Multi-site downscaling of maximum and minimum daily temperature using support vector machine

Climate change impact assessment studies involve downscaling large-scale atmospheric predictor variables (LSAPVs) simulated by general circulation models (GCMs) to site-scale meteorological variables. This article presents a least-square support vector machine (LS-SVM)-based methodology for multi-site downscaling of maximum and minimum daily temperature series. The methodology involves (1) delineation of sites in the study area into clusters based on correlation structure of predictands, (2) downscaling LSAPVs to monthly time series of predictands at a representative site identified in each of the clusters, (3) translation of the downscaled information in each cluster from the representative site to that at other sites using LS-SVM inter-site regression relationships, and (4) disaggregation of the information at each site from monthly to daily time scale using k-nearest neighbour disaggregation methodology. Effectiveness of the methodology is demonstrated by application to data pertaining to four sites in the catchment of Beas river basin, India. Simulations of Canadian coupled global climate model (CGCM3.1/T63) for four IPCC SRES scenarios namely A1B, A2, B1 and COMMIT were downscaled to future projections of the predictands in the study area. Comparison of results with those based on recently proposed multivariate multiple linear regression (MMLR) based downscaling method and multi-site multivariate statistical downscaling (MMSD) method indicate that the proposed method is promising and it can be considered as a feasible choice in statistical downscaling studies. The performance of the method in downscaling daily minimum temperature was found to be better when compared with that in downscaling daily maximum temperature. Results indicate an increase in annual average maximum and minimum temperatures at all the sites for A1B, A2 and B1 scenarios. The projected increment is high for A2 scenario, and it is followed by that for A1B, B1 and COMMIT scenarios. Projections, in general, indicated an increase in mean monthly maximum and minimum temperatures during January to February and October to December.

Development and Evaluation of Statistical Downscaling Models for Monthly Precipitation

Several statistical downscaling models have been developed in the past couple of decades to assess the hydrologic impacts of climate change by projecting the station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs). This paper presents and compares different statistical downscaling models that use multiple linear regression (MLR), positive coefficient regression (PCR), stepwise regression (SR), and support vector machine (SVM) techniques for estimating monthly rainfall amounts in the state of Florida. Mean sea level pressure, air temperature, geopotential height, specific humidity, U wind, and V wind are used as the explanatory variables/predictors in the downscaling models. Data for these variables are obtained from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis dataset and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model, version 3 (CGCM3) GCM simulations. The principal component analysis (PCA) and fuzzy c-means clustering method (FCM) are used as part of downscaling model to reduce the dimensionality of the dataset and identify the clusters in the data, respectively. Evaluation of the performances of the models using different error and statistical measures indicates that the SVM-based model performed better than all the other models in reproducing most monthly rainfall statistics at 18 sites. Output from the third-generation CGCM3 GCM for the A1B scenario was used for future projections. For the projection period 2001-10, MLR was used to relate variables at the GCM and NCEP grid scales. Use of MLR in linking the predictor variables at the GCM and NCEP grid scales yielded better reproduction of monthly rainfall statistics at most of the stations (12 out of 18) compared to those by spatial interpolation technique used in earlier studies.

Modeling of solar radiation management: a comparison of simulations using reduced solar constant and stratospheric sulphate aerosols

