[1] To examine the suitability of GPS radio occultation (RO) observations as a climate benchmark data set, this study aims at quantifying the structural uncertainty in GPS RO-derived vertical profiles of refractivity and measured refractivity trends obtained from atmospheric excess phase processing and inversion procedures. Five years (2002)(2003)(2004)(2005)(2006) of monthly mean climatologies (MMC) of retrieved refractivity from the experiment aboard the German satellite CHAMP generated by four RO operational centers were compared. Results show that the absolute values of fractional refractivity anomalies among the centers are, in general, 0.2% from 8 to 25 km altitude. The median absolute deviations among the centers are less than 0.2% globally. Because the differences in fractional refractivity produced by the four centers are, in general, unchanging with time, the uncertainty of the trend for fractional refractivity anomalies among centers is ±0.04% per 5 years globally. The primary cause of the trend uncertainty is due to different quality control methods used by the four centers, which yield different sampling errors for different centers. We used the National Centers for Environmental Prediction reanalysis in the same period to estimate sampling errors. After removing the sampling errors, the uncertainty of the trend for fractional refractivity anomalies among centers is between À0.03 and 0.01% per 5 years. Thus 0.03% per 5 years can be considered an upper bound in the processing scheme-induced uncertainty for global refractivity trend monitoring. Systematic errors common to all centers are not discussed in this article but are generally believed to be small.
High quality observations of the atmosphere are particularly required for monitoring global climate change. Radio occultation (RO) data, using Global Navigation Satellite System (GNSS) signals, are well suited for this challenge. The special climate utility of RO data arises from their long-term stability due to their self-calibrated nature. The German research satellite CHAllenging Minisatellite Payload for geoscientific research (CHAMP) continuously records RO profiles since August 2001 providing the first opportunity to create RO based climatologies for a multi-year period of more than 5 years. A period of missing CHAMP data from July 3, 2006 to August 8, 2006 can be bridged with RO data from the GRACE satellite (Gravity Recovery and Climate Experiment). We have built seasonal and zonal mean climatologies of atmospheric (dry) temperature, microwave refractivity, geopotential height and pressure with 10°lat-itudinal resolution. We show representative results with focus on dry temperatures and compare them with analysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Although we have available only about 150 CHAMP profiles per day (compared to millions of data entering the ECMWF analyses) the overall agreement between 8 and 30 km altitude is in general very good with systematic differences \0.5 K in most parts of the domain. Pronounced systematic differences (exceeding 2 K) in the tropical tropopause region and above Antarctica in southern winter can almost entirely be attributed to errors in the ECMWF analyses. Errors resulting from uneven sampling in space and time are a potential error source for single-satellite climatologies. The average CHAMP sampling error for seasonal zonal means is \0.2 K, higher values occur in restricted regions and time intervals which can be clearly identified by the sampling error estimation approach we introduced (which is based on ECMWF analysis fields). The total error of this new type of temperature climatologies is estimated to be \0.5 K below 30 km. The recently launched Taiwan/U.S. FORMOSAT-3/COSMIC constellation of 6 RO satellites started to provide thousands of RO profiles per day, but already now the single-satellite CHAMP RO climatologies improve upon modern operational climatologies in the upper troposphere-lower stratosphere and can act as absolute reference climatologies for validation of more bias-sensitive climate datasets and models.
Existing upper air records of radiosonde and operational satellite data recently showed a reconciliation of temperature trends but structural uncertainties remain. GPS radio occultation (RO) provides a new high‐quality record, profiling the upper troposphere and lower stratosphere with stability and homogeneity. Here we show that climate trends are since recently detected by RO data, consistent with earliest detection times estimated by simulations. Based on a temperature change detection study using the RO record within 1995–2008 we found a significant cooling trend in the tropical lower stratosphere in February while in the upper troposphere an emerging warming trend is obscured by El Niño variability. The observed trends and warming/cooling contrast across the tropopause agree well with radiosonde data and basically with climate model simulations, the latter tentatively showing less contrast. The performance of the short RO record to date underpins its capability to become a climate benchmark record in the future.
