The influence of anthropogenic emissions on aerosol distributions and the hydrological cycle are examined with a focus on monsoon precipitation over the Indian subcontinent, during January 2001 to December 2005, using the European Centre for Medium-Range Weather Forecasts-Hamburg (ECHAM5.5) general circulation model extended by the Hamburg Aerosol Module (HAM). The seasonal variability of aerosol optical depth (AOD) retrieved from the MODerate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellite is broadly well simulated (R 0.6–0.85) by the model. The spatial distribution and seasonal cycle of the precipitation observed over the Indian region are reasonably well simulated (R 0.5 to 0.8) by the model, while in terms of absolute magnitude, the model underestimates precipitation, in particular in the south-west (SW) monsoon season. The model simulates significant anthropogenic aerosol-induced changes in clear-sky net surface solar radiation (dimming greater than -7 W m-2), which agrees well with the observed trends over the Indian region. A statistically significant decreasing precipitation trend is simulated only for the SWmonsoon season over the central-north Indian region, which is consistent with the observed seasonal trend over the Indian region. In the model, this decrease results from a reduction in convective precipitation, where there is an increase in stratiform cloud droplet number concentration (CDNC) and solar dimming that resulted from increased stability and reduced evaporation. Similarities in spatial patterns suggest that surface cooling, mainly by the aerosol indirect effect, is responsible for this reduction in convective activity. When changes in large-scale dynamics are allowed by slightly disturbing the initial state of the atmosphere, aerosol absorption in addition leads to a further stabilization of the lower troposphere, further reducing convective precipitation.

The scale dependency of variance of total water mixing ratio is explored by analyzing data from a general circulation model (GCM), a numerical weather prediction model (NWP), and large-eddy simulations (LESs). For clarification, direct numerical simulation (DNS) data are additionally included, but the focus is placed on defining a general scaling behavior for scales ranging from global down to cloud resolving. For this, appropriate power-law exponents are determined by calculating and approximating the power density spectrum. The large-scale models (GCM and NWP) show a consistent scaling with a power-law exponent of approximately 22. For the high-resolution LESs, the slope of the power density spectrum shows evidence of being somewhat steeper, although the estimates are more uncertain. Also the transition between resolved and parameterized scales in a current GCM is investigated. Neither a spectral gap nor a strong scale break is found, but a weak scale break at high wavenumbers cannot be excluded. The evaluation of the parameterized total water variance of a state-of-the-art statistical scheme shows that the scale dependency is underestimated by this parameterization. This study and the discovered general scaling behavior emphasize the need for a development of scale-dependent parameterizations.

This study explores the viability of parameter estimation in the comprehensive general circulation model ECHAM6 using ensemble Kalman filter data assimilation techniques. Four closure parameters of the cumulus-convection scheme are estimated using increasingly less idealized scenarios ranging from perfect-model experiments to the assimilation of conventional observations. Updated parameter values from experiments with real observations are used to assess the error of the model state on short 6 h forecasts and on climatological timescales. All parameters converge to their default values in single parameter perfect-model experiments. Estimating parameters simultaneously has a neutral effect on the success of the parameter estimation, but applying an imperfect model deteriorates the assimilation performance. With real observations, single parameter estimation generates the default parameter value in one case, converges to different parameter values in two cases, and diverges in the fourth case. The implementation of the two converging parameters influences the model state: Although the estimated parameter values lead to an overall error reduction on short timescales, the error of the model state increases on climatological timescales.

