The transient response of global-mean precipitation to increasing carbon dioxide levels

The transient response of global-mean precipitation to an increase in atmospheric carbon dioxide levels of 1% yr(-1) is investigated in 13 fully coupled atmosphere-ocean general circulation models (AOGCMs) and compared to a period of stabilization. During the period of stabilization, when carbon dioxide levels are held constant at twice their unperturbed level and the climate left to warm, precipitation increases at a rate of similar to 2.4% per unit of global-mean surface-air-temperature change in the AOGCMs. However, when carbon dioxide levels are increasing, precipitation increases at a smaller rate of similar to 1.5% per unit of global-mean surface-air-temperature change. This difference can be understood by decomposing the precipitation response into an increase from the response to the global surface-temperature increase (and the climate feedbacks it induces), and a fast atmospheric response to the carbon dioxide radiative forcing that acts to decrease precipitation. According to the multi-model mean, stabilizing atmospheric levels of carbon dioxide would lead to a greater rate of precipitation change per unit of global surface-temperature change

The role of the basic state in the ENSO-monsoon relationship and implications for predictability

The impact of systematic model errors on a coupled simulation of the Asian Summer monsoon and its interannual variability is studied. Although the mean monsoon climate is reasonably well captured, systematic errors in the equatorial Pacific mean that the monsoon-ENSO teleconnection is rather poorly represented in the GCM. A system of ocean-surface heat flux adjustments is implemented in the tropical Pacific and Indian Oceans in order to reduce the systematic biases. In this version of the GCM, the monsoon-ENSO teleconnection is better simulated, particularly the lag-lead relationships in which weak monsoons precede the peak of El Nino. In part this is related to changes in the characteristics of El Nino, which has a more realistic evolution in its developing phase. A stronger ENSO amplitude in the new model version also feeds back to further strengthen the teleconnection. These results have important implications for the use of coupled models for seasonal prediction of systems such as the monsoon, and suggest that some form of flux correction may have significant benefits where model systematic error compromises important teleconnections and modes of interannual variability

Role of Perturbing Ocean Initial Condition in Simulated Regional Sea Level Change

Multiple lines of observational evidence indicate that the global climate has been getting warmer since the early 20th century. This warmer climate has led to a global mean sea level rise of about 18 cm during the 20th century, and over 6 cm for the first 15 years of the 21st century. Regionally the sea level rise is not uniform due in large part to internal climate variability. To better serve the community, the uncertainties of predicting/projecting regional sea level changes associated with internal climate variability need to be quantified. Previous research on this topic has used single-model large ensembles with perturbed atmospheric initial conditions (ICs). Here we compare uncertainties associated with perturbing ICs in just the atmosphere and just the ocean using a state-of-the-art coupled climate model. We find that by perturbing the oceanic ICs, the uncertainties in regional sea level changes increase compared to those with perturbed atmospheric ICs. Thus, in order for us to better assess the full spectrum of the impacts of such internal climate variability on regional and global sea level rise, approaches that involve perturbing both atmospheric and oceanic initial conditions are necessary

Time of steady climate change

Under an emission scenario where atmospheric greenhouse gas concentrations are stabilized, previous work suggests that on centennial time scales the rate of global temperature increases would steady at significantly lower rates than those of the 21st century. As climate change is not globally uniform, regional differences in achieving this steady rate of warming can be expected. Here, we define a “Time of Steady Change” (TSC) as the time of reaching this steady rate of warming, and we present a method for estimating TSC with the use of General Circulation Model experiments run under greenhouse gas stabilization scenarios. We find that TSC occurs latest in low latitudes and in the Arctic, despite these areas steadying at very different absolute warming rates. These broad patterns are robust across multiple General Circulation Model ensembles and alternative definitions of TSC. These results indicate large regional differences in the trajectory of climate change in coming centuries

A joint role for forced and internally-driven variability in the decadal modulation of global warming

Despite the observed monotonic increase in greenhouse-gas concentrations, global mean temperature displays important decadal fluctuations typically attributed to both external forcing and internal variability. Here, we provide a robust quantification of the relative contributions of anthropogenic, natural, and internally-driven decadal variability of global mean sea surface temperature (GMSST) by using a unique dataset consisting of 30-member large initial-condition ensembles with five Earth System Models (ESM-LE). We present evidence that a large fraction (~29–53%) of the simulated decadal-scale variance in individual timeseries of GMSST over 1950–2010 is externally forced and largely linked to the representation of volcanic aerosols. Comparison with the future (2010–2070) period suggests that external forcing provides a source of additional decadal-scale variability in the historical period. Given the unpredictable nature of future volcanic aerosol forcing, it is suggested that a large portion of decadal GMSST variability might not be predictable

