J. Landgraf

Retrieval of aerosol properties over land surfaces : capabilities of multiple-viewing-angle intensity and polarization measurements

We investigate the capabilities of different instrument concepts for the retrieval of aerosol properties over land. It was found that, if the surface reflection properties are unknown, only multiple-viewing-angle measurements of both intensity and polarization are able to provide the relevant aerosol parameters with sufficient accuracy for climate research. Furthermore, retrieval errors are only little affected when the number of viewing angles is increased at the cost of the number of spectral sampling points and vice versa. This indicates that there is a certain amount of freedom for the instrument design of dedicated aerosol instruments. The final choice on the trade-off between the spectral sampling and the number of viewing angles should be made taking other factors into account, such as instrument complexity and the ability to obtain global coverage.

Methane retrievals from greenhouse gases observing satellite (GOSAT) shortwave infrared measurements: performance comparison of proxy and physics retrieval algorithms

We compare two conceptually different methods for determining methane column-averaged mixing ratios image from Greenhouse Gases Observing Satellite (GOSAT) shortwave infrared (SWIR) measurements. These methods account differently for light scattering by aerosol and cirrus. The proxy method retrieves a CO_2 column which, in conjunction with prior knowledge on CO_2 acts as a proxy for scattering effects. The physics-based method accounts for scattering by retrieving three effective parameters of a scattering layer. Both retrievals are validated on a 19-month data set using ground-based X_CH_4 at 12 stations of the Total Carbon Column Observing Network (TCCON), showing comparable performance: for the proxy retrieval we find station-dependent retrieval biases from −0.312% to 0.421% of X_CH_4 a standard deviation of 0.22% and a typical precision of 17 ppb. The physics method shows biases between −0.836% and −0.081% with a standard deviation of 0.24% and a precision similar to the proxy method. Complementing this validation we compared both retrievals with simulated methane fields from a global chemistry-transport model. This identified shortcomings of both retrievals causing biases of up to 1ings and provide a satisfying validation of any methane retrieval from space-borne SWIR measurements, in our opinion it is essential to further expand the network of TCCON stations.

Evaluation of Global Ozone Monitoring Experiment (GOME) ozone profiles from nine different algorithms

An evaluation is made of ozone profiles retrieved from measurements of the nadir-viewing Global Ozone Monitoring Experiment (GOME) instrument. Currently four different approaches are used to retrieve ozone profile information from GOME measurements, which differ in the use of external information and a priori constraints. In total nine different algorithms will be evaluated exploiting the Optimal Estimation (Royal Netherlands Meteorological Institute, Rutherford Appleton Laboratory, University of Bremen, National Oceanic and Atmospheric Administration, Smithsonian Astrophysical Observatory), Phillips-Tikhonov Regularization (Space Research Organization Netherlands), Neural Network (Center for Solar Energy and Hydrogen Research, Tor Vergata University), and Data Assimilation (German Aerospace Center) approaches. Analysis tools are used to interpret data sets that provide averaging kernels. In the interpretation of these data, the focus is on the vertical resolution, the indicative altitude of the retrieved value, and the fraction of a priori information. The evaluation is completed with a comparison of the results to lidar data from the NDSC (Network for Detection of Stratospheric Change) stations in Andoya (Norway), Observatoire Haute Provence (France), Mauna Loa (USA), Lauder (New Zealand) and Dumont d’Urville (Antarctic) for the years 1997–1999. In total the comparison involves nearly 1000 ozone profiles, and allows the analysis of GOME data measured in different global regions and hence observational circumstances. The main conclusion of this paper is that unambiguous information on the ozone profile can at best be retrieved in the altitude range 15–48 km with a vertical resolution of 10 to 15 km, precision of 5–10%, and a bias up to 5% or 20% depending on the success of recalibration of the input spectra. The sensitivity of retrievals to ozone at lower altitudes varies from scheme to scheme and includes significant influence from a priori assumptions.

Anomalous carbon uptake in Australia as seen by GOSAT

One of the unanswered questions of climate change is how the biospheric uptake of carbon responds to events such as droughts and floods. Especially, semiarid regions have received interest recently, as they can respond very rapidly to changing environmental conditions. Here we report on a large enhanced carbon sink over Australia from the end of 2010 to early 2012 detected using the Greenhouse Gases Observing SATellite (GOSAT). This enhanced sink coincides with the strong La Nina episode, accompanied by record-breaking amounts of precipitation. This precipitation led to an enhanced growth of vegetation, resulting in large increases in biospheric carbon uptake in line with increased levels of vegetation fluorescence. An inversion based on the satellite retrievals confirms this strong anomaly in the sink of roughly 0.77 0.10PgCyr(-1) or 1.5 0.2PgC in total for the April 2010 to December 2011 period, which corresponds to 25% of the multiyear annual average gross primary production of the Australian biosphere.

