Clouds over the summertime Sahara: an evaluation of Met Office retrievals from Meteosat Second Generation using airborne remote sensing

Novel methods of cloud detection are applied to airborne remote sensing observations from the unique Fennec aircraft dataset, to evaluate the Met Office-derived products on cloud properties over the Sahara based on the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on-board the Meteosat Second Generation (MSG) satellite. Two cloud mask configurations are considered, as well as the retrievals of cloud-top height (CTH), and these products are compared to airborne cloud remote sensing products acquired during the Fennec campaign in June 2011 and June 2012. Most detected clouds (67 % of the total) have a horizontal extent that is smaller than a SEVIRI pixel (3 km  ×  3 km). We show that, when partially cloud-contaminated pixels are included, a match between the SEVIRI and aircraft datasets is found in 80 ± 8 % of the pixels. Moreover, under clear skies the datasets are shown to agree for more than 90 % of the pixels. The mean cloud field, derived from the satellite cloud mask acquired during the Fennec flights, shows that areas of high surface albedo and orography are preferred sites for Saharan cloud cover, consistent with published theories. Cloud-top height retrievals however show large discrepancies over the region, which are ascribed to limiting factors such as the cloud horizontal extent, the derived effective cloud amount, and the absorption by mineral dust. The results of the CTH analysis presented here may also have further-reaching implications for the techniques employed by other satellite applications facilities across the world

Satellite remote sensing of aerosols using geostationary observations from MSG-SEVIRI

Aerosols play a fundamental role in physical and chemical processes affecting regional and global climate, and have adverse effects on human health. Although much progress has been made over the past decade in understanding aerosol-climate interactions, their impact still remains one of the largest sources of uncertainty in climate change assessment. The wide variety of aerosol sources and the short lifetime of aerosol particles cause highly variable aerosol fields in both space and time. Groundbased measurements can provide continuous data with high accuracy, but often they are valid for a limited area and are not available for remote areas. Satellite remote sensing appears therefore to be the most appropriate tool for monitoring the high variability of aerosol properties over large scales. Passive remote sensing of aerosol properties is based on the ability of aerosols to scatter and absorb solar radiation. Algorithms for aerosol retrieval from satellites are used to derive the aerosol optical depth (AOD), which is the aerosol extinction integrated over the entire atmospheric column. The aim of the work described in this thesis was to develop and validate a new algorithm for the retrieval of aerosol optical properties from geostationary observations with the SEVIRI (Spinning Enhanced Visible and Infra-Red Imager) instrument onboard the MSG (Meteorological Second Generation) satellite. Every 15 minutes, MSG-SEVIRI captures a full scan of an Earth disk covering Europe and the whole African continent with a high spatial resolution. With such features MSG-SEVIRI offers the unique opportunity to explore transport of aerosols, and to study their impact on both air quality and climate. The SEVIRI Aerosol Retrieval Algorithm (SARA) presented in this thesis, estimates the AOD over sea and land surfaces using the three visible channels and one near-infrared channel of the instrument. Because only clear sky radiances can be used to derive aerosol information, a stand-alone cloud detection algorithm was developed to remove cloud contaminated pixels. The cloud mask was generated over Europe for different seasons, and it compared favorably with the results from other cloud detection algorithms - namely the cloud mask algorithm of Meteo-France for MSG-SEVIRI, and the MODIS (Moderate Resolution Imaging Spectroradiometer) algorithm. The aerosol information is extracted from cloud-free scenes using a method that minimizes the error between the measured and the simulated radiance. The signal observed at the satellite level results from the complex combination of the surface and the atmosphere contributions. The surface contribution is either parameterized (over sea), or based on a priori values (over land). The effects of atmospheric gases and aerosols on the radiance are simulated with the radiative transfer model DAK (Doubling-Adding-KNMI) for different atmospheric scenarios. The algorithm was applied for various case studies (i.e. forest fires, dust storm, anthropogenic pollution) over Europe, and the results were validated against groundbased measurements from the AERONET database, and evaluated by comparison with aerosol products derived from other space-borne instruments such as the Terra/- Aqua-MODIS sensors. In general, for retrievals over the ocean, AOD values as well as their diurnal variations are in good agreement with the observations made at AERONET coastal sites, and the spatial variations of the AOD obtained with the SARA algorithm are well correlated with the results derived from MODIS. Over land, the results presented should be considered as preliminary. They show reasonable agreement with AERONET and MODIS, however extra work is required to improve the accuracy of the retrievals based on the proposed metho

