Assimilation of MODIS Dark Target and Deep Blue observations in the dust aerosol component of NMMB-MONARCH version 1.0

Tomaso, Enza Di; Schutgens, Nick; Jorba, Oriol; García‐Pando, Carlos Pérez

doi:10.5194/gmd-10-1107-2017

Cited by 68 publications

(86 citation statements)

References 79 publications

(77 reference statements)

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“…The version (v1.0) of the NMMB-MONARCH model used here contributes to different model inter-comparisons like the International Cooperative for Aerosol Prediction (ICAP) initiative and the Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS), a project developed under the umbrella of the World Meteorological Organization (WMO) with a focus on improving the capabilities of sand and dust storm forecasts. For brevity reasons, only the main characteristics of the model are discussed here since a thorough description is provided in Pérez et al (2011, and references therein) as well as in recent publications presenting its developments and applications in gas-phase chemistry (Badia et al, 2017), volcanic ash dispersion (Marti et al, 2017) and data assimilation (Di Tomaso et al, 2017) studies. The spectral variation of the GOCART dust optical properties, utilized as inputs to the radiation transfer scheme, is presented in Sect.…”

Section: Model Descriptionmentioning

confidence: 99%

Direct radiative effects during intense Mediterranean desert dust outbreaks

et al. 2018

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Abstract. The direct radiative effect (DRE) during 20 intense and widespread dust outbreaks, which affected the broader Mediterranean basin over the period March 2000-February 2013, has been calculated with the NMMB-MONARCH model at regional (Sahara and European continent) and shortterm temporal (84 h) scales. According to model simulations, the maximum dust aerosol optical depths (AODs) range from ∼ 2.5 to ∼ 5.5 among the identified cases. At midday, dust outbreaks locally induce a NET (shortwave plus longwave) strong atmospheric warming (DRE ATM values up to 285 W m −2 ; Niger-Chad; dust AODs up to ∼ 5.5) and a strong surface cooling (DRE NETSURF values down to −337 W m −2 ), whereas they strongly reduce the downward radiation at the ground level (DRE SURF values down to −589 W m −2 over the Eastern Mediterranean, for extremely high dust AODs, 4.5-5). During night-time, reverse effects of smaller magnitude are found. At the top of the atmosphere (TOA), positive (planetary warming) DREs up to 85 W m −2 are found over highly reflective surfaces (Niger-Chad; dust AODs up to ∼ 5.5) while negative (planetary cooling) DREs down to −184 W m −2 (Eastern Mediterranean; dust AODs 4.5-5) are computed over dark surfaces at noon. Dust outbreaks significantly affect the mean regional radiation budget, with NET DREs ranging from −8.5 to 0.5 W m −2 , from −31.6 to 2.1 W m −2 , from −22.2 to 2.2 W m −2 and from −1.7 to 20.4 W m −2 for TOA, SURF, NETSURF and ATM, respectively. Although the shortwave DREs are larger than the longwave ones, the latter are comparable or even larger at TOA, particularly over the Sahara at midday. As a response to the strong surface day-time cooling, dust outbreaks cause a reduction in the regional sensible and latent heat fluxes by up to 45 and 4 W m −2 , respectively, averaged over land areas of the simulation domain. Dust outbreaks reduce the temperature at 2 m by up to 4 K during day-time, whereas a reverse tendency of similar magnitude is found during nighttime. Depending on the vertical distribution of dust loads and time, mineral particles heat (cool) the atmosphere by up to 0.9 K (0.8 K) during day-time (night-time) within atmospheric dust layers. Beneath and above the dust clouds, mineral particles cool (warm) the atmosphere by up to 1.3 K (1.2 K) at noon (night-time). On a regional mean basis, negative feedbacks on the total emitted dust (reduced by 19.5 %) and dust AOD (reduced by 6.9 %) are found when dust interacts with the radiation. Through the consideration of dust radiative effects in numerical simulations, the model positive and negative biases for the downward surface SW or LW radiation, respectively, with respect to Baseline Surface Radiation Network (BSRN) measurements, are reduced. In addition, they also reduce the model near-surface (at 2 m) nocturnal cold biases by up to 0.5 K (regional averages), as well as the model warm biases at 950 and 700 hPa, where the dust concentration is maximized, by up to 0.4 K. However, improvements are relatively small and do not happen in all ...

