Name
Title | ||
|---|---|---|
Sharing Satellite Observations with the Climate-Modeling Community: Software and Architecture |
Abstract | ||
|---|---|---|
The disparate communities of climate modeling and remote sensing are finding economic, political, and societal benefit from the direct comparisons of climate model outputs to satellite observations, using these comparisons to help tune models and to provide ground truth in understanding the Earth's climate processes. In the context of the Intergovernmental Panel on Climate Change (IPCC) and its upcoming 5th Assessment Report (AR5), the authors have been working with principals in both communities to build a software infrastructure that enables these comparisons. This infrastructure must overcome several software engineering challenges, including bridging heterogeneous data file formats and metadata formats, transforming swath-based remotely sensed data into globally gridded datasets, and navigating and aggregating information from the largely distributed ecosystem of organizations that house these climate model outputs and satellite data. The authors' focus in this article is on the description of software tools and services that meet these stringent challenges, and on informing the broader communities of climate modelers, remote sensing experts, and software engineers on the lessons learned from their experience so that future systems can benefit and improve upon their existing results. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/MS.2012.21 | IEEE Software |
Keywords | Field | DocType |
software tool,satellite data,climate modeling,heterogeneous data,software infrastructure,climate model output,satellite observations,climate process,climate-modeling community,software engineer,climate modeler,software engineering challenge,satellite navigation,satellite communication,artificial satellites,meta data,distributed applications,service oriented architecture,computational modeling,ecology,data models,software development,internet,meteorology,distributed databases,remote sensing | Data science,Metadata,Data modeling,Data mining,Climate model,Climate change,Systems engineering,Computer science,Ground truth,Software,Service-oriented architecture,Software development | Journal |
Volume | Issue | ISSN |
29 | 5 | 0740-7459 |
Citations | PageRank | References |
5 | 0.67 | 5 |
Authors | ||
10 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel Crichton | 1 | 21 | 3.26 |
| Chris Mattmann | 2 | 121 | 10.75 |
| Luca Cinquini | 3 | 128 | 13.91 |
| Amy Braverman | 4 | 36 | 8.40 |
| Duane Waliser | 5 | 12 | 1.63 |
| Michael Gunson | 6 | 9 | 4.65 |
| Andrew Hart | 7 | 28 | 5.34 |
| Cameron Goodale | 8 | 17 | 3.08 |
| Peter Lean | 9 | 5 | 0.67 |
| Jinwon Kim | 10 | 19 | 3.33 |