Search Results
Error Analysis and Improved Design of Target Board Reflection for Visibility Measurement by the Image Methodsurveillance have been studied over the past several years. Steffens (1949) proposed an idea of measuring visibility by using the visual characteristics of images, which is first measures the physical characteristics of the atmosphere and then indirectly transforms them into visibility. Bellver (1987) used a 1-yr measurement test to determine the meteorological range, which was performed by photographing black targets and the sky by an automatic recording microdensitometer. Kimura et al. (2007
surveillance have been studied over the past several years. Steffens (1949) proposed an idea of measuring visibility by using the visual characteristics of images, which is first measures the physical characteristics of the atmosphere and then indirectly transforms them into visibility. Bellver (1987) used a 1-yr measurement test to determine the meteorological range, which was performed by photographing black targets and the sky by an automatic recording microdensitometer. Kimura et al. (2007
Effect of Acoustic Doppler Velocimeter Sampling Volume Size on Measurements of Turbulence1. Introduction Acoustic Doppler velocimeters (ADVs) have been extensively used for both laboratory and field research over the past decades. The ability of ADVs to make nonintrusive, three-dimensional velocity measurements—even in nonclean environments—and their relatively low cost make them a compelling choice in many circumstances. The precision and sources of error of ADVs in the measurements of the mean and higher-order statistics of turbulent flows have been quantified. More precisely, it
1. Introduction Acoustic Doppler velocimeters (ADVs) have been extensively used for both laboratory and field research over the past decades. The ability of ADVs to make nonintrusive, three-dimensional velocity measurements—even in nonclean environments—and their relatively low cost make them a compelling choice in many circumstances. The precision and sources of error of ADVs in the measurements of the mean and higher-order statistics of turbulent flows have been quantified. More precisely, it
their generation and dissipation sites and for estimating their intensity, energy, and energy flux. Shipboard and moored acoustic Doppler current profiler (ADCP) measurements capture velocity fluctuations associated with NLIWs ( Chang et al. 2008 ; Lien et al. 2010, manuscript submitted to J. Phys. Oceanogr. ; Alford et al. 2010 ; Ramp et al. 2010 ). NLIWs may have vertical currents as large as O (0.1 m s −1 ) and are often distinct in ADCP vertical velocity records. ADCP velocity measurements
their generation and dissipation sites and for estimating their intensity, energy, and energy flux. Shipboard and moored acoustic Doppler current profiler (ADCP) measurements capture velocity fluctuations associated with NLIWs ( Chang et al. 2008 ; Lien et al. 2010, manuscript submitted to J. Phys. Oceanogr. ; Alford et al. 2010 ; Ramp et al. 2010 ). NLIWs may have vertical currents as large as O (0.1 m s −1 ) and are often distinct in ADCP vertical velocity records. ADCP velocity measurements
1. Introduction a. Manual snow depth measurements In Canada, for all meteorological stations prior to the 1960s, and for most nonsynoptic stations over their entire history, snowboards were used to measure new snow within a specified time period ( Potter 1965 ). The depth of snow on the board was measured with a ruler that, since 1978, has been 1 m long and graduated every 0.2 cm. The board was then reset on the surface of the snow cover to prepare for the next snowfall (SF) event. A limitation
1. Introduction a. Manual snow depth measurements In Canada, for all meteorological stations prior to the 1960s, and for most nonsynoptic stations over their entire history, snowboards were used to measure new snow within a specified time period ( Potter 1965 ). The depth of snow on the board was measured with a ruler that, since 1978, has been 1 m long and graduated every 0.2 cm. The board was then reset on the surface of the snow cover to prepare for the next snowfall (SF) event. A limitation
1. Introduction The presence of bubbles in a liquid can have a considerable influence on that liquid’s optical and acoustical properties, as well as providing opportunities for the exchange of gases across the bubble boundary. Consequently, accurate measurement of the number and size of the bubbles present is desirable in many fields of science, for example, chemical engineering, medicine, and oceanography. The aim of the research presented in this paper is to improve the measurement of the
1. Introduction The presence of bubbles in a liquid can have a considerable influence on that liquid’s optical and acoustical properties, as well as providing opportunities for the exchange of gases across the bubble boundary. Consequently, accurate measurement of the number and size of the bubbles present is desirable in many fields of science, for example, chemical engineering, medicine, and oceanography. The aim of the research presented in this paper is to improve the measurement of the
