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James Foster, Michael Bevis, and Steven Businger

Abstract

The sliding-window technique uses a moving time window to select GPS data for processing. This makes it possible to routinely incorporate the most recently collected data and generate estimates for atmospheric delay or precipitable water in (near) real time. As a consequence of the technique several estimates may be generated for each time epoch, and these multiple estimates can be used to explore and analyze the characteristics of the atmospheric estimates and the effect of the processing model and parameters. Examples of some of the analyses that can be undertaken are presented. Insights into the phenomenology of the atmospheric estimates provided by sliding-window analysis permit the fine-tuning of the GPS processing as well as the possibility of both improving the accuracy of the near-real-time estimates themselves and constraining the errors associated with them. The overlapping data windows and the multiple estimates that characterize the sliding-window method can lead to ambiguity in the meaning of many terms and expressions commonly used in GPS meteorology. In order to prevent confusion in discussions of sliding-window processing, a nomenclature is proposed that formalizes the meaning of the primary terms and defines the geometric and physical relationships between them.

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Joost A. Businger and Steven P. Oncley

Abstract

A method is proposed to measure scalar fluxes using conditional sampling. Only the mean concentrations of updraft and downdraft samples, the standard deviation of the vertical velocity, and a coefficient of proportionality, b, need to be known. The method has been simulated from existing time series of the vertical wind component, temperature, and humidity in the surface layer. It is found that b has an almost constant value of 0.6 for both scalars and over a wide stability range. This result encourages application to other scalars and suggests that the method may be used beyond the atmospheric surface layer in the lower part of the planetary boundary layer.

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Steven R. Chiswell, Steven Businger, Michael Bevis, Fredrick Solheim, Christian Rocken, and Randolph Ware

Abstract

Water vapor radiometer (WVR) retrieval algorithms require a priori information on atmospheric conditions along the line of sight of the radiometer in order to derive opacities from observed brightness temperatures. This paper's focus is the mean radiating temperature of the atmosphere (T mr), which is utilized in these algorithms to relate WVR measurements to integrated water vapor. Current methods for specifying T mr rely on the climatology of the WVR site-for example, a seasonal average-or information from nearby soundings to specify T mr. However, values of T mr, calculated from radiosonde data, not only vary according to site and season but also exhibit large fluctuations in response to local weather conditions. By utilizing output from numerical weather prediction (NWP) models, T mr can be accurately prescribed for an arbitrary WVR site at a specific time. Temporal variations in local weather conditions can he resolved by NWP models on timescales shorter than standard radiosonde soundings.

Currently used methods for obtaining T mr are reviewed. Values of T mr obtained from current methods and this new approach are compared to those obtained from in situ radiosonde soundings. The improvement of the T mr calculation using available model forecast data rather than climatological values yields a corresponding improvement of comparable magnitude in the retrieval of atmospheric opacity. Use of forecast model data relieves a WVR site of its dependency on local climatology or the necessity of a nearby sounding, allowing more accurate retrieval of observed conditions and increased flexibility in choosing site location. Furthermore, it is found that the calculation of precipitable water by means of atmospheric opacities does not require time-dependent tuning parameters when model data are used. These results were obtained using an archived subset of the full nested grid model output. The added horizontal and vertical resolution of operational data should further improve this approach.

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Antti T. Pessi, Steven Businger, K. L. Cummins, N. W. S. Demetriades, M. Murphy, and B. Pifer

Abstract

The waveguide between the earth’s surface and the ionosphere allows very low-frequency (VLF) emissions generated by lightning, called sferics, to propagate over long distances. The new Pacific Lightning Detection Network (PacNet), as a part of a larger long-range lightning detection network (LLDN), utilizes this attribute to monitor lightning activity over the central North Pacific Ocean with a network of ground-based lightning detectors that have been installed on four widely spaced Pacific islands (400–3800 km). PacNet and LLDN sensors combine both magnetic direction finding (MDF) and time-of-arrival (TOA)-based technology to locate a strike with as few as two sensors. As a result, PacNet/LLDN is one of the few observing systems, outside of geostationary satellites, that provides continuous real-time data concerning convective storms throughout a synoptic-scale area over the open ocean.

The performance of the PacNet/LLDN was carefully assessed. Long-range lightning flash detection efficiency (DE) and location accuracy (LA) models were developed with reference to accurate data from the U.S. National Lightning Detection Network (NLDN). Model calibration procedures are detailed, and comparisons of model results with lightning observations from the PacNet/LLDN in correlation with NASA’s Lightning Imaging Sensor (LIS) are presented. The daytime and nighttime flash DE in the north-central Pacific is in the range of 17%–23% and 40%–61%, respectively. The median LA is in the range of 13–40 km. The results of this extensive analysis suggest that the DE and LA models are reasonably able to reproduce the observed performance of PacNet/LLDN.

The implications of this work are that the DE and LA model outputs can be used in quantitative applications of the PacNet/LLDN over the North Pacific Ocean and elsewhere. For example, by virtue of the relationship between lightning and rainfall rates, these data also hold promise as input for NWP models as a proxy for latent heat release in convection. Moreover, the PacNet/LLDN datastream is useful for investigations of storm morphology and cloud microphysics over the central North Pacific Ocean. Notably, the PacNet/LLDN lightning datastream has application for planning transpacific flights and nowcasting of squall lines and tropical storms.

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