The Benguela Coastal Low-Level Jet in a Changing Climate

The main focus of this thesis was the study of the Benguela Coastal Low-Level Jet (CLLJ) variability, dynamics and structure, in the present and future climates. A fundamental first step was the development of an improved CLLJ detection algorithm to provide more accurate positive results. The analysis of the Benguela CLLJ was performed initially at a global scale, including the other CLLJ regions, using an ensemble of reanalyses at 0.7o. It was shown that the Benguela CLLJ occurs along the entire year and is characterized by a spatial displacement with two local maxima where the Benguela CLLJ is more frequent (-26oS and -17.5oS). Nonetheless, a more detailed analysis was needed to understand the physical mechanisms behind the occurrence of this coastal jet. The analysis of the present climate and future projections was done through dynamical downscaling at high resolution (25 km) with uncoupled and coupled atmosphere-ocean simulations. At a regional scale the importance of the local forcing in enhancing the frequency of occurrence of the Benguela CLLJ, particularly when the coastal jet is located more north, was shown. Under a warming climate, the frequency of occurrence and intensity of the Benguela CLLJ is projected to increase due to the changes in the St. Helen High, which intensifies the flow offshore the west coast of South Africa, and due to the intensification of the land-sea thermal contrasts. However, during spring, associated to the decrease in near-surface wind speed due to higher SSTs, the frequency and intensity of the Benguela CLLJ is expected to decrease near -17.5oS. The wind resource in the Southwestern African offshore region was analysed and revealed great potential in present and future climates, particularly in the areas where the Benguela CLLJ occurs

Climatologia de ciclones extratropicais num clima de mudança: cenário RCP8.5

Tese de mestrado em Ciências Geofísicas, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2013Neste estudo elabora-se uma análise climatológica dos ciclones extratropicais e das suas trajetórias nos climas presente e futuro (cenário RCP8.5), de modo a avaliar a qualidade de dois modelos climáticos globais, EC-Earth e NCAR CCSM4, na representação desses ciclones, e estudar qual o impacto do aquecimento global nas suas propriedades. Deste modo, utiliza-se um modelo de storm-tracking para identificação e caracterização dos ciclones extratropicais no Hemisfério Norte, com base no campo da vorticidade aos 850hPa que se aplica aos dois modelos e à reanálise ERA-Interim. Os modelos em estudo são avaliados comparando os seus resultados com os da reanálise ERA-Interim do ECMWF. Em geral ambos os modelos reproduzem bem os padrões de densidade de trajetória e de ciclogénese, e das intensidades médias no Hemisfério Norte quando comparados com a ERA-Interim. Nas regiões do Noroeste do Pacífico e da América do Norte e Sul da Gronelândia, a densidade de trajetória é elevada, sendo estas regiões atingidas em média por 16 ciclones extratropicais por mês, cujo padrão das intensidades médias mostra valores entre 5.5 e 6.5 x 10-5 s-1. Estes resultados estão em boa concordância com a reanálise ERA-Interim, o que permite a avaliação do impacto das alterações climáticas nos ciclones utilizando estes dois modelos. Em resultado do aquecimento global pode-se constatar uma redução do número de ciclones extratropicais no Hemisfério Norte, em todas as estações do ano, estando ambos os modelos em concordância. Relativamente aos ciclones mais intensos existe uma ligeira diminuição da densidade de trajetória nas latitudes extratropicais do Hemisfério Norte, exceto no Verão (JJA), onde os dois modelos apontam para um ligeiro aumento, de cerca de 8%. Nas bacias oceânicas, Atlântico e Pacífico Norte, existe uma diminuição na densidade de trajetória nas regiões de maior densidade no clima presente. Contudo, existem algumas regiões onde ocorrem alterações significativas quer na localização, quer na intensidade dos ciclones. Por exemplo, na região do Mediterrâneo, o número de ciclones diminui, num clima futuro, com especial destaque para as estações intermédias.In this study a climatological analysis of extratropical cyclones and their tracks in present and future climates (scenario RCP8.5) is computed, in order to evaluate the performance of two climate models, EC-Earth and NCAR CCSM4, on the representation of these cyclones, and assess climate change impact in their properties. Thus, a storm tracking model is used to identify and characterize the extratropical cyclones in the Northern Hemisphere, based on the relative vorticity at 850hPa , which is applied to the climate models and ERA-Interim reanalysis. The two climate models are evaluated against ERA-Interim reanalysis results. Overall, both models reproduce well the pattern of storm tracks, mean intensities and cyclogenesis density in the Northern Hemisphere when compared with ERA-Interim. The regions of the Northwest Pacific, North America and South of Greenland present the highest track densities. These regions are crossed on average by 16 extratropical cyclones/month, whose mean intensities are between 5.5 and 6.5 x 10-5 s-1 . The larger mean intensities are found in these regions. The models results in the present climate show a good agreement with reanalysis, supporting its use in a climatological analysis for a future climate scenario. Under the climate change scenario RCP8.5, both models reveal a decrease in the number of extra tropical cyclones in the Northern Hemisphere for all seasons. Furthermore, the track densities of the stronger storms are reduced in the future climate, with the exception of summer (JJA), when the models indicate a slight increase, of around 8%. In both ocean basins, North Atlantic and Pacific, there is a reduction in track density in regions of higher density in the present. Nevertheless, there are some regions where significant changes in the location or intensity of cyclones occur. In the Mediterranean region, the number of cyclones decreases in that future climate, especially in spring and autumn

