scholarly journals High-resolution temperature profiles (HRTP) retrieved from bi-chromatic stellar scintillation measurements by GOMOS/Envisat

2018 ◽  
Author(s):  
Viktoria F. Sofieva ◽  
Francis Dalaudier ◽  
Alain Hauchecorne ◽  
Valery Kan
Keyword(s):  
High Resolution ◽  
Gravity Wave ◽  
Temperature Fluctuations ◽  
Radiosonde Data ◽  
Retrieval Algorithm ◽  
Small Scale ◽  
Temperature Profiles ◽  
Vertical Resolution ◽  
Inversion Algorithm ◽  
Stellar Scintillation

Abstract. In this paper, we describe the inversion algorithm for retrievals of high vertical resolution temperature profiles using bi-chromatic stellar scintillation measurements in the occultation geometry. This retrieval algorithm has been improved with respect to nominal ESA processing and applied to the measurements by Global Ozone Monitoring by Occultation of Stars (GOMOS) operated on board Envisat in 2002–2012. The retrieval method exploits the chromatic refraction in the Earth's atmosphere. The bi-chromatic scintillations allow the determination of the refractive angle, which is proportional to the time delay between the photometer signals. The paper discusses the basic principle and detailed inversion algorithm for reconstruction of high resolution density, pressure and temperature profiles (HRTP) in the stratosphere from scintillation measurements. The HRTP profiles are retrieved with very good vertical resolution of ~200 m and high accuracy of ~1–3 K for altitudes of 15–32 km and with a global coverage. The best accuracy is achieved in in-orbital-plane occultations, and the accuracy weakly depends on star brightness. The whole GOMOS dataset has been processed with the improved HRTP inversion algorithm using the FMI's Scientific Processor; and the dataset (HRTP FSP v1) is in open access. The validation of small-scale fluctuations in the retrieved HRTP profiles is performed via comparison of vertical wavenumber spectra of temperature fluctuations in HRTP and in collocated radiosonde data. We found that the spectral features of temperature fluctuations are very similar in HRTP and collocated radiosonde temperature profiles. HRTP can be assimilated into atmospheric models, used in studies of stratospheric clouds and in analysis of internal gravity waves activity. As an example of geophysical applications, gravity wave potential energy has been estimated using the HRTP dataset. The obtained spatio-temporal distributions of gravity wave energy are in good agreement with the previous analyses using other measurements.

scholarly journals High-resolution temperature profiles retrieved from bichromatic stellar scintillation measurements by GOMOS/Envisat

2019 ◽  
Vol 12 (1) ◽  
pp. 585-598 ◽  
Author(s):  
Viktoria F. Sofieva ◽  
Francis Dalaudier ◽  
Alain Hauchecorne ◽  
Valery Kan
Keyword(s):  
High Resolution ◽  
Gravity Wave ◽  
Temperature Fluctuations ◽  
Radiosonde Data ◽  
Retrieval Algorithm ◽  
Small Scale ◽  
Temperature Profiles ◽  
Vertical Resolution ◽  
Inversion Algorithm ◽  
Stellar Scintillation

