GEOPHYSICAL RESEARCH LETTERS, VOL. 40, 1231–1236, doi:10.1002/grl.50246, 2013

Unprecedented upper-air dropsonde observations over Antarctica from the 2010 Concordiasi Experiment: Validation of satellite-retrieved temperature profiles Junhong Wang,1,2 Terry Hock,2 Stephen A. Cohn,2 Charlie Martin,2 Nick Potts,2 Tony Reale,3 Bomin Sun,4 and Frank Tilley4 Received 3 February 2013; revised 9 February 2013; accepted 11 February 2013; published 27 March 2013.

[1] The 2010 Concordiasi field experiment took place over (Figure 1). Also, the performance of radiosonde sensors is Antarctica from September to December 2010. During degraded at cold temperatures [Skony et al., 1994]. Com- Concordiasi, for the first time, 13 National Center for plex, heterogeneous surface conditions over Antarctica in- Atmospheric Research Driftsonde systems were launched troduce significant errors to satellite temperature retrievals. from McMurdo station, ascended to the stratosphere, and As a result of the lack of in-situ upper-air measurements then drifted with the winds. The Driftsonde provides a over Antarctica, satellite retrievals have not been well vali- unique platform to release dropsondes that measure the dated, especially over the Antarctic continent. atmosphere from the lower stratosphere to the surface in [3]Inordertofill gaps of upper-air observations over otherwise difficult to reach parts of the globe. A total of remote areas such as Antarctica, the National Center for 639 soundings were obtained and provided unprecedented Atmospheric Research (NCAR) has developed its Driftsonde high quality profiles over Antarctica. The sounding system (S. A. Cohn, T. Hock, J. Wang, and others, temperature profiles are compared with matched profiles Driftsondes: Providing In-Situ Dropsonde Observations from ten satellite products. All satellite products except over Remote Regions, submitted to Bull. Am. Meteorol. The Constellation Observing System for Meteorology, Soc., 2013). The objective of the Driftsonde system is to Ionosphere, and Climate (COSMIC) are consistent colder provide cost-effective upper-air observations over oceans than the sounding data, with larger discrepancies over and remote areas from days to months. The Driftsonde has the Antarctic continent than the coast and ocean. The promising science applications, including validating satellite COSMIC data are in agreement with the sounding remote sensing data and improving retrieval techniques. data and display no degradation over the continent. For example, the Driftsonde data collected during the Citation: Wang, J., T. Hock, S. A. Cohn, C. Martin, N. Potts, THORPEX-Pacific Asian Regional Campaign (T-PARC) T. Reale, B. Sun, and F. Tilley (2013), Unprecedented upper-air were used to validate satellite and global reanalysis products dropsonde observations over Antarctica from the 2010 Concordiasi [Wang et al., 2010]. In this study, we present an unprecedented Experiment: Validation of satellite-retrieved temperature profiles, upper-air dataset over Antarctica collected from the Geophys. Res. Lett., 40,1231–1236, doi:10.1002/grl.50246. NCAR Driftsonde system during the Concordiasi experi- ment in 2010 [Rabier et al., 2010]. The driftsonde data along with the radiosonde data are used to evaluate tem- 1. Introduction perature profiles from ten satellite products, and the dis- crepancies between the sonde and satellite data are [2] Antarctica plays an important role in the global investigated. climate system through teleconnections, Antarctic ice sheet changes, ozone depletion, and in other ways [SCAR, 2009]. However, it is very challenging to make measurements 2. Field Campaign, Data, and Analysis Method over Antarctica. Polar-orbiting passive satellites, GPS radio-occultation from COSMIC, and radiosondes are the [4] The NCAR Driftsonde system consists of a stratospheric only observing systems that provide routine upper-air balloon attached to a gondola that contains up to 56 Miniature observations over Antarctica. All of 16 operational radiosonde In-situ Sounding Technology (MIST) dropsondes. The stations over Antarctica except Amundsen-Scott (at the balloon is lifted up from the ground to the stratosphere South Pole) are along the coast, so they do not provide mea- and drifts with the wind. Sondes can be dropped either at a surements over the deep interior of the Antarctic continent prescheduled time or by command from the ground. The Driftsonde system has been used in three large field projects, African Monsoon Multidisciplinary Analysis in 2006 [Redelsperger et al., 2006], T-PARC in 2008 1Department of Atmospheric and Environmental Sciences, State [Parsons et al., 2008], and Concordiasi in 2010 [Rabier University of New York, Albany, New York, USA. et al., 2010]. 2 National Center for Atmospheric Research, Boulder, Colorado, USA. [5] The MIST sonde uses the same pressure/temperature/ 3NOAA/NESDIS, Camp Springs, Maryland, USA. 4 humidity sensor module as is used in the Vaisala RS92 IM System Group, Camp Springs, Maryland, USA. radiosonde [Vaisala, 2012a], and the accuracy of this module, Corresponding author: Junhong Wang, National Center for Atmospheric especially the temperature sensor, is well documented. Research, Boulder, CO, USA.E-mail: ([email protected]) Based on the manufacture’s technical data, the RS92 capacitive  ©2013. American Geophysical Union. All Rights Reserved. wire temperature sensor has an accuracy of 0.5 C when the 0094-8276/13/10.1002/grl.50246 Vaisala Ground Check Set (GC25) is used to perform the

