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Table 1: Overview of single level variables. Most static fields (except land-sea mask and orography) marked with * are available only as NetCDF-files below. Anchor table1 table1
Precipitation, cloud water and humidity | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
2r | % | 260242 | yes | yes | 2m | |
2sh | kg/kg | 174096 | yes | yes | 2m | |
tciwv | kg/m2 | 260057 | yes | yes | vertically integrated above the surface | |
tclw | kg/m2 | 78 | no | yes | vertically integrated above the surface | |
tciw | kg/m2 | 79 | no | yes | vertically integrated above the surface | |
tcolg | kg/m2 | 260001 | yes | yes | vertically integrated above the surface | |
tp | kg/m2 | 228228 | no | yes | surface | |
tirf | kg/m2 | 235015 | no | yes | surface | |
titspf | kg/m2 | 260645 | no | yes | surface | |
ptype | integer code | 260015 | no | yes | surface | |
sro | kg/m2 | 174008 | no | yes | surface | |
Percolation (drainage) | perc | kg/m2 | 260430 | no | yes | sub-surface |
Temperature and wind speed | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
10si | m/s | 207 | yes | yes | 10m | |
10wdir | degrees | 260260 | yes | yes | 10m | |
10m u-component of wind (defined relative to the rotated model grid) | 10u | m/s | 165 | yes | yes | 10m |
10m v component of wind | 10v | m/s | 166 | yes | yes | 10m |
10m eastward wind gust since previous post-processing | 10efg | m/s | 260646 | no | yes | 10m |
10m northward wind gust since previous post-processing | 10nfg | m/s | 260647 | no | yes | 10m |
10fg | m/s | 49 | no | yes | 10m | |
mx2t | K | 201 | no | yes | 2m | |
mn2t | K | 202 | no | yes | 2m | |
2t | K | 167 | yes | yes | 2m | |
skt | K | 235 | yes | yes | Surface |
Accumulated fluxes | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
al | % | 260509 |
yes** | yes | surface | ||||
eva | kg/m2 | 260259 | no | yes | surface | |
tisef | kg/m2 | 235072 | no | yes | surface | |
sshf | J/m2 | 146 | no | yes | surface | |
slhf | J/m2 | 147 | no | yes | surface | |
tislhef | J/m2 | 235019 | no | yes | surface | |
tislhsf | J/m2 | 235071 | no | yes | surface | |
dsrp | J/m2 | 47 | no | yes | surface | |
tidirswrf | J/m2 | 260264 | no | yes | surface | |
ssr | J/m2 | 176 | no | yes | surface | |
ssrd | J/m2 | 169 | no | yes | surface | |
ssrc | J/m2 | 210 | no | yes | surface | |
str | J/m2 | 177 | no | yes | surface | |
strd | J/m2 | 175 | no | yes | surface | |
strc | J/m2 | 211 | no | yes | surface | |
Top net solar radiation | tsr | J/m2 | 178 | no | yes | surface |
ttr | J/m2 | 179 | no | yes | surface | |
tisemf | kg⋅m/s | 235017 | no | yes | surface | |
tisnmf | kg⋅m/s | 235018 | no | yes | surface | |
Pressure | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
msl | Pa | 151 | yes | yes | surface (scaled to sea level) | |
sp | Pa | 134 | yes | yes | surface | |
Geometric cloud properties | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
hcc | % | 3075 | yes | yes | above 5000m | |
mcc | % | 3074 | yes | yes | 2500m - 5000m | |
lcc | % | 3073 | yes | yes | surface - 2500m | |
tcc | % | 228164 | yes | yes | above ground | |
fog | % | 260648 | no | yes | lowest model level | |
vis | m | 3020 | yes | yes | lowest model level | |
cdcb | m | 260107 | yes | yes | - | |
cdct | m | 260108 | yes | yes | - | |
Snow | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
rsn | kg/m3 | 33 | yes | yes | surface | |
sd | kg/m2 | 228141 | yes | yes | surface | |
fscov | 0-1 | 260289 | yes | no | surface | |
asn | % | 228032 | yes | no | surface | |
Surface roughness lengths | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