Abstract. In this paper, we describe the inversion algorithm for retrievals of high vertical resolution temperature profiles (HRTPs) using bichromatic stellar scintillation measurements in the occultation geometry. This retrieval algorithm has been improved with respect to nominal ESA processing and applied to the measurements by Global Ozone Monitoring by Occultation of Stars (GOMOS) operated on board Envisat in 2002–2012. The retrieval method exploits the chromatic refraction in the Earth's atmosphere. The bichromatic scintillations allow the determination of the refractive angle, which is proportional to the time delay between the photometer signals. The paper discusses the basic principle and detailed inversion algorithm for reconstruction of high-resolution density, pressure and temperature profiles in the stratosphere from scintillation measurements. The HRTPs are retrieved with a very good vertical resolution of ∼200 m and high precision (random uncertainty) of ∼1–3 K for altitudes of 15–32 km and with a global coverage. The best accuracy is achieved for in-orbital-plane occultations, and the precision weakly depends on star brightness. The whole GOMOS dataset has been processed with the improved HRTP inversion algorithm using the FMI's scientific processor; and the dataset (HRTP FSP v1) is in open access. The validation of small-scale fluctuations in the retrieved HRTPs is performed via comparison of vertical wavenumber spectra of temperature fluctuations in HRTPs and in collocated radiosonde data. We found that the spectral features of temperature fluctuations are very similar in HRTPs and collocated radiosonde temperature profiles. HRTPs can be assimilated into atmospheric models, used in studies of stratospheric clouds and used for the analysis of internal gravity waves' activity. As an example of geophysical applications, gravity wave potential energy has been estimated using the HRTP dataset. The obtained spatiotemporal distributions of gravity wave energy are in good agreement with the previous analyses using other measurements.

scholarly journals Analysis of vertical wave number spectrum of atmospheric gravity waves in the stratosphere using COSMIC GPS radio occultation data

2011 ◽  
Vol 4 (8) ◽  
pp. 1627-1636 ◽  
Author(s):  
T. Tsuda ◽  
X. Lin ◽  
H. Hayashi ◽  
Keyword(s):  
Gravity Waves ◽  
Radio Occultation ◽  
Temperature Fluctuations ◽  
Ground Level ◽  
Wave Number ◽  
Radiosonde Data ◽  
Small Scale ◽  
Vertical Resolution ◽  
Full Spectrum ◽  
Gps Radio Occultation

Abstract. GPS radio occultation (RO) is characterized by high accuracy and excellent height resolution, which has great advantages in analyzing atmospheric structures including small-scale vertical fluctuations. The vertical resolution of the geometrical optics (GO) method in the stratosphere is about 1.5 km due to Fresnel radius limitations, but full spectrum inversion (FSI) can provide superior resolutions. We applied FSI to COSMIC GPS-RO profiles from ground level up to 30 km altitude, although basic retrieval at UCAR/CDAAC sets the sewing height from GO to FSI below the tropopause. We validated FSI temperature profiles with routine high-resolution radiosonde data in Malaysia and North America collected within 400 km and about 30 min of the GPS RO events. The average discrepancy at 10–30 km altitude was less than 0.5 K, and the bias was equivalent with the GO results. Using the FSI results, we analyzed the vertical wave number spectrum of normalized temperature fluctuations in the stratosphere at 20–30 km altitude, which exhibits good consistency with the model spectra of saturated gravity waves. We investigated the white noise floor that tends to appear at high wave numbers, and the substantial vertical resolution of the FSI method was estimated as about 100–200 m in the lower stratosphere. We also examined a criterion for the upper limit of the FSI profiles, beyond which bending angle perturbations due to system noises, etc., could exceed atmospheric excess phase fluctuations. We found that the FSI profiles can be used up to about 28 km in studies of temperature fluctuations with vertical wave lengths as short as 0.5 km.

scholarly journals Analysis of vertical wave number spectrum of atmospheric gravity waves in the stratosphere using COSMIC GPS radio occultation data

2011 ◽  
Vol 4 (2) ◽  
pp. 2071-2097
Author(s):  
T. Tsuda ◽  
X. Lin ◽  
H. Hayashi ◽  
Keyword(s):  
Gravity Waves ◽  
Radio Occultation ◽  
Temperature Fluctuations ◽  
Ground Level ◽  
Wave Number ◽  
Radiosonde Data ◽  
Small Scale ◽  
Vertical Resolution ◽  
Full Spectrum ◽  
Gps Radio Occultation

