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EARL F. ROBINSON and ELLIS J. JOSEPH

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F. J. Robinson and S. C. Sherwood

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Simulations with the Weather Research and Forecasting (WRF) cloud-resolving model of deep moist convective events reveal net cooling near the tropopause (∼15–18 km above ground), caused by a combination of large-scale ascent and small-scale cooling by the irreversible mixing of turbulent eddies overshooting their level of neutral buoyancy. The turbulent cooling occurred at all CAPE values investigated (local peak values ranging from 1900 to 3500 J kg−1) and was robust to grid resolution, subgrid-scale turbulence parameterization, horizontal domain size, model dimension, and treatment of ice microphysics. The ratio of the maximum downward heat flux in the tropopause to the maximum tropospheric upward heat flux was close to 0.1. This value was independent of CAPE but was affected by changes in microphysics or subgrid-scale turbulence parameterization.

The convective cooling peaked roughly 1 km above the cold point in the background input sounding and the mean cloud- and (turbulent kinetic energy) TKE-top heights, which were all near 16.5 km above ground. It was associated with turbulent entrainment of stratospheric air from as high as 18.25 km into the troposphere. Typical cooling in the experiments was of order 1 K during convective events that produced order 10 mm of precipitation, which implied a significant contribution to the tropopause energy budget. Given the sharp concentration gradients and long residence times near the cold point, even such a small entrainment rate is likely consequential for the transport and ambient distribution of trace gases such as water vapor and ozone, and probably helps to explain the gradual increase of ozone typically observed below the tropical tropopause.

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P. F. J. Lermusiaux and A. R. Robinson

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A rational approach is used to identify efficient schemes for data assimilation in nonlinear ocean–atmosphere models. The conditional mean, a minimum of several cost functionals, is chosen for an optimal estimate. After stating the present goals and describing some of the existing schemes, the constraints and issues particular to ocean–atmosphere data assimilation are emphasized. An approximation to the optimal criterion satisfying the goals and addressing the issues is obtained using heuristic characteristics of geophysical measurements and models. This leads to the notion of an evolving error subspace, of variable size, that spans and tracks the scales and processes where the dominant errors occur. The concept of error subspace statistical estimation (ESSE) is defined. In the present minimum error variance approach, the suboptimal criterion is based on a continued and energetically optimal reduction of the dimension of error covariance matrices. The evolving error subspace is characterized by error singular vectors and values, or in other words, the error principal components and coefficients.

Schemes for filtering and smoothing via ESSE are derived. The data–forecast melding minimizes variance in the error subspace. Nonlinear Monte Carlo forecasts integrate the error subspace in time. The smoothing is based on a statistical approximation approach. Comparisons with existing filtering and smoothing procedures are made. The theoretical and practical advantages of ESSE are discussed. The concepts introduced by the subspace approach are as useful as the practical benefits. The formalism forms a theoretical basis for the intercomparison of reduced dimension assimilation methods and for the validation of specific assumptions for tailored applications. The subspace approach is useful for a wide range of purposes, including nonlinear field and error forecasting, predictability and stability studies, objective analyses, data-driven simulations, model improvements, adaptive sampling, and parameter estimation.

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A. R. Robinson, J. R. Luyten, and F. C. Fuglister

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The results from an observational experiment on the mesoscale space-time variability of the Gulf Stream are reported. Various techniques, including aerial surveys, ship trackings of the 15C isotherm at 200 m, drogues and moored current meters were used and are compared, to give estimates of the variability of the motion over a wide range of scales. A two-week time series of daily tracks of the Stream near 70W are used to interpolate instantaneous paths over 2° of longitude. These paths provide the first detailed information on the small-scale variability of the path indicator of the Gulf Stream northeast of Cape Hatteras. Similarly, the long time series of triweekly aerial surveys provides a detailed picture of the evolution of a large-scale meander.

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F. J. Robinson, M. D. Patterson, and S. C. Sherwood

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Sea breezes are often modeled as a wave response to transient heating in a stratified environment. They occur, however, as density currents with well-defined fronts, the understanding of which rests primarily on experiments and theory that do not include the stratification within and above the current and the steady heat input at the land surface. These gaps are investigated here via a sequence of idealized 2D density current simulations, progressing from the simplest classical case to more realistic surface heating and stratification.

