), and the annual precipitation and wind-driven rain load. For a known wall orientation, the impact of interior insulation on the risk for freeze-thaw damage is most determined by the elevation above sea level. Also the mould index in uninsulated walls correlates best with the elevation. On the contrary, the brick type is more important than the location when considering wood decay of embedded beam heads in retrofitted walls. To conclude, the risk for degradation cannot be generalised, especially over areas with complex variations in orographic and climatological conditions.

Patterns of Zoological Diversity in Iran—A Review

Iran is a country characterized by high biodiversity and complex biogeographic patterns. Its diverse landscape and steep climatic gradients have resulted in significant faunal diversity and high level of endemism. To better understand these patterns, we investigated the historical environmental drivers that have shaped Iran’s current geological and climatological conditions, and, consequently, have shaped the current zoological distribution patterns. Furthermore, we provide an overview of the country’s zoological diversity and zoogeography by reviewing published studies on its fauna. We analyzed nearly all available catalogs, updated checklists, and relevant publications, and synthesized them to present a comprehensive overview of Iran’s biodiversity. Our review reports approximately 37,500 animal species for Iran. We also demonstrated that the country serves as a biogeographic transition zone among three zoogeographical realms: the Palearctic, Oriental, and Saharo-Arabian, where distinct faunal elements intersect. This biogeographic complexity has made it challenging to delineate clear zoogeographical zones, leading to varying classifications depending on the taxon. The uplift of mountain ranges, in particular, has played a crucial role in shaping faunal diversity by serving as barriers, corridors, and glacial refugia. These mountains are largely the result of orogeny and plate collisions during the Mesozoic and Cenozoic eras, coupled with the development of the Tethyan Sea and the uplift of several ranges during the Miocene. Despite these insights, our understanding of biodiversity distribution in Iran remains incomplete, even for some well-studied taxa, such as certain vertebrate families and arthropods. We highlight the existing gaps in knowledge regarding zoogeographical patterns and propose approaches to address these gaps, particularly concerning less-studied species and the highly diverse group of insects.

Evidence of palaeoenvironmental and climatic changes from the interpreted radar wave pictures of near surface sediments around the River Nile, Assiut, Egypt

Different palaeoenvironmental features that pose natural geological, environmental, and engineering hazards to human operations occur frequently around the Nile Valley. Moreover, where these features were initially created, their relevance focuses on how the urban communities responded to the processes. So, a ground penetrating radar (GPR) field survey was carried out on different paleoenvironments of Pre-Quaternary and Quaternary sediment around Assiut. Deep and critical analyses of georadar facies were made to obtain clear images of these features with unprecedented resolution. The main objective of this study is to find some reasonable geological interpretations for these features. From this study, it is possible to identify and differentiate these features originating from different geological environments and climatological conditions in arid regions such as those around Assiut. In addition, the study serves as guidelines for environmental management and climatic changes for enhancing knowledge of urban development. Also, the study demonstrates how georadar can be used to create precise images of intricate shallow subsurface anatomy with possible palaeoenvironmental and palaeoclimatic indicators.

Soil nitrous oxide emissions from wheat-based rotations with different types of pulse crops

