Minding the weather: how expert forecasters think
The History of Expertise Studies -- Methods for Peering Into the Black Box -- Expert Knowledge -- Expert Reasoning -- Learning and Cognitive Flexibility -- Learning -- Cognitive Flexibility and Cognitive Transformation -- Expert Perceptual Skill -- Integrated Models of Expert "Macrocognition&qu...
Gespeichert in:
| Hauptverfasser: | , , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge, Massachusetts ; London, England
The MIT Press
[2017]
|
| Schlagworte: | |
| Online-Zugang: | DE-1050 |
| Zusammenfassung: | The History of Expertise Studies -- Methods for Peering Into the Black Box -- Expert Knowledge -- Expert Reasoning -- Learning and Cognitive Flexibility -- Learning -- Cognitive Flexibility and Cognitive Transformation -- Expert Perceptual Skill -- Integrated Models of Expert "Macrocognition"--Conclusions -- 7 How Do Forecasters Get to Be Expert Forecasters? -- Expertise versus Intelligence -- Forecasting Competitions -- Recognition of the Need for Training to High Proficiency -- A General Proficiency Scale -- The Proficiency Scaling Process -- U.S. Navy Weather Forecasting Case Study -- U.S. Air Force Weather Forecasting Case Study -- Integration of the Findings -- The Forecasting Process -- The "Quick Size-Up"--Use of Computer Models -- Sensemaking -- Conclusion -- 8 What Does Research on Forecaster Knowledge Tell Us? -- Preparation -- Critical Decision Method -- Concept Mapping -- It Is Not All Just in the Head -- Conclusion -- 9 What Does Research on Forecaster Perception Tell Us? -- How and Why Diagrams and Visualizations Aid Sensemaking -- Display Design Principles: Some Work, Some Don't -- Interpretation of Weather Maps by Forecasters and Non-Forecasters -- Forecasters' Understanding of Weather Charts: Filling in the Gaps -- From Cues to Patterns to Dynamics -- Perceptual Operations during the Forecasting Process -- Conclusions -- 10 What Does Research on Forecaster Reasoning Tell Us? -- Mental Models -- Modeling Forecaster Reasoning -- Modeling Forecaster Macrocognition -- Generic versus Specific Models -- Flexecution in Forecasting -- Conclusions -- 11 Can a Machine Imitate the Human? -- Can Computers Be Made to Think Like Forecasters? -- The Structure of Forecasting KBSs -- So How Well Did the Expert Systems Perform? -- Peering into the Black Box -- Metamorphosis from Expert Systems to Intelligent Systems |
| Beschreibung: | 1 Online-Ressource (xiv, 470 Seiten) |
| ISBN: | 9780262339407 |
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| 245 | 1 | 0 | |a Minding the weather |b how expert forecasters think |c Robert R. Hoffman, Daphne S. LaDue, H. Michael Mogil, Paul J. Roebber, and J. Gregory Trafton |
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| 505 | 8 | |a About the Authors -- Preface -- Acknowledgments -- Personal Acknowledgment -- 1 Introduction -- Motivation for the Study of Forecaster Reasoning -- The Data Overload Problem -- GOES Satellite Products -- NEXRAD Radar Products -- So, How Much Data Are There? -- Coping with Data Overload -- Some Key Terms -- Sources of Information Concerning Forecaster Cognition -- 2 What Is the Forecasting Workspace Like? -- Evolution of the Modern Workstation-based Workplace -- The Rise of the Workstation: AFOS, McIDAS, and PROFS -- How Many Displays? -- Visualization Design -- PRAVDA and Met.3D -- Met.3D -- Conclusions -- A Day in the Life: A Cautionary Tale about Work System Design -- 3 How Do People Come to Be Forecasters? -- Historical Background -- Forecasting Training within Meteorological Education -- College-Level Education -- The Interdependence of Meteorology Education and Forecaster Training -- Forecaster Training -- An Ethnographic Study of How People Get to Be Forecasters -- New Learning Venues -- COMET -- INNOVATIVE WEATHER -- Some Not-so-Formal Learning Venues -- Conclusions -- 4 How Do Forecasters Describe How They Reason? -- Teamwork -- Knowledge -- Perception and Recognition -- Conceptual Models -- General Forecasting Principles -- Reasoning Process -- Forecasters' Descriptions of Forecaster Reasoning -- Conclusions -- 5 How Well Do Forecasters (and Forecasts) Perform? -- Challenges in Measuring the Goodness of Forecasts -- "Goodness" and the Context of Use -- The Challenges of Measurement -- Forecast Verification Research -- How Good Are Those Probability Forecasts? -- Predictability versus Understandability -- Linear Models: Can the Human Forecaster Outperform a Simple Linear Model? -- Forecast Quality Is More Than Just "Hit Rate" -- A Cautionary Tale -- Conclusions -- 6 What Characterizes Expertise? | |