The climatic effects of Solar Radiation Management (SRM) geoengineering have been often modeled by simply reducing the solar constant. This is most likely valid only for space sunshades and not for atmosphere and surface based SRM methods. In this study, a global climate model is used to evaluate the differences in the climate response to SRM by uniform solar constant reduction and stratospheric aerosols. Our analysis shows that when global mean warming from a doubling of CO2 is nearly cancelled by both these methods, they are similar when important surface and tropospheric climate variables are considered. However, a difference of 1 K in the global mean stratospheric (61-9.8 hPa) temperature is simulated between the two SRM methods. Further, while the global mean surface diffuse radiation increases by similar to 23 % and direct radiation decreases by about 9 % in the case of sulphate aerosol SRM method, both direct and diffuse radiation decrease by similar fractional amounts (similar to 1.0 %) when solar constant is reduced. When CO2 fertilization effects from elevated CO2 concentration levels are removed, the contribution from shaded leaves to gross primary productivity (GPP) increases by 1.8 % in aerosol SRM because of increased diffuse light. However, this increase is almost offset by a 15.2 % decline in sunlit contribution due to reduced direct light. Overall both the SRM simulations show similar decrease in GPP (similar to 8 %) and net primary productivity (similar to 3 %). Based on our results we conclude that the climate states produced by a reduction in solar constant and addition of aerosols into the stratosphere can be considered almost similar except for two important aspects: stratospheric temperature change and the consequent implications for the dynamics and the chemistry of the stratosphere and the partitioning of direct versus diffuse radiation reaching the surface. Further, the likely dependence of global hydrological cycle response on aerosol particle size and the latitudinal and height distribution of aerosols is discussed.

Regional hydrological impacts of climate change: implications for water management in India

Climate change is most likely to introduce an additional stress to already stressed water systems in developing countries. Climate change is inherently linked with the hydrological cycle and is expected to cause significant alterations in regional water resources systems necessitating measures for adaptation and mitigation. Increasing temperatures, for example, are likely to change precipitation patterns resulting in alterations of regional water availability, evapotranspirative water demand of crops and vegetation, extremes of floods and droughts, and water quality. A comprehensive assessment of regional hydrological impacts of climate change is thus necessary. Global climate model simulations provide future projections of the climate system taking into consideration changes in external forcings, such as atmospheric carbon-dioxide and aerosols, especially those resulting from anthropogenic emissions. However, such simulations are typically run at a coarse scale, and are not equipped to reproduce regional hydrological processes. This paper summarizes recent research on the assessment of climate change impacts on regional hydrology, addressing the scale and physical processes mismatch issues. Particular attention is given to changes in water availability, irrigation demands and water quality. This paper also includes description of the methodologies developed to address uncertainties in the projections resulting from incomplete knowledge about future evolution of the human-induced emissions and from using multiple climate models. Approaches for investigating possible causes of historically observed changes in regional hydrological variables are also discussed. Illustrations of all the above-mentioned methods are provided for Indian regions with a view to specifically aiding water management in India.

Theoretical and experimental studies of the bell-jar-top inductively coupled plasma

The present paper describes a systematic study of argon plasmas in a bell-jar inductively coupled plasma (ICP) source over the range of pressure 5-20 mtorr and power input 0.2-0.5 kW, Experimental measurements as well as results of numerical simulations are presented. The models used in the study include the well-known global balance model (or the global model) as well as a detailed two-dimensional (2-D) fluid model of the system, The global model is able to provide reasonably accurate values for the global electron temperature and plasma density, The 2-D model provides spatial distributions of various plasma parameters that make it possible to compare with data measured in the experiments, The experimental measurements were obtained using a tuned Langmuir double-probe technique to reduce the RF interference and obtain the light versus current (I-V) characteristics of the probe. Time-averaged electron temperature and plasma density were measured for various combinations of pressure and applied RF power, The predictions of the 2-D model were found to be in good qualitative agreement with measured data, It was found that the electron temperature distribution T-e was more or less uniform in the chamber, It was also seen that the electron temperature depends primarily on pressure, but is almost independent of the power input, except in the very low-pressure regime. The plasma density goes up almost linearly with the power input.

Forecasting Climate Impacts on Future Production of Commercially Exploited Fish and Shellfish

