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David Santek

Abstract

The use of atmospheric motion vectors (AMVs) in NWP models continues to be an important source of information in data-sparse regions. These AMVs are derived from a time sequence of images from geostationary and polar-orbiting satellites. NWP centers have documented positive impact on model forecasts not only in regions where the AMVs are measured, but elsewhere as well. One example is the effect of the Moderate Resolution Imaging Spectroradiometer (MODIS) polar winds on forecasts in the middle and lower latitudes.

Using a preoperational version of NCEP’s Global Forecast System (GFS), an experiment was run during August and September 2004, with and without the MODIS polar winds. Several cases within this period were analyzed to determine how winds poleward of 70° latitude affect the height and wind fields into lower latitudes.

From the five cases examined, it was determined that the addition of the polar winds modifies the mass balance in synoptic-scale waves near the polar jet streams. This change in mass balance is evident in differences in the ageostrophic wind, which has an effect on the speed and amplitude of baroclinic waves that extends from the jet stream into lower latitudes in later forecast times. These results reveal the substantial impact that polar-only observations may have on the predictability of global weather systems.

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Roy W. Spencer and David A. Santek

Abstract

The global distribution of intense convective activity over land is shown to be measurable with satellite passive-microwave methods through a comparison of an empirical rain rate algorithm with a climatology of thunderstorm days for the months of June-August. With the 18 and 37 GHz channels of the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR), the strong volume scattering effects of precipitation can be measured. Even though a single frequency (37 GHz) is responsive to the scattering signature, two frequencies are needed to remove most of the effect that variations in thermometric temperatures and soil moisture have on the brightness temperatures. Because snow cover is also a volume scatterer of microwave energy at these microwavelengths, a discrimination procedure involving four of the SMMR channels is employed to separate the rain and snow classes, based upon their differences in average thermometric temperature.

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Donald P. Wylie, David Santek, and David O’C. Starr

Abstract

Operational satellite data from GOES-8 and GOES-9 were used to make stereoscopic measurements of cloud heights during the National Aeronautics and Space Administration’s Subsonic Aircraft: Contrail and Cloud Effects Special Study program. The stereoscopic data were used to differentiate between boundary layer wave clouds and cirrus in the mid- and upper troposphere. This separation was difficult to evaluate from radiometric data alone. Stereographic cloud height analysis provided a definitive result. The technique used for calculating cloud heights is described. GOES-8 and -9 data were better suited for stereoscopic measurements than data from previous satellites.

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Roy W. Spencer, Michael R. Howland, and David A. Santek

Abstract

In an attempt to determine the feasibility of detecting and monitoring severe weather with future satellite passive microwave observations, the severe weather characteristics of convective storms as observed by the Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) are investigated. Low 37 GHz brightness temperatures (due to scattering of upwelling radiation by precipitation size ice) were related to the occurrence of severe weather (large hail, strong winds or wind damage, tornados and funnel clouds) within one hour of the satellite observation time. During 1979 and 1980 over the study area within the United States, there were 263 storms that had cold 37 GHz signatures. Of these storms, 15 percent were reported as severe. The relative number of storms falling in hail, wind, or tornadic categories did not differ from those expected climatologically. Critical Success Indices (CSIs) of 0.32, 0.48 and 0.38 were achieved for the low brightness temperature thresholding of severe versus nonsevere storms during 1979, 1980 and the two years combined, respectively. The preliminary indication is that a future geostationary passive microwave imaging capability at 37 GHz (or possibly higher frequencies), with sufficient spatial and temporal resolution, would facilitate the detection and monitoring of severe convective storms. This capability would provide a useful complement to radar, especially over most of the globe which is not covered by radar.

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Carl C. Norton, Frederick R. Mosher, Barry Hinton, David W. Martin, David Santek, and William Kuhlow

Abstract

A technique has been developed to infer the optical thickness of Saharan dust from Synchronous Meteorological Satellite (SMS) brightness measurements at visible wavelengths. The scattering model consists of an air layer, a dust layer and a lower boundary of variable albedo. Single-scatter properties of the dust computed from Mie theory were the basis for calculations by plane-parallel theory of radiative transfer in the dust layer. Radiative interactions between air and dust layers and the lower boundary were calculated with an adding version of the doubling scheme. Optical thickness was determined from satellite brightness measurements through a lookup table produced by the adding program. SMS visible sensors were calibrated from the prelaunch calibration measurements and measurements of sun and space. Error analysis and tests indicate a potential accuracy of ∼0.1 unit of optical thickness. The main limits on accuracy are digitizing resolution of the SMS visible signals, and mistaking clouds for dust in the satellite imagery. This technique of inferring Saharan dust turbidity has been verified and fine-tuned using surface turbidity measurements during GATE and corresponding SMS imagery.

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Christopher Velden, Jaime Daniels, David Stettner, David Santek, Jeff Key, Jason Dunion, Kenneth Holmlund, Gail Dengel, Wayne Bresky, and Paul Menzel

The evolving constellation of environmental/meteorological satellites and their associated sensor technology is rapidly advancing. This is providing opportunities for creatively improving satellite-derived products used in weather analysis and forecasting. For example, the retrieval methods for deriving atmospheric motion vectors (AMVs) from satellites have been expanding and evolving since the early 1970s. Contemporary AMV processing methods are continuously being updated and advanced through the exploitation of new sensor technologies and innovative new approaches. It is incumbent upon the research community working in AMV extraction techniques to ensure that the quality of the current operational products meets or exceeds the needs of the user community. In particular, the advances in data assimilation and numerical weather prediction in recent years have placed an increasing demand on data quality.

