Quantifying the cost uncertainty of climate stabilization policies

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program; and, (S.M.)--Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering, 2005.Includes bibliographical references (p. 61-63).Climate change researchers are often asked to evaluate potential economic effects of climate stabilization policies. Policy costs are particularly important because policymakers use a cost/benefit framework to analyze policy options. Many different models have been developed to estimate economic costs and to inform cost/benefit decisions. This thesis examines what impact modelers' assumptions have on a model's results. Specifically, MIT's Emissions Prediction and Policy Analysis (EPPA) model is examined to understand how uncertainty in input parameters affect economic predictions of long-term climate stabilization policies. Eleven different categories of parameters were varied in a Monte Carlo simulation to understand their effect on two different climate stabilization policies. The Monte Carlo simulation results show that the structure of stabilization policy regulations has regional economic welfare effects. Carbon permits allocated by a tax-based emissions path favored energy importers with developed economies (e.g., the US and the EU). Countries with energy-intensive economies (e.g., China) will likely have negative welfare changes because of strict carbon policy constraints. Oil exporters (e.g., the Middle East) will also be negatively impacted because of terms of trade fluxes. These insights have implications for stabilization policy design. The uncertainty surrounding economic projections expose some countries to larger economic risks. Policies could be designed to share risks by implementing different permit allocation methods. Direct payments are another means to compensate countries disproportionately disadvantaged by a stabilization policy.by Travis Read Franck.S.M

Coastal communities and climate change : a dynamic model of risk perception, storms, and adaptation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 303-311).Climate change impacts, including sea-level rise and changes in tropical storm frequency and intensity, will pose signicant challenges to city planners and coastal zone managers trying to make wise investment and protection decisions. Meanwhile, policymakers are working to mitigate impacts by regulating greenhouse gas emissions. To design effective policies, policymakers need more accurate information than is currently available to understand how coastal communities will be affected by climate change. My research aims to improve coastal impact and adaptation assessments, which inform climate and adaptation policies. I relax previous assumptions of probabilistic annual storm damage and rational economic expectations-variables in previous studies that are suspect, given the stochastic nature of storm events and the real-world behavior of people. I develop a dynamic stochastic adaptation model that includes explicit storm events and boundedly rational storm perception. I also include endogenous economic growth, population growth, public adaptation measures, and relative sea-level rise. The frequency and intensity of stochastic storm events can change a region's long- term economic growth pattern and introduce the possibility of community decline. Previous studies using likely annual storm damage are unable to show this result. Additionally, I consider three decision makers (coastal managers, infrastructure investors, and residents) who differ regarding their perception of storm risk. The decision makers' perception of risk varies depending on their rationality assumptions.(cont.) Boundedly rational investors and residents perceive storm risk to be higher immediately after a storm event, which can drive down investment, decrease economic 3 growth, and increase economic recovery time, proving that previous studies provide overly optimistic economic predictions. Rationality assumptions are shown to change economic growth and recovery time estimates. Including stochastic storms and variable rationality assumptions will improve adaptation research and, therefore, coastal adaptation and climate change policies.by Travis Read Franck.Ph.D

Combining role-play with interactive simulation to motivate informed climate action: Evidence from the World Climate simulation

Climate change communication efforts grounded in the information deficit model have largely failed to close the gap between scientific and public understanding of the risks posed by climate change. In response, simulations have been proposed to enable people to learn for themselves about this complex and politically charged topic. Here we assess the impact of a widely-used simulation, World Climate, which combines a socially and emotionally engaging role-play with interactive exploration of climate change science through the C-ROADS climate simulation model. Participants take on the roles of delegates to the UN climate negotiations and are challenged to create an agreement that meets international climate goals. Their decisions are entered into C-ROADS, which provides immediate feedback about expected global climate impacts, enabling them to learn about climate change while experiencing the social dynamics of negotiations. We assess the impact of World Climate by analyzing pre- and post-survey results from >2,000 participants in 39 sessions in eight nations. We find statistically significant gains in three areas: (i) knowledge of climate change causes, dynamics and impacts; (ii) affective engagement including greater feelings of urgency and hope; and (iii) a desire to learn and do more about climate change. Contrary to the deficit model, gains in urgency were associated with gains in participants’ desire to learn more and intent to act, while gains in climate knowledge were not. Gains were just as strong among American participants who oppose government regulation of free markets–a political ideology that has been linked to climate change denial in the US–suggesting the simulation’s potential to reach across political divides. The results indicate that World Climate offers a climate change communication tool that enables people to learn and feel for themselves, which together have the potential to motivate action informed by science.National Science Foundation (U.S.) (grant DUE-124558)National Science Foundation (U.S.) (grant ICEER-1701062

