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Subseasonal variability of tropical Indian Ocean sea surface temperature is thought to influence the active-break cycle of the Asian monsoon. There are several open questions related to the role of surface fluxes, large-scale ocean circulation and subsurface ocean processes in the subseasonal variability of upper ocean temperature. We present a unified study of the subseasonal (2-90 day) variability of surface heat flux and upper ocean temperature and salinity throughout the tropical Indian Ocean in all seasons. We focus on the relation between surface fluxes and ocean response using a new satellitebased daily heat flux. The role of ocean processes (advection, entrainment and mixing) in determining SST variability is diagnosed from the daily satellite SST. Before the onset of the summer monsoon, sea surface temperature (SST) of the north Indian Ocean warms to 30-32oC. Climatological mean mixed layer depth in spring (March-May) is 10-20 m, and net surface heat flux (Qnet) is 80-100 Wm 2 into the ocean. It has been suggested that observed spring SST warming is small mainly due to (a) penetrative flux of solar radiation through the base of the mixed layer (Qpen), (b) advective cooling by upper ocean currents and (c) entrainment of sub-mixed layer cool water. We estimate the role of the first two processes in SST evolution from a two-week ARMEX experiment in April-May 2005 in the the southeastern Arabian Sea. The upper ocean is stratified by salinity and temperature, and mixed layer depth is shallow (6 to 12 m). Current speed at 2 m depth is high even under light winds. Currents within the mixed layer are quite distinct from those at 25 m. On subseasonal scales, SST warming is followed by rapid cooling. The cooling occurs although the ocean gains heat at the surface - Qnet is about 105 Wm 2 in the warming phase, and 25 Wm 2 in the cooling phase; penetrative loss Qpen, is 80 Wm 2 and 70 Wm 2. In the warming phase, SST rises mainly due to heat absorbed within the mixed layer, i.e. Qnet minus Qpen; Qpen, reduces the rate of SST warming by a factor of three. In the second phase, SST cools rapidly because (a) Qpen, is larger than Qnet, and (b) advective cooling is _85 Wm 2. A calculation using time-averaged heat fluxes and mixed layer depth suggests that diurnal variability of fluxes and upper ocean stratification tends to warm SST on subseasonal time scale. Buoy and satellite data suggest that a typical premonsoon intraseasonal SST cooling event occurs under clear skies and weak winds, when the ocean is gaining heat. In this respect, premonsoon SST cooling in the north Indian ocean is different from that due to MJO or monsoon ISO. As a follow-up to ARMEX, we use a short dataset from a field campaign in the premonsoon north Bay of Bengal to study diurnal variability of SST. In addition to the standard meteorological and hydrographic parameters measured from shipborne instruments and buoy sensors, we obtained a two-hourly record of subsurface sunlight profiles. Heat fluxes are seen to drive the SST warming during the day while both advection and entrainment/mixing are important during the night. The simple heat balance based on heat flux shows that it drives the diurnal cycle of SST, though ocean processes contribute towards night time cooling; this has been confirmed using the Price-Weller-Pinkel mixing model forced by heat flux and wind stress. A similar analysis for mixed layer salinity revealed that the salt balance in the region is dominated by advection rather than freshwater flux or entrainment/mixing. Buoy and satellite data show pronounced subseasonal oscillations of sea surface temperature (SST) in the summertime north Indian Ocean. The SST oscillations are forced mainly by surface heat flux associated with the active-break cycle of the south Asian summer monsoon. The input of freshwater (FW) from summer rain and rivers to the Bay is large, but not much is known about subseasonal salinity variability. We use 2002-2007 observations from Argo floats with 5-day repeat cycle to study the subseasonal response of temperature and salinity to surface heat and freshwater flux in the central Bay of Bengal and central Arabian Sea. Estimates of surface heat and freshwater flux are based on daily satellite data sampled along the float trajectory. We find that intraseasonal variability (ISV) of mixed layer temperature is mainly a response to net surface heat flux minus penetrative radiation during the