Supplementary Material for
Pankaj Kumar 1 , Sven Kotlarski 2 , Christopher Mosely 3 , Kevin Sieck 3 , Holger Frey 4 , Markus
Stoffel 5 , Daniela Jacob 1
1.
Climate Service Center 2.0, Helmholtz Zentrum Geesthacht, Fischertwiete 1, 20095 Hamburg,
Germany.
Tel: +49 -(0) 40 - 226 338 - 420 ; Fax: +49 -(0) 40 - 226 338 - 163 ;
E-Mail: pankaj.kumar@hzg.de
2.
Institute for Atmospheric and Climate Science, ETH Zurich, Switzerland
3.
Max Planck Institute for Meteorology Hamburg, Germany
4.
Department of Geography, University of Zurich- Irchel, Zurich, Switzerland
5.
Institute for Environmental Sciences, University of Geneva, Switzerland

Precipitation and near-surface air temperature: Figure-S1 shows the mean annual cycle of
REMO glacier
simulated precipitation for the Himalayan sub-regions along with the observations and reanalysis. The model generally overestimates precipitation over the region. For the Himalayan region as a whole, it overestimates annual mean precipitation by 17% to 59% with respect to the observations, and by 18% with respect to the MERRA reanalysis data (Table-S1). The model underestimates precipitation by 15% with respect to the forcing ERAI data. ERAI generally overestimated precipitation over this region as discussed in the main manuscript and as also reported by Ménégoz et al. [2013]. The annual cycle of temperature is well simulated by REMO glacier
. It shows a mean negative temperature bias of -0.5°C over the Himalayan region throughout the year compared to MERRA. However, observations data show large bias up to 3°C throughout the year.
The spatial pattern of simulated yearly mean winter and summer precipitation, and the corresponding reference data are shown in Figure-S2. Spatial precipitation variability is well reproduced by the model. Over the Karakoram, the model simulates more winter precipitation than observations.
Winter precipitation is fed by westerlies when moisture-laden winds are intercepted by the high mountains of the Karakoram (>5000m, Figure-1), leading to condensation and precipitation. Since the model (ca. 25 km resolution) resolves the topography better than MERRA/ERAI (ca. 50/80 km),
REMO glacier
can simulate these processes more realistically, and winter precipitation is likely to be underestimated by the reanalysis. None of the observational data sets is able to capture such an important local feature of precipitation over the Karakoram, which represents an important mass gain to large glaciers in winter. All the key characteristics of summer precipitation are well reproduced by the model, such as high precipitation over the eastern and central part and a gradual decrease in the West as a consequence of a weakening monsoon current. Ménégoz et al. [2013] reported that ERAI overestimates precipitation over EH and snowfall is underestimated throughout

the K-H. They have argued that over high altitudes their RCM has produced more realistic precipitation than ERAI due to the better-resolved topography, similar to this study.
Precipitation and temperature bias: Figure-S3 shows the mean seasonal bias of simulated precipitation over glacierized grid-boxes of the K-H sub-regions with respect to MERRA. The model generally shows a good agreement with MERRA over all regions. It shows a seasonal mean positive bias of ~0.5 mm/d over glacierized grid-boxes <40% over all regions, except JJA where it is showing a negative bias of 1 mm/d over glacierized grid-boxes <50%. Over higher glacierized gridboxes a systematic positive bias is apparent in all seasons.
The temperature bias over glacierized grid-boxes is shown in Figure-S4. REMO glacier generally has a warm bias for small glacier grid fractions. For grid-boxes with small glacier cover
(<15-30%) the mean positive bias amounts to about ~1ºC. The seasonal positive bias decreases with increasing glacierized grid-box fraction. Above glacier cover >30% a negative bias is apparent. The temperature bias is larger in SON and in some grid-boxes reaches ± 10ºC.

Observation/Reanalysis
GPCC
APHRODITE
CRU
UDW
Parameter
Precipitation
Precipitation
Temperature
Precipitation
Temperature
Precipitation
Temperature
Resolution K-H
~50km 29.2
~25km
73.7
-3.9
57.7
~50km
-3.4
23.2
~50km
-3.4
K
268.0
267.9
-6.9
151.6
-8.3
307.2
-6.5
WH
-2.3
42.4
-3.9
49.6
-4.0
-6.1
-4.9
CH
5.6
29.1
-4.2
47.8
-1.8
8.7
-2.4
Precipitation -12.1
8.2
-25.4
-7.3
-11.4
ERAI ~80km
MERRA
Temperature
Precipitation
Temperature
~50km
-0.5
21.9
-0.2
-1.7
19.8
-0.9
-0.2
13.0
-0.2
-0.1
0.3
-0.6
-0.6
39.7
0.3
Table-S1: Overview on the reference datasets. The numbers indicate the annual mean precipitation
(%) and temperature (°C) bias of the REMO glacier
simulation when compared against the respective reference dataset over Karakoram-Himalayas (K-H) and its four sub-regions (K, WH, CH, EH),
1989-2007. Statistics are computed after regridding all data to a 0.25° grid.
EH
46.2
105.5
-2.2
57.0
-1.6
31.6
-1.5

Figure-S1: Evaluation of the mean annual cycle (1989-2007) of precipitation (left axis; bars) and temperature (right axis; lines) over the Western Himalayas (top-left), Central Himalayas (topright) and Eastern Himalayas (bottom-left). MERRA/ERAI/REMO glacier
simulated precipitation is analyzed for both total precipitation (MERRA/ERAI/REMO) and rainfall (MERRA
Rainfall/ERAI Rainfall/REMO Rainfall) (no snow).

Figure-S2: Winter (DJF; left column) and summer (JJA; right column) mean precipitation [mm/d] for REMO glacier
and several observational and reanalysis datasets, period 1989-2007.

Figure-S3: Seasonal mean precipitation bias (1989-2007) with respect to MERRA against glacierized grid-box fraction for the four analysis domains. The solid line shows the seasonal mean bias at every 5% interval of glacierized grid box fraction.

Figure-S4: Same as Figure-3, but for mean seasonal temperature biases.