Abstract. GPS radio occultation (RO) is characterized by high accuracy and excellent height resolution, which has great advantages in analyzing atmospheric structures including small-scale vertical fluctuations. The vertical resolution of the geometrical optics (GO) method in the stratosphere is about 1.5 km due to Fresnel radius limitations, but full spectrum inversion (FSI) can provide superior resolutions. We applied FSI to COSMIC GPS-RO profiles from ground level up to 30 km altitude, although basic retrieval at UCAR/CDAAC sets the sewing height from GO to FSI below the tropopause. We validated FSI temperature profiles with routine high-resolution radiosonde data in Malaysia and North America collected within 400 km and about 30 min of the GPS RO events. The average discrepancy at 10–30 km altitude was less than 0.5 K, and the bias was equivalent with the GO results. Using the FSI results, we analyzed the vertical wave number spectrum of normalized temperature fluctuations in the stratosphere at 20–30 km altitude, which exhibits good consistency with the model spectra of saturated gravity waves. We investigated the white noise floor that tends to appear at high wave numbers, and the substantial vertical resolution of the FSI method was estimated as about 100–200 m in the lower stratosphere. We also examined a criterion for the upper limit of the FSI profiles, beyond which bending angle perturbations due to system noises, etc, could exceed atmospheric excess phase fluctuations. We found that the FSI profiles can be used up to about 28 km in studies of temperature fluctuations with vertical wave lengths as short as 0.5 km.

scholarly journals Dependence of Model Energy Spectra on Vertical Resolution

2016 ◽  
Vol 144 (4) ◽  
pp. 1407-1421 ◽  
Author(s):  
Michael L. Waite
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Vertical Mixing ◽  
Energy Spectra ◽  
Small Scale ◽  
Rossby Number ◽  
Vertical Resolution ◽  
Wide Range ◽  
Qualitative Shape ◽  
Vertical Grid

Abstract Many high-resolution atmospheric models can reproduce the qualitative shape of the atmospheric kinetic energy spectrum, which has a power-law slope of −3 at large horizontal scales that shallows to approximately −5/3 in the mesoscale. This paper investigates the possible dependence of model energy spectra on the vertical grid resolution. Idealized simulations forced by relaxation to a baroclinically unstable jet are performed for a wide range of vertical grid spacings Δz. Energy spectra are converged for Δz 200 m but are very sensitive to resolution with 500 m ≤ Δz ≤ 2 km. The nature of this sensitivity depends on the vertical mixing scheme. With no vertical mixing or with weak, stability-dependent mixing, the mesoscale spectra are artificially amplified by low resolution: they are shallower and extend to larger scales than in the converged simulations. By contrast, vertical hyperviscosity with fixed grid-scale damping rate has the opposite effect: underresolved spectra are spuriously steepened. High-resolution spectra are converged except for the stability-dependent mixing case, which are damped by excessive mixing due to enhanced shear over a wide range of horizontal scales. It is shown that converged spectra require resolution of all vertical scales associated with the resolved horizontal structures: these include quasigeostrophic scales for large-scale motions with small Rossby number and the buoyancy scale for small-scale motions at large Rossby number. It is speculated that some model energy spectra may be contaminated by low vertical resolution, and it is recommended that vertical-resolution sensitivity tests always be performed.

scholarly journals Evaluation of a Support Vector Machine–Based Single-Doppler Wind Retrieval Algorithm

2017 ◽  
Vol 34 (8) ◽  
pp. 1749-1761 ◽  
Author(s):  
Nan Li ◽  
Ming Wei ◽  
Yongjiang Yu ◽  
Wengang Zhang
Keyword(s):  
Support Vector Machine ◽  
High Resolution ◽  
Condition Number ◽  
Condition Numbers ◽  
Retrieval Algorithm ◽  
Support Vector ◽  
Small Scale ◽  
Wind Retrieval ◽  
Original Algorithm ◽  
Retrieval Accuracy