Foreword [pdf, < 0.1 MB] Acknowledgements PHASE 1 [pdf, 0.2 MB] Summary of the PICES/NPRB Workshop on Forecasting Climate Impacts on Future Production of Commercially Exploited Fish and Shellfish (July 19–20, 2007, Seattle, U.S.A.) Background Links to Other Programs Workshop Format Session I. Status of climate change scenarios in the PICES region Session II. What are the expected impacts of climate change on regional oceanography and what are some scenarios for these drivers for the next 10 years? Session III. Recruitment forecasting Session IV. What models are out there? How is climate linked to the model? Session V. Assumptions regarding future fishing scenarios and enhancement activities Session VI Where do we go from here? References Appendix 1.1 List of Participants PHASE 2 [pdf, 0.7 MB] Summary of the PICES/NPRB Workshop on Forecasting Climate Impacts on Future Production of Commercially Exploited Fish and Shellfish (October 30, 2007, Victoria, Canada) Background Workshop Agenda Forecast Feasibility Format of Information Modeling Approaches Coupled bio-physical models Stock assessment projection models Comparative approaches Similarities in Data Requests Opportunities for Coordination with Other PICES Groups and International Efforts BACKGROUND REPORTS PREPARED FOR THE PHASE 2 WORKSHOP Northern California Current (U.S.) groundfish production by Melissa Haltuch Changes in sablefish (Anoplopoma fimbria) recruitment in relation to oceanographic conditions by Michael J. Schirripa Northern California Current (British Columbia) Pacific cod (Gadus macrocephalus) production by Caihong Fu and Richard Beamish Northern California Current (British Columbia) sablefish (Anoplopoma fimbria) production by Richard Beamish Northern California Current (British Columbia) pink (Oncorhynchus gorbuscha) and chum (O. keta) salmon production by Richard Beamish Northern California Current (British Columbia) ocean shrimp (Pandalus jordani) production by Caihong Fu Alaska salmon production by Anne Hollowed U.S. walleye pollock (Theragra chalcogramma) production in the eastern Bering Sea and Gulf of Alaska by Kevin Bailey and Anne Hollowed U.S. groundfish production in the eastern Bering Sea by Tom Wilderbuer U.S. crab production in the eastern Bering Sea by Gordon H. Kruse Forecasting Japanese commercially exploited species by Shin-ichi Ito, Kazuaki Tadokoro and Yasuhiro Yamanka Russian fish production in the Japan/East Sea by Yury Zuenko, Vladimir Nuzhdin and Natalia Dolganova Chum salmon (Oncorhynchus keta) production in Korea by Sukyung Kang, Suam Kim and Hyunju Seo Jack mackerel (Trachurus japonicus) production in Korea by Jae Bong Lee and Chang-Ik Zhang Chub mackerel (Scomber japonicus) production in Korea by Jae Bong Lee, Sukyung Kang, Suam Kim, Chang-Ik Zhang and Jin Yeong Kim References Appendix 2.1 List of Participants PHASE 3 [pdf, < 0.1 MB] Summary of the PICES Workshop on Linking Global Climate Model Output to (a) Trends in Commercial Species Productivity and (b) Changes in Broader Biological Communities in the World’s Oceans (May 18, 2008, Gijón, Spain) Appendix 3.1 List of Participants Appendix 3.2 Workshop Agenda (Document contains 101 pages)

Anomalies in North American climate: the South Asian-tropical west Pacific connection

How do tropical heating fluctuations create North American climate anomalies? We propose some answers using the results from a simplified global atmospheric model. We find that the South Asian-tropical west Pacific area is especially effective at stimulating North American responses. The relatively strong tropical/extratropical interaction between these two areas is the result of two major processes acting on the Rossby wave signal induced by the tropical heating fluctuations. These factors are: 1) Wave guiding by the Asian-north Pacific subtropical jet; and 2) Wave amplification within unstable regions of the jet flank. These factors allow relatively small, remote, and short-term tropical fluctuations to have relatively large impacts on North American climate.

