940 resultados para global nonhydrostatic model
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[1] Iron is hypothesized to be an important micronutrient for ocean biota, thus modulating carbon dioxide uptake by the ocean biological pump. Studies have assumed that atmospheric deposition of iron to the open ocean is predominantly from mineral aerosols. For the first time we model the source, transport, and deposition of iron from combustion sources. Iron is produced in small quantities during fossil fuel burning, incinerator use, and biomass burning. The sources of combustion iron are concentrated in the industrialized regions and biomass burning regions, largely in the tropics. Model results suggest that combustion iron can represent up to 50% of the total iron deposited, but over open ocean regions it is usually less than 5% of the total iron, with the highest values (< 30%) close to the East Asian continent in the North Pacific. For ocean biogeochemistry the bioavailability of the iron is important, and this is often estimated by the fraction which is soluble ( Fe(II)). Previous studies have argued that atmospheric processing of the relatively insoluble Fe(III) occurs to make it more soluble ( Fe( II)). Modeled estimates of soluble iron amounts based solely on atmospheric processing as simulated here cannot match the variability in daily averaged in situ concentration measurements in Korea, which is located close to both combustion and dust sources. The best match to the observations is that there are substantial direct emissions of soluble iron from combustion processes. If we assume observed soluble Fe/black carbon ratios in Korea are representative of the whole globe, we obtain the result that deposition of soluble iron from combustion contributes 20-100% of the soluble iron deposition over many ocean regions. This implies that more work should be done refining the emissions and deposition of combustion sources of soluble iron globally.
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O objetivo deste estudo é avaliar a propagação de choques econômicos de alguns países sobre o crescimento econômico brasileiro, com principal destaque para China, Estados Unidos da América (EUA) e Argentina, que são os principais parceiros comerciais do Brasil. O aumento do comércio com a China tornou o Brasil muito mais vulnerável a choques no PIB chinês e menos vulnerável, do que no passado recente, a choques no PIB americano, enquanto que a influência da Argentina manteve-se estável. Foi aplicada a metodologia Vetor Autorregressivo Global (Global Var – GVAR), introduzida por Pesaran, Schuermann e Weiner (2004), Garratt, Lee, Pesaran e Shin (2006) e Dées, Di Mauro, Pesaran e Smith (2007), para analisar os canais de comércio e a transmissão de choques entre o resto do mundo e o Brasil. Usando dados trimestrais a partir de 1990 até o final de 2013, foi possível constatar que o aumento da relevância da economia Chinesa na balança comercial Brasileira exerce pressão sobre o crescimento econômico do Brasil. Em suma, a China tornou-se mais relevante para o crescimento econômico do Brasil do que os EUA e a Argentina.
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Incluye Bibliografía
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Climate change has the potential to impact on global, regional, and national disease burdens both directly and indirectly. Projecting and valuing these health impacts is important not only in terms of assessing the overall impact of climate change on various parts of the world, but also in terms of ensuring that national and regional decision-making institutions have access to the data necessary to guide investment decisions and future policy design. This report contributes to the research focusing on projecting and valuing the impacts of climate change in the Caribbean by projecting the climate change-induced excess disease burden for two climate change scenarios in Montserrat for the period 2010 - 2050, and by estimating the monetary value associated with this excess disease burden. The diseases initially considered in this report are variety of vector and water-borne impacts and other miscellaneous conditions; specifically, malaria, dengue fever, gastroenteritis/diarrheal disease, schistosomiasis, leptospirosis, ciguatera poisoning, meningococcal meningitis, and cardio-respiratory diseases. Disease projections were based on derived baseline incidence and mortality rates, available dose-response relationships found in the published literature, climate change scenario population projections for the A2 and B2 IPCC SRES scenario families, and annual temperature and precipitation anomalies as projected by the downscaled ECHAM4 global climate model. Monetary valuation was based on a transfer value of statistical life approach with a modification for morbidity. Using discount rates of 1%, 2% and 4%, results show mean annual costs (morbidity and mortality) ranges of $0.61 million (in the B2 scenario, discounted at 4% annually) – $1 million (in the A2 scenario, discounted at 1% annually) for Montserrat. These costs are compared to adaptation cost scenarios involving increased direct spending on per capita health care. This comparison reveals a high benefit-cost ratio suggesting that moderate costs will deliver significant benefit in terms of avoided health burdens in the period 2010-2050. The methodology and results suggest that a focus on coordinated data collection and improved monitoring represents a potentially important no regrets adaptation strategy for Montserrat. Also the report highlights the need for this to be part of a coordinated regional response that avoids duplication in spending.