AbstractWind retrieval algorithms are required for Doppler weather radars. In this article, a new wind retrieval algorithm of single-Doppler radar with a support vector machine (SVM) is analyzed and compared with the original algorithm with the least squares technique. Through an analysis of coefficient matrices of equations corresponding to the optimization problems for the two algorithms, the new algorithm, which contains a proper penalization parameter, is found to effectively reduce the condition numbers of the matrices and thus has the ability to acquire accurate results, and the smaller the analysis volume is, the smaller the condition number of the matrix. This characteristic makes the new algorithm suitable to retrieve mesoscale and small-scale and high-resolution wind fields. Afterward, the two algorithms are applied to retrieval experiments to implement a comparison and a discussion. The results show that the penalization parameter cannot be too small, otherwise it may cause a large condition number; it cannot be too large either, otherwise it may change the properties of equations, leading to retrieved wind direction along the radial direction. Compared with the original algorithm, the new algorithm has definite superiority with the appropriate penalization parameters for small analysis volumes. When the suggested small analysis volume dimensions and penalization parameter values are adopted, the retrieval accuracy can be improved by 10 times more than the traditional method. As a result, the new algorithm has the capability to analyze the dynamical structures of severe weather, which needs high-resolution retrieval, and the potential for quantitative applications such as the assimilation in numerical models, but the retrieval accuracy needs to be further improved in the future.

scholarly journals A Comparison between Gravity Wave Momentum Fluxes in Observations and Climate Models

2013 ◽  
Vol 26 (17) ◽  
pp. 6383-6405 ◽  
Author(s):  
Marvin A. Geller ◽  
M. Joan Alexander ◽  
Peter T. Love ◽  
Julio Bacmeister ◽  
Manfred Ern ◽  
...  
Keyword(s):  
High Resolution ◽  
Gravity Wave ◽  
Gravity Waves ◽  
Climate Models ◽  
Radiosonde Data ◽  
Wave Source ◽  
Wide Range ◽  
Momentum Fluxes ◽  
High Resolution Models ◽  
Wave Momentum

Abstract For the first time, a formal comparison is made between gravity wave momentum fluxes in models and those derived from observations. Although gravity waves occur over a wide range of spatial and temporal scales, the focus of this paper is on scales that are being parameterized in present climate models, sub-1000-km scales. Only observational methods that permit derivation of gravity wave momentum fluxes over large geographical areas are discussed, and these are from satellite temperature measurements, constant-density long-duration balloons, and high-vertical-resolution radiosonde data. The models discussed include two high-resolution models in which gravity waves are explicitly modeled, Kanto and the Community Atmosphere Model, version 5 (CAM5), and three climate models containing gravity wave parameterizations, MAECHAM5, Hadley Centre Global Environmental Model 3 (HadGEM3), and the Goddard Institute for Space Studies (GISS) model. Measurements generally show similar flux magnitudes as in models, except that the fluxes derived from satellite measurements fall off more rapidly with height. This is likely due to limitations on the observable range of wavelengths, although other factors may contribute. When one accounts for this more rapid fall off, the geographical distribution of the fluxes from observations and models compare reasonably well, except for certain features that depend on the specification of the nonorographic gravity wave source functions in the climate models. For instance, both the observed fluxes and those in the high-resolution models are very small at summer high latitudes, but this is not the case for some of the climate models. This comparison between gravity wave fluxes from climate models, high-resolution models, and fluxes derived from observations indicates that such efforts offer a promising path toward improving specifications of gravity wave sources in climate models.

scholarly journals Bayesian Model Verification of NWP Ensemble Forecasts

2013 ◽  
Vol 141 (1) ◽  
pp. 375-387 ◽  
Author(s):  
Andreas Röpnack ◽  
Andreas Hense ◽  
Christoph Gebhardt ◽  
Detlev Majewski
Keyword(s):  
Bayesian Approach ◽  
Horizontal Resolution ◽  
Model Verification ◽  
Radiosonde Data ◽  
Convective Precipitation ◽  
Ensemble Prediction ◽  
Small Scale ◽  
Observation Error ◽  
Temperature Profiles ◽  
The Bayesian Approach

