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- Author or Editor: Paul C. Liu x
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Abstract
An empirical spectral equation for fetch-limited deep-water wind waveswas derived by applying similarity analysis to wind and wave data recorded at the Lake Michigan Research Tower near Muskegon, Mich., during the autumn of 1967. The field data indicates that both the equilibrium range coefficient, β in S(ω) = βg 2ω−5 and the dimensionless peak-frequency parameter, ω m U */g, vary with Fo, where Fo = gF/U * 2 is the dimensionless fetch parameter with respect to fetch F and friction velocity U *. The equation produces reasonably good results in estimating actual wave spectra, provided sufficient duration is achieved in the wind field. The equation also indicates that a fully-developed state will not be reached at a steady wind speed as the very low-frequency waves grow continuously with increasing fetch.
Abstract
An empirical spectral equation for fetch-limited deep-water wind waveswas derived by applying similarity analysis to wind and wave data recorded at the Lake Michigan Research Tower near Muskegon, Mich., during the autumn of 1967. The field data indicates that both the equilibrium range coefficient, β in S(ω) = βg 2ω−5 and the dimensionless peak-frequency parameter, ω m U */g, vary with Fo, where Fo = gF/U * 2 is the dimensionless fetch parameter with respect to fetch F and friction velocity U *. The equation produces reasonably good results in estimating actual wave spectra, provided sufficient duration is achieved in the wind field. The equation also indicates that a fully-developed state will not be reached at a steady wind speed as the very low-frequency waves grow continuously with increasing fetch.
Abstract
This paper presents the results of a joint program combining airborne laser profilometer and Waverider buoy measurements of synoptic wave conditions in Lake Michigan during the passage of an intense cold front. Measurements were made both before and after passage of the front under different atmospheric stabilities. The results demonstrate the distinctive role stability plays in wave growth processes. Specifically, it is evident that the wind speed and fetch distance required to generate the same wave conditions are less for an unstable atmosphere than for a stable atmosphere. Therefore, an unstable atmosphere is usually accompanied by higher waves for the same 10 m winds. Fetch-limited wave growth is seen to follow stable or unstable quasi-equilibrium relations between corresponding wave-energy and peak-energy frequency parameters. Synoptic wave height maps for Lake Michigan have been prepared from the measured data.
Abstract
This paper presents the results of a joint program combining airborne laser profilometer and Waverider buoy measurements of synoptic wave conditions in Lake Michigan during the passage of an intense cold front. Measurements were made both before and after passage of the front under different atmospheric stabilities. The results demonstrate the distinctive role stability plays in wave growth processes. Specifically, it is evident that the wind speed and fetch distance required to generate the same wave conditions are less for an unstable atmosphere than for a stable atmosphere. Therefore, an unstable atmosphere is usually accompanied by higher waves for the same 10 m winds. Fetch-limited wave growth is seen to follow stable or unstable quasi-equilibrium relations between corresponding wave-energy and peak-energy frequency parameters. Synoptic wave height maps for Lake Michigan have been prepared from the measured data.
Abstract
The recently advanced approach of wavelet transforms is applied to the analysis of ocean currents. The conventional analyses of time series in the frequency domain can be readily generalized to the frequency.and time domain using wavelet transforms. An application of wavelet analysis to a set of observed current data acquired during the spring of 1991 in Lake Michigan shows some significant time-localized characteristics that would not be detected using the traditional Fourier transform approach.
Abstract
The recently advanced approach of wavelet transforms is applied to the analysis of ocean currents. The conventional analyses of time series in the frequency domain can be readily generalized to the frequency.and time domain using wavelet transforms. An application of wavelet analysis to a set of observed current data acquired during the spring of 1991 in Lake Michigan shows some significant time-localized characteristics that would not be detected using the traditional Fourier transform approach.
