Optimal filtering for Bayesian detection and attribution of climate change

2004 ◽  
Vol 24 (1) ◽  
pp. 45-55 ◽  
Author(s):  
R. Schnur ◽  
Kl. Hasselmann
2005 ◽  
Vol 18 (13) ◽  
pp. 2429-2440 ◽  
Author(s):  
Terry C. K. Lee ◽  
Francis W. Zwiers ◽  
Gabriele C. Hegerl ◽  
Xuebin Zhang ◽  
Min Tsao

Abstract A Bayesian analysis of the evidence for human-induced climate change in global surface temperature observations is described. The analysis uses the standard optimal detection approach and explicitly incorporates prior knowledge about uncertainty and the influence of humans on the climate. This knowledge is expressed through prior distributions that are noncommittal on the climate change question. Evidence for detection and attribution is assessed probabilistically using clearly defined criteria. Detection requires that there is high likelihood that a given climate-model-simulated response to historical changes in greenhouse gas concentration and sulphate aerosol loading has been identified in observations. Attribution entails a more complex process that involves both the elimination of other plausible explanations of change and an assessment of the likelihood that the climate-model-simulated response to historical forcing changes is correct. The Bayesian formalism used in this study deals with this latter aspect of attribution in a more satisfactory way than the standard attribution consistency test. Very strong evidence is found to support the detection of an anthropogenic influence on the climate of the twentieth century. However, the evidence from the Bayesian attribution assessment is not as strong, possibly due to the limited length of the available observational record or sources of external forcing on the climate system that have not been accounted for in this study. It is estimated that strong evidence from a Bayesian attribution assessment using a relatively stringent attribution criterion may be available by 2020.


2015 ◽  
Vol 8 (7) ◽  
pp. 1943-1954 ◽  
Author(s):  
D. R. Feldman ◽  
W. D. Collins ◽  
J. L. Paige

Abstract. Top-of-atmosphere (TOA) spectrally resolved shortwave reflectances and long-wave radiances describe the response of the Earth's surface and atmosphere to feedback processes and human-induced forcings. In order to evaluate proposed long-duration spectral measurements, we have projected 21st Century changes from the Community Climate System Model (CCSM3.0) conducted for the Intergovernmental Panel on Climate Change (IPCC) A2 Emissions Scenario onto shortwave reflectance spectra from 300 to 2500 nm and long-wave radiance spectra from 2000 to 200 cm−1 at 8 nm and 1 cm−1 resolution, respectively. The radiative transfer calculations have been rigorously validated against published standards and produce complementary signals describing the climate system forcings and feedbacks. Additional demonstration experiments were performed with the Model for Interdisciplinary Research on Climate (MIROC5) and Hadley Centre Global Environment Model version 2 Earth System (HadGEM2-ES) models for the Representative Concentration Pathway 8.5 (RCP8.5) scenario. The calculations contain readily distinguishable signatures of low clouds, snow/ice, aerosols, temperature gradients, and water vapour distributions. The goal of this effort is to understand both how climate change alters reflected solar and emitted infrared spectra of the Earth and determine whether spectral measurements enhance our detection and attribution of climate change. This effort also presents a path forward to understand the characteristics of hyperspectral observational records needed to confront models and inline instrument simulation. Such simulation will enable a diverse set of comparisons between model results from coupled model intercomparisons and existing and proposed satellite instrument measurement systems.


2008 ◽  
Vol 5 (3) ◽  
pp. 847-864 ◽  
Author(s):  
P. W. Boyd ◽  
S. C. Doney ◽  
R. Strzepek ◽  
J. Dusenberry ◽  
K. Lindsay ◽  
...  

Abstract. Concurrent changes in ocean chemical and physical properties influence phytoplankton dynamics via alterations in carbonate chemistry, nutrient and trace metal inventories and upper ocean light environment. Using a fully coupled, global carbon-climate model (Climate System Model 1.4-carbon), we quantify anthropogenic climate change relative to the background natural interannual variability for the Southern Ocean over the period 2000 and 2100. Model results are interpreted using our understanding of the environmental control of phytoplankton growth rates – leading to two major findings. Firstly, comparison with results from phytoplankton perturbation experiments, in which environmental properties have been altered for key species (e.g., bloom formers), indicates that the predicted rates of change in oceanic properties over the next few decades are too subtle to be represented experimentally at present. Secondly, the rate of secular climate change will not exceed background natural variability, on seasonal to interannual time-scales, for at least several decades – which may not provide the prevailing conditions of change, i.e. constancy, needed for phytoplankton adaptation. Taken together, the relatively subtle environmental changes, due to climate change, may result in adaptation by resident phytoplankton, but not for several decades due to the confounding effects of climate variability. This presents major challenges for the detection and attribution of climate change effects on Southern Ocean phytoplankton. We advocate the development of multi-faceted tests/metrics that will reflect the relative plasticity of different phytoplankton functional groups and/or species to respond to changing ocean conditions.


