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- Author or Editor: Lei Liu x
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Abstract
The intermittency of atmospheric turbulence plays an important role in the understanding of particle dispersal in the atmospheric boundary layer and in the statistical simulation of high-frequency wind speed in various applications. There are two kinds of intermittency, namely, the magnitude intermittency (MI) related to non-Gaussianity and the less studied clusterization intermittency (CI) related to long-term correlation. In this paper, we use a 20 Hz ultrasonic dataset lasting for 1 month to study CI of turbulent velocity fluctuations at different scales. Basing on the analysis of return-time distribution of telegraphic approximation series, we propose to use the shape parameter of the Weibull distribution to measure CI. Observations of this parameter show that contrary to MI, CI tends to weaken as the scale increases. Besides, significant diurnal variations, showing that CI tends to strengthen during the daytime (under unstable conditions) and weaken during the nighttime (under stable conditions), are found at different observation heights. In the convective boundary layer, the mixed-layer similarity is found to scale the CI exponent better than the Monin–Obukhov similarity. At night, CI is found to vary less with height in the regime with large mean wind speeds than in the regime with small mean wind speeds, according to the hockey-stick theory.
Abstract
The intermittency of atmospheric turbulence plays an important role in the understanding of particle dispersal in the atmospheric boundary layer and in the statistical simulation of high-frequency wind speed in various applications. There are two kinds of intermittency, namely, the magnitude intermittency (MI) related to non-Gaussianity and the less studied clusterization intermittency (CI) related to long-term correlation. In this paper, we use a 20 Hz ultrasonic dataset lasting for 1 month to study CI of turbulent velocity fluctuations at different scales. Basing on the analysis of return-time distribution of telegraphic approximation series, we propose to use the shape parameter of the Weibull distribution to measure CI. Observations of this parameter show that contrary to MI, CI tends to weaken as the scale increases. Besides, significant diurnal variations, showing that CI tends to strengthen during the daytime (under unstable conditions) and weaken during the nighttime (under stable conditions), are found at different observation heights. In the convective boundary layer, the mixed-layer similarity is found to scale the CI exponent better than the Monin–Obukhov similarity. At night, CI is found to vary less with height in the regime with large mean wind speeds than in the regime with small mean wind speeds, according to the hockey-stick theory.
Abstract
Observational surface data are utilized to reconstruct the subsurface density and geostrophic velocity fields via the “interior + surface quasigeostrophic” (isQG) method in a subdomain of the Antarctic Circumpolar Current (ACC). The input variables include the satellite-derived sea surface height (SSH), satellite-derived sea surface temperature (SST), satellite-derived or Argo-based sea surface salinity (SSS), and a monthly estimate of the stratification. The density reconstruction is assessed against a newly released high-resolution in situ dataset that is collected by a southern elephant seal. The results show that the observed mesoscale structures are reasonably reconstructed. In the Argo-SSS-based experiment, pattern correlations between the reconstructed and observed density mostly exceed 0.8 in the upper 300 m. Uncertainties in the SSS products notably influence the isQG performance, and the Argo-SSS-based experiment yields better density reconstruction than the satellite-SSS-based one. Through the two-dimensional (2D) omega equation, we further employ the isQG reconstructions to diagnose the upper-ocean vertical velocities (denoted w isQG2D), which are then compared against the seal-data-based 2D diagnosis of w seal. Notable discrepancies are found between w isQG2D and w seal, primarily because the density reconstruction does not capture the seal-observed smaller-scale signals. Within several subtransects, the Argo-SSS-based w isQG2D reasonably reproduce the spatial structures of w seal, but present smaller magnitude. We also apply the isQG reconstructions to the 3D omega equation, and the 3D diagnosis of w isQG3D is very different from w isQG2D, indicating the limitations of the 2D diagnostic equation. With reduced uncertainties in satellite-derived products in the future, we expect the isQG framework to achieve better subsurface estimations.
