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Abstract
Optical remote sensing measurements of cirrus cloud properties were collected by one airborne and four ground-based lidar systems over a 32-h period during this cue study from the First ISCCP (International Satellite Cloud Climatology Program) Regional Experiment (FIRE) Intensive Field Observation (IFO) program. The lidar systems were variously equipped to collect linear depolarization, intrinsically calibrated backscatter, and Doppler velocity information. Data presented here describe the temporal evolution and spatial distribution of cirrus clouds over an area encompassing southern and central Wisconsin. The cirrus cloud types include: (a) dissipating subvisual and “thin” fibrous cirrus cloud bands, (b) an isolated mesoscale uncinus complex (MUC), (c) a large-scale, deep cloud that developed into an organized cirrus structure within the lidar array, and (d) a series of intensifying mesoscale cirrus cloud masses. Although the cirrus frequently developed in the vertical from particle fallstreaks emanating from generating regions at or near cloud tops, glaciating supercooled (−30° to −35°C) altocumulus clouds contributed to the production of ice mass at the base of the deep cirrus cloud, apparently even through riming, and other mechanisms involving evaporation, wave motions, and radiative effects are indicated. The generating regions ranged in scale from ∼1.0-km cirrus uncinus cells, to organized MUC structures up to ∼120 km across.
Abstract
Optical remote sensing measurements of cirrus cloud properties were collected by one airborne and four ground-based lidar systems over a 32-h period during this cue study from the First ISCCP (International Satellite Cloud Climatology Program) Regional Experiment (FIRE) Intensive Field Observation (IFO) program. The lidar systems were variously equipped to collect linear depolarization, intrinsically calibrated backscatter, and Doppler velocity information. Data presented here describe the temporal evolution and spatial distribution of cirrus clouds over an area encompassing southern and central Wisconsin. The cirrus cloud types include: (a) dissipating subvisual and “thin” fibrous cirrus cloud bands, (b) an isolated mesoscale uncinus complex (MUC), (c) a large-scale, deep cloud that developed into an organized cirrus structure within the lidar array, and (d) a series of intensifying mesoscale cirrus cloud masses. Although the cirrus frequently developed in the vertical from particle fallstreaks emanating from generating regions at or near cloud tops, glaciating supercooled (−30° to −35°C) altocumulus clouds contributed to the production of ice mass at the base of the deep cirrus cloud, apparently even through riming, and other mechanisms involving evaporation, wave motions, and radiative effects are indicated. The generating regions ranged in scale from ∼1.0-km cirrus uncinus cells, to organized MUC structures up to ∼120 km across.
Abstract
During spring and early summer, a surface confluence zone, often referred to as the dryline, forms in the midwestern United States between continental and maritime air masses. The dewpoint temperature across the dryline can vary in excess of 18°C in a distance of less than 10 km. The movement of the dryline varies diurnally with boundary layer growth over sloping terrain leading to an eastward apparent propagation of the dryline during the day and a westward advection or retrogression during the evening. In this study, we examine the finescale structure of a retrogressing, dryline using data taken by a Doppler lidar, a dual-channel radiometer, and serial rawinsonde ascents. While many previous studies were unable to accurately measure the vertical motions in the vicinity of the dryline, our lidar measurements suggest that the convergence at the dryline is intense with maximum vertical motions of ∼5 m s−1. The winds obtained from the Doppler lidar Measurements were combined with the equations of motion to derive perturbation fields of pressure and virtual potential temperature θ v . Our observations indicate that the circulations associated with this retrogressing dryline were dominated by hot, dry air riding over a westward moving denser, moist flow in a manner similar to a density current. Gravity waves were observed above the dryline interface. Previous observational and numerical studies have shown that differential heating across the dryline may sometimes enhance regional pressure gradients and thus impact dryline movement. We propose that this regional gradient in surface heating in the presence of a confluent flow results in observed intense wind shifts and large horizontal gradients in θ v across the dryline. The local gradient in θ v influences the movement and flow characteristics of the dryline interface. This study is one of the most complete and novel uses of Doppler lidar to date.