COASTAL SEA-LEVEL AND THE LARGE-SCALE CLIMATE STATE - A DOWNSCALING EXERCISE FOR THE JAPANESE ISLANDS

A major problem which is envisaged in the course of man-made climate change is sea-level rise. The global aspect of the thermal expansion of the sea water likely is reasonably well simulated by present day climate models; the variation of sea level, due to variations of the regional atmospheric forcing and of the large-scale oceanic circulation, is not adequately simulated by a global climate model because of insufficient spatial resolution. A method to infer the coastal aspects of sea level change is to use a statistical ''downscaling'' strategy: a linear statistical model is built upon a multi-year data set of local sea level data and of large-scale oceanic and/or atmospheric data such as sea-surface temperature or sea-level air-pressure. We apply this idea to sea level along the Japanese coast. The sea level is related to regional and North Pacific sea-surface temperature and sea-level air pressure. Two relevant processes are identified. One process is the local wind set-up of water due to regional low-frequency wind anomalies; the other is a planetary scale atmosphere-ocean interaction which takes place in the eastern North Pacific.

青藏高原及邻区面波频散反演--岩石圈-软流层体系结构研究

The Qinghai-Tibet Plateau lies in the place of the continent-continent collision between Indian and Eurasian plates. Because of their interaction the shallow and deep structures are very complicated. The force system forming the tectonic patterns and driving tectonic movements is effected together by the deep part of the lithosphere and the asthenosphere. It is important to study the 3-D velocity structures, the spheres and layers structures, material properties and states of the lithosphere and the asthenosphere for getting knowledge of their formation and evolution, dynamic process, layers coupling and exchange of material and energy. Based on the Rayleigh wave dispersion theory, we study the 3-D velocity structures, the depths of interfaces and thicknesses of different layers, including the crust, the lithosphere and the asthenosphere, the lithosphere-asthenosphere system in the Qinghai-Tibet Plateau and its adjacent areas. The following tasks include: (1)The digital seismic records of 221 seismic events have been collected, whose magnitudes are larger than 5.0 over the Qinghai-Tibet Plateau and its adjacent areas. These records come from 31 digital seismic stations of GSN , CDSN、NCDSN and part of Indian stations. After making instrument response calibration and filtering, group velocities of fundamental mode of Rayleigh waves are measured using the frequency-time analysis (FTAN) to get the observed dispersions. Furthermore, we strike cluster average for those similar ray paths. Finally, 819 dispersion curves (8-150s) are ready for dispersion inversion. (2)From these dispersion curves, pure dispersion data in 2°×2° cells of the areas (18°N-42°N, 70°E-106°E) are calculated by using function expansion method, proposed by Yanovskaya. The average initial model has been constructed by taking account of global AK135 model along with geodetic, geological, geophysical, receiving function and wide-angle reflection data. Then, initial S-wave velocity structures of the crust and upper mantle in the research areas have been obtained by using linear inversion (SVD) method. (3)Taking the results of the linear inversion as the initial model, we simultaneously invert the S wave velocities and thicknesses by using non-linear inversion (improved Simulated Annealing algorithm). Moreover, during the temperature dropping the variable-scale models are used. Comparing with the linear results, the spheres and layers by the non-linear inversion can be recognized better from the velocity value and offset. (4)The Moho discontinuity and top interface of the asthenosphere are recognized from the velocity value and offset of the layers. The thicknesses of the crust, lithosphere and asthenosphere are gained. These thicknesses are helpful to studying the structural differentia between the Qinghai-Tibet Plateau and its adjacent areas and among geologic units of the plateau. The results of the inversion will provide deep geophysical evidences for studying deep dynamical mechanism and exploring metal mineral resource and oil and gas resources. The following conclusions are reached by the distributions of the S wave velocities and thicknesses of the crust, lithosphere and asthenosphere, combining with previous researches. (1)The crust is very thick in the Qinghai-Tibet Plateau, varying from 60 km to 80 km. The lithospheric thickness in the Qinghai-Tibet Plateau is thinner (130-160 km) than its adjacent areas. Its asthenosphere is relatively thicker, varies from 150 km to 230 km, and the thickest area lies in the western Qiangtang. India located in south of Main Boundary thrust has a thinner crust (32-38 km), a thicker lithosphere of about 190 km and a rather thin asthenosphere of only 60 km. Sichuan and Tarim basins have the crust thickness less than 50km. Their lithospheres are thicker than the Qinghai-Tibet Plateau, and their asthenospheres are thinner. (2)The S-wave velocity variation pattern in the lithosphere-asthenosphere system has band-belted distribution along east-westward. These variations correlate with geology structures sketched by sutures and major faults. These sutures include Main Boundary thrust (MBT), Yarlung-Zangbo River suture (YZS), Bangong Lake-Nujiang suture (BNS), Jinshajiang suture (JSJS), Kunlun edge suture (KL). In the velocity maps of the upper and middle crust, these sutures can be sketched. In velocity maps of 250-300 km depth, MBT, BNS and JSJS can be sketched. In maps of the crustal thickness, the lithospheric thickness and the asthenospheric thickness, these sutures can be still sketched. In particular, MBT can be obviously resolved in these velocity maps and thickness maps. (3)Since the collision between India and Eurasian plate, the “loss” of surface material arising from crustal shortening is caused not only by crustal thickening but also by lateral extrusion material. The source of lateral extrusion lies in the Qiangtang block. These materials extrude along the JSJS and BNS with both rotation and dispersion in Daguaiwan. Finally, it extends toward southeast direction. (4)There is the crust-mantle transition zone of no distinct velocity jump in the lithosphere beneath the Qiangtang Terrane. It has thinner lithosphere and developed thicker asthenosphere. It implies that the crust-mantle transition zone of partial melting is connected with the developed asthenosphere. The underplating of asthenosphere may thin the lithosphere. This buoyancy might be the main mechanism and deep dynamics of the uplift of the Qinghai-Tibet hinterland. At the same time, the transport of hot material with low velocity intrudes into the upper mantle and the lower crust along cracks and faults forming the crust-mantle transition zone.