Production of agricultural crops with a low greenhouse gas (GHG) footprint is essential to mitigate the adverse effects of climate change. The inclusion of pulse crops in cereal-based rotations can enhance environmental quality by providing biologically fixed N and thereby reducing the amount of synthetic N fertilizer required for the crop rotation. The inclusion of pulse crop has the potential to reduce N2O emissions from the agricultural system in both the legume phase and the subsequent wheat phase of the rotation. However, long-term studies are necessary to thoroughly investigate N2O emissions from rotations with pulse crops, particularly in the semiarid region where pulse crops are frequently grown. In the present study, we evaluated cumulative N2O emissions and emission intensity during the rotation cycle. The assessment was conducted over 4 years, during two complete 2-yr cycles of an established rotation (years 9–12), under the climatological conditions of 2018–2021. Four rotations including wheat-wheat, pea-wheat, lentil-wheat, and chickpea-wheat were selected from a trial in Swift Current, Saskatchewan (semiarid prairies/Brown Chernozem). Our experiment was subjected to below normal precipitation, with interannual variations in climate and the last 2 years (2020–21) were drier than the first two years (2018–2019). Under such climate, PW and LW demonstrated to be environmentally sustainable, always exporting the highest N in grains (133 kg N ha−1 averaged across PW and LW and cycles) and consistently achieving the lowest N2O intensity (2.8 g N2O-N per kg exported N averaged across PW and LW and cycles). Continuous wheat presented inconsistent results, with a significant reduction in exported N from years 9–10 to 11–12 (the driest cycle). Because WW also promoted the highest cumulative N2O emissions, N2O intensity over the 2-yr was always the highest for WW. The CW consistently promoted the lowest N exports and was not resilient to dry soil conditions, with 23% lower exported N in years 11–12 than in years 9–10. Hence including pulse crops with pea or lentil in the rotation reduced N2O emissions and enhanced wheat yield resiliency.

A Review of the Oceanography and Antarctic Bottom Water Formation Offshore Cape Darnley, East Antarctica

AbstractAntarctic Bottom Water (AABW) is the densest water mass in the world and drives the lower limb of the global thermohaline circulation. AABW is formed in only four regions around Antarctica and Cape Darnley, East Antarctica, is the most recently discovered formation region. Here, we compile 40 years of oceanographic data for this region to provide the climatological oceanographic conditions, and review the water mass properties and their role in AABW formation. We split the region into three sectors (East, Central and West) and identify the main water masses, current regimes and their influence on the formation of Cape Darnley Bottom Water (CDBW). In the eastern sector, Prydz Bay, the formation of Ice Shelf Water preconditions the water (cold and fresh) that flows into the central sector to E, enhancing sea ice production in Cape Darnley Polynya. This produces a high salinity variant of Dense Shelf Water (DSW) (up to 35.15 g/kg) that we coin Burton Basin DSW. In contrast, the western sector of the Cape Darnley Polynya produces a low salinity variant (up to 34.85 g/kg) we coin Nielsen Basin DSW. The resultant combined CDBW is the warmest (upper temperature bound of 0.05C) AABW formed around Antarctica with an upper bound salinity of 34.845 g/kg. Our findings will contribute to planning future observing systems at Cape Darnley, determining the role that CDBW plays in our global oceanic and climate systems, and modeling past and future climate scenarios.

The influence of El Niño on springtime synoptic-scale precipitation extremes in Southeastern China: insights from CMIP6 model simulations

This study focuses on El Niño impacts on springtime extreme precipitation in Southeastern China (SEC) by comparing observations with data from the Coupled Model Intercomparison Project phase 6 (CMIP6) historical runs. Observational and simulated results suggest that synoptic-scale temperature advection patterns over East Asia (EA) are closely associated with extreme precipitation in SEC, encompassing the Pearl River Basin (PRB), Yangtze River Basin (YRB), and Huaihe River Basin (HRB). Based on this, we introduce a temperature advection index (TAI) tailored to capture the cold-warm temperature advection dipole, which shows a significant positive correlation with SEC precipitation. Both observations and CMIP6 indicate that TAI-related circulations, characterized by upper-level synoptic-scale waves and a north–south oriented temperature gradient over EA, are conducive to extreme precipitation in northern PRB (NPRB)–YRB–HRB. However, the TAI-related synoptic-scale activities have a lesser impact on extreme precipitation in southern PRB (SPRB), as these disturbances mainly affect the mid-latitude weather. Further investigation reveals that during boreal spring following El Niño, 85% of extreme events in YRB–HRB are associated with positive TAI values, compared to 76% under climatological conditions. However, such a change in the association with TAI is not evident in CMIP6 simulations. From observations, atmospheric baroclinicity along the East Asian westerly jet is enhanced during El Niño, which promotes the development of TAI-related synoptic-scale disturbances. In contrast, CMIP6 models struggle to reproduce these observed baroclinicity signals during El Niño. This challenge arises from the background westerly jet bias and mean-state cold tongue bias in tropical Pacific temperature in models.

