The thesis is focused on analysis and possible modifications of methods and procedures allowing the determination of various cloud types using the satellite data. Today, the main methods are concentrated around two the most applied international projects, one being developed for the instrument MODIS on board American Terra and Aqua polar satellites, and the other one being developed for the instrument SEVIRI on the European geostationary satellite Meteosat. The algorithms used for automatic discrimination of several cloud types operationally are created on these models. The American program MODIS Atmosphere have been created by NASA and the European program NWC SAF have been developed by organization EUMETSAT. Content of the thesis is to specify how input parameters influence final result of cloud determination in both models, and how results are depending on the external meteorological and geographical conditions during data acquisition. The effort will be given to identification of main drawbacks at two models and to identify conditions when their respective application is limited, their results different and to make steps towards possible modifications to mitigate the drawbacks. The analysis will use ground data and optimal developed procedure for validation of satellite data processing. The...

El objetivo de este trabajo es estudiar la dinámica de los aerosoles en Perú y América del Sur, a partir de las imágenes promedios mensuales del espesor óptico de aerosoles (AOT) en la longitud de onda de 550 nm estimados por el sensor MODIS (Moderate Resolution Imaging Spectroradiometer) a bordo de los satélites TERRA y AQUA, para un periodo de catorce años (2000-2013). La importancia del estudio de la dinámica de los aerosoles es que vamos a tener en cuenta a la hora de usar los modelos de corrección atmosférica. El área de estudio corresponde a las latitudes 4°N a 24°S y las longitudes 83°W a 33°W (que abarca Perú y parte de América de Sur). Se ha usado datos AOT in-situ horarios de 6 estaciones AERONET de América del Sur (Brasil: Rio Branco, Paraná Ji, Alta Foresta, Campo Grande, Chile: Arica y Bolivia: La Paz). Para cada estación, se han obtenido los promedios mensuales y se ha generado una serie de tiempo AOT mensual de 14 años (168 datos AOT). Se emplearan datos imágenes AOT productos mensuales de nivel L3, 166 datos imágenes AOT procedentes del sensor MODIS abordo del satélite TERRA durante el período del 2000 al 2013, y 138 datos imágenes AOT productos mensuales procedentes del sensor MODIS abordo del satélite AQUA durante el periodo del 2002 al 2013. El software web GIOVANNI es usado para estimar las imágenes productos mensuales AOTMODIS-TERRA y AOT-MODIS-AQUA de 1º x 1º (110 km x 110 km) que abarca un área de aproximadamente 16 940 000 km2 y también para estimar las series de tiempo AOT-MODIS-TERRA y AOT-MODIS-AQUA promedios mensuales y promedios espaciales del área de estudio (166 datos AOT para TERRA y 138 datos AOT para AQUA). La serie de tiempo AOT-MODIS-TERRA toma valores máximos y mínimos entre 0,0 a 0,499, pudiendo obtener que sus valores máximos se presentan en la temporada seca del hemisferio sur (agosto a noviembre) durante los 14 años. La serie de tiempo AOT-MODIS-AQUA toma valores máximos y mínimos entre 0,0 a 0,493, pudiendo obtener que sus valores máximos se presentan en la temporada seca (agosto a noviembre) durante los 12 años. La serie de tiempo AOT-AERONET para Brasil (cuatro estaciones) muestra una variación estacional con máximos en la estación seca durante los 14 años y para Chile y Bolivia (una estación para Chile y una estación para Bolivia) muestra una variación estacional muy diferente a los datos AOT/MODIS, teniendo pocos registros de datos AOT. Las gráficas de dispersión de las series de tiempo AOT-MODIS vs AOT-AERONET muestran una alta correlación entre 0.8 y 0.9 en cuatro estaciones de Brasil y una baja correlación de 0.4 en una estación de Chile y 0.6 en una estación de Bolivia. / Tesis

