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A micrometeorological fog experiment was carried out in Budapest, Hungary during the winter half year of 2020–2021. The field observation involved (i) standard meteorological and radiosonde measurements; (ii) surface radiation balance and energy budget components, and (iii) ceilometer measurements. 23 fog events occurred during the whole campaign. Foggy events were categorized based on two different methods suggested by Tardif and Rasmussen (2007) and Lin et al. (2022). Using the Present Weather Detector and Visibility sensor (PWD12), duration of foggy periods are approximately shorter (~ 9%) compared to ceilometer measurements. The categorization of fog based on two different methods suggests that duration of radiation fogs is lower compared to that of cloud base lowering (CBL) fogs. The results of analysis of observed data about the longest fog event suggest that (i) it was a radiation fog that developed from the surface upwards with condition of a near neutral temperature profile. Near the surface the turbulent kinetic energy and turbulent momentum fluxes remained smaller than 0.4 m2 s–2 and 0.06 kg m–1 s–2, respectively. In the surface layer the vertical profile of the sensible heat flux was near constant (it changes with height ~ 10%), and during the evolution of the fog, its maximum value was smaller than 25 W m–2, (ii) the dissipation of the fog occurred due to increase of turbulence, (iii) longwave energy budget was close to zero during fog, and a significant increase of virtual potential temperature with height was observed before fog onset. The complete dataset gives an opportunity to quantify local effects, such as tracking the effect of strengthening of wind for modification of stability, surface layer profiles and visibility. Fog formation, development and dissipation are quantified based on the micrometeorological observations performed in suburb area of Budapest, providing a processing algorithm for investigating various fog events for synoptic analysis and for optimization of numerical model parameterizations. [ABSTRACT FROM AUTHOR]

Precipitation gauges used for observations in the 19th century are reconstructed and pairs of gauges are installed at two, climatologically different, regular weather observation sites (Norrköping and Katterjåkk). Norrköping is a quite well sheltered site with a low degree of frozen precipitation, while Katterjåkk is an open site with a high degree of frozen precipitation. One of the gauges at each site is equipped with a wind shield. Parallel observations are conducted from November 2016 through May 2021. Regular observations are also conducted manually with modern gauges and with automatic gauges at the sites. The wind shield effects (larger observed precipitation sums due to the inclusion of a wind shield) for the sheltered (Norrköping) and the open (Katterjåkk) sites are 7% and 16% for snow and 2% and 1% for rain, respectively. The modern gauges generally collect more precipitation than the historical shielded gauges, the difference is 0–8% for rain and almost up to 50% for snow. However, these differences can, in part, be ascribed to micrometeorologal conditions at the sites. The differences between observation methods are larger for snow and sleet than for rain. There are also larger differences in the open site than in the sheltered site. The most closely placed modern gauge relative to the historical gauges (automatic gauge in Norrköping, manual gauge in Katterjåkk) gives the most similar precipitation sums, suggesting that micrometeorology is more important than the observation method. The undercatch due to lacking wind shields in historical observations can probably not explain more than 20% of the increased observed precipitation in the late 19th and early 20th century. The question of potential influence on climatological precipitation series due to the transition from historical to modern observation methods remains unconcluded. [ABSTRACT FROM AUTHOR]

It has long been suspected that thermo-topographic flows, especially gravity currents, within vegetation canopies on complex terrain are one of the main reasons behind the failure to reconcile micrometeorological and biometric estimates of canopy-atmosphere exchange at many sites. However, the physical mechanisms governing the initiation and the scaling of these flows remain poorly understood. Here we present the results of a novel wind tunnel study that looks in detail at the flow within and above an open canopy in stably stratified conditions and investigates the physical mechanisms responsible for gravity currents within canopies. The wind tunnel simulations demonstrate that gravity currents are established through a complex balance of competing forces on the flow within the canopy. Three forcing terms act on the flow in the canopy as it passes over the hill. First is the hydrodynamic pressure gradient associated with the boundary layer flow aloft; second, a hydrostatic pressure gradient associated with the displacement of temperature and density surfaces by the hill, and finally a thermal wind term, where a streamwise pressure gradient is caused by changes in the depth of the temperature perturbations to the flow. The net balance of these forces is opposed by the canopy drag. Gravity currents, however, do not appear unless the turbulence, which supports the transport of momentum into the canopy, is also reduced. This suppression occurs preferentially deep within the canopy due to a Richardson number cut-off effect, which is directly linked to the different transport mechanisms of heat and momentum across the boundary layers on the canopy elements. The gravity current first appears at the ground surface, despite cooling profiles that are concentrated in the upper canopy. Once initiated, a gravity current can propagate substantial distances away from the triggering topography, driven by the thermal wind term. If shown to be robust these results have widespread implications for the micrometeorology, atmospheric boundary layer and numerical weather prediction communities. [ABSTRACT FROM AUTHOR]

With the increasing penetration of renewable energy resources, their variable, intermittent and unpredictable characteristics bring new challenges to the power system. These challenges require micro-meteorological data and techniques to provide more support for the power systems, including planning, dispatching, operation, and so on. This paper aims to provide readers with insights into the effects of micro-meteorology on power systems, as well as the actual improvement brought by micro-meteorology in some power system scenarios. This paper provides a review including the relevant micro-meteorological techniques such as observation, assimilation and numerical techniques, as well as artificial intelligence, presenting a relatively complete overview of the most recent and relevant micro-meteorology-related literature associated with power systems. The impact of micro-meteorology on power systems is analyzed in six different forms of power generation and three typical scenarios of different stages in the power system, as well as integrated energy systems and disaster prevention and reduction. Finally, a case study in China is provided. This case takes wind power prediction as an example in a power system to compare the performance when applying micro-meteorological data or not. The experimental results demonstrated that using the micro-meteorological reanalysis dataset with high spatial--temporal resolution for wind power prediction performed better, verifying the improvement of micro-meteorology to the power system to some extent. [ABSTRACT FROM AUTHOR]

Plant structures that enclose trapped air are morphologically and taxonomically diverse. They range from pubescence (trichomes) on various parts of plants to flowers, inflorescences, stems, culms (above-ground jointed stems of grasses), petioles, peduncles, scapes, fruits, bracts, leaves, galls, algal pneumatocysts, moss sporophytes, lichen podetia, and fungal fruiting bodies. Despite being familiar, such structures have not been studied systematically until recently when their complex thermodynamic functionality as microgreenhouses has been recognized. We propose the term “heliocaminiform” (Greco-Latin origin for “sun-room”) provides an umbrella term that describes form and function. Almost all the hollow structures we have examined have elevated internal temperatures of several degrees C above the surrounding air in sunshine, but those are abolished under cloud or at night. The potential importance for the additional heat is presumed to be in growth, maturation, reproduction, sexual function, and overall fitness of the plants. There seem to be no experimental studies on those effects even though they may help explain aspects of plants’ responses to climate change and to phenological mismatches with symbionts (mutualists and herbivores) as ecologically co-dependent partners. Our review and observations opens a remarkably new and hitherto surprisingly neglected avenue in botany which we hope others will explore.

