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Christopher S. Velden

Satellite imagery from the VISSR (Visible Infrared Spin Scan Radiometer) Atmospheric Sounder (VAS) 6.7-μm water-vapor absorption band is normally available to the National Hurricane Center (NHC) in real time (half-hourly intervals, 16 hours a day) through a remote Man-computer Interactive Data Access System (McIDAS) workstation located in the forecast center. Synoptic features that are not readily apparent in “visible” imagery or “11-μm-infrared” imagery are often well defined in the VAS “water-vapor” imagery with the help of special enhancement software that exists on McIDAS. A good example is Hurricane Elena (1985). Its erratic path in the Gulf of Mexico was responsible for the evacuation of nearly a million people in low-lying coastal areas during a three-day period. Imagery from the VAS 6.7-μm water-vapor channel clearly shows the interaction of a midlatitude trough with the hurricane, and supports other evidence that suggests this was responsible for altering Elena's course.

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Christopher S. Velden

Abstract

The evolution of upper-tropospheric thermal patterns associated with extratropical cyclone events is often not well represented by the conventional observational network, especially in marine situations. In this paper, a potential tool for qualitatively analyzing tropopause-level thermal structure and variations based on remotely sensed passive microwave data from satellites is examined. Specifically, warm anomalies associated with tropopause undulations in upper-tropospheric waves are captured in imagery from the 54.96-GHz channel of the Microwave Sounding Unit (MSU) onboard the current series of NOAA polar-orbiting satellites. Examples of this imagery during selected western North Atlantic cyclone events are presented, and the potential usefulness of these observations in analysis and forecasting is discussed.

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Christopher S. Velden

Abstract

Passive microwave observations from the current NOAA series of polar-orbiting satellites of a large sample of North Atlantic tropical cyclones are qualitatively and quantitatively analyzed. Microwave observations can penetrate the cloud cover associated with tropical cyclones and capture the upper-level warm temperature anomaly, which is characteristic of these storms. The data are used to develop a statistical algorithm for estimating surface intensity. Based upon hydrostatic assumptions, linear regression relationships are developed between the satellite-depicted horizontal temperature gradient of the upper-level warm core (ΔT 250), and the surface intensity (ΔP SFC) as measured by reconnaissance reports. A good correlation is found to exist. Results indicate that standard errors of estimate of 8 mb and 13 kts are found for surface pressure and maximum winds, respectively. These errors are reduced when the effects of storm latitude, eye size, and surface-pressure tendency on the relationship are included. Knowledge gained in examining the accuracies and limitations of the current microwave sounders in tropical cyclone applications will be helpful in setting quantitative observational guidelines for future instruments.

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Jeffrey Hawkins and Christopher Velden

Atmospheric and oceanographic field experiments are an important part of research programs aimed at enhancing observational analyses of meteorological and oceanic phenomena, validating new datasets, and/or supporting hypotheses. The Bulletin of the American Meteorological Society (BAMS) has chronicled many field programs, with a primary focus on the enhanced observational assets that were assembled to enable the projects' investigations. However, these field program summaries often overlook the multiple roles that satellite digital data, multispectral imagery, and derived products can play in premission planning, real-time forecasting and mission guidance, and extensive post–field phase analysis. In turn, these intensive observing periods often serve as crucial validation datasets for remotely sensed products and derived fields.

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Christopher S. Velden and John Sears

Abstract

Vertical wind shear is well known in the tropical cyclone (TC) forecasting community as an important environmental influence on storm structure and intensity change. The traditional way to define deep-tropospheric vertical wind shear in most prior research studies, and in operational forecast applications, is to simply use the vector difference of the 200- and 850-hPa wind fields based on global model analyses. However, is this rather basic approach to approximate vertical wind shear adequate for most TC applications? In this study, the traditional approach is compared to a different methodology for generating fields of vertical wind shear as produced by the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies (CIMSS). The CIMSS fields are derived with heavy analysis weight given to available high-density satellite-derived winds. The resultant isobaric analyses are then used to create two mass-weighted layer-mean wind fields, one upper and one lower tropospheric, which are then differenced to produce the deep-tropospheric vertical wind shear field. The principal novelty of this approach is that it does not rely simply on the analyzed winds at two discrete levels, but instead attempts to account for some of the variable vertical wind structure in the calculation. It will be shown how the resultant vertical wind shear fields derived by the two approaches can diverge significantly in certain situations; the results also suggest that in many cases it is superior in depicting the wind structure's impact on TCs than the simple two-level differential that serves as the common contemporary vertical wind shear approximation.