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Climate change has the potential to impact on global, regional, and national disease burdens both directly and indirectly. Projecting and valuing these health impacts is important not only in terms of assessing the overall impact of climate change on various parts of the world, but also of ensuring that national and regional decision-making institutions have access to the data necessary to guide investment decisions and future policy design. This report contributes to the research focusing on projecting and valuing the impacts of climate change in the Caribbean by projecting the climate change-induced excess disease burden for two climate change scenarios in Saint Lucia for the period 2010 - 2050, and by estimating the non-market, statistical life-based costs associated with this excess disease burden. The diseases initially considered in this report are a variety of vector and water-borne impacts and other miscellaneous conditions; specifically, malaria, dengue fever, gastroenteritis/diarrhoeal disease, schistosomiasis, leptospirosis, ciguatera poisoning, meningococcal meningitis, and cardio-respiratory diseases. Disease projections were based on derived baseline incidence and mortality rates, available dose-response relationships found in the published literature, climate change scenario population projections for the A2 and B2 IPCC SRES scenario families, and annual temperature and precipitation anomalies as projected by the downscaled ECHAM4 global climate model. Monetary valuation was based on a transfer value of statistical life approach with a modification for morbidity. Using discount rates of 1, 2, and 4%, results show mean annual costs (morbidity and mortality) ranges of $80.2 million (in the B2 scenario, discounted at 4% annually) -$182.4 million (in the A2 scenario, discounted at 1% annually) for St. Lucia.1 These costs are compared to adaptation cost scenarios involving direct and indirect interventions in health care. This comparison reveals a high benefit-cost ratio suggesting that moderate costs will deliver significant benefit in terms of avoided health costs from 2010-2050. In this context indirect interventions target sectors other than healthcare (e.g. water supply). It is also important to highlight that interventions can target both the supply of health infrastructure (including health status and disease monitoring), and households. It is suggested that a focus on coordinated data collection and improved monitoring represents a potentially important no regrets adaptation strategy for St Lucia. Also, the need for this to be part of a coordinated regional response that avoids duplication in spending is highlighted.
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Climate change is a naturally occurring phenomenon in which the earth‘s climate goes through cycles of warming and cooling; these changes usually take place incrementally over millennia. Over the past century, there has been an anomalous increase in global temperature, giving rise to accelerated climate change. It is widely accepted that greenhouse gas emissions from human activities such as industries have contributed significantly to the increase in global temperatures. The existence and survival of all living organisms is predicated on the ability of the environment in which they live not only to provide conditions for their basic needs but also conditions suitable for growth and reproduction. Unabated climate change threatens the existence of biophysical and ecological systems on a planetary scale. The present study aims to examine the economic impact of climate change on health in Jamaica over the period 2011-2050. To this end, three disease conditions with known climate sensitivity and importance to Jamaican public health were modelled. These were: dengue fever, leptospirosis and gastroenteritis in children under age 5. Historical prevalence data on these diseases were obtained from the Ministry of Health Jamaica, the Caribbean Epidemiology Centre, the Climate Studies Group Mona, University of the West Indies Mona campus, and the Meteorological Service of Jamaica. Data obtained spanned a twelve-year period of 1995-2007. Monthly data were obtained for dengue and gastroenteritis, while for leptospirosis, the annual number of cases for 1995-2005 was utilized. The two SRES emission scenarios chosen were A2 and B2 using the European Centre Hamburg Model (ECHAM) global climate model to predict climate variables for these scenarios. A business as usual (BAU) scenario was developed