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Learning about Climate Change
Overall Trends in Climate Change | Uncertainty | Emission and Climate Scenarios | Climate Models| Interpreting Outputs | Projections Used | Other Resources | References
Overall Trends in Climate Change
The climate is changing rapidly in Massachusetts in ways that have already impacted fish, wildlife, and their habitats. These impacts will continue as climate change increases over the coming decades.
Warming is occurring in all seasons, with the greatest changes in winter, at higher latitudes, and potentially at higher elevations. Seasonal warming is extending the growing season, particularly with more frost free days occurring earlier in spring. Precipitation amounts are increasing, especially in winter. Warmer winters are also resulting in more precipitation falling as rain instead of snow, leading to reduced snowpacks - though stronger blizzards may lead to locally higher snowpacks in Massachusetts and New England. In the summer, heavier downpours combined with longer dry streaks are expected, increasing the risk of both droughts and floods. Sea level is also rising at a rapid rate along the Massachusetts coastline, leading to coastal flooding, which is compounded by increasingly intense coastal storms, such as hurricanes.
- Temperature changes
- Precipitation changes
- Changes in hydrology
- Changes in winter
- Sea level rise
- Storms and floods
- Coastal Storms
- Change in timing of seasons
Climate changes over the past century can be explained through a combination of human and natural factors with the majority explained by human sources of emissions from burning fossil fuels. Even if all emissions ceased today, warming would continue for at least the next couple of decades. Therefore, it is important to explore ways to cope or adapt to these changes in addition to reducing or mitigating the effects of future warming. Local decisions made now in Massachusetts in how natural resources are managed and conserved can also make important differences in the ability of fish and wildlife species to cope with future climate changes.
Changes in temperature in Boston, MA from 1750 - 2013. Data courtesy of Berkeley Earth, http://www.berkeleyearth.org
Climate change is an area of active research, and many uncertainties and gaps in our knowledge exist. As described below, there are many steps in projecting climate impacts through modeling approaches that can introduce sources of uncertainty ranging from the amounts of carbon emissions to be released over the coming decades, to differences in how climate models represent the Earth system, to unknowns about how fish and wildlife species will respond. While these uncertainties and knowledge gaps pose challenges for planning, they should not prevent decisions and actions. There are many things that are certain for Massachusetts and the Northeast: the climate is warming, resulting in longer growing seasons, more extreme events, and many related impacts on wildlife and habitats (e.g., increased pests and disease, vegetation shifts). For these more certain aspects of climate change, plans and actions can be made with a high degree of confidence. For areas that are less certain, such as local scale precipitation and surface hydrology (e.g., terrestrial drought, river and stream flows, vernal pool formation), planners need to consider different management options and the available resources they have to deal with the full range of projected outcomes. Many decision-support approaches exist to guide actions in the face of uncertainty, including structured decision making and scenario planning.
Emission and Climate Scenarios
Storylines of Possible Futures are Developed From Emission Scenarios, Climate Scenarios, Model Variability and Uncertainty. Many aspects of future climate are uncertain. For instance, we do not know which policies or regulations will be enacted (if any) to help reduce greenhouse gas emissions. Nor do we know how technology and our culture will progress to decrease our dependence and use of fossil fuels. Our understanding of the Earth’s climate system is also imperfect. For instance, it is not clear if a warming atmosphere will affect El Niño and other natural phenomena, and how those effects will translate to climate patterns in Massachusetts. Our ability to predict the future is limited by the fact that our atmosphere cannot be perfectly represented by a set of equations (i.e., climate models). Because of these uncertainties, we cannot know how the future will look. However, we can know how the future might look. Therefore, future climate is described, not in terms of a single forecast, but as a range of possible conditions. Among that range, a few representative storylines, or “scenarios,” are examined (e.g., a worst-case scenario, a best-case scenario, and 1-2 mid-range scenarios). These storylines can be used to inform local adaptation strategies and actions related to the conservation and management of fish, wildlife and their habitats in Massachusetts.
- Emission scenarios describe future releases of greenhouse gases, aerosols, and other pollutants into the atmosphere, and are based on expected changes in human populations and technology.
- Climate scenarios describe the average characteristics of a possible future climate (e.g. hotter and drier).
- Overall, emissions scenarios are the driving force, or cause, while climate scenarios describe the effect.
