European air quality maps 2005 including uncertainty analysis

The objective of this report is (a) the updating and refinement of European air quality maps based on annual statistics of the 2005 observational data reported by EEA Member countries in 2006, and (b) the further improvement of the interpolation methodologies. The paper presents the results achieved and an uncertainty analysis of the interpolated maps and builds upon earlier reports from Horalék et al. (2005; 2007)

Oceanographic Weather Maps: Using Oceanographic Models to Improve Seabed Mapping Planning and Acquisition

In a world of high precision sensors, one of the few remaining challenges in multibeam echosounding is that of refraction based uncertainty. A poor understanding of oceanographic variability can lead to inadequate sampling of the water mass and the uncertainties that result from this can dominate the uncertainty budget of even state-of-the-art echosounding systems. Though dramatic improvements have been made in sensor accuracies over the past few decades, survey accuracy and efficiency is still potentially limited by a poor understanding of the “underwater weather”. Advances in the sophistication of numerical oceanographic forecast modeling, combined with ever increasing computing power, allow for the timely operation and dissemination of oceanographic nowcast and forecast model systems on regional and global scales. These sources of information, when examined using sound speed uncertainty analysis techniques, have the potential to change the way hydrographers work by increasing our understanding of what to expect from the ocean and when to expect it. Sound speed analyses derived from ocean modeling system’s three-dimensional predictions could provide guidance for hydrographers during survey planning, acquisition and post-processing of hydrographic data. In this work, we examine techniques for processing and visualizing of predictions from global and regional operational oceanographic forecast models and climatological analyses from an ocean atlas to better understand how these data could best be put to use to in the field of hydrograph

On daily interpolation of precipitation backed with secondary information

This paper investigates the potential impact of secondary information on rainfall mapping applying Ordinary Kriging. Secondary information tested is a natural area indicator, which is a combination of topographic features and weather conditions. Cross validation shows that secondary information only marginally improves the final mapping, indicating that a one-day accumulation time is possibly too short

Production of regional 1 km x 1 km water vapor fields through the integration of GPS and MODIS data

<p>Atmospheric water vapor is a crucial element in weather, climate and hydrology. With the recent advance in Global Positioning System (GPS) Meteorology, ground-based GPS has become an operational tool that can measure precipitable water vapor (PWV) with high accuracy (1~1.5mm) during all-weathers, and with high temporal resolution (e.g. 5 minutes) at low cost. But the spatial coverage of GPS receivers is limited, and restricts its applications. At present, two NASA Moderate Resolution Imaging Spectroradiometer (MODIS) can provide global coverage 2D water vapor field with a spatial resolution of 1 km × 1 km (at nadir) every 2 days, and at many latitudes can provide water vapor fields every 90 minutes, 4 times a day. The disadvantages of MODIS water vapor products are: 1). A systematic uncertainty of 5-10% is expected [Gao et al., 2003; Li et al., 2003]; 2). Since the MODIS water vapor retrieval relies on observations of water vapor attenuation of near Infrared (IR) solar radiation reflected by surfaces and clouds, it is sensitive to the presence of clouds. The frequency and the percentage of cloud free conditions at mid-latitudes is only 15-30% on average [Li et al., 2004]. Therefore, in order to extract a water vapor field above the Earth’s surface, an attempt needs to be made to fill in the cloudy pixels.</p> <p>In this paper, an inter-comparison between MODIS (collection 4) and GPS PWV products was performed in the region of the Southern California Integrated GPS Network (SCIGN). It is shown that MODIS appeared to overestimate PWV against GPS with a scale factor of 1.05 and a zero-offset of –0.7 mm. Taking into account the small standard deviation of the linear fit model, a GPS-derived correction linear fit model was proposed to calibrate MODIS PWV products, and a better agreement was achieved. In order to produce regional 1 km × 1 km water vapor fields, an integration approach was proposed: Firstly, MODIS near IR water vapor was calibrated using GPS data; secondly, an improved inverse distance weighted interpolation method (IIDW) was applied to fill in the cloudy pixels; thirdly, the densified water vapor field was validated using GPS data. It is shown that the integration approach was promising. After correction, MODIS and GPS PWV agreed to within 1.6 mm in terms of standard deviations using appropriate extent and power parameters of IIDW, and the coverage of water vapor fields increased by up to 21.6%. In addition, for the first time, spatial structure functions were derived from MODIS near IR water vapor, and large water vapor variations were observed from time to time.</p&gt

Data-based estimates of the ocean carbon sink variability – First results of the Surface Ocean pCO2 Mapping intercomparison (SOCOM)

Using measurements of the surface-ocean CO2 partial pressure (pCO2) and 14 different pCO2 mapping methods recently collated by the Surface Ocean pCO2 Mapping intercomparison (SOCOM) initiative, variations in regional and global sea–air CO2 fluxes are investigated. Though the available mapping methods use widely different approaches, we find relatively consistent estimates of regional pCO2 seasonality, in line with previous estimates. In terms of interannual variability (IAV), all mapping methods estimate the largest variations to occur in the eastern equatorial Pacific. Despite considerable spread in the detailed variations, mapping methods that fit the data more closely also tend to agree more closely with each other in regional averages. Encouragingly, this includes mapping methods belonging to complementary types – taking variability either directly from the pCO2 data or indirectly from driver data via regression. From a weighted ensemble average, we find an IAV amplitude of the global sea–air CO2 flux of 0.31 PgC yr−1 (standard deviation over 1992–2009), which is larger than simulated by biogeochemical process models. From a decadal perspective, the global ocean CO2 uptake is estimated to have gradually increased since about 2000, with little decadal change prior to that. The weighted mean net global ocean CO2 sink estimated by the SOCOM ensemble is −1.75 PgC yr−1 (1992–2009), consistent within uncertainties with estimates from ocean-interior carbon data or atmospheric oxygen trend