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John Sears and Christopher S. Velden

Abstract

Fields of atmospheric motion vectors (AMVs) are routinely derived by tracking features in sequential geostationary satellite infrared, water vapor, and visible-channel imagery. While AMVs produced operationally by global data centers are routinely evaluated against rawinsondes, there is a relative dearth of validation opportunities over the tropical oceans—in particular, in the vicinity of tropical disturbances when anomalous flow fields and strongly sheared environments commonly exist. A field experiment in 2010 called Pre-Depression Investigation of Cloud-Systems in the Tropics (PREDICT) was conducted in the tropical west Atlantic Ocean and provides an opportunity to evaluate the quality of tropical AMVs and analyses derived from them. The importance of such a verification is threefold: 1) AMVs often provide the only input data for numerical weather prediction (NWP) over cloudy areas of the tropical oceans, 2) NWP data assimilation methods are increasingly reliant on accurate flow-dependent observation-error characteristics, and 3) global tropical analysis and forecast centers often rely on analyses and diagnostic products derived from the AMV fields. In this paper, the authors utilize dropsonde information from high-flying PREDICT aircraft to identify AMV characteristics and to better understand their errors in tropical-disturbance situations. It is found that, in general, the AMV observation errors are close to those identified in global validation studies. However, some distinct characteristics are uncovered in certain regimes associated with tropical disturbances. High-resolution analyses derived from the AMV fields are also examined and are found to be more reflective of anomalous flow fields than the respective Global Forecast System global model analyses.

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Christopher S. Velden and Derrick Herndon

ABSTRACT

A consensus-based algorithm for estimating the current intensity of global tropical cyclones (TCs) from meteorological satellites is described. The method objectively combines intensity estimates from infrared and microwave-based techniques to produce a consensus TC intensity estimate, which is more skillful than the individual members. The method, called Satellite Consensus (SATCON), can be run in near–real time and employs information sharing between member algorithms and a weighting strategy that relies on the situational precision of each member. An evaluation of the consensus algorithm’s performance in comparison with its individual members and other available operational estimates of TC intensity is presented. It is shown that SATCON can provide valuable objective intensity estimates for poststorm assessments, especially in the absence of other data such as provided by reconnaissance aircraft. It can also serve as a near-real-time estimator of TC intensity for forecasters, with the ability to quickly reconcile differences in objective intensity methods and thus decrease the uncertainty and amount of time spent on the intensity analysis. Near-real-time SATCON estimates are being provided to global operational TC forecast centers.

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Kenneth Holmlund, Christopher S. Velden, and Michael Rohn

Abstract

The coverage and quality of atmospheric motion vectors (AMVs) derived from geostationary satellite imagery have improved considerably over the past few years. This is due not only to the deployment of the new generation of satellites, but is also a result of improved data processing and automated quality control (AQC) schemes. The postprocessing of the Geostationary Operational Environmental Satellite (GOES) derived displacement vectors at the National Oceanic and Atmospheric Administration/National Environmental Satellite, Data, and Information Service (NOAA/NESDIS) has been fully automated since early 1996. At the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) AQC was used as support to the manual quality control (MQC) for Meteosat vector fields until September 1998 when the MQC was discontinued and fully replaced with the automated procedure. The AQC schemes at the two organizations are quite diverse. Based on a method developed at the University of Wisconsin–Cooperative Institute for Meteorological Satellite Studies, the NOAA/NESDIS AQC involves an objective three-dimensional recursive filter analysis of the derived wind fields. The fit of each vector to that analysis yields a recursive filter flag (RFF). The AQC scheme employed at EUMETSAT derives a quality indicator (QI) for each individual vector based on the properties of the vector itself and its consistency with other AMVs in close proximity. Mainly relying on satellite data, this QI-based scheme has been proven to provide a good estimate of the reliability of the derived displacements, but it fails to identify fleets of winds that are consistently assigned to a wrong height. The RFF-based scheme is capable of readjusting the heights attributed to the wind vectors, which yields a better fit to the analysis and ancillary data. These quality estimates can be employed by the user community to select the part of the vector field that best suits their application, as well as in data assimilation schemes for optimizing the data selection procedures. Even though both schemes have already been successfully implemented into operational environments, the possibility exists to exploit the advantages of both approaches to create a superior combined methodology.

