Sensitivity of Summertime Convection to Aerosol Loading and Properties in the United Arab Emirates
Abstract
:1. Introduction
2. Materials and Methods
2.1. Numerical Model
2.2. WRF Experiments
- The nucleation of cloud droplets from is achieved through a lookup table with the activation fraction as a function of parameters such as the WRF-predicted temperature, updraft speed, number of available aerosols, and predefined values of the hygroscopicity parameter and the aerosol’s mean radius;
- Once nucleated, the aerosols are removed from , the third term on the right-hand-side (RHS) of Equation (5), but can be restored via hydrometeor evaporation, the fourth term in Equation (5). Aerosols can also be removed from the population by precipitation scavenging, the first term in Equations (5) and (6);
- For “water-friendly” aerosols, and when a climatological-based distribution is employed, a constant surface emission forcing is added in the lowest model layer based on the starting near-surface aerosol concentration. A similar contribution is not considered for the “ice-friendly” aerosols in the present version of the scheme, i.e., the last term on the RHS of Equation (6) is set to zero;
- The nucleation of dust particles into ice crystals occurs in the presence of supersaturation with respect to ice. Depending on the relative humidity (RH) with respect to water, condensation, immersion freezing (i.e., ice nucleation by particles immersed in supercooled water) and deposition nucleation (i.e., formation of ice from supersaturated water vapor on an insoluble particle without prior formation of liquid) can occur. These processes are accounted for by the second term on the RHS of Equation (6);
- The freezing of homogeneous nucleated deliquesced hygroscopic aerosols is also accounted for, with the decrease in represented by the second term on the RHS of Equation (5), while the freezing of existing water droplets is parameterized to be more effective in the presence of higher amounts of dust aerosols. Cloud ice sublimation returns the aerosols to , the third term on the RHS of Equation (6).
2.3. Observational and Reanalysis Datasets
2.4. Verification Diagnostics
3. Description of the Event (14 August 2013)
4. WRF Simulations
4.1. Aerosol Loading
4.2. Aerosol Interaction with Convection
4.2.1. ARI on Idealized and Climatological Aerosol Distributions
4.2.2. Sensitivity to Linear Scaling of Aerosol Loading
4.2.3. Sensitivity to Aerosol Properties
5. Discussion and Conclusions
- Two aerosol distributions are considered in this study: an idealized distribution, set up for the continental United States, and a climatological profile, based on a 7-year output of a general circulation model. The best agreement is found when the climatological values are multiplied by a factor of 5, in line with the dustier atmosphere during this event.
- For the simulations with the idealized and climatological aerosol distributions, when the aerosol–radiation interaction (ARI) effects are switched on, the daily averaged surface downward shortwave radiation flux is reduced by 3 W m−2 and 20 W m−2, respectively, leading to changes in the surface temperature within 1 K and in the air temperature within 0.5 K. Activating the ARI effects when the climatological aerosol loading is used leads to a roughly 47% increase in the domain-wide precipitation, as the convective cells are more active, and the stronger updrafts increase the fraction of activated aerosols.
- WRF has a cold bias over the UAE, which is not alleviated when interior nudging in the outermost and two outermost grids is employed. While the skill scores of the innermost nest improved in particular when interior nudging is applied to the two outermost grids, the cold bias in the 2.5 km grid persisted. This is because a change in the atmospheric circulation, in particular in the position of the AHL, leads to increased precipitation over the UAE and locally colder temperatures, which offset the higher temperatures that arise from more accurate boundary conditions.
- The downward and upward shortwave and the upward longwave radiation fluxes are found to decrease linearly as the aerosol loading is increased. As the aerosol loading goes up, the AHL shifts eastwards, with the low-level wind convergence taking place in a drier region, resulting in lower precipitation amounts falling in a more spatially confined area. In addition, the onset of convection is also delayed.
- When 20% of the aerosols are replaced with more absorbing (carbonaceous) particles, the roughly 87 W m−2 decrease in the surface net shortwave radiation flux is comparable to the drop when the aerosol loading is augmented by a factor of 10. This stresses that the aerosol composition plays a role as important as its amount on the surface radiative fluxes, at least for the range of values considered here.
- When accounting for the observed aerosol loading, using a climatology-based distribution is preferable to an idealized distribution as it can improve the representation of deep convection.
