Exploring Antarctic Land Surface Temperature Extremes Using Condensed Anomaly Databases

163 Pages·2017·4.42 MB·English

University of Colorado, Boulder
CU Scholar
Geography Graduate Theses & Dissertations Geography
Spring 1-1-2017
Exploring Antarctic Land Surface Temperature
Extremes Using Condensed Anomaly Databases
Glenn Edwin Grant
University of Colorado at Boulder, [email protected]
Follow this and additional works at:https://scholar.colorado.edu/geog_gradetds
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Grant, Glenn Edwin, "Exploring Antarctic Land Surface Temperature Extremes Using Condensed Anomaly Databases" (2017).
Geography Graduate Theses & Dissertations. 115.
https://scholar.colorado.edu/geog_gradetds/115
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EXPLORING ANTARCTIC LAND SURFACE TEMPERATURE EXTREMES
USING CONDENSED ANOMALY DATABASES
by
GLENN EDWIN GRANT
B.Sc., Southern Oregon University, 1983
M.A., University of Colorado, 2012

A dissertation submitted to the
Faculty of the Graduate School of the
University of Colorado in partial fulfillment
of the requirements for the degree of
Doctor of Philosophy
Department of Geography
2017
This dissertation entitled:
Exploring Antarctic Land Surface Temperature Extremes Using Condensed Anomaly Databases
written by Glenn Edwin Grant
has been approved for the Department of Geography

______________________________________________
Professor Mark Serreze (Geography)

______________________________________________
Mr. David Gallaher (National Snow and Ice Data Center)

Date: ______________________

The final copy of this dissertation has been examined by the signatories, and we find that both
the content and the form meet acceptable presentation standards of scholarly work in the
above mentioned discipline.

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Grant, Glenn Edwin (Ph.D., Geography)
Exploring Antarctic Land Surface Temperature Extremes Using Condensed Anomaly Databases
Dissertation directed by Professor Mark Serreze

Satellite observations have revolutionized the Earth Sciences and climate studies.
However, data and imagery continue to accumulate at an accelerating rate, and efficient tools
for data discovery, analysis, and quality checking lag behind. In particular, studies of long-term,
continental-scale processes at high spatiotemporal resolutions are especially problematic. The
traditional technique of downloading an entire dataset and using customized analysis code is
often impractical or consumes too many resources.
The Condensate Database Project was envisioned as an alternative method for data
exploration and quality checking. The project’s premise was that much of the data in any
satellite dataset is unneeded and can be eliminated, compacting massive datasets into more
manageable sizes. Dataset sizes are further reduced by retaining only anomalous data of high
interest. Hosting the resulting “condensed” datasets in high-speed databases enables
immediate availability for queries and exploration.
Proof of the project’s success relied on demonstrating that the anomaly database
methods can enhance and accelerate scientific investigations. The hypothesis of this
dissertation is that the condensed datasets are effective tools for exploring many scientific
questions, spurring further investigations and revealing important information that might
otherwise remain undetected.
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This dissertation uses condensed databases containing 17 years of Antarctic land surface
temperature anomalies as its primary data. The study demonstrates the utility of the
condensate database methods by discovering new information. In particular, the process
revealed critical quality problems in the source satellite data. The results are used as the
starting point for four case studies, investigating Antarctic temperature extremes, cloud
detection errors, and the teleconnections between Antarctic temperature anomalies and
climate indices.
The results confirm the hypothesis that the condensate databases are a highly useful tool
for Earth Science analyses. Moreover, the quality checking capabilities provide an important
method for independent evaluation of dataset veracity.

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Acknowledgements

Funding for this research was provided by the National Science Foundation through the
Polar Cyberinfrastructure Program, Project 1251257, “Condensate Database for Efficient
Anomaly Detection and Quality Assurance of Massive Cryospheric Data”, David W. Gallaher and
Qin Lv principal investigators. This dissertation was also made possible with the kind help and
patient encouragement of many NSIDC staff.

