Spectrometry: Report of panel

Spectroscopic measurements are required to define the spectral background and provide the detailed spectral information that is essential for the design of species-specific systems and the analysis of data obtained from them. This function of spectroscopic measurements is expected to be an important part of any tropospheric remote-sensing program, and both emission and absorption spectroscopy are relevant in this context. The data from such observations are of value to tropospheric science in their own right, during the initial phases while species-specific techniques and instruments are under development. In addition, there are a number of unresolved problems in tropospheric radiative transfer and spectroscopy which presently limit the accuracy and reliability of all remote sensing methods. Only through a supporting program of spectroscopic measurements can progress be made in improving the understanding of these aspects of radiative transfer and ultimately reaching the desired confidence in the accuracy to species-specific monitoring techniques

HIRDLS Observations and Simulation of a Lower Stratospheric Intrusion of Tropical Air to High Latitudes

On 26 January 2006, the High Resolution Dynamic Limb Sounder (HIRDLS) observed low mixing ratios of ozone and nitric acid in an approximately 2 km vertical layer near 100 hPa extending from the subtropics to 55 degrees N over North America. The subsequent evolution of the layer is simulated with the Global Modeling Initiative (GMI) model and substantiated with HIRDLS observations. Air with low mixing ratios of ozone is transported poleward to 80 degrees N. Although there is evidence of mixing with extratropical air and diabatic descent, much of the tropical intrusion returns to the subtropics. This study demonstrates that HIRDLS and the GMI model are capable of resolving thin intrusion events. The observations combined with simulation are a first step towards development of a quantitative understanding of the lower stratospheric ozone budget

Comparison of Upper Tropospheric Carbon Monoxide from MOPITT, ACE-FTS, and HIPPO-QCLS

Products from the Measurements Of Pollution In The Troposphere (MOPITT) instrument are regularly validated using in situ airborne measurements. However, few of these measurements reach into the upper troposphere, thus hindering MOPITT validation in that region. Here we evaluate upper tropospheric (~500 hPa to the tropopause) MOPITT CO profiles by comparing them to satellite Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) retrievals and to measurements from the High-performance Instrumented Airborne Platform for Environmental Research Pole to Pole Observations (HIPPO) Quantum Cascade Laser Spectrometer (QCLS). Direct comparison of colocated v5 MOPITT thermal infrared-only retrievals, v3.0 ACE-FTS retrievals, and HIPPO-QCLS measurements shows a slight positive MOPITT CO bias within its 10% accuracy requirement with respect to the other two data sets. Direct comparison of colocated ACE-FTS and HIPPO-QCLS measurements results in a small number of samples due to the large disparity in sampling pattern and density of these data sets. Thus, two additional indirect techniques for comparison of noncoincident data sets have been applied: tracer-tracer (CO-O3) correlation analysis and analysis of profiles in tropopause coordinates. These techniques suggest a negative bias of ACE-FTS with respect to HIPPO-QCLS; this could be caused by differences in resolution (horizontal, vertical) or by deficiencies in the ACE-FTS CO retrievals below ~20 km of altitude, among others. We also investigate the temporal stability of MOPITT and ACE-FTS data, which provide unique global CO records and are thus important in climate analysis. Our results indicate that the relative bias between the two data sets has remained generally stable during the 2004–2010 period. © 2014. American Geophysical Union

An examination of the long-term CO records from MOPITT and IASI: comparison of retrieval methodology

International audienceCarbon monoxide (CO) is a key atmospheric compound that can be remotely sensed by satellite on the global scale. Fifteen years of continuous observations are now available from the MOPITT/Terra mission (2000 to present). Another fifteen and more years of observations will be provided by the IASI/MetOp instrument series (2007–2023>). In order to study long term variability and trends, a homogeneous record is required, which is not straightforward as the retrieved products are instrument and processing dependent. The present study aims at evaluating the consistency between the CO products derived from the MOPITT and IASI missions, both for total columns and vertical profiles, during a six year overlap period (2008–2013). The analysis is performed by first comparing the available 2013 versions of the retrieval algorithms, and second using a dedicated reprocessing of MOPITT CO profiles and columns based on the IASI a priori constraints. MOPITT v5T total columns are generally slightly higher over land (bias ranging from 0 to 13%) than IASI v20100815 data. When IASI and MOPITT data are retrieved with the same a priori constraints, correlation coefficients are slightly improved. Large discrepancies (total column bias over 15%) observed in the Northern Hemisphere during the winter months are reduced by a factor of 2 to 2.5. The detailed analysis of retrieved vertical profiles compared with collocated aircraft data from the MOZAIC-IAGOS network, illustrates the advantages and disadvantages of a constant vs. a variable a priori. On one hand, MOPITT agrees better with the aircraft profiles for observations with persisting high levels of CO throughout the year due to pollution or seasonal fire activity (because the climatology-based a priori is supposed to be closer to the real atmospheric state). On the other hand, IASI performs better when unexpected events leading to high levels of CO occur, due to the less constrained variance-covariance matrix

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

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

Global Estimates of CO Sources with High Resolution by Adjoint Inversion of Multiple Satellite Datasets (MOPITT, AIRS, SCIAMACHY, TES)

We combine CO column measurements from the MOPITT, AIRS, SCIAMACHY, and TES satellite instruments in a full-year (May 2004–April 2005) global inversion of CO sources at 4°×5° spatial resolution and monthly temporal resolution. The inversion uses the GEOS-Chem chemical transport model (CTM) and its adjoint applied to MOPITT, AIRS, and SCIAMACHY. Observations from TES, surface sites (NOAA/GMD), and aircraft (MOZAIC) are used for evaluation of the a posteriori solution. Using GEOS-Chem as a common intercomparison platform shows global consistency between the different satellite datasets and with the in situ data. Differences can be largely explained by different averaging kernels and a priori information. The global CO emission from combustion as constrained in the inversion is $1350 Tg a^{−1}$. This is much higher than current bottom-up emission inventories. A large fraction of the correction results from a seasonal underestimate of CO sources at northern mid-latitudes in winter and suggests a larger-than-expected CO source from vehicle cold starts and residential heating. Implementing this seasonal variation of emissions solves the long-standing problem of models underestimating CO in the northern extratropics in winter-spring. A posteriori emissions also indicate a general underestimation of biomass burning in the GFED2 inventory. However, the tropical biomass burning constraints are not quantitatively consistent across the different datasets.Engineering and Applied Science