8 research outputs found
On the episodic nature of derecho-producing convective systems in the United States
Convectively generated windstorms occur over broad temporal and spatial scales; however, one of the larger-scale and
most intense of these windstorms has been given the name âderechoâ. This study illustrates the tendency for derechoproducing
mesoscale convective systems to group together across the United States â forming a derecho series. The
derecho series is recognized as any succession of derechos that develop within a similar synoptic environment with no
more than 72 h separating individual events. A derecho dataset for the period 1994â2003 was assembled to investigate
the groupings of these extremely damaging convective wind events. Results indicate that over 62% of the derechos in
the dataset were members of a derecho series. On average, nearly six series affected the United States annually. Most
derecho series consisted of two or three events; though, 14 series during the period of record contained four or more
events. Two separate series involved nine derechos within a period of nine days. Analyses reveal that derecho series
largely frequent regions of the Midwest, Ohio Valley, and the southâcentral Great Plains during May, June, and July.
Results suggest that once a derecho occurred during May, June, or July, there was a 58% chance that this event was
the first of a series of two or more, and about a 46% chance that this was the first of a derecho series consisting of
three or more events. The derecho series climatology reveals that forecasters in regions frequented by derechos should be
prepared for the probable regeneration of a derecho-producing convective system after an initial event occurs
Distribution of Mesoscale Convective Complex Rainfall in the United States
Several annual mesoscale convective complex (MCC) summaries have been compiled since Maddox strictly
defined their criteria in 1980. These previous studies have largely been independent of each other and therefore
have not established the extended spatial and temporal patterns associated with these large, quasi-circular, and,
typically, severe convective systems. This deficiency is primarily due to the difficulty of archiving enough
satellite imagery to accurately record each MCC based on Maddoxâs criteria. Consequently, this study utilizes
results from each of the MCC summaries compiled between 1978 and 1999 for the United States in order to
develop a more complete climatology, or description of long-term means and interannual variation, of these
storms. Within the 22-yr period, MCC summaries were compiled for a total of 15 yr. These 15 yr of MCC data
are employed to establish estimated tracks for all MCCs documented and, thereafter, are utilized to determine
MCC populations on a monthly, seasonal, annual, and multiyear basis. Subsequent to developing an extended
climatology of MCCs, the study ascertains the spatial and temporal patterns of MCC rainfall and determines
the precipitation contributions made by MCCs over the central and eastern United States. Results indicate that
during the warm season, significant portions of the Great Plains receive, on average, between 8% and 18% of
their total precipitation from MCC rainfall. However, there is large yearly and even monthly variability in the
location and frequency of MCC events that leads to highly variable precipitation contributions
Automated ice-sheet snowmelt detection using microwave radiometer measurements
Monitoring ice-sheet snowmelt is fundamental to understanding global climate change. A simple and automated snowmelt detection process is critical to the establishment of an ice-sheet snowmelt monitoring system. However, different ice-sheet snowmelt detection methods are based on a variety of thresholding schemes using different melt signals for dry and wet snow; these complicate the regular operation of an ice-sheet snowmelt monitoring. We propose an automated melt signal detection method developed using melt signals derived from the cross-gradient polarization ratio snowmelt detection method over Greenland and the wavelet transformation-based snowmelt detection method over Antarctica. Initial results indicate that the proposed method not only increases computational efficiency, practicability and operability but is also more accurate
Interactive Nonlinear Multiobjective Optimization Methods
An overview of interactive methods for solving nonlinear multiobjective
optimization problems is given. In interactive methods, the decision
maker progressively provides preference information so that the most
satisfactory Pareto optimal solution can be found for her or his. The
basic features of several methods are introduced and some theoretical
results are provided. In addition, references to modifications and applications
as well as to other methods are indicated. As the role of
the decision maker is very important in interactive methods, methods
presented are classified according to the type of preference information
that the decision maker is assumed to provide.peerReviewe