An analysis of the risk of cocoa moniliasis occurrence in Brazil as the result of climate change

The aim of this study was to evaluate the potential risk of moniliasis occurrence and the impacts of climate change on this disease in the coming decades, should this pathogen be introduced in Brazil. To this end, climate favorability maps were devised for the occurrence of moniliasis, both for the present and future time. The future scenarios (A2 and B2) focused on the decades of 2020, 2050 and 2080. These scenarios were obtained from six global climate models (GCMs) made available by the third assessment report of Intergovernmental Panel on Climate Change (IPCC). Currently, there are large areas with favorable climate conditions for moniliasis in Brazil, especially in regions at high risk of introduction of that pathogen. Considering the global warming scenarios provided by the IPCC, the potential risk of moniliasis occurrence in Brazil will be reduced. This decrease is predicted for both future scenarios, but will occur more sharply in scenario A2. However, there will still be areas with favorable climate conditions for the development of the disease, particularly in Brazil's main producing regions. Moreover, pathogen and host alike may undergo alterations due to climate change, which will affect the extent of their impacts on this pathosystem.

Effects of global climate changes on geographical distribution patterns of economically important plant species in cerrado

Different climate models, modeling methods and carbon emission scenarios were used in this paper to evaluate the effects of future climate changes on geographical distribution of species of economic and cultural importance across the Cerrado biome. As the results of several studies have shown, there are still many uncertainties associated with these projections, although bioclimatic models are still widely used and effective method to evaluate the consequences for biodiversity of these climate changes. In this article, it was found that 90% of these uncertainties are related to methods of modeling, although, regardless of the uncertainties, the results revealed that the studied species will reduce about 78% of their geographic distribution in Cerrado. For an effective work on the conservation of these species, many studies still need to be carried out, although it is already possible to observe that climate change will have a strong influence on the pattern of distribution of these species.

Numerical modelling of the impact of climate change on the morphology of Saint-Lawrence tributaries

Cette thèse examine les impacts sur la morphologie des tributaires du fleuve Saint-Laurent des changements dans leur débit et leur niveau de base engendrés par les changements climatiques prévus pour la période 2010–2099. Les tributaires sélectionnés (rivières Batiscan, Richelieu, Saint-Maurice, Saint-François et Yamachiche) ont été choisis en raison de leurs différences de taille, de débit et de contexte morphologique. Non seulement ces tributaires subissent-ils un régime hydrologique modifié en raison des changements climatiques, mais leur niveau de base (niveau d’eau du fleuve Saint-Laurent) sera aussi affecté. Le modèle morphodynamique en une dimension (1D) SEDROUT, à l’origine développé pour des rivières graveleuses en mode d’aggradation, a été adapté pour le contexte spécifique des tributaires des basses-terres du Saint-Laurent afin de simuler des rivières sablonneuses avec un débit quotidien variable et des fluctuations du niveau d’eau à l’aval. Un module pour simuler le partage des sédiments autour d’îles a aussi été ajouté au modèle. Le modèle ainsi amélioré (SEDROUT4-M), qui a été testé à l’aide de simulations à petite échelle et avec les conditions actuelles d’écoulement et de transport de sédiments dans quatre tributaires du fleuve Saint-Laurent, peut maintenant simuler une gamme de problèmes morphodynamiques de rivières. Les changements d’élévation du lit et d’apport en sédiments au fleuve Saint-Laurent pour la période 2010–2099 ont été simulés avec SEDROUT4-M pour les rivières Batiscan, Richelieu et Saint-François pour toutes les combinaisons de sept régimes hydrologiques (conditions actuelles et celles prédites par trois modèles de climat globaux (MCG) et deux scénarios de gaz à effet de serre) et de trois scénarios de changements du niveau de base du fleuve Saint-Laurent (aucun changement, baisse graduelle, baisse abrupte). Les impacts sur l’apport de sédiments et l’élévation du lit diffèrent entre les MCG et semblent reliés au statut des cours d’eau (selon qu’ils soient en état d’aggradation, de dégradation ou d’équilibre), ce qui illustre l’importance d’examiner plusieurs rivières avec différents modèles climatiques afin d’établir des tendances dans les effets des changements climatiques. Malgré le fait que le débit journalier moyen et le débit annuel moyen demeurent près de leur valeur actuelle dans les trois scénarios de MCG, des changements importants dans les taux de transport de sédiments simulés pour chaque tributaire sont observés. Ceci est dû à l’impact important de fortes crues plus fréquentes dans un climat futur de même qu’à l’arrivée plus hâtive de la crue printanière, ce qui résulte en une variabilité accrue dans les taux de transport en charge de fond. Certaines complications avec l’approche de modélisation en 1D pour représenter la géométrie complexe des rivières Saint-Maurice et Saint-François suggèrent qu’une approche bi-dimensionnelle (2D) devrait être sérieusement considérée afin de simuler de façon plus exacte la répartition des débits aux bifurcations autour des îles. La rivière Saint-François est utilisée comme étude de cas pour le modèle 2D H2D2, qui performe bien d’un point de vue hydraulique, mais qui requiert des ajustements pour être en mesure de pleinement simuler les ajustements morphologiques des cours d’eau.