sr | m | 173 | yes | no | surface | |
srlh | m | 260651 | yes | no | surface | |
Sea states | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
sst | K | 34 | yes | no | surface | |
ci | 0-1 | 31 | yes | no | surface | |
sist | K | 260649 | yes | yes | surface | |
sithick | m | 174098 | yes | no | surface | |
sitd | m | 260650 | yes | yes | surface | |
Static fields | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | Height |
lsm | % | 172 | no | no | surface | |
Sea tile fraction* | NA | 0-1 | NA | no | no | surface |
Inland water tile fraction* | NA | 0-1 | NA | no | no | surface |
Urban tile fraction* | NA | 0-1 | NA | no | no | surface |
Nature tile fraction* | NA | 0-1 | NA | no | no | surface |
Glacier fraction* | NA | 0-1 | NA | no | no | surface |
Subgrid orography average slope* | NA | 0-1 | NA | no | no | surface |
Subgrid orography standard deviation* | NA | m | NA | no | no | surface |
orog | m | 228002 | no | no | surface |
The static fields marked as * above are available as NetCDF files for the West and East domain respectively here: fractions.west.nc and fractions.east.nc
** Albedo is available at analysis time, but as a static climatological value which we discourage for use. Only the forecast time albedos should be used, see end of Section 5.5 below.
Soil level variables
Soil level variables are given for two model depths, where the first depth is the soil surface and the second depth is the so-called root depth. The root depth varies with the cover type climatology. Please note that the soil level variables are accommodated in the Arctic Regional Reanalysis single level variables catalogue entry.
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Soil level variables | |||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… |
vsi | m³/m³ | 260644 | yes | yes | |
vsw | m³/m³ | 260199 | yes | yes |
Model level variables
Model level variables are output at 65 hybrid model levels of the HARMONIE-AROME model. These follow the surface at the lowest levels and are gradually evolved into pure pressure levels at the highest levels. These are the levels at which the model computations are done. The height level and pressure level variables are interpolated from these data.
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Table 3: Overview of model level variables Anchor table3 table3
Model level variables | |||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2 |
q | kg/kg | 133 | yes | yes | |
t | K | 130 | yes | yes | |
u-component of wind (defined relative to the rotated model grid) | u | m/s | 131 | yes | yes |
v-component of wind (defined relative to the rotated model grid) | v | m/s | 132 | yes | yes |
ccl | % | 260257 | yes | yes | |
clwc | kg/kg | 246 | yes | yes | |
ciwc | kg/kg | 247 | yes | yes | |
crwc | kg/kg | 75 | yes | yes | |
cswc | kg/kg | 76 | yes | yes | |
grle | kg/kg | 260028 | yes | yes | |
tke | J/kg | 260155 | yes | yes |
Pressure level variables
Pressure level variables are interpolated to 23 specific pressure levels: 1000, 950, 925, 875, 850, 800, 750, 700, 600, 500, 400, 300, 200, 100, 70, 50, 30, 20 and 10 hPa. Thus, they are on isobaric surfaces.
Output of diagnostic variables at pressure levels are available in three hourly intervals at 00, 03, 06, 09, 12, 15, 18 and 21 UTC.
Long forecasts are available from the forecasts initiated at 00 and 12 UTC. Long forecasts include forecast lengths of 1, 2, 3, 4, 5, 6, 9, 12, 15, 18, 21, 24 and 30 hours.
Short forecasts of 1, 2 and 3 hours are made for the forecasts initiated at 03, 06, 09, 15, 18 and 21 UTC.
