A First Mass Production of Gas Electron Multipliers

We report on the manufacture of a first batch of approximately 2,000 Gas Electron Multipliers (GEMs) using 3M's fully automated roll to roll flexible circuit production line. This process allows low-cost, reproducible fabrication of a high volume of GEMs of dimensions up to 30$\times$30 cm$^{2}$. First tests indicate that the resulting GEMs have optimal properties as radiation detectors. Production techniques and preliminary measurements of GEM performance are described. This now demonstrated industrial capability should help further establish the prominence of micropattern gas detectors in accelerator based and non-accelerator particle physics, imaging and photodetection.Comment: 11 pages, 10 figures, to be submitted to Nucl. Instr. Meth.

A feasibility study for the retrieval of the total column precipitable water vapour from satellite observations in the blue spectral range

We present a new algorithm for satellite retrievals of the atmospheric water vapour column in the blue spectral range. The water vapour absorption cross section in the blue spectral range is much weaker than in the red spectral range. Thus the detection limit and the uncertainty of individual observations are systematically larger than for retrievals at longer wavelengths. Nevertheless, water vapour retrievals in the blue spectral range have also several advantages: since the surface albedo in the blue spectral range is similar over land and ocean, water vapour retrievals are more consistent than for longer wavelengths. Compared to retrievals at longer wavelengths, the sensitivity for atmospheric layers close to the surface is higher due to the (typically 2 to 3 times) higher ocean albedo in the blue. Water vapour retrievals in the blue spectral range are also possible for satellite sensors, which do not measure at longer wavelengths of the visible spectral range like the Ozone Monitoring Instrument (OMI). We investigated details of the water vapour retrieval in the blue spectral range based on radiative transfer simulations and observations from the Global Ozone Monitoring Experiment 2 (GOME-2) and OMI. It is demonstrated that it is possible to retrieve the atmospheric water vapour column density in the blue spectral range over most parts of the globe. The findings of our study are of importance also for future satellite missions (e.g. Sentinel 4 and 5)

UV Aerosol Indices from SCIAMACHY: introducing the SCattering Index (SCI)

The Absorbing Aerosol Index (AAI) is a useful tool for detecting aerosols that absorb UV radiation – especially in cases where other aerosol retrievals fail, such as over bright surfaces (e.g. desert) and in the presence of clouds. The AAI does not, however, consider contributions from scattering (hardly absorbing) aerosols and clouds: they cause negative AAI values and are usually disregarded. In this paper, we demonstrate the use of the AAI's negative counterpart, the SCattering Index (SCI) to detect scattering aerosols. Consideration of the full UV Aerosol Index scale is of importance if the Aerosol Index is to be used for the quantification of aerosol absorption in the future. <br><br> Maps of seasonally averaged SCI show significantly enhanced values in summer in Southeast USA and Southeast Asia, pointing to a high production of scattering aerosols (presumably mainly sulphate aerosols and secondary organic aerosols) in this season. The application of a cloud filter makes the presence of scattering aerosols even more clear. Radiative transfer calculations were performed to investigate the sensitivity of AAI and SCI to cloud parameters, and it is demonstrated that clouds cause significant SCI, in some special cases even small AAI values. The results from cloud modelling imply that cloud effects need to be taken into account when AAI and SCI are used in a quantitative manner. <br><br> The paper concludes with a comparison of aerosol parameters from AERONET and our Aerosol Indices (AAI and SCI) from SCIAMACHY, where reasonable agreement was found for six AERONET stations in Southeast USA, Southeast Asia, and Africa. These findings corroborate the suitability of SCI as a tool to detect scattering aerosols

Dependence of cloud properties derived from spectrally resolved visible satellite observations on surface temperature

