Collaborative Proposal: Improving Decadal Prediction of Artic Climate Variability and Change Using a Regional Artic Sys

1. Collaborative Proposal: Improving Decadal Prediction of Artic Climate Variability and Change Using a Regional Artic System Model (RASM) Pedagogical Applications and Practices PI: William Robertson, UTEP Research Assistant: Anna Carolina Barbosa, UTEP

3. Objective This project intends to develop pedagogical and curricular applications, based on a Regional Artic System Model (RASM), for high school, undergraduate and graduate educational levels. Project Components 1) Mapping the literature about students’ scientific illiteracy regarding climate change concepts; 2) Exploring the role that the media and science textbooks may have on students’ misconceptions and over interpretation about climate change; and, 3) Development of pedagogical practices and curriculum materials that aim at deconstructing students’ misconceptions about climate change processes as well as helping students comprehend the climate dynamics of cause and effect. Finally, this project will focus on the development of scientific pedagogical materials associated with the use of RASM climate change simulation software, which will help students develop both critical analysis of diverse sources of scientific information, literacy and civic scientific.

4. Based on your personal experience, what are the most common misconceptions about climate change among graduate and undergraduate students? • “Earth’s System us deterministic, which leads to erroneous assumptions about predictability”. • “There is no scientific consensus on the question of whether the Earth is warming and whether humans are contributing”. • “Undergraduates: that global warming is caused by the ozone hole. Graduates: the uncertainties in the model caused by the representation of various small-scale processes”. • “Understanding the relationship between global change and regional responses”. • “Lack of observational evidence for changing climate and that any observed change can be attributed to natural variability”. • “Undergraduate students are easily influenced by mass media” • “Historical climate research.”

5. In your opinion, what topics, associated with climate change processes, are the most poorly approached by the media? Why? • Basic statistics (averages, variance, medians and signals); variability, prediction, uncertainty and interconnectivity in the climate change. • the basic facts about longwaveradiative forcing due to trace gases. • Uncertainties in future climate projections, because uncertainty does not have the same meaning to the general public as it does to scientists. • The difficulty in separating natural variability from change and the consequent difficulty to attribute individual extreme events to climate change. • (1) The notion that proper reporting means "balance" between climate scientists and the "denier" community. (2) Failure to distinguish between local, seasonal features (i.e., hot/cold spells) and change on a global level. • The media provides an overly balanced view of questions regarding anthropogenic climate change - basically the media gives too much weight to arguments against anthropogenic climate change. • interpret global warming as surface temperature increase alone and link global warming with individual extreme events. • Carbon cycle.

6. What are the main pedagogical features that you can identify in this software (RASM)? • The main teachable feature from RASM is the how in nature interactions on a variety of scales produce results that could not have been foreseen by considering processes in isolation and on a single set of time and space scales. • I'd like to see software that gets across these basic physics ideas (…) give students a simple climate model to play with, and illustrate some key ideas about the Arctic (e.g., albedo feedback and polar amplification). • The model output can be used to document to the public/students just how much (and how fast) the Arctic will change in the future and how much it will change in different regions (say, Alaska vs. Siberia). • The pedagogical features will mostly come from the analysis of the arctic climate system that the software will enable at much higher spatial resolution than before. With this software, we can evaluate feedbacks in the climate system, such as the effects of the loss of sea ice and snow cover and the loss of permafrost. • (1) Ability to explore "what if" questions regarding Arctic climate processes • RASM is a very complex modeling system and is not appropriate for use as a direct teaching tool. • Not sure - seems like a very complicated model to use for teaching. • In this day and age this has to be visually compelling and interactive. I think it is important to bring in past evidence of large climate changes (e.g. enable to simulate 'snowball Earth conditions' as well as really warm, ice free conditions).

7. For which audience do you think this software might be useful? Why? • Output from RASM would be particularly useful for K-12 years 4-12 in explaining the usefulness of mathematics and physics to learn something tangible about systems seemingly too complex to understand. In this sense, RASM serves as a motivational tool and real world example for pursuing science and engineering. For college students, aspects of RASM physics can be isolated to demonstrate some key and basic physics concepts inherent in differential equations. (…)These examples are, of course, in addition to the broader use of RASM for all audiences, including the public, to extend messages about climate change beyond the simplistic thought that "when the worlds gets warmer, ice melts". • What I'm talking about might be appropriate for undergraduates or motivated high school students. But if adults could have fun with it too, all the better. • This model would be most useful to the scientific community in order for them to better understand the processes of rapid climate change in the Arctic. • The software itself is mostly relevant to climate researchers, which include atmospheric scientists, oceanographers, hydrologists, and ecologists with a strong background in environmental modeling. The reason for this is that the software requires supercomputers to run and consequently access to dedicated computing resources that are not available to many research groups. The results themselves should be of interest to a much wider audience and the outputs should be available for analysis by a much wider audience.

