The Impact of Saharan dust aerosols on tropical cyclones using wrf-chem: Model framework and satellite data constraint technique

We further evaluate our technique against measurements from the NAMMA DC-8 flight occurring on 5 September 2006. The MODIS RGB composite image has already been presented for this case study where a Saharan dust storm was being transported from western Africa to over the Atlantic Ocean (Figure 2a). A lower correlation exists between the GOCART and MODIS τ on 5 September (Figure 6a-b) compared to the 19 August case with values of 0.53 for this case. However, the two products show similar variability in the τ’s across the domain as the standard deviation for GOCART and MODIS is 0.29 and 0.28, respectively, where MODIS retrieves a maximum and minimum of 1.56 and 0.05 while GOCART has a maximum and minimum of 1.18 and 0.09. The mean τ for GOCART is 0.40 and for MODIS is 0.47. The largest discrepancies between the two products occur over the high reflecting desert where GOCART shows τ near 1.0 across a significant area of the desert while MODIS shows τ ranging from 0.2 to 1.0 throughout this same area. The correlation coefficient between the τ maps significantly increases to 0.73 when ignoring the τ’s over the bright desert region, which is noteworthy since the WRF-Chem model domains for our TC Florence simulations (i.e. Figure 1) do not extend over the bright desert. Nonetheless, the DC-8 aircraft measured a τ value of only 0.23 at the location of its descent profile in Figures 6a-b while the GOCART and MODIS values were about 0.9 and 0.4, respectively, at this location. Even though it is very difficult to compare a daily τ product from a space-based sensor and an instantaneous τ from an in situ instrument, the fact that GOCART value is almost four times the DC-8 value suggests that the MODIS retrieval is more representative than the GOCART simulation across the desert region. Fortunately, since MODIS retrievals are available across the bright desert, our satellite data constraint technique uses these τ values instead of the GOCART values when generating the three-dimensional extinction map for calculating the dust mass concentrations. In the combined MODIS/GOCART τ map (Figure 6c) over 70% of the domain is covered with the MODIS τ’s while less than 30% is covered with the GOCART τ’s. The τ_calipso map (Figure 6d) reveals large differences occurring between the MODIS/GOCART τ and the τ calculated from the CALIPSO 5 km extinction profiles with a low correlation coefficient of 0.40. A few similarities are seen between the maps, especially west of 24°W where the correlation coefficient increases to 0.54 for this region over the Atlantic Ocean with τ’s mostly less than 0.4, but overall the τ_calipso values are unreliable. For instance, the τ_calipso map is only able to capture a small area of large τ’s associated with the dust storm across western Africa and the Atlantic Ocean while both MODIS and GOCART suggest the area of large τ’s is much more extensive.

Next we validate the aerosol number concentrations derived using our technique with the number concentrations measured by the APS instrument of the DC-8 aircraft during the ascent and descent legs of its track on 5 September. Our derived number concentrations before and after the scaling procedure are compared against the DC-8 measurements. The non-scaled profile severely underestimates the peak concentration while the scaled profile agrees fairly closely to the peak concentration from the DC-8 aircraft (Figure 7a). The large difference between the non-scaled and scaled profiles is due to the much higher τ in the vicinity of the DC-8 ascent profile in the MODIS/GOCART map than in the τ_calipso map. For the descent leg of the DC-8 aircraft, our scaled concentration profile compares relatively well to the DC-8, except for the peak in concentration to about 35 cm^-3 in the DC-8 profile that is missing in our profile (Figure 7b). Also, the peak concentrations in our scaled profile occur at slightly higher heights than in the DC-8 profile. Once again the non-scaled profile significantly underestimates the number concentration beneath 5 km in height. This validation exercise further proves our reasoning for applying the scaling procedure in our technique. The results of our derived aerosol number concentrations are quite encouraging especially when considering the fact that the DC-8 profiles in Figure 6c-d occur roughly 400 to 500 km from the nearest CALIPSO measurements. This shows that once dust is lofted in the atmosphere its vertical structure does not vary significantly with distance during transport. Typically, dust storms gradually decrease in altitude during their transport across the Atlantic Ocean [Huang et al., 2010] which suggests that using daily composites of CALIPSO transects to understand the vertical structure of dust across our study region (i.e. Atlantic Ocean) is a valid method.