Accurate modeling of spectral fine-structure in Earth radiance spectra measured with the Global Ozone Monitoring Experiment

We present what we believe to be a novel approach to simulating the spectral fine structure (<1 nm) in measurements of spectrometers such as the Global Ozone Monitoring Experiment (GOME). GOME measures the Earths radiance spectra and daily solar irradiance spectra from which a reflectivity spectrum is commonly extracted. The high-frequency structures contained in such a spectrum are, apart from atmospheric absorption, caused by Raman scattering and by a shift between the solar irradiance and the Earths radiance spectrum. Normally, an a priori high-resolution solar spectrum is used to simulate these structures. We present an alternative method in which all the required information on the solar spectrum is retrieved from the GOME measurements. We investigate two approaches for the spectral range of 390-400 nm. First, a solar spectrum is reconstructed on a fine spectral grid from the GOME solar measurement. This approach leads to undersampling errors of up to 0.5% in the modeling of the Earths radiance spectra. Second, a combination of the solar measurement and one of the Earths radiance measurement is used to retrieve a solar spectrum. This approach effectively removes the undersampling error and results in residuals close to the GOME measurement noise of 0.1%.

Retrieval of cloud properties from near‐ultraviolet, visible, and near‐infrared satellite‐based Earth reflectivity spectra: A comparative study

6 Received 4 July 2007; revised 8 January 2008; accepted 28 February 2008; published XX Month 2008. 7 [1] In this study, we investigate the capability to retrieve cloud parameters from near8 ultraviolet, visible, and near-infrared satellite-based reflectivity measurements. These 9 parameters are essential to enable trace gas retrievals for cloud-contaminated satellite 10 scenes. We compare the retrieval of cloud top pressure, cloud fraction, and cloud optical 11 thickness from simulated reflectivity measurements in three wavelength ranges: (1) 350– 12 400 nm, which includes pronounced Ring effect structures; (2) 460–490 nm; and (3) 13 755–775 nm, which contain absorption features of O2-O2 and O2, respectively. Retrieval 14 simulations are performed for both a typical noise level of present-day space-borne 15 spectrometers and additional random-like measurement biases. Furthermore, we 16 investigated the importance of the spectral continuum for the retrieval of cloud properties. 17 It is found that reflectivity measurements in the wavelength ranges 350–400 and 755– 18 775 nm provide complementary information on cloud properties. Both spectral windows 19 provide more information on clouds than the 460–490 nm window. The best results 20 are obtained for the combination of the 350–400 and 755–775 nm windows. In this case 21 all three cloud parameters can be retrieved independently, and a high robustness is 22 obtained with respect to random-like measurement biases. Here it is not required to resolve 23 the Ring effect structures in the near-ultraviolet window. For this combination of 24 spectral windows the error on retrieved NO2 columns is reduced considerably. 25 Citation: van Deelen, R., O. P. Hasekamp, B. van Diedenhoven, and J. Landgraf (2008), Retrieval of cloud properties from near26 ultraviolet, visible, and near-infrared satellite-based Earth reflectivity spectra: A comparative study, J. Geophys. Res., 113, XXXXXX, 27 doi:10.1029/2007JD009129. 28

TROPOMI and TROPI: UV/VIS/NIR/SWIR instruments

TROPOMI (Tropospheric Ozone-Monitoring Instrument) is a five-channel UV-VIS-NIR-SWIR non-scanning nadir viewing imaging spectrometer that combines a wide swath (114°) with high spatial resolution (10 × 10 km2 ). The instrument heritage consists of GOME on ERS-2, SCIAMACHY on Envisat and, especially, OMI on EOS-Aura. TROPOMI has even smaller ground pixels than OMI-Aura but still exceeds OMIs signal-to-noise performance. These improvements optimize the possibility to retrieve tropospheric trace gases. In addition, the SWIR capabilities of TROPOMI are far better than SCIAMACHYs both in terms of spatial resolution and signal to noise performance. TROPOMI is part of the TRAQ payload, a mission proposed in response to ESAs EOEP call. The TRAQ mission will fly in a non-sun synchronous drifting orbit at about 720 km altitude providing nearly global coverage. TROPOMI measures in the UV-visible wavelength region (270-490 nm), in a near-infrared channel (NIR) in the 710-775 nm range and has a shortwave infrared channel (SWIR) near 2.3 μm. The wide swath angle, in combination with the drifting orbit, allows measuring a location up to 5 times a day at 1.5-hour intervals. The spectral resolution is about 0.45 nm for UVVIS- NIR and 0.25 nm for SWIR. Radiometric calibration will be maintained via solar irradiance measurements using various diffusers. The instrument will carry on-board calibration sources like LEDs and a white light source. Innovative aspects include the use of improved detectors in order to improve the radiation hardness and the spatial sampling capabilities. Column densities of trace gases (NO2, O3, SO2 and HCHO) will be derived using primarily the Differential Optical Absorption Spectroscopy (DOAS) method. The NIR channel serves to obtain information on clouds and the aerosol height distribution that is needed for tropospheric retrievals. A trade-off study will be conducted whether the SWIR channel, included to determine column densities of CO and CH4, will be incorporated in TROPOMI or in the Fourier Transform Spectrometer SIFTI on TRAQ. The TROPI instrument is similar to the complete TROPOMI instrument (UV-VIS-NIR-SWIR) and is proposed for the CAMEO initiative, as described for the U.S. NRC Decadal Study on Earth Science and Applications from Space. CAMEO also uses a non-synchronous drifting orbit, but at a higher altitude (around 1500 km). The TROPI instrument design is a modification of the TROPOMI design to achieve identical coverage and ground pixel sizes from a higher altitude. In this paper capabilities of TROPOMI and TROPI are discussed with emphasis on the UV-VIS-NIR channels as the TROPOMI SWIR channel is described in a separate contribution [5].

