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R. Meneghini, K. Nakamura, C. W. Ulbrich, and D. Atlas

Abstract

For a spaceborne meteorological radar, the use of frequencies above 10 GHz may be necessary to attain sufficient spatial resolution. As the frequency increases, however, attenuation by rain becomes significant. To extend the range of rain rates that can be accurately estimated, methods other than the conventional Z-R, or backscattering method, are needed. In this paper, tests are made of two attenuation-based methods using data from a dual-wavelength airborne radar operating at 3 cm and 0.87 cm. For the conventional dual-wavelength method, the differential attenuation is estimated from the relative decrease in the signal level with range. For the surface reference method, the attenuation is determined from the difference of surface return powers measured in the absence and the presence of rain. For purposes of comparison, and as an indication of the relative accuracies of the techniques, the backscattering, (Z-R), method, as applied to the 3 cm data, is employed. As the primary sources of error for the Z-R, dual-wavelength, and surface reference methods are nearly independent, some confidence in the results is warranted when thew methods yield similar rain rates. Cases of good agreement occur most often in stratiform rain for rain rates between a few mm h−1 to about 15 mm h−1; that is, where attenuation at the shorter wavelength is significant but not so severe as to result in a loss of signal. When the estimates disagree, it is sometimes possible to identify the likely error source by an examination of the return power profiles and a knowledge of the error sources.

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R. N. Hoffman, S. M. Leidner, J. M. Henderson, R. Atlas, J. V. Ardizzone, and S. C. Bloom

Abstract

In this study, a two-dimensional variational analysis method (2DVAR) is applied to select a wind solution from NASA Scatterometer (NSCAT) ambiguous winds. A 2DVAR method determines a “best” gridded surface wind analysis by minimizing a cost function. The cost function measures the misfit to the observations, the background, and the filtering and dynamical constraints. The ambiguity closest in direction to the minimizing analysis is selected. The 2DVAR method, sensitivity, and numerical behavior are described. 2DVAR is used with both NSCAT ambiguities and NSCAT backscatter values. Results are roughly comparable. When the background field is poor, 2DVAR ambiguity removal often selects low probability ambiguities. To avoid this behavior, an initial 2DVAR analysis, using only the two most likely ambiguities, provides the first guess for an analysis using all the ambiguities or the backscatter data. 2DVAR and median filter-selected ambiguities usually agree. Both methods require horizontal consistency, so disagreements occur in clumps, or as linear features. In these cases, 2DVAR ambiguities are often more meteorologically reasonable and more consistent with satellite imagery.

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G. R. Halliwell Jr., A. Srinivasan, V. Kourafalou, H. Yang, D. Willey, M. Le Hénaff, and R. Atlas

Abstract

A new fraternal twin ocean observing system simulation experiment (OSSE) system is validated in a Gulf of Mexico domain. It is the first ocean system that takes full advantage of design criteria and rigorous evaluation procedures developed to validate atmosphere OSSE systems that have not been fully implemented for the ocean. These procedures are necessary to determine a priori that the OSSE system does not overestimate or underestimate observing system impacts. The new system consists of 1) a nature run (NR) stipulated to represent the true ocean, 2) a data assimilation system consisting of a second ocean model (the “forecast model”) coupled to a new ocean data assimilation system, and 3) software to simulate observations from the NR and to add realistic errors. The system design is described to illustrate the requirements of a validated OSSE system. The chosen NR reproduces the climatology and variability of ocean phenomena with sufficient realism. Although the same ocean model type is used (the “fraternal twin” approach), the forecast model is configured differently so that it approximately satisfies the requirement that differences (errors) with respect to the NR grow at the same rate as errors that develop between state-of-the-art ocean models and the true ocean. Rigorous evaluation procedures developed for atmospheric OSSEs are then applied by first performing observing system experiments (OSEs) to evaluate one or more existing observing systems. OSSEs are then performed that are identical except for the assimilation of synthetic observations simulated from the NR. Very similar impact assessments were realized between each OSE–OSSE pair, thus validating the system without the need for calibration.

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George R. Halliwell Jr., Gustavo J. Goni, Michael F. Mehari, Villy H. Kourafalou, Molly Baringer, and Robert Atlas

Abstract

Credible tropical cyclone (TC) intensity prediction by coupled models requires accurate forecasts of enthalpy flux from ocean to atmosphere, which in turn requires accurate forecasts of sea surface temperature cooling beneath storms. Initial ocean fields must accurately represent ocean mesoscale features and the associated thermal and density structure. Observing system simulation experiments (OSSEs) are performed to quantitatively assess the impact of assimilating profiles collected from multiple underwater gliders deployed over the western North Atlantic Ocean TC region, emphasizing advantages gained by profiling from moving versus stationary platforms. Assimilating ocean profiles collected repeatedly at fixed locations produces large root-mean-square error reduction only within ~50 km of each profiler for two primary reasons. First, corrections performed during individual update cycles tend to introduce unphysical eddy structure resulting from smoothing properties of the background error covariance matrix and the tapering of innovations by a localization radius function. Second, advection produces rapid nonlinear error growth at larger distances from profiler locations. The ability of each individual moving glider to cross gradients and map mesoscale structure in its vicinity substantially reduces this nonlinear error growth. Glider arrays can be deployed with horizontal separation distances that are 50%–100% larger than those of fixed-location profilers to achieve similar mesoscale error reduction. By contrast, substantial larger-scale bias reduction in upper-ocean heat content can be achieved by deploying profiler arrays with separation distances up to several hundred kilometers, with moving gliders providing only modest additional improvement. Expected sensitivity of results to study region and data assimilation method is discussed.

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Robert Atlas, Ross N. Hoffman, Zaizhong Ma, G. David Emmitt, Sidney A. Wood Jr., Steven Greco, Sara Tucker, Lisa Bucci, Bachir Annane, R. Michael Hardesty, and Shirley Murillo

Abstract

The potential impact of Doppler wind lidar (DWL) observations from a proposed optical autocovariance wind lidar (OAWL) instrument is quantified in observing system simulation experiments (OSSEs). The OAWL design would provide profiles of useful wind vectors along a ground track to the left of the International Space Station (ISS), which is in a 51.6° inclination low-Earth orbit (LEO). These observations are simulated realistically, accounting for cloud and aerosol distributions inferred from the OSSE nature runs (NRs), and measurement and sampling error sources. The impact of the simulated observations is determined in both global and regional OSSE frameworks. The global OSSE uses the ECMWF T511 NR and the NCEP operational Global Data Assimilation System at T382 resolution. The regional OSSE uses an embedded hurricane NR and the NCEP operational HWRF data assimilation system with outer and inner domains of 9- and 3-km resolution, respectively.

The global OSSE results show improved analyses and forecasts of tropical winds and extratropical geopotential heights. The tropical wind RMSEs are significantly reduced in the analyses and in short-term forecasts. The tropical wind improvement decays as the forecasts lengthen. The regional OSSEs are limited but show some improvements in hurricane track and intensity forecasts.

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