ALBERT

Description: NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) archives and distributes rich collections of data on atmospheric greenhouse gases from multiple satellite missions and model results. Among those greenhouse gases, atmospheric methane is a powerful greenhouse gas contributing ~0.5 (W/m^2) to total radiative forcing, and its concentration has increased by about 150% since 1750. Observations or estimates of methane emissions typically have sparse spatial and temporal coverage. The lack of comprehensive spatial and temporal coverage of methane source and sink observations has made analyzing atmospheric methane trends challenging. In this study the GES DISC aims to provide the community with the resources to better understand changes in atmospheric methane concentrations and the underlying causes. We will utilize methane datasets from Atmospheric Infrared Sounder (AIRS) retrieved methane concentration and three Carbon Monitoring System (CMS) methane emission datasets (in regions of North America, Canada, and Mexico) to compare AIRS methane growth with corresponding CMS regional methane emissions. Comparisons of AIRS methane growth rates and CMS methane emissions suggests wetland emissions may impact methane growth rate trends over North America. As the record for CMS methane data is extended, both datasets can be used in conjunction to better understand impacts on atmospheric methane trends. GES DISCs new anomaly tool can also be used on select datasets to further quantify trends in atmospheric greenhouse gases.

Description: No abstract available

Description: We present results from an analysis of seasonal phase shifts in the global precipitation and surface temperatures. We use data from the TRMM (Tropical Rainfall Measuring Mission) Multi-satellite Precipitation Algorithm (TMPA), and the Atmospheric Infrared Sounder (AIRS) on Aqua satellite, all hosted at NASA Goddard Earth Science Data and Information Services Center (GES DISC). We explore the information content and data usability by first aggregating daily grids from the entire records of both missions to pentad (5-day) series which are then processed using Singular Value Decomposition approach. A strength of this approach is the normalized principal components that can then be easily converted from real to complex time series. Thus, we can separate the most informative, the seasonal, components and analyze unambiguously for potential seasonal phase drifts. TMPA and AIRS records represent correspondingly 20 and 15 years of data, which allows us to run simple phase learning from the first 5 years of records and use it as reference. The most recent 5 years are then phase-compared with the reference. We demonstrate that the seasonal phase of global precipitation and surface temperatures has been stable in the past two decades. However, a small global trend of delayed precipitation, and earlier arrival of surface temperatures seasons, are detectable at 95% confidence level. Larger phase shifts are detectable at regional level, in regions recognizable from the Eigen vectors to having strong seasonal patterns. For instance, in Central North America, including the North American Monsoon region, confident phase shifts of 1-2 days per decade are detected at 95% confidence level. While seemingly symbolic, these shifts are indicative of larger changes in the Earth Climate System. We thus also demonstrate a potential usability scenario of Earth Science Data Records curated at the NASA GES DISC in partnership with Earth Science Missions.

Description: No abstract available

Description: No abstract available

Description: The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been actively and continually engaged in improving the access to and use of Global Precipitation Measurement (GPM), Tropical Precipitation Measuring Mission (TRMM), and other precipitation data, including the following new services and ongoing development activities: Updates on GPM products and data services; New features in Giovanni; Ongoing development activities; Precipitation product and service outreach activities.

Description: By developing and enhancing various services and tools, the GES DISC provides users with the capability to access and visualize data, and to make comparisons of data from multiple sensor and models via a number of cross-discipline projects. Discovering Data via Faceted Web Interface Web interface to data products and services Search and Download mechanisms Dataset Landing Pages Accessing Data through Interoperable Services: GDS GrADS Data Server OPeNDAP - Open-source Project for a Network Data Access Protocol WMS OGC service GIS connector allowing IS tools to access data easier (coming soon) HTTPS -- direct online access Downloading Data Basics: Subset and egridding Service Parameter, Spatial, Time, Vertical, Mean averaging, format conversion, and regridding for L3/L4 gridded data Swath Data Subsetter Parameter, spatial subset of L2 /L1 data. Visualizing Data Online: Giovanni Visualization and Analysis L3/L4 gridded data AIRS NRT Viewer AIRS near-real-time DQVis L2 data quality visualization

Description: The Atmospheric Infrared Sounder (AIRS) mission began with the launch of Aqua in 2002. Over 15 years of AIRS products have been used by the climate research and application communities. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), in collaboration with NASA Sounder Team at JPL, provides processing, archiving, and distribution services for NASA sounders: the present Aqua AIRS mission and the succeeding Suomi National Polar-Orbiting Partnership (SNPP) Cross-track Infrared Sounder (CrIS) mission. We generated a Multi-year Monthly Mean and Anomaly product using 14 years of AIRS standard monthly product. The product includes Air Temperature at the Surface and Surface Skin Temperature, both in Ascending/Daytime and Descending/Nighttime mode. The temperature variables and their anomalies are deployed to Giovanni, a Web-based application developed by the GES DISC. Giovanni provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data without having to download the data. It is also a powerful tool that stakeholders can use for decision support in planning and preparing for increased climate variability. In this presentation, we demonstrate the functions in Giovanni with use cases employing AIRS Multi-year Monthly Mean and Anomaly variables.

