Month: September 2023

I’ve had to make many very difficult decision in my career, and running a company where employees depend on me getting it right for their job security is something I take very seriously.

Clearly the automotive industry is going through massive changes, and I mean really massive. Changes to the way factories are designed, built and run. Changes to materials and technologies in the car. Changes in working practices. Massive changes in car design, connectivity and propulsion methods. At every level the industry is changing. this is even more momentous than when steam gave way to internal combustion.

Our industry is tightly regulated by legislation on emissions, safety, recycling, energy efficiency etc. and these regulations are instigated by politicians who in turn are responding to what people currently care about, after all that’s how they get votes. But there is a big change in how many people view the car, for many in cities it is a bothersome dangerous burden and not the great personal freedom tool that it is to the rest of us. So politics is changing too, and so will laws in our industry.

Consumer preferences have changed dramatically too, in the past I have made outlandish bold statement vehicles for car PR organizations to help them engage with customers, but now this may be seen as wasteful and not environmentally sensitive (even though these were usually end of life pre-production prototypes destined for the scarp pile).

So I know that change is coming my way, whether I like it or not. And I have a duty to adapt my company to keep everyone gainfully employed.

But even more than that, when I started looking into this I was thinking about the future of my family, of everyone’s family, what future will it be?

I’m an engineer and I work on hard data. But the trouble with a thing like climate change is there is one hell of a lot of noise coming out of the media, governments and even more so from social media. People quoting wildly different facts and drawing opposing conclusions. After all getting likes, clicks or subscriptions takes a bit of drama.

So I looked at the sources of the data and found a much calmer discussion, based on science, data and well tested arguments. And what I found is a very big probability (after all nothing is 100% certain except death and taxes) that the world is currently warming up at a speed that is faster than at any point in its history. And it turns out that the speed of change is rather important, because that determines how long species have to adapt to the change, and currently its happening so fast that we are seeing species actually dying out at an increasing rate. And personally I don’t want that to happen.

We also have the problem of extreme weather, with substantially more energy in the atmosphere there are stronger winds, the jet stream is buckled and makes weather more changeable and extreme, and the higher heat means more evaporation and rain in some places, but drought and high temperatures in others. It’s a very complex system and one that appears to be a major area of research, modeling climate (the big averages) is apparently reasonably accurate whilst modeling weather (the detail of what will happen in precise locations at precise times) is still tricky.

The upshot of all this is I’ve had to rethink my business, career and lifestyle. My annual mileage is drastically reduced, we don’t have foreign family holidays, we buy local food produce more etc. In my business I’m concentrating on new energy powertrains (although my first EV conversion was in 1993!), synthetic fuels, sustainable oils, low energy production methods, renewable energy etc.

And I’m now working on public transport vehicles, converting buses to EV and hydrogen. Public transport is vital but has a long way to go, and I want to be part of that solution.

I’ve also started a training company to share sustainable skills to help people keep their machines running well for longer, reducing waste.

Hopefully I’m doing something right. Time will tell.

Climate change data verification is a critical process to ensure the accuracy, reliability, and credibility of climate-related information. The verification of climate change data involves several key steps and methodologies:

1. Data Collection: The first step is to collect data from various sources, including weather stations, satellites, ocean buoys, ice cores, tree rings, and more. This data encompasses a wide range of climate indicators such as temperature, precipitation, sea level, greenhouse gas concentrations, and more.
2. Quality Control: Raw data collected from different sources may contain errors, anomalies, or inconsistencies. Quality control procedures involve checking data for inaccuracies and correcting them. This includes identifying and addressing issues like sensor malfunctions, calibration errors, and data transmission problems.
3. Data Homogenization: When working with historical climate data collected over long periods, it’s essential to ensure consistency across time. Data homogenization involves adjusting historical records to account for changes in measurement methods, station locations, or instrumentation over time. This ensures that trends and anomalies are not artifacts of changes in data collection methods.
4. Peer Review: Climate scientists and researchers subject their data and findings to peer review. Peer review involves having other experts in the field assess the methodology, data sources, and conclusions. This process helps identify any potential biases, errors, or limitations in the data and analysis.
5. Data Transparency: To enhance transparency and credibility, climate scientists often make their data and methodologies publicly available. This allows other researchers to independently verify the results and conduct their own analyses.
6. Cross-Validation: Climate data is often cross-validated using multiple sources and methods. For example, temperature data collected from weather stations can be compared to satellite-based temperature measurements or reconstructed from proxies like tree rings and ice cores. Consistency across different sources and methods strengthens the confidence in the data.
7. Long-Term Trends: Climate data is analyzed for long-term trends to distinguish natural variability from anthropogenic (human-induced) changes. Statistical techniques, such as time series analysis and trend detection, help identify significant trends and their statistical significance.
8. Climate Models: Climate models are used to simulate past and future climate conditions. Data is used to validate these models by comparing their output to observed data. Models that accurately simulate historical climate conditions are more likely to produce reliable projections of future climate change.
9. Independent Verification: Independent organizations and government agencies often conduct their own assessments of climate data and trends. These assessments can serve as additional verification and validation processes.
10. Continuous Monitoring: Climate data is continually monitored and updated as new data becomes available. This ongoing process ensures that climate information remains current and accurate.

