EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Assessment of REgional MOdel REMO and its coupled version REMO-iMOVE over Central Asia

Praveen Rai, Katrin Ziegler, Daniel Abel, Felix Pollinger, and Heiko Paeth
Praveen Rai et al.
  • Institut für Geographie und Geologie, Universität Würzburg, Würzburg, Germany (

The climate over Central Asia has been investigated using the REMO (v2015) and its recent vegetation coupled version, REMO-iMOVE for the period of 2000-2015 at horizontal resolutions of 0.44° and 0.11°. Model evaluation is performed using the mean monthly bias patterns for temperature, precipitation, and leaf area index along with different statistical matrices. In comparison to the lower resolution of 0.44°, the spatial precipitation pattern at 0.11° is represented better. In the case of mean temperature, higher resolution simulation from both models tends to agree quite well with the validation dataset. Reduced bias in maximum and minimum temperature at 0.11° resolution is also observed over the study domain. There is improved temperature bias in REMO-iMOVE in comparison to the standard REMO version which has static vegetation while in the case of precipitation, the bias is larger in REMO-iMOVE. Since the iMOVE version is coupled to atmospheric and hydrological components, it has a clear advantage in capturing the vegetation cover and leaf area index better in comparison to the standalone REMO version. Overall, iMOVE is able to perform quite similar to REMO in simulating the mean climate of Central Asia but clearly advantageous in simulating vegetation parameters and temperature.

How to cite: Rai, P., Ziegler, K., Abel, D., Pollinger, F., and Paeth, H.: Assessment of REgional MOdel REMO and its coupled version REMO-iMOVE over Central Asia, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4191,, 2022.