Low Frequency Variability In Globally Integrated Tropical Cyclone Power Dissipation

Surface wind and temperature records from the European Centre for Medium- Range Weather Forecasts 40 Year Reanalysis (ERA-40) Project are used to estimate low-frequency variations in globally integrated tropical cyclone (TC) intensity from 1958 to 2001. For the first time, the annually integrated power dissipation (PD) is explicitly calculated on a global scale, and results show an upward trend in PD during much of the ERA-40 project period, although we argue this is at least partially due to limitations in cyclone representation in ERA-40. Comparing our estimated trend in PD with Emanuel\u27s (2005) approximation to PD reveals good agreement after 1978, coinciding with the onset of a major satellite observing-system epoch in ERA-40. The low pass (\u3e60 months) filtered PD time series correlates with mean annual tropical temperature, thus this result is consistent with the hypothesis that tropical temperatures may directly regulate the integrated intensity of TCs

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

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

Impact of anthropogenic climate change on the East Asian summer monsoon

The East Asian summer monsoon (EASM) is important for bringing rainfall to large areas of China. Historically, variations in the EASM have had major impacts including flooding and drought. We present an analysis of the impact of anthropogenic climate change on EASM rainfall in Eastern China using a newly updated attribution system. Our results suggest that anthropogenic climate change has led to an overall decrease in total monsoon rainfall over the past 65 years, and an increased number of dry days. However the model also predicts that anthropogenic forcings have caused the most extreme heavy rainfall events to become shorter in duration and more intense. With the potential for future changes in aerosol and greenhouse gas emissions, historical trends in monsoon rainfall may not be indicative of future changes, although extreme rainfall is projected to increase over East Asia with continued warming in the region

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

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

A comparative assessment of monthly mean wind speed products over the global ocean

The accurate estimation of marine wind speed is important for climate and air-sea interaction applications. There are many datasets of monthly mean wind speeds available based on either in situ measurements, satellite retrievals, atmospheric reanalysis assimilating both in situ and satellite data and blended datasets combining some or all of these other data sources. 12 different monthly mean wind speed datasets are compared for the period from 1987 to 2009. The results suggest that we cannot presently be confident that the monthly mean wind speed over the ocean is known to the ~0.2 ms-1 accuracy required for the calculation of air-sea heat fluxes. Comparisons are complicated by different representations of wind speed being presented in different datasets. The in situ and reanalysis datasets present stability dependent, earth-relative, wind speeds adjusted to a reference level of 10 m. The satellite and blended datasets present neutral equivalent, surface-relative, speeds adjusted to a reference level of 10 m. Differences between these estimates depend on atmospheric stability and ocean currents and can be greater than the required accuracy target. The adjustment for stability is itself uncertain but it is demonstrated that these uncertainties are likely to be smaller than biases caused when the effects of stability are neglected.Further differences among the datasets are identified. Biases are caused by unidentified rain in Ku-band scatterometer-derived wind speeds and by atmospheric effects on passive microwave wind retrievals. When satellite observations affected by rain are removed a fair-weather bias remains. Some datasets are biased low in coastal regions by the effects of lower wind speeds over land in atmospheric models affecting wind speeds near the coast. All these uncertainties combine to give a wide range of estimates of monthly mean wind speed for the chosen datasets with uncertainty in mean values, spatial patterns and changes over time

Capabilities of Global Ocean Programmes to Inform Climate Services

AbstractClimate services are identified as a means of providing the information that is needed to support decision makers in assessing the impacts of climate change on the oceans. We discuss the current observation programs to support these services, and their capacity to provide the information needed to monitor and address key science questions. An analysis of the current oceanographic observation programs is shown to be undersubscribed from their original plans. There are vulnerabilities in the current observing programs, particularly in relation to satellite measurements. The interaction of climate services with the research community, with policy makers and stakeholders and operational centres is outlined and leads to four recommendations. The key recommendations are for the more pervasisve development of climate services and for a modest increment in the observing program informed by the recommendations of the OceanObs’09 conference

El Niño Dynamics

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