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Abstract
A wind spiral model, similar to that proposed by Blackadar, is used to represent the flow above a surface of uniform roughness in the planetary boundary layer (extending up to ˜1 km). An attempt is made to determine the applicability of the mixing length model used and to evaluate an empirical parameter used in the model. This attempt, using existing experimental observations of surface shear stress and wind direction, is inconclusive and leads us to suspect that surface inhomogeneity has played a role in some of the experimental data.
Abstract
A wind spiral model, similar to that proposed by Blackadar, is used to represent the flow above a surface of uniform roughness in the planetary boundary layer (extending up to ˜1 km). An attempt is made to determine the applicability of the mixing length model used and to evaluate an empirical parameter used in the model. This attempt, using existing experimental observations of surface shear stress and wind direction, is inconclusive and leads us to suspect that surface inhomogeneity has played a role in some of the experimental data.
Abstract
A mixing length model is used to relate the turbulent shear stress to the mean velocity field within the planetary boundary layer above a change in surface roughness under conditions of neutral thermal stability. This model gives rise to a parabolic system of partial differential equations. Numerical solutions are given for the case of flow above a step change in surface roughness across a line perpendicular to the geostrophic wind direction. These results show that a very long fetch is required for a true equilibrium flow to exist above the new, downwind surface. In particular, the surface wind direction adjusts only slowly to the new conditions. This suggests that experimental observations of the angle between the surface and geostrophic wind directions in supposedly nondeveloping flows may well have been affected by surface roughness changes well upstream of the experimental site. Some comparisons are made with numerical results for internal boundary layers within the shallower surface layer of the atmosphere.
Abstract
A mixing length model is used to relate the turbulent shear stress to the mean velocity field within the planetary boundary layer above a change in surface roughness under conditions of neutral thermal stability. This model gives rise to a parabolic system of partial differential equations. Numerical solutions are given for the case of flow above a step change in surface roughness across a line perpendicular to the geostrophic wind direction. These results show that a very long fetch is required for a true equilibrium flow to exist above the new, downwind surface. In particular, the surface wind direction adjusts only slowly to the new conditions. This suggests that experimental observations of the angle between the surface and geostrophic wind directions in supposedly nondeveloping flows may well have been affected by surface roughness changes well upstream of the experimental site. Some comparisons are made with numerical results for internal boundary layers within the shallower surface layer of the atmosphere.
Abstract
Measured cloud spectral signatures in high-resolution infrared interferometer data have been separated from the clear-air signatures using singular value decomposition. Sets of empirical orthogonal functions (EOFs) have then been created from these signatures to investigate the possibility of cloudy view discrimination without the use of any background data. The measured data have been taken by the Airborne Research Interferometer Evaluation System (ARIES), which is specifically designed to gather data from an aircraft that are representative of the forthcoming Infrared Atmospheric Sounding Interferometer (IASI). EOF sets were based on 78 diverse modeled clear-air spectra, supplemented by selected measured spectra. Video data gave independent verification of cloudy and cloud-free views. The development of a cloud-detection scheme is detailed, and several possible cloud-detection procedures were tested. The most promising procedure is presented. Comparative tests are made with cloud-detection algorithms developed for earlier satellite instruments. The results are encouraging; clouds were detected in the measured test data with similar success to other schemes but without requiring prior information or even the uncompressing of transmitted data. With the prospect of IASI (and similar) data being compressed for transmission using EOFs, the procedure here could be implemented in NWP centers as an initial very inexpensive but accurate method to create a cloud-filtering mask.
Abstract
Measured cloud spectral signatures in high-resolution infrared interferometer data have been separated from the clear-air signatures using singular value decomposition. Sets of empirical orthogonal functions (EOFs) have then been created from these signatures to investigate the possibility of cloudy view discrimination without the use of any background data. The measured data have been taken by the Airborne Research Interferometer Evaluation System (ARIES), which is specifically designed to gather data from an aircraft that are representative of the forthcoming Infrared Atmospheric Sounding Interferometer (IASI). EOF sets were based on 78 diverse modeled clear-air spectra, supplemented by selected measured spectra. Video data gave independent verification of cloudy and cloud-free views. The development of a cloud-detection scheme is detailed, and several possible cloud-detection procedures were tested. The most promising procedure is presented. Comparative tests are made with cloud-detection algorithms developed for earlier satellite instruments. The results are encouraging; clouds were detected in the measured test data with similar success to other schemes but without requiring prior information or even the uncompressing of transmitted data. With the prospect of IASI (and similar) data being compressed for transmission using EOFs, the procedure here could be implemented in NWP centers as an initial very inexpensive but accurate method to create a cloud-filtering mask.
