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- Author or Editor: Andrew Sturman x
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Abstract
The world’s tropical coral reefs are at risk of severe bleaching episodes and species decline in response to global climate variability. The ecological and economic value of reef ecosystems is enormous, yet very little is known of the physical interactions that take place at the coral–ocean–atmosphere interfaces. This paper introduces and validates a novel technique for the acquisition of surface energy balance measurements over Heron Reef, part of the Capricorn Bunker Group of the southern Great Barrier Reef, Australia. Measurements of surface energy and radiation exchanges were made using a Campbell Scientific eddy covariance (EC) measurement system mounted on a floating pontoon anchored to the reef flat. A Nortek Vector velocimeter was positioned next to the pontoon to record wave motion. Wavelet analysis techniques were used to decompose the turbulent exchange of sensible heat measured by the EC unit and to compare vertical velocity measurements with wave-induced motion recorded by the velocimeter. The results indicate that although the EC system and the velocimeter share intermittent periods of high common power in their respective wavelet variance spectra, these regions are not coherent and differ in strength by more than an order of magnitude. It was concluded that over a standard averaging period of 30 min the wave-induced motion of the pontoon would not significantly interfere with the acquisition and calculation of turbulent fluxes of sensible and latent heat, thereby confirming the robustness of this method of obtaining surface energy balance measurements over coral reefs.
Abstract
The world’s tropical coral reefs are at risk of severe bleaching episodes and species decline in response to global climate variability. The ecological and economic value of reef ecosystems is enormous, yet very little is known of the physical interactions that take place at the coral–ocean–atmosphere interfaces. This paper introduces and validates a novel technique for the acquisition of surface energy balance measurements over Heron Reef, part of the Capricorn Bunker Group of the southern Great Barrier Reef, Australia. Measurements of surface energy and radiation exchanges were made using a Campbell Scientific eddy covariance (EC) measurement system mounted on a floating pontoon anchored to the reef flat. A Nortek Vector velocimeter was positioned next to the pontoon to record wave motion. Wavelet analysis techniques were used to decompose the turbulent exchange of sensible heat measured by the EC unit and to compare vertical velocity measurements with wave-induced motion recorded by the velocimeter. The results indicate that although the EC system and the velocimeter share intermittent periods of high common power in their respective wavelet variance spectra, these regions are not coherent and differ in strength by more than an order of magnitude. It was concluded that over a standard averaging period of 30 min the wave-induced motion of the pontoon would not significantly interfere with the acquisition and calculation of turbulent fluxes of sensible and latent heat, thereby confirming the robustness of this method of obtaining surface energy balance measurements over coral reefs.
Abstract
In February 2017, a wildfire occurred in the Port Hills on the southern boundary of Christchurch city in New Zealand. It was one of the country’s most severe fires of the last decade in terms of the scale of evacuation, infrastructure damage, and property loss. On the third day of the fire, fire behavior was unexpectedly active, and two rapid downhill fire-spread events took place, creating a dangerous situation for firefighters. The aim of this paper is to explore the atmospheric processes that influenced the fire behavior at a range of meteorological scales, from the synoptic to meso- and microscales. Meteorological and fire data analyzed include observed data together with model simulations of weather conditions at different scales: 1) the Weather Research and Forecasting (WRF) numerical weather prediction model, which provided the regional context of the fire; and 2) the California Meteorological (CALMET) diagnostic model, which was used to undertake a higher-resolution investigation of atmospheric processes near the fire. Results indicate that the fire was not strongly seasonally influenced. Instead, it appears the fire conditions were the effect of a specific combination of synoptic weather conditions and local meteorological conditions. The first rapid downhill fire-spread event was the result of airflow interaction with the intricate terrain of the Port Hills under stable nocturnal conditions. The second downhill fire-spread event bears similarities to vorticity-driven lateral spread, because the downhill component of the spread happened on a broad fire flank perpendicular to the surface wind direction and characteristic pyrocumulus convection occurred.
