A proof-of-concept balloon-borne Global Positioning System radio occultation profiling instrument for polar studies

Transcription

1 GEOPHYSICAL RESEARCH LETTERS, VOL. 39,, doi: /2011gl049982, 2012 A proof-of-concept balloon-borne Global Positioning System radio occultation profiling instrument for polar studies J. S. Haase, 1 J. Maldonado-Vargas, 2 F. Rabier, 3 P. Cocquerez, 4 M. Minois, 5 V. Guidard, 3 P. Wyss, 6 and A. V. Johnson 1 Received 12 October 2011; revised 15 December 2011; accepted 15 December 2011; published 21 January [1] Global warming has focused attention on the polar regions and recent changes in sea and land ice distribution. Accurate modeling of the future evolution of climate and weather in the Antarctic relies heavily on remote sensing observations. However, their reliable assimilation into numerical weather models and reanalyses is challenging because of the unique environment and sparsity of in-situ observations for validation. We developed a stratospheric balloon-borne GPS radio occultation system for the 2010 Concordiasi campaign to provide refractivity and derived temperature profiles for improving satellite data assimilation. The observed excess phase delay profiles agree with those simulated from model and dropsonde profiles. 711 occultations were recorded from two balloons, comparable to the number of profiles acquired by 13 driftsonde balloons. Of these profiles, 32% descended to 4 km above the surface, without open-loop receiver tracking technology, demonstrating it is possible to retrieve useful information with relatively simple low cost instruments. Citation: Haase, J. S., J. Maldonado-Vargas, F. Rabier, P. Cocquerez, M. Minois, V. Guidard, P. Wyss, and A. V. Johnson (2012), A proof-of-concept balloon-borne Global Positioning System radio occultation profiling instrument for polar studies, Geophys. Res. Lett., 39,, doi: /2011gl Department of Earth and Atmospheric Sciences, Purdue University, West Lafayette, Indiana, USA. 2 Department of Physics, University of Puerto Rico, Mayaguez, Puerto Rico. 3 Meteo-France and CNRS, CNRM-GAME/GMAP, Toulouse, France. 4 Centre National d Etudes Spatiales, Toulouse, France. 5 SOGETI High Tech, Blagnac, France. 6 Department of Chemistry, Purdue University, West Lafayette, Indiana, USA. Copyright 2012 by the American Geophysical Union /12/2011GL Introduction [2] Reanalyses datasets are important for understanding climate change in Antarctica. For example, recent use of reanalyses and microwave sounder data [Turner et al., 2009] showed that variations in the southern annular mode deepen the trough over the Amundson Sea, increasing the flow over the Ross Ice shelf and increasing the sea ice extent in the Ross Sea, while decreasing the sea ice extent in the Amundson-Bellingshausen Sea sectors. Reanalysis datasets have the advantage that they produce a multivariate, spatially complete record using a single version of a data assimilation system so no changes in the method or model can interfere with the interpretation of the temporal evolution of the atmospheric circulation. A significant recent improvement was made in the European Center for Medium- Range Weather Forecasts Interim Reanalyis (ERA-interim) over the Antarctic through the combined use of Global Positioning System radio occultation (GPS RO) and Advanced Microwave Sounding Unit (AMSU) sounding data [Dee et al., 2011]. GPS RO is used to anchor the variational bias correction of the AMSU data, providing better long-term consistency of the analyses. The Concordiasi campaign, initiated in the International Polar Year, was the most ambitious program of upper air sounding that has ever been carried out in the Antarctic. One of the primary objectives of the Concordiasi campaign was to provide independent data for assessing and improving the quality of hyperspectral satellite sounder data assimilation algorithms in numerical weather models and reanalyses in the Antarctic [Rabier et al., 2010]. The new generation of advanced hyperspectral sounders, such as the Atmospheric Infrared Sounder (AIRS) on the Aqua satellite, and the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite, as well as the AMSU-A and -B are providing a large amount of data in this otherwise data-sparse region. Assimilation of these data has a greater effect on the operational forecasts and reanalyses in Antarctica than in other regions of the globe. The quality of the data and the assimilation techniques