Attribution of climate extreme events

There is a tremendous desire to attribute causes to weather and climate events that is often challenging from a physical standpoint. Headlines attributing an event solely to either human-induced climate change or natural variability can be misleading when both are invariably in play. The conventional attribution framework struggles with dynamically driven extremes because of the small signal-to-noise ratios and often uncertain nature of the forced changes. Here, we suggest that a different framing is desirable, which asks why such extremes unfold the way they do. Specifically, we suggest that it is more useful to regard the extreme circulation regime or weather event as being largely unaffected by climate change, and question whether known changes in the climate system's thermodynamic state affected the impact of the particular event. Some examples briefly illustrated include 'snowmaggedon' in February 2010, superstorm Sandy in October 2012 and supertyphoon Haiyan in November 2013, and, in more detail, the Boulder floods of September 2013, all of which were influenced by high sea surface temperatures that had a discernible human component.

What does global mean temperature tell us about local climate?

The subject of climate feedbacks focuses attention on global mean surface air temperature (GMST) as the key metric of climate change. But what does knowledge of past and future GMST tell us about the climate of specific regions? In the context of the ongoing UNFCCC process, this is an important question for policy-makers as well as for scientists. The answer depends on many factors, including the mechanisms causing changes, the timescale of the changes, and the variables and regions of interest. This paper provides a review and analysis of the relationship between changes in GMST and changes in local climate, first in observational records and then in a range of climate model simulations, which are used to interpret the observations. The focus is on decadal timescales, which are of particular interest in relation to recent and near-future anthropogenic climate change. It is shown that GMST primarily provides information about forced responses, but that understanding and quantifying internal variability is essential to projecting climate and climate impacts on regional-to-local scales. The relationship between local forced responses and GMST is often linear but may be nonlinear, and can be greatly complicated by competition between different forcing factors. Climate projections are limited not only by uncertainties in the signal of climate change but also by uncertainties in the characteristics of real-world internal variability. Finally, it is shown that the relationship between GMST and local climate provides a simple approach to climate change detection, and a useful guide to attribution studies.

Irreducible uncertainty in near-term climate projections

Model simulations of the next few decades are widely used in assessments of climate change impacts and as guidance for adaptation. Their non-linear nature reveals a level of irreducible uncertainty which it is important to understand and quantify, especially for projections of near-term regional climate. Here we use large idealised initial condition ensembles of the FAMOUS global climate model with a 1 %/year compound increase in CO2 levels to quantify the range of future temperatures in model-based projections. These simulations explore the role of both atmospheric and oceanic initial conditions and are the largest such ensembles to date. Short-term simulated trends in global temperature are diverse, and cooling periods are more likely to be followed by larger warming rates. The spatial pattern of near-term temperature change varies considerably, but the proportion of the surface showing a warming is more consistent. In addition, ensemble spread in inter-annual temperature declines as the climate warms, especially in the North Atlantic. Over Europe, atmospheric initial condition uncertainty can, for certain ocean initial conditions, lead to 20 year trends in winter and summer in which every location can exhibit either strong cooling or rapid warming. However, the details of the distribution are highly sensitive to the ocean initial condition chosen and particularly the state of the Atlantic meridional overturning circulation. On longer timescales, the warming signal becomes more clear and consistent amongst different initial condition ensembles. An ensemble using a range of different oceanic initial conditions produces a larger spread in temperature trends than ensembles using a single ocean initial condition for all lead times. This highlights the potential benefits from initialising climate predictions from ocean states informed by observations. These results suggest that climate projections need to be performed with many more ensemble members than at present, using a range of ocean initial conditions, if the uncertainty in near-term regional climate is to be adequately quantified.

A global empirical system for probabilistic seasonal climate prediction

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961–2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño–Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

Revisiting trends in wetness and dryness in the presence of internal climate variability and water limitations over land

A theoretically expected consequence of the intensification of the hydrological cycle under global warming is that on average, wet regions get wetter and dry regions get drier (WWDD). Recent studies, however, have found significant discrepancies between the expected pattern of change and observed changes over land. We assess the WWDD theory in four climate models. We find that the reported discrepancy can be traced to two main issues: (1) unforced internal climate variability strongly affects local wetness and dryness trends and can obscure underlying agreement with WWDD, and (2) dry land regions are not constrained to become drier by enhanced moisture divergence since evaporation cannot exceed precipitation over multiannual time scales. Over land, where the available water does not limit evaporation, a “wet gets wetter” signal predominates. On seasonal time scales, where evaporation can exceed precipitation, trends in wet season becoming wetter and dry season becoming drier are also found.