Management flight simulators to support climate negotiations

a b s t r a c t Under the United Nations Framework Convention on Climate Change (UNFCCC) the nations of the world have pledged to limit warming to no more than 2 C above preindustrial levels. However, negotiators and policymakers lack the capability to assess the impact of greenhouse gas (GHG) emissions reduction proposals offered by the parties on warming and the climate. The climate is a complex dynamical system driven by multiple feedback processes, accumulations, time delays and nonlinearities, but research shows poor understanding of these processes is widespread, even among highly educated people with strong technical backgrounds. Existing climate models are opaque to policymakers and too slow to be effective either in the fast-paced context of policy making or as learning environments to help improve people's understanding of climate dynamics. Here we describe C-ROADS (Climate Rapid Overview And Decision Support), a transparent, intuitive policy simulation model that provides policymakers, negotiators, educators, businesses, the media, and the public with the ability to explore, for themselves, the likely consequences of GHG emissions policies. The model runs on an ordinary laptop in seconds, offers an intuitive interface and has been carefully grounded in the best available science. We describe the need for such tools, the structure of the model, and calibration to climate data and state of the art general circulation models. We also describe how C-ROADS is being used by officials and policymakers in key UNFCCC parties, including the United States, China and the United Nations

Automated data processing architecture for the Gemini Planet Imager Exoplanet Survey

The Gemini Planet Imager Exoplanet Survey (GPIES) is a multi-year direct imaging survey of 600 stars to discover and characterize young Jovian exoplanets and their environments. We have developed an automated data architecture to process and index all data related to the survey uniformly. An automated and flexible data processing framework, which we term the Data Cruncher, combines multiple data reduction pipelines together to process all spectroscopic, polarimetric, and calibration data taken with GPIES. With no human intervention, fully reduced and calibrated data products are available less than an hour after the data are taken to expedite follow-up on potential objects of interest. The Data Cruncher can run on a supercomputer to reprocess all GPIES data in a single day as improvements are made to our data reduction pipelines. A backend MySQL database indexes all files, which are synced to the cloud, and a front-end web server allows for easy browsing of all files associated with GPIES. To help observers, quicklook displays show reduced data as they are processed in real-time, and chatbots on Slack post observing information as well as reduced data products. Together, the GPIES automated data processing architecture reduces our workload, provides real-time data reduction, optimizes our observing strategy, and maintains a homogeneously reduced dataset to study planet occurrence and instrument performance.Comment: 21 pages, 3 figures, accepted in JATI

Dynamical Mass Measurement of the Young Spectroscopic Binary V343 Normae AaAb Resolved With the Gemini Planet Imager

We present new spatially resolved astrometry and photometry from the Gemini Planet Imager of the inner binary of the young multiple star system V343 Normae, which is a member of the beta Pictoris moving group. V343 Normae comprises a K0 and mid-M star in a ~4.5 year orbit (AaAb) and a wide 10" M5 companion (B). By combining these data with archival astrometry and radial velocities we fit the orbit and measure individual masses for both components of M_Aa = 1.10 +/- 0.10 M_sun and M_Ab = 0.290 +/- 0.018 M_sun. Comparing to theoretical isochrones, we find good agreement for the measured masses and JHK band magnitudes of the two components consistent with the age of the beta Pic moving group. We derive a model-dependent age for the beta Pic moving group of 26 +/- 3 Myr by combining our results for V343 Normae with literature measurements for GJ 3305, which is another group member with resolved binary components and dynamical masses.Comment: 12 pages, 7 figures. Accepted to A

Improving and Assessing Planet Sensitivity of the GPI Exoplanet Survey with a Forward Model Matched Filter

We present a new matched filter algorithm for direct detection of point sources in the immediate vicinity of bright stars. The stellar Point Spread Function (PSF) is first subtracted using a Karhunen-Lo\'eve Image Processing (KLIP) algorithm with Angular and Spectral Differential Imaging (ADI and SDI). The KLIP-induced distortion of the astrophysical signal is included in the matched filter template by computing a forward model of the PSF at every position in the image. To optimize the performance of the algorithm, we conduct extensive planet injection and recovery tests and tune the exoplanet spectra template and KLIP reduction aggressiveness to maximize the Signal-to-Noise Ratio (SNR) of the recovered planets. We show that only two spectral templates are necessary to recover any young Jovian exoplanets with minimal SNR loss. We also developed a complete pipeline for the automated detection of point source candidates, the calculation of Receiver Operating Characteristics (ROC), false positives based contrast curves, and completeness contours. We process in a uniform manner more than 330 datasets from the Gemini Planet Imager Exoplanet Survey (GPIES) and assess GPI typical sensitivity as a function of the star and the hypothetical companion spectral type. This work allows for the first time a comparison of different detection algorithms at a survey scale accounting for both planet completeness and false positive rate. We show that the new forward model matched filter allows the detection of $50\%$ fainter objects than a conventional cross-correlation technique with a Gaussian PSF template for the same false positive rate.Comment: ApJ accepte

