Testing climate models using GPS radio occultation: A sensitivity analysis

Leroy, S. S.; Anderson, James G.; Dykema, J. A.

doi:10.1029/2005jd006145

Cited by 54 publications

(56 citation statements)

References 35 publications

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“…De spite good ver ti cal res o lu tion of the ra dio sonde data, global cov er age is im pos si ble. In con trast, the RO tech nique of fers both global cov er age but good ver ti cal res o lu tion as well and is there fore no ta bly appli ca ble for de tailed at mo spheric mon i tor ing and cli mate stud ies (Leroy et al 2006). Since the avail abil ity of GPS RO data start ing with the GPS/MET ex per i ment (1995 -1997) sev eral stud ies con cern ing the up per tro po sphere and lower strato sphere (UTLS) re gion were per formed us ing the consec u tive RO mis sions (CHAMP, SAC-C, GRACE and FORMOSAT-3/COS MIC).…”

Section: Global Tropo Pause Pa Ram E Ters From Ra Dio Occultation Datamentioning

confidence: 99%

GPS Radio Occultation: Results from CHAMP, GRACE and FORMOSAT-3/COSMIC

Wickert¹,

Michalak²,

Schmidt³

et al. 2009

Terr. Atmos. Ocean. Sci.

106

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AB STRACTThe Tai wan/US FORMOSAT-3/COS MIC (FORMOsa SAT el lite mis sion -3/Con stel la tion Ob serv ing Sys tem for Me te o rol ogy, Ion o sphere and Cli mate) sat el lite con stel la tion was suc cess fully launched on 14 April 2006. It is ex pected to le ver age the use of the GPS (Global Po si tion ing Sys tem) ra dio occultation data for at mo spheric and ion o spheric re search to im prove global weather fore casts and aid cli mate change re lated stud ies. FORMOSAT-3/COS MIC, to gether with the Eu ro pean MetOp, Ger man CHAMP and US/Ger man GRACE-A sat el lites, form a 9 sat el lite con stel la tion for pre cise at mo spheric sound ing on a global scale. This sat el lite con stel la tion is expected to provide about 3500 occultation measurements daily.Re cent re sults and the sta tus of the CHAMP and GRACE-A or bit and occultation data anal y sis are re viewed and com ple mented with a re view of ini tial re sults from FORMOSAT-3/COS MIC at GFZ. The sig nif i cantly in creased po ten tial of the CHAMP, GRACE-A and FORMOSAT-3/COS MIC con stel la tion for at mo spheric stud ies, com pared to sin gle sat el lite mis sions, is dem on strated for se lected ap pli ca tions such as global mon i tor ing of wa ter va por dis tri bu tions, tropo pause parameters and ionospheric irregularities.

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Section: Global Tropo Pause Pa Ram E Ters From Ra Dio Occultation Datamentioning

confidence: 99%

GPS Radio Occultation: Results from CHAMP, GRACE and FORMOSAT-3/COSMIC

Wickert¹,

Michalak²,

Schmidt³

et al. 2009

Terr. Atmos. Ocean. Sci.

106

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“…Furthermore, geopotential height change (m decade −1 ) relates to relative pressure change (% decade −1 ) via the atmospheric scale height by a factor of about 70 m % −1 (e.g. Leroy et al, 2006b;Scherllin-Pirscher et al, 2011b) so that expected climate change signals in geopotential height of roughly 10 m decade −1 at low to mid latitudes (Leroy et al, 2006b;Lackner et al, 2011) suggest a stability requirement like 4 m decade −1 , and correspondingly of 0.06 % decade −1 for pressure, to be reasonable values.…”

Section: Mean Trends and Structural Uncertaintymentioning

confidence: 99%

Quantification of structural uncertainty in climate data records from GPS radio occultation

