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It the “mean effective on-track wind components” along the Great Circle track and any other track of known length are known, it is possible to compare flight-times along the two tracks. A graph is devised whereby it may be determined whether or not the longer track offers a shorter flight-time. By comparing several likely-looking tracks, that one which most closely, approximates the best-time track may be found.
It the “mean effective on-track wind components” along the Great Circle track and any other track of known length are known, it is possible to compare flight-times along the two tracks. A graph is devised whereby it may be determined whether or not the longer track offers a shorter flight-time. By comparing several likely-looking tracks, that one which most closely, approximates the best-time track may be found.
Abstract
Increases in surface ice nucleus concentrations at −20C (by a factor of 10 or higher) have been measured during precipitation from hailing and non-hailing convective storms; these increases are associated with the storm downdrafts. The intensity of the ice nucleus concentration fluctuations and the concentration at −20C are similar in both Alberta and Quebec storms. One of the seven convective storms for which measurements are presented was seeded with AgI released from an aircraft; the seeding material was subsequently detected at the surface.
If the observed higher ice nucleus concentration in the downdraft mixes with a storm updraft of 10 m sec−1, simple calculations indicate that no dramatic change would occur in the ice content of the updraft: to produce 5 gm m−3 of ice by −20C, in such an updraft, 105 times the normal background concentration of ice nuclei would be required.
Abstract
Increases in surface ice nucleus concentrations at −20C (by a factor of 10 or higher) have been measured during precipitation from hailing and non-hailing convective storms; these increases are associated with the storm downdrafts. The intensity of the ice nucleus concentration fluctuations and the concentration at −20C are similar in both Alberta and Quebec storms. One of the seven convective storms for which measurements are presented was seeded with AgI released from an aircraft; the seeding material was subsequently detected at the surface.
If the observed higher ice nucleus concentration in the downdraft mixes with a storm updraft of 10 m sec−1, simple calculations indicate that no dramatic change would occur in the ice content of the updraft: to produce 5 gm m−3 of ice by −20C, in such an updraft, 105 times the normal background concentration of ice nuclei would be required.
The San Antonio Mountain Experiment (SAMEX) involves a 3325 m, conically shaped, isolated mountain in north-central New Mexico where hourly observations of temperature, relative humidity, wind speed, wind direction, and precipitation are being taken at nine locations over a three- to five-year period that began in 1980. The experiment is designed to isolate the effect of topography on these meteorological variables by using a geometric configuration sufficiently simple to lead to generalized results. One remote automatic weather station (RAWS) is located at the peak (3322 m); four are located at midslope (3033 m) on southwest, southeast, northeast, and northwest aspects; and four are at the base (2743 m) on southwest, southeast, northeast, and northwest aspects. The surface observations are supplemented by rawinsonde, pibal, tethersonde, and constant-level balloon observations at selected times during each year. The unique set of meteorological data collected in the experiment will be used to 1) determine the effect of elevation and aspect on the meteorological variables; 2) compare the temperature, humidity, and wind components on the mountain with observations and/or predictions of these variables in the free air nearby; and 3) validate temperature, humidity, and wind models in complex terrain.
The San Antonio Mountain Experiment (SAMEX) involves a 3325 m, conically shaped, isolated mountain in north-central New Mexico where hourly observations of temperature, relative humidity, wind speed, wind direction, and precipitation are being taken at nine locations over a three- to five-year period that began in 1980. The experiment is designed to isolate the effect of topography on these meteorological variables by using a geometric configuration sufficiently simple to lead to generalized results. One remote automatic weather station (RAWS) is located at the peak (3322 m); four are located at midslope (3033 m) on southwest, southeast, northeast, and northwest aspects; and four are at the base (2743 m) on southwest, southeast, northeast, and northwest aspects. The surface observations are supplemented by rawinsonde, pibal, tethersonde, and constant-level balloon observations at selected times during each year. The unique set of meteorological data collected in the experiment will be used to 1) determine the effect of elevation and aspect on the meteorological variables; 2) compare the temperature, humidity, and wind components on the mountain with observations and/or predictions of these variables in the free air nearby; and 3) validate temperature, humidity, and wind models in complex terrain.
Abstract
The beam of a moderately sensitive 3-centimeter radar has been kept pointed to the zenith. Height/time records of snow echoes for seven winter weeks have been correlated with analyses of standard upper-air data. The major part of the record in nearly every storm contains trail patterns, formed as the snow falls from generating cells aloft. The majority of the related generating levels occur somewhere between 11,000 and 20,000 feet, between −12 and −34 degrees Celsius. Combined data from this and a previous study show that of 24 generating levels, 16 occur in maritime polar air and 16 occur in the lowest fifth of the relevant air-mass. In all but three of the cases of the present study, the snow generation takes place in stable air. Terminal speeds, deduced from the trail patterns, are estimated to range from 1 to 6 feet per second. At the leading edge of a storm, the radar usually records snow overhead for some time before any snow falls at the radar site. Occasionally the lower edge is patterned by pendulous extensions; these “stalactites” are associated with snow falling into dry air and are probably the pattern of overturning as air, chilled by evaporation, descends. Toward the end of a storm, the records tend to lack pattern, and the height of echo tends to lower. It may be that a different precipitation mechanism is involved; on the other hand, it may be that with decreasing intensity of snow the radar is unable to see to the higher levels where pattern exists.