Abstract
During spring and early summer, a surface confluence zone, often referred to as the dryline, forms in the midwestern United States between continental and maritime air masses. The dewpoint temperature across the dryline can vary in excess of 18°C in a distance of less than 10 km. The movement of the dryline varies diurnally with boundary layer growth over sloping terrain leading to an eastward apparent propagation of the dryline during the day and a westward advection or retrogression during the evening. In this study, we examine the finescale structure of a retrogressing, dryline using data taken by a Doppler lidar, a dual-channel radiometer, and serial rawinsonde ascents. While many previous studies were unable to accurately measure the vertical motions in the vicinity of the dryline, our lidar measurements suggest that the convergence at the dryline is intense with maximum vertical motions of ∼5 m s−1. The winds obtained from the Doppler lidar Measurements were combined with the equations of motion to derive perturbation fields of pressure and virtual potential temperature θ v . Our observations indicate that the circulations associated with this retrogressing dryline were dominated by hot, dry air riding over a westward moving denser, moist flow in a manner similar to a density current. Gravity waves were observed above the dryline interface. Previous observational and numerical studies have shown that differential heating across the dryline may sometimes enhance regional pressure gradients and thus impact dryline movement. We propose that this regional gradient in surface heating in the presence of a confluent flow results in observed intense wind shifts and large horizontal gradients in θ v across the dryline. The local gradient in θ v influences the movement and flow characteristics of the dryline interface. This study is one of the most complete and novel uses of Doppler lidar to date.
Abstract
Accurate measurement of wind speed profiles aloft in the marine boundary layer is a difficult challenge. The development of offshore wind energy requires accurate information on wind speeds above the surface at least at the levels occupied by turbine blades. Few measured data are available at these heights, and the temporal and spatial behavior of near-surface winds is often unrepresentative of that at the required heights. As a consequence, numerical model data, another potential source of information, are essentially unverified at these levels of the atmosphere. In this paper, a motion-compensated, high-resolution Doppler lidar–based wind measurement system that is capable of providing needed information on offshore winds at several heights is described. The system has been evaluated and verified in several ways. A sampling of data from the 2004 New England Air Quality Study shows the kind of analyses and information available. Examples include time–height cross sections, time series, profiles, and distributions of quantities such as winds and shear. These analyses show that there is strong spatial and temporal variability associated with the wind field in the marine boundary layer. Winds near the coast show diurnal variations, and frequent occurrences of low-level jets are evident, especially during nocturnal periods. Persistent patterns of spatial variability in the flow field that are due to coastal irregularities should be of particular concern for wind-energy planning, because they affect the representativeness of fixed-location measurements and imply that some areas would be favored for wind-energy production whereas others would not.
Abstract
Accurate measurement of wind speed profiles aloft in the marine boundary layer is a difficult challenge. The development of offshore wind energy requires accurate information on wind speeds above the surface at least at the levels occupied by turbine blades. Few measured data are available at these heights, and the temporal and spatial behavior of near-surface winds is often unrepresentative of that at the required heights. As a consequence, numerical model data, another potential source of information, are essentially unverified at these levels of the atmosphere. In this paper, a motion-compensated, high-resolution Doppler lidar–based wind measurement system that is capable of providing needed information on offshore winds at several heights is described. The system has been evaluated and verified in several ways. A sampling of data from the 2004 New England Air Quality Study shows the kind of analyses and information available. Examples include time–height cross sections, time series, profiles, and distributions of quantities such as winds and shear. These analyses show that there is strong spatial and temporal variability associated with the wind field in the marine boundary layer. Winds near the coast show diurnal variations, and frequent occurrences of low-level jets are evident, especially during nocturnal periods. Persistent patterns of spatial variability in the flow field that are due to coastal irregularities should be of particular concern for wind-energy planning, because they affect the representativeness of fixed-location measurements and imply that some areas would be favored for wind-energy production whereas others would not.
Addressing the need for high-quality wind information aloft in the layer occupied by turbine rotors (~30–150 m above ground level) is one of many significant challenges facing the wind energy industry. Without wind measurements at heights within the rotor sweep of the turbines, characteristics of the flow in this layer are unknown for wind energy and modeling purposes. Since flow in this layer is often decoupled from the surface, near-surface measurements are prone to errant extrapolation to these heights, and the behavior of the near-surface winds may not reflect that of the upper-level flow.
Addressing the need for high-quality wind information aloft in the layer occupied by turbine rotors (~30–150 m above ground level) is one of many significant challenges facing the wind energy industry. Without wind measurements at heights within the rotor sweep of the turbines, characteristics of the flow in this layer are unknown for wind energy and modeling purposes. Since flow in this layer is often decoupled from the surface, near-surface measurements are prone to errant extrapolation to these heights, and the behavior of the near-surface winds may not reflect that of the upper-level flow.
