Academic literature on the topic 'Atmosphere and Weather not elsewhere classified'

Vegetation modifies land-surface properties, mediating the exchange of energy, moisture, trace gases, and aerosols between the land and the atmosphere. These exchanges influence the atmosphere on local, regional, and global scales. Through altering surface properties, vegetation change can impact on weather and climate. We review current understanding of the processes through which tropical land-cover change (LCC) affects rainfall. Tropical deforestation leads to reduced evapotranspiration, increasing surface temperatures by 1–3 K and causing boundary layer circulations, which in turn increase rainfall over some regions and reduce it elsewhere. On larger scales, deforestation leads to reductions in moisture recycling, reducing regional rainfall by up to 40%. Impacts of future tropical LCC on rainfall are uncertain but could be of similar magnitude to those caused by climate change. Climate and sustainable development policies need to account for the impacts of tropical LCC on local and regional rainfall.

Unmanned aerial vehicle (UAV) imagery has been widely used in remote sensing and photogrammetry for some time. Increasingly often, apart from recording images in the red-green-blue (RGB) range, multispectral images are also recorded. It is important to accurately assess the radiometric quality of UAV imagery to eliminate interference that might reduce the interpretation potential of the images and distort the results of remote sensing analyses. Such assessment should consider the influence of the atmosphere and the seasonal and weather conditions at the time of acquiring the imagery. The assessment of the radiometric quality of images acquired in different weather conditions is crucial in terms of improving the interpretation potential of the imagery and improving the accuracy of determining the indicators used in remote sensing and in environmental monitoring. Until now, the assessment of radiometric quality of UAV imagery did not consider the influence of meteorological conditions at different times of year. This paper presents an assessment of the influence of weather conditions on the quality of UAV imagery acquired in the visible range. This study presents the methodology for assessing image quality, considering the weather conditions characteristic of autumn in Central and Eastern Europe. The proposed solution facilitates the assessment of the radiometric quality of images acquired in the visible range. Using the objective indicator of quality assessment developed in this study, images were classified into appropriate categories, allowing, at a later stage, to improve the results of vegetation indices. The obtained results confirm that the proposed quality assessment methodology enables the objective assessment of the quality of imagery acquired in different meteorological conditions.

Abstract. Very few studies of ecosystem–atmosphere exchange involving eddy covariance data have been conducted in Siberia, with none in the western Siberian middle taiga. This work provides the first estimates of carbon dioxide (CO2) and energy budgets in a typical bog of the western Siberian middle taiga based on May–August measurements in 2015. The footprint of measured fluxes consisted of a homogeneous mixture of tree-covered ridges and hollows with the vegetation represented by typical sedges and shrubs. Generally, the surface exchange rates resembled those of pine-covered bogs elsewhere. The surface energy balance closure approached 100 %. Net CO2 uptake was comparatively high, summing up to 202 gC m−2 for the four measurement months, while the Bowen ratio was seasonally stable at 28 %. The ecosystem turned into a net CO2 source during several front passage events in June and July. The periods of heavy rain helped keep the water table at a sustainably high level, preventing a usual drawdown in summer. However, because of the cloudy and rainy weather, the observed fluxes might rather represent the special weather conditions of 2015 than their typical magnitudes.

A cloud is a mass of water vapor floating in the atmosphere. It is visible from the ground and can remain at a variable height for some time. Clouds are very important because their interaction with the rest of the atmosphere has a decisive influence on weather, for instance by sunlight occlusion or by bringing rain. Weather denotes atmosphere behavior and is determinant in several human activities, such as agriculture or energy capture. Therefore, cloud detection is an important process about which several methods have been investigated and published in the literature. The aim of this paper is to review some of such proposals and the papers that have been analyzed and discussed can be, in general, classified into three types. The first one is devoted to the analysis and explanation of clouds and their types, and about existing imaging systems. Regarding cloud detection, dealt with in a second part, diverse methods have been analyzed, i.e., those based on the analysis of satellite images and those based on the analysis of images from cameras located on Earth. The last part is devoted to cloud forecast and tracking. Cloud detection from both systems rely on thresholding techniques and a few machine-learning algorithms. To compute the cloud motion vectors for cloud tracking, correlation-based methods are commonly used. A few machine-learning methods are also available in the literature for cloud tracking, and have been discussed in this paper too.