Classification of expansive soils among problematic soils in the brazilian semiarid from artificial neural networks

The climatological and geomorphological conditions of the Brazilian semiarid region favor the formation of potentially expansive soils. The development of neural networks to identify and classify expansive soils in Pernambuco, and the need to export to soils across the semiarid region of Brazil is investigated in this study using a Multi-Layer Perceptron (backpropagation). The neural network was developed using 87 experimental data points, divided into three groups. The Training Group, consisting of 53 samples, using data inputs: sand percentage, clay percentage, plasticity index, activity index, and geological, pedological, and climatological classification. Selection Group, made up of 17 samples, was used to select the best network architecture, genetics algorithms formed of 7 inputs and 3 hidden nodes. The Test Group used 17 samples to evaluate the predictive accuracy of the expansion potential, obtaining an accuracy rate of 88,2%. This network was validated by applying it to 67 samples of problematic soils of the collapsible, expansive, and soft type from the Brazilian semiarid region, reaching an accuracy of 76,1%. Probabilistic Neural Networks were found to be efficient in evaluating the behavior of expansive soils, with the ability to deal with the absence of sample input data, demonstrating the ability to capture movement trends in the expansion of the soil surface, indicating the functions that introduce the effects of the composition potential on the expansion behavior, and determining the limit values of each of the input variables for the samples from the database used.

Erythemal weighting function adjustment for a correct calculation of UV index in high-altitude cities

Abstract Andean cities are mostly characterized, and appreciated, by their high elevation. Commonly above 2500m above the sea level. However, a more subtle feature is their proximity to the Equator. These two characteristics provide these cities with unique climatological conditions. Complementary to this, the main autoethnography of the zone is “mestizo”, which is characterized by its type of skin (namely types III and IV). These kind of skins are highly adapted to radiation intensity (and atmosphere density) of the equatorial zone. We use measurements of radiation from sensors located at Quito in order to provide a novel method to computing the local ultraviolet-index range risk, taking into account an action spectrum of skin types III and IV, and the recommendations of the World Health Organization. The results of this study could be applied directly to cities with climatological conditions, and with population with skin types, similar to those from the Andean region.

Climatology and circulation conditions of potential foehn occurrence in the Polish Tatra Mountains

AbstractFoehn wind occurrence has generated great interest among researchers because of the destructive power and impact on the local climate. Based on anemometric data provided by a high-mountain station on Kasprowy Wierch in the Polish Tatra Mountains, the characteristics of the potential occurrence of foehn wind (referred to as halny in the Polish Tatras) are presented, including its speed and duration, as well as the frequency of occurrence on a multiannual, annual and daily basis. Halny winds occur most frequently in the cold period of the year (Oct–Feb), with the frequency peaking in November, and sporadically in the summer. The occurrence of foehn winds is strongly dependent on the synoptic situation. Therefore, the main aim of the study was to identify the circulation conditions conducive to their occurrence on the Polish side of the Tatra Mountains. Circulation conditions responsible for foehn formation were analysed using gridded sea level pressure (SLP) data from the NCEP-DOE (National Centers for Environmental Prediction-Department of Energy) reanalyses. The occurrence of foehn wind in the Tatra Mountains is associated with a low pressure system over north-western Europe, and above normal pressure over south-eastern Europe. The location and intensity of the centres of atmospheric influence on foehn days can vary, as indicated by the three types of pressure systems favouring the occurrence of the phenomenon, distinguished by the hierarchical grouping method. In type 1, the cyclonic centre spreads over northern Europe, in type 2 over western Europe and in type 3 over north-western Europe. In types 1 and 3, the air masses come from the south-west, and in type 2 more from the south. Type 3 is characterised by the greatest horizontal pressure gradients among the three circulation types and with the greatest SLP anomalies.