Microclimate—proximal climatic variation at scales of metres and minutes—can exacerbate or mitigate the impacts of climate change on biodiversity. However, most microclimate studies are temperature centric, and do not consider meteorological factors such as sunshine, hail and snow. Meanwhile, remote cameras have become a primary tool to monitor wild plants and animals, even at micro‐scales, and deep learning tools rapidly convert images into ecological data. However, deep learning applications for wildlife imagery have focused exclusively on living subjects. Here, we identify an overlooked opportunity to extract latent, ecologically relevant meteorological information. We produce an annotated image dataset of micrometeorological conditions across 49 wildlife cameras in South Africa's Maloti‐Drakensberg and the Swiss Alps. We train ensemble deep learning models to classify conditions as overcast, sunshine, hail or snow. We achieve 91.7% accuracy on test cameras not seen during training. Furthermore, we show how effective accuracy is raised to 96% by disregarding 14.1% of classifications where ensemble member models did not reach a consensus. For two‐class weather classification (overcast vs. sunshine) in a novel location in Svalbard, Norway, we achieve 79.3% accuracy (93.9% consensus accuracy), outperforming a benchmark model from the computer vision literature (75.5% accuracy). Our model rapidly classifies sunshine, snow and hail in almost 2 million unlabelled images. Resulting micrometeorological data illustrated common seasonal patterns of summer hailstorms and autumn snowfalls across mountains in the northern and southern hemispheres. However, daily patterns of sunshine and shade diverged between sites, impacting daily temperature cycles. Crucially, we leverage micrometeorological data to demonstrate that (1) experimental warming using open‐top chambers shortens early snow events in autumn, and (2) image‐derived sunshine marginally outperforms sensor‐derived temperature when predicting bumblebee foraging. These methods generate novel micrometeorological variables in synchrony with biological recordings, enabling new insights from an increasingly global network of wildlife cameras. [ABSTRACT FROM AUTHOR]

In this study, the effect of winglets on improving the performance of type h darrieus wind turbines was investigated. The aim is to determine the most suitable winglet design and find out the magnitude of the increase in wind turbine performance. The method used is experimentation to find the RPM and torque used for calculate the TSR value and turbine power. From all the trial and error experiments, the type of blended winglet that best suited the characteristics of the VAWT. The experimental results show that the addition of blended winglet increases RPM of 13.6% in the 3-blade turbine and turbine it increases of 9% in the 4-blade turbine. The increase in average torque is 13.2% in a 3-blade turbine and 9.4% in a 4-blade turbine. The average increase in power coefficient is 11% in a 3-blade turbine and 9% in a 4-blade blade. In conclusion, the addition of blended winglets produces better torque and power compared to turbine models without winglets. [ABSTRACT FROM AUTHOR]

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It has long been suspected that thermo-topographic flows, especially gravity currents, within vegetation canopies on complex terrain are one of the main reasons behind the failure to reconcile micrometeorological and biometric estimates of canopy-atmosphere exchange at many sites. However, the physical mechanisms governing the initiation and the scaling of these flows remain poorly understood. Here we present the results of a novel wind tunnel study that looks in detail at the flow within and above an open canopy in stably stratified conditions and investigates the physical mechanisms responsible for gravity currents within canopies. The wind tunnel simulations demonstrate that gravity currents are established through a complex balance of competing forces on the flow within the canopy. Three forcing terms act on the flow in the canopy as it passes over the hill. First is the hydrodynamic pressure gradient associated with the boundary layer flow aloft; second, a hydrostatic pressure gradient associated with the displacement of temperature and density surfaces by the hill, and finally a thermal wind term, where a streamwise pressure gradient is caused by changes in the depth of the temperature perturbations to the flow. The net balance of these forces is opposed by the canopy drag. Gravity currents, however, do not appear unless the turbulence, which supports the transport of momentum into the canopy, is also reduced. This suppression occurs preferentially deep within the canopy due to a Richardson number cut-off effect, which is directly linked to the different transport mechanisms of heat and momentum across the boundary layers on the canopy elements. The gravity current first appears at the ground surface, despite cooling profiles that are concentrated in the upper canopy. Once initiated, a gravity current can propagate substantial distances away from the triggering topography, driven by the thermal wind term. If shown to be robust these results have widespread implications for the micrometeorology, atmospheric boundary layer and numerical weather prediction communities.

Despite recent advances in both coupled fire modeling and measurement techniques to sample the fire environment, the fire–atmosphere coupling mechanisms that lead to fast propagating wildfires remain poorly understood. This knowledge gap adversely affects fire management when wildland fires propagate unexpectedly rapidly and shift direction due to the fire impacts on local wind conditions. In this work, we utilized observational data from the FireFlux2 prescribed burn and numerical simulations performed with a coupled fire–atmosphere model WRF-SFIRE to assess the small-scale impacts of fire on local micrometeorology under moderate wind conditions (10–12 m/s). The FireFlux2 prescribed burn provided a comprehensive observational dataset with in situ meteorological observations as well as IR measurements of fire progression. To directly quantify the effects of fire–atmosphere interactions, two WRF-SFIRE simulations were executed. One simulation was run in a two-way coupled mode in which the heat and moisture fluxes emitted from the fire were injected into the atmosphere, and the other simulation was performed in a one-way coupled mode for which the atmosphere was not affected by the fire. The difference between these two simulations was used to analyze and quantify the fire impacts on the atmospheric circulation at different sections of the fire front. The fire-released heat fluxes resulted in vertical velocities as high as 10.8 m/s at the highest measurement level (20 m above ground level) gradually diminishing with height and dropping to 7.9 m/s at 5.77 m. The fire-induced horizontal winds indicated the strongest fire-induced flow at the lowest measurement levels (as high as 3.3 m/s) gradually decreasing to less than 1 m/s at 20 m above ground level. The analysis of the simulated flow indicates significant differences between the fire-induced circulation at the fire head and on the flanks. The fire-induced circulation was much stronger near the fire head than at the flanks, where the fire did not produce particularly strong cross-fire flow and did not significantly change the lateral fire progression. However, at the head of the fire the fire-induced winds blowing across the front were the strongest and significantly accelerated fire progression. The two-way coupled simulation including the fire-induced winds produced 36.2% faster fire propagation than the one-way coupled run, and more realistically represented the fire progression. [ABSTRACT FROM AUTHOR]

Anaerobic decomposition in manure storage contributes to hydrogen sulfide (H2S) and methane (CH4) emissions. Coincident emission measurements were made of these gases from a western free stall dairy manure storage basin over a two-month period (August and September) as manure filled the basin and dried to assess the similarity or differences in the emissions characteristics. Path-integrated CH4 concentrations were measured from sampled air using photoacoustic spectrometric technology. Half-hourly emissions were determined using a backward Lagrangian Stochastic method utilizing on-site turbulence measurements. The median daily CH4 emission for the basin was 3.5 mg CH4 m−2 s−1 (772 g d−1 hd−1). Aging of the manure over the 44 days of this study did not appear to influence the CH4 emissions. A high correlation between the CH4 and H2S emissions during the study period suggested that the production and transport of these two gases from the basin were influenced by the same factors. Emissions did not appear to be influenced by the above-ground environmental conditions (wind speed, turbulent mixing, air temperature, change in barometric pressure, or vapor pressure deficit) but were likely more a function of the bacterial population present and/or available substrate for bacterial decomposition. Similarity in the CH4 to H2S emission ratio during basin manure filling and drying down to that of a slurry storage in a midwestern US dairy suggested that the bacterial species involved in the decomposition of dairy manure slurry is similar regardless of climate. [ABSTRACT FROM AUTHOR]

The description of atmospheric turbulence on heterogeneous surfaces and more specifically during stable stratification conditions, remains nowadays a relevant and open issue in micrometeorology. To partially remedy this problem, we investigate in this study, the behaviour of turbulence above a heterogeneous cultivated surface during stable and unstable conditions. The analyses were realized according to seasons using almost seven years of eddy covariance measurements acquired at 4.95 m height. The results showed that the turbulence kinetic energy per unit mass was on average less than 0.5 m2 s−2 at night but increased during the day. It hits around local noon a peak value ~ 1.6 m2 s−2 on average. The peak value is relatively lower (~ 0.92 m2 s−2) during the wet season compared to other periods (1.6 m2 s−2). The average value of turbulence intensities are Iu = 0.44, Iv = 0.50 and Iw = 0.22 following u, v, w wind speed directions. During stable conditions, there are turbulent movements when the flux Richardson number is less than a critical value estimated approximately to 0.17. The flux-variance similarity functions that characterize the behaviour of turbulence are seasonally dependent, especially under stable conditions. However, each of these functions obey the Monin–Obukhov Similarity Theory whatever the stratification except those of temperature under near-neutral conditions. The results obtained indicate that the atmospheric turbulence is relative to the type of ecosystem and the height of measurement. This process is led by aerodynamic parameters and wind speed. [ABSTRACT FROM AUTHOR]

Micrometeorology plays a pivotal role in advancing our understanding of agricultural systems by unraveling intricate interactions between climate dynamics and crop performance. This article presents a comprehensive analysis of the literature published on crop micrometeorology and indexed in Scopus database from 2000 to 2023. The query yielded only 146 documents, which were subsequently subjected to analysis using an R-based bibliometric tool to assess annual scientific production trend, document types, citation, and keyword analysis. The results revealed zero growth rate of the topic with an average 47.36 citations and total citation of 6536 in the analysis period. USA dominates the number of publications (28.1%), followed by China (17.8%), Japan (11.6%) and Australia (8.9%). India stood at 10th position with only 8 documents contributing 5.5% of the total publications included in the study. The key domains of current research in the realm of crop micrometeorology identified through bibliometric analysis were evapotranspiration, energy balance, gas emissions, and modelling based studies, which are discussed in details in the article. As climate change and global food security becomes more critical, this analysis highlights the role of micrometeorological works within the realm of climate change and crop studies.