using historical disease data for the period 2000-2009 (dengue fever and gastroenteritis) and 1995-2005 (leptospirosis) as the reference decades for the respective diseases. The BAU scenario examined the occurrence of the diseases in the absence of climate change. It assumed that the disease trend would remain unchanged over the projected period and the number of cases of disease for each decade would be the same as the reference decade. The model used in the present study utilized predictive empirical statistical modelling to extrapolate the climate/disease relationship in time, to estimate the number of climate change-related cases under future climate change scenarios. The study used a Poisson regression model that considered seasonality and lag effects to determine the best-fit model in relation to the diseases under consideration. Zhang and others (2008), in their review of climate change and the transmission of vector-borne diseases, found that: ―Besides climatic variables, few of them have included other factors that can affect the transmission of vector-borne disease….‖ (Zhang 2008) Water, sanitation and health expenditure are key determinants of health. In the draft of the second communication to IPCC, Jamaica noted the vulnerability of public health to climate change, including sanitation and access to water (MSJ/UNDP, 2009). Sanitation, which in its broadest context includes the removal of waste (excreta, solid, or other hazardous waste), is a predictor of vector-borne diseases (e.g. dengue fever), diarrhoeal diseases (such as gastroenteritis) and zoonoses (such as leptospirosis). In conceptualizing the model, an attempt was made to include non-climate predictors of these climate-sensitive diseases. The importance of sanitation and water access to the control of dengue, gastroenteritis and leptospirosis were included in the Poisson regression model. The Poisson regression model obtained was then used to predict the number of disease cases into the future (2011-2050) for each emission scenario. After projecting the number of cases, the cost associated with each scenario was calculated using four cost components. 1. Treatment cost morbidity estimate. The treatment cost for the number of cases was calculated using reference values found in the literature for each condition. The figures were derived from studies of the cost of treatment and represent ambulatory and non-fatal hospitalized care for dengue fever and gastroenteritis. Due to the paucity of published literature on the health care cost associated with leptospirosis, only the cost of diagnosis and antibiotic therapy were included in the calculation. 2. Mortality estimates. Mortality estimates are recorded as case fatality rates. Where local data were available, these were utilized. Where these were unavailable, appropriate reference values from the literature were used. 3. Productivity loss. Productivity loss was calculated using a human capital approach, by multiplying the expected number of productive days lost by the caregiver and/or the infected person, by GDP per capita per day (US$ 14) at 2008 GDP using 2008 US$ exchange rates. 4. No-option cost. The no-option cost refers to adaptation strategies for the control of dengue fever which are ongoing and already a part of the core functions of the Vector Control Division of the Ministry of Health, Jamaica. An estimated US$ 2.1 million is utilized each year in conducting activities to prevent the post-hurricane spread of vector borne diseases and diarrhoea. The cost includes public education, fogging, laboratory support, larvicidal activities and surveillance. This no-option cost was converted to per capita estimates, using population estimates for Jamaica up to 2050 obtained from the Statistical Institute of Jamaica (STATIN, 2006) and the assumption of one expected major hurricane per decade. During the decade 2000-2009, Jamaica had an average inflation of 10.4% (CIA Fact book, last updated May 2011). This average decadal inflation rate was applied to the no-option cost, which was inflated by 10% for each successive decade to adjust for changes in inflation over time.
