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C:\Users\Vabento\Dropbox UNIVERSIDADE DE LISBOA FACULDADE DE CIÊNCIAS The use of remotely sensed Land Surface Temperature for climate monitoring Doutoramento em Ciências Geofísicas e da Geoinformação Especialidade de Deteção Remota Virgílio Alexandre da Silva Marques Bento Tese orientada por: Professor Doutor Carlos da Camara Doutora Isabel Trigo Documento especialmente elaborado para a obtenção do grau de doutor 2018 UNIVERSIDADE DE LISBOA FACULDADE DE CIÊNCIAS The use of remotely sensed Land Surface Temperature for climate monitoring Doutoramento em Ciências Geofísicas e da Geoinformação Especialidade de Deteção Remota Virgílio Alexandre da Silva Marques Bento Tese orientada por: Professor Doutor Carlos da Camara Doutora Isabel Trigo Júri: Presidente: • Doutor João Manuel de Almeida Serra, Professor Catedrático Faculdade de Ciências da Universidade de Lisboa. Vogais: • Doutora Renata Libonati dos Santos, Professora Adjunto l Departamento de Meteorologia da Universidade Federal do Rio de Janeiro (Brasil); • Doutor Mário Jorge Modesto Gonzalez Pereira, Professor Auxiliar Escola de Ciências e Tecnologia da Universidade de Trás-os-Montes e Alto Douro; • Doutora Isabel Alexandra Martinho Franco Trigo, Investigadora Principal Instituto Português do Mar e da Atmosfera (Orientadora); • Doutor Carlos Alberto Leitão Pires, Professor Auxiliar Faculdade de Ciências da Universidade de Lisboa; • Doutora Célia Marina Pedroso Gouveia, Professora Auxiliar Convidada Faculdade de Ciências da Universidade de Lisboa. Documento especialmente elaborado para a obtenção do grau de doutor Fundação para a Ciência e Tecnologia, SFRH/BD/52559/2014 2018 Acknowledgments I want to start by thanking my advisers, Professor Carlos da Camara and Doctor Isabel Trigo, for their scientific guidance and support, and for the opportunity to work with them. To Professor Carlos da Camara, I want to leave a special thank you for the unconditional belief in my aptitudes, for his always welcome ideas and his unstoppable humour, which lightened the day in many occasions. I also want to leave a special thank you to Doctor Isabel Trigo for the extremely helpful guidance and speedy responses and comments to my questions and work, for the pragmatic and down to earth perspective, which helped me to define a common thread for this thesis, and for the patience shown in the moments I went “off track”. I also want to thank Doctor Anke Duguay-Tetzlaff at Meteoswiss and Doctor Célia Gouveia at IPMA for their help and insight on two different stages of this thesis. Finally, I want to thank Doctor João Martins, who helped me grow as a scientist both with his arguing efforts (first in the MSc thesis and then in the yearly presentations I had to do in the scope of this PhD) and with his suggestions during these last 4 years. Last, but not least, I want to thank the unconditional (and sometimes conditional) support, the adventures, the gastronomical experiences and the philosophical and pertinent discussions I had with my esteemed colleagues and friends Maria and Diogo. To my parents, who have always supported my decisions and were always there when I needed them, and to Daniela, who willingly decided to put up with me, I leave a very special thank you because without you three this thesis wouldn’t be a reality. This work was supported by FCT under the grant SFRH/BD/52559/2014. i ii Abstract Satellite remote sensing of the Earth has been continuously performed from different satellite platforms/constellations since the 1960s. The amount of radiometric information available in organisations like the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) may be compiled in Fundamental Climate Data Records (FCDRs), allowing the retrieval of climate records of geophysical variables, such as Land Surface Temperature (LST). Climate Data Records (CDRs) may then be used in a wide range of applications – such as drought monitoring or climate change studies, among others. Nevertheless, instruments onboard satellites of the same series, spanning decades of observations, may have different characteristics, which imposes a difficulty in the retrieval of LST. One of the most notable examples is the electromagnetic channels at which the earth is observed by these instruments. EUMETSAT Meteosat First Generation (MFG) – first launched in 1977 and last launched in 1997 – was designed to carry an instrument with only one channel in the thermal infrared region of the electromagnetic spectrum. On the other hand, Meteosat Second Generation (MSG) satellites – first launched in 2004 and currently still in operation – were designed to cover two thermal infrared channels. Since retrievals of LST are based on information from that window of the electromagnetic spectrum, and retrieval algorithms are