5. Climate Change Models

5 Climate Change Models

There are many climate change models (https://en.wikipedia.org/wiki/Climate_model). The IPCC evaluated climate models in AR4 in 2007 (https://www.ipcc.ch/report/ar4/wg1/) and in AR5 in 2013 (https://www.ipcc.ch/site/assets/uploads/2018/02/WG1AR5_Chapter09_FINAL.pdf).

5.1 Confidence in models

The 2013 IPCC evaluation states

• There continues to be very high confidence that models reproduce observed large-scale mean surface temperature patterns (pattern correlation of ~0.99), though systematic errors of several degrees are found in some regions, particularly over high topography, near the ice edge in the North Atlantic, and over regions of ocean upwelling near the equator

• There is very high confidence that models reproduce the general features of the global-scale annual mean surface temperature increase over the historical period, including the more rapid warming in the second half of the 20th century, and the cooling immediately following large volcanic eruptions.

• The simulation of large-scale patterns of precipitation has improved somewhat since the AR4, although models continue to perform less well for precipitation than for surface temperature. The spatial pattern correlation between modelled and observed annual mean precipitation has increased from 0.77 for models available at the time of the AR4 to 0.82 for current models.

• Models are able to capture the general characteristics of storm tracks and extratropical cyclones.

• Many models are able to reproduce the observed changes in upper ocean heat content from 1961 to 2005 with the multi-model mean time series falling within the range of the available observational estimates for most of the period.

• Current climate models reproduce the seasonal cycle of Arctic sea ice extent with a multi-model mean error of less than about 10% for any given month. There is robust evidence that the downward trend in Arctic summer sea ice extent is better simulated than at the time of the AR4, with about one quarter of the simulations showing a trend as strong as, or stronger, than in observations over the satellite era (since 1979).

• Section 9.8 Relating Model Performance to Credibility of Model Applications includes the following

We can demonstrate climate models are getting better with quantitative performance metrics based on historical observations. Although future climate projections cannot be directly evaluated, climate models are based, to a large extent, on verifiable physical principles and are able to reproduce many important aspects of past response to external forcing. In this way, they provide a scientifically sound preview of the climate response to different scenarios of anthropogenic forcing.

5.2 Uncertainties in future projections (https://skepticalscience.com/climate-models-intermediate.htm)

A common misconception is that climate models are biased towards exaggerating the effects from CO2. It bears mentioning that uncertainty can go either way. In fact, in a climate system with net positive feedback, uncertainty is skewed more towards a stronger climate response. For this reason, many of the IPCC predictions have subsequently been shown to underestimate the climate response. Satellite and tide-gauge measurements show that sea level rise is accelerating faster than IPCC predictions. The average rate of rise for 1993-2008 as measured from satellite is 3.4 millimetres per year while the IPCC Third Assessment Report (TAR) projected a best estimate of 1.9 millimetres per year for the same period. Observations are tracking along the upper range of IPCC sea level projections.

5.3 Climate Change Model Predictions

5.3.1 World Prediction

The IPCC reports results for several Representative Concentration Pathways (RCP). These models are run under specific scenarios of emission of CO2 and other greenhouse gases (see figure). In one, RCP8.5, we simply continue doing what we are doing, with escalating use of coal and oil which is designated the business-as-usual emission scenario. Not much renewable energy. Many believe this scenario is too pessimistic. Much more reasonable is RCP 4.5, which is designated as the modest actions to curb emissions scenario. This scenario modestly increased emissions through 2040, declining after 2050.

The implication of these emissions on global temperature is shown below based on a collection of climate models (CMIP-5). Under the extreme scenario, the earth warms by about 4C, but for the reasonable one (RCP4.5), global warming is about 2C (3.6F). This warming will not be uniform, being greater in the polar regions, less over the eastern oceans.