In this paper we analyse aerosol loading and its direct radiative effects over the Bay of Bengal (BoB) and Arabian Sea (AS) regions for the Integrated Campaign on Aerosols, gases and Radiation Budget (ICARB) undertaken during 2006, using satellite data from the MODerate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellites, the Aerosol Index from the Ozone Monitoring Instrument (OMI) on board the Aura satellite, and the European-Community Hamburg (ECHAM5.5) general circulation model extended by Hamburg Aerosol Module (HAM). By statistically comparing with large-scale satellite data sets, we firstly show that the aerosol properties measured during the ship-based ICARB campaign and simulated by the model are representative for the BoB and AS regions and the pre-monsoon season. In a second step, the modelled aerosol distributions were evaluated by a comparison with the measurements from the ship-based sunphotometer, and the satellite retrievals during ICARB. It is found that the model broadly reproduces the observed spatial and temporal variability in aerosol optical depth (AOD) over BoB and AS regions. However, AOD was systematically underestimated during high-pollution episodes, especially in the BoB leg. We show that this underprediction of AOD is mostly because of the deficiencies in the coarse mode, where the model shows that dust is the dominant component. The analysis of dust AOD along with the OMI Aerosol Index indicate that missing dust transport that results from too low dust emission fluxes over the Thar Desert region in the model caused this deficiency. Thirdly, we analysed the spatio-temporal variability of AOD comparing the ship-based observations to the large-scale satellite observations and simulations. It was found that most of the variability along the track was from geographical patterns, with a minor influence by single events. Aerosol fields were homogeneous enough to yield a good statistical agreement between satellite data at a 1° spatial, but only twice-daily temporal resolution, and the shipbased sunphotometer data at a much finer spatial, but dailyaverage temporal resolution. Examination of the satellite data further showed that the year 2006 is representative for the five-year period for which satellite data were available. Finally, we estimated the clear-sky solar direct aerosol radiative forcing (DARF). We found that the cruise represents well the regional-seasonal mean forcings. Constraining simulated forcings using the observed AOD distributions yields a robust estimate of regional-seasonal mean DARF of −8.6, −21.4 and +12.9Wm−2 at the top of the atmosphere (TOA), at the surface (SUR) and in the atmosphere (ATM), respectively, for the BoB region, and over the AS, of, −6.8, −12.8, and +6Wm−2 at TOA, SUR, and ATM, respectively.

Zugl.: Stuttgart, Univ., Diss., 2007.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第19976号 / 工博第4220号 / 新制||工||1653(附属図書館) / 33072 / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 立川 康人, 教授 堀 智晴, 准教授 KIM SUNMIN / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

ROCKE-3D is a contemporary Global Circulation Model allowing research into the complex processes behind the climate of planets. Using ROCKE-3D one can construct a model coupling atmosphere, land, and ocean revealing how the climate of a planet evolves over time. When constructing a model using ROCKE-3D, 2 different types of oceans can be used, one shallow without horizontal heat transfer and one fully coupled dynamic ocean. Simulations created using the different ocean types give rise to different results. In this project, the fractional habitability of the model 'planets' will be calculated using various methods in order to evaluate the differences between ocean types in ROCKE-3D simulations. There is also a hope to better understand how parameters such as rotation period and insolation, are affected when using different ocean types. The results show a large difference in predicted habitability fraction using two approximations for the ocean heat transport indicating that the Qflux approximation produces unrealistic models and should be avoided. / ROCKE-3D är en modern Global Circulation Model som tillåter forskning in i de komplexa processer som bygger planeters klimat. Vid användning av ROCKE-3D kan modeller som kopplar atmosfärer, land och hav konstrueras, detta kan avslöja hur en planets klimat utvecklas över tid. När en model konstrueras med ROCKE-3D kan 2 olika typer av hav användas, ett utan horisontell värmeöverföring som kallas för ett "Qflux" hav och ett fullt kopplat dynamiskt hav. Simulationer skapade med de olika havstyperna ger skillnad i resultat. I det här projektet, beräknas modell-planeternas fractional habitability för att evaluera skillnaden mellan havstyp i ROCKE-3D simulationer. Det finns även ett hopp för en bättre förståelse av hur parametrar, rotationsperiod och solinstrålning, påverkar när det är att föredra användningen av en viss havstyp. Resultaten visar att skillnaden i ""fractional habitability" mellan simulationer skapta med de 2 havstyperna minskar när solinstrålningen ökar, vilket visar att användandet av ett "Qflux" hav i skapandet av simulationer vid låg solinstrålning borde avrådas.

