At ChangingLives Corp, we understand the challenges that extreme weather events pose to businesses and individuals alike. Traditional weather forecasts often fall short in providing the accuracy and specificity needed to effectively plan for these events, leading to unexpected disruptions and costs. To address this, we have developed an AI-powered Climate Intelligence Platform that provides highly accurate, timely, and personalized predictions of extreme weather events. Our platform leverages advanced data science and machine learning techniques to analyze a vast array of climate data, generating detailed forecasts that go beyond traditional weather predictions. The global weather forecasting services market size was valued at USD 2.2 billion in 2021 and is expected to expand at a compound annual growth rate (CAGR) of 6.7% from 2022 to 2030. The market size is projected to grow from an estimated USD 1.7 billion in 2021 to USD 2.7 billion by 2026, at a CAGR of 9.9% during the forecast period. The weather forecasting services market is set to grow by USD 1,092.95 million from 2022 to 2027, progressing at a CAGR of 9.93% during the forecast period. The market size is projected to reach USD 3.78 Billion by 2030, growing at a CAGR of 6.53%. These figures suggest a significant opportunity in the weather forecasting services market. The growth is likely driven by the increasing need for accurate weather predictions across various sectors, including agriculture, energy, insurance, and more. As extreme weather events become more frequent due to climate change, the demand for advanced weather forecasting services is expected to continue to grow.
Category tags:CL Abor Jr
CEO
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Hozefa Sadriwala
CEO, Data Scientist, Teacher/Trainer, Consultant
jair wuilloud
Micheala Abor
"the idea is great, but your model only predict the temperature, what about renewable energy optimization mentioned in your ppt, the presentation is excellent. the idea is new but needs alot of work to make it real and apply al features you will work on it. business value is high but still wants to align with directions of your features. i expected that demo shows the features in the ppt (streamlit link). it should be more than just predicting temperature. I encourage you to continue pushing the boundaries of your idea and keep it up"
Walaa Nasr Elghitany
Data scientist and doctor