Name
Abstract | ||
|---|---|---|
This letter presents a method to calculate the width ω over the half-period of the cosine term in a diurnal temperature cycle (DTC) model. ω deduced from the thermal diffusion equation (TDE) is compared with ω obtained from solar geometry. The results demonstrate that ω deduced from the TDE describes the shape of the DTC model more adequately around sunrise and the time of maximum temperature than ω obtained from solar geometry. Additionally, taking into account the physical continuity of land surface temperature (LST) variation, a day-to-day temporal progression (DDTP) model of LST is developed to model several days of DTCs. The results indicate that the DDTP model fits in situ [or Spinning Enhanced Visible and Infrared Imager (SEVIRI)] LST well with a root-mean-square error (RMSE) less than 1 K. Compared with the DTC model, the DDTP model slightly increases the quality of LST fits around sunrise. Assuming that only six LST measurements corresponding to the NOAA/AVHRR and MODIS overpass times for each day are available, several days of DTCs can be predicted by the DDTP model with an RMSE less than 1.5 K. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/LGRS.2012.2228465 | IEEE Geosci. Remote Sensing Lett. |
Keywords | Field | DocType |
day-to-day temporal progression (ddtp),thermal diffusion equation,day-to-day temporal progression,diurnal temperature cycle (dtc),land surface temperature (lst),noaa avhrr overpass time,dtc model,modis overpass time,seviri instrument,solar geometry,sunrise,clear sky land surface temperature,land surface temperature,diurnal temperature cycle,modeling,spinning enhanced visible and infrared imager | Land surface temperature,Diurnal temperature variation,Remote sensing,Mean squared error,Sunrise,Sky,Atmospheric sciences,Infrared,Emissivity,Thermal diffusivity,Mathematics | Journal |
Volume | Issue | ISSN |
10 | 5 | 1545-598X |
Citations | PageRank | References |
5 | 0.56 | 1 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sibo Duan | 1 | 60 | 13.11 |
| Zhao-Liang Li | 2 | 416 | 127.21 |
| Hua Wu | 3 | 113 | 25.88 |
| Bo-Hui Tang | 4 | 103 | 26.15 |
| Xiaoguang Jiang | 5 | 15 | 7.42 |
| Guoqing Zhou | 6 | 73 | 19.78 |