| 520 | |a The History of Expertise Studies -- Methods for Peering Into the Black Box -- Expert Knowledge -- Expert Reasoning -- Learning and Cognitive Flexibility -- Learning -- Cognitive Flexibility and Cognitive Transformation -- Expert Perceptual Skill -- Integrated Models of Expert "Macrocognition"--Conclusions -- 7 How Do Forecasters Get to Be Expert Forecasters? -- Expertise versus Intelligence -- Forecasting Competitions -- Recognition of the Need for Training to High Proficiency -- A General Proficiency Scale -- The Proficiency Scaling Process -- U.S. Navy Weather Forecasting Case Study -- U.S. Air Force Weather Forecasting Case Study -- Integration of the Findings -- The Forecasting Process -- The "Quick Size-Up"--Use of Computer Models -- Sensemaking -- Conclusion -- 8 What Does Research on Forecaster Knowledge Tell Us? -- Preparation -- Critical Decision Method -- Concept Mapping -- It Is Not All Just in the Head -- Conclusion -- 9 What Does Research on Forecaster Perception Tell Us? -- How and Why Diagrams and Visualizations Aid Sensemaking -- Display Design Principles: Some Work, Some Don't -- Interpretation of Weather Maps by Forecasters and Non-Forecasters -- Forecasters' Understanding of Weather Charts: Filling in the Gaps -- From Cues to Patterns to Dynamics -- Perceptual Operations during the Forecasting Process -- Conclusions -- 10 What Does Research on Forecaster Reasoning Tell Us? -- Mental Models -- Modeling Forecaster Reasoning -- Modeling Forecaster Macrocognition -- Generic versus Specific Models -- Flexecution in Forecasting -- Conclusions -- 11 Can a Machine Imitate the Human? -- Can Computers Be Made to Think Like Forecasters? -- The Structure of Forecasting KBSs -- So How Well Did the Expert Systems Perform? -- Peering into the Black Box -- Metamorphosis from Expert Systems to Intelligent Systems | ||
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| author | Hoffman, Robert R. 1950- LaDue, Daphne S. Mogil, H. Michael Roebber, Paul J. Trafton, J. Gregory |
| author_GND | (DE-588)1069781231 (DE-588)140356851 |
| author_facet | Hoffman, Robert R. 1950- LaDue, Daphne S. Mogil, H. Michael Roebber, Paul J. Trafton, J. Gregory |
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| author_sort | Hoffman, Robert R. 1950- |
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| contents | About the Authors -- Preface -- Acknowledgments -- Personal Acknowledgment -- 1 Introduction -- Motivation for the Study of Forecaster Reasoning -- The Data Overload Problem -- GOES Satellite Products -- NEXRAD Radar Products -- So, How Much Data Are There? -- Coping with Data Overload -- Some Key Terms -- Sources of Information Concerning Forecaster Cognition -- 2 What Is the Forecasting Workspace Like? -- Evolution of the Modern Workstation-based Workplace -- The Rise of the Workstation: AFOS, McIDAS, and PROFS -- How Many Displays? -- Visualization Design -- PRAVDA and Met.3D -- Met.3D -- Conclusions -- A Day in the Life: A Cautionary Tale about Work System Design -- 3 How Do People Come to Be Forecasters? -- Historical Background -- Forecasting Training within Meteorological Education -- College-Level Education -- The Interdependence of Meteorology Education and Forecaster Training -- Forecaster Training -- An Ethnographic Study of How People Get to Be Forecasters -- New Learning Venues -- COMET -- INNOVATIVE WEATHER -- Some Not-so-Formal Learning Venues -- Conclusions -- 4 How Do Forecasters Describe How They Reason? -- Teamwork -- Knowledge -- Perception and Recognition -- Conceptual Models -- General Forecasting Principles -- Reasoning Process -- Forecasters' Descriptions of Forecaster Reasoning -- Conclusions -- 5 How Well Do Forecasters (and Forecasts) Perform? -- Challenges in Measuring the Goodness of Forecasts -- "Goodness" and the Context of Use -- The Challenges of Measurement -- Forecast Verification Research -- How Good Are Those Probability Forecasts? -- Predictability versus Understandability -- Linear Models: Can the Human Forecaster Outperform a Simple Linear Model? -- Forecast Quality Is More Than Just "Hit Rate" -- A Cautionary Tale -- Conclusions -- 6 What Characterizes Expertise? |
