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La classificació de la circulació atmosfèrica s’ha abordat de diferents maneres: mètodes manuals, mixtes, basats en l’estadística multivariant, entre d’altres. En aquest treball es fa un extens i actualitzat recorregut per aquests mètodes i es fa una proposta metodològica basada en l’anàlisi per components principals: el mètode de les puntuacions extremes. Aquesta metodologia, basada en l’aproximació tradicional que empra la matriu tipus S, proposa una estandardització espacial de les dades originals (malles), l’ús dels valors més elevats de les puntuacions factorials per a la determinació del nombre de grups de la classificació i els seus centroides, i finalment l’assignació dels casos a algun dels grups sense l’ús de les iteracions característiques dels mètodes de k-mitjanes. La proposta s’aplica posteriorment a diferents casos pràctics relacionats amb diferents enfocs de les ciències atmosfèriques: meteorologia de muntanya, variabilitat climàtica i canvi climàtic, cartografia climàtica i riscos meteorològics. Aquests casos pràctics es presenten a través de quatre articles publicats a diferents revistes internacionals. El primer cas fa una caracterització de les nevades intenses al Principat d’Andorra a partir de la classificació de la pressió en superfície a l’àmbit de l’Europa Occidental, obtenint-se set patrons de circulació que expliquen la varietat de situacions associades a nevades superiors a 30cm en 24 hores en algun lloc del Principat. La detecció d’aquesta variabilitat, i la detecció de situacions de la mateixa component però amb diferencies en el gradient de pressió fan del catàleg obtingut com una eina interessant en la predicció meteorològica en aquest sector del Pirineu. Aquest article va ser publicat a la revista International Journal of Climatology l’any 2005. El segon cas fa una classificació genèrica de la circulació atmosfèrica a l’Europa Occidental, entre 1960 i 2001 i emprant, com en el cas anterior, el reanàlisi de l’NCEP-NCAR (1 dada diària i 2.5º de resolució espacial). S’obtenen 20 patrons que expliquen de forma molt completa la variabilitat de la circulació atmosfèrica en aquest sector. A més, per cadascun dels patrons obtinguts s’ha calculat la seva distribució anual i la seva tendència al llarg del període. Precisament sobre aquest darrer punt, alguns patrons mostren tendències estadísticament significatives que apunten cap a un increment de les situacions de bloqueig anticiclònic durant les dècades estudiades. L’article fou publicat a International Journal of Climatology al 2006. El tercer cas aborda la obtenció de cartografia de temperatura i precipitació en zones d’orografia complexa (Andorra) relacionada amb els patrons de circulació obtinguts en el treball anterior. Els resultats, 80 mapes d’alta resolució calculats amb el mètode de la regressió múltiple, mostren la variabilitat climàtica local basada en la discriminació que estableix un catàleg de la circulació atmosfèrica. L’article fou publicat a la revista Theoretical and Applied Climatology al 2009. Finalment, el quart cas aborda l’activitat dels llamps al sector d’Andorra i Catalunya, però en aquest cas classificant una malla de pressió en superfície de més resolució temporal i espacial (dades cada 6 hores i a 1º). S’obtenen nou tipus de circulació atmosfèrica que representen situacions de caràcter advectiu (definides sobretot pel context sinòptic), dominades per la dinàmica mesoescalar (normalment efecte del dipol orogràfic pirinenc), o situacions de caràcter tèrmic dominades per la manca de gradient bàric. Aquest treball fou publicat a Physics and Chemistry of the Earth al 2010. Els resultats mostren que la proposta del mètode de les puntuacions extremes és una opció prou robusta per a la obtenció de tipus de circulació atmosfèrica i que pot ser aplicada a diferents resolucions temporals i espacials. Aquest mètode ha estat implementat al programari lliure COST733class desenvolupat en l’àmbit del projecte europeu COST733 (2005-2010) centrat en la comparació i avaluació de mètodes de classificació de la circulació atmosfèrica. / Atmospheric circulation types classification: a method proposal and applications The classification of atmospheric circulation has been addressed via different methodological approaches: manual methods, mixed methods, based on multivariate techniques, etc. In this work we present an extensive overview of the main existing typologies of circulation type classification methods for finally propose a new approach based on principal component analysis: the method of extreme scores. This new approach highlight the spatial standardization of the original data (gridded data), the use of the factor scores for determining the total amount of circulation types and their centroids, and finally support the non use of iterations for the final classification of all the cases into the groups via the Euclidian distance. The proposal is then applied to heavy snow precipitation events in Andorra (Pyrenees), to climate variability analysis over Western Europe, to the interpolation of climate variables in mountain areas (temperature and precipitation in Andorra) based on circulation types, and for analyze relevant lightning activity over the sector of Catalonia and Andorra. These applications are presented trough the corresponding publications in international scientific journals, and exemplify the usefulness of the atmospheric circulation classification methods for the study of mountain meteorology, climate variability and climate change, climate mapping in areas of complex topography using GIS techniques, and weather hazards situations. In addition, these applications also demonstrate the goodness of the proposed method of the extreme scores. This method of the extreme scores has been included in the classification software COST733class developed by the European project COST733 that was focused on the comparison and evaluation of circulation type classification methods.

