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Anthony J. Wimmers and Christopher S. Velden

Abstract

Conventional methods of viewing and combining retrieved geophysical fields from polar-orbiting satellites often complicate the work of end users because of the erratic time differences between overpasses, the significant time gaps between elements of a composite image, or simply the different requirements for interpretation between contributing instruments. However, it is possible to mitigate these issues for any number of retrieved quantities in which the tracer lifetime exceeds the sampling time. This paper presents a method that uses “advective blending” to create high-fidelity composites of data from polar-orbiting satellites at high temporal resolution, including a characterization of error as a function of time gap between satellite overpasses. The method is especially effective for tracers with lifetimes of longer than 7 h. Examples are presented using microwave-based retrievals of total precipitable water (TPW) over the ocean, from the Cooperative Institute for Meteorological Satellite Studies (CIMSS) Morphed Integrated Microwave Imagery at CIMSS TPW product (MIMIC-TPW). The mean average error of a global 0.25° × 0.25° product at 1-h resolution is 0.5–2 mm, which is very reasonable for most applications.

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Kenneth Holmlund, Christopher S. Velden, and Michael Rohn

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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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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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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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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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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 and Christopher S. Velden

A deep well-mixed, dry adiabatic layer forms over the Sahara Desert and Shale regions of North Africa during the late spring, summer, and early fall. As this air mass advances westward and emerges from the northwest African coast, it is undercut by cool, moist low-level air and becomes the Saharan air layer (SAL). The SAL contains very dry air and substantial mineral dust lifted from the arid desert surface over North Africa, and is often associated with a midlevel easterly jet. A temperature inversion occurs at the base of the SAL where very warm Saharan air overlies relatively cooler air above the ocean surface. Recently developed multispectral Geostationary Operational Environmental Satellite (GOES) infrared imagery detects the SAL's entrained dust and dry air as it moves westward over the tropical Atlantic. This imagery reveals that when the SAL engulfs tropical waves, tropical disturbances, or preexisting tropical cyclones (TCs), its dry air, temperature inversion, and strong vertical wind shear (associated with the midlevel easterly jet) can inhibit their ability to strengthen. The SAL's influence on TCs may be a factor in the TC intensity forecast problem in the Atlantic and may also contribute to this ocean basin's relatively reduced level of TC activity.

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Anthony J. Wimmers and Christopher S. Velden

Abstract

An improved version of the Automated Rotational Center Hurricane Eye Retrieval (ARCHER) tropical cyclone (TC) center-fixing algorithm, introduced here as “ARCHER-2,” is presented with a characterization of its accuracy and precision and a comparison with alternative methods. The algorithm is calibrated for 37- and 85–92-GHz microwave imagers; geostationary imagery at visible, near-infrared, and longwave infrared window channels; and scatterometer ambiguities. In addition to a center fix, ARCHER-2 produces a quantitative estimate of expected error that can be used automatically or manually to evaluate the suitability of a result. The median center-fix error ranges from 24 (using scatterometer) to 49 (using infrared window) km relative to the National Hurricane Center best track. Multisatellite, multisensor results can also be used together to produce a TC-track estimate that selects from the best of all of the available imagery in the ancillary “ARCHER-Track” product. The median error of ARCHER-Track varies between 17 and 38 km, depending on TC intensity and data latency. The bias of the product’s expected error varies between 0% and 12%, which translates to an average of only 4 km. When compared with operational, subjective center-fix estimates, the ARCHER-Track approach improves on 29%–43% of these cases at the tropical-depression and tropical-storm stages, at which further assistance is typically sought. This result demonstrates that ARCHER-2 and ARCHER-Track can complement and accelerate operational forecasting where needed and can furnish other automated TC-analysis methods with well-characterized center-fix information.

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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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Christopher S. Velden, Timothy L. Olander, and Raymond M. Zehr

Abstract

The standard method for estimating the intensity of tropical cyclones is based on satellite observations (Dvorak technique) and is utilized operationally by tropical analysis centers around the world. The technique relies on image pattern recognition along with analyst interpretation of empirically based rules regarding the vigor and organization of convection surrounding the storm center. While this method performs well enough in most cases to be employed operationally, there are situations when analyst judgment can lead to discrepancies between different analysis centers estimating the same storm.

In an attempt to eliminate this subjectivity, a computer-based algorithm that operates objectively on digital infrared information has been developed. An original version of this algorithm (engineered primarily by the third author) has been significantly modified and advanced to include selected “Dvorak rules,” additional constraints, and a time-averaging scheme. This modified version, the Objective Dvorak Technique (ODT), is applicable to tropical cyclones that have attained tropical storm or hurricane strength.

The performance of the ODT is evaluated on cases from the 1995 and 1996 Atlantic hurricane seasons. Reconnaissance aircraft measurements of minimum surface pressure are used to validate the satellite-based estimates. Statistical analysis indicates the technique to be competitive with, and in some cases superior to, the Dvorak-based intensity estimates produced operationally by satellite analysts from tropical analysis centers. Further analysis reveals situations where the algorithm needs improvement, and directions for future research and modifications are suggested.

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