The objective of this work is to assess the wind resources of the east coast of Maranhão, Brazil. Wind profilers were combined with micrometeorological towers and atmospheric reanalysis to investigate micro- and mesoscale aspects of wind variability. Field campaigns recorded winds in the dry and wet seasons, under the influence of the Intertropical Convergence Zone. The dry season was characterized by strong winds (8 to 12 m s − 1 ) from the northeast. Surface heat fluxes were generally positive (250 to 320 W m − 2 ) at midday and negative (−10 to −20 W m − 2 ) during the night. Convective profiles predominated near the beach, with strongly stable conditions rarely occurring before sunrise. Further inland, convective to strongly convective profiles occurred during the day, and neutral to strongly stable profiles at night. Wind speeds decreased during the rainy season (4 to 8 m s − 1 ), with increasingly easterly and southeasterly components. Cloud cover and precipitation reduced midday heat fluxes (77 W m − 2 ). Profiles were convective during midday and stable to strongly stable at night. Terrain roughness increased with distance from the ocean ranging from smooth surfaces ( z o = 0.95 mm) and rough pastures ( z o = 15.33 mm) to crops and bushes ( z o = 52.68 mm), and trees and small buildings ( z o = 246.46 mm) farther inland. Seasonal variations of the mean flow and sea and land breezes produced distinct diurnal patterns of wind speeds. The strongest (weakest) breeze amplitudes were observed in the dry (rainy) period. Daily changes in heat fluxes and fetch over land controlled the characteristics of wind profiles. During sea breezes, winds approached the coast at right angles, resulting in shorter fetches over land that maintained or enhanced oceanic convective conditions. During land breezes, winds blew from the mainland or with acute angles against the coastline, resulting in large fetches with nighttime surface cooling, generating strongly stable profiles. Coastal observations demonstrated that with increasing monopiles from 100 to 130 m it is possible to obtain similar capacity factors of beachfront turbines. [ABSTRACT FROM AUTHOR]

Potential evapotranspiration (PET) is a particularly important parameter for understanding water interactions and balance in ecosystems, while it is also crucial for assessing vegetation water requirements. The accurate estimation of PET is typically data demanding, while specific climatic, geographical and local factors may further complicate this task. Especially in city environments, where built-up structures may highly influence the micrometeorological conditions and urban green sites may occupy limited spaces, the selection of proper PET estimation approaches is critical, considering also data availability issues. In this study, a wide variety of empirical PET methods were evaluated against the FAO56 Penman–Monteith benchmark method in the environment of two Mediterranean urban green sites in Greece, aiming to investigate their accuracy and suitability under specific local conditions. The methods under evaluation cover all the range of empirical PET estimations: namely, mass transfer-based, temperature-based, radiation-based, and combination approaches, including 112 methods. Furthermore, 15 locally calibrated and adjusted models have been developed based on the general forms of the mass transfer, temperature, and radiation equations, improving the performance of the original models for local application. Among the 127 (112 original and 15 adjusted) evaluated methods, the radiation-based methods and adjusted models performed overall better than the temperature-based and the mass transfer methods, whereas the data-demanding combination methods received the highest ranking scores. The adjusted models seem to give accurate PET estimates for local use, while they might be applied in sites with similar conditions after proper validation. [ABSTRACT FROM AUTHOR]

The vegetation canopy's height and characteristics directly affect the turbulence that controls the exchange of mass and energy between the vegetation and the surrounding atmosphere. Turbulence also controls the momentum transfer towards the mass-carrying plant canopy and the accompanying atmospheric properties so that vegetation can contribute to pollutant deposition. This study aims to estimate the canopy capacity of oil palms to absorb pollutants based on their momentum transfer, the influence of atmospheric stability dynamics, and rainy and dry periods upon absorbed pollutants from PTPN VI in Jambi province for the period of January to December 2015 used micrometeorological observation data. The results showed that the dry deposition capacity value at the stable, neutral, and unstable atmospheric conditions were 2.06 x 10-3 kg/m², 3.50 x 10-3 kg/m², and 4.35 x 10-3 kg/m², respectively. The stable or unstable conditions affected the momentum transfer through decreasing or increasing turbulence. In stable conditions, the cooling of the atmosphere impacts the turbulence to be restrained. The result also showed that the dry deposition capacity during the dry and rainy periods were 4.5 x 10-3 kg/m² and 2.9 x 10-3 kg/m², respectively. Further, atmospheric conditions tended to be unstable during the dry period, while the rainy period tended to be stable. This research showed that the momentum transfer method can estimate gas type pollutants by vegetation. [ABSTRACT FROM AUTHOR]

Ammonia (NH3) is a naturally occurring, highly reactive and soluble alkaline trace gas, originating from both natural and anthropogenic sources. It is present throughout the biosphere, yet plays a complicated role in atmospheric acid–base reactions resulting in the formation of inorganic secondary inorganic aerosols (SIAs). While the general mechanisms are recognised, factors controlling the reactions leading to SIA formation are less explored. This review summarises the current knowledge of NH3 sources, emission and deposition processes and atmospheric reactions leading to the formation of SIA. Brief summaries of NH3 and SIA long-range transport and trans-boundary pollution, a discussion of precursor species to SIAs (other than NH3), abiotic and biotic controls and state-of-the-art methods of measurement and modelling of pollutants are also included. In Ireland, NH3 concentrations remained below National and European Union limits, until 2016 when a rise in emissions was seen due to agricultural expansion. However, due to a lack of continuous monitoring, source and receptor relationships are difficult to establish, including the appointment of precursor gases and aerosols to source regions and industries. Additionally, the lack of continuous monitoring leads to over- and underestimations of precursor gases present, resulting in inaccuracies of the estimated importance of NH3 as a precursor gas for SIA. These gaps in data can hinder the accuracy and precision of forecasting models. Deposition measurements and the modelling of NH3 present another challenge. Direct source measurements are required for the parameterization of bi-directional fluxes; however, high-quality data inputs can be limited by local micrometeorological conditions, or the types of instrumentation used. Long-term measurements remain challenging for both aerosols and precursor gases over larger areas or arduous terrains. [ABSTRACT FROM AUTHOR]

Assessing nutrient critical load exceedances requires complete and accurate atmospheric deposition budgets for reactive nitrogen (N r). The exceedance is the total amount of N r deposited to the ecosystem in excess of the critical load, which is the amount of N r input below which harmful effects do not occur. Total deposition includes all forms of N r (i.e., organic and inorganic) deposited to the ecosystem by wet and dry pathways. Here we present results from the Southern Appalachian Nitrogen Deposition Study (SANDS), in which a combination of measurements and field-scale modeling was used to develop a complete annual N r deposition budget for a deciduous forest at the Coweeta Hydrologic Laboratory. Wet deposition of ammonium, nitrate, nitrite, and bulk organic N were measured directly. The dry deposited N r fraction was estimated using a bidirectional resistance-based model driven with speciated measurements of N r air concentrations (e.g., ammonia, ammonium aerosol, nitric acid, nitrate aerosol, bulk organic N in aerosol, total alkyl nitrates, and total peroxy nitrates), micrometeorology, canopy structure, and biogeochemistry. Total annual deposition was ∼ 6.7 kg N ha -1 yr -1 , which is on the upper end of N r critical load estimates recently developed for similar ecosystems in the nearby Great Smoky Mountains National Park. Of the total (wet + dry) budget, 51.1 % was contributed by reduced forms of N r (NH x = ammonia + ammonium), with oxidized and organic forms contributing ∼ 41.3 % and 7.6 %, respectively. Our results indicate that reductions in NH x deposition would be needed to achieve the lowest estimates (∼ 3.0 kg N ha -1 yr -1) of N r critical loads in southern Appalachian forests. [ABSTRACT FROM AUTHOR]

