Presentation given during the kick-off of the TU Delft Climate Institute on March 1st 2012. Sea level rise is one of the reserach topics of the new institute. Dr Bert Vermeersen explained why.
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
Presentation given during the kick-off of the TU Delft Climate Institute on March 1st 2012. Sea level rise is one of the reserach topics of the new institute. Dr Bert Vermeersen explained why.
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
Impact of past and future climate change on diversity in tropical rainforestsUniversity of Adelaide
Craig’s research centers on the use of molecular approaches to study ecology and evolution and addresses questions including;
(1) the use of molecular markers to infer current and historical population processes at various spatial and temporal scales;
(2) the effects of historical changes in habitat on current distributions and diversity of faunas, with particular reference to rainforest biotas;
(3) improving the use of molecular information in conservation biology and the development of strategies that recognize evolutionary processes.
The geographic focus of this research program spans the tropical forests of Australasia, especially the wet tropics of northeastern Australia and western North America
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
Impact of past and future climate change on diversity in tropical rainforestsUniversity of Adelaide
Craig’s research centers on the use of molecular approaches to study ecology and evolution and addresses questions including;
(1) the use of molecular markers to infer current and historical population processes at various spatial and temporal scales;
(2) the effects of historical changes in habitat on current distributions and diversity of faunas, with particular reference to rainforest biotas;
(3) improving the use of molecular information in conservation biology and the development of strategies that recognize evolutionary processes.
The geographic focus of this research program spans the tropical forests of Australasia, especially the wet tropics of northeastern Australia and western North America
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
LATE QUATERNARY STRATIGRAPHIC EVOLUTION OF THE NORTHERN GULF OF MEXICO MARGINDaniel Matranga
Abstract: This volume presents results from several high-resolution stratigraphic investigations of late Quaternary strata of the northern Gulf of Mexico, from the Apalachicola River to the Rio Grande. The studies characterize deposition and strata formation associated with different fluvial and deltaic systems during the most recent glacioeustatic cycle (approximately 120 ka to present).
Information on status of biodiversity of india, Western Ghats and Coastal karnataka, mangroves of Karnataka, sacred groves of Karnataka, peoples biodiversity registers, etc.
A summary of key findings from the IPCC 5th Assessment Report by Anne Hollowed, Alaska Fisheries Science Center, USA
SICCME open session, 17 September 2014, ICES Annual Science Conference, A Coruña, Spain
Data mining and_visualization_of_earth_history_datasets_to_find_cause_effect_...Abdullah Khan Zehady
To know the future of our earth, we need to look back to the past and collect evidence and examine the geologic and biologic events. My projects with http://timescalecreator.org is our approach to analyze the largest publicly available earth historical data to test different hypothesis, to understand better about the past of our loving pale blue. Interestingly lots of the events under the surface of the earth or under the ocean show same periodic cycles that we see in the planetary motions in the solar system and even in the galaxy. Cyclostratigraphy is a field where we try to explore data from the rock or marine records and find possible orbital forcing. Everything is connected after all and we are star dusts !! ;)
Greening of the Arctic: An IPY initiative
1-Rationale and overview of the GOA initiative.
2-North American Arctic Transect.
3-Yamal Russia Transect.
4-Circumpolar analysis of 28-year trends of sea-ice concentration, land-surface temperatures and greening patterns
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
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
Global Situational Awareness of A.I. and where its headedvikram sood
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdfGetInData
Recently we have observed the rise of open-source Large Language Models (LLMs) that are community-driven or developed by the AI market leaders, such as Meta (Llama3), Databricks (DBRX) and Snowflake (Arctic). On the other hand, there is a growth in interest in specialized, carefully fine-tuned yet relatively small models that can efficiently assist programmers in day-to-day tasks. Finally, Retrieval-Augmented Generation (RAG) architectures have gained a lot of traction as the preferred approach for LLMs context and prompt augmentation for building conversational SQL data copilots, code copilots and chatbots.
In this presentation, we will show how we built upon these three concepts a robust Data Copilot that can help to democratize access to company data assets and boost performance of everyone working with data platforms.
Why do we need yet another (open-source ) Copilot?
How can we build one?
Architecture and evaluation
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
Samec - Regression analysis of relations among main Quaternary environmental changes indicators
1. Regression analysis of
relations among
Quaternary environmental
change indicators
Pavel Samec
2. Content
• Introduction
- Glacial/interglacial cycles
- The polyglacism theory
• Material
- Loess/paleosol proxy series
- Deep-sea mud proxy series
- Ice core proxy series
• Methods
- Exploratory data analysis
- Interpolation
- Multiple regression
- Logistic regression
• Results and Discussion
• Summary
• References
3. Introduction
The Quaternary is a period when the geological presence has developed.
The Quaternary Period is characterized by regular alternation of major
environmental changes with the intensity of glacial/interglacial.
• The glacial is an event of glaciations characterized by expansion of continental and
mountain glaciers, global marine regression, global reduction of vegetation biomass and
expansion of terrestrial sedimentary environments.
• The interglacial is an event of interglaciations characterized by minimal glaciations, global
marine transgression, global growth of vegetation biomass and an intensive soil
formation ont the most of land.
