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During September and October of 1984, the Wave Propagation Laboratory of NOAA used its pulsed infrared Doppler lidar in support of the U.S. Department of Energy's Atmospheric Studies in Complex Terrain (ASCOT) program. The lidar measured winds channeled within a narrow mountain valley on seven experiment nights, between 2300 and 1100 MST. We were able to quantitatively define the structure of the nocturnal drainage winds, monitor their decay in the morning, and sense the formation of a thermally driven up-valley flow later in the day.
During September and October of 1984, the Wave Propagation Laboratory of NOAA used its pulsed infrared Doppler lidar in support of the U.S. Department of Energy's Atmospheric Studies in Complex Terrain (ASCOT) program. The lidar measured winds channeled within a narrow mountain valley on seven experiment nights, between 2300 and 1100 MST. We were able to quantitatively define the structure of the nocturnal drainage winds, monitor their decay in the morning, and sense the formation of a thermally driven up-valley flow later in the day.
Abstract
Comparisons between measurements of a wind component by a Doppler lidar and by a conventional anemometer are presented. The two measurement techniques provided thirteen 15 min data sets which agreed within 0.04 m s−1 on the average. The maximum difference was 0.12 m s−1, which constitutes less than 3% discrepancy, referred to the period average. The results conclusively demonstrate the ability of Doppler lidar to measure winds with a high degree of velocity resolution and accuracy.
Abstract
Comparisons between measurements of a wind component by a Doppler lidar and by a conventional anemometer are presented. The two measurement techniques provided thirteen 15 min data sets which agreed within 0.04 m s−1 on the average. The maximum difference was 0.12 m s−1, which constitutes less than 3% discrepancy, referred to the period average. The results conclusively demonstrate the ability of Doppler lidar to measure winds with a high degree of velocity resolution and accuracy.
Abstract
After four growing seasons, soil below white oak trees exposed to elevated atmospheric carbon dioxide levels (ambient + 300 ppm) had an average of 14% more soil carbon than soil below trees exposed to ambient levels of carbon dioxide. The soil carbon inventories in five soil cores collected from ambient chambers and six soil cores collected from elevated chambers at the Global Change Field Research Site, Oak Ridge, Tennessee, were measured. The authors conclude that the increase in soil carbon was due to an increase in belowground soil carbon input, because aboveground litter inputs were excluded by experimental design. These findings are consistent with the hypothesis that elevated carbon dioxide levels are increasing the amount of carbon stored in soil.
Abstract
After four growing seasons, soil below white oak trees exposed to elevated atmospheric carbon dioxide levels (ambient + 300 ppm) had an average of 14% more soil carbon than soil below trees exposed to ambient levels of carbon dioxide. The soil carbon inventories in five soil cores collected from ambient chambers and six soil cores collected from elevated chambers at the Global Change Field Research Site, Oak Ridge, Tennessee, were measured. The authors conclude that the increase in soil carbon was due to an increase in belowground soil carbon input, because aboveground litter inputs were excluded by experimental design. These findings are consistent with the hypothesis that elevated carbon dioxide levels are increasing the amount of carbon stored in soil.
Abstract
Different methods have been used to obtain the daily rainfall time series required to drive conceptual rainfall–runoff models, depending on data availability, time constraints, and modeling objectives. This paper investigates the implications of different rainfall inputs on the calibration and simulation of 4 rainfall–runoff models using data from 240 catchments across southeast Australia. The first modeling experiment compares results from using a single lumped daily rainfall series for each catchment obtained from three methods: single rainfall station, Thiessen average, and average of interpolated rainfall surface. The results indicate considerable improvements in the modeled daily runoff and mean annual runoff in the model calibration and model simulation over an independent test period with better spatial representation of rainfall. The second experiment compares modeling using a single lumped daily rainfall series and modeling in all grid cells within a catchment using different rainfall inputs for each grid cell. The results show only marginal improvement in the “distributed” application compared to the single rainfall series, and only in two of the four models for the larger catchments. Where a single lumped catchment-average daily rainfall series is used, care should be taken to obtain a rainfall series that best represents the spatial rainfall distribution across the catchment. However, there is little advantage in driving a conceptual rainfall–runoff model with different rainfall inputs from different parts of the catchment compared to using a single lumped rainfall series, where only estimates of runoff at the catchment outlet is required.