General Circulation Models (GCMs) are tools designed to simulate time series of climate variables globally, accounting for effects of greenhouse gases in the atmosphere. They attempt to represent the physical processes in the atmosphere, ocean, cryosphere and land surface. They are currently the most credible tools available for simulating the response of the global climate system to increasing greenhouse gas concentrations, and to provide estimates of climate variables (e.g. air temperature, precipitation, wind speed, pressure etc.) on a global scale. GCMs demonstrate a significant skill at the continental and hemispheric spatial scales and incorporate a large proportion of the complexity of the global system; they are, however, inherently unable to represent local subgrid-scale features and dynamics. The spatial scale on which a GCM can operate (e.g., 3.75° longitude x 3.75° latitude for Coupled Global Climate Model, CGCM2) is very coarse compared to that of a hydrologic process (e.g., precipitation in a region, streamflow in a river etc.) of interest in the climate change impact assessment studies. Moreover, accuracy of GCMs, in general, decreases from climate related variables, such as wind, temperature, humidity and air pressure to hydrologic variables such as precipitation, evapotranspiration, runoff and soil moisture, which are also simulated by GCMs. These limitations of the GCMs restrict the direct use of their output in hydrology. This thesis deals with developing statistical downscaling models to assess climate change impacts and methodologies to address GCM and scenario uncertainties in assessing climate change impacts on hydrology. Downscaling, in the context of hydrology, is a method to project the hydrologic variables (e.g., rainfall and streamflow) at a smaller scale based on large scale climatological variables (e.g., mean sea level pressure) simulated by a GCM. A statistical downscaling model is first developed in the thesis to predict the rainfall over Orissa meteorological subdivision from GCM output of large scale Mean Sea Level Pressure (MSLP). Gridded monthly MSLP data for the period 1948 to 2002, are obtained from the National Center for Environmental Prediction/ National Center for Atmospheric Research (NCEP/NCAR) reanalysis project for a region spanning 150 N -250 N in latitude and 800 E -900 E in longitude that encapsulates the study region. The downscaling model comprises of Principal Component Analysis (PCA), Fuzzy Clustering and Linear Regression. PCA is carried out to reduce the dimensionality of the larger scale MSLP and also to convert the correlated variables to uncorrelated variables. Fuzzy clustering is performed to derive the membership of the principal components in each of the clusters and the memberships obtained are used in regression to statistically relate MSLP and rainfall. The statistical relationship thus obtained is used to predict the rainfall from GCM output. The rainfall predicted with the GCM developed by CCSR/NIES with B2 scenario presents a decreasing trend for non-monsoon period, for the case study. Climate change impact assessment models developed based on downscaled GCM output are subjected to a range of uncertainties due to both ‘incomplete knowledge’ and ‘unknowable future scenario’ (New and Hulme, 2000). ‘Incomplete knowledge’ mainly arises from inadequate information and understanding about the underlying geophysical process of global change, leading to limitations in the accuracy of GCMs. This is also termed as GCM uncertainty. Uncertainty due to ‘unknowable future scenario’ is associated with the unpredictability in the forecast of socio-economic and human behavior resulting in future Green House Gas (GHG) emission scenarios, and can also be termed as scenario uncertainty. Downscaled outputs of a single GCM with a single climate change scenario represent a single trajectory among a number of realizations derived using various GCMs and scenarios. Such a single trajectory alone can not represent a future hydrologic scenario, and will not be useful in assessing hydrologic impacts due to climate change. Nonparametric methods are developed in the thesis to model GCM and scenario uncertainty for prediction of drought scenario with Orissa meteorological subdivision as a case study. Using the downscaling technique described in the previous paragraph, future rainfall scenarios are obtained for all available GCMs and scenarios. After correcting for bias, equiprobability transformation is used to convert the precipitation into Standardized Precipitation Index-12 (SPI-12), an annual drought indicator, based on which a drought may be classified as a severe drought, mild drought etc. Disagreements are observed between different predictions