COSMIC Radio Occultation Processing: Cross-Center Comparison and Validation

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 operatorbased 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.

The Radio Occultation Processing Package, ROPP

“…OCC has been shown to generate refractivities that are in excellent agreement (less than 0.2 % systematic difference) with those calculated at UCAR and by forward modelling ECMWF analyses (http: //www.ecmwf.int; Gorbunov et al, 2011). ROPP PP provides routines to compute L1 and L2 bending angles from excess phase data by geometrical optics and wave optics methods.…”

Validation of refractivity profiles derived from GRAS raw-sampling data

“…The profile-to-profile intercomparison with other teams participating in the GRAS RS study is on-going. Cross-center comparison studies (Marquardt et al, 2010;Gorbunov et al, 2011b;Zus et al, 2011) will be beneficial to study uncertainties in different processing software packages.…”

On the comparisons of tropical relative humidity in the lower and middle troposphere among COSMIC radio occultations and MERRA and ECMWF data sets

“…Kursinski et al (1997), Rocken et al (1997), Kursinski and Hajj (2001), and Colard and Healey (2003) described the retrieval process of humidity profiles from GPSRO observations. Steiner et al (1999), Gorbunov and Kornblueh (2001), Divakarla et al (2006), Ho et al (2007), Chou et al (2009), Ho et al (2010, Sun et al (2010), Gorbunov et al (2011), Kishore et al (2011), Wang et al (2013, and Vergados et al (2014) validated the GPSRO-based humidity retrievals against reanalyses, radiosondes, and satellite observations, while recently Kursinski and Gebhardt (2014) reported an innovative technique to further reduce and eliminate retrieval biases in the middle-troposphere humidity products.…”