Research Interests: Computational Fluid Dynamics, Environmental Design, Energy efficiency, Computational Fluid Dynamics (CFD) modelling and simulation, Environmental Design of Buildings, and 5 moreThermal comfort & Energy efficiency in hot climates, Natural ventilation as a passive cooling strategy, Historical Climate Change, Maunder MInimum, and Buildings’ Monitoring
Three methods of downscaling are applied to climate change experiments to obtain regional climate information for Spain and the region designated as 'Southern Europe' by the lntergovernmental Panel on Climate Change (IPCC). The first... more
Three methods of downscaling are applied to climate change experiments to obtain regional climate information for Spain and the region designated as 'Southern Europe' by the lntergovernmental Panel on Climate Change (IPCC). The first method (direct interpolation of the grid points nearest the region analysed) gives a poor representation of the local climate. Its estimate of climate change simulated by different climate models is inconsistent. The success of the second method (timeslice), which uses a dynamical model to obtain the regional information, strongly depends on the horizontal resolution of the dynamical model. It provides the most reliable assessment of the regional climate, with the highest resolution. However, the computational expense of this high resolution limits the sample size. The third method (statistical downscaling) is an inexpensive tool for obtaining information on a regional scale. The problem is that this approach requires observational data sets to train the model. This limits the application of this method to well-observed quantities and regions. Both the time-slice and the statistical models indicate a lengthening of dry spells over Spain under CO2-doubling conditions.
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In a transient climate simulation of the last 500 years with a coupled atmosphere-ocean model driven by estimated solar variability, volcanic activity and atmospheric concentrations of greenhouse gases for the last centuries, the model... more
In a transient climate simulation of the last 500 years with a coupled atmosphere-ocean model driven by estimated solar variability, volcanic activity and atmospheric concentrations of greenhouse gases for the last centuries, the model simulates a climate colder than present conditions almost globally, and the degree of cooling is larger than most empirical reconstructions. The model simulates two clear minima of the global mean temperature around 1700 A.D. (the Late Maunder Minimum) and around 1820 A.D. (the Dalton Minimum). The temperature trends simulated after the recovery from these minima are as large as the observed warming in the 20th century. Additionally, in the Late Maunder Minimum the simulated temperature field in Europe agrees well with empirical reconstructions from proxy-data, with an intense drop of air-temperature in the North Atlantic ocean, an extensive sea-ice cover south of Greenland, lower salinity in North Atlantic at high latitudes, and reduced intensities of the Golf Stream and the Kuroshio Stream.
A statistical strategy to deduct regional~scale features from climate general circulation model (GCM) simulations has been designed and tested. The main idea is to interrelate the characteristic patterns of observed simultaneous... more
A statistical strategy to deduct regional~scale features from climate general circulation model (GCM) simulations has been designed and tested. The main idea is to interrelate the characteristic patterns of observed simultaneous variations of regional climate parameters and of large-scale atmospheric flow using the canonical correlation technique. The large-scale North Atlantic sea level pressure (SLP) is related to the regional, variable, winter (DJF) mean Iberian Peninsula rainfall. The skill of the resulting statistical model is shown by reproducing, to a good approximation, the winter mean Iberian rainfall from 1900 to present from the observed North Atlantic mean SLP distributions. It is shown that this observed relationship between these two variables is not well reproduced in the output of a general circulation model (GCM). The implications for Iberian rainfall changes as the response to increasing atmospheric greenhouse-gas concentrations simulated by two GCM experiments are examined with the proposed statistical model. In an instantaneous "2 CO~'' doubling experiment, using the simulated change of the mean North Atlantic SLP field to predict Iberian rainfall yields, there is an insignificant increase of area-averaged rainfall of l mm/month,
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With a state-of-the-art climate model, the effect of time varying solar and volcanic aerosol forcing has been simulated. During the winters 1675-1710, a marked global cooling was simulated. This event mimics, in terms of broad patterns... more
With a state-of-the-art climate model, the effect of time varying solar and volcanic aerosol forcing has been simulated. During the winters 1675-1710, a marked global cooling was simulated. This event mimics, in terms of broad patterns and time mean intensity, the strong cooling “Late Maunder Minimum” (LMM, 1675-1710) in Europe documented in various historical sources and early instrumental timeseries. The modelled LMM is causally related to the solar and volcanic forcing anomalies in the decades preceding and during the LMM creating an almost global cooling and large-scale circulation and sea ice coverage anomalies consistent with the phenomenon known as “Great Salinity Anomaly”.
