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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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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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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.

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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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Details about the data fields

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The wind direction D clockwise from North can be calculated as

$$ D = tan_atan {2}^{-1} \frac ({u/U},{v/V}) + 180^{\circ} + \alpha,  (4) $$ 

where 𝛼 where 𝛼 is the local rotation of the model grid relative to North, and tan₂^-1 atan2 is the very specific 2-argument arcus tangens function atan2, which is included in most programming languages. With atan2 both the sign in the numerator and the denominator are independently important for the resulting angle. Take 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/From/Examples/#wind-direction-obtained-from-x-y-wind-to-wind-direction.

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.

Variables at the top of the atmosphere

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 - SW_net/SW↓, where SW↓ is the downward solar flux at the surface, and SW_net 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

At the top of the atmosphere (TOA) the accumulated solar net TOA radiation and the accumulated thermal net TOA radiation are output variables in At the top of the atmosphere (TOA) the accumulated solar net TOA radiation and the accumulated thermal net TOA radiation are output variables in units of J/m². These are both considered on a horizontal surface and are both positive in the downward direction. Since the downward solar TOA radiation is always larger than the upward solar TOA radiation, the solar net TOA radiation is always positive. Since there is virtually no downward thermal TOA radiation, the thermal net TOA radiation is always negative. The TOA is the highest model half-level. Thus, the variables at this level are explicitly calculated.

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The snow variables are given as instantaneous values from the most recent model time step relative to the output time. The snow density output unit is kg/m³, the snow water equivalent (SWE) output is in units of kg/m², and the snow fraction output has fractional units in the range 0-1. The snow depth can be derived from these variables.

Sea and sea

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ice variables

For the sea the sea surface temperature is is output in units of K. For areas partially or completely covered with sea - ice, the following variables are output:   Sea - ice area fraction [-], upper layer sea ice temperature [K], sea - ice thickness [m], and sea - ice snow thickness  [m]. Here the sea-. For sea ice thickness please note that the routine that computes this variable does not reproduce the evolution of ice thickness with all its complexity. Rather this variable should be treated as a rough estimate in order to get reasonable estimations for the energy fluxes. The sea ice fraction and sea surface temperatures are in fact interpolated input data and are only updated once every day. During the course of a forecast they are kept constant. All other sea and sea - ice variables are given as instantaneous values from the most recent model time step relative to the output time.

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The model level variables are computed at the full model levels, and are given as instantaneous values from the most recent model time step relative to the output time. There are 65 vertical model levels in HARMONIE-AROME.  These full model levels are hybrid-sigma coordinates that are counted from the model top toward the surface. They go from being pure pressure levels, i.e. levels with constant pressure starting at 10 hPa, 30 hPa, etc. to being relative to the surface topography in height. Level 64 is at approximately 30 m height and level 65 is at approximately 12 m height above the surface. For a more detailed description of the vertical model layers, see Annex 8.3. The following thermodynamic variables are the output variables at model levels: Temperature [K], u-component of wind [m/s], v-component of wind [m/s], turbulent kinetic energy [J/kg]. Here turbulent kinetic energy is the mean kinetic energy per unit mass from eddies in turbulent flow. Note that the HARMONIE-AROME weather forecasting model with 2.5 x 2.5 km² resolution does not explicitly resolve this turbulent energy. The u- and v- wind components follow the direction of the Lambertian model grid with the u-component being directed 90 degrees clockwise relative to the v-component. From these model level wind components, the model level wind speed and wind direction relative north can be calculated with Equations 3 and 4. The grid rotation angle 𝛼 can be computed with this script: https://github.com/metno/NWPdocs/wiki/From-x-y-wind-to-wind-direction.