poleward of 65 latitude in the Antarctic environment have not yet been fully tested because of difficulties over snow and ice, and because cloudy conditions can affect 75 90% of the data [Bouchard et al., 2010]. The unique characteristics of very cold surface temperatures in stable atmospheric profiles over the plateaus and warmer surfaces over sea ice make cloud detection in IASI and AIRS data challenging [Lavanant et al., 2011]. IASI temperature and humidity profile retrieval algorithms also have difficulty accurately reproducing the very cold stable profiles over the plateau [Pougatchev et al., 2009]. Therefore, independent confirmation that the data assimilation is moving the analyses in the correct direction is critical. Concordiasi was designed to collect an unprecedented dataset of additional radiosonde profiles (in 2008 and 2009) and stratospheric balloon driftsonde profiles (in 2010), for verification of these algorithms. The National Science Foundation funded an innovative, high-risk, proof-of-concept effort to develop a GPS radio occultation system for the stratospheric balloons to provide additional sounding data for validation of model assimilation results and IASI retrieval algorithms. Previous results from space borne radio occultation profile assimilation into global models have shown positive impact over the Antarctic for 48 hour forecasts [Wee et al., 2008], and suggested that shorter term forecast impact was neutral because of the sparse spatial sampling of the radio occultation 1of5

2 Laboratoire de Méteorologie Dynamique (LMDOz) and a TSEN. More information on the ROC package can be found in Text S1 and Figures S1 and S2 of the auxiliary material. 1 PSC18 was launched 29 September 2010 and flew for 54 days. PSC19 was equipped with the ROC package with a single receiver, an ozone sensor designed by the University of Colorado at Boulder (UCOz) and a TSEN. PSC19 was launched 8 October 2010 and flew for 42 days (See Table S1 of the auxiliary material). The flight trajectories for both flights are shown in Figure 1. The average flight altitude for both balloons was 17.3 km. Figure 1. Flight trajectories for PSC18 and PSC19, the flights carrying the ROC instrument. PSC18 shown in blue, PSC19 is shown in black. Blue and black diamond symbols indicate the locations of the occultation recordings. Red diamonds show the locations of the dropsondes released from the 13 MSD balloons. The blue star indicates the location of a dropsonde close in space and time to the occultation data analyzed below. profiles. The new observation technique has high interest from the community because of its potential to increase density in localized areas. This paper demonstrates the feasibility of deriving atmospheric profiles from balloon occultations. 2. The Concordiasi Campaign [3] During the Concordiasi field campaign from September 2010 through January 2011, the Centre National d Etudes Spatiales (CNES, the French space agency) launched a constellation of nineteen long duration stratospheric balloons from the National Science Foundation (NSF) McMurdo research station. Thirteen flights were equipped with meteorological and stratospheric dynamics (MSD) payloads including an in-situ Thermodynamic Sensor (TSEN) measuring pressure and temperature, and a National Center for Atmospheric Research Earth Observation Laboratory driftsonde package. Dropsondes were released for several purposes: for IASI validation during overflights of the Metop-A satellite, and targeted observations when passing over sensitive areas where the ECMWF ensemble model indicated higher than normal model errors. These dropsonde profiles are available to serve as reference data for comparison with the new radio occultation profiles. The locations of all dropsondes are shown in Figure 1. [4] Six of the flights were equipped with physics and stratospheric chemistry (PSC) payloads Flight PSC18 was equipped with the GPS radio occultation (ROC) experiment package with two receivers, an ozone sensor designed by the 3. Data Analysis [5] The balloon borne GPS radio occultation technique is based on the same principle as radio occultation from low earth orbiting satellites. Recordings are made of signals from GPS satellites as they set behind the Earth s limb relative to the receiver [Kursinski et al., 1997; Vorobev and Krasil nikova, 1994]. As the line of sight of the GPS signal passes successively deeper into the atmosphere, the