Regional climate model applications on sub-regional scales over the Indian monsoon region: The role of domain size on downscaling uncertainty

Regional climate models are becoming increasingly popular to provide high resolution climate change information for impacts assessments to inform adaptation options. Many countries and provinces requiring these assessments are as small as 200,000 km2 in size, significantly smaller than an ideal domain needed for successful applications of one-way nested regional climate models. Therefore assessments on sub-regional scales (e.g., river basins) are generally carried out using climate change simulations performed for relatively larger regions. Here we show that the seasonal mean hydrological cycle and the day-to-day precipitation variations of a sub-region within the model domain are sensitive to the domain size, even though the large scale circulation features over the region are largely insensitive. On seasonal timescales, the relatively smaller domains intensify the hydrological cycle by increasing the net transport of moisture into the study region and thereby enhancing the precipitation and local recycling of moisture. On daily timescales, the simulations run over smaller domains produce higher number of moderate precipitation days in the sub-region relative to the corresponding larger domain simulations. An assessment of daily variations of water vapor and the vertical velocity within the sub-region indicates that the smaller domains may favor more frequent moderate uplifting and subsequent precipitation in the region. The results remained largely insensitive to the horizontal resolution of the model, indicating the robustness of the domain size influence on the regional model solutions. These domain size dependent precipitation characteristics have the potential to add one more level of uncertainty to the downscaled projections.

Tropical cyclones in a T159 Resolution Global Climate Model: comparison with observations and re-analyses

Tropical cyclones have been investigated in a T159 version of the MPI ECHAM5 climate model using a novel technique to diagnose the evolution of the 3-dimensional vorticity structure of tropical cyclones, including their full life cycle from weak initial vortex to their possible extra-tropical transition. Results have been compared with reanalyses (ERA40 and JRA25) and observed tropical storms during the period 1978-1999 for the Northern Hemisphere. There is no indication of any trend in the number or intensity of tropical storms during this period in ECHAM5 or in re-analyses but there are distinct inter-annual variations. The storms simulated by ECHAM5 are realistic both in space and time, but the model and even more so the re-analyses, underestimate the intensities of the most intense storms (in terms of their maximum wind speeds). There is an indication of a response to ENSO with a smaller number of Atlantic storms during El Niño in agreement with previous studies. The global divergence circulation responds to El Niño by setting up a large-scale convergence flow, with the center over the central Pacific with enhanced subsidence over the tropical Atlantic. At the same time there is an increase in the vertical wind shear in the region of the tropical Atlantic where tropical storms normally develop. There is a good correspondence between the model and ERA40 except that the divergence circulation is somewhat stronger in the model. The model underestimates storms in the Atlantic but tends to overestimate them in the Western Pacific and in the North Indian Ocean. It is suggested that the overestimation of storms in the Pacific by the model is related to an overly strong response to the tropical Pacific SST anomalies. The overestimation in 2 the North Indian Ocean is likely to be due to an over prediction in the intensity of monsoon depressions, which are then classified as intense tropical storms. Nevertheless, overall results are encouraging and will further contribute to increased confidence in simulating intense tropical storms with high-resolution climate models.

How may tropical cyclones change in a warmer climate?

