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Carl E. Hane
,
John A. Haynes
,
David L. Andra Jr.
, and
Frederick H. Carr

Abstract

Mesoscale convective systems that affect a limited area within the southern plains of the United States during late morning hours during the warm season are investigated. A climatological study over a 5-yr period documents the initiation locations and times, tracks, associated severe weather, and relation to synoptic features over the lifetimes of 145 systems. An assessment is also made of system evolution in each case during the late morning. For a subset of 48 systems, vertical profiles of basic variables from Rapid Update Cycle (RUC) model analyses are used to characterize the environment of each system. Scatter diagrams and discriminant analyses are used to assess which environmental variables are most promising in helping to determine which of two classes of evolutionary character each system will follow.

Full access
Charles H. White
,
Imme Ebert-Uphoff
,
John M. Haynes
, and
Yoo-Jeong Noh

Abstract

Superresolution is the general task of artificially increasing the spatial resolution of an image. The recent surge in machine learning (ML) research has yielded many promising ML-based approaches for performing single-image superresolution including applications to satellite remote sensing. We develop a convolutional neural network (CNN) to superresolve the 1- and 2-km bands on the GOES-R series Advanced Baseline Imager (ABI) to a common high resolution of 0.5 km. Access to 0.5-km imagery from ABI band 2 enables the CNN to realistically sharpen lower-resolution bands without significant blurring. We first train the CNN on a proxy task, which allows us to only use ABI imagery, namely, degrading the resolution of ABI bands and training the CNN to restore the original imagery. Comparisons at reduced resolution and at full resolution with Landsat-8/Landsat-9 observations illustrate that the CNN produces images with realistic high-frequency detail that is not present in a bicubic interpolation baseline. Estimating all ABI bands at 0.5-km resolution allows for more easily combining information across bands without reconciling differences in spatial resolution. However, more analysis is needed to determine impacts on derived products or multispectral imagery that use superresolved bands. This approach is extensible to other remote sensing instruments that have bands with different spatial resolutions and requires only a small amount of data and knowledge of each channel’s modulation transfer function.

Significance Statement

Satellite remote sensing instruments often have bands with different spatial resolutions. This work shows that we can artificially increase the resolution of some lower-resolution bands by taking advantage of the texture of higher-resolution bands on the GOES-16 ABI instrument using a convolutional neural network. This may help reconcile differences in spatial resolution when combining information across bands, but future analysis is needed to precisely determine impacts on derived products that might use superresolved bands.

Open access
Yi Huang
,
Steven T. Siems
,
Michael J. Manton
,
Luke B. Hande
, and
John M. Haynes

Abstract

A climatology of the structure of the low-altitude cloud field (tops below 4 km) over the Southern Ocean (40°–65°S) in the vicinity of Australia (100°–160°E) has been constructed with CloudSat products for liquid water and ice water clouds. Averaging over longitude and time, CloudSat produces a roughly uniform cloud field between heights of approximately 750 and 2250 m across the extent of the domain for both winter and summer. This cloud field makes a transition from consisting primarily of liquid water at the lower latitudes to ice water at the higher latitudes. This transition is primarily driven by the gradient in the temperature, which is commonly between 0° and −20°C, rather than by direct physical observation.

The uniform lower boundary is a consequence of the CloudSat cloud detection algorithm being unable to reliably separate radar returns because of the bright surface versus returns due to clouds, in the lowest four range bins above the surface. This is potentially very problematic over the Southern Ocean where the depth of the boundary layer has been observed to be as shallow as 500 m. Cloud fields inferred from upper-air soundings at Macquarie Island (54.62°S, 158.85°E) similarly suggest that the peak frequency lies between 260 and 500 m for both summer and winter. No immediate explanation is available for the uniformity of the cloud-top boundary. This lack of a strong seasonal cycle is, perhaps, remarkable given the large seasonal cycles in both the shortwave (SW) radiative forcing experienced and the cloud condensation nuclei (CCN) concentration over the Southern Ocean.

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Shannon Mason
,
Jennifer K. Fletcher
,
John M. Haynes
,
Charmaine Franklin
,
Alain Protat
, and
Christian Jakob

Abstract

A deficit of shortwave cloud forcing over the Southern Ocean is persistent in many global climate models. Cloud regimes have been widely used in model evaluation studies to make a process-oriented diagnosis of cloud parameterization errors, but cloud regimes have some limitations in resolving both observed and simulated cloud behavior. A hybrid methodology is developed for identifying cloud regimes from observed and simulated cloud simultaneously.

Through this methodology, 11 hybrid cloud regimes are identified in the ACCESS1.3 model for the high-latitude Southern Ocean. The hybrid cloud regimes resolve the features of observed cloud and characterize cloud errors in the model. The simulated properties of the hybrid cloud regimes, and their occurrence over the Southern Ocean and in the context of extratropical cyclones, are evaluated, and their contributions to the shortwave radiation errors are quantified.

Three errors are identified: an overall deficit of cloud fraction, a tendency toward optically thin low and midtopped cloud, and an absence of a shallow frontal-type cloud at high latitudes and in the warm fronts of extratropical cyclones.

To demonstrate the utility of the hybrid cloud regimes for the evaluation of changes to the model, the effects of selected changes to the model microphysics are investigated.

