Revolutions in the Middle East and Northern Africa

Political developments in North Africa and the Middle East that have begun in January 2011 are gaining strength and involve an increasing number of Arab countries. The participants of the Roundtable – experts from IMEMO, Institute of Oriental Studies (RAS), Institute of the USA and Canada (RAS) and Mrs. E. Suponina from “Moscow News” newspaper analyzed a wide range of issues associated with these events. Among them are: 1) the reasons for such a large-scale explosion, 2) the nature of the discussed developments (revolutions, riots?) and who are the subjects of the current “Arab drama”, 3) the role of Islam and political Islamism, 4) the role of external factors.

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Events in Northern Africa and Middle East: Causes and Consequences (the end)

World Economy and International Relations ◽

10.20542/0131-2227-2011-8-52-66 ◽

2011 ◽

pp. 52-66

Author(s):

I. Labinskaya

Keyword(s):

Middle East ◽

North Africa ◽

Northern Africa ◽

External Factors ◽

Protest Movements ◽

Research Institutes ◽

Internal And External Factors

A discussion of the developments in North Africa and Middle East by a group of experts from three research institutes and the newspaper “Moscow news” is continued. It has begun in the previous of the magazine. Now, an attempt is made to identify possible scenarios of further developments, as well as the roles of the various actors, including protest movements. Internal and external factors of what is happening in these regions are classified.

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China and the Revolutions in the Middle East and North Africa

Middle East Law and Governance ◽

10.1163/187633711x591549 ◽

2011 ◽

Vol 3 (1-2) ◽

pp. 192-203 ◽

Cited By ~ 2

Author(s):

Randall Peerenboom

Keyword(s):

Social Justice ◽

Middle East ◽

North Africa ◽

Authoritarian Regimes ◽

Northern Africa ◽

Mena Countries ◽

Turn On ◽

Potential Sources ◽

The Government

The 2011 revolutions in the Middle East and Northern Africa (MENA) led to considerable hope for some people that China would experience a similar political uprising, as well as considerable anxiety for the ruling regime. The government’s immediate response was to downplay the risk of a similar event occurring in China by distinguishing between China and MENA, while at the same time cracking down on activists and other potential sources of instability—including attempts to organize popular revolutionary protests in China. Although the government has so far managed to avoid a similar uprising, neither response has been entirely successful. Despite a number of significant diff erences between China and MENA countries, there are enough commonalities to justify concerns about political instability. Moreover, relying on repression alone is not a long-term solution to the justified demands of Chinese citizens for political reforms and social justice. Whether China will ultimately be able to avoid the fate of authoritarian regimes in MENA countries will turn on its ability to overcome a series of structural challenges while preventing sudden and unpredictable events, like those that gave rise to the Arab revolutions, from spinning out of control.

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A reanalysis-based study of desert dust in Northern Africa, the Middle East and Europe in a recent decade

10.7185/gold2021.7588 ◽

2021 ◽

Author(s):

Enza Di Tomaso ◽

Jerónimo Escribano ◽

Paul Ginoux ◽

Sara Basart ◽

Francesca Macchia ◽

...

Keyword(s):

Middle East ◽

Recent Decade ◽

Northern Africa ◽

Desert Dust

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A 10-year regional reanalysis of desert dust aerosol at high spatial resolution

10.5194/egusphere-egu21-11644 ◽

2021 ◽

Author(s):

Enza Di Tomaso ◽

Jerónimo Escribano ◽

Paul Ginoux ◽

Sara Basart ◽

Francesca Macchia ◽

...

Keyword(s):

