Water is undeniably among the most important natural resources and the most critical in semi-arid regions like the Intermountain West of the United States. Such regions are characterized by low precipitation, the majority of which is transferred to the atmosphere from the soil and vegetation as evapotranspiration (ET). Quantification of ET is thus crucial for understanding the balance of water within the region, which is important for efficiently planning the available water resources. This study was motivated towards advancing the estimation of actual ET (ETA) in mountain ecosystems, where the variation in different types of vegetation and non-uniformity of soil including considerable stone content creates challenges for estimating water use as ET. With the aim of addressing the effect of stone content in controlling soil moisture and ET, this study examined the influence of stone content on bulk soil hydraulic properties. An averaging model referred to as a binary mixing model was used to describe the way in which water is held and released in stony soil. This approach was based on the individual hydraulic behavior of the background soil and of the stones within the soil. The effect of soil stone content on ETA was evaluated by accounting for the water retention properties of stones in the soil using a numerical simulation model (HYDRUS-1D). The results revealed overestimation of simulated ETA when effects of stone content were not accounted for in comparison to ETA measured by the state-of-the-art “eddy covariance” measurement method for ETA. An even larger-scale model was evaluated, named the Noah-Multiphysics (Noah-MP) land surface model. The land surface model was run using different arrangements of complexity to determine the importance of stone content information on simulation results. The version of the model with information about stone content along with detailed soil properties was able to provide the best Noah-MP prediction of ET. The study suggests that improvement in representation of soil properties including stone content information, can substantially advance the ability of numerical and land surface models to more accurately simulate soil water flow and ETA.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The following study quantifies the seasonal and annual distribution of energy balance components (sensible heat fluxes, latent, soil, and net radiation) in this flooded irrigated rice ecosystem in Southern Brazil for three different periods (Fallow 1: 22 July 2003 to 24 November 2003; Rice: 25 November 2003 to 04 April 2004 and Fallow 2: 05 April 2004 to 21 July 2004). In addition, it has been applied the Noah Land Surface Model with the objective of estimating the surface energy fluxes. An important challenge is to implement a new version of Noah Land Surface Model applied to flooded agricultural land called Noah-Paddy. The stabilization of the models has been performed using the atmospheric forcing data obtained from South American Land Data Assimilation System (SALDAS) for the period 22 July 2000 to 21 July 2003. The models were simulated using the observed atmospheric forcing from a micrometeorological tower installed on a flooded irrigated rice paddies located in the city of Paraíso do Sul - RS. The initial conditions were obtained from the last time step of the spin-up experiment performed with atmospheric forcing data of SALDAS. The models results were compared with experimental data for surface energy fluxes. From the simulated results generated by the Noah Land Surface Model, it seems that when the rice crop is flooded, the model does not satisfactorily represents the experimental data. However, using the Noah-Paddy model the components of surface energy balance are more realistic for the system surface-water-atmosphere. The most important contribution performed in this research was to describe the diffent physical processes originated by the presence of a body of water between the soil surface and the atmosphere. This physical system occorr always in flooded agricultural crops in wich the rice paddies field are predominant. / No presente trabalho, quantifica-se a distribuição sazonal e anual das componentes do balanço de energia (fluxos de calor sensível, latente, do solo e saldo de radiação) em um ecossistema de arroz irrigado por inundação localizado no Sul do Brasil para três períodos distintos ao longo do ano (Pousio 1: 22Jul2003 a 24Nov2003; Arroz: 25Nov2003 a 04Abr2004 e Pousio 2: 05Abr2004 a 21Jul2004). Além disso, é utilizado o Modelo de Superfície Noah (Noah LSM) com o objetivo de estimar os fluxos de energia superficiais. Um dos desafios mais importantes é a implementação de uma nova versão do Noah LSM aplicado para áreas agrícolas alagáveis chamado Noah-Paddy. A estabilização dos modelos foi realizada utilizando dados de forçantes atmosféricas do South American Land Data Assimilation System (SALDAS) para o período de 22Jul2000 a 21Jul2003. Os modelos foram executados usando dados de forçantes atmosféricas observados obtidos a partir da torre micrometeorológica instalada sobre uma cultura de arroz irrigado por inundação localizada em Paraíso do Sul - RS. As condições iniciais foram obtidas a partir do último passo de tempo do experimento spin-up realizado com os dados de forçantes atmosféricas do SALDAS. O desempenho dos modelos estudados foi comparado com dados experimentais de fluxos de energia superficiais. A partir dos resultados obtidos pela simulação do Noah LSM verifica-se que, quando a cultura do arroz está irrigada, o modelo não representa satisfatoriamente os dados experimentais. Porém, utilizando o Noah-Paddy as trocas de energia superficiais são representadas de forma mais realísticas para o sistema superfície-água-atmosfera. A contribuição mais importante realizada neste trabalho foi a descrição dos diferentes processos físicos originados pela presença de uma massa de água entre a superfície do solo e a atmosfera. Esse sistema físico ocorre sempre em culturas agrícolas alagadas nas quais as plantações de arroz são predominantes.

