Analysis of the performance of a ship-borne scanning wind lidar in the Arctic and Antarctic

Zentek, Rolf; Kohnemann, Svenja; Heinemann, Günther

doi:10.5194/amt-11-5781-2018

Cited by 9 publications

(13 citation statements)

References 20 publications

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“…ERA5 and ERA-Interim show similar values. This good agreement could stem partially from the fact that the radio soundings of the ship (2-3 d −1 ) are assimilated in ERA5 and ERA-Interim, which show also good agreement with the lidar data (Zentek et al, 2018). The computation of the statistics for different heights showed that the wind speed RMSE of CCLM is largest around a height of 1000 m, while the RMSE of ERA5 and ERA-Interim is mostly constant with height ( Fig.…”

Section: Overall Statisticssupporting

confidence: 54%

“…Benefits of modelling a fractional sea ice cover are investigated in Gutjahr et al (2016). As daily sea ice thickness data like PIOMAS (Zhang and Rothrock, 2003) are not available for Antarctica, we assume two different ice classes depending on the initial sea ice concentration. Grid points with a sea ice concentration of 0 %-15 % are set to open water.…”

Section: Cclmmentioning

confidence: 99%

“…We installed a Doppler lidar onboard the RV Polarstern and measured vertical profiles of horizontal wind speed and direction from 24 December till 30 January. In Zentek et al (2018) we compared the measurements to radio soundings and ship measurements and found a bias (root-mean-square deviation) of approx. 0.1 (1) m s −1 for wind speed and 1 (10) • for wind direction, respectively.…”

Section: Wind Lidarmentioning

confidence: 99%

“…The first LLJ occurred between 00:00 and 02:00 UTC (LLJ1). The LLJ between 06:00 and 08:00 UTC (LLJ2) was captured by the radio sounding at 07:00 UTC (Zentek et al, 2018), and the wind maximum between 10:00 and 14:00 UTC (LLJ3) was also measured by a radio sounding at heights of 800 to 1000 m at 12:00 UTC. While the 6hourly ERA-Interim data cannot reproduce the structure and evolution of the wind field of the lidar measurements, the hourly ERA5 data capture LLJ2 and LLJ3, which is likely explained by the assimilation of radio sounding data.…”

Section: Case Study Amentioning

confidence: 99%

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Verification of the regional atmospheric model CCLM v5.0 with conventional data and lidar measurements in Antarctica

Zentek

Heinemann

2020

Geosci. Model Dev.

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Abstract. The nonhydrostatic regional climate model CCLM was used for a long-term hindcast run (2002–2016) for the Weddell Sea region with resolutions of 15 and 5 km and two different turbulence parametrizations. CCLM was nested in ERA-Interim data and used in forecast mode (suite of consecutive 30 h long simulations with 6 h spin-up). We prescribed the sea ice concentration from satellite data and used a thermodynamic sea ice model. The performance of the model was evaluated in terms of temperature and wind using data from Antarctic stations, automatic weather stations (AWSs), an operational forecast model and reanalyses data, and lidar wind profiles. For the reference run we found a warm bias for the near-surface temperature over the Antarctic Plateau. This bias was removed in the second run by adjusting the turbulence parametrization, which results in a more realistic representation of the surface inversion over the plateau but resulted in a negative bias for some coastal regions. A comparison with measurements over the sea ice of the Weddell Sea by three AWS buoys for 1 year showed small biases for temperature around ±1 K and for wind speed of 1 m s−1. Comparisons of radio soundings showed a model bias around 0 and a RMSE of 1–2 K for temperature and 3–4 m s−1 for wind speed. The comparison of CCLM simulations at resolutions down to 1 km with wind data from Doppler lidar measurements during December 2015 and January 2016 yielded almost no bias in wind speed and a RMSE of ca. 2 m s−1. Overall CCLM shows a good representation of temperature and wind for the Weddell Sea region. Based on these encouraging results, CCLM at high resolution will be used for the investigation of the regional climate in the Antarctic and atmosphere–ice–ocean interactions processes in a forthcoming study.

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Section: Overall Statisticssupporting

confidence: 54%

Section: Cclmmentioning

confidence: 99%

Section: Wind Lidarmentioning

confidence: 99%

Section: Case Study Amentioning

confidence: 99%

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Verification of the regional atmospheric model CCLM v5.0 with conventional data and lidar measurements in Antarctica

Zentek

Heinemann

2020

Geosci. Model Dev.

