Optimizing China’s Afforestation Strategy: Biophysical Impacts of Afforestation with Five Locally Adapted Forest Types

Generally, afforestation had a daily cooling effect for all paired comparisons except for DNF. The net cooling effects of ENF, EBF, DBF, and MF were −0.22 ± 0.11 °C (mean ± 95% confidence interval, the same below), −0.50 ± 0.10 °C, −0.33 ± 0.05 °C, and −0.36 ± 0.06 °C, respectively. The daily cooling effect consisted of a large cooling effect during the day and a small warming effect at night (see Figure 2a,c). However, DNFs showed the opposite pattern, with daytime cooling surpassed by nighttime warming (Figure 2a,c, see GRA->DNF), resulting in a net warming of 0.69 ± 0.24 °C. These regionally averaged conclusions in mid-latitudes generally align with previous satellite-data-driven studies in terms of direction, but some differences in magnitude have been noted [9,11,17,25]. Until now, only limited studies have focused on the classification of sub-divided forests. Zhao et al. [14] have found that DBF expansion from grasslands lead to a regionally averaged LST decrease with the value of −0.11 ± 0.81 °C (mean ± SD) in North America. Meanwhile, ENF expansion induced cooling to a magnitude of −1.27 ± 1.6 °C (mean ± SD).

Our results suggested that the cooling effects of broadleaf forests were stronger than those of needleleaf forests, while Zhao et al. [14] showed the opposite. The reason for this discrepancy is still unclear, even though similar LST data and methodologies were used. Possible reasons could be the influence of significant spatial variations in sample distribution, the length of time series data utilized, and data quality control.

Combining Figure 1, Figure 2 and Figure 3, we further detected the relation between the distribution of paired vegetation cover types and their latitudinal patterns of ΔLST. Stable and adjacently distributed ENF and GRA were mainly concentrated in Southwestern China; they also occurred sporadically in the Xinjiang Province and Southeastern China (refer to Figure 1b). In the regional average, the ΔLST between ENF and GRA was negative; this means that the cooling effect during the day was stronger than the warming effect at night. On average, the comparison between ENF and GRA indicated a relatively weak cooling effect compared to the comparisons between broadleaf forests and grasslands (i.e., EBF vs. GRA, DBF vs. GRA), as well as between MF and GRA (see Figure 2e). The reasons for this are discussed in Section 4.

The comparison between EBF and GRA, as well as that between DNF and GRA, formed an interesting contrast: the former was distributed in Southern China (Figure 1c, below 30° N), while the latter was found in Northeastern China (Figure 1d, above 48° N). Correspondingly, EBF showed a significant cooling effect compared to GRA, while DNF exhibited a significant warming effect relative to GRA.

The distribution of DBF vs. GRA and MF vs. GRA spanned from the south to the north (Figure 1e,f), exhibiting similar and distinct patterns of latitudinal variation in ΔLST (Figure 3d,e). During the daytime, DBF (MF) showed a cooling effect compared to the surrounding GRA, but the magnitude of cooling decreased with the increasing latitude (see Figure 2b, DBF (MF)). At night, DBF (MF) had a higher LST than the neighboring GRA, and the magnitude of warming increased with the latitude (see Figure 2d, DBF (MF)). Daily ΔLST represented a transition from cooling to warming, with the transition zone occurring between 44 and 47° N (ΔLST = −0.02 $\pm$ 0.08 °C for DBF vs. GRA, and ΔLST = 0.11 $\pm$ 0.21 °C for MF vs. GRA). In addition, DBF and MF showed average daily cooling effects of −0.65 $\pm$ 0.07 °C and −0.48 $\pm$ 0.06 °C, $\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{p}\mathrm{e}\mathrm{c}\mathrm{t}\mathrm{i}\mathrm{v}\mathrm{e}\mathrm{l}\mathrm{y}$, between 20 and 43° N, as well as average daily warming effects of 0.53 $\pm$ 0.08 °C and 0.81 $\pm$ 0.18 °C between 48 and 53° N.