Abstract
The sensitivity of warm stratocumulus cloud albedo to changes in droplet concentration, termed “cloud susceptibility,” is calculated using data from the UKMO Meteorological Research Flight. Stratocumulus clouds in the eastern Pacific, South Atlantic, subtropical regions of the North Atlantic, and around the British Isles are studied. The range of susceptibility measured is large and maritime clouds are shown to have the largest susceptibility. Numerical simulations of the changes in cloud radiative and microphysical properties with increasing droplet concentration are carried out. These highlight the high sensitivity of maritime clouds to changes in droplet concentration and the rapid reduction in sensitivity as the cloud droplet concentration increases.
Abstract
The sensitivity of warm stratocumulus cloud albedo to changes in droplet concentration, termed “cloud susceptibility,” is calculated using data from the UKMO Meteorological Research Flight. Stratocumulus clouds in the eastern Pacific, South Atlantic, subtropical regions of the North Atlantic, and around the British Isles are studied. The range of susceptibility measured is large and maritime clouds are shown to have the largest susceptibility. Numerical simulations of the changes in cloud radiative and microphysical properties with increasing droplet concentration are carried out. These highlight the high sensitivity of maritime clouds to changes in droplet concentration and the rapid reduction in sensitivity as the cloud droplet concentration increases.
Abstract
Efforts to parameterize ice shelf basal melting within climate models are limited by an incomplete understanding of the influence of ice base slope on the turbulent ice shelf–ocean boundary current (ISOBC). Here, we examine the relationship between ice base slope, boundary current dynamics, and melt rate using 3D, turbulence-permitting large-eddy simulations (LESs) of an idealized ice shelf–ocean boundary current forced solely by melt-induced buoyancy. The range of simulated slopes (3%–10%) is appropriate to the grounding zone of small Antarctic ice shelves and to the flanks of relatively wide ice base channels, and the initial conditions are representative of warm-cavity ocean conditions. In line with previous studies, the simulations feature the development of an Ekman boundary layer adjacent to the ice, overlaying a broad pycnocline. The time-averaged flow within the pycnocline is in thermal wind balance, with a mean shear that is only weakly dependent on the ice base slope angle α, resulting in a mean gradient Richardson number 〈Ri g 〉 that decreases approximately linearly with sinα. Combining this inverse relationship with a linear approximation to the density profile, we derive formulations for the friction velocity, thermal forcing, and melt rate in terms of slope angle and total buoyancy input. This theory predicts that melt rate varies like the square root of slope, which is consistent with the LES results and differs from a previously proposed linear trend. The derived scalings provide a potential framework for incorporating slope dependence into parameterizations of mixing and melting at the base of ice shelves.
Significance Statement
The majority of Antarctica’s contribution to sea level rise can be attributed to changes in ocean-driven melting at the base of ice shelves (the floating extensions of the Antarctic ice sheet). Turbulent ocean currents and melting are strongest where the ice base is steeply sloped, but few studies have systematically examined this effect. We use an idealized ice shelf–ocean model to examine how variations in ice base slope influence ocean mixing and ice melting. We derive a formula predicting that melting varies like the square root of the ice base slope, and this scaling is supported by the simulations. These results provide a potential framework for improving the representation of ice shelf melting in climate models.