The simulation performance of the land surface model Community Land Model 5.0 (CLM5.0) is tested by using the eddy correlation system and micrometeorological tower observational data at the Maqu observation field in 2016. The results show that the CLM5.0 model has a good simulation effect on the soil temperature and can well reflect the seasonal variation characteristics of soil temperature. In addition, the model can well simulate the seasonal variation in shallow soil moisture (5 cm and 10 cm). However, the deviations between the simulated and observed values are large. CLM5.0 cannot simulate the water holding capacity of shallow soil well, resulting in its underestimation. The simulation performance of the upward longwave radiation and net radiation is substantially better than that of the upward shortwave radiation due to the change in surface albedo caused by precipitation from March to July. CLM5.0 can also well reproduce the variation trend of the latent heat flux and 5 cm soil heat flux (heat exchange of soil at 5 cm). When the leaf area index (LAI) and Medlyn slope values are changed to 10%, 20%, and 50% of the default values, the simulation effects of soil moisture at depths of 5 cm and 10 cm are significantly improved, and the best simulation effects are achieved at 0.5 times the default values. This result indicates that lower LAI and Medlyn slope values are more suitable for simulating shallow soil moisture. [ABSTRACT FROM AUTHOR]

The general objective of this research was to propose a new fire risk index, specifically the Fire Risk Atlantic Forest (FIAF) index in Itatiaia National Park (PNI). The data were collected from two levels (2 and 10 m) of a micrometeorological tower, with a time series on an hourly scale, daily from 2018 to 2021. Two multiple regression models were generated for the two collection levels (FIAF 2 and 10 m) and, based on the statistical criteria and the choice of the best model, a future simulation was generated using the scenario SSP 4.5 for 2022 to 2050. The correlation matrix between the data from the FIAF and fire foci models was also analyzed. The FIAF model was compared with the traditional models already used in Brazil, such as the Angström indices, Monte Alegre Formula (FMA), and the improved Monte Alegre Formula (FMA+) models. The results showed that the FIAF model at 10 m overestimated the results observed mainly during the dry season. The FIAF 2 m model presented the highest correlation with a fire foci value greater than 0.74. In the future simulation, the years that presented the highest extreme risks were: 2025, 2035, 2041, and 2049. Thus, it is possible to state that the FIAF model at the 2 m level was the best model for predicting the degree of fire risk in the PNI. [ABSTRACT FROM AUTHOR]

Measurements of atmosphere-surface exchange are largely limited by the availability of fast-response gas analyzers; this limitation hampers our understanding of the role of terrestrial ecosystems in atmospheric chemistry and global change. Current micrometeorological methods, compatible with slow-response gas analyzers, are difficult to implement, or rely on empirical parameters that introduce large systematic errors. Here, we develop a new micrometeorological method, optimized for slow-response gas analyzers, that directly measures exchange rates of different atmospheric constituents, with minimal requirements. The new method requires only the sampling of air at a constant rate and directing it into one of two reservoirs, depending on the direction of the vertical wind velocity. An integral component of the new technique is an error diffusion algorithm that minimizes the biases in the measured fluxes and achieves direct flux estimates. We demonstrate that the new method provides an unbiased estimate of the flux, with accuracy within 0.1% of the reference eddy covariance flux, and importantly, allows for significant enhancements in the signal-to-noise ratio of measured scalars without compromising accuracy. Our new method provides a simple and reliable way to address complex environmental questions and offers a promising avenue for advancing our understanding of ecological systems and atmospheric chemistry. • New method for atmospheric exchange measurements with slow-response gas analyzers. • Minimal implementation requirements similar to relaxed eddy accumulation. • Error diffusion algorithm developed to minimize flux biases to less than 0.1%. • Enables increasing the signal-to-noise ratio without losing accuracy. [ABSTRACT FROM AUTHOR]

With large tracts of Tropical Dry Forests (TDF) in the Americas previously deforested, many places are currently undergoing secondary ecological succession. These processes vary in time and space, creating a landscape with forests of different ages or successional stages. These secondary forests need moreneed more understanding about how their ecosystem functionality is restored and recovering along the succession path. In particular, it is poorly understood how different successional stages moderate extremes of Essential Climatic Variables (ECV) such as temperature, relative humidity, soil moisture, and the fraction of Absorbed Photosynthetic Active Radiation (f APAR). This paper, therefore, studies the linkages between high temporal resolution tower-based optical canopy phenology time series and seasonal changes in local ECV conditions between early (10–12 years) and late (50+ years) successional stage TDF in southeastern Brazil. We compare diurnal and seasonal patterns of understory ECVs between early/late plots and investigate the canopy's Climate Moderating Capacity (CMC). Our data indicate at least 100 mm of precipitation within two weeks is necessary to initiate leaf flushing in this TDF. We also find that soil moisture and daytime air humidity strongly correlate (R2 > 0.75) with seasonal patterns in canopy vegetation greenness indices and f APAR with a cross-correlation time lag peak of 12–15 days. Our results suggest that the late stage is more effective at cooling (−1.4 ± 0.6 °C vs −0.8 ± 0.6 °C) and reducing daytime evaporation (−0.41 ± 0.2 kPa vs −0.18 ± 0.12 °C) in the understory during the growing season than the early stage. Results suggest that the CMC varies with seasonal canopy leaf area dynamics and with heat and moisture scales, becoming significantly stronger when temperatures and vapour pressure deficits were highest, and correlated strongly with canopy f APAR dynamics (R2 = 0.82). These findings demonstrate that TDFs can effectively regain microclimatic buffering capacity. • The study focuses on how early and late successional stages of TDFs restore ecosystem functionality. • Late succession TDFs are more efficient in cooling and reducing daytime evapotranspiration than early succession TDFs. • There is a strong correlation between canopy vegetation greenness indices and seasonal ECVs patterns. • The microclimatic buffering capacity of TDFs is a complex interplay of seasonal leaf area dynamics and climatic conditions. [ABSTRACT FROM AUTHOR]

Due to climate change, urban populations will be affected by worsening heat stress. The use of blue–green infrastructure can be an effective countermeasure for urban planners. In this study, the ENVI-met modelling system is used to investigate the impacts of different heat adaptation strategies, such as additional urban trees, irrigation policies, and the use of high reflective surface materials. However, under certain local conditions, these measures can have conflicting effects, e.g., trees can provide shadow but also reduce the cooling ventilation. To address such conflicts, we developed an online tool visualising urban climate simulation data and applying a new decomposition algorithm that translates the biophysical processes (i.e., radiation, ventilation, evapotranspiration, and heat storage) into surface temperature changes during heat wave events. This approach allows us to (1) identify factors responsible for heat, (2) comparatively evaluate heat mitigation of different land development scenarios, and (3) find trade-offs for conflicting adaptation measures. This online tool can support the decision-making of local stakeholders. [ABSTRACT FROM AUTHOR]

The study was carried out with objectives to ascertain the micrometeorology, mixing height, and air pollutants simulation in a Western Ghats valley of India. This valley area had number of industries and a gas based combined cycle power plant (CCPP) of 4080 MW capacity is also proposed. The wind speed and directions, ambient air temperature, and humidity were assessed with the help of a weather monitoring station. The mixing height was estimated with the help of minisonde system. The air pollutants simulation was assessed for complex terrain (valley) with baseline data collection and impact assessment by Gaussian Dispersion Model based Industrial Source Complex Version 3. During night time calm condition prevails (99%), whereas; during 24 hours wind from north direction was the prevailing one followed by north-west. Diurnal variation in mixing height was recorded with maximum (903 m) during afternoon (2.30 pm). In case of sulphur dioxide (SO2) release from the proposed CCPP the 24-hourly ground level concentration was 468 µg/m³ whereas, for oxides of nitrogen (NOX) it was 281 µg/m³. Due to the prevailing micrometeorological and mixing height conditions the pollutants from the proposed CCPP will get build up and may result into air pollution episodes and photochemical smog formation. To prevent the build-up of air pollutants increasing the stack height (>250 m) of CCPP and reducing the NOx concentration in flue gas to 25 ppm, limitation/restriction of total design capacity of proposed project, and optimize the different combinations of these options may be attempted. [ABSTRACT FROM AUTHOR]

