Statistical Evaluation of the Temperature Forecast Error in the
Lower-Level Troposphere on Short-Range Timescales Induced by Aerosol
Variability
Abstract
This study statistically evaluated the aerosol impact on the temperature
error in the lower-level troposphere in short-range numerical weather
prediction (NWP). The Global Ensemble Forecast System version 12
(GEFSv12) reforecast exhibited large temperature errors in high-loading
areas (North India, Africa, South America, and China). In 1-day GEFSv12
forecasts, the largest average temperature error occurred in the aerosol
optical depth (AOD) peak month, and the daily error distribution
corresponded to the daily AOD distribution. Even though the temperature
error in the 1-day operational forecasts was smaller than that in the
GEFSv12 forecasts, the forecast uncertainties in the operational
forecasts were comparable to those in 3-day GEFSv12 forecasts over
high-loading areas. The daily temperature errors in all NWP models
exhibited a correlation coefficient of ~0.5–0.6 for the
AOD over Central Africa and northern South America and
~0.3–0.6 for AOD anomalies over China and northern
South America. These results indicated that the yearly aerosol
variability contributed 25–36% to errors, and the daily variability
contributed 10–36% to temperature errors in 3-day forecasts. Although
the correlation was low, aerosol impacts also emerged in North India and
Central Africa. Partial correlation and composite analysis suggested
that the direct effect mainly influenced temperature forecast errors
over northern South America, whereas both direct and indirect effects
influenced temperature errors over China. Model intercomparison revealed
that operational NWP models could experience common forecast errors
associated with aerosols in high-loading areas.