usually based on a split-windows (two adjacent thermal infrared windows) methodology – typically the Generalised Split Windows (GSW) – a different approach must be taken to homogenise the retrievals over a long period of time, with the aim of compiling an LST CDR. In this context, this thesis aims at developing single-channel/mono-window algorithms that can be used with information from MFG and MSG constellations of satellites. Two algorithms were developed – the Statistical Mono-Window (SMW) and the Physical Mono-Window (PMW) – and consequently two climate data records were compiled in partnership with the Satellite Application Facility on Climate Monitoring (CM SAF) and Land Surface Analysis (LSA SAF). These CDRs are now available to download at the CM SAF website. iii The mentioned retrieval algorithms are sensitive to the amount of water vapor present on the atmosphere and use information from ECMWF ERA-Interim fields. However, its relatively coarse spatial resolution may lead to systematic errors in the humidity profiles with implications in LST, particularly over mountainous areas. This limitation was studied, and its implications discussed in this thesis with focus on the improvement of the LST retrievals over these high-altitude regions. Also, a discussion is provided focusing on the best process for the calibration of regression coefficients that constitute SMW and GSW. Another objective of this thesis is to use an LST CDR for an application focused on drought monitoring. The Vegetation Health Index (VHI) has been widely used for monitoring and characterising droughts. This index takes into account ecosystem features in terms of fluctuations between prescribed maxima and minima of NDVI (Vegetation Condition Index, VCI) and of Land Surface Temperature (LST; Thermal Condition Index, TCI), and is estimated as the weighted sum of these two contributions. Since there is no a priori knowledge about vegetation and temperature contributions, VHI is typically taken as the average of both contributions, i.e., a weight of 0.5 is assumed. It is shown that by maximising the correlations between VHI and the multiscalar drought indicator SPEI (Standardized Precipitation-Evapotranspiration Index) it is possible to evaluate the relative roles of VCI and TCI for different climate regions. This application is developed over a Euro-Mediterranean region and then further applied on a global scale and over the Meteosat disk, using the LST CDR previously developed. In summary, this thesis is focused on the development, improvement and application of LST climate data records. Keywords: Climate Data Record, EUMETSAT, Land Surface Temperature, Remote Sensing, Vegetation Health Index. iv Resumo A utilização de Deteção Remota através de satélites que orbitam a Terra com o objetivo de estimar a temperatura da superfície do solo (aqui abreviada utilizando o acrónimo inglês LST proveniente de “Land Surface Temperature”) é uma técnica cuja origem remonta às décadas de 1960/70. Foi por esta altura que satélites meteorológicos, com o intuito de estudar a atmosfera e a superfície da Terra, começaram a ser desenvolvidos por organizações como a EUMETSAT, a ESA, a NASA ou a NOAA. Ao longo dos anos foram lançados diversas séries de satélites, nomeadamente as séries Meteosat da EUMETSAT (atualmente lançados 11 satélites), GOES da NOAA (lançados 16 satélites) ou os satélites japoneses Himawari (lançados 9). Estes satélites podem apresentar dois tipos de órbitas distintas: órbita geostacionária e órbita polar. A primeira é uma órbita circular definida sobre o equador e que segue a direção da rotação da Terra, ao passo que uma órbita polar (ou neste caso específico uma órbita polar aproximada ou órbita sincronizada com o sol) se distingue por se realizar a altitudes mais baixas, observando um determinado ponto da superfície da Terra aproximadamente à mesma hora local. Exemplos de satélites meteorológicos com órbita geostacionária são os operados pela EUMETSAT “Meteosat First and Second Generation” (MFG e MSG), cuja relevância para esta tese é central. Uma mais valia de já existirem décadas de informação de satélite é a possibilidade de se poder começar a desenvolver aplicações climatológicas baseadas em variáveis como a LST. No entanto, é importante referir que apesar de existirem séries de satélites operados continuamente ao longo do tempo, com o evoluir do tempo evoluem também os sensores que esses satélites transportam a bordo. A LST é recuperada utilizando sensores capazes de “ver” em janelas correspondentes ao infravermelho térmico – tipicamente correspondente ao intervalo entre os 8 e 15 no espectro electromagnético – sendo que um dos - algoritmos mais utilizados para esse efeito é o denominado “Generalised Split Windows” (GSW). Este algoritmo
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