17 research outputs found
The SPARC Water Vapor Assessment II: assessment of satellite measurements of upper tropospheric humidity
Nineteen limb-viewing data sets (occultation, passive thermal, and UV scattering) and two nadir upper tropospheric humidity (UTH) data sets are intercompared and also compared to frost-point hygrometer balloon sondes. The upper troposphere considered here covers the pressure range from 300-100 hPa. UTH is a challenging measurement, because concentrations vary between 2-1000 ppmv (parts per million by volume), with sharp changes in vertical gradients near the tropopause. Cloudiness in this region also makes the measurement challenging. The atmospheric temperature is also highly variable ranging from 180-250 K. The assessment of satellite-measured UTH is based on coincident comparisons with balloon frost-point hygrometer sondes, multi-month mapped comparisons, zonal mean time series comparisons, and coincident satellite-to-satellite comparisons. While the satellite fields show similar features in maps and time series, quantitatively they can differ by a factor of 2 in concentration, with strong dependencies on the amount of UTH. Additionally, time-lag response-corrected Vaisala RS92 radiosondes are compared to satellites and the frost-point hygrometer measurements. In summary, most satellite data sets reviewed here show on average similar to 30 % agreement amongst themselves and frost-point data but with an additional similar to 30 % variability about the mean bias. The Vaisala RS92 sonde, even with a time-lag correction, shows poor behavior for pressures less than 200 hPa
The SPARC Water Vapor Assessment II: assessment of satellite measurements of upper tropospheric humidity
Nineteen limb-viewing data sets (occultation, passive thermal, and UV scattering) and two nadir upper tropospheric humidity (UTH) data sets are intercompared and also compared to frost-point hygrometer balloon sondes. The upper troposphere considered here covers the pressure range from 300–100 hPa. UTH is a challenging measurement, because concentrations vary between 2–1000 ppmv (parts per million by volume), with sharp changes in vertical gradients near the tropopause. Cloudiness in this region also makes the measurement challenging. The atmospheric temperature is also highly variable ranging from 180–250 K. The assessment of satellite-measured UTH is based on coincident comparisons with balloon frost-point hygrometer sondes, multi-month mapped comparisons, zonal mean time series comparisons, and coincident satellite-to-satellite comparisons. While the satellite fields show similar features in maps and time series, quantitatively they can differ by a factor of 2 in concentration, with strong dependencies on the amount of UTH. Additionally, time-lag response-corrected Vaisala RS92 radiosondes are compared to satellites and the frost-point hygrometer measurements. In summary, most satellite data sets reviewed here show on average ∼30 % agreement amongst themselves and frost-point data but with an additional ∼30 % variability about the mean bias. The Vaisala RS92 sonde, even with a time-lag correction, shows poor behavior for pressures less than 200 hPa
-WAVVAP) campaign
[1] We present a validation study for the ground-based Middle Atmospheric Water Vapour Radiometer (MIAWARA) operating at 22 GHz. MIAWARA measures the water vapor profile in the range of 20-80 km. The validation was conducted in two phases at different geographical locations. During the first operational period the radiometer was operated at middle latitudes in Bern, Switzerland, and the measured water vapor profiles were compared with the HALOE satellite instrument. The agreement between HALOE and MIAWARA was for most altitudes better than 10%. The agreement between the balloon instruments and MIAWARA was better than 2% for a total number of 10 comparable flights. This showed the potential of MIAWARA in water vapor retrieval down to 20 km. In addition, the northern Finland MIAWARA profiles were compared with POAM III water vapor profiles. This comparison confirmed the good agreement with the other instruments, and the difference between MIAWARA and POAM was generally less than 8%. Finally, the tipping curve calibration was validated with tipping curve measurements of the All-Sky Multi Wavelength Radiometer (ASMUWARA) which was operated 10 months side by side with MIAWARA. The agreement of the tropospheric opacity derived from these tipping curves agree within 1%
The SPARC water vapour assessment II: comparison of annual, semi-annual and quasi-biennial variations in stratospheric and lower mesospheric water vapour observed from satellites
