High Resolution Marine Meteorological Analysis Utilizing SEASAT Data

Peteherych, S.; Woiceshyn, P. M.; Appleby, William; Chu, L.-B.; Spagnol, John C.

doi:10.1007/978-1-4613-3315-9_66

Cited by 6 publications

(4 citation statements)

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“…Scatterometer data provide the ability to correct weather analyses over the oceans and to improve forecasts and warnings of severe weather conditions for maritime interests. Peteherych et al (1981) demonstrated the potential improvement in coastal marine forecasting due to SASS. Atlas et al (1999) showed examples in which scatterometer wind patterns are able to represent the precise location, structure, and intensity of significant meteorological features.…”

Section: Use Of Scatterometer Winds By Marine Forecastersmentioning

confidence: 93%

The Effects of Marine Winds from Scatterometer Data on Weather Analysis and Forecasting

Atlas¹,

Hoffman²,

Leidner³

et al. 2001

Bull. Amer. Meteor. Soc.

111

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Satellite scatterometer observations of the ocean surface wind speed and direction improve the depiction of storms at sea. Over the ocean, scatterometer surface winds are deduced from multiple measurements of reflected radar power made from several directions. In the nominal situation, the scattering mechanism is Bragg scattering from centimeter-scale waves, which are in equilibrium with the local wind. These data are especially valuable where observations are otherwise sparse-mostly in the Southern Hemisphere extratropics and Tropics, but also on occasion in the North Atlantic and North Pacific. The history of scatterometer winds research and its application to weather analysis and forecasting is reviewed here. Two types of data impact studies have been conducted to evaluate the effect of satellite data, including satellite scatterometer data, for NWP. These are simulation experiments (or observing system simulation experiments or OSSEs) designed primarily to assess the potential impact of planned satellite observing systems, and real data impact experiments (or observing system experiments or OSEs) to evaluate the actual impact of available space-based data. Both types of experiments have been applied to the series of satellite scatterometers carried on the Seasat, European Remote Sensing-1 and-2, and the Advanced Earth Observing System-1 satellites, and the NASA Quick Scatterometer. Several trends are evident: The amount of scatterometer data has been increasing. The ability of data assimilation systems and marine forecasters to use the data has improved substantially. The ability of simulation experiments to predict the utility of new sensors has also improved significantly.

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Section: Use Of Scatterometer Winds By Marine Forecastersmentioning

confidence: 93%

The Effects of Marine Winds from Scatterometer Data on Weather Analysis and Forecasting

Atlas¹,

Hoffman²,

Leidner³

et al. 2001

Bull. Amer. Meteor. Soc.

111

View full text Add to dashboard Cite

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“…Scatterometers have the ability to detect mesoscale features that may not be present in large-scale analyses (Peteherych et al 1981;Atlas et al 1999Atlas et al , 2001. The panels in the middle row show in a similar format the ALLOBS analysis and the ambiguities closest to this analysis, and the bottom row shows the NORAIN analysis and the ambiguities closest to NORAIN.…”

Section: An Analysis Impact Example Of Quikscat Datamentioning

confidence: 96%

An Introduction to the Near–Real–Time QuikSCAT Data

Hoffman

Leidner

2005

Weather and Forecasting

125

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The NASA Quick Scatterometer (QuikSCAT ) satellite carries the SeaWinds instrument, the first satellite-borne scanning radar scatterometer. QuikSCAT, which was launched on 19 June 1999, is designed to provide accurate ocean surface winds in all conditions except for moderate to heavy rain (i.e., except for vertically integrated rain rate Ͼ2.0 km mm h Ϫ1 , the value used to tune the SeaWinds rain flag). QuikSCAT data are invaluable in providing high-quality, high-resolution winds to detect and locate precisely significant meteorological features and to produce accurate ocean surface wind analyses. QuikSCAT has an 1800-kmwide swath. A representative swath of data in the North Atlantic at 2200 UTC 28 September 2000, which contains several interesting features, reveals some of the capabilities of QuikSCAT. Careful quality control is vital for flagging data that are affected by rain and for flagging errors during ambiguity removal. In addition, an understanding of the instrument and algorithm characteristics provides insights into the factors controlling data quality for QuikSCAT. For example data quality is reduced for low wind speeds, and for locations either close to nadir or to the swath edges. The special data characteristics of the QuikSCAT scatterometer are revealed by examining the likelihood or objective function. The objective function is equal to the sum of squared scaled differences between observed and simulated normalized reflected radar power. The authors present typical examples and discuss the associated data quality concerns for different parts of the swath, for different wind speeds, and for rain versus no rain.

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“…A detailed study of the potential impact of SASS wind data on coastal marine forecasting has been performed by the Canadian Atmospheric Environment Service (Peteherych et al, 1981). In their experiment, meteorologists at three regional weather centers in a simulated real-time mode, utilized Seasat wind data in addition to satellite cloud imagery and conventional observations to prepare regional analyses and forecasts.…”

Section: Effect Of Sass Data On Subjective Analysis and Forecastingmentioning

confidence: 99%