Evaluating dust emission model performance using dichotomous satellite observations of dust emission

Measurements of dust in the atmosphere have long been used to calibrate dust emission models. However, there is growing recognition that atmospheric dust confounds the magnitude and frequency of emission from dust sources and hides potential weaknesses in dust emission model formulation. In the satellite era, dichotomous (presence = 1 or absence = 0) observations of dust emission point sources (DPS) provide a valuable inventory of regional dust emission. We used these DPS data to develop an open and transparent framework to routinely evaluate dust emission model (development) performance using coincidence of simulated and observed dust emission (or lack of emission). To illustrate the utility of this framework, we evaluated the recently developed albedo-based dust emission model (AEM) which included the traditional entrainment threshold (u*ts) at the grain scale, fixed over space and static over time, with sediment supply infinite everywhere. For comparison with the dichotomous DPS data, we reduced the AEM simulations to its frequency of occurrence in which soil surface wind friction velocity (us*) exceeds the u*ts, P(us* > u*ts). We used a global collation of nine DPS datasets from established studies to describe the spatio-temporal variation of dust emission frequency. A total of 37,352 unique DPS locations were aggregated into 1,945 1° grid boxes to harmonise data across the studies which identified a total of 59,688 dust emissions. The DPS data alone revealed that dust emission does not usually recur at the same location, are rare (1.8 %) even in North Africa and the Middle East, indicative of extreme, large wind speed events. The AEM over-estimated the occurrence of dust emission by between 1 and 2 orders of magnitude. More diagnostically, the AEM simulations coincided with dichotomous observations ~71 % of the time but simulated dust emission ~27 % of the time when no dust emission was observed. Our analysis indicates that u*ts was typically too small, needed to vary over space and time, and at the grain-scale u*ts is incompatible with the us* scale (MODIS 500 m). During observed dust emission, us* was too small because wind speeds were too small and/or the wind speed scale (ERA5; 11 km) is incompatible with the us* scale. The absence of any limit to sediment supply caused the AEM to simulate dust emission whenever P (us* > u*ts), producing many false positives when and where wind speeds were frequently large. Dust emission model scaling needs to be reconciled and new parameterisations are required for u*ts and to restrict sediment supply varying over space and time. Whilst u*ts remains poorly constrained and unrealistic assumptions persist about sediment supply and availability, the DPS data provide a basis for the calibration of dust emission models for operational use. As dust emission models develop, these DPS data provide a consistent, reproducible, and valid framework for their routine evaluation and potential model optimisation. This work emphasises the growing recognition that dust emission models should not be evaluated against atmospheric dust.

Contrasting Mineral Dust Abundances from X-Ray Diffraction and Reflectance Spectroscopy

Mineral dust particles dominate aerosol mass in the atmosphere and directly modify Earth’s radiative balance through absorption and scattering. This radiative forcing varies strongly with mineral composition, yet there is still limited knowledge on the mineralogy of atmospheric dust. In this study, we performed X-ray diffraction (XRD) and reflectance spectroscopy measurements on 37 different atmospheric dust samples collected as airfall in an urban setting to determine mineralogy and the relative proportions of minerals in the dust mixture. Most commonly, XRD has been used to characterize dust mineralogy; however, without prior special sample preparation, this technique is less effective for identifying poorly crystalline or amorphous phases. In addition to XRD measurements, we performed visible, near-infrared, and short-wave infrared (VNIR/SWIR) reflectance spectroscopy for these natural dust samples as a complementary technique to determine minerology and mineral abundances. Reflectance spectra of dust particles are a function of a nonlinear combination of mineral abundances in the mixture. Therefore, we used a Hapke radiative transfer model along with a linear spectral mixing approach to derive relative mineral abundances from reflectance spectroscopy. We compared spectrally derived abundances with those determined semi-quantitatively from XRD. Our results demonstrate that total clay mineral abundances from XRD are correlated with those from reflectance spectroscopy and follow similar trends; however, XRD underpredicts the total amount of clay for many of the samples. On the other hand, calcite abundances are significantly underpredicted by SWIR compared to XRD. This is caused by the weakening of absorption features associated with the fine particle size of the samples, as well as the presence of dark non-mineral materials (e.g., asphalt) in these samples. Another possible explanation for abundance discrepancies between XRD and SWIR is related to the differing sensitivity of the two techniques (crystal structure vs chemical bonds). Our results indicate that it is beneficial to use both XRD and reflectance spectroscopy to characterize airfall dust, because the former technique is good at identifying and quantifying the SWIR-transparent minerals (e.g., quartz, albite, and microcline), while the latter technique is superior for determining abundances for clays and non-mineral components.

Impact of dust-cloud-radiation interactions on surface albedo: a case study of "Tiramisu" snow in Urumqi, China

Dust-cloud-surface radiation interactions (DCRI) is a complex nonlinear relation referring to the influences of both atmospheric dust and dust-on-snow on surface albedo. A “Tiramisu” snow event occurred on December 1st, 2018, in Urumqi, China, providing an excellent testbed for exploring the comprehensive effect induced by atmospheric dust and those deposited atop fresh snowpack on surface radiation. A detailed analysis indicates that the decrease of snow albedo by 0.17–0.26 (22–34%) is contributed by the effects both the dust-cloud interactions and dust-on-snow at synoptic scale in this case. In particular, dust well mixed with ice clouds at altitudes of 2.5–5.5 km disrupted the “seeder-feeder” structure of clouds and heterogeneous ice nucleation. Dust-induced changes in the low layer of ice cloud (3.3–5.5 km) under a low temperature of –20 °C resulted in a 31.8% increase in the ice particle radius and 84.6% in the ice water path, which acted to indirectly buffer the incident solar radiation reaching the surface. Dust particles deposited on the snow surface further caused snow darkening since the snow albedo was found to decrease by 11.8–23.3%. These findings underscore the importance of considering the comprehensive effect of dust-cloud-radiation interactions in the future.

