Optimal estimation of tropospheric H 2 O and δD with IASI/METOP
TL;DR: In this article, the IASI spectra were used to retrieve H2O profiles between the surface and the upper troposphere as well as middle tro- pospheric D values.
Abstract: We present optimal estimates of tropospheric H2O and D derived from radiances measured by the instrument IASI (Infrared Atmospheric Sounding Interferometer) flown on EUMETSAT's polar orbiter METOP. We document that the IASI spectra allow for retrieving H2O profiles between the surface and the upper troposphere as well as middle tro- pospheric D values. A theoretical error estimation suggests a precision for H2O of better than 35 % in the lower tro- posphere and of better than 15 % in the middle and upper troposphere, respectively, whereby surface emissivity and atmospheric temperature uncertainties are the leading error sources. For the middle tropospheric D values we estimate a precision of 15-20 ‰ with the measurement noise being the dominating error source. The accuracy of the IASI products is estimated to about 20-10 % and 10 ‰ for lower to upper tropospheric H2O and middle tropospheric D, respectively. It is limited by systematic uncertainties in the applied spec- troscopic parameters and the a priori atmospheric tempera- ture profiles. We compare our IASI products to a large num- ber of near coincident radiosonde in-situ and ground-based FTS (Fourier Transform Spectrometer) remote sensing mea- surements. The bias and the scatter between the different H2O and D data sets are consistent with the combined theo- retical uncertainties of the involved measurement techniques.
Citations
More filters
TL;DR: In this article, a new short-wave infrared (SWIR) retrieval of the column-averaged HDO/H2O ratio from the Japanese Greenhouse Gases Observing Satellite (GOSAT) is reported.
Abstract: . We report a new shortwave infrared (SWIR) retrieval of the column-averaged HDO/H2O ratio from the Japanese Greenhouse Gases Observing Satellite (GOSAT). From synthetic simulation studies, we have estimated that the inferred δD values will typically have random errors between 20‰ (desert surface and 30° solar zenith angle) and 120‰ (conifer surface and 60° solar zenith angle). We find that the retrieval will have a small but significant sensitivity to the presence of cirrus clouds, the HDO a priori profile shape and atmospheric temperature, which has the potential of introducing some regional-scale biases in the retrieval. From comparisons to ground-based column observations from the Total Carbon Column Observing Network (TCCON), we find differences between δD from GOSAT and TCCON of around −30‰ for northern hemispheric sites which increase up to −70‰ for Australian sites. The bias for the Australian sites significantly reduces when decreasing the spatial co-location criteria, which shows that spatial averaging contributes to the observed differences over Australia. The GOSAT retrievals allow mapping the global distribution of δD and its variations with season, and we find in our global GOSAT retrievals the expected strong latitudinal gradients with significant enhancements over the tropics. The comparisons to the ground-based TCCON network and the results of the global retrieval are very encouraging, and they show that δD retrieved from GOSAT should be a useful product that can be used to complement datasets from thermal-infrared sounder and ground-based networks and to extend the δD dataset from SWIR retrievals established from the recently ended SCIAMACHY mission.
50 citations
TL;DR: In this paper, the authors present the final MUSICA products, and discuss the characteristics and potential of the NDACC/FTIR and MetOp/IASI {H2O,δD} data pairs.
Abstract: . In the lower/middle troposphere, {H2O,δD} pairs are good proxies for moisture pathways; however, their observation, in particular when using remote sensing techniques, is challenging. The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) addresses this challenge by integrating the remote sensing with in situ measurement techniques. The aim is to retrieve calibrated tropospheric {H2O,δD} pairs from the middle infrared spectra measured from ground by FTIR (Fourier transform infrared) spectrometers of the NDACC (Network for the Detection of Atmospheric Composition Change) and the thermal nadir spectra measured by IASI (Infrared Atmospheric Sounding Interferometer) aboard the MetOp satellites. In this paper, we present the final MUSICA products, and discuss the characteristics and potential of the NDACC/FTIR and MetOp/IASI {H2O,δD} data pairs. First, we briefly resume the particularities of an {H2O,δD} pair retrieval. Second, we show that the remote sensing data of the final product version are absolutely calibrated with respect to H2O and δD in situ profile references measured in the subtropics, between 0 and 7 km. Third, we reveal that the {H2O,δD} pair distributions obtained from the different remote sensors are consistent and allow distinct lower/middle tropospheric moisture pathways to be identified in agreement with multi-year in situ references. Fourth, we document the possibilities of the NDACC/FTIR instruments for climatological studies (due to long-term monitoring) and of the MetOp/IASI sensors for observing diurnal signals on a quasi-global scale and with high horizontal resolution. Fifth, we discuss the risk of misinterpreting {H2O,δD} pair distributions due to incomplete processing of the remote sensing products.
