#ClimateModels

[undergroundusa]

PODCAST SEGMENT 1: "Scientists like Ole Humlum and Murray Salby noticed that temperatures often rise before CO₂ levels go up, by about 6 to 12 months. That’s like saying the oven heats up before you turn it on…"

READ & LISTEN NOW: https://www.undergroundusa.com/p/a-house-of-climate-cards-built-on

[nschool]

How Data Science is Helping Fight Climate Change

Climate change is no longer a distant threat—it’s a reality affecting ecosystems, economies, and everyday lives. From rising sea levels to extreme weather events, the impact is global. But there’s a powerful tool helping scientists, policymakers, and activists respond more effectively: Data Science.

With the explosion of big data, sensors, satellites, and machine learning algorithms, data science is becoming a central force in the fight against climate change. Let’s explore how.

1. Predicting Climate Patterns with Machine Learning

One of the most powerful applications of data science is in climate modeling and forecasting. Traditional models were limited in processing power and granularity. Now, with advanced machine learning techniques and high-performance computing, scientists can:

Simulate climate changes decades into the future

Predict weather patterns more accurately

Model extreme events like hurricanes, floods, or droughts

For example, DeepMind’s AI model, trained on vast datasets of radar data, can now predict rainfall with higher precision than traditional methods. These forecasts help communities prepare for disasters and reduce damage.

2. Satellite Imagery and Earth Observation

Satellites continuously gather images and climate data from space. These images are rich with information—about deforestation, glacier melting, ocean temperatures, and more.

Data scientists use image recognition and geospatial analytics to:

Monitor forest cover loss in the Amazon

Track ice sheet melting in Antarctica

Identify urban heat islands in growing cities

Measure carbon emissions from industrial zones

Organizations like NASA, ESA, and Google Earth Engine are publishing petabytes of open climate data for researchers to build models, apps, and solutions.

3. Carbon Footprint Analysis

Governments and companies are under increasing pressure to reduce their carbon footprints. But first, they need to measure them accurately.

Data science enables:

Carbon accounting across supply chains

IoT integration in factories for real-time emission tracking

Predictive models to simulate the impact of green policies

For instance, companies like Microsoft and Apple are using advanced analytics to reduce their net carbon emissions and optimize energy use across data centers.

4. Climate-Smart Agriculture

Agriculture is both a victim and a contributor to climate change. Data science is helping farmers adapt through climate-smart agriculture practices:

Yield prediction using historical and weather data

Soil health monitoring through sensors and analytics

Pest and disease detection using AI-driven image classification

Precision irrigation to reduce water usage

Platforms like IBM’s Watson Decision Platform for Agriculture use AI to give farmers insights that boost productivity while reducing environmental impact.

5. Greener Cities with Smart Data

Urban areas contribute heavily to CO₂ emissions. With smart data collected from sensors, traffic cams, GPS, and public utilities, data scientists help cities become more sustainable:

Optimizing public transport to reduce fuel consumption

Monitoring air quality in real-time

Planning green spaces using heat maps

Managing waste and recycling more efficiently

Cities like Singapore, Amsterdam, and San Francisco are already leading the way in becoming “smart cities,” using data science to reduce emissions and improve quality of life.

6. Renewable Energy Optimization

The shift to solar, wind, and hydro power brings new challenges: fluctuating outputs, grid integration, and energy storage. Here’s where data science steps in:

Forecasting sunlight and wind speeds to predict energy generation

Optimizing battery storage and distribution

Balancing supply and demand across the smart grid

AI models from companies like Google DeepMind have already improved the output prediction of wind farms by up to 20%.

7. Climate Research and Citizen Science

Open-source projects and platforms allow anyone to contribute to climate research. Data scientists use crowd-sourced data to:

Map plastic waste in oceans

Collect wildlife migration data

Record local temperature anomalies

Tools like Zooniverse, Kaggle, and Climate Central invite data scientists and enthusiasts to work on real-world climate datasets and challenges.

8. Policy and Decision-Making Support

Data science doesn't just help collect and analyze data—it also helps governments make better decisions.

Predictive models simulate the outcome of climate policies

Visualization tools make complex data easier for decision-makers to understand

Data-driven reports guide investments in green technologies

The Intergovernmental Panel on Climate Change (IPCC), for example, uses advanced data analytics to build global climate reports that influence international treaties and agreements.

Challenges and Ethical Considerations

While data science offers powerful tools, it also comes with challenges:

Data privacy in sensor-based tracking

Biases in datasets or algorithms

Digital divide, where developing countries may lack infrastructure for data collection

Data scientists must follow ethical guidelines and ensure inclusive, transparent, and responsible use of technology in climate work.