Abstract Forecasts of convective precipitation have large uncertainties. To consider the forecast uncertainties of convection-permitting models, a convection-permitting ensemble prediction system (EPS) based on the Consortium for Small-scale Modeling (COSMO) model with a horizontal resolution of 2.8 km covering all of Germany is being developed by the Deutscher Wetterdienst (DWD). The deterministic model is named COSMO-DE. Vertical structures of temperature and humidity affect the potential for convective instability. For verification of vertical model profiles, radiosonde data are used. However, the observed state is uncertain by itself because of the well-known limits in observing the atmosphere. In this work the authors use a probabilistic approach, which considers the observation error as well as the model uncertainty to validate multidimensional state vectors (e.g., temperature profiles) of the COSMO-DE-EPS and of two mesoscale ensembles with horizontal resolution of 10 km and parameterized convection. The mesoscale ensembles are the COSMO short-range EPS (COSMO-SREPS) and the COSMO limited-area EPS (COSMO-LEPS). The approach is based on Bayesian statistics and allows for both verification and comparison of ensembles. The investigation period comprises August 2007 for a comparison of the COSMO-DE-EPS with the COSMO-SREPS. A period of 5 days in July 2007 is used to demonstrate the potential of the Bayesian approach for verification by evaluating the COSMO-SREPS and COSMO-LEPS against COSMO-EU analyses. Based on the Bayesian approach, it is shown that the temperature profiles modeled by the COSMO-DE-EPS are more consistent with the observed profiles than those of COSMO-SREPS.

scholarly journals Influence of convection on the upper tropospheric O<sub>3</sub> and NO<sub>x</sub> budget in southeastern China

2021 ◽  
Author(s):  
Xin Zhang ◽  
Yan Yin ◽  
Ronald van der A ◽  
Henk Eskes ◽  
Jos van Geffen ◽  
...  
Keyword(s):  
High Resolution ◽  
Air Pollutants ◽  
Production Efficiency ◽  
Retrieval Algorithm ◽  
Small Scale ◽  
Southeastern China ◽  
Upper Troposphere ◽  
Mixing Ratios ◽  
Sensitivity Tests ◽  
Strong Convection

Abstract. Thunderstorms can significantly influence the air composition via strong updraft and lightning nitrogen oxides (LNOx). In this study, the ozonesondes and TROPOMI nitrogen dioxide (NO2) observations for two cases are combined with model to investigate the effects of typical strong convection on vertical redistribution of air pollutants in Nanjing, southeastern China. The ozonesonde observations show higher O3 and water vapor mixing ratios in the upper troposphere (UT) after convection, indicating the strong updraft transporting lower-level airmass into the UT, and the possible downward O3-rich air near the top of UT over the convective period. During the whole convection life cycle, the UT O3 production is driven by the chemistry (> 87 %) and reduced by the LNOx (−40 %). Sensitivity tests demonstrate that neglecting LNOx in standard TROPOMI NO2 products causes overestimated air mass factors over fresh lightning regions and the opposite for outflow and aged lightning areas. Therefore, a new high-resolution retrieval algorithm is applied to estimate the LNOx production efficiency. Our work shows the demand for high-resolution modeling and satellite observations on LNOx emissions of both active and dissipated convection, especially small-scale storms.

scholarly journals Intraseasonal to interannual variability of Kelvin wave momentum fluxes as derived from high-resolution radiosonde data

2017 ◽  
Author(s):  
Jeremiah P. Sjoberg ◽  
Thomas Birner ◽  
Richard H. Johnson
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Momentum Flux ◽  
Radiosonde Data ◽  
Boreal Summer ◽  
Vertical Resolution ◽  
Madden Julian Oscillation ◽  
Kelvin Wave ◽  
Momentum Fluxes ◽  
Wave Momentum

