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Abstract
Airborne tracer simulations are typically performed using a dispersion model driven by a high-resolution meteorological model. Besides solving the dynamic equations of momentum, heat, and moisture on the resolved model grid, mesoscale models must account for subgrid-scale fluxes and other unresolved processes. These are estimated through parameterization schemes of eddy diffusion, convection, and surface interactions, and they make use of prescribed parameters set by the user. Such “free” model parameters are often poorly constrained, and a range of plausible values exists for each. Evolutionary programming (EP) is a process to improve the selection of the parameters. A population of simulations is first run with a different set of parameter values for each member, and the member judged most accurate is selected as the “parent” of a new “generation.” After a number of iterations, the simulations should approach a configuration that is best adapted to the atmospheric conditions. We apply the EP process to simulate the first release of the 1994 European Tracer Experiment (ETEX) project, which comprised two experiments in which a tracer was released in western France and sampled by an observing network. The EP process is used to improve a simulation of the RAMS mesoscale weather model, with weather data collected during ETEX being used to “score” the individual members according to how well each simulation matches the observations. The meteorological simulations from before and after application of the EP process are each used to force a dispersion model to create a simulation of the ETEX release, and substantial improvement is observed when these are validated against sampled tracer concentrations.
Abstract
Airborne tracer simulations are typically performed using a dispersion model driven by a high-resolution meteorological model. Besides solving the dynamic equations of momentum, heat, and moisture on the resolved model grid, mesoscale models must account for subgrid-scale fluxes and other unresolved processes. These are estimated through parameterization schemes of eddy diffusion, convection, and surface interactions, and they make use of prescribed parameters set by the user. Such “free” model parameters are often poorly constrained, and a range of plausible values exists for each. Evolutionary programming (EP) is a process to improve the selection of the parameters. A population of simulations is first run with a different set of parameter values for each member, and the member judged most accurate is selected as the “parent” of a new “generation.” After a number of iterations, the simulations should approach a configuration that is best adapted to the atmospheric conditions. We apply the EP process to simulate the first release of the 1994 European Tracer Experiment (ETEX) project, which comprised two experiments in which a tracer was released in western France and sampled by an observing network. The EP process is used to improve a simulation of the RAMS mesoscale weather model, with weather data collected during ETEX being used to “score” the individual members according to how well each simulation matches the observations. The meteorological simulations from before and after application of the EP process are each used to force a dispersion model to create a simulation of the ETEX release, and substantial improvement is observed when these are validated against sampled tracer concentrations.
Abstract
Water vapor radiometer (WVR) retrieval algorithms require a priori information on atmospheric conditions along the line of sight of the radiometer in order to derive opacities from observed brightness temperatures. This paper's focus is the mean radiating temperature of the atmosphere (T mr), which is utilized in these algorithms to relate WVR measurements to integrated water vapor. Current methods for specifying T mr rely on the climatology of the WVR site-for example, a seasonal average-or information from nearby soundings to specify T mr. However, values of T mr, calculated from radiosonde data, not only vary according to site and season but also exhibit large fluctuations in response to local weather conditions. By utilizing output from numerical weather prediction (NWP) models, T mr can be accurately prescribed for an arbitrary WVR site at a specific time. Temporal variations in local weather conditions can he resolved by NWP models on timescales shorter than standard radiosonde soundings.
Currently used methods for obtaining T mr are reviewed. Values of T mr obtained from current methods and this new approach are compared to those obtained from in situ radiosonde soundings. The improvement of the T mr calculation using available model forecast data rather than climatological values yields a corresponding improvement of comparable magnitude in the retrieval of atmospheric opacity. Use of forecast model data relieves a WVR site of its dependency on local climatology or the necessity of a nearby sounding, allowing more accurate retrieval of observed conditions and increased flexibility in choosing site location. Furthermore, it is found that the calculation of precipitable water by means of atmospheric opacities does not require time-dependent tuning parameters when model data are used. These results were obtained using an archived subset of the full nested grid model output. The added horizontal and vertical resolution of operational data should further improve this approach.
