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Found 4 result(s)

MODES

Modal view of atmospheric circulation

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MODES focuses on the representation of the inertio-gravity circulation in numerical weather prediction models, reanalyses, ensemble prediction systems and climate simulations. The project methodology relies on the decomposition of global circulation in terms of 3D orthogonal normal-mode functions. It allows quantification of the role of inertio-gravity waves in atmospheric varibility across the whole spectrum of resolved spatial and temporal scales. MODES is compiled by using gfortran although other options have been succesfully tested. The application requires the use of the netcdf and (optionally) grib-api libraries.

Measurements Of Pollution In The Troposphere

MOPITT

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Measurements Of Pollution In The Troposphere (MOPITT) was launched into sun-synchronous polar orbit on December 18, 1999, aboard TERRA, a NASA satellite orbiting 705 km above the Earth. MOPITT monitors changes in pollution patterns and the effects on Earth’s troposphere. MOPITT uses near-infrared radiation at 2.3 µm and thermal-infrared radiation at 4.7 µm to calculate atmospheric profiles of CO.

National Ecological Observatory Network

NEON

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Funded by the National Science Foundation (NSF) and proudly operated by Battelle, the National Ecological Observatory Network (NEON) program provides open, continental-scale data across the United States that characterize and quantify complex, rapidly changing ecological processes. The Observatory’s comprehensive design supports greater understanding of ecological change and enables forecasting of future ecological conditions. NEON collects and processes data from field sites located across the continental U.S., Puerto Rico, and Hawaii over a 30-year timeframe. NEON provides free and open data that characterize plants, animals, soil, nutrients, freshwater, and the atmosphere. These data may be combined with external datasets or data collected by individual researchers to support the study of continental-scale ecological change.

Climate Hazards Center Data Archive

CHC Data Archive

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Using a combination of remote sensing data and ground observations as inputs, CHC scientists have developed rainfall estimation techniques and other resources to support drought monitoring and predict crop performance in parts of the world vulnerable to crop failure. Policymakers within governments and non-governmental organizations rely on CHC decision-support products to make critical resource allocation decisions. The CHC's scientific focus is "geospatial hydroclimatology," with an emphasis on the early detection and forecasting of hydroclimatic hazards related to food-security droughts and floods. Basic research seeks an improved understanding of the climatic processes that govern drought and flood hazards in FEWS NET countries (https://fews.net/). The CHC develops better techniques, algorithms, and modeling applications in order to use remote sensing and other geospatial data for hazards early warning.