Abstract
We compare results from a simple parametric, dynamical, deep-water wave prediction model with two sets of measured wave height maps of Lake Michigan. The measurements were made with an airborne laser altimeter under two distinctly different wind fields during November 1977. The results show that the model predicted almost all of the synoptic features. Both the magnitude and the general pattern of the predicted wave-height contours compared well with the measurements. The model also predicts the direction for wave propagation in conjunction with the wave height map, which is useful for practical ship routing and can be significantly different form the prevailing wind direction.
Abstract
We compare results from a simple parametric, dynamical, deep-water wave prediction model with two sets of measured wave height maps of Lake Michigan. The measurements were made with an airborne laser altimeter under two distinctly different wind fields during November 1977. The results show that the model predicted almost all of the synoptic features. Both the magnitude and the general pattern of the predicted wave-height contours compared well with the measurements. The model also predicts the direction for wave propagation in conjunction with the wave height map, which is useful for practical ship routing and can be significantly different form the prevailing wind direction.
Abstract
The Cirrus Parcel Model Comparison Project, a project of the GCSS [Global Energy and Water Cycle Experiment (GEWEX) Cloud System Studies] Working Group on Cirrus Cloud Systems, involves the systematic comparison of current models of ice crystal nucleation and growth for specified, typical, cirrus cloud environments. In Phase 1 of the project reported here, simulated cirrus cloud microphysical properties from seven models are compared for “warm” (−40°C) and “cold” (−60°C) cirrus, each subject to updrafts of 0.04, 0.2, and 1 m s−1. The models employ explicit microphysical schemes wherein the size distribution of each class of particles (aerosols and ice crystals) is resolved into bins or the evolution of each individual particle is traced. Simulations are made including both homogeneous and heterogeneous ice nucleation mechanisms (all-mode simulations). A single initial aerosol population of sulfuric acid particles is prescribed for all simulations. Heterogeneous nucleation is disabled for a second parallel set of simulations in order to isolate the treatment of the homogeneous freezing (of haze droplets) nucleation process. Analysis of these latter simulations is the primary focus of this paper.
Qualitative agreement is found for the homogeneous-nucleation-only simulations; for example, the number density of nucleated ice crystals increases with the strength of the prescribed updraft. However, significant quantitative differences are found. Detailed analysis reveals that the homogeneous nucleation rate, haze particle solution concentration, and water vapor uptake rate by ice crystal growth (particularly as controlled by the deposition coefficient) are critical components that lead to differences in the predicted microphysics.
Systematic differences exist between results based on a modified classical theory approach and models using an effective freezing temperature approach to the treatment of nucleation. Each method is constrained by critical freezing data from laboratory studies, but each includes assumptions that can only be justified by further laboratory research. Consequently, it is not yet clear if the two approaches can be made consistent. Large haze particles may deviate considerably from equilibrium size in moderate to strong updrafts (0.2–1 m s−1) at −60°C. The equilibrium assumption is commonly invoked in cirrus parcel models. The resulting difference in particle-size-dependent solution concentration of haze particles may significantly affect the ice particle formation rate during the initial nucleation interval. The uptake rate for water vapor excess by ice crystals is another key component regulating the total number of nucleated ice crystals. This rate, the product of particle number concentration and ice crystal diffusional growth rate, which is particularly sensitive to the deposition coefficient when ice particles are small, modulates the peak particle formation rate achieved in an air parcel and the duration of the active nucleation time period. The consequent differences in cloud microphysical properties, and thus cloud optical properties, between state-of-the-art models of ice crystal initiation are significant.
Intermodel differences in the case of all-mode simulations are correspondingly greater than in the case of homogeneous nucleation acting alone. Definitive laboratory and atmospheric benchmark data are needed to improve the treatment of heterogeneous nucleation processes.