of SPI-12, resulting from different GCMs and scenarios. Assuming SPI-12 to be a random variable at every time step, nonparametric methods based on kernel density estimation and orthonormal series are used to determine the nonparametric probability density function (pdf) of SPI-12. Probabilities for different categories of drought are computed from the estimated pdf. It is observed that there is an increasing trend in the probability of extreme drought and a decreasing trend in the probability of near normal conditions, in the Orissa meteorological subdivision. The single valued Cumulative Distribution Functions (CDFs) obtained from nonparametric methods suffer from limitations due to the following: (a) simulations for all scenarios are not available for all the GCMs, thus leading to a possibility that incorporation of these missing climate experiments may result in a different CDF, (b) the method may simply overfit to a multimodal distribution from a relatively small sample of GCMs with a limited number of scenarios, and (c) the set of all scenarios may not fully compose the universal sample space, and thus, the precise single valued probability distribution may not be representative enough for applications. To overcome these limitations, an interval regression is performed to fit an imprecise normal distribution to the SPI-12 to provide a band of CDFs instead of a single valued CDF. Such a band of CDFs represents the incomplete nature of knowledge, thus reflecting the extent of what is ignored in the climate change impact assessment. From imprecise CDFs, the imprecise probabilities of different categories of drought are computed. These results also show an increasing trend of the bounds of the probability of extreme drought and decreasing trend of the bounds of the probability of near normal conditions, in the Orissa meteorological subdivision. Water resources planning requires the information about future streamflow scenarios in a river basin to combat hydrologic extremes resulting from climate change. It is therefore necessary to downscale GCM projections for streamflow prediction at river basin scales. A statistical downscaling model based on PCA, fuzzy clustering and Relevance Vector Machine (RVM) is developed to predict the monsoon streamflow of Mahanadi river at Hirakud reservoir, from GCM projections of large scale climatological data. Surface air temperature at 2m, Mean Sea Level Pressure (MSLP), geopotential height at a pressure level of 500 hecto Pascal (hPa) and surface specific humidity are considered as the predictors for modeling Mahanadi streamflow in monsoon season. PCA is used to reduce the dimensionality of the predictor dataset and also to convert the correlated variables to uncorrelated variables. Fuzzy clustering is carried out to derive the membership of the principal components in each of the clusters and the memberships thus obtained are used in RVM regression model. RVM involves fewer number of relevant vectors and the chance of overfitting is less than that of Support Vector Machine (SVM). Different kernel functions are used for comparison purpose and it is concluded that heavy tailed Radial Basis Function (RBF) performs best for streamflow prediction with GCM output for the case considered. The GCM CCSR/NIES with B2 scenario projects a decreasing trend in future monsoon streamflow of Mahanadi which is likely to be due to high surface warming. A possibilistic approach is developed next, for modeling GCM and scenario uncertainty in projection of monsoon streamflow of Mahanadi river. Three GCMs, Center for Climate System Research/ National Institute for Environmental Studies (CCSR/NIES), Hadley Climate Model 3 (HadCM3) and Coupled Global Climate Model 2 (CGCM2) with two scenarios A2 and B2 are used for the purpose. Possibilities are assigned to GCMs and scenarios based on their system performance measure in predicting the streamflow during years 1991-2005, when signals of climate forcing are visible. The possibilities are used as weights for deriving the possibilistic mean CDF for the three standard time slices, 2020s, 2050s and 2080s. It is observed that the value of streamflow at which the possibilistic mean CDF reaches the value of 1 reduces with time, which shows reduction in probability of occurrence of extreme high flow events in future and therefore there is likely to be a decreasing trend in the monthly peak flow. One possible reason for such a decreasing trend may be the significant increase in temperature due to climate warming. Simultaneous occurrence of reduction in Mahandai streamflow and increase in extreme drought in Orissa meteorological subdivision is likely to pose a challenge for water resources engineers in meeting water demands in future.

