ALBERT

Description: An Arctic and Antarctic sea ice area and extent dataset has been generated by EUMETSAT's Ocean and Sea Ice Satellite Application Facility (OSISAF) using the record of microwave radiometer data from NASA's Nimbus 7 Scanning Multichannel Microwave radiometer (SMMR) and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager and Sounder (SSMIS) satellite sensors. The dataset covers the period from October 1978 to April 2015 and updates and further developments are planned for the next phase of the project. The methodology for computing the sea ice concentration uses (1) numerical weather prediction (NWP) data input to a radiative transfer model for reduction of the impact of weather conditions on the measured brightness temperatures; (2) dynamical algorithm tie points to mitigate trends in residual atmospheric, sea ice, and water emission characteristics and inter-sensor differences/biases; and (3) a hybrid sea ice concentration algorithm using the Bristol algorithm over ice and the Bootstrap algorithm in frequency mode over open water. A new sea ice concentration uncertainty algorithm has been developed to estimate the spatial and temporal variability in sea ice concentration retrieval accuracy. A comparison to US National Ice Center sea ice charts from the Arctic and the Antarctic shows that ice concentrations are higher in the ice charts than estimated from the radiometer data at intermediate sea ice concentrations between open water and 100 % ice. The sea ice concentration climate data record is available for download at www.osi-saf.org, including documentation.

Description: Fugitive emissions from waste disposal sites are important anthropogenic sources of the greenhouse gas methane (CH4). As a result of the growing world population and the recognition of the need to control greenhouse gas emissions, this anthropogenic source of CH4 has received much recent attention. However, the accurate assessment of the CH4 emissions from landfills by modeling and existing measurement techniques is challenging. This is because of inaccurate knowledge of the model parameters and the extent of and limited accessibility to landfill sites. This results in a large uncertainty in our knowledge of the emissions of CH4 from landfills and waste management. In this study, we present results derived from data collected during the research campaign COMEX (CO2 and Methane EXperiement) in late summer 2014 in the Los Angeles (LA) Basin. The objective of COMEX, which comprised aircraft observations of methane by the remote sensing Methane Airborne MAPper (MAMAP) instrument and a Picarro greenhouse gas in-situ analyser, was the quantitative investigation of CH4 emissions. Enhanced CH4 concentrations or "CH4 plumes" were detected downwind of landfills by remote sensing aircraft surveys. Subsequent to each remote sensing survey, the detected plume was sampled within the atmospheric boundary layer by in-situ measurements of atmospheric parameters such as wind information and dry gas mixing ratios of CH4 and carbon dioxide (CO2) from the same aircraft. This was undertaken to facilitate the independent estimation of the surface fluxes for the validation of the remote sensing estimates. During the COMEX campaign, four landfills in the LA Basin were surveyed. One landfill has repeatedly shown a clear emission plume. This landfill, the Olinda Alpha Landfill, was observed on four days during the last week of August and first days of September 2014. Emissions were estimated for all days using a mass balance approach. The derived emissions are between 13.0 and 18.2 kt CH4/yr with related uncertainties in the range of 17 % to 46 %. The comparison of the remote sensing and in-situ based CH4 emission rate estimates reveals good agreement within the error bars with an average absolute difference of around 2.3 kt CH4/yr. The US Environmental Protection Agency (EPA) reported inventory value is 11.5 kt CH4/yr in 2014, on average 3.0 kt CH4/yr (±1.5 kt CH4/yr) lower than our estimates acquired in late Summer 2014. This difference may in part be explained by a possible leak located on the south-western slope of the landfill, which we identified in the observations of the Airborne Visible/Infrared Imaging Spectrometer – Next Generation (AVIRIS-NG) instrument, flown contemporaneously aboard a second aircraft on one day.