summer monsoon season. In winter and spring, however, temperature variability appears to be mainly due to ocean processes rather than local heat flux. Variability of mixed layer freshwater content is generally independent of local surface flux (precipitation minus evaporation) in all seasons. There are occasions when intense monsoon rainfall leads to local freshening, but these are rare. The large subseasonal fluctuations observed in FW appear to be due to advection, suggesting that freshwater from rivers and rain moves in eddies or filaments. We have developed a new daily satellite-based heat flux dataset for the tropical Indian Ocean (30oE 120oE; 30oS 30oN); satellite data include surface air temperature and relative humidity from the Atmospheric Infrared Sounder (AIRS). On the seasonal scale (> 90 days) the flux compares reasonably well with climatologies and other daily data. On the subseasonal scale, our flux product has realistic behaviour relative to buoy data at validation sites. An important result is that ocean processes (advection, entrainment/detrainment, mixing at the base of the mixed layer) cool the tropical Indian Ocean SST by 8oC over the year. The largest contribution of ocean processes (_20oC SST cooling over the year) is in the western equatorial Indian Ocean. Ocean processes generally cool the upper ocean in all seasons and all regions, except in boreal winter, when they warm the north Indian Ocean. This is likely due to entrainment of warm sub-mixed layer water in regions of inversions. On subseasonal (2-90 days) scales, the contribution of air temperature and humidity to latent heat flux is roughly equal to the contribution from wind speed variability: Another interesting finding is that the contribution of air temperature and humidity increases away from the equator. One of the most important contributions of this thesis is the demonstration that tropical Indian Ocean SST has a coherent response to intraseasonal changes in heat flux associated with organised convection in the summer hemisphere. SST responds to flux in (i) the northeast Indian Ocean during May-October and (ii) the 15oS-5oN region during November-April. In the winter hemisphere and in regions with no organised convection, it is ocean processes and not fluxes which drive the subseasonal changes in SST. This result suggests that SST ISV feeds back to organise and sustain organised convection in the tropical atmosphere.

Surface temperature control of a thin plate is investigated. Temperature is controlled on one side of the plate using the other side temperature measurements. This is a decades-old problem, reactivated more recently by the awareness that this is a fractional-order problem that justifies the investigation of the use of fractional order calculus. The approach is based on a transfer function obtained from the one-dimensional heat conduction equation solution that results in a fractional-order s-domain representation. Both the inverse problem approach and the fractional controller approach are studied here to control the surface temperature, the first one using inverse problem plus a Proportional only controller, and the second one using only the fractional controller. The direct problem defined as the ratio of the output to the input, while the inverse problem defined as the ratio of the input to the output. Both transfer functions are obtained, and the resulting fractional-order transfer functions were approximated using Taylor expansion and Zero-Pole expansion. The finite number of terms transfer functions were used to form an open-loop control scheme and a closed-loop control scheme. Simulation studies were done for both control schemes and experiments were carried out for closed-loop control schemes. For the fractional controller approach, the fractional controller was designed and used in a closed-loop scheme. Simulations were done for fractional-order-integral, fractional-order-derivative and fractional-integral-derivative controller designs. The experimental study focussed on the fractional-order-integral-derivative controller design. The Fractional-order controller results are compared to integer-order controller’s results. The advantages of using fractional order controllers were evaluated. Both Zero-Pole and Taylor expansions are used to approximate the plant transfer functions and both expansions results are compared. The results show that the use of fractional order controller performs better, in particular concerning the overshoot.

