Comparative analysis of temperature profiles between atmosphere radiosonde data and ERA-interim reanalysis in Central Yakutia

2021 ◽  
Author(s):  
Michael S. Vasiliev ◽  
Boroyev N. Roman
Keyword(s):  
Comparative Analysis ◽  
Radiosonde Data ◽  
Temperature Profiles ◽  
Central Yakutia

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 GPS radio occultation with CHAMP and SAC-C: global monitoring of thermal tropopause parameters

2005 ◽  
Vol 5 (6) ◽  
pp. 1473-1488 ◽  
Author(s):  
T. Schmidt ◽  
S. Heise ◽  
J. Wickert ◽  
G. Beyerle ◽  
C. Reigber
Keyword(s):  
Standard Deviation ◽  
Potential Temperature ◽  
Weather Forecast ◽  
Lapse Rate ◽  
Radiosonde Data ◽  
Temperature Profiles ◽  
Quasi Biennial Oscillation ◽  
Data Set ◽  
Medium Range Weather Forecast ◽  
Satellite Missions

Abstract. In this study the global lapse-rate tropopause (LRT) pressure, temperature, potential temperature, and sharpness are discussed based on Global Positioning System (GPS) radio occultations (RO) from the German CHAMP (CHAllenging Minisatellite Payload) and the U.S.-Argentinian SAC-C (Satelite de Aplicaciones Cientificas-C) satellite missions. Results with respect to seasonal variations are compared with operational radiosonde data and ECMWF (European Centre for Medium-Range Weather Forecast) operational analyses. Results on the tropical quasi-biennial oscillation (QBO) are updated from an earlier study. CHAMP RO data are available continuously since May 2001 with on average 150 high resolution temperature profiles per day. SAC-C data are available for several periods in 2001 and 2002. In this study temperature data from CHAMP for the period May 2001-December 2004 and SAC-C data from August 2001-October 2001 and March 2002-November 2002 were used, respectively. The bias between GPS RO temperature profiles and radiosonde data was found to be less than 1.5K between 300 and 10hPa with a standard deviation of 2-3K. Between 200-20hPa the bias is even less than 0.5K (2K standard deviation). The mean deviations based on 167699 comparisons between CHAMP/SAC-C and ECMWF LRT parameters are (-2.1±37.1)hPa for pressure and (0.1±4.2)K for temperature. Comparisons of LRT pressure and temperature between CHAMP and nearby radiosondes (13230) resulted in (5.8±19.8)hPa and (-0.1±3.3)K, respectively. The comparisons between CHAMP/SAC-C and ECMWF show on average the largest differences in the vicinity of the jet streams with up to 700m in LRT altitude and 3K in LRT temperature, respectively. The CHAMP mission generates the first long-term RO data set. Other satellite missions will follow (GRACE, COSMIC, MetOp, TerraSAR-X, EQUARS) generating together some thousand temperature profiles daily.

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 An investigation of seasonal temperature trends in the Antarctic using CHAMP GPS radio occultation data

2011 ◽  
Vol 4 (1) ◽  
pp. 511-525
Author(s):  
K. Zhang ◽  
E. Fu ◽  
D. Silcock ◽  
Y. Kuleshov
Keyword(s):  
Radio Occultation ◽  
Space Mission ◽  
Radiosonde Data ◽  
Polar Regions ◽  
Temperature Profiles ◽  
Seasonal Temperature ◽  
Antarctic Region ◽  
Gps Radio Occultation ◽  
Temperature Trends ◽  
The Antarctic

Abstract. GPS radio occultation (RO) has been recognized as an alternative atmospheric upper air observation technique due to its distinct features and technological merits. This technique is best used for meteorological studies in remote and/or difficult-to-access areas such as the Polar Regions. The CHAllenging Minisatellite Payload (CHAMP) space mission has provided about eight years of high quality global coverage atmospheric profiles. This study first evaluates the accuracy of CHAMP RO retrieved temperature profiles in the Antarctic region by using radiosonde data. Different collocation criteria have been applied. The overall results show a good agreement between the two data sets. Utilizing seven completed years of CHAMP temperature profiles, the study then investigates seasonal temperature trends at 100 hPa and 500 hPa pressure levels in the Antarctic region. Detailed temperature variations in both spatial and temporal domains are revealed and their implications for climate change are discussed.