5.3.2 US Predictions

The following are findings from the Climate Science Special Report of the Fourth National Climate Assessment issued in 2018 by the U.S. Global Change Research Program (https://www.globalchange.gov/nca4)

1. Global annual average temperature

a. Increased by about 1.8°F from 1901 to 2016

b. Will increase by the end of this century compared to preindustrial temperatures

i. With significant reductions in emissions - 3.6°F (2°C) or less

ii. Without significant reductions - 9°F (5°C) or more

2. US annual average temperature

a. Increased by about 1.8°F from 1901 to 2016

b. Additional increases of about 2.5°F (1.4°C) are expected over the next few decades regardless of future emissions

c. Increases ranging from 3°F to 12°F (1.6°–6.6°C) are expected by the end of century depending on emission reductions

3. Rising global sea levels

a. 7-8 inches (16-21 cm) since 1900

b. Relative to the year 2000

i. 1 to 4 feet (0.3 to 1.3 m) by the end of the century is very likey

ii. 8 feet (2.4 m) by 2100 is physically possible, although the probability of such an extreme outcome cannot currently be assessed

4. Frequency, depth, and extent of tidal flooding are expected to continue to increase

a. Severe Storms

i. Increased hurricane activity

ii. landfalling “atmospheric rivers” on the West Coast

b. US Precipitation

i. significant increases are projected in winter and spring over the Northern Great Plains, the Upper Midwest, and the Northeast

ii. increases in the frequency and intensity of heavy precipitation events in most parts of the United States

iii. Surface soil moisture over most of the United States is likely to decrease

5.3.3 Dissenting Views on Model Predictions - Models Overpredict Global Warming

i) Richard Lindzen has expressed his concern over the validity of computer models used to predict future climate change. Lindzen said that predicted warming may be overestimated because of their handling of the climate system's water vapor feedback. (https://en.wikipedia.org/wiki/Richard_Lindzen#Views_on_climate_change)

ii) Will Harper, Fred Singer disagrees with the scientific consensus on climate change, stating that "Some small fraction of the 1 °C warming during the past two centuries must have been due to increasing CO2, which is indeed a greenhouse gas", but argues that "most of the warming has probably been due to natural causes.” However, he provides no evidence to support this contention. (https://en.wikipedia.org/wiki/William_Happer)

iii) Naomi Oreskes has published a paper “The Scientific Consensus on Climate Change: How Do We Know We’re Not Wrong?” refuting the dissenters positions (http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.800.4969&rep=rep1&type=pdf)

A common misconception is that climate models are biased towards exaggerating the effects from CO2. It bears mentioning that uncertainty can go either way. In fact, in a climate system with net positive feedback, uncertainty is skewed more towards a stronger climate response For this reason, many of the IPCC predictions have subsequently been shown to underestimate the climate response. Satellite and tide-gauge measurements show that sea level rise is accelerating faster than IPCC predictions. The average rate of rise for 1993-2008 as measured from satellite is 3.4 millimetres per year while the IPCC Third Assessment Report (TAR) projected a best estimate of 1.9 millimetres per year for the same period. Observations are tracking along the upper range of IPCC sea level projections.

Climate models are unable yet to predict abrupt climate change events, or most of the past abrupt climate shifts.

There are at least two types of potential abrupt change events: compound events, where multiple extreme climate events occur simultaneously or sequentially (creating greater overall impact), and critical threshold or tipping point events, where some threshold is crossed in the climate system (that leads to large impacts). The probability of abrupt change events—some of which may be abrupt and/or irreversible—as well as other more predictable but difficult-to-manage impacts, increases as the influence of human activities on the climate system increases. (Chapter 15 Fourth National Climate Assessment).

5.3.4.1 Tipping Points

A tipping point is a critical threshold at which the future state of a system can be qualitatively altered by a small change in forcing. A tipping element is a part of the Earth system (at least sub-continental in scale) that has a tipping point. Policy-relevant tipping elements are those that could be forced past a tipping point by human activities. Abrupt climate change is the subset of tipping point change which occurs faster than its cause. Tipping point change also includes transitions that are slower than their cause (in both cases the rate is determined by the system itself). In either case the change in state may be reversible or irreversible. Reversible means that when the forcing is returned below the tipping point the system recovers its original state (either abruptly or gradually). Irreversible means that it does not (it takes a larger change in forcing to recover). Reversibility in principle does not mean that changes will be reversible in practice.

