# Summertime Aerosol Radiative Effects and Their Dependence on Temperature over the Southeastern USA
## 3 Results and Discussion
### Radiative Impacts  
In order to estimate the climate effect of the temperature-dependent AOD (or biogenic) component in the southeastern USA, the regional direct radiative effects (DRE) were calculated from the observations and the simulations. For the measurement-based estimate, the linear regression fit between the AOD and temperature anomalies (see Equation (1)) was used. The slope of (7 \(\pm\) 6) \(\times\) 10\({}^{-3}\) K\({}^{-1}\) represents our best estimate with 95% confidence. Using this AOD change per temperature degree in the following equation, we estimated the regional DRE of the temperature-dependent AOD component (e.g., [84]):  
\[DRE=S_{rad}\varphi AOD(1-C_{c})T_{atm}^{2}(1-R_{s})^{2}\left(2R_{s}\frac{1- \omega}{\left(1-R_{s}\right)^{2}}-\beta\omega\right) \tag{5}\]  
where \(S_{rad}\) is the incident solar radiation (461 W/m\({}^{2}\)) at the top of the atmosphere integrated over the 24-h day, \(\phi\) is the mean daytime value of the secant of the solar zenith angle (1.33), \(C_{c}\) is the fractional cloud amount (0.0 for clear-sky and 0.6 for all-sky), \(T_{atm}\) is the aerosol-free atmospheric transmission (0.76), \(R_{s}\) is the shortwave surface reflectance (0.15), \(\omega\) is the single scattering albedo (0.972), and \(\beta\) is the up-scatter fraction (0.21). All values used in the equation, except for \(S_{rad}\) and \(\phi\), were taken from [PERSON] et al. [18]. The region and season averaged \(S_{rad}\) and \(\phi\) were calculated with the help of the tools in the LibRadtran package [85]. The original equation by [PERSON] and [PERSON] [84] was designed for global DRE estimates and it includes the global variables day length and solar constant, thus the equation was modified for regional calculations by replacing them with \(S_{md}\) and \(\phi\) to get a regional DRE estimate. Using these assumptions, the measurement-based DRE estimates for the whole domain are \(-\)0.33 \(\pm\) 0.29 W/m\({}^{2}\)/K and \(-\)0.13 \(\pm\) 0.11 W/m\({}^{2}\)/K for clear- and all-sky conditions, respectively. For the mixed forest pixels, the corresponding DRE estimates are \(-\)1.3 \(\pm\) 0.7 W/m\({}^{2}\)/K and \(-\)0.5 \(\pm\) 0.3 W/m\({}^{2}\)/K for clear- and all-sky conditions, respectively. We also estimated the summertime clear-sky DRE of biogenic aerosols from the model simulations by calculating the difference between the net clear sky top-of-atmosphere solar radiation from the CONTROL and the noBIOSOA simulations as a function of temperature anomalies. A linear fit to the dataset produced the following function: \(DRE_{bio}=-\)0.29\((\pm\) 0.09)\(LST_{amo}-\)1.59 \((\pm\) 0.11) (see Figure S13 for details). Thus, a one Kelvin increase in temperature corresponds to a biogenic DRE of \(-\)0.29 \(\pm\) 0.09 W/m\({}^{2}\) and so the model-based clear-sky DRE estimate is in a very good agreement with the observation-based estimate for the whole domain. [PERSON] et al. [15] analysed long-term observations of aerosol particles and biogenic vapors in continental mid- and high-latitude environments. Their results showed that aerosol cooling effects are strengthened by increasing biogenic vapour emissions in warmer temperatures. When compared with the DRE estimates presented by [PERSON] et al. [15] for several locations across Europe, our DRE estimates for the southeastern USA are more negative. For the growth season (T \(>\) 5 \({}^{\circ}\)C) [PERSON] et al. [15] reported a DRE average of \(-\)0.03 (\(-\)0.060-0.006) W/m\({}^{2}\)/K. Thus, our regional DRE estimates are five times larger than their maximum estimate and our DRE estimate for the mixed forests is over 20 times larger. Furthermore, [PERSON] et al. [86] estimated the DRE for the Pallas-Sodankyla Global Atmosphere Watch (GAW) station in Northern Finland with two methods: ground-based remote sensing and in-situ observations.