Abstract
In February 2017, a wildfire occurred in the Port Hills on the southern boundary of Christchurch city in New Zealand. It was one of the country’s most severe fires of the last decade in terms of the scale of evacuation, infrastructure damage, and property loss. On the third day of the fire, fire behavior was unexpectedly active, and two rapid downhill fire-spread events took place, creating a dangerous situation for firefighters. The aim of this paper is to explore the atmospheric processes that influenced the fire behavior at a range of meteorological scales, from the synoptic to meso- and microscales. Meteorological and fire data analyzed include observed data together with model simulations of weather conditions at different scales: 1) the Weather Research and Forecasting (WRF) numerical weather prediction model, which provided the regional context of the fire; and 2) the California Meteorological (CALMET) diagnostic model, which was used to undertake a higher-resolution investigation of atmospheric processes near the fire. Results indicate that the fire was not strongly seasonally influenced. Instead, it appears the fire conditions were the effect of a specific combination of synoptic weather conditions and local meteorological conditions. The first rapid downhill fire-spread event was the result of airflow interaction with the intricate terrain of the Port Hills under stable nocturnal conditions. The second downhill fire-spread event bears similarities to vorticity-driven lateral spread, because the downhill component of the spread happened on a broad fire flank perpendicular to the surface wind direction and characteristic pyrocumulus convection occurred.
Abstract
Vertical profiles of wind velocity and air temperature from a sound detection and ranging (sodar) radio acoustic sounding system (RASS)-derived dataset within an alpine valley of the New Zealand Southern Alps were analyzed. The data covered the month of September 2013, and self-organizing maps (SOM; a data-clustering approach that is based on an unsupervised machine-learning algorithm) are used to detect topological relationships between profiles. The results of the SOM were shown to reflect the physical processes within the valley boundary layer by preserving valley boundary layer dynamics and its response to wind shear. By examining the temporal evolution of ridgetop wind speed and direction and SOM node transitions, the sensitivity of the valley boundary layer to ridgetop weather conditions was highlighted. The approach of using a composite variable (wind speed and potential temperature) with SOM was successful in revealing the coupling of dynamics and atmospheric stability. The results reveal the capabilities of SOM in analyzing large datasets of atmospheric boundary layer measurements and elucidating the connectivity of ridgetop wind speeds and valley boundary layers.
Abstract
Vertical profiles of wind velocity and air temperature from a sound detection and ranging (sodar) radio acoustic sounding system (RASS)-derived dataset within an alpine valley of the New Zealand Southern Alps were analyzed. The data covered the month of September 2013, and self-organizing maps (SOM; a data-clustering approach that is based on an unsupervised machine-learning algorithm) are used to detect topological relationships between profiles. The results of the SOM were shown to reflect the physical processes within the valley boundary layer by preserving valley boundary layer dynamics and its response to wind shear. By examining the temporal evolution of ridgetop wind speed and direction and SOM node transitions, the sensitivity of the valley boundary layer to ridgetop weather conditions was highlighted. The approach of using a composite variable (wind speed and potential temperature) with SOM was successful in revealing the coupling of dynamics and atmospheric stability. The results reveal the capabilities of SOM in analyzing large datasets of atmospheric boundary layer measurements and elucidating the connectivity of ridgetop wind speeds and valley boundary layers.
Abstract
This paper introduces a set of descriptors applied to weather regimes that allow for a detailed monitoring of the location and intensity of their atmospheric centers of action (e.g., troughs and ridges) and the gradients between them, when applicable. Descriptors are designed to document the effect of climate variability and change in modulating the character of daily weather regimes, rather than merely their occurrence statistics. As a case study, the methodology is applied to Aotearoa New Zealand (ANZ), using ERA5 ensemble reanalysis data for the period 1979–2019. Here, we analyze teleconnections between the regimes and their descriptors and large-scale climate variability. Results show a significant modulation of centers of action by the phase of the southern annular mode, with a strong relationship identified with the latitude of atmospheric ridges. Significant associations with El Niño–Southern Oscillation are also identified. Modes of large-scale variability have a stronger influence on the regimes’ intrinsic features than their occurrence. This demonstrates the usefulness of such descriptors, which help explain the relationship between midlatitude transient perturbations and large-scale modes of climate variability. In future research, this methodological framework will be applied to analyze (i) low-frequency changes in weather regimes under climate change, in line with the southward shift of storm tracks, and (ii) regional-scale effects on the climate of ANZ, resulting from interaction with its topography.