In the classical situation where the entire horizontal density contrast is imposed initially, the front quickly attains a constant speed determined by traditional formulas based on the density contrast across the front and the current depth, or by the amount of heat needed to produce it from an initially barotropic fluid. However, these diagnostic and prognostic tools fail completely if the current is driven by a gradual input of heat, analogous to a real sea-breeze situation. In this case the current accelerates slowly at first, remaining much slower than would be expected based on classical formulas.

The motion of a classical density current is mostly inertial, with accelerations occurring at the current head; while in the continuously heated case, the entire current accelerates, requiring interior body forces to develop slowly owing to heating of the density current itself. This explains why observed sea-breeze fronts propagate more slowly than predicted from classical formulas, and may help to explain why larger landmasses, where fronts have more time to accelerate, often experience stronger convective storms when triggered by sea-breeze effects.

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F. J. Robinson, S. C. Sherwood, and Y. Li

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Observations show substantial variations of the intensity of tropical and/or summertime deep convection on land that are not explained by standard measures of convective instability. One feature that distinguishes land surfaces is their heterogeneity. The possible importance of this is investigated here by calculating the response of a nonrotating atmosphere to localized, transient surface heating using both the linearized equations of motion and a cloud-resolving configuration of the Weather Research and Forecasting (WRF) numerical model with moist physics, each in 2D. Both models predict that the depth of the resulting surface heat low near storm center will be greatest for a particular horizontal scale of heating. The linear model reveals that this is a resonant scale determined by the product of the environmental buoyancy frequency, characteristic heating time scale, and thickness of the thermal boundary layer, and the resonance occurs when the aspect ratio of the applied heating matches the ratio of vertical and horizontal wavenumbers demanded by the dispersion relation for buoyancy (gravity) waves. For realistic conditions, the resonant horizontal scale is roughly 50 km. The numerical model indicates that other measures of convective intensity, such as updraft speed and storm height, are largely controlled by the depth of the heat low, despite the presence of conditional instability and the vigorous growth of moist convective plumes. Predictions here agree with reported observations of storm severity over islands of different sizes. These findings may help explain why observed geographical variations in storm intensity defy parcel theory and indicate that phenomena often attributed to parcel entrainment may instead be due largely to storm-scale dynamical constraints.

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F. J. Robinson, S. C. Sherwood, D. Gerstle, C. Liu, and D. J. Kirshbaum

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Moist convection is well known to be generally more intense over continental than maritime regions, with larger updraft velocities, graupel, and lightning production. This study explores the transition from maritime to continental convection by comparing the trends in Tropical Rainfall Measuring Mission (TRMM) radar and microwave (37 and 85 GHz) observations over islands of increasing size to those simulated by a cloud-resolving model. The observed storms were essentially maritime over islands of <100 km2 and continental over islands >10 000 km2, with a gradual transition in between.

Equivalent radar and microwave quantities were simulated from cloud-resolving runs of the Weather Research and Forecasting model via offline radiation codes. The model configuration was idealized, with islands represented by regions of uniform surface heat flux without orography, using a range of initial sounding conditions without strong horizontal winds or aerosols. Simulated storm strength varied with initial sounding, as expected, but also increased sharply with island size in a manner similar to observations. Stronger simulated storms were associated with higher concentrations of large hydrometeors. Although biases varied with different ice microphysical schemes, the trend was similar for all three schemes tested and was also seen in 2D and 3D model configurations. The successful reproduction of the trend with such idealized forcing supports previous suggestions that mesoscale variation in surface heating—rather than any difference in humidity, aerosol, or other aspects of the atmospheric state—is the main reason that convection is more intense over continents and large islands than over oceans.

Some dynamical storm aspects, notably the peak rainfall and minimum surface pressure low, were more sensitive to surface forcing than to the atmospheric sounding or ice scheme. Large hydrometeor concentrations and simulated microwave and radar signatures, however, were at least as sensitive to initial humidity levels as to surface forcing and were more sensitive to the ice scheme.

