Improved dust representation in the Community Atmosphere Model

Albani, Samuel; Mahowald, N. M.; Perry, A. T.; Scanza, Rachel A.; Zender, Charles S.; Heavens, N. G.; Maggi, Valter; Kok, Jasper F.; Otto‐Bliesner, Bette L.

doi:10.1002/2013ms000279

Cited by 295 publications

(533 citation statements)

References 130 publications

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“…This correction factor has not been active in MESSy versions up to 2.52, and the higher AOD over the Middle East obtained without the factor generally resembles the satellite observations more closely; its impact when evaluated using soil moisture values from the current EMAC bucket model is rather small (see in the Supplement). Therefore, it remains inactive for the present study, consistent with previous studies (Abdelkader et al, 2015Metzger et al, 2016;Albani et al, 2014). Nevertheless, the monthly vegetation data described above account for secondary effects of soil moisture variations via the vegetation factor.…”

Section: Soil Moisture Termsupporting

confidence: 84%

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Revised mineral dust emissions in the atmospheric chemistry–climate model EMAC (MESSy 2.52 DU_Astitha1 KKDU2017 patch)

et al. 2018

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Abstract. To improve the aeolian dust budget calculations with the global ECHAM/MESSy atmospheric chemistryclimate model (EMAC), which combines the Modular Earth Submodel System (MESSy) with the ECMWF/Hamburg (ECHAM) climate model developed at the Max Planck Institute for Meteorology in Hamburg based on a weather prediction model of the European Centre for Medium-Range Weather Forecasts (ECMWF), we have implemented new input data and updates of the emission scheme.The data set comprises land cover classification, vegetation, clay fraction and topography. It is based on up-todate observations, which are crucial to account for the rapid changes of deserts and semi-arid regions in recent decades. The new Moderate Resolution Imaging Spectroradiometer (MODIS)-based land cover and vegetation data are time dependent, and the effect of long-term trends and variability of the relevant parameters is therefore considered by the emission scheme. All input data have a spatial resolution of at least 0.1 • compared to 1 • in the previous version, equipping the model for high-resolution simulations.We validate the updates by comparing the aerosol optical depth (AOD) at 550 nm wavelength from a 1-year simulation at T106 (about 1.1 • ) resolution with Aerosol Robotic Network (AERONET) and MODIS observations, the 10 µm dust AOD (DAOD) with Infrared Atmospheric Sounding Interferometer (IASI) retrievals, and dust concentration and deposition results with observations from the Aerosol Comparisons between Observations and Models (AeroCom) dust benchmark data set. The update significantly improves agreement with the observations and is therefore recommended to be used in future simulations.

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Section: Soil Moisture Termsupporting

confidence: 84%

“…Its basic principles are shared with emission schemes used in many other models (e.g. Zender et al, 2003;Jones et al, 2012;Albani et al, 2014;Huneeus et al, 2011), but alternative approaches exist (e.g. Shao, 2001;Kok et al, 2014).…”

Section: K Klingmüller Et Al: Revised Mineral Dust Emissions In Emacmentioning

confidence: 99%

Revised mineral dust emissions in the atmospheric chemistry–climate model EMAC (MESSy 2.52 DU_Astitha1 KKDU2017 patch)

et al. 2018

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“…We attribute about 20 % of global dust emissions to historical LULCC (Table 1). Once these relationships between land use and dust are developed in the current climate, the natural dust source, along with changes in vegetation and climate are allowed to interact with the prognostic dust scheme to predict changes in dust concentrations (Mahowald et al, 2006;Albani et al, 2014). The extreme expansion of crop and pasture area in the TEC leads to more than a tripling of global dust emissions, from natural and human-impacted sources, by the year 2100 using this methodology (Table 1).…”

