Contrasting trends of mass and optical properties of aerosols over the Northern Hemisphere from 1992 to 2011

Atmospheric aerosols affect both human health and climate. PMX is the mass concentration of aerosol particles that have aerodynamic diameters less than X μm, PM<sub>10</sub> was initially selected to measure the environmental impact of aerosols. Recently, it was realized that fine particles are more hazardous than larger ones and should be measured. Consequently, observational data for PM<sub>2.5</sub> have been obtained but only for a much shorter period than that of PM<sub>10</sub>. Optical extinction of aerosols, the inverse of meteorological visibility, is sensitive to particles less than 1.0 μm. These fine particles only account for a small part of total mass of aerosols although they are very efficient in light extinction. Comparisons are made between PM<sub>10</sub> and PM<sub>2.5</sub> over the period when the latter is available and with visibility data for a longer period. PM<sub>10</sub> has decreased by 44% in Europe from 1992 to 2009, 33% in the US from 1993 to 2010, 10% in Canada from 1994 to 2009, and 26% in China from 2000 to 2011. However, in contrast, aerosol optical extinction has increased 7% in the US, 10% in Canada, and 18% in China during the above study periods. The reduction of optical extinction over Europe of 5% is also much less than the 44% reduction in PM<sub>10</sub>. Over its short period of record PM<sub>2.5</sub> decreased less than PM<sub>10</sub>. Hence, PM<sub>10</sub> is neither a good measure of changes in smaller particles nor of their long-term trends, a result that has important implications for both climate impact and human health effects. The increased fraction of anthropogenic aerosol emission, such as from vehicle exhaust, to total atmospheric aerosols partly explains this contrasting trend of optical and mass properties of aerosols

Considering long-memory when testing for changepoints in surface temperature:a classification approach based on the time-varying spectrum

Changepoint models are increasingly used to represent changes in the rate of warming in surface temperature records. On the opposite hand, a large body of literature has suggested long‐memory processes to characterize long‐term behavior in surface temperatures. While these two model representations provide different insights into the underlying mechanisms, they share similar spectrum properties that create “ambiguity” and challenge distinguishing between the two classes of models. This study aims to compare the two representations to explain temporal changes and variability in surface temperatures. To address this question, we extend a recently developed time‐varying spectral procedure and assess its accuracy through a synthetic series mimicking observed global monthly surface temperatures. We vary the length of the synthetic series to determine the number of observations needed to be able to accurately distinguish between changepoints and long‐memory models. We apply the approach to two gridded surface temperature data sets. Our findings unveil regions in the oceans where long‐memory is prevalent. These results imply that the presence of long‐memory in monthly sea surface temperatures may impact the significance of trends, and special attention should be given to the choice of model representing memory (short versus long) when assessing long‐term changes

Different atmospheric moisture divergence responses to extreme and moderate El Niños

On seasonal and inter-annual time scales, vertically integrated moisture divergence provides a useful measure of the tropical atmospheric hydrological cycle. It reflects the combined dynamical and thermodynamical effects, and is not subject to the limitations that afflict observations of evaporation minus precipitation. An empirical orthogonal function (EOF) analysis of the tropical Pacific moisture divergence fields calculated from the ERA-Interim reanalysis reveals the dominant effects of the El Niño-Southern Oscillation (ENSO) on inter-annual time scales. Two EOFs are necessary to capture the ENSO signature, and regression relationships between their Principal Components and indices of equatorial Pacific sea surface temperature (SST) demonstrate that the transition from strong La Niña through to extreme El Niño events is not a linear one. The largest deviation from linearity is for the strongest El Niños, and we interpret that this arises at least partly because the EOF analysis cannot easily separate different patterns of responses that are not orthogonal to each other. To overcome the orthogonality constraints, a self-organizing map (SOM) analysis of the same moisture divergence fields was performed. The SOM analysis captures the range of responses to ENSO, including the distinction between the moderate and strong El Niños identified by the EOF analysis. The work demonstrates the potential for the application of SOM to large scale climatic analysis, by virtue of its easier interpretation, relaxation of orthogonality constraints and its versatility for serving as an alternative classification method. Both the EOF and SOM analyses suggest a classification of “moderate” and “extreme” El Niños by their differences in the magnitudes of the hydrological cycle responses, spatial patterns and evolutionary paths. Classification from the moisture divergence point of view shows consistency with results based on other physical variables such as SST

