Validation of long-term measurements of water vapor from the midstratosphere to the mesosphere at two Network for the Detection of Atmospheric Composition Change sites

2013 ◽  
Vol 118 (2) ◽  
pp. 934-942 ◽  
Author(s):  
Gerald E. Nedoluha ◽  
R. Michael Gomez ◽  
Helen Neal ◽  
Alyn Lambert ◽  
Dale Hurst ◽  
...  
Keyword(s):  
Water Vapor ◽  
Atmospheric Composition ◽  
Composition Change

scholarly journals Re-analysis of ground-based microwave ClO measurements from Mauna Kea, 1992 to early 2012

2013 ◽  
Vol 13 (17) ◽  
pp. 8643-8650 ◽  
Author(s):  
B. J. Connor ◽  
T. Mooney ◽  
G. E. Nedoluha ◽  
J. W. Barrett ◽  
A. Parrish ◽  
...  
Keyword(s):  
Atmospheric Composition ◽  
Composition Change ◽  
Major Focus ◽  
Short Term ◽  
Data Set ◽  
Long Term Changes ◽  
The Difference ◽  
Long Term Trend ◽  
Linear Decline

Abstract. We present a re-analysis of upper stratospheric ClO measurements from the ground-based millimeter-wave instrument from January 1992 to February 2012. These measurements are made as part of the Network for the Detection of Atmospheric Composition Change (NDACC) from Mauna Kea, Hawaii, (19.8° N, 204.5° E). Here, we use daytime and nighttime measurements together to form a day–night spectrum, from which the difference in the day and night profiles is retrieved. These results are then compared to the day–night difference profiles from the Upper Atmosphere Research Satellite (UARS) and Aura Microwave Limb Sounder (MLS) instruments. We also compare them to our previous analyses of the same data, in which we retrieved the daytime ClO profile. The major focus will be on comparing the year-to-year and long-term changes in ClO derived by the two analysis methods, and comparing these results to the long-term changes reported by others. We conclude that the re-analyzed data set has less short-term variability and exhibits a more constant long-term trend that is more consistent with other observations. Data from 1995 to 2012 indicate a linear decline of mid-stratospheric ClO of 0.64 ± 0.15% yr−1 (2σ).

scholarly journals Technical Note: Harmonized retrieval of column-integrated atmospheric water vapor from the FTIR network – first examples for long-term records and station trends

2009 ◽  
Vol 9 (22) ◽  
pp. 8987-8999 ◽  
Author(s):  
R. Sussmann ◽  
T. Borsdorff ◽  
M. Rettinger ◽  
C. Camy-Peyret ◽  
P. Demoulin ◽  
...  
Keyword(s):  
Water Vapor ◽  
Regional Scale ◽  
Significant Trend ◽  
Atmospheric Water Vapor ◽  
Atmospheric Composition ◽  
Time Interval ◽  
Atmospheric Water ◽  
Uncertainty Interval ◽  
Homogeneous Surface