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Pressure level variables | ||||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… | |
r | % | 157 | yes | yes | ||
t | K | 130 | yes | yes | ||
u-component of wind (defined relative to the rotated model grid) | u | m/s | 131 | yes | yes | |
v-component of wind (Component defined relative to the rotated model grid) | v | m/s | 132 | yes | yes | |
wz | m/s | 260238 | yes | yes | ||
ccl | % | 260257 | yes | yes | ||
clwc | kg/kg | 246 | yes | yes | ||
ciwc | kg/kg | 247 | yes | yes | ||
crwc | kg/kg | 75 | yes | yes | ||
cswc | kg/kg | 76 | yes | yes | ||
grle | kg/kg | 260028 | yes | yes | ||
papt | K | 3014 | yes | yes | ||
z | m²/s² | 129 | yes | yes | ||
pv | K·m²/ (kg·s) | 60 | yes | yes |
Height level variables
Height level variables are interpolated to 11 specific height levels: 15, 30, 50, 75, 100, 150, 200, 250, 300, 400 and 500 metres above the surface.
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Height level variables | |||||
Name | Short Name | Unit | Param ID | Analysis: 0,3,...,21 | Forecast: 1,2,3,… |
r | % | 157 | yes | yes | |
t | K | 130 | yes | yes | |
ws | m/s | 10 | yes | yes | |
wdir | deg | 3031 | yes | yes | |
clwc | kg/kg | 246 | yes | yes | |
ciwc | kg/kg | 247 | yes | yes | |
Pressure | pres | Pa | 54 | yes | yes |
Details about the data fields
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The wind direction D clockwise from North can be calculated as
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LaTeX Formatting |
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$$ D = atan atan2{2} ({u},{v}) + 180^{\circ} + \alpha, (4) $$ |
where 𝛼 is the local rotation of the model grid relative to North, and atan2 is the very specific 2-argument arcus tangens function, which is included in most programming languages. For definition of the atan2 function, see for instance at https://en.wikipedia.org/wiki/Atan2. Take care to check if the atan2 result is in radians, in which case it should be converted to degrees with the factor 180°/π. Also take care to check if the resulting direction is between 0° and 360°. Note that the wind direction is the direction from which the wind comes! The grid rotation angle 𝛼 can be computed with this script: https://github.com/metno/NWPdocs/wiki/Examples/#wind-direction-obtained-from-x-y-wind.
10-metre u and v wind gust components are also output. These are computed from the diagnosed 10-metre winds and the turbulent kinetic energy (pers. comm. Gwenaëlle Hello, Meteo France, 2007).
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All energy fluxes at the surface are output as accumulated variables from the initial time of the forecast to the forecast hour in question with the unit J/m2. They Note that a different accumulation applies to the albedo, see below. The other accumulated variables are considered positive downward to the surface. Energy fluxes are not output variables at the analysis times. Average hourly energy fluxes in W/m2 can be computed by subtracting two successive hourly accumulated variables and dividing by 3600 s. The solar radiation variables at the surface are accumulated downward, direct, direct normal and net solar radiation. Direct normal solar radiation is considered on a plane perpendicular to the direction to the sun, while the other solar variables are considered on a horizontal surface. The albedo in units of % is also given. Multiplying this with the accumulated downward solar radiation gives the accumulated upward solar radiation. The net solar radiation is the difference between the downward solar radiation and the upward solar radiation. Note that the albedo should only be used from forecast data, as the analysis time albedo are is incorrect – and not used in the model. The variable accumulated net clear sky solar radiation is the net solar radiation of a cloud free atmosphere. Dividing this with one minus the albedo gives the accumulated downward clear sky solar radiation. The thermal radiance variables at the surface are accumulated downward, net, and net clear sky thermal radiation. The thermal radiation variables are all considered on a horizontal surface. The net thermal radiation is the difference between the downward thermal radiation and the upward thermal radiation. The upward thermal radiation can be calculated by subtracting the net thermal radiation from the downward thermal radiation. The accumulated surface sensible heat flux is the conductive energy from the atmosphere to the surface. If this is going from the surface to the atmosphere it has negative values. The accumulated latent heat flux is the sum of all latent energy fluxes that are due to the phase transitions of water. Here condensation causes a positive latent heat flux to the surface, and evaporation causes a negative heat flux from the surface. The latent heat due to evaporation and sublimation are given as individual output variables.