This thesis examines the development and validation of Canadian Land Surface Scheme (CLASS) for various wetland landscapes individually, along with an evaluation of modelled results over a heterogeneous surface with airborne observations. A further statistical analysis of the effects of land surface classification procedures over the study area and their influence on modelled results is performed. CLASS is tested over individual wetland types: bog, fen and marsh in a stand-alone (non-GCM coupled) mode. Atmospheric conditions are provided for the eight site locations from tower measured data, while each surface is parameterized within the model from site specific measurements. Resulting model turbulent and radiative flux output is then statistically evaluated against observed tower data. Findings show that while CLASS models vascular dominated wetland areas (fen and marsh) quite well, non-vascular wetlands (bogs) are poorly represented, even with improved soil descriptions. At times when the water table is close to the surface, evaporation is greatly overestimated, whereas lowered water tables generate a vastly underestimated latent heat flux. Because CLASS does not include a moisture transfer scheme applicable for non-vascular vegetation, the description of this vegetation type as either a vascular plant or bare soil appears inappropriate. / CLASS was then tuned for a specific bog location found in the Hudson Bay Lowland (HBL) during the Northern Wetlands Study (NOWES). With bog surfaces better described within the model, testing of CLASS over a highly heterogeneous 169 km2 HBL region is then undertaken. The model is first modified for lake and pond surfaces and then separate runs for bog, fen, lake and tree/shrub categories is undertaken. Using a GIS, the test region under which airborne flux measurements are available is divided into 104 grid cells and proportions of each surface type are calculated within each cell. Findings indicate that although the modelled grid average radiation and flux values are reasonably well reproduced (4% error for net radiation, 10% for latent heat flux and 30% for sensible heat flux), spatial agreement between modelled and observed grid cells is disappointing. (Abstract shortened by UMI.)

Large-scale atmospheric disturbances play important roles in determining the general circulation of the atmosphere during the North Pacific boreal winter. A number of scientific questions have been raised due to these disturbances’ spatial and temporal complexity as well as the hydrological implication associated with them. In this dissertation, the principal goal is to further improve our understanding of the atmospheric high frequency (HF) and intermediate frequency (IF) disturbances active over the North Pacific. The study focuses on their energetics, intraseasonal and interannual variability, and the resulting hydrological impact over the eastern North Pacific and Western U.S. including extreme events. To delineate the characteristics of HF and IF disturbances in the troposphere, we first derive a new set of equations governing the local eddy kinetic energy (EKE), and assess the critical processes maintaining local budgets of the HF and IF EKE. The diagnosis assesses the 3-D patterns of energy flux convergence (EFC), barotropic conversion (BT), baroclinic conversion (BC), and cross-frequency eddy-eddy interaction (CFEI). The local EKE budget analysis is followed by an investigation of the modulation of HF and IF eddy activity by different modes of low frequency climate variability. On interannual timescales, the response of various local energetic processes to El Niño-Southern Oscillation (ENSO) determines the HF and IF EKE anomalies and the role of CFEI process is important in producing these anomalies. Also on interannual timescales, winter precipitation deficits associated with suppressed cyclonic activity, i.e., negative HF EKE anomalies, are linked to severe droughts over the U.S. Southern Great Plain (SGP) region. The suppressed cyclonic activity is, in turn, tied to phase changes in the West Pacific (WP) teleconnection pattern. On intraseasonal timescales, variations in HF disturbances (a.k.a. storm tracks) over the North Pacific are closely coupled with tropical convection anomalies induced by the Madden-Julian Oscillation (MJO), and partly drive larger scale intraseasonal flow anomalies in this region through eddy-eddy interactions. Anomalous HF eddy activity induces subseasonal transitions between “wet” and “dry” regimes over the west coast of North America. Also on intraseasonal timescales, the East Asian cold surge (EACS) is found to provide a remote