It’s important to note that the verification of climate change data is an ongoing and collaborative effort involving scientists, researchers, and organizations worldwide. Rigorous verification processes help build confidence in our understanding of climate change and its impacts, which is crucial for informing policy decisions and mitigation strategies.

Climate change data is collected from various sources and through multiple methods to monitor and understand changes in the Earth’s climate system. Some of the primary sources of climate change data include:

1. Weather Stations: Weather stations around the world record meteorological data such as temperature, precipitation, wind speed, and atmospheric pressure. This historical weather data is crucial for assessing long-term climate trends.

2. Satellites: Earth-observing satellites provide a wealth of data on various climate-related parameters. Satellites can measure sea surface temperatures, ice cover, land surface temperatures, greenhouse gas concentrations, and more, offering a global perspective.

3. Ocean Buoys: Floating ocean buoys equipped with sensors collect data on sea surface temperatures, ocean currents, and other oceanic conditions. These buoys are strategically positioned in oceans to monitor changes over time.

4. Ice Cores: Ice cores extracted from glaciers and polar ice caps provide valuable data on past climate conditions. By analyzing the composition of ice cores, scientists can reconstruct historical climate patterns, including temperature and atmospheric composition.

5. Tree Rings: The study of tree rings (dendrochronology) helps researchers understand past climate variability. Tree rings can reveal information about temperature, precipitation, and droughts over centuries or even millennia.

6. Proxy Data: Various proxy data sources, such as lake sediments, coral reefs, and cave formations, provide indirect evidence of past climate conditions. These proxies are used to reconstruct historical climate records.

7. Climate Models: Climate models simulate the Earth’s climate system, allowing scientists to project future climate scenarios based on various greenhouse gas emissions scenarios. Climate models use historical data as input to validate their accuracy and make predictions.

8. Atmospheric Measurements: Instruments like weather balloons and aircraft are used to collect atmospheric data, including temperature, humidity, and greenhouse gas concentrations in different layers of the atmosphere.

9. Environmental Sensors: Ground-based sensors, such as those used in weather networks and environmental monitoring stations, measure various climate-related parameters at specific locations.

10. Oceanographic Research: Oceanographic research vessels collect data on ocean temperatures, currents, and salinity levels through direct measurements and sampling.

11. Carbon Dioxide (CO2) Monitoring: A global network of CO2 monitoring stations tracks greenhouse gas concentrations in the atmosphere. The Mauna Loa Observatory in Hawaii is a prominent example.

12. Glaciological Research: Glaciologists study glaciers and ice sheets to monitor their changes in size and mass. This data helps assess contributions to sea-level rise.

13. Paleoclimatology: The study of past climates through the examination of geological and biological evidence provides insights into long-term climate trends.

14. Hydrological Data: Data on river flow, snowpack, and groundwater levels are important for understanding how climate change affects water resources.

15. Environmental Surveys: Surveys and studies conducted by environmental agencies, research institutions, and organizations worldwide provide valuable data on climate change impacts on ecosystems, biodiversity, and human societies.

Climate data is often collected and curated by government agencies, research institutions, and international organizations. It is made available to scientists, policymakers, and the public through various databases, research papers, and climate monitoring platforms. These data sources collectively contribute to our understanding of climate change and its impacts on the planet.

It’s a very good question, and there is a very good answer. Trust in climate change data is built on a combination of rigorous scientific processes and not just one data point, the data has transparency in that it is openly available for independent review, it’s rigorously peer reviewed by other scientists who desperately want to show how clever they are by spotting a mistake, and importantly there’s the convergence of evidence from multiple independent sources often working in very different areas. Here are key reasons why we should trust climate change data:

1. The Scientific Method

Climate change data is collected and analyzed using the scientific method, a systematic and evidence-based approach. Scientists follow established protocols for data collection, measurement, and analysis to ensure accuracy and reliability.