Advancements in decadal climate predictability: the role of nonoceanic drivers

We review recent progress in understanding the role of sea ice, land surface, stratosphere, and aerosols in decadal-scale predictability and discuss the perspectives for improving the predictive capabilities of current Earth system models (ESMs). These constituents have received relatively little attention because their contribution to the slow climatic manifold is controversial in comparison to that of the large heat capacity of the oceans. Furthermore, their initialization as well as their representation in state-of-the-art climate models remains a challenge. Numerous extraoceanic processes that could be active over the decadal range are proposed. Potential predictability associated with the aforementioned, poorly represented, and scarcely observed constituents of the climate system has been primarily inspected through numerical simulations performed under idealized experimental settings. The impact, however, on practical decadal predictions, conducted with realistically initialized full-fledged climate models, is still largely unexploited. Enhancing initial-value predictability through an improved model initialization appears to be a viable option for land surface, sea ice, and, marginally, the stratosphere. Similarly, capturing future aerosol emission storylines might lead to an improved representation of both global and regional short-term climatic changes. In addition to these factors, a key role on the overall predictive ability of ESMs is expected to be played by an accurate representation of processes associated with specific components of the climate system. These act as “signal carriers,” transferring across the climatic phase space the information associated with the initial state and boundary forcings, and dynamically bridging different (otherwise unconnected) subsystems. Through this mechanism, Earth system components trigger low-frequency variability modes, thus extending the predictability beyond the seasonal scale.

Understanding climate change projections for precipitation over western Europe with a weather typing approach

Precipitation over western Europe (WE) is projected to increase (decrease) roughly northward (equatorward) of 50°N during the 21st century. These changes are generally attributed to alterations in the regional large-scale circulation, e.g., jet stream, cyclone activity, and blocking frequencies. A novel weather typing within the sector (30°W–10°E, 25–70°N) is used for a more comprehensive dynamical interpretation of precipitation changes. A k-means clustering on daily mean sea level pressure was undertaken for ERA-Interim reanalysis (1979–2014). Eight weather types are identified: S1, S2, S3 (summertime types), W1, W2, W3 (wintertime types), B1, and B2 (blocking-like types). Their distinctive dynamical characteristics allow identifying the main large-scale precipitation-driving mechanisms. Simulations with 22 Coupled Model Intercomparison Project 5 models for recent climate conditions show biases in reproducing the observed seasonality of weather types. In particular, an overestimation of weather type frequencies associated with zonal airflow is identified. Considering projections following the (Representative Concentration Pathways) RCP8.5 scenario over 2071–2100, the frequencies of the three driest types (S1, B2, and W3) are projected to increase (mainly S1, +4%) in detriment of the rainiest types, particularly W1 (−3%). These changes explain most of the precipitation projections over WE. However, a weather type-independent background signal is identified (increase/decrease in precipitation over northern/southern WE), suggesting modifications in precipitation-generating processes and/or model inability to accurately simulate these processes. Despite these caveats in the precipitation scenarios for WE, which must be duly taken into account, our approach permits a better understanding of the projected trends for precipitation over WE.

Are Reanalysis Data Useful for Calculating Climate Indices over South America?

Precipitation and temperature climate indices are calculated using the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and validated against observational data from some stations over Brazil and other data sources. The spatial patterns of the climate indices trends are analyzed for the period 1961-1990 over South America. In addition, the correlation and linear regression coefficients for some specific stations were also obtained in order to compare with the reanalysis data. In general, the results suggest that NCEP/NCAR reanalysis can provide useful information about minimum temperature and consecutive dry days indices at individual grid cells in Brazil. However, some regional differences in the climate indices trends are observed when different data sets are compared. For instance, the NCEP/NCAR reanalysis shows a reversal signal for all rainfall annual indices and the cold night index over Argentina. Despite these differences, maps of the trends for most of the annual climate indices obtained from the NCEP/NCAR reanalysis and BRANT analysis are generally in good agreement with other available data sources and previous findings in the literature for large areas of southern South America. The pattern of trends for the precipitation annual indices over the 30 years analyzed indicates a change to wetter conditions over southern and southeastern parts of Brazil, Paraguay, Uruguay, central and northern Argentina, and parts of Chile and a decrease over southwestern South America. All over South America, the climate indices related to the minimum temperature (warm or cold nights) have clearly shown a warming tendency; however, no consistent changes in maximum temperature extremes (warm and cold days) have been observed. Therefore, one must be careful before suggesting an), trends for warm or cold days.