Abstract
Efforts to parameterize ice shelf basal melting within climate models are limited by an incomplete understanding of the influence of ice base slope on the turbulent ice shelf–ocean boundary current (ISOBC). Here, we examine the relationship between ice base slope, boundary current dynamics, and melt rate using 3D, turbulence-permitting large-eddy simulations (LESs) of an idealized ice shelf–ocean boundary current forced solely by melt-induced buoyancy. The range of simulated slopes (3%–10%) is appropriate to the grounding zone of small Antarctic ice shelves and to the flanks of relatively wide ice base channels, and the initial conditions are representative of warm-cavity ocean conditions. In line with previous studies, the simulations feature the development of an Ekman boundary layer adjacent to the ice, overlaying a broad pycnocline. The time-averaged flow within the pycnocline is in thermal wind balance, with a mean shear that is only weakly dependent on the ice base slope angle α, resulting in a mean gradient Richardson number 〈Ri g 〉 that decreases approximately linearly with sinα. Combining this inverse relationship with a linear approximation to the density profile, we derive formulations for the friction velocity, thermal forcing, and melt rate in terms of slope angle and total buoyancy input. This theory predicts that melt rate varies like the square root of slope, which is consistent with the LES results and differs from a previously proposed linear trend. The derived scalings provide a potential framework for incorporating slope dependence into parameterizations of mixing and melting at the base of ice shelves.
Significance Statement
The majority of Antarctica’s contribution to sea level rise can be attributed to changes in ocean-driven melting at the base of ice shelves (the floating extensions of the Antarctic ice sheet). Turbulent ocean currents and melting are strongest where the ice base is steeply sloped, but few studies have systematically examined this effect. We use an idealized ice shelf–ocean model to examine how variations in ice base slope influence ocean mixing and ice melting. We derive a formula predicting that melting varies like the square root of the ice base slope, and this scaling is supported by the simulations. These results provide a potential framework for improving the representation of ice shelf melting in climate models.
Abstract
Projected changes in atmospheric ridges and associated temperature and precipitation anomalies are assessed for the end of the twenty-first century in a suite of 27 models contributing to phase 6 of the Coupled Model Intercomparison Project (CMIP6) under a high-end emissions scenario over the Pacific–North American region. Ridges are defined as spatially coherent regions of positive zonal anomalies in 500-hPa geopotential height. The frequency of ridge days in the historical period varies by geography and season; however, ridge days are broadly more common over the region in winter and least common in summer. The CMIP6 models are credible in reproducing key features of reanalysis-derived ridge climatology. The CMIP6 models also reproduce historical temperature and precipitation anomalies associated with ridges. These associations include positive temperature anomalies over and to the west/northwest of the ridge peak and negative precipitation anomalies southeast of the ridge peak. Future projections show a general decrease in ridge days across most of the region in fall through spring, with considerable model agreement. Projections for summer are different, with robust projections of increases in the number of ridge days across parts of the interior western United States and Canada. The CMIP6 models project modest decreases in the probability of stronger ridges and modest increases in the probability of weaker ridges in fall and winter. Future ridges show similar temperature and precipitation anomaly associations as in the historical climate period, when future anomalies are computed relative to future climatology.
Significance Statement
Atmospheric ridges over the Pacific–North American region are a type of atmospheric circulation pattern associated with important weather and climate impacts. These impacts include heatwaves and drought. This study uses climate models to understand how ridges and their impacts may change under future climate warming. The results suggest that ridge days will be less common across parts of the domain in fall, winter, and spring. In summer, an increase in ridge days is projected in a region centered on Montana. Results suggest that temperature and precipitation patterns associated with ridges will change at a similar rate to the overall mean climate. This work provides evidence that continued climate warming will alter atmospheric circulation over the Pacific–North American region in complex ways.
Abstract
Projected changes in atmospheric ridges and associated temperature and precipitation anomalies are assessed for the end of the twenty-first century in a suite of 27 models contributing to phase 6 of the Coupled Model Intercomparison Project (CMIP6) under a high-end emissions scenario over the Pacific–North American region. Ridges are defined as spatially coherent regions of positive zonal anomalies in 500-hPa geopotential height. The frequency of ridge days in the historical period varies by geography and season; however, ridge days are broadly more common over the region in winter and least common in summer. The CMIP6 models are credible in reproducing key features of reanalysis-derived ridge climatology. The CMIP6 models also reproduce historical temperature and precipitation anomalies associated with ridges. These associations include positive temperature anomalies over and to the west/northwest of the ridge peak and negative precipitation anomalies southeast of the ridge peak. Future projections show a general decrease in ridge days across most of the region in fall through spring, with considerable model agreement. Projections for summer are different, with robust projections of increases in the number of ridge days across parts of the interior western United States and Canada. The CMIP6 models project modest decreases in the probability of stronger ridges and modest increases in the probability of weaker ridges in fall and winter. Future ridges show similar temperature and precipitation anomaly associations as in the historical climate period, when future anomalies are computed relative to future climatology.
