TY  - JOUR
A1  - Rai, P.
A1  - Ziegler, K.
A1  - Abel, D.
A1  - Pollinger, F.
A1  - Paeth, H.
T1  - Performance of a regional climate model with interactive vegetation (REMO-iMOVE) over Central Asia
JF  - Theoretical and Applied Climatology
N2  - The current study evaluates the regional climate model REMO (v2015) and its new version REMO-iMOVE, including interactive vegetation and plant functional types (PFTs), over two Central Asian domains for the period of 2000–2015 at two different horizontal resolutions (0.44° and 0.11°). Various statistical metrices along with mean bias patterns for precipitation, temperature, and leaf area index have been used for the model evaluation. A better representation of the spatial pattern of precipitation is found at 0.11° resolution over most of Central Asia. Regarding the mean temperature, both model versions show a high level of agreement with the validation data, especially at the higher resolution. This also reduces the biases in maximum and minimum temperature. Generally, REMO-iMOVE shows an improvement regarding the temperature bias but produces a larger precipitation bias compared to the REMO conventional version with interannually static vegetation. Since the coupled version is capable to simulate the mean climate of Central Asia like its parent version, both can be used for impact studies and future projections. However, regarding the new vegetation scheme and its spatiotemporal representation exemplified by the leaf area index, REMO-iMOVE shows a clear advantage over REMO. This better simulation is caused by the implementation of more realistic and interactive vegetation and related atmospheric processes which consequently add value to the regional climate model.
KW  - regional climate model (RCM)
KW  - interactive vegetation
KW  - REMO-iMOVE
KW  - Central Asia
KW  - evaluation
Y1  - 2022
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-324155
SN  - 0177-798X
VL  - 150
IS  - 3-4
ER  - 
TY  - JOUR
A1  - Dietz, Andreas J.
A1  - Conrad, Christopher
A1  - Kuenzer, Claudia
A1  - Gesell, Gerhard
A1  - Dech, Stefan
T1  - Identifying Changing Snow Cover Characteristics in Central Asia between 1986 and 2014 from Remote Sensing Data
JF  - Remote Sensing
N2  - Central Asia consists of the five former Soviet States Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan, therefore comprising an area of similar to 4 Mio km(2). The continental climate is characterized by hot and dry summer months and cold winter seasons with most precipitation occurring as snowfall. Accordingly, freshwater supply is strongly depending on the amount of accumulated snow as well as the moment of its release after snowmelt. The aim of the presented study is to identify possible changes in snow cover characteristics, consisting of snow cover duration, onset and offset of snow cover season within the last 28 years. Relying on remotely sensed data originating from medium resolution imagers, these snow cover characteristics are extracted on a daily basis. The resolution of 500-1000 m allows for a subsequent analysis of changes on the scale of hydrological sub-catchments. Long-term changes are identified from this unique dataset, revealing an ongoing shift towards earlier snowmelt within the Central Asian Mountains. This shift can be observed in most upstream hydro catchments within Pamir and Tian Shan Mountains and it leads to a potential change of freshwater availability in the downstream regions, exerting additional pressure on the already tensed situation.
KW  - AVHRR data
KW  - satellite
KW  - Northern Xinjiang
KW  - cloud
KW  - products
KW  - Central Asia
KW  - climate change
KW  - Amu Darya
KW  - Syr Darya
KW  - Tian Shan
KW  - snow
KW  - snow cover
KW  - snow cover duration
KW  - Pamir
KW  - AVHRR
KW  - MODIS
KW  - algorithm
KW  - validation
Y1  - 2014
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-114470
SN  - 2072-4292
VL  - 6
IS  - 12
ER  -