Mountain meadows in the western USA are experiencing increased rates of conifer encroachment due to climate change and land management practices. Past research has focused on conifer removal as a meadow restoration strategy, but there has been limited work on conifer transpiration in a pre-restoration state. Meadow restoration by conifer removal has the primary goal of recovering sufficient growing season soil moisture necessary for endemic, herbaceous meadow vegetation. Therefore, conifer water use represents an important hydrologic output toward evaluating the efficacy of this active management approach. This study quantified and evaluated transpiration of encroached conifers in a mountain meadow using sap flow prior to restoration by tree removal. We report results of lodgepole pine transpiration estimates for an approximate 1-year period and an evaluation of key environmental variables influencing water use during a dry growing season. The study was conducted at Rock Creek Meadow (RCM) in the southern Cascade Range near Chester, CA, USA. Sap flow data were collected in a sample of lodgepole pine and scaled on a per-plot basis to the larger meadow using tree survey data within a stratified random sampling design (simple scaling). These estimates were compared to a MODIS evapotranspiration (ET) estimate for the meadow. The 1-year period for transpiration estimates overlapped each of the 2019 and 2020 growing seasons partially. The response of lodgepole pine transpiration to solar radiation, air temperature, vapor pressure deficit, and volumetric soil water content was investigated by calibrating a modified Jarvis-Stewart (MJS) model to hourly sap flow data collected during the 2020 growing season, which experienced below average antecedent winter precipitation. The model was validated using spatially different sap flow data in the meadow from the 2021 growing season, also part of a dry year. Calibration and validation were completed using a MCMC approach via the DREAM(ZS) algorithm and a generalized likelihood (GL) function, enabling model parameter and total uncertainty assessment. We also used the model to inform transpiration scaling for the calibration period in select plots in the meadow, which allowed comparison with simple scaling transpiration estimates. Average total lodgepole pine transpiration at RCM was estimated between 220.57 ± 25.28 and 393.39 ± 45.65 mm for the entire campaign (mid-July 2019 to mid-August 2020) and between 100.22 ± 11.49 and 178.75 ± 20.74 mm for the 2020 partial growing season (April to mid-August). The magnitude and seasonal timing were similar to MODIS ET. The model showed good agreement between observed and predicted sap velocity for the 2020 partial growing season (RMSE = 1.25 cm h-1), with meteorological variables modulating early growing season sap flow and volumetric soil water content decline imposing transpiration decrease in the late growing season. The model validation performed similarly to calibration in terms of performance metrics and the influence of meteorological variables. The consistency of the declining volumetric soil water content effect during the late growing season between periods could not be evaluated due to an abridged validation period. Overall, the implementation GL-DREAM(ZS) showed promise for future use in MJS models. Lastly, the model derived transpiration estimates for the 2020 partial growing season showed some of the potential utility in using the MJS model to scale sap flow at the study locale. It also highlights some of the key limitations of this approach as it is executed in the present study.

Yes / Dust storms are one of the natural phenomena, which have increased in frequency in recent years in North Africa, Australia and northern China. Satellite remote sensing is the common method for monitoring dust storms but its use for identifying dust storms over sandy ground is still limited as the two share similar characteristics. In this study, an artificial neural network (ANN) is used to detect dust storm using 46 sets of data acquired between 2001 and 2010 over North Africa by the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites. The ANN uses image data generated from Brightness Temperature Difference (BTD) between bands 23 and 31 and BTD between bands 31 and 32 with three bands 1, 3, and 4, to classify individual pixels on the basis of their multiple-band values. In comparison with the manually detection of dust storms, the ANN approach gave better result than the Thermal Infrared Integrated Dust Index approach for dust storms detection over the Sahara. The trained ANN using data from the Sahara desert gave an accuracy of 0.88 when tested on data from the Gobi desert and managed to detect 90 out of the 96 dust storm events captured worldwide by Terra and Aqua satellites in 2011 that were classified as dusty images on NASA Earth Observatory. / IEEE Geoscience and Remote Sensing Society