et al. 2013

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Global Positioning System (GPS) radio occultation (RO) has provided continuous observations of the Earth's atmosphere since 2001 with global coverage, all-weather capability, and high accuracy and vertical resolution in the upper troposphere and lower stratosphere (UTLS). Precise time measurements enable long-term stability but careful processing is needed. Here we provide climate-oriented atmospheric scientists with multicenter-based results on the long-term stability of RO climatological fields for trend studies. We quantify the structural uncertainty of atmospheric trends estimated from the RO record, which arises from current processing schemes of six international RO processing centers, DMI Copenhagen, EUM Darmstadt, GFZ Potsdam, JPL Pasadena, UCAR Boulder, and WEGC Graz. Monthly-mean zonal-mean fields of bending angle, refractivity, dry pressure, dry geopotential height, and dry temperature from the CHAMP mission are compared for September 2001 to September 2008. We find that structural uncertainty is lowest in the tropics and mid-latitudes (50° S to 50° N) from 8 km to 25 km for all inspected RO variables. In this region, the structural uncertainty in trends over 7 yr is <0.03% for bending angle, refractivity, and pressure, <3 m for geopotential height of pressure levels, and <0.06 K for temperature; low enough for detecting a climate change signal within about a decade. Larger structural uncertainty above about 25 km and at high latitudes is attributable to differences in the processing schemes, which undergo continuous improvements. Though current use of RO for reliable climate trend assessment is bound to 50° S to 50° N, our results show that quality, consistency, and reproducibility are favorable in the UTLS for the establishment of a climate benchmark record

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“…Comparing data types for satellite and in situ measurements, there are three satellite measurements [total outgoing longwave radiation trend, radiance trend at 995 cm −1 , and dry pressure trend at 5.5 km, the occultation surrogate (10)] that appear to rank above or equal to the best in situ measurement (geopotential height trend at 500 hPa). This ranking could be taken to indicate that the CLARREO instrumentation is well chosen.…”

Section: Discussionmentioning

confidence: 99%

“…Δσ ¼ ðσ y − σ yjd Þ∕σ y ; [10] with y t the truth of the predicted quantity y, which can be known only in a perfect model test.…”

Section: Calculationsmentioning

confidence: 99%

Discriminating between climate observations in terms of their ability to improve an ensemble of climate predictions

Huang

Leroy

Goody

2011

Proc. Natl. Acad. Sci. U.S.A.

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In view of the cost and complexity of climate-observing systems, it is a matter of concern to know which measurements, by satellite or in situ, can best improve the accuracy and precision of long-term ensembles of climate projections. We follow a statistical procedure to evaluate the relative capabilities of a wide variety of observable data types for improving the accuracy and precision of an ensemble of Intergovernmental Panel on Climate Change (IPCC) models. Thirty-two data types are evaluated for their potential for improving a 50-y surface air temperature trend prediction with data from earlier periods, with an emphasis on 20 y. Data types can be ordered in terms of their ability to increase the precision of a forecast. Results show that important conclusions can follow from this ordering. The small size of the IPCC model ensemble (20 members) creates uncertainties in these conclusions, which need to be substantiated with the larger ensembles expected in the future. But the larger issue of whether the methodology can provide useful answers is demonstrated.climate monitoring | climate model | remote sensing | climate change S atellite observations are an increasingly important source of climate observations. They can give continuous global coverage with the same instruments, and it is now possible to design simple instruments that can be referred confidently to international standards, assuring the value of the observations in perpetuity. An example of this approach is National Aeronautics and Space Administration's Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission, which has recently been suspended indefinitely due to national fiscal constraints. CLAR-REO, as last configured, contained a thermal infrared interferometer, a global positioning system (GPS) radio occultation instrument, and a shortwave spectrometer to measure reflected solar radiation. It becomes a matter of concern to know whether these are the best measurements for improving long-term climate projections, and if not, which measurements are.In this paper, we ask how far a given observable data type is capable of improving an ensemble of climate trend predictions, directly. This is a standard problem in the statistical literature, which we have adapted to the requirements of this paper. The widely used ensemble of climate models employed by the Intergovernmental Panel on Climate Change (1) Fourth Assessment Report (IPCC-AR4) provides an example of an ensemble, and we anticipate that ensembles of projections will be a common feature of future climate studies. An ensemble of projections can be characterized, at a minimum, by a mean and a standard deviation, which may be identified with the most likely projection and its precision, respectively. These important parameters can be modified by taking account of measured data not previously incorporated into the models. The data need not be the same as the predicted quantities. For example, the prediction may be of globally averaged surface temperature trends. The measured data ...

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Testing climate models using GPS radio occultation: A sensitivity analysis

Cited by 54 publications

References 35 publications

GPS Radio Occultation: Results from CHAMP, GRACE and FORMOSAT-3/COSMIC

GPS Radio Occultation: Results from CHAMP, GRACE and FORMOSAT-3/COSMIC

Quantification of structural uncertainty in climate data records from GPS radio occultation

Discriminating between climate observations in terms of their ability to improve an ensemble of climate predictions

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