Drafting Authors: Neil Adger, Pramod Aggarwal, Shardul Agrawala, Joseph Alcamo, Abdelkader Allali, Oleg Anisimov, Nigel Arnell, Michel Boko, Osvaldo Canziani, Timothy Carter, Gino Casassa, Ulisses Confalonieri, Rex Victor Cruz, Edmundo de Alba Alcaraz, William Easterling, Christopher Field, Andreas Fischlin, Blair Fitzharris, Carlos Gay García, Clair Hanson, Hideo Harasawa, Kevin Hennessy, Saleemul Huq, Roger Jones, Lucka Kajfež Bogataj, David Karoly, Richard Klein, Zbigniew Kundzewicz, Murari Lal, Rodel Lasco, Geoff Love, Xianfu Lu, Graciela Magrín, Luis José Mata, Roger McLean, Bettina Menne, Guy Midgley, Nobuo Mimura, Monirul Qader Mirza, José Moreno, Linda Mortsch, Isabelle Niang-Diop, Robert Nicholls, Béla Nováky, Leonard Nurse, Anthony Nyong, Michael Oppenheimer, Jean Palutikof, Martin Parry, Anand Patwardhan, Patricia Romero Lankao, Cynthia Rosenzweig, Stephen Schneider, Serguei Semenov, Joel Smith, John Stone, Jean-Pascal van Ypersele, David Vaughan, Coleen Vogel, Thomas Wilbanks, Poh Poh Wong, Shaohong Wu, Gary Yohe

Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change

One of the major concerns with a potential change in climate is that an increase in extreme events will occur. Results of observational studies suggest that in many areas that have been analyzed, changes in total precipitation are amplified at the tails, and changes in some temperature extremes have been observed. Model output has been analyzed that shows changes in extreme events for future climates, such as increases in extreme high temperatures, decreases in extreme low temperatures, and increases in intense precipitation events. In addition, the societal infrastructure is becoming more sensitive to weather and climate extremes, which would be exacerbated by climate change. In wild plants and animals, climate-induced extinctions, distributional and phenological changes, and species' range shifts are being documented at an increasing rate. Several apparently gradual biological changes are linked to responses to extreme weather and climate events.

https://www7.nau.edu/mpcer/direnet/publications/publications_e/files/Easterling_et_al_2000.pdf

Climate Extremes: Observations, Modeling, and Impacts

A suite of climate change indices derived from daily temperature and precipitation data, with a primary focus on extreme events, were computed and analyzed. By setting an exact formula for each index and using specially designed software, analyses done in different countries have been combined seamlessly. This has enabled the presentation of the most up-to-date and comprehensive global picture of trends in extreme temperature and precipitation indices using results from a number of workshops held in data-sparse regions and high-quality station data supplied by numerous scientists world wide. Seasonal and annual indices for the period 1951-2003 were gridded. Trends in the gridded fields were computed and tested for statistical significance. Results showed widespread significant changes in temperature extremes associated with warming, especially for those indices derived from daily minimum temperature. Over 70% of the global land area sampled showed a significant decrease in the annual occurrence of cold nights and a significant increase in the annual occurrence of warm nights. Some regions experienced a more than doubling of these indices. This implies a positive shift in the distribution of daily minimum temperature throughout the globe. Daily maximum temperature indices showed similar changes but with smaller magnitudes. Precipitation changes showed a widespread and significant increase, but the changes are much less spatially coherent compared with temperature change. Probability distributions of indices derived from approximately 200 temperature and 600 precipitation stations, with near-complete data for 1901-2003 and covering a very large region of the Northern Hemisphere midlatitudes (and parts of Australia for precipitation) were analyzed for the periods 1901-1950, 1951-1978 and 1979-2003. Results indicate a significant warming throughout the 20th century. Differences in temperature indices distributions are particularly pronounced between the most recent two periods and for those indices related to minimum temperature. An analysis of those indices for which seasonal time series are available shows that these changes occur for all seasons although they are generally least pronounced for September to November. Precipitation indices show a tendency toward wetter conditions throughout the 20th century.