Abstract. We present a method for harmonized retrieval of integrated water vapor (IWV) from existing, long-term, measurement records at the ground-based mid-infrared solar FTIR spectrometry stations of the Network for the Detection of Atmospheric Composition Change (NDACC). Correlation of IWV from FTIR with radiosondes shows an ideal slope of 1.00(3). This optimum matching is achieved via tuning one FTIR retrieval parameter, i.e., the strength of a Tikhonov regularization constraining the derivative (with respect to height) of retrieved water profiles given in per cent difference relative to an a priori profile. All other FTIR-sonde correlation parameters (intercept=0.02(12) mm, bias=0.02(5) mm, standard deviation of coincident IWV differences (stdv)=0.27 mm, R=0.99) are comparable to or better than results for all other ground-based IWV sounding techniques given in the literature. An FTIR-FTIR side-by-side intercomparison reveals a strong exponential increase in stdv as a function of increasing temporal mismatch starting at Δt≈1 min. This is due to atmospheric water vapor variability. Based on this result we derive an upper limit for the precision of the FTIR IWV retrieval for the smallest Δt(=3.75 min) still giving a statistically sufficient sample (32 coincidences), i.e., precision(IWVFTIR)<0.05 mm (or 2.2% of the mean IWV). The bias of the IWV retrievals from the two different FTIR instruments is nearly negligible (0.02(1) mm). The optimized FTIR IWV retrieval is set up in the standard NDACC algorithm SFIT 2 without changes to the code. A concept for harmonized transfer of the retrieval between different stations deals with all relevant control parameters; it includes correction for differing spectral point spacings (via regularization strength), and final quality selection of the retrievals (excluding the highest residuals (measurement minus model), 5% of the total). As first application examples long-term IWV data sets are retrieved from the FTIR records of the Zugspitze (47.4° N, 11.0° E, 2964 m a.s.l.) and Jungfraujoch (46.5° N, 8.0° E, 3580 m a.s.l.) NDACC sites. Station-trend analysis comprises a linear fit after subtracting an intra-annual model (3 Fourier components) and constructing an uncertainty interval [95% confidence] via bootstrap resampling. For the Zugspitze a significant trend of 0.79 [0.65, 0.92] mm/decade is found for the time interval [1996–2008], whereas for the Jungfraujoch no significant trend is found. This confirms recent findings that strong variations of IWV trends do occur above land on the local to regional scale (≈250 km) in spite of homogeneous surface temperature trends. This paper provides a basis for future exploitation of more than a dozen existing, multi-decadal FTIR measurement records around the globe for climate studies.

scholarly journals Ground-based water vapor raman lidar measurements up to the upper troposphere and lower stratosphere for long-term monitoring

2012 ◽  
Vol 5 (1) ◽  
pp. 17-36 ◽  
Author(s):  
T. Leblanc ◽  
I. S. McDermid ◽  
T. D. Walsh
Keyword(s):  
Water Vapor ◽  
Lower Stratosphere ◽  
Lower Troposphere ◽  
Atmospheric Composition ◽  
Raman Lidar ◽  
Upper Troposphere ◽  
Lidar Measurements ◽  
Development Data ◽  
Instrumental Development

Abstract. Recognizing the importance of water vapor in the upper troposphere and lower stratosphere (UTLS) and the scarcity of high-quality, long-term measurements, JPL began the development of a powerful Raman lidar in 2005 to try to meet these needs. This development was endorsed by the Network for the Detection of Atmospheric Composition Change (NDACC) and the validation program for the EOS-Aura satellite. In this paper we review the stages in the instrumental development, data acquisition and analysis, profile retrieval and calibration procedures of the lidar, as well as selected results from three validation campaigns: MOHAVE (Measurements of Humidity in the Atmosphere and Validation Experiments), MOHAVE-II, and MOHAVE 2009. In particular, one critical result from this latest campaign is the very good agreement (well below the reported uncertainties) observed between the lidar and the Cryogenic Frost-Point Hygrometer in the entire lidar range 3–20 km, with a mean bias not exceeding 2% (lidar dry) in the lower troposphere, and 3% (lidar moist) in the UTLS. Ultimately the lidar has demonstrated capability to measure water vapor profiles from ∼1 km above the ground to the lower stratosphere with a precision of 10% or better near 13 km and below, and an estimated accuracy of 5%. Since 2005, nearly 1000 profiles have been routinely measured, and since 2009, the profiles have typically reached 14 km for one-hour integration times and 1.5 km vertical resolution, and can reach 21 km for 6-h integration times using degraded vertical resolutions. These performance figures show that, with our present target of routinely running our lidar two hours per night, 4 nights per week, we can achieve measurements with a precision in the UTLS equivalent to that achieved if launching one CFH per month.

scholarly journals Re-analysis of ground-based microwave ClO measurements from Mauna Kea, 1992 to early 2012

2012 ◽  
Vol 12 (11) ◽  
pp. 30571-30588
Author(s):  
B. J. Connor ◽  
T. Mooney ◽  
G. E Nedoluha ◽  
J. W. Barrett ◽  
A. Parrish ◽  
...  
Keyword(s):  
Atmospheric Composition ◽  
Composition Change ◽  
Major Focus ◽  
Short Term ◽  
Data Set ◽  
Trend Data ◽  
The Difference ◽  
Long Term Trend ◽  
Linear Decline