Abstract
Observational surface data are utilized to reconstruct the subsurface density and geostrophic velocity fields via the “interior + surface quasigeostrophic” (isQG) method in a subdomain of the Antarctic Circumpolar Current (ACC). The input variables include the satellite-derived sea surface height (SSH), satellite-derived sea surface temperature (SST), satellite-derived or Argo-based sea surface salinity (SSS), and a monthly estimate of the stratification. The density reconstruction is assessed against a newly released high-resolution in situ dataset that is collected by a southern elephant seal. The results show that the observed mesoscale structures are reasonably reconstructed. In the Argo-SSS-based experiment, pattern correlations between the reconstructed and observed density mostly exceed 0.8 in the upper 300 m. Uncertainties in the SSS products notably influence the isQG performance, and the Argo-SSS-based experiment yields better density reconstruction than the satellite-SSS-based one. Through the two-dimensional (2D) omega equation, we further employ the isQG reconstructions to diagnose the upper-ocean vertical velocities (denoted w isQG2D), which are then compared against the seal-data-based 2D diagnosis of w seal. Notable discrepancies are found between w isQG2D and w seal, primarily because the density reconstruction does not capture the seal-observed smaller-scale signals. Within several subtransects, the Argo-SSS-based w isQG2D reasonably reproduce the spatial structures of w seal, but present smaller magnitude. We also apply the isQG reconstructions to the 3D omega equation, and the 3D diagnosis of w isQG3D is very different from w isQG2D, indicating the limitations of the 2D diagnostic equation. With reduced uncertainties in satellite-derived products in the future, we expect the isQG framework to achieve better subsurface estimations.
Abstract
When evaluated against the 1/30°-resolution, submesoscale-resolving OFES model outputs, the previously published “interior + surface quasigeostrophic” method (from the 2013 study by Wang et al., denoted W13) for reconstructing the ocean interior from sea surface information is found to perform improperly in depicting smaller-scale oceanic motions (associated with horizontal scales smaller than about 150 km). This could be attributed to the fact that the W13 method uses only the barotropic and first baroclinic modes for the downward projection of sea surface height (SSH), while SSH at smaller scales significantly reflects other higher-order modes. To overcome this limitation of W13, an extended method (denoted L19) is proposed by employing a scale-dependent vertical projection of SSH. Specifically, the L19 method makes the projection via two gravest modes as proposed in the W13 method only for larger-scale (>150 km) signals, but for smaller scales (≤150 km) it exploits the framework of the “effective” surface quasigeostrophic (eSQG) method. Evaluation of the W13, eSQG, and L19 methods shows that the proposed L19 method can achieve the most satisfactory subsurface reconstruction in terms of both the flow and density fields in the upper 1000 m. Our encouraging results highlight the potential applicability of L19 method to the high-resolution SSH data from the upcoming Surface Water and Ocean Topography (SWOT) satellite mission.
Abstract
When evaluated against the 1/30°-resolution, submesoscale-resolving OFES model outputs, the previously published “interior + surface quasigeostrophic” method (from the 2013 study by Wang et al., denoted W13) for reconstructing the ocean interior from sea surface information is found to perform improperly in depicting smaller-scale oceanic motions (associated with horizontal scales smaller than about 150 km). This could be attributed to the fact that the W13 method uses only the barotropic and first baroclinic modes for the downward projection of sea surface height (SSH), while SSH at smaller scales significantly reflects other higher-order modes. To overcome this limitation of W13, an extended method (denoted L19) is proposed by employing a scale-dependent vertical projection of SSH. Specifically, the L19 method makes the projection via two gravest modes as proposed in the W13 method only for larger-scale (>150 km) signals, but for smaller scales (≤150 km) it exploits the framework of the “effective” surface quasigeostrophic (eSQG) method. Evaluation of the W13, eSQG, and L19 methods shows that the proposed L19 method can achieve the most satisfactory subsurface reconstruction in terms of both the flow and density fields in the upper 1000 m. Our encouraging results highlight the potential applicability of L19 method to the high-resolution SSH data from the upcoming Surface Water and Ocean Topography (SWOT) satellite mission.