scholarly journals Assessments of the Retrieval of Atmospheric Profiles from GNSS Radio Occultation Data in Moist Tropospheric Conditions Using Radiosonde Data

2020 ◽  
Vol 12 (17) ◽  
pp. 2717
Author(s):  
Ying Li ◽  
Yunbin Yuan ◽  
Xiaoming Wang
Keyword(s):  
Radio Occultation ◽  
Satellite System ◽  
Specific Humidity ◽  
Radiosonde Data ◽  
Temperature Profiles ◽  
Standard Deviations ◽  
Mean Differences ◽  
June July ◽  
Global Navigation Satellite ◽  
Humidity Profiles

The Global Navigation Satellite System (GNSS) Radio Occultation (RO) retrieved temperature and specific humidity profiles can be widely used for weather and climate studies in troposphere. However, some aspects, such as the influences of background data on these retrieved moist profiles have not been discussed yet. This research evaluates RO retrieved temperature and specific humidity profiles from Wegener Center for Climate and Global Change (WEGC), Radio Occultation Meteorology Satellite Application Facility (ROM SAF) and University Corporation for Atmospheric Research (UCAR) Boulder RO processing centers by comparing with measurements from 10 selected Integrated Global Radiosonde Archive (IGRA) radiosonde stations in different latitudinal bands over 2007 to 2010. The background profiles used for producing their moist profiles are also compared with radiosonde. We found that RO retrieved temperature profiles from all centers agree well with radiosonde. Mean differences at polar, mid-latitudinal and tropical stations are varying within ±0.2 K, ±0.5 K and from −1 to 0.2 K, respectively, with standard deviations varying from 1 to 2 K for most pressure levels. The differences between RO retrieved and their background temperature profiles for WEGC are varying within ±0.5 K at altitudes above 300 hPa, and the differences for ROM SAF are within ±0.2 K, and that for UCAR are within 0.5 K at altitudes below 300 hPa. Both RO retrieved and background specific humidity above 600 hPa are found to have large positive differences (up to 40%) against most radiosonde measurements. Discrepancies of moist profiles among the three centers are overall minor at altitudes above 300 hPa for temperature and at altitudes above 700 hPa for specific humidity. Specific humidity standard deviations are largest at tropical stations in June July August months. It is expected that the outcome of this research can help readers to understand the characteristics of moist products among centers.

scholarly journals Comparison between Backscatter Lidar and Radiosonde Measurements of the Diurnal and Nocturnal Stratification in the Lower Troposphere

2007 ◽  
Vol 24 (7) ◽  
pp. 1231-1244 ◽  
Author(s):  
Giovanni Martucci ◽  
Renaud Matthey ◽  
Valentin Mitev ◽  
Hans Richner
Keyword(s):  
Mixed Layer Depth ◽  
Potential Temperature ◽  
Lower Troposphere ◽  
Correlation Coefficients ◽  
Residual Layer ◽  
Radiosonde Data ◽  
Aerosol Layer ◽  
Temperature Profiles ◽  
Layer Depth ◽  
Stable Conditions

Abstract A collection of boundary layer heights has been derived from measurements performed by a ground-based backscatter lidar in Neuchâtel, Switzerland (47.000°N, 6.967°E, 485 m ASL). A dataset of 98 cases have been collected during 2 yr. From these data, 61 are noon and 37 are midnight cases. The following two different schemes were used to retrieve the mixed layer depth and the height of the residual layer from the measurements: the gradient and variance methods. The obtained values were compared with those derived from the potential temperature profiles as computed from radiosonde data. For nocturnal cases, the height of the first aerosol layer above the residual layer was also compared to the corresponding potential temperature value. Correlation coefficients between lidar and radiosonde in both convective and stable conditions are between 0.88 and 0.97.

