Global dust cycle and uncertainty in CMIP5 models

Abstract

Abstract. Dust cycle is an important component of the Earth system and have been implemented into climate models and Earth System Models (ESMs). An assessment of the dust cycle in these models is vital to address the strengths and weaknesses of these models in simulating dust aerosol and its interactions with the Earth system and enhance the future model developments. This study presents a comprehensive evaluation of global dust cycle in 15 models participating in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The various models are compared with each other and with an aerosol reanalysis as well as station observations of dust deposition and concentrations. The results show that the global dust emission in these models ranges from 735 to 8186 Tg yr−1 and the annual mean dust burden ranges from 2.5 to 41.9 Tg, both of which scatter by a factor of about 10–20. The models generally agree with each other and observations in reproducing the dust belt that extends from North Africa, Middle East, Central and South Asia, to East Asia, although they differ largely in the spatial extent of this dust belt. The models also differ in other dust source regions such as North America and Australia, where the contributions of these sources to global dust emissions vary by a factor of more than 500. We suggest that the coupling of dust emission with dynamic vegetation can enlarge the range of simulated dust emission. For the removal process, all the models estimate that wet deposition is a smaller sink than dry deposition and wet deposition accounts for 12–39 % of total deposition. The models also estimate that most (77–91 %) of dust particles are deposited onto continents and 9–23 % of them are deposited into oceans. A linear relationship between dust burden, lifetime, and fraction of wet deposition to total deposition from these models suggests a general consistency among the models. Compared to the observations, most models reproduce the dust deposition and dust concentrations within a factor of 10 at most stations, but larger biases by more than a factor of 10 are also noted at specific regions and for certain models. These results cast a doubt on the interpretation of the simulations of dust-affected fields in climate models and highlight the need for further improvements of dust cycle especially on dust emission in climate models.

Global Dust Variability Explained by Drought Sensitivity in CMIP6 Models

“…CMIP6 models vary widely in both annual dust emission and its interannual variability over all regions. Consistent with previous studies (e.g., Wu et al, 2020), MER-RA-2 underestimates mean annual dust emission over all regions when compared to the Global Circulation Models (GCMs). The intermodel spread in annual regional emission and each region's contribution to the ARYAL AND EVANS 10.1029/2021JF006073 5 of 20 total global emission is shown in Table 2, and the interannual standard deviation of each region is shown in Table 3.…”

“…The CMIP6 models diverge greatly in simulating dust emission, and its spatial and temporal variability. Consistent with previous studies (e.g., Evan et al, 2014;Pu & Ginoux, 2018;Wu et al, 2020), MERRA-2 reanalysis highly underestimates models' average dust emission over most dust source regions (Figure 2). Relative contribution of all dust source regions to the global total emission from CMIP6 ensemble and MERRA-2 are fairly consistent (Table 2).…”

“…Models also show how the dust climate relationship would evolve in different climatic and anthropogenic scenarios (Pu & Ginoux, 2017, 2018; Singh et al., 2017). Studies have shown that models can simulate the general pattern of spatial variability of dust concentration (Ginoux et al., 2001; Huneeus et al., 2011; Pu & Ginoux, 2018; Yue et al., 2009; Wu et al., 2020). However, models diverge significantly in simulating dust load and its spatial variability at different temporal scales (e.g., Pu & Ginoux, 2018; Wu et al., 2018; Yuan et al., 2019).…”

“…Recently, a few studies have analyzed climate models' performance on global dust emission. For instance, Pu and Ginoux (2018) and Wu et al (2020) examined the Coupled Model Intercomparison Project Phase 5 (CMIP5) outputs and found that while the models simulate the general spatial pattern of dust, they tend to underestimate dust emission. The frequencies of dust emission significantly vary on interannual to decadal timescales (e.g., Evan & Mukhopadhyay, 2010;Evan et al, 2016;Mahowald et al, 2010;Middleton, 2019).…”

Recent (1980 to 2015) Trends and Variability in Daily‐to‐Interannual Soluble Iron Deposition from Dust, Fire, and Anthropogenic Sources

“…Global land cover change since 1980 is minimal (Figure S2), and both dust iron and fire iron are classed as “natural” iron sources, although in reality can be modulated by human activity as well. Annual dust emissions for all versions of CAM (CAM6: 3,439–3,658 Tg a −1 ; CAM5: 3,753–5,053 Tg a −1 ; and CAM4: 1,775–2,324 Tg a −1 ) fall within the full range (735–8,186 Tg a −1 ) calculated by CMIP5 dust models (Wu et al, 2020). Satellite Era trends and variability in fire and anthropogenic iron emission and deposition are presented and discussed here for the first time.…”