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 m-2 (for files downloaded before 2021/03/19), the correct unit should be m per time step (e.g., m h-1 for the hourly product, m d-1 for the daily product, etc.), instead of W m-2.
• 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 55-year 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 two-way 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 re-initialization 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 spin-up 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 post-processed into product-files: one single file per variable and per year at various aggregation levels.

Fig. 1: WRF domain setup for HAR v2. © TU Berlin	Time Span:	1980-2020
	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 h-1
grdflx	Ground Heat Flux	2d	W m-2
hfx	Upward Heat Flux at the Surface	2d	W m-2
lh	Latent Heat Flux at the Surface	2d	W m-2
lwdown	Downward Long Wave Flux at Ground Surface	2d	W m-2
lwup	Upward Long Wave Flux at Ground Surface	2d	W m-2
netrad	Net Radiation at Ground Surface	2d	W m-2
pblh	PBL Height	2d	m
potevap	Potential Evaporation	2d	W m-2
prcp	Total Precipitation	2d	mm h-1
prcp_fr	Frozen Precipitation	2d	mm h-1
psfc	SFC Pressure	2d	Pa
q2	Water Vapor Mixing Ratio at 2 m	2d	kg kg-1
scld	total column clouds	2d	-
slp	Sea Level Pressure	2d	hPa
snowfall	Grid Scale Snow and Ice	2d	mm h-1
sst	Sea Surface Temperature	2d	K
swdown	Downward Short Wave Flux at Ground Surface	2d	W m-2
swup	Upward Short Wave Flux at Ground Surface	2d	W m-2
t2	Temperature at 2 m	2d	K
tsk	Surface Skin Temperature	2d	K
u10	u at 10m	2d	m s-1
v10	v at 10m	2d	m s-1
ws10	10 m Wind Speed	2d	m s-1
u_intvaporflux	Column Integrated Zonal Water Vapor Flux	2d	kg m-1 s-1
v_intvaporflux	Column Integrated Meridional Water Vapor Flux	2d	kg m-1 s-1
w_intvaporflux	Column Integrated Vertical Water Vapor Flux	2d	kg m-1 s-1
u_intliquidflux	Column Integrated Zonal Liquid Water Flux	2d	kg m-1 s-1
v_intliquidflux	Column Integrated Meridional Liquid Water Flux	2d	kg m-1 s-1
w_intliquidflux	Column Integrated Vertical Liquid Water Flux	2d	kg m-1 s-1
u_intsolidflux	Column Integrated Zonal Solid Water Flux	2d	kg m-1 s-1
v_intsolidflux	Column Integrated Meridional Solid Water Flux	2d	kg m-1 s-1
w_intsolidflux	Column Integrated Vertical Solid Water Flux	2d	kg m-1 s-1
intvaporflux	Column Integrated Absolute Water Vapor Flux	2d	kg m-1 s-1
intliquidflux	Column Integrated Absolute Liquid Water Flux	2d	kg m-1 s-1
intsolidflux	Column Integrated Absolute Solid Water Flux	2d	kg m-1 s-1
3d Variables
geopotential	Full Model Geopotential on Mass Points	3d_press	m2 s-2
qliquid	Liquid Water Mixing Ratio	3d_press	kg kg-1
qsolid	Solid Water Mixing Ratio	3d_press	kg kg-1
qvapor	Water Vapor Mixing Ratio	3d_press	kg kg-1
theta	Potential Temperature (theta)	3d_press	K
u	x-wind component	3d_press	m s-1
v	y-wind component	3d_press	m s-1
w	z-wind component	3d_press	m s-1
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	s-1
f	Coriolis sine latitude term	static	s-1
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 2004-2018, 10 km Domain © TU Berlin	Fig. 3: Mean Precipitation JJA 2004-2018, 10 km Domain © TU Berlin
Fig. 4: Mean Air Temperature at 2 m DJF 2004-2018, 10 km Domain © TU Berlin	Fig. 5: Mean Air Temperature at 2 m JJA 2004-2018, 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 atmosphere-related processes in High and Central Asia. If you have any question please contact:
Xun Wang (HARv2 production),
Marco Otto (regional climatology)