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Mittelfristige Klimaprognose (MiKlip), an 8-yr German national research project on decadal climate prediction, is organized around a global prediction system comprising the Max Planck Institute Earth System Model (MPI-ESM) together with... more
Mittelfristige Klimaprognose (MiKlip), an 8-yr German national research project on decadal climate prediction, is organized around a global prediction system comprising the Max Planck Institute Earth System Model (MPI-ESM) together with an initialization procedure and a model evaluation system. This paper summarizes the lessons learned from MiKlip so far; some are purely scientific, others concern strategies and structures of research that target future operational use. Three prediction system generations have been constructed, characterized by alternative initialization strategies; the later generations show a marked improvement in hindcast skill for surface temperature. Hindcast skill is also identified for multiyear-mean European summer surface temperatures, extratropical cyclone tracks, the quasi-biennial oscillation, and ocean carbon uptake, among others. Regionalization maintains or slightly enhances the skill in European surface temperature inherited from the global model and...
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Research Interests: Environmental Science, Geology, Oceanography, Climatology, Climate modeling, and 10 moreMonsoon, Climate Dynamics, Atmospheric sciences, East Asian Monsoon, Tibetan Plateau, Asian monsoon, Intertropical Convergence Zone, WALKER CIRCULATION, Atlantic Meridional Overtunrning Circulation, and Orography
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The evidence of climate change from observations of the atmosphere and surface has grown significantly during recent years. At the same time new improved ways of characterizing and quantifying uncertainty have highlighted the challenges... more
The evidence of climate change from observations of the atmosphere and surface has grown significantly during recent years. At the same time new improved ways of characterizing and quantifying uncertainty have highlighted the challenges that remain for developing long-term global and regional climate quality data records. Currently, the obser¬vations of the atmosphere and surface indicate the following changes
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The main goal of this study is to obtain an improvement of the spring precipitation estimation at local scale, taking into account the atmospheric circulation on the Atlantic-European region, by a statistical downscaling procedure. First... more
The main goal of this study is to obtain an improvement of the spring precipitation estimation at local scale, taking into account the atmospheric circulation on the Atlantic-European region, by a statistical downscaling procedure. First we have fitted the precipitation amounts from the 19 stations with a HMM with 7 states. The stations are situated in localities crossed by the Danube or situated on the principal tributaries. The number of hidden states has been determined by means of BIC values. A NHMM has been applied then to precipitation occurrence associated with the information about atmospheric circulation over Atlantic-European region. The atmospheric circulation is quantified by the first 10 components of the decomposition in the EOFs or MEOFs. The predictors taking into account CWTs for SLP and the first summary variable from a SVD have also been tested. The atmospheric predictors are derived from SLP, geopotential, temperature, and specific and relative humidity at 850 hP...
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Research Interests: Earth Sciences, Geology, Human Evolution, Climate Change, Climatology, and 15 moreAtmospheric Modeling, East Africa, Climate modeling, Indian Ocean, Orbital forcing, Interdisciplinary research, Climate Modelling, Cenozoic, Eemian interglacial, General Circulation Models, Climate Model, Interglacial, Glacial, Eemian, and Global Climate Model
Cities demonstrate higher nocturnal temperatures than surrounding rural areas, which is called “urban heat island” (UHI) effect. Climate change projections also indicate increase in the frequency and intensity of heat waves, which will... more
Cities demonstrate higher nocturnal temperatures than surrounding rural areas, which is called “urban heat island” (UHI) effect. Climate change projections also indicate increase in the frequency and intensity of heat waves, which will intensify the UHI effect. As megacity Tehran is affected by severe heatwaves in summer, this study investigates its UHI characteristics and suggests some feasible mitigation strategies in order to reduce the air temperature and save energy. Temperature monitoring in Tehran shows clear evidence of the occurrence of the UHI effect, with a peak in July, where the urban area is circa 6 K warmer than the surrounding areas. The mobile measurements show a park cool island of 6-7 K in 2 central parks, which is also confirmed by satellite images. The effectiveness of three UHI mitigation strategies high albedo material (HAM), greenery on the surface and on the roofs (VEG), and a combination of them (HYBRID) has been studied using simulation with the microscale...