/pdf/global-observed-changes-in-daily-climate-extremes-of-50pijshpdk.pdf

Global observed changes in daily climate extremes of temperature and precipitation

/pdf/statistical-analysis-in-climate-research-51ik9f04rx.pdf

Statistical Analysis in Climate Research

Stimulation of Toll-like receptors (TLRs) triggers activation of a common MyD88-dependent signaling pathway as well as a MyD88-independent pathway that is unique to TLR3 and TLR4 signaling pathways leading to interferon (IFN)-beta production. Here we disrupted the gene encoding a Toll/IL-1 receptor (TIR) domain-containing adaptor, TRIF. TRIF-deficient mice were defective in both TLR3- and TLR4-mediated expression of IFN-beta and activation of IRF-3. Furthermore, inflammatory cytokine production in response to the TLR4 ligand, but not to other TLR ligands, was severely impaired in TRIF-deficient macrophages. Mice deficient in both MyD88 and TRIF showed complete loss of nuclear factor kappa B activation in response to TLR4 stimulation. These findings demonstrate that TRIF is essential for TLR3- and TLR4-mediated signaling pathways facilitating mammalian antiviral host defense.

https://science.sciencemag.org/content/sci/301/5633/640.full.pdf

Role of adaptor TRIF in the MyD88-independent toll-like receptor signaling pathway.

1. Introduction Part I. Fundamentals: 2. Probability theory 3. Distributions of climate variables 4. Concepts in statistical inference 5. Estimation Part II. Confirmation and Analysis: 6. The statistical test of a hypothesis 7. Analysis of atmospheric circulation problems Part III. Fitting Statistical Models: 8. Regression 9. Analysis of variance Part IV. Time Series: 10. Time series and stochastic processes 11. Parameters of univariate and bivariate time series 12. Estimating covariance functions and spectra Part V. Eigen Techniques: 13. Empirical orthogonal functions 14. Canonical correlation analysis 15. POP analysis 16. Complex eigentechniques Part VI. Other Topics: 17. Specific statistical concepts in climate research 18. Forecast quality evaluation Part VII. Appendices.

/pdf/statistical-analysis-in-climate-research-4slttxsmqi.pdf

https://hal.archives-ouvertes.fr/hal-03026507/document

Understanding and Attributing Climate Change

[1] The area burned by forest fires in Canada has increased over the past four decades, at the same time as summer season temperatures have warmed. Here we use output from a coupled climate model to demonstrate that human emissions of greenhouse gases and sulfate aerosol have made a detectable contribution to this warming. We further show that human-induced climate change has had a detectable influence on the area burned by forest fire in Canada over recent decades. This increase in area burned is likely to have important implications for terrestrial emissions of carbon dioxide and for forest ecosystems.

/pdf/detecting-the-effect-of-climate-change-on-canadian-forest-4jp3pdjp9u.pdf

Detecting the effect of climate change on Canadian forest fires

Changes in temperature and precipitation extremes are examined in transient climate change simulations performed with the second-generation coupled global climate model of the Canadian Centre for Climate Modelling and Analysis. Three-member ensembles were produced for the time period 1990–2100 using the IS92a, A2, and B2 emission scenarios of the Intergovernmental Panel on Climate Change. The return values of annual extremes are estimated from a fitted generalized extreme value distribution with time-dependent location and scale parameters by the method of maximum likelihood. The L-moment return value estimates are revisited and found to be somewhat biased in the context of transient climate change simulations. The climate response is of similar magnitude in the integrations with the IS92a and A2 emission scenarios but more modest for the B2 scenario. Changes in temperature extremes are largely associated with changes in the location of the distribution of annual extremes without substantial chan...

Francis W. Zwiers

Papers

Statistical Analysis in Climate Research

Statistical Analysis in Climate Research

Understanding and Attributing Climate Change

Detecting the effect of climate change on Canadian forest fires

Estimating Extremes in Transient Climate Change Simulations