Abstract
This paper introduces a set of descriptors applied to weather regimes that allow for a detailed monitoring of the location and intensity of their atmospheric centers of action (e.g., troughs and ridges) and the gradients between them, when applicable. Descriptors are designed to document the effect of climate variability and change in modulating the character of daily weather regimes, rather than merely their occurrence statistics. As a case study, the methodology is applied to Aotearoa New Zealand (ANZ), using ERA5 ensemble reanalysis data for the period 1979–2019. Here, we analyze teleconnections between the regimes and their descriptors and large-scale climate variability. Results show a significant modulation of centers of action by the phase of the southern annular mode, with a strong relationship identified with the latitude of atmospheric ridges. Significant associations with El Niño–Southern Oscillation are also identified. Modes of large-scale variability have a stronger influence on the regimes’ intrinsic features than their occurrence. This demonstrates the usefulness of such descriptors, which help explain the relationship between midlatitude transient perturbations and large-scale modes of climate variability. In future research, this methodological framework will be applied to analyze (i) low-frequency changes in weather regimes under climate change, in line with the southward shift of storm tracks, and (ii) regional-scale effects on the climate of ANZ, resulting from interaction with its topography.
Abstract
Strong winds crossing elevated terrain and descending to its lee occur over mountainous areas worldwide. Winds fulfilling these two criteria are called foehn in this paper although different names exist depending on the region, the sign of the temperature change at onset, and the depth of the overflowing layer. These winds affect the local weather and climate and impact society. Classification is difficult because other wind systems might be superimposed on them or share some characteristics. Additionally, no unanimously agreed-upon name, definition, nor indications for such winds exist. The most trusted classifications have been performed by human experts. A classification experiment for different foehn locations in the Alps and different classifier groups addressed hitherto unanswered questions about the uncertainty of these classifications, their reproducibility, and dependence on the level of expertise. One group consisted of mountain meteorology experts, the other two of master’s degree students who had taken mountain meteorology courses, and a further two of objective algorithms. Sixty periods of 48 h were classified for foehn–no foehn conditions at five Alpine foehn locations. The intra-human-classifier detection varies by about 10 percentage points (interquartile range). Experts and students are nearly indistinguishable. The algorithms are in the range of human classifications. One difficult case appeared twice in order to examine the reproducibility of classified foehn duration, which turned out to be 50% or less. The classification dataset can now serve as a test bed for automatic classification algorithms, which—if successful—eliminate the drawbacks of manual classifications: lack of scalability and reproducibility.
Abstract
Strong winds crossing elevated terrain and descending to its lee occur over mountainous areas worldwide. Winds fulfilling these two criteria are called foehn in this paper although different names exist depending on the region, the sign of the temperature change at onset, and the depth of the overflowing layer. These winds affect the local weather and climate and impact society. Classification is difficult because other wind systems might be superimposed on them or share some characteristics. Additionally, no unanimously agreed-upon name, definition, nor indications for such winds exist. The most trusted classifications have been performed by human experts. A classification experiment for different foehn locations in the Alps and different classifier groups addressed hitherto unanswered questions about the uncertainty of these classifications, their reproducibility, and dependence on the level of expertise. One group consisted of mountain meteorology experts, the other two of master’s degree students who had taken mountain meteorology courses, and a further two of objective algorithms. Sixty periods of 48 h were classified for foehn–no foehn conditions at five Alpine foehn locations. The intra-human-classifier detection varies by about 10 percentage points (interquartile range). Experts and students are nearly indistinguishable. The algorithms are in the range of human classifications. One difficult case appeared twice in order to examine the reproducibility of classified foehn duration, which turned out to be 50% or less. The classification dataset can now serve as a test bed for automatic classification algorithms, which—if successful—eliminate the drawbacks of manual classifications: lack of scalability and reproducibility.