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The development of the East African Rift System (EARS) caused by tectonic forcing is supposed to influence the regional climate in East Africa. However, also changes in the Earth's orbital parameters have an influence on climate. To... more
The development of the East African Rift System (EARS) caused by tectonic forcing is supposed to influence the regional climate in East Africa. However, also changes in the Earth's orbital parameters have an influence on climate. To analyse the influence of both tectonic and orbital forcing a regional climate model is applied. The regional model used in this study is the non-hydrostatic CLM, which is the climate version of the regional weather prediction model of the German Meteorological Service and which is developed as a community effort of several universities and research centers (www.clm-community.eu). The regional simulations are driven by different global simulations performed with the coupled ocean-atmosphere general circulation model ECHO-G. To analyse the impact of the development of the EARS different topographies representing different stages of the development are applied in the models. The results indicate that the tectonic forcing has a strong impact on precipit...
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Research Interests: Environmental Science, Climate Change, Climatology, Climate, Downscaling, and 15 moreAtmospheric sciences, global Climate change, Developing Country, North Atlantic, Atmospheric Pressure, Iberia, Iberian Peninsula, Greenhouse Gas, Climate Model, Canonical Correlation, Mathematical Model, Atmospheric Circulation, Greenhouse Effect, Large Scale, and Business as Usual
Research Interests: Earth Sciences, Environmental Science, Climate Change, Climatology, Climate variability, and 11 moreClimate, Greenhouse Gas, Climate Model, Gcm, Greenhouse gases, Atmospheric Carbon Dioxide, Simulation Model, Climate Sensitivity, Intergovernmental Panel on Climate Change (IPCC), Model simulation, and Force Control
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Research Interests: Environmental Science, Oceanography, Climate Change, Climatology, Global Warming, and 15 moreClimate Dynamics, Atmospheric sciences, Performance Model, Land Surface Temperature, Conceptual Model, Climate Model, Northern Hemisphere, Annual Cycle, Atmospheric Carbon Dioxide, Latitude, Climate Sensitivity, present day, Seasonal Cycle, Model simulation, and Model performance
Research Interests: Environmental Science, Oceanography, Climatology, Atmospheric Modeling, Sea surface temperature, and 14 moreMonsoon, Climate Dynamics, Atmospheric sciences, Indian summer monsoon, High Resolution, El Nino-Southern Oscillation, Annual Cycle, Southern Oscillation, Simulation Model, Climate Simulation, Interannual Variability, parameter space, Seasonal Cycle, and Model simulation
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Research Interests: Environmental Science, Oceanography, Climatology, Atmospheric Modeling, Sea surface temperature, and 11 moreClimate Dynamics, Seasonality, Atmospheric sciences, Ocean Circulation, Air-Sea Interaction, Oscillations, Model development, Temperature measurement, Climate Model, Atmospheric Circulation, and Interannual Variability
Research Interests: Environmental Science, Oceanography, Climate Change, Climatology, Atmospheric Modeling, and 15 moreGlobal Warming, Climate Dynamics, Southern Ocean, Atmospheric sciences, Sea level rise, Ocean Circulation, Land Surface Temperature, Greenhouse Gas, Mathematical Model, Atmospheric Circulation, Greenhouse gases, Greenhouse Effect, Business as Usual, Mixed layer, and surface temperature
We propose a general fingerprint strategy to detect anthropogenic climate change and present application to near surface temperature trends. An expected time-space-variable pattern of anthropogenic climate change (the 'signal') is... more
We propose a general fingerprint strategy to detect anthropogenic climate change and present application to near surface temperature trends. An expected time-space-variable pattern of anthropogenic climate change (the 'signal') is identified through application of an appropriate optimally matched space-time filter (the 'fingerprint') to the observations. The signal and the fingerprint are represented in a space with sufficient observed and simulated data. The signal pattern is derived from a model-generated prediction of anthropogenic climate change. Application of the fingerprint filter to the data yields a scalar detection variable. The statistically optimal fingerprint is obtained by weighting the model-predicted pattern towards low-noise directions. A combination of model output and observations is used to estimate the noise characteristics of the detection variable, arising from the natural variability of climate in the absence of external forcing. We test then the null hypothesis that the observed climate change is part of natural climate variability. We conclude that a statistically significant externally induced warming has been observed, with the caveat of a possibly inadequate estimate of the internal climate variability. In order to attribute this warming uniquely to anthropogenic greenhouse gas forcing, more information on the climate's response to other forcing mechanisms (e.g. changes in solar radiation, volcanic or anthropogenic aerosols) and their interaction is needed. (orig./KW)Available from TIB Hannover: RR 1347(142) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman
