This document summarizes research on linkages between Arctic sea ice loss and mid-latitude weather patterns. It finds that while sea ice loss can influence the atmosphere, the role of sea ice is small relative to Arctic amplification and internal variability. Models forced only by sea ice changes do not capture the full vertical extent of Arctic warming seen in models that include all climate forcings. Increased warming in the mid-troposphere is associated with a stronger Siberian High pressure system and cold extremes over Asia, but the stratospheric response is unclear due to high natural variability in the future climate.
Linking the Quasi-Biennial Oscillation and Projected Arctic Sea-Ice Loss to S...Zachary Labe
20th Conference on Middle Atmosphere at the 99th Annual Meeting of the American Meteorological Society (abstract: https://ams.confex.com/ams/2019Annual/meetingapp.cgi/Paper/352664)
The Pan-Arctic Impacts of Thinning Sea IceZachary Labe
The Arctic is rapidly changing. However, long-term observations of trends in Arctic sea-ice thickness are still quite limited. In this presentation, Zachary will discuss the different methods (satellite instruments and climate model simulations) of observing sea-ice thickness in order to understand changes in the recent Arctic amplification era. He will also highlight the far-reaching environmental and societal impacts from a thinning Arctic sea-ice cover.
Communicating Arctic climate change through data-driven storiesZachary Labe
Arctic Science Summit Week 2021 (Session 2: “The 4 Essential Cs - Coordination, Communication, Community, and Collaboration”):
In this presentation, I will discuss the power of sharing Arctic climate change information through accessible and engaging data visualizations. In particular, I will focus on using social media (Twitter) as one tool for communicating science to broad audiences.
Linking the Quasi-Biennial Oscillation and Projected Arctic Sea-Ice Loss to S...Zachary Labe
20th Conference on Middle Atmosphere at the 99th Annual Meeting of the American Meteorological Society (abstract: https://ams.confex.com/ams/2019Annual/meetingapp.cgi/Paper/352664)
The Pan-Arctic Impacts of Thinning Sea IceZachary Labe
The Arctic is rapidly changing. However, long-term observations of trends in Arctic sea-ice thickness are still quite limited. In this presentation, Zachary will discuss the different methods (satellite instruments and climate model simulations) of observing sea-ice thickness in order to understand changes in the recent Arctic amplification era. He will also highlight the far-reaching environmental and societal impacts from a thinning Arctic sea-ice cover.
Communicating Arctic climate change through data-driven storiesZachary Labe
Arctic Science Summit Week 2021 (Session 2: “The 4 Essential Cs - Coordination, Communication, Community, and Collaboration”):
In this presentation, I will discuss the power of sharing Arctic climate change information through accessible and engaging data visualizations. In particular, I will focus on using social media (Twitter) as one tool for communicating science to broad audiences.
Substantial disagreement continues between modeling studies in attributing midlatitude climate extremes to Arctic sea-ice anomalies. This is a result of uncertainties due to internal variability, nonlinear interactions, model biases, or more likely a combination of these effects. In this study, we use large ensembles from two high-top atmospheric general circulation models (SC-WACCM4 and E3SM) to separate the sea ice-forced signal from atmospheric internal variability (noise). Following protocol for the Polar Amplification Model Intercomparison Project (PAMIP), each simulation is prescribed with either pre-industrial, present-day, or future levels of sea-ice concentration, which are associated with global warming projections of 2°C. We use 300 ensemble members per simulation to obtain large sample sizes for robust statistics in the context of internal variability.
While an equatorward shift of the eddy-driven jet is found in boreal winter, the response to future sea-ice loss is small relative to climatology and highly sensitive to the number of ensemble members considered. On average, a sea ice-forced signal in the large-scale circulation cannot be distinguished from atmospheric internal variability in our simulations. A low signal-to-noise ratio is also demonstrated in the stratosphere, where the sign of the polar vortex response can be interpreted differently depending on the ensemble size. However, the local thermodynamic effects are statistically significant with strong surface warming and increases in precipitation found in the vicinity of newly ice-free areas. This warming is generally confined to the Arctic, and there is little response in the midlatitudes. Our results highlight the important role of internal variability in the extratropics and emphasize the need for especially large ensembles (>150-200 members) when assessing the dynamical response to both present-day and future Arctic sea-ice loss. (from https://ams.confex.com/ams/2020Annual/meetingapp.cgi/Paper/367289)
Satellite passive microwave measurements of the climate crisisChelle Gentemann
Invited presentation at the NASEM Committee on Radio Frequencies 2021 Fall Meeting. An overview of how passive microwave measurements are used to understand climate change.