Observations of snow cells, together with terminal-speed evidence of aggregation at low temperatures, suggest a turbulent convective mechanism, even though the cells occur in stable air. The role of growing ice crystals, acting as a thermal source, is examined. In moist stable air, the latent heat of sublimation released by growing ice crystals may result in significant vertical development, comparable to the observed depth of snow-generating cells. Calculated updraft velocities are comparable to the terminal speeds of ice crystals or aggregates. In air containing supercooled water cloud, the “sublimational” updraft is much lower than in cloud-free air; thus, shear and turbulence could develop across a cloud boundary in the presence of growing ice crystals, and be a significant factor in their aggregation. It is suggested that cloud boundaries, along which aggregation is favored, may serve as the bases for the snow-generating cells.
Abstract
The beam of a moderately sensitive 3-centimeter radar has been kept pointed to the zenith. Height/time records of snow echoes for seven winter weeks have been correlated with analyses of standard upper-air data. The major part of the record in nearly every storm contains trail patterns, formed as the snow falls from generating cells aloft. The majority of the related generating levels occur somewhere between 11,000 and 20,000 feet, between −12 and −34 degrees Celsius. Combined data from this and a previous study show that of 24 generating levels, 16 occur in maritime polar air and 16 occur in the lowest fifth of the relevant air-mass. In all but three of the cases of the present study, the snow generation takes place in stable air. Terminal speeds, deduced from the trail patterns, are estimated to range from 1 to 6 feet per second. At the leading edge of a storm, the radar usually records snow overhead for some time before any snow falls at the radar site. Occasionally the lower edge is patterned by pendulous extensions; these “stalactites” are associated with snow falling into dry air and are probably the pattern of overturning as air, chilled by evaporation, descends. Toward the end of a storm, the records tend to lack pattern, and the height of echo tends to lower. It may be that a different precipitation mechanism is involved; on the other hand, it may be that with decreasing intensity of snow the radar is unable to see to the higher levels where pattern exists.
Observations of snow cells, together with terminal-speed evidence of aggregation at low temperatures, suggest a turbulent convective mechanism, even though the cells occur in stable air. The role of growing ice crystals, acting as a thermal source, is examined. In moist stable air, the latent heat of sublimation released by growing ice crystals may result in significant vertical development, comparable to the observed depth of snow-generating cells. Calculated updraft velocities are comparable to the terminal speeds of ice crystals or aggregates. In air containing supercooled water cloud, the “sublimational” updraft is much lower than in cloud-free air; thus, shear and turbulence could develop across a cloud boundary in the presence of growing ice crystals, and be a significant factor in their aggregation. It is suggested that cloud boundaries, along which aggregation is favored, may serve as the bases for the snow-generating cells.
Abstract
The local ensemble tangent linear model (LETLM) provides an alternative method for creating the tangent linear model (TLM) and adjoint of a nonlinear model that promises to be easier to maintain and more computationally scalable than earlier methods. In this paper, we compare the ability of the LETLM to predict the difference between two nonlinear trajectories of the Navy’s global weather prediction model at low resolution (2.5° at the equator) with that of the TLM currently used in the Navy’s four-dimensional variational (4DVar) data assimilation scheme. When compared to the pair of nonlinear trajectories, the traditional TLM and the LETLM have improved skill relative to persistence everywhere in the atmosphere, except for temperature in the planetary boundary layer. In addition, the LETLM was, on average, more accurate than the traditional TLM (error reductions of about 20% in the troposphere and 10% overall). Sensitivity studies showed that the LETLM was most sensitive to the number of ensemble members, with the performance gradually improving with increased ensemble size up to the maximum size attempted (400). Inclusion of physics in the LETLM ensemble leads to a significantly improved representation of the boundary layer winds (error reductions of up to 50%), in addition to improved winds and temperature in the free troposphere and in the upper stratosphere/lower mesosphere. The computational cost of the LETLM was dominated by the cost of ensemble propagation. However, the LETLM can be precomputed before the 4DVar data assimilation algorithm is executed, leading to a significant computational advantage.