Similar to previous findings, this study found that the biophysical climate impact of forestation on LST could be further translated into the latitudinal dependence of a warming effect in northern high latitudes and cooling effects in other latitudes, with the transitional latitude near 45–50° N [9,25]. These cooling or warming effects are mainly driven by the relative strength of the albedo-induced radiative warming and evapotranspiration (hereafter, ET)-dominated non-radiative cooling [4,7]. In this work, near boreal regions (>47° N), radiative warming surpassed non-radiative cooling, causing a positive LST signal. The radiative warming comes from the fact that forest canopies have a lower albedo due to their greater height, unevenness, and darker color compared to grasslands, resulting in the absorption of more solar shortwave radiation energy [21]. The monthly results further indicated that this positive LST signal mainly occurred from November to the following April (Figure 4c). This is because snow-covered short vegetation surfaces reflect more shortwave radiation energy back into Space [30]. For the remaining mid-latitude zones in this study, non-radiative cooling was found to counteract radiative warming, leading to an overall negative ΔLST. Tall, rough canopies like those in conifer forests exhibit strong ET and latent heat release when soil moisture is sufficient, resulting in a cooling effect [21]. This effect is most pronounced at lower latitudes but diminishes as the latitude increases due to soil moisture limitations [7,31]. The cooling effect primarily occurs during the daytime and depends on stomatal opening for transpiration [32,33]. Seasonally, non-radiative cooling showed larger magnitudes in the growing season than in the dormant season (Figure 4c).

The latitudinal pattern of ΔLST is also impacted by the seasonal variations. Figure 4 provided valuable insights into the intricate spatiotemporal ΔLST patterns. Given the extensive latitudinal distribution of DBF and GRA, they served as representative examples of these patterns. During the daytime, DBF generally exhibited a cooling effect, except for regions situated north of 47° N during the winter months (specifically, in December and January, as depicted in Figure 4a). Conversely, DBF predominantly displayed a warming effect at night, except for areas located south of 30° N and especially during the summer (as indicated in Figure 4b). The daily ΔLST revealed pronounced spatiotemporal heterogeneity. In regions positioned south of 41° N, ΔLST consistently showcased a cooling trend throughout the year. In regions north of 42° N, the prevailing pattern involved cooling during the summer and warming during the winter. Additionally, with increasing latitude, the duration and intensity of winter warming exhibited an upward trend. It is worth noting that the temperature effect in the range of 44–47° N was not significant and represented a transitional region. This could be attributed to the opposite diurnal and seasonal impacts that had similar magnitudes and hence canceled each other out on daily and annual scales (refer to Figure 4c). Interestingly, in regions south of 30° N, the spatiotemporal characteristics of daily ΔLST were mainly inherited from those of daytime ΔLST, mainly due to strong ET cooling of temperate forests. In regions north of 47° N, especially in winter when the ET cooling effect was weak, the spatiotemporal characteristics of daily ΔLST were mainly inherited from those of nighttime ΔLST; here, albedo-induced warming becomes notable.

Unlike the cooling effect of forests compared to grasslands at low latitudes, ENF and MF exhibited a warming region around 30° N (see Figure 3a,e, indicated in orange); the warming effect at night exceeded the cooling effect during the day (see Figure 2b,d,f, ENF and MF). We enlarged this region to examine the details, as shown in Figure 5a,b. The warming region was found to be mainly located in high-altitude mountainous areas (Figure 5c), and this was covered with snow in winter, as shown in Figure 5d. The dark forest canopies conceal the underlying snow-covered grassland surface and further lower surface albedo. Thus, the forest surface absorbs more energy, subsequently generating a local warming effect, like its behavior in high-latitude regions. These phenomena suggest that intricate local conditions, such as high altitudes, can cause local warming [34,35].