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- Author or Editor: A. Van Delden x
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Abstract
Data from a wind profiler are used to investigate the vertical structure of the sea breeze with the accompanying return current at the North Sea coast in the Netherlands for three sea-breeze cases. In one of the cases, with a very weak and constant background flow, the return current mass flux approximately compensates for the sea-breeze mass flux. To study the sea breeze with the accompanying return current, a simple two-dimensional mesoscale model is constructed. It is found that the sea breeze as well as the return current of the three cases in this study are simulated well by the model. In the case mentioned above, the model indicates an overcompensation of the sea breeze by the return current. It is found that the latter is a function of the initial vertical temperature profile and the depth of the boundary layer, and that it can be as much as 30%. The overcompensation is balanced by a mass flow (in the sea-breeze direction) at a larger height (“return–return current”). As such, a three-layer structure for the sea breeze becomes evident.
Abstract
Data from a wind profiler are used to investigate the vertical structure of the sea breeze with the accompanying return current at the North Sea coast in the Netherlands for three sea-breeze cases. In one of the cases, with a very weak and constant background flow, the return current mass flux approximately compensates for the sea-breeze mass flux. To study the sea breeze with the accompanying return current, a simple two-dimensional mesoscale model is constructed. It is found that the sea breeze as well as the return current of the three cases in this study are simulated well by the model. In the case mentioned above, the model indicates an overcompensation of the sea breeze by the return current. It is found that the latter is a function of the initial vertical temperature profile and the depth of the boundary layer, and that it can be as much as 30%. The overcompensation is balanced by a mass flow (in the sea-breeze direction) at a larger height (“return–return current”). As such, a three-layer structure for the sea breeze becomes evident.
Abstract
Principal component analysis (PCA) was applied to 182 half-hour runs containing time series of turbulent wind velocity and temperature measured in the convective atmospheric surface layer. A field experiment with four sonic anemometers on the vertices and one in the centroid of a square (with sides of 80 m) was performed to obtain the necessary dataset. Physical explanations of the most important eigenvectors are presented. Two of the major principal components (PCs) identify the variance in wind speed along and across the background wind direction. Always, one major PC accounts for the presence of large-scale thermal activity: periods with higher (lower) temperatures coincide with lower (higher) wind speeds, convergence (divergence) in the wind fields, and upward (downward) movements. As an application, variance in the velocity fields was expressed in terms of horizontal divergence and vertical vorticity. These can be derived directly from the eigenvectors when PCA is combined with a planimetric method. Using the PC that identifies thermal activity, it is found that the magnitude of divergence increases and the magnitude of vorticity decreases when atmospheric conditions become more unstable. It is found that the (absolute) ratio between vorticity and divergence scales with a function of the friction velocity divided by the convective vertical scaling velocity. Both kinematic parameters are larger for updrafts than for downdrafts. It is concluded that PCA can be a useful tool to distinguish variance of thermal and nonthermal origin and in the estimation of the kinematics of dominant flow fields.
Abstract
Principal component analysis (PCA) was applied to 182 half-hour runs containing time series of turbulent wind velocity and temperature measured in the convective atmospheric surface layer. A field experiment with four sonic anemometers on the vertices and one in the centroid of a square (with sides of 80 m) was performed to obtain the necessary dataset. Physical explanations of the most important eigenvectors are presented. Two of the major principal components (PCs) identify the variance in wind speed along and across the background wind direction. Always, one major PC accounts for the presence of large-scale thermal activity: periods with higher (lower) temperatures coincide with lower (higher) wind speeds, convergence (divergence) in the wind fields, and upward (downward) movements. As an application, variance in the velocity fields was expressed in terms of horizontal divergence and vertical vorticity. These can be derived directly from the eigenvectors when PCA is combined with a planimetric method. Using the PC that identifies thermal activity, it is found that the magnitude of divergence increases and the magnitude of vorticity decreases when atmospheric conditions become more unstable. It is found that the (absolute) ratio between vorticity and divergence scales with a function of the friction velocity divided by the convective vertical scaling velocity. Both kinematic parameters are larger for updrafts than for downdrafts. It is concluded that PCA can be a useful tool to distinguish variance of thermal and nonthermal origin and in the estimation of the kinematics of dominant flow fields.
Abstract
The horizontal perturbation wind field within thermal structures encountered in the atmospheric surface layer was investigated. A field experiment with four sonic anemometers on the vertices and one in the centroid of a square (with sides of 80 m) was performed to obtain the necessary dataset. Structures were selected on a typical ramplike appearance in the temperature time series. Ultimately, a set of 47 “ramps” was obtained. Conditional sampling and block averaging followed by a compositing technique were applied to construct ensemble averages of turbulent temperature and horizontal and vertical velocity. Properties of the horizontal velocity field were expressed in terms of ensemble averages of horizontal divergence, vertical vorticity, and deformation.