Because we do not know how humans will respond to climate change, more than one scenario or storyline is often used in future projections to portray a range of possible futures; for example, a high amount of climatic change would be depicted by a scenario in which emissions continue at current rates, and a low amount of change would assume policies and regulations reduce the emission of greenhouse gases.
Up until 2013, the Special Report on Emissions Scenarios (SRES) emission storylines were primarily used for making future climate projections. Some of the most commonly used SRES storylines ranging from highest to lowest future emissions are:
- A1Fi: the highest scenario of high fossil fuels and rapid economic growth
- A1B: a mid-range scenario, which describes a balance of all energy sources
- A2: a slow rate of future change in a heterogeneous world
- B1: the slowest change of declining global population by mid-century and simultaneous increase in clean technologies
In 2013, the Intergovernmental Panel on Climate Change (IPCC) provided an updated (from the 2007 SRES) series of four emission scenarios known as Representative Concentration Pathways (RCPs), based on explicit policies, such as mitigation to reduce greenhouse gas emissions, as well as demographic, economic, and technological shifts. RCPs range from:
- RCP 2.6: a low scenario that assumes major reductions in emissions and shifts in climate policies, involving action by both developed and undeveloped nations
- RCP 4.5: a moderate scenario where emissions peak around mid-century and then decline rapidly over the second half of the century
- RCP 8.5: the highest scenario, which assumes that we continue on the approximate climate trajectory we are currently on - often referred to as “business-as-usual”
Differences in projections using SRES and RCPs reflect differences in the emissions scenarios (future human behavior) rather than differences among the climate models, although many new climate models have been added and existing models were improved. Both sets of scenarios are useful and have similar results. Studies that began their work around 2013 are more likely to use RCPs to inform their future projections, but many recently published studies still use the SRES. Lastly, it is important to note that all of the SRES and RCP scenarios are equally likely as there are no probabilities associated with them. SRES and RCP scenarios also may not encompass all possible futures; however, they can be used to describe how our climate system may respond through a number of possible pathways of future emissions.
Figure showing emission levels from SRES and RCPs scenarios from Walsh et al. 2014.
- Climate models are the tools that are used to study the impacts of greenhouse gas emissions on Earth’s climate.
- Emission scenarios are inputs into large scale models known as General Circulation Models? or Global Climate Models (GCMs).
- GCMs capture physical processes of our global climate system including the atmosphere, ocean, ice sheet, and land surfaces.
Several climate models have been developed by different institutions around the world. Although these models were built from similar fundamental physical principles, they can predict different future conditions due to differences in how they represent more complex processes, such as land-atmosphere interactions. GCMs also have different spatial resolutions. Because different models can produce different results, it is customary to use an average across multiple models, known as an “ensemble average.” Over the last few decades, confidence in projections of future climate change using GCMs has increased as research has improved our understanding of large scale processes on Earth.
Simulating our complex atmosphere with a climate model can require enormous computer resources and computation time. Global models, in particular, can take weeks to months to run on even the most advanced supercomputers. To save time and resources, global models are run at coarse resolution, and thus poorly represent local scale changes. Downscaling techniques are helpful in transforming the climate change information obtained from GCMs to much higher spatial resolution and can help us better understand local and regional scale climate changes. Similarly to GCMs, downscaling approaches can also yield different model results. While downscaling is a necessary step for adequately representing the local climate, the additional modeling introduces additional uncertainties due to differences in how models capture fine-scale atmospheric processes.
World Climate Research Program (WCRP) and Coupled Model Intercomparison Project (CMIP) are collections of model outputs that are freely available to the public. In 2008, CMIP5 were developed (extending upon CMIP3; there is no CMIP4) to serve as the basis for the new RCP scenarios.
There are multiple steps to climate modeling approaches and in developing projections of how fish and wildlife will be impacted by future changes. Emission scenarios, depicting possible futures, are input to large scale GCMs, which then inform more regional scale climate impacts. Regional climate projections in temperature and precipitation can then be incorporated into species or habitat models to estimate the response or impact on a particular fish and wildlife species of interest at a given location (e.g., Cape Cod and the Islands of MA). Figure created and used with permission by R. Palmer and M. Wiley; original image sources included in figure are (from top left to bottom right) 2014 National Climate Assessment Report, NOAA, University of Oregon, A. Polebitski (University of Wisconsin Plattville), Conservation Assessment and Prioritization System, and USGS.