Abstract
Different methods have been used to obtain the daily rainfall time series required to drive conceptual rainfall–runoff models, depending on data availability, time constraints, and modeling objectives. This paper investigates the implications of different rainfall inputs on the calibration and simulation of 4 rainfall–runoff models using data from 240 catchments across southeast Australia. The first modeling experiment compares results from using a single lumped daily rainfall series for each catchment obtained from three methods: single rainfall station, Thiessen average, and average of interpolated rainfall surface. The results indicate considerable improvements in the modeled daily runoff and mean annual runoff in the model calibration and model simulation over an independent test period with better spatial representation of rainfall. The second experiment compares modeling using a single lumped daily rainfall series and modeling in all grid cells within a catchment using different rainfall inputs for each grid cell. The results show only marginal improvement in the “distributed” application compared to the single rainfall series, and only in two of the four models for the larger catchments. Where a single lumped catchment-average daily rainfall series is used, care should be taken to obtain a rainfall series that best represents the spatial rainfall distribution across the catchment. However, there is little advantage in driving a conceptual rainfall–runoff model with different rainfall inputs from different parts of the catchment compared to using a single lumped rainfall series, where only estimates of runoff at the catchment outlet is required.
A new millimeter-wave cloud radar (MMCR) has been designed to provide detailed, long-term observations of nonprecipitating and weakly precipitating clouds at Cloud and Radiation Testbed (CART) sites of the Department of Energy's Atmospheric Radiation Measurement (ARM) program. Scientific requirements included excellent sensitivity and vertical resolution to detect weak and thin multiple layers of ice and liquid water clouds over the sites and long-term, unattended operations in remote locales. In response to these requirements, the innovative radar design features a vertically pointing, single-polarization, Doppler system operating at 35 GHz (Ka band). It uses a low-peak-power transmitter for long-term reliability and high-gain antenna and pulse-compressed waveforms to maximize sensitivity and resolution. The radar uses the same kind of signal processor as that used in commercial wind profilers. The first MMCR began operations at the CART in northern Oklahoma in late 1996 and has operated continuously there for thousands of hours. It routinely provides remarkably detailed images of the ever-changing cloud structure and kinematics over this densely instrumented site. Examples of the data are presented. The radar measurements will greatly improve quantitative documentation of cloud conditions over the CART sites and will bolster ARM research to understand how clouds impact climate through their effects on radiative transfer. Millimeter-wave radars such as the MMCR also have potential applications in the fields of aviation weather, weather modification, and basic cloud physics research.
A new millimeter-wave cloud radar (MMCR) has been designed to provide detailed, long-term observations of nonprecipitating and weakly precipitating clouds at Cloud and Radiation Testbed (CART) sites of the Department of Energy's Atmospheric Radiation Measurement (ARM) program. Scientific requirements included excellent sensitivity and vertical resolution to detect weak and thin multiple layers of ice and liquid water clouds over the sites and long-term, unattended operations in remote locales. In response to these requirements, the innovative radar design features a vertically pointing, single-polarization, Doppler system operating at 35 GHz (Ka band). It uses a low-peak-power transmitter for long-term reliability and high-gain antenna and pulse-compressed waveforms to maximize sensitivity and resolution. The radar uses the same kind of signal processor as that used in commercial wind profilers. The first MMCR began operations at the CART in northern Oklahoma in late 1996 and has operated continuously there for thousands of hours. It routinely provides remarkably detailed images of the ever-changing cloud structure and kinematics over this densely instrumented site. Examples of the data are presented. The radar measurements will greatly improve quantitative documentation of cloud conditions over the CART sites and will bolster ARM research to understand how clouds impact climate through their effects on radiative transfer. Millimeter-wave radars such as the MMCR also have potential applications in the fields of aviation weather, weather modification, and basic cloud physics research.
Abstract
The high-resolution Doppler lidar (HRDL) was developed to provide higher spatial, temporal, and velocity resolution and more reliable performance than was previously obtainable with CO2-laser-based technology. The improved performance is needed to support continued advancement of boundary layer simulation models and to facilitate high-resolution turbulent flux measurements. HRDL combines a unique, eye-safe, near-IR-wavelength, solid-state laser transmitter with advanced signal processing and a high-speed scanner to achieve 30-m range resolution and a velocity precision of ∼10 cm s−1 under a variety of marine and continental boundary layer conditions, depending on atmospheric and operating conditions. An attitude-compensating scanner has been developed to facilitate shipboard marine boundary layer observations. Vertical velocities, fine details of the wind profile near the surface, turbulence kinetic energy profiles, and momentum flux are measurable with HRDL. The system is also useful for cloud studies. The HRDL technology, capabilities, and field performance are discussed.