Abstract
Water vapor radiometer (WVR) retrieval algorithms require a priori information on atmospheric conditions along the line of sight of the radiometer in order to derive opacities from observed brightness temperatures. This paper's focus is the mean radiating temperature of the atmosphere (T mr), which is utilized in these algorithms to relate WVR measurements to integrated water vapor. Current methods for specifying T mr rely on the climatology of the WVR site-for example, a seasonal average-or information from nearby soundings to specify T mr. However, values of T mr, calculated from radiosonde data, not only vary according to site and season but also exhibit large fluctuations in response to local weather conditions. By utilizing output from numerical weather prediction (NWP) models, T mr can be accurately prescribed for an arbitrary WVR site at a specific time. Temporal variations in local weather conditions can he resolved by NWP models on timescales shorter than standard radiosonde soundings.
Currently used methods for obtaining T mr are reviewed. Values of T mr obtained from current methods and this new approach are compared to those obtained from in situ radiosonde soundings. The improvement of the T mr calculation using available model forecast data rather than climatological values yields a corresponding improvement of comparable magnitude in the retrieval of atmospheric opacity. Use of forecast model data relieves a WVR site of its dependency on local climatology or the necessity of a nearby sounding, allowing more accurate retrieval of observed conditions and increased flexibility in choosing site location. Furthermore, it is found that the calculation of precipitable water by means of atmospheric opacities does not require time-dependent tuning parameters when model data are used. These results were obtained using an archived subset of the full nested grid model output. The added horizontal and vertical resolution of operational data should further improve this approach.
Abstract
Emerging networks of Global Positioning System (GPS) receivers can be used in the remote sensing of atmospheric water vapor. The time-varying zenith wet delay observed at each GPS receiver in a network can be transformed into an estimate of the precipitable water overlying that receiver. This transformation is achieved by multiplying the zenith wet delay by a factor whose magnitude is a function of certain constants related to the refractivity of moist air and of the weighted mean temperature of the atmosphere. The mean temperature varies in space and time and must be estimated a priori in order to transform an observed zenith wet delay into an estimate of precipitable water. We show that the relative error introduced during this transformation closely approximates the relative error in the predicted mean temperature. Numerical weather models can be used to predict the mean temperature with an rms relative error of less than 1%.
Abstract
Emerging networks of Global Positioning System (GPS) receivers can be used in the remote sensing of atmospheric water vapor. The time-varying zenith wet delay observed at each GPS receiver in a network can be transformed into an estimate of the precipitable water overlying that receiver. This transformation is achieved by multiplying the zenith wet delay by a factor whose magnitude is a function of certain constants related to the refractivity of moist air and of the weighted mean temperature of the atmosphere. The mean temperature varies in space and time and must be estimated a priori in order to transform an observed zenith wet delay into an estimate of precipitable water. We show that the relative error introduced during this transformation closely approximates the relative error in the predicted mean temperature. Numerical weather models can be used to predict the mean temperature with an rms relative error of less than 1%.
This paper provides an overview of applications of the Global Positioning System (GPS) for active measurement of the Earth's atmosphere. Microwave radio signals transmitted by GPS satellites are delayed (refracted) by the atmosphere as they propagate to Earth-based GPS receivers or GPS receivers carried on low Earth orbit satellites.
The delay in GPS signals reaching Earth-based receivers due to the presence of water vapor is nearly proportional to the quantity of water vapor integrated along the signal path. Measurement of atmospheric water vapor by Earth-based GPS receivers was demonstrated during the GPS/STORM field project to be comparable and in some respects superior to measurements by ground-based water vapor radiometers. Increased spatial and temporal resolution of the water vapor distribution provided by the GPS/STORM network proved useful in monitoring the moisture-flux convergence along a dryline and the decrease in integrated water vapor associated with the passage of a midtropospheric cold front, both of which triggered severe weather over the area during the course of the experiment.
Given the rapid growth in regional networks of continuously operating Earth-based GPS receivers currently being implemented, an opportunity exists to observe the distribution of water vapor with increased spatial and temporal coverage, which could prove valuable in a range of operational and research applications in the atmospheric sciences.
The first space-based GPS receiver designed for sensing the Earth's atmosphere was launched in April 1995. Phase measurements of GPS signals as they are occluded by the atmosphere provide refractivity profiles (see the companion article by Ware et al. on page 19 of this issue). Water vapor limits the accuracy of temperature recovery below the tropopause because of uncertainty in the water vapor distribution. The sensitivity of atmospheric refractivity to water vapor pressure, however, means that refractivity profiles can in principle yield information on the atmospheric humidity distribution given independent information on the temperature and pressure distribution from NWP models or independent observational data.