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Research Interests: Mechanical Engineering, Aerospace Engineering, Environmental Science, Climatology, Space, and 13 moreAtmospheric sciences, Numerical Simulation, Orbital forcing, Land Surface Temperature, Temperature Distribution, North America, Climate Model, Solar radiation, Three Dimensional, Snow Cover, Eemian, Solar Variability, and surface temperature
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Research Interests: Earth Sciences, Geology, Climate Change, Climate variability, Heat Transport, and 15 moreDesertification, North Atlantic Oscillation, Holocene, Quaternary Science, Land Cover, Solar Activity, History and archaeology, Late Holocene, Little Ice Age, Northern Hemisphere, Greenhouse gases, Quaternary Science Reviews, Numerical Model, Boundary Condition, and European Alps
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A set of ensemble experiments has been run focusing on the Dalton minimum to identify the individual contributions of solar variability, volcanism, greenhouse gas concentration changes and the combination of these forcing on climate.... more
A set of ensemble experiments has been run focusing on the Dalton minimum to identify the individual contributions of solar variability, volcanism, greenhouse gas concentration changes and the combination of these forcing on climate. Additionally an idealized experiment has been carried out, where a sinusoidal forcing corresponding to the period of the Gleissberg-cycle, which led to the Dalton minimum, has been prescribed. Both, the volcanic and the solar forcing contribute to the global cooling during the Dalton minimum. The volcanic forcing, however, plays the major role for the global mean temperature. The temperature rise due to the greenhouse gases concentration increase counteracts this cooling only marginally. For the European region significant reduction of the solar constant (in the range of the imposed volcanic forcing) shift the NAO into the negative phase, thus enhancing the cooling over Europe. The experimental setup, which does not allow to take the volcanic aerosol fo...
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A dense monitoring network is vital for the reliable assessment of PM10 in different parts of an urban area. In this study, a new idea is employed for the re-construction of the 20 shut-down PM10 monitoring stations of Berlin. It... more
A dense monitoring network is vital for the reliable assessment of PM10 in different parts of an urban area. In this study, a new idea is employed for the re-construction of the 20 shut-down PM10 monitoring stations of Berlin. It endeavours to find the non-linear relationship between the hourly PM10 concentration of both the still operating and the shut-down PM10 monitoring stations by using a fuzzy modelling technique, called modified active learning method (MALM). In addition, the simulations were performed by using not only raw PM10 databases but also log-transformed PM10 databases for skewness reduction. According to the results of hourly PM10 simulation (root mean square error about 13.0 μg/m(3), correlation coefficient 0.88), the shut-down stations have been appropriately simulated and the idea of dense monitoring network development by the re-construction of the shut-down stations was realised. The results of simulations using raw and log-transformed databases showed that data transformation has no significant effect on the performance of MALM in the simulation of shut-down PM10 stations. By the combination of the 11 still operating stations and the 20 re-constructed stations, a dense monitoring network was generated for Berlin and was utilised for the calculation of the reliable monthly and mean annual PM10 concentration for five different PM10 zones in Berlin (the suburban-background, urban-background, urban-traffic, rural-background and suburban-traffic areas). The results showed that the mean annual concentration of PM10 at the five zones increased by about 13.0% in 2014 (26.3 μg/m(3)) in comparison with 2013 (23.3 μg/m(3)). Furthermore, the mean annual concentration of PM10 in the traffic lanes of the suburban (2013 25.0 μg/m(3), 2014 26.9 μg/m(3)) and urban (2013 27.7 μg/m(3), 2014 31.3 μg/m(3)) areas is about 14 and 20% higher than the PM10 concentration of suburban-background (2013 21.3 μg/m(3), 2014 24.5 μg/m(3)) and urban-background (2013 23.0 μg/m(3), 2014 26.1 μg/m(3)) areas, respectively.
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We investigate the assimilation of Tree-Ring-Width (TRW) chronologies into an atmospheric global climate model using Ensemble Kalman Filter (EnKF) techniques and a process-based tree-growth forward model as observation operator. Our... more
We investigate the assimilation of Tree-Ring-Width (TRW) chronologies into an atmospheric global climate model using Ensemble Kalman Filter (EnKF) techniques and a process-based tree-growth forward model as observation operator. Our results, within a perfect-model experiment setting, indicate that the non-linear response of tree-growth to surface temperature and soil moisture does deteriorate the operation of the time-averaged (EnKF) methodology. Moreover, this skill loss appeared significantly sensitive to the structure of growth rate function, used to represent the Principle of Limiting Factors (PLF)s within the forward model. On the other hand, it was observed that the error reduction achieved by assimilating a particular pseudo-TRW chronology is modulated by the strength of the yearly internal variability of the model at the chronology site. This result might help the dendrochronology community to optimize their sampling efforts. In our experiments, the ''online''...