In order to substantiate the differences of the two methodologies, the two schemes were applied to the high-density AMV fields derived during the 1998 North Pacific Experiment from GOES and the Geostationary Meteorological Satellite (controlled by the Japan Meteorological Agency) multispectral imagery data. The performance of the two schemes was evaluated by examining departures from the analysis fields of the European Centre for Medium-Range Weather Forecasts (ECMWF) assimilation scheme, and a new combined methodology was further evaluated by looking at the impact on medium-range forecasts verified against the operational forecasts. It will be shown that the new combined AQC approach yields superior ECMWF forecast results.

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Shixuan Zhang, Zhaoxia Pu, and Christopher Velden

Abstract

The impacts of enhanced satellite-derived atmospheric motion vectors (AMVs) on the numerical prediction of intensity changes during Hurricanes Gonzalo (2014) and Joaquin (2015) are examined. Enhanced AMVs benefit from special data-processing strategies and are examined for impact on model forecasts via assimilation experiments by employing the National Centers for Environmental Prediction (NCEP) operational Hurricane Weather Research and Forecasting (HWRF) Model using a Gridpoint Statistical Interpolation analysis system (GSI)-based ensemble–variational hybrid system. Two different data assimilation (DA) configurations, one with and one without the use of vortex initialization (VI), are compared. It is found that the assimilation of enhanced AMVs can improve the HWRF track and intensity forecasts of Gonzalo and Joaquin during their intensity change phases. The degree of data impact depends on the DA configuration used. Overall, assimilation of enhanced AMVs in the innermost domain (e.g., storm inner-core region and its immediate vicinity) outperforms other DA configurations, both with and without VI, as it results in better track and intensity forecasts. Compared to the experiment with VI, assimilation of enhanced AMVs without VI reveals more notable data impact on the forecasts of Hurricane Gonzalo, as the VI before DA alters the first guess and reduces the actual number of AMV observations assimilated into the DA system. Even with VI, assimilation of enhanced AMVs in the inner-core region can at least partially mitigate the negative effect of VI on the intensity forecast of Hurricane Gonzalo and alleviate the unrealistic vortex weakening in the simulation by removing unrealistic outflow structure and unfavorable thermodynamic conditions, thus leading to improved intensity forecasts.

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Christopher S. Velden and John A. Young

Abstract

The 1992/93 Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (COARE) was specifically designed to monitor multiscale interactions between the atmosphere and ocean over the western Pacific warm pool. To help meet this objective, satellite observations were used to augment the enhanced COARE conventional data array in both space and time.

In this paper the authors present a descriptive overview of convective cloud variability and sea surface temperature during the four-month intensive observational period (IOP) as revealed by satellite. Time series of Geostationary Meteorological Satellite infrared brightness temperatures are evaluated at selected equatorial locations in the western Pacific and eastern Indian Oceans. Intraseasonal modes of transient convection/cloudiness are revealed, with two eastward-propagating Madden-Julian oscillations identified. Spectral analysis on the time series data indicates that higher-frequency variations in regional convective activity are also found to occur.

Several satellite cloud signatures and patterns were detected during a strong west wind burst event in late December (1992), and these are described in detail. Time-composited sea surface temperature (SST) fields derived from satellite radiances indicate that significant regional variations in SST occurred during the passage of the west wind event. The satellite-derived SST fields compiled during the IOP are validated against in situ observations in the COARE domain, with a 0.25°C warm bias noted in the composited satellite data.

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