Efficient vector radiative transfer calculations in vertically inhomogeneous cloudy atmospheres

Accurate radiative transfer calculations in cloudy atmospheres are generally time consuming, limiting their practical use in satellite remote sensing applications. We present a model to efficiently calculate the radiative transfer of polarized light in atmospheres that contain homogeneous cloud layers. This model combines the Gauss-Seidel method, which is efficient for inhomogeneous cloudless atmospheres, with the doubling method, which is efficient for homogeneous cloud layers. Additionally to reduce the computational effort for radiative transfer calculations in absorption bands, the cloud reflection and transmission matrices are interpolated over the absorption and scattering optical thicknesses within the cloud layer. We demonstrate that the proposed radiative transfer model in combination with this interpolation technique is efficient for the simulation of satellite measurements for inhomogeneous atmospheres containing one homogeneous cloud layer. For example, the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) measurements in the oxygen A band (758-773 nm) and the Hartley-Huggins ozone band (295-335 nm) with a spectral resolution of 0.4 nm can be simulated for these atmospheres within 1 min on a 2.8 GHz PC with an accuracy better than 0.1%.

Validation of Global Ozone Monitoring Experiment ozone profiles and evaluation of stratospheric transport in a global chemistry transport model

This paper presents a validation of Global Ozone Monitoring Experiment (GOME) ozone (O3) profiles which are used to evaluate stratospheric transport in the chemistry transport model (CTM) Tracer Model version 5 (TM5) using a linearized stratospheric O3 chemistry scheme. A comparison of GOME O3 profile measurements with independent O3 sonde measurements at midlatitudes shows an excellent agreement. Differences are smaller than 5%, well within the uncertainty of the O3 sonde measurements. Within the tropics, the GOME O3 profile differences are larger, with a clear lower stratospheric negative O3 bias with compensating positive biases in the troposphere and higher stratosphere. The TM5 model with linearized O3 chemistry simulates realistic lower and middle stratospheric spatial and temporal O3 variations on both short (daily) and long (seasonal) timescales. Model stratospheric O3 is significantly overestimated in the extratropics and slightly underestimated in the tropics, as is also shown in a comparison with Total Ozone Mapping Spectrometer total O3 column measurements. This model bias predominantly occurs in the lower stratosphere and is present throughout the year, albeit with seasonal variations: The bias is larger during local winter compared with local summer. The particular spatial and seasonal variations of the model bias suggest a too fast meridional stratospheric transport in TM5, which agrees with earlier found shortcomings of using winds from data assimilation systems. The model results are very sensitive to the data assimilation method in the numerical weather prediction that provides the model wind fields. A large reduction (up to 50% of the bias) in modeled lower stratospheric midlatitude O3 was found when winds from four-dimensional instead of three-dimensional data assimilation were used. Previous work has shown that using different forecast periods was important for improving the age of air. Model results differed with different forecast periods (up to 3 days), although the effect was mainly confined to high-latitude lower stratospheric O3. Apparently, using different forecast periods is more important for age-of-air calculations than for stratospheric O3 calculations. A positive bias in the extratropical lower stratosphere of about 20% remained, possibly related to the lack of heterogeneous polar stratospheric O3 destruction in TM5. Copyright 2007 by the American Geophysical Union.

Toward Global Mapping of Methane With TROPOMI: First Results and Intersatellite Comparison to GOSAT

The TROPOspheric Monitoring Instrument (TROPOMI), launched on 13 October 2017, aboard the Sentinel‐5 Precursor satellite, measures reflected sunlight in the ultraviolet, visible, near‐infrared, and shortwave infrared spectral range. It enables daily global mapping of key atmospheric species for monitoring air quality and climate. We present the first methane observations from November and December 2017, using TROPOMI radiance measurements in the shortwave infrared band around 2.3 μm. We compare our results with the methane product obtained from the Greenhouse gases Observing SATellite (GOSAT). Although different spectral ranges and retrieval methods are used, we find excellent agreement between the methane products acquired from the two satellites with a mean difference of 13.6 ppb, standard deviation of 19.6 ppb, and Pearsons correlation coefficient of 0.95. Our preliminary results capture the latitudinal gradient and show expected regional enhancements, for example, in the African Sudd wetlands, with much more detail than has been observed before.