Abstract
The high-resolution Doppler lidar (HRDL) was developed to provide higher spatial, temporal, and velocity resolution and more reliable performance than was previously obtainable with CO2-laser-based technology. The improved performance is needed to support continued advancement of boundary layer simulation models and to facilitate high-resolution turbulent flux measurements. HRDL combines a unique, eye-safe, near-IR-wavelength, solid-state laser transmitter with advanced signal processing and a high-speed scanner to achieve 30-m range resolution and a velocity precision of ∼10 cm s−1 under a variety of marine and continental boundary layer conditions, depending on atmospheric and operating conditions. An attitude-compensating scanner has been developed to facilitate shipboard marine boundary layer observations. Vertical velocities, fine details of the wind profile near the surface, turbulence kinetic energy profiles, and momentum flux are measurable with HRDL. The system is also useful for cloud studies. The HRDL technology, capabilities, and field performance are discussed.
Abstract
To demonstrate the usefulness of active remote-sensing systems in observing forest fire plume behavior, we studied two fires, one using a 3.2-cm-wavelength Doppler radar, and one more extensively, using Doppler lidar. Both instruments observed the kinematics of the convection column, including the presence of two different types of rotation in the columns, and monitored the behavior of the smoke plume.
The first fire, a forest fire that burned out of control, was observed by the Doppler radar during late-morning and afternoon hours. Strong horizontal ambient winds produced a bent-over convection column, which the radar observed to have strong horizontal flow at its edges and weaker flow along the centerline of the plume. This velocity pattern implies that the column consisted of a pair of counterrotating horizontal vortices (rolls), with rising motion along the centerline and sinking along the edges. The radar tracked the smoke plume for over 30 km. It also provided circular depolarization ratio measurements, which gave information that the scattering particles were mostly flat or needle shaped as viewed by the radar, perhaps pine needles or possibly flat ash platelets being viewed edge on.
The second fire, observed over a 5-h period by Doppler lidar, was a prescribed forest fire ignited in the afternoon. During the first hour of the fire the lidar observed many kinematic quantities of the convection column, including flow convergence and anticyclonic whole-column, rotation of the nearly vertical column, with a vorticity of approximately 10−2 s−1 and an estimated peak vertical velocity w of 1 5 m s−1. After the first hour ambient meteorological conditions changed, the whole-column rotation ceased, and the convection column and smoke plume bent over toward the lidar in stronger horizontal flow. At two times during this later stage, w was estimated to be 24 and 10 m s−1. Lidar observations show that the smoke plume of this second fire initially went straight up in the convection column to heights of over 2 km, so most of the smoke was injected into the atmosphere above the unstable, afternoon, convective boundary layer, or mixed layer. Later, as the horizontal winds increased, a larger friction of the smoke remained in the mixed layer. Finally, very late in the afternoon, after ignitions had ceased and the fire was smoldering, almost all of the smoke remained within the mixed layer.
These analyses show that lidar and radar can provide valuable three-dimensional datasets on kinematic quantities and smoke distribution in the vicinity of fires. This kind of information should be of great value in understanding and modeling convection-column dynamics and smoke-plume behavior.
Abstract
To demonstrate the usefulness of active remote-sensing systems in observing forest fire plume behavior, we studied two fires, one using a 3.2-cm-wavelength Doppler radar, and one more extensively, using Doppler lidar. Both instruments observed the kinematics of the convection column, including the presence of two different types of rotation in the columns, and monitored the behavior of the smoke plume.
The first fire, a forest fire that burned out of control, was observed by the Doppler radar during late-morning and afternoon hours. Strong horizontal ambient winds produced a bent-over convection column, which the radar observed to have strong horizontal flow at its edges and weaker flow along the centerline of the plume. This velocity pattern implies that the column consisted of a pair of counterrotating horizontal vortices (rolls), with rising motion along the centerline and sinking along the edges. The radar tracked the smoke plume for over 30 km. It also provided circular depolarization ratio measurements, which gave information that the scattering particles were mostly flat or needle shaped as viewed by the radar, perhaps pine needles or possibly flat ash platelets being viewed edge on.