Abstract
Using the extended “interior + surface quasigeostrophic” method from the 2019 study by Liu et al. (hereafter L19), subsurface density and horizontal velocities can be reconstructed from sea surface buoyancy and surface height. This study explores the potential of L19 for diagnosing the upper-ocean vertical velocity w field from high-resolution surface information, employing the 1/30° horizontal resolution OFES model output. Specifically, we employ the L19-reconstructed density and horizontal velocity fields in a diabatic version of the omega equation that incorporates a simplified parameterization for turbulent vertical mixing. The w diagnosis is evaluated against OFES output in the Kuroshio Extension region of the North Pacific, and the result indicates that the L19 method constitutes an effective framework. Statistically, the OFES-simulated and L19-diagnosed w fields have a 2-yr-averaged spatial correlation of 0.42–0.51 within the mixed layer and 0.51–0.67 throughout the 1000-m upper ocean below the mixed layer. Including the diabatic turbulent mixing effect has improved the w diagnoses inside the mixed layer, particularly for the cold-season days with the largest correlation improvement reaching 0.31. Our encouraging results suggest that the L19 method can be applied to the high-resolution sea surface height data from the forthcoming Surface Water and Ocean Topography (SWOT) satellite mission for reconstructing 3D hydrodynamic conditions of the upper ocean.
Abstract
Using the extended “interior + surface quasigeostrophic” method from the 2019 study by Liu et al. (hereafter L19), subsurface density and horizontal velocities can be reconstructed from sea surface buoyancy and surface height. This study explores the potential of L19 for diagnosing the upper-ocean vertical velocity w field from high-resolution surface information, employing the 1/30° horizontal resolution OFES model output. Specifically, we employ the L19-reconstructed density and horizontal velocity fields in a diabatic version of the omega equation that incorporates a simplified parameterization for turbulent vertical mixing. The w diagnosis is evaluated against OFES output in the Kuroshio Extension region of the North Pacific, and the result indicates that the L19 method constitutes an effective framework. Statistically, the OFES-simulated and L19-diagnosed w fields have a 2-yr-averaged spatial correlation of 0.42–0.51 within the mixed layer and 0.51–0.67 throughout the 1000-m upper ocean below the mixed layer. Including the diabatic turbulent mixing effect has improved the w diagnoses inside the mixed layer, particularly for the cold-season days with the largest correlation improvement reaching 0.31. Our encouraging results suggest that the L19 method can be applied to the high-resolution sea surface height data from the forthcoming Surface Water and Ocean Topography (SWOT) satellite mission for reconstructing 3D hydrodynamic conditions of the upper ocean.
Abstract
Three statistic methods [generalized equilibrium feedback analysis (GEFA), linear inverse modeling (LIM), and fluctuation–dissipation theorem (FDT)] are compared for their assessment of the atmospheric response to sea surface temperature variability in the coupled climate system with a sample length comparable with the observations (decades). The comparison is made first in an idealized coupled model and then in the observations. For daily to pentad data, for a linear stochastic system, the simple model study demonstrates that all three methods are able to provide a consistent assessment of the atmospheric response. For monthly data, GEFA is able to produce an assessment comparable with the daily or pentad assessments using the three methods. The consistence of the three methods is further confirmed in the observations for the responses of the atmospheric geopotential height (at 200 hPa) to the tropical ENSO mode and the North Pacific mode. It is found that the three methods produce a consistent response with the overall pattern correlation over 0.95 and the amplitude difference within 10%–20%. The consistent results in both the simple model and the observations suggest that the three statistical methods can be used as a cross validation on the robustness of the assessment of the atmospheric response to surface forcing in the observations.