Estimates of net primary (NPP) and ecosystem production (NEP) are needed for tropical savanna, which is structurally diverse but understudied compared to tropical rainforest. We used eddy covariance and inventory methods to estimate carbon (C) fluxes for an upland mixed grassland and a seasonally flooded forest to determine the correspondence between these methods and assess the contribution of C cycling components to the total NPP. Both techniques provided similar estimates of net ecosystem CO2 exchange (−3.0 ‒ 2.3 MgC ha−1 y−1 for eddy covariance vs. −2.0 ‒ 4.3 MgC ha−1 y−1 for inventory), gross primary production (7.5–16.3 MgC ha−1 y−1 for eddy covariance vs. 8.7–18.4 MgC ha−1 y−1 for inventory), and total NPP (0.9–7.5 MgC ha−1 y−1 for eddy covariance vs. 2.0–9.5 MgC ha−1 y−1 for inventory). Belowground NPP accounted for 49%–53% of the total NPP for both ecosystems, followed by aboveground litter (26%–27%) and wood (16%–17%) production. Increases in water availability increased the potential for C storage, but the mechanism was different in the savanna types. Compared to other savanna ecosystems, the mixed grassland had a lower productivity and C use efficiency (CUE = NPP/GPP = 0.28), while the Cerrado forest had a high CUE (0.58) and similar C flux rates to other tropical savanna forests. The agreement in the C cycle estimates derived from the eddy covariance and inventory methods increases our confidence in the productivity estimates for these tropical savanna ecosystems. Plain Language Summary: Estimates of net primary and ecosystem production are needed for tropical savannas, which are highly diverse but understudied compared to tropical forests. Several methods have been used to measure primary and ecosystem production; however, these approaches have errors and uncertainties. We used available methods to estimate the productivity of a grass‐dominated savanna in the southern Amazon Basin and a seasonally flooded forest in the northern Pantanal to assess the correspondence in the productivity estimated from these methods and evaluate the contribution of above and belowground processes to the overall ecosystem productivity. Productivity estimates derived from the different techniques were similar. Belowground processes accounted for 49%–53% of the productivity followed by leaf (26%–27%) and wood (16%–17%) production. Increases in water availability increased the productivity for both savanna types, but for different reasons. An increase in soil moisture caused an increase productivity in the mixed grassland but a decline in carbon losses from the seasonally flooded forest. Compared to other savanna ecosystems, the mixed grassland had lower productivity while the forest had high productivity. While our measurements are spatially and temporally limited, the broad agreement in the different methods increases our confidence in the productivity estimates for these tropical savanna ecosystems. Key Points: Estimates of C cycling from inventory and eddy covariance methods were similar for two floristically different tropical savannas of BrazilBelowground NPP was 49%–53% of the total NPP for both ecosystems, followed by aboveground litter (26%–27%) and wood (16%–17%) productionThe grass dominated savanna had a low C use efficiency (CUE = NPP/GPP = 0.28) while the Cerrado forest had a CUE = 0.58 [ABSTRACT FROM AUTHOR]

Potential evapotranspiration (PET) is a particularly important parameter for understanding water interactions and balance in ecosystems, while it is also crucial for assessing vegetation water requirements. The accurate estimation of PET is typically data demanding, while specific climatic, geographical and local factors may further complicate this task. Especially in city environments, where built-up structures may highly influence the micrometeorological conditions and urban green sites may occupy limited spaces, the selection of proper PET estimation approaches is critical, considering also data availability issues. In this study, a wide variety of empirical PET methods were evaluated against the FAO56 Penman–Monteith benchmark method in the environment of two Mediterranean urban green sites in Greece, aiming to investigate their accuracy and suitability under specific local conditions. The methods under evaluation cover all the range of empirical PET estimations: namely, mass transfer-based, temperature-based, radiation-based, and combination approaches, including 112 methods. Furthermore, 15 locally calibrated and adjusted models have been developed based on the general forms of the mass transfer, temperature, and radiation equations, improving the performance of the original models for local application. Among the 127 (112 original and 15 adjusted) evaluated methods, the radiation-based methods and adjusted models performed overall better than the temperature-based and the mass transfer methods, whereas the data-demanding combination methods received the highest ranking scores. The adjusted models seem to give accurate PET estimates for local use, while they might be applied in sites with similar conditions after proper validation.

The objective of this work is to assess the wind resources of the east coast of Maranhão, Brazil. Wind profilers were combined with micrometeorological towers and atmospheric reanalysis to investigate micro- and mesoscale aspects of wind variability. Field campaigns recorded winds in the dry and wet seasons, under the influence of the Intertropical Convergence Zone. The dry season was characterized by strong winds (8 to 12 m s−1) from the northeast. Surface heat fluxes were generally positive (250 to 320 W m−2) at midday and negative (−10 to −20 W m−2) during the night. Convective profiles predominated near the beach, with strongly stable conditions rarely occurring before sunrise. Further inland, convective to strongly convective profiles occurred during the day, and neutral to strongly stable profiles at night. Wind speeds decreased during the rainy season (4 to 8 m s−1), with increasingly easterly and southeasterly components. Cloud cover and precipitation reduced midday heat fluxes (77 W m−2). Profiles were convective during midday and stable to strongly stable at night. Terrain roughness increased with distance from the ocean ranging from smooth surfaces (zo = 0.95 mm) and rough pastures (zo = 15.33 mm) to crops and bushes (zo = 52.68 mm), and trees and small buildings (zo = 246.46 mm) farther inland. Seasonal variations of the mean flow and sea and land breezes produced distinct diurnal patterns of wind speeds. The strongest (weakest) breeze amplitudes were observed in the dry (rainy) period. Daily changes in heat fluxes and fetch over land controlled the characteristics of wind profiles. During sea breezes, winds approached the coast at right angles, resulting in shorter fetches over land that maintained or enhanced oceanic convective conditions. During land breezes, winds blew from the mainland or with acute angles against the coastline, resulting in large fetches with nighttime surface cooling, generating strongly stable profiles. Coastal observations demonstrated that with increasing monopiles from 100 to 130 m it is possible to obtain similar capacity factors of beachfront turbines.

This paper presents enhancements to, and the demonstration of, the General Urban area Microclimate Predictions tool (GUMP), which is designed to provide hyper-local weather predictions by combining machine-learning (ML) models and computational fluid dynamic (CFD) simulations. For the further development and demonstration of GUMP, the Embry–Riddle Aeronautical University (ERAU) campus was used as a test environment. Local weather sensors provided data to train ML models, and CFD models of urban- and suburban-like areas of ERAU’s campus were created and iterated through with a wide assortment of inlet wind speed and direction combinations. ML weather sensor predictions were combined with best-fit CFD models from a database of CFD flow fields, providing flight operational areas with a fully expressed wind flow field. This field defined a risk map for uncrewed aircraft operators based on flight plans and individual flight performance metrics. The potential applications of GUMP are significant due to the immediate availability of weather predictions and its ability to easily extend to arbitrary urban and suburban locations.