In the short term (over the next 5-20 years), the direction and magnitude of warming in the global climate are mostly consistent across all emissions scenarios and with strong agreement across climate models. There is high certainty that Massachusetts and the greater Northeast United States will continue to experience warming. It is likely that Massachusetts will experience precipitation shifts from snow to rain, though shifts in the amount of total precipitation (rain and snow) are less certain. Severe weather events (e.g., thunderstorms, tornadoes) are challenging to project. Soil moisture and evapotranspiration (movement of water among plants, land, waterbodies, and atmosphere) trends are neither robustly observed nor consistent amongst modeling studies.
Interpreting Climate Model Outputs
Interpretation of climate model outputs can be aided by a firm understanding of some important terms. Projections show a range of what could happen based on a range of future scenarios. In contrast, predictions describe what will happen assuming one particular scenario plays out. A forecast is a prediction used exclusively in predicting short-term (i.e., days to weeks) weather patterns. Model projections (i.e., what could happen) are not predictions (i.e., what will happen) because the final outcome depends on how greenhouse gas emissions change over time as policies and human activities shift.
Projections Used in the Climate Action Tool
Climate projections reported on this website use a combination of SRES and RCP emission scenarios as well as different GCMs and downscaling approaches. Generally, Climate Change Tree Atlas projections used PCM and GFDL models and high (A1Fi) and low (B1) SRES scenarios. Climate Change Bird Atlas projections used the Met Office Hadley Centre model (HadCM3), the Geophysical Fluid Dynamics Laboratory (GFDL CM2.1) Model, and the Parallel Climate Model (PCM) coupled with high (A1Fi) and low (B1) SRES scenarios. The Designing Sustainable Landscapes Project used an ensemble of 14 Atmosphere-Ocean General Circulation Models (AOGCMs) and RCPs 4.5 and 8.5.
- Climate Funding Opportunities
- Designing Sustainable Landscapes Project
- Climate Change Bird Atlas
- Climate Change Tree Atlas
- Coastal Landscape Response to Sea-Level Rise Assessment for the Northeastern United States
- The Third National Climate Assessment Report
- Integrating Climate Change into Northeast and Midwest State Wildlife Action Plans
- NCDC. 2015. Climate at a Glance
- USGS National Climate Change Viewer
- National Oceanic and Atmospheric Administration
- University of Oregon, Department of Geography, Global Climate Animations
- University of Massachusetts Amherst Conservation Assessment and Prioritization System (CAPS) Program
Hammond, J. S., R. L. Keeney, and H. Raiffa. 1999. Smart choices: A practical guide to making better decisions. Harvard Business Review Press, Cambridge, Massachusetts.
Hayhoe, K., C. P., Wake, T. G. Huntington, L. Luo, M. D. Schwartz, J. Sheffield, E. F. Wood, B. Anderson, J. Bradbury, A. DeGaetano, T. Troy, and D. Wolfe. 2006. Past and future changes in climate and hydrological indicators in the U.S. Northeast. Climate Dynamics 28:381-407.
Intergovernmental Panel on Climate Change (IPCC). 2007. Climate change 2007: impacts, adaptation, and vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. M. L. Parry, O. F. Canziani, J. P. Palutikof, P. J. van der Linden, and C. E. Hanson, editors. Cambridge University Press, Cambridge, UK.
Intergovernmental Panel on Climate Change (IPCC). 2013: Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Stocker, T.vF., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, and P.M. Midgley, editors. Cambridge University Press, Cambridge, UK.
Knutti R, and J. Sedláček. 2013. Robustness and uncertainties in the new CMIP5 climate model projections. Nature Climate Change 3:369-373.
Moss, R. H., et al. 2010. The next generation of scenarios for climate change research and assessment. Nature 463:747-756.
Rowland, E. L., M. S. Cross, and H. Hartmann. 2014. Considering Multiple Futures: Scenario Planning To Address Uncertainty in Natural Resource Conservation. US Fish and Wildlife Service, Washington, DC.
Walsh, J., D. Wuebbles, K. Hayhoe, J. Kossin, K. Kunkel, G. Stephens, P. Thorne, R. Vose, M. Wehner, J. Willis, D. Anderson, S. Doney, R. Feely, P. Hennon, V. Kharin, T. Knutson, F. Landerer, T. Lenton, J. Kennedy, and R. Somerville, 2014: Ch. 2: Our Changing Climate. Climate Change Impacts in the United States: The Third National Climate Assessment, J. M. Melillo, Terese (T.C.) Richmond, and G. W. Yohe, Eds., U.S. Global Change Research Program, 19-67.
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