Abstract. We present a re-analysis of upper stratospheric ClO measurements from the ground-based millimeter-wave instrument from January 1992 to February 2012. These measurements are made as part of the Network for the Detection of Atmospheric Composition Change (NDACC) from Mauna Kea, Hawaii, (19.8° N, 204.5° E). Here, we use daytime and nighttime measurements together to form a day-night spectrum, from which the difference in the day and night profiles is retrieved. These results are then compared to the day-night difference profiles from the UARS and Aura Microwave Limb Sounder (MLS) instruments. We also compare them to our previous analyses of the same data, in which we retrieved the daytime ClO profile. The major focus will be on comparing the year-to-year and long-term changes in ClO derived by the two analysis methods. We conclude that the re-analyzed data set has less short-term variability and exhibits a more constant long-term trend. Data from 1995–2012 indicate a linear decline of mid-stratospheric ClO of 0.64 ± 0.08% yr−1.

scholarly journals Ground-based water vapor Raman lidar measurements up to the upper troposphere and lower stratosphere – Part 2: Data analysis and calibration for long-term monitoring

2011 ◽  
Vol 4 (4) ◽  
pp. 5111-5145 ◽  
Author(s):  
T. Leblanc ◽  
I. S. McDermid ◽  
T. D. Walsh
Keyword(s):  
Water Vapor ◽  
Data Analysis ◽  
Lower Stratosphere ◽  
Companion Paper ◽  
Atmospheric Composition ◽  
Raman Lidar ◽  
Upper Troposphere ◽  
Current Configuration ◽  
Instrumental Development

Abstract. The well-recognized, key role of water vapor in the upper troposphere and lower stratosphere (UT/LS) and the scarcity of high-quality, long-term measurements triggered the development by JPL of a powerful Raman lidar to try to meet these needs. This development started in 2005 and was endorsed by the Network for the Detection of Atmospheric Composition Change (NDACC) and the validation program for the EOS-Aura satellite. In this paper we review all the stages of the instrument data acquisition, data analysis, profile retrieval and calibration procedures, as well as selected results from the recent validation campaign MOHAVE-2009 (Measurements of Humidity in the Atmosphere and Validation Experiments). The stages in the instrumental development and the conclusions from three validation campaigns (including MOHAVE-2009) are presented in details in a companion paper (McDermid et al., 2011). In its current configuration, the lidar demonstrated capability to measure water vapor profiles from ~1 km above the ground to the lower stratosphere with an estimated accuracy of 5 %. Since 2005, nearly 1000 profiles have been routinely measured with a precision of 10 % or better near 13 km. Since 2009, the profiles have typically reached 14 km for 1 h integration times and 1.5 km vertical resolution, and can reach 21 km for 6-h integration times using degraded vertical resolutions.

scholarly journals Ground-based water vapor Raman lidar measurements up to the upper troposphere and lower stratosphere – Part 1: Instrument development, optimization, and validation

2011 ◽  
Vol 4 (4) ◽  
pp. 5079-5109 ◽  
Author(s):  
I. S. McDermid ◽  
T. Leblanc ◽  
T. D. Walsh
Keyword(s):  
Water Vapor ◽  
Lower Stratosphere ◽  
Companion Paper ◽  
Atmospheric Composition ◽  
Raman Lidar ◽  
Upper Troposphere ◽  
Lidar Measurements ◽  
Instrumental Development ◽  
Validation Experiments

Abstract. Recognizing the importance of water vapor in the upper troposphere and lower stratosphere (UT/LS) and the scarcity of high-quality, long-term measurements, JPL began the development of a powerful Raman lidar in 2005 to try to meet these needs. This development was endorsed by the Network for the Detection of Atmospheric Composition Change (NDACC) and the validation program for the EOS-Aura satellite. In this paper we review the stages in the instrumental development of the lidar and the conclusions from three validation campaigns: MOHAVE, MOHAVE-II, and MOHAVE 2009 (Measurements of Humidity in the Atmosphere and Validation Experiments). The data analysis, profile retrieval and calibration procedures, as well as additional results from MOHAVE-2009 are presented in detail in a companion paper (Leblanc et al., 2011a). Ultimately the lidar has demonstrated capability to measure water vapor profiles from ~1 km above the ground to the lower stratosphere, reaching 14 km for 1-h integrated profiles and 21 km for 6-h integrated profiles, with a precision of 10 % or better near 13 km and below, and an estimated accuracy of 5 %.