Section: Dust Emissionsmentioning

confidence: 99%

Potential climate forcing of land use and land cover change

2014

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Abstract. Pressure on land resources is expected to increase as global population continues to climb and the world becomes more affluent, swelling the demand for food. Changing climate may exert additional pressures on natural lands as present-day productive regions may shift, or soil quality may degrade, and the recent rise in demand for biofuels increases competition with edible crops for arable land. Given these projected trends there is a need to understand the global climate impacts of land use and land cover change (LULCC). Here we quantify the climate impacts of global LULCC in terms of modifications to the balance between incoming and outgoing radiation at the top of the atmosphere (radiative forcing, RF) that are caused by changes in long-lived and short-lived greenhouse gas concentrations, aerosol effects, and land surface albedo. We attribute historical changes in terrestrial carbon storage, global fire emissions, secondary organic aerosol emissions, and surface albedo to LULCC using simulations with the Community Land Model version 3.5. These LULCC emissions are combined with estimates of agricultural emissions of important trace gases and mineral dust in two sets of Community Atmosphere Model simulations to calculate the RF of changes in atmospheric chemistry and aerosol concentrations attributed to LULCC. With all forcing agents considered together, we show that 40 % (±16 %) of the present-day anthropogenic RF can be attributed to LULCC. Changes in the emission of non-CO 2 greenhouse gases and aerosols from LULCC enhance the total LULCC RF by a factor of 2 to 3 with respect to the LULCC RF from CO 2 alone. This enhancement factor also applies to projected LULCC RF, which we compute for four future scenarios associated with the Representative Concentration Pathways. We attribute total RFs between 0.9 and 1.9 W m −2 to LULCC for the year 2100 (relative to a preindustrial state). To place an upper bound on the potential of LULCC to alter the global radiation budget, we include a fifth scenario in which all arable land is cultivated by 2100. This theoretical extreme case leads to a LULCC RF of 3.9 W m −2 (±0.9 W m −2 ), suggesting that not only energy policy but also land policy is necessary to minimize future increases in RF and associated climate changes.

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“…Three overlapping modal modes are used to represent aerosol size distribution in MADE-SORGAM: Aitken (0.01-0.1 µm), accumulation (0.1-1.0 µm), and coarse modes (1.0-10.0 µm), assuming a log-normal distribution within each mode (Liu et al, 2012;Albani et al, 2014;Mahowald et al, 2014). Sea salt, soilderived dust, and anthropogenic emissions are treated in the accumulation and coarse modes, and other aerosol species are treated in the Aitken and accumulation modes.…”

Section: Introductionmentioning

confidence: 99%

Consistent response of Indian summer monsoon to Middle East dust in observations and simulations

Jin

Wei

et al. 2015

Atmos. Chem. Phys.

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Abstract. The response of the Indian summer monsoon (ISM) circulation and precipitation to Middle East dust aerosols on sub-seasonal timescales is studied using observations and the Weather Research and Forecasting model coupled with online chemistry (WRF-Chem). Satellite data show that the ISM rainfall in coastal southwest India, central and northern India, and Pakistan is closely associated with the Middle East dust aerosols. The physical mechanism behind this dust-ISM rainfall connection is examined through ensemble simulations with and without dust emissions. Each ensemble includes 16 members with various physical and chemical schemes to consider the model uncertainties in parameterizing short-wave radiation, the planetary boundary layer, and aerosol chemical mixing rules. Experiments show that dust aerosols increase rainfall by about 0.44 mm day −1 (∼ 10 % of the climatology) in coastal southwest India, central and northern India, and north Pakistan, a pattern consistent with the observed relationship. The ensemble mean rainfall response over India shows a much stronger spatial correlation with the observed rainfall response than any other ensemble members. The largest modeling uncertainties are from the boundary layer schemes, followed by short-wave radiation schemes. In WRF-Chem, the dust aerosol optical depth (AOD) over the Middle East shows the strongest correlation with the ISM rainfall response when dust AOD leads rainfall response by about 11 days. Further analyses show that increased ISM rainfall is related to enhanced southwesterly monsoon flow and moisture transport from the Arabian Sea to the Indian subcontinent, which are associated with the development of an anomalous low-pressure system over the Arabian Sea, the southern Arabian Peninsula, and the Iranian Plateau due to dust-induced heating in the troposphere. The dust-induced heating in the mid-upper troposphere is mainly located in the Iranian Plateau rather than the Tibetan Plateau. This study demonstrates a thermodynamic mechanism that links remote desert dust emissions in the Middle East to ISM circulation and precipitation variability on subseasonal timescales, which may have implications for ISM rainfall forecasts.

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Improved dust representation in the Community Atmosphere Model

Cited by 295 publications

References 130 publications

Revised mineral dust emissions in the atmospheric chemistry–climate model EMAC (MESSy 2.52 DU_Astitha1 KKDU2017 patch)

Revised mineral dust emissions in the atmospheric chemistry–climate model EMAC (MESSy 2.52 DU_Astitha1 KKDU2017 patch)

Potential climate forcing of land use and land cover change

Consistent response of Indian summer monsoon to Middle East dust in observations and simulations

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