Come to our AGU session: Quantitative Modeling of Social and Environmental Systems

Jesse and I are convening a session at the American Geophysical Union with our colleagues Ram Fishman and Gordon McCord this coming Monday. If you're in the Bay Area, come check it out! We have a diverse and exciting lineup.

U14A.  Quantitative Modeling of Social and Environmental Systems
4:00 PM - 6:00 PM Monday; 102 (Moscone South)

4:00 PM - 4:30 PM
U14A-01. Climate Change: Modeling the Human Response
Michael Oppenheimer; Solomon M. Hsiang; Robert E. Kopp
ABSTRACT: Integrated assessment models have historically relied on forward modeling including, where possible, process-based representations to project climate change impacts. Some recent impact studies incorporate the effects of human responses to initial physical impacts, such as adaptation in agricultural systems, migration in response to drought, and climate-related changes in worker productivity. Sometimes the human response ameliorates the initial physical impacts, sometimes it aggravates it, and sometimes it displaces it onto others. In these arenas, understanding of underlying socioeconomic mechanisms is extremely limited. Consequently, for some sectors where sufficient data has accumulated, empirically based statistical models of human responses to past climate variability and change have been used to infer response sensitivities which may apply under certain conditions to future impacts, allowing a broad extension of integrated assessment into the realm of human adaptation. We discuss the insights gained from and limitations of such modeling for benefit-cost analysis of climate change. 
4:30 PM - 5:00 PM
U14A-02. Dams and Intergovernmental Transfers
Xiaojia Bao
ABSTRACT: Gainers and Losers are always associated with large scale hydrological infrastructure construction, such as dams, canals and water treatment facilities. Since most of these projects are public services and public goods, Some of these uneven impacts cannot fully be solved by markets. This paper tried to explore whether the governments are paying any effort to balance the uneven distributional impacts caused by dam construction or not. It showed that dam construction brought an average 2% decrease in per capita tax revenue in the upstream counties, a 30% increase in the dam-location counties and an insignificant increase in downstream counties. Similar distributional impacts were observed for other outcome variables. like rural income and agricultural crop yields, though the impacts differ across different crops. The paper also found some balancing efforts from inter-governmental transfers to reduce the unevenly distributed impacts caused by dam construction. However, overall the inter-governmental fiscal transfer efforts were not large enough to fully correct those uneven distributions, reflected from a 2% decrease of per capita GDP in upstream counties and increase of per capita GDP in local and downstream counties. This paper may shed some lights on the governmental considerations in the decision making process for large hydrological infrastructures. 
5:00 PM - 5:30 PM
U14A-03. Physically-based Assessment of Tropical Cyclone Damage and Economic Losses
Ning Lin
ABSTRACT: Estimating damage and economic losses caused by tropical cyclones (TC) is a topic of considerable research interest in many scientific fields, including meteorology, structural and coastal engineering, and actuarial sciences. One approach is based on the empirical relationship between TC characteristics and loss data. Another is to model the physical mechanism of TC-induced damage. In this talk we discuss about the physically-based approach to predict TC damage and losses due to extreme wind and storm surge.  
We first present an integrated vulnerability model, which, for the first time, explicitly models the essential mechanisms causing wind damage to residential areas during storm passage, including windborne-debris impact and the pressure-debris interaction that may lead, in a chain reaction, to structural failures (Lin and Vanmarcke 2010; Lin et al. 2010a). This model can be used to predict the economic losses in a residential neighborhood (with hundreds of buildings) during a specific TC (Yau et al. 2011) or applied jointly with a TC risk model (e.g., Emanuel et al 2008) to estimate the expected losses over long time periods. Then we present a TC storm surge risk model that has been applied to New York City (Lin et al. 2010b; Lin et al. 2012; Aerts et al. 2012), Miami-Dade County, Florida (Klima et al. 2011), Galveston, Texas (Lickley, 2012), and other coastal areas around the world (e.g., Tampa, Florida; Persian Gulf; Darwin, Australia; Shanghai, China). 
These physically-based models are applicable to various coastal areas and have the capability to account for the change of the climate and coastal exposure over time. We also point out that, although made computationally efficient for risk assessment, these models are not suitable for regional or global analysis, which has been a focus of the empirically-based economic analysis (e.g., Hsiang and Narita 2012). A future research direction is to simplify the physically-based models, possibly through parameterization, and make connections to the global loss data and economic analysis. 
5:30 PM - 6:00 PM
U14A-04. Modeling agricultural commodity prices and volatility in response to anticipated climate change
David B. Lobell; Nam Anh Tran; Jarrod Welch; Michael Roberts; Wolfram Schlenker
ABSTRACT: Food prices have shown a positive trend in the past decade, with episodes of rapid increases in 2008 and 2011. These increases pose a threat to food security in many regions of the world, where the poor are generally net consumers of food, and are also thought to increase risks of social and political unrest. The role of global warming in these price reversals have been debated, but little quantitative work has been done. A particular challenge in modeling these effects is that they require understanding links between climate and food supply, as well as between food supply and prices. Here we combine the anticipated effects of climate change on yield levels and volatility with an empirical competitive storage model to examine how expected climate change might affect prices and social welfare in the international food commodity market. We show that price level and volatility do increase over time in response to decreasing yield, and increasing yield variability. Land supply and storage demand both increase, but production and consumption continue to fall leading to a decrease in consumer surplus, and a corresponding though smaller increase in producer surplus.

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