Changes in the surface energy balance over areas affected by wildfires: a diagnostic study in Continental Portugal

Tese de Mestrado, Ciências Geofísicas (Meteorologia e Oceanografia), 2021, Universidade de Lisboa, Faculdade de CiênciasThe Mediterranean region is recurrently affected by large wildfire events. Because of climate change associated to anthropogenic factors, wildfire events have become more frequent and have been affecting larger areas, and it is likely that the problem will become even more serious in the near future. It is therefore important to better understand the impacts of large wildfire events both on surface parameters and surface energy balance. Downward surface shortwave and longwave fluxes (DSSF, DSLF), surface albedo (AL), surface emissivity (EM) and land surface temperature (LST) are retrieved from the Satellite Application Facility on Land Surface Analysis (LSA-SAF). Besides analysing each parameter, this work uses this information to study longwave and shortwave radiation (LW, SW) balances and the surface net radiation. Based on the analysis of 5 different areas affected by wildfires in 2020, it can be inferred that, as seen in previous studies, DSSF and DSLF do not show significant changes after the fire, AL and EM show a decrease, especially for the larger burned areas, and LST presents an increase between 1.5℃ and 10℃ after the fires. This increase in LST is the main cause for the increased differences, between averaged values for burned (BB) and unburned (UB) pixels, in the LW balances that lead to changes in net radiation. The LSA-SAF also disseminates data computed using a surface balance model (SEB), namely evapotranspiration (EVAP), sensible and latent heat fluxes (H, LE), and skin temperature (TSK). A comparison between TSK and LST shows that the model is not well representing the surface behaviour. Moreover, a comparison of the net radiation results obtained with the SEB model with the ones obtained through remotely sensed data indicates that LE and H are not enough to characterize the net radiation and therefore the ground heat flux (G) cannot be neglected.A região mediterrânica é recorrentemente afetada por grandes incêndios florestais. As alterações climáticas associadas a fatores antropogénicos, têm vindo a tornar episódios de fogo mais frequentes e a afetar maiores áreas. Torna-se, assim, cada vez mais premente entender os impactos dos grandes incêndios florestais, especialmente sobre os parâmetros de superfície e sobro o balanço de energia. O presente trabalho utiliza dados, obtidos através de deteção remota por satélite, disseminados pela Satellite Application Facility on Land Surface Analysis (LSA-SAF). Os dados baseiam-se em observações efetuadas pelo Spinning Enhanced Visible and Infrared Imager (SEVIRI), o radiómetro a bordo dos satélites da série Meteosat Second Generation (MSG). Os dados de satélite disseminados e analisados neste trabalho consistem nos fluxos radiativos à superfície de ondas curtas e longas (downward surface shortwave and longwave fluxes – DSSF, DSLF), no albedo (AL), na emissividade (EM) e na temperatura de superfície do solo (land surface temperature – LST). Estes dados permitem estudar as alterações nos balanços radiativos de ondas curtas (shortwave radiation – SW) e longas (longwave radiation – LW) e no balanço radiativo (resultante da combinação dos dois primeiros balanços) e avaliar o impacto dos incêndios nas propriedades da superfície e no balanço energético. Neste trabalho foram analisadas cinco áreas afetadas por incêndios em 2020, quatro das quais em Portugal e uma em Espanha. Para além dos dados de satélite, a LSA-SAF também dissemina dados obtidos através de um modelo de balanço de energia à superfície (surface energy balance - SEB), nomeadamente a evapotranspiração (EVAP), os fluxos de calor sensível e latente (sensible and latent heat fluxes – H, LE) e a temperatura da pele (skin temperature – TSK). Com o objetivo de analisar o desempenho do modelo, efetuaram-se comparações entre os resultados obtidos pelo modelo SEB e os resultados derivados de observações de satélite. Para cada uma das áreas estudadas, selecionaram-se conjuntos de pixéis queimados (burned – BB) e não queimados (unburned – UB) e procedeu-se a uma comparação sistemática do comportamento dos parâmetros selecionados antes e após os eventos de incêndio. Os dados considerados foram entre as 12h e as 14h30 UTC, período de tempo que, em geral, inclui o máximo diário de LST. A fração do ano considerada, entre maio e outubro de 2020, que contém um número suficiente de observações por satélite, é adequada para analisar o comportamento das variáveis escolhidas. A análise dos resultados obtidos através