scholarly journals The SPARC water vapor assessment II: intercomparison of satellite and ground-based microwave measurements

2017 ◽  
Vol 17 (23) ◽  
pp. 14543-14558 ◽  
Author(s):  
Gerald E. Nedoluha ◽  
Michael Kiefer ◽  
Stefan Lossow ◽  
R. Michael Gomez ◽  
Niklaus Kämpfer ◽  
...  
Keyword(s):  
Water Vapor ◽  
Middle Atmosphere ◽  
Atmospheric Composition ◽  
Microwave Measurements ◽  
Interannual Variations ◽  
Composition Change ◽  
Mauna Loa ◽  
Trend Assessment ◽  
The Mean ◽  
Almost All

Abstract. As part of the second SPARC (Stratosphere–troposphere Processes And their Role in Climate) water vapor assessment (WAVAS-II), we present measurements taken from or coincident with seven sites from which ground-based microwave instruments measure water vapor in the middle atmosphere. Six of the ground-based instruments are part of the Network for the Detection of Atmospheric Composition Change (NDACC) and provide datasets that can be used for drift and trend assessment. We compare measurements from these ground-based instruments with satellite datasets that have provided retrievals of water vapor in the lower mesosphere over extended periods since 1996. We first compare biases between the satellite and ground-based instruments from the upper stratosphere to the upper mesosphere. We then show a number of time series comparisons at 0.46 hPa, a level that is sensitive to changes in H2O and CH4 entering the stratosphere but, because almost all CH4 has been oxidized, is relatively insensitive to dynamical variations. Interannual variations and drifts are investigated with respect to both the Aura Microwave Limb Sounder (MLS; from 2004 onwards) and each instrument's climatological mean. We find that the variation in the interannual difference in the mean H2O measured by any two instruments is typically  ∼  1%. Most of the datasets start in or after 2004 and show annual increases in H2O of 0–1 % yr−1. In particular, MLS shows a trend of between 0.5 % yr−1 and 0.7 % yr−1 at the comparison sites. However, the two longest measurement datasets used here, with measurements back to 1996, show much smaller trends of +0.1 % yr−1 (at Mauna Loa, Hawaii) and −0.1 % yr−1 (at Lauder, New Zealand).

scholarly journals Technical Note: New trends in column-integrated atmospheric water vapor – Method to harmonize and match long-term records from the FTIR network to radiosonde characteristics

2009 ◽  
Vol 9 (3) ◽  
pp. 13199-13233 ◽  
Author(s):  
R. Sussmann ◽  
T. Borsdorff ◽  
M. Rettinger ◽  
C. Camy-Peyret ◽  
P. Demoulin ◽  
...  
Keyword(s):  
Water Vapor ◽  
Trend Analysis ◽  
Technical Note ◽  
Significant Trend ◽  
Atmospheric Water Vapor ◽  
Atmospheric Composition ◽  
Time Interval ◽  
Atmospheric Water ◽  
Uncertainty Interval

