Name
Abstract | ||
|---|---|---|
Atmospheric aerosols play a central role in the Earthu0027s radiative budget. Together with various greenhouse gases, aerosols represent the most significant anthropogenic forcing responsible for climate change. However, uncertainties about the origin and composition of aerosol particles, their size distribution, concentration, spatial and temporal variability, make climate change prediction challenging. In order to quantify the influence of aerosols on the Earthu0027s climate and to better validate climate models, information about their global abundance, properties and height distribution are needed. We use measurements of the Oxygen A and B bands from the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) to retrieve aerosol parameters such as optical depth, height and effective radius. Aerosol retrievals are ill-posed because of the large spatial and temporal variability in their composition and vertical distribution. We compare several retrieval methods and determine the optimum technique for the retrieval algorithm. |
Year | Venue | Field |
|---|---|---|
2018 | IGARSS | Optical depth,Climate model,Climate change,Computer science,Aerosol,Remote sensing,Atmospheric sciences,Forcing (mathematics),Radiative transfer,Effective radius,Greenhouse gas |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vijay Natraj | 1 | 1 | 1.76 |
| Jonathan H. Jiang | 2 | 39 | 21.46 |
| Adrian Doicu | 3 | 10 | 5.02 |
| Diego G. Loyola | 4 | 6 | 1.09 |
| Pushkar Kopparla | 5 | 0 | 0.34 |
| Yuk L. Yung | 6 | 0 | 1.69 |