Abstract
The concept of boundary layer mixing height for meteorology and air quality applications using lidar data is reviewed, and new algorithms for estimation of mixing heights from various types of lower-tropospheric coherent Doppler lidar measurements are presented. Velocity variance profiles derived from Doppler lidar data demonstrate direct application to mixing height estimation, while other types of lidar profiles demonstrate relationships to the variance profiles and thus may also be used in the mixing height estimate. The algorithms are applied to ship-based, high-resolution Doppler lidar (HRDL) velocity and backscattered-signal measurements acquired on the R/V Ronald H. Brown during Texas Air Quality Study (TexAQS) 2006 to demonstrate the method and to produce mixing height estimates for that experiment. These combinations of Doppler lidar–derived velocity measurements have not previously been applied to analysis of boundary layer mixing height—over the water or elsewhere. A comparison of the results to those derived from ship-launched, balloon-radiosonde potential temperature and relative humidity profiles is presented.
Abstract
The concept of boundary layer mixing height for meteorology and air quality applications using lidar data is reviewed, and new algorithms for estimation of mixing heights from various types of lower-tropospheric coherent Doppler lidar measurements are presented. Velocity variance profiles derived from Doppler lidar data demonstrate direct application to mixing height estimation, while other types of lidar profiles demonstrate relationships to the variance profiles and thus may also be used in the mixing height estimate. The algorithms are applied to ship-based, high-resolution Doppler lidar (HRDL) velocity and backscattered-signal measurements acquired on the R/V Ronald H. Brown during Texas Air Quality Study (TexAQS) 2006 to demonstrate the method and to produce mixing height estimates for that experiment. These combinations of Doppler lidar–derived velocity measurements have not previously been applied to analysis of boundary layer mixing height—over the water or elsewhere. A comparison of the results to those derived from ship-launched, balloon-radiosonde potential temperature and relative humidity profiles is presented.
Abstract
The NOAA/WPL pulsed coherent Doppler lidar was used during the Texas Frontal Experiment in 1985 to study mesoscale preconvective atmospheric conditions. On 22 April 1985, the Doppler lidar, in conjunction with serial rawinsonde ascents and National Weather Service rawinsonde ascents, observed atmospheric features such as middle-tropospheric frontal and vertical wind shear layers and the planetary boundary layer. The lidar showed unique evidence of the downward transport of strong winds from an elevated vertical speed shear (frontal) layer into the planetary boundary layer. The lidar provided further evidence of atmospheric processes such as clear-air turbulence within frontal layers, and dry convection turbulence within the superadiabatic planetary boundary layer. As a result, high-technology remote sensing instruments such as the Doppler lidar show considerable promise for future studies of small-scale weather systems in a nonprecipitating atmosphere.
Abstract
The NOAA/WPL pulsed coherent Doppler lidar was used during the Texas Frontal Experiment in 1985 to study mesoscale preconvective atmospheric conditions. On 22 April 1985, the Doppler lidar, in conjunction with serial rawinsonde ascents and National Weather Service rawinsonde ascents, observed atmospheric features such as middle-tropospheric frontal and vertical wind shear layers and the planetary boundary layer. The lidar showed unique evidence of the downward transport of strong winds from an elevated vertical speed shear (frontal) layer into the planetary boundary layer. The lidar provided further evidence of atmospheric processes such as clear-air turbulence within frontal layers, and dry convection turbulence within the superadiabatic planetary boundary layer. As a result, high-technology remote sensing instruments such as the Doppler lidar show considerable promise for future studies of small-scale weather systems in a nonprecipitating atmosphere.
Abstract
Wind turbine wakes in the atmosphere are three-dimensional (3D) and time dependent. An important question is how best to measure atmospheric wake properties, both for characterizing these properties observationally and for verification of numerical, conceptual, and physical (e.g., wind tunnel) models of wakes. Here a scanning, pulsed, coherent Doppler lidar is used to sample a turbine wake using 3D volume scan patterns that envelop the wake and simultaneously measure the inflow profile. The volume data are analyzed for quantities of interest, such as peak velocity deficit, downwind variability of the deficit, and downwind extent of the wake, in a manner that preserves the measured data. For the case study presented here, in which the wake was well defined in the lidar data, peak deficits of up to 80% were measured 0.6–2 rotor diameters (D) downwind of the turbine, and the wakes extended more than 11D downwind. Temporal wake variability over periods of minutes and the effects of atmospheric gusts and lulls in the inflow are demonstrated in the analysis. Lidar scanning trade-offs important to ensuring that the wake quantities of interest are adequately sampled by the scan pattern, including scan coverage, number of scans per volume, data resolution, and scan-cycle repeat interval, are discussed.