Self Cite

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show abstract

“…We installed a Doppler lidar onboard the RV Polarstern and measured vertical profiles of horizontal wind speed and direction from 24th December till 30th January. In Zentek et al (2018) we compared the measurements to radio soundings and ship measurements and found a bias (root mean square deviation) of approx. 0.1 (1) ms −1 for wind speed and 1 (10)°for wind direction, respectively.…”

Section: Lidarmentioning

confidence: 99%

Verification of the regional atmospheric model CCLM v5.0 with conventional data and Lidar measurements in Antarctica

Zentek¹,

Heinemann²

2019

Preprint

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Abstract. The non-hydrostatic regional climate model CCLM was used for a long-term hindcast run (2002–2016) for the Weddell Sea region with resolutions of 15 and 5 km and two different turbulence parametrizations. CCLM was nested in ERA-Interim data. We prescribed sea-ice concentration from satellite data, and used a thermodynamic sea-ice model. The performance of the model was evaluated in terms of temperature and wind using data from Antarctic stations, AWS over land and sea ice, operational forecast model and reanalyses data, and lidar wind profiles. For the reference run we found a warm bias for the near-surface temperature over the Antarctic plateau. This bias was removed in the second run by adjusting the turbulence parametrization, which results in a more realistic representation of the surface inversion over the plateau. Differences in other regions were small. A comparison with measurements over the sea ice of the Weddell Sea by three AWS buoys for one year showed small biases for temperature around 1 K and for wind speed of 1 m s−1. Comparisons of radio soundings showed a model bias around zero and a RMSE of 1–2 K for temperature and of 3–4 m s−1 for wind speed. The comparison of CCLM simulations at resolutions down to 1 km with wind data from Doppler Lidar measurements during December 2015 and January 2016 yielded almost no bias in wind speed and RMSE of ca. 2 m s−1. Overall CCLM shows a good representation of temperature and wind for the Weddell Sea region. These results encourage for further studies using CCLM data for the regional climate in the Antarctic at high resolutions and the study of atmosphere-ice-ocean interactions processes.

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Classification of Turbulent Mixing Driven Sources in Marine Atmospheric Boundary Layer With Use of Shipborne Coherent Doppler Lidar Observations

Wang,

Dai,

et al. 2023

JGR Atmospheres

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A method to identify the turbulent mixing sources within the marine atmospheric boundary layer (MABL) based on the shipborne coherent Doppler lidar measurements is introduced in this paper. Combining with the coherent Doppler lidar Signal‐to‐Noise Ratio (SNR), vertical velocity skewness, turbulence kinetic energy dissipation rate (TKEDR) and wind shear intensity, the categories of turbulent mixing sources and the specific turbulent mixing sources could be determined. The method is applied into two voyages of MABL observation during May 2021 in the South China Sea and during April 2022 in the Bohai Sea and Yellow Sea. The turbulent mixing processes are captured and the classification of the turbulence driven sources within the MABL are realized. The temporal‐spatial evolution characteristics of the turbulence mixing process in the MABL are investigated under different weather conditions containing clear‐sky day, cloudy‐sky day and sea‐fog day. The convective mixing process is recognized in the daytime of the clear‐sky day and the intermittent cloud‐driven turbulence exists below the cloud layer. Additionally, the turbulent mixing is weak which could not act as the main driven source during the sea‐fog day. Furthermore, the dominant turbulence scale analyses of different turbulence sources are conducted based on the cospectra of the vertical velocity and the horizontal speed measurements. The turbulence parameters of different turbulence sources are statistical analysed and compared in different sea areas.The classification method has the broad application prospects on the study of the air‐sea interaction.

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Analysis of the performance of a ship-borne scanning wind lidar in the Arctic and Antarctic

Cited by 9 publications

References 20 publications

Verification of the regional atmospheric model CCLM v5.0 with conventional data and lidar measurements in Antarctica

Verification of the regional atmospheric model CCLM v5.0 with conventional data and lidar measurements in Antarctica

Verification of the regional atmospheric model CCLM v5.0 with conventional data and Lidar measurements in Antarctica

Classification of Turbulent Mixing Driven Sources in Marine Atmospheric Boundary Layer With Use of Shipborne Coherent Doppler Lidar Observations

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