Finally, we present an example of the derived dust mass concentration profiles that are input into the WRF-Chem model. Figure 8a displays the CALIOP backscatter measured during a nighttime CALIPSO transect at approximately 0300 UTC on 5 September which is the central transect in our domain. An extended region of dust aerosols are lofted from about 2-5 km poleward of 10°N, and the dust associated with the highest backscatter values are located between 21 and 25°N as indicated by the pink and blue colors. Some clouds associated with high backscatter are causing complete attenuation of the CALIOP lidar signal, especially from 16-18°N, making it impossible for the lidar to measure the dust beneath the clouds. Fortunately, our satellite data constraint technique ensures that the strongly attenuated CALIPSO backscatter profiles are not used to derive the final dust mass concentrations input into the WRF-Chem model. The scaled mass concentrations input into the model along this CALIPSO transect are shown in Figure 8b where fairly large concentrations greater than 1000 μg m^-3 are derived for the dust storm from 12-19°N. The CALIOP lidar is also completely attenuated over most of its transect from 5-10°N due to the high, thick convective clouds that are often present in this region. These convective clouds are clearly seen in the southern portion of the MODIS RGB image on 5 September (i.e. Figure 2a). Although the CALIOP lidar is completely attenuated by the clouds, we still derive some mass concentration approaching 800 μg m^-3 along this section of the transect. The few CALIPSO backscatter profiles that do not undergo strong attenuation from 5-10°N allow us to understand the vertical structure of the dust among the clouds. Note that the dust mass concentrations we present here are the total mass concentrations which means they are the summation of the concentrations calculated for the four WRF-Chem sectional diameter bins. Overall, our technique appears to ingest reliable dust mass concentration profiles into the WRF-Chem model.

Our satellite data constraint technique uses a constant lidar ratio of 39 sr for all the dust aerosols across the study domains for the TC Florence case. However, Omar et al. [2010] calculated the lidar ratio from measurements gathered during numerous DC-8 flights through dust layers throughout the NAMMA campaign in August and September 2006, and they found that the lidar ratio for dust during this time period varied from 35-43 sr. The lidar ratio is important for calculating the extinction profiles from the CALIPSO attenuated backscatter measurements. In addition, even though Chen et al. [2011] found that the imaginary refractive index varied from 0.0015-0.0044 for the dust layers during the NAMMA campaign, our technique uses a constant imaginary index of 0.0022 when conducting the Mie calculations that impact our dust mass concentration values. Thus, we test the sensitivity of the dust mass concentrations to the range of lidar ratios and imaginary indices found during the NAMMA campaign.

Figure 9 shows the percentage difference in the mass concentration values calculated by our technique along the CALIPSO transect on 5 September at 0300 UTC when changing the constant lidar ratio and imaginary index values to 35 sr and 0.0015. We already showed the original mass concentration values when using a constant lidar ratio and imaginary index of 39 sr and 0.0022 (Figure 8a). There is only a slight difference in the mass concentrations throughout the CALIPSO transect as the differences are mostly from 0-2%. Larger differences of 3-5% appear for the dust layers south of 12°N with a couple outlier values greater than 7%. But, for the most part, setting the lidar ratio and imaginary indices to these lower values did not have a significant impact on the results of our technique. Note that the range in the imaginary indices found for the dust layers during the NAMMA campaign had a near negligible impact on our calculated mass concentrations compared to the range in the lidar ratios. Thus, the percentage differences are due almost entirely to using the lower lidar ratio. Also, we do not show the percentage difference results when using the higher lidar ratio and imaginary index of 43 sr and 0.0044 since they are nearly identical to Figure 9.

Table 4 shows the variations of the mass concentration values in the four sectional diameter bins in WRF-Chem when using a lidar ratio of 35, 39, and 43 sr. The results in Table 4 are for the dust layer associated with the higher percentage differences of 3-5% in Figure 9 which is located 3-5 km in height from 9-13°N. The majority of the percentage differences in the total mass concentrations in Figure 9 were caused by the largest diameter bin (Bin 4) as the concentration values varied from 264.4-278.4 μg m^-3 for the range of lidar ratios of 35-43 sr. The variation in the concentration values are reduced when moving from the largest to smallest size bins which is expected as the range in lidar ratio will have a greater impact on the higher mass concentrations.