Description: Modeling studies have shown that cloud feedbacks are sensitive to the spatial pattern of sea surface temperature (SST) anomalies, while cloud feedbacks themselves strongly influence the magnitude of SST anomalies. Observational counterparts to such patterned interactions are still needed. Here we show that distinct large-scale patterns of SST and low-cloud cover (LCC) emerge naturally from objective analyses of observations and demonstrate their close coupling in a positive local SST-LCC feedback loop that may be important for both internal variability and climate change. The two patterns that explain the maximum amount of covariance between SST and LCC correspond to the Interdecadal Pacific Oscillation (IPO) and the Atlantic Multidecadal Oscillation (AMO), leading modes of multidecadal internal variability. Spatial patterns and time series of SST and LCC anomalies associated with both modes point to a strong positive local SST-LCC feedback. In many current climate models, our analyses suggest that SST-LCC feedback strength is too weak compared to observations. Modeled local SST-LCC feedback strength affects simulated internal variability so that stronger feedback produces more intense and more realistic patterns of internal variability. To the extent that the physics of the local positive SST-LCC feedback inferred from observed climate variability applies to future greenhouse warming, we anticipate significant amount of delayed warming because of SST-LCC feedback when anthropogenic SST warming eventually overwhelm the effects of internal variability that may mute anthropogenic warming over parts of the ocean. We postulate that many climate models may be underestimating both future warming and the magnitude of modeled internal variability because of their weak SST-LCC feedback.

Description: This collection contains measurements of physical and chemical soil properties on the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained in general by bi-annual weeding and mowing. Since 2010, plot size was reduced to 5 x 6 m and plots were weeded three times per year. The following series of datasets are contained in this collection: 1. Physical soil properties - Soil texture: Proportion of sand, silt and clay in the fine soil was measured in April 2002 before plot establishment at 27 locations distributed throughout the experimental site. Undisturbed soil cores were taken to 100 cm depth and separated in depth increments with a resolution of 10 to 20 cm. Grain size fractions according to DIN 19683-2 were then determined by a combined sieve and hydrometer analysis. Values for each plot were interpolated by ordinary kriging. - Bulk density: Bulk density was sampled down to 100 cm depth in 2002 and 30 cm depth in 2004, 2006 and 2008. Several undisturbed soil cores were taken per plot and separated in depth increments before the bulk material was sieved, dried and weighed. - Soil hydraulic properties: Field capacity and permanent wilting point at 10, 20 and 30 cm depth were derived from soil texture data of 2002 and bulk density 2006 by using pedotransfer functions. Applied was equation four and five of Zacharias and Wessolek (2007) to derive parameters of the water retention curve. Water contents at field capacity and permanent wilting point were obtained using the van Genuchte Eq (e.g. eq 1 in Zacharias and Wessolek), and calculating water contents at - 330 cm matric potential (field capacity, 1/3 of atmospheric pressure) and at -15000 cm. -Soil porosity: the fraction of total volume occupied by pores or voids measured at matric potential 0, already published on https://doi.pangaea.de/10.1594/PANGAEA.865254. 2. Chemical soil properties - Lime content: Percentage of CaCO3 in the soil was measured in April 2002 before plot establishment at 27 locations distributed throughout the experimental site. Undisturbed soil cores were taken to 100 cm depth and separated in depth increments with a resolution of 10 to 20 cm. The bulk material was sieved and CaCO3 content of the fine soil was determined as volumetric determination according to DIN 19684-5. - Soil organic matter: Percentage of soil organic matter was measured in April 2002 before plot establishment at 27 locations distributed throughout the experimental site. Undisturbed soil cores were taken to 100 cm depth and separated in depth increments with a resolution of 10 to 20 cm. The bulk material was sieved and organic content of the fine soil was determined using a loss-on-ignition method. - Soil pH value: soil pH value was determined 2002 and 2010 in water and 2002 also in calcium chloride. Five soil samples were taken per plot and bulk material was diluted in water and calcium chloride. PH values were then measured with an electrode.