Significance Statement
Atmospheric ridges over the Pacific–North American region are a type of atmospheric circulation pattern associated with important weather and climate impacts. These impacts include heatwaves and drought. This study uses climate models to understand how ridges and their impacts may change under future climate warming. The results suggest that ridge days will be less common across parts of the domain in fall, winter, and spring. In summer, an increase in ridge days is projected in a region centered on Montana. Results suggest that temperature and precipitation patterns associated with ridges will change at a similar rate to the overall mean climate. This work provides evidence that continued climate warming will alter atmospheric circulation over the Pacific–North American region in complex ways.
Abstract
Soil moisture plays a fundamental role in regulating the summertime surface energy balance across Europe. Understanding the spatial and temporal behavior in soil moisture and its control on evapotranspiration (ET) is critically important and influences heat wave events. Global climate models (GCMs) exhibit a broad range of land responses to soil moisture in regions that lie between wet and dry soil regimes. In situ observations of soil moisture and evaporation are limited in space, and given the spatial heterogeneity of the landscape, are unrepresentative of the GCM gridbox scale. On the other hand, satelliteborne observations of land surface temperature (LST) can provide important information at the larger scale. As a key component of the surface energy balance, LST is used to provide an indirect measure of surface drying across the landscape. To isolate soil moisture constraints on evaporation, time series of clear-sky LST are analyzed during dry spells lasting at least 10 days from March to October. Averaged over thousands of dry spell events across Europe, and accounting for atmospheric temperature variations, regional surface warming of between 0.5 and 0.8 K is observed over the first 10 days of a dry spell. Land surface temperatures are found to be sensitive to antecedent rainfall; stronger dry spell warming rates are observed following relatively wet months, indicative of soil moisture memory effects on the monthly time scale. Furthermore, clear differences in surface warming rate are found between cropland and forest, consistent with contrasting hydrological and aerodynamic properties.
Abstract
Soil moisture plays a fundamental role in regulating the summertime surface energy balance across Europe. Understanding the spatial and temporal behavior in soil moisture and its control on evapotranspiration (ET) is critically important and influences heat wave events. Global climate models (GCMs) exhibit a broad range of land responses to soil moisture in regions that lie between wet and dry soil regimes. In situ observations of soil moisture and evaporation are limited in space, and given the spatial heterogeneity of the landscape, are unrepresentative of the GCM gridbox scale. On the other hand, satelliteborne observations of land surface temperature (LST) can provide important information at the larger scale. As a key component of the surface energy balance, LST is used to provide an indirect measure of surface drying across the landscape. To isolate soil moisture constraints on evaporation, time series of clear-sky LST are analyzed during dry spells lasting at least 10 days from March to October. Averaged over thousands of dry spell events across Europe, and accounting for atmospheric temperature variations, regional surface warming of between 0.5 and 0.8 K is observed over the first 10 days of a dry spell. Land surface temperatures are found to be sensitive to antecedent rainfall; stronger dry spell warming rates are observed following relatively wet months, indicative of soil moisture memory effects on the monthly time scale. Furthermore, clear differences in surface warming rate are found between cropland and forest, consistent with contrasting hydrological and aerodynamic properties.
Abstract
When long integrations of climate models forced by observed boundary conditions are compared against observations, differences appear that have spatial and temporal coherence. These differences are due to several causes, the largest of which are fundamental model errors and the internal variability inherent in a GCM integration. Uncertainties in the observations themselves are small in comparison. The present paper constitutes a first attempt to compare the time dependence of these spatial difference patterns with the time dependence of simulated spatial patterns of climate change associated with anthropogenic sources.