GPI spectra of HR 8799 c, d, and e from 1.5 to 2.4μ\mum with KLIP Forward Modeling

We explore KLIP forward modeling spectral extraction on Gemini Planet Imager coronagraphic data of HR 8799, using PyKLIP and show algorithm stability with varying KLIP parameters. We report new and re-reduced spectrophotometry of HR 8799 c, d, and e in H & K bands. We discuss a strategy for choosing optimal KLIP PSF subtraction parameters by injecting simulated sources and recovering them over a range of parameters. The K1/K2 spectra for HR 8799 c and d are similar to previously published results from the same dataset. We also present a K band spectrum of HR 8799 e for the first time and show that our H-band spectra agree well with previously published spectra from the VLT/SPHERE instrument. We show that HR 8799 c and d show significant differences in their H & K spectra, but do not find any conclusive differences between d and e or c and e, likely due to large error bars in the recovered spectrum of e. Compared to M, L, and T-type field brown dwarfs, all three planets are most consistent with mid and late L spectral types. All objects are consistent with low gravity but a lack of standard spectra for low gravity limit the ability to fit the best spectral type. We discuss how dedicated modeling efforts can better fit HR 8799 planets' near-IR flux and discuss how differences between the properties of these planets can be further explored.Comment: Accepted to AJ, 25 pages, 16 Figure

Performance of the Gemini Planet Imager Non-Redundant Mask and spectroscopy of two close-separation binaries HR 2690 and HD 142527

The Gemini Planet Imager (GPI) contains a 10-hole non-redundant mask (NRM), enabling interferometric resolution in complement to its coronagraphic capabilities. The NRM operates both in spectroscopic (integral field spectrograph, henceforth IFS) and polarimetric configurations. NRM observations were taken between 2013 and 2016 to characterize its performance. Most observations were taken in spectroscopic mode with the goal of obtaining precise astrometry and spectroscopy of faint companions to bright stars. We find a clear correlation between residual wavefront error measured by the AO system and the contrast sensitivity by comparing phase errors in observations of the same source, taken on different dates. We find a typical 5-$\sigma$ contrast sensitivity of $2-3~\times~10^{-3}$ at $\sim\lambda/D$. We explore the accuracy of spectral extraction of secondary components of binary systems by recovering the signal from a simulated source injected into several datasets. We outline data reduction procedures unique to GPI's IFS and describe a newly public data pipeline used for the presented analyses. We demonstrate recovery of astrometry and spectroscopy of two known companions to HR 2690 and HD 142527. NRM+polarimetry observations achieve differential visibility precision of $\sigma\sim0.4\%$ in the best case. We discuss its limitations on Gemini-S/GPI for resolving inner regions of protoplanetary disks and prospects for future upgrades. We summarize lessons learned in observing with NRM in spectroscopic and polarimetric modes.Comment: Accepted to AJ, 22 pages, 14 figure

Characterizing 51 Eri b from 1-5 μ\mum: a partly-cloudy exoplanet

We present spectro-photometry spanning 1-5 $\mu$m of 51 Eridani b, a 2-10 M$_\text{Jup}$ planet discovered by the Gemini Planet Imager Exoplanet Survey. In this study, we present new $K1$ (1.90-2.19 $\mu$m) and $K2$ (2.10-2.40 $\mu$m) spectra taken with the Gemini Planet Imager as well as an updated $L_P$ (3.76 $\mu$m) and new $M_S$ (4.67 $\mu$m) photometry from the NIRC2 Narrow camera. The new data were combined with $J$ (1.13-1.35 $\mu$m) and $H$ (1.50-1.80 $\mu$m) spectra from the discovery epoch with the goal of better characterizing the planet properties. 51 Eri b photometry is redder than field brown dwarfs as well as known young T-dwarfs with similar spectral type (between T4-T8) and we propose that 51 Eri b might be in the process of undergoing the transition from L-type to T-type. We used two complementary atmosphere model grids including either deep iron/silicate clouds or sulfide/salt clouds in the photosphere, spanning a range of cloud properties, including fully cloudy, cloud free and patchy/intermediate opacity clouds. Model fits suggest that 51 Eri b has an effective temperature ranging between 605-737 K, a solar metallicity, a surface gravity of $\log$(g) = 3.5-4.0 dex, and the atmosphere requires a patchy cloud atmosphere to model the SED. From the model atmospheres, we infer a luminosity for the planet of -5.83 to -5.93 ($\log L/L_{\odot}$), leaving 51 Eri b in the unique position as being one of the only directly imaged planet consistent with having formed via cold-start scenario. Comparisons of the planet SED against warm-start models indicates that the planet luminosity is best reproduced by a planet formed via core accretion with a core mass between 15 and 127 M$_{\oplus}$.Comment: 27 pages, 19 figures, Accepted for publication in The Astronomical Journa