Experiential Learning via a Loss & Damage Registry on Climate Adaptation
Climate change is transforming our lives; global temperatures are rising leading to increased frequency, duration and intensity of drought and flood events. Between 2012 and 2020, an estimated a half million people moved across US States on account of climate induced stresses such as floods, fire, heat, and drought. This means that human livelihoods are adversely affected on account of food and water insecurity and climate change induced displacement of people. Agriculture Research for Development (AR4D) has the potential to enhance the accountability of climate adaptation efforts by identifying financing systems and monitoring regimes that compensate for "loss and damage" of infrastructure, cultural assets and harm to human health especially for historically marginalized communities who are disproportionately affected by climate change. In this connection, The Climate Panel initiative supports innovations in data-driven learning and collaborative problem solving with a focus on advancing the resilience of Water-Energy-Food (WEF) systems. Climate resilient WEF planning is fundamentally different from the conventional approach because it necessitates rigorous and integrative assessment of key risks across sectors, departments, and planning themes. The United States Environmental Protection Agency (EPA) recently emphasized adaptation planning and monitoring in its Climate Resilience Screening Index (CRSI) Report, 2021.
The CRSI provides an overview of the capacity of individual States to respond to climate change risks, indicating which States are most resilient or vulnerable to climate change impacts. Mapping is however only the first step. The critical step that should follow next is to incentivize each State to implement adaptation plans by monitoring the use of federal funds through a robust rating and rewards framework. Human centered technology design would employ data analytics to capture localized features of the environmental challenges to facilitate robust adaption planning. The Climate Panel seeks to develop a Loss & Damage Registry that can monitor a rating and rewards regime that responds to local specificities by creating opportunities for experiential learning. Too often what is considered scientifically significant is not translated into policy and practice. The nuanced understanding of trade-offs between economic growth and environmental resource conservation/socially inclusive development can support a process of prioritization and targeting of the area and community which stands to benefit the most from climate change interventions at the level of U.S. States. There are important lessons that can be drawn from co-curation of data and environmental models via a Loss & Damage Registry that can potentially offer benefits to practitioners and students from a variety of disciplines ranging from cloud computing, earth systems science, environmental geosciences, geography, environmental studies, and social science research methodology.
Discover Environmental Science Courses - What We Offer
The Climate Panel has developed a “model of models” to help us understand and act by connecting data to models to influence decision-making at the level of local governments and communities. The Climate Panel is an open-access platform that uses experiential learning techniques to co-curate a model of 3 steps: (a) constructing typologies of trade-offs, (b) constructing composite indices and (c) identifying institutional pathways that address acute environmental trade-offs. The 3 step approach underlies a tutorial to thesis model (or the T2T model) that will guide participants from an initial introduction to climate change-induced disasters to develop a personally crafted thesis for which they may draw upon two examples: one of global wastewater reuse and another of watershed management. The thesis will double up both as a personal testament of individual learning while at the same time generating a field guide that demonstrates innovative approaches to undertaking environmental planning by focussing on water-energu-food systems.
The T2T model will explore the modalities for co-design and co-curation by using data and models sourced from multiple sources and using different medium (public, private, SMS, remote sensed data) to nudge practitioners to consider the use of typologies of trade-offs and composite indices as tools that can guide environmental planning and management. The following are the key learning outcomes of the T2T model which our environmental science courses will explore through climate tutorials spread over 12 lectures covering a three- month period (mid September to mid December & mid March to mid June every year for the period 2021 to 2031):
Data harmonization: ontologies, units and formats/semantics of data collection and use
Data transformation: indicator selection, weight allocation and composite indices
Data valorization: categorizing geographies based on planetary thresholds, trade-off intensity & institutional response to environmental disasters.