The ensemble-averaged behavior at the five masts during passage of thermal activity was consistent. The convergent wind field within a ramp attains its maximum simultaneously with the maximum in vertical velocity. Both precede the temperature extreme. The air in the ramp is clearly decelerated. while it is accelerated in die succeeding downdraft. In the frame of reference moving with the ramp the average orientation of the wind vector in the accompanying downdrafts always directed toward the position of the ramp. Within the ramp, direction of air is measured in the direction of the mean wind. Near the microfront, contraction of air occurs with a maximum in the succeeding downdraft. Vertical vorticity (of opposite sign) is measured in the right and left half of the ramps. Phenomena involved in the generation of this vorticity are discussed. The strength of the background wind might play a role in the generation of these rotations.
Abstract
The horizontal perturbation wind field within thermal structures encountered in the atmospheric surface layer was investigated. A field experiment with four sonic anemometers on the vertices and one in the centroid of a square (with sides of 80 m) was performed to obtain the necessary dataset. Structures were selected on a typical ramplike appearance in the temperature time series. Ultimately, a set of 47 “ramps” was obtained. Conditional sampling and block averaging followed by a compositing technique were applied to construct ensemble averages of turbulent temperature and horizontal and vertical velocity. Properties of the horizontal velocity field were expressed in terms of ensemble averages of horizontal divergence, vertical vorticity, and deformation.
The ensemble-averaged behavior at the five masts during passage of thermal activity was consistent. The convergent wind field within a ramp attains its maximum simultaneously with the maximum in vertical velocity. Both precede the temperature extreme. The air in the ramp is clearly decelerated. while it is accelerated in die succeeding downdraft. In the frame of reference moving with the ramp the average orientation of the wind vector in the accompanying downdrafts always directed toward the position of the ramp. Within the ramp, direction of air is measured in the direction of the mean wind. Near the microfront, contraction of air occurs with a maximum in the succeeding downdraft. Vertical vorticity (of opposite sign) is measured in the right and left half of the ramps. Phenomena involved in the generation of this vorticity are discussed. The strength of the background wind might play a role in the generation of these rotations.
Crowdsourcing Urban Air Temperatures through Smartphone Battery Temperatures in São Paulo, BrazilAbstract
Crowdsourcing as a method to obtain and apply vast datasets is rapidly becoming prominent in meteorology, especially for urban areas where routine weather observations are scarce. Previous studies showed that smartphone battery temperature readings can be used to estimate the daily and citywide air temperature via a direct heat transfer model. This work extends model estimates by studying smaller temporal and spatial scales. The study finds the number of battery readings influences the accuracy of temperature retrievals. Optimal results are achieved for 700 or more retrievals. An extensive dataset of over 10 million battery temperature readings for estimating hourly and daily air temperatures is available for São Paulo, Brazil. The air temperature estimates are validated with measurements from a WMO station, an Urban Flux Network site, and data from seven citizen weather stations. Daily temperature estimates are good (coefficient of determination ρ 2 of 86%), and the study shows they improve by optimizing model parameters for neighborhood scales (<1 km2) as categorized in local climate zones (LCZs). Temperature differences between LCZs can be distinguished from smartphone battery temperatures. When validating the model for hourly temperature estimates, the model requires a diurnally varying parameter function in the heat transfer model rather than one fixed value for the entire day. The results show the potential of large crowdsourced datasets in meteorological studies, and the value of smartphones as a measuring platform when routine observations are lacking.
Abstract
Crowdsourcing as a method to obtain and apply vast datasets is rapidly becoming prominent in meteorology, especially for urban areas where routine weather observations are scarce. Previous studies showed that smartphone battery temperature readings can be used to estimate the daily and citywide air temperature via a direct heat transfer model. This work extends model estimates by studying smaller temporal and spatial scales. The study finds the number of battery readings influences the accuracy of temperature retrievals. Optimal results are achieved for 700 or more retrievals. An extensive dataset of over 10 million battery temperature readings for estimating hourly and daily air temperatures is available for São Paulo, Brazil. The air temperature estimates are validated with measurements from a WMO station, an Urban Flux Network site, and data from seven citizen weather stations. Daily temperature estimates are good (coefficient of determination ρ 2 of 86%), and the study shows they improve by optimizing model parameters for neighborhood scales (<1 km2) as categorized in local climate zones (LCZs). Temperature differences between LCZs can be distinguished from smartphone battery temperatures. When validating the model for hourly temperature estimates, the model requires a diurnally varying parameter function in the heat transfer model rather than one fixed value for the entire day. The results show the potential of large crowdsourced datasets in meteorological studies, and the value of smartphones as a measuring platform when routine observations are lacking.