Abstract. We present a method for harmonized retrieval of integrated water vapor (IWV) trends from existing, long-term, measurement records at the ground-based mid-infrared solar FTIR spectrometry stations of the Network for the Detection of Atmospheric Composition Change (NDACC). Correlation of IWV from FTIR with radiosondes shows an ideal slope of 1.00(3). This optimum matching is achieved via tuning one FTIR retrieval parameter, i.e., the strength of a Tikhonov regularization constraining the derivative (with respect to height) of retrieved water profiles given in per cent difference relative to an a priori profile. All other FTIR-sonde correlation parameters (intercept =0.02(12) mm, bias =0.02(5) mm, standard deviation of coincident IWV differences (stdv)=0.27 mm, R=0.99) are comparable to or better than results for all other ground-based IWV sounding techniques given in the literature. An FTIR-FTIR side-by-side intercomparison reveals a strong exponential increase in stdv as a function of increasing temporal mismatch starting at Δt ~1 min. This is due to atmospheric water vapor variability. Based on this result we derive an upper limit for the precision of the FTIR IWV retrieval for the smallest Δt(=3.75 min) still giving a statistically sufficient sample (32 coincidences), i.e., precision (IWVFTIR)<0.05 mm (or 2.2% of the mean IWV). The bias of the IWV retrievals from the two different FTIR instruments is nearly negligible (0.02(1) mm). The optimized FTIR IWV retrieval is set up in the standard NDACC algorithm SFIT 2 without changes to the code. A concept for harmonized transfer of the retrieval between different stations deals with all relevant control parameters; it includes correction for differing spectral point spacings (via regularization strength), and final quality selection of the retrievals (excluding the highest residuals (measurement minus model), 5% of the total). The method is demonstrated via IWV trend analysis from the FTIR records at the Zugspitze (47.4° N, 11.0° E, 2964 m a.s.l.) and Jungfraujoch (46.5° N, 8.0° E, 3580 m a.s.l.) NDACC stations. Trend analysis comprises a linear fit after subtracting an intra-annual model (3 Fourier components) and constructing an uncertainty interval (95% confidence) via bootstrap resampling. For the Zugspitze a significant trend of 0.79 (0.65, 0.92) mm/decade is found for the time interval (1996–2008). There is a significantly increased trend of 1.41 (1.14, 1.69) mm/decade in the second part of the time series (2003–2008) compared to 0.63 (0.20, 1.06) mm/decade in the first part (1996–2002). For the Jungfraujoch no significant trend is found in any of the periods (1988–2008), (1996–2008), (1996–2002), or (2003–2008). The results imply either an altitude dependency with a significantly higher trend below 3.58 km than above, and/or strong, regional variations of IWV trends on the scale of ~250 km. This is in line with a widespread, complex, IWV trend picture over Eurasia during the last decades. Our paper provides a basis for future exploitation of more than a dozen existing, multi-decadal FTIR measurement records around the globe for joint IWV trend studies within NDACC that complement existing trend data sets which are based primarily on radiosondes.

scholarly journals The SPARC water vapor assessment II: intercomparison of satellite and ground-based microwave measurements

2017 ◽  
Author(s):  
Gerald E. Nedoluha ◽  
Michael Kiefer ◽  
Stefan Lossow ◽  
R. Michael Gomez ◽  
Niklaus Kämpfer ◽  
...  
Keyword(s):  
Time Series ◽  
Water Vapor ◽  
Middle Atmosphere ◽  
Atmospheric Composition ◽  
Microwave Measurements ◽  
Interannual Variations ◽  
Composition Change ◽  
Trend Assessment ◽  
The Mean ◽  
Almost All

Abstract. As part of the second SPARC (Stratosphere-troposphere Processes And their Role in Climate) water vapour assessment (WAVAS-II), we present measurements taken from, or coincident with, seven sites from which ground-based microwave instruments measure water vapor in the middle atmosphere. Six of the ground-based instruments are part of the Network for the Detection of Atmospheric Composition Change (NDACC) and provide datasets which can be used for drift and trend assessment. We compare measurements from these ground-based instruments with satellite datasets that have provided retrievals of water vapor in the lower mesosphere over extended periods since 1996. We first compare biases between the satellite and ground-based instruments from the upper stratosphere to the upper mesosphere. We then show a number of time series comparisons at 0.46 hPa, a level that is sensitive to changes in H2O and CH4 entering the stratosphere, but, because almost all CH4 has been oxidized, is relatively insensitive to dynamical variations. Interannual variations and drifts are investigated both with respect to the Aura Microwave Limb Sounder (MLS) (from 2004 onwards), and with respect to each instrument's climatological mean. We find that the variation in the interannual difference in the mean H2O measured by any two instruments is typically ~ 1 %. Most of the datasets start in, or after, 2004, and show annual increases in H2O of 0–1 %/year. In particular, MLS shows a trend of between 0.5 %/year and 0.7 %/year at the comparison sites. However the two longest measurement datasets used here, with measurements back to 1996, show a much smaller trend of between +0.1 %/year and −0.1 %/year.

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