signal path is refracted (bent and delayed) creating an excess Doppler shift in the carrier frequency of the GPS signal. From the atmospheric refractivity, information on the temperature and humidity structure of the atmosphere can be inferred. The CHAMP [Wickert et al., 2001], MetOP-GRAS [GRAS Science Advisory Group, 1998], SAC-C [Hajj et al., 2004], and COSMIC/FORMOSAT-3 [Rocken et al., 2000; Wu et al., 2005] radio occultation missions have demonstrated the utility of GPS radio occultation. The concept has reached an operational status with global coverage producing on the order of 3000 soundings per day. Previous studies have demonstrated that this type of measurement can be made with a receiver onboard an aircraft where the location of the receiver within the atmosphere results in an asymmetric measurement geometry [Garrison et al., 2007]. The airborne geometry requires modifications to the standard radio occultation profiling method [Healy et al., 2002; Lesne et al., 2002; Xie et al., 2008; Zuffada et al., 1999], however it gives much more control in the locations of the soundings. [6] We used raytracing [Syndergaard et al., 2005; Hoeg et al., 1995] to calculate the predicted excess Doppler and demonstrate the consistency of the balloon borne radio occultation data with other sounding data. The global model or dropsonde profile values for P, T, and RH are converted to refractivity using equation (1) for the refractive index of the neutral atmosphere at GPS frequencies: N ¼ ðn 1Þ10 6 ¼ 77:60P T þ 70:4e þ 3: e T T 2 where N is refractivity, n is the refractive index, P is the atmospheric pressure in hpa, T is atmospheric temperature in Kelvin, and e is water vapor partial pressure in hpa [Bevis et al., 1994]. We made a direct comparison of the excess Doppler calculated using raytracing to the observed excess Doppler as has been carried out for ground-based observations at low elevations [Sokolovskiy et al., 2001], however our recordings of signals below the horizon permit unambiguous retrieval of refractivity. The data processing 1 Auxiliary materials are available in the HTML. doi: / 2011GL ð1þ 2of5

3 Figure 2. (top) Excess Doppler for the GPS RO observations for PRN25 corrected by high elevation GPS satellite PRN13, and excess Doppler calculated for the ARPEGE model profile and the dropsonde profile. The excess Doppler in the GPS signal increases as the line of sight between the balloon and the occulting GPS satellite moves lower in the atmosphere. (bottom) Red: ARPEGE GPS RO Doppler; Blue: Dropsonde GPS RO Doppler. method used to calculate the observed excess Doppler is provided in the auxiliary material. 4. Results [7] The observed Doppler profile for setting satellite 25 was recorded by receiver V191 on balloon PSC19. The occultation started (ie. when the tangent point is at balloon receiver height) at 16:20 Z on 24 Sep 2010 when the balloon was at (lat, lon) The signal was lost 34 minutes later at a tangent point height of 3.7 km above the reference ellipsoid, or 2.7 km above the land surface. Because the receiver on the balloon was moving much more slowly (33 m/s) than the transmitting GPS satellite (3.06 km/s), the tangent point (point of closest approach to the surface) moved away from the balloon location as the raypath descended in the atmosphere. The horizontal drift of the tangent point over the duration of the occultation in this case was 390 km Comparison With Model and Dropsonde Profiles [8] The comparison profiles come from the Météo-France global model, Action de Recherche Petite Echelle/Grande Echelle (ARPEGE), which means research project on small and large scales [Courtier et al., 1994]. This model, developed in collaboration with the European Center for Medium-Range Weather Forecasts (ECMWF), uses a stretched grid centered on DomeC Station in Antarctica. The model has 70 vertical levels using hybrid coordinates from 17m above the surface up to 0.05 hpa. Spectral truncation at T798 gives a horizontal resolution of km over Antarctica and 60 km at the antipodes. Centering the stretched grid over Antarctica provides much better representation of the orography, which reaches 4 km for the mountains on the eastern plateau and 1 km over the Antarctic Peninsula [Bouchard et al., 2010]. It uses a Four-dimensional variational assimilation system [Rabier et al., 2000] to assimilate conventional data as well as a large range of satellite data, including spaceborne GPS radio