Abstract
Three statistic methods [generalized equilibrium feedback analysis (GEFA), linear inverse modeling (LIM), and fluctuation–dissipation theorem (FDT)] are compared for their assessment of the atmospheric response to sea surface temperature variability in the coupled climate system with a sample length comparable with the observations (decades). The comparison is made first in an idealized coupled model and then in the observations. For daily to pentad data, for a linear stochastic system, the simple model study demonstrates that all three methods are able to provide a consistent assessment of the atmospheric response. For monthly data, GEFA is able to produce an assessment comparable with the daily or pentad assessments using the three methods. The consistence of the three methods is further confirmed in the observations for the responses of the atmospheric geopotential height (at 200 hPa) to the tropical ENSO mode and the North Pacific mode. It is found that the three methods produce a consistent response with the overall pattern correlation over 0.95 and the amplitude difference within 10%–20%. The consistent results in both the simple model and the observations suggest that the three statistical methods can be used as a cross validation on the robustness of the assessment of the atmospheric response to surface forcing in the observations.
Abstract
There has been considerable discussion concerning the accuracy of values of ice water content (IWC) in ice clouds derived from measurements of radar reflectivity (Z). In this paper, the various published relationships that are based on ice particle size spectra recorded from aircraft are analyzed, and it is shown that a relationship between ice water content and reflectivity can be derived (IWC = 0.137Z 0.64 at 94 GHz and IWC = 0.097Z 0.59 at 35 GHz), which only varies by 20%–30% for different climatological areas, providing the same ice density as a function of particle size is assumed. Uncertainty as to the true variation of density of ice particles with size may reduce the average IWC for a given Z by up to 30% for an IWC of ≈0.1 g m−3 and 20% for an IWC of ≈0.01 g m−3. Individual values of IWC derived from a single measurement of Z are likely to have an error of about +100% and −50%, but if some characteristic size estimate is available, this is reduced to about +50% and −30%. The remaining errors are due to deviations of the size spectra from exponentiality, so there is no advantage in measuring the characteristic size more precisely than this limit. Remote sensing of ice particle size is not trivial, and it is shown that if instead of size, an estimate of the temperature of the ice cloud to within 6 K is available, then, rather surprisingly, the reduction in the error of IWC is almost as good as that achieved using size. Essentially this result is reflecting the well-known correlation of crystal size with temperature. When the mean values of IWC for a given Z and T are compared for a tropical and midlatitude dataset using a common ice density variation with size, then the difference is usually less than 25%. A spaceborne instrument may need to integrate over horizontal distances of 10 km to achieve sufficient sensitivity; this necessity may introduce a bias into the retrieved IWC because the relationship between IWC and Z is not linear, but analysis shows that any bias should be less than 10%.
Abstract
There has been considerable discussion concerning the accuracy of values of ice water content (IWC) in ice clouds derived from measurements of radar reflectivity (Z). In this paper, the various published relationships that are based on ice particle size spectra recorded from aircraft are analyzed, and it is shown that a relationship between ice water content and reflectivity can be derived (IWC = 0.137Z 0.64 at 94 GHz and IWC = 0.097Z 0.59 at 35 GHz), which only varies by 20%–30% for different climatological areas, providing the same ice density as a function of particle size is assumed. Uncertainty as to the true variation of density of ice particles with size may reduce the average IWC for a given Z by up to 30% for an IWC of ≈0.1 g m−3 and 20% for an IWC of ≈0.01 g m−3. Individual values of IWC derived from a single measurement of Z are likely to have an error of about +100% and −50%, but if some characteristic size estimate is available, this is reduced to about +50% and −30%. The remaining errors are due to deviations of the size spectra from exponentiality, so there is no advantage in measuring the characteristic size more precisely than this limit. Remote sensing of ice particle size is not trivial, and it is shown that if instead of size, an estimate of the temperature of the ice cloud to within 6 K is available, then, rather surprisingly, the reduction in the error of IWC is almost as good as that achieved using size. Essentially this result is reflecting the well-known correlation of crystal size with temperature. When the mean values of IWC for a given Z and T are compared for a tropical and midlatitude dataset using a common ice density variation with size, then the difference is usually less than 25%. A spaceborne instrument may need to integrate over horizontal distances of 10 km to achieve sufficient sensitivity; this necessity may introduce a bias into the retrieved IWC because the relationship between IWC and Z is not linear, but analysis shows that any bias should be less than 10%.
