The performance of Aeolus in heterogeneous atmospheric conditions using high-resolution radiosonde data

13Citations
Citations of this article
14Readers
Mendeley users who have this article in their library.

Abstract

The European Space Agency Aeolus mission aims to measure wind profiles from space. A major challenge is to retrieve high quality winds in heterogeneous atmospheric conditions, i.e. where both the atmospheric dynamics and optical properties vary strongly within the sampling volume. In preparation for launch we aim to quantify the expected error of retrieved winds from atmospheric heterogeneity, particularly in the vertical, and develop algorithms for wind error correction, as part of the level-2B processor (L2Bp). We demonstrate that high-resolution data from radiosondes provide valuable input to establish a database of collocated wind and atmospheric optics at 10 m vertical resolution to simulate atmospheric conditions along Aeolus' lines of sight. The database is used to simulate errors of Aeolus winds retrieved from the Mie and Rayleigh channel signals. The non-uniform distribution of molecules in the measurement bin introduces height assignment errors in Rayleigh channel winds up to 2.5% of the measurement bin size in the stratosphere which translates to 0.5 ms -1 bias for typical atmospheric conditions, if not corrected. The presence of cloud or aerosol layers in the measurement bin yields biases in Mie channel winds which cannot be easily corrected and mostly exceed the mission requirement of 0.4 m s -1. The collocated Rayleigh channel wind solution is generally preferred because of smaller biases, in particular for transparent cloud and aerosol layers with one-way transmission above 0.8. The results show that Aeolus L2Bp, under development, can be improved by the estimation of atmosphere optical properties to correct for height assignment errors and to identify wind solutions potentially detrimental when used in Numerical Weather Prediction. © 2014 Author(s).

Figures

  • Fig. 1. Left panel: molecular backscatter (dashed) and attenuated molecular backscatter, 2  i.e., the weight function (solid). Right panel: weight function first-order (D1, solid) and 3  second-order derivatives (D2 multiplied by 1000, dashed), see Eq. (8). 4 
  • Fig. 2. Aeolus Rayleigh channel height assignment error, H, for a particle-free 19  atmosphere and measurement bin size of 1000 m (dashed), 1500 m (solid) and 2000 m 20  (dash-dotted). The dotted line denotes H equal to zero. 21 
  • Fig. 3. Mie (left column) and Rayleigh (right column) wind error bias (ms-1) (top row), 2  standard deviation (ms-1) (middle row) and RMSE (ms-1) (bottom row) as a function 3  of the one-way transmission of the particle layer, c, and particle layer thickness z 4  (m). The measurement bin size l is set at 1000 m, the wind-shear is taken constant 5  over the bin with a value of 0.01 s-1. The black solid lines in the bottom panels denote 6  the Aeolus mission wind error bias requirement of 0.4 ms-1. 7 
  • Table 1. Aeolus height assignment error (m) and wind error (m s−1) (italic) RMSE for Mie (second column) and Rayleigh (third column) channel winds for typical atmospheric scenes with cloud and aerosol layers (first column). The numbers are based on Eqs. (13), (17) and (18), a 1000 m bin size and constant 0.01 s−1 wind shear over the bin.
  • Fig. 4 shows a typical example of the application of the Zhang2010 method to 1 
  • Table 2. Typical values of backscatter (second column) and extinction (third column) for various cloud types (first column) in the UV, visible and near-infrared part of the electromagnetic spectrum. The backscatter and extinction values are extracted from Vaughan et al. (1998). FW cumulus means fair weather cumulus, PSC means polar stratospheric cloud.
  • Fig. 5. Simulations of the growth factor (red), Eq. (20), and lidar ratio (sr) (blue), Eq. 10  (22), as a function of RH. 11 
  • Fig. 6. Mean location and thickness of all, low, middle, high and deep convective 4 

References Powered by Scopus

Analysis of atmospheric lidar observations: Some comments

1704Citations
N/AReaders
Get full text

Lidar inversion with variable backscatter/extinction ratios

758Citations
N/AReaders
Get full text

Improved Magnus form approximation of saturation vapor pressure

661Citations
N/AReaders
Get full text

Cited by Powered by Scopus

The impact of Aeolus wind retrievals on ECMWF global weather forecasts

105Citations
N/AReaders
Get full text

Technical note: First comparison of wind observations from ESA's satellite mission Aeolus and ground-based radar wind profiler network of China

65Citations
N/AReaders
Get full text

Airborne wind lidar observations over the North Atlantic in 2016 for the pre-launch validation of the satellite mission Aeolus

43Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Sun, X. J., Zhang, R. W., Marseille, G. J., Stoffelen, A., Donovan, D., Liu, L., & Zhao, J. (2014). The performance of Aeolus in heterogeneous atmospheric conditions using high-resolution radiosonde data. Atmospheric Measurement Techniques, 7(8), 2695–2717. https://doi.org/10.5194/amt-7-2695-2014

Readers over time

‘14‘15‘16‘17‘18‘20‘23‘2500.751.52.253

Readers' Seniority

Tooltip

Researcher 5

45%

PhD / Post grad / Masters / Doc 4

36%

Professor / Associate Prof. 2

18%

Readers' Discipline

Tooltip

Earth and Planetary Sciences 6

60%

Environmental Science 2

20%

Physics and Astronomy 1

10%

Engineering 1

10%

Save time finding and organizing research with Mendeley

Sign up for free
0