scholarly journals Comparative Assessment of COSMIC Radio Occultation Data and TIMED/SABER Satellite Data over China

2015 ◽  
Vol 54 (9) ◽  
pp. 1931-1943 ◽  
Author(s):  
Z. Q. Fan ◽  
Z. Sheng ◽  
H. Q. Shi ◽  
X. Yi ◽  
Y. Jiang ◽  
...  
Keyword(s):  
Radio Occultation ◽  
Satellite Observation ◽  
Comparative Assessment ◽  
Observation Data ◽  
Cosmic Radio ◽  
Temperature Deviation ◽  
Height Range ◽  
Broadband Emission ◽  
Occultation Data ◽  
Good Agreement

AbstractThe accuracy of temperature data from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) radio occultation and Thermosphere, Ionosphere, Mesosphere Energetics, and Dynamics/Sounding of the Atmosphere using Broadband Emission Radiometry (TIMED/SABER) observation over China is analyzed. High-resolution sounding data are used to assess the accuracy of these two kinds of satellite observation data at corresponding heights, and the two sets of data are compared in the height range 15–40 km. Very good agreement between radiosondes and COSMIC is observed in the stratosphere. In the troposphere COSMIC temperatures are about 2 K higher than the radiosonde observations. SABER detection at 15–32 km agrees well with a maximum warm bias of ~2 K around 25-km altitude. The comparison between SABER and COSMIC for altitudes 15–40 km also indicates higher temperatures of SABER in the lower stratosphere. The standard deviations are all greater than 2.5 K and are larger near 15 km and smallest at 20 km. The temperature deviation and in particular the standard deviation comparing SABER and COSMIC changes with altitude, season, and latitude. The results of this comparative assessment can offer a basis for research into the application of COSMIC and TIMED/SABER over China.

scholarly journals COSMIC Radio Occultation Processing: Cross-Center Comparison and Validation

2011 ◽  
Vol 28 (6) ◽  
pp. 737-751 ◽  
Author(s):  
Michael E. Gorbunov ◽  
A. V. Shmakov ◽  
Stephen S. Leroy ◽  
Kent B. Lauritsen
Keyword(s):  
Data Processing ◽  
Radio Occultation ◽  
Weather Prediction ◽  
Processing System ◽  
Fourier Integral ◽  
Small Scale ◽  
Cosmic Radio ◽  
Structural Uncertainty ◽  
Height Range ◽  
The Tropics

Abstract A radio occultation data processing system (OCC) was developed for numerical weather prediction and climate benchmarking. The data processing algorithms use the well-established Fourier integral operator–based methods, which ensure a high accuracy of retrievals. The system as a whole, or in its parts, is currently used at the Global Navigation Satellite System Receiver for Atmospheric Sounding (GRAS) Satellite Application Facility at the Danish Meteorological Institute, German Weather Service, and Wegener Center for Climate and Global Change. A statistical comparison of the inversions of the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) data by the system herein, University Corporation for Atmospheric Research (UCAR) data products, and ECMWF analyses is presented. Forty days of 2007 and 2008 were processed (from 5 days in the middle of each season) for the comparison of OCC and ECMWF, and 20 days of April 2009 were processed for the comparison of OCC, UCAR, and ECMWF. The OCC and UCAR inversions are consistent. For the tropics, the systematic difference between OCC and UCAR in the retrieved refractivity in the 2–30-km height interval does not exceed 0.1%; in particular, in the 9–25-km interval it does not exceed 0.03%. Below 1 km in the tropics the OCC – UCAR bias reaches 0.2%, which is explained by different cutoff and filtering schemes implemented in the two systems. The structure of the systematic OCC – ECMWF difference below 4 km changes in 2007, 2008, and 2009, which is explained by changes in the ECMWF analyses and assimilation schemes. It is estimated that in the 4–30-km height range the OCC occultation processing system obtains refractivities with a bias not exceeding 0.2%. The random error ranges from 0.3%–0.5% in the upper troposphere–lower stratosphere to about 2% below 4 km. The estimate of the bias below 4 km can currently be done with an accuracy of 0.5%–1% resulting from the structural uncertainty of the radio occultation (RO) data reflecting the insufficient knowledge of the atmospheric small-scale structures and instrumental errors. The OCC – UCAR bias is below the level of the structural uncertainty.