International audienceCloud climate feedback constitutes the most important uncertainty in climate modelling, and currently even its sign is still unknown. In the recently published report of the intergovernmental panel on climate change (IPCC), 6 out of 20 climate models showed a positive and 14 a negative cloud radiative feedback in a doubled CO2 scenario. The radiative budget of clouds has also been investigated by experimental methods, especially by studying the relation of satellite observed broad band shortwave and longwave radiation to sea surface temperature. Here we present a new method for the investigation of the dependence of cloud properties on temperature changes, derived from spectrally resolved satellite observations in the visible spectral range. Our study differs from previous investigations in three important ways: first, we directly extract cloud properties (effective cloud fraction and effective cloud top height) and relate them to surface temperature. Second, we retrieve the cloud altitude from the atmospheric O2 absorption instead from thermal IR radiation. Third, our correlation analysis is performed using 7.5 years of global monthly anomalies (with respect to the average of the same month for all years). For most parts of the globe (except the tropics) we find a negative correlation of effective cloud fraction versus surface-near temperature. In contrast, for the effective cloud top height a positive correlation is found for almost the whole globe. Both findings might serve as an indicator for an overall positive cloud radiative feedback. Another peculiarity of our study is that the cloud-temperature relationships are determined for fixed locations (instead to spatial variations over selected areas) and are based on the "natural" variability over several years (instead the anomaly for a strong El-Nino event). From a detailed comparison to cloud properties from the International Satellite Cloud Climatology Project (ISCCP), in general good agreement is found. However, also systematic differences occurred indicating that our results provide independent and complementary information on cloud properties. Climate models should thus aim to reproduce our findings. Recommendations for the development of a "processor" to convert model results into the cloud sensitive quantities observed by the satellite are given

Global Patterns of Lightning Properties Derived by LIS

The Lightning Imaging Sensor LIS aboard the TRMM satellite provides unmatched empirical data of the global lightning distribution (up to approx.35deg S/N) since end of 1997. Climatological flash rate densities derived from LIS are standard references, e.g. for flash rate parameterizations used in GCMs. It is known that flash characteristics are quite variable, and that various quantities (like the flash energy or the NOx production per flash) vary considerably, statistically as well as systematically on regional and seasonal scales. LIS provides information beyond flash counts, in particular radiance and flash footprint. Here we present an analysis of global patterns of various lightning properties derived from LIS, in relation to the number of flashes. These normalized flash characteristics show consistent spatial patterns of regions with "strong" versus regions with "weak" lightning. Most striking is a clear land-ocean contrast, with oceanic flashes being "stronger" than continental flashes. But also over continents, flash strength shows systematic variations. Highest continental values are found over the US, while values over South America and India are quite low. These regional variations cannot be simply parameterized as function of latitude. Information on spatial patterns of mean flash "strength", though rather qualitative up to now, is potentially a valuable input for improving empirical parameterizations based on flash counts (like precipitation or lightning NOx). Further investigation is in progress to come to a more physical and quantitative understanding of the spatial patterns of the different LIS properties. In particular, it has to be checked how far they could be related to established lightning properties (like energy or the fraction of intra-cloud to cloud-to-ground flashes) or to meteorological quantities (like CAPE)

Satellite monitoring of different vegetation types by differential optical absorption spectroscopy (DOAS) in the red spectral range

International audienceA new method for the satellite remote sensing of different types of vegetation and ocean colour is presented. In contrast to existing algorithms, our method analyses weak narrow-band reflectance structures (i.e. "fingerprint" structures) of vegetation in the red spectral range. It is based on differential optical absorption spectroscopy (DOAS), which is usually applied for the analysis of atmospheric trace gas absorptions. Since the spectra of atmospheric absorption and vegetation reflectance are simultaneously included in the analysis, the effects of atmospheric scattering and absorption are automatically corrected. The inclusion of the vegetation spectra also significantly improves the results of the trace gas retrieval. The global maps of the fitting coefficients for the vegetation spectra (indicating the fraction of the observed ground scene covered by vegetation) illustrate the seasonal cycle of different vegetation types. In addition to the vegetation distribution on land, they also show patterns of biological activity in the oceans. Our results indicate that improved sets of vegetation spectra might lead to more accurate and more specific identification of vegetation type in the future