Un modèle de surface continentale (LSM en anglais) est un modèle numérique décrivant les échanges d'eau et d'énergie entre la surface terrestre et l'atmosphère. La physique de la surface de la terre comprend une vaste collection de processus complexes. L'équilibre entre la complexité du modèle et sa résolution, confronté à des limitations de calcul, représente une question fondamentale dans le développement d'un LSM. Les observations des phénomènes étudiés sont nécessaires afin d’adapter la valeur des paramètres du modèle à des variables reproduisant le monde réel. Le processus d'étalonnage consiste en une recherche des paramètres du modèle qui minimisent l’écart entre les résultats du modèle et un ensemble d'observations. Dans ce travail, nous montrons comment l'assimilation variationnelle de données est appliquée aux bilans d'énergie et d'eau du modèle de surface continentale ORCHIDEE afin d’étalonner les paramètres internes du modèle. Cette partie du modèle est appelé SECHIBA. Le logiciel YAO est utilisé pour faciliter la mise en œuvre de l'assimilation variationnelle 4DVAR. Une analyse de sensibilité a été réalisée afin d'identifier les paramètres les plus influents sur la température. Avec la hiérarchie des paramètres obtenue, des expériences jumelles à partir d'observations synthétiques ont été mises en œuvre. Les résultats obtenus suggèrent que l'assimilation de la température de surface a le potentiel d'améliorer les estimations de variables, en ajustant correctement les paramètres de contrôle. Enfin, plusieurs assimilations ont été faites en utilisant des observations de données réelles du site SMOSREX à Toulouse, France. Les expériences faites en utilisant différentes valeurs initiales pour les paramètres, montrent les limites de l'assimilation de la température pour contraindre les paramètres de contrôle. Même si l'estimation des variables est améliorée, ceci est dû à des valeurs finales des paramètres aux limites des intervalles prescrit de la fonction de coût. Afin de parvenir à un minimum, il faudrait permettre aux paramètres de visiter des valeurs irréalistes. Les résultats montrent que SECHIBA ne simule pas correctement simultanément la température et les flux et la relation entre les deux n’est pas toujours cohérente selon le régime (ou les valeurs des paramètres que l’on utilise). Il faut donc travailler sur la physique pour mieux simuler la température. En outre, la sensibilité des paramètres à la température n’est pas toujours suffisante, donnant une fonction de coût plate dans l’espace des paramètres prescrit. Nos résultats montrent que le système d'assimilation mis en place est robuste, puisque les résultats des expériences jumelles sont satisfaisants. Le couplage entre l'hydrologie et la thermodynamique dans SECHIBA doit donc être revu afin d'améliorer l'estimation des variables. Une étude exhaustive de l'erreur des mesures doit être menée afin de récupérer des termes de pondération dans la fonction de coût. Enfin, l'assimilation d'autres variables telles que l'humidité du sol peut maintenant être réalisée afin d'évaluer l'impact sur les performances de l’assimilation. / A land surface model (LSM) is a numerical model describing the exchange of water and energy between the land surface and the atmosphere. Land surface physics includes an extensive collection of complex processes. The balance between model complexity and resolution, subject to computational limitations, represents a fundamental query in the development of a LSM. With the purpose of adapting the value of the model parameters to values that reproduces results in the real world, measurements are necessary in order to compare to our estimations to the real world. The calibration process consists in an optimization of model parameters for a better agreement between model results and a set of observations, reducing the gap between the model and the available measurements. Here we show how variational data assimilation is applied to the energy and water budgets modules of the ORCHIDEE land surface model in order to constrain the model internal parameters. This part of the model is denoted SECHIBA. The adjoint semi-generator software denoted YAO is used as a framework to implement the 4DVAR assimilation. A sensitivity analysis was performed in order to identify the most influent parameters to temperature. With the parameter hierarchy resolved, twin experiments using synthetic observations were implemented for controlling the most sensitive parameters. Results obtained suggest that land surface temperature assimilation has the potential of improving the output estimations by adjusting properly the control parameters. Finally, several assimilations were made using observational meteorology dataset from the SMOSREX site in Toulouse, France. The experiments implemented, using different prior values for the parameters, show the limits of the temperature assimilation to constrain control parameters. Even though variable estimation is slightly improved, this is due to final parameter values are at the edge of a variation interval in the cost function. Effectively reaching a minimum would require allowing the parameters to visit unrealistic values. SECHIBA does not correctly simulates simultaneously temperature and fluxes and the relationship between the two is not always consistent according to the regime (or parameter values that are used). We must therefore work on the physical aspects to better simulate the temperature. Likewise, the parameter sensitivity to temperature is not always sufficient, giving as a result a flat cost function. Our results show that the assimilation system implemented is robust, since performances results in twin experiments are satisfactory. The coupling between the hydrology and the thermodynamics in SECHIBA must be reviewed in order to improve variable estimation. An exhaustive study of the prior errors in the measurements must be conducted in order to retrieve more adapted weighing terms in the cost function. Finally, the assimilation of other variables such as soil moisture should be performed to evaluate the impacts in constraining control parameters