2. Peer Review

Research findings and data are subject to peer review, where experts in the field evaluate the methodology, data quality, and conclusions. This process helps identify errors, biases, or limitations in the data or analysis.

3. Transparency

Data sources, collection methods, and analysis techniques are typically documented and made available to the scientific community and the public. This transparency allows others to replicate studies and verify results independently.

4. Consistency Across Studies

Multiple independent studies conducted by scientists around the world consistently support the conclusion that the Earth’s climate is changing due to human activities. This convergence of evidence reinforces the reliability of climate change data.

5. Long-Term Monitoring

Many climate data sets span decades or even centuries, providing a historical record of climate trends. Long-term monitoring helps identify patterns and anomalies, contributing to our understanding of climate change.

6. Global Collaboration

Climate scientists from different countries and institutions collaborate on research and data analysis. This international cooperation ensures a diversity of perspectives and reduces the likelihood of bias or manipulation.

7. Data Validation

Climate data is subject to rigorous validation processes. Researchers use various methods, including cross-validation with independent data sets and comparison with physical principles, to confirm the accuracy of measurements.

8. Independent Verification

Government agencies, universities, research institutions, and organizations worldwide collect and analyze climate data independently. This redundancy in data collection and analysis provides checks and balances.

9. Historical Records

Historical climate data, such as temperature records, ice core data, and proxy records, offer insights into past climate conditions. These records help validate current climate models and observations.

10. Scientific Consensus

The overwhelming majority of climate scientists and scientific organizations agree that climate change is occurring, largely driven by human activities. Scientific consensus is a strong indicator of the reliability of climate change data.

11. Real-World Impacts

Observations of real-world impacts, such as rising global temperatures, sea-level rise, melting ice sheets, and changes in weather patterns, align with the predictions made by climate models based on climate data.

12. Reproducibility

The ability of different researchers to reproduce climate data and results independently adds another layer of credibility to the findings.

13. Continuous Monitoring

Climate data is continually monitored and updated as new data becomes available. This ongoing process ensures that climate information remains current and accurate.

Of course no scientific data is entirely immune to errors or uncertainties, but the combination of rigorous scientific practices, peer review, transparency, and the convergence of evidence from multiple sources makes climate change data highly reliable and trustworthy. Hopefully it forms the foundation for informed policymaking and effective climate action to address the challenges of global changes.

Ralph Hosier is a British automotive engineer and television presenter known for his work in the automotive industry and appearances on various automotive-related television shows. He has decades of expertise in advanced vehicle engineering and modifications. Ralph has been involved in designing and building custom and modified vehicles, and he has shared his knowledge and experiences with audiences through television programs and publications. He has had a diverse and notable career in the automotive industry, here is an overview of Ralph Hosier’s career:

1. Automotive Engineering: Ralph Hosier is well-known for his expertise in automotive engineering, particularly in the field of vehicle modifications and customizations. He has been designing and building custom vehicles since the late ’80s, often pushing the boundaries of what’s possible in terms of automotive engineering. He has worked in the automotive industry at R&D facilities for large and small companies including many years working with Ford, JLR and Rolls Royce and Bentley.
2. Television Presenter: Ralph Hosier has appeared on various automotive-related television programs including Supercar Megabuild, Mission Ignition, Scrapyard Supercar, where he shares his knowledge and passion for cars as well as working behind the scenes helping to create the shows. He is known for his engaging and informative presentations, often demonstrating the intricacies of vehicle modifications and automotive engineering.
3. Engineering Projects: Throughout his career, Ralph has worked on a wide range of automotive projects, including performance enhancements, restorations, and unique vehicle builds. He has been involved in projects that showcase innovative engineering solutions and creative design.
4. Writing: Ralph Hosier has also contributed to automotive publications and magazines, where he has written articles on topics related to automotive engineering, vehicle modifications, and industry trends.
5. Consulting: Beyond his media appearances, Ralph has provided consulting services to the automotive industry. His expertise in vehicle modifications and engineering solutions has been sought after by both automotive manufacturers and enthusiasts.
6. Educational Outreach: Ralph has been involved in educational initiatives related to automotive engineering. He has participated in workshops, seminars, and events aimed at educating individuals about the technical aspects of cars and modifications.

Ralph is a chartered engineer, a member of the Institute of the Motor Industry (IMI), a member of the Institute of Engineering and Technology (IET) and a member of the Guild of Motoring Writers.
There are now more letters after his name than there are in it 

R.Hosier B.Eng(Hons) C.Eng MIET MIMI MGoMW