Improved total atmospheric water vapour amount determination from near-infrared filter measurements with sun photometers

International audienceIn this work we explore the effect of the contribution of the solar spectrum to the recorded signal in wavelengths outside the typical 940-nm filter's bandwidth. We use gaussian-shaped filters as well as actual filter transmission curves to study the implications imposed by the non-zero out-of-band contribution to the coefficients used to derive precipitable water from the measured water vapour band transmittance. The moderate-resolution SMARTS radiative transfer code is used to predict the incident spectrum outside the filter bandpass for different atmospheres, solar geometries and aerosol optical depths. The high-resolution LBLRTM radiative transfer code is used to calculate the water vapour transmittance in the 940 nm band. The absolute level of the out-of-band transmittance has been chosen to range from 10?6 to 10?4, and typical response curves of commercially available silicon photodiodes are included into the calculations. It is shown that if the out-of-band transmittance effect is neglected, as is generally the case, then the derived columnar water vapour is systematically underestimated by a few percents. The actual error depends on the specific out-of-band transmittance, optical air mass of observation and water vapour amount. We apply published parameterized transmittance functions to determine the filter coefficients. We also introduce an improved, three-parameter, fitting function that can describe the theoretical data accurately, with significantly less residual effects than with the existing functions. Further investigations will use experimental data from field campaigns to validate these findings

Technical Note: Improved total atmospheric water vapour amount determination from near-infrared filter measurements with sun photometers

International audienceIn this work we explore the effect of the contribution of the solar spectrum to the recorded signal in wavelengths outside the typical 940-nm filter's bandwidth. We employ gaussian-shaped filters as well as actual filter transmission curves, mainly AERONET data, to study the implications imposed by the non-zero out-of-band contribution to the coefficients used to derive precipitable water from the measured water vapour band transmittance. Published parameterized transmittance functions are applied to the data to determine the filter coefficients. We also introduce an improved, three-parameter, fitting function that can describe the theoretical data accurately, with significantly less residual effects than with the existing functions. The moderate-resolution SMARTS radiative transfer code is used to predict the incident spectrum outside the filter bandpass for different atmospheres, solar geometries and aerosol optical depths. The high-resolution LBLRTM radiative transfer code is used to calculate the water vapour transmittance in the 940-nm band. The absolute level of the out-of-band transmittance has been chosen to range from 10?6 to 10?4, and typical response curves of commercially available silicon photodiodes are included into the calculations. It is shown that if the out-of-band transmittance effect is neglected, as is generally the case, then the derived columnar water vapour is mainly underestimated by a few percents. The actual error depends on the specific out-of-band transmittance, optical air mass of observation and water vapour amount. Further investigations will use experimental data from field campaigns to validate these findings

Analysis of solar direct irradiance models under clear-skies: Evaluation of the improvements for locally adapted models

Direct solar irradiance has to be determined for the design of many energy applications such as photovoltaic systems and concentration systems, and the generation of solar potential maps for energy use. Knowledge of the accurate values of radiation components in a local area will allow optimal sizing of solar energy conversion systems. The estimated values of direct solar irradiance from models are still necessary at those sites where no measurements are available. In this work, different models used for the estimation of the direct component of solar irradiance are analyzed. First, an evaluation of the performance of eight existing original models was performed from which three were selected. Second, the selected models were calibrated to adapt them to our studied geographical area, which is the important aspect of this work, and an assessment of performance improvements for locally adapted models is reported. Experimental data consisted of hourly horizontal global, direct, and diffuse solar irradiance values, provided by the National Meteorological Agency in Spain (AEMET) for Madrid. Long-term data series, corresponding to a total period of time of 32 years (1980–2011), have been used in this study. Only clear sky models were treated at present. The three selected models were adapted to the specific location of Madrid, and root mean square error (RMSE) and mean-biased error were determined. By comparing the performance in the direct horizontal irradiance estimation from existing original and the corresponding locally adapted models, it is found that the values of RMSE decreased from 9.9% to 5.7% for the Louche model, from 7.8% to 7.4% for the Robledo-Soler model, and finally from 8.8% to 6.7% for the European Solar Radiation Atlas model. Thus, significant improvements can be reached when parametric models are locally adapted. In our case, it is up to approximately 4% for the Louche model. It is expected that calibrated algorithms presented in this work will be applicable to regions of similar climatic characteristics.Spanish Government (grant ENE2011-27511) and the Department of Culture and Education of the Regional Government of Castilla y León, Spain (grant BU358A12-2

