scholarly journals Evaluation of natural aerosols in CRESCENDO Earth system models (ESMs): mineral dust

2021 ◽  
Vol 21 (13) ◽  
pp. 10295-10335
Author(s):  
Ramiro Checa-Garcia ◽  
Yves Balkanski ◽  
Samuel Albani ◽  
Tommi Bergman ◽  
Ken Carslaw ◽  
...  

Abstract. This paper presents an analysis of the mineral dust aerosol modelled by five Earth system models (ESMs) within the project entitled Coordinated Research in Earth Systems and Climate: Experiments, kNowledge, Dissemination and Outreach (CRESCENDO). We quantify the global dust cycle described by each model in terms of global emissions, together with dry and wet deposition, reporting large differences in the ratio of dry over wet deposition across the models not directly correlated with the range of particle sizes emitted. The multi-model mean dust emissions with five ESMs is 2836 Tg yr−1 but with a large uncertainty due mainly to the difference in the maximum dust particle size emitted. The multi-model mean of the subset of four ESMs without particle diameters larger than 10 µ m is 1664 (σ=651) Tg yr−1. Total dust emissions in the simulations with identical nudged winds from reanalysis give us better consistency between models; i.e. the multi-model mean global emissions with three ESMs are 1613 (σ=278) Tg yr−1, but 1834 (σ=666) Tg yr−1 without nudged winds and the same models. Significant discrepancies in the globally averaged dust mass extinction efficiency explain why even models with relatively similar global dust load budgets can display strong differences in dust optical depth. The comparison against observations has been done in terms of dust optical depths based on MODIS (Moderate Resolution Imaging Spectroradiometer) satellite products, showing global consistency in terms of preferential dust sources and transport across the Atlantic. The global localisation of source regions is consistent with MODIS, but we found regional and seasonal differences between models and observations when we quantified the cross-correlation of time series over dust-emitting regions. To faithfully compare local emissions between models we introduce a re-gridded normalisation method that can also be compared with satellite products derived from dust event frequencies. Dust total deposition is compared with an instrumental network to assess global and regional differences. We find that models agree with observations within a factor of 10 for data stations distant from dust sources, but the approximations of dust particle size distribution at emission contributed to a misrepresentation of the actual range of deposition values when instruments are close to dust-emitting regions. The observed dust surface concentrations also are reproduced to within a factor of 10. The comparison of total aerosol optical depth with AERONET (AErosol RObotic NETwork) stations where dust is dominant shows large differences between models, although with an increase in the inter-model consistency when the simulations are conducted with nudged winds. The increase in the model ensemble consistency also means better agreement with observations, which we have ascertained for dust total deposition, surface concentrations and optical depths (against both AERONET and MODIS retrievals). We introduce a method to ascertain the contributions per mode consistent with the multi-modal direct radiative effects, which we apply to study the direct radiative effects of a multi-modal representation of the dust particle size distribution that includes the largest particles.

2020 ◽  
Author(s):  
Ramiro Checa-Garcia ◽  
Yves Balkanski ◽  
Samuel Albani ◽  
Tommi Bergman ◽  
Ken Carslaw ◽  
...  

Abstract. This paper presents an analysis of the mineral dust aerosol modelled by five Earth System Models (ESM) within the Coordinated Research in Earth Systems and Climate: Experiments, kNowledge, Dissemination and Outreach (CRESCENDO) project. We quantify the global dust cycle described by each model in terms of global emissions together with dry and wet depositions, reporting large differences in ratio of dry over wet deposition across the models not directly correlated with the range of particle sizes emitted. The multi-model mean dust emissions was 2954 Tg yr−1 but with a large uncertainty due mainly to the difference in maximum dust particle size emitted. For the subset of ESMs without particles larger than 10 μm we obtained 1664 (σ = 650) Tg yr−1. Total dust emissions with identical nudged winds from reanalysis give us better consistency between models with 1530 (σ = 282) Tg yr−1. Significant discrepancies in the globally averaged dust mass extinction efficiency explain why even models with relatively similar dust load global budgets can display strong differences in dust optical depths. The comparison against observations has been done in terms of dust optical depths based on MODIS satellite products, showing a global consistency in terms of preferential dust sources and transport across the Atlantic. However, we found regional and seasonal differences between models and observations when we quantified the cross-correlation of time-series over dust emitting regions. To faithfully compare local emissions between models we introduce a re-gridded normalization method, that also can be compared with satellite products derived from dust events frequencies. Dust total depositions are compared with instrumental network to assess global and regional differences. We found that models agree with observations distant from dust sources within a factor 10, but the approximations of dust particle size distribution at emission contributed to a misrepresentation of the actual range of deposition values when instruments are close to dust emitting regions. The observational dust surface concentrations also are reproduced within a factor 10. The comparison of total aerosol optical depths with AERONETv3 stations where dust is dominant shows large differences between models, however with an increase of the inter-model consistency when the simulations are conducted with nudged-winds. The increase of the model ensemble consistency also means a better agreement with observations, which we have ascertained for dust total deposition, surface concentrations and optical depths (against both AERONETv3 and MODIS-DOD retrievals). We estimated the direct radiative effects of a multi-modal representation of the dust particle size distribution that includes the largest particles measured at FENNEC experiment. We introduced a method to ascertain the contributions per mode consistent with the multimodal direct radiative effects.


