Data Mining Atmospheric/Oceanic Parameters in the Design of a Long-Range Nephelometric Forecast Tool (Hardcover)

Richard F. Benz

ISBN 10: 1025097319 / ISBN 13: 9781025097312

Published by Hutson Street Press, 2025

About this Item

Hardcover. The Department of Defense calls for long-range forecasts to aid in the planning of operations. The goal of this research was to explore the feasibility of predicting, one month in advance, the total monthly cloud cover over the country of Afghanistan. In an attempt to reach this goal, the following objectives were achieved: 1) climatological synoptic study of Afghanistan; 2) survey of Real Time Nephanalysis, outgoing longwave radiation (OLR), and surface observational data; 3) examination of teleconnection indices and sea surface temperatures; 4) standard statistical analysis for prediction; and 5) classification tree analysis (CART). In addition, due to current world events, CART analysis was also applied over the country of Iraq (see Appendix C). Data were examined using standard statistical regression techniques, including linear and multiple linear regression, and then CART analysis was used for exploring possible concealed predictive structures. Standard statistics showed a strong negative correlation between monthly average OLR and surface observational total cloud cover from the fall through spring months. However, linear regression revealed very weak relationships between the predictor and predictand variables. As well, CART results contained misclassification rates that exceeded established thresholds for operational use. Further studies using CART for atmospheric science applications should be pursued.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Seller Inventory # 9781025097312

Bibliographic Details

• Title: Data Mining Atmospheric/Oceanic Parameters in the Design of a Long-Range Nephelometric Forecast Tool (Hardcover)
• Publisher: Hutson Street Press
• Publication Date: 2025
• Language: English
• ISBN 10: 1025097319
• ISBN 13: 9781025097312
• Binding: Hardcover
• Condition: new

About this title

Synopsis

The Department of Defense calls for long-range forecasts to aid in the planning of operations. The goal of this research was to explore the feasibility of predicting, one month in advance, the total monthly cloud cover over the country of Afghanistan. In an attempt to reach this goal, the following objectives were achieved: 1) climatological synoptic study of Afghanistan; 2) survey of Real Time Nephanalysis, outgoing longwave radiation (OLR), and surface observational data; 3) examination of teleconnection indices and sea surface temperatures; 4) standard statistical analysis for prediction; and 5) classification tree analysis (CART). In addition, due to current world events, CART analysis was also applied over the country of Iraq (see Appendix C). Data were examined using standard statistical regression techniques, including linear and multiple linear regression, and then CART analysis was used for exploring possible concealed predictive structures. Standard statistics showed a strong negative correlation between monthly average OLR and surface observational total cloud cover from the fall through spring months. However, linear regression revealed very weak relationships between the predictor and predictand variables. As well, CART results contained misclassification rates that exceeded established thresholds for operational use. Further studies using CART for atmospheric science applications should be pursued.

This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.

This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.

As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.