Abstract
Nonspherical ice crystal optical properties are of fundamental importance to atmospheric radiative transfer through an ice cloud and the remote sensing of its properties. In practice, the optical properties of individual ice crystals need to be integrated over particle size distributions to derive the bulk optical properties of ice clouds. Given a particle size distribution represented in terms of size bins, the conventional approach uses the microphysical and optical properties of ice crystals at the bin centers as approximations to the bin-averaged values. However, errors are incurred when the size bins are large. To reduce the potential errors, a kernel technique is utilized to calculate the bulk optical properties of ice clouds by computing the bin-averaged values instead of using the bin-center values. Comparisons between the solutions based on the conventional method and the kernel technique for different numbers of size bins from in situ measurements demonstrate that the results computed from the kernel technique are more accurate. The present study illustrates that, for a given size distribution, 40 or more size bins should be used to calculate the bulk optical properties of ice clouds by the conventional method. Although the accuracy of bulk-scattering properties can be improved by using fine bin resolutions in the single-scattering property computation, the advantage of using a precomputed database of scattering kernels allows efficient computation of ice cloud bulk optical properties without losing the accuracy.
Abstract
Nonspherical ice crystal optical properties are of fundamental importance to atmospheric radiative transfer through an ice cloud and the remote sensing of its properties. In practice, the optical properties of individual ice crystals need to be integrated over particle size distributions to derive the bulk optical properties of ice clouds. Given a particle size distribution represented in terms of size bins, the conventional approach uses the microphysical and optical properties of ice crystals at the bin centers as approximations to the bin-averaged values. However, errors are incurred when the size bins are large. To reduce the potential errors, a kernel technique is utilized to calculate the bulk optical properties of ice clouds by computing the bin-averaged values instead of using the bin-center values. Comparisons between the solutions based on the conventional method and the kernel technique for different numbers of size bins from in situ measurements demonstrate that the results computed from the kernel technique are more accurate. The present study illustrates that, for a given size distribution, 40 or more size bins should be used to calculate the bulk optical properties of ice clouds by the conventional method. Although the accuracy of bulk-scattering properties can be improved by using fine bin resolutions in the single-scattering property computation, the advantage of using a precomputed database of scattering kernels allows efficient computation of ice cloud bulk optical properties without losing the accuracy.
Abstract
This study identifies several modes of coevolution of various types of El Niño–Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) by performing rotated season-reliant empirical orthogonal function (S-EOF) analysis with consideration of ENSO asymmetry. The first two modes reveal that early-onset ENSO is associated with subsequent strong IOD development, whereas late-onset ENSO forces an obscure IOD pattern with marginal SST anomalies in the western Indian Ocean. Further studies show that El Niño starting before early summer can more easily force an IOD event than that starting in late summer or fall, even when they are of equivalent magnitudes. This is because the atmospheric responses over the Indian Ocean to the eastern Pacific warming are in sharp contrast between early and late summer. Early-onset (late onset) El Niño can (cannot) cause favorable atmospheric circulation conditions over the Indian Ocean for inducing the western Indian Ocean warming, which facilitates the subsequent IOD development. In addition, the different propagations of ocean dynamic Rossby waves during the early- or late-onset types of ENSO are also accountable for the different IOD development. For the higher-order modes, the rotated S-EOF of “Niño only” cases shows a coevolution between a negative IOD mode and a date line Pacific El Niño, with warm sea surface temperature anomalies originating from the northern Pacific meridional mode.
Abstract
This study identifies several modes of coevolution of various types of El Niño–Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) by performing rotated season-reliant empirical orthogonal function (S-EOF) analysis with consideration of ENSO asymmetry. The first two modes reveal that early-onset ENSO is associated with subsequent strong IOD development, whereas late-onset ENSO forces an obscure IOD pattern with marginal SST anomalies in the western Indian Ocean. Further studies show that El Niño starting before early summer can more easily force an IOD event than that starting in late summer or fall, even when they are of equivalent magnitudes. This is because the atmospheric responses over the Indian Ocean to the eastern Pacific warming are in sharp contrast between early and late summer. Early-onset (late onset) El Niño can (cannot) cause favorable atmospheric circulation conditions over the Indian Ocean for inducing the western Indian Ocean warming, which facilitates the subsequent IOD development. In addition, the different propagations of ocean dynamic Rossby waves during the early- or late-onset types of ENSO are also accountable for the different IOD development. For the higher-order modes, the rotated S-EOF of “Niño only” cases shows a coevolution between a negative IOD mode and a date line Pacific El Niño, with warm sea surface temperature anomalies originating from the northern Pacific meridional mode.