There is ample growth in scientific evidence about climate change. Since, hydrometeorological processes are sensitive to climate variability and changes, ascertaining the linkages and feedbacks between the climate and the hydrometeorological processes becomes critical for environmental quality, economic development, social well-being etc. As the river basin integrates some of the important systems like ecological and socio-economic systems, the knowledge of plausible implications of climate change on hydrometeorology of a river basin will not only increase the awareness of how the hydrological systems may change over the coming century, but also prepare us for adapting to the impacts of climate changes on water resources for sustainable management and development. In general, quantitative climate impact studies are based on several meteorological variables and possible future climate scenarios. Among the meteorological variables, sic “cardinal” variables are identified as the most commonly used in impact studies (IPCC, 2001). These are maximum and minimum temperatures, precipitation, solar radiation, relative humidity and wind speed. The climate scenarios refer to plausible future climates, which have been constructed for explicit use for investigating the potential consequences of anthropogenic climate alterations, in addition to the natural climate variability. Among the climate scenarios adapted in impact assessments, General circulation model(GCM) projections based on marker scenarios given in Intergovernmental Panel on Climate Change’s (IPCC’s) Special Report on Emissions Scenarios(SRES) have become the standard scenarios. The GCMs are run at coarse resolutions and therefore the output climate variables for the various scenarios of these models cannot be used directly for impact assessment on a local(river basin)scale. Hence in the past, several methodologies such as downscaling and disaggregation have been developed to transfer information of atmospheric variables from the GCM scale to that of surface meteorological variables at local scale. The most commonly used downscaling approaches are based on transfer functions to represent the statistical relationships between the large scale atmospheric variables(predictors) and the local surface variables(predictands). Recently Support vector machine (SVM) is proposed, and is theoretically proved to have advantages over other techniques in use such as transfer functions. The SVM implements the structural risk minimization principle, which guarantees the global optimum solution. Further, for SVMs, the learning algorithm automatically decides the model architecture. These advantages make SVM a plausible choice for use in downscaling hydrometeorological variables. The literature review on use of transfer function for downscaling revealed that though a diverse range of transfer functions has been adopted for downscaling, only a few studies have evaluated the sensitivity of such downscaling models. Further, no studies have so far been carried out in India for downscaling hydrometeorological variables to a river basin scale, nor there was any prior work aimed at downscaling CGCM3 simulations to these variables at river basin scale for various IPCC SRES emission scenarios. The research presented in the thesis is motivated to assess the impact of climate change on streamflow at river basin scale for the various IPCC SRES scenarios (A1B, A2, B1 and COMMIT), by integrating implications of climate change on all the six cardinal variables. The catchment of Malaprabha river (upstream of Malaprabha reservoir) in India is chosen as the study area to demonstrate the effectiveness of the developed models, as it is considered to be a climatically sensitive region, because though the river originates in a region having high rainfall it feeds arid and semi-arid regions downstream. The data of the National Centers for Environmental Prediction (NCEP), the third generation Canadian Global Climate Model (CGCM3) of the Canadian Center for Climate Modeling and Analysis (CCCma), observed hydrometeorological variables, Digital Elevation model (DEM), land use/land cover map, and soil map prepared based on PAN and LISS III merged, satellite images are considered for use in the developed models. The thesis is broadly divided into four parts. The first part comprises of general introduction, data, techniques and tools used. The second part describes the process of assessment of the implications of climate change on monthly values of each of the six cardinal variables in the study region using SVM downscaling models