[1] The sampling error of Global Positioning System (GPS) radio occultation (RO) derived temperature climatologies is computed over a representative time span of 2 years and compared for Sun-synchronous and non-Sun-synchronous Low Earth Orbit (LEO) satellites. The main focus lies on the sampling error's local time component, which is caused by incomplete sampling of the diurnal cycle and which depends on the geometry of the satellite orbits. The Sun-synchronous satellite MetOp (Meteorological Operational European weather satellite) and the non-Sun-synchronous satellite CHAMP (Challenging Minisatellite Payload), both carrying GPS RO instruments on board, serve as representative cases. For the Sun-synchronous satellite MetOp the local time component remains constant during the whole observation period such that the magnitude of the local time errors in monthly mean or longer-term mean RO climatologies is generally lower than ±0.1 K. Except for potential long-term effects of global warming on the diurnal cycle, which might require calibration, this small local time component is stable on decadal timescales and is mainly positive in the Northern Hemisphere and at low latitudes, whereas it is mainly negative in the Southern Hemisphere. These features are attributable to a slight orbit-determined asymmetry in local time sampling. The typical (temporally stable) local time error of an annual mean MetOp climatology resolved into 18 zonal bands amounts to $0.04 K. For the non-Sun-synchronous satellite CHAMP the local time error component in monthly mean RO climatologies is also small (up to about ±0.15 K) but more variable (about zero mean) at middle and high latitudes. At low latitudes it results in sinusoidally varying positive and negative deviations with a several-months period, resulting from the local time drift of the satellite. The magnitude of local time errors is slightly larger compared to MetOp since the monthly averaging period is too short for CHAMP to entirely sample a diurnal cycle; a longer averaging period further decreases CHAMP's local time component. An annual mean climatology resolved into 18 zonal bands shows for CHAMP a typical local time residual error component of $0.03 K. The overall evidence is that even with single RO satellites, monthly climatologies of high accuracy (sampling error <0.3 K) with the local time component being a minor part (<0.1 K to 0.15 K) can be obtained.Citation: Pirscher, B., U. Foelsche, B. C. Lackner, and G. Kirchengast (2007), Local time influence in single-satellite radio occultation climatologies from Sun-synchronous and non-Sun-synchronous satellites,
[1] The characteristics of atmospheric tides in the upper troposphere and lower stratosphere region are investigated using radio occultation (RO) measurements performed by the Formosa Satellite Mission-3/Constellation Observing System for Meteorology, Ionosphere, and Climate (FORMOSAT-3/COSMIC) satellite constellation and compared to tides observed in short-term forecast model fields of European Centre for Medium-Range Weather Forecasts (ECMWF) and National Centers for Environmental Prediction (NCEP). Spectral analysis of 2 years of monthly data (2007 to 2008) yields the migrating diurnal tide to be the largest spectral component. This diurnal tide shows similar temporal, latitudinal, and altitudinal characteristics in all data sets equatorward of 50°. Beyond 50°, COSMIC local time sampling is insufficient within 1 month, which prevents space-time spectral analysis from isolating atmospheric waves. Diurnal tides of temperature are characterized by largest amplitudes in the tropics (0.8 K to 1.0 K at an altitude of 30 km). Amplitudes of diurnal tides analyzed in model data are more pronounced by ∼20%. An annual cycle of the amplitudes, characteristically linked to the movement of the intertropical convergence zone, is clearly revealed. Tropical diurnal phase features downward progression of waves fronts with a vertical wavelength of 20 km. Extratropical diurnal tides are most pronounced in the model data sets with amplitudes of up to 0.5 K at 30 km. In this analysis we also see the influence of high-altitude initialization of RO data by background information in using data processed by two different centers (University Corporation for Atmospheric Research (UCAR) and Wegener Center (WEGC)). UCAR data, initialized by a climatology without tidal information, exhibit no appreciable extratropical diurnal tides, while WEGC data, initialized by ECMWF forecasts, show more pronounced ones. Overall the results underpin the utility of the local-time resolving COSMIC RO constellation data for monitoring diurnal tide dynamics in the stratosphere. The agreement between observational and model data further confirms that the tidal dynamics is appropriately captured in the models, which is important for other (middle/upper) atmosphere models relying on ECMWF or NCEP dynamics.Citation: Pirscher, B., U. Foelsche, M. Borsche, G. Kirchengast, and Y.-H. Kuo (2010), Analysis of migrating diurnal tides detected in FORMOSAT-3/COSMIC temperature data,
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