8. At present, graduate student and higher. RASM requires substantial knowledge about the Arctic, computing environments and programming to have utility. An advanced undergraduate might be able to handle all this, but that would be a rare case. • Advanced climate graduate students may benefit from access to RASM output. • Graduate-level climate modellers. • I can imagine making it useful at all levels (K-12, undergrad, grad). • This project will also emphasize the recruitment and mentoring of underrepresented groups and will provide undergraduates, graduate students, and postdocs with practical training in coupled climate system modeling and analysis. The PIs will incorporate research findings in their courses and departmental seminars and will contribute model improvements and findings to aid arctic climate-change predictions.

9. When compared to other simulation software such as Powersin, or Air pollution modules based on Gaussian Models 1.1, what are the innovations that this software may offer to improve undergraduate and high school students' understandings about climate change? • First, output from this model enables a rich exploration of the different components of the Arctic System and what is in the Geosphere: Terrestrial and marine ecosystems, hydrology, sea ice, land ice, atmosphere and ocean. It's important to establish basic facts about how the earth system interacts that most students don't know, e.g., the difference between sea ice and icebergs. Second, the model can be used as an example of basic physics, including conservation of energy and mass, all of which are essential to model climate change. Examples to highlight these points are: Conservation of thermal energy leading to melting of ice, conservation of salinity in the ocean, and advection of ice, air and water within the model. By communicating how the model simply uses laws that students can prove to themselves in the classroom, RASM can be broken down and explained in tangible terms that make it seem less like wizardry, and more the result of cold hard logic, thus making the results believable and understandable. • If fully completed, the output from this fully coupled model will demonstrate to students just how much (and how fast) the vegetation, sea ice, and land ice in the Arctic will change/disappear.

10. Rather than treating large sections of the Arctic like monolithic elements, the software we are developing is spatially explicit and will represent the Arctic at much higher spatial resolution than before. In addition, it dynamically links the atmosphere, ocean and land surface to model the interactions between these components at very short timesteps. Output from this model is likely to lead to insight that may lead to simplifications and parameterizations that can then be emulated in simulation software such as powersim. • RASM would need a graphical interface and probably porting to a Windows/Mac environment to function on a high school or undergraduate level. Because of the complexity of the model, only relatively short (several week/month) climate simulations are likely feasible, unless a coarse-resolution version were developed. So, this software may be too cumbersone to offer innovations on the undergrad/high school level. • It isn't obvious to me that RASM or output from RASM is appropriate for use at the high school or undergraduate level. • Is this meant to be used by undergrad/high school students directly? If so, I suppose ability to simulate the coupled climate system (though the high school better have a supercomputer handy).

11. What are some biological, chemical, and physical variables that can be manipulated using this software? • Physical variables: sea ice strength, sea ice solar reflectivity (shortwave albedo), sea ice roughness. These in turn affecting sea ice drag, velocity and thickness, feeding back to the ocean and atmospheric state. • * solar intensity * greenhouse gas concentrations * surface land cover (ice, snow, trees, tundra, etc.) and albedo * fraction of high and low clouds * wind speed/pressure patterns • None unless you're a modeler and can change the model code. However, the output variables that would be of most use to users (if given) would be surface or near-surface temperature, snow fraction, snow depth, sea ice fraction, sea ice depth, land ice fraction, land ice depth, fractional vegetation cover, and vegetation type. • On the land surface side of the model, the following need to be specified (and can therefore be manipulated): Vegetation type and characteristics, albedo, soil characteristics, topography, river network.

12. Bio: land vegetation parameters Physical: boundary conditions, various parameters affecting convection, cloud microphysics, albedos of various, resolution • Biology and chemistry are mainly absent in the current version of RASM. Alteration of physical variables and representation of these processes in RASM requires in-depth changes to the model code. • Ocean/ice/land/atmosphere physical system. • It should include the known feedbacks (e.g. ice-albedo feedback, ice-elevation feedback, feedbacks involving greenhouse gases) • Changes in the freshwater flux between arctic climate system components resulting from decadal changes in land and sea ice, seasonal snow, vegetation, and ocean circulation. Changing energetics due to decadal changes in ice mass, vegetation, and air.

