Apr 25, 2008

-A Close Review on Global Warming

I thought it's time (although better then late) to have a close look on the technicalities of this serious issue that is overlooked by many and mostly politicians!

Global warming is the increase in the average temperature of the Earth's near-surface air and oceans since the mid-twentieth century and its projected continuation.

The average global air temperature near the Earth's surface increased 0.74 ± 0.18 °C (1.33 ± 0.32 °F) during the hundred years ending in 2005

Climate model projections summarized by the IPCC indicate that average global surface temperature will likely rise a further 1.1 to 6.4 °C (2.0 to 11.5 °F) during the twenty-first century. The range of values results from the use of differing scenarios of future greenhouse gas emissions as well as models with differing climate sensitivity. Although most studies focus on the period up to 2100, warming and sea level rise are expected to continue for more than a thousand years even if greenhouse gas levels are stabilized. The delay in reaching equilibrium is a result of the large heat capacity of the oceans.

Increasing global temperature will cause sea level to rise, and is expected to increase the intensity of extreme weather events and to change the amount and pattern of precipitation. Other effects of global warming include changes in agricultural yields, trade routes, glacier retreat, species extinctions and increases in the ranges of disease vectors.

Remaining scientific uncertainties include the amount of warming expected in the future, and how warming and related changes will vary from region to region around the globe. Most national governments have signed and ratified the Kyoto Protocol aimed at reducing greenhouse gas emissions, but there is ongoing political and public debate worldwide regarding what, if any, action should be taken to reduce or reverse future warming or to adapt to its expected consequences.

This image shows the instrumental record of global average temperatures as compiled by the Climatic Research Unit of the University of East Anglia and the Hadley Centre of the UK Meteorological Office. Data set HadCRUT3 was used. HadCRUT3 is a record of surface temperatures collected from land and ocean-based stations. The most recent documentation for this data set is Brohan, P., J.J. Kennedy, I. Haris, S.F.B. Tett and P.D. Jones (2006). "Uncertainty estimates in regional and global observed temperature changes: a new dataset from 1850". J. Geophysical Research 111: D12106. doi:10.1029/2005JD006548. Following the common practice of the IPCC, the zero on this figure is the mean temperature from 1961-1990.

Global average radiative forcing estimates and ranges in 2005 for anthropogenic greenhouse gases and other important agents and mechanisms.

Understanding global warming requires understanding the changes in climate forcings that have occurred since the industrial revolution. These include positive forcing from increased greenhouse gases, negative forcing from increased sulphate aerosols and poorly constrained forcings from indirect aerosol feedbacks as well as minor contributions from solar variability and other factors. The poorly constrained aerosol effects results from both limited physical understanding of how aerosols interact with the atmosphere and limited knowledge of aerosol concentrations during the pre-industrial period. This is a significant source of uncertainty in comparing modern climate forcings to past states.

Contrary to the impression given by this figure, it is not possible to simply sum the radiative forcing contributions from all sources and obtain a total forcing. This is because different forcing terms can interact to either amplify or interfere with each other. For example, in the case of greenhouse gases, two different gases may share the same absorption bands thus partially limiting their effectiveness when taken in combination.

This figure shows the history of atmospheric carbon dioxide concentrations as directly measured at Mauna Loa, Hawaii. This curve is known as the Keeling curve, and is an essential piece of evidence of the man-made increases in greenhouse gases that are believed to be the cause of global warming. The longest such record exists at Mauna Loa, but these measurements have been independently confirmed at many other sites around the world.

The annual fluctuation in carbon dioxide is caused by seasonal variations in carbon dioxide uptake by land plants. Since many more forests are concentrated in the Northern Hemisphere, more carbon dioxide is removed from the atmosphere during Northern Hemisphere summer than Southern Hemisphere summer. This annual cycle is shown in the inset figure by taking the average concentration for each month across all measured years.

The red curve shows the average monthly concentrations, and blue curve is a moving 12 month average.

This picture depicts the last three solar cycles as measured in solar irradiance, sunspot numbers, solar flare activity, and 10.7 cm radio flux. Solar irradiance, i.e the direct solar power at the top of the Earth's atmosphere, is depicted as both a daily measurement and a moving annual average. All other data are depicted as the annual average value.