Middle East ◽

Data Assimilation ◽

Spatial Resolution ◽

Weather Prediction ◽

Reanalysis Data ◽

Northern Africa ◽

Dust Aerosol ◽

Data Set ◽

Desert Dust ◽

Deep Blue

Desert dust is the most abundant aerosol by mass residing in the atmosphere. It plays a key role in the Earth&#8217;s system by influencing the radiation balance, by affecting cloud formation and cloud chemistry, and by acting as a fertilizer for the growth of phytoplankton and for soil through its deposition over the ocean and land.Due to the nature of its emission and transport, atmospheric dust concentrations are highly variable in space and time and, therefore, require a continuous monitoring by measurements. Dust observations are best exploited by being combined with model simulations for the production of analyses and reanalyses, i.e., complete and consistent four dimensional reconstructions of the atmosphere. Existing aerosol (and dust) reanalyses for the global domain have been produced by total aerosol constraint and at relatively coarse spatial resolution, while regional reanalyses exclude some of the regions containing the major sources of desert dust in Northern Africa and the Middle East.We present here a 10-year reanalysis data set of desert dust at a horizontal resolution of 0.1&#176;, and which covers the domain of Northern Africa, the Middle East and Europe. The reanalysis has been produced by assimilating in the MONARCH chemical weather prediction system (Di Tomaso et al., 2017) satellite retrievals over dust source regions with specific dust observational constraint (Ginoux et al., 2012; Pu and Ginoux, 2016).Furthermore, we describe its evaluation in terms of data assimilation diagnostics and comparison against independent observations. Statistics of analysis departures from assimilated observations prove the consistency of the data assimilation system showing that the analysis is closer to the observations than the first-guess. Temporal mean of analysis increments show that the assimilation led to an overall reduction of dust with pattern of systematic corrections that vary with the seasons, and can be linked primarily to misrepresentation of source strength.Independent evaluation of the analysis with AERONET observations indicates that the reanalysis data set is highly accurate, and provides therefore a reliable historical record of atmospheric desert dust concentrations in a recent decade.ReferencesDi Tomaso, E., Schutgens, N. A. J., Jorba, O., and P&#233;rez Garc&#237;a-Pando, C. (2017): Assimilation of MODIS Dark Target and Deep Blue observations in the dust aerosol component of NMMB-MONARCH version 1.0, Geosci. Model Dev., 10, 1107-1129.Ginoux, P., Prospero, J. M., Gill, T. E., Hsu, N. C. and Zhao, M. (2012): Global-Scale Attribution of Anthropogenic and Natural Dust Sources and Their Emission Rates Based on Modis Deep Blue Aerosol Products. Rev Geophys 50.Pu, B., and Ginoux, P. (2016). The impact of the Pacific Decadal Oscillation on springtime dust activity in Syria. Atmospheric Chemistry and Physics, 16(21), 13431-13448.Acknowledgements The authors acknowledge the DustClim project which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (435690462); PRACE (eDUST/eFRAGMENT1/eFRAGMENT2), RES (AECT-2020-3-0013/AECT-2019-3-0001/AECT-2020-1-0007) for awarding access to MareNostrum at BSC and for technical support.

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Towards high-towards high-resolution dust reanalysis for Northern Africa, the Middle East and Europe

10.5194/egusphere-egu2020-17599 ◽

2020 ◽

Author(s):

Enza Di Tomaso ◽

Sara Basart ◽

Jeronimo Escribano ◽

Paul Ginoux ◽

Oriol Jorba ◽

...

Keyword(s):

Kalman Filter ◽

Middle East ◽

Data Assimilation ◽

Dust Storms ◽

Northern Africa ◽

Combine Model ◽

Climate Services ◽

Deep Blue ◽

Satellite Retrievals ◽

The Impact

DustClim (Dust Storms Assessment for the development of user-oriented Climate Services in Northern Africa, Middle East and Europe) is a project of the European Research Area For Climate Services (ERA4CS). DustClim is aiming to provide reliable information on sand and dust storms for developing dust-related services for selected socio-economic sectors: air quality, aviation and solar energy.This contribution will describe the work done within the DustClim project towards the production of a dust reanalysis over the domain of Northern Africa, the Middle East and Europe at an unprecedented high spatial resolution (at 10km x 10km) using the state-of-art Multiscale Online Nonhydrostatic Atmosphere Chemistry model (MONARCH) and its data assimilation capability (Di Tomaso et al., 2017). An ensemble-based Kalman filter (namely the local ensemble transform Kalman filter &#8211; LETKF) has been utilized to optimally combine model simulations and satellite retrievals.Dust ensemble forecasts are used to estimate flow-dependent forecast uncertainty, which is used by the data assimilation scheme to optimally combine model prior information with satellite retrievals. Satellite observations from MODIS Deep Blue with specific observational constraint for dust (Ginoux et al., 2012; Pu and Ginoux, 2016; Sayer et al., 2014) are considered for assimilation over land surfaces, including source regions. MONARCH ensemble has been generated by applying multi-parameters, multi-physics, multi-meteorological initial and boundary conditions perturbations. Sensitive parameters of the assimilation configuration like the balance between observational and background uncertainty, or the spatial location of errors have been carefully calibrated.The dust reanalysis for the period 2011-2016 is being compared against independent dust-filtered observations from AERONET (AErosol RObotic NETwork) show the benefit of the assimilation of dust-related MODIS Deep Blue products over areas not easily covered by other observational datasets. Particularly relevant is the improvement of the model skills over the Sahara.References: Di Tomaso, E., Schutgens, N. A. J., Jorba, O., and P&#233;rez Garc&#237;a-Pando, C. (2017): Assimilation of MODIS Dark Target and Deep Blue observations in the dust aerosol component of NMMB-MONARCH version 1.0, Geosci. Model Dev., 10, 1107-1129, doi:10.5194/gmd-10-1107-2017. Ginoux, P., Prospero, J. M., Gill, T. E., Hsu, N. C. and Zhao, M. Global-Scale Attribution of Anthropogenic and Natural Dust Sources and Their Emission Rates Based on Modis Deep Blue Aerosol Products. Rev Geophys 50, doi:10.1029/2012rg000388 (2012). Pu, B., and Ginoux, P. (2016). The impact of the Pacific Decadal Oscillation on springtime dust activity in Syria. Atmospheric Chemistry and Physics, 16(21), 13431-13448. Sayer, A. M., Munchak, L. A., Hsu, N. C., Levy, R. C., Bettenhausen, C., and Jeong, M.-J.: MODIS Collection 6 aerosol products: Comparison between Aqua&#8217;s e-Deep Blue, Dark Target, and &#8220;merged&#8221; data sets, and usage recommendations, J. Geophys. Res.-Atmos., 119, 13965&#8211;13989, doi:10.1002/2014JD022453, 2014.Acknowledgement DustClim project is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462). We acknowledge PRACE for awarding access to HPC resources through the eDUST and eFRAGMENT1 projects.&#160;

