An official website of the United States government
Background. We describe and provide an initial evaluation of the Climate Action Simulation, a simulation-based role-playing game that enables participants to learn for themselves about the response of the climate-energy system to potential policies and actions. Participants gain an understanding of the scale and urgency of climate action, the impact of different policies and actions, and the dynamics and interactions of different policy choices. Intervention. The Climate Action Simulation combines an interactive computer model, En-ROADS, with a role-play in which participants make decisions about energy and climate policy. They learn about the dynamics of the climate and energy systems as they discover how En-ROADS responds to their own climate-energy decisions. Methods. We evaluated learning outcomes from the Climate Action Simulation using pre- and post-simulation surveys as well as a focus group. Results. Analysis of survey results showed that the Climate Action Simulation increases participants’ knowledge about the scale of emissions reductions and policies and actions needed to address climate change. Their personal and emotional engagement with climate change also grew. Focus group participants were overwhelmingly positive about the Climate Action Simulation, saying it left them feeling empowered to make a positive difference in addressing the climate challenge. Discussion and Conclusions. Initial evaluation results indicate that the Climate Action Simulation offers an engaging experience that delivers gains in knowledge about the climate and energy systems, while also opening affective and social learning pathways.
more »
« less
The dynamics and changes of the world’s monsoons
The seasonal rainy phase observed in many places across Earth is shaping the climate and is being changed by global climate trends.
more »
« less
- Award ID(s):
- 2123327
- PAR ID:
- 10487165
- Publisher / Repository:
- Physics Today
- Date Published:
- Journal Name:
- Physics Today
- Volume:
- 76
- Issue:
- 9
- ISSN:
- 0031-9228
- Page Range / eLocation ID:
- 32 to 38
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract The Miocene epoch (23.03–5.33 Ma) was a time interval of global warmth, relative to today. Continental configurations and mountain topography transitioned toward modern conditions, and many flora and fauna evolved into the same taxa that exist today. Miocene climate was dynamic: long periods of early and late glaciation bracketed a ∼2 Myr greenhouse interval—the Miocene Climatic Optimum (MCO). Floras, faunas, ice sheets, precipitation,pCO2, and ocean and atmospheric circulation mostly (but not ubiquitously) covaried with these large changes in climate. With higher temperatures and moderately higherpCO2(∼400–600 ppm), the MCO has been suggested as a particularly appropriate analog for future climate scenarios, and for assessing the predictive accuracy of numerical climate models—the same models that are used to simulate future climate. Yet, Miocene conditions have proved difficult to reconcile with models. This implies either missing positive feedbacks in the models, a lack of knowledge of past climate forcings, or the need for re‐interpretation of proxies, which might mitigate the model‐data discrepancy. Our understanding of Miocene climatic, biogeochemical, and oceanic changes on broad spatial and temporal scales is still developing. New records documenting the physical, chemical, and biotic aspects of the Earth system are emerging, and together provide a more comprehensive understanding of this important time interval. Here, we review the state‐of‐the‐art in Miocene climate, ocean circulation, biogeochemical cycling, ice sheet dynamics, and biotic adaptation research as inferred through proxy observations and modeling studies.more » « less
-
Abstract Improved estimation of climate niches is critical, given climate change. Plant adaptation to climate depends on their physiological traits and their distributions, yet traits are rarely used to inform the estimation of species climate niches, and the power of a trait‐based approach has been controversial, given the many ecological factors and methodological issues that may result in decoupling of species' traits from their native climate.For 107 species across six ecosystems of California, we tested the hypothesis that mechanistic leaf and wood traits can robustly predict the mean of diverse species' climate distributions, when combining methodological improvements from previous studies, including standard trait measurements and sampling plants growing together at few sites. Further, we introduce an approach to quantify species' trait‐climate mismatch.We demonstrate a strong power to predict species mean climate from traits. As hypothesized, the prediction of species mean climate is stronger (and mismatch lower) when traits are sampled for individuals closer to species' mean climates.Improved resolution of species' climate niches based on mechanistic traits can importantly inform conservation of vulnerable species under the threat of climatic shifts in upcoming decades. Read the freePlain Language Summaryfor this article on the Journal blog.more » « less
-
Summary Predictive relationships between plant traits and environmental factors can be derived at global and regional scales, informing efforts to reorient ecological models around functional traits. However, in a changing climate, the environmental variables used as predictors in such relationships are far from stationary. This could yield errors in trait–environment model predictions if timescale is not accounted for.Here, the timescale dependence of trait–environment relationships is investigated by regressingin situtrait measurements of specific leaf area, leaf nitrogen content, and wood density on local climate characteristics summarized across several increasingly long timescales.We identify contrasting responses of leaf and wood traits to climate timescale. Leaf traits are best predicted by recent climate timescales, while wood density is a longer term memory trait. The use of sub‐optimal climate timescales reduces the accuracy of the resulting trait–environment relationships.This study concludes that plant traits respond to climate conditions on the timescale of tissue lifespans rather than long‐term climate normals, even at large spatial scales where multiple ecological and physiological mechanisms drive trait change. Thus, determining trait–environment relationships with temporally relevant climate variables may be critical for predicting trait change in a nonstationary climate system.more » « less
-
Abstract The Gulf Stream is a vital limb of the North Atlantic circulation that influences regional climate, sea level, and hurricane activity. Given the Gulf Stream's relevance to weather and climate, many studies have attempted to estimate trends in its volumetric transport from various data sets, but results have been inconclusive, and no consensus has emerged whether it is weakening with climate change. Here we use Bayesian analysis to jointly assimilate multiple observational data sets from the Florida Straits to quantify uncertainty and change in Gulf Stream volume transport since 1982. We find with virtual certainty (probabilityP > 99%) that Gulf Stream volume transport through the Florida Straits declined by 1.2 ± 1.0 Sv in the past 40 years (95% credible interval). This significant trend has emerged from the data set only over the past ten years, the first unequivocal evidence for a recent multidecadal decline in this climate‐relevant component of ocean circulation.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1063/PT.3.5308