Abstract
Wind turbine wakes in the atmosphere are three-dimensional (3D) and time dependent. An important question is how best to measure atmospheric wake properties, both for characterizing these properties observationally and for verification of numerical, conceptual, and physical (e.g., wind tunnel) models of wakes. Here a scanning, pulsed, coherent Doppler lidar is used to sample a turbine wake using 3D volume scan patterns that envelop the wake and simultaneously measure the inflow profile. The volume data are analyzed for quantities of interest, such as peak velocity deficit, downwind variability of the deficit, and downwind extent of the wake, in a manner that preserves the measured data. For the case study presented here, in which the wake was well defined in the lidar data, peak deficits of up to 80% were measured 0.6–2 rotor diameters (D) downwind of the turbine, and the wakes extended more than 11D downwind. Temporal wake variability over periods of minutes and the effects of atmospheric gusts and lulls in the inflow are demonstrated in the analysis. Lidar scanning trade-offs important to ensuring that the wake quantities of interest are adequately sampled by the scan pattern, including scan coverage, number of scans per volume, data resolution, and scan-cycle repeat interval, are discussed.
In 1992 the atmospheric lidar remote sensing groups of the National Aeronautics and Space Administration Marshall Space Flight Center, the National Oceanic and Atmospheric Administration/Environmental Technology Laboratory (NOAA/ETL), and the Jet Propulsion Laboratory began a joint collaboration to develop an airborne high-energy Doppler laser radar (lidar) system for atmospheric research and satellite validation and simulation studies. The result is the Multicenter Airborne Coherent Atmospheric Wind Sensor (MACAWS), which has the capability to remotely sense the distribution of wind and absolute aerosol backscatter in three-dimensional volumes in the troposphere and lower stratosphere.
A factor critical to the programmatic feasibility and technical success of this collaboration has been the utilization of existing components and expertise that were developed for previous atmospheric research by the respective institutions. For example, the laser transmitter is that of the mobile ground-based Doppler lidar system developed and used in atmospheric research for more than a decade at NOAA/ETL.
The motivation for MACAWS is threefold: 1) to obtain fundamental measurements of subsynoptic-scale processes and features to improve subgrid-scale parameterizations in large-scale models, 2) to obtain datasets in order to improve the understanding of and predictive capabilities for meteorological systems on subsynoptic scales, and 3) to validate (simulate) the performance of existing (planned) satellite-borne sensors.
Initial flight tests were made in September 1995; subsequent flights were made in June 1996 following system improvements. This paper describes the MACAWS instrument, principles of operation, examples of measurements over the eastern Pacific Ocean and western United States, and future applications.
In 1992 the atmospheric lidar remote sensing groups of the National Aeronautics and Space Administration Marshall Space Flight Center, the National Oceanic and Atmospheric Administration/Environmental Technology Laboratory (NOAA/ETL), and the Jet Propulsion Laboratory began a joint collaboration to develop an airborne high-energy Doppler laser radar (lidar) system for atmospheric research and satellite validation and simulation studies. The result is the Multicenter Airborne Coherent Atmospheric Wind Sensor (MACAWS), which has the capability to remotely sense the distribution of wind and absolute aerosol backscatter in three-dimensional volumes in the troposphere and lower stratosphere.
A factor critical to the programmatic feasibility and technical success of this collaboration has been the utilization of existing components and expertise that were developed for previous atmospheric research by the respective institutions. For example, the laser transmitter is that of the mobile ground-based Doppler lidar system developed and used in atmospheric research for more than a decade at NOAA/ETL.
The motivation for MACAWS is threefold: 1) to obtain fundamental measurements of subsynoptic-scale processes and features to improve subgrid-scale parameterizations in large-scale models, 2) to obtain datasets in order to improve the understanding of and predictive capabilities for meteorological systems on subsynoptic scales, and 3) to validate (simulate) the performance of existing (planned) satellite-borne sensors.
Initial flight tests were made in September 1995; subsequent flights were made in June 1996 following system improvements. This paper describes the MACAWS instrument, principles of operation, examples of measurements over the eastern Pacific Ocean and western United States, and future applications.