Abstract. Observational estimates of Kelvin wave momentum fluxes in the tropical lower stratosphere remains challenging. Here we extend a method based on linear wave theory to estimate time series of these momentum fluxes from high-resolution radiosonde data. Testing the sensitivity to vertical resolution, our estimated momentum fluxes are found to be most sensitive to vertical resolution greater than 1 km, largely due to overestimation of the vertical wavelength. Estimates of momentum fluxes derived from reanalyses and coarse-resolution satellite data are notably larger. Daily time series are produced for sounding sites operated by the U.S. Department of Energy (DOE) and from the recent Dynamics of the Madden-Julian Oscillation (DYNAMO) field campaign. Our momentum flux estimates are found to be robust to different data sources and processing, and in quantitative agreement with estimates from prior studies. Climatological analysis is performed over the selected 11 year span of data from the ARM sites. Analyses for the available 11-year span of data reveal the expected seasonal cycle of momentum flux maxima in boreal winter and minima in boreal summer and variability associated with the quasi-biennial oscillation (QBO) of maxima during easterly phase and minima during westerly phase. Analysis of Madden-Julian Oscillation (MJO) active periods suggests that the MJO provides a nontrivial increase in lowermost stratospheric momentum fluxes, though statistical significance is not found due to the small number of events observed in the available time series.

scholarly journals Probabilistic description of ice-supersaturated layers in low resolution profiles of relative humidity

2010 ◽  
Vol 10 (2) ◽  
pp. 2357-2395 ◽  
Author(s):  
N. C. Dickson ◽  
K. M. Gierens ◽  
H. L. Rogers ◽  
R. L. Jones
Keyword(s):  
High Resolution ◽  
Relative Humidity ◽  
Climate Models ◽  
Numerical Models ◽  
Spatial Scales ◽  
Error Function ◽  
Global Distribution ◽  
Small Scale ◽  
Vertical Resolution ◽  
Average Relative Humidity

Abstract. The global observation, assimilation and prediction in numerical models of ice super-saturated (ISS) regions (ISSR) are crucial if the climate impact of aircraft condensations trails (contrails) is to be fully understood, and if, for example, contrail formation is to be avoided through aircraft operational measures. A robust assessment of the global distribution of ISSR will further this debate, and ISS event occurrence, frequency and spatial scales have recently attracted significant attention. The mean horizontal path length through ISSR as observed by MOZAIC aircraft is 150 km (±250 km). The average vertical thickness of ISS layers is 600–800 m (±575 m) but layers ranging from 25 m to 3000 m have been observed, with up to one third of ISS layers thought to be less than 100 m deep. Given their small scales compared to typical atmospheric model grid sizes, statistical representations of the spatial scales of ISSR are required, in both horizontal and vertical dimensions, if global occurrence of ISSR is to be adequately represented in climate models. This paper uses radiosonde launches made by the UK Meteorological Office, from the British Isles, Gibraltar, St. Helena and the Falkland Islands between January 2002 and December 2006, to investigate the probabilistic occurrence of ISSR. Specifically each radiosonde profile is divided into 50- and 100-hPa pressure layers, to emulate the coarse vertical resolution of some atmospheric models. Then the high resolution observations contained within each thick pressure layer are used to calculate an average relative humidity and an ISS fraction for each individual thick pressure layer. These relative humidity pressure layer descriptions are then linked through a probability function to produce an s-shaped curve describing the ISS fraction in any average relative humidity pressure layer. An empirical investigation has shown that this one curve is statistically valid for mid-latitude locations, irrespective of season and altitude, however, pressure layer depth is an important variable. Using this empirical understanding of the s-shaped relationship a mathematical model was developed to represent the ISS fraction within any arbitrary thick pressure layer. Here the statistical distributions of actual high resolution RHi observations in any thick pressure layer, along with an error function, are used to mathematically describe the s-shape. Two models were developed to represent both 50- and 100-hPa pressure layers with each reconstructing their respective s-shapes within 8–10% of the empirical curves. These new models can be used, to represent the small scale structures of ISS events, in modelled data where only low vertical resolution is available. This will be useful in understanding, and improving the global distribution, both observed and forecasted, of ice super-saturation.

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