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(a) The capacitive wire is very small and thus responds quickly to temperature changes, with a response time of less than 1s at 100 hPa [Vaisala, 2012a]. The solar radiation error has a maximum value of 0.98C at 1 hPa and 0 solar zenith angle and mainly depends on solar zenith angle and pressure [Vaisala, 2012b]. The Vaisala RS92 demonstrated its accurate performance in the WMO radiosonde intercomparison project in 2010 and showed a temperature accuracy of 0.3Cand 0.6C from the surface to 100 hPa and from 100 hPa to 10 hPa, respectively [Nash et al., 2011]. Therefore, the MIST dropsonde temperature measurement can be considered as a reference to validate the satellite products. [6] Concordiasi is a joint French-United States initiative that began during the International Polar Year. The Concordiasi field experiment in 2010 took place over Antarctica from September to December 2010 [Rabier et al., 2010]. The scientific objective of Concordiasi was to combine innovative measurements and modeling for better analysis and prediction of the weather over Antarctica. During Concordiasi, a total of 639 carefully quality controlled MIST soundings were collected during 13 Driftsonde flights launched from McMurdo station (Figure 1). The quality control process is described in Wang et al. [2011]. The 13 Driftsonde balloons (b) remained operational for different periods of time ranging from 43 to 94 days. They achieved unprecedented spatial and temporal coverage of Antarctica, providing high quality Coast High Plateau atmospheric profiles (Figure 1). Fifty-two soundings released Coast Transit from one Driftsonde illustrate the detailed temperature structures observed from the surface to 60 hPa (Figure 1). The temperature profiles over land show very strong near-surface inversions, while those over the ocean and coast frequently show complex structure and inversions in the lower troposphere (Figure 1). Waves are seen in the upper troposphere and lower Pressure (hPa) stratosphere in all profiles (Figure 1). In addition to temperature profiles, the relative humidity and wind speed/direction profiles are also available for further exploration. [7] The NOAA PROducts Validation System (NPROVS) provides a centralized validation protocol for routine −801000 900 800 700 600 500 −60 400 300 200 100 −40 0 −200 20 40 60 80 100 120 140 Temperature (C+3) monitoring and comparison of derived atmospheric satellite products against in-situ observations (i.e., radiosonde and Figure 1. The upper panel shows map of dropsonde locations dropsonde) and Numerical Weather Prediction products (yellow squares), radiosonde stations (big purple balloons), and [Reale et al., 2012]. In this work, NPROVS was used to locations of 52 dropsondes (small colored balloons) from 21 identify in-situ Concordiasi soundings from either dropsondes October to 9 November 2010 on a single Driftsonde. The or radiosondes that are collocated with ten satellite products lower panel shows corresponding temperature profiles for from five different types of remote sensing instruments. A the52sondeswitha3Coffsetaddedtoeachprofile from separationcriterionofnomorethan6htemporallyand left to right. 150 km spatially was used. The satellite temperature products used are from the Advanced InfraRed Sounder ground check [Vaisala, 2012a]. The temperature measurement (AIRS) [Goldberg et al., 2003], the Infrared Atmospheric is subject to calibration, solar heating, and sensor response Sounding Interferometer (IASI), the Advanced TIROS time errors. The GC25 is used to correct the calibration error Operational Vertical Sounder (ATOVS) [Reale et al., 2008], by comparing the sonde temperature measurement on the the Microwave Integrated Retrieval System (MIRS) ground with a reference sensor inside the GC25. The six-year [Boukabara et al., 2007], and GPS RO from COSMIC (2006–2011) GC temperature data at Lindenberg, Germany [Anthes et al., 2008]. Both the AIRS and IASI are show a consistent warm bias with a mean value of hyperspectral instruments. Together, they provide 3 of the  ~0.15 C[Holger Vömel, 2011, personal communication]. 10 products because IASI products are provided by both The NCAR dropsonde group also tested one MIST sonde NOAA and European Organization for the Exploitation of in our calibration chamber and found a mean warm bias of Meteorological Satellites (EUMETSAT) but using different  0.16 C. By applying the GC temperature correction, the retrieval algorithms [Maddy et al., 2009; Schlussel et al., warm bias is removed in the RS92 data. However, it is 2005]. The NOAA IASI product is available under both impractical to use the GC25 for dropsondes stored inside the clear and cloudy conditions, while the EUMETSAT IASI unmanned driftsonde gondola. Therefore, the calibration is only for clear sky. Together, ATOVS and MIRS provide  bias of ~0.15 C exists in the Concordiasi dropsonde data. six products because they are both flown on the MetOp,

