Observations of shallow convective clouds generated by solar heating of dark smoke plumes

The SEVIRI instrument on the Meteosat Second Generation satellite with both fine spatial and temporal resolution allows to detect and follow the dynamics of fast developing meteorological events like spreading smoke plumes and the lifecycles of convective clouds. Smoke plumes have the ability to change the atmospheric heat content due to absorption and reduced reflection of solar radiation. By these means they can trigger formation of shallow convective clouds at their edge. A heavy smoke plume emerging from burning Lebanese oil tanks and spreading over adjacent deserts on 17 July 2006 has been observed as an example of such an effect. This study suggests a physical explanation of the observed convection along the edge of the smoke plume, namely the strong thermal contrast resulting from solar heating of the smoke layer

Understanding the aerosol information content in multi-spectral reflectance measurements using a synergetic retrieval algorithm

An information content analysis for multi-wavelength SYNergetic AErosol Retrieval algorithm SYNAER was performed to quantify the number of independent pieces of information that can be retrieved. In particular, the capability of SYNAER to discern various aerosol types is assessed. This information content depends on the aerosol optical depth, the surface albedo spectrum and the observation geometry. The theoretical analysis is performed for a large number of scenarios with various geometries and surface albedo spectra for ocean, soil and vegetation. When the surface albedo spectrum and its accuracy is known under cloud-free conditions, reflectance measurements used in SYNAER is able to provide for 2–4° of freedom that can be attributed to retrieval parameters: aerosol optical depth, aerosol type and surface albedo. <br><br> The focus of this work is placed on an information content analysis with emphasis to the aerosol type classification. This analysis is applied to synthetic reflectance measurements for 40 predefined aerosol mixtures of different basic components, given by sea salt, mineral dust, biomass burning and diesel aerosols, water soluble and water insoluble aerosols. The range of aerosol parameters considered through the 40 mixtures covers the natural variability of tropospheric aerosols. After the information content analysis performed in Holzer-Popp et al. (2008) there was a necessity to compare derived degrees of freedom with retrieved aerosol optical depth for different aerosol types, which is the main focus of this paper. <br><br> The principle component analysis was used to determine the correspondence between degrees of freedom for signal in the retrieval and derived aerosol types. The main results of the analysis indicate correspondence between the major groups of the aerosol types, which are: water soluble aerosol, soot, mineral dust and sea salt and degrees of freedom in the algorithm and show the ability of the SYNAER to discern between this aerosol types. <br><br> The results of the work will be further used for the development of the promising methodology of the construction error covariance matrices in the assimilation system

Synergetic aerosol retrieval from SCIAMACHY and AATSR onboard ENVISAT

International audienceThe synergetic aerosol retrieval method SYNAER (Holzer-Popp et al., 2002a) has been extended to the use of ENVISAT measurements. It exploits the complementary information of a radiometer and a spectrometer onboard one satellite platform to extract aerosol optical depth (AOD) and speciation (as choice from a representative set of pre-defined mixtures of water-soluble, soot, mineral dust, and sea salt components). SYNAER consists of two retrieval steps. In the first step the radiometer is used to do accurate cloud screening, and subsequently to quantify the aerosol optical depth (AOD) at 550 nm and spectral surface brightness through a dark field technique. In the second step the spectrometer is applied to choose the most plausible aerosol type through a least square fit of the measured spectrum with simulated spectra using the AOD and surface brightness retrieved in the first step. This method was developed and a first case study evaluation against few (15) multi-spectral ground-based AERONET sun photometer observations was conducted with a sensor pair (ATSR-2 and GOME) onboard ERS-2. However, due to instrumental limitations the coverage of SYNAER/ERS-2 and the AERONET network in 1997/98 is very sparse and thus only few coincidences with AERONET were found. Therefore, SYNAER was transferred to similar sensors AATSR and SCIAMACHY onboard ENVISAT. While transferring to the new sensor pair a thorough evaluation of the synergetic methodology and its information content has been conducted, which led to significant improvements in the methodology: an update of the aerosol model, an improved cloud detection, and an enhanced dark field albedo characterization. This paper describes the information content analysis and these improvements in detail and presents first results of applying the SYNAER methodology to AATSR and SCIAMACHY

