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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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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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Russell L. Elsberry, Eric A. Hendricks, Christopher S. Velden, Michael M. Bell, Melinda Peng, Eleanor Casas, and Qingyun Zhao

Abstract

A dynamic initialization assimilation scheme is demonstrated utilizing rapid-scan atmospheric motion vectors (AMVs) at 15-min intervals to simulate the real-time capability that now exists from the new generation of geostationary meteorological satellites. The impacts of these AMVs are validated with special Tropical Cyclone Intensity Experiment (TCI-15) datasets during 1200–1800 UTC 4 October leading up to a NASA WB-57 eyewall crossing of Hurricane Joaquin. Incorporating the AMV fields in the Spline Analysis at Mesoscale Utilizing Radar and Aircraft Instrumentation (SAMURAI) COAMPS Dynamic Initialization (SCDI) means there are 30 and 90 time steps on the 15- and 5-km grids, respectively, during which the mass fields are adjusted to these AMV-based wind increments during each 15-min assimilation period. The SCDI analysis of the three-dimensional vortex structure of Joaquin at 1800 UTC 4 October closely replicates the vortex tilt analyzed from the High-Definition Sounding System (HDSS) dropwindsondes. Vertical wind shears based on the AMVs at 15-min intervals are well correlated with the extreme rapid decay, an interruption of that rapid decay, and the subsequent period of constant intensity of Joaquin. Utilizing the SCDI analysis as the initial conditions for two versions of the COAMPS-TC model results in an accurate 72-h prediction of the interruption of the rapid decay and the period of constant intensity. Upscaling a similar SCDI analysis based on the 15-min interval AMVs provides a more realistic intensity and structure of Tropical Storm Joaquin for the initial conditions of the Navy Global Environmental Model (NAVGEM) than the synthetic TC vortex used operationally. This demonstration for a single 6-h period of AMVs indicates the potential for substantial impacts when an end-to-end cycling version is developed.

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Eric A. Hendricks, Russell L. Elsberry, Christopher S. Velden, Adam C. Jorgensen, Mary S. Jordan, and Robert L. Creasey

Abstract

The objective in this study is to demonstrate how two unique datasets from the Tropical Cyclone Intensity (TCI-15) field experiment can be used to diagnose the environmental and internal factors contributing to the interruption of the rapid decay of Hurricane Joaquin (2015) and then a subsequent 30-h period of constant intensity. A special CIMSS vertical wind shear (VWS) dataset reprocessed at 15-min intervals provides a more precise documentation of the large (~15 m s−1) VWS throughout most of the rapid decay period, and then the timing of a rapid decrease in VWS to moderate (~8 m s−1) values prior to, and following, the rapid decay period. During this period, the VWS was moderate because Joaquin was between large VWSs to the north and near-zero VWSs to the south, which is considered to be a key factor in how Joaquin was able to be sustained at hurricane intensity even though it was moving poleward over colder water. A unique dataset of High Definition Sounding System (HDSS) dropwindsondes deployed from the NASA WB-57 during the TCI-15 field experiment is utilized to calculate zero-wind centers during Joaquin center overpasses that reveal for the first time the vortex tilt structure through the entire troposphere. The HDSS datasets are also utilized to calculate the inertial stability profiles and the inner-core potential temperature anomalies in the vertical. Deeper lower-tropospheric layers of near-zero vortex tilt are correlated with stronger storm intensities, and upper-tropospheric layers with large vortex tilts due to large VWSs are correlated with weaker storm intensities.

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Kerry Emanuel, Eugenia Kalnay, Craig Bishop, Russell Elsberry, Ronald Gelaro, Daniel Keyser, Steven Lord, David Rogers, Melvyn Shapiro, Christopher Snyder, and Christopher Velden

One of the most significant impediments to progress in forecasting weather over North America is the relative paucity of routine observations over data-sparse regions adjacent to the United States. Prospectus Development Team Seven was convened to consider ways to promote research that seeks to determine implementations of observing systems that are optimal for weather prediction in the United States. An “optimal” measurement system is considered to be one that maximizes the ratio of societal benefit to overall cost. The thrust of the conclusions is that existing means of estimating the value of current observing systems and the potential benefits of new or proposed observing systems are underutilized. At the same time, no rational way exists for comparing the cost of observations across the spectrum of federal agencies responsible for measuring the atmosphere and ocean. The authors suggest that a rational procedure for configuring an observation system that is optimal for weather prediction would consist of the following steps.

The authors believe that a rational approach to atmospheric measurement is critical to further improvements in weather prediction and that such improvements might very well be made within the current budget of routine observations, integrated across all of the responsible federal agencies. This document outlines a proposed strategy for rationalizing atmosphere observations in aid of weather prediction in the United States. The paper begins with a summary of recommendations.