The u and v components of the accumulated surface momentum flux are given as output variables in units of kg m/s. The momentum roughness length and the heat roughness length as used in the model are given as output in units of m. Note that the roughness lengths should only be used from forecast data, as the analysis time values are incorrect – and not used in the model.
The albedo is accumulated with a special procedure, noting that it changes over time depending on e.g. snowfall. It is derived from the formula: albedo = 1 - SWnet/SW↓, where SW↓ is the downward solar flux at the surface, and SWnet is the net (downward minus upward) solar flux at the surface. The solar fluxes are accumulated over a given time interval. This time interval is one hour until the +6h forecast range and three hours afterwards. So these albedos represent averages over hourly or 3-hourly periods prior to the forecast time. Instantaneous albedos at the output times would be less precise than using these accumulated variables, see alsosection 4 in the note by Hogan, 2015. The problem with this procedure is that in some cases unphysical albedo values (>100%) may occur due to rounding errors. There is also an analysis time albedo provided in the data set, which can be quite different from the actual albedo at forecast times ad therefore it is not recommended to be used.
Variables at the top of the atmosphere
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Name | Levels |
Pressure | Surface as well as mean sea level |
U-component of wind | Pressure levels (50 - 1000 hPa) |
V-component of windy | Pressure levels (50 - 1000 hPa) |
Temperature | Pressure levels (50 - 1000 hPa) |
Geopotential (East domain only) | Pressure levels (50 - 1000 hPa) |
Relative humidity (East domain)/Specific humidity (West domain) | Pressure levels (50 - 1000 hPa) |
In section 6.5 we present uncertainties measured as statistics of actual deviations from observations (also known as verification statistics). Note that observations are a reference not identical to the actual truth, as they also will have uncertainties as well as representativeness issues. This verification statistics is provided for a set of near-surface quantities which are covered by the meteorological observation network, including 2m temperature, 10m winds and precipitation.
Field based atmospheric uncertainty estimation
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Name | Short name | Unit | Level | Summer statistics | Winter statistics | ||
Upper Bound STDV | Refined STDV | Upper Bound STDV | Refined STDV | ||||
Surface pressure | sp | Pa | 0m above ground | 37.20 | 26.78 | 41.14 | 38.67 |
Mean sea level pressure | msl | Pa | 0m above sea level | 38.18 | 27.49 | 42.15 | 39.62 |
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Figure 2: Climatological analysis error standard deviation for u-component of wind: summer statistics (left), winter statistics (right) as function of standard vertical pressure levels for the CARRA-East domain.