A discussion is provided of some of the research opportunities that exist to capitalize on the complementary nature of the methods of active atmospheric monitoring by GPS and other observation systems for use in weather and climate studies and in numerical weather prediction models.
This paper provides an overview of applications of the Global Positioning System (GPS) for active measurement of the Earth's atmosphere. Microwave radio signals transmitted by GPS satellites are delayed (refracted) by the atmosphere as they propagate to Earth-based GPS receivers or GPS receivers carried on low Earth orbit satellites.
The delay in GPS signals reaching Earth-based receivers due to the presence of water vapor is nearly proportional to the quantity of water vapor integrated along the signal path. Measurement of atmospheric water vapor by Earth-based GPS receivers was demonstrated during the GPS/STORM field project to be comparable and in some respects superior to measurements by ground-based water vapor radiometers. Increased spatial and temporal resolution of the water vapor distribution provided by the GPS/STORM network proved useful in monitoring the moisture-flux convergence along a dryline and the decrease in integrated water vapor associated with the passage of a midtropospheric cold front, both of which triggered severe weather over the area during the course of the experiment.
Given the rapid growth in regional networks of continuously operating Earth-based GPS receivers currently being implemented, an opportunity exists to observe the distribution of water vapor with increased spatial and temporal coverage, which could prove valuable in a range of operational and research applications in the atmospheric sciences.
The first space-based GPS receiver designed for sensing the Earth's atmosphere was launched in April 1995. Phase measurements of GPS signals as they are occluded by the atmosphere provide refractivity profiles (see the companion article by Ware et al. on page 19 of this issue). Water vapor limits the accuracy of temperature recovery below the tropopause because of uncertainty in the water vapor distribution. The sensitivity of atmospheric refractivity to water vapor pressure, however, means that refractivity profiles can in principle yield information on the atmospheric humidity distribution given independent information on the temperature and pressure distribution from NWP models or independent observational data.
A discussion is provided of some of the research opportunities that exist to capitalize on the complementary nature of the methods of active atmospheric monitoring by GPS and other observation systems for use in weather and climate studies and in numerical weather prediction models.
Abstract
Turbulence and winds below 328 m were measured on 5 successive nights in a program to study tracer transport in the nocturnal boundary layer at a site with moderately complex terrain and mixed land use. The instruments included sonic anemometers and CO2/H2O analyzers at four levels on a 328 m tall tower, a minisodar/RASS system, a midrange sodar, a ceilometer, and an array of 61 m towers. Preliminary simulations indicated satisfactory perfluorocarbon mixing to 68 m but insufficient transport to the 328 m level on both weakly stable and stable nights, possibly due to insufficient turbulence kinetic energy and/or small vertical mixing lengths, or the presence of meso-β fronts, e.g., sea-breeze fronts, that could transport trace chemicals efficiently to 328 m. To examine the problem further, time–height distributions of turbulence kinetic energy (TKE), mixing length, Richardson number, potential temperature, and winds were derived from the observations of mean winds and temperature and the TKE budget equation, interpolated to fit the observations, under the flux/gradient and z-less scaling assumptions, and displayed with aerosol profiles. The results indicated higher and more variable levels of TKE and mixing lengths above a typical turbulence maximum at 30–50 m. Oscillations with periods of ∼2 h were common and occasional meso-β fronts and shear zones between 75 and 150 m were seen, which increased TKE aloft and in some cases led to a poorly defined boundary layer top.
Significance Statement
The atmosphere’s boundary layer is the interface between the free atmosphere and natural and human activity near Earth’s surface. The daytime boundary layer has been studied extensively and, because of vigorous sun-driven mixing, is well understood and readily parameterized in forecast and global climate models. In contrast, the nocturnal boundary layer is less well understood or predictable because turbulence is weak and tends to decouple it from the surface and the free atmosphere above. This paper focuses on the least-studied upper part of the nocturnal boundary layer over the southeastern United States where topography and land–sea contrast affect winds, turbulence, and chemical transport.