Rock magnetism in soils of the Pampean plain. Buenos Aires province, Argentina. Linking climate and magnetic behaviour

Results of the study of Argiudolls in two localities (Zarate and Veronica) of the Pampean plain, Argentina, are presented in this contribution. This is a typical area covered by loess. The magnetic studies carried out allowed to determine the presence of detrital magnetite and titanomagnetite, as well as maghemite, pedogenic goethite and superparamagnetic particles (SP). In Veronica soils, a depletion of ferromagnetic minerals is recorded The dominant process in these soils has been the reductive loss of detrital magnetite and titanomagnetite. This is associated with a greater degree of evolution of the soil, which is determined by the concentration and type of detected clays. The higher clay concentration in these soils facilitated reducing conditions and a greater loss of detrital magnetic particles. The loss is reinforced under poor drainage conditions. In the poorly drained soil of Zarate, a concentration of magnetic particles is observed in the Bt horizon, which is associated with an illuviation process. The well drained soil of the same locality shows neoformation of SP particles. These particles would have an ephemeral life until a new wet period in the annual cycle occurs. Although some characteristics of the magnetic signal appear reinforced by the conditions of drainage, this aspect does not seem to be too significant, at least in the Pampean region with low topographic gradients.

Related changes in biodiversity, insolation and climate in the Atlantic rainforest since the last interglacial

The long-term Colonia record is located in the Atlantic rainforest domain in Brazil (23 degrees 52`S 46 degrees 42`20 `` W 900 m a.s.l.). The 780 cm long core CO3 provides a coverage of a complete interglacial/glacial cycle for the first time in a neotropical rainforest. Information on the behavior of tropical climates compared to global changes in temperatures indicates specific climate responses in terms of precipitation at these latitudes. Winter extratropical circulation was very active during the last interglacial and most of the glacial. Floristic composition of the rainforest changed several times in each phase of expansion, twice during the interglacial, and three times during glacial episodes. Araucaria was well developed in the area of Sao Paulo until the beginning of the first dry phase of the glacial at ca. 50,000 yr B.P. Changes in insolation controlled the expansion of the rainforest and the tropical hydrological cycle as evidenced by a strong precession signal. However precession had no impact on regional climatic features. The two interglacials (MIS 5e and Holocene) showed completely different patterns attesting to the continuous evolution of the forest. The biodiversity index (Shannon-Wiener Index) remained high during both the interglacial and glacial attesting to the permanence of small patches of rainforest refugia during drier phases. The lowest Shannon-Wiener Indexes were recorded between 23,000 and 12,000 yr B.P. and 40,000 and 30,000 yr B.P. and characterize two marked phases of stress for the rainforest. (C) 2008 Elsevier B.V. All rights reserved.

Homogeneity assessment of a station climate series (1933-2005) in the Metropolitan Area of São Paulo: instruments change and urbanization effects

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Homogeneity assessment of a station climate series (1933-2005) in the Metropolitan Area of Sao Paulo: instruments change and urbanization effects

This work assessed homogeneity of the Institute of Astronomy, Geophysics and Atmospheric Sciences (IAG) weather station climate series, using various statistical techniques. The record from this target station is one of the longest in Brazil, having commenced in 1933 with observations of precipitation, and temperatures and other variables later in 1936. Thus, it is one of the few stations in Brazil with enough data for long-term climate variability and climate change studies. There is, however, a possibility that its data may have been contaminated by some artifacts over time. Admittedly, there was an intervention on the observations in 1958, with the replacement of instruments, for which the size of impact has not been yet evaluated. The station transformed in the course of time from rural to urban, and this may also have influenced homogeneity of the observations and makes the station less representative for climate studies over larger spatial scales. Homogeneity of the target station was assessed applying both absolute, or single station tests, and tests relatively to regional climate, in annual scale, regarding daily precipitation, relative humidity, maximum (TMax), minimum (TMin), and wet bulb temperatures. Among these quantities, only precipitation does not exhibit any inhomogeneity. A clear signal of change of instruments in 1958 was detected in the TMax and relative humidity data, the latter certainly because of its strong dependence on temperature. This signal is not very clear in TMin, but it presents non-climatic discontinuities around 1953 and around 1970. A significant homogeneity break is found around 1990 for TMax and wet bulb temperature. The discontinuities detected after 1958 may have been caused by urbanization, as the observed warming trend in the station is considerably greater than that corresponding to regional climate.