Ce travail s'inscrit dans le cadre de recherche sur les maladies vectorielles de Lyme et Virus du Nil au sein de l'Agence de Santé Publique du Canada (ASPC) ayant pour finalité d'évaluer et de cartographier les risques sanitaires associés à ces maladies infectieuses liées au climat aux échelles municipales, provinciales et fédérale. Dans ce contexte, cette recherche vise à démontrer la faisabilité, la pertinence et les enjeux de recourir aux méthodes de réduction d'échelle pour obtenir à une haute résolution spatio-temporelle (100/30 m et 1 jour) avec au plus des marges d'erreur de 2 unités, des déterminants climatiques et microclimatiques (DCMC) en milieu hétérogène du Canada. Un cadre méthodologique d'application des méthodes de réduction d'échelle, Random Forest Regression (RFR), Thermal sharpening (TsHARP), Pixel block intensity modulation (PBIM), a été proposé pour estimer la température de surface (LST) de MODIS 1000 m à 100/30 m. Des expérimentations basées sur cette approche ont été effectuées sur trois sites au Québec à différentes époques. Les résultats, spatialement représentatifs, ont été validés avec les températures de l'air et celles prises par de Landsat 08 avec des marges d'erreur autour de 2°C. L'analyse des résultats démontre la capacité effective des méthodes de réduction d'échelle à discriminer la LST dans l'espace. Toutefois, dans le contexte du projet de l'ASPC, ces résultats sont non concluants à 100/30 m en l'absence d'une plus-value significative au plan spatial de LST. Cette analyse a conduit à discuter des enjeux temporels, spatiaux, méthodologiques et de gestion de gros volumes de données en lien avec la réduction d'échelle dans le contexte du projet. / This research is part of the Public Health Agency of Canada's (PHAC) research on Lyme and West Nile Virus vector-borne diseases, which aims to assess and map the health risks associated with these climate-related infectious diseases at the municipal, provincial and federal levels. In this context, this research aims to demonstrate the feasibility, relevance and challenges of using downscaling methods to obtain high spatial and temporal resolution (100/30 m and 1 day), with margins of error of no more than 2 units, of climatic and microclimatic determinants (CMDs) in a heterogeneous Canadian environment. A methodological framework for the application of downscaling methods, Random Forest Regression (RFR), Thermal sharpening (TsHARP), Pixel block intensity modulation (PBIM), has been proposed to estimate the surface temperature (LST) from MODIS 1000 m to 100/30 m. Experiments with our approach were carried out at three sites in Quebec at different times. The spatially representative results were validated with air and Landsat 08 temperatures with error margins around 2°C. The analysis of our results demonstrates the effective capacity of downscaling methods to discriminate LST in space. However, in the context of the ASPC project, these results are inconclusive at 100/30 m in the absence of a significant, expected increase in the spatial accuracy of LST. This analysis led to a discussion of the temporal, spatial, methodological and large data volume management issues related to downscaling in the context of the project.

Human-caused forest fires have increased in magnitude and frequency, affecting global vegetation and requiring a re-evaluation of fire regimes. Changing fire regimes have led to reduced burned areas in fire- dependent ecosystems and increased areas in fire-independent ecosystems, resulting in changes in land cover and posing a threat to native plant communities. This study focuses on monitoring vegetation recovery after fires in California, USA, using the Enhanced Vegetation Index (EVI) from MODIS time series. The goal is to determine the full recovery time and half recovery time (HRT) after forest fires in year 2017 and analyze the influence of burn severity on three land cover classes in two different climate zones in California.Analyzes show that the "Closed Forest" land cover type exhibits the longest recovery period, followed by the "Open Forest" type and “Herbaceous/Shrub” type in both climate zones but no general connection between recovery time and climate zone was observed. It is found that burn severity degree affects HRT but not the full recovery time in both Mediterranean and Semi-arid climate zones. The study mainly highlights the variations in forest fire recovery patterns between land cover types, as well as differences observed between climate zones.

