Thesis advisor: Hilary Palevsky / The ocean plays a key role in global carbon cycling, taking up CO2 from the atmosphere. A fraction of this CO2 is converted into organic carbon through primary production in the surface ocean and sequestered in the deep ocean through a process known as the biological pump. The ability of the biological pump to sequester carbon away from the atmosphere is influenced by the interaction between the annual cycle of ocean mixed layer depth (MLD), primary production, and ecosystem processes that influence export efficiency. Gravitational sinking of particulate organic carbon (POC) is the largest component of the biological pump and the aspect that is best represented in Earth System Models (ESMs). I use ESM data from CESM2, an ESM participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6), to investigate how a high-emissions climate change scenario will impact POC flux globally and regionally over the 21st century. The model simulates a 4.4% decrease in global POC flux at the 100 m depth horizon, from 7.12 Pg C/yr in the short-term (2014-2034) to 6.81 Pg C/yr in the long-term (2079-2099), indicating that the biological pump will become less efficient overall at sequestering carbon. However, the extent of change varies across the globe, including the largest POC flux declines in the North Atlantic, where the maximum annual MLD is projected to shoal immensely. In the future, a multi-model comparison across ESMs will allow for further analysis on the variability of these changes to the biological pump. / Thesis (BS) — Boston College, 2021. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Departmental Honors. / Discipline: Earth and Environmental Science.

abstract: Earth-system models describe the interacting components of the climate system and technological systems that affect society, such as communication infrastructures. Data assimilation addresses the challenge of state specification by incorporating system observations into the model estimates. In this research, a particular data assimilation technique called the Local Ensemble Transform Kalman Filter (LETKF) is applied to the ionosphere, which is a domain of practical interest due to its effects on infrastructures that depend on satellite communication and remote sensing. This dissertation consists of three main studies that propose strategies to improve space- weather specification during ionospheric extreme events, but are generally applicable to Earth-system models: Topic I applies the LETKF to estimate ion density with an idealized model of the ionosphere, given noisy synthetic observations of varying sparsity. Results show that the LETKF yields accurate estimates of the ion density field and unobserved components of neutral winds even when the observation density is spatially sparse (2% of grid points) and there is large levels (40%) of Gaussian observation noise. Topic II proposes a targeted observing strategy for data assimilation, which uses the influence matrix diagnostic to target errors in chosen state variables. This strategy is applied in observing system experiments, in which synthetic electron density observations are assimilated with the LETKF into the Thermosphere-Ionosphere- Electrodynamics Global Circulation Model (TIEGCM) during a geomagnetic storm. Results show that assimilating targeted electron density observations yields on average about 60%–80% reduction in electron density error within a 600 km radius of the observed location, compared to 15% reduction obtained with randomly placed vertical profiles. Topic III proposes a methodology to account for systematic model bias arising ifrom errors in parametrized solar and magnetospheric inputs. This strategy is ap- plied with the TIEGCM during a geomagnetic storm, and is used to estimate the spatiotemporal variations of bias in electron density predictions during the transitionary phases of the geomagnetic storm. Results show that this strategy reduces error in 1-hour predictions of electron density by about 35% and 30% in polar regions during the main and relaxation phases of the geomagnetic storm, respectively. / Dissertation/Thesis / Doctoral Dissertation Applied Mathematics 2018