Abstract
The local ensemble tangent linear model (LETLM) provides an alternative method for creating the tangent linear model (TLM) and adjoint of a nonlinear model that promises to be easier to maintain and more computationally scalable than earlier methods. In this paper, we compare the ability of the LETLM to predict the difference between two nonlinear trajectories of the Navy’s global weather prediction model at low resolution (2.5° at the equator) with that of the TLM currently used in the Navy’s four-dimensional variational (4DVar) data assimilation scheme. When compared to the pair of nonlinear trajectories, the traditional TLM and the LETLM have improved skill relative to persistence everywhere in the atmosphere, except for temperature in the planetary boundary layer. In addition, the LETLM was, on average, more accurate than the traditional TLM (error reductions of about 20% in the troposphere and 10% overall). Sensitivity studies showed that the LETLM was most sensitive to the number of ensemble members, with the performance gradually improving with increased ensemble size up to the maximum size attempted (400). Inclusion of physics in the LETLM ensemble leads to a significantly improved representation of the boundary layer winds (error reductions of up to 50%), in addition to improved winds and temperature in the free troposphere and in the upper stratosphere/lower mesosphere. The computational cost of the LETLM was dominated by the cost of ensemble propagation. However, the LETLM can be precomputed before the 4DVar data assimilation algorithm is executed, leading to a significant computational advantage.
Abstract
An ensemble-based tangent linear model (TLM) is described and tested in data assimilation experiments using a global shallow-water model (SWM). A hybrid variational data assimilation system was developed with a 4D variational (4DVAR) solver that could be run either with a conventional TLM or a local ensemble TLM (LETLM) that propagates analysis corrections using only ensemble statistics. An offline ensemble Kalman filter (EnKF) is used to generate and maintain the ensemble. The LETLM uses data within a local influence volume, similar to the local ensemble transform Kalman filter, to linearly propagate the state variables at the central grid point. After tuning the LETLM with offline 6-h forecasts of analysis corrections, cycling experiments were performed that assimilated randomly located SWM height observations, based on a truth run with forced bottom topography. The performance using the LETLM is similar to that of the conventional TLM, suggesting that a well-constructed LETLM could free 4D variational methods from dependence on conventional TLMs. This is a first demonstration of the LETLM application within a context of a hybrid-4DVAR system applied to a complex two-dimensional fluid dynamics problem. Sensitivity tests are included that examine LETLM dependence on several factors including length of cycling window, size of analysis correction, spread of initial ensemble perturbations, ensemble size, and model error. LETLM errors are shown to increase linearly with correction size in the linear regime, while TLM errors increase quadratically. As nonlinearity (or forecast model error) increases, the two schemes asymptote to the same solution.
Abstract
An ensemble-based tangent linear model (TLM) is described and tested in data assimilation experiments using a global shallow-water model (SWM). A hybrid variational data assimilation system was developed with a 4D variational (4DVAR) solver that could be run either with a conventional TLM or a local ensemble TLM (LETLM) that propagates analysis corrections using only ensemble statistics. An offline ensemble Kalman filter (EnKF) is used to generate and maintain the ensemble. The LETLM uses data within a local influence volume, similar to the local ensemble transform Kalman filter, to linearly propagate the state variables at the central grid point. After tuning the LETLM with offline 6-h forecasts of analysis corrections, cycling experiments were performed that assimilated randomly located SWM height observations, based on a truth run with forced bottom topography. The performance using the LETLM is similar to that of the conventional TLM, suggesting that a well-constructed LETLM could free 4D variational methods from dependence on conventional TLMs. This is a first demonstration of the LETLM application within a context of a hybrid-4DVAR system applied to a complex two-dimensional fluid dynamics problem. Sensitivity tests are included that examine LETLM dependence on several factors including length of cycling window, size of analysis correction, spread of initial ensemble perturbations, ensemble size, and model error. LETLM errors are shown to increase linearly with correction size in the linear regime, while TLM errors increase quadratically. As nonlinearity (or forecast model error) increases, the two schemes asymptote to the same solution.
Abstract
An ensemble-based linearized forecast model has been developed for data assimilation applications for numerical weather prediction. Previous studies applied this local ensemble tangent linear model (LETLM) to various models, from simple one-dimensional models to a low-resolution (~2.5°) version of the Navy Global Environmental Model (NAVGEM) atmospheric forecast model. This paper applies the LETLM to NAVGEM at higher resolution (~1°), which required overcoming challenges including 1) balancing the computational stencil size with the ensemble size, and 2) propagating fast-moving gravity modes in the upper atmosphere. The first challenge is addressed by introducing a modified local influence volume, introducing computations on a thin grid, and using smaller time steps. The second challenge is addressed by applying nonlinear normal mode initialization, which damps spurious fast-moving modes and improves the LETLM errors above ~100 hPa. Compared to a semi-Lagrangian tangent linear model (TLM), the LETLM has superior skill in the lower troposphere (below 700 hPa), which is attributed to better representation of moist physics in the LETLM. The LETLM skill slightly lags in the upper troposphere and stratosphere (700–2 hPa), which is attributed to nonlocal aspects of the TLM including spectral operators converting from winds to vorticity and divergence. Several ways forward are suggested, including integrating the LETLM in a hybrid 4D variational solver for a realistic atmosphere, combining a physics LETLM with a conventional TLM for the dynamics, and separating the LETLM into a sequence of local and nonlocal operators.