de dados de satélite está em concordância com resultados de estudos anteriores. A DSSF e a DSLF não mostram diferenças significativas após os incêndios, um resultado esperado considerando que estes fluxos não dependem das características do solo. O AL e a EM sofrem uma descida nos pixéis BB após o incêndio, sendo a descida mais acentuada nos incêndios onde a área queimada é maior. Com o escurecimento do solo e diminuição da densidade de vegetação, é de esperar que a LST aumente após a ocorrência de um incêndio, o que, de facto, se observou. A LST aumenta em todos os casos estudados entre 1.5℃ e 10℃. No caso do balanço de SW, observam-se anomalias que são consistentes com as anomalias observadas no AL. Já no caso do balanço de LW, tem-se, na maior parte dos casos, um aumento absoluto da radiação LW que sai dos pixéis BB, a qual resulta do aumento de LST. O impacto das anomalias de EM neste balanço é mais difícil de analisar considerando que as estimativas são utilizadas para estimar a LST. Em 4 dos 5 casos, observase uma anomalia no balanço de LW que é superior à no balanço de SW. Assim sendo, quando se calcula o balanço total de radiação, como sendo a soma dos balanços de SW e LW, observam-se anomalias no sentido das anomalias do balanço de LW. Tem-se, assim, para a maioria dos eventos, uma diminuição do balanço total de radiação depois de um incêndio, a qual resulta do maior aumento de LW libertada para o espaço em comparação com a absorção de SW. Na análise do modelo SEB, começa por comparar-se a TSK com a LST, pois, para uma boa representação das alterações das características do solo, a TSK deve seguir de perto o comportamento da LST. Apesar de, mostrar um aumento tal como a LST, o aumento da TSK é significativamente menor, no máximo metade do observado na LST. A EVAP, bem como o LE que resulta da EVAP, mostram uma diminuição após os incêndios. Este resultado é expectável considerando a diminuição/extinção de vegetação provocada pelo incêndio. No caso de H, tendo em conta o aumento da temperatura à superfície, é esperado um aumento de H após o incêndio. Este aumento é observado na maior parte dos casos. Utilizando os dois fluxos de calor sensível e latente à superfície (H e LE) e desprezando o fluxo de calor do solo (ground heat flux – G), pode-se estimar o balanço total de radiação da superfície como sendo a soma de H e LE mas, neste caso, ao contrário dos resultados obtidos quando se somam os balanços de SW e LW (baseados nas observações por satélite) não se observa nenhuma alteração após o incêndio. Este resultado sugere que se averigue qual o impacto do fator G no cálculo do balanço. Recalculou-se, portanto, o balanço total de radiação total à superfície como sendo a soma dos fluxos H, LE e G, sendo de notar que, uma vez que, neste trabalho, G é obtido através de dados de satélite, pode não corresponder ao valor estimado que é calculado pelo modelo (o qual resulta da resolução da equação de balanço de energia). Apesar disso, estes novos resultados, aproximam-se dos resultados obtidos com base em dados de satélite no período de tempo antes do incêndio. Na maior parte dos casos, a inclusão de G é relevante para que os resultados obtidos sejam compatíveis com os resultados obtidos com dados de satélite. Em geral, não há um sinal significativo do incêndio na série temporal dos dados modelados. Apenas num dos casos se observa um aumento da radiação total que parece resultar do aumento de G, mas deve novamente notar-se que tal se pode dever ao facto de G ter sido calculado com dados de satélite e não pelo modelo. Isto, porque como já referido, a LST obtida pelos dados de satélite mostra um aumento muito mais significativo que o observado nos dados de TSK provenientes do modelo SEB. Os resultados dos dados de satélite são consistentes com os resultados observados em estudos anteriores e mostram a relevância que a LST tem nas anomalias observadas no balanço radiativo à superfície. Por outro lado, os resultados obtidos com o modelo SEB apresentaram algumas discrepâncias quando comparados com os resultados obtidos com dados de satélite, representando mal o comportamento do solo depois da ocorrência de um incêndio. Pôde-se também observar que, desprezando o G, os resultados perdem qualidade e, por isso, G é uma variável relevante para o estudo realizado. Este resultado mostra que seria importante que o conjunto de dados disseminados pela LSA-SAF incluísse os valores de G. Os resultados do modelo poderiam também ser melhorados, caso a TSK obtida fosse mais consistente com a LST detetada remotamente; para isso em vez de recorrer a valores estáticos da fração de cobertura vegetal, seria vantajoso utilizar valores diários da fração de coberto vegetal