MAMMALS IN PORTUGAL : A data set of terrestrial, volant, and marine mammal occurrences in P ortugal

Mammals are threatened worldwide, with 26% of all species being includedin the IUCN threatened categories. This overall pattern is primarily associatedwith habitat loss or degradation, and human persecution for terrestrial mam-mals, and pollution, open net fishing, climate change, and prey depletion formarine mammals. Mammals play a key role in maintaining ecosystems func-tionality and resilience, and therefore information on their distribution is cru-cial to delineate and support conservation actions. MAMMALS INPORTUGAL is a publicly available data set compiling unpublishedgeoreferenced occurrence records of 92 terrestrial, volant, and marine mam-mals in mainland Portugal and archipelagos of the Azores and Madeira thatincludes 105,026 data entries between 1873 and 2021 (72% of the data occur-ring in 2000 and 2021). The methods used to collect the data were: live obser-vations/captures (43%), sign surveys (35%), camera trapping (16%),bioacoustics surveys (4%) and radiotracking, and inquiries that represent lessthan 1% of the records. The data set includes 13 types of records: (1) burrowsjsoil moundsjtunnel, (2) capture, (3) colony, (4) dead animaljhairjskullsjjaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8),observation in shelters, (9) photo trappingjvideo, (10) predators dietjpelletsjpine cones/nuts, (11) scatjtrackjditch, (12) telemetry and (13) vocalizationjecholocation. The spatial uncertainty of most records ranges between 0 and100 m (76%). Rodentia (n=31,573) has the highest number of records followedby Chiroptera (n=18,857), Carnivora (n=18,594), Lagomorpha (n=17,496),Cetartiodactyla (n=11,568) and Eulipotyphla (n=7008). The data setincludes records of species classified by the IUCN as threatened(e.g.,Oryctolagus cuniculus[n=12,159],Monachus monachus[n=1,512],andLynx pardinus[n=197]). We believe that this data set may stimulate thepublication of other European countries data sets that would certainly contrib-ute to ecology and conservation-related research, and therefore assisting onthe development of more accurate and tailored conservation managementstrategies for each species. There are no copyright restrictions; please cite thisdata paper when the data are used in publications.info:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Familial hypercholesterolaemia in children and adolescents from 48 countries: a cross-sectional study