Dependence of cloud fraction and cloud top height on surface temperature derived from spectrally resolved UV/vis satellite observations

International audienceCloud climate feedback constitutes the most important uncertainty in climate modelling, and currently even its sign is still unknown. In the recently published report of the intergovernmental panel on climate change (IPCC), from 20 climate models 6 showed a positive and 14 a negative cloud radiative feedback in a doubled CO2 scenario. The radiative budget of clouds has also been investigated by experimental methods, especially by studying the relation of satellite observed broad band shortwave and longwave radiation to sea surface temperature. Here we present a new method for the investigation of the dependence of cloud properties on temperature changes, derived from spectrally resolved UV/vis satellite observations. Our study differs from previous investigations in three important ways: first, we directly extract cloud properties (amount and altitude) and relate them to surface temperature. Second, we retrieve the cloud altitude from the atmospheric O2 absorption instead from thermal IR radiation. Third, our correlation analysis is performed using 7.5 years of global monthly anomalies (with respect to the average of the same month for all years). For most parts of the globe (except the tropics) we find a negative correlation of cloud fraction versus surface-near temperature. In contrast, for the cloud top height a positive correlation is found for almost the whole globe. Both findings might serve as an indicator for an overall positive cloud climate feedback. Another peculiarity of our study is that the cloud-temperature relationships are determined for fixed locations (instead to spatial variations over selected areas) and are based on the "natural" variability over several years (instead the anomaly for a strong El-Nino event). Thus our results might be especially representative for the extrapolation to long term climate changes. Climate models should aim to reproduce our findings: if substantial differences are found, this might indicate that important details are not yet well captured by these models. If good agreement is found, from the models reliable information on the magnitude and the detail mechanisms of cloud climate feedback could be gained

Satellite monitoring of different vegetation types by differential optical absorption spectroscopy (DOAS) in the red spectral range

A new method for the satellite remote sensing of different types of vegetation and ocean colour is presented. In contrast to existing algorithms relying on the strong change of the reflectivity in the red and near infrared spectral region, our method analyses weak narrow-band (few nm) reflectance structures (i.e. "fingerprint" structures) of vegetation in the red spectral range. It is based on differential optical absorption spectroscopy (DOAS), which is usually applied for the analysis of atmospheric trace gas absorptions. Since the spectra of atmospheric absorption and vegetation reflectance are simultaneously included in the analysis, the effects of atmospheric absorptions are automatically corrected (in contrast to other algorithms). The inclusion of the vegetation spectra also significantly improves the results of the trace gas retrieval. The global maps of the results illustrate the seasonal cycles of different vegetation types. In addition to the vegetation distribution on land, they also show patterns of biological activity in the oceans. Our results indicate that improved sets of vegetation spectra might lead to more accurate and more specific identification of vegetation type in the future

NOx Emission Trends over Chinese Cities Estimated from OMI Observations During 2005 to 2015

Satellite NO2 observations have been widely used to evaluate emission changes. To determine trends in NOx emission over China, we used a method independent of chemical transport models to quantify the NOx emissions from 48 cities and 7 power plants over China, on the basis of Ozone Monitoring Instrument (OMI) NO2 observations during 2005 to 2015. We found that NOx emissions over 48 Chinese cities increased by 52 from 2005 to 2011 and decreased by 21 from 2011 to 2015. The decrease since 2011 could be mainly attributed to emission control measures in power sector; while cities with different dominant emission sources (i.e. power, industrial and transportation sectors) showed variable emission decline timelines that corresponded to the schedules for emission control in different sectors. The time series of the derived NOx emissions was consistent with the bottom-up emission inventories for all power plants (r = 0.8 on average), but not for some cities (r = 0.4 on average). The lack of consistency observed for cities was most probably due to the high uncertainty of bottom-up urban emissions used in this study, which were derived from downscaling the regional-based emission data to cities by using spatial distribution proxies