A study on spatio-temporal trend of rubber leaf fall phenomenon using planetscope multi-index vegetation imagery in relations to climatological conditions

Background: Rubber plants are one of the most important plantation commodities in Indonesia. However, rubber production has declined due to leaf fall disease caused by the pathogen Pestalotiopsis sp. This study aims to analyze the spatial and temporal distribution of rubber plant leaf fall disease using multi-vegetation indices from PlanetScope imagery, as well as to analyze the influence of climatological conditions on the disease. Methods: The research was conducted at the Sembawa Rubber Research Center Garden, South Sumatra, using PlanetScope imagery data and climatological data in 2017 (before leaf fall) and 2023 (after leaf fall). Finding: Spatially, the 2023 leaf fall occurred in almost the entire garden area with poor to moderate levels. Blocks 2013D, 2012F, and 2009F experienced the most severe levels, with a total defoliated area reaching 396.76 ha. Analysis of monthly variations in vegetation index values revealed a decrease in values during leaf fall due to Pestalotiopsis sp., specifically in February, May, and September 2023. Statistical test results showed significant differences in vegetation index values between 2017 and 2023. Furthermore, based on Spearman's correlation analysis, there was a positive correlation between vegetation index values and humidity, but no significant correlation with rainfall and temperature. Conclusion: This research provides insights into mapping and monitoring rubber leaf fall disease using remote sensing data and climatological factors, which can be used for more effective rubber plantation management. However, the study has some limitations: monthly Planet data for 2017 is not fully available, several Planet image scenes from 2017 still have more than 50% cloud cover, and there may be biases as plants falling into the low health class are included in the high range of vegetation index values. Novelty/Originality of this Study: The study employs multi-vegetation indices derived from high-resolution PlanetScope imagery to detect and assess rubber leaf fall disease (LFD) within a plantation environment. By integrating spatial and temporal analyses with climatological data, the research provides a precise and comprehensive method for monitoring LFD and understanding its environmental determinants, thereby enhancing traditional rubber plantation management practices.

Uncertainty in simulated brightness temperature due to sensitivity to atmospheric gas spectroscopic parameters from the centimeter- to submillimeter-wave range

Abstract. Atmospheric radiative transfer models are extensively used in Earth observation to simulate radiative processes occurring in the atmosphere and to provide both upwelling and downwelling synthetic brightness temperatures for ground-based, airborne, and satellite radiometric sensors. For a meaningful comparison between simulated and observed radiances, it is crucial to characterize the uncertainty in such models. The purpose of this work is to quantify the uncertainty in radiative transfer models due to uncertainty in the associated spectroscopic parameters and to compute simulated brightness temperature uncertainties for millimeter- and submillimeter-wave channels of downward-looking satellite radiometric sensors (MicroWave Imager, MWI; Ice Cloud Imager, ICI; MicroWave Sounder, MWS; and Advanced Technology Microwave Sounder, ATMS) as well as upward-looking airborne radiometers (International Submillimetre Airborne Radiometer, ISMAR, and Microwave Airborne Radiometer Scanning System, MARSS). The approach adopted here is firstly to study the sensitivity of brightness temperature calculations to each spectroscopic parameter separately, then to identify the dominant parameters and investigate their uncertainty covariance, and finally to compute the total brightness temperature uncertainty due to the full uncertainty covariance matrix for the identified set of relevant spectroscopic parameters. The approach is applied to a recent version of the Millimeter-wave Propagation Model, taking into account water vapor, oxygen, and ozone spectroscopic parameters, though the approach is general and can be applied to any radiative transfer code. A set of 135 spectroscopic parameters were identified as dominant for the uncertainty in simulated brightness temperatures (26 for water vapor, 109 for oxygen, none for ozone). The uncertainty in simulated brightness temperatures is computed for six climatology conditions (ranging from sub-Arctic winter to tropical) and all instrument channels. Uncertainty is found to be up to few kelvins [K] in the millimeter-wave range, whereas it is considerably lower in the submillimeter-wave range (less than 1 K).