This research examines the persistence of a pandemic in urban environments subjected to intensive densification processes, applying chaotic analysis tools to hourly time series constructed by relating accumulated patients with meteorological and pollutant variables (measured at ground level). To investigate this objective, seven communes of the metropolitan region of Santiago de Chile that present intensive urbanization processes that affect urban micrometeorology, favoring the concentration of pollutants, were considered. Quotients were constructed between the number of hourly patients with SARS-CoV-2 that accumulated in each commune over a period of two years and the hourly variables of urban micrometeorology (temperature, magnitude of wind speed, relative humidity) and pollutant concentration (tropospheric ozone, particulate material of 2.5 and 10 μm) constituting a new family of time series. Chaos theory was applied to these new time series, obtaining the chaotic parameters Lyapunov coefficient, correlation entropy, Lempel–Ziv complexity, Hurst coefficient and the fractal dimension in each measurement commune. The results showed that the accumulated patients (2020–2022), of the order of 400,000, belonged to the five communes (with a built area of approximately 300,000 m2 in recent years) that had the highest urban densification, which affected urban meteorology, favored the concentration of pollutants and made the SARS-CoV-2 pandemic more persistent. The "ideal" density of built housing should balance a pandemic and nullify its expansion. [ABSTRACT FROM AUTHOR]

Urban-scale Numerical Weather Prediction (NWP) systems will be important tools for decision-making in and around large cities in a changing climate exposed to more extreme weather events. Such a state-of-the-art real-time system down to 250-m grid spacing was implemented in the context of the Toronto 2015 Panamerican games, Canada (PanAm). Combined with the Global Environmental Multiscale (GEM) model, attention was brought to the representation of the detailed urban landscape, and to the inclusion of sub-daily variation of the Great Lakes surface temperature. Results show a refined representation of the urban coastal environment micro-meteorology with a strong anisotropy of the urban heat island reaching about 2 °C on average for the summer season, coastal upwelling, and mesoscale features such as cumulus clouds and lake-breeze flow. Objective evaluation at the surface with a dense observational network reveals an overall good performance of the system and a clear improvement in comparison to reference forecasts at 2.5-km grid spacing in particular for standard deviation errors in urban areas up to 0.3 °C for temperature and dew point temperature, and up to 0.5 m s − 1 for the wind speed, as well as for precipitation with an increased Equitable Threat Score (ETS) by up to 0.3 for the evening accumulation. The study provides confidence in the capacity of the new system to improve weather forecasts to be delivered to urban dwellers although further investigation of the initialization methods in urban areas is needed. [ABSTRACT FROM AUTHOR]

Assessing nutrient critical load exceedances requires complete and accurate atmospheric deposition budgets for reactive nitrogen (Nr). The exceedance is the total amount of Nr deposited to the ecosystem in excess of the critical load, which is the amount of Nr input below which harmful effects do not occur. Total deposition includes all forms of Nr (i.e., organic and inorganic) deposited to the ecosystem by wet and dry pathways. Here we present results from the Southern Appalachian Nitrogen Deposition Study (SANDS), in which a combination of measurements and fieldscale modeling were used to develop a complete annual Nr deposition budget for a deciduous forest at the Coweeta Hydrologic Laboratory. Wet deposition of ammonium, nitrate, nitrite, and bulk organic N were measured directly. The dry deposited Nr fraction was estimated using a bidirectional resistance-based model driven with speciated measurements of Nr air concentrations (e.g., ammonia, ammonium aerosol, nitric acid, nitrate aerosol, bulk organic N in aerosol, total alkyl nitrates, and total peroxy nitrates), micrometeorology, canopy structure, and biogeochemistry. Total annual deposition was  6.6 kg N ha-1 yr-1, which is on the upper end of Nr critical load estimates recently developed for similar ecosystems in nearby Great Smoky Mountains National Park. Of the total (wet + dry) budget, 50.7% was contributed by reduced forms of Nr (NHx = ammonia + ammonium), with oxidized and organic forms contributing  41.6% and 7.7%, respectively. Our results indicate that reductions in NHx deposition would be needed to achieve the lowest estimates ( 3.0 kg N ha-1 yr-1) of Nr critical loads in southern Appalachian forests. [ABSTRACT FROM AUTHOR]

The high quality and efficient production of greenhouse vegetation depend on micrometeorology environmental adjusting such as system warming and illumination supplement. In order to improve the quantity, quality, and efficiency of greenhouse vegetation, it is necessary to figure out the relationship between the crop growth conditions and environmental meteorological factors, which could give constructive suggestions for precise control of the greenhouse environment and reduce the running costs. The parameters from the color information of the plant canopy reflect the internal physiological conditions, thus, the RGB model has been widely used in the color analysis of digital pictures of leaves. We take photographs of Begonia Fimbristipula Hance (BFH) growing in the greenhouse at a fixed time every day and measure the meteorological factors. The results showed that the color scale for the single leaf, single plant, and the populated canopy of the BFH photographs all have skewed cumulative distribution histograms. The color gradation skewness-distribution (CGSD) parameters of the RGB model were increased from 4 to 20 after the skewness analysis, which greatly expanded the canopy leaf color information and could simultaneously describe the depth and distribution characteristics of the canopy color. The 20 CGSD parameters were sensitive to the micrometeorology factors, especially to the radiation and temperature accumulation. The multiple regression models of mean, median, mode, and kurtosis parameters to microclimate factors were established, and the spatial models of skewness parameters were optimized. The models can well explain the response of canopy color to microclimate factors and can be used to monitor the variation of plant canopy color under different micrometeorology. [ABSTRACT FROM AUTHOR]

Simple Summary: Greenhouse gases (GHG) are the major responsible drivers for global warming and climate change. Methane (CH4) is deemed the second most important GHG emitted from anthropogenic sources in terms of global warming potential (GWP) and quantity. Ruminants contribute to approximately one-fourth of all agricultural anthropogenic sources of CH4 emissions. As such, ample time and resources were committed to developing strategies to reduce CH4 emission from ruminants and its negative impacts on the environment. This has led to the development of several techniques for measuring and estimating CH4 emissions from ruminants. This review summarizes state-of-the-art and futuristic technologies for measuring and estimating CH4 emissions from ruminants, and their strengths and limitations, for easy understanding. This review aims to elucidate the contemporary methods of measuring and estimating methane (CH4) emissions from ruminants. Six categories of methods for measuring and estimating CH4 emissions from ruminants are discussed. The widely used methods in most CH4 abatement experiments comprise the gold standard respiration chamber, in vitro incubation, and the sulfur hexafluoride (SF6) techniques. In the spot sampling methods, the paper discusses the sniffer method, the GreenFeed system, the face mask method, and the portable accumulation chamber. The spot sampling relies on the measurement of short-term breath data adequately on spot. The mathematical modeling methods focus on predicting CH4 emissions from ruminants without undertaking extensive and costly experiments. For instance, the Intergovernmental Panel on Climate Change (IPCC) provides default values for regional emission factors and other parameters using three levels of estimation (Tier 1, 2 and 3 levels), with Tier 1 and Tier 3 being the simplest and most complex methods, respectively. The laser technologies include the open-path laser technique and the laser CH4 detector. They use the laser CH4 detector and wireless sensor networks to measure CH4 flux. The micrometeorological methods rely on measurements of meteorological data in line with CH4 concentration. The last category of methods for measuring and estimating CH4 emissions in this paper is the emerging technologies. They include the blood CH4 concentration tracer, infrared thermography, intraruminal telemetry, the eddy covariance (EC) technique, carbon dioxide as a tracer gas, and polytunnel. The emerging technologies are essential for the future development of effective quantification of CH4 emissions from ruminants. In general, adequate knowledge of CH4 emission measurement methods is important for planning, implementing, interpreting, and comparing experimental results. [ABSTRACT FROM AUTHOR]

The RHAPS (Redox-Activity And Health-Effects Of Atmospheric Primary And Secondary Aerosol) project was launched in 2019 with the major objective of identifying specific properties of the fine atmospheric aerosol from combustion sources that are responsible for toxicological effects and can be used as new metrics for health-related outdoor pollution studies. In this paper, we present the overall methodology of RHAPS and introduce the phenomenology and the first data observed. A comprehensive physico-chemical aerosol characterization has been achieved by means of high-time resolution measurements (e.g., number size distributions, refractory chemical components, elemental composition) and low-time resolution analyses (e.g., oxidative potential, toxicological assays, chemical composition). Preliminary results indicate that, at the real atmospheric conditions observed (i.e., daily PM1 from less than 4 to more than 50 μg m−3), high/low mass concentrations of PM1, as well as black carbon (BC) and water soluble Oxidative Potential (WSOP,) do not necessarily translate into high/low toxicity. Notably, these findings were observed during a variety of atmospheric conditions and aerosol properties and with different toxicological assessments. Findings suggest a higher complexity in the relations observed between atmospheric aerosol and toxicological endpoints that go beyond the currently used PM1 metrics. Finally, we provide an outlook to companion papers where data will be analyzed in more detail, with the focus on source apportionment of PM1 and the role of source emissions on aerosol toxicity, the OP as a predictive variable for PM1 toxicity, and the related role of SOA possessing redox-active capacity, exposure-response relationships for PM1, and air quality models to forecast PM1 toxicity. [ABSTRACT FROM AUTHOR]