Impact of FORMOSAT-3/COSMIC radio occultation data on the prediction of super cyclone Gonu (2007): a case study

2013 ◽  
Vol 70 (2) ◽  
pp. 1209-1230 ◽  
Author(s):  
S. K. A. V. Prasad Rao Anisetty ◽  
Ching-Yuang Huang ◽  
Shu-Ya Chen
Keyword(s):  
Radio Occultation ◽  
Cosmic Radio ◽  
Super Cyclone ◽  
Occultation Data ◽  
Radio Occultation Data

scholarly journals The tropical tropopause layer in reanalysis data sets

2019 ◽  
Author(s):  
Susann Tegtmeier ◽  
James Anstey ◽  
Sean Davis ◽  
Rossana Dragani ◽  
Yayoi Harada ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Radio Occultation ◽  
Reanalysis Data ◽  
Radiosonde Data ◽  
Data Sets ◽  
Tropical Tropopause Layer ◽  
Tropical Tropopause ◽  
Occultation Data ◽  
Cold Point ◽  
Good Agreement

Abstract. The tropical tropopause layer (TTL) is the transition region between the well mixed, convective troposphere and the radiatively controlled stratosphere with air masses showing chemical and dynamical properties of both regions. The representation of the TTL in meteorological reanalysis data sets is important for studying the complex interactions of circulation, convection, trace gases, clouds and radiation. In this paper, we present the evaluation of TTL characteristics in reanalysis data sets that has been performed as part of the SPARC (Stratosphere– troposphere Processes and their Role in Climate) Reanalysis Intercomparison Project (S-RIP). The most recent atmospheric reanalysis data sets all provide realistic representations of the major characteristics of the temperature structure within the TTL. There is good agreement between reanalysis estimates of tropical mean temperatures and radio occultation data, with relatively small cold biases for most data sets. Temperatures at the cold point and lapse rate tropopause levels, on the other hand, show warm biases in reanalyses when compared to observations. This tropopause-level warm bias is related to the vertical resolution of the reanalysis data, with the smallest bias found for data sets with the highest vertical resolution around the tropopause. Differences of the cold point temperature maximise over equatorial Africa, related to Kelvin wave activity and associated disturbances in TTL temperatures. Model simulations of air mass transport into the stratosphere driven by reanalyses with a warm cold point bias can be expected to have too little dehydration. Interannual variability in reanalysis temperatures is best constrained in the upper TTL, with larger differences at levels below the cold point. The reanalyses reproduce the temperature responses to major dynamical and radiative signals such as volcanic eruptions and the QBO. Long-term reanalysis trends in temperature in the upper TTL show good agreement with trends derived from adjusted radiosonde data sets indicating significant stratospheric cooling of around −0.5 to −1 K/decade. At 100 hPa and the cold point, most of the reanalyses suggest small but significant cooling trends of −0.3 to −0.6 K/decade that are statistically consistent with trends based on the adjusted radiosonde data sets. Advances of the reanalysis and observational systems over the last decades have led to a clear improvement of the TTL reanalyses products over time. Biases of the temperature profiles and differences in interannual variability clearly decreased in 2006, when densely sampled radio occultation data started being assimilated by the reanalyses. While there is an overall good agreement, different reanalyses offer different advantages in the TTL such as realistic profile and cold point temperature, continuous time series or a realistic representation of signals of interannual variability. Their use in model simulations and in comparisons with climate model output should be tailored to their specific strengths and weaknesses.

scholarly journals A Characterization of the Quality of the Stratospheric Temperature Distributions from SABER based on Comparisons with COSMIC Data

2016 ◽  
Vol 33 (11) ◽  
pp. 2401-2413
Author(s):  
Z. Q. Fan ◽  
Z. Sheng ◽  
H. Q. Shi ◽  
X. H. Zhang ◽  
C. J. Zhou
Keyword(s):  
Atmospheric Temperature ◽  
Temperature Data ◽  
Detection Accuracy ◽  
Observation Data ◽  
Cosmic Radio ◽  
Broadband Emission ◽  
Stratospheric Temperature ◽  
Weather Situation ◽  
Important Field ◽  
Temperature Standard

AbstractGlobal stratospheric temperature measurement is an important field in the study of climate and weather. Dynamic and radiative coupling between the stratosphere and troposphere has been demonstrated in a number of studies over the past decade or so. However, studies of the stratosphere were hampered by a shortage of observation data before satellite technology was used in atmospheric sounding. Now, the data from the Thermosphere, Ionosphere, Mesosphere Energetics, and Dynamics/Sounding of the Atmosphere using Broadband Emission Radiometry (TIMED/SABER) observations make it easier to study the stratosphere. The precision and accuracy of TIMED/SABER satellite soundings in the stratosphere are analyzed in this paper using refraction error data and temperature data obtained from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) radio occultation sounding system and TIMED/SABER temperature data between April 2006 and December 2009. The results show high detection accuracy of TIMED/SABER satellite soundings in the stratosphere. The temperature standard deviation (STDV) errors of SABER are mostly in the range from of 0–3.5 K. At 40 km the STDV error is usually less than 1 K, which means that TIMED/SABER temperature is close to the real atmospheric temperature at this height. The distributions of SABER STDV errors follow a seasonal variation: they are approximately similar in the months that belong to the same season. As the weather situation is complicated and fickle, the distribution of SABER STDV errors is most complex at the equator. The results in this paper are consistent with previous research and can provide further support for application of the SABER’s temperature data.

Sign in / Sign up

Export Citation Format

Share Document