Impact of Sea Level Rise from Storm Surge USADag Lohmann
We're quantifying the impact that a 30cm sea level rise has on losses from hurricanes for each individual location in the USA. We're also looking at losses from a hypothetical sea level in the year 1900. Summaries are shown by state and selected maps.
Summary of results: Based on current conditions of exposure (e.g. buildings and other economic assets) we have an annual average loss of about $5 Billion from our simulations. Given the sea level in 1900 that loss would go to $4 Billion. Current projections of sea level rise vary widely, but most have us exceed 30cm between 2040 and 2080. Some go much higher (many meters), while the most optimistic ones are around 30cm at the end of the century. Given the same exposure, same sea defenses, and same hurricanes, losses would go up to an average of $6.9 Billion / year (called the average annual loss or AAL).
From our climate panel in Grand Junction on August 4:
Our Forest, Our Water, Our Land: Local Impacts on Climate Change. Sponsored by Conservation Colorado, Mesa County Library, Math & Science Center
Revisiting projections of Arctic climate change linkagesZachary Labe
16 November 2023…
Department Seminar (Presentation): Revisiting projections of Arctic climate change linkages, Tongji University, Shanghai, China. Remote Presentation.
References:
Labe, Z.M., Y. Peings, and G. Magnusdottir (2018), Contributions of ice thickness to the atmospheric response from projected Arctic sea ice loss, Geophysical Research Letters, DOI: 10.1029/2018GL078158
Labe, Z.M., Y. Peings, and G. Magnusdottir (2019). The effect of QBO phase on the atmospheric response to projected Arctic sea ice loss in early winter, Geophysical Research Letters, DOI: 10.1029/2019GL083095
Labe, Z.M., Y. Peings, and G. Magnusdottir (2020). Warm Arctic, cold Siberia pattern: role of full Arctic amplification versus sea ice loss alone, Geophysical Research Letters, DOI: 10.1029/2020GL088583
Peings, Y., Z.M. Labe, and G. Magnusdottir (2021), Are 100 ensemble members enough to capture the remote atmospheric response to +2°C Arctic sea ice loss?
Journal of Climate, DOI: 10.1175/JCLI-D-20-0613.1
Labe, Z.M. and E.A. Barnes (2022), Comparison of climate model large ensembles with observations in the Arctic using simple neural networks. Earth and Space Science, DOI: 10.1029/2022EA002348
Reexamining future projections of Arctic climate linkagesZachary Labe
10 May 2024…
Atmospheric and Oceanic Sciences Student/Postdoc Seminar (Presentation): Reexamining future projections of Arctic climate linkages, Princeton University, USA.
References...
Labe, Z.M., Y. Peings, and G. Magnusdottir (2018), Contributions of ice thickness to the atmospheric response from projected Arctic sea ice loss,
Geophysical Research Letters, DOI:10.1029/2018GL078158
Labe, Z.M., Y. Peings, and G. Magnusdottir (2019). The effect of QBO phase on the atmospheric response to projected Arctic sea ice loss in early winter, Geophysical Research Letters, DOI:10.1029/2019GL083095
Labe, Z.M., Y. Peings, and G. Magnusdottir (2020). Warm Arctic, cold Siberia pattern: role of full Arctic amplification versus sea ice loss alone, Geophysical Research Letters, DOI:10.1029/2020GL088583
Labe, Z.M., May 2020: The effects of Arctic sea-ice thickness loss and stratospheric variability on mid-latitude cold spells. University of California, Irvine. Doctoral Dissertation.
Peings, Y., Z.M. Labe, and G. Magnusdottir (2021), Are 100 ensemble members enough to capture the remote atmospheric response to +2°C Arctic sea ice loss? Journal of Climate, DOI:10.1175/JCLI-D-20-0613.1
Substantial disagreement continues between modeling studies in attributing midlatitude climate extremes to Arctic sea-ice anomalies. This is a result of uncertainties due to internal variability, nonlinear interactions, model biases, or more likely a combination of these effects. In this study, we use large ensembles from two high-top atmospheric general circulation models (SC-WACCM4 and E3SM) to separate the sea ice-forced signal from atmospheric internal variability (noise). Following protocol for the Polar Amplification Model Intercomparison Project (PAMIP), each simulation is prescribed with either pre-industrial, present-day, or future levels of sea-ice concentration, which are associated with global warming projections of 2°C. We use 300 ensemble members per simulation to obtain large sample sizes for robust statistics in the context of internal variability.
