Basit Khan

Dr. Basit Khan

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Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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20 March 2020 in Geoscientific Model Development
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Björn MarongaBjörn Maronga
Björn Maronga
SBSabine Banzhaf
Sabine Banzhaf
CBCornelia Burmeister
Cornelia Burmeister
TEThomas Esch
Thomas Esch
RFRenate Forkel
Renate Forkel
SRSiegfried Raasch
Siegfried Raasch
In this paper, we describe the PALM model system 6.0. PALM (formerly an abbreviation for Parallelized Large-eddy Simulation Model and now an independent name) is a Fortran-based code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. This is a follow-up paper to the PALM 4.0 model description in Maronga et al. (2015). During the last years, PALM has been significantly improved and now offers a variety of new components. In particular, much effort was made to enhance the model with components needed for applications in urban environments, like fully interactive land surface and radiation schemes, chemistry, and an indoor model. This paper serves as an overview paper of the PALM 6.0 model system and we describe its current model core. The individual components for urban applications, case studies, validation runs, and issues with suitable input data are presented and discussed in a series of companion papers in this special issue.

1 March 2021 in Geoscientific Model Development
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BKBasit Khan
Basit Khan
SBSabine Banzhaf
Sabine Banzhaf
ECEdward C. Chan
Edward C. Chan
RFRenate Forkel
Renate Forkel
FKFarah Kanani-Sühring
Farah Kanani-Sühring
MSMatthias Sühring
Matthias Sühring
In this article we describe the implementation of an online-coupled gas-phase chemistry model in the turbulence-resolving PALM model system 6.0 (formerly an abbreviation for Parallelized Large-eddy Simulation Model and now an independent name). The new chemistry model is implemented in the PALM model as part of the PALM-4U (PALM for urban applications) components, which are designed for application of the PALM model in the urban environment (Maronga et al., 2020). The latest version of the Kinetic PreProcessor (KPP, 2.2.3) has been utilized for the numerical integration of gas-phase chemical reactions. A number of tropospheric gas-phase chemistry mechanisms of different complexity have been implemented ranging from the photostationary state (PHSTAT) to mechanisms with a strongly simplified volatile organic compound (VOC) chemistry (e.g. the SMOG mechanism from KPP) and the Carbon Bond Mechanism 4 (CBM4; Gery et al., 1989 ), which includes a more comprehensive, but still simplified VOC chemistry. Further mechanisms can also be easily added by the user. In this work, we provide a detailed description of the chemistry model, its structure and input requirements along with its various features and limitations. A case study is presented to demonstrate the application of the new chemistry model in the urban environment. The computation domain of the case study comprises part of Berlin, Germany. Emissions are considered using street-type-dependent emission factors from traffic sources. Three chemical mechanisms of varying complexity and one no-reaction (passive) case have been applied, and results are compared with observations from two permanent air quality stations in Berlin that fall within the computation domain. Even though the feedback of the model's aerosol concentrations on meteorology is not yet considered in the current version of the model, the results show the importance of online photochemistry and dispersion of air pollutants in the urban boundary layer for high spatial and temporal resolutions. The simulated NOx and O3 species show reasonable agreement with observations. The agreement is better during midday and poorest during the evening transition hours and at night. The CBM4 and SMOG mechanisms show better agreement with observations than the steady-state PHSTAT mechanism.

6 May 2021 in Geoscientific Model Development
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DLDongqi Lin
Dongqi Lin
BKBasit Khan
Basit Khan
MKMarwan Katurji
Marwan Katurji
LBLeroy Bird
Leroy Bird
RFRicardo Faria
Ricardo Faria
LRLaura Revell
Laura Revell
A set of Python-based tools, WRF4PALM, has been developed for offline nesting of the PALM model system 6.0 into the Weather Research and Forecasting (WRF) modelling system. Time-dependent boundary conditions of the atmosphere are critical for accurate representation of microscale meteorological dynamics in high-resolution real-data simulations. WRF4PALM generates initial and boundary conditions from WRF outputs to provide time-varying meteorological forcing for PALM. The WRF model has been used across the atmospheric science community for a broad range of multidisciplinary applications. The PALM model system 6.0 is a turbulence-resolving large-eddy simulation model with an additional Reynolds-averaged Navier–Stokes (RANS) mode for atmospheric and oceanic boundary layer studies at microscale (Maronga et al., 2020). Currently PALM has the capability to ingest output from the regional scale Consortium for Small-scale Modelling (COSMO) atmospheric prediction model. However, COSMO is not an open source model and requires a licence agreement for operational use or academic research (http://www.cosmo-model.org/, last access: 23 April 2021). This paper describes and validates the new free and open-source WRF4PALM tools (available at https://github.com/dongqi-DQ/WRF4PALM, last access: 23 April 2021). Two case studies using WRF4PALM are presented for Christchurch, New Zealand, which demonstrate successful PALM simulations driven by meteorological forcing from WRF outputs. The WRF4PALM tools presented here can potentially be used for micro- and mesoscale studies worldwide, for example in boundary layer studies, air pollution dispersion modelling, wildfire emissions and spread, urban weather forecasting, and agricultural meteorology.