Drought, and its associated impacts, represents one of the costliest natural hazards worldwide, highlighting the need for prediction and preparedness. While advancements have been made in monitoring current droughts, prediction of onset and termination have proven to be much more challenging. This is because drought is unlike any other natural hazard and cannot be characterised by a single weather event. There is also a high degree of spatial variability in this phenomenon across the vast expanse of the Australian continent. Therefore, by characterising regionally specific expressions of drought, we may improve drought predictability. In this study, we analyse the timing of onset and termination of meteorological droughts across Australia from 1900 to 2015, as well as their local and regional climate controls. We show that meteorological drought onset has a strong seasonal signature across Australia that varies spatially, whereas termination is less seasonally restricted. Using a Random Forest modelling approach with predictor variables representative of large-scale ocean-atmosphere phenomena and local climate, up to 75% of the variance in the Standardised Precipitation Index during both onset and termination could be explained. This study offers support to continued development in long-lead forecasting of local and large-scale ocean/atmosphere conditions to improve drought prediction in Australia and elsewhere.

Abstract Fair-weather cumuli are fundamental in regulating the vertical structure of water vapor and entropy in the lowest 2–3 km of the earth’s atmosphere over vast areas of the oceans. In this study, a long record of profiling cloud radar observations at the Atmospheric Radiation Measurement Program (ARM) Climate Research Facility (ACRF) at Nauru Island is used to investigate cloud vertical air motion statistics over an 8-yr observing period. Appropriate processing of the observed low radar reflectivities provides radar volume samples that contain only small cloud droplets; thus, the Doppler velocities are used as air motion tracers. The technique is applied to shallow boundary layer clouds (less than 1000 m thick) during the 1999–2007 period when radar data are available. Using the boundary layer winds from the soundings obtained at the Nauru ACRF, the fair-weather cumuli fields are classified in easterly and westerly boundary layer wind regimes. This distinction is necessary to separate marine-forced (westerlies) from land-forced (easterlies) shallow clouds because of a well-studied island effect at the Nauru ACRF. The two regimes exhibit large diurnal differences in cloud fraction and cloud dynamics as manifested by the analysis of the hourly averaged vertical air motion statistics. The fair-weather cumuli fields associated with easterlies exhibit a strong diurnal cycle in cloud fraction and updraft strength and fraction, indicating a strong influence of land-forced clouds. In contrast over the fair-weather cumuli with oceanic origin, land-forced clouds are characterized by uniform diurnal cloudiness and persistent updrafts at the cloud-base level. This study provides a unique observational dataset appropriate for testing fair-weather cumulus mass flux and turbulence parameterizations in numerical models.

Alaska lost 10% of its boreal forest area due to vigorous forest fires in 2004 and 2005. Repeated lightningcaused forest fires adversely impact residents and influence earth’s atmosphere in every fire season. The authors have reported on the weather conditions of Alaska’s most severe lightning occurrence in mid June 2005. This paper examines a range of weather indices like soar, instability, ‘dry lightning’ and other factors that could clearly explain lightning characteristics in Alaska. First, lightning occurrence days from May to September were classified into ‘non or small lightning’ days and ‘lightning’ days to determine threshold values. Second, ‘lightning’ days were categorized into ‘less severe,’ ‘severe,’ ‘very severe,’ and ‘extremely severe’ to notice controlling factors on the lightning severity. Based on this analysis, the lifted index (LIFT) was selected as sensitive to assess upper air instability, and Te850 (environmental temperature at 850 hPa) was selected as sensitive to assess warm and moist air masses. Finally, the possibilities of lightning forecasts in Alaska are discussed using lightning occurrence and LIFT and Te850 in 2005. As there is a time-lag between LIFT measurements (14:00) and the lightning peak (-17:00), and around one day time-lag between Te850 and lightning occurrence, lightning forecasts using LIFT and Te850 could provide a simply applicable forecast index for Alaska.