Tropical Cyclones (TC) under different climate conditions in the Northern Hemisphere have been investigated with the Max Planck Institute (MPI) coupled (ECHAM5/MPIOM) and atmosphere (ECHAM5) climate models. The intensity and size of the TC depend crucially on resolution with higher wind speed and smaller scales at the higher resolutions. The typical size of the TC is reduced by a factor of 2.3 from T63 to T319 using the distance of the maximum wind speed from the centre of the storm as a measure. The full three dimensional structure of the storms becomes increasingly more realistic as the resolution is increased. For the T63 resolution, three ensemble runs are explored for the period 1860 until 2100 using the IPCC SRES scenario A1B and evaluated for three 30 year periods at the end of the 19th, 20th and 21st century, respectively. While there is no significant change between the 19th and the 20th century, there is a considerable reduction in the number of the TC by some 20% in the 21st century, but no change in the number of the more intense storms. Reduction in the number of storms occurs in all regions. A single additional experiment at T213 resolution was run for the two latter 30-year periods. The T213 is an atmospheric only experiment using the transient Sea Surface Temperatures (SST) of the T63 resolution experiment. Also in this case, there is a reduction by some 10% in the number of simulated TC in the 21st century compared to the 20th century but a marked increase in the number of intense storms. The number of storms with maximum wind speeds greater than 50ms-1 increases by a third. Most of the intensification takes place in 2 the Eastern Pacific and in the Atlantic where also the number of storms more or less stays the same. We identify two competing processes effecting TC in a warmer climate. First, the increase in the static stability and the reduced vertical circulation is suggested to contribute to the reduction in the number of storms. Second, the increase in temperature and water vapor provide more energy for the storms so that when favorable conditions occur, the higher SST and higher specific humidity will contribute to more intense storms. As the maximum intensity depends crucially on resolution, this will require higher resolution to have its full effect. The distribution of storms between different regions does not, at first approximation, depend on the temperature itself but on the distribution of the SST anomalies and their influence on the atmospheric circulation. Two additional transient experiments at T319 resolution where run for 20 years at the end of the 20th and 21st century, respectively using the same conditions as in the T213 experiments. The results are consistent with the T213 study. The total number of tropical cyclones were similar to the T213 experiment but were generally more intense. The change from the 20th to the 21st century was also similar with fewer TC in total but with more intense cyclones.

Monitoring present day changes in water vapour and the radiative energy balance using satellite data, reanalyses and models

A combination of satellite data, reanalysis products and climate models are combined to monitor changes in water vapour, clear-sky radiative cooling of the atmosphere and precipitation over the period 1979-2006. Climate models are able to simulate observed increases in column integrated water vapour (CWV) with surface temperature (Ts) over the ocean. Changes in the observing system lead to spurious variability in water vapour and clear-sky longwave radiation in reanalysis products. Nevertheless all products considered exhibit a robust increase in clear-sky longwave radiative cooling from the atmosphere to the surface; clear-sky longwave radiative cooling of the atmosphere is found to increase with Ts at the rate of ~4 Wm-2 K-1 over tropical ocean regions of mean descending vertical motion. Precipitation (P) is tightly coupled to atmospheric radiative cooling rates and this implies an increase in P with warming at a slower rate than the observed increases in CWV. Since convective precipitation depends on moisture convergence, the above implies enhanced precipitation over convective regions and reduced precipitation over convectively suppressed regimes. To quantify this response, observed and simulated changes in precipitation rate are analysed separately over regions of mean ascending and descending vertical motion over the tropics. The observed response is found to be substantially larger than the model simulations and climate change projections. It is currently not clear whether this is due to deficiencies in model parametrizations or errors in satellite retrievals.

Introduction. Stochastic physics and climate modelling

Finite computing resources limit the spatial resolution of state-of-the-art global climate simulations to hundreds of kilometres. In neither the atmosphere nor the ocean are small-scale processes such as convection, clouds and ocean eddies properly represented. Climate simulations are known to depend, sometimes quite strongly, on the resulting bulk-formula representation of unresolved processes. Stochastic physics schemes within weather and climate models have the potential to represent the dynamical effects of unresolved scales in ways which conventional bulk-formula representations are incapable of so doing. The application of stochastic physics to climate modelling is a rapidly advancing, important and innovative topic. The latest research findings are gathered together in the Theme Issue for which this paper serves as the introduction.

