scholarly journals Monthly and Seasonal Variation of the Tropopause Pressure on the Middle East

2019 ◽  
Vol 28 (2) ◽  
pp. 13-25
Author(s):  
Abdulhaleem Hussin Labban Abdulhaleem Hussin Labban
Keyword(s):  
Seasonal Variation ◽  
Middle East ◽  
Pressure Distribution ◽  
Short Wave ◽  
Reanalysis Data ◽  
Summer Season ◽  
Zonal Distribution ◽  
Data Set ◽  
Study Region ◽  
Autumn Season

tropopause is the natural boundary between two different atmospheric layers, that is, stratosphere and troposphere. However, both of these layers (stratosphere and troposphere) differs significantly in terms of various dynamical and chemical parameters (for example, temperature, pressure, water vapors, etc.). It is therefore necessary to study the tropopause in order to better understand the static and dynamic conditions of aforementioned atmospheric parameters. This study therefore highlights the monthly and seasonal variation of tropopause pressure over the Middle East region. For this, reanalysis data set of tropopause pressure over Middle-East through the period from 1948 to 2006 are acquired from National Centers for Environmental Prediction (NCEP). Average of monthly and seasonal tropopause pressure distribution over the study region are estimated and discussed. The results of the study show that the summer seasons and the first month of autumn season have similar tropopause pressure distribution over the study region. The results of the study also show that the distribution of tropopause pressure for summer season started as a short wave at the end of spring season. In addition, northern part of the study region has zonal distribution of tropopause pressure with the exception of summer season as well as for the first month of autumn season.

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

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

<p>Desert dust is the most abundant aerosol by mass residing in the atmosphere. It plays a key role in the Earth’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.</p><p>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.</p><p>We present here a 10-year reanalysis data set of desert dust at a horizontal resolution of 0.1°, 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).</p><p>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.</p><p>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.</p><p><strong>References</strong></p><p>Di Tomaso, E., Schutgens, N. A. J., Jorba, O., and Pérez García-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.</p><p>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.</p><p>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.</p><p><strong>Acknowledgements </strong></p><p>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.</p>

scholarly journals Zonal-mean data set of global atmospheric reanalyses on pressure levels

2018 ◽  
Author(s):  
Patrick Martineau ◽  
Jonathon S. Wright ◽  
Nuanliang Zhu ◽  
Masatomo Fujiwara
Keyword(s):  
Three Dimensional ◽  
Short Wave ◽  
Reanalysis Data ◽  
Environmental Data ◽  
Data Sets ◽  
Heating Rates ◽  
Data Set ◽  
Intercomparison Project ◽  
Complete Set ◽  
Transformed Eulerian Mean

Abstract. This data set, which is prepared for the SPARC-Reanalysis Intercomparison Project (S-RIP), provides several zonal-mean diagnostics computed from reanalysis data on pressure levels. Diagnostics are currently provided for a variety of reanalyses, including ERA-40, ERA-Interim, ERA-20C, NCEP-NCAR, NCEP-DOE, CFSR, 20CR v2 and v2c, JRA-25, JRA-55, JRA-55C, JRA-55AMIP, MERRA, and MERRA-2. The data set will be expanded to include additional reanalyses as they become available. Basic dynamical variables (such as temperature, geopotential height and three-dimensional winds) are provided in addition to a complete set of terms from the Eulerian-mean and transformed Eulerian-mean momentum equations. Total diabatic heating and its long-wave and short-wave components are included as availability permits, along with heating rates diagnosed from the basic dynamical variables using the zonal-mean thermodynamic equation. Two versions of the data set are provided, one that uses horizontal and vertical grids provided by the various reanalysis centers, and another that uses a common grid to facilitate comparison among data sets. For the common grid, all diagnostics are interpolated horizontally onto a regular 2.5° ×2.5° grid for a subset of pressure levels that are common amongst all included reanalyses. The dynamical (Martineau, 2017, http://dx.doi.org/10.5285/b241a7f536a244749662360bd7839312) and diabatic (Wright, 2017, http://dx.doi.org/10.5285/70146c789eda4296a3c3ab6706931d56) variables are archived and maintained by the Centre for Environmental Data Analysis (CEDA).

