1] We update the Goddard Institute for Space Studies (GISS) analysis of global surface temperature change, compare alternative analyses, and address questions about perception and reality of global warming. Satellite-observed night lights are used to identify measurement stations located in extreme darkness and adjust temperature trends of urban and periurban stations for nonclimatic factors, verifying that urban effects on analyzed global change are small. Because the GISS analysis combines available sea surface temperature records with meteorological station measurements, we test alternative choices for the ocean data, showing that global temperature change is sensitive to estimated temperature change in polar regions where observations are limited. We use simple 12 month (and n × 12) running means to improve the information content in our temperature graphs. Contrary to a popular misconception, the rate of warming has not declined. Global temperature is rising as fast in the past decade as in the prior 2 decades, despite year-to-year fluctuations associated with the El Niño-La Niña cycle of tropical ocean temperature. Record high global 12 month running mean temperature for the period with instrumental data was reached in 2010.

Abstract. We examine the sensitivity of a climate model to a wide range of radiative forcings, including changes of solar irradiance, atmospheric CO2, 03, CFCs, clouds, aerosols, surface •bedo, and a "ghost" forcing introduced at arbitrary heights, latitudes, longitudes, seasons, and times of day. We show that, in general, the climate response, specifically the global mean temperature change, is sensitive to the altitude, latitude, and nature of the forcing; that is, the response to a given forcing can vary by 50% or more depending upon characteristics of the forcing other than its magnitude measured in watts per square meter. The consistency of the response among different forcings is higher, within 20% or better, for most of the globally distributed forcings suspected of influencing global mean temperature in the past century, but exceptions occur for certain changes of ozone or absorbing aerosols, for which the climate response is less well behaved. In •1 cases the physic• basis for the variations of the response can be understood. The principal •nechanisms involve •terations of lapse rate and decrease (increase) of large-sc•e cloud cover in layers that are preferentially heated (cooled). Although the magnitude of these effects must be model-dependent, the existence and sense of the mechanisms appear to be reasonable. Overall, we reaffirm the value of the radiative forcing concept for predicting climate response and for comparative studies of different forcings; indeed, the present results can help improve the accuracy of such an•yses and define error estimates. Our results also emphasize the need for measurexnents having the specificity and precision needed to define poorly known forcings such as absorbing aerosols and ozone change. Available data on aerosol single scatter •bedo ixnply that anthropogenic aerosols cause less cooling than has co•nmonly been asstuned. However, negative forcing due to the net ozone change since 1979 appears to have counterbalanced 30-50% of the positive forcing due to the increase of well-xnixed greenhouse gases in the same period. As the net ozone change includes halogen-driven ozone depletion with negative radiative forcing and a tropospheric ozone increase with positive radiative forcing, it is possible that the h•ogen-driven ozone depletion has counterbalanced more than h•f of the radiative forcing due to wellxnixed greenhouse gases since 1979.

[1] We use a global climate model to compare the effectiveness of many climate forcing agents for producing climate change. We find a substantial range in the ''efficacy'' of different forcings, where the efficacy is the global temperature response per unit forcing relative to the response to CO 2 forcing. Anthropogenic CH 4 has efficacy $110%, which increases to $145% when its indirect effects on stratospheric H 2 O and tropospheric O 3 are included, yielding an effective climate forcing of $0.8 W/m 2 for the period 1750-2000 and making CH 4 the largest anthropogenic climate forcing other than CO 2 . Black carbon (BC) aerosols from biomass burning have a calculated efficacy $58%, while fossil fuel BC has an efficacy $78%. Accounting for forcing efficacies and for indirect effects via snow albedo and cloud changes, we find that fossil fuel soot, defined as BC + OC (organic carbon), has a net positive forcing while biomass burning BC + OC has a negative forcing. We show that replacement of the traditional instantaneous and adjusted forcings, Fi and Fa, with an easily computed alternative, Fs, yields a better predictor of climate change, i.e., its efficacies are closer to unity. Fs is inferred from flux and temperature changes in a fixed-ocean model run. There is remarkable congruence in the spatial distribution of climate change, normalized to the same forcing Fs, for most climate forcing agents, suggesting that the global forcing has more relevance to regional climate change than may have been anticipated. Increasing greenhouse gases intensify the Hadley circulation in our model, increasing rainfall in the Intertropical Convergence Zone (ITCZ), Eastern United States, and East Asia, while intensifying dry conditions in the subtropics including the Southwest United States, the Mediterranean region, the Middle East, and an expanding Sahel. These features survive in model simulations that use all estimated forcings for the period 1880-2000. Responses to localized forcings, such as land use change and heavy regional concentrations of BC aerosols, include more specific regional characteristics. We suggest that anthropogenic tropospheric O 3 and the BC snow albedo effect contribute substantially to rapid warming and sea ice loss in the Arctic. As a complement to a priori forcings, such as Fi, Fa, and Fs, we tabulate the a posteriori effective forcing, Fe, which is the product of the forcing and its efficacy. Fe requires calculation of the climate response and introduces greater model dependence, but once it is calculated for a given amount of a forcing agent it provides a good prediction of the response to other forcing amounts.