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Johannes Schmetz, W. Paul Menzel, Christopher Velden, Xiangqian Wu, Leo van de Berg, Steve Nieman, Christopher Hayden, Kenneth Holmlund, and Carlos Geijo

This paper describes the results from a collaborative study between the European Space Operations Center, the European Organization for the Exploitation of Meteorological Satellites, the National Oceanic and Atmospheric Administration, and the Cooperative Institute for Meteorological Satellite Studies investigating the relationship between satellite-derived monthly mean fields of wind and humidity in the upper troposphere for March 1994. Three geostationary meteorological satellites GOES-7, Meteosat-3, and Meteosat-5 are used to cover an area from roughly 160°W to 50°E. The wind fields are derived from tracking features in successive images of upper-tropospheric water vapor (WV) as depicted in the 6.5-μ absorption band. The upper-tropospheric relative humidity (UTH) is inferred from measured water vapor radiances with a physical retrieval scheme based on radiative forward calculations.

Quantitative information on large-scale circulation patterns in the upper troposphere is possible with the dense spatial coverage of the WV wind vectors. The monthly mean wind field is used to estimate the large-scale divergence; values range between about −5 × 10−6 and 5 × 10−6 sec−1 when averaged over a scale length of about 1000–2000 km. The spatial patterns of the UTH field and the divergence of the wind field closely resemble one another, suggesting that UTH patterns are principally determined by the large-scale circulation.

Since the upper-tropospheric humidity absorbs upwelling radiation from lower-tropospheric levels and therefore contributes significantly to the atmospheric greenhouse effect, this work implies that studies on the climate relevance of water vapor should include threedimensional modeling of the atmospheric dynamics. The fields of UTH and WV winds are useful parameters for a climate-monitoring system based on satellite data. The results from this 1-month analysis suggest the desirability of further GOES and Meteosat studies to characterize the changes in the upper-tropospheric moisture sources and sinks over the past decade.

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Kerry Emanuel, Philippe Caroff, Sandy Delgado, Charles “Chip” Guard, Mark Guishard, Christopher Hennon, John Knaff, Kenneth R. Knapp, James Kossin, Carl Schreck, Christopher Velden, and Jonathan Vigh
Open access
Stanley Q. Kidder, Mitchell D. Goldberg, Raymond M. Zehr, Mark DeMaria, James F. W. Purdom, Christopher S. Velden, Norman C. Grody, and Sheldon J. Kusselson

The first Advanced Microwave Sounding Unit (AMSU) was launched aboard the NOAA-15 satellite on 13 May 1998. The AMSU is well suited for the observation of tropical cyclones because its measurements are not significantly affected by the ice clouds that cover tropical storms. In this paper, the following are presented: 1) upper-tropospheric thermal anomalies in tropical cyclones retrieved from AMSU data, 2) the correlation of maximum temperature anomalies with maximum wind speed and central pressure, 3) winds calculated from the temperature anomaly field, 4) comparison of AMSU data with GOES and AVHRR imagery, and 5) tropical cyclone rainfall potential. The AMSU data appear to offer substantial opportunities for improvement in tropical cyclone analysis and forecasting.

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Robert F. Rogers, Sim Aberson, Michael M. Bell, Daniel J. Cecil, James D. Doyle, Todd B. Kimberlain, Josh Morgerman, Lynn K. Shay, and Christopher Velden

Abstract

Hurricane Patricia was a historic tropical cyclone that broke many records, such as intensification rate, peak intensity, and overwater weakening rate, during its brief 4-day lifetime in late October 2015 in the eastern Pacific basin. Patricia confounded all of the intensity forecast guidance owing to its rapid intensity changes. Fortunately, the hurricane-penetrating National Oceanic and Atmospheric Administration WP-3D and U.S. Air Force C-130 aircraft and the National Aeronautics and Space Administration WB-57 high-altitude jet, under support of the Office of Naval Research, conducted missions through and over Patricia prior to and during its extreme intensity changes on all 4 days, while an extensive array of pressure sensors sampled Patricia after landfall. The observations collected from these missions include traditional data sources such as airborne Doppler radar and flight-level instruments as well as new data sources like a high-density array of dropsondes released from high-altitude and wide-swath radiometer. The combination of data from these sources and from satellites provides an excellent opportunity to investigate the physical processes responsible for Patricia’s structure and evolution and offers the potential to improve forecasts of tropical cyclone rapid intensity changes. This paper provides an overview of Patricia as well as the data collected during the aircraft missions.

Open access
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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