The life cycle of anvil cirrus clouds from a combination of passive and active satellite remote sensing

Anvil cirrus clouds form in the upper troposphere from the outflow of ice crystals from deep convective cumulonimbus clouds. By reflecting incoming solar radiation as well as absorbing terrestrial thermal radiation, and re-emitting it at significantly lower temperatures, they play an important role for the Earth’s radiation budget. Nevertheless the processes that govern their life cycle are not well understood and, hence, they remain one of the largest uncertainties in atmospheric remote sensing and climate and weather modelling. In this thesis the temporal evolution of the anvil cirrus properties throughout their life cycle is investigated, as is their relationship with the meteorological conditions. For a comprehensive retrieval of the anvil cirrus properties, a new algorithm for the remote sensing of cirrus clouds called CiPS (Cirrus Properties from SEVIRI) is developed. Utilising a set of artificial neural networks, CiPS combines the large spatial coverage and high temporal resolution of the imaging radiometer SEVIRI aboard the geostationary satellites Meteosat Second Generation, with the high vertical resolution and sensitivity to thin cirrus clouds of the lidar CALIOP aboard the polar orbiting satellite CALIPSO. In comparison to CALIOP, CiPS detects 71 % and 95 % of all cirrus clouds with an ice optical thickness (IOT) of 0.1 and 1.0 respectively. Furthermore, CiPS retrieves the corresponding cloud top height, IOT, ice water path (IWP) and, by parameterisation, effective ice crystal radius. This way, macrophysical, microphysical and optical properties can be combined to interpret the temporal evolution of the anvil cirrus clouds. Together with a tool for identifying convective activity and a new cirrus tracking algorithm, CiPS is used to analyse the life cycle of 132 anvil cirrus clouds observed over southern Europe and northern Africa in July 2015. Although the anvil cirrus clouds grow optically thick during the convective phase, they become thinner at a rapid pace as convection ceases. Two hours after the last observed convective activity, 92±7 % of the anvil cirrus area has IOT_CiPS < 1 and IWP_CiPS < 30 g m−2 on average, with highest probability density around 0.1–0.2 and 1.5–3 g m−2 respectively. During the same time period, the cloud top height is observed to decrease. Since this is observed for both long-lived and short-lived anvil cirrus, it is deduced that in this life phase the amount of ice in the anvil is mainly controlled by sedimentation. This is in line with a corresponding decrease in the estimated effective radius. While the convective strength has no evident effect on the IOT and IWP, stronger vertical updraught is clearly correlated with higher cloud top height and larger effective radius. Larger ice crystals are, however, observed to be removed effectively within 2-3 h after convection has ceased, suggesting that the convective strength has no impact on the ice crystal sizes in ageing anvils. In this life stage, upper tropospheric relative humidity, as derived from ERA5 reanalysis data, is shown to have a larger impact on the anvil cirrus life cycle, where higher relative humidity govern larger and especially more long-lived anvil cirrus clouds