Background: Approximately 450 000 children are born with familial hypercholesterolaemia worldwide every year, yet only 2·1% of adults with familial hypercholesterolaemia were diagnosed before age 18 years via current diagnostic approaches, which are derived from observations in adults. We aimed to characterise children and adolescents with heterozygous familial hypercholesterolaemia (HeFH) and understand current approaches to the identification and management of familial hypercholesterolaemia to inform future public health strategies. Methods: For this cross-sectional study, we assessed children and adolescents younger than 18 years with a clinical or genetic diagnosis of HeFH at the time of entry into the Familial Hypercholesterolaemia Studies Collaboration (FHSC) registry between Oct 1, 2015, and Jan 31, 2021. Data in the registry were collected from 55 regional or national registries in 48 countries. Diagnoses relying on self-reported history of familial hypercholesterolaemia and suspected secondary hypercholesterolaemia were excluded from the registry; people with untreated LDL cholesterol (LDL-C) of at least 13·0 mmol/L were excluded from this study. Data were assessed overall and by WHO region, World Bank country income status, age, diagnostic criteria, and index-case status. The main outcome of this study was to assess current identification and management of children and adolescents with familial hypercholesterolaemia. Findings: Of 63 093 individuals in the FHSC registry, 11 848 (18·8%) were children or adolescents younger than 18 years with HeFH and were included in this study; 5756 (50·2%) of 11 476 included individuals were female and 5720 (49·8%) were male. Sex data were missing for 372 (3·1%) of 11 848 individuals. Median age at registry entry was 9·6 years (IQR 5·8-13·2). 10 099 (89·9%) of 11 235 included individuals had a final genetically confirmed diagnosis of familial hypercholesterolaemia and 1136 (10·1%) had a clinical diagnosis. Genetically confirmed diagnosis data or clinical diagnosis data were missing for 613 (5·2%) of 11 848 individuals. Genetic diagnosis was more common in children and adolescents from high-income countries (9427 [92·4%] of 10 202) than in children and adolescents from non-high-income countries (199 [48·0%] of 415). 3414 (31·6%) of 10 804 children or adolescents were index cases. Familial-hypercholesterolaemia-related physical signs, cardiovascular risk factors, and cardiovascular disease were uncommon, but were more common in non-high-income countries. 7557 (72·4%) of 10 428 included children or adolescents were not taking lipid-lowering medication (LLM) and had a median LDL-C of 5·00 mmol/L (IQR 4·05-6·08). Compared with genetic diagnosis, the use of unadapted clinical criteria intended for use in adults and reliant on more extreme phenotypes could result in 50-75% of children and adolescents with familial hypercholesterolaemia not being identified. Interpretation: Clinical characteristics observed in adults with familial hypercholesterolaemia are uncommon in children and adolescents with familial hypercholesterolaemia, hence detection in this age group relies on measurement of LDL-C and genetic confirmation. Where genetic testing is unavailable, increased availability and use of LDL-C measurements in the first few years of life could help reduce the current gap between prevalence and detection, enabling increased use of combination LLM to reach recommended LDL-C targets early in life

Mammals in Portugal: a data set of terrestrial, volant, and marine mammal occurrences in Portugal

Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n =31,573) has the highest number of records followed by Chiroptera (n = 18,857), Carnivora (n = 18,594), Lagomorpha (n = 17,496), Cetartiodactyla (n = 11,568) and Eulipotyphla (n = 7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n = 12,159], Monachus monachus [n = 1,512], and Lynx pardinus [n = 197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation-related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Critical analysis of CMIPs past climate model projections in a regional context: The Iberian climate

This is the peer reviewed version of the following article: Soares, P. M. M., Lemos, G., & Lima, D. C. A. (2023). Critical analysis of CMIPs past climate model projections in a regional context: The Iberian climate. International Journal of Climatology, 1– 21, which has been published in final form at https://doi.org/10.1002/joc.7973. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.The Iberian Peninsula is a known climate change hotspot. In the last decades, the Coupled Model Intercomparison Project (CMIP) has allowed for thousands of Global Climate Model (GCM) simulations to be conducted, an important tool to assess and understand future changes in Earth's climate. The comparison of past future projections with observations provides a robust evaluation of the models’ skill according to different emission scenarios. Here, a comprehensive performance assessment of GCM-simulated mean, maximum, and minimum temperatures, and accumulated precipitation is conducted for Iberia, by retrospectively comparing historical simulations and past future projections from CMIPs 1 to 6 with reference datasets. From means to extremes, and multi-year intra-annual cycles to inter-annual trends, GCM simulations are compared with Iberia0.1 and E-OBS observational gridded datasets, and ERA5 reanalysis. The matching between the variables’ distributions is assessed through the distribution added values (DAVs), a measure of gain or loss in performance between CMIPs. Results show relevant improvements in the description of the Iberian climate throughout the CMIP effort, for historical and past future periods. While the representation of intra-annual cycles (inter-annual trends) is enhanced after CMIP3 (CMIP2), GCMs from all CMIPs are generally able to depict the observed warming trend. Nevertheless, until 2021, a slight detrimental effect in the performance of CMIP6 models is found, in comparison with CMIP5 ones, with positive DAVs obtained only for past future temperature projections (less than 2%). A continuous monitorization of modelling accuracy for Iberia is needed, considering the increasing relevance of climate change information for adaptation strategies.info:eu-repo/semantics/acceptedVersio