L'évolution naturelle du climat, perturbée depuis les révolutions industrielles, est fortement marquée dans les hautes latitudes en particulier en Sibérie où une anomalie de température de +0.8°C est constatée depuis les années 2000 contre une anomalie moyenne de +0.4°C pour les moyennes latitudes. La Sibérie est couverte par des pergélisols lui conférant ainsi des particularités, notamment pour les régimes hydrologiques des rivières. Les projections climatiques prédisant jusqu'à un réchauffement de l'ordre de +5°C d'ici 2100, il est primordial d'en évaluer les impacts. La modélisation numérique à bases physiques s'avère être un outil intéressant pour répondre à ces questions. Ainsi, afin d'évaluer la réponse hydrologique au changement climatique en Sibérie nous avons travaillé sur l'évaluation multi-échelles des bilans d'énergie et d'eau avec le modèle ORCHIDEE. Ce modèle a été adapté aux caractéristiques des milieux froids, avec une amélioration de la représentation de la neige, une prise en compte du gel de l'eau du sol et une carte de végétation plus représentative de la végétation sibérienne. Une évaluation en mode forcé i.e. sans couplage avec l'atmosphère a été menée dans un premier temps. Ainsi, nous avons évalué ORCHIDEE au temps présent (1979-2009) à l'échelle du site en nous concentrant sur les données d'humidité et de température du sol dont nous disposions. Une analyse de sensibilité du modèle nous a permis d'identifier les paramètres les plus influents sur les bilans d'énergie et d'eau dans le sol. Leur étalonnage sur sites nous a permis de montrer que le modèle ORCHIDEE est capable de simuler correctement les transferts verticaux de chaleur et d'eau et les contenus en eau et températures du sol résultants. Par la suite nous avons étendu l'évaluation à la région de la Sibérie en confrontant nos résultats de simulation à des produits satellitaires, permettant une évaluation sur une série temporelle conséquente et sur une grande zone. Nous avons rassemblé un grand nombre d'observations telles que des données d'albédo, d'équivalent en eau pour la neige..., auxquelles nous avons comparé nos résultats de simulation. Ce travail nous a permis de montrer que le modèle simule de façon satisfaisante les bilans d'énergie et d'eau en Sibérie, mais aussi de mettre en avant l'importance du choix du forçage climatique. Ainsi, l'utilisation d'un second forçage climatique nous a permis de montrer l'importance du partitionnement pluie/neige ainsi que la sous-estimation possible des précipitations dans les forçages. Le modèle validé a été utilisé ensuite pour mener des études d'impacts, en utilisant 2 forçages climatiques sur le temps futur (2005 à 2099) sous scénario d'émission des gaz à effet de serre RCP8.5. Ainsi nous avons pu évaluer la variabilité liée au forçage et l'impact de l'évolution du climat sur les variables des bilans d'énergie et d'eau. Une limite autour de la latitude 60°N a été définie lors de l'analyse des précipitations futures et choisie pour orienter notre analyse selon deux zones de part et d'autre de la limite. Nous avons analysé les cycles saisonniers des variables de surface nous permettant de mettre en évidence les impacts du réchauffement climatique en lien avec l'augmentation de la température de l'air et leurs différences spatiales. Nous avons montré que la fonte du manteau neigeux est plus précoce au Sud et engendre une avance temporelle du pic de crue de printemps pour la Lena et l'Amour. Sur l'Ob et le Ienisseï, des changements ont été aussi montrés (une diminution du débit au cours du temps pour l'Ob et une augmentation pour le Ienisseï, sans changement de phasage temporel), qui pourraient conduire à des impacts socio-économiques importants pour les populations locales. Cette étude nous a également permis de montrer que les nouvelles conditions climatiques sont plus favorables à la végétation. Nous avons montré aussi la cohérence des deux projections climatiques étudiées. / The natural evolution of the climate, disturbed since the industrial revolutions, is strongly marked in the high latitudes especially in Siberia where a temperature anomaly of +0.8°C has been observed since the 2000s against an average anomaly of + 0.4°C for The mid-latitudes. Siberia is covered by permafrost, giving it particularities, especially for the hydrological regimes of rivers. Climatic projections predicting up to +5°C warming by 2100, it is essential to evaluate their impacts. Physical-based numerical modeling is an interesting tool to answer these questions. Thus, in order to evaluate the hydrological response