The second fire, observed over a 5-h period by Doppler lidar, was a prescribed forest fire ignited in the afternoon. During the first hour of the fire the lidar observed many kinematic quantities of the convection column, including flow convergence and anticyclonic whole-column, rotation of the nearly vertical column, with a vorticity of approximately 10−2 s−1 and an estimated peak vertical velocity w of 1 5 m s−1. After the first hour ambient meteorological conditions changed, the whole-column rotation ceased, and the convection column and smoke plume bent over toward the lidar in stronger horizontal flow. At two times during this later stage, w was estimated to be 24 and 10 m s−1. Lidar observations show that the smoke plume of this second fire initially went straight up in the convection column to heights of over 2 km, so most of the smoke was injected into the atmosphere above the unstable, afternoon, convective boundary layer, or mixed layer. Later, as the horizontal winds increased, a larger friction of the smoke remained in the mixed layer. Finally, very late in the afternoon, after ignitions had ceased and the fire was smoldering, almost all of the smoke remained within the mixed layer.
These analyses show that lidar and radar can provide valuable three-dimensional datasets on kinematic quantities and smoke distribution in the vicinity of fires. This kind of information should be of great value in understanding and modeling convection-column dynamics and smoke-plume behavior.
Abstract
The design, construction, and first results are presented of a 915-MHz Doppler wind profiler that may be mounted on a moving platform such as a mobile land vehicle, ocean buoy, or a ship. The long dwell times in multiple beam directions, required for the detection of weak atmospheric radar echoes, are obtained by a passive phased array antenna, controlled by a motion control and monitoring (MCM) computer that acquires platform motion measurements and compensates in real time for the platform rotations. The platform translational velocities are accounted for in the signal processing system (SPS) before the calculation of the wind velocity profiles. The phased array antenna, MCM, and SPS are described, and radar-derived wind profiles are compared with those from rawinsonde balloons released during the first test cruise of the system, as the NOAA R/V Ronald H. Brown performed ship maneuvers.
Abstract
The design, construction, and first results are presented of a 915-MHz Doppler wind profiler that may be mounted on a moving platform such as a mobile land vehicle, ocean buoy, or a ship. The long dwell times in multiple beam directions, required for the detection of weak atmospheric radar echoes, are obtained by a passive phased array antenna, controlled by a motion control and monitoring (MCM) computer that acquires platform motion measurements and compensates in real time for the platform rotations. The platform translational velocities are accounted for in the signal processing system (SPS) before the calculation of the wind velocity profiles. The phased array antenna, MCM, and SPS are described, and radar-derived wind profiles are compared with those from rawinsonde balloons released during the first test cruise of the system, as the NOAA R/V Ronald H. Brown performed ship maneuvers.
Twelve national research organizations joined forces on a 30-day, 6800 n mi survey of the Central and Tropical Western Pacific on NOAA's Research Vessel Discoverer. The Combined Sensor Program (CSP), which began in American Samoa on 14 March 1996, visited Manus Island, Papua New Guinea, and ended in Hawaii on 13 April, used a unique combination of in situ, satellite, and remote sensors to better understand relationships between atmospheric and oceanic variables that affect radiative balance in this climatically important region. Besides continuously measuring both shortwave and longwave radiative fluxes, CSP instruments also measured most other factors affecting the radiative balance, including profiles of clouds (lidar and radar), aerosols (in situ and lidar), moisture (balloons, lidar, and radiometers), and sea surface temperature (thermometers and Fourier Transform Infrared Radiometers). Surface fluxes of heat, momentum, and moisture were also measured continuously. The Department of Energy's Atmospheric Radiation Measurement Program used the mission to validate similar measurements made at their CART site on Manus Island and to investigate the effect (if any) of large nearby landmasses on the island-based measurements.
Twelve national research organizations joined forces on a 30-day, 6800 n mi survey of the Central and Tropical Western Pacific on NOAA's Research Vessel Discoverer. The Combined Sensor Program (CSP), which began in American Samoa on 14 March 1996, visited Manus Island, Papua New Guinea, and ended in Hawaii on 13 April, used a unique combination of in situ, satellite, and remote sensors to better understand relationships between atmospheric and oceanic variables that affect radiative balance in this climatically important region. Besides continuously measuring both shortwave and longwave radiative fluxes, CSP instruments also measured most other factors affecting the radiative balance, including profiles of clouds (lidar and radar), aerosols (in situ and lidar), moisture (balloons, lidar, and radiometers), and sea surface temperature (thermometers and Fourier Transform Infrared Radiometers). Surface fluxes of heat, momentum, and moisture were also measured continuously. The Department of Energy's Atmospheric Radiation Measurement Program used the mission to validate similar measurements made at their CART site on Manus Island and to investigate the effect (if any) of large nearby landmasses on the island-based measurements.
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.