Solar-Terrestrial Signal Record in Tree Ring Width Time Series from Brazil

This work investigates the behavior of the sunspot number and Southern Oscillation Index (SOI) signal recorded in the tree ring time series for three different locations in Brazil: Humaita in Amaznia State, Porto Ferreira in So Paulo State, and Passo Fundo in Rio Grande do Sul State, using wavelet and cross-wavelet analysis techniques. The wavelet spectra of tree ring time series showed signs of 11 and 22 years, possibly related to the solar activity, and periods of 2-8 years, possibly related to El Nio events. The cross-wavelet spectra for all tree ring time series from Brazil present a significant response to the 11-year solar cycle in the time interval between 1921 to after 1981. These tree ring time series still have a response to the second harmonic of the solar cycle (5.5 years), but in different time intervals. The cross-wavelet maps also showed that the relationship between the SOI x tree ring time series is more intense, for oscillation in the range of 4-8 years.

Influence of climate changes on cross allergies: possible involvement of pollen transglutaminase

Allergies are a complex of symptoms derived from altered IgE-mediated reactions of the immune system towards substances known as allergens. Allergic sensibilization can be of food or respiratory origin and, in particular, apple and hazelnut allergens have been identified in pollens or fruits. Allergic cross-reactivity can occur in a patient reacting to similar allergens from different origins, justifying the research in both systems as in Europe a greater number of people suffers from apple fruit allergy, but little evidence exists about pollen. Apple fruit allergies are due to four different classes of allergens (Mal d 1, 2, 3, 4), whose allergenicity is related both to genotype and tissue specificity; therefore I have investigated their presence also in pollen at different time of germination to clarify the apple pollen allergenic potential. I have observed that the same four classes of allergens found in fruit are expressed at different levels also in pollen, and their presence might support that the apple pollen can be considered allergenic as the fruit, deducing that apple allergy could also be indirectly caused by sensitization to pollen. Climate changes resulting from increases in temperature and air pollution influence pollen allergenicity, responsible for the dramatic raise in respiratory allergies (hay fever, bronchial asthma, conjunctivitis). Although the link between climate change and pollen allergenicity is proven, the underlying mechanism is little understood. Transglutaminases (TGases), a class of enzymes able to post-translationally modify proteins, are activated under stress and involved in some inflammatory responses, enhancing the activity of pro-inflammatory phospholipase A2, suggesting a role in allergies. Recently, a calcium-dependent TGase activity has been identified in the pollen cell wall, raising the possibility that pollen TGase may have a role in the modification of pollen allergens reported above, thus stabilizing them against proteases. This enzyme can be involved also in the transamidation of proteins present in the human mucosa interacting with surface pollen or, finally, the enzyme itself can represent an allergen, as suggested by studies on celiac desease. I have hypothesized that this pollen enzyme can be affected by climate changes and be involved in exhacerbating allergy response. The data presented in this thesis represent a scientific basis for future development of studies devoted to verify the hypothesis set out here. First, I have demonstrated the presence of an extracellular TGase on the surface of the grain observed either at the apical or the proximal parts of the pollen-tube by laser confocal microscopy (Iorio et al., 2008), that plays an essential role in apple pollen-tube growth, as suggested by the arrest of tube elongation by TGase inhibitors, such as EGTA or R281. Its involvement in pollen tube growth is mainly confirmed by the data of activity and gene expression, because TGase showed a peak between 15 min and 30 min of germination, when this process is well established, and an optimal pH around 6.5, which is close to that recorded for the germination medium. Moreover, data show that pollen TGase can be a glycoprotein as the glycosylation profile is linked both with the activation of the enzyme and with its localization at the pollen cell wall during germination, because from the data presented seems that the active form of TGase involved in pollen tube growth and pollen-stylar interaction is more exposed and more weakly bound to the cell wall. Interestingly, TGase interacts with fibronectin (FN), a putative SAMs or psECM component, inducing possibly intracellular signal transduction during the interaction between pollen-stylar occuring in the germination process, since a protein immunorecognised by anti-FN antibody is also present in pollen, in particular at the level of pollen grain cell wall in a punctuate pattern, but also along the shank of the pollen tube wall, in a similar pattern that recalls the signal obtained with the antibody anti TGase. FN represents a good substrate for the enzyme activity, better than DMC usually used as standard substrate for animal TGase. Thus, this pollen enzyme, necessary for its germination, is exposed on the pollen surface and consequently can easily interact with mucosal proteins, as it has been found germinated pollen in studies conducted on human mucus (Forlani, personal communication). I have obtained data that TGase activity increases in a very remarkable way when pollen is exposed to stressful conditions, such as climate changes and environmental pollution. I have used two different species of pollen, an aero allergenic (hazelnut, Corylus avellana) pollen, whose allergenicity is well documented, and an enthomophylus (apple, Malus domestica) pollen, which is not yet well characterized, to compare data on their mechanism of action in response to stressors. The two pollens have been exposed to climate changes (different temperatures, relative humidity (rH), acid rain at pH 5.6 and copper pollution (3.10 µg/l)) and showed an increase in pollen surface TGase activity that is not accompanied to an induced expression of TGase immunoreactive protein with AtPNG1p. Probably, climate change induce an alteration or damage to pollen cell wall that carries the pollen grains to release their content in the medium including TGase enzyme, that can be free to carry out its function as confirmed by the immunolocalisation and by the in situ TGase activity assay data; morphological examination indicated pollen damage, viability significantly reduced and in acid rain conditions an early germination of apple pollen, thus possibly enhancing the TGase exposure on pollen surface. Several pollen proteins were post-translationally modified, as well as mammalian sPLA2 especially with Corylus pollen, which results in its activation, potentially altering pollen allergenicity and inflammation. Pollen TGase activity mimicked the behaviour of gpl TGase and AtPNG1p in the stimulation of sPLA2, even if the regulatory mechanism seems different to gpl TGase, because pollen TGase favours an intermolecular cross-linking between various molecules of sPLA2, giving rise to high-molecular protein networks normally more stable. In general, pollens exhibited a significant endogenous phospholipase activity and it has been observed differences according to the allergenic (Corylus) or not-well characterized allergenic (Malus) attitude of the pollen. However, even if with a different intensity level in activation, pollen enzyme share the ability to activate the sPLA2, thus suggesting an important regulatory role for the activation of a key enzyme of the inflammatory response, among which my interest was addressed to pollen allergy. In conclusion, from all the data presented, mainly presence of allergens, presence of an extracellular TGase, increasing in its activity following exposure to environmental pollution and PLA2 activation, I can conclude that also Malus pollen can behave as potentially allergenic. The mechanisms described here that could affect the allergenicity of pollen, maybe could be the same occurring in fruit, paving the way for future studies in the identification of hyper- and hypo- allergenic cultivars, in preventing environmental stressor effects and, possibly, in the production of transgenic plants.