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NOAA-18, and NOAA-19 satellites. The tenth product, GPS (Figure 3). ATOVS has the smallest correlation coefficients, RO, is available from the constellation of GPS satellites. In which is in concord with its large RMSE shown in Figure 2. the following discussions, we group these ten products The reproducibility is also clearly illustrated by individual into two categories: radiance-derived (including all except matched profiles (see one example in Figure 3). The general COSMIC) and GPS-RO (i.e., COSMIC). structure of the AIRS profiles matches very well with the dropsonde data. However, these retrievals do not resolve the fi detailed structure near the surface and tropopause. The cold 3. Intercomparisons of Temperature Pro les bias of the AIRS data is also evident in the scatter plot. [8] The mean bias and root-mean-square error (RMSE) of [10] The larger cold bias of the radiance-derived satellite temperature differences between sondes and satellite data relative to the dropsonde data than relative to the products are shown in Figure 2. Note that Figure 2 only radiosonde data remains unexplained. Only nine of the 16 shows ATOVS and MIRS data from NOAA-19; the data radiosonde stations use the Vaisala RS92 radiosonde which from MetOp and NOAA-18 have similar features. We first has the same temperature thermistor as in the dropsondes, focus on the results for the nine radiance-derived products but there are no systematic differences seen in the satellite cold and then the COSMIC data in the last paragraph of this bias relative to different types of radiosondes (not shown). section. All satellite data are consistently colder than The radiosonde and dropsonde temperature datasets collected the dropsonde data except in ~400–200 hPa for during Concordiasi do differ in spatial and temporal coverage. EUMETSAT_IASI and MIRS and below ~850 hPa for The Driftsonde (dropsonde) soundings cover a much larger NOAA_IASI and ATOVS. This cold bias varies from one area with greater spatial variability in temperature (Figure 1). product to another one and changes with altitude. The In contrast, the radiosonde stations are all along the coast RMSE generally increases with pressures and is consistent except the South Pole station, so the radiosonde profiles among different products except ATOVS, which has the mainly characterize the variability along the coast. A map largest RMSE. There are no significant discrepancies for of the temperature differences at 500 hPa between the different satellites using the same sounders, such as ATOVS dropsonde data and the AIRS and IASI retrievals (Figure 4) on NOAA19, NOAA18, and MetOp. All radiance-derived shows that a cold bias over the continent prevails and has much satellite products are also shown to be colder than the larger magnitude than that along the coast and the surrounding radiosonde data collected from the stations shown in ocean, where a warm bias is sometimes found. Histograms Figure 1. The cold bias with respect to dropsonde data has of the differences are also shown in Figure 4 for surface a larger magnitude than that relative to radiosonde data pressures smaller and larger 900 hPa, approximately (see an example for NOAA_IASI in Figure 2). representing the continent and the coastal/ocean region, [9] The reproducibility of the satellite data is presented as respectively. The bias is clearly larger over the continent. profiles of the correlation coefficients between the sonde Such contrast in the satellite bias between the continent and satellite data for all matched soundings and scatter plots and the ocean is also confirmed by the differences between of temperature comparisons at 500 hPa (Figure 3). The the radiosonde stations along the coast and South Pole temperatures from the satellite and sonde data are highly station (not shown). The same conclusion can be drawn correlated with statistically significant correlation coefficients for other radiance-derived satellite products.

