Extended Residence Climate School

Extended Residence CLIM

Extended Residence enrollment category for Climate School students.

• Instructor: Hanna Chipman
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• 0 points

Summer Internship in Climate and Society

SUMMER INTERN:CLIM & SOC

Prerequisites: enrollment in the M.A. Program in Climate and Society. During the third and final term of study for the 12-month M.A. Program in Climate and Society, students must complete an internship and simultaneously enroll in CLMT 5006. The summer internship requires a minimum of 210  hours of professional participation during the Summer Term in a position related to core issues of concern to the Program. The selected position must be approved by the Director of the M.A. Program by a specified date in the Spring Semester preceding the Summer Term. The position must be substantive in nature and must constitute a practical, professional experience. Students will be evaluated on the basis of oral and written updates on the work, a student internship report to be submitted at the end of the Summer Term, and on the basis of a supervisor report form to be submitted by the site supervisor for the internship.

• M 5:30 p.m.-7 p.m.
• W 8:30 a.m.-10 a.m.
• Instructor: Catherine L Vaughan
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• Instructor: Andrew J Kruczkiewicz
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• 3 points

Capstone Workshop in Climate and Society

In this course, students will work jointly with a client organization in the climate and society field. Under the guidance of the instructors, they will take a short request from the organization for a specific product (data analysis, program development, curricular and training material, or other related items), develop a work plan, implement the work plan, and present the final product to the client. This course gives students direct experience in the co-production of knowledge in the climate and society field, a valuable skill in the contemporary world. It extends the training in the integration of natural science and social science that is a hallmark of the Climate + Society program. It includes training in the construction of a boundary object--a final product--conducted jointly with the client organization; this training includes instruction in project design, implementation and evaluation, and in communication between organizations.

• W 11 a.m.-1 p.m.
• Instructor: Michael J Puma
  h-index: 23 Info
• Instructor: Jeffrey Schlegelmilch
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• Instructor: Ben S Orlove
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• 3 points

Building Equitable Community Partnership

Building Partnerships in

Disaster management is a continuum that is affected by decisions, investments and dynamics that occur before, during and after disasters. The issue of equity in disaster management is emerging from an abundance of evidence that shows that societal inequities often translate into inequitable outcomes and disproportionate impacts from disasters. Community engagement strategies are often touted as a solution to the inequities, but many aspects of community participation are complex, with additional
effort and investments required for working with vulnerable and marginalized communities. Further, power dynamics between disaster experts and vulnerable communities may bias approaches to disaster management as well as representation within relevant power structures. This seminar is designed to provide an introduction to some of the variables that impact vulnerability and inequity in disaster management, ultimately leading to inequitable outcomes. It also provides an overview of current and emerging strategies in community engagement designed to foster a “whole of community” approach to disaster management.

The purpose of this course is to prepare those entering the climate policy and practice workforce for addressing these challenges by providing an overview of issues of equity and building community partnerships in disaster management. At the end of this course learners will be able to:


Describe social determinants of disaster vulnerability and resilience

Describe how governance and financial structures can drive inequity in the disaster cycle

Identify whole community approaches for disaster management

Identify mechanisms to develop partnerships with underserved communities and emergent partners in disaster management

Demonstrate the ability to develop strategies for disaster management based on best practices for community engagement and addressing equity concerns.

• TR 3 p.m.-4:45 p.m.
• Instructor: Jeffrey Schlegelmilch
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• 1.5 points

Financing Renewable Energy

With climate change visibly affecting communities around the world, it is essential to society to transition to renewable energy sources to minimize further climate warming. As for any generation source, installation of renewables is very capital intensive. This course will examine key “ingredients” necessary to finance a renewable project / make it economic, including but not limited to:


Ability to finance at the project level

Different forms of capital available / requirements to successfully finance

Revenue models for renewables investors and required returns

Role of government incentives in financing renewable energy / latest US legislation

Key technical issues that arise with increased renewables penetration

Global geopolitical landscape and its impact on energy transition

Equity an inclusion in the approach to building a renewable landscape


As part of the course, we will review multiple case studies and will approach the topics both from theoretical and quantitative perspectives.