Meteorological data from two observation sites in Uppsala, the Observatory Park (Op) andthe Geocentre (Gc), during the period January 1998 to September 2000, have been used tocheck the differences in the temperature climate at the two places. Since Op is situatedcloser to the city centre than Gc the site is thought to be more affected by the so calledurban heat island effect. Dependence on different meteorological parameters, time of theday and time of the year, has been investigated and different methods to correct thetemperature for the inhomogeneity that was introduced when the observation site wasmoved from the Observatory Park to the Geocentre. From the different methods investigated it is shown that to correct the temperaturesmeasured at the Geocentre to make them represent the conditions at the Observatory Parka division according to wind speed, wind direction, cloudiness and time of the year wasshown to be the most reliable method. But if it had been possible to divide the material alsointo hours of the day, this would probably have increased the reliability of the correction.For practical purposes a correction simply based on the monthly mean differences betweenthe two sites is probably accurate enough, as the most important factor is the annual cycle inthe temperature difference between the two urban sites. / Väderdata från två observationsplatser i Uppsala, Observatorieparken (Op) och Geocentrum(Gc), under perioden januari 1998 till september 2000, har använts för att undersökaskillnader i temperaturklimatet vid de två platserna. Eftersom Op ligger närmare stadenscentrum än Gc, anses platsen vara mer påverkad av den så kallade värmeöeffekten. Beroendeav olika meteorologiska parametrar, tid på dygnet och tid på året, har undersökts, samt olikametoder att korrigera för inhomogeniteten i temperaturen som introducerades dåobservationsplatsen flyttades från Observatorieparken till Geocentrum. Bland de olika metoder som undersökts för att korrigera de vid Geocentrum uppmättatemperaturerna så att de ska representera förhållandena vid Observatorieparken, visas enuppdelning med avseende på vindhastighet, vindriktning, molnighet och tid på året vara denmest pålitliga metoden, men hade det varit möjligt att dela in materialet även i tid på dygnet,skulle detta troligtvis ha ökat pålitligheten av korrektionen. För praktisk användning är enkorrektion baserad endast på de månatliga medelskillnaderna mellan de två platsernaantagligen tillräcklig, eftersom den viktigaste faktorn är den årliga cykeln itemperaturskillnaden mellan de två platserna.

Vegetation controls the exchange of heat, mass and momentum between the land surface and the atmosphere, and is also the primary producer that sustains life on Earth. We combine theoretical analyses, satellite and in-situ observations, and Earth system model simulations in this dissertation to illustrate the key role of vegetation in the climate system and human society. Specifically, this is accomplished via three studies, described below. First, we address the problem of how to retrieve Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FPAR) from a novel satellite Bidirectional Reflectance Factor product derived from the Multi-Angle Implementation of Atmospheric Correction algorithm. The LAI/FPAR retrieval is done via a radiative transfer model using the recently developed theory of spectral invariants. Our analyses show that the LAI/FPAR data sets developed in this study have higher accuracy and better stability relative to the existing products, especially in cloudy conditions and under high aerosol loadings. Second, we analyze the long-term trend in LAI derived from the Moderate Resolution Imaging Spectroradiometer observations and identify its main driver. We find that over a third of the terrestrial vegetation shows statistically significant increasing trends in LAI (i.e., Earth greening) during the 21st century. Both remote sensing and inventory data show that land-use management is the key driver of this greening, arising primarily from large-scale tree planting and intensive agriculture in emerging countries like China and India. This finding highlights the need for a more realistic representation of land-use practices in Earth system models. Third, we use a new method based on the concept of “two-resistances” and the Community Land Model (CLM5) runs with prescribed satellite-derived LAI to quantify the impacts of Earth greening on land surface temperature (LST). We find that over 90% of the Earth greening can lead to a local cooling effect at the annual scale. Further attribution analysis with multiple data sources reveals that aerodynamic resistance is the dominant factor controlling the LST change. The greening produces a decrease in aerodynamic resistance, which favors increased heat dissipation by turbulent fluxes, including the latent heat flux. These studies that span LAI data production, long-term trends and their impacts highlight the importance of vegetation dynamics in the natural and human systems.