Land Surface Temperature Product Validation Best Practice Protocol Version 1.0 - October, 2017

The Global Climate Observing System (GCOS) has specified the need to systematically generate andvalidate Land Surface Temperature (LST) products. This document provides recommendations on goodpractices for the validation of LST products. Internationally accepted definitions of LST, emissivity andassociated quantities are provided to ensure the compatibility across products and reference data sets. Asurvey of current validation capabilities indicates that progress is being made in terms of up-scaling and insitu measurement methods, but there is insufficient standardization with respect to performing andreporting statistically robust comparisons.Four LST validation approaches are identified: (1) Ground-based validation, which involvescomparisons with LST obtained from ground-based radiance measurements; (2) Scene-based intercomparisonof current satellite LST products with a heritage LST products; (3) Radiance-based validation,which is based on radiative transfer calculations for known atmospheric profiles and land surface emissivity;(4) Time series comparisons, which are particularly useful for detecting problems that can occur during aninstrument's life, e.g. calibration drift or unrealistic outliers due to undetected clouds. Finally, the need foran open access facility for performing LST product validation as well as accessing reference LST datasets isidentified

Characterising Saharan Dust Sources and Export using Remote Sensing and Regional Modelling

The PhD-thesis aims to characterise the Saharan dust cycle at diffent seasons using satellite remote sensing techniques and regional modelling studies. A dust index based on 15-minute infrared satellite measurements provided by the SEVIRI instrument onboard the Meteosat Second Generation (MSG) satellite is used to infer spatio-temporal charcteristics of dust sources north of 5°N over Africa since March 2006. The spatial distribution of dust sources points towards the importance of endorehic drainage systems in mountain areas. The temporal distribution of the time-of-day when dust mobilisation starts shows maximum activity during local morning hours, pointing towards the role of the breakdown of the nocturnal low-level jet. Details of the role and ability of the low-level jet breakdown for dust entrainment were studied using regional modelling. Furthermore, the seasonal dust export towards the tropical North Atlantic is considered using regional modelling

The life cycle of anvil cirrus clouds from a combination of passive and active satellite remote sensing