Abstract
The Cirrus Parcel Model Comparison Project, a project of the GCSS [Global Energy and Water Cycle Experiment (GEWEX) Cloud System Studies] Working Group on Cirrus Cloud Systems, involves the systematic comparison of current models of ice crystal nucleation and growth for specified, typical, cirrus cloud environments. In Phase 1 of the project reported here, simulated cirrus cloud microphysical properties from seven models are compared for “warm” (−40°C) and “cold” (−60°C) cirrus, each subject to updrafts of 0.04, 0.2, and 1 m s−1. The models employ explicit microphysical schemes wherein the size distribution of each class of particles (aerosols and ice crystals) is resolved into bins or the evolution of each individual particle is traced. Simulations are made including both homogeneous and heterogeneous ice nucleation mechanisms (all-mode simulations). A single initial aerosol population of sulfuric acid particles is prescribed for all simulations. Heterogeneous nucleation is disabled for a second parallel set of simulations in order to isolate the treatment of the homogeneous freezing (of haze droplets) nucleation process. Analysis of these latter simulations is the primary focus of this paper.
Qualitative agreement is found for the homogeneous-nucleation-only simulations; for example, the number density of nucleated ice crystals increases with the strength of the prescribed updraft. However, significant quantitative differences are found. Detailed analysis reveals that the homogeneous nucleation rate, haze particle solution concentration, and water vapor uptake rate by ice crystal growth (particularly as controlled by the deposition coefficient) are critical components that lead to differences in the predicted microphysics.
Systematic differences exist between results based on a modified classical theory approach and models using an effective freezing temperature approach to the treatment of nucleation. Each method is constrained by critical freezing data from laboratory studies, but each includes assumptions that can only be justified by further laboratory research. Consequently, it is not yet clear if the two approaches can be made consistent. Large haze particles may deviate considerably from equilibrium size in moderate to strong updrafts (0.2–1 m s−1) at −60°C. The equilibrium assumption is commonly invoked in cirrus parcel models. The resulting difference in particle-size-dependent solution concentration of haze particles may significantly affect the ice particle formation rate during the initial nucleation interval. The uptake rate for water vapor excess by ice crystals is another key component regulating the total number of nucleated ice crystals. This rate, the product of particle number concentration and ice crystal diffusional growth rate, which is particularly sensitive to the deposition coefficient when ice particles are small, modulates the peak particle formation rate achieved in an air parcel and the duration of the active nucleation time period. The consequent differences in cloud microphysical properties, and thus cloud optical properties, between state-of-the-art models of ice crystal initiation are significant.
Intermodel differences in the case of all-mode simulations are correspondingly greater than in the case of homogeneous nucleation acting alone. Definitive laboratory and atmospheric benchmark data are needed to improve the treatment of heterogeneous nucleation processes.
Abstract
The capability of all-sky microwave radiance assimilation in the Gridpoint Statistical Interpolation (GSI) analysis system has been developed at the National Centers for Environmental Prediction (NCEP). This development effort required the adaptation of quality control, observation error assignment, bias correction, and background error covariance to all-sky conditions within the ensemble–variational (EnVar) framework. The assimilation of cloudy radiances from the Advanced Microwave Sounding Unit-A (AMSU-A) microwave radiometer for ocean fields of view (FOVs) is the primary emphasis of this study.
In the original operational hybrid 3D EnVar Global Forecast System (GFS), the clear-sky approach for radiance data assimilation is applied. Changes to data thinning and quality control have allowed all-sky satellite radiances to be assimilated in the GSI. Along with the symmetric observation error assignment, additional situation-dependent observation error inflation is employed for all-sky conditions. Moreover, in addition to the current radiance bias correction, a new bias correction strategy has been applied to all-sky radiances. In this work, the static background error variance and the ensemble spread of cloud water are examined, and the levels of cloud variability from the ensemble forecast in single- and dual-resolution configurations are discussed. Overall, the all-sky approach provides more realistic simulated brightness temperatures and cloud water analysis increments, and improves analysis off the west coasts of the continents by reducing a known bias in stratus. An approximate 10% increase in the use of AMSU-A channels 1–5 and a 12% increase for channel 15 are also observed. The all-sky AMSU-A radiance assimilation became operational in the 4D EnVar GFS system upgrade of 12 May 2016.