Multi-model trends in the Sahara induced by increasing CO2

[1] Five of eighteen climate system models participating the Coupled Model Intercomparison Project (CMIP) are chosen here for analysis based on their ability to simulate a reasonable present-day climatology of the Sahara Desert with similar rainfall distributions and meridional boundaries as in the observational data. When CO 2 concentration is increased at one percent per year for 80 years in these models the Sahara moves north, becomes hotter and dries. Compared to the 40-year control run climatology, the mean average northward shift is around 0.55°latitude and the surface temperature is about 1.8°C warmer at year 70 when the CO 2 doubles. The local enhanced greenhouse effect from increased CO 2 increases the net surface sensible heat flux, which in turn contributes to the warming trend

The solar influence on the probability of relatively cold UK winters in the future

Recent research has suggested that relatively cold UK winters are more common when solar activity is low (Lockwood et al 2010 Environ. Res. Lett. 5 024001). Solar activity during the current sunspot minimum has fallen to levels unknown since the start of the 20th century (Lockwood 2010 Proc. R. Soc. A 466 303–29) and records of past solar variations inferred from cosmogenic isotopes (Abreu et al 2008 Geophys. Res. Lett. 35 L20109) and geomagnetic activity data (Lockwood et al 2009 Astrophys. J. 700 937–44) suggest that the current grand solar maximum is coming to an end and hence that solar activity can be expected to continue to decline. Combining cosmogenic isotope data with the long record of temperatures measured in central England, we estimate how solar change could influence the probability in the future of further UK winters that are cold, relative to the hemispheric mean temperature, if all other factors remain constant. Global warming is taken into account only through the detrending using mean hemispheric temperatures. We show that some predictive skill may be obtained by including the solar effect

Warming will affect phytoplankton differently: evidence through a mechanistic approach

Although the consequences of global warming in aquatic ecosystems are only beginning to be revealed, a key to forecasting the impact on aquatic communities is an understanding of individual species' vulnerability to increased temperature. Despite their microscopic size, phytoplankton support about half of the global primary production, drive essential biogeochemical cycles and represent the basis of the aquatic food web. At present, it is known that phytoplankton are important targets and, consequently, harbingers of climate change in aquatic systems. Therefore, investigating the capacity of phytoplankton to adapt to the predicted warming has become a relevant issue. However, considering the polyphyletic complexity of the phytoplankton community, different responses to increased temperature are expected. We experimentally tested the effects of warming on 12 species of phytoplankton isolated from a variety of environments by using a mechanistic approach able to assess evolutionary adaptation (the so-called ratchet technique). We found different degrees of tolerance to temperature rises and an interspecific capacity for genetic adaptation. The thermal resistance level reached by each species is discussed in relation to their respective original habitats. Our study additionally provides evidence on the most resistant phytoplankton groups in a future warming scenario

The upper end of climate model temperature projections is inconsistent with past warming

Climate models predict a large range of possible future temperatures for a particular scenario of future emissions of greenhouse gases and other anthropogenic forcings of climate. Given that further warming in coming decades could threaten increasing risks of climatic disruption, it is important to determine whether model projections are consistent with temperature changes already observed. This can be achieved by quantifying the extent to which increases in well mixed greenhouse gases and changes in other anthropogenic and natural forcings have already altered temperature patterns around the globe. Here, for the first time, we combine multiple climate models into a single synthesized estimate of future warming rates consistent with past temperature changes. We show that the observed evolution of near-surface temperatures appears to indicate lower ranges (5–95%) for warming (0.35–0.82 K and 0.45–0.93 K by the 2020s (2020–9) relative to 1986–2005 under the RCP4.5 and 8.5 scenarios respectively) than the equivalent ranges projected by the CMIP5 climate models (0.48–1.00 K and 0.51–1.16 K respectively). Our results indicate that for each RCP the upper end of the range of CMIP5 climate model projections is inconsistent with past warming