Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Earth science
Reexamination Certificate
2000-02-08
2002-07-23
McElheny, Jr., Donald E. (Department: 2862)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Earth science
Reexamination Certificate
active
06424917
ABSTRACT:
Two identical copies of a computer program listing appendix have been filed in conjunction with the present application and are hereby incorporated by reference in their entireties into the present disclosure. Each copy is on a CD-R medium compatible with an IBM PC running MS Windows. The computer program listing appendix includes the following files:
Filename
Size in bytes
Creation date
Allthere.f90
582
Oct. 16, 2001
Am2.f90
2,951
Oct. 16, 2001
Am3.f90
1,576
Oct. 16, 2001
Amcomp.f90
1,984
Oct. 16, 2001
Newcity.f90
3,569
Oct. 16, 2001
Oneam.f90
6,384
Oct. 16, 2001
Seedc2.f90
2,254
Oct. 16, 2001
Seedcomp.f90
2,332
Oct. 16, 2001
Seedpick.f90
5,316
Oct. 16, 2001
Ssc.f
12,702
Oct. 16, 2001
Both copies of the computer program listing appendix were created Oct. 16, 2001. The creation date of the files on the CD-R media reflects the date of creation of the media, not the date of origination of the programs listed in the files.
BACKGROUND OF THE INVENTION
The present invention relates to a system and method for classification of air masses and more specifically to an improvement to the spatial synoptic classification.
Synoptic weather-typing, or the classification of weather conditions or patterns into categories, is an endeavor which has been undertaken numerous times within the past century, with many different methodologies, techniques, goals, and results. The reasons for synoptic classification are twofold: It is a tool for improved understanding of the climate system, and it is useful for climate impact applications. It is largely for this second reason that synoptic weather-typing has flourished once again during the past two decades; increased concern over the impacts of weather, especially for the purpose of understanding possible implications of climate change, have driven the search for more, and better, weather-typing schemes.
Synoptic climatology has been defined as a deductive science which integrates the simultaneous atmospheric dynamics and coupled response of the surface environment. While the atmospheric dynamics and the surface environment are individually studied by atmospheric scientists and members of many other sciences, only in synoptic climatology are the relationships between the two the focus of study. The synoptic climatologist usually employs statistical rather than mathematical analysis; as a result, the researcher forsakes individual atmospheric dynamic effects for the holistic-effect of the atmosphere. Indeed, it is this aggregate of conditions with which the surface environment coexists and interacts.
Classification is a rudiment of synoptic climatology; modern classification schemes can be traced back to common origins in the early part of the 20th century. There are nearly as many ways of classifying classification schemes as there arc schemes. For example, schemes have been subdivided on the basis of scale: local, regional, or global; or on the basis of methodology: objective, subjective, and multi-stage objective (which implies subjective decisions made amidst objective stages); or into subjective and automated (a more appropriate term than objective) methods. Some methods are circulation-to-environment, implying classification is done first and applied to environment later; these contrast with environment-to-circulation methods which account for environmental concerns in their classification methodology. Weather types (or air mass designations) are the goal of some schemes; map-pattern classifications of others.
Before the advent of high-speed computers, virtually all synoptic methods were subjective, or manual. Much early work, before the wide availability of upper air data, centered on air mass identification. An air mass is a contiguous and relatively homogeneous volume of air with respect to its thermal profile and moisture characteristics. Frontal theory, first promoted by the “Bergen school” of meteorologists after the end of World War I, led to the first widely used, and best-known air mass identification system. Four main air masses affecting the middle latitudes were identified: continental polar (cP), continental tropical (cT), maritime polar (mP), and maritime tropical (mT). These airmass monikers, with various modifications and refinements, have appeared in introductory meteorological textbooks to this day.
Manual techniques have gone far beyond these simple theoretical designations. The Muller Classification developed a system which has proven useful for a variety of applications, from insect populations to air quality. That system, set up for New Orleans, La., but easily extrapolated to much of the Gulf Coast, identifies eight distinct sea-level pressure and front patterns typically found in the region (e.g. “Continental High”, “Gulf Return”, “Tropical Cyclone”). Updates are continually performed, and the calendar is complete from 1951.
The Lamb Catalogue is another famous weather-typing scheme, designed for sea-level pressure patterns over the United Kingdom, but as with Muller's system, transferable elsewhere. The system contains 27 different classifications, combinations of the direction of wind flow (eight cardinal points and unclassifiable) and curvature of wind flow (cyclonic, anticyclonic, or neither). The system has been used for numerous applications, including temperature forecasting and rainfall acidity.
Developed for Central Europe, Grosswetterlagen differs from the above two systems in that it examines several-day-long patterns first and then divides them into individual days. The four main categories are zonal, meridional, mixed, and unclassified. Twenty-nine subcategories are defined by further classifying the main categories according to anticyclonic, cyclonic, directional, and strength of flow considerations. Both Grosswetterlagen and the Lamb Catalogue have been retroactively created through the 19th century.
Subjective schemes such as these have several benefits. The investigator is in full control of the process and classification, which can be performed without access to significant computer resources. The classification system can thus be tailored precisely to the researcher's needs. Unfortunately, these main attractions of manual classifications are also their drawbacks. These schemes can be difficult to export to other locations, and are also quite time consuming. Subjectivity can become excessive: different researchers will not necessarily agree on classifications for a given day; thus these schemes are not replicable.
The computer revolution of recent decades has resulted in the development of many more synoptic classification methods, especially automated ones. One such method is called correlation-based map patterns. The ultimate product is similar to Muller's, but the human decision is replaced by an automatic grouping based on similarity of (usually) sea-level pressure patterns in the region of interest. Correlation coefficients are computed between all map pairs, comparing pressure values at corresponding grid points. The first key day is the map with the highest average correlation with other maps. Maps above a certain threshold of correlation with the key day are then grouped and removed from the pool. The process then iterates; maps can later migrate to other groups if their correlation is higher with a newly selected key day. Much care must be taken in defining the several necessary parameters, namely the minimum correlation threshold and the number of categories desired. This method, unlike the manual method, assures the reproducibility of classification, and has been used for a variety of research. Of course, this method can easily produce categories which do not conform to investigator needs. Within-category variability can often be significant and reduce potential benefit from the system, and slight changes in input thresholds can result in significantly different results.
Another very common group of synoptic classification methods in recent times is eigenvector-based. Typically this involves two steps: a “reduction of variables” and clustering of those reduce
Kalkstein Lawrence S.
Sheridan Scott C.
Blank Rome Comisky & McCauley LLP
McElheny Jr. Donald E.
Surveillance Data Inc.
LandOfFree
Weather typing system and method with spatial synoptic... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Weather typing system and method with spatial synoptic..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Weather typing system and method with spatial synoptic... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-2818722