• The physical basis of dew formation in canopies is theoretically summarized. • The critical relative humidity for dew formation depends on effective radiation. • Condensation rate largely varies with relative humidity and effective radiation. • Condensation rate also depends on air temperature and exchange velocity of canopy. • Two physical indices for assessing leaf wetness duration and amount are proposed. Dew formation on leaves plays an important role in plant growth and water use, but it also contributes to the development of a variety of plant diseases. However, the quantitative relationship between dew formation in plant canopies and meteorological conditions has not been fully elucidated. In the present study, a one-layer energy-balance model (1L-model) of a plant canopy was developed to systematically investigate this relationship, obtaining the following results: (1) Dew formation (condensation rate) on leaves is highly dependent on four parameters: effective radiation, relative humidity, air temperature, and exchange velocity (k L) of the plant canopy. (2) Dew formation occurs when relative humidity (rh) exceeds the critical value (rh cr), wherein rh cr decreases with a decrease in effective radiation and is lower at lower air temperatures. (3) Under conditions where rh > rh cr , the condensation rate reaches a maximum at a specific exchange velocity; however, condensation does not occur when k L is greater than the critical value. (4) The maximum condensation rate increases with decreasing effective radiation, but rapidly decreases with decreasing relative humidity, and increases with increasing air temperature under humid conditions. Given these theoretical considerations, we proposed two physical indices (reference dew amount, W 0, and potential dew amount, W p) calculated from meteorological conditions using the 1L-model. Here, W p is the maximum dew amount for given meteorological conditions, excluding wind speed. The efficacy of W 0 and W p in assessing leaf wetness duration (LWD) and dew amount in plant canopies was confirmed through actual measurements in a rice paddy and numerical simulations using a more comprehensive multilayer energy-balance model. This study contributes to a better understanding of the nature of dew formation on plants and improves the accuracy of LWD and dew amount estimation in plant canopies for the prevention of various plant diseases. [Display omitted] [ABSTRACT FROM AUTHOR]

• New instrumentation measured N 2 O fluxes using 88 % to 97 % less power. • N 2 O fluxes measured via low-power flux-gradient compared well against eddy-covariance. • Results verified the accuracy of the FG method and new instrumentation. • The FG method captured more emissions during rain and freeze-thaw periods than EC. • The low-power FG system expands opportunities for remote N 2 O emission measurement. Nitrous oxide (N 2 O) emissions from agricultural soils occur as pulses presenting a challenge for assessing mitigation practices. Since the timing and magnitude of pulses is dependent on soil and climatic conditions, side-by-side comparisons are needed. The flux gradient (FG) and eddy covariance (EC) methods both capture spatially and temporally variable N 2 O emissions, but FG requirements are more flexible for operation using low power and/or in a multi-plot configuration with one gas analyzer. Instrumentation for N 2 O flux measurement requires strong pumps (> 500 W), limiting deployment. Here we developed new instrumentation using the FG method with minimal power (∼30 W). Field measurements were conducted in 2017 and 2018 in an agricultural field in Ontario, Canada to test the equipment's measurement quality, power consumption, and ease-of-use. A low-power FG system (FG LP) was co-located with an N 2 O EC flux tower (N 2 O-EC) and an existing multi-plot FG system (FG MP) was operated ∼50 m away. The FG LP fluxes correlated well with N 2 O-EC (r2 = 0.97, slope = 1.05), and ran uninterrupted with minimal maintenance using only 30 W. The non-co-located FG MP still showed relatively good correlation with N 2 O-EC (r2 = 0.65) through the growing season although there was a mismatch in measurement footprints, and N 2 O fluxes are well-known to occur in hot spots. Better agreement was observed for FG MP measured CO 2 fluxes and the EC system (slope = 0.97, r2 = 0.93), giving additional confidence in the FG MP. The FG systems captured important N 2 O pulses during rainy, foggy and dewy periods when N 2 O-EC data was discarded. Results confirmed the functionality of the new FG LP system and verified FG measurements against EC N 2 O fluxes. The low power option provides possibilities to expand measurement to locations with power restrictions using a multi-plot configuration for side-by-side comparisons essential for evaluating effects of agricultural practices on N 2 O emissions. [ABSTRACT FROM AUTHOR]

• Urban environments were tested for conservation of rare understory tree species. • Urban sites showed intermediate radiation between canopy open areas and forest sites. • Increased light enhanced photosynthesis, water use efficiency, and chlorophyll level. • Terraces can support species conservation via indoor gardening. • Urban environments have huge potential for conservation of rare tree species. To investigate the potential for urban environments on Jeju Island, South Korea, to support the conservation of rare understory shrub species, specifically Daphne jejudoensis and Maesa japonica with limited habitat availability, several study sites were selected to assess the performance of these plants after transplanting. A study site similar to the original habitat (Fo), sites between building gaps (GapJ and GapC), a flowerbed in front of a building (FbJ), the rooftop of a building (Roof), and indoor terraces at higher latitude areas (TeSD and TeSM) were selected. Building gap sites and terrace sites displayed similar but a little lower canopy coverage to the forest site (80−90 %). The flowerbed site showed ∼ 50 % coverage, and the Roof site showed ∼ 30 % canopy coverage. Therefore, urban environmental sites (GapJ, GapC, TeSD, and TeSM) displayed similar canopy coverage to original habitats of D. jejudoensis and M. japonica , with stronger light intensity than the Fo site. Shortwave radiation energy from the sky hemisphere at urban environmental sites was only 15−50 % that of the Roof site and only 3 % that of the Fo site. Therefore, urban environmental sites displayed intermediate radiation between canopy open areas and forest sites. This increased light intensity and radiation led to significantly better performance for both shrub species in terms of photosynthetic rate, water use efficiency, and chlorophyll content at urban environmental sites compared with canopy-opened Roof sites. Furthermore, these sites supported similar plant growth for D. jejudoensis and better growth for M. japonica compared with the Fo site. Therefore, urban environments possess huge potential for successful conservation of rare tree species with limited habitat range. Additionally, results for terrace sites suggest that D. jejudoensis and M. japonica have great potential as indoor gardening plants, which could support species conservation through public engagement. As a pioneering study, our findings highlight the great potential for species conservation using stable and accessible urban environments around buildings. [ABSTRACT FROM AUTHOR]

• Leaf turgor pressure varied significantly in the azimuthal, vertical, and radial apple canopies under drip irrigation. • Water potential, leaf thickness, and solar radiation affected the variation in canopy leaf turgor. • MaxP p was optimal for soil moisture monitoring based on the XGBoost model. • The LPCP probe should be installed in the middle position of the east canopy's central layer for apple trees. Leaf turgor pressure is a relevant metric for determining plant water content. To diagnose an apple tree water shortage, it is critical to precisely establish the features of leaf turgor pressure change in the canopy. In the current study, we continually monitored the leaf turgor pressure parameter (P p) at different azimuthal, vertical, and radial locations of the apple canopy based on leaf patch clamp pressure (LPCP) probes. The results demonstrated that the P p curves on sunny and rainy days were significantly different. A peak occurred on sunny days, during which the turgor pressure remained constant around midday. Under full irrigation, there was a greater change rate and daily maximum of P p (maxP p) at the east (azimuthal), upper layer (vertical), and distal (radial) positions. While leaf turgor pressure dramatically decreased with incomplete watering, maxP p significantly increased at the central and lower layers of the east canopy, as well as on the proximal and middle of the radial parts. This spatial heterogeneity in canopy leaf turgor pressure was related to the soil water potential, midday leaf water potential, sponge tissue thickness, and canopy solar radiation. Then, the ideal drought stress indicator parameter (maxP p) and canopy turgor monitoring leaf location (the middle position of the eastern canopy central layer's radial branch) were determined by multiparameter assessment. The findings presented above serve as a theoretical foundation for the construction of an intelligent irrigation system based on apple tree water status monitoring. [ABSTRACT FROM AUTHOR]