to climate change in Siberia we worked on the multi-scale evaluation of energy and water balances with the ORCHIDEE model. This model was adapted to the characteristics of cold environments, with an improvement of the representation of the snow, a consideration of the freezing of the soil water and a map of vegetation more representative of the Siberian vegetation. An evaluation in forced mode i.e. without coupling with the atmosphere was carried out initially. Thus, we evaluated ORCHIDEE at the present time (1979-2009) at the site scale, concentrating on the soil moisture and soil temperature data available. A sensitivity analysis of the model allowed to identify the most influential parameters on the balance of energy and water in the soil. Their on-site calibration allowed to show that the ORCHIDEE model is able to correctly simulate the vertical transfers of heat and water and the resulting water and soil temperature contents. We then extended the evaluation to the Siberian region by comparing simulation results with remote sensing data, allowing an evaluation over a substantial time series and over a large area. We collected a large number of observations such as albedo data, water equivalent for snow ..., on which we compared the simulation results. This work allowed to show that the model simulates satisfactorily the energy and water balance in Siberia, but also to highlight the importance of the choice of climatic forcing. Thus, the use of a second climatic forcing enabled to show the importance of rain/snow partitioning and the possible underestimation of precipitation in forcing. The validated model was then used to carry out impact studies, using 2 climatic forcings on the future time (2005 to 2099) under scenario of emission of greenhouse gases RCP8.5. Thus, we were able to evaluate the variability related to forcing and the impact of climate change on the variables of energy and water balance. A boundary around latitude 60°N has been defined in the analysis of future precipitation and chosen to orient our analysis in two zones on either side of the boundary. We analyzed the seasonal cycles of the surface variables allowing us to highlight the impacts of global warming in relation to the increase in the air temperature and their spatial differences. We have shown that the melting of the snowpack is earlier in the South and generates a temporal advance of the spring flood peak for the Lena and the Amur. On the Ob and Yenisei, changes have also been shown (a decrease in flow over time for the Ob and an increase for the Yenisei, without any change in temporal phasing), which could lead to socio-economic impacts Important for local populations. This study also allowed us to show that the new climatic conditions are more favorable to vegetation. We also showed the coherence of the two climate projections studied.

L’évolution du climat sur les prochaines dizaines voire centaines d’années pose de nombreuses interrogations, du fait de l’impact de l’homme. Les émissions de gaz à effet de serre depuis le début de l’ère industrielle entrainent une augmentation des températures. Celle-ci est susceptible d’affecter les écosystèmes terrestres, notamment dans les régions boréales où les augmentations de température observées et projetées sont plus importantes. Une évolution de ces écosystèmes peut entrainer des rétroactions sur le climat. Ainsi le phénomène actuel observé de verdissement des régions boréales (ou « Arctic greening ») peut augmenter ce réchauffement via une diminution de l’albédo. Afin de répondre à ces interrogations, des modèles climatiques ont été développés, intégrant des modèles de surface continentale représentant les flux de matière et d’énergie. Le travail effectué dans cette thèse a été mené à partir de l’un d’eux, le modèle de surface continentale ORCHIDEE, qui comprend une description succincte de la végétation boréale. L’objectif de cette thèse était donc l’implémentation puis la modélisation de la végétation boréale.Afin de décrire la végétation présente au niveau des hautes latitudes, i.e. les toundras et les steppes, de nouveaux types de végétation (PFTs) ont été intégrés au modèle à partir des PFTs déjà présents. Tout d’abord, les plantes non vasculaires (NVPs) ont été introduites pour représenter les lichens et les bryophytes, ensuite les buissons pour représenter une strate intermédiaire entre les arbres et les herbacées, et enfin des herbacées C3 boréales pour distinguer la végétation considérée dans les steppes boréales et les prairies tempérées. La description de cette végétation boréale s’est accompagnée de l’intégration de nouveaux processus caractéristiques, allant de l’implémentation d’interactions nouvelles telles que la protection des buissons par la neige en hiver, au simple choix de nouveaux paramètres du PFT, en passant par la modification de processus déjà présents dans le modèle comme la conductance stomatique des NVPs. D’autres processus en lien avec la végétation ont également été mis à jour ou corrigés. Enfin, pour modéliser la dynamique de la végétation boréale, les nouveaux PFTs ont été intégrés à la description initialement présente dans le modèle.Ces modifications ont permis de modéliser la végétation boréale et ses impacts sur les autres variables du système (flux de matière ou d’énergie), soit avec une végétation prescrite (simulations