Analysis of satellite scatterometer data and its impact on weather forecasting

Atlas, Robert; Peteherych, S.; Woiceshyn, P. M.; Wurtele, M. G.

doi:10.1109/oceans.1982.1151769

Cited by 2 publications

(1 citation statement)

References 8 publications

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“…1). The work done by Overland et al (1980), and Atlas et al (1982) clearly showed that the scatterometer system was highly successful in delineating surface weather patterns with significantly greater resolution than can possibly be achieved by in situ observational systems. A positive impact on forecast skill has been found in some cases when SASS winds are incorporated into numerical weather prediction models (see, for example, Duffy and Atlas 1986, Stoffelen and Cats, 1991, Lenzen et al 1993).…”

Section: Introductionmentioning

confidence: 99%

Construction of Marine Surface Pressure Fields from Scatterometer Winds Alone

et al. 1997

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A series of six-hourly, synoptic, gridded, global surface wind fields with a resolution of 100 km has been generated using the dataset of dealiased Seasat satellite scatterometer (SASS) winds produced as described by Peteherych et al. (1984). This paper k an account of the construction of surface pressure fields from these SASS synoptic wind fields only, as carried out by different methods, and the comparison of these pressure fields with U. S. National Centers for Environmental Prediction (NCEP) analyses, with the pressure fields of the European Centre for Medium Range Weather Forecasting (ECMWF) and with the special analyses of the Gulf of Alaska Experiment (GOASEX). One of the methods we use to derive the pressure fields utilizes a two-layer planetary boundary layer (PBL) model iterative scheme that relates the geostrophic wind vector to the surface wind vector, surface roughness, humidity, diabatic and baroclinic effects and secondary flow. A second method involves the assumption of zero twodimensional divergence, leading to a Poisson equation (the 'balance equation') in pressure, with the wind field serving as a forcing function. The pressure fields computed from the SASS winds using a two-layer PBL model closely approximate the N.MC and ECMWF fields. In some cases, the PBL-modelderived pressure fields can detect mesoscale features not resolved in either the N.MC or ECMWF analyses. Balanced-pressure fields are much smoother and less well resolved than the PBL-model-derived or NIMC fields. Systematic differences between balanced pressure fields and the PBL-model-derived fields are attributed to the neglect of. horizontal divergence in the balance equation. The effect of stratification is found to produce a larger impact than secondary flow or thermal wind effects on the derived pressure fields. Inclusion of secondary flow tends to weaken both low and high pressure

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Section: Introductionmentioning

confidence: 99%

Construction of Marine Surface Pressure Fields from Scatterometer Winds Alone

et al. 1997

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Satellite remote sensing of meteorological parameters for global numerical weather prediction

Isaacs¹,

Hoffman²,

Kaplan³

1986

Reviews of Geophysics

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Remote sensing of meteorological parameters helps to provide the initial conditions for numerical weather prediction (NWP). Desired fields include those of temperature, moisture, winds, clouds, and surface properties. For high horizontal resolution and global coverage, satellite data are an unrivaled source of information. The basic form of this information is satellite sensor‐incident, wavelength‐dependent radiance (or equivalently, brightness temperature). The process of retrieving meteorological information from the observed radiances involves solving an inverse problem. Often the inverse problem is ill posed or poorly conditioned. A variety of methods have been used to make the inverse problem more tractable: in essence, some a priori information is required. The inverse problem is the opposite of the calculation of radiances, given the relevant meteorological profiles, surface conditions, and sensor geometry. This so‐called forward problem is an integral part of physical retrieval methods which are now generally favored over conventional statistical retrieval methods. Physical retrieval methods, in practice, actually rely to a certain degree on a priori statistics. Temperature retrievals, especially in the southern hemisphere, are of proven importance in NWP involving global scale models. Vertical temperature profiles are obtained from observed radiances in a set of emission bands with varying optical depths. In comparison to conventional radiosonde data, current temperature retrievals have coarse vertical resolution. There is also some evidence that retrieved synoptic features are somewhat smoothed horizontally in spite of the high horizontal resolution of the temperature retrievals. The usefulness of other geophysical parameters for NWP is not well established and is largely untested, although a great many retrieval methods have been proposed or developed for a variety of potentially interesting parameters. The reason for this is twofold: these data are expected to have the most impact on mesoscale modeling, but mesoscale analysis systems are still relatively primitive. Moisture variables—that is, specific humidity, clouds, and precipitation—are retrievable and are potentially very useful. It is theoretically possible to retrieve specific humidity profiles by using methods analogous to those used to retrieve temperatures. However, results to date with available sensors have not been wholly satisfactory. Other moisture parameters are somewhat easier to retrieve; for example, cloud cover may be obtained by a variety of techniques from imagery in visible and/or infrared spectral regions, and vertically integrated water vapor is well correlated with emissions at microwave frequencies, especially over the ocean. Unfortunately, these parameters are not readily assimilated by a global NWP model, and special methods are required. A variety of other meteorological parameters which may be used for NWP are retrievable. These include winds at the surface from microwave sensors and cloud drift winds aloft, as well as o...

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Analysis of satellite scatterometer data and its impact on weather forecasting

Abstract: A review is presented of the need for remotely sensed marine surface wind data and its application to weather analysis and forecasting.

Cited by 2 publications

References 8 publications

Construction of Marine Surface Pressure Fields from Scatterometer Winds Alone

Construction of Marine Surface Pressure Fields from Scatterometer Winds Alone

Satellite remote sensing of meteorological parameters for global numerical weather prediction

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