Atmospheric boundary layer during northeast monsoon over Tamilnadu and neighbourhood - A study using TOVS data

Thermodynamic structure of atmospheric boundary layer during October - December covering southwest and northeast monsoon activities over interior Tamilnadu (ITN), coastal Tamilnadu (CTN) and adjoining Bay of Bengal (BOB) has been studied using TIROS Operational Vertical Sounder (TOVS) data of 1996-98. Heights of neutral stratified mixed layer, cloud layer and planetary boundary layer (PBL) have been estimated through available standard pressure level data. Highest PBL occurs during active northeast monsoon. Cloud layer thickness during weak northeast monsoon over interior Tamilnadu is significantly higher than that over coastal Tamilnadu and also over Bay of Bengal. Convective stability (instability) of the atmosphere in 850-700 hPa layer is associated with weak / withdrawal (active) phase of northeast monsoon. One of the plausible reasons for subdued rainfall activity during weak northeast monsoon over interior Tamilnadu could be convective instability seen over this region in 850-700 hPa layer. But the same is absent in CTN and BOB where no rainfall activity exists during weak monsoon phase. Virtual temperature lapse rate in 850-700 hPa layer exceeding (less than) 6oK/km is associated with active (weak) phase of northeast monsoon over the interior, coastal Tamilnadu and Bay of Bengal.

BOREAL- A fixed-wing unmanned aerial system for the measurement of wind and turbulence in the atmospheric boundary layer

An instrumentation package for wind and turbulence observations in the atmospheric boundary layer on an unmanned aerial vehicle (UAV) called BOREAL has been developed. BOREAL is a fixed wing UAV built by BOREAL company which weighs up to 25kg (5kg of payload) and has a wingspan of 4.2m. With a light payload and optimal weather conditions, it has a flight endurance of nine hours. The instrumental payload was designed in order to measure every parameter required for the computation of the three wind components, at a rate of 100 s−1 which is fast enough to capture turbulence fluctuations: a GPS-IMU platform measures the three components of the groundspeed a well as the attitude angles; the airplane nose has been replaced by a five-hole probe in order to measure the angles of attack and sideslip, according to the so-called radome technique. This probe was calibrated using computational fluid dynamics (CFD) simulations and wind tunnel tests. The remaining instruments are a Pitot tube for static and dynamic pressure measurement, and temperature/humidity sensors in dedicated housings. The optimal airspeed at which the vibrations are significantly reduced to an acceptable level was defined from qualification flights. With appropriate flight patterns, the reliability of the mean wind estimates, through self-consistency and comparison with observations performed at 60m on an instrumented tower could be assessed. Promising first observations of turbulence up to frequencies around 10Hz and corresponding to a spatial resolution to the order of 3m, are hereby presented.

Inter-comparison of wind measurements in the atmospheric boundary layer and the lower troposphere with Aeolus and a ground-based coherent Doppler lidar network over China