scholarly journals Seasonal Variation of Rainy and Dry Season Per Capita Water Consumption in Freetown City Sierra Leone

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 499
Author(s):  
Salmatta Ibrahim A ◽  
Fayyaz Ali Memon ◽  
David Butler
Keyword(s):  
Seasonal Variation ◽  
Water Use ◽  
Water Consumption ◽  
Low Income ◽  
Rainy Season ◽  
Predictor Variable ◽  
Dry Season ◽  
Data Set ◽  
Per Capita ◽  
End Use

Ensuring a sustainable urban water supply for developing/low-income countries requires an understanding of the factors affecting water consumption and technical evidence of individual consumption which can be used to design an improved water demand projection. This paper compared dry and rainy season water sources available for consumption and the end-use volume by each person in the different income groups. The study used a questionnaire survey to gather household data for a total of 398 households, which was analysed to develop the relationship between per capita water consumption characteristics: Socio-economic status, demographics, water use behaviour around indoor and outdoor water use activities. In the per capita water consumption patterns of Freetown, a seasonal variation was found: In the rainy season, per capita water consumption was found to be about 7% higher than the consumption for the full sample, whilst in the dry season, per capita water consumption was almost 14% lower than the full survey. The statistical analysis of the data shows that the average per capita water consumption for both households increases with income for informal slum-, low-, middle- and high-income households without piped connection (73, 78, 94 and 112 L/capita/day) and with connection (91, 97, 113 and 133 L/capita/day), respectively. The collected data have been used to develop 20 statistical models using the multiple linear stepwise regression method for selecting the best predictor variable from the data set. It can be seen from the values that the strongest significant relationships of per capita consumption are with the number of occupants (R = −0.728) in the household and time spent to fetch water for use (R = −0.711). Furthermore, the results reveal that the highest fraction of end use is showering (18%), then bathing (16%), followed by toilet use (14%). This is not in agreement with many developing countries where toilet use represents the largest component of indoor end use.

Going Abroad: Transnational Solicitation and Contention by Ethnopolitical Organizations

2014 ◽  
Vol 68 (4) ◽  
pp. 945-978 ◽  
Author(s):  
Victor Asal ◽  
Justin Conrad ◽  
Peter White
Keyword(s):  
Middle East ◽  
Organizational Behavior ◽  
North Africa ◽  
Political Activity ◽  
Political Movements ◽  
Data Set ◽  
Organization Level ◽  
Foreign State ◽  
Level Data ◽  
Minorities At Risk

AbstractExisting literature on contentious political movements has generally focused on domestic political activity. Using the new Minorities at Risk Organizational Behavior–Middle East data set (MAROB-ME), which contains organization-level data for 104 ethnopolitical organizations in the Middle East and North Africa, we analyze the decision of both violent and nonviolent organizations to engage in political activity transnationally. Among the results, we find that diaspora support is associated with transnational nonviolent protest, whereas foreign state support and domestic repression increase the use of transnational violence. The most robust finding, however, is that participation in the domestic electoral process consistently reduces the likelihood that an organization will engage in any political activity abroad.

scholarly journals Biogeochemical processes and buffering capacity concurrently affect acidification in a seasonally hypoxic coastal marine basin

2015 ◽  
Vol 12 (5) ◽  
pp. 1561-1583 ◽  
Author(s):  
M. Hagens ◽  
C. P. Slomp ◽  
F. J. R. Meysman ◽  
D. Seitaj ◽  
J. Harlay ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Primary Production ◽  
Water Column ◽  
Bottom Water ◽  
Substantial Reduction ◽  
Buffering Capacity ◽  
Total Alkalinity ◽  
Acid Base ◽  
Data Set ◽  
Ph Fluctuations