de la période récente), soit avec une végétation dynamique (simulations présentes et futures, à partir des scénarios RCPs 4.5 et 8.5). Les simulations effectuées avec la végétation prescrite montrent que l’on représente mieux le comportement de la végétation avec les nouveaux PFTs. Avec les PFTs originaux la productivité et la biomasse étaient surestimées dans les régions boréales et entrainaient une sous-estimation de l’albédo et une surestimation de la transpiration. Les simulations avec une végétation dynamique ont démontré la capacité du modèle à représenter avec la nouvelle végétation boréale les biomes actuels ainsi que l’« Arctic greening ». Par contre, l’embuissonement observé dans plusieurs études n’a pas été reproduit. Globalement l’introduction des PFTs boréaux s’est traduite par une meilleure description des écosystèmes arctiques et des échanges d’énergie et de matière avec l’atmosphère. Par contre, la protection du pergélisol par les NVPs n’a pas été aussi importante qu’attendu et a été compensée par une augmentation de l’humidité du sol.L’introduction de la nouvelle végétation boréale dans le modèle ORCHIDEE semble donc pertinente et met en évidence l’importance de la représentation de ces écosystèmes. Ce travail ouvre donc des perspectives pour améliorer les simulations climatiques, tant futures que passées. Comme la modélisation de la végétation depuis l’Holocène afin de simuler la quantité de carbone contenu aujourd’hui dans le pergélisol. / Climate evolution over the next ten to hundred years involves many questions, linked to the impact of man. Indeed, greenhouse gases emissions since the beginning of the industrial era lead to an increase in temperature. The latter can affect terrestrial ecosystems, particularly in boreal regions where observed and projected temperature increase is larger than in mid-latitudes. Evolution of these ecosystems can trigger climate feedbacks. For example, the currently observed « Arctic greening » phenomenon could enhance the warming via a decrease in albedo due to the increase in vegetation cover. In order to address these questions, climate models were developped, including continental surface models taking into account the fluxes of mass and energy. In this thesis, such a model was used, the continental surface scheme ORCHIDEE, which includes a succinct description of boreal vegetation. The aim of this work was thus the implementation and the modeling of boreal vegetation.In order to describe high-latitude vegetation, i.e. toundras and steppes, new plant functional types (PFTs) were integrated into the model based on existing PFTs. First, non-vascular plants (NVPs) were integrated to represent lichens and bryophytes found in desert toundras and peatlands, then shrubs to represent an intermediate stratum between trees and grasses in toundras, and finally boreal C3 grasses to distinguish vegetation found in boreal steppes and temperate grasslands. The description of this boreal vegetation was accompanied by the integration of new charachteristic processes, from the implementation of new interactions such as the protection of shrubs by snow in winter, to the simple choice of new PFT parameters such as the lower photosynthetic capacity of boreal C3 grasses compared to temperate C3 grasses, through the modification of existing processes such as the stomatal conductance of NVPs. Other processes linked to vegetation were also updated or corrected. Finally, to model the dynamics of boreal vegetation, new PFTs were integrated into the initial description in the model.Those changes enabled the modeling of boreal vegetation and its impact on other variables (mass or energy fluxes), either using a prescribed vegetation (simulations on the recent period), or using a dynamical vegetation (recent and future simulations using RCPs 4.5 and 8.5). Simulations using the prescribed vegetation indicated that vegetation behaviour is better represented with the new PFTs. With original PFTs, productivity and biomass were overestimated in boreal regions, and lead to an underestimation of albedo and an overestimation of transpiration. Simulations using a dynamical vegetation demonstrated the ability of the model, using the new boreal vegetation, to represent current-day biomes as well as « Arctic greening ». However, the shrubification observed in several studies was not reproduced. Similarly, the impact of new PFTs on other model outputs is important, with for example a decrease in productivity or albedo in winter compared to the original vegetation. Thus, the introduction of boreal PFTs generally resulted in a better description of Arctic ecosystems and of the exchanges of energy and mass with the atmosphere. On the other hand, the protection of permafrost by NVPs was not as substantial as expected and was compensated by an increase in soil humidity (due to shrubs and boreal grasses).The introduction of the new boreal vegetation in the ORCHIDEE model thus seems relevant, and highlights the importance of representing these ecosystems. This work opens up new perspectives to improve future and past climate simulations. The next step consists in modeling vegetation since the Holocene into the future in order to simulate the current amounts of carbone in the permafrost, and to project the outcome of these stocks in the context of climate change and permafrost melt.