Ces travaux ont pour objectif général d'améliorer la représentation spatio-temporelle des processus hydrologiques de surface à partir de modèles dont la complexité est adaptée aux informations disponibles par la télédétection multi-capteur/multi-résolution. Nous avons poursuivi des développements méthodologiques (désagrégation, assimilation, modélisation du bilan d'énergie) autour de l'estimation de l'humidité du sol dans le contexte de la gestion des ressources en eau dans les régions semi-arides. Récemment, des missions spatiales permettent d'observer l'humidité des sols en surface; notamment avec le capteur AMSR-E (Advanced Microwave Scanning Radiometer-EOS) et la mission SMOS (Soil Moisture Ocean Salinity). Toutefois la résolution spatiale de ces capteurs est trop large (> 40 km) pour des applications hydrologiques. Afin de résoudre le problème d'échelle, l'algorithme de désagrégation DisPATCh (Disaggregation based on Physical and Theoretical Scale Change) a été développé en se basant sur un modèle d'évapotranspiration. Dans la première partie de thèse, l'algorithme est appliqué et validé sur le bassin du Murrumbidgee (sud-est de l'Australie) avec une résolution spatiale cible de 1 km à partir des données de LST (Température de surface) et NDVI (indice de végétation) issues de MODIS (MODerate resolution Imaging Spectroradiometer) et de deux produits d'humidité du sol basse résolution : SMOS et AMSR-E. Les résultats montrent que la désagrégation est plus efficace en été, où la performance du modèle d'évapotranspiration est optimale. L'étude précédente a notamment mis en évidence que la résolution temporelle des données DisPATCh est limitée par la couverture nuageuse visible sur les images MODIS et la résolution temporelle des radiomètres micro-ondes (3 jours pour SMOS). Dans la deuxième partie, une nouvelle approche est donc développée pour assurer la continuité temporelle des données d'humidité de surface en assimilant les données DisPATCh dans un modèle dynamique de type force-restore, forcé par des données météorologiques issus de ré-analyses, dont les précipitations. La méthode combine de manière originale un système variationnel (2D-VAR) pour estimer l'humidité du sol en zone racinaire et une approche séquentielle (filtre de Kalman simplifié) pour analyser l'humidité du sol en surface. La performance de l'approche est évaluée sur deux zones: la région Tensift-Haouz au Maroc et la région de Yanco en Australie. Les résultats montrent que le couplage désagrégation/assimilation de l'humidité du sol est un outil performant pour estimer l'humidité en surface à l'échelle journalière, même lorsque les données météorologiques sont incertaines. Dans la troisième partie, une méthode de correction des effets topographiques sur la LST est développée dans le but d'étendre l'applicabilité de DisPATCh aux zones vallonnées ou montagneuses qui jouent souvent le rôle de château d'eau sur les régions semi-arides. Cette approche, basée sur un modèle de bilan d'énergie à base physique, est testée avec les données ASTER (Advanced Spaceborne Thermal Emission Reflection Radiometer) et Landsat sur la vallée d'Imlil dans le Haut Atlas Marocain. Les résultats indiquent que les effets topographiques ont été fortement réduits sur les images de LST à ~100 m de résolution et que la LST corrigée pourrait être utilisée comme une signature de l'état hydrique en montagne. Les perspectives ouvertes par ces travaux concernent la correction/désagrégation des données de précipitations et l'estimation des apports par l'irrigation pour une gestion optimisée de l'eau. / This thesis aims to improve the spatio-temporal resolution of surface water fluxes at the land surface-atmosphere interface based on appropriate models that rely on readily available multi-sensor remote sensing data. This work has been set up to further develop (disaggregation, assimilation, energy balance modeling) approaches related to soil moisture monitoring in order to optimize water management over semi-arid areas. Currently, the near surface soil moisture data sets available at global scale have a spatial resolution that is too coarse for hydrological applications. Especially, the near surface soil moisture retrieved from passive microwave observations such as AMSR-E (Advanced Microwave Scanning Radiometer-EOS) and SMOS (Soil Moisture and Ocean Salinity) data have a spatial resolution of about 60 km and 40 km, respectively. In this context, the downscaling algorithm "DISaggregation based on Physical And Theoretical scale Change" (or DisPATCh) has been developed. The near surface soil moisture variability is estimate within a low resolution pixel at the targeted 1 km resolution based on an evapotranspiration model using LST (Land surface