Eficiencia biológica y evaluación de los compuestos bioactivos de cepas silvestres mexicanas de Hericium erinaceus

The basidiomycete Hericium erinaceus is one of the most consumed edibles and medicinal mushrooms in the world and appreciated in traditional Chinese medicine. In Mexico it is known as lion's mane. The biological efficiency of wild strains of H. erinaceus cultivated in different substrates in the Durango region, mainly agave bagasse, a waste from mezcal production, was evaluated. The CCH003 strain from Espinazo del diablo showed the highest biological efficiency of 42.33 % and a productivity rate of 0.47 %, with a total cultivation period of 90 days and three harvests. Regarding the evaluation of bioactive compounds, the same strain obtained significant differences compared to the others, it presented the highest values for all determinations; 60 ± 0.018 mg EAG.g ES-1 in phenolic content, 4.21 ± 0.013 mg EQ.g ES-1 for flavonoids, 71.16 ± 0.002 mg EAA.g ES-1 in CAT, 0.0012 ± 0.001 mg AA.g ES-1 for by ABTS and 121 ± 0.107 µg EAG.mL-1 by DPPH. The variability of the results in the tests carried out provides information on how the type of substrate, climatological and geographical conditions and stage of maturity influence the development of the fungus, including the production of secondary metabolites, even if it is the same species. It is expected that this information will be useful to promote the use of agave bagasse as a substrate in the cultivation of H. erinaceus and thereby diversify rural activities in the region, and in the future generate new studies on the effect of conditions on the production of bioactive compounds. Keywords: agave bagasse, antioxidant, medicinal mushrooms.

An Examination of the Wrangel Island Sea Ice Thickness Dipole

AbstractThe Beaufort Sea High is a high‐pressure system located in the Beaufort Sea that influences ocean circulation in the western Arctic known as the Beaufort Gyre. Wrangel Island, located in the western Chukchi Sea, typically experiences easterly sea ice motion due to the Beaufort Gyre. We find that under these climatological conditions, moving ice is blocked by the island and accumulates on its eastern side, while ice on its western side continues to drift leaving an area of open water and reduced ice thickness along the western side of the island. This results in an ice thickness dipole across the island. A reversal in the atmospheric circulation across the western Arctic results in a dipole with the opposing sign. We find the dipole is present throughout the year and is strongest in January when the difference in ice thickness between the eastern and western sides of the island is approximately 1 m. During the spring, it is associated with the transient opening of a polynya to the west of the island. The dipole is the result of opposing ice divergence and convergence across the western Arctic and may impact ocean circulation and ecosystems within the Chukchi Sea.

Natural ventilation to improve indoor air quality (IAQ) in existing homes: The development of health-based and context-specific user guidelines

Acceptable indoor air quality (IAQ) is one of the most relevant aspects of a healthy home environment. Despite advances in mechanical and hybrid ventilation systems, natural ventilation still constitutes a crucial intervention to improve IAQ in existing homes; especially in older and/or vulnerable ones. The challenge, however, is optimizing natural ventilation strategies so IAQ is reached while thermal discomfort (and potentially associated energy consumption) is minimized.The complexity of identifying factors that may determine the possibilities of natural ventilation in existing homes has traditionally hindered the efforts from the scientific community to communicate straightforward answers for end-users. This work develops a methodology that, based on real case studies and through a series of simulations, provides simple, context-specific criteria and recommendations in order to reach acceptable IAQ through natural ventilation strategies in existing homes. The use of a minimum ventilation time (MVT) indicator, alongside considerations for different seasons and housing types, are translated into step-by-step guidelines aimed at helping the end-user to (i) gain knowledge regarding the opportunities and limitations for natural ventilation in the dwelling, and (ii) identify which specific actions should be carried out under different conditions to maintain minimum IAQ.The conceptual framework and methodology presented, while illustrated for the case of Barcelona, can be replicated for different cities or regions with differing housing characteristics and climatological conditions, and can easily accommodate other locally relevant factors.