While an equatorward shift of the eddy-driven jet is found in boreal winter, the response to future sea-ice loss is small relative to climatology and highly sensitive to the number of ensemble members considered. On average, a sea ice-forced signal in the large-scale circulation cannot be distinguished from atmospheric internal variability in our simulations. A low signal-to-noise ratio is also demonstrated in the stratosphere, where the sign of the polar vortex response can be interpreted differently depending on the ensemble size. However, the local thermodynamic effects are statistically significant with strong surface warming and increases in precipitation found in the vicinity of newly ice-free areas. This warming is generally confined to the Arctic, and there is little response in the midlatitudes. Our results highlight the important role of internal variability in the extratropics and emphasize the need for especially large ensembles (>150-200 members) when assessing the dynamical response to both present-day and future Arctic sea-ice loss. (from https://ams.confex.com/ams/2020Annual/meetingapp.cgi/Paper/367289)
Satellite passive microwave measurements of the climate crisisChelle Gentemann
Invited presentation at the NASEM Committee on Radio Frequencies 2021 Fall Meeting. An overview of how passive microwave measurements are used to understand climate change.
Impact of Sea Level Rise from Storm Surge USADag Lohmann
We're quantifying the impact that a 30cm sea level rise has on losses from hurricanes for each individual location in the USA. We're also looking at losses from a hypothetical sea level in the year 1900. Summaries are shown by state and selected maps.
Summary of results: Based on current conditions of exposure (e.g. buildings and other economic assets) we have an annual average loss of about $5 Billion from our simulations. Given the sea level in 1900 that loss would go to $4 Billion. Current projections of sea level rise vary widely, but most have us exceed 30cm between 2040 and 2080. Some go much higher (many meters), while the most optimistic ones are around 30cm at the end of the century. Given the same exposure, same sea defenses, and same hurricanes, losses would go up to an average of $6.9 Billion / year (called the average annual loss or AAL).
From our climate panel in Grand Junction on August 4:
Our Forest, Our Water, Our Land: Local Impacts on Climate Change. Sponsored by Conservation Colorado, Mesa County Library, Math & Science Center
Revisiting projections of Arctic climate change linkagesZachary Labe
16 November 2023…
Department Seminar (Presentation): Revisiting projections of Arctic climate change linkages, Tongji University, Shanghai, China. Remote Presentation.
References:
Labe, Z.M., Y. Peings, and G. Magnusdottir (2018), Contributions of ice thickness to the atmospheric response from projected Arctic sea ice loss, Geophysical Research Letters, DOI: 10.1029/2018GL078158
Labe, Z.M., Y. Peings, and G. Magnusdottir (2019). The effect of QBO phase on the atmospheric response to projected Arctic sea ice loss in early winter, Geophysical Research Letters, DOI: 10.1029/2019GL083095
Labe, Z.M., Y. Peings, and G. Magnusdottir (2020). Warm Arctic, cold Siberia pattern: role of full Arctic amplification versus sea ice loss alone, Geophysical Research Letters, DOI: 10.1029/2020GL088583
Peings, Y., Z.M. Labe, and G. Magnusdottir (2021), Are 100 ensemble members enough to capture the remote atmospheric response to +2°C Arctic sea ice loss?
Journal of Climate, DOI: 10.1175/JCLI-D-20-0613.1
Labe, Z.M. and E.A. Barnes (2022), Comparison of climate model large ensembles with observations in the Arctic using simple neural networks. Earth and Space Science, DOI: 10.1029/2022EA002348
Reexamining future projections of Arctic climate linkagesZachary Labe
10 May 2024…
Atmospheric and Oceanic Sciences Student/Postdoc Seminar (Presentation): Reexamining future projections of Arctic climate linkages, Princeton University, USA.
References...
Labe, Z.M., Y. Peings, and G. Magnusdottir (2018), Contributions of ice thickness to the atmospheric response from projected Arctic sea ice loss,
Geophysical Research Letters, DOI:10.1029/2018GL078158
Labe, Z.M., Y. Peings, and G. Magnusdottir (2019). The effect of QBO phase on the atmospheric response to projected Arctic sea ice loss in early winter, Geophysical Research Letters, DOI:10.1029/2019GL083095
Labe, Z.M., Y. Peings, and G. Magnusdottir (2020). Warm Arctic, cold Siberia pattern: role of full Arctic amplification versus sea ice loss alone, Geophysical Research Letters, DOI:10.1029/2020GL088583
Labe, Z.M., May 2020: The effects of Arctic sea-ice thickness loss and stratospheric variability on mid-latitude cold spells. University of California, Irvine. Doctoral Dissertation.