The analysis procedure was to project the model minus observed near-surface temperature difference fields onto estimates of the anthropogenic “signal” (in this case the response to greenhouse-gas and sulfate-aerosol forcing). The temporal behavior of this projection was then compared with the estimated temporal evolution of the anthropogenic signal. Such comparisons were performed on timescales of 10, 20, and 30 yr. For trends of only 10 yr in length, the model minus observed spatial difference patterns are of the same magnitude and have the same time rate of change as the expected anthropogenic signal. In the case of 20- and 30-yr trends, the prospects are favorable for discriminating between temperature changes due to anthropogenic signal changes and changes associated with model minus observed difference structures. This suggests that attempts to quantitatively detect anthropogenic climate change should be based on temporal samples of at least several decades in length. This study also shows the importance of distinguishing between purely statistical detection and what the authors term practical prediction. It is found that the results of the detection analysis are sensitive to the spatial resolution at which it is performed: for the specific case of near-surface temperature, higher spatial resolution improves ability to discriminate between an anthropogenic signal and the type of model error/internal variability “noise” considered here.
Abstract
When long integrations of climate models forced by observed boundary conditions are compared against observations, differences appear that have spatial and temporal coherence. These differences are due to several causes, the largest of which are fundamental model errors and the internal variability inherent in a GCM integration. Uncertainties in the observations themselves are small in comparison. The present paper constitutes a first attempt to compare the time dependence of these spatial difference patterns with the time dependence of simulated spatial patterns of climate change associated with anthropogenic sources.
The analysis procedure was to project the model minus observed near-surface temperature difference fields onto estimates of the anthropogenic “signal” (in this case the response to greenhouse-gas and sulfate-aerosol forcing). The temporal behavior of this projection was then compared with the estimated temporal evolution of the anthropogenic signal. Such comparisons were performed on timescales of 10, 20, and 30 yr. For trends of only 10 yr in length, the model minus observed spatial difference patterns are of the same magnitude and have the same time rate of change as the expected anthropogenic signal. In the case of 20- and 30-yr trends, the prospects are favorable for discriminating between temperature changes due to anthropogenic signal changes and changes associated with model minus observed difference structures. This suggests that attempts to quantitatively detect anthropogenic climate change should be based on temporal samples of at least several decades in length. This study also shows the importance of distinguishing between purely statistical detection and what the authors term practical prediction. It is found that the results of the detection analysis are sensitive to the spatial resolution at which it is performed: for the specific case of near-surface temperature, higher spatial resolution improves ability to discriminate between an anthropogenic signal and the type of model error/internal variability “noise” considered here.
Abstract
Convection over the Tibetan Plateau (TP) has been linked to heavy rain and flooding in downstream parts of China. Understanding processes which influence the development of convection on the TP could contribute to better forecasting of these extreme events. TP scale (~1000 km) soil moisture gradients have been shown to influence formation of convective systems over the eastern TP. The importance of smaller-scale (~10 km) variability has been identified in other regions (including the Sahel and Mongolia) but has yet to be investigated for the TP. In addition, compared to studies over flat terrain, much less is known about soil moisture–convection feedbacks above complex topography. In this study we use satellite observations of cold cloud, land surface temperature, and soil moisture to analyze the effect of mesoscale soil moisture heterogeneity on the initiation of strong convection in the complex TP environment. We find that strong convection is favored over negative (positive) land surface temperature (soil moisture) gradients. The signal is strongest for less vegetation and low topographic complexity, though still significant up to a local standard deviation of 300 m in elevation, accounting for 65% of cases. In addition, the signal is dependent on background wind. Strong convective initiation is only sensitive to local (tens of kilometers) soil moisture heterogeneity for light wind speeds, though large-scale (hundreds of kilometers) gradients may still be important for strong wind speeds. Our results demonstrate that, even in the presence of complex topography, local soil moisture variability plays an important role in storm development.
