4 research outputs found

    Planetary boundary layer height by means of lidar and numerical simulations over New Delhi, India

    Get PDF
    In this work, the height of the planetary boundary layer (PBLH) is investigated over Gwal Pahari (Gual Pahari), New Delhi, for almost a year. To this end, ground-based measurements from a multiwavelength Raman lidar were used. The modified wavelet covariance transform (WCT) method was utilized for PBLH retrievals. Results were compared to data from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and the Weather Research and Forecasting (WRF) model. In order to examine the difficulties of PBLH detection from lidar, we analyzed three cases of PBLH diurnal evolution under different meteorological and aerosol load conditions. In the presence of multiple aerosol layers, the employed algorithm exhibited high efficiency (r=0.9) in the attribution of PBLH, whereas weak aerosol gradients induced high variability in the PBLH. A sensitivity analysis corroborated the stability of the utilized methodology. The comparison with CALIPSO observations yielded satisfying results (r=0.8), with CALIPSO slightly overestimating the PBLH. Due to the relatively warmer and drier winter and, correspondingly, colder and rainier pre-monsoon season, the seasonal PBLH cycle during the measurement period was slightly weaker than the cycle expected from long-term climate records.</p

    Measurements and modeling of optical-equivalent snow grain sizes under arctic low-sun conditions

    Get PDF
    The size and shape of snow grains directly impacts the reflection by a snowpack. In this article, different approaches to retrieve the optical-equivalent snow grain size (ropt_{opt}) or, alternatively, the specific surface area (SSA) using satellite, airborne, and ground-based observations are compared and used to evaluate ICON-ART (ICOsahedral Nonhydrostatic—Aerosols and Reactive Trace gases) simulations. The retrieval methods are based on optical measurements and rely on the ropt_{opt}-dependent absorption of solar radiation in snow. The measurement data were taken during a three-week campaign that was conducted in the North of Greenland in March/April 2018, such that the retrieval methods and radiation measurements are affected by enhanced uncertainties under these low-Sun conditions. An adjusted airborne retrieval method is applied which uses the albedo at 1700 nm wavelength and combines an atmospheric and snow radiative transfer model to account for the direct-to-global fraction of the solar radiation incident on the snow. From this approach, we achieved a significantly improved uncertainty (<25%) and a reduced effect of atmospheric masking compared to the previous method. Ground-based in situ measurements indicated an increase of ropt_{opt} of 15 µm within a five-day period after a snowfall event which is small compared to previous observations under similar temperature regimes. ICON-ART captured the observed change of ropt_{opt} during snowfall events, but systematically overestimated the subsequent snow grain growth by about 100%. Adjusting the growth rate factor to 0.012 µm2^{2} s1^{-1} minimized the difference between model and observations. Satellite-based and airborne retrieval methods showed higher ropt_{opt} over sea ice (<300 µm) than over land surfaces (<100 µm) which was reduced by data filtering of surface roughness features. Moderate-Resolution Imaging Spectroradiometer (MODIS) retrievals revealed a large spread within a series of subsequent individual overpasses, indicating their limitations in observing the snow grain size evolution in early spring conditions with low Sun

    Atmospheric and Surface Processes, and Feedback Mechanisms Determining Arctic Amplification: A Review of First Results and Prospects of the (AC)3 Project

    Get PDF
    Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC)3 project has been established in 2016. It comprises modeling and data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, ship-borne, and satellite data of physical, chemical, and meteorological properties of the Arctic atmosphere, cryosphere, and upper ocean that are available for the Arctic climate research community. Short-term changes and indications of long-term trends in Arctic climate parameters have been detected using existing and new data

    Planetary boundary layer height by means of lidar and numerical simulations over New Delhi, India

    No full text
    In this work, the height of the planetary boundary layer (PBLH) is investigated over Gwal Pahari (Gual Pahari), New Delhi, for almost a year. To this end, ground-based measurements from a multiwavelength Raman lidar were used. The modified wavelet covariance transform (WCT) method was utilized for PBLH retrievals. Results were compared to data from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and the Weather Research and Forecasting (WRF) model. In order to examine the difficulties of PBLH detection from lidar, we analyzed three cases of PBLH diurnal evolution under different meteorological and aerosol load conditions. In the presence of multiple aerosol layers, the employed algorithm exhibited high efficiency (&lt;span classCombining double low line&quot;inline-formula&quot;&gt;&lt;i&gt;r&lt;/i&gt;Combining double low line0.9&lt;/span&gt;) in the attribution of PBLH, whereas weak aerosol gradients induced high variability in the PBLH. A sensitivity analysis corroborated the stability of the utilized methodology. The comparison with CALIPSO observations yielded satisfying results (&lt;span classCombining double low line&quot;inline-formula&quot;&gt;&lt;i&gt;r&lt;/i&gt;Combining double low line0.8&lt;/span&gt;), with CALIPSO slightly overestimating the PBLH. Due to the relatively warmer and drier winter and, correspondingly, colder and rainier pre-monsoon season, the seasonal PBLH cycle during the measurement period was slightly weaker than the cycle expected from long-term climate records. © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License
    corecore