Subseasonal extremes of precipitation and active-break cycles of the Indian summer monsoon in a climate-change scenario

Changes to the behaviour of subseasonal precipitation extremes and active-break cycles of the Indian summer monsoon are assessed in this study using pre-industrial and 2 × CO2 integrations of the Hadley Centre coupled model HadCM3, which is able to simulate the monsoon seasonal cycle reasonably. At 2 × CO2, mean summer rainfall increases slightly, especially over central and northern India. The mean intensity of daily precipitation during the monsoon is found to increase, consistent with fewer wet days, and there are increases to heavy rain events beyond changes in the mean alone. The chance of reaching particular thresholds of heavy rainfall is found to approximately double over northern India, increasing the likelihood of damaging floods on a seasonal basis. The local distribution of such projections is uncertain, however, given the large spread in mean monsoon rainfall change and associated extremes amongst even the most recent coupled climate models. The measured increase of the heaviest precipitation events over India is found to be broadly in line with the degree of atmospheric warming and associated increases in specific humidity, lending a degree of predictability to changes in rainfall extremes. Active-break cycles of the Indian summer monsoon, important particularly due to their effect on agricultural output, are shown to be reasonably represented in HadCM3, in particular with some degree of northward propagation. We note an intensification of both active and break events, particularly when measured against the annual cycle, although there is no suggestion of any change to the duration or likelihood of monsoon breaks. Copyright © 2009 Royal Meteorological Society

Land surface anomaly simulations and predictions with a climate model: an El Nino Southern Oscillation case study

The ability of climate models to reproduce and predict land surface anomalies is an important but little-studied topic. In this study, an atmosphere and ocean assimilation scheme is used to determine whether HadCM3 can reproduce and predict snow water equivalent and soil moisture during the 1997–1998 El Nino Southern Oscillation event. Soil moisture is reproduced more successfully, though both snow and soil moisture show some predictability at 1- and 4-month lead times. This result suggests that land surface anomalies may be reasonably well initialized for climate model predictions and hydrological applications using atmospheric assimilation methods over a period of time.

The potential to narrow uncertainty in regional climate predictions

Faced by the realities of a changing climate, decision makers in a wide variety of organisations are increasingly seeking quantitative predictions of regional and local climate. An important issue for these decision makers, and for organisations that fund climate research, is what is the potential for climate science to deliver improvements - especially reductions in uncertainty - in such predictions? Uncertainty in climate predictions arises from three distinct sources: internal variability, model uncertainty and scenario uncertainty. Using data from a suite of climate models we separate and quantify these sources. For predictions of changes in surface air temperature on decadal timescales and regional spatial scales, we show that uncertainty for the next few decades is dominated by sources (model uncertainty and internal variability) that are potentially reducible through progress in climate science. Furthermore, we find that model uncertainty is of greater importance than internal variability. Our findings have implications for managing adaptation to a changing climate. Because the costs of adaptation are very large, and greater uncertainty about future climate is likely to be associated with more expensive adaptation, reducing uncertainty in climate predictions is potentially of enormous economic value. We highlight the need for much more work to compare: a) the cost of various degrees of adaptation, given current levels of uncertainty; and b) the cost of new investments in climate science to reduce current levels of uncertainty. Our study also highlights the importance of targeting climate science investments on the most promising opportunities to reduce prediction uncertainty.

Examining the interaction of growing crops with local climate using a coupled crop-climate model

This paper examines to what extent crops and their environment should be viewed as a coupled system. Crop impact assessments currently use climate model output offline to drive process-based crop models. However, in regions where local climate is sensitive to land surface conditions more consistent assessments may be produced with the crop model embedded within the land surface scheme of the climate model. Using a recently developed coupled crop–climate model, the sensitivity of local climate, in particular climate variability, to climatically forced variations in crop growth throughout the tropics is examined by comparing climates simulated with dynamic and prescribed seasonal growth of croplands. Interannual variations in land surface properties associated with variations in crop growth and development were found to have significant impacts on near-surface fluxes and climate; for example, growing season temperature variability was increased by up to 40% by the inclusion of dynamic crops. The impact was greatest in dry years where the response of crop growth to soil moisture deficits enhanced the associated warming via a reduction in evaporation. Parts of the Sahel, India, Brazil, and southern Africa were identified where local climate variability is sensitive to variations in crop growth, and where crop yield is sensitive to variations in surface temperature. Therefore, offline seasonal forecasting methodologies in these regions may underestimate crop yield variability. The inclusion of dynamic crops also altered the mean climate of the humid tropics, highlighting the importance of including dynamical vegetation within climate models.

