Why is weather forcasting so difficult?!
There are lots of ideas in here:
http://www.google.com/search?q=difficulties+in+weather+forecasting&ie=utf-8&oe=utf-8&aq=t&rls=org.mozilla:en-US:official&client=firefox-a
And here is a collection of a science writer's articles that address some aspect of climate change, even sometimes whether to believe it or not!
http://blogs.chron.com/sciguy/archives/climate_change/
Weather forecasting is a complex task because it involves predicting the state of the atmosphere at a specific location and time in the future. Several factors contribute to the difficulty of weather forecasting:
1. Chaotic nature of the atmosphere: The atmosphere is a complex, chaotic system. It is affected by numerous variables such as temperature, pressure, humidity, wind patterns, solar radiation, and interactions between landforms and oceans. Tiny changes in one location can have significant effects on weather patterns elsewhere, making it challenging to accurately predict future weather conditions.
2. Data limitations: To make accurate predictions, weather forecasters rely on vast amounts of data collected from weather stations, satellites, radars, buoys, and weather balloons. However, data gaps, errors, and delays can occur, hindering the accuracy of forecasts. Not having complete or timely data can lead to uncertainties in predicting weather patterns.
3. Computational power and modeling limitations: Weather forecasting relies on mathematical models that simulate the atmosphere and its behavior. These models require extensive computational power to process the vast amount of data and equations involved. However, no model can perfectly replicate the complexity of the atmosphere, and uncertainties and limitations are inherent in these models.
4. Time scale and spatial resolution: Predicting short-term weather accurately is relatively easier compared to long-term forecasts. Short-term forecasts utilize the current conditions and can be updated frequently. However, as the time scale increases, the potential for errors and uncertainties also increases. Additionally, spatial resolution plays a role as weather systems can vary significantly over small distances, making it crucial to have detailed data and accurate modeling at smaller scales.
5. Human interpretation: Weather forecasting involves human interpretation and decision-making. Meteorologists analyze data, leverage their expertise, and apply their knowledge to interpret models and make predictions. Despite advancements in technology, human judgments and interpretations are still essential. The skill and experience of meteorologists play a vital role in improving the accuracy of forecasts.
To overcome these challenges and improve weather forecasting, ongoing research, technological advancements, increased data collection, better modeling techniques, and collaboration among meteorological organizations are undertaken.