基于三重震相波形模拟研究亚洲东北部上地幔过渡带速度结构

Both the global and regional P wave tomographic studies have revealed significant deep structural heterogeneities in subduction zone regions. In particular, low-velocity anomalies have been observed beneath the descending high-velocity slabs in a number of subduction zones. The limited resolution at large depths and possible trade-off between the high and low velocities, however, make it difficult to substantiate this feature and evaluate the vertical extent of the low-velocity structure. From broadband waveform modeling of triplicated phases near the 660-km discontinuity for three deep events, we constrained both the P and SH wave velocity structures around the base of the upper mantle in northeast Asia. For the two events beneath the southern Kurile, the rays traveled through the lowermost transition zone and uppermost lower mantle under the descending Pacific slab. Our preferred models consistently suggest normal-to-lower P and significantly low SH velocities above and below the 660-km discontinuity extending to about 760-km depth compared with the global IASP91 model, corroborating previous observations for a slow structure underneath the slab. In contrast, both high P and SH velocity anomalies are shown in our preferred models for the Japan subduction zone region, likely reflecting the structural feature of a slab stagnant above the 660-km discontinuity. The velocity jumps across the 660-km discontinuity were found to be on average 4.5% and 7% for P and S waves under the south Kurile, and 3% and 6% under the Japan subduction zone. The respective velocity contrasts in the two regions are consistent with mineralogical models for colder slab interior and hotter under-slab areas. Based on mineral physics data, the depth-averaged ~1.5% P and ~2.5% SH velocity differences in the depth range of 560-760 km between the two regions could be primarily explained by a 350~450K temperature variation, although the presence of about 0.5wt%~1wt% water might also contribute to the subtle velocity variations near the base of the transition zone in the southern Kurile. From our modeling results, we speculate that the slow structure in the southern Kurile may be correlated to the low velocity zone observed previously around the 410-km discontinuity under Northern Honshu. Both are probably associated with a thermal anomaly rooted in the lower mantle beneath the subduction zone in northeast Asia.

