Syllabus

Course Code & Title: ENVS 0070G, Historical climatology and global climate change
Semester: Fall Days: T Th Time: 2:30-3:50pm
Classroom Location: Smith-Buonanno Hall 206
Instructor:

Dr. Daniel Ibarra, Assistant Professor of Earth, Environmental, and Planetary Sciences and Environment and Society

Dr. Natasha Sekhon, Voss Postdoctoral and Presidential Diversity Fellow

Preferred Contact Info: daniel_ibarra@brown.edu; natasha_sekhon@brown.edu
Office Hours: Dr. Ibarra – Mondays 2pm; Dr. Sekhon – Wednesdays 9am
Office Location: Ibarra: IBES 314; Sekhon: IBES 218
Prerequisites: none
Web Content: https://sites.brown.edu/envs-0070g/

SYLLABUS

 

COURSE DESCRIPTION:

This course will look at climate trends through the lens of civilizations across the globe. The Maya, Indus and Nile have been cradles to great civilizations, each impacted to a different degree by climate variability. Climate change is now causing history to repeat itself through the displacement of people as climate refugees in places such as Honduras, Pakistan and Ethiopia. In this course, we will focus on and analyze instrumental, observational and geologic datasets to assess the role of climate in shaping past civilization and modern society.

 

We will use Python (an open-source coding language) to conduct statistical analyses to investigate climate trends on a daily to millennial timescales, interface with digitization efforts of historical records, and discuss literature looking at the role of climate in shaping society and ancient civilizations. Our course will also introduce the study of past climates, paleoclimatology, when observational data was not present. The course will end by discussing the future of our global civilization. As a final project, students in groups of 3-4, will pick a time period and location of interest over the last millennium to analyze climate datasets.

 

COURSE GOALS:

By the end of this course, students will be able to:

1) Think like an environmental scientist: Differentiate between observations and interpretations of climate data. Utilizing the scientific method to come to conclusions.

2) Analytical Skills: Critically evaluate data from multiple sources. Test hypothesis using the correct statistical tests.

3) Creative Problem Solving: Identify and access appropriate data, archives, resources to assess climate trends. Formulate and design independent research. Integrate knowledge from multiple sources.

4) Communication: Ability to summarize and communicate effectively through professional writing. Use of visual representation of data and results. Communicate effectively through oral presentation.

 

COURSE RELATED WORK EXPECTATIONS:

Over 14 weeks, students will spend 3 hours per week in class (42 hours total). Assignments and readings are estimated at around 4 hours per week (56 hours).

(42 hrs + 56 hrs = 98 hrs)

 

WRITING REQUIREMENT

As this is a WRIT-designated course, you will be required to complete a minimum of two written assignments. You will receive substantive feedback on your writing, which you will use to help you revise your work or to complete subsequent writing assignments.

 

ACCESSIBILITY AND ACCOMMODATIONS:

Brown University is committed to full inclusion of all students. Please inform me early in the term if you have a disability or other conditions that might require accommodations or modification of any of these course procedures. You may speak with me after class or during office hours. For more information, please contact Student and Employee Accessibility Services at 401-863-9588 or SEAS@brown.edu. Students in need of short-term academic advice or support can contact one of the deans in the Dean of the College office.

 

DIVERSITY AND INCLUSION

It is our intent that students from all diverse backgrounds and perspectives be well served by this course, that students’ learning needs be addressed both in and out of class, and that the diversity that students bring to this class be viewed as a resource, strength and benefit. It is my intent to present materials and activities that are respectful of diversity: gender, sexuality, disability, age, socioeconomic status, ethnicity, race, and culture. Your suggestions are encouraged and greatly appreciated, and can be integrated into discussions as the semester evolves. Please let me know ways to improve the effectiveness of the course for you personally or for other students or student groups. In addition, if any of our class meetings conflict with your religious events, please let me know so that we can make arrangements for you. (Adapted from: University of Iowa College of Education)

 

Furthermore, we want to create a learning environment for students that supports a diversity of thoughts, perspectives and experiences, and honors your identities (including race, gender, class, sexuality, religion, ability, etc.) To help accomplish this:

  • If you have a name and/or set of pronouns that differ from those that appear in your official Brown records, please let your professor and teaching assistants know.
  • If you feel like your performance in the class is being impacted by your experiences outside of class, please don’t hesitate to come and talk with your instructor, as they want to be a resource for you. Remember that you can also submit anonymous feedback via the feedback form linked in canvas (which will lead to your instructor making a general announcement to the class, if necessary to address your concerns). If you prefer to speak with someone outside of the course, Dean Bhattacharyya, Associate Dean of the College for Diversity Programs, is an excellent resource.
  • All of us are still in the process of learning about diverse perspectives and identities. If something was said in class (by anyone) that made you feel uncomfortable, please talk to your professor about it. (Again, anonymous feedback is always an option).