Conclusion: The Role of Data Scientists in a Greener Future

Climate change is a complex, urgent problem—but data science gives us the power to understand, predict, and act.

As a data scientist, you're not just crunching numbers. You're helping to:

Save forests

Reduce emissions

Optimize energy use

Protect communities

Shape global policies

It’s a field where technology meets responsibility. And in the climate battle, every line of clean, purposeful code matters.

[joelekm]

NVIDIA’s AI Chips: Revolutionizing Industries & Shaping the Future | AI Vault

Discover how NVIDIA's groundbreaking AI chips, including the H100 and A100, are revolutionizing industries and shaping the future of artificial intelligence. From powering self-driving cars and advancing medical diagnostics to accelerating drug discovery and enabling ultra-realistic gaming experiences, these chips are redefining the limits of technology. With mass production scaling up, NVIDIA is democratizing access to transformative AI hardware, making it accessible for startups, researchers, and enterprises worldwide. This video delves into the innovations behind NVIDIA's chips, their impact on healthcare, automotive, gaming, and scientific research, and the challenges and opportunities of scaling production. Join us to explore how NVIDIA is building the foundation for a smarter, more connected world.

[swiftnliftnewsandarticle]

How can AI contribute to more accurate weather prediction and natural disaster preparedness?

AI plays a significant role in enhancing weather prediction and natural disaster preparedness in several ways:

1.Data Analysis: Artificial intelligence systems can analyze large volumes of meteorological data, such as satellite photos, radar data, and historical weather trends, faster and more precisely than traditional methods. This helps discover trends and forecast future weather events.

2. Machine Learning Models: Machine learning techniques can increase weather model accuracy by learning from previous weather patterns and adjusting predictions in real time. These models can continuously learn and improve their forecasts.

3. Simulation and Modeling: Artificial intelligence can improve numerical weather prediction models by optimizing the simulations used to forecast atmospheric conditions. This results in more accurate and timely forecasts.

4. Early Warning Systems: Artificial intelligence-powered systems can provide early warnings of catastrophic weather occurrences including hurricanes, tornadoes, and flooding. By combining data from several sources, these systems can detect possible disasters and notify authorities and communities.

5. Risk Assessment: Artificial intelligence can assess the risk of natural disasters by examining geographic, meteorological, and sociological aspects. This information is useful for emergency response planning and resource allocation.

6. Real-time Monitoring: Artificial intelligence systems can monitor meteorological data and ambient factors in real time, enabling for swift forecast modifications and responses to emergent risks.

7. Predictive Analytics: Using historical data and real-time inputs, AI can forecast the likelihood and potential impact of specific weather events, allowing communities to better prepare.

8. Resource Optimization: AI can assist in disaster preparedness by helping to optimize the distribution of supplies and the location of emergency shelters based on anticipated needs.

9. Public Education and Awareness: AI-powered platforms can assist in informing the public about critical information and updates, enhancing community readiness and reaction to emergencies.

Overall, integrating AI into meteorology enhances the ability to predict weather changes accurately and prepare for natural disasters, ultimately reducing risks and saving lives.

[eco-modern-city]

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A post shared by eco modern city🇨🇦 (@eco_modern_city)

According to independent analyses by NASA and the National Oceanic and Atmospheric Administration (NOAA), Earth's average global surface temperature in 2019 was the second warmest since modern record-keeping began in 1880. The year 2016 ranks as the warmest. . Follow @eco_modern_city • 📽: Global temperature rise from 1880 to 2019. Higher-than-normal temperatures are shown in red and lower-than-normal temperatures are shown in blue. Each frame represents global temperature anomalies (changes) in five-year averages. Credit: NASA’s Scientific Visualization Studio. Data provided by Robert B. Schmunk (NASA’s Goddard Institute for Space Studies). . Credit: @nasaclimatechange • #nasa #noaa #globalwarming #climatechange #temperature #atmosphere #ocean #tbt #fbf #science #earthscience #climatescience #celsius #fahrenheit #ghg #humanactivity #climatemodel #co2 #greenhousegas (at Toronto, Ontario) https://www.instagram.com/p/B-zxzgOnDEp/?igshid=eo26jfbb3qx1

[meteorologistjoecioffi]

Long Range Unfavorable For Major Snow Events I-95 Corridor Next 2 Weeks

Long Range Unfavorable For Major Snow Events I-95 Corridor Next 2 Weeks

Long Range Unfavorable For Major Snow Events I-95 Corridor Next 2 Weeks

Snow weenies are utterly unreasonable creatures. They demand non stop snow from November 1st through April 30th and anything less is considered a bad winter to them; bad meaning that the winter was terrible for snow lovers. They throw trantrums like 5 year olds who can’t get ice cream even though they haven’t eaten their…