temperature) and NDVI (vegetation index) derived from MODIS (MODerate resolution Imaging Spectroradiometer) data. Within a first step, DisPATCh is applied to SMOS and AMSR-E soil moisture products over the Murrumbidgee river catchment in Southeastern Australia and is evaluated during a one-year period. It is found that the downscaling efficiency is lower in winter than during the hotter months when DisPATCh performance is optimal. However, the temporal resolution of DisPATCh data is limited by the gaps in MODIS images due to cloud cover, and by the temporal resolution of passive microwave observations (global coverage every 3 days for SMOS). The second step proposes an approach to overcome these limitations by assimilating the 1 km resolution DisPATCh data into a simple dynamic soil model forced by reanalysis meteorological data including precipitation. The original approach combines a variational scheme for root-zone soil moisture analysis and a sequential approach for the update of surface soil moisture. The performance is assessed using ground measurements of soil moisture in the Tensift-Haouz region in Morocco and the Yanco area in Australia during 2014. It is found that the downscaling/assimilation scheme is an efficient approach to estimate the dynamics of the 1 km resolution surface soil moisture at daily time scale, even when coarse scale and inaccurate meteorological data including rainfall are used. The third step presents a physically-based method to correct LST data for topographic effects in order to offer the opportunity for applying DisPATCh over mountainous areas. The approach is tested using ASTER (Advanced Spaceborne Thermal Emission Reflection Radiometer) and Landsat data over a 6 km by 6 km steep-sided area in the Moroccan Atlas. It is found that the strong correlations between LST and illumination over rugged terrain before correction are greatly reduced at ~100 m resolution after the topographic correction. Such a correction method could potentially be used as a proxy of the surface water status over mountainous terrain. This thesis opens the path for developing new remote sensing-based methods in order to retrieve water inputs -including both precipitation and irrigation- at high spatial resolution for water management.

Decades of research have fostered a greater understanding of the environmental controls that drive tropical cyclone (TC) intensity change, yet the community has achieved only small improvements in intensity forecasting. Numerous environmental factors impact TC intensity, such as vertical wind shear and sea surface temperatures (SSTs), but little research has focused on establishing if SST change under the TC, or SST gradients, influence these intensity changes. This study investigated three methods to compute SST gradients. The first method calculated the SST change within fixed distances along the track. In the second and third methods, the SST was calculated over the distance traversed by the TC in two separate six-hour periods. By examining 455 24-hour weakening episodes in the eastern North Pacific, this study revealed that the first SST gradient method explained the highest 24-hour weakening variance for TCs located within SSTs at or lower than 26.5 degrees C.

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The experimental work involves calculation of radial distribution of heat transfer coefficient at the surface of a flat Aluminium plate being impinged by a turbulent flame jet. Heat transfer coefficient distribution at the surface is computed from the measured heat flux and temperature data using a reference method and a slope method. The heat transfer coefficient (h) has a nearly bell shaped radial distribution at the plate surface for H/d =3.3. The value of h drops by 37 % from r/d =0 to r/d= 2. Upon increasing the axial distance to H/d = 5, the stagnation point h decreased by 15%. Adiabatic surface temperature (AST) distribution at the plate surface was computed from the measured heat flux and temperature. AST values were found to be lower than the measured gas temperature values at the stagnation point. Radial distribution of gas temperature at the surface was estimated by least squares linear curve fitting through the convection dominated region of net heat flux data and was validated by experimental measurements with an aspirated thermocouple. For low axial distances (H/d =3.3), the gas temperature dropped by only 15 % from r/d = 0 to r/d = 2. Total heat flux distribution is separated into radiative and convective components with the use of calculated heat transfer coefficient and estimated gas temperatures. At H/d = 3.3, the radiation was found to be less than 25 % of the net heat flux for r/d ≤ 2. / Master of Science