Burning and meteorological conditions during the 2002 Yakutsk wildfire season are thoroughly discussed in LS17. Mainly, there were two distinguishable fire periods: the fire period 1 (FP1, from 1 August to 11 August) and the fire period 2 (FP2, from 12 August to the end of August). During FP1, relatively small amounts of smoke particles were swirled into a relatively strong frontal system (FS1). In the beginning of FP2, the domain was under the influence of the strong blocking high-pressure system. Large amounts of smoke particles were released during this period interacted with a relatively weak frontal system (FS2), coming from the west of the domain later.
3.1. Comporison of Modeled Radiative Fluxs against the SRB Dataset
Firstly, in
Figure 1 we compare the SRB SW
TOA↑ and SW
TOA↑ modeled by the SMOKE case for the entire simulation period (30 days). Please note that here we used positive values to represent SW
TOA↑. Since we output modeled variables every two hours in contrast to the 3-h temporal resolution of the SRB dataset, for each day, we calculated the daily SW
TOA↑ by averaging the SW
TOA↑ at 0000, 0600, 1200, and 1800 UTC. In addition, to accommodate the spatial resolutions of the model grid and SRB dataset, we averaged all the model grids within each 1° × 1° grid. In total, 44,370 pairs of modeled daily SW
TOA↑ and SRB daily SW
TOA↑ are labeled in the scatter plot as shown in
Figure 1. To compare modeled and SRB values, we conduct a regression analysis. The regression line, as shown by the black line in
Figure 1, is set to pass (0,0) point. The regression coefficient between modeled and SRB daily SW
TOA↑ equals 0.76, which indicates that the model tends to underestimate the magnitude of SW
TOA↑. The fact that modeled SW
TOA↑ is lower than SRB retrievals is very likely due to “too few, too bright” clouds modeled by numerical models [
23], as in WRF-Chem-SMOKE. For example, our result is very similar to the study conducted in [
24], which examines the radiative forcing of smoke in the Amazonia region using the WRF-Chem model. They found that modeled daily SW
SFC↓ is 10% larger than SRB SW
SFC↓, mainly due to optical thin clouds produced by the model. The smaller daily SW
TOA↑ (e.g., the points below the regression line) in our study can be explained by the same reason.
Another possible explanation for the smaller magnitude of modeled daily SW
TOA↑ compared to the SRB daily SW
TOA↑ is due to the fact that SRB misclassifies the strong smoke plumes as cloud layers. Strictly speaking, the SRB dataset (v3.0) does not account for the real-time aerosol/smoke field, but only considers the standard aerosol profiles.
Figure 2 shows the SRB cloud fraction field at 0600 UTC on 19 August 2002. The SRB cloud fractions are retrieved from ISCCP and used as inputs in the SRB dataset. Compared to the true color image shown in
Figure 3, we find that the SRB dataset classifies many 1° × 1° grids as having a cloud fraction higher than 0.95. However, the 1° × 1° grids in two regions (62° N–66° N, 115° E–125° E and 67° N–73° N, 110° E–150° E) are actually covered by strong smoke plumes. Because of the higher reflectivity associated with cloud pixels as compared to smoke pixels, the SRB dataset tends to overestimate SW
TOA↑.
In order to prove our reasoning above, we further generated two more scatter plots, in which the SRB and modeled daily SW
TOA↑ pairs were screened by different criteria. Firstly, we calculated the modeled cloud fractions, which are assumed as the ratios of the number of model grids with daily averaged total water path (TWP, only 0000, 0600, 1200, and 1800 UTC; four time steps) larger than 0.1 kg/m
2 to the total number of model grids in each 1° × 1° grid. In
Figure 4a, we label the SRB and modeled daily SW
TOA↑ pairs, if the absolute differences between SRB retrieved cloud fraction and modeled cloud fractions are smaller than 0.05. The regression and correlation analyses, as well as average values, show that the modeled daily SW
TOA↑ are reasonably modeled compared to SRB. In addition to all-sky radiative fluxes discussed above, the SRB dataset also provides clear-sky radiative fluxes, which are calculated by assuming the absence of clouds. Therefore, we select the modeled daily SW
TOA↑ with daily averaged TWP and AOD in the 1° × 1° grid (only 0000, 0600, 1200, and 1800 UTC; four time steps), which are below 0.1 kg/m
2 and 0.01, respectively, and compare the values against the clear-sky SRB daily SW
TOA↑ in
Figure 4b. Again, the statistical analyses show a good agreement between model simulation and the SRB dataset. These results highlight the importance of reasonable representations of modeled cloud properties.