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Name | Short name | Unit | Level | Summer statistics | Winter statistics | ||
Upper Bound STDV | Refined STDV | Upper Bound STDV | Refined STDV | ||||
u-component of wind | u | m/s | 50hPa | 0.545 | 0.223 | 0.556 | 0.228 |
u-component of wind | u | m/s | 100hPa | 0.372 | 0.153 | 0.397 | 0.169 |
u-component of wind | u | m/s | 150hPa | 0.584 | 0.239 | 0.619 | 0.254 |
u-component of wind | u | m/s | 200hPa | 0.865 | 0.355 | 0.923 | 0.378 |
u-component of wind | u | m/s | 250hPa | 1.077 | 0.442 | 1.089 | 0.447 |
u-component of wind | u | m/s | 300hPa | 1.290 | 0.530 | 1.240 | 0.508 |
u-component of wind | u | m/s | 400hPa | 1.282 | 0.526 | 1.292 | 0.530 |
u-component of wind | u | m/s | 500hPa | 1.284 | 0.526 | 1.364 | 0.559 |
u-component of wind | u | m/s | 600hPa | 1.322 | 0.648 | 1.392 | 0.738 |
u-component of wind | u | m/s | 700hPa | 1.346 | 0.740 | 1.404 | 0.927 |
u-component of wind | u | m/s | 800hPa | 1.344 | 0.833 | 1.324 | 1.006 |
u-component of wind | u | m/s | 850hPa | 1.331 | 0.865 | 1.274 | 1.045 |
u-component of wind | u | m/s | 900hPa | 1.311 | 0.905 | 1.275 | 1.122 |
u-component of wind | u | m/s | 925hPa | 1.315 | 0.921 | 1.295 | 1.178 |
u-component of wind | u | m/s | 950hPa | 1.330 | 0.958 | 1.305 | 1.227 |
u-component of wind | u | m/s | 1000hPa | 1.302 | 0.937 | 1.172 | 1.102 |
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Name | Short name | Unit | Level | Summer statistics | Winter statistics | ||
Upper Bound STDV | Refined STDV | Upper Bound STDV | Refined STDV | ||||
v-component of wind | v | m/s | 50hPa | 0.541 | 0.222 | 0.541 | 0.222 |
v-component of wind | v | m/s | 100hPa | 0.376 | 0.154 | 0.384 | 0.157 |
v-component of wind | v | m/s | 150hPa | 0.597 | 0.245 | 0.599 | 0.246 |
v-component of wind | v | m/s | 200hPa | 0.884 | 0.362 | 0.898 | 0.368 |
v-component of wind | v | m/s | 250hPa | 1.105 | 0.453 | 1.061 | 0.435 |
v-component of wind | v | m/s | 300hPa | 1.337 | 0.548 | 1.209 | 0.496 |
v-component of wind | v | m/s | 400hPa | 1.313 | 0.538 | 1.270 | 0.521 |
v-component of wind | v | m/s | 500hPa | 1.328 | 0.544 | 1.351 | 0.554 |
v-component of wind | v | m/s | 600hPa | 1.363 | 0.668 | 1.391 | 0.737 |
v-component of wind | v | m/s | 700hPa | 1.383 | 0.761 | 1.402 | 0.925 |
v-component of wind | v | m/s | 800hPa | 1.382 | 0.857 | 1.332 | 1.012 |
v-component of wind | v | m/s | 850hPa | 1.363 | 0.886 | 1.282 | 1.051 |
v-component of wind | v | m/s | 900hPa | 1.342 | 0.926 | 1.277 | 1.124 |
v-component of wind | v | m/s | 925hPa | 1.344 | 0.941 | 1.293 | 1.177 |
v-component of wind | v | m/s | 950hPa | 1.361 | 0.980 | 1.299 | 1.221 |
v-component of wind | v | m/s | 1000hPa | 1.318 | 0.949 | 1.167 | 1.097 |
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Name | Short name | Unit | Level | Summer statistics | Winter statistics | ||
Upper Bound STDV | Refined STDV | Upper Bound STDV | Refined STDV | ||||
temperature | t | K | 50hPa | 0.141 | 0.058 | 0.142 | 0.058 |
temperature | t | K | 100hPa | 0.122 | 0.050 | 0.122 | 0.050 |
temperature | t | K | 150hPa | 0.230 | 0.094 | 0.224 | 0.092 |
temperature | t | K | 200hPa | 0.466 | 0.191 | 0.441 | 0.181 |