occultation profiles. [9] The nearest ARPEGE model grid profile is at (lat, lon) at 18Z on 24 Sep 2010, which is 37 km from the occultation starting tangent point and 418 km from the occultation ending point. The nearest dropsonde profile was released at 18:38Z on 24 Sep 2010 at (lat, lon) at m altitude. The distance from the occultation location was 216 km at the top of the profile and 511 km at the lowest point of the occultation profile. Because the dropsonde profile and the ARPEGE model profile locations were at a significant distance from the first and last tangent points of the GPS RO profile, one would not expect perfect agreement between the two, so we smoothed the ARPEGE and dropsonde profiles before running the raytracer in order to compare with the average properties of the atmosphere. [10] The observed GPS RO excess Doppler profile as a function of time, and the simulated excess Doppler for the ARPEGE and dropsonde profiles are shown in Figure 2. Details on the data processing method used to calculate excess Doppler are provided in the auxiliary material. The noise level of the GPS RO excess Doppler observations prior to the start of the occultation, when the excess Doppler should be zero, had a bias of m/s and standard deviation of m/s. This standard deviation was comparable to that required for retrieving refractivity values with 0.5% accuracy below approximately 11 km, as described by Xie et al. [2008], and would correspond to a temperature accuracy of approximately 1 K. The difference between the smoothed ARPEGE model excess Doppler and the GPS RO observations had mean 0.0 m/s and standard deviation m/s. The difference between the excess Doppler calculated from the smoothed dropsonde profile and the GPS RO observations had mean 0.0 m/s and standard deviation of m/s. This level of agreement in Doppler corresponds to less than 1% difference in refractivity below 11 km height, and would correspond to a temperature agreement of better than 2 K. Given the large horizontal tangent point drift, it demonstrates a realistic agreement among the different profiles. We derive a refractivity profile for this occultation using the retrieval method described by Xie et al. [2008] for comparison with the ARPEGE and dropsonde profiles. While a comparison for one profile is not sufficient to provide a comprehensive statistical evaluation of the errors, there is a good level of agreement. The RMS difference between the ARPEGE model refractivity and the radio occultation refractivity is 1.5% between 8 and 16 km height, and the RMS difference between the dropsonde and radio occultation profiles is 0.9% (see Figure S3 in the auxiliary material) Measurement Statistics [11] The 54 day flight for PSC18 and 42 day flight for PSC19 provided a rich dataset. Even with the imposed data 3of5

4 Figure 3. Histograms of the penetration depth of the occultation measurements for flight (left) PSC18 and (right) PSC19. (top) Penetration depth in terms of height above the WGS84 reference ellipsoid. (bottom) Penetration in terms of height above the land surface. transmission limits of 1.2 Mbytes per day, this resulted in successfully recording 7 to 10 occultations per 24 hours of flight time. These occultations had a minimum quality criterion of at least 7 minutes of continuous recording below the horizon. The receivers did not have any open loop tracking capability, so the lower recording limit occurred when phase variations due to refractivity structure exceeded the capabilities of the phase locked loop tracking. However, there were still 55 of the 711 profiles that approached within 1 km of the surface topography or ocean surface. Figure 3 shows the distribution of penetration depth for each flight. Flight PSC18 had 43% of the occultations reach within 4 km of the surface, however only 22% of the occultations reached within 4 km of the surface for flight PSC19. We believe this is because PSC19 spent more time over the ocean where there could be a warmer moister boundary layer that could produce stronger vertical refractivity gradients. Surprisingly, the number of rising occultations was comparable to the number of setting occultations, with similar quality. The total number of dropsondes released by the 13 MSD balloons was 647. While the dropsondes provide more information in terms of wind, and direct measurements of moisture, it is impressive that the two radio occultation balloons produced a comparable number of profiles. 