The ~11 year solar magnetic cycle is a fundemental aspect of the sun's behavior and is associated with variations in total output and activity. Irradiance measurements have only been available during the last three cycles and are based on a composite of many different observing satellites. However, the high correlation between irradiance measurements and other proxies of solar activity make it reasonable to estimate past solar activity. Most important among these proxies is the record of sunspot observations that has been recorded since ~1610. Since sunspots and associated faculae are directly responsible for small changes in the brightness of the sun, they are closely correlated to changes in solar output. Direct measurements of radio emissions from the Sun at 10.7 cm also provide a proxy of solar activity that can be measured from the ground since the Earth's atmosphere is transparent at this wavelength. Lastly, solar flares are a type of solar activity that can impact life on Earth by affecting electrical systems, especially satellites. Flares usually occur in the presence of sunspots, and hence the two are correlated, but flares themselves make only tiny perturbations of the solar luminosity.

Recently, it has been claimed that the total solar irradiance is varying in ways that aren't duplicated by changes in sunspot observations or radio emissions. However, this conclusion is disputed. Some believe that shifts in irradiance may be the result of calibration problems in the measuring satellites.These speculations also admit the possibility that a small long-term trend might exist in solar irradiance, though the data chosen for this plot do not have a significant trend. Also, the differences in flare activity over the three cycles would not be related to possible measurement artifacts in irradiance.

With respect to global warming, though solar activity has been at relatively high levels during the recent period, the fact that solar activity has been near constant during the last 30 years precludes solar variability from playing a large role in recent warming. It is estimated that the resdiual effects of the prolonged high solar activity account for between 18 and 36% of warming from 1950 to 1999.

This image is a comparison of 10 different published reconstructions of mean temperature changes during the last 2000 years. More recent reconstructions are plotted towards the front and in redder colors, older reconstructions appear towards the back and in bluer colors. An instrumental history of temperature is also shown in black. The medieval warm period and little ice age are labeled at roughly the times when they are historically believed to occur, though it is still disputed whether these were truly global or only regional events. The single, unsmoothed annual value for 2004 is also shown for comparison. (Image:Instrumental Temperature Record.png shows how 2004 relates to other recent years).

For the purposes of this comparison, the author is agnostic as to which, if any, of the reconstructions of global mean temperature is an accurate reflection of temperature fluctuations during the last 2000 years. However, since this plot is a fair representation of the range of reconstructions appearing in the published scientific literature, it is likely that such reconstructions, accurate or not, will play a significant role in the ongoing discussions of global climate change and global warming.

For each reconstruction, the raw data has been decadally smoothed with a σ = 5 yr Gaussian weighted moving average. Also, each reconstruction was adjusted so that its mean matched the mean of the instrumental record during the period of overlap. The variance (i.e. the scale of fluctuations) was not adjusted (except in one case noted below).

Except as noted below, all original data for this comparison comes from and links therein. It should also be noted that many reconstructions of past climate report substantial error bars, which are not represented on this figure.

This figure shows the Antarctic temperature changes during the last several glacial/interglacial cycles of the present ice age and a comparison to changes in global ice volume. The present day is on the left.

The first two curves shows local changes in temperature at two sites in Antarctica as derived from deuterium isotopic measurements (δD) on ice cores (EPICA Community Members 2004, Petit et al. 1999). The final plot shows a reconstruction of global ice volume based on δ18O measurements on benthic foraminifera from a composite of globally distributed sediment cores and is scaled to match the scale of fluctuations in Antarctic temperature (Lisiecki and Raymo 2005). Note that changes in global ice volume and changes in Antarctic temperature are highly correlated, so one is a good estimate of the other, but differences in the sediment record do no necessarily reflect differences in paleotemperature. Horizontal lines indicate modern temperatures and ice volume. Differences in the alignment of various features reflect dating uncertainty and do not indicate different timing at different sites.

The Antarctic temperature records indicate that the present interglacial is relatively cool compared to previous interglacials, at least at these sites. The Liesecki & Raymo (2005) sediment reconstruction does not indicate signifcant differences between modern ice volume and previous interglacials, though some other studies do report slightly lower ice volumes / higher sea levels during the 120 ka and 400 ka interglacials (Karner et al. 2001, Hearty and Kaufman 2000).

It should be noted that temperature changes at the typical equatorial site are believed to have been significantly less than the changes observed at high latitude.