Clouds in the atmospheres of extrasolar planets. I. Climatic effects of multi-layered clouds for Earth-like planets and implications for habitable zones

The effects of multi-layered clouds in the atmospheres of Earth-like planets orbiting different types of stars are studied. The radiative effects of cloud particles are directly correlated with their wavelength-dependent optical properties. Therefore the incident stellar spectra may play an important role for the climatic effect of clouds. We discuss the influence of clouds with mean properties measured in the Earth's atmosphere on the surface temperatures and Bond albedos of Earth-like planets orbiting different types of main sequence dwarf stars.Comment: accepted for publication in A&

DNA Nucleobase Synthesis at Titan Atmosphere Analog by Soft X-rays

Titan, the largest satellite of Saturn, has an atmosphere chiefly made up of N2 and CH4 and includes traces of many simple organic compounds. This atmosphere also partly consists of haze and aerosol particles which during the last 4.5 gigayears have been processed by electric discharges, ions, and ionizing photons, being slowly deposited over the Titan surface. In this work, we investigate the possible effects produced by soft X-rays (and secondary electrons) on Titan aerosol analogs in an attempt to simulate some prebiotic photochemistry. The experiments have been performed inside a high vacuum chamber coupled to the soft X-ray spectroscopy beamline at the Brazilian Synchrotron Light Source, Campinas, Brazil. In-situ sample analyses were performed by a Fourier transform infrared spectrometer. The infrared spectra have presented several organic molecules, including nitriles and aromatic CN compounds. After the irradiation, the brownish-orange organic residue (tholin) was analyzed ex-situ by gas chromatographic (GC/MS) and nuclear magnetic resonance (1H NMR) techniques, revealing the presence of adenine (C5H5N5), one of the constituents of the DNA molecule. This confirms previous results which showed that the organic chemistry on the Titan surface can be very complex and extremely rich in prebiotic compounds. Molecules like these on the early Earth have found a place to allow life (as we know) to flourish.Comment: To appear in Journal of Physical Chemistry A.; Number of pages: 6; Number of Figures: 5; Number of Tables: 1; Number of references:49; Full paper at http://pubs.acs.org/doi/abs/10.1021/jp902824

Impacts of extreme 2013–2014 winter conditions on Lake Michigan's fall heat content, surface temperature, and evaporation

Since the late 1990s, the Laurentian Great Lakes have experienced persistent low water levels and above average over‐lake evaporation rates. During the winter of 2013–2014, the lakes endured the most persistent, lowest temperatures and highest ice cover in recent history, fostering speculation that over‐lake evaporation rates might decrease and that water levels might rise. To address this speculation, we examined interseasonal relationships in Lake Michigan's thermal regime. We find pronounced relationships between winter conditions and subsequent fall heat content, modest relationships with fall surface temperature, but essentially no correlation with fall evaporation rates. Our findings suggest that the extreme winter conditions of 2013–2014 may have induced a shift in Lake Michigan's thermal regime and that this shift coincides with a recent (and ongoing) rise in Great Lakes water levels. If the shift persists, it could (assuming precipitation rates remain relatively constant) represent a return to thermal and hydrologic conditions not observed on Lake Michigan in over 15 years.Key PointsLake Michigan has been in an altered thermal regime since the late 1990sThe 2013–2014 winter may return Lake Michigan to pre‐1998 thermal conditionsHydrological impacts of the 2013–2014 cold winter remain unclearPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/112001/1/grl52850.pd

Non-linear Autoregressive Neural Networks to Forecast Short-Term Solar Radiation for Photovoltaic Energy Predictions