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No. of bitstreams: 2 Tese - Frederico Augusto Martins Valtuille Faleiro - 2016.pdf: 7096330 bytes, checksum: 04cfce04ef128c5bd6e99ce18bb7f650 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2016-03-07 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / The climate changes are one of the major threats to the biodiversity and it is expected to increase its impact along the 21st century. The climate change affect all levels of the biodiversity from individuals to biomes, reducing the ecosystem services. Despite of this, the prediction of climate change impacts on biodiversity is still a challenge. Overcoming these issues depends on improvements in different aspects of science that support predictions of climate change impact on biodiversity. The common practice to predict the climate change impact consists in formulate ecological niche models based in the current climate and project the changes based in the future climate predicted by the climate models. However, there are some recognized limitations both in the formulation of the ecological niche model and in the use of predictions from the climate models that need to be analyzed. Here, in the first chapter we review the science behind the climate models in order to reduce the knowledge gap between the scientific community that formulate the climate models and the community that use the predictions of these models. We showed that there is not consensus about evaluate the climate models, obtain regional models with higher spatial resolution and define consensual models. However, we gave some guidelines for use the predictions of the climate models. In the second chapter, we tested if the predictions of correlative ecological niche models fitted with presence-absence match the predictions of models fitted with abundance data on the metrics of climate change impact on orchid bees in the Atlantic Forest. We found that the presence-absence models were a partial proxy of change in abundance when the output of the models was continuous, but the same was not true when the predictions were converted to binary. The orchid bees in general will decrease the abundance in the future, but will retain a good amount of suitable sites in the future and the distance to gained climatic suitable areas can be very close, despite of great variation. The change in the species richness and turnover will be mainly in the western and some regions of southern of the Atlantic Forest. In the third chapter, we discussed the drawbacks in using the estimations of realized niche instead the fundamental niche, such as overpredicting the effect of climate change on species’ extinction risk. We proposed a framework based on phylogenetic comparative and missing data methods to predict the dimensions of the fundamental niche of species with missing data. Moreover, we explore sources of uncertainty in predictions of fundamental niche and highlight future directions to overcome current limitations of phylogenetic comparative and missing data methods to improve predictions. We conclude that it is possible to make better use of the current knowledge about species’ fundamental niche with phylogenetic information and auxiliary traits to predict the fundamental niche of poorly-studied species. In the fourth chapter, we used the framework of the chapter three to test the performance of two recent phylogenetic modeling methods to predict the thermal niche of mammals. We showed that PhyloPars had better performance than Phylogenetic Eigenvector Maps in predict the thermal niche. Moreover, the error and bias had similar phylogenetic pattern for both margins of the thermal niche while they had differences in the geographic pattern. The variance in the performance was explained by taxonomic differences and not by methodological aspects. Finally, our models better predicted the upper margin than the lower margin of the thermal niche. This is a good news for predicting the effect of climate change on species without physiological data. We hope our finds can be used to improve the predictions of climate change effect on the biodiversity in future studies and support the political decisions on minimizing the effects of climate change on biodiversity. / As mudanças climáticas são uma das principais ameaças à biodiversidade e é esperado que aumente seu impacto ao longo do século XXI. As mudanças climáticas afetam todos os níveis de biodiversidade, de indivíduos à biomas, reduzindo os serviços ecossistêmicos. Apesar disso, as predições dos impactos das mudanças climáticas na biodiversidade é ainda um desafio. A superação dessas questões depende de melhorias em diferentes aspectos da ciência que dá suporte para predizer o impacto das mudanças climáticas na biodiversidade. A prática comum para predizer o impacto das mudanças climáticas consiste em formular modelos de nicho ecológico baseado no clima atual e projetar as mudanças baseadas no clima futuro predito pelos modelos climáticos. No entanto, existem algumas limitações reconhecidas na formulação do modelo de nicho ecológico e no uso das predições dos modelos climáticos que precisam ser analisadas. Aqui, no primeiro capítulo nós revisamos a ciência por detrás dos modelos climáticos com o intuito de reduzir a lacuna de conhecimentos entre a comunidade científica que formula os modelos climáticos e a comunidade que usa