103
mountains (> 5000 m or 6000 m), there have been only few studies which dynamically downscale the observed climate to higher resolution for this region (Tiwari
et al. 2018a, b). Tiwari et al. (2018a) have carried out sensitivity studies using the
weather research and forecast (WRF) model, but this study is only for 1 year of
simulation. Tiwari et al. (2018b) have downscaled the global model projections
using the WRF model for the western Himalayan region under various representative concentration pathways (RCP) scenarios. However, large bias in the global
model projections affects the circulation and precipitation process within the WRF
model domain. Maussion et al. (2014) have carried out the high Asia reanalysis
which is based on short-term forecasts (model is reinitialized every 36 h) using the
WRF model. Therefore, there have been no dynamic downscaling studies covering
the entire Himalaya in seasonal scale.
The main objective of the present study is to simulate the climate of the Himalaya
during winter seasons and to examine the interannual variability of precipitation and
temperature. The WRF model and the regional climate model (RegCM4) have been
used for the study. Section 2 of the paper has the model configurations and data
used. Results are described in Sect. 3. The study is concluded in Sect. 4.
2 The Data and Model Configuration
Two sets of modeling simulations for dynamic downscaling over the Himalaya have
been carried out. The first set of experiment involves high-resolution modeling
using the WRF model while the other set uses the RegCM4 model.
2.1 Data
Six hourly high resolutions (0.75° × 0.75°) European Centre for Medium Range
Weather Forecast (ECMWF) Reanalysis-Interim (ERA-I) data (Dee et al. 2011)
from 1991 to 2010 have been used as initial and boundary conditions of the WRF
model as well as for model diagnostics. The Global Precipitation Climatology
Centre (GPCC) monthly precipitation dataset at 0.5° × 0.5° resolution (Schneider
et al. 2011) and the surface temperature (Ts) data at 0.5° × 0.5° compiled by Climate
Research Unit (CRU) of East Anglia, UK (Harris et al. 2014) have been used as
observations of precipitation and temperatures respectively. In addition, the observed
gridded India Meteorological Department (IMD) precipitation data at 0.25° × 0.25°
resolution (Pai et al. 2014) is used to compare model simulations over the Indian
area. The RegCM4 model uses the hindcasts from a global model at T80 horizontal
resolution (Kar et al. 2011). This model is atmosphere only model (2-tier) forced
with observed and forecasted sea surface temperature (SST). The RegCM4 modelsimulated results are validated with the NCEP- Department of Energy (DOE)
reanalysis-2 data (Kanamitsu et al. 2002).
High-Resolution Dynamic Downscaling of Winter Climate over the Himalaya
mountains (> 5000 m or 6000 m), there have been only few studies which dynamically downscale the observed climate to higher resolution for this region (Tiwari
et al. 2018a, b). Tiwari et al. (2018a) have carried out sensitivity studies using the
weather research and forecast (WRF) model, but this study is only for 1 year of
simulation. Tiwari et al. (2018b) have downscaled the global model projections
using the WRF model for the western Himalayan region under various representative concentration pathways (RCP) scenarios. However, large bias in the global
model projections affects the circulation and precipitation process within the WRF
model domain. Maussion et al. (2014) have carried out the high Asia reanalysis
which is based on short-term forecasts (model is reinitialized every 36 h) using the
WRF model. Therefore, there have been no dynamic downscaling studies covering
the entire Himalaya in seasonal scale.
The main objective of the present study is to simulate the climate of the Himalaya
during winter seasons and to examine the interannual variability of precipitation and
temperature. The WRF model and the regional climate model (RegCM4) have been
used for the study. Section 2 of the paper has the model configurations and data
used. Results are described in Sect. 3. The study is concluded in Sect. 4.
2 The Data and Model Configuration
Two sets of modeling simulations for dynamic downscaling over the Himalaya have
been carried out. The first set of experiment involves high-resolution modeling
using the WRF model while the other set uses the RegCM4 model.
2.1 Data
Six hourly high resolutions (0.75° × 0.75°) European Centre for Medium Range
Weather Forecast (ECMWF) Reanalysis-Interim (ERA-I) data (Dee et al. 2011)
from 1991 to 2010 have been used as initial and boundary conditions of the WRF
model as well as for model diagnostics. The Global Precipitation Climatology
Centre (GPCC) monthly precipitation dataset at 0.5° × 0.5° resolution (Schneider
et al. 2011) and the surface temperature (Ts) data at 0.5° × 0.5° compiled by Climate
Research Unit (CRU) of East Anglia, UK (Harris et al. 2014) have been used as
observations of precipitation and temperatures respectively. In addition, the observed
gridded India Meteorological Department (IMD) precipitation data at 0.25° × 0.25°
resolution (Pai et al. 2014) is used to compare model simulations over the Indian
area. The RegCM4 model uses the hindcasts from a global model at T80 horizontal
resolution (Kar et al. 2011). This model is atmosphere only model (2-tier) forced
with observed and forecasted sea surface temperature (SST). The RegCM4 modelsimulated results are validated with the NCEP- Department of Energy (DOE)
reanalysis-2 data (Kanamitsu et al. 2002).
High-Resolution Dynamic Downscaling of Winter Climate over the Himalaya