NOAA_IASI NOAA_IASI.RAOB Aqua_AIRS NOAA_IASI.Drift NOAA19_ATOVS COSMIC.RAOB NOAA19_MIRS COSMIC.Drift EMET_IASI COSMIC Pressure (hPa) Pressure (hPa) 1000 900 800 700 600 500 400 300 200 100 0 −4 −3 −2 −101234561000 −4 900 −3 800 −2 700−1 600 500 0123456 400 300 200 100 0 Mean bias/RMSE (C) Mean bias/RMSE (C)

Figure 2. The left panel shows mean (solid line) and RMS (dashed line) differences between six satellite products and the dropsonde data. The right panel shows mean and RMS differences between NOAA_IASI or COSMIC and dropsonde (red and blue lines, denoted as “Drift” in the legend) or radiosonde data (black and green lines, denoted as “RAOB” in the legend).

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NOAA_IASI N/Cor/Mean: 252 0.87 −1.13 Aqua_AIRS

NOAA19_ATOVS −30 NOAA19_MIRS EMET_IASI

−34 COSMIC

−38

−42

T500 (C NOAA_IASI)

−46

−50 −50 −46 −42 −38 −34 −30

Aqua_AIRS.Drift 40 00199A 20101001 300

0

Driftsonde

100 Aqua_AIRS Pressure (hPa)

200

300

400

500

600

Pressure (hPa)

700

800

900

10000.5 900 0.6 800 700 0.7 600 500 0.8 4000.9 300 200 1.0 100 0

1000 Correlation (satellite/driftsonde) −90 −80 −70 −60 −50 −40 −30 −20 −10 0 Temperature (C)

Figure 3. The left panel shows correlation coefficient profiles of temperatures between satellite and dropsonde data for six satellite products. Scatter plot of matched temperatures at 500 hPa for NOAA_IASI versus dropsonde is in the upper right panel. The lower right panel shows temperature profiles for one matched sounding from dropsonde (black line) and AIRS (red line) data.

T500hPa (C NOAA_IASI−Driftsonde) T500hPa (C NOAA_IASI vs Driftsonde)

Coast/Ocean N/Mean/SD: 95/−0.51/1.32 45 <−5 Continent N/Mean/SD: 157/−2.21/2.14 −5~−4 −4~−3 −3~−2 −2~−1 −1~0 0~1 1~2 2~3 Frequency (%)

3~4 15 25 35 4~5 >5 5 0 −10−8−6−4−2 0246810 T500 (C Sonde−Sat)

T500hPa (C Aqua_AIRS−Driftsonde) T500hPa (C Aqua_AIRS vs Driftsonde)

Coast/Ocean N/Mean/SD: 162/−2.08/1.77 <−5 Continent N/Mean/SD: 201/−3.11/1.7 −5~−4

−4~−3 ) −3~−2 −2~−1 −1~0 0~1 1~2 2~3

3~4 Frequency (% 4~5 >5 0 5 15 25 35 45 −10−8−6−4−2 0246810 T500 (C Sonde−Sat)

Figure 4. Left panels: Maps of 500 hPa temperature differences between NOAA_IASI/AIRS and dropsonde data at dropsonde locations. Right panels: histogram of temperature differences for soundings over the coast and ocean (black line) and continent (red lines). Number of samplings and mean and standard deviation of the differences are also shown in the legend. The “X” symbols on the maps are the radiosonde stations.