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As atividades humanas que alteram as concentrações de gases de efeito estufa terão influências diretas sobre os problemas fitossanitários. A fim de minimizar tanto a perda de produção, quanto a qualidade de safras, além de orientar a escolha de estratégias de adaptação e de gestão, novos estudos para investigar os impactos das mudanças climáticas na agricultura - nas escalas espaciais e temporais - e seus patógenos são necessários. O objetivo principal deste trabalho foi investigar o impacto da mudança climática global, na ecoclimatologia da mosca-negra-dos-citrus (Aleurocanthus woglumi Ashby) no Estado do Pará. Para isso, foram analisadas as exigências térmicas da A. woglumi, desenvolvidas em laboratório e no zoneamento ecoclimatológico, com base no número de gerações do inseto a cada ano, realizado a partir de dados de temperatura do ar de 15 estações meteorológicas ao longo do estado. Em seguida, foi simulado o aumento populacional de insetos estudados, através das projeções do modelo climático global CCSM 3.0, entre os anos de 2030 e 2090. Os resultados das simulações sugerem que o número de gerações do inseto vai aumentar 50% no Estado do Pará.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Die Verifikation numerischer Modelle ist für die Verbesserung der Quantitativen Niederschlagsvorhersage (QNV) unverzichtbar. Ziel der vorliegenden Arbeit ist die Entwicklung von neuen Methoden zur Verifikation der Niederschlagsvorhersagen aus dem regionalen Modell der MeteoSchweiz (COSMO-aLMo) und des Globalmodells des Europäischen Zentrums für Mittelfristvorhersage (engl.: ECMWF). Zu diesem Zweck wurde ein neuartiger Beobachtungsdatensatz für Deutschland mit stündlicher Auflösung erzeugt und angewandt. Für die Bewertung der Modellvorhersagen wurde das neue Qualitätsmaß „SAL“ entwickelt. Der neuartige, zeitlich und räumlich hoch-aufgelöste Beobachtungsdatensatz für Deutschland wird mit der während MAP (engl.: Mesoscale Alpine Program) entwickelten Disaggregierungsmethode erstellt. Die Idee dabei ist, die zeitlich hohe Auflösung der Radardaten (stündlich) mit der Genauigkeit der Niederschlagsmenge aus Stationsmessungen (im Rahmen der Messfehler) zu kombinieren. Dieser disaggregierte Datensatz bietet neue Möglichkeiten für die quantitative Verifikation der Niederschlagsvorhersage. Erstmalig wurde eine flächendeckende Analyse des Tagesgangs des Niederschlags durchgeführt. Dabei zeigte sich, dass im Winter kein Tagesgang existiert und dies vom COSMO-aLMo gut wiedergegeben wird. Im Sommer dagegen findet sich sowohl im disaggregierten Datensatz als auch im COSMO-aLMo ein deutlicher Tagesgang, wobei der maximale Niederschlag im COSMO-aLMo zu früh zwischen 11-14 UTC im Vergleich zu 15-20 UTC in den Beobachtungen einsetzt und deutlich um das 1.5-fache überschätzt wird. Ein neues Qualitätsmaß wurde entwickelt, da herkömmliche, gitterpunkt-basierte Fehlermaße nicht mehr der Modellentwicklung Rechnung tragen. SAL besteht aus drei unabhängigen Komponenten und basiert auf der Identifikation von Niederschlagsobjekten (schwellwertabhängig) innerhalb eines Gebietes (z.B. eines Flusseinzugsgebietes). Berechnet werden Unterschiede der Niederschlagsfelder zwischen Modell und Beobachtungen hinsichtlich Struktur (S), Amplitude (A) und Ort (L) im Gebiet. SAL wurde anhand idealisierter und realer Beispiele ausführlich getestet. SAL erkennt und bestätigt bekannte Modelldefizite wie das Tagesgang-Problem oder die Simulation zu vieler relativ schwacher Niederschlagsereignisse. Es bietet zusätzlichen Einblick in die Charakteristiken der Fehler, z.B. ob es sich mehr um Fehler in der Amplitude, der Verschiebung eines Niederschlagsfeldes oder der Struktur (z.B. stratiform oder kleinskalig konvektiv) handelt. Mit SAL wurden Tages- und Stundensummen des COSMO-aLMo und des ECMWF-Modells verifiziert. SAL zeigt im statistischen Sinne speziell für stärkere (und damit für die Gesellschaft relevante Niederschlagsereignisse) eine im Vergleich zu schwachen Niederschlägen gute Qualität der Vorhersagen des COSMO-aLMo. Im Vergleich der beiden Modelle konnte gezeigt werden, dass im Globalmodell flächigere Niederschläge und damit größere Objekte vorhergesagt werden. Das COSMO-aLMo zeigt deutlich realistischere Niederschlagsstrukturen. Diese Tatsache ist aufgrund der Auflösung der Modelle nicht überraschend, konnte allerdings nicht mit herkömmlichen Fehlermaßen gezeigt werden. Die im Rahmen dieser Arbeit entwickelten Methoden sind sehr nützlich für die Verifikation der QNV zeitlich und räumlich hoch-aufgelöster Modelle. Die Verwendung des disaggregierten Datensatzes aus Beobachtungen sowie SAL als Qualitätsmaß liefern neue Einblicke in die QNV und lassen angemessenere Aussagen über die Qualität von Niederschlagsvorhersagen zu. Zukünftige Anwendungsmöglichkeiten für SAL gibt es hinsichtlich der Verifikation der neuen Generation von numerischen Wettervorhersagemodellen, die den Lebenszyklus hochreichender konvektiver Zellen explizit simulieren.