3.2. The Impact of Smoke on Radiative Fluxes during the Fire Period 1
Figure 5 shows SRB radiative fluxes in the first column and radiative fluxes modeled by SMOKE and CLEAN in the second and third columns at 0600 UTC on 9, 10 and 12 August. On 9 August, smoke plumes are located around 60° N–65° N, 125° E–135° E. In this region, the values of SW
TOA↑ in the SRB dataset are around 150–200 W/m
2 as shown in
Figure 5a, while SW
TOA↑ produced by the SMOKE and CLEAN cases, as shown in
Figure 5b,c, are 175–250 W/m
2 and 50–100 W/m
2, the difference between which can be interpreted as the smoke direct radiative forcing in this region. When examining the SW
TOA↑ associated with the frontal system (FS1 in LS17), we found that no significant difference exists between SMOKE and CLEAN, and both cases underestimate the magnitudes and the horizontal extents of SW
TOA↑ compared to the SRB dataset.
By 0600 UTC 10 August, smoke particles have almost been swirled in FS1. As smoke particles being activated as CCN and IN (shown in
Figure 4 in LS17), they strongly affect radiation fields via the indirect aerosol effect. The spatial distributions of SW
TOA↑ modeled by SMOKE and CLEAN (shown in
Figure 5e,f, respectively) significantly differ from each other in the lower portion of FS1. In particular, the lower portion of FS1 in CLEAN has the cloud coverage with the larger horizontal extent and appears further downwind. Comparing against the SRB dataset, we find that the SMOKE case performs much better in terms of simulating the spatial distributions of SW
TOA↑. In order to explain how smoke, via functioning as CCN and IN, induces such differences in cloud properties and resulting SW
TOA↑, we examine the smoke-induced changes in cloud properties along the cross-section labeled in
Figure 5e (as shown by the white line from 131° E, 61° N to 137° E, 61° N).
Similar to
Figure 6 in LS17,
Figure 6 in this study shows smoke-induced changes in cloud water content, rain water content, ice water content, and snow water content (CWC, RWC, IWC, and SWC) in color contours as well as column-integrated cloud droplet number concentration (CDNC) and IN in curve lines at 0600 UTC on 10 August 2002. As shown in
Figure 6a,b, the CLEAN case produces a cloud cell with a large amount of RWC and SWC at 135 km along the X-axis, while the corresponding cloud cell in SMOKE, located around 145 km along the X-axis, contains a moderate amount of RWC, but it lacks the strong vertical development and SWC. This is probably due to the high CDNC, which suppress the collision-coalescence and riming processes in this region. As shown in
Figure 6b, we find that a relatively large amount of IN is activated at the forward edge of the lower portion of FS1. As a result, the higher IN concentration promotes the formation of SWC and quickly depletes the water content in this region. In contrast, CLEAN produces a layer with a moderate amount of CWC. Therefore, the combined effects of CDNC and IN lead to the smoke-induced changes in cloud properties, which further cause differences in SW
TOA↑ as shown in
Figure 5e,f.
On 10 August 2002, according to the SRB dataset, values of SW
TOA↑ behind (to the west of) FS1 are around 250–450 W/m
2. These fairly high values are due to the presence of stratocumulus clouds behind the frontal system as shown in the MODIS true color image in
Figure 7. However, both SMOKE and CLEAN fail to produce a considerable amount of the cloud coverage, which eventually causes underestimated SW
TOA↑ behind FS1 on 10 August.
As discussed in LS17, by the time of 0400~0600 UTC 12 August 2002, the upper portion of FS1 has developed into a sub-polar vortex, while the lower portion of FS1 has become a mid-latitude cyclone system. As shown in
Figure 5g, the magnitudes of SW
TOA↑ associated with the mid-latitude cyclone are around 300~450 W/m
2. (Values of SW
TOA↑ in only a few 1° × 1° grids are higher than 450 W/m
2.) When examining the SW
TOA↑ modeled by SMOKE and CLEAN in the same region, we find that the magnitudes in both cases are higher than 450 W/m
2, but lower than 600 W/m
2 as shown in
Figure 5h,i. However, it should be noted that the performance by SMOKE exceeds that by CLEAN on 12 August, since SMOKE produces fewer model grids with SW
TOA↑ higher than 450 W/m
2. This is probably due to the fact that IN activated from smoke particles keep depleting the cloud water within the cyclone.
3.3. The Impact of Smoke on Radiative Fluxes during the Fire Period 2
On 19 August, dense smoke plumes cover a vast region and exert the significant radiative forcing at TOA and the surface. Meanwhile, around the western and eastern edges of the blocking high-pressure system, where the pressure cap is relatively weak, two cloud decks (shallow convections) appear, which are contaminated by smoke particles. The smoke-induced changes in radiative fluxes via the direct and indirect aerosol effects on 19 August and the following two days will be the focus of this section.
