The Climate Web
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The Climate Web 10/5/2026
Top-Level Topical Headings
Top Level Extracted Materials Headings
E - Decisionmaking Top Level
E - Barriers to Climate Progress
E - Decisionmaking Barriers
E - Decisionmaking w Uncertainty
E - Probabilistic Decision-Making
E - Changing Probability Distributions
Parents
2 Degrees Target TOC
E - Extreme Event Impacts
E - Impacts Top Level
E - Probabilistic Decision-Making
Risks - Societal TOC
Under-Estimated Risk TOC
Worst Case Climate Change TOC
Children
1900-2010 (2011) Anomalies are clearly trending towards hot and very hot temperatures
1900-2010 (2011) U.S. temperature anomalies not nearly as clear as other parts of the world
1950-2010 (2011) Fraction of surface area that's cold or hot shifting significantly
1950-2010 (2011) One can see a systematic warming signal in a number of regions
1950-2010 (2011) The extreme heat tail of anomalies has shifted by 1 SD over 3 decades
1950-2010 (2011) We can track how annual anomalies diverge in terms of SDs from the baseline
1950-2011 (2011) The fraction of land area with very high extremes is increasing
1955-2007 (2011) We can track how surface temperatures are changing over time
1955-2011 (2011) The proportion of surface area displaying >3 SDs is growing significantly
1oC - Socioeconomic impacts of climate change already manifesting
2009 Choosing the right strategy in probability space
2009 Risk of temperature directly related to concentrations, and varies widely over time
2010 In probability distributions, modes and means and uncertainty are important
2010 rainfall anomaly against future probability distributions
2012 Extreme events are growing in probability faster than projected by the models
2012 Ratio of high to low records in the U.S. 1950's to 2000's
2013 Probability of catastrophe by treatment
2013 temperatures against future probability distribution
2015 The shock scenario
2016 Annual mean surface temperature anomaly
2016 Changing likelihood of extreme events
2016 Comparison of El Nino strength and temperature trend
2016 Decadal mean surface temperature anomaly
2016 Global surface temperature, annual and running mean
2016 ocean temperature anomaly against future probability distribution
2017 It's all about probabilities
2019 A cumulative distribution function (CDF) transforms a probability distribution into an exceedance curve from 0 to 100%. A complementary CDF (CCDF) does the reverse, from 100% to 0%
2020-2050 (2020) Increase in long tail risk of hurricane damages in Florida
2030-2050 (2020) Risk of >15% global yield failure increases 2x and 5x
2040 (2013) Median Projected Change in 1% Annual Flood Discharge
2040 (2013) Median Projected Change in SFHA
2050 (2020) Economic impact of extreme flood could be 5-10 times greater than today
2060 (2013) Median Projected Change in 1% Annual Flood Discharge
2060 (2013) Median Projected Change in SFHA
2080 (2013) Median Projected Change in 1% Annual Flood Discharge
2080 (2013) Median Projected Change in SFHA
2100 (2013) Median Projected Change in 1% Annual Flood Discharge
2100 (2013) Median Projected Change in Flood Hazard Parameter
2100 (2013) Median Projected Change in SFHA for 2100
2100 (2013) Monte Carlo Distribution for 1% Annual Flood Discharge change
Abnormal markets - stock exchange not normally distributed
And climate tipping points may be much more likely than we've thought
And there's a clear analogy to abrupt climate change
Attribution of changing water scarcity to climate and population
b. By increasing variability with the existing mean
Beta distribution
Brownian motion and stock prices - normal distributions
CCDF complementary cumulative probability function
Change in exceedance probability for normally distributed data
Change in risk of occurrence due to a trend in the mean
Changing global water scarcity risk levels
Changing likelihood of Australian extreme events
Changing likelihood of flooding
Changing temperature probabilities in Colorado River Basin
Conceptual diagram of shifting probabilities
Does climate fit into normal distribution? Evidence that it does not
E - Changing Return Periods
E - Climate Change Fingerprint
E - Communicating shifting extremes
E - Exceedance Curves
E - Forecasted Probabilities
Effect of mitigation on global emergence in drivers of ecosystem stress
End-century project flow reductions Colorado River Basin
Expected extremes based on linear change in SD
Future warming projections constrasting model vs. paleo estimates
Gamma distribution
Geographic variation in attribution variables
Increase in probability of extremes
It's a Matter of Risk and Probabiliy
Lognormal distribution
Mapped Amplification Factors
Mapping flood levels
Mid-century projected flow reductions Colorado River Basin
Moscow July Anomalies
Normal/Gaussian distribution
Northwest Atlantic cod harvest
Power law = better fit for stock extremes
Precautionary principle: making decisions without probabilities sensible, but don't take to extremes
Probability distribution with varying uncertainty around the same mean
Probability distribution with varying uncertainty around the same mode
Reconstructed global mean temperatures
Redrawing this figure using a ratio scale
Regional variation in water scarcity
Responding to fire risks: unlikely but we buy fire insurance
SAT Surface Air Temperature
Sensitivity of global SAT to radiative forcing anomalies
Shifting distribution of temperature anomalies in the Northern hemisphere, winter and summer
Small average changes in temperature can hide dramatic changes at extremes
SST Sea Surface Temperature
Stock market performance on a ratio scale
Storylines used for RCPs and SSPs
The "tails" of normal and fat-tailed distribution
The 2003 European heat wave against the normal distribution
The distribution of outcomes of rolling 10 dice at once
The distribution of outcomes of rolling two dice
The more dice, the closer you get to a "normal" distribution
The normal probability curve
Three possible outcomes in terms of probability shifts
understanding shifts in extremes due to climate change
Variations in severity of water scarcity
Weibull distribution
What causes extreme events in nature and in finance
Why uncertainty increases risk
Jumps
I - ChangingProbabilityDistributions