Shows climate model predictions for global warming under the SRES A2 emissions scenario relative to global average temperatures in 2000. The A2 scenario is characterized by a politically and socially diverse world that exhibits sustained economic growth but does not address the inequities between rich and poor nations, and takes no special actions to combat global warming or environmental change issues. This world in 2100 is characterized by large population (15 billion), high total energy use, and moderate levels of fossil fuel dependency (mostly coal). The A2 scenario is the most well-studied of the SRES scenarios that assume no attempt to address global warming.

The IPCC predicts global temperature change of 1.4-5.8°C due to global warming from 1990-2100. As evidenced above (a range of 2.5°C in 2100), much of this uncertainty results from disagreement among climate models, though additional uncertainty comes from different emissions scenarios.

This figure shows the average rate of thickness change in mountain glaciers around the world. This information, known as the glaciological mass balance, is found by measuring the annual snow accumulation and subtracting surface ablation driven by melting, sublimation, or wind erosion. These measurements do not account for thinning associated with iceberg calving, flow related thinning, or subglacial erosion. All values are corrected for variations in snow and firn density and expressed in meters of water equivalent (Dyurgerov 2002).

Measurements are shown as both the annual average thickness change and the accumulated change during the fifty years of measurements presented. Years with a net increase in glacier thickness are plotted upwards and in red; years with a net decrease in glacier thickness (i.e. positive thinning) are plotted downward and in blue. Only three years in the last 50 have experienced thickening in the average.

Systematic measurements of glacier thinning began in the 1940s, but fewer than 15 sites had been measured each year until the late 1950s. Since then more than 100 sites have contributed to the average in some years (Dyurgerov 2002, Dyurgerov and Meier 2005). Error bars indicate the standard error in the mean.

Other observations, based on glacier length records, suggest that glacier retreat has occurred nearly continuously since the early 1800s and the end of the little ice age, but variations in rate have occurred, including a significant acceleration during the twentieth century that is believed to have been a response to global warming (Oerlemans 2005) 

Greenhouse Gas Concentration Stabilization Level Scenario Categories. Self-drawn based on Figure in the IPCC Fourth Assessment Report, Working Group III, Summary for Policymakers. The text in the report reads:

"Stabilization scenario categories as reported in Figure (coloured bands) and their relationship to equilibrium global mean temperature change above preindustrial, using (i) “best estimate” climate sensitivity of 3°C (black line in middle of shaded area), (ii) upper bound of likely range of climate sensitivity of 4.5°C (red line at top of shaded area) (iii) lower bound of likely range of climate sensitivity of 2°C (blue line at bottom of shaded area). Coloured shading shows the concentration bands for stabilization of greenhouse gases in the atmosphere corresponding to the stabilization scenario categories I to VI as indicated in Figure. The data are drawn from AR4 WGI, Chapter 10.8. [i.e. from the IPCC Fourth Assessment Report, Working Group I]"

This plot is based on the NASA GISS Surface Temperature Analysis (GISTEMP), which combines the 2001 GISS land station analysis data set (Hansen et al. 2001) with the Rayner/Reynolds oceanic sea surface temperature data set (Rayner 2000, Reynolds et al. 2002).
The data itself was prepared through the GISTEMP online mapping tool, and the specific dataset used is available here. This data was replotted in a Mollweide projection with a continuous and symmetric color scale. The smoothing radius is 1200 km, meaning that the reported temperature may depend on measurement stations located up to 1200 km away, if necessary.

This figure shows the predicted distribution of temperature change due to global warming from Hadley Centre HadCM3 climate model. These changes are based on the IS92a ("business as usual") projections of carbon dioxide and other greenhouse gas emissions during the next century, and essentially assume normal levels of economic growth and no significant steps are taken to combat global greenhouse gas emissions.

The plotted colors show predicted surface temperature changes expressed as the average prediction for 2070-2100 relative to the model's baseline temperatures in 1960-1990. The average change is 3.0°C, placing this model towards the low end of the Intergovernmental Panel on Climate Change's 1.4-5.8°C predicted climate change from 1990 to 2100. As can be expected from their lower specific heat, continents warm more rapidly than the oceans in the model with an average of 4.2°C to 2.5°C respectively. The lowest predicted warming is 0.55°C south of South America, and the highest is 9.2°C in the Arctic Ocean (points exceeding 8°C are plotted as black).

This model is fairly homogeneuous except for strong warming around the Arctic Ocean related to melting sea ice and strong warming in South America related predicted changes in the El Niño cycle. This pattern is not a universal feature of models, as other models can produce large variations in other regions (e.g Africa and India) and less extreme changes in places like South America.

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