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[11] Several factors can contribute to the temperature study shows that the unique Concordiasi dataset is useful differences between the sonde and radiance-derived satellite for validating satellite products over Antarctica, especially data shown above, including the spatial and temporal separation over the continent where the upper-air data are scarce. Many between the sondes and the satellite overpasses, errors in the scientific applications of the Concordiasi dropsonde data sonde temperature measurements, and deficiencies in the remain to be discovered, such as studying Antarctic satellite retrievals. No correlation is found between the surface-based inversions [Zhang et al., 2011] and validating temperature bias and the spatial or temporal separations, global reanalysis and model products. For example, previous suggesting that the first factor is not important. As discussed studies have shown that the near-surface temperature is too in section 2, the main errors in sonde temperature measurements warm in the weather models over the Antarctic plateau, but are calibration error, solar heating, and sensor response too cold over the surrounding sea ice due to the challenges time errors. The calibration error of ~0.15C(warmbias) in simulating the strong near-surface inversions in models is much smaller than the differences between the dropsonde [Rabier et al., 2010]. and satellite data shown in Figure 2. The sensor response [14] NPROVS was used to co-locate the Concordiasi error is expected to cause cold/warm biases in the dropsonde and radiosonde data with ten satellite products. dropsonde/radiosonde data in the troposphere. It should Comparisons of temperature profiles show consistent cold result the satellite data to have a smaller cold bias relative biases in all nine radiance-derived satellite products. The to the dropsonde data than to the radiosonde data, which is magnitude of the cold bias ranges from 0Cto4Cvaries contrary to Figure 2. The dependence of solar radiation from one product to another one and changes over altitude. errors on solar zenith angle and pressure was not found in The cold bias is larger relative to dropsonde measurements the data. Therefore, deficiencies in the radiance-derived than radiosonde measurements for all radiance-derived satellite retrievals are suspected as the primary reason for products. This is attributed to the spatial coverage difference the cold bias. These deficiencies are known to include the between the dropsonde and radiosonde data. All radiosonde difference between surface skin temperature and surface stations but one are located along the coast, while the air temperature, the complex and varied surface types over dropsondes cover the continent, coast, and surrounding Antarctica, cloud contamination, and the ability to resolve ocean (Figure 1). All radiance-derived products exhibit complex temperature structures [cf., Rabier et al., 2010]. larger cold biases over the Antarctic continent than over Detailed investigation of the causes for the cold bias in the coast and ocean. This finding would not be possible the satellite data is beyond the scope of this study and without the complete spatial coverage of the Concordiasi will require close collaboration with each satellite dropsonde data. Possible causes for the cold bias and larger product developer. bias over the continent are discussed, but investigation of [12] Comparing to the dropsonde data, the COSMIC deficiencies in satellite retrievals are left for future work. performs better than or at least the same as the radiance-derived Collaboration with the satellite product developers is temperature data above 800 hPa and shows a mean cold essential to understand these differences and improve the bias of 0.48C, which is within the 0.5C uncertainty of products. The COSMIC performs much better than other the temperature sensor (Figure 2). The COSMIC above satellite products with very good agreement with the 900 hPa agrees very well with the radiosonde data with a radiosonde data and a small cold bias comparing with the mean difference close to zero (Figure 2). The COSMIC data dropsonde data. It indicates that the GPS RO technique has also did not show the land/ocean contrast in the temperature advantages over traditional MW, IR and even hyper-spectral bias relative to the dropsonde data displayed in Figure 4. techniques. These are the absence of its dependence on surface This is likely due to the fact that the GPS RO technique is properties and availability under all weather conditions. not affected by surface conditions and weather such as Finally, the satellite retrievals do reproduce the general clouds. Our findings are inconsistent with the ~2Ccoldbias structure of temperature profiles reasonably well in spite found by Wang and Lin [2007] in the COSMIC temperature of the cold bias. data comparing to the radiosonde data. This is speculated [15]Thefindings on the systematic errors of the satellite to be partially due to the slower response of Vaisala RS80 temperature retrievals over Antarctica have potential significant or RS90 temperature sensor used in Wang and Lin [2007] implications on past and future research on Antarctic weather than Vaisala RS92 launched at nine out of 13 radiosonde and climate. Over Antarctica, the scarcity of in-situ observations stations during Concordiasi period. Note that the slow especially over the interior continent makes it more response causes a warm bias in the radiosonde data. important to assimilate satellite data in weather and climate models and to analyze satellite data to study the Antarctic climate changes. Previous studies also show that satellite 4. Conclusions data have much larger impact on the forecasts and [13] Thirteen NCAR Driftsonde systems were deployed reanalyses in Antarctica than in areas, such as the Arctic, in the Concordiasi field experiment over Antarctica where more in-situ measurements are available [cf., Rabier from September to December 2010. They collected 639 et al., 2010]. As a result, any systematic error in the satellite unprecedented pressure, temperature, humidity, and wind retrievals would translate in greater errors in model forecasts profiles from the stratosphere to the surface with high data and reanalyses. Bracegirdle and Marshall [2012] found that quality, high vertical resolution, and large spatial coverage. four current global reanalysis products show a domination The soundings cover the Antarctic continent, coast, and of cold biases over the period 1999–2008 when compared surrounding ocean, including areas where in-situ upper-air with the radiosonde data, with the largest bias at observations have never before been made. The Antarctic Amundsen-Scott station. This result is consistent with the polar vortex provides ideal conditions for deploying the long characteristics of satellite biases found in this study. Further duration stratospheric balloons carrying the Driftsondes. This investigation is required to understand whether such a cold