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Evaluation of NMMB-MONARCH dust reanalysis within the DustClim ERA4CS project

10.5194/egusphere-egu2020-21863 ◽

2020 ◽

Author(s):

Michail Mytilinaios ◽

Lucia Mona ◽

Francesca Barnaba ◽

Sergio Ciamprone ◽

Serena Trippetta ◽

...

Keyword(s):

Middle East ◽

Size Distribution ◽

Optical Depth ◽

Extinction Coefficient ◽

Dust Storms ◽

Northern Africa ◽

Dust Deposition ◽

Dust Extinction ◽

Dust Size Distribution

An advanced dust reanalysis with high spatial (at 10km x 10km) and temporal resolution is produced in the framework of DustClim project (Dust Storms Assessment for the development of user-oriented Climate Services in Northern Africa, Middle East and Europe) [1], aiming to provide reliable information on dust storms current conditions and predictions, focusing on the dust impacts on various socio-economic sectors.This regional reanalysis is based on the assimilation of dust-related satellite observations from MODIS instrument [2], in the Multiscale Online Nonhydrostatic Atmosphere Chemistry model (NMMB-MONARCH) [3], over the region of Northern Africa, Middle East and Europe. The reanalysis is now available for a seven-year period (2011-2016) providing the following dust products: Columnar and surface concentration, distributed in 8 dust particle size bins, with effective radius ranging from 0,15&#956;m to 7,1&#956;m, dust load, dry and wet dust deposition, dust optical depth (DOD) and coarse dust optical depth (radius>1&#956;m) at 550nm and profiles of dust extinction coefficient at 550nm.A thorough evaluation of the reanalysis is in progress to assess the quality and uncertainty of the dust simulations, using dust-filtered products, retrieved from different measurement techniques, both from in-situ and remote sensing observations. The datasets considered for the DustClim reanalysis evaluation, provide observations of variables that are included in the model simulations. The DOD is provided by AERONET network [4] and by IASI [5], POLDER [6], MISR [7] and MODIS space-borne sensors; Dust extinction profiles are provided by ACTRIS/EARLINET network [8] and CALIPSO/LIVAS dataset [9]; Dust PM10 surface concentrations derived from INDAAF/SDT [10] network and estimated from PM10 measurements [11] performed within EEA/EIONET [12] network; Dust deposition measurements collected by the INDAAF/SDT and the CARAGA/DEMO [13] networks; Dust size distribution from in situ observations (ground-based and airborne); And column-averaged dust size distribution at selected stations from the AERONET network.In this work, we present the results of the model evaluation for the year 2012. The first evaluation results will focus on dust extinction coefficient profiles from EARLINET and LIVAS, on DOD using AERONET, MISR and MODIS datasets, and on dust PM10 concentration from INDAAF/SDT network. Moreover, a DOD climatology covering the whole reanalysis period (2011-2016) will be compared with the results obtained from AERONET network.&#160;References[1] https://sds-was.aemet.es/projects-research/dustclim[2] https://modis.gsfc.nasa.gov/[3] Di Tomaso et al., Geosci. Model Dev., 10, 1107-1129, doi:10.5194/gmd-10-1107-2017., 2017.[4] https://aeronet.gsfc.nasa.gov/[5] Cuesta et al., J. Geophys. Res., 120, 7099-7127, 2015.[6] http://www.icare.univ-lille1.fr/parasol/overview/[7] https://misr.jpl.nasa.gov/[8] https://www.earlinet.org/[9] Marinou et al., Atmos. Chem. Phys., 17, 5893&#8211;5919, https://doi.org/10.5194/acp-17-5893-2017, 2017.[10] https://indaaf.obs-mip.fr/[11] Barnaba et al., Atmospheric environment, 161, 288-305, 2017.[12] https://www.eionet.europa.eu/[13] Laurent et al., Atmos. Meas. Tech., 8, 2801&#8211;2811, 2015.&#160;&#160;AcknowledgementDustClim project is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462).

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