At 0600 UTC on 19 August, the SRB SW
TOA↑ associated with the smoke plumes are around 175~250 W/m
2, as shown in
Figure 8a. It should be noted that the SRB SW
TOA↑ are calculated by assuming the smoke plumes as clouds. Comparing against the SRB dataset, we find that the SMOKE case successfully reproduces the magnitudes and the spatial distribution of the SW
TOA↑ field below 67° N, between 110° E~130° E, as shown in
Figure 8b; however, SMOKE significantly underestimates the magnitudes of SW
TOA↑ above 67° N, between 110° E and 125° E by about 100 W/m
2. The difference between SRB and modeled SW
TOA↑ is probably due to the false assumption of cloud layers in the SRB dataset or underestimations in modeled smoke AODs in this region. Apparently, the CLEAN case does not reproduce the SW
TOA↑ associated with the smoke plume.
As shown in
Figure 8b, around the eastern edge of the blocking high-pressure system, the liquid-phase cloud deck, which stretches from west (130° E) to east (150° E) along 68° N, is greatly affected by smoke particles. As shown in
Figure 9a, large amounts of CDNC are activated from smoke particles within this cloud deck at 0600 UTC on 19 August. Due to the first indirect aerosol effect, the cloud deck in the SMOKE case becomes more reflective than the one in the CLEAN case. As a result, the values of SW
TOA↑ produced by SMOKE are around 250 W/m
2, which are much closer to the SRB SW
TOA↑ as compared to CLEAN in this region.
When examining the cloud deck around the western edge of the blocking high-pressure system (from 67° N 100° E to 56° N 115° E), we find that this cloud deck, which is also in the liquid phase, is contaminated by a relatively small amount of smoke particles. Consequently, column-integrated CDNC activated from smoke particles are relatively low in this area (~4 × 10
10 m
−2). The values of SRB SW
TOA↑ associated with this cloud deck are generally within 450–600 W/m
2 as shown in
Figure 8a. Therefore, we find that the SMOKE case performs better than the CLEAN case in simulating SW
TOA↑, since the latter predicts too many model grids with SW
TOA↑ higher than 600 W/m
2 as shown in
Figure 8c. In order to interpret smoke-induced changes in SW
TOA↑, we examine smoke-induced changes in cloud properties (CWC, RWC, and column-integrated CDNC) along the cross-sections labeled in
Figure 8b at 0600 UTC on 19 August. As shown in
Figure 10, relatively low CDNC in the SMOKE case actually promote the rain formation, while more CWC is predicted by the CLEAN case in the cloud deck. Therefore, the cloud deck in the SMOKE case is optically thinner and less reflective than the one in CLEAN.
During the following two days (20 and 21 August), the direct aerosol effect of smoke remains significant. For example, magnitudes of SRB SW
TOA↑ associated with the smoke plumes are still around 175–250 W/m
2. The SMOKE case performs reasonably in predicting the magnitudes and the spatial distributions of radiative fluxes associated with the smoke plumes. The intensity of the cloud deck around the western edge of the blocking high-pressure system weakens on 20 and 21 August. For example, we find that the number of 1° × 1° grids with SRB SW
TOA↑ higher than 450 W/m
2 declines on 20 August compared to the previous day, and the shallow convective clouds degrade to stratocumulus clouds on 21 August. Comparing the SW
TOA↑ modeled by SMOKE and CLEAN against the SRB dataset on 20 and 21 August, we find that the SMOKE case performs much better than the CLEAN case in simulating the SW
TOA↑ associated with the cloud deck around the western edge of the blocking high-pressure system. Specifically, similar to the previous day on 19 August, the CLEAN case overestimates the number of model grids with SW
TOA↑ higher than 600 W/m
2 on 20 August as shown in
Figure 8f. On 21 August, however, the CLEAN case underestimates the magnitudes of SW
TOA↑ associated with the cloud deck between 90° E and 100° E below 65° N by 100–200 W/m
2 as shown in
Figure 8i. This is due to the fact that the stratocumulus clouds have been well mixed with the smoke plume by 21 August. High CDNC are activated from the smoke particles as shown in
Figure 9b. Due to the first indirect aerosol effect, the albedo of the cloud deck in the SMOKE was higher.
Although the microphysical effect of smoke is the focus of our study, we cannot rule out the importance of the semi-direct or the radiative effect of smoke. Here, we show one example of how the semi-direct effect of smoke completely suppresses the development of one short-lived shallow cloud deck. As shown in
Figure 8c, the white square highlights one liquid-phase shallow cloud deck, which is only predicted by the CLEAN case at 0600 UTC on 19 August. The cloud deck has a cloud lifetime of less than 2 h, since it does not appear in the CLEAN case at 0400 UTC. In the same area, the SMOKE case predicts heavy smoke plumes for a few days. Therefore, in order to interpret the semi-direct effect of smoke on this cloud deck, we examine the difference in area-averaged heating profiles at 0400 UTC between SMOKE and CLEAN in
Figure 11. Apparently, the strong smoke plumes in this area significantly heat the atmosphere. The difference in area-averaged heating profiles between the two cases peaked around 2 km above the terrain. As a result, very likely due to the stability of the atmosphere being increased by the presence of smoke, the development of the cloud deck was completely suppressed in the SMOKE case.