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

Observed and simulated full-depth ocean heat-content changes for 1970–2005

Greenhouse-gas emissions have created a planetary energy imbalance that is primarily manifested by increasing ocean heat content (OHC). Updated observational estimates of full-depth OHC change since 1970 are presented that account for recent advancements in reducing observation errors and biases. The full-depth OHC has increased by 0.74 [0.68, 0.80]  ×  1022 J yr−1 (0.46 Wm−2) and 1.22 [1.16–1.29]  ×  1022 J yr−1 (0.75 Wm−2) for 1970–2005 and 1992–2005, respectively, with a 5 to 95 % confidence interval of the median. The CMIP5 models show large spread in OHC changes, suggesting that some models are not state-of-the-art and require further improvements. However, the ensemble median has excellent agreement with our observational estimate: 0.68 [0.54–0.82]  ×  1022 J yr−1 (0.42 Wm−2) from 1970 to 2005 and 1.25 [1.10–1.41]  ×  1022 J yr−1 (0.77 Wm−2) from 1992 to 2005. These results increase confidence in both the observational and model estimates to quantify and study changes in Earth's energy imbalance over the historical period. We suggest that OHC be a fundamental metric for climate model validation and evaluation, especially for forced changes (decadal timescales)

El Niño Dynamics

Bringer of storms and droughts, the El Niño∕Southern Oscillation results from the complex, sometimes chaotic interplay of ocean and atmosphere

El Niño Dynamics

Bringer of storms and droughts, the El Niño∕Southern Oscillation results from the complex, sometimes chaotic interplay of ocean and atmosphere

Rossby wave dynamics of the North Pacific extra-tropical response to El Niño: importance of the basic state in coupled GCMs

The extra-tropical response to El Nino in a "low" horizontal resolution coupled climate model, typical of the Intergovernmental Panel on Climate Change fourth assessment report simulations, is shown to have serious systematic errors. A high resolution configuration of the same model has a much improved response that is similar to observations. The errors in the low resolution model are traced to an incorrect representation of the atmospheric teleconnection mechanism that controls the extra-tropical sea surface temperatures (SSTs) during El Nino. This is due to an unrealistic atmospheric mean state, which changes the propagation characteristics of Rossby waves. These erroneous upper tropospheric circulation anomalies then induce erroneous surface circulation features over the North Pacific. The associated surface wind speed and direction errors create erroneous surface flux and upwelling anomalies which finally lead to the incorrect extra-tropical SST response to El Nino in the low resolution model. This highlights the sensitivity of the climate response to a single link in a chain of complex climatic processes. The correct representation of these processes in the high resolution model indicates the importance of horizontal resolution in resolving such processes

The Reliability of Global and Hemispheric Surface Temperature Records

The purpose of this review article is to discuss the development and associated estimation of uncertainties in the global and hemispheric surface temperature records. The review begins by detailing the groups that produce surface temperature datasets. After discussing the reasons for similarities and differences between the various products, the main issues that must be addressed when deriving accurate estimates, particularly for hemispheric and global averages, are then considered. These issues are discussed in the order of their importance for temperature records at these spatial scales: biases in SST data, particularly before the 1940s; the exposure of land-based thermometers before the development of louvred screens in the late 19th century; and urbanization effects in some regions in recent decades. The homogeneity of land-based records is also discussed; however, at these large scales it is relatively unimportant. The article concludes by illustrating hemispheric and global temperature records from the four groups that produce series in near-real time