The polyglacism theory deals with common variability of marine and
terrestrial sedimentation features in relation to the variability of the
external physical environment that indicate the global impacts of multiple
oscillations glacial/interglacial.
The aim of the study was using of the logistic regression for better
description of assumed polyglacial relationships.
4. Material
• Data
- Loess/paleosol series (Chinese Loess Plateau; 6.9-0 Ma; Sun et al. 2012)
- Deep sea d18O (East Pacific; 470-4 Ka; Lea et al. 2000)
- Ice core (East Antarctica; 803-2 Ka; Barnola et al. 1999; Petit et al. 2000)
• Analysed periods
- Middle-Upper Pleistocene (470-12 Ka)
- Upper Pleistocene – Holocene (126-1 Ka)
5. The Central Chinese Loess Plateau eolian sediment magnetic
susceptibility (MS) (data according to Sun et al. 2012).
350
300
250
200
150
100
50
0
6.8 6.4 6.0 5.7 5.4 5.1 4.9 4.6 4.1 3.8 3.6 3.2 3.0 2.7 2.4 2.1 1.7 1.5 1.2 0.9 0.6 0.3 0.0
MS (10-8 m3/kg)
Dating (Ma)
The East Equatorial Pacific average sea surface temperatures and
oxygen proxy record (data according to Lea et a. 2000).
d18O T (°C)
3
2
1
0
-1
-2
-3
32
28
24
20
16
461 384 306 245 176 124 80 36 4
Dating (Ka)
sea surface temperature
oxygen isotopical signal
6. Methods
• Global temperature deviations were main features of the
glacial/interglacial cycle.
• Glacial – 0
• Interglacial - 1
DT (°C) CO2 (ppm)
4
2
0
-2
-4
-6
-8
-10
300
280
260
240
220
200
180
314 231 136 2
carbon dioxide (ppm) Dating (Ka)
temperature deviations
(°C)
CO2 (ppm)
300
275
250
225
200
175
150
-10 -8 -6 -4 -2 0 2
DT (°C)
North Atlantic
East Equatorial Pacific
Antarctica
dCO2
1.00
0.75
0.50
0.25
0.00
0.00 0.30 0.60 0.90 1.20 1.50
Ttropy/Tpolar
7. • Exploratory data analysis
- Test on normality distribution
- Regression diagnosis
- Linear correlation and regression
• Interpolation
- Transformation according to 0-1 limits
• Regression analysis
- Linear regression
- Multiple regression
- Logistic regression
Data calibration
EDA
Linear regression
Binomical
interpolation
Multiple regression Logistic regression
8. Results and discussion
Exploratory linear regression of basic Quaternary sedimentation core
properties. y – receptor; x – predictor; F –Fischer-Snedecorov’s testing
criterion; t – Student’s t-test criterion; r ‒ correlation coefficient; SC –
Scott’s test on multicolinearity; C-W – Cook-Weisberg’s test on
heteroscedasticity; J-B – Jarque-Berrae’s test on normality of residues;
Wa – Wald’s test on autocorrelation.
12. Summary
• Changes in the basic soil properties of a loess/paleosol sequences reliably
do not indicate changes in the intensity of glacial/interglacial cycles
between the Middle and Upper Pleistocene.
• Changes in the basic soil properties of a loess/paleosol sequences have
been reflecting climatic changes statistically more significantly than the
deep-sea sedimentation since the Upper Pleistocene (cycle eem‒visla) .
• Correlations of atmospheric CO2 and surface temperatures are greater
than correlation of other polyglacial phenomenas.
• Linear regression revealed on the assumption that the dependences of soil
properties were smaller than polyglacial relations of other environmental
indicators.
• Logistic regression suggested that temporal variability in feedbacks
between climatic change predictors and properties of forming sediments
may be cause of the lack of a simple Quaternary climatic change
indication.
13. References
• BARNOLA J.M. et al. (1999): Historical CO2 record from the Vostok ice core. In:
Trends: A Compendium of Data on Global Change. U. S. Department of Energy Oak
Ridge.
• HEIKKINEN R.K. et al. (2006): Methods and uncertainties in bioclimatic envelope
modelling under climate change. Progress in Physical Geography 30: 6751‒6777.
• KUKLA J. (1978): The Classical European Glacial Stages: Correlation with deep-sea
sediments. Transactions of the Nebraska Academy of Science 6: 57–93.
• KUKLA G., CÍLEK V. (1996): Plio-Pleistocene megacycles: record of climate and
tectonics. Palaeogeography, Palaeoclimatology, Palaeoecology 120: 171‒194.
• LEA D.W. et al. (2000): Climate impact of late Quaternary equatorial Pacific sea
surface temperature variations. Science 289: 1719–1724.
• OSBORN J. W. (2010): Improving your data transformation: Applying the Box-Cox
transformation. Practical Assessment, Research & Evaluation 15: 2‒9.
• PETIT J.R. (1999): Climate and atmospheric history of the past 420,000 years from
the Vostok ice core, Antarctica. Nature 399: 429–436.
• SUN Y. (2012): Seven million years of wind and precipitation variability on the
Chinese Loess Plateau. Earth and Planetary Science Letters 297: 525–535.