| ctrlnum | (OCoLC)1302316558 (DE-599)BVBBV047865079 |
| format | Electronic eBook |
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| id | DE-604.BV047865079 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T19:18:48Z |
| indexdate | 2024-07-20T04:08:11Z |
| institution | BVB |
| isbn | 9780262339407 |
| language | English |
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| publishDate | 2017 |
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| spelling | Hoffman, Robert R. 1950- Verfasser (DE-588)1069781231 aut Minding the weather how expert forecasters think Robert R. Hoffman, Daphne S. LaDue, H. Michael Mogil, Paul J. Roebber, and J. Gregory Trafton Cambridge, Massachusetts ; London, England The MIT Press [2017] 1 Online-Ressource (xiv, 470 Seiten) txt rdacontent c rdamedia cr rdacarrier About the Authors -- Preface -- Acknowledgments -- Personal Acknowledgment -- 1 Introduction -- Motivation for the Study of Forecaster Reasoning -- The Data Overload Problem -- GOES Satellite Products -- NEXRAD Radar Products -- So, How Much Data Are There? -- Coping with Data Overload -- Some Key Terms -- Sources of Information Concerning Forecaster Cognition -- 2 What Is the Forecasting Workspace Like? -- Evolution of the Modern Workstation-based Workplace -- The Rise of the Workstation: AFOS, McIDAS, and PROFS -- How Many Displays? -- Visualization Design -- PRAVDA and Met.3D -- Met.3D -- Conclusions -- A Day in the Life: A Cautionary Tale about Work System Design -- 3 How Do People Come to Be Forecasters? -- Historical Background -- Forecasting Training within Meteorological Education -- College-Level Education -- The Interdependence of Meteorology Education and Forecaster Training -- Forecaster Training -- An Ethnographic Study of How People Get to Be Forecasters -- New Learning Venues -- COMET -- INNOVATIVE WEATHER -- Some Not-so-Formal Learning Venues -- Conclusions -- 4 How Do Forecasters Describe How They Reason? -- Teamwork -- Knowledge -- Perception and Recognition -- Conceptual Models -- General Forecasting Principles -- Reasoning Process -- Forecasters' Descriptions of Forecaster Reasoning -- Conclusions -- 5 How Well Do Forecasters (and Forecasts) Perform? -- Challenges in Measuring the Goodness of Forecasts -- "Goodness" and the Context of Use -- The Challenges of Measurement -- Forecast Verification Research -- How Good Are Those Probability Forecasts? -- Predictability versus Understandability -- Linear Models: Can the Human Forecaster Outperform a Simple Linear Model? -- Forecast Quality Is More Than Just "Hit Rate" -- A Cautionary Tale -- Conclusions -- 6 What Characterizes Expertise? The History of Expertise Studies -- Methods for Peering Into the Black Box -- Expert Knowledge -- Expert Reasoning -- Learning and Cognitive Flexibility -- Learning -- Cognitive Flexibility and Cognitive Transformation -- Expert Perceptual Skill -- Integrated Models of Expert "Macrocognition"--Conclusions -- 7 How Do Forecasters Get to Be Expert Forecasters? -- Expertise versus Intelligence -- Forecasting Competitions -- Recognition of the Need for Training to High Proficiency -- A General Proficiency Scale -- The Proficiency Scaling Process -- U.S. Navy Weather Forecasting Case Study -- U.S. Air Force Weather Forecasting Case Study -- Integration of the Findings -- The Forecasting Process -- The "Quick Size-Up"--Use of Computer Models -- Sensemaking -- Conclusion -- 8 What Does Research on Forecaster Knowledge Tell Us? -- Preparation -- Critical Decision Method -- Concept Mapping -- It Is Not All Just in the Head -- Conclusion -- 9 What Does Research on Forecaster Perception Tell Us? -- How and Why Diagrams and Visualizations Aid Sensemaking -- Display Design Principles: Some Work, Some Don't -- Interpretation of Weather Maps by Forecasters and Non-Forecasters -- Forecasters' Understanding of Weather