Why are weather forecasts sometimes wrong?
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Forecasts can be occasionally wrong. This can have several causes:
- Difficult and very changeable weather conditions: with a sharp climatic boundary between adjacent areas. In such weather conditions, forecast differences of 50-100 km will affect massively the quality, since the predicted temperatures and precipitation will often occur within only a few kilometers of the selected location. Very small-scale differences in the mountains or along coastlines can cause very small-scale differences, which can not be reproduced even by a good weather calculation.
- Missing or wrong observations: the observations are used to initialize the calculations, and an incomplete initialization may produce misleading results.
- Faulty weather calculations: such errors can occasionally occur in weather models, and can be resolved with the help of repeated and detailed observation, and detailed user feedback.
- Erroneous measurements: unfortunately faulty measurements are not uncommon, and deceive the observer about the actual conditions, suggesting that a correct forecast is wrong.
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Hello, and I apologize if this isn't the right place to ask this question.
Where I live, Santa Cruz de la Sierra, Bolivia, the map and cross-section often show the asterisk (*) symbol for convective clouds, even though I frequently observe stratus clouds. How do you determine that there are convective clouds and not another type of cloud?
For example, today Meteoblue says there are convective clouds, but the reality is that there are stratus clouds.
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Hello, and thank you for your question.
meteoblue determines convective clouds by analyzing numerical weather models and satellite data, focusing on factors such as vertical extent, cloud base and top heights, and atmospheric conditions that indicate convection. The asterisk (*) symbol on maps and cross-sections denotes the vertical extent of convective clouds in hPa. Differences between the forecast and your local observations, like seeing stratus clouds instead, can result from model resolution limits, timing differences, local microclimate effects, or satellite detection challenges, especially for low clouds such as stratus. Additionally, forecast icons represent conditions averaged over an area of approximately 20–30 km, which may not precisely reflect local cloud types.
We hope we were able to answer your questions and wish you pleasant weather with meteoblue.
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@Miloslav-Tlamicha said in Why are weather forecasts sometimes wrong?:
Forecasts can be occasionally wrong. This can have several causes:
Difficult and very changeable weather conditions: with a sharp climatic boundary between adjacent areas. In such weather conditions, forecast differences of 50-100 km will affect massively the quality, since the predicted temperatures and precipitation will often occur within only a few kilometers of the selected location. Very small-scale differences in the mountains or along coastlines can cause very small-scale differences, which can not be reproduced even by a good weather calculation.
Missing or wrong observations: the observations are used to initialize the calculations, and an incomplete initialization may produce misleading results.
Faulty weather calculations: such errors can occasionally occur in weather models, and can be resolved with the help of repeated and detailed observation, and detailed user feedback.
Erroneous measurements: unfortunately faulty measurements are not uncommon, and deceive the observer about the actual conditions, suggesting that a correct forecast is wrong.This is a great breakdown of why forecasting remains one of the most complex challenges in science. The point about climatic boundaries is especially true—when you're dealing with coastal or mountainous terrain, a 50km shift is the difference between a sunny day and a localized storm.
I deal with similar data accuracy challenges while managing the technical side of my utility portal at visit, where ensuring the right information reaches the user at the right time is critical. Whether it's weather models or automated data scripts, user feedback remains the best tool we have to identify those 'faulty calculations' and improve the system. Thanks for sharing this insight!
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@Miloslav-Tlamicha said in Why are weather forecasts sometimes wrong?:
Forecasts can be occasionally wrong. This can have several causes:
Difficult and very changeable weather conditions: with a sharp climatic boundary between adjacent areas. In such weather conditions, forecast differences of 50-100 km will affect massively the quality, since the predicted temperatures and precipitation will often occur within only a few kilometers of the selected location. Very small-scale differences in the mountains or along coastlines can cause very small-scale differences, which can not be reproduced even by a good weather calculation.
Missing or wrong observations: the observations are used to initialize the calculations, and an incomplete initialization may produce misleading results.
Faulty weather calculations: such errors can occasionally occur in weather models, and can be resolved with the help of repeated and detailed observation, and detailed user feedback.
Erroneous measurements: unfortunately faulty measurements are not uncommon, and deceive the observer about the actual conditions, suggesting that a correct forecast is wrong.This is a great breakdown of why forecasting remains one of the most complex challenges in science. The point about climatic boundaries is especially true—when you're dealing with coastal or mountainous terrain, a 50km shift is the difference between a sunny day and a localized storm.
I deal with similar data accuracy challenges while managing the technical side of my utility portal at visit, where ensuring the right information reaches the user at the right time is critical. Whether it's weather models or automated data scripts, user feedback remains the best tool we have to identify those 'faulty calculations' and improve the system. Thanks for sharing this insight!
@jhon-stone said in Why are weather forecasts sometimes wrong?:
@Miloslav-Tlamicha said in Why are weather forecasts sometimes wrong?:
Forecasts can be occasionally wrong. This can have several causes:
Difficult and very changeable weather conditions: with a sharp climatic boundary between adjacent areas. In such weather conditions, forecast differences of 50-100 km will affect massively the quality, since the predicted temperatures and precipitation will often occur within only a few kilometers of the selected location. Very small-scale differences in the mountains or along coastlines can cause very small-scale differences, which can not be reproduced even by a good weather calculation.
Missing or wrong observations: the observations are used to initialize the calculations, and an incomplete initialization may produce misleading results.
Faulty weather calculations: such errors can occasionally occur in weather models, and can be resolved with the help of repeated and detailed observation, and detailed user feedback.
Erroneous measurements: unfortunately faulty measurements are not uncommon, and deceive the observer about the actual conditions, suggesting that a correct forecast is wrong.This is a great breakdown of why forecasting remains one of the most complex challenges in science. The point about climatic boundaries is especially true—when you're dealing with coastal or mountainous terrain, a 50km shift is the difference between a sunny day and a localized storm.
I deal with similar data accuracy challenges while managing the technical side of my utility portal at visit, where ensuring the right information reaches the user at the right time is critical. Whether it's weather models or automated data scripts, user feedback remains the best tool we have to identify those 'faulty calculations' and improve the system. Thanks for sharing this insight!
True, user feedback is an invaluable way of verifying forecast services!
