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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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John Lewis, Andrew Van Tuyl, and Christopher Velden

Abstract

Deep-layer mean winds over the tropical Atlantic are routinely derived during the hurricane season at the Space Science and Engineering Center, Madison, Wisconsin, using imagery and soundings from the VISSR Atmospheric Sounder (VAS) aboard GOES. These analyses are 6–12 h apart and a method has been developed to build continuity into these winds. First, a static analysis is made at each time which vertically blends gradient wind shear derived from VAS temperatures with winds derived from tracking the visible and infrared imagery. The deep layer mean (DLM) winds that come from the static analyses are subsequently adjusted in time using the conservation of absolute vorticity as a constraint.

This methodology is used to derive the large-scale circulation that accompanied Hurricane Debby (1982) in the Atlantic Ocean. Dropwindsonde data collected around Debby and the National Meteorological Center's analyses are used to qualitatively verify the analyses. Results indicate dial the vertical blending process is especially valuable in reconstructing the synoptic flow when the track winds are sparse at midlevel. The temporal adjustment is applied to three analysis periods and acts like an averaging process that smooths the fields. Subjective verification of the time adjusted DLM winds indicates an improvement at the initial time, but a degradation at the final time.

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James P. Kossin and Christopher S. Velden

Abstract

A pronounced and highly significant bias is uncovered in tropical cyclone minimum sea level pressure (MSLP) estimates calculated using the Dvorak technique. The bias is present in operational estimates from each of the primary Atlantic tropical analysis centers (TACs). The bias can be approximated as a linear function of latitude and is caused by the dependence of tropopause temperature on latitude. On average, MSLP estimates from each TAC are consistently too high (compared to aircraft reconnaissance measurements) at higher latitudes and too low at lower latitudes. The latitude of zero bias is near 23°N. Because the relationship between tropopause temperature and latitude is fairly robust among the global ocean basins, the latitude-dependent bias that exists in Dvorak technique MSLP estimates of Atlantic basin tropical cyclones should extend to Dvorak technique estimates in all ocean basins.

A simple linear fit is constructed between the Dvorak technique MSLP estimate errors and latitude, and this is applied as a latitude-dependent bias correction to the MSLP estimates. The correction has a significant effect on the error statistics of the samples from each TAC. Root-mean-square error is reduced by roughly 11%, 9%, and 10%, respectively, in the Tropical Analysis and Forecast Branch (TAFB), Satellite Analysis Branch (SAB), and Air Force Global Weather Center (AFGWC) samples.

Using available wind data, it is shown that a much weaker latitude-dependent bias exists in Dvorak technique estimates of near-surface wind (V max). This is consistent with a recent study that used aircraft-based data from Atlantic tropical cyclones (TCs) to demonstrate that for a given MSLP, the associated measured V max tends to be weaker at higher latitudes. The empirical relationship between MSLP and V max used in the Dvorak technique has no dependence on latitude, which indirectly introduces a bias in the estimated wind that counteracts the bias in the MSLP estimates. This suggests that historical best-track data formed using Dvorak technique estimates contain a systematic latitude-dependent MSLP bias and a systematic inconsistency in the relationship between MSLP and V max. Correction of the MSLP bias in past tropical cyclones that were estimated using the Dvorak technique may have measurable effects on the present tropical cyclone climatology.

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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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Jason P. Dunion and Christopher S. Velden

Abstract

Beginning with the 1997 hurricane season, the Cooperative Institute for Meteorological Satellite Studies at the University of Wisconsin—Madison began demonstrating the derivation of real-time Geostationary Operational Environmental Satellite (GOES) low-level cloud-drift winds in the vicinity of Atlantic tropical cyclones. The winds are derived from tracking low-level clouds in sequential, high-resolution GOES visible channel imagery. Since then, these data have been provided to the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Division (HRD) for evaluation in their real-time tropical cyclone surface wind objective analyses (H*Wind) that are disseminated to forecasters at the NOAA National Hurricane Center on an experimental basis. These wind analyses are proving useful as guidance to support forecasters's tropical cyclone advisories and warnings. The GOES satellite wind observations often provide essential near-surface coverage in the outer radii of the tropical cyclone circulation where conventional in situ observations (e.g., ships and buoys) are frequently widely spaced or nonexistent and reconnaissance aircraft do not normally fly. The GOES low-level cloud-tracked winds are extrapolated to the surface using a planetary boundary layer model developed at HRD for hurricane environments.

In this study, the unadjusted GOES winds are validated against wind profiles from the newly deployed global positioning system dropwindsondes, and the surface-adjusted winds are compared with collocated in situ surface measurements. The results show the ability of the GOES winds to provide valuable quantitative data in the periphery of tropical cyclones. It is also shown that the current scheme employed to extrapolate the winds to the surface results in small biases in both speed and direction. Nonlinear adjustments to account for these biases are presented.