Mangrove is one of the ecologically significant ecosystems in coastal areas, both on environment and biological resources. Radar remote sensing demonstrates a high potential in detecting, identifying, mapping and monitoring mangrove forests. Advantages of radar remote sensing are that almost unaffected by the weather phenomena in the atmosphere, e.g. clouds so that it can acquire images at day and night times. This study considers possibilities of ALOS PALSAR (L-band) and ENVISAT ASAR APP (C-band) for identifying mangrove forests. Results show that using single-date data of ENVISAT ASAR APP including dual polarization HH&HV are difficult to classify mangrove objects; whilst single-date data of ALOS PALSAR with dual polarization HH&HV have a better classification for tree density but at species level identification (e.g. Avicenna or Rhizophora) is more difficult. Results classified according to forest cover density data with overall accuracy of 81.91.

Abstract. Relationships between solar activity and climate in the North Atlantic region have long been reported and, more recently, mechanisms have been proposed to explain these. Normally such relationships are tested over decadal time scales. Here, daily sea surface temperature fields bridging the period of exceptionally low solar activity between solar cycles 23 and 24 have been analysed. The day-to-day variability of the fields has been measured and the fields have been classified, using cluster analysis. The main water masses are clearly expressed, together with detail of their interactions. Three features relate to the level of solar activity. First, there is a statistically significant difference in the day-to-day variability of the sea surface temperature field between the period of lowest solar activity and the remaining periods. Second, during the transition from summer to winter, there are systematic, inter-annual changes in the day-to-day variability of the sea surface temperature field. Third, the forms of the late summer temperature fields exhibit symmetry about the years of lowest solar activity. These features are attributable to variability in the passage of weather systems. The influence on North Atlantic surface climate of variations in the solar ultraviolet band acting through the stratosphere has been reported in a number of studies. This provides a credible mechanism for solar activity influencing sea surface temperatures in the Greenland Sea.

Abstract Urban–coastal circulations affect urban weather, dispersion and transport of pollutants and contaminants, and climate. Proper characterization and prediction of thermodynamic and dynamic processes in such environments are warranted. A new generation of observation and modeling systems is enabling unprecedented characterization of the three-dimensionality of the urban environment, including morphological parameters. Urban areas of Houston, Texas, are classified according to lidar-measured building heights and assigned typical urban land surface parameters appropriate to each classification. The lidar data were degraded from 1 m to the model resolution (1 km) with the goal of evaluating the impact of degraded resolution urban canopy parameters (UCPs) and three-dimensionality on the coastal–urban mesoscale circulations in comparison to typical two-dimensional urban slab approaches. The study revealed complex interactions between the sea breeze and urban heat island and offers a novel diagnostic tool, the bulk Richardson shear number, for identifying shallow mesoscale circulation. Using the Advanced Research Weather Research and Forecasting model (ARW-WRF) coupled to an atmosphere–land surface–urban canopy model, the authors simulated a theoretical sea-breeze day and confirmed that while coastal morphology can itself lead to complex sea-breeze front structures, including preferred areas of vertical motion, the urban environment can have an impact on the evolution of the sea-breeze mesoscale boundary. The inclusion of lidar-derived UCPs, even at degraded resolution, in the model’s land surface representation can lead to significant differences in patterns of skin surface temperature, convergence, and vertical motion, which have implications for many aspects of urban weather.

This research has developed an assessment model and framework to measure cascading economic impacts in terms of gross domestic product (GDP) loss due to severe weather-induced power outages. The major objectives of this research were to (1) identify physical correlations between different industries within an economic system, (2) define deterministic relationships through the values of interconnectedness and interdependency between 71 industries, (3) complete probabilistic estimation of economic impacts using historical economic data spanning from 1997 to 2016, and (4) develop an assessment model that can be used in the future to measure economic loss in terms of gross domestic product (GDP) across 71 industries.

Methane (CH₄) is the second most powerful greenhouse gas (GHG) behind carbon dioxide (CO₂), and is able to trap a large amount of long-wave radiation, leading to surface warming. Carbon monoxide (CO) plays an important role in controlling the oxidizing capacity of the atmosphere by reacting with OH radicals that affect atmospheric CH₄ dynamics. Terrestrial ecosystems play an important role in determining the amount of these gases into the atmosphere. However, global quantifications of CH₄ emissions from wetlands and its sinks from uplands, and CO exchanges between land and the atmosphere are still fraught with large uncertainties, presenting a big challenge to interpret complex atmospheric CH₄ dynamics in recent decades. In this dissertation, I apply modeling approaches to estimate the global CH₄ and CO exchanges between land ecosystems and the atmosphere and analyze how they respond to contemporary and future climate change.