Cities are heterogeneous environments, and pollutant concentrations are often higher in streets compared with in the upper roughness sublayer (urban background) and cannot be represented using chemical-transport models that have a spatial resolution on the order of kilometers. Computational Fluid Dynamics (CFD) models coupled to chemistry/aerosol models may be used to compute the pollutant concentrations at high resolution over limited areas of cities; however, they are too expensive to use over a whole city. Hence, simplified street-network models, such as the Model of Urban Network of Intersecting Canyons and Highways (MUNICH), have been developed. These include the main physico-chemical processes that influence pollutant concentrations: emissions, transport, deposition, chemistry and aerosol dynamics. However, the streets are not discretized precisely, and concentrations are assumed to be homogeneous in each street segment. The complex street micro-meteorology is simplified by considering only the vertical transfer between the street and the upper roughness sublayer as well as the horizontal transfer between the streets. This study presents a new parametrization of a horizontal wind profile and vertical/horizontal transfer coefficients. This was developed based on a flow parametrization in a sparse vegetated canopy and adapted to street canyons using local-scale simulations performed with the CFD model Code_Saturne. CFD simulations were performed in a 2D infinite street canyon, and three streets of various aspect ratios ranging from 0.3 to 1.0 were studied with different incoming wind directions. The quantities of interest (wind speed in the street direction and passive tracer concentration) were spatially averaged in the street to compare with MUNICH. The developed parametrization depends on the street characteristics and wind direction. This effectively represents the average wind profile in a street canyon and the vertical transfer between the street and the urban roughness sublayer for a wide range of street aspect ratios while maintaining a simple formulation. [ABSTRACT FROM AUTHOR]

Present study is a maiden attempt to assess net ecosystem exchange (NEE) of carbon dioxide (CO2) flux from jute crop (Corchorus olitorius L.) in the Indo-Gangetic plain by using open-path eddy covariance (EC) technique. Diurnal variations of NEE were strongly influenced by growth stages of jute crop. Daytime peak NEE varied from − 5 µmol m−2 s−1 (in germination stage) to − 23 µmol m−2 s−1 (in fibre development stage). The ecosystem was net CO2 source during nighttime with an average NEE value of 5–8 μmol m−2 s−1. Combining both daytime and nighttime CO2 fluxes, jute ecosystem was found to be a net CO2 sink on a daily basis except the initial 9 days from date of sowing. Seasonal and growth stage-wise NEEs were computed, and the seasonal total NEE over the jute season was found to be − 268.5 gC m−2 (i.e. 10.3 t CO2 ha-1). In different jute growth stages, diurnal variations of NEE were strongly correlated (R2 > 0.9) with photosynthetic photon flux density (PPFD). Ecosystem level photosynthetic efficiency parameters were estimated at each growth stage of jute crop using the Michaelis–Menten equation. The maximum values of photosynthetic capacity (Pmax, 63.3 ± 1.15 µmol CO2 m−2 s−1) and apparent quantum yield (α, 0.072 ± 0.0045 µmol CO2 µmol photon−1) were observed during the active vegetative stage, and the fibre development stage, respectively. Results of the present study would significantly contribute to understanding of the carbon flux from the Indian agro-ecosystems, which otherwise are very sparse. [ABSTRACT FROM AUTHOR]

Two 11‐year simulations were conducted to investigate the influence of two runoff schemes in the community land model version 4.5 (CLM45) on the Amazon surface energy balance and surface climate using a high‐resolution regional climate model (RegCM4‐CLM45). The default scheme is TOPMODEL (TOP), while the alternative is Variable Infiltration Capacity (VIC). In the two simulations, the vegetation status is prescribed (satellite phenology; SP). The first simulation was designated as SP‐TOP, while the second simulation was referred to as SP‐VIC, and both of them were evaluated using reanalysis products (e.g., ERA5) and micrometeorology data measurements. Results show that the SP‐VIC severely underestimates latent heat and overestimates sensible heat fluxes, more than SP‐TOP in comparison with the ERA5. This explains the large warm bias observed in the winter season. On the other hand, the SP‐VIC shows a slightly smaller dry bias than SP‐TOP against the Climate Research Unit (CRU) data. Our results show that SP‐VIC does not improve the quality of the simulation compared to SP‐TOP, which suggests the necessity of additional calibration of the VIC surface parameters using in situ observations of the Amazon and revising the VIC runoff scheme to perform new sensitivity experiments. The same needs to be done with SP‐TOP. [ABSTRACT FROM AUTHOR]

There is a need to quantify agriculture’s potential to sequester carbon (C) to inform global approaches aimed at mitigating climate change effects. Many factors including climate, crop, soil management practices, and soil type can influence the contribution of agriculture to the global carbon cycle. The objective of this study was to investigate the C sequestration potential of conservation agriculture (CA) (defined by minimal soil disturbance, maintaining permanent soil cover, and crop rotations). This study used micrometeorological methods to measure carbon dioxide (CO2) flux from several alternative CA practices in Harare, central Zimbabwe. Micrometeorological methods can detect differences in total CO2 emissions of agricultural management practices; our results show that CA practices produce less CO2 emissions. Over three years of measurement, the mean and standard error (SE) of CO2 emissions for the plot with the most consistent CA practices was 0.564 ± 0.0122 g CO2 m−2 h−1, significantly less than 0.928 ± 0.00859 g CO2 m−2 h−1 for the conventional tillage practice. Overall CA practices of no-till with the use of cover crops produced fewer CO2 emissions than conventional tillage and fallow.

Abstract The discontinuous permafrost region of northwestern Canada is experiencing rapid warming resulting in dramatic land cover change from forested peatland permafrost terrain to treeless wetlands. Extensive research has been conducted throughout this region to gain insight into how climate‐induced land cover change will impact water resources and ecosystem function. This paper presents a hydrological and micrometeorological dataset collected in the Scotty Creek basin, Northwest Territories, Canada over the period of 01 October 2014 to 30 September 2015, a sample of the intensive and coordinated measurements collected annually at this site. Micrometeorological data collected from four stations, one located in each of the land cover types representative of those comprising the Scotty Creek basin including bog, channel fen, stable peat plateau and peat plateau undergoing rapid permafrost degradation and loss, are presented. Monitored micrometeorological variables include incoming and outgoing shortwave and longwave radiation, air temperature, relative humidity, wind speed, precipitation (rain and snow) and snow depth. Deep ground temperatures (~1–10 m below the ground surface) from a channel fen as well as disturbed sites common to the basin including a seismic line and winter road are presented. Water levels were also monitored in the representative land cover types over this period. This dataset is available from the Wilfrid Laurier University Library Research Data Repository (https://doi.org/10.5683/SP/OQDRJG) and can be used in coordination with other hydrological and micrometeorological datasets to examine spatio‐temporal effects of meteorological conditions on local hydrological responses across cold regions.

The general objective of this research was to propose a new fire risk index, specifically the Fire Risk Atlantic Forest (FIAF) index in Itatiaia National Park (PNI). The data were collected from two levels (2 and 10 m) of a micrometeorological tower, with a time series on an hourly scale, daily from 2018 to 2021. Two multiple regression models were generated for the two collection levels (FIAF 2 and 10 m) and, based on the statistical criteria and the choice of the best model, a future simulation was generated using the scenario SSP 4.5 for 2022 to 2050. The correlation matrix between the data from the FIAF and fire foci models was also analyzed. The FIAF model was compared with the traditional models already used in Brazil, such as the Angström indices, Monte Alegre Formula (FMA), and the improved Monte Alegre Formula (FMA+) models. The results showed that the FIAF model at 10 m overestimated the results observed mainly during the dry season. The FIAF 2 m model presented the highest correlation with a fire foci value greater than 0.74. In the future simulation, the years that presented the highest extreme risks were: 2025, 2035, 2041, and 2049. Thus, it is possible to state that the FIAF model at the 2 m level was the best model for predicting the degree of fire risk in the PNI.