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Kurt F. Brueske and Christopher S. Velden

Abstract

Satellite-borne passive microwave radiometers, such as the Advanced Microwave Sounding Unit (AMSU) on the NOAA polar-orbiting series, are well suited to monitor tropical cyclones (TCs) by virtue of their ability to assess changes in tropospheric warm core structure in the presence of clouds. The temporal variability in TC upper-tropospheric warm anomaly (UTWA) size, structure, and magnitude provides vital information on changes in kinematic structure and minimum sea level pressure (MSLP) through well-established thermodynamic and dynamic principles. This study outlines the aspects of several factors affecting the effective AMSU measurement accuracy of UTWAs, including the practical application of a previously developed maximum likelihood regression algorithm designed to explicitly correct for TC scan geometry and UTWA–antenna gain pattern interaction issues (UTWA subsampling) unique to TC warm core applications. This single-channel AMSU approach (54.96 GHz) is the first step toward a more elaborate multichannel application that is currently under study. Independent application of the single-channel algorithm in the Atlantic and eastern Pacific basins in 2000 and 2001 demonstrates that AMSU-derived UTWAs are moderately correlated with coincident TC MSLP. In addition, further improvements in correlation, and MSLP estimate accuracy, are possible through application of the proposed corrective retrieval algorithm, provided that 1) accurate estimates of TC eye size (a proxy for the UTWA horizontal dimension) are available and 2) the peak upper-tropospheric warming represented by the AMSU-A 54.94-GHz radiances corresponds with the actual TC thermal structure. This study recommends potential remedies for both of these algorithm skill prerequisites that include the incorporation of improved eye size estimates from ancillary data sources and/or the utilization of additional AMSU-A upper-tropospheric sounding channels.

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Robert T. Merrill and Christopher S. Velden

Abstract

Isentropic coordinate analyses of rawinsondes and cloud motion wind vectors derived from geostationary satellite imagery are employed to describe the three-dimensional upper-tropospheric and lower-stratospheric circulation attending western North Pacific Supertyphoon Flo during September 1990. Outflow from the storm is concentrated in several evolving channels in the horizontal. In terms of vertical structure, net outflow evaluated at 6° latitude (666 km) radius is found to occur at higher levels and over an increasing range of potential temperature θ as the tropical cyclone intensifies. Outflow on the equatorward side of the tropical cyclone tends to occur at greater θ values (higher altitudes) than poleward outflow. Potential vorticity also decreases within the corresponding isentropic layers associated with the outflow. The implications of the vertical variability of outflow structure in terms of the interactions between storm and environment, and effects on storm structural changes, are considered briefly.

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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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Anthony Wimmers, Christopher Velden, and Joshua H. Cossuth

Abstract

A deep learning convolutional neural network model is used to explore the possibilities of estimating tropical cyclone (TC) intensity from satellite images in the 37- and 85–92-GHz bands. The model, called “DeepMicroNet,” has unique properties such as a probabilistic output, the ability to operate from partial scans, and resiliency to imprecise TC center fixes. The 85–92-GHz band is the more influential data source in the model, with 37 GHz adding a marginal benefit. Training the model on global best track intensities produces model estimates precise enough to replicate known best track intensity biases when compared to aircraft reconnaissance observations. Model root-mean-square error (RMSE) is 14.3 kt (1 kt ≈ 0.5144 m s−1) compared to two years of independent best track records, but this improves to an RMSE of 10.6 kt when compared to the higher-standard aircraft reconnaissance-aided best track dataset, and to 9.6 kt compared to the reconnaissance-aided best track when using the higher-resolution TRMM TMI and Aqua AMSR-E microwave observations only. A shortage of training and independent testing data for category 5 TCs leaves the results at this intensity range inconclusive. Based on this initial study, the application of deep learning to TC intensity analysis holds tremendous promise for further development with more advanced methodologies and expanded training datasets.

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Jason P. Dunion, Christopher D. Thorncroft, and Christopher S. Velden

Abstract

The diurnal cycle of tropical convection and the tropical cyclone (TC) cirrus canopy has been described extensively in previous studies. However, a complete understanding of the TC diurnal cycle remains elusive and is an area of ongoing research. This work describes a new technique that uses infrared satellite image differencing to examine the evolution of the TC diurnal cycle for all North Atlantic major hurricanes from 2001 to 2010. The imagery reveals cyclical pulses in the infrared cloud field that regularly propagate radially outward from the storm. These diurnal pulses begin forming in the storm’s inner core near the time of sunset each day and continue to move away from the storm overnight, reaching areas several hundreds of kilometers from the circulation center by the following afternoon. A marked warming of the cloud tops occurs behind this propagating feature and there can be pronounced structural changes to a storm as it moves away from the inner core. This suggests that the TC diurnal cycle may be an important element of TC dynamics and may have relevance to TC structure and intensity change. Evidence is also presented showing the existence of statistically significant diurnal signals in TC wind radii and objective Dvorak satellite-based intensity estimates for the 10-yr hurricane dataset that was examined. Findings indicate that TC diurnal pulses are a distinguishing characteristic of the TC diurnal cycle and the repeatability of TC diurnal pulsing in time and space suggests that it may be an unrealized, yet fundamental TC process.

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