The representation of high-latitude surface processes and quantifying surface-climate feedbacks are some of the most serious shortcomings of present day Arctic land surface modelling. The energy balance of seasonally snow-covered sparse deciduous forests at high latitudes is poorly understood and inaccurately represented within hydrological and climate models. Snow cover plays an important role in wintertime fluxes of energy, water and carbon, controlling the length of the active growing season and hence the overall carbon balance of Arctic ecosystems. Snow cover is non-uniform and spatially variable, as wind redistributes snow from areas of exposed open tundra to sheltered areas within the forest, where a deeper snowpack develops. Low solar zenith angles, coupled with sparse deciduous leafless trees, cast shadows across the snow surface. The spatial distribution of canopy gaps determines the timing of direct radiation which penetrates down through the canopy to the snow surface. The forest canopy also excludes incoming longwave radiation and yet also emits longwave radiation to the snow surface. Consequently the forest canopy plays a key role in the radiation balance of sparse forests. To improve our knowledge of these complex processes, meteorological and field observations were taken in an area of highly heterogeneous birch Betula pubescens ssp. czerepanovii forest in Abisko, Sweden during the spring of 2008 and 2009. Detailed measurements of short and longwave radiation above and below the canopy, hemispherical photographs, tree temperatures and snow surveys were conducted to quantify the radiation balance of the sparse deciduous forest. An array of below canopy pyranometers found the mean canopy transmissivity to be 74 % in 2008 and 76 % in 2009. Hemispherical photographs taken at the pyranometer locations analysed with Gap Light Analyzer (GLA) showed reasonable agreement with a mean canopy transmissivity of 75 % in 2008 and 74 % in 2009. The canopy transmissivity was found to be independent of the diffuse fraction of radiation as the canopy is very sparse. A series of survey grids and transects were established to scale up from the below canopy pyranometers to the landscape scale. Hemispherical photographs analysed with GLA showed the sparse forest canopy had a mean transmissivity of 78 % and a mean LAI of 0.25, whereas the open tundra had a mean transmissivity of 97 % and a mean LAI of < 0.01. Snow surveys showed the sparse forest snow depth to vary between 0.34 and 0.55 m, whereas the snow depth in the open tundra varied between 0.12 and 0.18 m. Observations of canopy temperatures showed a strong influence of incident shortwave radiation warming the tree branches to temperatures up to 15 °C warmer than ambient air temperature on the south facing sides of the trees, and up to 6 °C on the north facing sides of the trees. To reproduce the observed radiation balance, two canopy models (Homogenous and Clumped) were developed. The Homogeneous canopy model assumes a single tree tile with a uniform sparse canopy. The Clumped canopy model assumes a tree and a grass tile, where the tree tile is permanently in shade from the canopy and the grass tile receives all the incoming radiation. These canopy models identified the need for a parameter that accounts for the spatial and temporal variation of the shaded gaps within the sparse forest. JULES (Joint UK Land Environment Simulator) is the community land surface model used in the UK Hadley Centre GCM suite. Modifications of the land-surface interactions were included in JULES to represent the shaded gaps within the sparse deciduous forest. New parameterisations were developed for the time-varying sunlit fractions of the gap (flit), the sky-view fraction (fv), and the longwave radiation emitted from the canopy (LWtree). These model developments were informed by field observations of the forest canopy and evaluated against the below canopy short and longwave radiation observed data sets. The JULES Shaded gap model output showed a strong positive relationship with the observations of below canopy shortwave and longwave radiation. The JULES Shaded gap model improves the ratio of observed to modelled short and longwave radiation on sunny days compared to the JULES model. The JULES Shaded gap model reduces the time to snow melt by 2 to 4 days compared to the JULES model, making the model output more aligned with in-situ observational data. This shortening of the modelled snow-season directly impacts on the simulated carbon and water balance regionally and has wider relevance at the pan-Arctic scale. When JULES Shaded Gap was evaluated on the global scale, it improved the modelled snowmass across large areas of sparse forest in northern Canada, Scandinavia and Northern Russia with respect to GlobSnow. The performance of the land surface-snow-vegetation interactions of JULES was improved by using the Shaded gap to model the radiation balance of sparse forests in climate-sensitive Arctic regions. Furthermore these observational data can be used to develop and evaluate high latitude land-surface processes and biogeochemical feedbacks in other earth system models.