Peings, Y., Z.M. Labe, and G. Magnusdottir (2021), Are 100 ensemble members enough to capture the remote atmospheric response to +2°C Arctic sea ice loss? Journal of Climate, DOI:10.1175/JCLI-D-20-0613.1
Evaluating and communicating Arctic climate change projectionZachary Labe
20 February 2023…
Climate Change and Agriculture Guest (Presentation): Evaluating and communicating Arctic climate change projections, Kansas State University, USA.
References...
Delworth, T. L., Cooke, W. F., Adcroft, A., Bushuk, M., Chen, J. H., Dunne, K. A., ... & Zhao, M. (2020). SPEAR: The next generation GFDL modeling system for seasonal to multidecadal prediction and projection. Journal of Advances in Modeling Earth Systems, 12(3), e2019MS001895, https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2019MS001895
Labe, Z.M. and E.A. Barnes (2022), Comparison of climate model large ensembles with observations in the Arctic using simple neural networks. Earth and Space Science, DOI:10.1029/2022EA002348, https://doi.org/10.1029/2022EA002348
Labe, Z.M., Y. Peings, and G. Magnusdottir (2020). Warm Arctic, cold Siberia pattern: role of full Arctic amplification versus sea ice loss alone, Geophysical Research Letters, DOI:10.1029/2020GL088583, https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020GL088583
Peings, Y., Cattiaux, J., Vavrus, S. J., & Magnusdottir, G. (2018). Projected squeezing of the wintertime North-Atlantic jet. Environmental Research Letters, 13(7), 074016, https://iopscience.iop.org/article/10.1088/1748-9326/aacc79/meta
Guest Lecture: Our changing Arctic in the past and futureZachary Labe
22 August 2023…
Guest lecture for “Introduction to Global Climate Change (ESS 15)” (Invited): Our changing Arctic in the past and future, University of California, Irvine, CA. Remote Presentation.
References...
Delworth, T. L., Cooke, W. F., Adcroft, A., Bushuk, M., Chen, J. H., Dunne, K. A., ... & Zhao, M. (2020). SPEAR: The next generation GFDL modeling system for seasonal to multidecadal prediction and projection. Journal of Advances in Modeling Earth Systems, 12(3), e2019MS001895, https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2019MS001895
Labe, Z.M. and E.A. Barnes (2022), Comparison of climate model large ensembles with observations in the Arctic using simple neural networks. Earth and Space Science, DOI:10.1029/2022EA002348, https://doi.org/10.1029/2022EA002348
Labe, Z.M., Y. Peings, and G. Magnusdottir (2020). Warm Arctic, cold Siberia pattern: role of full Arctic amplification versus sea ice loss alone, Geophysical Research Letters, DOI:10.1029/2020GL088583, https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020GL088583
This is a pdf. due to file size we are not able to upload the PowerPoint presentation you can email info@thecccw.org.uk for a copy which includes video clips
This is just a simple effort of laying a background of slides for new presenters. You can download, edit and present the topic. I hope you find it a bit helpful.
CLIMATE CHANGE, SEA-LEVEL RISE and COASTAL GEOLOGIC HAZARDSriseagrant
CLIMATE CHANGE, SEA-LEVEL RISE
and
COASTAL GEOLOGIC HAZARDS
URI Climate Change Symposium
5 May 2011
Jon C. Boothroyd
Rhode Island State Geologist,
Research Professor Emeritus – Quaternary Geology
-------------
Rhode Island Geological Survey and Department of Geosciences
College of the Environment and Life Sciences
University of Rhode Island
jon_boothroyd@uri.edu
Techniques and Considerations for Improving Accessibility in Online MediaZachary Labe
3 April 2024…
United States Association of Polar Early Career Scientists (USAPECS) IDEA Training Course (Presentation): Accessibility and disability in online spaces. Remote Presentation.
An intro to explainable AI for polar climate scienceZachary Labe
26 March 2024…
GFDL Polar Climate Interest Group (Presentation): An intro to explainable AI for polar climate science, NOAA GFDL, Princeton, NJ.
References:
Labe, Z.M. and E.A. Barnes (2022), Comparison of climate model large ensembles with observations in the Arctic using simple neural networks. Earth and Space Science, DOI:10.1029/2022EA002348, https://doi.org/10.1029/2022EA002348
Labe, Z.M. and E.A. Barnes (2021), Detecting climate signals using explainable AI with single-forcing large ensembles. Journal of Advances in Modeling Earth Systems, DOI:10.1029/2021MS002464, https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2021MS002464
Using accessible data to communicate global climate changeZachary Labe
25 March 2024…
Climate Communication Workshop: Learn How To Make Your Research Matter (Keynote Presentation): Using accessible data to communicate global climate change, Temple University, Philadelphia, PA.
