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F. Harnisch, S. B. Healy, P. Bauer, and S. J. English


An ensemble of data assimilations (EDA) approach is used to estimate how the impact of Global Navigation Satellite System (GNSS) radio occultation (RO) measurements scales as a function of observation number in the ECMWF numerical weather prediction system. The EDA provides an estimate of the theoretical analysis and short-range forecast error statistics, based on the ensemble “spread,” which is the standard deviation of the ensemble members about the ensemble mean. This study is based on computing how the ensemble spread of various parameters changes as a function of the number of simulated GNSS RO observations. The impact from 2000 up to 128 000 globally distributed simulated GNSS RO profiles per day is investigated. It is shown that 2000 simulated GNSS RO measurements have an impact similar to real measurements in the EDA and that the EDA-based impact of real data can be related to the impact in observing system experiments. The dependence of the ensemble statistics on observation error statistics assumed when assimilating the data, rather than the actual observation errors, is emphasized. There is no evidence of “saturation” of forecast impact even with 128 000 GNSS RO profiles per day. However, this result is a well-known consequence of always improving the theoretical analysis and short-range forecast error statistics when adding new observations that are assumed to have uncorrelated observation errors. In general, it is found that 16 000 GNSS RO profiles per day have around half the impact of 128 000 profiles, based on the reduction of ensemble spread values where the GNSS RO measurements have the largest impact.

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Jordis S. Tradowsky, Chris P. Burrows, Sean B. Healy, and John R. Eyre


A new method to estimate radiosonde temperature biases using radio occultation measurements as a reference has been developed. The bias is estimated as the difference between mean radio occultation and mean radiosonde departures from collocated profiles extracted from the Met Office global numerical weather prediction (NWP) system. Using NWP background profiles reduces the impact of spatial and temporal collocation errors. The use of NWP output also permits determination of the lowest level at which the atmosphere is sufficiently dry to analyze radio occultation dry temperature retrievals. The authors demonstrate the advantages of using a new tangent linear version of the dry temperature retrieval algorithm to propagate bending angle departures to dry temperature departures. This reduces the influence of a priori assumptions compared to a nonlinear retrieval. Radiosonde temperature biases, which depend on altitude and the solar elevation angle, are presented for five carefully chosen upper-air sites and show strong intersite differences, with biases exceeding 2 K at one of the sites. If implemented in NWP models to correct radiosonde temperature biases prior to assimilation, this method could aid the need for consistent anchor measurements in the assimilation system. The method presented here is therefore relevant to NWP centers, and the results will be of interest to the radiosonde community by providing site-specific temperature bias profiles. The new tangent linear version of the linear Abel transform and the hydrostatic integration are described in the interests of the radio occultation community.

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R. A Anthes, P. A Bernhardt, Y. Chen, L. Cucurull, K. F. Dymond, D. Ector, S. B. Healy, S.-P. Ho, D. C Hunt, Y.-H. Kuo, H. Liu, K. Manning, C. McCormick, T. K. Meehan, W J. Randel, C. Rocken, W S. Schreiner, S. V. Sokolovskiy, S. Syndergaard, D. C. Thompson, K. E. Trenberth, T.-K. Wee, N. L. Yen, and Z Zeng

The radio occultation (RO) technique, which makes use of radio signals transmitted by the global positioning system (GPS) satellites, has emerged as a powerful and relatively inexpensive approach for sounding the global atmosphere with high precision, accuracy, and vertical resolution in all weather and over both land and ocean. On 15 April 2006, the joint Taiwan-U.S. Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC)/Formosa Satellite Mission 3 (COSMIC/FORMOSAT-3, hereafter COSMIC) mission, a constellation of six microsatellites, was launched into a 512-km orbit. After launch the satellites were gradually deployed to their final orbits at 800 km, a process that took about 17 months. During the early weeks of the deployment, the satellites were spaced closely, offering a unique opportunity to verify the high precision of RO measurements. As of September 2007, COSMIC is providing about 2000 RO soundings per day to support the research and operational communities. COSMIC RO data are of better quality than those from the previous missions and penetrate much farther down into the troposphere; 70%–90% of the soundings reach to within 1 km of the surface on a global basis. The data are having a positive impact on operational global weather forecast models.

With the ability to penetrate deep into the lower troposphere using an advanced open-loop tracking technique, the COSMIC RO instruments can observe the structure of the tropical atmospheric boundary layer. The value of RO for climate monitoring and research is demonstrated by the precise and consistent observations between different instruments, platforms, and missions. COSMIC observations are capable of intercalibrating microwave measurements from the Advanced Microwave Sounding Unit (AMSU) on different satellites. Finally, unique and useful observations of the ionosphere are being obtained using the RO receiver and two other instruments on the COSMIC satellites, the tiny ionosphere photometer (TIP) and the tri-band beacon.

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