temperature | t | K | 250hPa | 0.490 | 0.201 | 0.438 | 0.180 |
temperature | t | K | 300hPa | 0.392 | 0.161 | 0.406 | 0.167 |
temperature | t | K | 400hPa | 0.314 | 0.129 | 0.341 | 0.140 |
temperature | t | K | 500hPa | 0.346 | 0.142 | 0.359 | 0.147 |
temperature | t | K | 600hPa | 0.399 | 0.196 | 0.399 | 0.211 |
temperature | t | K | 700hPa | 0.465 | 0.256 | 0.465 | 0.307 |
temperature | t | K | 800hPa | 0.537 | 0.333 | 0.485 | 0.369 |
temperature | t | K | 850hPa | 0.586 | 0.381 | 0.508 | 0.417 |
temperature | t | K | 900hPa | 0.614 | 0.424 | 0.520 | 0.458 |
temperature | t | K | 925hPa | 0.604 | 0.423 | 0.531 | 0.483 |
temperature | t | K | 950hPa | 0.612 | 0.441 | 0.546 | 0.513 |
temperature | t | K | 1000hPa | 0.582 | 0.419 | 0.576 | 0.504 |
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Name | Short name | Unit | Level | Summer statistics | Winter statistics | ||
Upper Bound STDV | Refined STDV | Upper Bound STDV | Refined STDV | ||||
geopotential | z | m²/s² | 50hPa | 42.17 | 17.29 | 41.54 | 17.03 |
geopotential | z | m²/s² | 100hPa | 41.29 | 16.93 | 40.39 | 16.56 |
geopotential | z | m²/s² | 150hPa | 39.06 | 16.01 | 38.22 | 15.67 |
geopotential | z | m²/s² | 200hPa | 30.34 | 12.44 | 30.41 | 12.47 |
geopotential | z | m²/s² | 250hPa | 29.65 | 12.16 | 29.87 | 12.25 |
geopotential | z | m²/s² | 300hPa | 31.28 | 12.82 | 30.92 | 12.68 |
geopotential | z | m²/s² | 400hPa | 29.68 | 12.17 | 29.56 | 12.12 |
geopotential | z | m²/s² | 500hPa | 27.60 | 11.32 | 27.56 | 11.30 |
geopotential | z | m²/s² | 600hPa | 26.57 | 13.02 | 26.47 | 14.03 |
geopotential | z | m²/s² | 700hPa | 25.99 | 14.29 | 25.93 | 17.11 |
geopotential | z | m²/s² | 800hPa | 25.40 | 15.75 | 25.48 | 19.36 |
geopotential | z | m²/s² | 850hPa | 25.13 | 16.33 | 25.68 | 21.06 |
geopotential | z | m²/s² | 900hPa | 25.40 | 17.53 | 26.80 | 23.58 |
geopotential | z | m²/s² | 925hPa | 25.89 | 18.12 | 27.77 | 25.27 |
geopotential | z | m²/s² | 950hPa | 26.74 | 19.25 | 29.02 | 27.28 |
geopotential | z | m²/s² | 1000hPa | 29.47 | 21.22 | 32.43 | 30.48 |
Table 12: Climatological analysis error standard deviation relative humidity for the CARRA-East domain. Anchor table12 table12
Name | Short name | Unit | Level | Summer statistics | Winter statistics | ||
Upper Bound STDV | Refined STDV | Upper Bound STDV | Refined STDV | ||||
relative humidity | r | % | 50hPa | 0.024 | 0.010 | 1.256 | 0.515 |
relative humidity | r | % | 100hPa | 0.010 | 0.004 | 0.194 | 0.080 |
relative humidity | r | % | 150hPa | 0.040 | 0.016 | 0.425 | 0.174 |
relative humidity | r | % | 200hPa | 0.534 | 0.219 | 1.913 | 0.784 |
relative humidity | r | % | 250hPa | 3.223 | 1.321 | 4.900 | 2.009 |
relative humidity | r | % | 300hPa | 6.153 | 2.523 | 8.861 | 3.633 |
relative humidity | r | % | 400hPa | 8.236 | 3.377 | 12.634 | 5.180 |
relative humidity | r | % | 500hPa | 7.181 | 2.944 | 12.562 | 5.150 |
relative humidity | r | % | 600hPa | 6.819 | 3.341 | 11.824 | 6.267 |
relative humidity | r | % | 700hPa | 6.740 | 3.707 | 11.522 | 7.605 |
relative humidity | r | % | 800hPa | 6.544 | 4.057 | 9.638 | 7.325 |
relative humidity | r | % | 850hPa | 6.118 | 3.977 | 8.194 | 6.719 |
