A 1D Var Retrieval of Relative Humidity Using the ERA5 Dataset for the Assimilation of Raman Lidar Measurements

Gamage, S. Mahagammulla; Sica, R. J.; Martucci, Giovanni; Haefele, Alexander

doi:10.1175/jtech-d-19-0170.1

Cited by 8 publications

(4 citation statements)

References 27 publications

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“…In order to set the latter, a relative humidity profile with respect to water RH(η), depending on the model level η and the surface relative humidity RH 0 , has been defined. It is inspired from the ERA-Interim (Romps, 2014) and ERA5 (Gamage et al, 2020) average relative humidity profile. The profile, as shown in Figure 1, has a maximum value of the RH 0 at the surface, above which it decreases to 70 % RH 0 at 800hPa.…”

Section: Moisture Initialisationmentioning

confidence: 99%

Analytical and adaptable initial conditions for moist baroclinic waves in a global hydrostatic model

Bouvier

Broek

Ekblom

et al. 2023

Preprint

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Abstract. This article presents a description of an analytical, stable and flexible initial background state for moist baroclinic wave simulation on an aquaplanet in order to test dynamical core of numerical weather prediction models and study the dynamics and evolution of extra-tropical cyclones. The initial background state is derived from an analytical zonal wind speed field, or jet structure, and the hydrostatic primitive equations for moist adiabatic and frictionless flow in spherical coordinates. A baroclinic wave can develop only if a unbalanced perturbation is added to the zonal wind speed field. The implementation of this baroclinic wave simulation have been done on the Open Integrated Forecasting System (OpenIFS) cy43r3, a global numerical weather prediction model developed by the European Centre for Medium-range Weather Forecasts. In total, seven parameters can be used to control the generation of the initial background state and hence the development of the baroclinic waves in the OpenIFS configuration file: the jet's width, the jet's height, the maximum zonal mean wind speed of the jet, the horizontal mean of the surface virtual temperature, the surface relative humidity, the lapse rate and the surface roughness. Nine dry and nine moist initial background states have been generated to test their stability without perturbations. The meteorological stability of the initial state is investigated by examining the spatial distributions of the equivalent potential temperature, the absolute vorticity and the Brunt-Väisälä frequency. Moreover, the Root-Mean-Squared-Error (RMSE) of the zonal wind speed has been computed to assess their numerical stability. Finally, six of these moist initial initial background state have been used with an unbalanced perturbation to ensure that the baroclinic lifecycles developing are physically realistic. The resulting baroclinic wave is shown to be sensitive to the jet's width. This configuration for baroclinic wave simulations will be used to create large baroclinic lifecycles ensemble to study how extra-tropical cyclones may evolve in the future.

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Section: Moisture Initialisationmentioning

confidence: 99%

Analytical and adaptable initial conditions for moist baroclinic waves in a global hydrostatic model

Bouvier

Broek

Ekblom

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…In this paper, the Monte Carlo method was employed based on the random generation of input parameters by a Gaussian distribution with the original values and errors as mean and standard deviation, respectively. The error of RH was considered as about 10 % according to the uncertainty from ERA5 (Gamage et al, 2020). Additionally, MPEs of the fine volume concentration and extinction coefficient mentioned in Sect.…”

Section: Uncertainty Assessment Of Component Estimationmentioning

confidence: 99%

Algorithm for vertical distribution of boundary layer aerosol components in remote-sensing data

Wang

Yang²,

Wang³

et al. 2022

Atmos. Meas. Tech.