To keep pace with these demands, innovative research toward improving methods of deriving winds from satellites has been a focus of the World Meteorological Organization and Coordination Group for Meteorological Satellites (CGMS) cosponsored International Winds Workshops (IWWs). The IWWs are held every 2 yr, and bring together AMV researchers from around the world to present new ideas on AMV extraction techniques, interpretation, and applications. The NWP community is always well represented at these workshops, which provide an important exchange of information on the latest in data assimilation issues. This article draws from recent IWWs, and describes several new advances in satellite-produced wind technologies, derivation methodologies, and products. Examples include AMVs derived from Geostationary Operational Environmental Satellite (GOES) rapid scans and the shortwave IR channel, AMVs over the polar regions from the Moderate Resolution Imaging Spectroradiometer (MODIS), improved AMV products from the new Meteosat Second Generation satellite, and new processing approaches for deriving AMVs. The article also provides a glimpse into the pending opportunities that will be afforded with emerging/anticipated new sensor technologies.

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Brett T. Hoover, David A. Santek, Anne-Sophie Daloz, Yafang Zhong, Richard Dworak, Ralph A. Petersen, and Andrew Collard

Abstract

Automated aircraft observations of wind and temperature have demonstrated positive impact on numerical weather prediction since the mid-1980s. With the advent of the Water Vapor Sensing System (WVSS-II) humidity sensor, the expanding fleet of commercial aircraft with onboard automated sensors is also capable of delivering high quality moisture observations, providing vertical profiles of moisture as aircraft ascend out of and descend into airports across the continental United States. Observations from the WVSS-II have to date only been monitored within the Global Data Assimilation System (GDAS) without being assimilated. In this study, aircraft moisture observations from the WVSS-II are assimilated into the GDAS, and their impact is assessed in the Global Forecast System (GFS). A two-season study is performed, demonstrating a statistically significant positive impact on both the moisture forecast and the precipitation forecast at short range (12–36 h) during the warm season. No statistically significant impact is observed during the cold season.

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Matthew A. Lazzara, Richard Dworak, David A. Santek, Brett T. Hoover, Christopher S. Velden, and Jeffrey R. Key

Abstract

Atmospheric motion vectors (AMVs) are derived from satellite-observed motions of clouds and water vapor features. They provide crucial information in regions void of conventional observations and contribute to forecaster diagnostics of meteorological conditions, as well as numerical weather prediction. AMVs derived from geostationary (GEO) satellite observations over the middle latitudes and tropics have been utilized operationally since the 1980s; AMVs over the polar regions derived from low‐earth (polar)‐orbiting (LEO) satellites have been utilized since the early 2000s. There still exists a gap in AMV coverage between these two sources in the latitude band poleward of 60° and equatorward of 70° (both hemispheres). To address this AMV gap, the use of a novel approach to create image sequences that consist of composites derived from a combination of LEO and GEO observations that extend into the deep middle latitudes is explored. Experiments are performed to determine whether the satellite composite images can be employed to generate AMVs over the gap regions. The derived AMVs are validated over both the Southern Ocean/Antarctic and the Arctic gap regions over a multiyear period using rawinsonde wind observations. In addition, a two-season numerical model impact study using the Global Forecast System indicates that the assimilation of these AMVs can improve upon the control (operational) forecasts, particularly during lower-skill (dropout) events.

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Matthew A. Lazzara, John M. Benson, Robert J. Fox, Denise J. Laitsch, Joseph P. Rueden, David A. Santek, Delores M. Wade, Thomas M. Whittaker, and J. T. Young

On 12 October 1998, it was the 25th anniversary of the Man computer Interactive Data Access System (McIDAS). On that date in 1973, McIDAS was first used operationally by scientists as a tool for data analysis. Over the last 25 years, McIDAS has undergone numerous architectural changes in an effort to keep pace with changing technology. In its early years, significant technological breakthroughs were required to achieve the functionality needed by atmospheric scientists. Today McIDAS is challenged by new Internet-based approaches to data access and data display. The history and impact of McIDAS, along with some of the lessons learned, are presented here.

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Derek J. Posselt, Longtao Wu, Kevin Mueller, Lei Huang, Fredrick W. Irion, Shannon Brown, Hui Su, David Santek, and Christopher S. Velden

Abstract

This study examines the error characteristics of atmospheric motion vectors (AMVs) obtained by tracking the movement of water vapor features. A high-resolution numerical simulation of a dynamic weather event is used as a baseline, and AMVs tracked from retrieved water vapor fields are compared with the “true” winds produced by the model. The sensitivity of AMV uncertainty to time interval, AMV tracking window size, water vapor content, horizontal gradient, and wind structure is examined. AMVs are derived from the model water vapor field at a specific height and also from water vapor fields vertically blurred using smoothing functions consistent with high-spectral-resolution infrared (IR) and high-frequency microwave (MW) water vapor sounders. Uncertainties in water vapor AMVs are state dependent and are largest for regions with small water vapor content and small water vapor spatial gradient and in places where the flow runs parallel to contours of constant water vapor content. Smoothing of water vapor consistent with IR and MW retrievals does not increase AMV uncertainty; however, the yield of AMVs from IR sounders is much lower than from MW sounders because of the inability of IR sounders to retrieve water vapor below clouds. The yield and error are similar for AMVs in the lower and upper troposphere, even though the water vapor content in the upper troposphere is much smaller. The results have implications for the design of new observing systems, as well as the specification of errors when AMVs are ingested in data assimilation systems.

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