Global surface temperature has increased Ϸ0.2°C per decade in the past 30 years, similar to the warming rate predicted in the 1980s in initial global climate model simulations with transient greenhouse gas changes. Warming is larger in the Western Equatorial Pacific than in the Eastern Equatorial Pacific over the past century, and we suggest that the increased West-East temperature gradient may have increased the likelihood of strong El Niños, such as those of 1983 and 1998. Comparison of measured sea surface temperatures in the Western Pacific with paleoclimate data suggests that this critical ocean region, and probably the planet as a whole, is approximately as warm now as at the Holocene maximum and within Ϸ1°C of the maximum temperature of the past million years. We conclude that global warming of more than Ϸ1°C, relative to 2000, will constitute ''dangerous'' climate change as judged from likely effects on sea level and extermination of species.climate change ͉ El Niños ͉ global warming ͉ sea level ͉ species extinctions G lobal temperature is a popular metric for summarizing the state of global climate. Climate effects are felt locally, but the global distribution of climate response to many global climate forcings is reasonably congruent in climate models (1), suggesting that the global metric is surprisingly useful. We will argue further, consistent with earlier discussion (2, 3), that measurements in the Western Pacific and Indian Oceans provide a good indication of global temperature change.We first update our analysis of surface temperature change based on instrumental data and compare observed temperature change with predictions of global climate change made in the 1980s. We then examine current temperature anomalies in the tropical Pacific Ocean and discuss their possible significance. Finally, we compare paleoclimate and recent data, using the Earth's history to estimate the magnitude of global warming that is likely to constitute dangerous human-made climate change. Modern Global Temperature ChangeGlobal surface temperature in more than a century of instrumental data is recorded in the Goddard Institute for Space Studies analysis for 2005. Our analysis, summarized in Fig. 1, uses documented procedures for data over land (4), satellite measurements of sea surface temperature (SST) since 1982 (5), and a ship-based analysis for earlier years (6). Estimated 2 error (95% confidence) in comparing nearby years of global temperature (Fig. 1 A), such as 1998 and 2005, decreases from 0.1°C at the beginning of the 20th century to 0.05°C in recent decades (4). Error sources include incomplete station coverage, quantified by sampling a modelgenerated data set with realistic variability at actual station locations (7), and partly subjective estimates of data quality problems (8). The estimated uncertainty of global mean temperature implies that we can only state that 2005 was probably the warmest year.The map of temperature anomalies for the first half-decade of the 21st century (Fig. 1B), relative to 1951-1980 ...

"Climate dice," describing the chance of unusually warm or cool seasons, have become more and more "loaded" in the past 30 y, coincident with rapid global warming. The distribution of seasonal mean temperature anomalies has shifted toward higher temperatures and the range of anomalies has increased. An important change is the emergence of a category of summertime extremely hot outliers, more than three standard deviations (3σ) warmer than the climatology of the 1951-1980 base period. This hot extreme, which covered much less than 1% of Earth's surface during the base period, now typically covers about 10% of the land area. It follows that we can state, with a high degree of confidence, that extreme anomalies such as those in Texas and Oklahoma in 2011 and Moscow in 2010 were a consequence of global warming because their likelihood in the absence of global warming was exceedingly small. We discuss practical implications of this substantial, growing, climate change.climate impacts | climate anomalies | heat waves T he greatest barrier to public recognition of human-made climate change is probably the natural variability of local climate. How can a person discern long-term climate change, given the notorious variability of local weather and climate from day to day and year to year?This question assumes great practical importance because of the need for the public to appreciate the significance of humanmade global warming. Actions to stem emissions of the gases that cause global warming are unlikely to approach what is needed until the public recognizes that human-made climate change is underway and perceives that it will have unacceptable consequences if effective actions are not taken to slow the climate change. A recent survey in the United States (1) confirms that public opinion about the existence and importance of global warming depends strongly on their perceptions of recent local climate variations. Early public recognition of climate change is critical. Stabilizing climate with conditions resembling those of the Holocene, the world in which civilization developed, can only be achieved if rapid reduction of fossil fuel emissions begins soon (2).It was suggested decades ago (3) that by the early 21st century the informed public should be able to recognize that the frequency of unusually warm seasons had increased, because the "climate dice," describing the probability of unusually warm or unusually cool seasons, would be sufficiently loaded (biased) as to be discernible to the public. Recent high profile heat waves, such as the one in Texas and Oklahoma in the summer of 2011, raise the question of whether these extreme events are related to the on-going global warming trend, which has been attributed with a high degree of confidence to human-made greenhouse gases (4).Summer, when most biological productivity occurs, is probably the season when climate change will have its biggest impact on humanity. Global warming causes spring warmth to come earlier and cooler conditions that initiate fall to be delayed. Thu...