and k-nearest neighbor (k-NN) disaggregation technique. Further, the sensitivity of the SVM downscaling models to the choice of predictors, predictand, calibration period, season and location is evaluated. The third part describes the impact assessment of climate change on streamflow in the study region using the SWAT hydrologic model, and SVM downscaling models. The fourth part presents summary of the work presented in the thesis, conclusions draws, and the scope for future research. The development of SVM downscaling model begins with the selection of probable predictors (large scale atmospheric variables). For this purpose, the cross-correlations are computed between the probable predictor variables in NCEP and GCM data sets, and the probable predictor variables in NCEP data set and the predictand. A pool of potential predictors is then stratified (which is optional and variable dependant) based on season and or location by specifying threshold values for the computed cross-correlations. The data on potential predictors are first standardized for a baseline period to reduce systemic bias (if any) in the mean and variance of predictors in GCM data, relative to those of the same in NCEP reanalysis data. The standardized NCEP predictor variables are then processed using principal component analysis (PCA) to extract principal components (PCs) which are orthogonal and which preserve more than 98% of the variance originally present in them. A feature vector is formed for each month using the PCs. The feature vector forms the input to the SVM model, and the contemporaneous value of predictand is its output. Finally, the downscaling model is calibrated to capture the relationship between NCEP data on potential predictors (i.e feature vectors) and the predictand. Grid search procedure is used to find the optimum range for each of the parameters. Subsequently, the optimum values of parameters are obtained from the selected ranges, using the stochastic search technique of genetic algorithm. The SVM model is subsequently validated, and then used to obtain projections of predictand for simulations of CGCM3. Results show that precipitation, maximum and minimum temperature, relative humidity and cloud cover are projected to increase in future for A1B, A2 and B1 scenarios, whereas no trend is discerned with theCOMMIT. The projected increase in predictands is high for A2 scenario and is least for B1 scenario. The wind speed is not projected to change in future for the study region for all the aforementioned scenarios. The solar radiation is projected to decrease in future for A1B, A2 and B1 scenarios, whereas no trend is discerned with the COMMIT. To assess the monthly streamflow responses to climate change, two methodologies are considered in this study namely (i) downscaling and disaggregating the meteorological variables for use as inputs in SWAT and (ii) directly downscaling streamflow using SVM. SWAT is a physically based, distributed, continuous time hydrological model that operates on a daily time scale. The hydrometeorologic variables obtained using SVM downscaling models are disaggregated to daily scale by using k-nearest neighbor method developed in this study. The other inputs to SWAT are DEM, land use/land cover map, soil map, which are considered to be the same for the present and future scenarios. The SWAT model has projected an increase in future streamflows for A1B, A2 andB1 scenarios, whereas no trend is discerned with the COMMIT. The monthly projections of streamflow at river basin scale are also obtained using two SVM based downscaling models. The first SVM model (called one-stage SVM model) considered feature vectors prepared based on monthly values of large scale atmospheric variables as inputs, whereas the second SVM model (called two-stage SVM model) considered feature vectors prepared from the monthly projections of cardinal variables as inputs. The trend in streamflows projected using two-stage SVM model is found to be similar to that projected by SWAT for each of the scenarios considered. The streamflow is not projected to change for any of the scenarios considered with the one-stage SVM downscaling model. The relative performance of the SWAT and the two SVM downscaling models in simulating observed streamflows is evaluated. In general, all the three models are able to simulate the streamflows well. Nevertheless, the performance of SWAT model is better. Further, among the two SVM models, the performance of one-stage streamflow downscaling model is marginally better than that of the two-stage streamflow downscaling model.