49 citations
TL;DR: In this paper, the Smithsonian Astrophysical Observatory (SAO) OMI operational retrieval algorithm was used to derive the slant column density (SCD) of water vapor using the 430-480 nm spectral region after extensive optimization.
Abstract: . There are distinct spectral features of water vapor in the wavelength range covered by the Ozone Monitoring Instrument (OMI) visible channel. Although these features are much weaker than those at longer wavelengths, they can be exploited to retrieve useful information about water vapor. They have an advantage in that their small optical depth leads to fairly simple interpretation as measurements of the total water vapor column density. We have used the Smithsonian Astrophysical Observatory (SAO) OMI operational retrieval algorithm to derive the slant column density (SCD) of water vapor using the 430–480 nm spectral region after extensive optimization. We convert from SCD to vertical column density (VCD) using the air mass factor (AMF), which is calculated using look-up tables of scattering weights and assimilated water vapor profiles. Our Level 2 product includes not only water vapor VCD but also the associated scattering weights and AMF. In the tropics, our standard water vapor product has a median SCD of 1.3 × 1023 molecules cm−2 and a median relative uncertainty of about 11%, about a factor of 2 better than that from a similar OMI algorithm that uses a narrower retrieval window. The corresponding median VCD is about 1.2 × 1023 molecules cm−2. We have examined the sensitivities of SCD and AMF to various parameters and compared our results with those from the GlobVapour product, the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Aerosol Robotic NETwork (AERONET).
47 citations
TL;DR: In this article, the quality of humidity measurements from global operational radiosonde sensors in upper, middle, and lower troposphere for the period 2000-2011 were investigated using satellite observations from three microwave water vapor channels operating at 183.31±1, 183.6±3, and 183.7±7 GHz.
Abstract: [1] The quality of humidity measurements from global operational radiosonde sensors in upper, middle, and lower troposphere for the period 2000–2011 were investigated using satellite observations from three microwave water vapor channels operating at 183.31±1, 183.31±3, and 183.31±7 GHz. The radiosonde data were partitioned based on sensor type into 19 classes. The satellite brightness temperatures (Tb) were simulated using radiosonde profiles and a radiative transfer model, then the radiosonde simulated Tb's were compared with the observed Tb's from the satellites. The surface affected Tb's were excluded from the comparison due to the lack of reliable surface emissivity data at the microwave frequencies. Daytime and nighttime data were examined separately to see the possible effect of daytime radiation bias on the sonde data. The error characteristics among different radiosondes vary significantly, which largely reflects the differences in sensor type. These differences are more evident in the mid-upper troposphere than in the lower troposphere, mainly because some of the sensors stop responding to tropospheric humidity somewhere in the upper or even in the middle troposphere. In the upper troposphere, most sensors have a dry bias but Russian sensors and a few other sensors including GZZ2, VZB2, and RS80H have a wet bias. In middle troposphere, Russian sensors still have a wet bias but all other sensors have a dry bias. All sensors, including Russian sensors, have a dry bias in lower troposphere. The systematic and random errors generally decrease from upper to lower troposphere. Sensors from China, India, Russia, and the U.S. have a large random error in upper troposphere, which indicates that these sensors are not suitable for upper tropospheric studies as they fail to respond to humidity changes in the upper and even middle troposphere. Overall, Vaisala sensors perform better than other sensors throughout the troposphere exhibiting the smallest systematic and random errors. Because of the large differences between different radiosonde humidity sensors, it is important for long-term trend studies to only use data measured using a single type of sensor at any given station. If multiple sensor types are used then it is necessary to consider the bias between sensor types and its possible dependence on humidity and temperature.