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Table of Contents

1 Introduction ..................................................................................................................... 1
1.1 Background ....................................................................................................................... 2
1.1.1 Motivation ............................................................................................................. 2
1.1.2 Antarctic Land Surface Temperature Extremes..................................................... 4
1.1.3 Geography ............................................................................................................. 8
1.1.4 Objectives .............................................................................................................. 9
1.2 Previous Work ................................................................................................................ 12
1.2.1 Definition of Extreme Temperatures ................................................................... 12
1.2.2 Climate Regime Subregions ................................................................................. 15
1.2.3 Recent Climate Change Findings ......................................................................... 16
1.3 Physical Basis .................................................................................................................. 19
1.3.1 Remote Sensing of LSTs ....................................................................................... 23
1.3.2 Energy Balance at the Surface ............................................................................. 24
1.3.3 Uncertainties and Validation ............................................................................... 29
1.3.4 Comparisons between LSTs and Near-Surface Air Temperatures ...................... 33
2 Data ................................................................................................................................ 36
2.1 MODIS/Terra Land Surface Temperatures ..................................................................... 36
2.1.1 Cloud Masking Confidence Level ......................................................................... 39
2.1.2 Discovered Data Errors and Artifacts .................................................................. 40
2.2 Reanalysis Datasets ........................................................................................................ 43
2.2.1 MERRA-2 .............................................................................................................. 43
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2.2.2 ERA Interim .......................................................................................................... 44
2.3 Elevation ......................................................................................................................... 44
2.4 Surface Observations ...................................................................................................... 44
2.5 Climate Indices ............................................................................................................... 44
3 Methods ......................................................................................................................... 46
3.1 Anomaly Detection and Condensed Databases ............................................................. 46
3.1.1 Dataset Cleaning .................................................................................................. 48
3.1.2 Creating Baselines ................................................................................................ 50
3.1.3 Anomaly Determination ...................................................................................... 50
3.1.4 Creating and Using Anomaly Databases .............................................................. 51
3.2 Ancillary Analysis Programs ............................................................................................ 53
4 Results and Discussion .................................................................................................... 55
4.1 Baseline Statistics ........................................................................................................... 55
4.1.1 Sample Population ............................................................................................... 55
4.1.2 Percentiles ........................................................................................................... 57
4.1.3 Median, Mean, and Standard Deviation ............................................................. 58
4.1.4 Linear Regressions ............................................................................................... 61
4.1.5 Absolute Maxima and Minima ............................................................................ 65
4.2 Spatial Patterns of LST Extremes .................................................................................... 69
4.2.1 Highest Temperatures ......................................................................................... 69
4.2.2 Lowest Temperatures .......................................................................................... 72
4.3 Temporal Patterns of LST Extremes ............................................................................... 74
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4.3.1 Skewness .............................................................................................................. 80
4.4 Teleconnections to Climate Indices ................................................................................ 81
4.4.1 Southern Annual Mode Index .............................................................................. 83
4.4.2 Southern Oscillation Index ................................................................................... 86
4.4.3 Sea Ice Extent ....................................................................................................... 88
4.5 Case Studies .................................................................................................................... 90
4.5.1 South Pole Temperature Trend ........................................................................... 91
4.5.2 Extreme Cold event ............................................................................................. 94
4.5.3 Extreme Warm event ......................................................................................... 103
4.5.4 Cloud-Free Observations Discontinuity ............................................................. 107
5 Conclusion .................................................................................................................... 113
5.1 Findings ......................................................................................................................... 115
5.1.1 Data Quality ....................................................................................................... 115
5.1.2 Baseline Descriptive Statistics ........................................................................... 115
5.1.3 Spatial Patterns of Extremes ............................................................................. 117
5.1.4 Temporal Patterns of Extremes ......................................................................... 118
5.1.5 Teleconnections ................................................................................................. 119
5.1.6 Case Studies ....................................................................................................... 120
5.2 Applications .................................................................................................................. 122
5.3 Future Work .................................................................................................................. 124
References........................................................................................................................... 126
Appendix A. Database System Design and Performance ...................................................... 134
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A.1 Database Architecture ................................................................................................... 134
A.2 Database Administration ............................................................................................... 138
A.3 Data Ingestion................................................................................................................ 140
A.4 Data Retrieval ................................................................................................................ 141
Appendix B. Structured Query Language (SQL) Queries ....................................................... 143
B.1 Spatial Extremes Queries ............................................................................................... 143
B.2 Temporal Analysis Queries ............................................................................................ 144
B.3 Case Studies ................................................................................................................... 145
Appendix C. Acronyms and Symbols .................................................................................... 146

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