The High Asia Refined analysis version 2 (HAR v2)
The High Asia Refined analysis version 2 (HAR v2) is an atmospheric dataset
generated within the framework of the
CaTeNA project
(Climatic and Tectonic Natural Hazards in Central Asia) funded by the Federal Ministry of
Education and Research (BMBF). Compared to the old version
(HAR
),
HAR v2 has an extended 10 km domain covering the whole Tibetan Plateau and the surrounding
mountains (Fig.1), as well as a longer temporal coverage. It will be extended back
to 1979 and will be continuously updated in the future.
Important message (2021/03/22):
 Due to a mistake in the WRF model, the units of potevap (potential evaporation) in our products
were wrong and have been corrected. If the unit of potevap in your nc file is W m2
(for files downloaded before 2021/03/19), the correct unit should be m per time step
(e.g., m h1 for the hourly product, m d1 for the daily product, etc.), instead of W m2.
 The WRF model sometimes outputs negative values of mixing ratio (
WRF Support Forum
).
If you are using mixing ratio variables (q2, qvapor, qsolid, and qliquid),
we suggest modifying the negative values to very small positive values.
We apologize for any inconvenience caused.
Description
The HAR v2 dataset is generated by dynamical downscaling using the Weather Research and Forecasting model (WRF)
version 4.1.
ERA5 reanalysis data
provided by ECMWF is used as forcing data. In addition, snow depth from
the Japanese 55year Reanalysis
is applied to correct snow depth initialized from ERA5, since ERA5 largely overestimates
snow depth over the Tibetan Plateau (
Orsolini et al., 2019
).
The domain setup (Fig.1) consists of twoway nested domains with 30 km and 10 km grid spacing. Note that,
HAR v2 only provides results from the 10 km domain. The forcing strategy is daily reinitialization
adopted from the HAR (
Maussion et al., 2011
,
2014
). Each run starts at 12:00 UTC and contains 36 h, with the first 12 h as spinup time.
This strategy avoids the model from deviating too far from the forcing data and provides
computational flexibility since daily runs are totally independent of each other and can
be computed in parallel and in any sequence.
Same as HAR, the output of the model is postprocessed into productfiles:
one single file per variable and per year at various aggregation levels.
Fig. 1: WRF domain setup for HAR v2.
© TU Berlin

Time Span:

19802020

Spatial Resolution:

10 km

Temporal Resolution:

hourly (h), daily (d), monthly (m), yearly (y)

Data Format:

compressed NetCDF 4

Pressure Levels (hPa):

1000, 975, 925, 900, 850, 800, 700, 650, 600, 550, 500, 450, 400, 350, 300, 250, 200, 150, 100, 75

List of Selected Variables
Variable Name

Variable Description

Type

Unit

albedo

Albedo

2d



et

Evapotranspiration

2d

mm h1

grdflx

Ground Heat Flux

2d

W m2

hfx 
Upward Heat Flux at the Surface  2d 
W m2 
lh 
Latent Heat Flux at the Surface  2d 
W m2 
lwdown 
Downward Long Wave Flux at Ground Surface  2d 
W m2 
lwup 
Upward Long Wave Flux at Ground Surface  2d 
W m2 
netrad 
Net Radiation at Ground Surface  2d 
W m2 
pblh 
PBL Height  2d 
m 
potevap 
Potential Evaporation  2d 
W m2 
prcp 
Total Precipitation
 2d 
mm h1 
prcp_fr 
Frozen Precipitation  2d 
mm h1 
psfc 
SFC Pressure  2d 
Pa 
q2 
Water Vapor Mixing Ratio at 2 m  2d 
kg kg1 
scld 
total column clouds  2d 
 
slp 
Sea Level Pressure  2d 
hPa 
snowfall 
Grid Scale Snow and Ice  2d 
mm h1 
sst 
Sea Surface Temperature  2d 
K 
swdown 
Downward Short Wave Flux at Ground Surface  2d 
W m2 
swup 
Upward Short Wave Flux at Ground Surface  2d 
W m2 
t2 
Temperature at 2 m  2d 
K 
tsk 
Surface Skin Temperature  2d 
K 
u10 
u at 10m  2d 
m s1 
v10 
v at 10m  2d 
m s1 
ws10 
10 m Wind Speed  2d 
m s1 
u_intvaporflux 
Column Integrated Zonal Water Vapor Flux  2d 
kg m1 s1 
v_intvaporflux 
Column Integrated Meridional Water Vapor Flux  2d 
kg m1 s1 
w_intvaporflux 
Column Integrated Vertical Water Vapor Flux  2d 
kg m1 s1 
u_intliquidflux 
Column Integrated Zonal Liquid Water Flux  2d 
kg m1 s1 
v_intliquidflux 
Column Integrated Meridional Liquid Water Flux  2d 
kg m1 s1 
w_intliquidflux 
Column Integrated Vertical Liquid Water Flux  2d 
kg m1 s1 
u_intsolidflux 
Column Integrated Zonal Solid Water Flux  2d 
kg m1 s1 
v_intsolidflux 
Column Integrated Meridional Solid Water Flux  2d 
kg m1 s1 
w_intsolidflux 
Column Integrated Vertical Solid Water Flux  2d 
kg m1 s1 
intvaporflux 
Column Integrated Absolute Water Vapor Flux  2d 
kg m1 s1 
intliquidflux 
Column Integrated Absolute Liquid Water Flux  2d 
kg m1 s1 
intsolidflux 
Column Integrated Absolute Solid Water Flux  2d 
kg m1 s1 
3d Variables




geopotential 
Full Model Geopotential on Mass Points  3d_press 
m2 s2 
qliquid 
Liquid Water Mixing Ratio  3d_press 
kg kg1 
qsolid 
Solid Water Mixing Ratio  3d_press 
kg kg1 
qvapor 
Water Vapor Mixing Ratio  3d_press 
kg kg1 
theta 
Potential Temperature (theta)  3d_press 
K 
u 
xwind component  3d_press 
m s1 
v 
ywind component  3d_press 
m s1 
w 
zwind component  3d_press 
m s1 
Static Variables




hgt 
Terrain Height  static 
m 
lu_index 
Land Use Category  static 
 
cosalpha 
Local cosine of map rotation  static 
 
sinalpha 
Local sine of map rotation  static 
 
lai 
Leaf area index  static 
area/area 
e 
Coriolis cosine latitude term  static 
s1 
f 
Coriolis sine latitude term  static 
s1 
isltyp 
Dominant soil category  static 
 
ivgtyp 
Dominant vegetation category  static 
 
vegfra 
Vegetation fraction  static 
 
landmask 
Land mask (1 for land, 0 for water)  static 
 
mapfac_m 
Map scale factor on mass grid  static 
 
mapfac_mx 
map scale factor on mass grid, x direction  static 
 
mapfac_my 
map scale factor on mass grid, y direction  static 
 
Examples
Fig. 2: Mean Precipitation DJF 20042018, 10 km Domain
© TU Berlin

Fig. 3: Mean Precipitation JJA 20042018, 10 km Domain
© TU Berlin

Fig. 4: Mean Air Temperature at 2 m DJF 20042018, 10 km Domain
© TU Berlin

Fig. 5: Mean Air Temperature at 2 m JJA 20042018, 10 km Domain
© TU Berlin

Data Access
Please refer to Wang et al. (2021) when using the HAR v2 data.
Here you can find the data download page
We are looking forward to new collaborations towards
a better understanding of atmosphererelated processes in High and Central Asia. If you have any question please contact:
Xun Wang (HARv2 production),
Marco Otto (regional climatology)