Coupling of Wave Data and Underwater Acoustic Measurements in a Maritime High-Traffic Coastal Area: A Case Study in the Strait of Sicily. Therefore, in the development of a noise-monitoring plan in marine shallow waters, a comparative study coupling wave data and underwater acoustic measurements contributes to distinguishing the main natural abiotic underwater noise from anthropogenic noise ( Buscaino et al. 2016 ). X-band marine radars are useful active microwave remote sensing systems for sea-state monitoring either offshore or close to the coastline. Sea surface analyses by marine radar are based on the acquisition of consecutive radar
. Therefore, in the development of a noise-monitoring plan in marine shallow waters, a comparative study coupling wave data and underwater acoustic measurements contributes to distinguishing the main natural abiotic underwater noise from anthropogenic noise ( Buscaino et al. 2016 ). X-band marine radars are useful active microwave remote sensing systems for sea-state monitoring either offshore or close to the coastline. Sea surface analyses by marine radar are based on the acquisition of consecutive radar
A UAV–RTK Lidar System for Wave and Tide Measurements in Coastal Zones1. Introduction Airborne scanning lidar is frequently used for mapping topography in coastal areas and for monitoring shoreline variations (e.g., Stockdon et al. 2002 ) and beach erosion (e.g., Sallenger et al. 2003 ). Lidar has been extended and proven to be a useful tool for coastal sea surface (e.g., Reineman et al. 2009 ; Vrbancich et al. 2011 ) and wave dissipation rate measurements (e.g., Huang et al. 2012 ). However, the abovementioned studies rely on massive lidar systems, such as
1. Introduction Airborne scanning lidar is frequently used for mapping topography in coastal areas and for monitoring shoreline variations (e.g., Stockdon et al. 2002 ) and beach erosion (e.g., Sallenger et al. 2003 ). Lidar has been extended and proven to be a useful tool for coastal sea surface (e.g., Reineman et al. 2009 ; Vrbancich et al. 2011 ) and wave dissipation rate measurements (e.g., Huang et al. 2012 ). However, the abovementioned studies rely on massive lidar systems, such as
vulnerability to flooding are both increasing ( Hirabayashi et al. 2013 ; Huang et al. 2015 ). For these reasons, accurate precipitation measurements are needed by watershed managers, hydrologists, emergency management agencies, meteorologists, and climatologists. Solid precipitation measurements, in particular, are subject to large measurement errors, due primarily to undercatch caused by wind ( Fortin et al. 2008 ; Goodison et al. 1998 ; Goodison 1978 ; Rasmussen et al. 2012 ; Sugiura et al. 2003
vulnerability to flooding are both increasing ( Hirabayashi et al. 2013 ; Huang et al. 2015 ). For these reasons, accurate precipitation measurements are needed by watershed managers, hydrologists, emergency management agencies, meteorologists, and climatologists. Solid precipitation measurements, in particular, are subject to large measurement errors, due primarily to undercatch caused by wind ( Fortin et al. 2008 ; Goodison et al. 1998 ; Goodison 1978 ; Rasmussen et al. 2012 ; Sugiura et al. 2003
1. Introduction Snowfall measurement is challenging due to the wide variety of snow hydrometeors and due to the large upstream disturbance of the airflow upstream of typical shield/gauge measurement systems commonly used (typically a catching/weighing gauge). Weighing gauges impact the accuracy of the measurement due to its alteration on the local flow field around the gauge and hence the trajectory of oncoming snowflakes that it is trying to measure ( Nitu et al. 2018 ). Previous studies (e
1. Introduction Snowfall measurement is challenging due to the wide variety of snow hydrometeors and due to the large upstream disturbance of the airflow upstream of typical shield/gauge measurement systems commonly used (typically a catching/weighing gauge). Weighing gauges impact the accuracy of the measurement due to its alteration on the local flow field around the gauge and hence the trajectory of oncoming snowflakes that it is trying to measure ( Nitu et al. 2018 ). Previous studies (e
Turbulence Measurements from Compliant Moorings. Part II: Motion Correction1. Introduction Acoustic Doppler velocimeters (ADVs) have been used to make high-precision measurements of water velocity for over 20 years ( Kraus et al. 1994 ; Lohrmann et al. 1995 ). During that time, they have been deployed around the world to measure turbulence from a range of platforms, including in the laboratory setting ( Voulgaris and Trowbridge 1998 ); from stationary structures on ocean, river, and lake bottoms ( Kim et al. 2000 ; Lorke 2007 ; Cartwright et al. 2009 ); in surface
1. Introduction Acoustic Doppler velocimeters (ADVs) have been used to make high-precision measurements of water velocity for over 20 years ( Kraus et al. 1994 ; Lohrmann et al. 1995 ). During that time, they have been deployed around the world to measure turbulence from a range of platforms, including in the laboratory setting ( Voulgaris and Trowbridge 1998 ); from stationary structures on ocean, river, and lake bottoms ( Kim et al. 2000 ; Lorke 2007 ; Cartwright et al. 2009 ); in surface