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Mineral dust is an important component of the Earth's climate system and provides essential nutrientsrnto oceans and rain forests. During atmospheric transport, dust particles directly and indirectly influencernweather and climate. The strength of dust sources and characteristics of the transport, in turn, mightrnbe subject to climatic changes. Earth system models help for a better understanding of these complexrnmechanisms.rnrnThis thesis applies the global climate model ECHAM5/MESSy Atmospheric Chemistry (EMAC) for simulationsrnof the mineral dust cycle under different climatic conditions. The prerequisite for suitable modelrnresults is the determination of the model setup reproducing the most realistic dust cycle in the recentrnclimate. Simulations with this setup are used to gain new insights into properties of the transatlanticrndust transport from Africa to the Americas and adaptations of the model's climate forcing factors allowrnfor investigations of the impact of climatic changes on the dust cycle.rnrnIn the first part, the most appropriate model setup is determined through a number of sensitivity experiments.rnIt uses the dust emission parametrisation from Tegen et al. 2002 and a spectral resolutionrnof T85, corresponding to a horizontal grid spacing of about 155 km. Coarser resolutions are not able tornaccurately reproduce emissions from important source regions such as the Bodele Depression in Chad orrnthe Taklamakan Desert in Central Asia. Furthermore, the representation of ageing and wet deposition ofrndust particles in the model requires a basic sulphur chemical mechanism. This setup is recommended forrnfuture simulations with EMAC focusing on mineral dust.rnrnOne major branch of the global dust cycle is the long-range transport from the world's largest dustrnsource, the Sahara, across the Atlantic Ocean. Seasonal variations of the main transport pathways to thernAmazon Basin in boreal winter and to the Caribbean during summer are well known and understood,rnand corroborated in this thesis. Both Eulerian and Lagrangian methods give estimates on the typicalrntransport times from the source regions to the deposition on the order of nine to ten days. Previously, arnhuge proportion of the dust transported across the Atlantic Ocean has been attributed to emissions fromrnthe Bodele Depression. However, the contribution of this hot spot to the total transport is very low inrnthe present results, although the overall emissions from this region are comparable. Both model resultsrnand data sets analysed earlier, such as satellite products, involve uncertainties and this controversy aboutrndust transport from the Bodele Depression calls for future investigations and clarification.rnrnAforementioned characteristics of the transatlantic dust transport just slightly change in simulationsrnrepresenting climatic conditions of the Little Ice Age in the middle of the last millennium with meanrnnear-surface cooling of 0.5 to 1 K. However, intensification of the West African summer monsoon duringrnthe Little Ice Age is associated with higher dust emissions from North African source regions and wetterrnconditions in the Sahel. Furthermore, the Indian Monsoon and dust emissions from the Arabian Peninsula,rnwhich are affected by this circulation, are intensified during the Little Ice Age, whereas the annual globalrndust budget is similar in both climate epochs. Simulated dust emission fluxes are particularly influencedrnby the surface parameters. Modifications of the model do not affect those in this thesis, to be able tornascribe all differences in the results to changed forcing factors, such as greenhouse gas concentrations.rnDue to meagre comparison data sets, the verification of results presented here is problematic. Deeperrnknowledge about the dust cycle during the Little Ice Age can be obtained by future simulations, based onrnthis work, and additionally using improved reconstructions of surface parameters. Better evaluation ofrnsuch simulations would be possible by refining the temporal resolution of reconstructed dust depositionrnfluxes from existing ice and marine sediment cores.
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The marine aragonite cycle has been included in the global biogeochemical model PISCES to study the role of aragonite in shallow water CaCO3 dissolution. Aragonite production is parameterized as a function of mesozooplankton biomass and aragonite saturation state of ambient waters. Observation-based estimates of marine carbonate production and dissolution are well reproduced by the model and about 60% of the combined CaCO3 water column dissolution from aragonite and calcite is simulated above 2000 m. In contrast, a calcite-only version yields a much smaller fraction. This suggests that the aragonite cycle should be included in models for a realistic representation of CaCO3 dissolution and alkalinity. For the SRES A2 CO2 scenario, production rates of aragonite are projected to notably decrease after 2050. By the end of this century, global aragonite production is reduced by 29% and total CaCO3 production by 19% relative to pre-industrial. Geographically, the effect from increasing atmospheric CO2, and the subsequent reduction in saturation state, is largest in the subpolar and polar areas where the modeled aragonite production is projected to decrease by 65% until 2100.
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In terms of atmospheric impact, the volcanic eruption of Mt. Pinatubo (1991) is the best characterized large eruption on record. We investigate here the model-derived stratospheric warming following the Pinatubo eruption as derived from SAGE II extinction data including recent improvements in the processing algorithm. This method, termed SAGE_4λ, makes use of the four wavelengths (385, 452, 525 and 1024 nm) of the SAGE II data when available, and uses a data-filling procedure in the opacity-induced "gap" regions. Using SAGE_4λ, we derived aerosol size distributions that properly reproduce extinction coefficients also at much longer wavelengths. This provides a good basis for calculating the absorption of terrestrial infrared radiation and the resulting stratospheric heating. However, we also show that the use of this data set in a global chemistry–climate model (CCM) still leads to stronger aerosol-induced stratospheric heating than observed, with temperatures partly even higher than the already too high values found by many models in recent general circulation model (GCM) and CCM intercomparisons. This suggests that the overestimation of the stratospheric warming after the Pinatubo eruption may not be ascribed to an insufficient observational database but instead to using outdated data sets, to deficiencies in the implementation of the forcing data, or to radiative or dynamical model artifacts. Conversely, the SAGE_4λ approach reduces the infrared absorption in the tropical tropopause region, resulting in a significantly better agreement with the post-volcanic temperature record at these altitudes.