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Abstract: In a transient climate simulation of the last 500 years with a coupled atmosphere-ocean modeldriven by estimated solar variability, volcanic activity and atmospheric concentrations of greenhousegases for the last centuries, the... more
Abstract: In a transient climate simulation of the last 500 years with a coupled atmosphere-ocean modeldriven by estimated solar variability, volcanic activity and atmospheric concentrations of greenhousegases for the last centuries, the model simulates a climate colder than present conditions almostglobally, and the degree of cooling is larger than most empirical reconstructions. The modelsimulates two clear minima of the global
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The improvement in resolution of climate models is always been mentioned as one of the most important factors when investigating past climatic conditions especially in order to evaluate and compare the results against proxy data.... more
The improvement in resolution of climate models is always been mentioned as one of the most important factors when investigating past climatic conditions especially in order to evaluate and compare the results against proxy data. <br><br> In this paper we present for the first time a set of high resolution simulations for different time slices of mid-to-late Holocene performed over Europe using a Regional Climate Model. Through a validation against a new pollen-based climate reconstructions dataset, covering almost all of Europe, we test the model performances for paleoclimatic applications and investigate the response of temperature to variations in the seasonal cycle of insolation, with the aim of clarifying earlier debated uncertainties, giving physically plausible interpretations of both the pollen data and the model results. <br><br> The results reinforce previous findings showing that summertime temperatures were driven mainly by changes in insolation a...
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ENVI-met is a computer program to simulate the microclimate in urban environment. It is a helpful program to simulate the urban climate in cities and can assist for environmental planning of new towns. One of the objective of... more
ENVI-met is a computer program to simulate the microclimate in urban environment. It is a helpful program to simulate the urban climate in cities and can assist for environmental planning of new towns. One of the objective of climatological part of the project Young Cities „Developing Energy-Efficient Urban Fabric in the Tehran-Karaj Region‟ is to simulate the micro climate (with 1m resolution) in 35ha area of new town Hashtgerd, which is located 65 km far from mega city Tehran
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Urban heat island (UHI) is one of the most important environmental hazards in the city that impact on quality of life. This might prove to be a very unsustainable factor, leading to excessive energy use for cooling and putting urban... more
Urban heat island (UHI) is one of the most important environmental hazards in the city that impact on quality of life. This might prove to be a very unsustainable factor, leading to excessive energy use for cooling and putting urban population at great morbidity and mortality risks and then to unliveable city. UHI is expected to pose increasing challenges for Tehran metropolitan area in the following decades, placing greater stress and impacts on multiple social and biophysical systems, including population health, social comfort, urban infrastructure, energy demand and water supplies. Therefore, we should take an action now to avoid possible serious environmental damage and design our cities to reduce the UHI effects significantly. The focus of this research was on the effects of two factors including vegetation cover and albedo of materials on the intensity of the UHI, through a case study on the Tehran metropolitan area. The original contributions of the research work were develo...
One of the objectives of climatological part of project Young Cities 'Developing Energy-Efficient Urban Fabric in the Tehran-Karaj Region' is to simulate the micro climate (with 1m resolution) in 35ha of new town Hashtgerd, which... more
One of the objectives of climatological part of project Young Cities 'Developing Energy-Efficient Urban Fabric in the Tehran-Karaj Region' is to simulate the micro climate (with 1m resolution) in 35ha of new town Hashtgerd, which is located 65 km far from mega city Tehran. The Project aims are developing, implementing and evaluating building and planning schemes and technologies which allow to plan and build sustainable, energy-efficient and climate sensible form mass housing settlements in arid and semi-arid regions ("energy-efficient fabric"). Climate sensitive form also means designing and planning for climate change and its related effects for Hashtgerd New Town. By configuration of buildings and open spaces according to solar radiation, wind and vegetation, climate sensitive urban form can create outdoor thermal comfort. To simulate the climate on small spatial scales, the micro climate model Envi-met has been used to simulate the micro climate in 35 ha. The E...