Abstract. Coastal areas are impacted by multiple natural and anthropogenic processes and experience stronger pH fluctuations than the open ocean. These variations can weaken or intensify the ocean acidification signal induced by increasing atmospheric pCO2. The development of eutrophication-induced hypoxia intensifies coastal acidification, since the CO2 produced during respiration decreases the buffering capacity in any hypoxic bottom water. To assess the combined ecosystem impacts of acidification and hypoxia, we quantified the seasonal variation in pH and oxygen dynamics in the water column of a seasonally stratified coastal basin (Lake Grevelingen, the Netherlands). Monthly water-column chemistry measurements were complemented with estimates of primary production and respiration using O2 light–dark incubations, in addition to sediment–water fluxes of dissolved inorganic carbon (DIC) and total alkalinity (TA). The resulting data set was used to set up a proton budget on a seasonal scale. Temperature-induced seasonal stratification combined with a high community respiration was responsible for the depletion of oxygen in the bottom water in summer. The surface water showed strong seasonal variation in process rates (primary production, CO2 air–sea exchange), but relatively small seasonal pH fluctuations (0.46 units on the total hydrogen ion scale). In contrast, the bottom water showed less seasonality in biogeochemical rates (respiration, sediment–water exchange), but stronger pH fluctuations (0.60 units). This marked difference in pH dynamics could be attributed to a substantial reduction in the acid–base buffering capacity of the hypoxic bottom water in the summer period. Our results highlight the importance of acid–base buffering in the pH dynamics of coastal systems and illustrate the increasing vulnerability of hypoxic, CO2-rich waters to any acidifying process.

scholarly journals Sources of light-absorbing aerosol in arctic snow and their seasonal variation

2010 ◽  
Vol 10 (6) ◽  
pp. 13755-13796 ◽  
Author(s):  
D. A. Hegg ◽  
S. G. Warren ◽  
T. C. Grenfell ◽  
S. J. Doherty ◽  
A. D. Clarke
Keyword(s):  
Seasonal Variation ◽  
Biomass Burning ◽  
Chemical Constituents ◽  
Dominant Role ◽  
Data Sets ◽  
Source Attribution ◽  
Data Set ◽  
Pmf Model ◽  
The North ◽  
Absorbing Aerosols

Abstract. Two data sets consisting of measurements of light absorbing aerosols (LAA) in arctic snow together with suites of other corresponding chemical constituents are presented; the first from Siberia, Greenland and near the North Pole obtained in 2008, and the second from the Canadian arctic obtained in 2009. A preliminary differentiation of the LAA into black carbon (BC) and non-BC LAA is done. Source attribution of the light absorbing aerosols was done using a positive matrix factorization (PMF) model. Four sources were found for each data set (crop and grass burning, boreal biomass burning, pollution and marine). For both data sets, the crops and grass biomass burning was the main source of both LAA species, suggesting the non-BC LAA was brown carbon. Depth profiles at most of the sites allowed assessment of the seasonal variation in the source strengths. The biomass burning sources dominated in the spring but pollution played a more significant (though rarely dominant) role in the fall, winter and, for Greenland, summer. The PMF analysis is consistent with trajectory analysis and satellite fire maps.

scholarly journals Development of a daily gridded precipitation data set for the Middle East

2008 ◽  
Vol 12 ◽  
pp. 165-170 ◽  
Author(s):  
A. Yatagai ◽  
P. Xie ◽  
P. Alpert
Keyword(s):  
Middle East ◽  
Climate Models ◽  
Daily Precipitation ◽  
Rain Gauge ◽  
Monthly Precipitation ◽  
Data Set ◽  
Key Points ◽  
Fertile Crescent ◽  
Precipitation Analysis ◽  
The Impact

Abstract. We show an algorithm to construct a rain-gauge-based analysis of daily precipitation for the Middle East. One of the key points of our algorithm is to construct an accurate distribution of climatology. One possible advantage of this product is to validate high-resolution climate models and/or to diagnose the impact of climate changes on local hydrological resources. Many users are familiar with a monthly precipitation dataset (New et al., 1999) and a satellite-based daily precipitation dataset (Huffman et al., 2001), yet our data set, unlike theirs, clearly shows the effect of orography on daily precipitation and other extreme events, especially over the Fertile Crescent region. Currently the Middle-East precipitation analysis product is consisting of a 25-year data set for 1979–2003 based on more than 1300 stations.