Issues with running the TRMM simulator on 2D simulations are discussed, but they appear to be less serious than sensitivities to model microphysics, which were similar in 2D and 3D. This supports the further use of 2D simulations to economically explore modeling uncertainties.

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Laurence S. Kalkstein, Paul F. Jamason, J. Scott Greene, Jerry Libby, and Lawrence Robinson

Last summer, Philadelphia, Pennsylvania, instituted a new Hot Weather–Health Watch/Warning System (PWWS) to alert the city's residents of potentially oppressive weather situations that could negatively affect health. In addition, the system was used by the Philadelphia Department of Public Health for guidance in the implementation of mitigation procedures during dangerous weather. The system is based on a synoptic climatological procedure that identifies “oppressive” air masses historically associated with increased human mortality. Airmass occurrence can be predicted up to 48 h in advance with use of model output statistics guidance forecast data. The development and statistical basis of the system are discussed, and an analysis of the procedure's ability to forecast weather situations associated with elevated mortality counts is presented. The PWWS, through greater public awareness of excessive heat conditions, may have played an important role in reducing Philadelphia's total heat-related deaths during the summer of 1995.

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Kristie L. Ebi, Thomas J. Teisberg, Laurence S. Kalkstein, Lawrence Robinson, and Rodney F. Weiher

The Philadelphia, Pennsylvania, Hot Weather-Health Watch/Warning System was initiated in 1995 to alert the city's population to take precautionary actions when hot weather posed risks to health. The number of lives saved and the economic benefit of this system were estimated using data from 1995 to 1998. Excess mortality in people 65 yr of age and older was defined as reported mortality minus mortality predicted by a historical trend line developed over the period of 1964–88. Excess mortality during heat waves was explained using multiple linear regression. Two variables were convincingly associated with mortality: the time of season when a particular heat wave started, and a warning variable indicating whether or not a heat wave warning had been issued. The estimated coefficient of the warning variable was about −2.6, suggesting that when a warning was issued, 2.6 lives were saved, on average, for each warning day and for 3 days after the warning ended. Given the number of warnings issued over the 3-yr period, the system saved an estimated 117 lives. Estimated dollar costs for running the system were small compared with estimates of the value of a life.

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C. J. Donlon, S. J. Keogh, D. J. Baldwin, I. S. Robinson, I. Ridley, T. Sheasby, I. J. Barton, E. F. Bradley, T. J. Nightingale, and W. Emery

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Satellite sea surface skin temperature (SSST) maps are readily available from precisely calibrated radiometer systems such as the ERS along-track scanning radiometer and, in the near future, from the moderate-resolution imaging spectroradiometer. However, the use of subsurface bulk sea surface temperature (BSST) measurements as the primary source of in situ data required for the development of new sea surface temperature algorithms and the accurate validation of these global datasets is questionable. This is because BSST measurements are not a measure of the sea surface skin temperature, which is actually observed by a satellite infrared radiometer. Consequently, the use of BSST data for validation and derivation of satellite derived “pseudo-BSST” and SSST datasets will limit their accuracy to at least the rms deviation of the BSST–SSST difference, typically about ±0.5 K. Unfortunately, the prohibitive cost and difficulty of deploying infrared radiometers at sea has prevented the regular collection of a comprehensive global satellite SSST validation dataset. In response to this situation, an assessment of the TASCO THI-500L infrared radiometer system as a potential candidate for the widespread validation of satellite SSST observations is presented. This is a low-cost, broadband radiometer that has been commonly deployed in the field to measure SSST by several research groups. A comparison between SSST derived from TASCO THI-500L measurements and contemporaneous scanning infrared sea surface temperature radiometer measurements, which are accurate to better than 0.1 K, demonstrates low bias (0.1 K) and rms (0.08 K) differences between the two instruments. However, to achieve this accuracy, the TASCO THI-500L radiometer must be deployed with care to ensure that the radiometer fore-optics are kept free of salt water contamination and shaded from direct sunlight. When this is done, this type of low-cost radiometer system could form the core of a global SSST validation program.

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