37 citations
TL;DR: Schneider et al. as mentioned in this paper used the ISOWAT II diode-laser spectrometer during the MUlti-platform remote sensing of isotopologues for investigating the Cycle of Atmospheric water (MUSICA) airborne campaign.
Abstract: . Vertical profiles of water vapor (H2O) and its isotope ratio D / H expressed as δD(H2O) were measured in situ by the ISOWAT II diode-laser spectrometer during the MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) airborne campaign. We present recent modifications of the instrument design. The instrument calibration on the ground as well as in flight is described. Based on the calibration measurements, the humidity-dependent uncertainty of our airborne data is determined. For the majority of the airborne data we achieved an accuracy (uncertainty of the mean) of Δ(δD) a10‰. Vertical profiles between 150 and ~7000 m were obtained during 7 days in July and August 2013 over the subtropical North Atlantic Ocean near Tenerife. The flights were coordinated with ground-based (Network for the Detection of Atmospheric Composition Change, NDACC) and space-based (Infrared Atmospheric Sounding Interferometer, IASI) FTIR remote sensing measurements of δD(H 2O) as a means to validate the remote sensing humidity and δD(H2O) data products. The results of the validation are presented in detail in a separate paper (Schneider et al., 2014). The profiles were obtained with a high vertical resolution of around 3 m. By analyzing humidity and δD(H2O) correlations we were able to identify different layers of air masses with specific isotopic signatures. The results are discussed.
34 citations
References
More filters
Harvard University1, University of Reims Champagne-Ardenne2, College of William & Mary3, Old Dominion University4, University of Lisbon5, University of Burgundy6, California Institute of Technology7, Centre national de la recherche scientifique8, Université catholique de Louvain9, University of York10, University College London11, National Institute of Standards and Technology12, University of Waterloo13, National Center for Atmospheric Research14, University of Cologne15, Karlsruhe Institute of Technology16, Langley Research Center17
TL;DR: The new HITRAN is greatly extended in terms of accuracy, spectral coverage, additional absorption phenomena, added line-shape formalisms, and validity, and molecules, isotopologues, and perturbing gases have been added that address the issues of atmospheres beyond the Earth.
Abstract: This paper describes the contents of the 2016 edition of the HITRAN molecular spectroscopic compilation. The new edition replaces the previous HITRAN edition of 2012 and its updates during the intervening years. The HITRAN molecular absorption compilation is composed of five major components: the traditional line-by-line spectroscopic parameters required for high-resolution radiative-transfer codes, infrared absorption cross-sections for molecules not yet amenable to representation in a line-by-line form, collision-induced absorption data, aerosol indices of refraction, and general tables such as partition sums that apply globally to the data. The new HITRAN is greatly extended in terms of accuracy, spectral coverage, additional absorption phenomena, added line-shape formalisms, and validity. Moreover, molecules, isotopologues, and perturbing gases have been added that address the issues of atmospheres beyond the Earth. Of considerable note, experimental IR cross-sections for almost 300 additional molecules important in different areas of atmospheric science have been added to the database. The compilation can be accessed through www.hitran.org. Most of the HITRAN data have now been cast into an underlying relational database structure that offers many advantages over the long-standing sequential text-based structure. The new structure empowers the user in many ways. It enables the incorporation of an extended set of fundamental parameters per transition, sophisticated line-shape formalisms, easy user-defined output formats, and very convenient searching, filtering, and plotting of data. A powerful application programming interface making use of structured query language (SQL) features for higher-level applications of HITRAN is also provided.
7,638 citations
TL;DR: The relationship between deuterium and oxygen-18 concentrations in natural meteoric waters from many parts of the world has been determined with a mass spectrometer and shows a linear correlation over the entire range for waters which have not undergone excessive evaporation.
Abstract: The relationship between deuterium and oxygen-18 concentrations in natural meteoric waters from many parts of the world has been determined with a mass spectrometer. The isotopic enrichments, relative to ocean water, display a linear correlation over the entire range for waters which have not undergone excessive evaporation.