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Section: Model Descriptionmentioning

confidence: 99%

Direct radiative effects during intense Mediterranean desert dust outbreaks

et al. 2018

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“…The NMMB/BSC-Dust model (NMMB: Nonhydrostatic Multiscale Model on the B Grid; BSC: Barcelona Supercomputing Center) is the mineral dust module of the NMMB-MONARCH (MONARCH: Multiscale Online Nonhydrostatic AtmospheRe CHemistry) Haustein et al, 2012;Spada et al, 2013;Badia and Jorba, 2014;Di Tomaso et al, 2017) designed and developed at BSC in collaboration with NOAA NCEP (NOAA: US National Oceanic and Atmospheric Administration; NCEP: National Centers for Environmental Prediction) and the NASA Goddard Institute for Space Studies. The NMMB-MONARCH model considers all relevant atmospheric aerosol types such as dust, sea salt, sulfates, organic, and black carbon, as well as aerosolformation-relevant gases.…”

Section: Nmmb/bsc-dustmentioning

confidence: 99%

Profiling of Saharan dust from the Caribbean to western Africa – Part 2: Shipborne lidar measurements versus forecasts

et al. 2017

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Abstract. A unique 4-week ship cruise from Guadeloupe to Cabo Verde in April-May 2013 (see part 1, Rittmeister et al., 2017) is used for an in-depth comparison of dust profiles observed with a polarization/Raman lidar aboard the German research vessel Meteor over the remote tropical Atlantic and respective dust forecasts of a regional (SKIRON) and two global atmospheric (dust) transport models (NMMB/BSCDust, MACC/CAMS). New options of model-observation comparisons are presented. We analyze how well the modeled fine dust (submicrometer particles) and coarse dust contributions to light extinction and mass concentration match respective lidar observations, and to what extent models, adjusted to aerosol optical thickness observations, are able to reproduce the observed layering and mixing of dust and nondust (mostly marine) aerosol components over the remote tropical Atlantic. Based on the coherent set of dust profiles at well-defined distances from Africa (without any disturbance by anthropogenic aerosol sources over the ocean), we investigate how accurately the models handle dust removal at distances of 1500 km to more than 5000 km west of the Saharan dust source regions. It was found that (a) dust predictions are of acceptable quality for the first several days after dust emission up to 2000 km west of the African continent, (b) the removal of dust from the atmosphere is too strong for large transport paths in the global models, and (c) the simulated fine-to-coarse dust ratio (in terms of mass concentration and light extinction) is too high in the models compared to the observations. This deviation occurs initially close to the dust sources and then increases with distance from Africa and thus points to an overestimation of fine dust emission in the models.

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“…A detailed description of the individual models is beyond the scope of this paper. For a review of the current systems that provide aerosol forecasts, some with focus on dust, see for example Benedetti et al (2014) and Sessions et al (2015).Ensemble systems are presented in Rubin et al (2016) andDi Tomaso et al (2017). An overview of regional 240 aerosol forecasting systems can be found in Menut and Bessagnet (2010); Kukkonen et al (2011);Zhang et al (2012a, b); Baklanov et al (2014).…”

Section: Aerosol Prediction Modelsmentioning

confidence: 99%

Status and future of Numerical Atmospheric Aerosol Prediction with a focus on data requirements

Benedetti¹,

Reid²,

Baklanov³

et al. 2018

Preprint

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Abstract. Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centres due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation and military authorities, solar energy plant managers, providers of climate services, and health professionals. The prediction of aerosol particle properties in Numerical Weather Prediction (NWP) models faces a number of challenges owing to 5 the complexity of atmospheric aerosol processes and their sensitivity to the underlying meteorological conditions. Errors in aerosol prediction concern all processes involved in the aerosol life cycle.These include errors on the source terms (for both anthropogenic and natural emissions), errors directly dependent on the meteorology (e.g., mixing, transport, scavenging by precipitation), as well as errors related to aerosol chemistry (e.g., nucleation, gas-aerosol partitioning, chemical transfor-10 mation and growth, hygroscopicity). The main goal of current research on aerosol forecast consists in prioritizing these errors and trying to reduce the most important ones through model development and data assimilation. Aerosol particle observations from satellite and ground-based platforms have been crucial to guide model development of the recent years, and have been made more readily available for model evaluation and assimilation. However, for the sustainability of the aerosol parti-15 cle prediction activities around the globe, it is crucial that quality aerosol observations continue to be made available from different platforms (space, near-surface, and aircraft) and freely shared. This white paper reviews current requirements for aerosol observations in the context of the operational activities carried out at various global and regional centres. Some of the requirements are equally applicable to aerosol-climate research. However, the focus here is on the global operational prediction 20 of aerosol properties such as mass concentrations and optical parameters. Most operational models are based on bulk schemes that do not predict the size distribution of the aerosol particles. Others are based on a mix of "bin" and bulk schemes with limited capability to simulate the size information.However the next generation of aerosol operational models will have the capability to predict both mass and number density which will provide a more complete description of the aerosols properties. 25A brief overview of the state-of-the-art is provided with an introduction on the importance of aerosol prediction activities. The criteria on which the requirements for aerosol observations are based are also outlined. Assimilation and evaluation aspects are discussed from the perspective of the user requirements.

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Assimilation of MODIS Dark Target and Deep Blue observations in the dust aerosol component of NMMB-MONARCH version 1.0

Cited by 68 publications

References 79 publications

Direct radiative effects during intense Mediterranean desert dust outbreaks

Direct radiative effects during intense Mediterranean desert dust outbreaks

Profiling of Saharan dust from the Caribbean to western Africa – Part 2: Shipborne lidar measurements versus forecasts

Status and future of Numerical Atmospheric Aerosol Prediction with a focus on data requirements

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