Water in a Frozen Arctic: Cross-Disciplinary PerspectivesZachary Labe
14 March 2024…
United States Association of Polar Early Career Scientists (USAPECS) Webinar (Host): Water in a Frozen Arctic: Cross-Disciplinary Perspectives. Remote Panel.
Event Page: https://www.usapecs.org/post/webinar-water-frozen-arctic
Explainable AI approach for evaluating climate models in the ArcticZachary Labe
27 March 2024…
IARPC Collaborations, Modelers’ Community of Practice (Presentation): Explainable AI approach for evaluating climate models in the Arctic. Remote Presentation.
References...
Labe, Z. M., & Barnes, E. A. (2022). Comparison of climate model large ensembles with observations in the Arctic using simple neural networks. Earth and Space Science, 9(7), e2022EA002348, https://doi.org/10.1029/2022EA002348
Explainable neural networks for evaluating patterns of climate change and var...Zachary Labe
12 March 2024…
Sharing Science – North American Webinar, Young Earth System Scientists (YESS) Community (Presentation): Explainable neural networks for evaluating patterns of climate change and variability. Remote Presentation.
References...
Labe, Z.M., E.A. Barnes, and J.W. Hurrell (2023). Identifying the regional emergence of climate patterns in the ARISE-SAI-1.5 simulations. Environmental Research Letters, DOI:10.1088/1748-9326/acc81a
Applications of machine learning for climate change and variabilityZachary Labe
23 February 2024…
Department of Environmental Sciences Seminar (Presentation): Applications of machine learning for climate change and variability, Rutgers University, New Brunswick, NJ.
References:
Labe, Z.M. and E.A. Barnes (2021), Detecting climate signals using explainable AI with single-forcing large ensembles. Journal of Advances in Modeling Earth Systems, DOI:10.1029/2021MS002464
Labe, Z.M. and E.A. Barnes (2022), Predicting slowdowns in decadal climate warming trends with explainable neural networks. Geophysical Research Letters, DOI:10.1029/2022GL098173
Labe, Z. M., Johnson, N. C., & Delworth, T. L. (2024). Changes in United States summer temperatures revealed by explainable neural networks. Earth's Future, DOI:10.1029/2023EF003981
data-driven approach to identifying key regions of change associated with fut...Zachary Labe
Labe, Z.M., T.L. Delworth, N.C. Johnson, and W.F. Cooke. A data-driven approach to identifying key regions of change associated with future climate scenarios, 23rd Conference on Artificial Intelligence for Environmental Science, Baltimore, MD (Jan 2024). https://ams.confex.com/ams/104ANNUAL/meetingapp.cgi/Paper/431300
Distinguishing the regional emergence of United States summer temperatures be...Zachary Labe
Labe, Z.M., N.C. Johnson, and T.L. Delworth. Distinguishing the regional emergence of United States summer temperatures between observations and climate model large ensembles, 23rd Conference on Artificial Intelligence for Environmental Science, Baltimore, MD (Jan 2024). https://ams.confex.com/ams/104ANNUAL/meetingapp.cgi/Paper/431288
Researching and Communicating Our Changing ClimateZachary Labe
6 December 2023…
Mercer County Community College (Presentation): Meet the climate scientists: our journey and our science, West Windsor Township, NJ, USA.
Visualizing climate change through dataZachary Labe
18 November 2023…
NJ State Museum Planetarium (Presentation): Visualizing climate change through data, Trenton, NJ.
References...
Eischeid, J.K., M.P. Hoerling, X.-W. Quan, A. Kumar, J. Barsugli, Z.M. Labe, K.E. Kunkel, C.J. Schreck III, D.R. Easterling, T. Zhang, J. Uehling, and X. Zhang (2023). Why has the summertime central U.S. warming hole not disappeared? Journal of Climate, DOI:10.1175/JCLI-D-22-0716.1, https://journals.ametsoc.org/view/journals/clim/36/20/JCLI-D-22-0716.1.xml
Using explainable machine learning to evaluate climate change projectionsZachary Labe
5 October 2023…
Atmosphere and Ocean Climate Dynamics Seminar (Presentation): Using explainable machine learning to evaluate climate change projections, Yale University, New Haven, CT. Remote Presentation.
References...