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John M. Haynes
,
Christian Jakob
,
William B. Rossow
,
George Tselioudis
, and
Josephine Brown

Abstract

Clouds over the Southern Ocean are often poorly represented by climate models, but they make a significant contribution to the top-of-atmosphere (TOA) radiation balance, particularly in the shortwave portion of the energy spectrum. This study seeks to better quantify the organization and structure of Southern Hemisphere midlatitude clouds by combining measurements from active and passive satellite-based datasets. Geostationary and polar-orbiter satellite data from the International Satellite Cloud Climatology Project (ISCCP) are used to quantify large-scale, recurring modes of cloudiness, and active observations from CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) are used to examine vertical structure, radiative heating rates, and precipitation associated with these clouds. It is found that cloud systems are organized into eight distinct regimes and that ISCCP overestimates the midlevel cloudiness of these regimes. All regimes contain a relatively high occurrence of low cloud, with 79% of all cloud layers observed having tops below 3 km, but multiple-layered clouds systems are present in approximately 34% of observed cloud profiles. The spatial distribution of regimes varies according to season, with cloud systems being geometrically thicker, on average, during the austral winter. Those regimes found to be most closely associated with midlatitude cyclones produce precipitation the most frequently, although drizzle is extremely common in low-cloud regimes. The regimes associated with cyclones have the highest in-regime shortwave cloud radiative effect at the TOA, but the low-cloud regimes, by virtue of their high frequency of occurrence over the oceans, dominate both TOA and surface shortwave effects in this region as a whole.

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Ryan P. Crompton
,
K. John McAneney
,
Keping Chen
,
Roger A. Pielke Jr.
, and
Katharine Haynes
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Ryan P. Crompton
,
K. John McAneney
,
Keping Chen
,
Roger A. Pielke Jr.
, and
Katharine Haynes

Abstract

This study reevaluates the history of building damage and loss of life due to bushfire (wildfire) in Australia since 1925 in light of the 2009 Black Saturday fires in Victoria in which 173 people lost their lives and 2298 homes were destroyed along with many other structures. Historical records are normalized to estimate building damage and fatalities had events occurred under the societal conditions of 2008/09. There are relationships between normalized building damage and the El Niño–Southern Oscillation and Indian Ocean dipole phenomena, but there is no discernable evidence that the normalized data are being influenced by climatic change due to the emission of greenhouse gases. The 2009 Black Saturday fires rank second in terms of normalized fatalities and fourth in terms of normalized building damage. The public safety concern is that, of the 10 years with the highest normalized building damage, the 2008/09 bushfire season ranks third, behind the 1925/26 and 1938/39 seasons, in terms of the ratio of normalized fatalities to building damage. A feature of the building damage in the 2009 Black Saturday fires in some of the most affected towns—Marysville and Kinglake—is the large proportion of buildings destroyed either within bushland or at very small distances from it (<10 m). Land use planning policies in bushfire-prone parts of this country that allow such development increase the risk that bushfires pose to the public and the built environment.

Full access
Ryan P. Crompton
,
K. John McAneney
,
Keping Chen
,
Roger A. Pielke Jr.
, and
Katharine Haynes
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Steven D. Miller
,
John M. Forsythe
,
Philip T. Partain
,
John M. Haynes
,
Richard L. Bankert
,
Manajit Sengupta
,
Cristian Mitrescu
,
Jeffrey D. Hawkins
, and
Thomas H. Vonder Haar

Abstract

The launch of the NASA CloudSat in April 2006 enabled the first satellite-based global observation of vertically resolved cloud information. However, CloudSat’s nonscanning W-band (94 GHz) Cloud Profiling Radar (CPR) provides only a nadir cross section, or “curtain,” of the atmosphere along the satellite ground track, precluding a full three-dimensional (3D) characterization and thus limiting its utility for certain model verification and cloud-process studies. This paper details an algorithm for extending a limited set of vertically resolved cloud observations to form regional 3D cloud structure. Predicated on the assumption that clouds of the same type (e.g., cirrus, cumulus, and stratocumulus) often share geometric and microphysical properties as well, the algorithm identifies cloud-type-dependent correlations and uses them to estimate cloud-base height and liquid/ice water content vertical structure. These estimates, when combined with conventional retrievals of cloud-top height, result in a 3D structure for the topmost cloud layer. The technique was developed on multiyear CloudSat data and applied to Moderate Resolution Imaging Spectroradiometer (MODIS) swath data from the NASA Aqua satellite. Data-exclusion experiments along the CloudSat ground track show improved predictive skill over both climatology and type-independent nearest-neighbor estimates. More important, the statistical methods, which employ a dynamic range-dependent weighting scheme, were also found to outperform type-dependent near-neighbor estimates. Application to the 3D cloud rendering of a tropical cyclone is demonstrated.

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Carl E. Hane
,
Jill D. Watts
,
David L. Andra Jr.
,
John A. Haynes
,
Edward Berry
,
Robert M. Rabin
, and
Frederick H. Carr

Abstract

The factors that influence the evolution of convective systems during the late morning over much of the Great Plains are not understood well. It is known that in this region the majority of such systems dissipate or decrease in intensity during this period. With this fact in mind, a summary is given of comments made during the occurrence of morning convective systems by forecasters at two National Weather Service (NWS) offices relating to factors that were most important in determining their forecasts of system evolution. In addition, results of a preliminary climatological study covering eight summer months for 181 summer precipitation systems affecting the county warning areas of the two NWS offices during late morning are presented. Revealed among the significant system characteristics is that approximately two-thirds of the included systems either decreased in intensity or dissipated during the late morning.

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