Abstract
An ensemble-based linearized forecast model has been developed for data assimilation applications for numerical weather prediction. Previous studies applied this local ensemble tangent linear model (LETLM) to various models, from simple one-dimensional models to a low-resolution (~2.5°) version of the Navy Global Environmental Model (NAVGEM) atmospheric forecast model. This paper applies the LETLM to NAVGEM at higher resolution (~1°), which required overcoming challenges including 1) balancing the computational stencil size with the ensemble size, and 2) propagating fast-moving gravity modes in the upper atmosphere. The first challenge is addressed by introducing a modified local influence volume, introducing computations on a thin grid, and using smaller time steps. The second challenge is addressed by applying nonlinear normal mode initialization, which damps spurious fast-moving modes and improves the LETLM errors above ~100 hPa. Compared to a semi-Lagrangian tangent linear model (TLM), the LETLM has superior skill in the lower troposphere (below 700 hPa), which is attributed to better representation of moist physics in the LETLM. The LETLM skill slightly lags in the upper troposphere and stratosphere (700–2 hPa), which is attributed to nonlocal aspects of the TLM including spectral operators converting from winds to vorticity and divergence. Several ways forward are suggested, including integrating the LETLM in a hybrid 4D variational solver for a realistic atmosphere, combining a physics LETLM with a conventional TLM for the dynamics, and separating the LETLM into a sequence of local and nonlocal operators.
Abstract
Tropical cloud clusters (TCCs) are traditionally defined as synoptic-scale areas of deep convection and associated cirrus outflow. They play a critical role in the energy balance of the tropics, releasing large amounts of latent heat high in the troposphere. If conditions are favorable, TCCs can develop into tropical cyclones (TCs), which put coastal populations at risk. Previous work, usually connected with large field campaigns, has investigated TCC characteristics over small areas and time periods. Recently, developments in satellite reanalysis and global best track assimilation have allowed for the creation of a much more extensive database of TCC activity. The authors use the TCC database to produce an extensive global analysis of TCCs, focusing on TCC climatology, variability, and genesis productivity (GP) over a 28-yr period (1982–2009). While global TCC frequency was fairly consistent over the time period, with relatively small interannual variability and no noticeable trend, regional analyses show a high degree of interannual variability with clear trends in some regions. Approximately 1600 TCCs develop around the globe each year; about 6.4% of those develop into TCs. The eastern North Pacific Ocean (EPAC) basin produces the highest number of TCCs (per unit area) in a given year, but the western North Pacific Ocean (WPAC) basin has the highest GP (~12%). Annual TCC frequency in some basins exhibits a strong correlation to sea surface temperatures (SSTs), particularly in the EPAC, North Atlantic Ocean, and WPAC. However, GP is not as sensitive to SST, supporting the hypothesis that the tropical cyclogenesis process is most sensitive to atmospheric dynamical considerations such as vertical wind shear and large-scale vorticity.
Abstract
Tropical cloud clusters (TCCs) are traditionally defined as synoptic-scale areas of deep convection and associated cirrus outflow. They play a critical role in the energy balance of the tropics, releasing large amounts of latent heat high in the troposphere. If conditions are favorable, TCCs can develop into tropical cyclones (TCs), which put coastal populations at risk. Previous work, usually connected with large field campaigns, has investigated TCC characteristics over small areas and time periods. Recently, developments in satellite reanalysis and global best track assimilation have allowed for the creation of a much more extensive database of TCC activity. The authors use the TCC database to produce an extensive global analysis of TCCs, focusing on TCC climatology, variability, and genesis productivity (GP) over a 28-yr period (1982–2009). While global TCC frequency was fairly consistent over the time period, with relatively small interannual variability and no noticeable trend, regional analyses show a high degree of interannual variability with clear trends in some regions. Approximately 1600 TCCs develop around the globe each year; about 6.4% of those develop into TCs. The eastern North Pacific Ocean (EPAC) basin produces the highest number of TCCs (per unit area) in a given year, but the western North Pacific Ocean (WPAC) basin has the highest GP (~12%). Annual TCC frequency in some basins exhibits a strong correlation to sea surface temperatures (SSTs), particularly in the EPAC, North Atlantic Ocean, and WPAC. However, GP is not as sensitive to SST, supporting the hypothesis that the tropical cyclogenesis process is most sensitive to atmospheric dynamical considerations such as vertical wind shear and large-scale vorticity.