Abstract
Convection over the Tibetan Plateau (TP) has been linked to heavy rain and flooding in downstream parts of China. Understanding processes which influence the development of convection on the TP could contribute to better forecasting of these extreme events. TP scale (~1000 km) soil moisture gradients have been shown to influence formation of convective systems over the eastern TP. The importance of smaller-scale (~10 km) variability has been identified in other regions (including the Sahel and Mongolia) but has yet to be investigated for the TP. In addition, compared to studies over flat terrain, much less is known about soil moisture–convection feedbacks above complex topography. In this study we use satellite observations of cold cloud, land surface temperature, and soil moisture to analyze the effect of mesoscale soil moisture heterogeneity on the initiation of strong convection in the complex TP environment. We find that strong convection is favored over negative (positive) land surface temperature (soil moisture) gradients. The signal is strongest for less vegetation and low topographic complexity, though still significant up to a local standard deviation of 300 m in elevation, accounting for 65% of cases. In addition, the signal is dependent on background wind. Strong convective initiation is only sensitive to local (tens of kilometers) soil moisture heterogeneity for light wind speeds, though large-scale (hundreds of kilometers) gradients may still be important for strong wind speeds. Our results demonstrate that, even in the presence of complex topography, local soil moisture variability plays an important role in storm development.
Abstract
Direct numerical simulations of stratified turbulence are used to test several fundamental assumptions involved in the Osborn, Osborn–Cox, and Thorpe methods commonly used to estimate the turbulent diffusivity from field measurements. The forced simulations in an idealized triply periodic computational domain exhibit characteristic features of stratified turbulence including intermittency and layer formation. When calculated using the volume-averaged dissipation rates from the simulations, the vertical diffusivities inferred from the Osborn and Osborn–Cox methods are within 40% of the value diagnosed using the volume-averaged buoyancy flux for all cases, while the Thorpe-scale method performs similarly well in the simulation with a relatively large buoyancy Reynolds number (Re b ≃ 240) but significantly overestimates the vertical diffusivity in simulations with Re b < 60. The methods are also tested using a limited number of vertical profiles randomly selected from the computational volume. The Osborn, Osborn–Cox, and Thorpe-scale methods converge to their respective estimates based on volume-averaged statistics faster than the vertical diffusivity calculated directly from the buoyancy flux, which is contaminated with reversible contributions from internal waves. When applied to a small number of vertical profiles, several assumptions underlying the Osborn and Osborn–Cox methods are not well supported by the simulation data. However, the vertical diffusivity inferred from these methods compares reasonably well to the exact value from the simulations and outperforms the assumptions underlying these methods in terms of the relative error. Motivated by a recent theoretical development, it is speculated that the Osborn method might provide a reasonable approximation to the diffusivity associated with the irreversible buoyancy flux.
Abstract
Direct numerical simulations of stratified turbulence are used to test several fundamental assumptions involved in the Osborn, Osborn–Cox, and Thorpe methods commonly used to estimate the turbulent diffusivity from field measurements. The forced simulations in an idealized triply periodic computational domain exhibit characteristic features of stratified turbulence including intermittency and layer formation. When calculated using the volume-averaged dissipation rates from the simulations, the vertical diffusivities inferred from the Osborn and Osborn–Cox methods are within 40% of the value diagnosed using the volume-averaged buoyancy flux for all cases, while the Thorpe-scale method performs similarly well in the simulation with a relatively large buoyancy Reynolds number (Re b ≃ 240) but significantly overestimates the vertical diffusivity in simulations with Re b < 60. The methods are also tested using a limited number of vertical profiles randomly selected from the computational volume. The Osborn, Osborn–Cox, and Thorpe-scale methods converge to their respective estimates based on volume-averaged statistics faster than the vertical diffusivity calculated directly from the buoyancy flux, which is contaminated with reversible contributions from internal waves. When applied to a small number of vertical profiles, several assumptions underlying the Osborn and Osborn–Cox methods are not well supported by the simulation data. However, the vertical diffusivity inferred from these methods compares reasonably well to the exact value from the simulations and outperforms the assumptions underlying these methods in terms of the relative error. Motivated by a recent theoretical development, it is speculated that the Osborn method might provide a reasonable approximation to the diffusivity associated with the irreversible buoyancy flux.