电离层参量M(3000)F2和hmF2的经验正交函数方法建模研究

The ionospheric parameter M(3000)F2 (the so-called transmission factor or the propagation factor) is important not only in practical applications such as frequency planning for radio-communication but also in ionospheric modeling. This parameter is strongly anti-correlated with the ionospheric F2-layer peak height hmF2，a parameter often used as a key anchor point in some widely used empirical models of the ionospheric electron density profile (e.g., in IRI and NeQuick models). Since hmF2 is not easy to obtain from measurements and M(3000)F2 can be routinely scaled from ionograms recorded by ionosonde/digisonde stations distributed globally and its data has been accumulated for a long history, usually the value of hmF2 is calculated from M(3000)F2 using the empirical formula connecting them. In practice, CCIR M(3000)F2 model is widely used to obtain M(3000)F2 value. However, recently some authors found that the CCIR M(3000)F2 model has remarkable discrepancies with the measured M(3000)F2, especially in low-latitude and equatorial regions. For this reason, the International Reference Ionosphere (IRI) research community proposes to improve or update the currently used CCIR M(3000)F2 model. Any efforts toward the improvement and updating of the current M(3000)F2 model or newly development of a global hmF2 model are encouraged. In this dissertation, an effort is made to construct the empirical models of M(3000)F2 and hmF2 based on the empirical orthogonal function (EOF) analysis combined with regression analysis method. The main results are as follows: 1. A single station model is constructed using monthly median hourly values of M(3000)F2 data observed at Wuhan Ionospheric Observatory during the years of 1957–1991 and compared with the IRI model. The result shows that EOF method is possible to use only a few orders of EOF components to represent most of the variance of the original data set. It is a powerful method for ionospheric modeling. 2. Using the values of M(3000)F2 observed by ionosondes distributed globally, data at grids uniformly distributed globally were obtained by using the Kriging interpolation method. Then the gridded data were decomposed into EOF components using two different coordinates: (1) geographical longitude and latitude; (2) modified dip (Modip) and local time. Based on the EOF decompositions of the gridded data under these two coordinates systems, two types of the global M(3000)F2 model are constructed. Statistical analysis showed that the two types of the constructed M(3000)F2 model have better agreement with the observational M(3000)F2 than the M(3000)F2 model currently used by IRI. The constructed models can represent the global variations of M(3000)F2 better. 3. The hmF2 data used to construct the hmF2 model were converted from the observed M(3000)F2 based on the empirical formula connecting them. We also constructed two types of the global hmF2 model using the similar method of modeling M(3000)F2. Statistical analysis showed that the prediction of our models is more accurate than the model of IRI. This demonstrated that using EOF analysis method to construct global model of hmF2 directly is feasible. The results in this thesis indicate that the modeling technique based on EOF expansion combined with regression analysis is very promising when used to construct the global models of M(3000)F2 and hmF2. It is worthwhile to investigate further and has the potential to be used to the global modeling of other ionospheric parameters.

Multiple environmental controls on phytoplankton growth strategies determine adaptive responses of the N : P ratio

The controls on the 'Redfield' N:P stoichiometry of marine phytoplankton and hence the N:P ratio of the deep ocean remain incompletely understood. Here, we use a model for phytoplankton ecophysiology and growth, based on functional traits and resource-allocation trade-offs, to show how environmental filtering, biotic interactions, and element cycling in a global ecosystem model determine phytoplankton biogeography, growth strategies and macromolecular composition. Emergent growth strategies capture major observed patterns in marine biomes. Using a new synthesis of experimental RNA and protein measurements to constrain per-ribosome translation rates, we determine a spatially variable lower limit on adaptive rRNA:protein allocation and hence on the relationship between the largest cellular P and N pools. Comparison with the lowest observed phytoplankton N:P ratios and N:P export fluxes in the Southern Ocean suggests that additional contributions from phospholipid and phosphorus storage compounds play a fundamental role in determining the marine biogeochemical cycling of these elements.