• TR 6:15 p.m.-8 p.m.
• Instructor: Nadejda Zaets
  CULPA: 3 Info
• 3 points

Disaster Research Methods

The field of disaster research is relatively new in the United States, as a specific field of study, with the first disaster research center being founded in the early 1960s. The field itself is now highly multi-disciplinary, drawing from the social sciences, anthropology, political science, computer science, engineering, earth sciences, psychology, and medicine and public health. These academic fields have intersected with the practice community by informing holistic emergency planning for all members of a community. Furthermore, these research outputs have informed federal and state policy, the private sector, and community organizations to inform program design and implementation. Translating research into practice remains a constant challenge in this rapidly evolving field. The methodological approaches to disaster research are just as diverse and have become increasingly complex with the advent of big data, the ubiquity of spatial information, and novel cross-disciplinary research. As a new era of compound and cascading disasters has triggered a constant “response” mode within the field of emergency management, the need for practitioners and research with a fluency in research and evaluation methods is required to critically evaluate or generate high quality and ethically based research.

• TR 3 p.m.-4:45 p.m.
• Instructor: Jonathan J Sury
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• 1.5 points

Climate Ethics, Leadership and Managemen

Climate Ethics, Leader &

Often, our progress toward the remediation of persistently accumulating human damage to our collective home, the biosphere, is attributed to large-scale entities having a rather amorphous quality. Such are the industrial revolution, the global north, capitalism, colonialism, and countless preoccupied, habituated or denialist components of the human population. Yet, the dynamics of all types of leadership and management, whether in public, civic or private organizations, frequently push back on the progress desired, in more specific ways. These dynamics are so characteristic that climate ethics, an offshoot of environmental ethics, may seem to be cornered or futile. However, looking more closely at the essential functions of leadership and management, we may find the possibilities of change for the better: change that reverses climate change, or more widely, unsustainability. Conversely, we may find inadequate possibilities for such critical change.

In this course, leadership and management are explored to determine their dynamics are and how these afflict our biospheric home—including virtually all life.  The course is divided into 4 sections, the 1st is two weeks long, the 2nd and 3rd are each four weeks long, and the 4th is two weeks long.  The topic of the 1st section is climate ethics, their content and context:  how they work and how they are tripped by surrounding problematic discourses. The topic of the 2nd section is leadership: at its becomingly best, and how it demeans itself with incapability, irresponsibility and corruptibility. The topic of the 3rd section is management: at its operationally best, and how it degrades itself with dysfunctional hierarchy, captive systematization, and offensive behavior.  The topic of the 4th section reverts to climate ethics: the necessity of accruing and maintaining value—of the right kind, and the necessity of creating and applying guidance—of the right kind.  It is not only because the impacts of problematic ways of doing things are harmful to the biosphere but also because those impacts have others, which are increasingly desperate, rancorous and volatile.

• MW 3 p.m.-4:45 p.m.
• Instructor: Adela J Gondek
  CULPA: 2 Info
• 3 points

Financial Analysis of Climate Risk: An I

Fin. Analysis of Climate

The signing of the Paris Treaty in 2015 signaled a recognition by nearly all the world’s governments of the need to reduce greenhouse gas emissions to avoid the worst effects of climate change. Meanwhile, the changing climate is already having negative impacts on business assets and operations around the world. Despite evidence that climate change poses a threat to business as usual for many companies, the financial sector has yet to form a consistent view on how to value risks and opportunities associated with climate change. There are multiple reasons for this. Climate-related disclosures vary widely from company to company, as do the ways that climate risks affect different sectors and geographies. The policy landscape is varied and fast changing. Unfortunately, many financial analysts lack the technical knowledge to assess corporate disclosures and actions pertaining to climate.

This 6-week course provides a practical overview of how analysts in the financial sector can assess corporate climate risk and opportunity among publicly traded corporates, using public data. The class will begin with the concept of how business leaders and financial analysts understand climate risk – alongside other concepts such as decarbonization, transition planning and climate impacts from a policy perspective. 