Firstly, I develop a process-based biogeochemistry model embedded in Terrestrial Ecosystem Model (TEM) to quantify the CO exchange between soils and the atmosphere at the global scale (Chapter 2). Parameterizations were conducted by using the CO in situ data for eleven representative ecosystem types. The model is then extrapolated to global terrestrial ecosystems. Globally soils act as a sink of atmospheric CO. Areas near the equator, Eastern US, Europe and eastern Asia will be the largest sink regions due to their optimum soil moisture and high temperature. The annual global soil net flux of atmospheric CO is primarily controlled by air temperature, soil temperature, SOC and atmospheric CO concentrations, while its monthly variation is mainly determined by air temperature, precipitation, soil temperature and soil moisture.

Secondly, to better quantify the global CH₄ emissions from wetlands and their uncertainties, I revise, parameterize and verify a process-based biogeochemical model for methane for various wetland ecosystems (Chapter 3). The model is then extrapolated to the global scale to quantify the uncertainty induced from four different types of uncertainty sources including parameterization, wetland type distribution, wetland area distribution and meteorological input. Spatially, the northeast US and Amazon are two hotspots of CH₄ emissions, while consumption hotspots are in the eastern US and eastern China. The relationships between both wetland emissions and upland consumption and El Niño and La Niña events are analyzed. This study highlights the need for more in situ methane flux data, more accurate wetland type and area distribution information to better constrain the model uncertainty.

Thirdly, to further constrain the global wetland CH₄ emissions, I develop a predictive model of CH₄ emissions using an artificial neural network (ANN) approach and available field observations of CH₄ fluxes (Chapter 4). Eleven explanatory variables including three transient climate variables (precipitation, air temperature and solar radiation) and eight static soil property variables are considered in developing the ANN models. The models are then extrapolated to the global scale to estimate monthly CH₄ emissions from 1979 to 2099. Significant interannual and seasonal variations of wetland CH₄ emissions exist in the past four decades, and the emissions in this period are most sensitive to variations in solar radiation and air temperature. This study reduced the uncertainty in global CH₄ emissions from wetlands and called for better characterizing variations of wetland areas and water table position and more long-term observations of CH₄ fluxes in tropical regions.

Finally, in order to study a new pathway of CH₄ emissions from palm tree stem, I develop a two-dimensional diffusion model. The model is optimized using field data of methane emissions from palm tree stems (Chapter 5). The model is then extrapolated to Pastaza-Marañón foreland basin (PMFB) in Peru by using a process-based biogeochemical model. To our knowledge, this is among the first efforts to quantify regional CH₄ emissions through this pathway. The estimates can be improved by considering the effects of changes in temperature, precipitation and radiation and using long-period continuous flux observations. Regional and global estimates of CH₄ emissions through this pathway can be further constrained using more accurate palm swamp classification and spatial distribution data of palm trees at the global scale.

Clouds are visual indicators of physical processes taking place in the atmosphere. They provide information about winds, stability, moisture content, and traveling weather systems that can be used in short-term (several hour) and long-term (24-36-hour) weather forecasts and in field assessments of weather conditions. Most clouds form when moist air is lifted and cooled. Lifting occurs when air rises over low pressure areas, is carried up inclined frontal surfaces, is carried upward by convective currents that originate at the heated ground, or flows over mountains. Clouds are classified according to their appearance (table 7.1) and the approximate altitude of their bases (table 7.2) following a simple scheme that was developed in 1803 by an English druggist, Luke Howard. This scheme can be expanded to describe certain clouds more precisely (World Meteorological Organization, 1987). The cloud types listed in table 7.1 are pictured in figure 7.1. The two basic cloud classifications are stratiform and cumuliform. Stratiform clouds form horizontal layers, with the horizontal dimension much greater than the vertical dimension. Cumuliform clouds, on the other hand, have roughly equal horizontal and vertical dimensions, giving them the appearance of a cotton ball. Stratiform clouds are given the stem name stratus, and cumuliform clouds are given the stem name cumulus.Stratiform and cumuliform clouds are assigned to one of three height classifications: high, middle, or low. High clouds are composed of ice crystals rather than water droplets and are named using the prefix cirro- (cirrocumulus or cirrostratus). Clouds at midlevels, which may be composed of either water or ice particles, are given the prefix alto- (altocumulus or altostratus). Low clouds are given no prefix (stratus or cumulus). When a stratus deck is composed of an array of individual cumulus elements or lumps, the term stratocumulus is used. Cirrus are stringy or fibrous high clouds that are neither stratiform nor cumuliform. Towering cumulus extend through low and middle levels of the atmosphere. A thunderstorm cloud, called a cumulonimbus. extends through low, middle, and high levels of the atmosphere and is accompanied by lightning and showery precipitation. Clouds that bring widespread, light precipitation but not lightning, thunder, or hail are called nimbostratus.