scholarly journals An investigation of atmospheric temperature profiles in the Australian region using collocated GPS radio occultation and radiosonde data

2011 ◽  
Vol 4 (10) ◽  
pp. 2087-2092 ◽  
Author(s):  
K. Zhang ◽  
E. Fu ◽  
D. Silcock ◽  
Y. Wang ◽  
Y. Kuleshov
Keyword(s):  
Standard Deviation ◽  
Radio Occultation ◽  
Atmospheric Temperature ◽  
Radiosonde Data ◽  
Data Sets ◽  
Temperature Profiles ◽  
Gps Radio Occultation ◽  
The One ◽  
Distinct Features ◽  
The Impact

Abstract. GPS radio occultation (RO) has been recognised as an alternative atmospheric upper air observation technique due to its distinct features and technological merits. The CHAllenging Minisatellite Payload (CHAMP) RO satellite and FORMOSAT-3/COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate) RO constellation together have provided about ten years of high quality global coverage RO atmospheric profiles. This technique is best used for meteorological studies in the difficult-to-access areas such as deserts and oceans. To better understand and use RO data, effective quality assessment using independent radiosonde data and its associated collocation criteria used in tempo-spatial domain are important. This study compares GPS RO retrieved temperature profiles from both CHAMP (between May 2001 and October 2008) and FORMOSAT-3/COSMIC (between July 2006 and December 2009) with radiosonde data from 38 Australian radiosonde stations. The overall results show a good agreement between the two data sets. Different collocation criteria within 3 h and 300 km between the profile pairs have been applied and the impact of these different collocation criteria on the evaluation results is found statistically insignificantly. The CHAMP and FORMOSAT-3/COSMIC temperature profiles have been evaluated at 16 different pressure levels and the differences between GPS RO and radiosonde at different levels of the atmosphere have been studied. The result shows that the mean temperature difference between radiosonde and CHAMP is 0.39 °C (with a standard deviation of 1.20 °C) and the one between radiosonde and FORMOSAT-3/COSMIC is 0.37 °C (with a standard deviation of 1.24 °C). Different collocation criteria have been applied and insignificant differences were identified amongst the results.

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 GPS radio occultation with CHAMP: monitoring of climate change parameters

2004 ◽  
Vol 4 (6) ◽  
pp. 7837-7857 ◽  
Author(s):  
T. Schmidt ◽  
S. Heise ◽  
J. Wickert ◽  
G. Beyerle ◽  
C. Reigber
Keyword(s):  
Water Vapor ◽  
Radio Occultation ◽  
Radiosonde Data ◽  
Temperature Profiles ◽  
Satellite Mission ◽  
Data Set ◽  
Gps Radio Occultation ◽  
Temperature Bias ◽  
Retrieval Scheme ◽  
Data Source

Abstract. The Global Positioning System (GPS) radio occultation (RO) technique offers a valuable new data source for global and continuous monitoring of the Earth's atmosphere. Refractivity, temperature and water vapor profiles with high accuracy and vertical resolution can be derived from this method. The GPS RO technique requires no calibration, is not affected by clouds, aerosols or precipitation, and the occultations are almost uniformly distributed over the globe. In this paper the potential of GPS RO for monitoring of the temperature is demonstrated exemplarily for the tropical upper troposphere and lower stratosphere (UTLS) region using GPS RO data from the German CHAMP (CHAllenging Minisatellite Payload) satellite mission. In addition, results of a 1DVAR retrieval scheme to derive tropospheric water vapor profiles using ECMWF data as background will be discussed. CHAMP RO data are available since 2001 with up to 200 high resolution temperature profiles per day. The temperature bias between CHAMP temperature profiles and radiosonde data as well as ECMWF analyses is less than 0.5 K between 300–30 hPa. The CHAMP RO experiment generates the first long-term RO data set. Other satellite missions will follow (GRACE, TerraSAR-X, COSMIC, METOP) generating some thousand profiles of atmospheric parameters daily.

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