Asymmetric impacts on Mars' polar vortices from the 2018 Global Dust Storm

<p><strong>Introduction:</strong>  Like Earth, Mars possesses dynamical atmospheric features known as polar vortices. These are regions of cold, isolated polar air surrounded by powerful westerly wind jets which can create barriers to transport of atmospheric dust, water, and chemical species. They have a complex and asymmetrical (north/south) relationship with atmospheric dust loading [1]. Regional and global dust events have been shown to cause rapid vortex displacement [2,3] in the northern vortex, while the southern vortex appears more robust.</p> <p>Unlike Earth, Mars also experiences planet-encircling Global Dust Storms: spectacular, planet-spanning events which dramatically increase atmospheric dust loading. The most recent such event in 2018 (beginning at northern autumn equinox) [4] was observed by multiple spacecraft, including the ExoMars Trace Gas Orbiter (TGO) and the Mars Reconnaissance Orbiter (MRO), enabling the opportunity to study its effects on the polar vortices in detail.</p> <p>We do this by assimilating [5] spacecraft data from TGO’s Atmospheric Chemistry Suite (ACS) [6,7] and MRO’s Mars Climate Sounder (MCS) [8,9] into the LMD-UK Mars Global Climate Model [10], a 4D numerical model of the martian atmosphere.</p> <p><strong>Results: </strong>We present our recently published results [11], where we find that the 2018 GDS had asymmetrical impacts in each hemisphere: the northern polar vortex remained relatively robust, while the southern polar vortex was significantly disrupted. This asymmetry was due to both the storm’s latitudinal extent, which was greater in the south than in the north, and its timing, occurring as the southern vortex was already decaying after equinox. Both polar vortices and especially the northern showed reductions in their ellipticity, and this correlated with a reduction in high-latitude stationary wave activity in both hemispheres. We show that the characteristic elliptical shape of Mars’ polar vortices is the pattern of the stationary waves; this was suppressed during the storm by the shifting of the polar jet away from regions of high mechanical forcing in the north, and by the reduced polar jet due to the decreased meridional temperature gradient in the south. These asymmetric effects suggest enhanced transport into the southern, but not northern, polar region during GDS around northern autumn equinox, as well as more longitudinally symmetric transport around both poles.</p> <p><strong> </strong></p> <p><strong>References:</strong> [1] Waugh, D. W. et al (2016) <em>J. Geophys. Res. Planets, 121, </em>1770-1785. [2] Guzewich, S. D. et al (2016) <em>Icarus, 278, </em>100-118. [3] Mitchell, D. M. et al (2015) <em>Q.J.R. Meteorol. Soc., 141, </em>550-562. [4] Kass, D. M et al (2019) <em>GRL, 47</em>(23). [5] Lewis, S. R. et al (2007) <em>Icarus, 192</em>(2). [6] Korablev, O. et al (2018) <em>Space Sci. Rev., 214</em>(7). [7] Fedorova, A. A. et al (2020) <em>Science, 367</em>(6475). [8] McCleese, D. J. et al (2007) <em>JGR (Planets), 112</em>(E5). [9] Kleinböhl, A. et al (2009) <em>JGR (Planets), 114</em>(E10). [10] Forget, F. et al (1999) <em>JGR (Planets), 104</em>(E10). [11] Streeter, P. M. et al (2021) <em>JGR (Planets), </em>e2020JE006774.</p>

Influence of Dust on the Initiation of Neoproterozoic Snowball Earth Events

It has been demonstrated previously that atmospheric dust loading during the Precambrian could have been an order of magnitude higher than in the present day and could have cooled the global climate by more than 10 °C. Here, using the fully coupled atmosphere-ocean general circulation model CESM1.2.2, we determine whether such dust loading could have facilitated the formation of Neoproterozoic snowball Earth events. Our results indicate global dust emission decreases as atmospheric CO2 concentration (pCO2) decreases due to increasing snow coverage, but atmospheric dust loading does not change or even increases due to decreasing precipitation and strengthening June-July-August (JJA) Hadley circulation. The latter lifts more dust particles to high altitude and thus increases the lifetime of these particles. As the climate becomes colder and the surface albedo higher, the cooling effect of dust becomes weaker; when the global mean surface temperature is approximately -13 °C, dust has negligible cooling effect. The threshold pCO2 at which Earth enters a snowball state is between 280 to 140 ppmv when there is no dust, and is similar when there is relatively light dust loading (~4.4 times present-day value). However, the threshold pCO2 decreases dramatically to between 70 to 35 ppmv when there is heavy dust loading (~33 times present-day value), due to the decrease in planetary albedo which increases the energy input into the climate system. Therefore, dust makes it more difficult for Earth to enter a snowball state.