We study climate sensitivity and feedback processes in three independent ways: (1) by using a three dimensional (3-D) global climate model for experiments in which solar irradiance S o is increased 2 percent or CO 2 is doubled, (2) by using the CLIMAP climate boundary conditions to analyze the contributions of different physical processes to the cooling of the last ice age (18K years ago), and (3) by using estimated changes in global temperature and the abundance of atmospheric greenhouse gases to deduce an empirical climate sensitivity for the period 1850-1980. Our 3-D global climate model yields a warming of ~4°C for either a 2 percent increase of S o or doubled CO 2. This indicates a net feedback factor of f = 3-4, because either of these forcings would cause the earth's surface temperature to warm 1.2-1.3°C to restore radiative balance with space, if other factors remained unchanged. Principal positive feedback processes in the model are changes in atmospheric water vapor, clouds and snow/ice cover. Feedback factors calculated for these processes, with atmospheric dynamical feedbacks implicitly incorporated, are respectively f water vapor ~ 1.6, f clouds ~ 1.3 and f snow/ice ~ 1.1, with the latter mainly caused by sea ice changes. A number of potential feedbacks, such as land ice cover, vegetation cover and ocean heat transport were held fixed in these experiments. We calculate land ice, sea ice and vegetation feedbacks for the 18K climate to be f land ice ~ 1.2-1.3, f sea ice ~ 1.2, and f vegetation ~ 1.05-1.1 from their effect on the radiation budget at the top of the atmosphere. This sea ice feedback at 18K is consistent with the smaller f snow/ice ~ 1.1 in the S o and CO 2 experiments, which applied to a warmer earth with less sea ice. We also obtain an empirical estimate of f = 2-4 for the fast feedback processes (water vapor, clouds, sea ice) operating on 10-100 year time scales by comparing the cooling due to slow or specified changes (land ice, CO 2 , vegetation) to the total cooling at 18K. The temperature increase believed to have occurred in the past 130 years (approximately 0.5°C) is also found to imply a climate sensitivity of 2.5-5°C for doubled CO 2 (f = 2-4), if (1) the temperature increase is due to the added greenhouse gases, (2) the 1850 CO 2 abundance was 270 ± 10 ppm, and (3) the heat perturbation is mixed like a passive tracer in the ocean with vertical mixing coefficient k ~ 1 cm 2 s −1. These analyses indicate that f is substantially greater than unity on all time scales. Our best estimate for the current climate due to processes operating on the 10-100 year time scale is f = 2-4, corresponding to a climate sensitivity of 2.5-5°C for doubled CO 2. The physical process contributing the greatest uncertainty to f on this time scale appears to be the cloud feedback.

Our climate model, driven mainly by increasing human-made greenhouse gases and aerosols, among other forcings, calculates that Earth is now absorbing 0.85 +/- 0.15 watts per square meter more energy from the Sun than it is emitting to space. This imbalance is confirmed by precise measurements of increasing ocean heat content over the past 10 years. Implications include (i) the expectation of additional global warming of about 0.6 degrees C without further change of atmospheric composition; (ii) the confirmation of the climate system's lag in responding to forcings, implying the need for anticipatory actions to avoid any specified level of climate change; and (iii) the likelihood of acceleration of ice sheet disintegration and sea level rise.

A full description of the ModelE version of the Goddard Institute for Space Studies (GISS) atmospheric general circulation model (GCM) and results are presented for present-day climate simulations (ca. 1979). This version is a complete rewrite of previous models incorporating numerous improvements in basic physics, the stratospheric circulation, and forcing fields. Notable changes include the following: the model top is now above the stratopause, the number of vertical layers has increased, a new cloud microphysical scheme is used, vegetation biophysics now incorporates a sensitivity to humidity, atmospheric turbulence is calculated over the whole column, and new land snow and lake schemes are introduced. The performance of the model using three configurations with different horizontal and vertical resolutions is compared to quality-controlled in situ data, remotely sensed and reanalysis products. Overall, significant improvements over previous models are seen, particularly in upper-atmosphere temperatures and winds, cloud heights, precipitation, and sea level pressure. Data-model comparisons continue, however, to highlight persistent problems in the marine stratocumulus regions.