Ocean Science ◽  
2016 ◽  
Vol 12 (2) ◽  
pp. 561-575 ◽  
Author(s):  
Tihomir S. Kostadinov ◽  
Svetlana Milutinović ◽  
Irina Marinov ◽  
Anna Cabré

Abstract. Owing to their important roles in biogeochemical cycles, phytoplankton functional types (PFTs) have been the aim of an increasing number of ocean color algorithms. Yet, none of the existing methods are based on phytoplankton carbon (C) biomass, which is a fundamental biogeochemical and ecological variable and the “unit of accounting” in Earth system models. We present a novel bio-optical algorithm to retrieve size-partitioned phytoplankton carbon from ocean color satellite data. The algorithm is based on existing methods to estimate particle volume from a power-law particle size distribution (PSD). Volume is converted to carbon concentrations using a compilation of allometric relationships. We quantify absolute and fractional biomass in three PFTs based on size – picophytoplankton (0.5–2 µm in diameter), nanophytoplankton (2–20 µm) and microphytoplankton (20–50 µm). The mean spatial distributions of total phytoplankton C biomass and individual PFTs, derived from global SeaWiFS monthly ocean color data, are consistent with current understanding of oceanic ecosystems, i.e., oligotrophic regions are characterized by low biomass and dominance of picoplankton, whereas eutrophic regions have high biomass to which nanoplankton and microplankton contribute relatively larger fractions. Global climatological, spatially integrated phytoplankton carbon biomass standing stock estimates using our PSD-based approach yield  ∼  0.25 Gt of C, consistent with analogous estimates from two other ocean color algorithms and several state-of-the-art Earth system models. Satisfactory in situ closure observed between PSD and POC measurements lends support to the theoretical basis of the PSD-based algorithm. Uncertainty budget analyses indicate that absolute carbon concentration uncertainties are driven by the PSD parameter No which determines particle number concentration to first order, while uncertainties in PFTs' fractional contributions to total C biomass are mostly due to the allometric coefficients. The C algorithm presented here, which is not empirically constrained a priori, partitions biomass in size classes and introduces improvement over the assumptions of the other approaches. However, the range of phytoplankton C biomass spatial variability globally is larger than estimated by any other models considered here, which suggests an empirical correction to the No parameter is needed, based on PSD validation statistics. These corrected absolute carbon biomass concentrations validate well against in situ POC observations.


2015 ◽  
Vol 12 (3) ◽  
pp. 573-644 ◽  
Author(s):  
T. S. Kostadinov ◽  
S. Milutinović ◽  
I. Marinov ◽  
A. Cabré

Abstract. Owing to their important roles in biogeochemical cycles, phytoplankton functional types (PFTs) have been the aim of an increasing number of ocean color algorithms. Yet, none of the existing methods are based on phytoplankton carbon (C) biomass, which is a fundamental biogeochemical and ecological variable and the "unit of accounting" in Earth System models. We present a novel bio-optical algorithm to retrieve size-partitioned phytoplankton carbon from ocean color satellite data. The algorithm is based on existing algorithms to estimate particle volume from a power-law particle size distribution (PSD). Volume is converted to carbon concentrations using a compilation of allometric relationships. We quantify absolute and fractional biomass in three PFTs based on size – picophytoplankton (0.5–2 μm in diameter), nanophytoplankton (2–20 μm) and microphytoplankton (20–50 μm). The mean spatial distributions of total phytoplankton C biomass and individual PFTs, derived from global SeaWiFS monthly ocean color data, are consistent with current understanding of oceanic ecosystems, i.e. oligotrophic regions are characterized by low biomass and dominance of picoplankton, whereas eutrophic regions have large biomass to which nanoplankton and microplankton contribute relatively larger fractions. Global spatially integrated phytoplankton carbon biomass standing stock estimates using our PSD-based approach yield on average ~0.2–0.3 Gt of C, consistent with analogous estimates from two other ocean color algorithms, and several state-of-the-art Earth System models. However, the range of phytoplankton C biomass spatial variability globally is larger than estimated by any other models considered here, because the PSD-based algorithm is not a priori empirically constrained and introduces improvement over the assumptions of the other approaches. Satisfactory in situ closure observed between PSD and POC measurements lends support to the theoretical basis of the PSD-based algorithm. Uncertainty budget analyses indicate that absolute carbon concentration uncertainties are driven by the PSD parameter No which determines particle number concentration to first order, while uncertainties in PFTs' fractional contributions to total C biomass are mostly due to the allometric coefficients.


2019 ◽  
Vol 138 ◽  
pp. 01027
Author(s):  
Nadezhda Menzelintseva ◽  
Natalia Karapuzova ◽  
Awadh M. Redhwan ◽  
Ekaterina Fomina

The particle size distribution of dust in the air of the work area has been determined for some cement plant shops. An experimental study has been conducted to explore the effects of microclimate parameters on the dust particle size distribution on the shop floor in the cement milling shop and cement packing shop, and regression equations have been obtained. A mathematical model has been developed to forecast the dust particle size distribution in the air of work areas of cement plants.


Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 819
Author(s):  
Patrick N. Gatlin ◽  
Merhala Thurai ◽  
Christopher Williams ◽  
Elisa Adirosi

Precipitation plays a vital role within the Earth system [...]


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