1235 WANG ET AL.: DROPSONDE OBSERVATIONS OVER ANTARCTICA bias in the reanalyses is a result of biases in the input satellite Parsons, D., P. Harr, T. Nakazawa, S. Jones, and M. Weissmann (2008), An fi overview of the THORPEX-Pacific Asian Regional Campaign (T-PARC) data. In spite of signi cant efforts to reconstruct in-situ during August–September 2008, Preprints, 28th Conf. on Hurricanes and Antarctic temperature records and study trends [Screen Tropical Meteorology, Orlando, FL, Amer. Meteor. Soc., 7C.7. and Simmonds, 2012; references therein], there are still Rabier, F., et al. (2010), The CONCORDIASI Project in Antarctica, Bull. – few studies using the satellite data other than Johanson Am. Meteor. Soc., 91,69 86, doi:10.1175/2009BAMS2764.1 Reale, T., B. Sun, F. H. Tilley, M. Pettey (2012), The NOAA Products and Fu [2007]. Further improvement of satellite temperature Validation System (NPROVS), J. Atmos. Oceanic Technol., 29,629–645. retrievals over Antarctica is needed to reconstruct consistent doi:10.1175/JTECH-D-11-00072.1. long-term records for climate studies. Reale, T., F. Tilley, M. Ferguson, and A. Allegrino (2008), NOAA operational sounding products for ATOVS, Int. J. Remote Sens., 29, 4615–4651, doi:10.1080/01431160802020502. [16] Acknowledgments. The Concordiasi driftsonde data have been Redelsperger, J.-L., C. D. Thorncroft, A. Diedhiou, T. Lebel, D. J. Parker, obtained through cooperation between UCAR and CNES, under the J. Polcher (2006), African Monsoon Multidisciplinary Analysis: An sponsorship of the NSF and the CNES. NSF Office of Polar Program international research project and field campaign, Bull. Amer. Meteor. supported the Concordiasi Driftsonde deployment through the grant Soc., 87, 1739–1746. doi:10.1175/BAMS-87-12-1739. ANT-0733007. We are grateful to all NCAR/EOL and French CNAS staff SCAR (2009), Antarctic Climate Change and the Environment, Edited by that developed Driftsonde system, and all of people who participated J Turner, R A Bindschadler, P Convey, G Di Prisco, E Fahrbach, J Gutt, in Concordiasi to deploy and operate the system and collect the data. D A Hodgson, P A Mayewski and C P Summerhayes, Published in We also would like to thank Florence Rabier and other Concordiasi principle Cambridge by SCAR, ISBN 978-0-948277-22-1. investigators for leading the project. Comments from Jordan Powers and Schlussel, P., T. H. Hultberg, P. L. Phillips, T. August, and X. Calbet (2005), Bill Brown have been very helpful. The National Center for Atmospheric The operational IASI level 2 processor, Adv. Space Res., 26,982–988, Research is sponsored by the National Science Foundation. doi:10.1016/j.asr.2005.03.008. Screen, J. A., and I. 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