relative humidity | r | % | 900hPa | 5.215 | 3.598 | 6.820 | 6.002 |
relative humidity | r | % | 925hPa | 4.674 | 3.272 | 6.303 | 5.736 |
relative humidity | r | % | 950hPa | 4.285 | 3.085 | 5.767 | 5.421 |
relative humidity | r | % | 1000hPa | 3.477 | 2.503 | 4.277 | 4.020 |
Uncertainties for the CARRA-West model domain
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Name | Short name | Unit | Level | Upper Bound STDV | Refined STDV |
Surface pressure | sp | Pa | 0m above ground | 26.11 | 7.04 |
Mean sea level pressure | msl | Pa | 0m above sea level | 39.44 | 10.64 |
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Figure 7: Climatological analysis error standard deviation for u-component of wind (left plot) and for v-component of wind (right plot) as function of standard vertical pressure levels for the CARRA-West domain.
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Name | Short name | Unit | Level | Upper Bound STDV | Refined STDV |
u-component of wind | u | m/s | 50hPa | 0.540 | 0.146 |
u-component of wind | u | m/s | 100hPa | 0.370 | 0.100 |
u-component of wind | u | m/s | 150hPa | 0.447 | 0.121 |
u-component of wind | u | m/s | 200hPa | 0.611 | 0.165 |
u-component of wind | u | m/s | 250hPa | 0.732 | 0.198 |
u-component of wind | u | m/s | 300hPa | 0.871 | 0.235 |
u-component of wind | u | m/s | 400hPa | 0.869 | 0.235 |
u-component of wind | u | m/s | 500hPa | 0.862 | 0.233 |
u-component of wind | u | m/s | 600hPa | 0.887 | 0.240 |
u-component of wind | u | m/s | 700hPa | 0.893 | 0.241 |
u-component of wind | u | m/s | 800hPa | 0.856 | 0.231 |
u-component of wind | u | m/s | 850hPa | 0.831 | 0.224 |
u-component of wind | u | m/s | 900hPa | 0.810 | 0.219 |
u-component of wind | u | m/s | 925hPa | 0.803 | 0.217 |
u-component of wind | u | m/s | 950hPa | 0.799 | 0.216 |
u-component of wind | u | m/s | 1000hPa | 0.773 | 0.209 |
Anchor | ||||
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Name | Short name | Unit | Level | Upper Bound STDV | Refined STDV |
v-component of wind | v | m/s | 50hPa | 0.535 | 0.144 |
v-component of wind | v | m/s | 100hPa | 0.360 | 0.097 |
v-component of wind | v | m/s | 150hPa | 0.449 | 0.135 |
v-component of wind | v | m/s | 200hPa | 0.603 | 0.162 |
v-component of wind | v | m/s | 250hPa | 0.714 | 0.193 |
v-component of wind | v | m/s | 300hPa | 0.851 | 0.230 |
v-component of wind | v | m/s | 400hPa | 0.853 | 0.230 |
v-component of wind | v | m/s | 500hPa | 0.852 | 0.230 |
v-component of wind | v | m/s | 600hPa | 0.877 | 0.237 |
v-component of wind | v | m/s | 700hPa | 0.884 | 0.239 |
v-component of wind | v | m/s | 800hPa | 0.852 | 0.230 |
v-component of wind | v | m/s | 850hPa | 0.826 | 0.223 |
v-component of wind | v | m/s | 900hPa | 0.801 | 0.216 |
v-component of wind | v | m/s | 925hPa | 0.794 | 0.214 |
v-component of wind | v | m/s | 950hPa | 0.792 | 0.214 |
v-component of wind | v | m/s | 1000hPa | 0.763 | 0.206 |
Anchor | ||||
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Figure 8: Climatological analysis error standard deviation for temperature (left plot) and specific humidity (right plot) as a function of standard pressure levels for the CARRA-West domain.