After the successful launch of Aeolus, which is the first spaceborne wind lidar developed by the European Space Agency (ESA), on 22 August 2018, we deployed several ground-based coherent Doppler wind lidars (CDLs) to verify the wind observations from Aeolus. By the simultaneous wind measurements with CDLs at 17 stations over China, the Rayleigh-clear and Mie-cloudy horizontal-line-of-sight (HLOS) wind velocities from Aeolus in the atmospheric boundary layer and the lower troposphere are compared with those from CDLs. To ensure the quality of the measurement data from CDLs and Aeolus, strict quality controls are applied in this study. Overall, 52 simultaneous Mie-cloudy comparison pairs and 387 Rayleigh-clear comparison pairs from this campaign are acquired. All of the Aeolus-produced Level 2B (L2B) Mie-cloudy HLOS wind and Rayleigh-clear HLOS wind and CDL-produced HLOS wind are compared individually. For the inter-comparison result of Mie-cloudy HLOS wind and CDL-produced HLOS wind, the correlation coefficient, the standard deviation, the scaled mean absolute deviation (MAD) and the bias are 0.83, 3.15 m s−1, 2.64 m s−1 and −0.25 m s−1, respectively, while the y=ax slope, the y=ax+b slope and the y=ax+b intercept are 0.93, 0.92 and −0.33 m s−1. For the Rayleigh-clear HLOS wind, the correlation coefficient, the standard deviation, the scaled MAD and the bias are 0.62, 7.07 m s−1, 5.77 m s−1 and −1.15 m s−1, respectively, while the y=ax slope, the y=ax+b slope and the y=ax+b intercept are 1.00, 0.96 and −1.2 m s−1. It is found that the standard deviation, the scaled MAD and the bias on ascending tracks are lower than those on descending tracks. Moreover, to evaluate the accuracy of Aeolus HLOS wind measurements under different product baselines, the Aeolus L2B Mie-cloudy HLOS wind data and L2B Rayleigh-clear HLOS wind data under Baselines 07 and 08, Baselines 09 and 10, and Baseline 11 are compared against the CDL-retrieved HLOS wind data separately. From the comparison results, marked misfits between the wind data from Aeolus Baselines 07 and 08 and wind data from CDLs in the atmospheric boundary layer and the lower troposphere are found. With the continuous calibration and validation and product processor updates, the performances of Aeolus wind measurements under Baselines 09 and 10 and Baseline 11 are improved significantly. Considering the influence of turbulence and convection in the atmospheric boundary layers and the lower troposphere, higher values for the vertical velocity are common in this region. Hence, as a special note, the vertical velocity could impact the HLOS wind velocity retrieval from Aeolus.

Testing the efficacy of atmospheric boundary layer height detection algorithms using uncrewed aircraft system data from MOSAiC

During the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, meteorological conditions over the lowest 1 km of the atmosphere were sampled with the DataHawk2 (DH2) fixed wing uncrewed aircraft system (UAS). Of particular interest is the atmospheric boundary layer (ABL) height, as ABL structure can be closely coupled to cloud properties, surface fluxes, and the atmospheric radiation budget. The high temporal resolution of the UAS observations allows us to subjectively identify ABL height for 65 out of the total 89 flights conducted over the central Arctic Ocean between 23 March and 26 July 2020 by visually analyzing profiles of virtual potential temperature, humidity, and bulk Richardson number. Comparing this subjective ABL height with the ABL heights identified by various previously published objective methods allows us to determine which objective methods are most successful at accurately identifying ABL height in the central Arctic environment. The objective methods we use are the Liu-Liang, Heffter, virtual potential temperature gradient maximum, and bulk Richardson number methods. In the process of testing these objective methods on the DH2 data, numerical thresholds were adapted to work best for the UAS-based sampling. To determine if conclusions are robust across different measurement platforms, the subjective and objective ABL height determination processes were repeated using the radiosonde profile closest in time to each DH2 flight. For both the DH2 and radiosonde data, it is determined that the bulk Richardson number method is the most successful at identifying ABL height, while the Liu-Liang method is least successful.

Dynamic interactions between city and atmospheric boundary layer – urbisphere Berlin campaign