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The Atlantic meridional overturning circulation affects the latitudinal distribution of heat, and is a key component of the climate system. Proxy reconstructions, based on sedimentary Pa-231/Th-230 ratios and the difference between surface-and deep-water radiocarbon ages, indicate that during the last glacial period, the overturning circulation was reduced during millennial-scale periods of cooling(1-5). However, much debate exists over the robustness of these proxies(6-8). Here e combine proxy reconstructions of sea surface and air temperatures and a global climate model to quantitatively estimate changes in the strength of the Atlantic meridional overturning circulation during the last glacial period. We find that, relative to the Last Glacial Maximum, the overturning circulation was reduced by approximately 14 Sv during the cold Heinrich event 1. During the Younger Dryas cold event, the overturning circulation was reduced by approximately 12 Sv, relative to the preceding warm interval. These changes are consistent with qualitative estimates of the overturning circulation from sedimentary Pa-231/Th-230 ratios. In addition, we find that the strength of the overturning circulation during the Last Glacial Maximum and the Holocene epoch are indistinguishable within the uncertainty of the reconstruction.
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Rapid changes in atmospheric methane (CH4), temperature and precipitation are documented by Greenland ice core data both for glacial times (the so called Dansgaard-Oeschger (D-O) events) as well as for a cooling event in the early Holocene (the 8.2 kyr event). The onsets of D-O warm events are paralleled by abrupt increases in CH4 by up to 250 ppb in a few decades. Vice versa, the 8.2 kyr event is accompanied by an intermittent decrease in CH4 of about 80 ppb over 150 yr. The abrupt CH4 changes are thought to mainly originate from source emission variations in tropical and boreal wet ecosystems, but complex process oriented bottom-up model estimates of the changes in these ecosystems during rapid climate changes are still missing. Here we present simulations of CH4 emissions from northern peatlands with the LPJ-Bern dynamic global vegetation model. The model represents CH4 production and oxidation in soils and transport by ebullition, through plant aerenchyma, and by diffusion. Parameters are tuned to represent site emission data as well as inversion-based estimates of northern wetland emissions. The model is forced with climate input data from freshwater hosing experiments using the NCAR CSM1.4 climate model to simulate an abrupt cooling event. A concentration reduction of ~10 ppb is simulated per degree K change of mean northern hemispheric surface temperature in peatlands. Peatland emissions are equally sensitive to both changes in temperature and in precipitation. If simulated changes are taken as an analogy to the 8.2 kyr event, boreal peatland emissions alone could only explain 23 of the 80 ppb decline in atmospheric methane concentration. This points to a significant contribution to source changes from low latitude and tropical wetlands to this event.
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Climate change alone influences future levels of tropospheric ozone and their precursors through modifications of gas-phase chemistry, transport, removal, and natural emissions. The goal of this study is to determine at what extent the modes of variability of gas-phase pollutants respond to different climate change scenarios over Europe. The methodology includes the use of the regional modeling system MM5 (regional climate model version)-CHIMERE for a target domain covering Europe. Two full-transient simulations covering from 1991–2050 under the SRES A2 and B2 scenarios driven by ECHO-G global circulation model have been compared. The results indicate that the spatial patterns of variability for tropospheric ozone are similar for both scenarios, but the magnitude of the change signal significantly differs for A2 and B2. The 1991–2050 simulations share common characteristics for their chemical behavior. As observed from the NO2 and α-pinene modes of variability, our simulations suggest that the enhanced ozone chemical activity is driven by a number of parameters, such as the warming-induced increase in biogenic emissions and, to a lesser extent, by the variation in nitrogen dioxide levels. For gas-phase pollutants, the general increasing trend for ozone found under A2 and B2 forcing is due to a multiplicity of climate factors, such as increased temperature, decreased wet removal associated with an overall decrease of precipitation in southern Europe, increased photolysis of primary and secondary pollutants as a consequence of lower cloudiness and increased biogenic emissions fueled by higher temperatures.