Natural Hazards in a Changing World: Methods for Analyzing Trends and Non‐Linear Changes

AbstractEstimating the frequency and magnitude of natural hazards largely hinges on stationary models, which do not account for changes in the climatological, hydrological, and geophysical baseline conditions. Using five diverse case studies encompassing various natural hazard types, we present advanced statistical and machine learning methods to analyze and model transient states from long‐term inventory data. A novel storminess metric reveals increasing European winter windstorm severity from 1950 to 2010. Non‐stationary extreme value models quantify trends, seasonal shifts, and regional differences in extreme precipitation for Germany between 1941 and 2021. Utilizing quantile sampling and empirical mode decomposition on 148 years of daily weather and discharge data in the European Alps, we assess the impacts of changing snow cover, precipitation, and anthropogenic river network modifications on river runoff. Moreover, a probabilistic framework estimates return periods of glacier lake outburst floods in the Himalayas, demonstrating large differences in 100‐year flood levels. Utilizing a Bayesian change point algorithm, we track the onset of increased seismicity in the southern central United States and find correlation with wastewater injections into deep wells. In conclusion, data science reveals transient states for very different natural hazard types, characterized by diverse forms of change, ranging from gradual trends to sudden change points and from altered seasonality to overall intensity variations. In synergy with the physical understanding of Earth science, we gain important new insights into the dynamics of the studied hazards and their possible mechanisms.

Seasonal variation of the water quality in an intermittent river perennified by hydraulic work: a case study of the Terra Nova river basin, Northeast Brazil

The hydrographic basins inserted in the Brazilian semi-arid region tend to aridization and intermittency due to climatological and geological conditions, suffering great anthropic pressure and experiencing seasonal changes in water quality. The aim of this study was to analyze the seasonal variation of the water quality in an intermittent river perennified by hydraulic work: a case study of the Terra Nova river basin (TNRB), located in the state of Pernambuco, Brazil. Physical, chemical and biological parameters were analysed. Water samples were collected at eight sampling points in the TRNB, from 2009 to 2022, totaling 26 campaigns. The Water Quality Index (WQI) adapted by the Environmental Sanitation Technology Company of the State of São Paulo (CETESB) was applied. The results were evaluated spatially and temporally. It was observed that in most campaigns there was no water at the monitoring points, both in the rainy season (77.8%) and in the dry season (73.5%). During the sampling period the WQI ranged from Excellent (81) to Bad (24) in the TNRB. Point Q06 stood out from the others, presenting the only WQI classified as Excellent. With regard to seasonality, the dry season ranged from Excellent (81) to Bad (24), while in the rainy season it ranged from Good (78) to Bad (22). To improve water quality it is necessary to invest in basic sanitation in the TNRB municipalities, environmental recovery, environmental education and monitoring with the aim of mitigating conflicts and impacts.