5. Conclusion and Discussion [12] The first results from the deployment of GPS radio occultation systems on stratospheric balloons demonstrate the feasibility of using this platform for atmospheric sounding. The occultation measurements have been shown to agree with predicted values of excess phase calculated by raytracing through one-dimensional model profiles from the Météo-France ARPEGE model and a nearby dropsonde. The agreement in Doppler shift indicates that an agreement within 2% of the refractivity should be possible in retrievals. An extensive dataset has been collected of 711 soundings with 32% extending to a height within 4 km of the Earth surface, comparable to the number of soundings collected from dropsondes during the campaign. These data will be a valuable contribution to reanalyses produced for the Concordiasi time period. COSMIC radio occultation data currently provides the second highest impact in forecasts from the Global Modeling and Assimilation Office (GMAO) system in the Antarctic [Gelaro, 2011], so there are high hopes that the Concordiasi dataset will provide comparable impact. The Concordiasi experiment, by augmenting operational data with balloon radio occultation profiles and dropsonde profiles, will be an exceptionally good time period for improving and testing assimilation algorithms. The balloon occultation profiles also will be used for comparison with the AIRS and IASI sounder data. It is through this improvement in assimilation methods that the Concordiasi radio occultation dataset will have a long lasting impact on diagnosing the effects of global change on atmospheric processes in the Antarctic. Ultimately, the improved satellite radiance assimilation methods will be incorporated into reanalyses so that data from high spectral resolution infrared sensors are used in the long-term assessment of atmospheric conditions for climate research. It is important that these reanalysis products replicate temperature and moisture profiles accurately, for example, when diagnosing the effects of global change on westerlies that control ice accumulation or rapid warming on the ice shelves. Current research to determine the relative impact of CO2 increases versus ozone as the causative factor for increased westerlies, and thus changes in surface temperatures on the ice shelves, rely on accurate reanalyses [Thompson and Solomon, 2002, 2005]. The resulting improvement in the representation of polar dynamics will be useful for coupled chemistry models that simulate the distribution of ozone and its evolution during the spring breakup of the polar vortex [Massart et al., 2009; Rabier et al., 2010]. [13] Acknowledgments. This work was supported by NSF grants and ANT We thank the following people and organizations for their support: NSF Office of Polar Programs for the instrument deployment field support; J. Zimmerman and M. Everly at the Purdue University AMY Chemistry Facility for assistance with hardware development; O. Gallien, J.-M. Nicot, and the team at CNES for assistance with the GPS ROC payload integration; S. Cohn, J. Wang, and NCAR EOL for supplying the dropsonde dataset; University of Puerto Rico of Mayaguez for funding a summer internship for portions of this work; B. Murphy and P. Muradyan for assistance with the data processing. Maps were produced using the GMT software, Concordiasi was built by an international scientific group and is currently supported by the following agencies: Météo-France, CNES, CNRS/INSU, NSF, NCAR, University of Wyoming, Purdue University, University of Colorado, the Alfred Wegener Institute, the Met Office, and ECMWF. Concordiasi also benefits from logistic or financial support of the operational polar agencies IPEV, PNRA, USAP and BAS, and from BSRN measurements at Concordia. 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Rabier, Meteo-France and CNRS, CNRM-GAME/ GMAP, F Toulouse, France. (florence.rabier@meteo.fr; vincent. guidard@meteo.fr) J. S. Haase and A. V. Johnson, Department of Earth and Atmospheric Sciences, Purdue University, 550 Stadium Mall Dr., West Lafayette, IN , USA. (jhaase@purdue.edu; ablanch@purdue.edu) J. Maldonado-Vargas, Department of Physics, University of Puerto Rico, Mayaguez, Puerto Rico, (jayson.maldonado@upr.edu) M. Minois, SOGETI High Tech, BP 90076, F Blagnac, France. (marc.minois@cnes.fr) P. Wyss, Department of Chemistry, Purdue University, West Lafayette, IN , USA. (wyss@purdue.edu) 5of5