Aerosol retrieval experiments in the ESA Aerosol_cci project

Within the ESA Climate Change Initiative (CCI) project Aerosol_cci (2010–2013), algorithms for the production of long-term total column aerosol optical depth (AOD) datasets from European Earth Observation sensors are developed. Starting with eight existing pre-cursor algorithms three analysis steps are conducted to improve and qualify the algorithms: (1) a series of experiments applied to one month of global data to understand several major sensitivities to assumptions needed due to the ill-posed nature of the underlying inversion problem, (2) a round robin exercise of "best" versions of each of these algorithms (defined using the step 1 outcome) applied to four months of global data to identify mature algorithms, and (3) a comprehensive validation exercise applied to one complete year of global data produced by the algorithms selected as mature based on the round robin exercise. The algorithms tested included four using AATSR, three using MERIS and one using PARASOL. This paper summarizes the first step. Three experiments were conducted to assess the potential impact of major assumptions in the various aerosol retrieval algorithms. In the first experiment a common set of four aerosol components was used to provide all algorithms with the same assumptions. The second experiment introduced an aerosol property climatology, derived from a combination of model and sun photometer observations, as a priori information in the retrievals on the occurrence of the common aerosol components. The third experiment assessed the impact of using a common nadir cloud mask for AATSR and MERIS algorithms in order to characterize the sensitivity to remaining cloud contamination in the retrievals against the baseline dataset versions. The impact of the algorithm changes was assessed for one month (September 2008) of data: qualitatively by inspection of monthly mean AOD maps and quantitatively by comparing daily gridded satellite data against daily averaged AERONET sun photometer observations for the different versions of each algorithm globally (land and coastal) and for three regions with different aerosol regimes. The analysis allowed for an assessment of sensitivities of all algorithms, which helped define the best algorithm versions for the subsequent round robin exercise; all algorithms (except for MERIS) showed some, in parts significant, improvement. In particular, using common aerosol components and partly also a priori aerosol-type climatology is beneficial. On the other hand the use of an AATSR-based common cloud mask meant a clear improvement (though with significant reduction of coverage) for the MERIS standard product, but not for the algorithms using AATSR. It is noted that all these observations are mostly consistent for all five analyses (global land, global coastal, three regional), which can be understood well, since the set of aerosol components defined in Sect. 3.1 was explicitly designed to cover different global aerosol regimes (with low and high absorption fine mode, sea salt and dust)

The ESA climate change initiative: Satellite data records for essential climate variables

The ESA’s Climate Change Initiative is reprocessing and reassessing over 40 years of multi-sensor satellite records to generate consistent, traceable, long-term datasets of “essential climate variables” for the climate modeling and research communities

Sloan Digital Sky Survey IV: Mapping the Milky Way, Nearby Galaxies, and the Distant Universe

We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median $z\sim 0.03$). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between $z\sim 0.6$ and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July

The 13th Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-IV Survey Mapping Nearby Galaxies at Apache Point Observatory

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) began observations in July 2014. It pursues three core programs: APOGEE-2,MaNGA, and eBOSS. In addition, eBOSS contains two major subprograms: TDSS and SPIDERS. This paper describes the first data release from SDSS-IV, Data Release 13 (DR13), which contains new data, reanalysis of existing data sets and, like all SDSS data releases, is inclusive of previously released data. DR13 makes publicly available 1390 spatially resolved integral field unit observations of nearby galaxies from MaNGA,the first data released from this survey. It includes new observations from eBOSS, completing SEQUELS. In addition to targeting galaxies and quasars, SEQUELS also targeted variability-selected objects from TDSS and X-ray selected objects from SPIDERS. DR13 includes new reductions ofthe SDSS-III BOSS data, improving the spectrophotometric calibration and redshift classification. DR13 releases new reductions of the APOGEE-1data from SDSS-III, with abundances of elements not previously included and improved stellar parameters for dwarf stars and cooler stars. For the SDSS imaging data, DR13 provides new, more robust and precise photometric calibrations. Several value-added catalogs are being released in tandem with DR13, in particular target catalogs relevant for eBOSS, TDSS, and SPIDERS, and an updated red-clump catalog for APOGEE.This paper describes the location and format of the data now publicly available, as well as providing references to the important technical papers that describe the targeting, observing, and data reduction. The SDSS website, http://www.sdss.org, provides links to the data, tutorials and examples of data access, and extensive documentation of the reduction and analysis procedures. DR13 is the first of a scheduled set that will contain new data and analyses from the planned ~6-year operations of SDSS-IV.PostprintPeer reviewe

Sloan Digital Sky Survey IV: Mapping the Milky Way, Nearby Galaxies, and the Distant Universe

We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median $z\sim 0.03$). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between $z\sim 0.6$ and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July