We will then move to focus on industry-specific analysis in four sectors – 1) oil and gas, 2) consumer staples, 3) mining, and 4) financial services. In each, we will survey the tools that investors have to assess climate risk and opportunity, taking into account policy, voluntary frameworks, and technology. For each of these elements, we will review both how these tools can assist with climate risk analysis as well as their limitations and inconsistencies. We will consider ways the analyst can work with relevant data and reconcile public corporate claims with evidence through corporate disclosures.

• F 11 a.m.-2:30 p.m.
• 1.5 points

Machine Learning for Climate Science and

Machine Learn for Climate

The application of Machine Learning (ML) to climate science and environmental sustainability has become increasingly popular in recent years, promising to revolutionize how we analyze and address critical environmental challenges. This course will introduce students to the fundamental concepts and methods of ML, emphasizing their practical applications to climate science and environmental sustainability efforts.

Students will gain both theoretical knowledge and practical skills through hands-on experience with machine learning methods and coding. The course is designed to provide familiarity with the design, implementation, and evaluation of machine learning models towards addressing specific problems in climate science and sustainability. By working with real-world datasets, students will develop a deeper understanding of both the capabilities and limitations of ML tools in climate research and for evaluating environmental sustainability solutions. This course will cover essential topics such as data preprocessing, model selection, evaluation metrics, and the ethical implications of ML in climate science.

As ML tools become increasingly important to these application areas, this course will be invaluable for those looking to interact with scientists and engineers, manage scientific projects, and develop policies in the realm of climate science and sustainability.

• TR 11 a.m.-12:45 p.m.
• 1.5 points

Spatial Analysis of Food Security

Spatial Analysis Food Sec

Globally, there are over 2 billion people suffering from moderate-to-severe food insecurity, with an estimated 600 million people projected to be chronically undernourished by 2030. One key aspect to understanding food insecurity is its spatial distribution and trends that contribute to how food secure a population is. This course will teach students how to collect and analyze spatial data related to food security, as well as touch on important topics in food insecurity. The course will focus on taking real-life food security questions and applying spatial analysis techniques to these questions. In the course, we will cover an introduction to spatial analysis, natural experiments in geography, applying remote sensing to food insecurity, climate shocks and food security, and seasonal forecasting and food security.

It will have an in-class aspect, which will mainly focus on topics in food security and how they relate to data collection, and a lab section which will be an opportunity for students to collect data directly, clean the data, and analyze the data using the R programming language with spatial research methods. Example topics in class will be climate variability and food insecurity, women’s role in agriculture and their rates of food insecurity relative to men, and population and health. These topics will then be further explored in the lab section of the class: specifically focusing on downloading weather data for time series analysis, using a convergence of datasets to map hotspots, and investigating how survey data intersects with spatial datasets.

In this course, there will be two components; a lecture and a lab. The lecture will be short and focus on relevant topics in Food Security and methodology used to quantitative analyze these topics. The lab will be a computer-based lab in R, analyzing relevant food security data using techniques discussed during the lecture to provide a practical base for quantitative analyses.

• MW 1 p.m.-2:45 p.m.
• Instructor: Sarah L Blakeley
  Info
• 1.5 points

Computing and Research Methods for Clima

Clim Data Sci Research Me

Computing and data analysis have become an indispensable tool for researchers and industry professionals working in virtually any aspect of the modern world. This course will introduce students to the fundamental concepts and methods that are broadly applicable to any data science project, with a thematic focus on climate and environmental data. This includes an introduction to Unix, programming, common data formats, analysis, and visualization. The primary focus will be to teach students the foundations of Python in a climate data science context, which is of the most widely used and accessible programming languages today. Students will also be introduced to cloud computing, which will be the primary tool for in class assignments and projects. 

The course is designed to be accessible for any students with an interest in being able to ask and answer questions using data. This course will also be invaluable for those looking to interact with scientists and engineers, manage scientific projects, and develop policies in the realm of climate science and sustainability.

• TR 11 a.m.-12:45 p.m.
• Instructor: Dhruv Balwada
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• 1.5 points