This thesis examines the structure of the Tropical Easterly Jet (TEJ) in a General Circulation Model (GCM). The TEJ is observed only during the Indian summer monsoon period and is strongest during July and August. The jet structure simulated by an atmospheric GCM (CAM-3.1) in July has been compared with reanalysis data. The simulated TEJ was displaced westward by ~ 25◦ when compared to observations. The removal of orography had no impact on the jet structure. This demonstrated that the Tibetan Plateau did not play an important role in the location and structure of the jet. The changes in cumulus scheme in the GCM had a large influence on the location of the jet maxima. To examine the factors which control the location and structure of the jet, a series of experiments were conducted using an aqua-planet version of the model. The impact of different sea surface temperature (SST) profiles was studied. The rainfall in the GCM was primarily in the regions where the SST attained a maximum. By altering the location of SST maximum (and hence the rainfall maximum), the impact of location of rainfall maximum on the location and structure of the jet was studied. When the rainfall maximum was located close to the equator, it did not generate a strong jet but had an influence on the vertical structure of the jet. A large number of simulations were conducted with multiple rainfall maxima and the need for these was demonstrated since only then was the observed jet structure well simulated. Based on the simulations, it was concluded that the simulation of the TEJ by CAM-3.1 was unrealistic because of large unrealistic rainfall over Saudi Arabia in this GCM. Equatorial heating has been shown to be important to simulate proper jet structure. The zonal structure of the jet was also influenced by rainfall in the Pacific Ocean. Although the aqua-planet configuration of the CAM-3.1 GCM provided several useful insights, the simulation was not perfect on account of errors in the simulation of the temperature profile in the lower troposphere. An ideal-physics configuration of the GCM was used. This removed the cumulus physics and instead imposed the observed heating pro-files. Both upper tropospheric friction and radiative-convective atmospheric temperatures were required to simulate the TEJ. The problems with the simulation of structure in the jet exit region was corrected by using radiative-convective atmospheric temperatures that were qualitatively similar to those observed in northern hemisphere summer time. The ideal-physics configuration reconfirmed that the Saudi Arabian rainfall was responsible for the westward shift of the TEJ in the simulations. The ideal-physics simulations showed that the simple analytical model proposed by Gillin1980 was not suitable for the simulation of TEJ. The above the simulations indicate that a shift in the location of the jet is related to a shift in the rainfall pattern. Based on this insight one would expect that the jet location will be different in good and bad monsoon periods. This is indeed the case. In July 2002 the Indian monsoon failed after beginning well in June. In June the TEJ is consequently located west ward compared to July. The same situation prevails even in good and poor monsoon years. In a good monsoon year (July 1988) the jet maximum is located westward when compared to a bad monsoon year (July 2002). In this thesis we have clearly demonstrated the role of anomalous rainfall on the location of the TEJ. This thesis has shown that an accurate simulation of the TEJ depends upon the accurate simulation of various rainfall centers that act as multiple heat sources in the atmosphere. The rainfall in the equatorial region does not influence the strength of the TEJ but alters the vertical structure of the jet. The strength the jet is dependent on the intensity of rainfall and the latitudinal distance from the equator. The complex vertical structure of the jet is not simulated by simple analytical models of the jet.

Particulate matter suspended in air (i.e. aerosol particles) exerts a substantial influence on the climate of our planet and is responsible for causing severe public health problems in many regions across the globe. Human activities have altered the natural and anthropogenic emissions of aerosol particles through direct emissions or indirectly by modifying natural sources. The climate effects of the latter have been largely overlooked. Humans have dramatically altered the land surface of the planet causing changes in natural aerosol emissions from vegetated areas. Regulation on anthropogenic and natural aerosol emissions have the potential to affect the climate on regional to global scales. Furthermore, the regional climate effects of aerosol particles could potentially be very different than the ones caused by other climate forcers (e.g. well mixed greenhouse gases). The main objective of this work was to investigate the climatic effects of land use and air pollution via aerosol changes. Using numerical model simulations it was found that land use changes in the past millennium have likely caused a positive radiative forcing via aerosol climate interactions. The forcing is an order of magnitude smaller and has an opposite sign than the radiative forcing caused by direct aerosol emissions changes from other human activities. The results also indicate that future reductions of fossil fuel aerosols via air quality regulations may lead to an additional warming of the planet by mid-21st century and could also cause an important Arctic amplification of the warming. In addition, the mean position of the intertropical convergence zone and the Asian monsoon appear to be sensitive to aerosol emission reductions from air quality regulations. For these reasons, climate mitigation policies should take into consideration aerosol air pollution, which has not received sufficient attention in the past.