2012Monthly Notices of the Royal Astronomical SocietyOpen access

The ultimate meteorological question from observational astronomers: how good is the cloud cover forecast?

Quanzhi Ye, S.-S. Chen

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Abstract

To evaluate the capability of numerical cloud forecasting as a meteorological reference for astronomical observations, we compare the cloud forecast from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model for total, layer and convective cloud with normalized satellite observations from the International Satellite Cloud Climatology Project (ISCCP) for the period of 2005 July–2008 June. In general, the model forecast is consistent with the ISCCP observations. For total cloud cover, our result shows the goodness of the GFS model forecast, with a mean error within ±15 per cent in most areas. The global mean probability of <30 per cent forecast error (polar regions excluded) declines from 73 per cent to 58 per cent throughout the 180-h forecast period and is more skilled than the ISCCP-based climatology forecast up to τ ∼ 120 h. Comparison using layer clouds reveals a distinct negative regional tendency for low cloud forecast and a questionable positive global tendency for high cloud forecast. Fractional and binary comparisons are performed on the convective cloud forecast and it is revealed that the GFS model can identify less than half of such cloud. In short, our result suggests that the GFS model can provide satisfactory worldwide total cloud forecasts up to a week ahead for observation-scheduling purposes, but layer and convective cloud forecasts are less reliable than the total cloud forecast.

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To evaluate the capability of numerical cloud forecasting as a meteorological reference for astronomical observations, we compare the cloud forecast from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model for total, layer and convective cloud with normalized satellite observations from the International Satellite Cloud Climatology Project (ISCCP) for the period of 2005 July–2008 June. In general, the model forecast is consistent with the ISCCP observations. For total cloud cover, our result shows the goodness of the GFS model forecast, with a mean error within ±15 per cent in most areas. The global mean probability of <30 per cent forecast error (polar regions excluded) declines from 73 per cent to 58 per cent throughout the 180-h forecast period and is more skilled than the ISCCP-based climatology forecast up to τ ∼ 120 h. Comparison using layer clouds reveals a distinct negative regional tendency for low cloud forecast and a questionable positive global tendency for high cloud forecast. Fractional and binary comparisons are performed on the convective cloud forecast and it is revealed that the GFS model can identify less than half of such cloud. In short, our result suggests that the GFS model can provide satisfactory worldwide total cloud forecasts up to a week ahead for observation-scheduling purposes, but layer and convective cloud forecasts are less reliable than the total cloud forecast.

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Available abstract

To evaluate the capability of numerical cloud forecasting as a meteorological reference for astronomical observations, we compare the cloud forecast from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model for total, layer and convective cloud with normalized satellite observations from the International Satellite Cloud Climatology Project (ISCCP) for the period of 2005 July–2008 June. In general, the model forecast is consistent with the ISCCP observations. For total cloud cover, our result shows the goodness of the GFS model forecast, with a mean error within ±15 per cent in most areas. The global mean probability of <30 per cent forecast error (polar regions excluded) declines from 73 per cent to 58 per cent throughout the 180-h forecast period and is more skilled than the ISCCP-based climatology forecast up to τ ∼ 120 h. Comparison using layer clouds reveals a distinct negative regional tendency for low cloud forecast and a questionable positive global tendency for high cloud forecast. Fractional and binary comparisons are performed on the convective cloud forecast and it is revealed that the GFS model can identify less than half of such cloud. In short, our result suggests that the GFS model can provide satisfactory worldwide total cloud forecasts up to a week ahead for observation-scheduling purposes, but layer and convective cloud forecasts are less reliable than the total cloud forecast.

Key concepts: International Satellite Cloud Climatology Project, Cloud cover, Cloud computing, Meteorology, Environmental science, Global Forecast System, Satellite, Forecast skill

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