13. Will this software provide novice users practical examples of climate change simulations that can assist them in utilizing the software? • I don't foresee an opportunity for students to use RASM in their own right, due to the military architecture on which it is being run, unless you have arranged access to a supercomputer for students to use. However, data rich model history files can be arranged for students to explore using various easy-to-use software (e.g. ncview) which would enable them to piece together evolution of different variables in the model and how the different variables are interconnected. • I think it's always helpful to see a few examples before trying things on your own. • I'm new to this team, so I don't know if anything like this is planned. • Not at present. • I do not see how RASM can be used by novice users. • It certainly could be used to do so.

14. Yes, the team is putting a quickstart guide together for using the software. However, novice users in this case refers to graduate students and researchers in climate science with a solid background in scientific computing. At this point, I don't think that anyone realistically envisions that RASM itself will be a tool to be used at the undergraduate or high school level. However, the science results should guide more interactive and pedagogical models such as powersim type simulation models. • The PIs will incorporate research findings in their courses and departmental seminars and will contribute model improvements and findings to aid arctic climate-change predictions. Finally, the RASM code will be made freely available to the community. Simulation results will be broadly disseminated through peer-reviewed publications, presentations at conferences and workshops, the project web site, and public lectures.

15. Based on your answers to the previous survey, how could the RASM software help deconstruct the five most common misconceptions identified among high school students about climate change? • 1) “Inflated estimates of temperature change”; • 2) “Confusion between CFCs, the ozone hole, and climate change”; • 3) “Perceived evidence – warmer weather focus”; • 4) “All environmental harms cause climate change”; • 5) “Confusing weather and climate” (Rajeev Gowda, 1997, p. 2233-2235)

16. Recommendations for the development of pedagogical materials associated with the use of RASM software • Mapping undergraduate and graduate students’ misconceptions about climate change processes in order to develop more adequate and improved curriculum materials and efficient teacher training courses; • Understanding of implicit mechanisms through which students might assimilate climate change information transmitted by the media. • Taking into consideration the difference between “professional-quality and educational software” (Jennings and Kuhlman, 1997, p.152). • Moreover, we recommend that environmental-related software developers take into consideration the following considerations described by Jennings (1997): “narrow focus”; “mechanistic flexible”; “user-friendly front end”; “blunder control”; “learning curve”; “rapid run times”; “visual impact”; “detailed result documentation”; “processing feedback”; “low cost”; “machine flexibility”; “technical documentation”; and, “information-rich example applications” (p.2-3).

17. References • Choi, S., Niyogi, D., Shepardson, D.P., & Charusombat, U. (2010). Do Earth and Environmental Science Textbooks Promote Middle and High School Students’ Conceptual Development About Climate Change? BAMS, p.890-898. • Cordero, E.C., Todd, A.M. & Abellera, D. (2008). Climate Change Education and the Ecological Footprint. American Meteorological Society, p.865-872. • Henriques, L. Children’s Ideas About Weather: A Review of the Literature. • Hodson, D. (2010). Science Education as a Call for Action. Canadian Journal of Science, Mathematics and Technology Education, 10(3), p. 197-206. • Jennings, A.A. (1997). A Bioremediation teaching module based on BIO1D. Environmental Modelling & Software, 12(1), p. 1-18. • Jennings, A.A. & Kuhlman, S.J. (1997). An air pollution transport teaching module based on GAUSSIAN MODELS 1.1. Environmental Modelling & Software, 12(2-3), p. 151-160. • Kempton, W. How the Public Views Climate Change: research points to better ways to address widespread misconceptions about the problem and how to solve it. • Kim, C. & Fortner, R.W. (2006). Issue-Specific Barriers to Addressing Environmental Issues in the Classroom: an exploratory study. The Journal of Environmental Education, 37(3), p.15-22. • Littledyke, M. & Manolas, E. (2010). Ideology, Epistemology and Pedagogy: Barriers and Drivers to Education for Sustainability in Science Education. Journal of Baltic Science Education, 9(4), p.285-301. • Manolas, E. & Filho, W.L. (2011). The use of Cooperative Learning in Dispelling Student Misconceptions on Climate Change. Journal of Baltic Science Education, 10(3), p.168-182. • Rajeev Gowda, M.V., Fox, J.C., & Magelky, R.D. (1997). Students’ Understanding of Climate Change: Insights for Scientists and Educators. Educational Affairs, 78(10), p. 2232-2240.