1 January 2015 in Tellus B: Chemical and Physical Meteorology
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BKBasit Khan
Basit Khan
GSGeorgiy Stenchikov
Georgiy Stenchikov
BWBernadett Weinzierl
Bernadett Weinzierl
SKStoitchko Kalenderski
Stoitchko Kalenderski
SOSergey Osipov
Sergey Osipov
Dust plume formation in the free troposphere and aerosol size distribution during the Saharan Mineral Dust Experiment in North Africa

23 September 2024 in Atmospheric Chemistry and Physics
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Hengheng ZhangHengheng Zhang
Hengheng Zhang
WHWei Huang
Wei Huang
XSXiaoli Shen
Xiaoli Shen
RRRamakrishna Ramisetty
Ramakrishna Ramisetty
JSJunwei Song
Junwei Song
HSHarald Saathoff
Harald Saathoff
Aerosol distributions are of great relevance for air quality, especially for cities like Stuttgart, which has limited air exchange due to its location in a basin. We collected a comprehensive set of data from remote sensing and in situ methods including radiosondes for the urban background of downtown Stuttgart to determine the impact of boundary layer mixing processes on local air quality and to evaluate the simulation results of the high-resolution large eddy simulation (LES) model PALM-4U at 10 m grid spacing. Stagnant meteorological conditions caused accumulation of aerosols, and chemical composition analysis shows that ammonium nitrate (37 ± 9 %) and organic aerosol (OA; 34 ± 9 %) dominated during this winter study. Case studies show that clouds during previous nights can weaken temperature inversion and accelerate boundary layer mixing after sunrise by up to 3 h. This is important for ground-level aerosol dilution during the morning rush hour. Furthermore, our observations validate results of the LES model PALM-4U in terms of boundary layer heights and aerosol mixing for 48 h. The simulated aerosol concentrations follow the trend of our observations but are still underestimated by a factor of 4.5 ± 2.1 due to missing secondary aerosol formation processes and uncertainties of emissions and boundary conditions in the model. This paper firstly evaluates the PALM-4U model performance in simulating aerosol spatio-temporal distributions, which can help to improve the LES model and to better understand sources and sinks for air pollution as well as the role of horizontal and vertical transport.

25 April 2018 in International Journal of Climatology
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BKBasit Khan
Basit Khan
YAYasser Abualnaja
Yasser Abualnaja
AAAbdullah M. Al‐Subhi
Abdullah M. Al‐Subhi
MNMohammedali Nellayaputhenpeedika
Mohammedali Nellayaputhenpeedika
MTManoj Nellikkattu Thody
Manoj Nellikkattu Thody
ASAndrew P. Sturman
Andrew P. Sturman
Long‐term near‐surface observations from five coastal stations, high‐resolution model data from Modern Era Retrospective‐Analysis for Research and Applications (MERRA) and high‐resolution daily sea surface temperature (SST) from National Ocean and Atmospheric Administration (NOAA) are used to investigate the climatology of sea breezes over the eastern side of the Red Sea region. Results show existence of separate sea breeze systems along different segments of the Red Sea coastline. Based on the physical character and synoptic influences, sea breezes in the Red Sea are broadly divided into three regions: the north and the middle Red Sea (NMRS), the Red Sea convergence zone (RSCZ) and the southern Red Sea (SRS) regions. On average, sea breezes developed on 67% of days of the 10‐year study period. Although sea breezes occur almost all year, this mesoscale phenomenon is most frequent from May to October (78% of the total sea breeze days). The sea breeze frequency increases from north to south (equatorwards), and sea breeze characteristics appear to vary both temporally and spatially. In addition to land–sea thermal differential, coastline shape, latitude and topography, the prevailing northwesterly at NMRS region, the convergence of northwesterly and southeasterly wind system at RSCZ region and the northeast and southwest monsoon at SRS region play an important role in defining the sea breeze characteristics over the Red Sea.