- Even in the short term, such as 2-day simulations, the fields in the interior of the WRF nests can be substantially different from those in the input dataset. Employing nudging in the outer nests is preferable to only applying it in the outermost nest or not doing it altogether, as it helps to at least partially correct some of the WRF biases.
- It is vital to accurately represent the properties of the observed aerosols in the model, more so than the amount, provided the order of magnitude is in line with that observed.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A. Sensitivity to Nudging Formulation
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Parameterization Scheme | Option |
---|---|
Cloud Microphysics | Thompson–Eidhammer scheme [49] (In the default version, only ACI effects are activated; ARI effects are switched on through an option in the model’s namelist) |
Planetary Boundary Layer (PBL) | Mellor–Yamada Nakanishi Niino (MYNN) level 2.5 [50,51], with mass-flux scheme [45] activated |
Radiation | Rapid Radiative Transfer Model for Global Circulation Models [52] |
Cumulus | 22.5 km and 7.5 km grids: Kain–Fritsch [53], with subgrid-scale cloud feedbacks to radiation [54] 2.5 km grid: no cumulus scheme |
Land Surface Model (LSM) | Noah LSM with MultiParameterization options [55,56] |
Sea Surface Temperature (SST) | 6-hourly ERA-5 SSTs + simple skin temperature scheme [47] |
Numerical Experiment | Aerosol Profile | ARI Setting | Nudging |
---|---|---|---|
1. WRF-IDEAL | IDEAL | - | - |
2. WRF-IDEAL-ARI_R | IDEAL | RURAL | - |
3. WRF-CLIM | CLIM | - | - |
4. WRF-CLIM-ARI_R | CLIM | RURAL | - |
5. WRF-CLIM-ARI_R-NUDGE | CLIM | RURAL | NUDGE |
6. WRF-5×CLIM-ARI_R-NUDGE | 5×CLIM | RURAL | NUDGE |
7. WRF-5×CLIM-ARI_U-NUDGE | 5×CLIM | URBAN | NUDGE |
8. WRF-5×CLIM-ARI_M-NUDGE | 5×CLIM | MARITIME | NUDGE |
9. WRF-10×CLIM-ARI_R-NUDGE | 10×CLIM | RURAL | NUDGE |
Field | Diagnostic | WRF-1 | WRF-2 | WRF-3 | WRF-4 | WRF-5 | WRF-6 | WRF-7 | WRF-8 | WRF-9 |
---|---|---|---|---|---|---|---|---|---|---|
Temperature | BIAS (K) | –2.4720 | –2.4530 | –2.4050 | –2.5551 | –2.5464 | –2.7312 | –3.4674 | –2.8168 | –3.0556 |
μ | –0.5263 | –0.5219 | –0.5166 | –0.5603 | –0.5746 | –0.6649 | –1.0292 | –0.6428 | –0.7843 | |
ρ | 0.4113 | 0.4118 | 0.4255 | 0.4374 | 0.4655 | 0.5213 | 0.6299 | 0.4815 | 0.5504 | |
η | 0.9979 | 0.9977 | 0.9975 | 0.9986 | 0.9989 | 1.0000 | 0.9859 | 0.9997 | 0.9993 | |
α | 0.5896 | 0.5892 | 0.5756 | 0.5632 | 0.5350 | 0.4787 | 0.3790 | 0.5187 | 0.4499 | |
Mixing Ratio | BIAS (g kg–1) | –2.2123 | –2.0726 | –2.4731 | –2.3181 | –2.8098 | –2.6691 | –2.6477 | –2.8422 | –2.7686 |
μ | –0.3835 | –0.3605 | –0.4279 | –0.4004 | –0.4713 | –0.4315 | –0.4205 | –0.4603 | –0.4170 | |
ρ | 0.3511 | 0.3563 | 0.3565 | 0.3399 | 0.3942 | 0.3417 | 0.3341 | 0.3609 | 0.3041 | |
η | 0.9915 | 0.9916 | 0.9933 | 0.9898 | 0.9999 | 1.0000 | 0.9995 | 0.9995 | 0.9962 | |