Abstract
The capability of all-sky microwave radiance assimilation in the Gridpoint Statistical Interpolation (GSI) analysis system has been developed at the National Centers for Environmental Prediction (NCEP). This development effort required the adaptation of quality control, observation error assignment, bias correction, and background error covariance to all-sky conditions within the ensemble–variational (EnVar) framework. The assimilation of cloudy radiances from the Advanced Microwave Sounding Unit-A (AMSU-A) microwave radiometer for ocean fields of view (FOVs) is the primary emphasis of this study.
In the original operational hybrid 3D EnVar Global Forecast System (GFS), the clear-sky approach for radiance data assimilation is applied. Changes to data thinning and quality control have allowed all-sky satellite radiances to be assimilated in the GSI. Along with the symmetric observation error assignment, additional situation-dependent observation error inflation is employed for all-sky conditions. Moreover, in addition to the current radiance bias correction, a new bias correction strategy has been applied to all-sky radiances. In this work, the static background error variance and the ensemble spread of cloud water are examined, and the levels of cloud variability from the ensemble forecast in single- and dual-resolution configurations are discussed. Overall, the all-sky approach provides more realistic simulated brightness temperatures and cloud water analysis increments, and improves analysis off the west coasts of the continents by reducing a known bias in stratus. An approximate 10% increase in the use of AMSU-A channels 1–5 and a 12% increase for channel 15 are also observed. The all-sky AMSU-A radiance assimilation became operational in the 4D EnVar GFS system upgrade of 12 May 2016.
Abstract
The Global Land–Atmosphere Coupling Experiment (GLACE) is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: land–atmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. The 12 AGCM groups participating in GLACE performed a series of simple numerical experiments that allow the objective quantification of this element for boreal summer. The derived coupling strengths vary widely. Some similarity, however, is found in the spatial patterns generated by the models, with enough similarity to pinpoint multimodel “hot spots” of land–atmosphere coupling. For boreal summer, such hot spots for precipitation and temperature are found over large regions of Africa, central North America, and India; a hot spot for temperature is also found over eastern China. The design of the GLACE simulations are described in full detail so that any interested modeling group can repeat them easily and thereby place their model’s coupling strength within the broad range of those documented here.
Abstract
The Global Land–Atmosphere Coupling Experiment (GLACE) is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: land–atmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. The 12 AGCM groups participating in GLACE performed a series of simple numerical experiments that allow the objective quantification of this element for boreal summer. The derived coupling strengths vary widely. Some similarity, however, is found in the spatial patterns generated by the models, with enough similarity to pinpoint multimodel “hot spots” of land–atmosphere coupling. For boreal summer, such hot spots for precipitation and temperature are found over large regions of Africa, central North America, and India; a hot spot for temperature is also found over eastern China. The design of the GLACE simulations are described in full detail so that any interested modeling group can repeat them easily and thereby place their model’s coupling strength within the broad range of those documented here.
Abstract
The 12 weather and climate models participating in the Global Land–Atmosphere Coupling Experiment (GLACE) show both a wide variation in the strength of land–atmosphere coupling and some intriguing commonalities. In this paper, the causes of variations in coupling strength—both the geographic variations within a given model and the model-to-model differences—are addressed. The ability of soil moisture to affect precipitation is examined in two stages, namely, the ability of the soil moisture to affect evaporation, and the ability of evaporation to affect precipitation. Most of the differences between the models and within a given model are found to be associated with the first stage—an evaporation rate that varies strongly and consistently with soil moisture tends to lead to a higher coupling strength. The first-stage differences reflect identifiable differences in model parameterization and model climate. Intermodel differences in the evaporation–precipitation connection, however, also play a key role.
Abstract
The 12 weather and climate models participating in the Global Land–Atmosphere Coupling Experiment (GLACE) show both a wide variation in the strength of land–atmosphere coupling and some intriguing commonalities. In this paper, the causes of variations in coupling strength—both the geographic variations within a given model and the model-to-model differences—are addressed. The ability of soil moisture to affect precipitation is examined in two stages, namely, the ability of the soil moisture to affect evaporation, and the ability of evaporation to affect precipitation. Most of the differences between the models and within a given model are found to be associated with the first stage—an evaporation rate that varies strongly and consistently with soil moisture tends to lead to a higher coupling strength. The first-stage differences reflect identifiable differences in model parameterization and model climate. Intermodel differences in the evaporation–precipitation connection, however, also play a key role.