Anvil cirrus clouds form in the upper troposphere from the outflow of ice crystals from deep convective cumulonimbus clouds. By reflecting incoming solar radiation as well as absorbing terrestrial thermal radiation, and re-emitting it at significantly lower temperatures, they play an important role for the Earth’s radiation budget. Nevertheless the processes that govern their life cycle are not well understood and, hence, they remain one of the largest uncertainties in atmospheric remote sensing and climate and weather modelling. In this thesis the temporal evolution of the anvil cirrus properties throughout their life cycle is investigated, as is their relationship with the meteorological conditions. For a comprehensive retrieval of the anvil cirrus properties, a new algorithm for the remote sensing of cirrus clouds called CiPS (Cirrus Properties from SEVIRI) is developed. Utilising a set of artificial neural networks, CiPS combines the large spatial coverage and high temporal resolution of the imaging radiometer SEVIRI aboard the geostationary satellites Meteosat Second Generation, with the high vertical resolution and sensitivity to thin cirrus clouds of the lidar CALIOP aboard the polar orbiting satellite CALIPSO. In comparison to CALIOP, CiPS detects 71 % and 95 % of all cirrus clouds with an ice optical thickness (IOT) of 0.1 and 1.0 respectively. Furthermore, CiPS retrieves the corresponding cloud top height, IOT, ice water path (IWP) and, by parameterisation, effective ice crystal radius. This way, macrophysical, microphysical and optical properties can be combined to interpret the temporal evolution of the anvil cirrus clouds. Together with a tool for identifying convective activity and a new cirrus tracking algorithm, CiPS is used to analyse the life cycle of 132 anvil cirrus clouds observed over southern Europe and northern Africa in July 2015. Although the anvil cirrus clouds grow optically thick during the convective phase, they become thinner at a rapid pace as convection ceases. Two hours after the last observed convective activity, 92±7 % of the anvil cirrus area has IOT_CiPS < 1 and IWP_CiPS < 30 g m−2 on average, with highest probability density around 0.1–0.2 and 1.5–3 g m−2 respectively. During the same time period, the cloud top height is observed to decrease. Since this is observed for both long-lived and short-lived anvil cirrus, it is deduced that in this life phase the amount of ice in the anvil is mainly controlled by sedimentation. This is in line with a corresponding decrease in the estimated effective radius. While the convective strength has no evident effect on the IOT and IWP, stronger vertical updraught is clearly correlated with higher cloud top height and larger effective radius. Larger ice crystals are, however, observed to be removed effectively within 2-3 h after convection has ceased, suggesting that the convective strength has no impact on the ice crystal sizes in ageing anvils. In this life stage, upper tropospheric relative humidity, as derived from ERA5 reanalysis data, is shown to have a larger impact on the anvil cirrus life cycle, where higher relative humidity govern larger and especially more long-lived anvil cirrus clouds

Detection of vegetation drying signals using diurnal variation of land surface temperature: Application to the 2018 East Asia heatwave

Satellite-based vegetation monitoring provides important insights regarding spatiotemporal variations in vegetation growth from a regional to continental scale. Most current vegetation monitoring methodologies rely on spectral vegetation indices (VIs) observed by polar-orbiting satellites, which provide one or a few observations per day. This study proposes a new methodology based on diurnal changes in land surface temperatures (LSTs) using Japan's geostationary satellite, Himawari-8/Advanced Himawari Imager (AHI). AHI thermal infrared observation provides LSTs at 10-min frequencies and ∼ 2 km spatial resolution. The DTC parameters that summarize the diurnal cycle waveform were obtained by fitting a diurnal temperature cycle (DTC) model to the time-series LST information for each day. To clarify the applicability of DTC parameters in detecting vegetation drying under humid climates, DTC parameters from in situ LSTs observed at vegetation sites, as well as those from Himawari-8 LSTs, were evaluated for East Asia. Utilizing the record-breaking heat wave that occurred in East Asia in 2018 as a case study, the anomalies of DTC parameters from the Himawari-8 LSTs were compared with the drying signals indicated by VIs, latent heat fluxes (LE), and surface soil moisture (SM). The results of site-based and satellite-based analyses revealed that DTR (diurnal temperature range) correlates with the evaporative fraction (EF) and SM, whereas Tmax (daily maximum LST) correlates with LE and VIs. Regarding other temperature-related parameters, T0 (LST around sunrise), Ta (temperature rise during daytime), and δT (temperature fall during nighttime) are unstable in quantification by DTC model. Moreover, time-related parameters, such as tm (time reaching Tmax), are more sensitive to topographic slope and geometric conditions than surface thermal properties at humid sites in East Asia, although they correlate with EF and SM at a semi-arid site in Australia. Additionally, the spatial distribution of the DTR anomaly during the 2018 heat wave corresponds with the drying signals indicated as negative SM anomalies. Regions with large positive anomalies in Tmax and DTR correspond to area with visible damage to vegetation, as indicated by negative VI anomalies. Hence, combined Tmax and DTR potentially detects vegetation drying indetectable by VIs, thereby providing earlier and more detailed vegetation monitoring in both humid and semi-arid climates