α | 0.6519 | 0.6468 | 0.6459 | 0.6635 | 0.6059 | 0.6584 | 0.6661 | 0.6393 | 0.6970 | |
SLP | BIAS (hPa) | 3.0872 | 3.0702 | 3.0680 | 3.0084 | 2.7449 | 2.7320 | 2.6919 | 2.9786 | 2.8215 |
μ | 0.6995 | 0.6957 | 0.6940 | 0.6788 | 0.6292 | 0.6231 | 0.6210 | 0.6823 | 0.6438 | |
ρ | –0.0456 | –0.0430 | –0.0442 | –0.0475 | –0.0610 | –0.0734 | –0.0731 | –0.0809 | –0.0823 | |
η | 0.8324 | 0.8318 | 0.8310 | 0.8303 | 0.8431 | 0.8431 | 0.8499 | 0.8474 | 0.8454 | |
α | 1.0380 | 1.0358 | 1.0367 | 1.0394 | 1.0515 | 1.0619 | 1.0621 | 1.0686 | 1.0696 | |
SWDOWN | BIAS (W m–2) | 99.4563 | 96.7037 | 97.7780 | 77.5172 | 73.7791 | 9.2294 | –112.3040 | 35.3777 | –45.8454 |
μ | 0.5863 | 0.5732 | 0.5717 | 0.4975 | 0.4742 | 0.0747 | -0.5850 | 0.2613 | –0.3298 | |
ρ | 0.9082 | 0.9077 | 0.9059 | 0.9114 | 0.9111 | 0.9182 | 0.8415 | 0.9118 | 0.9077 | |
η | 0.9736 | 0.9747 | 0.9738 | 0.9835 | 0.9838 | 0.9995 | 0.8341 | 0.9982 | 0.9595 | |
α | 0.1175 | 0.1152 | 0.1178 | 0.1036 | 0.1036 | 0.0823 | 0.2981 | 0.0898 | 0.1291 | |
Horizontal Wind | BIAS (SPEED; m s–1) | 3.0946 | 3.1309 | 3.1145 | 3.1785 | 3.5708 | 4.1674 | 3.1660 | 4.0691 | 4.4585 |
μ (SPEED) | 0.7686 | 0.7572 | 0.7667 | 0.7572 | 0.7817 | 0.8530 | 0.6813 | 0.8714 | 0.9156 | |
ρ | 0.1557 | 0.1571 | 0.1407 | 0.1226 | 0.1293 | 0.0513 | 0.0785 | 0.0597 | 0.0182 | |
η | 0.9728 | 0.9679 | 0.9717 | 0.9715 | 0.9568 | 0.9498 | 0.9252 | 0.9618 | 0.9545 | |
α | 0.8485 | 0.8479 | 0.8633 | 0.8809 | 0.8763 | 0.9513 | 0.9274 | 0.9425 | 0.9826 | |
PRECIPIATION BIAS (mm) | –42.4447 | –40.5812 | –51.0678 | –50.4518 | –38.0378 | –41.5867 | –35.7302 | –48.5239 | –45.6105 |
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Fonseca, R.; Francis, D.; Weston, M.; Nelli, N.; Farah, S.; Wehbe, Y.; AlHosari, T.; Teixido, O.; Mohamed, R. Sensitivity of Summertime Convection to Aerosol Loading and Properties in the United Arab Emirates. Atmosphere 2021, 12, 1687. https://doi.org/10.3390/atmos12121687
Fonseca R, Francis D, Weston M, Nelli N, Farah S, Wehbe Y, AlHosari T, Teixido O, Mohamed R. Sensitivity of Summertime Convection to Aerosol Loading and Properties in the United Arab Emirates. Atmosphere. 2021; 12(12):1687. https://doi.org/10.3390/atmos12121687
Chicago/Turabian StyleFonseca, Ricardo, Diana Francis, Michael Weston, Narendra Nelli, Sufian Farah, Youssef Wehbe, Taha AlHosari, Oriol Teixido, and Ruqaya Mohamed. 2021. "Sensitivity of Summertime Convection to Aerosol Loading and Properties in the United Arab Emirates" Atmosphere 12, no. 12: 1687. https://doi.org/10.3390/atmos12121687
APA StyleFonseca, R., Francis, D., Weston, M., Nelli, N., Farah, S., Wehbe, Y., AlHosari, T., Teixido, O., & Mohamed, R. (2021). Sensitivity of Summertime Convection to Aerosol Loading and Properties in the United Arab Emirates. Atmosphere, 12(12), 1687. https://doi.org/10.3390/atmos12121687