[wordforestorg]

Climate modelling isn't the only way of forecasting what our climate-changed world will look like by the century's end and beyond. Indeed, the huge complexities and caveats involved in trying to build an accurate picture of a carbon-soaked planet from initial tenets, may not even make it the best.⁠ ⁠ Instead, we can look back in time to periods in Earth's 4.6 billion-year history, when conditions prevailed that can help to shed light on where we are headed as climate breakdown gathers pace.⁠ ⁠ By kind permission of our Special Scientific Adviser, Bill McGuire, read more in his blog 'Forward To The Past - Just What Is The Climate Change Bottom Line?'⁠ ⁠ https://www.wordforest.org/2021/09/03/forward-to-the-past/⁠ ⁠ #climatemodelling #climatescience #BillMcGuire #Environment #Permian https://instagr.am/p/CTW1w8RM78h/

[lularoefail]

Tweeted

#ClimateChangeIsReal but no need for #climatealarm because #globalcooling is happening, (not #GlobalWarming due to#CO2.) The #climatemodels are #wrong. They're a hoax..nothing more than a #tax #pyramidscheme https://t.co/DhR2uHhsxF

— Norman Millsap (@Norm_Millsap) June 1, 2018

[importantnotimportant]

Happy Tuesday, earthlings!! Check out episode 16 of the pod! This week, we talk to Dr. Kate Marvel about the present and future of climate modeling.  Dr. Marvel is a climate scientist and a writer and a theoretical physicist by training. She is now an associate research scientist at NASA’s Goddard Institute for Space Studies and Columbia University’s Department of Applied Physics and Applied Mathematics. Kate's research focuses on how human activities affect the climate and what we can expect in the future, using satellite observations, computer models, and basic physics to study the human impact on variables from rainfall patterns to cloud cover. Spoiler- clouds are CRAZY. Link in bio! #marvel #nasa #climatemodel #climatescience #physics #climate #science #climatechange #humanimpact #podcast #future #important — view on Instagram https://ift.tt/2I48jpq

[climatemodelscalendar]

[climatehaiku]

glamour, meet science / climate models redefined / data decks the walls  mh, eg

get one: http://climatemodels.org/

[joelekm]

Revolutionizing the Future | How NVIDIA’s AI Chips Are Transforming Industries | AI Vault

Discover how NVIDIA's groundbreaking AI chips, including the H100 and A100, are revolutionizing industries and shaping the future of artificial intelligence. From powering self-driving cars and advancing medical diagnostics to accelerating drug discovery and enabling ultra-realistic gaming experiences, these chips are redefining the limits of technology. With mass production scaling up, NVIDIA is democratizing access to transformative AI hardware, making it accessible for startups, researchers, and enterprises worldwide. This video delves into the innovations behind NVIDIA's chips, their impact on healthcare, automotive, gaming, and scientific research, and the challenges and opportunities of scaling production. Join us to explore how NVIDIA is building the foundation for a smarter, more connected world.

[earthtank]

January Climate Model Peter deMenocal. Have you gotten your Climate Model calendar yet?

[lamontlog-blog]

Climate scientists and climate models are in agreement that hydroclimate will change as a result of rising greenhouse gas emissions. Are these changes already underway? What is the significance of these trends versus natural climate variability? In this video from May 2014, climate scientist Richard Seager discusses these topics at Yale's Climate and Energy Institute.

[joelekm]

Revolutionizing the Future | How NVIDIA’s AI Chips Are Transforming Industries | AI Vault

Discover how NVIDIA's groundbreaking AI chips, including the H100 and A100, are revolutionizing industries and shaping the future of artificial intelligence. From powering self-driving cars and advancing medical diagnostics to accelerating drug discovery and enabling ultra-realistic gaming experiences, these chips are redefining the limits of technology. With mass production scaling up, NVIDIA is democratizing access to transformative AI hardware, making it accessible for startups, researchers, and enterprises worldwide. This video delves into the innovations behind NVIDIA's chips, their impact on healthcare, automotive, gaming, and scientific research, and the challenges and opportunities of scaling production. Join us to explore how NVIDIA is building the foundation for a smarter, more connected world.

[climatemodelscalendar]

The Climate Models calendar is now hanging on walls around the world! We want to see yours in action too. Use the hashtag #ClimateModels on Twitter, Facebook or Instagram and we'll repost for all to see.