as predições dos modelos. Nós mostramos que não existe consenso sobre avaliar os modelos climáticos, obter modelos regionais com maior resolução espacial e definir modelos consensuais. No entanto, nós damos algumas orientações para usar as predições dos modelos climáticos. No segundo capítulo, nós testamos se as predições dos modelos correlativos de nicho ecológicos ajustados com presença-ausência são congruentes com aqueles ajustados com dados de abundância nas medidas de impacto das mudanças climáticas em abelhas de orquídeas da Mata Atlântica. Nós encontramos que os modelos com presença-ausência foram substitutos parciais das mudanças na abundância quando o resultado dos modelos foi contínuo (adequabilidade), mas o mesmo não ocorreu quando as predições foram convertidas para binárias. As espécies de abelhas, de modo geral, irão diminuir em abundância no futuro, mas reterão uma boa quantidade de locais adequados no futuro e a distância para áreas climáticas adequadas ganhadas podem estar bem próximo, apesar da grande variação. A mudança na riqueza e na substituição de espécies ocorrerá principalmente no Oeste e algumas regiões no sul da Mata Atlântica. No terceiro capítulo, nós discutimos as desvantagens no uso de estimativas do nicho realizado ao invés do nicho fundamental, como superestimar o efeito das mudanças climáticas no risco de extinção das espécies. Nós propomos um esquema geral baseado em métodos filogenéticos comparativos e métodos de dados faltantes para predizer as dimensões do nicho fundamental das espécies com dados faltantes. Além disso, nós exploramos as fontes de incerteza nas predições do nicho fundamental e destacamos direções futuras para superar as limitações atuais dos métodos comparativos filogenéticas e métodos de dados faltantes para melhorar as predições. Nós concluímos que é possível fazer melhor uso do conhecimento atual sobre o nicho fundamental das espécies com informação filogenética e caracteres auxiliares para predizer o nicho fundamental de espécies pouco estudadas. No quarto capítulo, nós usamos o esquema geral do capítulo três para testar a performance de dois novos métodos de modelagem filogenética para predizer o nicho térmico dos mamíferos. Nós mostramos que o “PhyloPars” teve uma melhor performance que o “Phylogenetic Eigenvector Maps” em predizer o nicho térmico. Além disso, o erro e o viés tiveram um padrão filogenético similar para ambas as margens do nicho térmico, enquanto eles apresentaram diferentes padrões espaciais. A variância na performance foi explicada pelas diferenças taxonômicas e não pelas diferenças em aspectos metodológicos. Finalmente, nossos modelos melhor predizem a margem superior do que a margem inferior do nicho térmico. Essa é uma boa notícia para predizer o efeito das mudanças climáticas em espécies sem dados fisiológicos. Nós esperamos que nossos resultados possam ser usados para melhorar as predições do efeito das mudanças climáticas na biodiversidade em estudos futuros e dar suporte para decisões políticas para minimização dos efeitos das mudanças climáticas na biodiversidade.

Do changes in how cross-equatorial energy transport is partitioned between the ocean and atmosphere impact the hemispheric climate response to forcing? To find out, we alter the cross-equatorial ocean heat transport in a state-of-the-art GCM and ascertain how changes in energy transport and its partitioning impact hemispheric climate and precipitation sensitivity following abrupt CO2-doubling. We further evaluate the applicability our results in CMIP6-class ESMs, where AMOC facilitates the northward cross-equatorial ocean heat transport. In our experiments, changes in ocean cross-equatorial energy transport trigger compensating changes in atmospheric energy transport through changes in the Hadley cells and a shift in the Intertropical Convergence Zone. However, the climate sensitivity in each hemisphere is linearly related to the ocean heat transport convergence, not atmospheric energy transport convergence, due to the impact of ocean heating on evaporation and atmospheric specific humidity. Similarly, we also find that ocean heat transport convergence controls the hemispheric precipitation sensitivity through the impact of ocean heating on surface evaporation. This relationship is also evident in CMIP6 models, where we find differences in hemispheric precipitation sensitivity to be related to the Atlantic Meridional Overturning Circulation (AMOC). Changes in the AMOC control hemispheric differences in upper ocean heat content, which then affect how the hydrologic cycle responds to CO2 forcing in each hemisphere. These results suggest that ocean dynamics impact the hemispheric climate response to CO2 forcing, particularly how much regional precipitation changes with warming. / Graduate