scholarly journals Evaluation of the Performance of CFSR Reanalysis Data Set for Estimating Potential Evapotranspiration (PET) in Turkey

2021 ◽  
Author(s):  
AHMET IRVEM ◽  
Mustafa OZBULDU
Keyword(s):  
Potential Evapotranspiration ◽  
Meteorological Data ◽  
Reanalysis Data ◽  
Actual Evapotranspiration ◽  
Observation Data ◽  
Reanalysis Dataset ◽  
Data Set ◽  
Climate Forecast System Reanalysis ◽  
Mountainous Regions ◽  
Weather Stations

Abstract Evapotranspiration is an important parameter for hydrological, meteorological and agricultural studies. However, the calculation of actual evapotranspiration is very challenging and costly. Therefore, Potential Evapotranspiration (PET) is typically calculated using meteorological data to calculate actual evapotranspiration. However, it is very difficult to get complete and accurate data from meteorology stations in, rural and mountainous regions. This study examined the availability of the Climate Forecast System Reanalysis (CFSR) reanalysis data set as an alternative to meteorological observation stations in the computation of potential annual and seasonal evapotranspiration. The PET calculations using the CFSR reanalysis dataset for the period 1987-2017 were compared to data observed at 259 weather stations observed in Turkey. As a result of the assessments, it was determined that the seasons in which the CFSR reanalysis data set had the best prediction performance were the winter (C'= 0.76 and PBias = -3.77) and the autumn (C' = 0.75 and PBias = -12.10). The worst performance was observed for the summer season. The performance of the annual prediction was determined as C'= 0.60 and PBias = -15.27. These findings indicate that the results of the PET calculation using the CFSR reanalysis data set are relatively successful for the study area. However, the data should be evaluated with observation data before being used especially in the summer models.

A novel method to identify subseasonal clustering episodes of extreme precipitation events and their contribution to large accumulations

2021 ◽  
Author(s):  
Jérôme Kopp ◽  
Pauline Rivoire ◽  
S. Mubashshir Ali ◽  
Yannick Barton ◽  
Olivia Martius
Keyword(s):  
Time Scales ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Time Window ◽  
Heat Waves ◽  
Reanalysis Data ◽  
Data Set ◽  
Temporal Clustering ◽  
Extreme Precipitation Events ◽  
Precipitation Events

<p>Temporal clustering of extreme precipitation events on subseasonal time scales is a type of compound event, which can cause large precipitation accumulations and lead to floods. We present a novel count-based procedure to identify subseasonal clustering of extreme precipitation events. Furthermore, we introduce two metrics to characterise the frequency of subseasonal clustering episodes and their relevance for large precipitation accumulations. The advantage of this approach is that it does not require the investigated variable (here precipitation) to satisfy any specific statistical properties. Applying this methodology to the ERA5 reanalysis data set, we identify regions where subseasonal clustering of annual high precipitation percentiles occurs frequently and contributes substantially to large precipitation accumulations. Those regions are the east and northeast of the Asian continent (north of Yellow Sea, in the Chinese provinces of Hebei, Jilin and Liaoning; North and South Korea; Siberia and east of Mongolia), central Canada and south of California, Afghanistan, Pakistan, the southeast of the Iberian Peninsula, and the north of Argentina and south of Bolivia. Our method is robust with respect to the parameters used to define the extreme events (the percentile threshold and the run length) and the length of the subseasonal time window (here 2 – 4 weeks). The procedure could also be used to identify temporal clustering of other variables (e.g. heat waves) and can be applied on different time scales (e.g. for drought years). <span>For a complementary study on the subseasonal clustering of European extreme precipitation events and its relationship to large-scale atmospheric drivers, please refer to Barton et al.</span></p>

Sign in / Sign up

Export Citation Format

Share Document