Maritime Aerosol Network as a Component of AERONET - First Results and Comparison with Global Aerosol Models and Satellite Retrievals

The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. Over 80 cruises were completed through early 2010 with deployments continuing. Measurement areas included various parts of the Atlantic Ocean, the Northern and Southern Pacific Ocean, the South Indian Ocean, the Southern Ocean, the Arctic Ocean and inland seas. MAN deploys Microtops handheld sunphotometers and utilizes a calibration procedure and data processing traceable to AERONET. Data collection included areas that previously had no aerosol optical depth (AOD) coverage at all, particularly vast areas of the Southern Ocean. The MAN data archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we present results of AOD measurements over the oceans, and make a comparison with satellite AOD retrievals and model simulations

The CM SAF ATOVS data record: overview of methodology and evaluation of total column water and profiles of tropospheric humidity

Recently, the reprocessed Advanced Television Infrared Observation Satellite (TIROS)-N Operational Vertical Sounder (ATOVS) tropospheric water vapour and temperature data record was released by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM~SAF). ATOVS observations from infrared and microwave sounders onboard the National Oceanic and Atmospheric Agency (NOAA)-15–19 satellites and EUMETSAT's Meteorological Operational (Metop-A) satellite have been consistently reprocessed to generate 13 years (1999–2011) of global water vapour and temperature daily and monthly means with a spatial resolution of 90 km × 90 km. The data set is referenced under the following digital object identifier (DOI): <a href="http://dx.doi.org/10.5676/EUM_SAF_CM/WVT_ATOVS/V001">doi:10.5676/EUM_SAF_CM/WVT_ATOVS/V001</a>. After preprocessing, a maximum likelihood solution scheme was applied to the observations to simultaneously infer temperature and water vapour profiles. In a post-processing step, an objective interpolation method (Kriging) was applied to allow for gap filling. The product suite includes total precipitable water vapour (TPW), layer-integrated precipitable water vapour (LPW) and layer mean temperature for five tropospheric layers between the surface and 200 hPa, as well as specific humidity and temperature at six tropospheric levels between 1000 and 200 hPa. To our knowledge, this is the first time that the ATOVS record (1998–now) has been consistently reprocessed (1999–2011) to retrieve water vapour. TPW and LPW products were compared to corresponding products from the Global Climate Observing System (GCOS) Upper-Air Network (GUAN) radiosonde observations and from the Atmospheric Infrared Sounder (AIRS) version 5 satellite data record. TPW shows a good agreement with the GUAN radiosonde data: average bias and root mean square error (RMSE) are −0.2 and 3.3 kg m⁻², respectively. For LPW, the maximum absolute (relative) bias and RMSE values decrease (increase) strongly with height. The maximum bias and RMSE are found at the lowest layer and are −0.7 and 2.5 kg m⁻², respectively. While the RMSE relative to AIRS is generally smaller, the TPW bias relative to AIRS is larger, with dominant contributions from precipitating areas. The consistently reprocessed ATOVS data record exhibits improved quality and stability relative to the operational CM SAF products when compared to the TPW from GUAN radiosonde data over the period 2004–2011. Finally, it became evident that the change in the number of satellites used for the retrieval combined with the use of the Kriging leads to breakpoints in the ATOVS data record; therefore, a variability analysis of the data record is not recommended for the time period from January 1999 to January 2001

The impact of temperature errors on perceived humidity supersaturation

A Monte Carlo method is used to study the propagation of temperature uncertainties into relative humidity with respect to ice (RH i ) calculated from specific humidity. For a flat specific humidity distribution and Gaussian temperature uncertainties the resulting RH i distribution drops exponentially at high RH i values—much slower than a Gaussian. This agrees well with the RH i distribution measured by the Microwave Limb Sounder (MLS), which means that such remotely measured RH i distributions can be explained, at least partly, by temperature uncertainties.Upprättat; 2003; 20070502 (pafi

Radiative transfer calculations for a passive microwave satellite sensor : comparing a fast model and a line-by-line model

A comparison between the fast radiative transfer model Radiative Transfer for the TIROS Operational Vertical Sounder (RTTOV-7) and the physical radiative transfer model Atmospheric Radiative Transfer Simulator ( ARTS) was carried out. Radiances were simulated for the sounding channels of the Advanced Microwave Sounding Unit B (AMSU-B) for the whole globe for a single time of a single day ( 1 January 2000, 0000 UT). Temperature, pressure, and specific humidity profiles from the reanalysis data set ERA-40 of the European Centre for Medium-Range Weather Forecasts (ECMWF) were used as input for both models; geopotential height profiles were also used but only as input for ARTS. The simulations were made for two different surface emissivities, 0.60 and 0.95. The low surface emissivity case exhibits the larger radiance differences. Although the global values of the mean difference and standard deviation are small ( for example, the global mean difference for channel 18 is 0.014 K and the standard deviation is 0.232 K), the examination of the geographical distribution of the differences shows that large positive or negative values are observed over dry regions of high northern and southern latitudes and over dry elevated regions. The origin of these differences was found to be due to errors introduced by the transmittance parametrization used in RTTOV.Validerad; 2006; 20070427 (pafi)</p

A cautionary note on the use of Gaussian statistics in satellite-based UTH climatologies

This letter presents a cautionary note on the assumption of Gaussian behavior for upper tropospheric humidity (UTH) derived from satellite data in climatological studies, which can introduce a wet bias in the climatology. An example study using European Centre for Medium-Range Weather Forecasts reanalysis data shows that this wet bias can reach up to 6 %RH, which is significant for climatological applications. A simple Monte Carlo approach demonstrates that these differences and their link to the variability of brightness temperatures are due to a log-normal distribution of the UTH. This problem can be solved by using robust estimators such as the median instead of the arithmetic mean.Validerad; 2006; 20070427 (pafi)</p

Characterisation of Barley Transformation into Malt by Three-Way Factor Analysis of near Infrared Spectra

Data collected for the spectral study of time series can be presented as a three-way array in which the three modes are the batches, time and wavelengths. The parallel factor analysis (PARAFAC) model is relevant for the analysis of three-way data tables, while the malting process consists of the time transformation of barley into malt. Furthermore, samples were collected on each day of an industrial malting process and their near infrared spectra were recorded in diffuse reflectance mode from 1100 to 2500 nm. The time and the wavelength modes associated with the first component showed that the spectra intensities allowed the classification of samples according to time. A study of the other loading vectors weighted by their coefficients on the time-mode explain some phenomena taking place during malting [the appearance of soluble substances (1950 nm), β-glucan degradation (2240–2360 nm), moisture modification (1450 and 1950 nm)…]. PARAFAC allowed us to separate batches according to the malting process to which they were submitted. Batches were also differentiated according to the chemical modification rate that occurred as expressed by the biochemical analyses results of the final malts. This work shows that PARAFAC can be a useful tool in the study of time series. </jats:p

Genetic diversity and geographical distribution of wild Saccharomyces cerevisiae strains from the wine-producing area of Charentes, France

Electrophoretic karyotyping, mitochondrial DNA restriction fragment length polymorphism analysis, and PCR amplification of interspersed repeats were used to study the variability, phylogenetic affinities, and biogeographic distribution of wild Saccharomyces cerevisiae enological yeasts. The survey concentrated on 42 individual wine cellars in the Charentes area (Cognac region, France). A limited number (35) of predominant S. cerevisiae strains responsible for the fermentation process have been identified by the above molecular methods of differentiation. One strain (ACI) was found to be distributed over the entire area surveyed. There seemed to be little correlation between geographic location and genetic affinity.</jats:p