Methods and resources for climate impacts research: achieving synergy

The prediction of climate variability and change requires the use of a range of simulation models. Multiple climate model simulations are needed to sample the inherent uncertainties in seasonal to centennial prediction. Because climate models are computationally expensive, there is a tradeoff between complexity, spatial resolution, simulation length, and ensemble size. The methods used to assess climate impacts are examined in the context of this trade-off. An emphasis on complexity allows simulation of coupled mechanisms, such as the carbon cycle and feedbacks between agricultural land management and climate. In addition to improving skill, greater spatial resolution increases relevance to regional planning. Greater ensemble size improves the sampling of probabilities. Research from major international projects is used to show the importance of synergistic research efforts. The primary climate impact examined is crop yield, although many of the issues discussed are relevant to hydrology and health modeling. Methods used to bridge the scale gap between climate and crop models are reviewed. Recent advances include large-area crop modeling, quantification of uncertainty in crop yield, and fully integrated crop–climate modeling. The implications of trends in computer power, including supercomputers, are also discussed.

Modelling climate change: the role of unresolved processes

Our understanding of the climate system has been revolutionized recently, by the development of sophisticated computer models. The predictions of such models are used to formulate international protocols, intended to mitigate the severity of global warming and its impacts. Yet, these models are not perfect representations of reality, because they remove from explicit consideration many physical processes which are known to be key aspects of the climate system, but which are too small or fast to be modelled. The purpose of this paper is to give a personal perspective of the current state of knowledge regarding the problem of unresolved scales in climate models. A recent novel solution to the problem is discussed, in which it is proposed, somewhat counter-intuitively, that the performance of models may be improved by adding random noise to represent the unresolved processes.

Modelling European winter wind storm losses in current and future climate

Severe wind storms are one of the major natural hazards in the extratropics and inflict substantial economic damages and even casualties. Insured storm-related losses depend on (i) the frequency, nature and dynamics of storms, (ii) the vulnerability of the values at risk, (iii) the geographical distribution of these values, and (iv) the particular conditions of the risk transfer. It is thus of great importance to assess the impact of climate change on future storm losses. To this end, the current study employs—to our knowledge for the first time—a coupled approach, using output from high-resolution regional climate model scenarios for the European sector to drive an operational insurance loss model. An ensemble of coupled climate-damage scenarios is used to provide an estimate of the inherent uncertainties. Output of two state-of-the-art global climate models (HadAM3, ECHAM5) is used for present (1961–1990) and future climates (2071–2100, SRES A2 scenario). These serve as boundary data for two nested regional climate models with a sophisticated gust parametrizations (CLM, CHRM). For validation and calibration purposes, an additional simulation is undertaken with the CHRM driven by the ERA40 reanalysis. The operational insurance model (Swiss Re) uses a European-wide damage function, an average vulnerability curve for all risk types, and contains the actual value distribution of a complete European market portfolio. The coupling between climate and damage models is based on daily maxima of 10 m gust winds, and the strategy adopted consists of three main steps: (i) development and application of a pragmatic selection criterion to retrieve significant storm events, (ii) generation of a probabilistic event set using a Monte-Carlo approach in the hazard module of the insurance model, and (iii) calibration of the simulated annual expected losses with a historic loss data base. The climate models considered agree regarding an increase in the intensity of extreme storms in a band across central Europe (stretching from southern UK and northern France to Denmark, northern Germany into eastern Europe). This effect increases with event strength, and rare storms show the largest climate change sensitivity, but are also beset with the largest uncertainties. Wind gusts decrease over northern Scandinavia and Southern Europe. Highest intra-ensemble variability is simulated for Ireland, the UK, the Mediterranean, and parts of Eastern Europe. The resulting changes on European-wide losses over the 110-year period are positive for all layers and all model runs considered and amount to 44% (annual expected loss), 23% (10 years loss), 50% (30 years loss), and 104% (100 years loss). There is a disproportionate increase in losses for rare high-impact events. The changes result from increases in both severity and frequency of wind gusts. Considerable geographical variability of the expected losses exists, with Denmark and Germany experiencing the largest loss increases (116% and 114%, respectively). All countries considered except for Ireland (−22%) experience some loss increases. Some ramifications of these results for the socio-economic sector are discussed, and future avenues for research are highlighted. The technique introduced in this study and its application to realistic market portfolios offer exciting prospects for future research on the impact of climate change that is relevant for policy makers, scientists and economists.