Estimating the Surface Air Temperature by Remote Sensing in Northwest China Using an Improved Advection-Energy Balance for Air Temperature Model
To estimate the surface air temperature by remote sensing, the advection-energy balance for the surface air temperature (ADEBAT) model is developed which assumes the surface air temperature is driven by the local driving force and the advective driving force. The local driving force produces a local...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-01-01
|
| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2016/4294219 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832558120961835008 |
|---|---|
| author | Suhua Liu Hongbo Su Renhua Zhang Jing Tian Weizhen Wang |
| author_facet | Suhua Liu Hongbo Su Renhua Zhang Jing Tian Weizhen Wang |
| author_sort | Suhua Liu |
| collection | DOAJ |
| description | To estimate the surface air temperature by remote sensing, the advection-energy balance for the surface air temperature (ADEBAT) model is developed which assumes the surface air temperature is driven by the local driving force and the advective driving force. The local driving force produces a local surface air temperature whereas the advective driving force changes it by adding an exotic air temperature. An advection factor f is defined to measure the quantity of the exotic air brought by the advection. Since the f is determined by the advection, this paper improves it to a regional scale by using the Inverse Distance Weighting (IDW) method whereas the original ADEBAT model uses a constant of f for a block of area. Results retrieved by the improved ADEBAT (IADEBAT) model are evaluated and comparison was made with the in situ measurements, with an R2 (correlation coefficient) of 0.77, an RMSE (Root Mean Square Error) of 0.31 K, and a MAE (Mean Absolute Error) of 0.24 K. The evaluation shows that the IADEBAT model has higher accuracy than the original ADEBAT model. Evaluations together with a t-test of the MAD (Mean Absolute Deviation) reveal that the IADEBAT model has a significant improvement. |
| format | Article |
| id | doaj-art-a50d8f6fdbbb4e9c85965b4a8a143535 |
| institution | Kabale University |
| issn | 1687-9309 1687-9317 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Meteorology |
| spelling | doaj-art-a50d8f6fdbbb4e9c85965b4a8a1435352025-02-03T01:33:13ZengWileyAdvances in Meteorology1687-93091687-93172016-01-01201610.1155/2016/42942194294219Estimating the Surface Air Temperature by Remote Sensing in Northwest China Using an Improved Advection-Energy Balance for Air Temperature ModelSuhua Liu0Hongbo Su1Renhua Zhang2Jing Tian3Weizhen Wang4Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaDepartment of Civil, Environmental and Geomatics Engineering, Florida Atlantic University, Florida, FL 33431, USAKey Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaKey Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaHeihe Remote Sensing Experimental Research Station, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, ChinaTo estimate the surface air temperature by remote sensing, the advection-energy balance for the surface air temperature (ADEBAT) model is developed which assumes the surface air temperature is driven by the local driving force and the advective driving force. The local driving force produces a local surface air temperature whereas the advective driving force changes it by adding an exotic air temperature. An advection factor f is defined to measure the quantity of the exotic air brought by the advection. Since the f is determined by the advection, this paper improves it to a regional scale by using the Inverse Distance Weighting (IDW) method whereas the original ADEBAT model uses a constant of f for a block of area. Results retrieved by the improved ADEBAT (IADEBAT) model are evaluated and comparison was made with the in situ measurements, with an R2 (correlation coefficient) of 0.77, an RMSE (Root Mean Square Error) of 0.31 K, and a MAE (Mean Absolute Error) of 0.24 K. The evaluation shows that the IADEBAT model has higher accuracy than the original ADEBAT model. Evaluations together with a t-test of the MAD (Mean Absolute Deviation) reveal that the IADEBAT model has a significant improvement.http://dx.doi.org/10.1155/2016/4294219 |
| spellingShingle | Suhua Liu Hongbo Su Renhua Zhang Jing Tian Weizhen Wang Estimating the Surface Air Temperature by Remote Sensing in Northwest China Using an Improved Advection-Energy Balance for Air Temperature Model Advances in Meteorology |
| title | Estimating the Surface Air Temperature by Remote Sensing in Northwest China Using an Improved Advection-Energy Balance for Air Temperature Model |
| title_full | Estimating the Surface Air Temperature by Remote Sensing in Northwest China Using an Improved Advection-Energy Balance for Air Temperature Model |
| title_fullStr | Estimating the Surface Air Temperature by Remote Sensing in Northwest China Using an Improved Advection-Energy Balance for Air Temperature Model |
| title_full_unstemmed | Estimating the Surface Air Temperature by Remote Sensing in Northwest China Using an Improved Advection-Energy Balance for Air Temperature Model |
| title_short | Estimating the Surface Air Temperature by Remote Sensing in Northwest China Using an Improved Advection-Energy Balance for Air Temperature Model |
| title_sort | estimating the surface air temperature by remote sensing in northwest china using an improved advection energy balance for air temperature model |
| url | http://dx.doi.org/10.1155/2016/4294219 |
| work_keys_str_mv | AT suhualiu estimatingthesurfaceairtemperaturebyremotesensinginnorthwestchinausinganimprovedadvectionenergybalanceforairtemperaturemodel AT hongbosu estimatingthesurfaceairtemperaturebyremotesensinginnorthwestchinausinganimprovedadvectionenergybalanceforairtemperaturemodel AT renhuazhang estimatingthesurfaceairtemperaturebyremotesensinginnorthwestchinausinganimprovedadvectionenergybalanceforairtemperaturemodel AT jingtian estimatingthesurfaceairtemperaturebyremotesensinginnorthwestchinausinganimprovedadvectionenergybalanceforairtemperaturemodel AT weizhenwang estimatingthesurfaceairtemperaturebyremotesensinginnorthwestchinausinganimprovedadvectionenergybalanceforairtemperaturemodel |