Abstract
What impacts do typhoons have on local labor markets? Few empirical researches have been conducted in China. By collecting the data of 23 quarters (3-month intervals) of Guangdong province from 2009 to 2014 and using the generalized method of moments (GMM), this paper analyzes the impacts of typhoons on labor markets from the perspectives of general effect, regional effect, intensity effect, and time effect. In addition, a comparative analysis is carried out between this study and similar studies of developed countries. The results show that 1) massive typhoons resulted in a 12.5% increase in employment but did not have a significant impact on Guangdong’s per capita employee remuneration, and 2) there are periodic features to typhoons’ impacts on employment. Typhoons influence employment in a four-quarter cycle. In the quarter affected by a typhoon, the first quarter, the number of employees increased by 17.4%. The quantity of labor employed in the subsequent two quarters shows no significant change. In the last quarter, the number of employed people decreases by 17.0%, which returns to predisaster levels. Additionally, 3) the results of this study are different from those of studies involving developed countries, which may be caused by the distinctiveness of China’s labor market. Finally, conclusions and corresponding suggestions are presented.
Abstract
What impacts do typhoons have on local labor markets? Few empirical researches have been conducted in China. By collecting the data of 23 quarters (3-month intervals) of Guangdong province from 2009 to 2014 and using the generalized method of moments (GMM), this paper analyzes the impacts of typhoons on labor markets from the perspectives of general effect, regional effect, intensity effect, and time effect. In addition, a comparative analysis is carried out between this study and similar studies of developed countries. The results show that 1) massive typhoons resulted in a 12.5% increase in employment but did not have a significant impact on Guangdong’s per capita employee remuneration, and 2) there are periodic features to typhoons’ impacts on employment. Typhoons influence employment in a four-quarter cycle. In the quarter affected by a typhoon, the first quarter, the number of employees increased by 17.4%. The quantity of labor employed in the subsequent two quarters shows no significant change. In the last quarter, the number of employed people decreases by 17.0%, which returns to predisaster levels. Additionally, 3) the results of this study are different from those of studies involving developed countries, which may be caused by the distinctiveness of China’s labor market. Finally, conclusions and corresponding suggestions are presented.
Abstract
The authors compared the assessment of the seasonal cycle of the atmospheric response to surface forcing in three statistical methods, generalized equilibrium feedback analysis (GEFA), linear inverse modeling (LIM), and fluctuation–dissipation theorem (FDT). These methods are applied to both a conceptual climate model and the observation. It is found that LIM and GEFA are able to reproduce the major features of the seasonal response consistently, whereas FDT tends to generate a bias of the phase of the seasonal cycle. The success of LIM and GEFA for the assessment of the seasonal response is due to the slowly varying nature of the annual cycle relative to the atmospheric response time. Therefore, the authors recommend GEFA and LIM as two independent methods for the assessment of the seasonal atmospheric response in the observation.
Abstract
The authors compared the assessment of the seasonal cycle of the atmospheric response to surface forcing in three statistical methods, generalized equilibrium feedback analysis (GEFA), linear inverse modeling (LIM), and fluctuation–dissipation theorem (FDT). These methods are applied to both a conceptual climate model and the observation. It is found that LIM and GEFA are able to reproduce the major features of the seasonal response consistently, whereas FDT tends to generate a bias of the phase of the seasonal cycle. The success of LIM and GEFA for the assessment of the seasonal response is due to the slowly varying nature of the annual cycle relative to the atmospheric response time. Therefore, the authors recommend GEFA and LIM as two independent methods for the assessment of the seasonal atmospheric response in the observation.