Land surfaces have changed as a result of human and natural processes, such asdeforestation, urbanization, desertification and natural disasters like wildfires. Land use and landcover change impacts local and regional climates through various bio geophysical processes acrossmany time scales. More realistic representation of land surface parameters within the land surfacemodels are essential to for climate models to accurately simulate the effects of past, current andfuture land surface processes. In this study, we evaluated the sensitivity and accuracy of theWeather Research and Forecasting (WRF) model though the default MODIS land cover data andannually updated land cover data over southeast of United States. Findings of this study indicatedthat the land surface fluxes, and moisture simulations are more sensitive to the surfacecharacteristics over the southeast US. Consequently, we evaluated the WRF temperature andprecipitation simulations with more accurate observations of land surface parameters over thestudy area. We evaluate the model performance for the default and updated land cover simulationsagainst observational datasets. Results of the study showed that updating land cover resulted insubstantial variations in surface heat fluxes and moisture balances. Despite updated land use andland cover data provided more representative land surface characteristics, the WRF simulated 2- m temperature and precipitation did not improved due to use of updated land cover data. Further,we conducted machine learning experiments to post-process the Noah-MP land surface modelsimulations to determine if post processing the model outputs can improve the land surfaceparameters. The results indicate that the Noah-MP simulations using machine learning remarkablyimproved simulation accuracy and gradient boosting, and random forest model had smaller meanerror bias values and larger coefficient of determination over the majority of stations. Moreover,the findings of the current study showed that the accuracy of surface heat flux simulations byNoah-MP are influenced by land cover and vegetation type.

This research investigates soil respiration (Rs) in a boreal jack pine (Pinus banksiana Lamb.) fire scar chronosequence at Sharpsand Creek, Ontario, Canada. During two field campaigns in 2006 and 2007, Rs was measured in a chronosequence of fire scars in the range 0 to 59 years since fire. Mean Rs adjusted for soil temperature (Ts) and soil moisture (Ms) (Rs T,M) ranged from 0.56 μmol CO2/m2/s (32 years post fire) to 8.18 μmol CO2/m2/s (58 years post fire). Coefficient of variation (CV) of Rs adjusted for Ts and Ms ranged from 20% (16 years post fire) to 56% (58 years post fire). Across the field site, there was a significant exponential relationship between Rs adjusted for soil organic carbon (Cs) and Ts (P = 1.24*10-06; Q10 = 2.21) but no effect of Ms on Rs adjusted for Cs and Ts for the range 0.21 to 0.77 volumetric Ms (P = 0.702). Rs T,M significantly (P = 0.030) decreased after burning mature forest, though no significant (P > 0.1) difference could be detected between recently burned and unburned young forest. Rs was measured in recently burned boreal jack pine fire scar age categories that differed in their burn history and there was a significant difference in Rs T,M between previously 32 v 16 year old (P = 0.000) and previously 32 v 59 year old (P = 0.044) scars. There was a strong significant exponential increase in S R T,M with time since fire (r2 = 0.999; P = 0.006) for the chronosequence 0, 16 and 59 years post fire, and for all these age categories, Rs T,M was significantly different from one another (P < 0.05). The Joint UK Land Environment Simulator (JULES) was used to model vegetation re-growth over successional time at Sharpsand Creek, though it appeared to perform poorly in simulating leaf area index and canopy height. JULES probably over estimated heterotrophic Rs at Sharpsand Creek when Ts corrected simulated values were compared with measured Rs T,M. The results of this study contribute to a better quantitative understanding of Rs in boreal jack pine fire scars and will facilitate improvements in C cycle modelling. Further work is needed in quantifying autotrophic and heterotrophic contributions to soil respiration in jack pine systems, monitoring soil respiration for extended time periods after fire and improving the ability of JULES to simulate successional vegetation re-growth.