Abstract
To advance the understanding of meteorological processes in offshore coastal regions, the spatial variability of wind profiles must be characterized and uncertainties (errors) in NWP model wind forecasts quantified. These gaps are especially critical for the new offshore wind energy industry, where wind profile measurements in the marine atmospheric layer spanned by wind turbine rotor blades, generally 50–200 m above mean sea level (MSL), have been largely unavailable. Here, high-quality wind profile measurements were available every 15 min from the National Oceanic and Atmospheric Administration/Earth System Research Laboratory (NOAA/ESRL)’s high-resolution Doppler lidar (HRDL) during a monthlong research cruise in the Gulf of Maine for the 2004 New England Air Quality Study. These measurements were compared with retrospective NWP model wind forecasts over the area using two NOAA forecast-modeling systems [North American Mesoscale Forecast System (NAM) and Rapid Refresh (RAP)]. HRDL profile measurements quantified model errors, including their dependence on height above sea level, diurnal cycle, and forecast lead time. Typical model wind speed errors were ∼2.5 m s−1, and vector-wind errors were ∼4 m s−1. Short-term forecast errors were larger near the surface—30% larger below 100 m than above and largest for several hours after local midnight (biased low). Longer-term, 12-h forecasts had the largest errors after local sunset (biased high). At more than 3-h lead times, predictions from finer-resolution models exhibited larger errors. Horizontal variability of winds, measured as the ship traversed the Gulf of Maine, was significant and raised questions about whether modeled fields, which appeared smooth in comparison, were capturing this variability. If not, horizontal arrays of high-quality, vertical-profiling devices will be required for wind energy resource assessment offshore. Such measurement arrays are also needed to improve NWP models.
Abstract
To advance the understanding of meteorological processes in offshore coastal regions, the spatial variability of wind profiles must be characterized and uncertainties (errors) in NWP model wind forecasts quantified. These gaps are especially critical for the new offshore wind energy industry, where wind profile measurements in the marine atmospheric layer spanned by wind turbine rotor blades, generally 50–200 m above mean sea level (MSL), have been largely unavailable. Here, high-quality wind profile measurements were available every 15 min from the National Oceanic and Atmospheric Administration/Earth System Research Laboratory (NOAA/ESRL)’s high-resolution Doppler lidar (HRDL) during a monthlong research cruise in the Gulf of Maine for the 2004 New England Air Quality Study. These measurements were compared with retrospective NWP model wind forecasts over the area using two NOAA forecast-modeling systems [North American Mesoscale Forecast System (NAM) and Rapid Refresh (RAP)]. HRDL profile measurements quantified model errors, including their dependence on height above sea level, diurnal cycle, and forecast lead time. Typical model wind speed errors were ∼2.5 m s−1, and vector-wind errors were ∼4 m s−1. Short-term forecast errors were larger near the surface—30% larger below 100 m than above and largest for several hours after local midnight (biased low). Longer-term, 12-h forecasts had the largest errors after local sunset (biased high). At more than 3-h lead times, predictions from finer-resolution models exhibited larger errors. Horizontal variability of winds, measured as the ship traversed the Gulf of Maine, was significant and raised questions about whether modeled fields, which appeared smooth in comparison, were capturing this variability. If not, horizontal arrays of high-quality, vertical-profiling devices will be required for wind energy resource assessment offshore. Such measurement arrays are also needed to improve NWP models.
The deployment of a space-based Doppler lidar would provide information that is fundamental to advancing the understanding and prediction of weather and climate.
This paper reviews the concepts of wind measurement by Doppler lidar, highlights the results of some observing system simulation experiments with lidar winds, and discusses the important advances in earth system science anticipated with lidar winds.
Observing system simulation experiments, conducted using two different general circulation models, have shown 1) that there is a significant improvement in the forecast accuracy over the Southern Hemisphere and tropical oceans resulting from the assimilation of simulated satellite wind data, and 2) that wind data are significantly more effective than temperature or moisture data in controlling analysis error. Because accurate wind observations are currently almost entirely unavailable for the vast majority of tropical cyclones worldwide, lidar winds have the potential to substantially improve tropical cyclone forecasts. Similarly, to improve water vapor flux divergence calculations, a direct measure of the ageostrophic wind is needed since the present level of uncertainty cannot be reduced with better temperature and moisture soundings alone.
The deployment of a space-based Doppler lidar would provide information that is fundamental to advancing the understanding and prediction of weather and climate.
This paper reviews the concepts of wind measurement by Doppler lidar, highlights the results of some observing system simulation experiments with lidar winds, and discusses the important advances in earth system science anticipated with lidar winds.
Observing system simulation experiments, conducted using two different general circulation models, have shown 1) that there is a significant improvement in the forecast accuracy over the Southern Hemisphere and tropical oceans resulting from the assimilation of simulated satellite wind data, and 2) that wind data are significantly more effective than temperature or moisture data in controlling analysis error. Because accurate wind observations are currently almost entirely unavailable for the vast majority of tropical cyclones worldwide, lidar winds have the potential to substantially improve tropical cyclone forecasts. Similarly, to improve water vapor flux divergence calculations, a direct measure of the ageostrophic wind is needed since the present level of uncertainty cannot be reduced with better temperature and moisture soundings alone.