Nowadays, green energy is considered as a viable solution to hinder CO2 emissions and greenhouse effects. Indeed, it is expected that Renewable Energy Sources (RES) will cover 40% of the total energy request by 2040. This will move forward decentralized and cooperative power distribution systems also called smart grids. Among RES, solar energy will play a crucial role. However, reliable models and tools are needed to forecast and estimate with a good accuracy the renewable energy production in short-term time periods. These tools will unlock new services for smart grid management. In this paper, we propose an innovative methodology for implementing two different non-linear autoregressive neural networks to forecast Global Horizontal Solar Irradiance (GHI) in short-term time periods (i.e. from future 15 to 120min). Both neural networks have been implemented, trained and validated exploiting a dataset consisting of four years of solar radiation values collected by a real weather station. We also present the experimental results discussing and comparing the accuracy of both neural networks. Then, the resulting GHI forecast is given as input to a Photovoltaic simulator to predict energy production in short-term time periods. Finally, we present the results of this Photovoltaic energy estimation discussing also their accuracy

Previsual symptoms of Xylella fastidiosa infection revealed in spectral plant-trait alterations

Plant pathogens cause significant losses to agricultural yields, and increasingly threaten food security, ecosystem integrity, and societies in general. Xylella fastidiosa (Xf) is one of the most dangerous plant bacteria worldwide, causing several diseases with profound impacts on agriculture and the environment. Primarily occurring in the Americas, its recent discovery in Asia and Europe demonstrates a dramatically broadened geographic range. The Xf pathogen has thus re-emerged as a global threat, with its poorly contained expansion in Europe creating a socio-economic, cultural, and political disaster. Xf represents a threat of global proportion because it can infect over 350 plant species worldwide, and the early detection of Xf has been identified as a critical need for its eradication. Here, we show that changes in plant functional traits retrieved from airborne imaging spectroscopy and thermography reveal Xf infection in trees before symptoms are visible. We obtained accuracies of disease detection exceeding 80% when high-resolution solar-induced fluorescence quantified by 3D simulations and thermal-based stress indicators were coupled with photosynthetic traits sensitive to rapid pigment dynamics and degradation. Moreover, we found that the visually asymptomatic trees originally scored as affected via spectral plant trait alterations (presumed false positives) developed Xf symptoms four months later at almost double the rate of the asymptomatic trees classified as not affected by remote sensing. We demonstrate that spectral plant trait alterations caused by Xf infection are detectable at the landscape scale before symptoms are visible, a critical requirement to help eradicate some of the most devastating plant diseases worldwide.JRC.D.1-Bio-econom

Asian dust events of April 1998

On April 15 and 19, 1998, two intense dust storms were generated over the Gobi desert by springtime low-pressure systems descending from the northwest. The windblown dust was detected and its evolution followed by its yellow color on SeaWiFS satellite images, routine surface-based monitoring, and through serendipitous observations. The April 15 dust cloud was recirculating, and it was removed by a precipitating weather system over east Asia. The April 19 dust cloud crossed the Pacific Ocean in 5 days, subsided to the surface along the mountain ranges between British Columbia and California, and impacted severely the optical and the concentration environments of the region. In east Asia the dust clouds increased the albedo over the cloudless ocean and land by up to 10-20%, but it reduced the near-UNI cloud reflectance, causing a yellow coloration of all surfaces. The yellow colored backscattering by the dust eludes a plausible explanation using simple Mie theory with constant refractive index. Over the West Coast the dust layer has increased the spectrally uniform optical depth to about 0.4, reduced the direct solar radiation by 30-40%, doubled the diffuse radiation, and caused a whitish discoloration of the blue sky. On April 29 the average excess surface-level dust aerosol concentration over the valleys of the West Coast was about 20-50 mug/m(3) with local peaks \u3e 100 mug/m(3). The dust mass mean diameter was 2-3 mum, and the dust chemical fingerprints were evident throughout the West Coast and extended to Minnesota. The April 1998 dust event has impacted the surface aerosol concentration 2-4 times more than any other dust event since 1988. The dust events were observed and interpreted by an ad hoc international web-based virtual community. It would be useful to set up a community-supported web-based infrastructure to monitor the global aerosol pattern for such extreme aerosol events, to alert and to inform the interested communities, and to facilitate collaborative analysis for improved air quality and disaster management