2019 ◽  
Vol 100 (10) ◽  
pp. 1987-2007 ◽  
Author(s):  
Thomas Knutson ◽  
Suzana J. Camargo ◽  
Johnny C. L. Chan ◽  
Kerry Emanuel ◽  
Chang-Hoi Ho ◽  
...  

AbstractAn assessment was made of whether detectable changes in tropical cyclone (TC) activity are identifiable in observations and whether any changes can be attributed to anthropogenic climate change. Overall, historical data suggest detectable TC activity changes in some regions associated with TC track changes, while data quality and quantity issues create greater challenges for analyses based on TC intensity and frequency. A number of specific published conclusions (case studies) about possible detectable anthropogenic influence on TCs were assessed using the conventional approach of preferentially avoiding type I errors (i.e., overstating anthropogenic influence or detection). We conclude there is at least low to medium confidence that the observed poleward migration of the latitude of maximum intensity in the western North Pacific is detectable, or highly unusual compared to expected natural variability. Opinion on the author team was divided on whether any observed TC changes demonstrate discernible anthropogenic influence, or whether any other observed changes represent detectable changes. The issue was then reframed by assessing evidence for detectable anthropogenic influence while seeking to reduce the chance of type II errors (i.e., missing or understating anthropogenic influence or detection). For this purpose, we used a much weaker “balance of evidence” criterion for assessment. This leads to a number of more speculative TC detection and/or attribution statements, which we recognize have substantial potential for being false alarms (i.e., overstating anthropogenic influence or detection) but which may be useful for risk assessment. Several examples of these alternative statements, derived using this approach, are presented in the report.


2006 ◽  
Vol 19 (20) ◽  
pp. 5058-5077 ◽  
Author(s):  
Gabriele C. Hegerl ◽  
Thomas R. Karl ◽  
Myles Allen ◽  
Nathaniel L. Bindoff ◽  
Nathan Gillett ◽  
...  

Abstract A significant influence of anthropogenic forcing has been detected in global- and continental-scale surface temperature, temperature of the free atmosphere, and global ocean heat uptake. This paper reviews outstanding issues in the detection of climate change and attribution to causes. The detection of changes in variables other than temperature, on regional scales and in climate extremes, is important for evaluating model simulations of changes in societally relevant scales and variables. For example, sea level pressure changes are detectable but are significantly stronger in observations than the changes simulated in climate models, raising questions about simulated changes in climate dynamics. Application of detection and attribution methods to ocean data focusing not only on heat storage but also on the penetration of the anthropogenic signal into the ocean interior, and its effect on global water masses, helps to increase confidence in simulated large-scale changes in the ocean. To evaluate climate change signals with smaller spatial and temporal scales, improved and more densely sampled data are needed in both the atmosphere and ocean. Also, the problem of how model-simulated climate extremes can be compared to station-based observations needs to be addressed.


2009 ◽  
Vol 22 (13) ◽  
pp. 3838-3855 ◽  
Author(s):  
H. G. Hidalgo ◽  
T. Das ◽  
M. D. Dettinger ◽  
D. R. Cayan ◽  
D. W. Pierce ◽  
...  

Abstract This article applies formal detection and attribution techniques to investigate the nature of observed shifts in the timing of streamflow in the western United States. Previous studies have shown that the snow hydrology of the western United States has changed in the second half of the twentieth century. Such changes manifest themselves in the form of more rain and less snow, in reductions in the snow water contents, and in earlier snowmelt and associated advances in streamflow “center” timing (the day in the “water-year” on average when half the water-year flow at a point has passed). However, with one exception over a more limited domain, no other study has attempted to formally attribute these changes to anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together with a set of global climate model simulations and a hydrologic model (applied to three major hydrological regions of the western United States—the California region, the upper Colorado River basin, and the Columbia River basin), it is found that the observed trends toward earlier “center” timing of snowmelt-driven streamflows in the western United States since 1950 are detectably different from natural variability (significant at the p < 0.05 level). Furthermore, the nonnatural parts of these changes can be attributed confidently to climate changes induced by anthropogenic greenhouse gases, aerosols, ozone, and land use. The signal from the Columbia dominates the analysis, and it is the only basin that showed a detectable signal when the analysis was performed on individual basins. It should be noted that although climate change is an important signal, other climatic processes have also contributed to the hydrologic variability of large basins in the western United States.


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