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Abstract. The vertical distribution of atmospheric aerosol components is vital to the estimation of radiative forcing and the catalysis of atmospheric photochemical processes. Based on the synergy of ground-based lidar and sun-photometer in Generalized Aerosol Retrieval from Radiometer and Lidar Combined data (GARRLiC), this paper developed a new algorithm to get the vertical mass concentration profiles of fine-mode aerosol components for the first time. Retrieval of aerosol properties was achieved based on the sky radiance at multiple scatter angles, total optical depth (TOD) at 440, 675, 870, and 1020 nm, and lidar signals at 532 and 1064 nm. In addition, the internal mixing model and normalized volume size distribution (VSD) model were established according to the absorption and water solubility of the aerosol components, to separate the profiles of black carbon (BC), water-insoluble organic matter (WIOM), water-soluble organic matter (WSOM), ammonium nitrate-like (AN), and fine aerosol water (AW) content. Results showed a reasonable vertical distribution of aerosol components compared with in situ observations and reanalysis data. The estimated and observed BC concentrations matched well with a correlation coefficient up to 0.91, while there was an evident overestimation of organic matter (OM = WIOM + WSOM, NMB = 0.98). Moreover, the retrieved AN concentrations were closer to the simulated results (R = 0.85), especially in polluted conditions. The BC and OM correlations were relatively weaker, with a correlation coefficient of ∼ 0.5. Besides, the uncertainties caused by the input parameters (i.e., relative humidity (RH), volume concentration, and extinction coefficients) were assessed using the Monte Carlo method. The AN and AW had smaller uncertainties at higher RH. Herein, the proposed algorithm was also applied to remote-sensing measurements in Beijing with two typical cases. In the clean condition with low RH, there were comparable AN and WIOM, but peaking at different altitudes. On the other hand, in the polluted case, AN was dominant and the maximum mass concentration occurred near the surface. We expected that the algorithm could provide a new idea for lidar inversion and promote the development of aerosol component profiles.

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“…In this paper, Monte Carlo method was employed based on the random generation of input parameters by a Gaussian distribution with the original values and errors as mean and standard deviation, respectively. The error of RH was considered as about 10 % according to the uncertainty from ERA5 (Gamage et al, 2020).…”

Section: Uncertainty Assessment Of Components Estimationmentioning

confidence: 99%

Algorithm for vertical distribution of boundary layer aerosol components in remote sensing data

Wang

Yang

Wang

et al. 2022

Preprint

View full text Add to dashboard Cite

Abstract. The vertical distribution of atmospheric aerosol components is vital to the estimation of radiation forcing and the catalysis of atmospheric photochemical processes. Based on the synergy of ground-based lidar and sun-photometer, this paper developed a new algorithm to get the vertical mass concentration profiles of fine aerosol components for the first time. The sky radiance at multiple scatter angles, the total optical depth (TOD) at 440, 675, 870, and 1020 nm, and the lidar signals at 532 nm and 1064 nm were applied to retrieve the aerosol properties. Besides, the internal mixing model and normalized volume size distribution model were constructed, according to the absorption and water-solubility of aerosol components, to separate the profiles of black carbon (BC), water-insoluble organic matter (WIOM), water-soluble organic matter (WSOM), ammonium nitrate-like (AN), and fine aerosol water content (AW). The results showed a reasonable vertical distribution of aerosol components compared with in situ observations and reanalysis data. The estimated and observed BC concentration matched well with a correlation coefficient up to 0.91, while there was an evident overestimation of OM (NMB=0.98). And the retrieved AN concentrations were closer to the simulated results (the correlation coefficient of 0.85), especially in the polluted condition. The correlations of BC and OM were weaker relatively, with a correlation coefficient of about 0.5. Besides, the uncertainties caused by input parameters (i.e. RH, volume concentration, and extinction coefficients) were assessed by Monte Carlo method. AN and AW had smaller uncertainties at higher RH. In this paper, the algorithm was also applied to the remote sensing measurements of Beijing and two typical cases were presented. Under the clean condition with low RH, there were comparable AN and WIOM but peaking at different altitudes. While in the polluted case, AN was dominant and the maximum mass concentration occurred near the surface. We expected the algorithm can provide a new idea for lidar inversion and promote the development of aerosol components profiles.

show abstract

A 1D Var Retrieval of Relative Humidity Using the ERA5 Dataset for the Assimilation of Raman Lidar Measurements

Cited by 8 publications

References 27 publications

Analytical and adaptable initial conditions for moist baroclinic waves in a global hydrostatic model

Analytical and adaptable initial conditions for moist baroclinic waves in a global hydrostatic model

Algorithm for vertical distribution of boundary layer aerosol components in remote-sensing data

Algorithm for vertical distribution of boundary layer aerosol components in remote sensing data

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