 

BOOKS, SUPPLIES & MATERIALS

The course will be divided into a series of quantitative lab-based assignments where students will develop coding skills. The instructor will provide Jupyter Notebook exercises for students to finish in class, which will be hands-on and encourage peer to peer learning. Subsequent assignments will be based on in class exercises.

 

The course will also have a lecture component where instructor will provide PowerPoint presentations discussing meteorological concepts and relevant Peer-Reviewed Journal Articles. Students will visit the John Carter Brown Library and view the evolution of historical weather maps. The trip will be followed by a discussion on the value in historic maps, who made the maps and the reason behind their existence.

 

Brown University undergraduates with concerns about the non-tuition cost(s) of a course at Brown, including this course, may apply to the Dean of the College Academic Emergency Fund to determine options for financing these costs, while ensuring their privacy. The fund can be found in the Emergency Funds, Curricular & Co-curricular Gap (E-Gap) Funds in UFunds. Information and procedures are available here.

 

SUPPLEMENTARY READINGS

There is no required textbook, the instructor will provide relevant chapters from books and journals through Canvas. But if students are interested, the course will heavily draw from Climate Dynamics by Kerry H. Cook (Princeton Press), Paleoclimatology: Reconstructing Climates of the Quaternary by Raymond Bradley (Academic Press), Climate Reconstruction and Impacts from the Archives of Society PAGES.

 

ASSESSMENT:

Engagement through active class participation is the best way to learn and retain information taught in class. Your participation grade will therefore be determined by each student’s level of participation during the lecture and lab sections of the course. If a concept or exercise is not clear, students are encouraged to request clarification from the instructor through a respectful approach and attend office hours if needed.

 

Grades will be determined by the following levels of performance

  • Class Participation and Discussion – 15% (5% Participation, 10% Canvas Paper Discussions)
  • Assignments – 25% (5x, 5% each)
  • Project Proposal – 20%
  • Final Project – 35% (20% final report, 15% final presentation)
  • Class Attendance – 5%

 

MISSED EXAMS OR ASSIGNMENTS (including late assignments)

Late submissions of any assignment will not be accepted, except under documented emergency circumstances. We encourage you to use e-mail or meet with us after class at the earliest to resolve any concerns.

 

ACADEMIC INTEGRITY

Academic achievement is ordinarily evaluated on the basis of work that a student produces independently. Students who submit academic work that uses others’ ideas, words, research, or images without proper attribution and documentation are in violation of the academic code. Infringement of the academic code entails penalties ranging from reprimand to suspension, dismissal, or expulsion from the University.

 

A student’s name on any exercise (e.g., a theme, report, notebook, performance, computer program, course paper, quiz, or examination) is regarded as assurance that the exercise is the result of the student’s own thoughts and study, stated in their own words, and produced without assistance, except as quotation marks, references, and footnotes acknowledging the use of printed sources or other outside help (Academic Code, p. 5).

 

GUIDELINES FOR DISCUSSION

In class discussion is an important learning component of this course.  Ideas and comments should be expressed thoughtfully and with respect to one’s peers.  Critiques should remain civil and allow for rebuttal.  It’s also important to allow time for others to participate and never interrupt or talk over fellow students.  Respecting your peers and openly listening to their comments creates a positive learning environment.

 

COURSE POLICIES:

Phones should be set to silent mode and put away.  Laptop computers are allowed only for the purpose of note-taking and class related work (such as coding exercises).  Students who misuse technology will be expected to take hand written notes instead.  Multiple infractions will negatively impact the student’s final participation grade.