A shortlist of nine potential policy-relevant tipping elements in the climate system that could pass a tipping point this century and undergo a transition this millennium under projected climate change. These are shown with some other candidates in Figure 1.

We should be most concerned about those tipping points that are nearest (least avoidable) and those that have the largest negative impacts. Generally, the more rapid and less reversible a transition is, the greater its impacts. Additionally, any positive feedback to global climate change may increase concern, as can interactions whereby tipping one element encourages tipping another.

The following are some of the most concerning tipping elements:

The Greenland ice sheet (GIS) may be nearing a tipping point where it is committed to shrink. Once underway the transition to a smaller ice cap will have low reversibility, although it is likely to take several centuries (and is therefore not abrupt). The impacts via sea level rise will ultimately be large and global but will depend on the rate of ice sheet shrinkage. Latest work suggests there may be several stable states for ice volume, with the first transition involving retreat of the ice sheet onto land and around 1.5 m of sea level rise.

The West Antarctic ice sheet (WAIS) is currently assessed to be further from a tipping point than the GIS, but this is more uncertain.

The Amazon rainforest experienced widespread drought in 2005 turning the region from a sink to a source (0.6-0.8 PgC yr-1) of carbon. If anthropogenic-forced lengthening of the dry season continues, and droughts increase in frequency or severity, the rainforest could reach a tipping point resulting in dieback of up to ~80% of the rainforest, and its replacement by savannah. This could take a few decades, would have low reversibility, large regional impacts, and knock-on effects far away. Widespread dieback is expected in a >4 °C warmer world, and it could be committed to at a lower global temperature, long before it begins to be observed.

The Sahel and West African Monsoon (WAM) have experienced rapid but reversible changes in the past, including devastating drought from the late 1960s through the 1980s. Forecast future weakening of the Atlantic thermohaline circulation contributing to ‘Atlantic Niño’ conditions, including strong warming in the Gulf of Guinea, could disrupt the seasonal onset of the WAM16 and its later ‘jump’ northwards into the Sahel.

The Indian Summer Monsoon (ISM) is probably already being disrupted by an atmospheric brown cloud (ABC) haze that sits over the sub-continent and, to a lesser degree, the Indian Ocean. The ABC haze is comprised of a mixture of soot, which absorbs sunlight, and some reflecting sulfate. It causes heating of the atmosphere rather than the land surface, weakening the seasonal establishment of a land-ocean temperature gradient which is critical in triggering monsoon onset

Estimation of likelihood under different scenarios

If we pass climate tipping points due to human activities (which in IPCC language are called “large scale discontinuities”), then this would qualify as dangerous anthropogenic interference (DAI) in the climate system. Relating actual regional tipping points to e.g. global mean temperature change is always indirect, often difficult and sometimes not meaningful. Considering a longer list of 9 potential tipping elements, Figure 2 summarizes recent information on the likelihood of tipping them under the IPCC range of projected global warming this century. (https://www.epa.gov/sites/production/files/2017-09/documents/ee-0564_all.pdf)

For some of the tipping points, it may be possible to detect whether that part of the climate system is getting closer to a tipping point. All parts of the climate system are sometimes disturbed by weather events. After the disruption, the system moves back to its equilibrium. A storm may damage sea ice, which grows back after the storm has passed. If a system is getting closer to tipping, this restoration to its normal state might take increasingly longer, which can be used as a warning sign of tipping (https://en.wikipedia.org/wiki/Tipping_points_in_the_climate_system).

Major restructuring of the Atlantic meridional overturning circulation, the Greenland and West Antarctic ice sheets, the Amazon rainforest and ENSO, are a source of concern for climate policy. Another paper (https://www.pnas.org/content/106/13/5041) elicited subjective probability intervals for the occurrence of such major changes under global warming from 43 scientists. Although the expert estimates highlight large uncertainty, they allocate significant probability to some of the events listed above. The paper deduced conservative lower bounds for the probability of triggering at least 1 of those events of 0.16 for medium (2–4 °C), and 0.56 for high global mean temperature change (above 4 °C) relative to year 2000 levels.