In this thesis, we have presented a systematic analysis of the change of cloud properties due to variation in aerosol concentration over Indian region using satellite observations, and Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) simulations. The Tropical Rainfall Measurement Mission (TRMM) based Microwave Imager (TMI) estimates (2A12) have been used to compare and contrast the characteristics of cloud liquid water and ice over the Indian land region and the surrounding oceans, during the pre-monsoon (May) and monsoon (June–September) seasons. Based on the spatial homogeneity of rainfall, we have selected five regions for our study (three over ocean, two over land). In general, we find that the mean cloud liquid water and cloud ice content of land and oceanic regions are different, with the ocean regions showing higher amount of CLW. A comparison across the ocean regions suggests that the cloud liquid water over the or graphically influenced Arabian Sea (close to the Indian west coast) behaves differently from the cloud liquid water over a trapped ocean (Bay of Bengal) or an open ocean (Equatorial Indian Ocean). Specifically, the Arabian Sea region shows higher liquid water for a lower range of rainfall, whereas the Bay of Bengal and the Equatorial Indian Ocean show higher liquid water for a higher range of rainfall. Apart from geographic differences, we also documented seasonal differences by comparing cloud liquid water profiles between monsoon and pre-monsoon periods, as well as between early and peak phases of the monsoon. We find that the cloud liquid water during the lean periods of rainfall (May or June) is higher than during the peak and late monsoon season (July-September) for raining clouds over central India. However, this is not true over the ocean. As active and break phases are important signatures of the monsoon progression, we also analyzed the differences in cloud liquid water during various phases of the monsoon, namely, active, break, active-to-break (a2b) and break-to-active (b2a) transition phases. We find that the cloud liquid water content during the b2a transition phase is significantly higher than that during the a2b transition phase over central India. We speculate that this could be attributed to higher amount of aerosol loading over this region during the break phase. We lend credence to this aerosol-liquid water/rain association by comparing the central Indian cloud liquid water with Southeast Asia (where the aerosol loading is significantly smaller) and find that in the latter region, there are no significant differences in cloud liquid water during the different phases of their monsoon. The second part of our study involves evaluating the ability of the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) to simulate the observed variation of cloud liquid water and rain efficiency. We have used no chemistry option, and the model was run with constant aerosol concentration. The model simulations (at 4.5 km resolution) are done for the month of June–July 2004 since this period was particularly favorable for the study of an active–break cycle of the monsoon. We first evaluate the sensitivity of the model to different parameterizations (microphysical, boundary layer, land surface) on the simulation of rain over central India and Bay of Bengal. This is done to identify an “optimal” combination of parameterizations which reproduces the best correlation with observed rain over these regions. In this default configuration (control run), where the aerosol concentration is kept constant throughout the simulation period, the model is not able to reproduce the observed variations of cloud liquid water during the different phases of an active-break cycle. To this end, we proceeded to modify the model by developing an aerosol-rain relation, using Aerosol Robotic Network (AERONET) and TRMM 3B42 data that realistically captures the variation of aerosol with rain. It is worth highlighting here that our goal was to primarily isolate the indirect effect of aerosols in determining the observed changes in cloud liquid water (CLW) during the active-break phases of the Indian monsoon, without getting into the complexity of a full chemistry model such as that incorporated in WRF-Chem. Moreover, the proposed modification (modified run) is necessitated by the lack of realistic emission estimates over the Indian region as well as the presence of inherent biases in monsoon simulation in WRF. The main differences we find between the modified and control simulations is in the mean as well as spatial variability of CLW. We find that the proposed modification (i.e., rate of change of aerosol concentration as a function of rain rate) leads to a realistic variation in the CLW during the active-break cycle of Indian monsoon. Specifically, the peak value of CLW in the b2a (a2b) phase is larger (smaller) in the modified as compared to the control run. These results indicate a stronger change in CLW amount in the upper levels between the two transition phases in the modified scheme as compared to the control simulation. More significantly, we also observe a change in sign at the lower levels of the atmosphere, i.e., from a strong positive difference in the control run to a negative difference in the modified simulation, similar to that observed. Additionally, we investigated the impact of the proposed modification, via CLW changes, on cloud coverage, size of clouds and their spatial variability. We find that the transformation of optically thin clouds to thick clouds during the break phase was associated with larger cloud size in modified compared to the control simulation. Moreover, the higher rate of decay of the spatial variability of CLW with grid resolution, using the modified scheme, suggests that clusters of larger clouds are more in the modified compared to control simulation. Taken together, the interactive aerosol loading proposed in this thesis yields model simulations that better mimic the observed CLW variability between the transition phases.