The ‘CO2SafeArrest’ Joint Industry Project (JIP) was set up with the twin aims of: (1) investigating the fracture propagation and arrest characteristics of steel pipelines carrying anthropogenic carbon dioxide (CO2), and (2) investigating the dispersion of CO2 following its release into the atmosphere. The project involves two full-scale burst tests of 24-inch, X65 buried line pipes filled with a mixture of CO2 and nitrogen (N2). An overview of the CO2SafeArrest JIP and details of the fracture propagation and arrest investigation appear elsewhere in two companion papers. This paper presents the experimental investigation and computational fluid dynamics (CFD) simulations of the dispersion of CO2 following its explosive release into the atmosphere over the terrain at the test site in the first test. The setting up of the experiment and the CFD model is described in detail, including the representation of terrain topography and weather (wind) conditions, and the condition at the ‘inlet to the dispersion domain’. The modelling was carried out prior to the actual event, and simulated the dispersion of the CO2 cloud for different wind speeds and directions. This analysis confirmed that the sensor layout set up to obtain spot measurements CO2 concentration over the terrain at the site was adequate. The predicted and experimental values of CO2 concentration at the nominated locations over the duration of the dispersion were found to be in good agreement. Results of this study are expected to be used in developing a generalized model for the dispersion of CO2 and for estimating the ‘consequence distance’ for such events. It is noted that this distance is necessarily a function of time due to the highly transient nature of the event.

The 5 Russian Arctic Seas have common features, but differ significantly from each other in the sea ice regime and navigation specifics. Navigation in the Arctic is a big challenge, especially during the winter season. However, it is necessary, due to limited natural resources elsewhere on Earth that may be easier for exploitation. Therefore sea ice is an important issue for future development. We foresee that the Arctic may become ice free in summer as a result of global warming and even light yachts will be able to pass through the Eastern Passage. There have been several such examples in the last years. But sea ice is an inherent feature of Arctic Seas in winter, it is permanently immanent for the Central Arctic Basin. That is why it is important to get appropriate knowledge about sea ice properties and operations in ice conditions. Four seas, the Kara, Laptev, East Siberian, and Chukchi have been examined in the book “Russian Arctic Seas. Navigation Condition and Accidents”, Marchenko, 2012 [1]. The book is devoted to the eastern sector of the Arctic, with a description of the seas and accidents caused by heavy ice conditions. The traditional physical-geographical characteristics, information about the navigation conditions and the main sea routes and reports on accidents that occurred in the 20th century have reviewed. An additional investigation has been performed for more recent accidents and for the Barents Sea. Considerable attention has been paid to problems associated with sea ice caused by the present development of the Arctic. Sea ice can significantly affect shipping, drilling, and the construction and operation of platforms and handling terminals. Sea ice is present in the main part of the east Arctic Sea most of the year. The Barents Sea, which is strongly influenced and warmed by the North Atlantic Current, has a natural environment that is dramatically different from those of the other Arctic seas. The main difficulties with the Barents Sea are produced by icing and storms and in the north icebergs. The ice jet is the most dangerous phenomenon in the main straits along the Northern Sea Route and in Chukchi Seas. The accidents in the Arctic Sea have been classified, described and connected with weather and ice conditions. Behaviour of the crew is taken into consideration. The following types of the ice-induced accidents are distinguished: forced drift, forced overwintering, shipwreck, and serious damage to the hull in which the crew, sometimes with the help of other crews, could still save the ship. The main reasons for shipwrecks and damages are hits of ice floes (often in rather calm ice conditions), ice nipping (compression) and drift. Such investigation is important for safety in the Arctic.