Articles | Volume 15, issue 17
Model description paper
13 Sep 2022
Model description paper |  | 13 Sep 2022

Improved CASA model based on satellite remote sensing data: simulating net primary productivity of Qinghai Lake basin alpine grassland

Chengyong Wu, Kelong Chen, Chongyi E, Xiaoni You, Dongcai He, Liangbai Hu, Baokang Liu, Runke Wang, Yaya Shi, Chengxiu Li, and Fumei Liu


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on gmd-2021-258', Juan Antonio Añel, 21 Apr 2022
    • AC1: 'The modified model code and the relevant data of gmd-2021-258', Chengyong Wu, 01 May 2022
  • RC1: 'Comment on gmd-2021-258', Anonymous Referee #1, 25 Apr 2022
    • AC2: 'Reply on RC1', Chengyong Wu, 04 May 2022
  • RC2: 'Comment on gmd-2021-258', Anonymous Referee #2, 27 May 2022
    • AC3: 'Reply on RC2', Chengyong Wu, 03 Jun 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Chengyong Wu on behalf of the Authors (12 Jul 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (14 Jul 2022) by Hisashi Sato
RR by Anonymous Referee #2 (02 Aug 2022)
ED: Publish as is (03 Aug 2022) by Hisashi Sato
Short summary
The traditional Carnegie–Ames–Stanford Approach (CASA) model driven by multisource data such as meteorology, soil, and remote sensing (RS) has notable disadvantages. We drove the CASA using RS data and conducted a case study of the Qinghai Lake basin alpine grassland. The simulated result is similar to published and measured net primary productivity (NPP). It may provide a reference for simulating vegetation NPP to satisfy the requirements of accounting carbon stocks and other applications.