Anchor | ||||
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Name | Short name | Unit | Level | Upper Bound STDV | Refined STDV |
temperature | t | K | 50hPa | 0.130 | 0.035 |
temperature | t | K | 100hPa | 0.112 | 0.030 |
temperature | t | K | 150hPa | 0.169 | 0.045 |
temperature | t | K | 200hPa | 0.276 | 0.075 |
temperature | t | K | 250hPa | 0.285 | 0.077 |
temperature | t | K | 300hPa | 0.263 | 0.071 |
temperature | t | K | 400hPa | 0.227 | 0.061 |
temperature | t | K | 500hPa | 0.235 | 0.063 |
temperature | t | K | 600hPa | 0.259 | 0.070 |
temperature | t | K | 700hPa | 0.350 | 0.095 |
temperature | t | K | 800hPa | 0.473 | 0.128 |
temperature | t | K | 850hPa | 0.500 | 0.135 |
temperature | t | K | 900hPa | 0.508 | 0.137 |
temperature | t | K | 925hPa | 0.509 | 0.137 |
temperature | t | K | 950hPa | 0.520 | 0.140 |
temperature | t | K | 1000hPa | 0.542 | 0.146 |
Table 17: Climatological analysis error standard deviation for specific humidity for the CARRA-West domain. Anchor table17 table17
Name | Short name | Unit | Level | Upper Bound STDV | Refined STDV |
specific humidity | r | g/kg | 50hPa | 0. | 0. |
specific humidity | r | g/kg | 100hPa | 0. | 0. |
specific humidity | r | g/kg | 150hPa | 0. | 0. |
specific humidity | r | g/kg | 200hPa | 0.001 | 0.0002 |
specific humidity | r | g/kg | 250hPa | 0.002 | 0.0004 |
specific humidity | r | g/kg | 300hPa | 0.006 | 0.001 |
specific humidity | r | g/kg | 400hPa | 0.020 | 0.005 |
specific humidity | r | g/kg | 500hPa | 0.048 | 0.013 |
specific humidity | r | g/kg | 600hPa | 0.082 | 0.022 |
specific humidity | r | g/kg | 700hPa | 0.113 | 0.031 |
specific humidity | r | g/kg | 800hPa | 0.127 | 0.034 |
specific humidity | r | g/kg | 850hPa | 0.126 | 0.034 |
specific humidity | r | g/kg | 900hPa | 0.119 | 0.032 |
specific humidity | r | g/kg | 925hPa | 0.115 | 0.031 |
specific humidity | r | g/kg | 950hPa | 0.112 | 0.030 |
specific humidity | r | g/kg | 1000hPa | 0.099 | 0.027 |
Questions & Answers on field uncertainty estimates
For information and "questions and answers" (Q&A) on the uncertainty estimates for the ERA5 host reanalysis used on the lateral boundaries of this Arctic Regional Reanalysis, see this link:
ERA5: uncertainty estimation
The field uncertainty estimates provided here apply a different approach. The below Q&A is similar to the Q&A for the global reanalysis, adapted to apply for the uncertainty estimates provided here (for the Arctic reanalysis).
...
Since the regional reanalysis is run nested into the ERA5 global reanalysis, it is affected by the known issues of ERA5. In addition to those issues, we have found that ERA5 uses incorrect glacier masks for most of the glaciers in the regional Arctic reanalysis domain, and the glaciers in ERA5 always have an analysis albedo of 0.85. This is wrong, since for instance exposed glacier ice albedos during summer are unaccounted for. These areas affect the general circulation and thermodynamic state in ERA5 and can affect the quality of the Arctic regional reanalysis.
Additionally, the Arctic reanalysis has the following known issues:
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