Indirect and Semi-direct Aerosol Campaign
The Impact of Arctic Aerosols on Clouds
Abstract
A comprehensive dataset of microphysical and radiative properties of aerosols and clouds in the boundary layer in the vicinity of Barrow, Alaska, was collected in April 2008 during the Indirect and Semi-Direct Aerosol Campaign (ISDAC). ISDAC's primary aim was to examine the effects of aerosols, including those generated by Asian wildfires, on clouds that contain both liquid and ice. ISDAC utilized the Atmospheric Radiation Measurement Pro- gram's permanent observational facilities at Barrow and specially deployed instruments measuring aerosol, ice fog, precipitation, and radiation. The National Research Council of Canada Convair-580 flew 27 sorties and collected data using an unprecedented 41 stateof- the-art cloud and aerosol instruments for more than 100 h on 12 different days. Aerosol compositions, including fresh and processed sea salt, biomassburning particles, organics, and sulfates mixed with organics, varied between flights. Observations in a dense arctic haze on 19 April and above, within, and below the single-layer stratocumulus on 8 and 26 April are enabling a process-oriented understanding of how aerosols affect arctic clouds. Inhomogeneities in reflectivity, a close coupling of upward and downward Doppler motion, and a nearly constant ice profile in the single-layer stratocumulus suggests that vertical mixing is responsible for its longevity observed during ISDAC. Data acquired in cirrus on flights between Barrow and Fairbanks, Alaska, are improving the understanding of the performance of cloud probes in ice. Ultimately, ISDAC data will improve the representation of cloud and aerosol processes in models covering a variety of spatial and temporal scales, and determine the extent to which surface measurements can provide retrievals of aerosols, clouds, precipitation, and radiative heating.
A supplement to this article is available online:
Abstract
A comprehensive dataset of microphysical and radiative properties of aerosols and clouds in the boundary layer in the vicinity of Barrow, Alaska, was collected in April 2008 during the Indirect and Semi-Direct Aerosol Campaign (ISDAC). ISDAC's primary aim was to examine the effects of aerosols, including those generated by Asian wildfires, on clouds that contain both liquid and ice. ISDAC utilized the Atmospheric Radiation Measurement Pro- gram's permanent observational facilities at Barrow and specially deployed instruments measuring aerosol, ice fog, precipitation, and radiation. The National Research Council of Canada Convair-580 flew 27 sorties and collected data using an unprecedented 41 stateof- the-art cloud and aerosol instruments for more than 100 h on 12 different days. Aerosol compositions, including fresh and processed sea salt, biomassburning particles, organics, and sulfates mixed with organics, varied between flights. Observations in a dense arctic haze on 19 April and above, within, and below the single-layer stratocumulus on 8 and 26 April are enabling a process-oriented understanding of how aerosols affect arctic clouds. Inhomogeneities in reflectivity, a close coupling of upward and downward Doppler motion, and a nearly constant ice profile in the single-layer stratocumulus suggests that vertical mixing is responsible for its longevity observed during ISDAC. Data acquired in cirrus on flights between Barrow and Fairbanks, Alaska, are improving the understanding of the performance of cloud probes in ice. Ultimately, ISDAC data will improve the representation of cloud and aerosol processes in models covering a variety of spatial and temporal scales, and determine the extent to which surface measurements can provide retrievals of aerosols, clouds, precipitation, and radiative heating.
A supplement to this article is available online:
Abstract
Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time series over land, but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols and because of the large climate variability presently limits confidence in attribution of observed changes.
Abstract
Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time series over land, but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols and because of the large climate variability presently limits confidence in attribution of observed changes.