Sea-Level climate variability in the Mediterranean Sea

Sea-level variability is characterized by multiple interacting factors described in the Fourth Assessment Report (Bindoff et al., 2007) of the Intergovernmental Panel on Climate Change (IPCC) that act over wide spectra of temporal and spatial scales. In Church et al. (2010) sea-level variability and changes are defined as manifestations of climate variability and change. The European Environmental Agency (EEA) defines sea level as one of most important indicators for monitoring climate change, as it integrates the response of different components of the Earths system and is also affected by anthropogenic contributions (EEA, 2011). The balance between the different sea-level contributions represents an important source of uncertainty, involving stochastic processes that are very difficult to describe and understand in detail, to the point that they are defined as an enigma in Munk (2002). Sea-level rate estimates are affected by all these uncertainties, in particular if we look at possible responses to sea-level contributions to future climate. At the regional scale, lateral fluxes also contribute to sea-level variability, adding complexity to sea-level dynamics. The research strategy adopted in this work to approach such an interesting and challenging topic has been to develop an objective methodology to study sea-level variability at different temporal and spatial scales, applicable in each part of the Mediterranean basin in particular, and in the global ocean in general, using all the best calibrated sources of data (for the Mediterranean): in-situ, remote-sensig and numerical models data. The global objective of this work was to achieve a deep understanding of all of the components of the sea-level signal contributing to sea-level variability, tendency and trend and to quantify them.