Projecting marine fish production and catch potential in Bangladesh in the 21st century under long-term environmental change and management scenarios

The fisheries sector is crucial to the Bangladeshi economy and wellbeing, accounting for 4.4% of national Gross Domestic Product (GDP) and 22.8% of agriculture sector production, and supplying ca.60% of the national animal protein intake. Fish is vital to the 16 million Bangladeshis living near the coast, a number that has doubled since the 1980s. Here we develop and apply tools to project the long term productive capacity of Bangladesh marine fisheries under climate and fisheries management scenarios, based on downscaling a global climate model, using associated river flow and nutrient loading estimates, projecting high resolution changes in physical and biochemical ocean properties, and eventually projecting fish production and catch potential under different fishing mortality targets. We place particular interest on Hilsa shad (Tenualosa ilisha), which accounts for ca.11% of total catches, and Bombay duck (Harpadon nehereus), a low price fish that is the second highest catch in Bangladesh and is highly consumed by low income communities. It is concluded that the impacts of climate change, under greenhouse emissions scenario A1B, are likely to reduce the potential fish production in the Bangladesh Exclusive Economic Zone (EEZ) by less than 10%. However, these impacts are larger for the two target species. Under sustainable management practices we expect Hilsa shad catches to show a minor decline in potential catch by 2030 but a significant (25%) decline by 2060. However, if overexploitation is allowed catches are projected to fall much further, by almost 95% by 2060, compared to the Business as Usual scenario for the start of the 21st century. For Bombay duck, potential catches by 2060 under sustainable scenarios will produce a decline of less than 20% compared to current catches. The results demonstrate that management can mitigate or exacerbate the effects of climate change on ecosystem productivity.

Neural network based control for synchronous generators

In this paper, a Radial Basis Function neural network based AVR is proposed. A control strategy which generates local linear models from a global neural model on-line is used to derive controller feedback gains based on the Generalised Minimum Variance technique. Testing is carried out on a micromachine system which enables evaluation of practical implementation of the scheme. Constraints imposed by gathering training data, computational load, and memory requirements for the training algorithm are addressed.

Optimisation of Kinetic Parameters for an After-treatment Catalyst

Mathematical modelling has become an essential tool in the design of modern catalytic systems. Emissions legislation is becoming increasingly stringent, and so mathematical models of aftertreatment systems must become more accurate in order to provide confidence that a catalyst will convert pollutants over the required range of conditions. 
Automotive catalytic converter models contain several sub-models that represent processes such as mass and heat transfer, and the rates at which the reactions proceed on the surface of the precious metal. Of these sub-models, the prediction of the surface reaction rates is by far the most challenging due to the complexity of the reaction system and the large number of gas species involved. The reaction rate sub-model uses global reaction kinetics to describe the surface reaction rate of the gas species and is based on the Langmuir Hinshelwood equation further developed by Voltz et al. [1] The reactions can be modelled using the pre-exponential and activation energies of the Arrhenius equations and the inhibition terms. 
The reaction kinetic parameters of aftertreatment models are found from experimental data, where a measured light-off curve is compared against a predicted curve produced by a mathematical model. The kinetic parameters are usually manually tuned to minimize the error between the measured and predicted data. This process is most commonly long, laborious and prone to misinterpretation due to the large number of parameters and the risk of multiple sets of parameters giving acceptable fits. Moreover, the number of coefficients increases greatly with the number of reactions. Therefore, with the growing number of reactions, the task of manually tuning the coefficients is becoming increasingly challenging. 
In the presented work, the authors have developed and implemented a multi-objective genetic algorithm to automatically optimize reaction parameters in AxiSuite®, [2] a commercial aftertreatment model. The genetic algorithm was developed and expanded from the code presented by Michalewicz et al. [3] and was linked to AxiSuite using the Simulink add-on for Matlab. 
The default kinetic values stored within the AxiSuite model were used to generate a series of light-off curves under rich conditions for a number of gas species, including CO, NO, C_{3H8 and C3H6. These light-off curves were used to generate an objective function.} 
This objective function was used to generate a measure of fit for the kinetic parameters. The multi-objective genetic algorithm was subsequently used to search between specified limits to attempt to match the objective function. In total the pre-exponential factors and activation energies of ten reactions were simultaneously optimized. 
The results reported here demonstrate that, given accurate experimental data, the optimization algorithm is successful and robust in defining the correct kinetic parameters of a global kinetic model describing aftertreatment processes.