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 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.

Spatiotemporal Variations in Summertime Arctic Aerosol Optical Depth Caused by Synoptic‐Scale Atmospheric Circulation in Three Reanalyses

“…On short‐range to subseasonal timescales, errors in some forecasts (e.g., for surface to lower‐troposphere temperature) are related to simplified aerosol treatment in NWP models (Benedetti & Vitart, 2018; Huang & Ding, 2021; Rémy et al., 2015; Rodwell & Jung, 2008; Yamagami et al., 2022; Zhang et al., 2016). Furthermore, long‐term trends in concentrations and optical properties of aerosols and their impacts on climate remain unclear in both observation and modeling studies (e.g., Schmale et al., 2022; Xian, Zhang, O’Neill, Toth, et al., 2022).…”