" A strategy using statistically optimal fingerpints to detect anthropogenic climate change is outlined and applied to near-surface temperature trends. The components of this strategy include observations, information about natural... more
" A strategy using statistically optimal fingerpints to detect anthropogenic climate change is outlined and applied to near-surface temperature trends. The components of this strategy include observations, information about natural climate variability, and a "guess pattern' ' representing the expected time-space pattem of anthropogenic climate change. 'I'he expected anthropogenic climate change is identified through projection of the observations onto an appropriate optimal fingerprint, yielding a scalar-detection variable. The statistically optimal fingerprint is obtained by weighting the components of the guess pattern (truncated to some small-dimensional space) toward low-noise directions. The null hypothesis that the observed climate change is part of natural climate variability is then tested.
This strategy is applied to detecting a greenhouse-gas-induced climate change in the spatial pattem of near-surface temperature trends defined for time intervals of 15-30 years. The expected pattem of climate change is derived from a transient simulation with a coupled ocean-atmosphere general circulation model. Global gridded near-surface temperature observations are used to represent the observed climate change. Information on the natural variability needed to establish the statistics of the detection variable is extracted from long control simulations of coupled ocean-atmosphere models and, additionally, from the observations themselves (from which an estimated greenhouse warming signal has been removed). While the model control simulations contain only variability caused by the internal dynamics of the atmosphere-ocean system, the observations additionally contain the response to various extemal forcings (e.g., volcanic eruptions, changes in solar radiation, and residual anthropogenic forcing). The resulting estimate of climate noise has large uncertainties but is qualitatively the best the authors can presently offer.
The null hypothesis that the latest observed 2O-yr and 3O-yr trend of near-surface temperature (ending in 1994) is part of natural variability is rejected with a risk of less than 2.5% to 5% (the 5% level is derived from the variability of one model control simulation dominated by a questionable extreme event). In other words, the probability that the warming is due to our estimated natural variability is less than 2.5% to 5%. The increase in the signal-to-noise ratio by optimization of the fingerprint is of the order of 10%-30% in most cases.
The predicted signals are dominated by the global mean component; the pattem correlation excluding the global mean is positive but not very high. Both the evolution of the detection variable and also the pattem correlation results are consistent with the model prediction for greenhouse-gas-induced climate change. However, in order to attribute the observed warming uniquely to anthropogenic greenhouse gas forcing, more information on the climate's response to other forcing mechanisms (e.g., changes in solar radiation, volcanic, or anthropogenic sulfate aerosols) and their interaction is needed.
It is concluded that a statistically significant externally induced warming has been observed, but our caveat that the estimate of the internal climate variability is still uncertain is emphasized"
This strategy is applied to detecting a greenhouse-gas-induced climate change in the spatial pattem of near-surface temperature trends defined for time intervals of 15-30 years. The expected pattem of climate change is derived from a transient simulation with a coupled ocean-atmosphere general circulation model. Global gridded near-surface temperature observations are used to represent the observed climate change. Information on the natural variability needed to establish the statistics of the detection variable is extracted from long control simulations of coupled ocean-atmosphere models and, additionally, from the observations themselves (from which an estimated greenhouse warming signal has been removed). While the model control simulations contain only variability caused by the internal dynamics of the atmosphere-ocean system, the observations additionally contain the response to various extemal forcings (e.g., volcanic eruptions, changes in solar radiation, and residual anthropogenic forcing). The resulting estimate of climate noise has large uncertainties but is qualitatively the best the authors can presently offer.
The null hypothesis that the latest observed 2O-yr and 3O-yr trend of near-surface temperature (ending in 1994) is part of natural variability is rejected with a risk of less than 2.5% to 5% (the 5% level is derived from the variability of one model control simulation dominated by a questionable extreme event). In other words, the probability that the warming is due to our estimated natural variability is less than 2.5% to 5%. The increase in the signal-to-noise ratio by optimization of the fingerprint is of the order of 10%-30% in most cases.
The predicted signals are dominated by the global mean component; the pattem correlation excluding the global mean is positive but not very high. Both the evolution of the detection variable and also the pattem correlation results are consistent with the model prediction for greenhouse-gas-induced climate change. However, in order to attribute the observed warming uniquely to anthropogenic greenhouse gas forcing, more information on the climate's response to other forcing mechanisms (e.g., changes in solar radiation, volcanic, or anthropogenic sulfate aerosols) and their interaction is needed.
It is concluded that a statistically significant externally induced warming has been observed, but our caveat that the estimate of the internal climate variability is still uncertain is emphasized"