I am happy to inform that the project that I am collaborating with Dr. Enrique Vivoni and Giuseppe Mascaro was selected as a finalist for the Google App Engine Research Award.
Objective
The project proposes new ways to visualize and accesss data set for global climate data. Our first step is providing access to land surface temperature.
Background Information
Progress has been made through ground and space-based observing networks and the development of sophisticated numerical models. A class of these models, known as Land Surface Models or LSMs, simulates terrestrial water and energy processes and their two-way interaction with the Earth's atmosphere.
We plan to base our analysis on the Global Land Data Assimilation System (GLDAS), jointly developed by NASA and NOAA, and uses a series of four LSMs to provide global, 0.25 and 1 degree, 3-hourly fields of a wide range of geophysical variables over the period of 1979 to present.
Procedures for downloading, visualizing and interpreting the data requires advanced technical skills typically possessed by scientist involved in geophysical disciplines. We try to make it easy for normal users.
Execution
Our initial step is to focus only on land surface temperature (LST) at 3-hourly resolution from the period 1980 to 2010 as a target variable. We expect the query tools to allow a range of inquiry into the land surface temperature distribution at:
Objective
The project proposes new ways to visualize and accesss data set for global climate data. Our first step is providing access to land surface temperature.
Background Information
Progress has been made through ground and space-based observing networks and the development of sophisticated numerical models. A class of these models, known as Land Surface Models or LSMs, simulates terrestrial water and energy processes and their two-way interaction with the Earth's atmosphere.
We plan to base our analysis on the Global Land Data Assimilation System (GLDAS), jointly developed by NASA and NOAA, and uses a series of four LSMs to provide global, 0.25 and 1 degree, 3-hourly fields of a wide range of geophysical variables over the period of 1979 to present.
Procedures for downloading, visualizing and interpreting the data requires advanced technical skills typically possessed by scientist involved in geophysical disciplines. We try to make it easy for normal users.
Execution
Our initial step is to focus only on land surface temperature (LST) at 3-hourly resolution from the period 1980 to 2010 as a target variable. We expect the query tools to allow a range of inquiry into the land surface temperature distribution at:
- Specific location
- Across different time periods
- For memorable events (for example, Hurricane Katrina)
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