Risk assessment of mold growth across the US due to weather variations

Mold growth in residential and commercial buildings poses a serious problem to various communities. There are several facets of the problem, the most prominent of which are chronic public health risks, business losses, and monetary and labor resources needed for mold containment and mitigation. In addition, there may be severe renovation work needed if the problem is left unattended. This paper describes a probabilistic framework for mold growth risk assessment on various construction materials and shows its application across a variety of climate conditions. Mold growth is contingent upon three ingredients: temperature, moisture, and nutrients. A specific construction material of interest represents the latter, while the other two are modeled through Monte-Carlo simulations. Mold growth is characterized by the mold growth index, which is tracked over ten years, with hourly time resolution. Analysis of the temperature and relative humidity empirical data revealed that these quantities are statistically dependent. Accounting for these interdependencies is crucial for realistic simulations of temperature and humidity and were numerically reproduced in the developed method. The developed framework allowed for realistic assessment of mold growth risk. It was applied across 60 US metropolitan areas in different climatological zones to quantify mold growth risk. The proposed framework allows for quantitative risk assessment of mold growth in different climatological conditions. Such a capability is needed for decision makers for timely mold mitigation, preventing health hazards, and avoiding large financial losses for emergency mold remediation and building repair.

Influence of methyl jasmonate and methyl jasmonate plus urea foliar applications on amino acids composition throughout ‘Tempranillo’ grape ripening over two seasons

This work studies the impact of foliar application of methyl jasmonate (MeJA) and methyl jasmonate plus urea (MeJA + Ur) on the evolution of amino acid content in ‘Tempranillo’ grapes during ripening, across two vintages. To achieve this goal, sample grapes were harvested at five different timing. Fol1: 1 day before first foliar application; Fol2: 1 day before second foliar application; Preharvest: 15 days after second foliar application; Harvest: the day of harvest; and Postharvest: 15 days after harvest. The effect of foliar treatments was season dependent, being effective to improve the amino acids content of grapes only in the first vintage. Among the treatments studied, foliar application of MeJA-Ur showed better results. The evolution of amino acids during ripening also was different among seasons. Overall, in the 2019, amino acids reached their highest content at Preharvest or Harvest samples, whereas in the 2020 season, these highest concentrations were reached at Postharvest. Asparagine might serve as a suitable amino acid for controlling grape ripening, as its content decreased from Fol1 to Postharvest in the two vintages. Moreover, differences on the total amino acids content at Harvest date between vintages were observed, probably due to different climatological conditions. Therefore, this study pioneers the examination of the impact of foliar applications of MeJA and MeJA + Ur on the amino acids evolution in ‘Tempranillo’ grapes during ripening. The need for further research is clear to comprehend the complex interaction between foliar treatments and grape amino acids dynamics for optimizing nitrogen quality of grapes.

Dense Time Series Generation of Surface Water Extents through Optical–SAR Sensor Fusion and Gap Filling

Surface water is a vital component of the Earth’s water cycle and characterizing its dynamics is essential for understanding and managing our water resources. Satellite-based remote sensing has been used to monitor surface water dynamics, but cloud cover can obscure surface observations, particularly during flood events, hindering water identification. The fusion of optical and synthetic aperture radar (SAR) data leverages the advantages of both sensors to provide accurate surface water maps while increasing the temporal density of unobstructed observations for monitoring surface water spatial dynamics. This paper presents a method for generating dense time series of surface water observations using optical–SAR sensor fusion and gap filling. We applied this method to data from the Copernicus Sentinel-1 and Landsat 8 satellite data from 2019 over six regions spanning different ecological and climatological conditions. We validated the resulting surface water maps using an independent, hand-labeled dataset and found an overall accuracy of 0.9025, with an accuracy range of 0.8656–0.9212 between the different regions. The validation showed an overall false alarm ratio (FAR) of 0.0631, a probability of detection (POD) of 0.8394, and a critical success index (CSI) of 0.8073, indicating that the method generally performs well at identifying water areas. However, it slightly underpredicts water areas with more false negatives. We found that fusing optical and SAR data for surface water mapping increased, on average, the number of observations for the regions and months validated in 2019 from 11.46 for optical and 55.35 for SAR to 64.90 using both, a 466% and 17% increase, respectively. The results show that the method can effectively fill in gaps in optical data caused by cloud cover and produce a dense time series of surface water maps. The method has the potential to improve the monitoring of surface water dynamics and support sustainable water management.