Charts: Filling in the Gaps -- From Cues to Patterns to Dynamics -- Perceptual Operations during the Forecasting Process -- Conclusions -- 10 What Does Research on Forecaster Reasoning Tell Us? -- Mental Models -- Modeling Forecaster Reasoning -- Modeling Forecaster Macrocognition -- Generic versus Specific Models -- Flexecution in Forecasting -- Conclusions -- 11 Can a Machine Imitate the Human? -- Can Computers Be Made to Think Like Forecasters? -- The Structure of Forecasting KBSs -- So How Well Did the Expert Systems Perform? -- Peering into the Black Box -- Metamorphosis from Expert Systems to Intelligent Systems Meteorologie (DE-588)4038953-4 gnd rswk-swf Wettervorhersage (DE-588)4079256-0 gnd rswk-swf Wettervorhersage (DE-588)4079256-0 s Meteorologie (DE-588)4038953-4 s DE-604 LaDue, Daphne S. Verfasser aut Mogil, H. Michael Verfasser (DE-588)140356851 aut Roebber, Paul J. Verfasser aut Trafton, J. Gregory Verfasser aut Erscheint auch als Druck-Ausgabe 978-0-262-03606-1 |
| spellingShingle | Hoffman, Robert R. 1950- LaDue, Daphne S. Mogil, H. Michael Roebber, Paul J. Trafton, J. Gregory Minding the weather how expert forecasters think About the Authors -- Preface -- Acknowledgments -- Personal Acknowledgment -- 1 Introduction -- Motivation for the Study of Forecaster Reasoning -- The Data Overload Problem -- GOES Satellite Products -- NEXRAD Radar Products -- So, How Much Data Are There? -- Coping with Data Overload -- Some Key Terms -- Sources of Information Concerning Forecaster Cognition -- 2 What Is the Forecasting Workspace Like? -- Evolution of the Modern Workstation-based Workplace -- The Rise of the Workstation: AFOS, McIDAS, and PROFS -- How Many Displays? -- Visualization Design -- PRAVDA and Met.3D -- Met.3D -- Conclusions -- A Day in the Life: A Cautionary Tale about Work System Design -- 3 How Do People Come to Be Forecasters? -- Historical Background -- Forecasting Training within Meteorological Education -- College-Level Education -- The Interdependence of Meteorology Education and Forecaster Training -- Forecaster Training -- An Ethnographic Study of How People Get to Be Forecasters -- New Learning Venues -- COMET -- INNOVATIVE WEATHER -- Some Not-so-Formal Learning Venues -- Conclusions -- 4 How Do Forecasters Describe How They Reason? -- Teamwork -- Knowledge -- Perception and Recognition -- Conceptual Models -- General Forecasting Principles -- Reasoning Process -- Forecasters' Descriptions of Forecaster Reasoning -- Conclusions -- 5 How Well Do Forecasters (and Forecasts) Perform? -- Challenges in Measuring the Goodness of Forecasts -- "Goodness" and the Context of Use -- The Challenges of Measurement -- Forecast Verification Research -- How Good Are Those Probability Forecasts? -- Predictability versus Understandability -- Linear Models: Can the Human Forecaster Outperform a Simple Linear Model? -- Forecast Quality Is More Than Just "Hit Rate" -- A Cautionary Tale -- Conclusions -- 6 What Characterizes Expertise? Meteorologie (DE-588)4038953-4 gnd Wettervorhersage (DE-588)4079256-0 gnd |
| subject_GND | (DE-588)4038953-4 (DE-588)4079256-0 |
| title | Minding the weather how expert forecasters think |
| title_auth | Minding the weather how expert forecasters think |
| title_exact_search | Minding the weather how expert forecasters think |
| title_exact_search_txtP | Minding the weather how expert forecasters think |
| title_full | Minding the weather how expert forecasters think Robert R. Hoffman, Daphne S. LaDue, H. Michael Mogil, Paul J. Roebber, and J. Gregory Trafton |
| title_fullStr | Minding the weather how expert forecasters think Robert R. Hoffman, Daphne S. LaDue, H. Michael Mogil, Paul J. Roebber, and J. Gregory Trafton |
| title_full_unstemmed | Minding the weather how expert forecasters think Robert R. Hoffman, Daphne S. LaDue, H. Michael Mogil, Paul J. Roebber, and J. Gregory Trafton |
| title_short | Minding the weather |
| title_sort | minding the weather how expert forecasters think |
| title_sub | how expert forecasters think |
| topic | Meteorologie (DE-588)4038953-4 gnd Wettervorhersage (DE-588)4079256-0 gnd |
| topic_facet | Meteorologie Wettervorhersage |
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