COURSE CALENDAR/OUTLINE:

Date Topic Assignment
Thursday, September 8 Introduction To Course No Reading
Tuesday, September 13

Climate vs. weather

Python: Read csv files, Dataframes, Datetime Function

  1. Gaia Vince “The century of climate migration: why we need to plan for the great upheaval” 2022, The Guardian.

Chapter 1 -3 of Atmosphere, Weather and Climate by Barry and Chorley

Thursday, September 15 Climate Variability Across Scales (CVAS): Diurnal Variability and Synoptic Variability Chapters 3, 9-12 from Ahrens’ Meteorology Today
Tuesday, September 20

Types of Data: Observational Data

Python: Plotting with matplotlib 

LIDAR of Maya

https://www.nationalgeographic.com/history/article/maya-laser-lidar-guatemala-pacunam

Intro to climate models

https://www.climate.gov/maps-data/climate-data-primer/predicting-climate/climate-models

Thursday, September 22 CVAS: Monsoons

Chapter 1 and 2 of The Monsoons and Climate Change by Carvalho and Jones

          Assignment 1 Due

Tuesday, September 27

CVAS: Hurricanes & Forest Fires

Python: Time-Series Analysis I 

  • What is a Time Series? 
  • Visualize the Time Series
  • Patterns in a Time Series
  • Detrend a Time Series 
  • Deseasonalize a Time Series

Swain, Daniel L. “A shorter, sharper rainy season amplifies California wildfire risk.” Geophysical Research Letters 48.5 (2021): e2021GL092843.

Burrows, Kate, and Patrick L. Kinney. “Exploring the climate change, migration and conflict nexus.” International journal of environmental research and public health 13.4 (2016): 443

Thursday, September 29

Types of Data: Historical Records

and Crowd Sourced Science

 

Old Weather – Transcribed Historic Ship Logs;

BBC’s Shipping Forecast;

Bocanegra-Valle, Ana. “The constructing of shipping forecasts in English: A pilot study.” Procedia-Social and Behavioral Sciences 212 (2015): 278-282.;

Cullen, Beth, and Christina Leigh Geros. “Constructing the Monsoon: Colonial Meteorological Cartography, 1844–1944.” History of Meteorology 9 (2020)

 

Tuesday, October 4

Python: Time-Series Analysis II

(Autocorrelation Tests; Lag Plots; Dealing with Missing Data; Smoothing Data)

Assignment 2 Due
Thursday, October 6 CVAS: El Nino Southern Oscillation; Decadal to Multidecadal Variability

Trenberth, K. El. “El Niño southern oscillation (ENSO).” Sea (1996).

McPhaden, Michael J., Stephen E. Zebiak, and Michael H. Glantz. “ENSO as an integrating concept in earth science.” science 314.5806 (2006): 1740-1745.

   Initial Final Project Topic Discussion/Brainstorming

Tuesday, October 11 CANCELED
Thursday, October 13

Python: Statistical Tests I

(Descriptive Statistical Tests; Correlation Coefficients) 

Open Source Climate Data: NOAA Data Base/Climate Explorer

WMO’s Climate Explorer; NOAA’s NCEI

NOAA’s Reanalysis Dataset (Gridded)

 

Tuesday, October 18

Python: Statistical Tests II

 (Regression Analysis; T-Tests)

Assignment 3 Due
Thursday, October 20 CVAS: Floods and Droughts Trenberth, Kevin E. “The impact of climate change and variability on heavy precipitation, floods, and droughts.” Encyclopedia of hydrological sciences 17 (2005).
Tuesday, October 25 CVAS: Intrinsic (Milankovitch cycles) vs External (Volcanic) Forcings Chapter 2 of Paleoclimatology by Bradley
Thursday, October 27 Paleoclimatology Archives and Proxies Selected sections from Paleoclimatology by Bradley with a focus on stable isotope records
Tuesday, November 1 Drs. Kate Burrows and Raymond Hunter

Deng, Hengfang, et al. “High-resolution human mobility data reveal race and wealth disparities in disaster evacuation patterns.” Humanities and Social Sciences Communications 8.1 (2021): 1-8.

Arnold, T. Elliott, et al. “Drought and the collapse of the Tiwanaku Civilization: New evidence from Lake Orurillo, Peru.” Quaternary Science Reviews 251 (2021): 106693.

 

Thursday, November 3

Climate and Civilization: Maya

Assignment 4 Due

Medina-Elizalde, Martín, et al. “High-resolution speleothem record of precipitation from the Yucatan Peninsula spanning the Maya Preclassic Period.” Global and Planetary Change 138 (2016): 93-102.