<p class="western">In order to better understand dynamic interactions between a city and the regional atmospheric boundary layer, the '<em>urbisphere </em>Berlin campaign' is being conducted during 2021-2022 in Germany within the ERC Synergy <em>urbisphere</em> grant. <em>urbisphere</em> aims to enhance understanding, forecasting, and projecting feedbacks between climate change and drivers of urban transformation. One foci is the development of the next generation of urban climate <span lang="en-GB">simulations</span> with dynamic atmosphere-urban <span lang="en-GB">feedbacks</span>.</p> <p class="western">A <span lang="en-GB">key aspect</span> of <em>urbisphere</em> are comprehensive measurement campaigns in different cities. These involve undertaking high-quality research <span lang="en-GB">observations</span> on urban effects for observation-based studies as well as for model development and evaluation. The <span lang="en-GB">Berlin</span> campaign is investigating the dynamics of the atmospheric boundary layer within and beyond the city, and how the atmosphere dynamically responds to urban surface forcings, emissions, and human activity cycles <span lang="en-GB">from</span> diurnal to an annual cycle. <span lang="en-GB">A</span> dense network of ground-based remote sensing instruments (e.g. automatic lidars and ceilometers, doppler-wind lidars) for mixing-layer height detection within the city and along a rural-urban-rural transect, scintillometer paths <span lang="en-GB">for</span> spatially averaged information on turbulent sensible heat flux, and radiation measurements for quantification of the influence of urban emissions, aerosols and clouds on downwelling radiative fluxes is deployed. Altogether, the additional observations supplement the existing Urban Climate Observatory (UCO) in Berlin to allow for a comprehensive and spatially detailed understanding of city-atmosphere interactions, and the effect of cities on downwind regions. This contribution provides an overview of the measurement campaign and gives first insights into collected data.</p>

Uncertainty Assessment for HATPRO Microwave Radiometer Measurements and Calibrations

<p>The atmospheric boundary layer (ABL) is the most important under-sampled part of the atmosphere. ABL monitoring is crucial for short-range forecasting of severe weather within highly resolving numerical weather predictions (NWP). Top-priority atmospheric variables for NWP applications like temperature (T) and humidity (H) profiles are currently not adequately measured. Ground-based microwave radiometers (MWRs) like HATPRO (Humidity And Temperature PROfiler) are particularly well suited to obtain such T-profiles in the ABL as well as coarse resolution H-profiles. It has been shown by previous studies that the assimilation of MWR observations is beneficial for NWP models, however MWR data are not yet routinely assimilated into operational NWP. The HATPRO measures in zenith and other angles throughout the troposphere over an area with ~10 km radius and has a temporal resolution on the order of seconds. Measured brightness temperatures (TB) are used to retrieve the T- and H-profiles. Path integrated values IWV (Integrated Water Vapor) and LWP (Liquid Water Path) are quite reliable with excellent uncertainties up to 0.5 kg/m<sup>2</sup> and 20 g/m<sup>2</sup>, respectively.</p> <p>Driven by the E-PROFILE program, a business case proposal was recently accepted by EUMETNET to continuously provide MWR data to the European meteorological services. Also, the European Research Infrastructure for the observation of Aerosol, Clouds, and Trace gases (ACTRIS) and the European COST action PROBE (PROfiling the atmospheric Boundary layer at European scale) currently focus on establishing continent-wide quality and observation standards for MWR networks for research as well as for NWP applications. The German Weather Service (DWD) also investigates the potential of HATPRO networks for improving short-term weather forecasts over Germany.</p> <p>For all this it is important to obtain an overview of what HATPROs are capable of in regard to their measurement uncertainty. This was done by conducting coordinated experiments at JOYCE (Jülich Observatory for Cloud Evolution) and the FESSTVaL (Field Experiment on Submesoscale Spatio-Temporal Variability at Lindenberg) campaign in 2021 within a prototype MWR network. The goal is to develop a standard procedure for error characterization that can be applied to any HATPRO network instrument (guidance for operators).</p> <p>Important error components are absolute calibration errors (biases), drifts (instrument stability, leaps between calibrations), radiometric noise and also location specific radio frequency interferences (RFI). For the absolute calibration with liquid nitrogen, the repeatability, the integration time and the time between calibrations are essential. Differences between consecutive calibrations are analysed, the right duration of a calibration and the right amount of time between calibrations are proposed, referring to the magnitude of the observed drifts. For the determination of noise levels for each channel, covariance matrices (correlated noise) of measured brightness temperatures on the cold- and hotload references are presented. RFI are detectable via clear-sky azimuth- and/or elevation scans.</p>