Labe, Z.M., E.A. Barnes, and J.W. Hurrell (2023). Identifying the regional emergence of climate patterns in the ARISE-SAI-1.5 simulations. Environmental Research Letters, DOI:10.1088/1748-9326/acc81a, https://iopscience.iop.org/article/10.1088/1748-9326/acc81a
Contrasting polar climate change in the past, present, and futureZachary Labe
28 September 2023…
Guest lecture for “Observing and Modeling Climate Change (EES 3506/5506)” (Presentation): Contrasting polar climate change in the past, present, and future, Temple University, Philadelphia, PA. Remote Presentation.
Climate change extremes by season in the United StatesZachary Labe
11 September 2023…
Hershey Horticulture Society (Presentation): Climate change extremes by season in the United States, Hershey, PA, USA.
References...
Eischeid, J.K., M.P. Hoerling, X.-W. Quan, A. Kumar, J. Barsugli, Z.M. Labe, K.E. Kunkel, C.J. Schreck III, D.R. Easterling, T. Zhang, J. Uehling, and X. Zhang (2023). Why has the summertime central U.S. warming hole not disappeared? Journal of Climate, DOI:10.1175/JCLI-D-22-0716.1
Labe, Z.M., T.R. Ault, and R. Zurita-Milla (2016), Identifying Anomalously Early Spring Onsets in the CESM Large Ensemble Project, R. Clim Dyn, DOI:10.1007/s00382-016-3313-2
Labe, Z.M., N.C. Johnson, and T.L Delworth (2023). Changes in United States summer temperatures revealed by explainable neural networks. Preprint. DOI: 10.22541/essoar.168987129.98069596/v1
Monitoring indicators of climate change through data-driven visualizationZachary Labe
19 June 2023…
La Uni Climática - IV Edition (Presentation): Monitoring indicators of climate change through data-driven visualization. Remote Presentation.
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptxMAGOTI ERNEST
Although Artemia has been known to man for centuries, its use as a food for the culture of larval organisms apparently began only in the 1930s, when several investigators found that it made an excellent food for newly hatched fish larvae (Litvinenko et al., 2023). As aquaculture developed in the 1960s and ‘70s, the use of Artemia also became more widespread, due both to its convenience and to its nutritional value for larval organisms (Arenas-Pardo et al., 2024). The fact that Artemia dormant cysts can be stored for long periods in cans, and then used as an off-the-shelf food requiring only 24 h of incubation makes them the most convenient, least labor-intensive, live food available for aquaculture (Sorgeloos & Roubach, 2021). The nutritional value of Artemia, especially for marine organisms, is not constant, but varies both geographically and temporally. During the last decade, however, both the causes of Artemia nutritional variability and methods to improve poorquality Artemia have been identified (Loufi et al., 2024).
Brine shrimp (Artemia spp.) are used in marine aquaculture worldwide. Annually, more than 2,000 metric tons of dry cysts are used for cultivation of fish, crustacean, and shellfish larva. Brine shrimp are important to aquaculture because newly hatched brine shrimp nauplii (larvae) provide a food source for many fish fry (Mozanzadeh et al., 2021). Culture and harvesting of brine shrimp eggs represents another aspect of the aquaculture industry. Nauplii and metanauplii of Artemia, commonly known as brine shrimp, play a crucial role in aquaculture due to their nutritional value and suitability as live feed for many aquatic species, particularly in larval stages (Sorgeloos & Roubach, 2021).
Toxic effects of heavy metals : Lead and Arsenicsanjana502982
Heavy metals are naturally occuring metallic chemical elements that have relatively high density, and are toxic at even low concentrations. All toxic metals are termed as heavy metals irrespective of their atomic mass and density, eg. arsenic, lead, mercury, cadmium, thallium, chromium, etc.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
ESR spectroscopy in liquid food and beverages.pptxPRIYANKA PATEL
With increasing population, people need to rely on packaged food stuffs. Packaging of food materials requires the preservation of food. There are various methods for the treatment of food to preserve them and irradiation treatment of food is one of them. It is the most common and the most harmless method for the food preservation as it does not alter the necessary micronutrients of food materials. Although irradiated food doesn’t cause any harm to the human health but still the quality assessment of food is required to provide consumers with necessary information about the food. ESR spectroscopy is the most sophisticated way to investigate the quality of the food and the free radicals induced during the processing of the food. ESR spin trapping technique is useful for the detection of highly unstable radicals in the food. The antioxidant capability of liquid food and beverages in mainly performed by spin trapping technique.
The Evolution of Science Education PraxiLabs’ Vision- Presentation (2).pdfmediapraxi
The rise of virtual labs has been a key tool in universities and schools, enhancing active learning and student engagement.