Kennett, Douglas J., et al. “Drought-Induced Civil Conflict Among the Ancient Maya.” Nature communications 13.1 (2022): 1-10.

Tuesday, November 8 University Holiday
Thursday, November 10

Introduction to peer review process

Project Proposal Peer-Review Exercise

Draft of Project Proposal (1-2 pages; not graded)

Visit to the John Carter Brown Library

Tuesday, November 15 Climate and Civilization: Ancient China

Chen, Siying, et al. “Climate records in ancient Chinese diaries and their application in historical climate reconstruction–a case study of Yunshan Diary.” Climate of the Past 16.5 (2020): 1873-1887.

Dong, Guanghui, et al. “Climate-driven desertification and its implications for the ancient Silk Road trade.” Climate of the Past 17.3 (2021): 1395-1407.

Thursday, November 17 Climate and Civilization: Nile Delta/Assyrian

Meklach, Yassin, et al. “Potential of Arabic documentary sources for reconstructing past climate in the western Mediterranean region from AD 680 to 1815.” The Holocene 31.11-12 (2021): 1662-1669.

Sinha, Ashish, et al. “Role of climate in the rise and fall of the Neo-Assyrian Empire.” Science advances 5.11 (2019): eaax6656.

Project Proposal Due (1-2 pages; graded)

Tuesday, November 22 Climate and Civilization: Indus Valley

Staubwasser, Michael, et al. “Climate change at the 4.2 ka BP termination of the Indus valley civilization and Holocene south Asian monsoon variability.” Geophysical Research Letters 30.8 (2003).

Dutt, Som, et al. “A long arid interlude in the Indian summer monsoon during∼ 4,350 to 3,450 cal. yr BP contemporaneous to displacement of the Indus valley civilization.” Quaternary International 482 (2018): 83-92.

Thanksgiving Break 23-27 November 2022 No Classes
Tuesday, November 29

Proxy & Observational Data Comparison

+

Anthropocene

Okazaki, A., & Yoshimura, K. (2017). Development and evaluation of a system of proxy data assimilation for paleoclimate reconstruction. Climate of the Past, 13(4), 379-393.

Proxy System Models (PRYSM, Karsolution)

Xu, Chi, et al. “Future of the human climate niche.” Proceedings of the National Academy of Sciences 117.21 (2020): 11350-11355.

Thursday, December 1 Final Projects Working Session and Peer Review

 

 

Tuesday, December 6 Final Project Presentations Part I Draft of Final Project Technical Report Due (not graded)
Thursday, December 8 Final Project Presentations Part II
Tuesday, December 20 Final Projects Due

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

There will be 5 groups of 3-4 students (randomly chosen) that will work towards a final project culminating in a 5-6 page technical report style paper. Throughout the semester, students will be introduced to different types of available datasets and their accessibility. In parallel, students will be taught how to plot and test for correlations amongst the dataset in Python. Groups will then be required to choose a topic and dataset to work on through the remainder of the semester. A two-page bulleted outline and topic proposal will be required that will discuss the relevancy of the topic to climate trends, how the dataset will be checked for quality control, the hypothesis and relevant statistical tests that will be carried out to test the stated hypothesis.

 

An example topic and dataset might be: did the last two severe El-Nino’s (1997/1998; 2015/2016) develop drought conditions experienced by the Philippines? The dataset used would be monthly rainfall data averaged at a national level. And a t-test of seasonal El-Nino and non-El Nino’s will be carried out to test the null hypothesis that El-Nino rainfall averages are lower than non-El Nino rainfall averages for the season of interest.

 

The 5-6 page technical report includes references and 4+ associated Python made figures. The technical report will end with the limitations of the study and a few statements on what type of dataset if available would strengthen the project. Each technical report will also have an author contribution section which will breakdown the responsibility of each student. There will be no abstract but a Plain-Language Summary (150 words) at the beginning of the Technical Report for consumption by the public. Peer-review is a cornerstone of academic studies. As such, a draft of each technical report will be evaluated in class by the other groups based on a criteria table provided by the instructor.

 

In addition to a technical report, each group will present a short (~15 minute) presentation followed by a class discussion of the findings.

 

The instructor reserves the right to make changes to any part of this document should it be necessary and appropriate.