forcing of the winter precipitation anomalies in the western U.S. This modulation is achieved through “atmospheric rivers” (ARs), which are narrow channels of concentrated moisture transport in the atmosphere and are responsible for over 70% of the extreme precipitation events in the western U.S.. EACS effectively modulates the IF disturbance activity over the North Pacific, and the anomalous IF disturbances lead to the formation of an AR over the eastern North Pacific that ultimately induces precipitation anomalies in the western U.S. Analyses of the simulations from the NCAR Community Climate System Model version 4 (CCSM4) demonstrate that the connections among the EACS, AR and western U.S. precipitation are better captured by a model with higher spatial resolutions. The improved simulation of these connections is achieved mainly through a better representation of the IF disturbances, and the associated scale-interaction processes in the higher resolution model.

Abstract This thesis studies the long-term relation between the solar wind driven energetic particle forcing into the atmosphere and the tropospheric circulation in the Northern Hemisphere winter. The work covers the period of more than one hundred years since the turn of the 20th century to present. The thesis makes a statistical analysis of satellite measurements of precipitating energetic electrons, sunspot number data and geomagnetic activity, and compares them with temperature and pressure measurements made at the Earth's surface. Recent results, both observational and from chemistry climate models, have indicated significant effects in the Earth's middle atmosphere due to the energetic electrons precipitating from the magnetosphere. These effects include the formation of reactive hydrogen and nitrogen oxides in the high latitude mesosphere and the depletion of ozone caused by them. Ozone is a radiatively active and important gas, which affects the thermal structure and dynamics of the middle atmosphere. Accordingly, the depletion of ozone can intensify the large scale stratospheric circulation pattern called the polar vortex. Winter weather conditions on the surface have been shown to be dependent on the polar vortex strength. This thesis shows that there is a significant relation between the average fluxes of medium energy (ten to hundred keVs) precipitating electrons and surface temperatures in parts of the Northern Hemisphere in winter time. Temperatures are positively correlated with electron fluxes in North Eurasia and negatively correlated in Greenland during the period 1980-2010 which is covered by direct satellite observations of precipitating particles. This difference is especially notable when major sudden stratospheric warmings and the quasi-biennial oscillation (QBO), which both are known to affect the polar vortex strength, are taken into account. When extended to the late 19th century, the analysis shows that a similar temperature pattern is predominated during the declining phase of the sunspot cycle. The high speed solar wind streams and energetic particle precipitation typically maximize also at the declining phase of the solar cycle. This specific temperature pattern is related to the variability of the northern annular mode (NAM), which is the most significant circulation pattern in the Northern Hemisphere winter. Before the space era, geomagnetic activity measured by ground observations can be used as a proxy for energetic particle precipitation. Earlier studies have found a significant positive correlation between geomagnetic activity and NAM since the 1960s. We find that, when the QBO measured at 30 hPa height is in the easterly phase, a positive correlation is extended to the beginning of 1900s. We also show that high geomagnetic activity causes a stronger effect in the Northern Hemisphere winter than high sunspot activity, especially in the Atlantic and Eurasia. A comprehensive knowledge of the Earth's climate system and all its drivers is crucial for the future projection of climate. Solar variability effects have been estimated to produce only a small factor to the global climate change. However, there is increasing evidence, including the results presented in this thesis, that the different forms of solar variability can have a substantial effect to regional and seasonal climate variability. With this new evidence, the solar wind related particle effects in the atmosphere are now gaining increasing attention. These effects will soon be included in the next coupled model inter comparison project (CMIP6) as an additional solar related climate effect. This emphasizes the relevance of this thesis.