Abstract
Turbulence and winds below 328 m were measured on 5 successive nights in a program to study tracer transport in the nocturnal boundary layer at a site with moderately complex terrain and mixed land use. The instruments included sonic anemometers and CO2/H2O analyzers at four levels on a 328 m tall tower, a minisodar/RASS system, a midrange sodar, a ceilometer, and an array of 61 m towers. Preliminary simulations indicated satisfactory perfluorocarbon mixing to 68 m but insufficient transport to the 328 m level on both weakly stable and stable nights, possibly due to insufficient turbulence kinetic energy and/or small vertical mixing lengths, or the presence of meso-β fronts, e.g., sea-breeze fronts, that could transport trace chemicals efficiently to 328 m. To examine the problem further, time–height distributions of turbulence kinetic energy (TKE), mixing length, Richardson number, potential temperature, and winds were derived from the observations of mean winds and temperature and the TKE budget equation, interpolated to fit the observations, under the flux/gradient and z-less scaling assumptions, and displayed with aerosol profiles. The results indicated higher and more variable levels of TKE and mixing lengths above a typical turbulence maximum at 30–50 m. Oscillations with periods of ∼2 h were common and occasional meso-β fronts and shear zones between 75 and 150 m were seen, which increased TKE aloft and in some cases led to a poorly defined boundary layer top.
Significance Statement
The atmosphere’s boundary layer is the interface between the free atmosphere and natural and human activity near Earth’s surface. The daytime boundary layer has been studied extensively and, because of vigorous sun-driven mixing, is well understood and readily parameterized in forecast and global climate models. In contrast, the nocturnal boundary layer is less well understood or predictable because turbulence is weak and tends to decouple it from the surface and the free atmosphere above. This paper focuses on the least-studied upper part of the nocturnal boundary layer over the southeastern United States where topography and land–sea contrast affect winds, turbulence, and chemical transport.
Abstract
A simple approach to estimating vertically integrated atmospheric water vapor, or precipitable water, from Global Positioning System (GPS) radio signals collected by a regional network of ground-based geodetic GPS receiver is illustrated and validated. Standard space geodetic methods are used to estimate the zenith delay caused by the neutral atmosphere, and surface pressure measurements are used to compute the hydrostatic (or “dry”) component of this delay. The zenith hydrostatic delay is subtracted from the zenith neutral delay to determine the zenith wet delay, which is then transformed into an estimate of precipitable water. By incorporating a few remote global tracking stations (and thus long baselines) into the geodetic analysis of a regional GPS network, it is possible to resolve the absolute (not merely the relative) value of the zenith neutral delay at each station in the augmented network. This approach eliminates any need for external comparisons with water vapor radiometer observations and delivers a pure GPS solution for precipitable water. Since the neutral delay is decomposed into its hydrostatic and wet components after the geodetic inversion, the geodetic analysis is not complicated by the fact that some GPS stations are equipped with barometers and some are not. This approach is taken to reduce observations collected in the field experiment GPS/STORM and recover precipitable water with an rms error of 1.0–1.5 mm.
Abstract
A simple approach to estimating vertically integrated atmospheric water vapor, or precipitable water, from Global Positioning System (GPS) radio signals collected by a regional network of ground-based geodetic GPS receiver is illustrated and validated. Standard space geodetic methods are used to estimate the zenith delay caused by the neutral atmosphere, and surface pressure measurements are used to compute the hydrostatic (or “dry”) component of this delay. The zenith hydrostatic delay is subtracted from the zenith neutral delay to determine the zenith wet delay, which is then transformed into an estimate of precipitable water. By incorporating a few remote global tracking stations (and thus long baselines) into the geodetic analysis of a regional GPS network, it is possible to resolve the absolute (not merely the relative) value of the zenith neutral delay at each station in the augmented network. This approach eliminates any need for external comparisons with water vapor radiometer observations and delivers a pure GPS solution for precipitable water. Since the neutral delay is decomposed into its hydrostatic and wet components after the geodetic inversion, the geodetic analysis is not complicated by the fact that some GPS stations are equipped with barometers and some are not. This approach is taken to reduce observations collected in the field experiment GPS/STORM and recover precipitable water with an rms error of 1.0–1.5 mm.