💥 Let’s dive into the future of science and shed light on PraxiLabs’ crucial role in transforming this field!
BREEDING METHODS FOR DISEASE RESISTANCE.pptxRASHMI M G
Plant breeding for disease resistance is a strategy to reduce crop losses caused by disease. Plants have an innate immune system that allows them to recognize pathogens and provide resistance. However, breeding for long-lasting resistance often involves combining multiple resistance genes
Travis Hills' Endeavors in Minnesota: Fostering Environmental and Economic Pr...Travis Hills MN
Travis Hills of Minnesota developed a method to convert waste into high-value dry fertilizer, significantly enriching soil quality. By providing farmers with a valuable resource derived from waste, Travis Hills helps enhance farm profitability while promoting environmental stewardship. Travis Hills' sustainable practices lead to cost savings and increased revenue for farmers by improving resource efficiency and reducing waste.
ANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptxRASHMI M G
Abnormal or anomalous secondary growth in plants. It defines secondary growth as an increase in plant girth due to vascular cambium or cork cambium. Anomalous secondary growth does not follow the normal pattern of a single vascular cambium producing xylem internally and phloem externally.
DERIVATION OF MODIFIED BERNOULLI EQUATION WITH VISCOUS EFFECTS AND TERMINAL V...Wasswaderrick3
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Why is it difficult to resolve future projections of Arctic-midlatitude linkages?
1. Why is it difficult to resolve
future projections of
Arctic-midlatitude linkages?
Zachary Labe
(Currently - postdoc with Libby)
Yannick Peings & Gudrun Magnusdottir
(PhD work - UC Irvine)
2 December 2020
Colorado State University
BMRRTH
Group Meeting
2. INPUT LAYER
HIDDEN LAYERS
OUTPUT LAYER
Layer-wise Relevance Propagation2-m Temperature
“2000-2009”Decade:
Labe and Barnes, in prep
REVEALING CLIMATE SIGNAL WITH XAI
19. [Newson, 1973;
Nature]
“…great warming of the
lower layers of the
troposphere over the
Arctic basin... In fact,
there is a lowering of
mid-latitude continental
temperatures near the
surface”
25. [ SIT ]
Sea Ice
Thickness
Depth between sea
surface and ice/snow
layer
[ SIC ]
Sea Ice
Concentration
Fraction (%) of seawater
covered by ice
Snow
Ice
[ SIE ]
Sea Ice
Extent
Area of seawater
covered by any
amount of ice (>15%)
26. [ SIT ]
Sea Ice
Thickness
Depth between sea
surface and ice/snow
layer
[ SIC ]
Sea Ice
Concentration
Fraction (%) of seawater
covered by ice
Snow
Ice
[ SIE ]
Sea Ice
Extent
Area of seawater
covered by any
amount of ice (>15%)
27. [ SIT ]
Sea Ice
Thickness
Depth between sea
surface and ice/snow
layer
[ SIC ]
Sea Ice
Concentration
Fraction (%) of seawater
covered by ice
Snow
Ice
[ SIE ]
Sea Ice
Extent
Area of seawater
covered by any
amount of ice (>15%)
29. R/V Lance – Greenland Sea – May 2017
Turbulent heat fluxes
[ SIC ]
30. R/V Lance – Greenland Sea – May 2017
Turbulent heat fluxes
[ SIC + SIT ]
31. WACCM4
Whole Atmosphere
Community Climate
Model version 4 –
Specified Chemistry
“high top”
chemistry-climate
atmosphere
model
Physical
parameterizations
from CAM4
• 66 vertical levels – extending to
5 x 10-6 hPa (140 km)
• 1.9° latitude x 2.5° longitude
• QBO prescribed from
radiosonde observations
• Improved representation of
sudden stratospheric warming
(SSW) events
• fixed radiative forcings from
year 2000
32. Future Arctic
How does sea-ice thickness
decline influence the large-
scale atmospheric response?
Significant thermodynamic
response over Arctic Ocean
Poleward weakening of jet
LABE ET AL. 2018, GRL
33. Future Arctic
Significant thermodynamic
response over Arctic Ocean
Poleward weakening of jet
LABE ET AL. 2018, GRL
How does sea-ice thickness
decline influence the large-
scale atmospheric response?
37. Assess the role of the Quasi-biennial
Oscillation (QBO) on the atmospheric
response to Arctic sea-ice loss
(Non)linearity in the polar
stratosphere?