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La plataforma interior del Sur de la provincia de Buenos Aires (El Rincón) es un ambiente altamente variable, escasamente conocido y de gran importancia para la región. En la presente investigación se realiza por primera vez un estudio integral del área relacionando la variabilidad climática, las características espacio-temporales de la hidrografía de la plataforma interior y sus implicancias en la vida marina y consecuentemente en la pesca como actividad económica regional. A partir del análisis de la variabilidad de las precipitaciones, balances hídricos y caudales de los principales ríos del área de estudio con relación al ENSO, se concluyó que el Niño 2002-2003 generó un período húmedo en el área de estudio. A su vez, la Niña 2007-2008 generó una fuerte sequia en esos años y mitad de 2009. El evento Niña 2007-2008 tuvo un gran impacto en la hidrografía costera del área de estudio por la disminución en las precipitaciones y en el monto total de las descargas de ríos que aportan agua dulce, nutrientes y sedimentos. La altura del oleaje de la zona costera de Monte Hermoso y Pehuén Co oscila entre 0,25 y 1 m, con períodos menores a 8 segundos. Alturas mayores a 2 m y períodos mayores a 12 segundos tienen sólo el 1 % de probabilidad de ocurrir. Estos resultados son directamente aplicables a la deriva litoral de la zona de estudio y al transporte de sedimentos. La temperatura superficial del mar osciló entre 6 °C a mediados de invierno y 23 °C en verano. La salinidad del mar es muy alta (entre ~34 y 36) como también la turbidez (entre 20 y 100 NTU). Se demostró entonces la gran influencia del estuario de Bahía Blanca en la hidrografía de la zona costera de Pehuén Co y Monte Hermoso. Se utilizaron imágenes satelitales Aqua MODIS (1 km) como herramienta para obtener datos físicos y biológicos de la zona del Rincón. Se realizó la validación del producto temperatura superficial del mar en la zona de El Rincón con datos in situ y se obtuvieron resultados precisos. Por otro lado, se determinaron las propiedades ópticas inherentes aph, bbp y adg (absorción por fitoplancton, retrodispersión por material particulado y absorción por material detrítico) como proxy de las características físico-biológicas del agua y la clorofila-a a la vez que se analizó la variabilidad inter-anual y estacional de las mismas en el período 2002-2010. El análisis de las series de tiempo demostró que la variabilidad temporal de los parámetros estuvo dominada por la señal estacional. En la zona costera aph y bbp presentaron una tendencia positiva y una fuerte variabilidad inter-anual. Finalmente, se relacionó los desembarques totales anuales de pesca en el puerto de Bahía Blanca con la variabilidad interanual de los parámetros físico-biológicos oceanográficos y atmosféricos. Se demostró que las fluctuaciones climáticas evidenciadas en el presente estudio a partir de las precipitaciones y caudales, generan cambios en la composición física del agua alterando en principio la base de la cadena trófica marina (fitoplancton) y directa o indirectamente al zooplancton y las comunidades pelágicas. / The inner shelf of the South of the Buenos Aires Province (El Rincón) is a highly variable environment, which is very important for the natural resources of the area and it remains unknown. In the present work a comprehensive study of the relationship between the climate variability, the spatial and temporal physical characteristics of the inner shelf and the impacts on the marine biology is presented for the very first time. The climate variability was analyzed by the oscillation of the precipitations, the water balances and discharge of the main rivers. It was conclude that the Niño event (2002-2003) produced a wet period in the area. On contrary, the Niña event (2007-2008) was responsible of a strong drought which continued until mid 2009. La Niña event had a major impact on the coastal hydrography of the study area because of the diminution of the precipitations and the discharge of the rivers, which provide fresh water, nutrients and sediments to the system. Most of significant wave heights of the coastal zone of Monte Hermoso and Pehuén Co ranged between 0,25 and 1 m, related to significant periods of less than 8 seconds. Wave heights of more than 2 m and periods longer than 12 seconds had only 1 % chance of occurring. These results are important to explain the littoral drift and sediment transport of the study area. Sea surface temperature oscillated between 6 °C in winter and 23 °C in summer. High values of salinity and turbidity were registered (~34 – 36, 20 – 100 NTU, respectively). The physical characteristics of the coastal hydrography of Monte Hermoso and Pehuén Co are clearly driven by the influence of the Bahia Blanca estuary plume on the study area. MODIS Aqua satellite imagery was used as a tool to obtain physical and biological data of El Rincón zone. The validation of Sea Surface Temperature product was done with in situ dataset obtaining accurate results. In addition, the inherent optical properties (IOPs) aph, bbp and adg (absorption by phytoplankton, backscattering by particulate matter, absorption by colored dissolved organic matter) and chlorophyll-a were used as a proxy to determine the spatial and temporal distribution of the physical and biological characteristics of the sea between 2002-2010. The time series analysis demonstrated that the temporal variability of the parameters was mainly produced by the seasonal signal. In the coastal zone, aph and bbp had positive tendency and a high inter annual variability. Finally, annual fish landings in the Bahía Blanca port were related to inter annual variability of the physical-biological oceanographic and atmospheric parameters. The climate fluctuations (precipitations and discharge of the rivers) produce changes in the physical composition of the water, altering the sea food web (phytoplankton) and the zooplankton and pelagic communities.