Ce travail documente la variabilité spatiale et temporelle du rayonnement solaire à la surface sur le sud-ouest de l'océan Indien (SOOI) et l'île de La Réunion à l'aide de deux modèles régionaux de climat (MRC) : les modèles RegCM et WRF. La première partie de ce travail est dédiée à l'analyse de la variabilité temporelle du rayonnement solaire à l'aide du modèle RegCM sur le SOOI avec une résolution spatiale modérée (50km). S'agissant du premier travail sur la modélisation régionale du climat pour l'étude du rayonnement solaire dans le SOOI, une première série de tests pour illustrer les performances du modèle et sa sensibilité au choix des paramétrisations physiques (transfert radiatif, convection), à la taille du modèle, et à la résolution spatiale, est effectuée. Le schéma radiatif par défaut, le schéma CCM, et le schéma convectif mixte : Grell sur les terres et Emanuel sur les océans, donnent les résultats les plus satisfaisants pour la région, comparés aux autres options disponibles. La variabilité climatique interannuelle, intrasaisonnière et jour-à-jour est ensuite examinée sur la base des indices climatiques. Dans un premier temps, plusieurs paramètres (vent horizontal, température, humidité relative) issus des réanalyses ERA-Interim et utilisés comme paramètres d'entrée pour le modèle RegCM, sont analysés en lien avec ceux correspondant fournis en sortie du modèle, pour vérifier l'aptitude du modèle à maintenir les signaux ENSO (El-Nino Southern Oscillation), IOD (Indian Ocean Dipole), MJO (Madden-Julian Oscillation) et les Talwegs Tropicaux-Tempérés (TTT). Dans un second temps, le rayonnement solaire à la surface simulé par le modèle RegCM est mis en lien avec ces différents modes de variabilité. La seconde partie du travail est consacrée à l'analyse de la variabilité spatiale du rayonnement solaire à la surface à La Réunion à l'aide du modèle WRF à très haute résolution spatiale (750m) pour différentes échelles de temps : interannuelle, intrasaisonnière, jour-à-jour. Une classification est appliquée sur les sorties de rayonnement produites par WRF, et le lien avec la circulation atmosphérique de grande échelle est analysé dans chacune des classes. Les résultats de la modélisation sont validés à l'aide des données d'observations du réseau Météo France et des produits satellite CM SAF. Les résultats indiquent que les MRC ont la capacité de représenter la variabilité temporelle et spatiale du rayonnement solaire à La Réunion. / This work documents the temporal and spatial variability of surface solar radiation (SSR) over the southwest Indian Ocean (SWIO) and Reunion Island using two complementary Regional Climate Models (RCMs): RegCM4 and WRF. The first part of the work is dedicated to the analysis of the temporal variability of SSR based on RegCM4 over the SWIO at a moderate spatial resolution (50km). Because RegCM4 is the first RCM that focuses on the solar radiation research over the SWIO region, a first series of test experiments with this model to illustrate the model performance and its sensitivity to the choice of the physical parameterizations (radiation, convection), the domain size, and the spatial resolution, are performed. The default CCM radiative and the mixed convective scheme: Grell scheme over land and Emanuel scheme over ocean, give better performance over the SWIO compared to the other available options. The interannual, intraseasonal and synoptic climate variability is then examined through the climate indices and several ERA-Interim parameters (U, V, T and RH) are firstly analyzed along with the corresponding RegCM4 output data to check whether the RegCM4 model forced by ERA-Interim reanalyses is able to maintain the El-Nino Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), the Madden-Julian Oscillation (MJO) and the Tropical Temperate Trough (TTT) signals. Secondly, simulated SSR in association with the different modes of variability is examined. In the second part, SSR spatial variability over Reunion Island is analyzed based on WRF simulations at very fine resolution (750m) for seasonal, intraseasonal, and daily time scales. Clustering classification is applied to WRF simulated SSR over Reunion and the effect from the atmospheric circulation is checked together. Météo France observations and CM SAF are used to validate the results of the model. The results indicate that regional climate models have the ability to present the temporal and spatial variability of SSR over Reunion.

Indiana University-Purdue University Indianapolis (IUPUI)

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