We also conduct a sensitivity test on using the MODIS L3 daily AOD product as opposed to the MODIS L2 instantaneous AOD product. For this sensitivity test, we compare the two AOD products on 2 September 2006 as we initialize our TC Florence simulation on this day at 1200 UTC. The MODIS L3 daily AOD product (Terra and Aqua) on 2 September for the region centered over the WRF-Chem model domain is shown in Figure 10a. The MODIS L2 AOD retrieved from all the available Aqua and Terra overpasses across this region on 2 September is displayed in Figure 10b. All the Aqua and Terra daytime overpasses over this region occur during the daytime between about 1200 and 1800 UTC as AOD is not retrieved at nighttime, and these AOD retrievals are then used to produce the L3 daily product. Thus, we essentially use a +6 hour time window by using the MODIS L3 daily product in our satellite data constraint technique since we initialize and update the WRF-Chem model at 1200 UTC on each day of the simulation. The major advantage of using the MODIS L3 daily product is the greater coverage of AOD across the domain which is clearly seen by comparing Figures 10a-b. However, the greater AOD coverage comes at a cost as the L3 daily product has a much coarser spatial resolution of 1° by 1° compared to the 10 km resolution of the L2 product. The coarser spatial resolution of the L3 daily product could lead to significant discrepancies between the AOD of the two MODIS products. Fortunately, for our TC Florence simulation, the MODIS L2 and L3 products compare closely which suggests that we are not introducing major uncertainties into the model simulation by using the L3 product. An example of the close comparison between the products is displayed in Figure 11. The scatter plot shows a very high correlation of 0.96 between the L2 and L3 AOD on 2 September. The largest differences between the two products occur for AOD > 1.0 which implies that the spatial distribution of the large AOD regions are varying more strongly than the smaller AOD regions. However, overall the two MODIS products agree very closely as the mean AOD across the domain for the L3 and L2 products are 0.37 and 0.34, respectively.

The combined MODIS/GOCART AOD map used to initialize the aerosol fields of the WRF-Chem model on 2 September at 1200 UTC is shown in Figure 12a where the northern half of the domain is mostly filled with MODIS L3 AOD. Figure 12b shows the combined MODIS/GOCART AOD if the L2 product was used in our study. The GOCART AOD covers a significant area of the northern half of the domain in Figure 12b which would introduce major uncertainties into our model simulation as the GOCART AOD is much lower than MODIS across the optically thicker regions of the dust storm. The GOCART model is unable to effectively transport the dust storm across the Atlantic which is leading to the large discrepancies between the GOCART and MODIS AOD. Therefore, the mean AOD across the domain in Figure 12b is only 0.24 while the mean AOD is 0.34 in Figure 12a. Consequently, using the MODIS L2 AOD product instead of the L3 daily product in our satellite data constraint technique will reduce the impact of the aerosol-radiation and aerosol-cloud interaction processes.

In this paper, we present a detailed overview of a technique for applying constraints based on satellite observations to improve the representation of three dimensional dust aerosol fields in WRF-Chem model, to be utilized for studying Saharan dust impact on TCs. Our unique technique combines the aerosol vertical structure from CALIPSO with the horizontal distribution from MODIS and GOCART to derive best estimates of three-dimensional distribution of aerosols, which is important for accurately simulating the impacts of the aerosol-radiation and aerosol-cloud interaction processes. We apply our technique to two case studies on 19 August and 5 September 2006 since in-situ aircraft measurements during the NAMMA campaign were available on these days to help validate the results of the technique. The significant conclusions from this paper are as follows:

1. In comparison to in situ observations in cloud-free regions, there was considerable improvement in the aerosol number concentration profiles upon the application of our satellite data constraint technique. For instance, observations and our technique both showed aerosol number concentrations from 20-30 cm^-3 between 2 and 5 km for Saharan dust moving over the eastern Atlantic Ocean on 5 September 2006.

2. In cloudy regions, we found that our technique was able to derive realistic mass concentrations for profiles where the CALIOP lidar was strongly attenuated. This is especially important for our TC simulations involving optically thick clouds that strongly attenuate the CALIOP signal which cause poor-quality backscatter measurements that should not be used assimilated into a model.

3. Overall, our technique is able to provide the model with a complete three dimensional distribution of aerosols in clear and cloudy conditions which is critical for conducting realistic simulations of aerosols interacting with a TC environment. The impacts of the aerosol direct and indirect radiative effects on a TC environment are dependent upon the horizontal and vertical distribution of aerosols in the atmosphere.

Although the technique performs well over ocean, it should be applied with caution over other regions and seasons where dust is not the dominant aerosol type and the transport pathways of the aerosol may be very different. In the second part of this two-part series, we apply the technique developed to investigate the potential impact of dust aerosols on TC development through conducting WRF-Chem model simulations on TC Florence taking place during the NAMMA campaign.

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