A large portion of Earth¿s terrestrial surface is subject to arid climatic water stress. As in these regions the hydrological cycle and the vegetation dynamics are tightly interconnected, a coupled modeling of these two systems is needed to fully reproduce the ecosystems¿ behavior over time and to predict possible future responses to climate change. In this thesis, the performance of three parsimonious dynamic vegetation models, suitable for inclusion in an operational ecohydrological model, are tested in a semi-arid Aleppo pine forest area in the south-east of Spain. The first model considered, HORAS (Quevedo & Francés, 2008), simulates growth as a function of plant transpiration (T), evaluating environmental restraints through the transpiration-reference evapotranspiration ratio. The state variable related to vegetation is R, relative foliar biomass, which is equivalent to FAO crop coefficient (Allen et al., 1998), but not fixed in time. The HORAS model was then abandoned because of its unsatisfactory results, probably due to a poor simulation of evaporation and transpiration processes. As for the other two models, WUE-model and LUE-model, the state variable is the leaf biomass (Bl, kg dry mass m-2 vegetation cover). Both models simulate gross primary production (GPP), in the first case as a function of transpiration and water use efficiency (WUE), in the second case as a function of absorbed photosynthetically active radiation (APAR) and light use efficiency (LUE). Net primary production (NPP) is then calculated taking into account respiration. The modelling is focused particularly on simulating foliar biomass, which is obtained from NPP through an allocation equation based on the maximum leaf area index (LAI) sustainable by the system, and considering turnover. An analysis of the information offered by MODIS EVI, NDVI, and LAI products was also performed, in order to investigate vegetation dynamics in the study site and to select the best indices to be used as observational verification for models. MODIS EVI is reported in literature (Huete et al., 2002) to be highly correlated with leaf biomass. In accordance with the phenological cycle timing described for the Aleppo pine in similar climates (Muñoz et al., 2003), the EVI showed maximum values in spring and minimum values in winter. Similar results were found applying the aforementioned WUE- and LUE- models to the study area. Contrasting simulated LAI with the EVI series, the correlation coefficients rWUE = 0.45 and rLUE = 0.57 were found for the WUE-model and LUE-model respectively. Concerning NDVI, its own definition links this index to the ¿greenness¿ of the target, so that it appears highly linked to chlorophyll content and vegetation condition, but only indirectly related to LAI. Photosynthetic pigment concentrations are reported to be sensitive to water stress in Aleppo pine (Baquedano and Castillo, 2006) so, to compare the models¿ results with NDVI, the simulated LAI was corrected by plant water-stress. The resulting correlation coefficients were rWUE = 0.62 and rLUE = 0.59. Lastly, MODIS LAI and ET were found to be unreliable in the study area because very low compared to field data and to values reported in literature (e.g. Molina & del Campo, 2012) for the same species in similar climatic conditions. The performance of both WUE- and LUE- models in this semi-arid region is found to be reasonable. However, the LUE-model presents the advantages of a better performance, the possibility to be used in a wider range of climates and to have been extensively tested in literature. / Pasquato, M. (2013). Comparison of parsimonious dynamic vegetation modelling approaches for semiarid climates [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/34326