Statistical Evaluation of the Temperature Forecast Error in the Lower‐Level Troposphere on Short‐Range Timescales Induced by Aerosol Variability

• Published in: Journal of geophysical research. Atmospheres Vol. 127; no. 13
• Main Authors: Yamagami, A., Kajino, M., Maki, T.
• Format: Journal Article
• Language: English
• Published: 16.07.2022
• ISSN: 2169-897X; 2169-8996
• DOI: 10.1029/2022JD036595

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 interannual 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. Plain Language Summary Atmospheric aerosols significantly impact weather and climate system via direct (aerosol‐radiation interactions) and indirect (aerosol‐cloud interactions) effects. Aerosol influences are, however, treated via a monthly climatology (i.e., real‐time spatiotemporal variations are not included) in short‐to medium‐range numerical weather predictions. This study assessed the aerosol influences on temperature forecasts in the lower‐level troposphere on short‐range timescales. The results indicated that the variability in monthly and daily temperature errors almost corresponded to the aerosol optical depth (AOD) variability in high‐loading areas (North India, Africa, South America, and China). The correlation coefficients of the temperature error and AOD ranged from ∼0.5 to 0.6 over central Africa and northern South America, indicating that the interannual aerosol variability contributed ∼25%–36% to this error. In addition, the correlation between the error and AOD anomalies reached 0.6 over northern South America and 0.3 over China. These results suggested a 10%–36% contribution of the daily aerosol variability. Additionally, the direct effect dominated over northern South America, while the both direct and indirect effects were important over China. Model intercomparison in this study revealed that state‐of‐the‐art numerical weather prediction (NWP) models are subject to a common error source associated with the aerosol variability in high‐loading regions. Key Points The lower‐troposphere temperature error was correlated with the aerosol optical depth (AOD) (R was ∼0.6) over Africa and northern South America (N. S. America) The error was correlated with AOD anomaly over N. S. America and China due to direct and both direct and indirect effects, respectively Operational short‐range forecasts experienced common errors associated with interannual and daily aerosol variabilities in these regions