6,721 citations
TL;DR: A standard, based on the set of ocean water samples used by Epstein and Mayeda to obtain a reference standard for oxygen-18 data, but defined relative to the National Bureau of Standards isotopic reference water sample, is proposed for reporting both deuterium and oxygen- 18 variations in natural watersrelative to the same water.
Abstract: A standard, based on the set of ocean water samples used by Epstein and Mayeda to obtain a reference standard for oxygen-18 data, but defined relative to the National Bureau of Standards isotopic reference water sample, is proposed for reporting both deuterium and oxygen-18 variations in natural waters relative to the same water. The range of absolute concentrations of both isotopes in meteoric-waters is discussed.
1,773 citations
28 Nov 2003
TL;DR: In this article, the authors describe the background behind the prevailing view on water vapor feedback and some of the arguments raised by its critics, and attempt to explain why these arguments have not modified the consensus within the climate research community.
Abstract: ■ Abstract Water vapor is the dominant greenhouse gas, the most important gaseous source of infrared opacity in the atmosphere. As the concentrations of other greenhouse gases, particularly carbon dioxide, increase because of human activity, it is centrally important to predict how the water vapor distribution will be affected. To the extent that water vapor concentrations increase in a warmer world, the climatic effects of the other greenhouse gases will be amplified. Models of the Earth’s climate indicate that this is an important positive feedback that increases the sensitivity of surface temperatures to carbon dioxide by nearly a factor of two when considered in isolation from other feedbacks, and possibly by as much as a factor of three or more when interactions with other feedbacks are considered. Critics of this consensus have attempted to provide reasons why modeling results are overestimating the strength of this feedback. Our uncertainty concerning climate sensitivity is disturbing. The range most often quoted for the equilibrium global mean surface temperature response to a doubling of CO2 concentrations in the atmosphere is 1.5C to 4.5C. If the Earth lies near the upper bound of this sensitivity range, climate changes in the twenty-first century will be profound. The range in sensitivity is primarily due to differing assumptions about how the Earth’s cloud distribution is maintained; all the models on which these estimates are based possess strong water vapor feedback. If this feedback is, in fact, substantially weaker than predicted in current models, sensitivities in the upper half of this range would be much less likely, a conclusion that would clearly have important policy implications. In this review, we describe the background behind the prevailing view on water vapor feedback and some of the arguments raised by its critics, and attempt to explain why these arguments have not modified the consensus within the climate research community.
1,030 citations
TL;DR: In this article, the authors compare the effect of different averaging kernels and error covariances on the performance of different profiles and derived quantities such as the total column of a constituent.
Abstract: [1] When intercomparing measurements made by remote sounders, it is necessary to make due allowance for the differing characteristics of the observing systems, particularly their averaging kernels and error covariances. We develop the methods required to do this, applicable to any kind of retrieval method, not only to optimal estimators. We show how profiles and derived quantities such as the total column of a constituent may be properly compared, yielding different averaging kernels. We find that the effect of different averaging kernels can be reduced if the retrieval or the derived quantity of one instrument is simulated using the retrieval of the other. We also show how combinations of measured signals can be found, which can be compared directly. To illustrate these methods, we apply them to two real instruments, calculating the expected amplitudes and variabilities of the diagnostics for a comparison of CO measurements made by a ground-based Fourier Transform spectrometer (FTIR) and the “measurement of pollution in the troposphere” instrument (MOPITT), which is mounted on the EOS Terra platform. The main conclusions for this case are the following: (1) Direct comparison of retrieved profiles is not satisfactory, because the expected standard deviation of the difference is around half of the expected natural variability of the true atmospheric profiles. (2) Comparison of the MOPITT profile retrieval with a simulation using FTIR is much more useful, though still not ideal, with expected standard deviation of differences of around 20% of the expected natural variability. (3) Direct comparison of total columns gives an expected standard deviation of about 9%, while comparison of MOPITT with a simulation derived from FTIR improved this to 8%. (4) There is only one combination of measured signals that can be usefully compared. The difference is expected to have a standard deviation of about 5.5% of the expected natural variability, which is mostly due to noise.
656 citations