In the framework of the second SPARC (Stratosphere-troposphere Processes And their Role in Climate) water vapour assessment (WAVAS-II), the amplitudes and phases of the annual, semi-annual and quasi-biennial variation in stratospheric and lower mesospheric water were compared using 30 data sets from 13 different satellite instruments. These comparisons aimed to provide a comprehensive overview of the typical uncertainties in the observational database which can be considered in subsequent observational and modelling studies. For the amplitudes, a good agreement of their latitude and altitude distribution was found. Quantitatively there were differences in particular at high latitudes, close to the tropopause and in the lower mesosphere. In these regions, the standard deviation over all data sets typically exceeded 0.2 ppmv for the annual variation and 0.1 ppmv for the semi-annual and quasi-biennial variation. For the phase, larger differences between the data sets were found in the lower mesosphere. Generally the smallest phase uncertainties can be observed in regions where the amplitude of the variability is large. The standard deviations of the phases for all data sets were typically smaller than a month for the annual and semi-annual variation and smaller than 5 months for the quasi-biennial variation. The amplitude and phase differences among the data sets are caused by a combination of factors. In general, differences in the temporal variation of systematic errors and in the observational sampling play a dominant role. In addition, differences in the vertical resolution of the data, the considered time periods and influences of clouds, aerosols as well as non-local thermodynamic equilibrium (NLTE) effects cause differences between the individual data sets
The SPARC water vapour assessment II: biases and drifts of water vapour satellite data records with respect to frost point hygrometer records
Satellite data records of stratospheric water vapour have been compared to balloon-borne frost point hygrometer (FP) profiles that are coincident in space and time. The satellite data records of 15 different instruments cover water vapour data available from January 2000 through December 2016. The hygrometer data are from 27 stations all over the world in the same period. For the comparison, real or constructed averaging kernels have been applied to the hygrometer profiles to adjust them to the measurement characteristics of the satellite instruments. For bias evaluation, we have compared satellite profiles averaged over the available temporal coverage to the means of coincident FP profiles for individual stations. For drift determinations, we analysed time series of relative differences between spatiotemporally coincident satellite and hygrometer profiles at individual stations. In a synopsis we have also calculated the mean biases and drifts (and their respective uncertainties) for each satellite record over all applicable hygrometer stations in three altitude ranges (10–30 hPa, 30–100 hPa, and 100 hPa to tropopause). Most of the satellite data have biases <10 % and average drifts <1 % yr−1 in at least one of the respective altitude ranges. Virtually all biases are significant in the sense that their uncertainty range in terms of twice the standard error of the mean does not include zero. Statistically significant drifts (95 % confidence) are detected for 35 % of the ≈ 1200 time series of relative differences between satellites and hygrometers
The SPARC water vapor assessment II: intercomparison of satellite and ground-based microwave measurements
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)
Comparison of Three High Resolution Real-Time Spectrometers for Microwave Ozone Profiling Instruments
In this contribution, we present a comparison of three digital real-time spectrometers used in passive remote sensing of ozone and other trace gases in the middle atmosphere. During a period of six months, we connected the spectrometers to the same radiometric front-end to perform parallel observations of the ozone emission line at 110.836 GHz. This allowed us to better characterize a bias previously observed on the integrated spectra of the Acqiris AC240, a widely used digital spectrometer which has been used for more than a decade in many operational microwave radiometers. We investigated the bias under different atmospheric conditions and found that it is caused by multiple sources. Nonlinearities in the calibration are responsible for part of the bias, but a larger contribution stems from a second effect in the AC240. Although this error source is still partly unexplained, we found that a simple correction scheme simulating a spectral leakage can be applied to the integrated spectra of the AC240 and worked well on our range of observations. We also show that by applying our bias correction to the spectra, we can correct the bias in the ozone retrievals. There is still a need for further measurements to validate this approximate correction, but it could help to correct the numerous time series of ozone and other atmospheric constituents recorded by the AC240