38. Assess the role of the Quasi-biennial
Oscillation (QBO) on the atmospheric
response to Arctic sea-ice loss
Composite response by
QBO phase (~67 years)
Modulation
by QBO
Sea ice
experiments
40. Assess the role of the Quasi-biennial
Oscillation (QBO) on the atmospheric
response to Arctic sea-ice loss
Composite response by
QBO phase (~67 years)
Modulation
by QBO
Sea ice
experiments
Future (2051-2080)
Historical (1975-2005)
41. Assess the role of the Quasi-biennial
Oscillation (QBO) on the atmospheric
response to Arctic sea-ice loss
Composite response by
QBO phase (~67 years)
Modulation
by QBO
Sea ice
experiments
Future (2051-2080)
Historical (1975-2005)
42. Assess the role of the Quasi-biennial
Oscillation (QBO) on the atmospheric
response to Arctic sea-ice loss
Modulation
by QBO
Sea ice
experiments
Composite response by
QBO phase (~67 years)
Easterly (QBO-E)
Westerly (QBO-W)
43. Assess the role of the Quasi-biennial
Oscillation (QBO) on the atmospheric
response to Arctic sea-ice loss
Modulation
by QBO
Sea ice
experiments
Composite response by
QBO phase (~67 years)
Easterly (QBO-E)
Westerly (QBO-W)
44. Assess the role of the Quasi-biennial
Oscillation (QBO) on the atmospheric
response to Arctic sea-ice loss
Sea ice
experiments
Composite response by
QBO phase (~67 years)
Modulation
by QBO
Surface (thermodynamic)
Troposphere/Stratosphere
51. MOTIVATION
ARCTIC SEA ICE
MID-LATITUDE
WEATHER
Sea-ice thickness variability is important for reinforcing the
atmospheric response
Strength of Siberian High closely related to Eurasia cold spells
QBO can modulate teleconnections due to Arctic sea-ice loss
52. MOTIVATION
ARCTIC SEA ICE
MID-LATITUDE
WEATHER
Sea-ice thickness variability is important for reinforcing the
atmospheric response
Strength of Siberian High closely related to Eurasia cold spells
QBO can modulate teleconnections due to Arctic sea-ice loss
53. MOTIVATION
ARCTIC SEA ICE
MID-LATITUDE
WEATHER
Sea-ice thickness variability is important for reinforcing the
atmospheric response
Strength of Siberian High closely related to Eurasia cold spells
QBO can modulate teleconnections due to Arctic sea-ice loss
72. Atmospheric response sensitive to changes in Arctic sea-ice
thickness variability and background state (QBO)
Role of sea ice is small relative to Arctic amplification
(and internal variability)
Zachary Labe
zmlabe@rams.colostate.edu
@ZLabe
73. Atmospheric response sensitive to changes in Arctic sea-ice
thickness variability and background state (QBO)
Role of sea ice is small relative to Arctic amplification
(and internal variability)
QUESTIONS…
Zachary Labe
zmlabe@rams.colostate.edu
@ZLabe
97. Dependence of the
Siberian High response on
polar mid-tropospheric
warming
Gray bar shows the
uncertainty range between
NCEP/NCAR R1 and ERA5
for 10-year epochs
98. 1. Climate models forced only by sea-ice anomalies do not
capture the vertical extent of Arctic warming
2. Increase in 1000-500 hPa layer is linked to a strengthening of
the Siberian High and cold anomalies in eastern Asia
3. Role of the stratosphere is unclear due to large internal
variability at future global warming levels of 2°C
Arctic amplification >> sea-ice loss
99. 1. Climate models forced only by sea-ice anomalies do not
capture the vertical extent of Arctic warming
2. Increase in 1000-500 hPa layer is linked to a strengthening of
the Siberian High and cold anomalies in eastern Asia
3. Role of the stratosphere is unclear due to large internal
variability at future global warming levels of 2°C
Arctic amplification >> sea-ice loss
114. 1. Small signal in dynamical response to sea ice decline
relative to internal variability and climatology
2. Strong surface warming and increase in precipitation mostly
confined to Arctic Ocean
3. AGCM experiments need even larger ensembles (>200
members) to address the noise
Is the circulation response to Arctic sea ice
loss actually robust in the context of
internal variability?
119. NAME SEA ICE FORCING DURATION
Historical Average 1976-2005 LENS SIT
Average 1976-2005 LENS SIC
ONDJFM;
200 members
Future Future 2051-2080 LENS SIT
Future 2051-2080 LENS SIC
ONDJFM;
200 members
All experiments have average 1976-2005 LENS SST*
Atmospheric General Circulation Model
Experiments