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Static fields are output variables that do not change depending on the model initial time or the forecast length (in other words they are time-independent). These include the land-sea mask, that is the fraction of land in a given model grid box of 2.5 x 2.5 km² in units of %, and the orography in units of m. There are two more orography-related static parameters: subgrid orography average slope and subgrid orography standard deviation. For each model grid box in HARMONIE-AROME 4 tile fractions are defined in units of fraction. These are: The fraction of sea, the fraction of inland water (lakes and rivers), the fraction of urban areas, and the fraction of nature, i.e. land areas that are not inland water or urban. The fraction of glaciers is also output. This is assumed to be a constant field with glacier extents representative of the middle of the full reanalysis period (19971991-2021). Glacier extent in remote Arctic locations is not available as accurately mapped yearly datasets. The official maps are outdated due to major calving events in the recent decades. HARMONIE-AROME has not yet been designed to deal with changing land-sea masks or other surface classifications. Thus, these are static fields.

What are the uncertainties of the data fields?

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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.

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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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Uncertainties for the CARRA-West model domain

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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.

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.

Questions & Answers on field uncertainty estimates

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The Arctic reanalysis system applies the so-called 3D variational data assimilation (3D-VAR) reanalysis method. The 3D-VAR method is depicted schematically in Figure 19. At fixed points in time the model state is adjusted based on the observed state, taking into account the statistics of model and observation errors. The Arctic reanalysis system is run with eight cycles per day performing analyses at 00 UTC, 03 UTC, 06 UTC, 09 UTC, 12 UTC, 15 UTC, 18 UTC and 21 UTC. The forecast lengths vary between 3 and 30 hours.

 Definition of the 65 vertical layer structure in HARMONIE 

The CARRA vertical coordinate system is a terrain-following hybrid vertical coordinate, which means that it is terrain following at the bottom and pressure based on the top of the atmosphere. It has the advantage to describe the surface terrain properly, but also benefitting the advantage of having the pressure coordinate at the top of the atmosphere.

CARRA uses 65 model levels (level 65 is the surface and level 1 is the top of the atmosphere), which is further splitted into the so called half levels. CARRA has 66 half levels and the pressure of each half level can be obtained by the following formula:

P (k+1/2) = A (k+1/2) + B (k+1/2) * Ps

where k=0.... 65, Ps is surface pressure and the A and B coefficients (see below) valid at each half level. 

The full model level pressure [1, 2, ...65] is defined as the mean of the pressure of each pair of neighbouring half levels [0,5, 1.5, ...65.5]. The model variables are defined in the full model levels. 

The A and B coefficients are listed below (from the top to the bottom).

'AHALF'=>'0.00000000, 2000.00000000, 4000.21287319, 6002.09662113, 7911.25838577, 9633.01049417,11169.37146237, 12522.57753978, 13695.00149653, 14689.11546998, 15507.49052823, 16154.69697732, 16632.12471208, 16940.14949960,  17082.34869816, 17065.28164099, 16898.18367797, 16592.58939571,  16161.90395878,  15620.94340550,  14985.46502362, 14271.70773051, 13495.95994372, 12674.16909910, 11821.60314859, 10952.57042620, 10080.20053763, 9216.28565403, 8371.17893039, 7553.74479607, 6771.35457397, 6029.92021691, 5333.95880836, 4686.68074804, 4090.09511346, 3545.12645110, 3051.73811264, 2609.05813936, 2215.50455766, 1868.90774223, 1566.62821060, 1305.66882073, 1081.85503306, 890.47596795, 727.74548529, 590.17748096, 474.58767980, 378.08857614, 298.07947335, 232.23312781, 178.48015386, 134.99207440, 100.16369201, 72.59529482, 51.07508967, 34.56216490, 22.17022046, 13.15225964, 6.88641310, 2.86306141, 0.67344356, 0.00000000, 0.00000000, 0.00000000, 0.00000000, 0.00000000

'BHALF'=>'0.00000000,  0.00000000,  0.00000000, 0.00000000, 0.00095468, 0.00382570, 0.00862327, 0.01535782, 0.02404046, 0.03468314, 0.04729839, 0.06195102, 0.07868187, 0.09744325, 0.11815586, 0.14071098, 0.16497348, 0.19078554,   0.21797086, 0.24633925, 0.27569119, 0.30582244, 0.33652825, 0.36760726, 0.39886479, 0.43011564, 0.46118624, 0.49191624, 0.52215946, 0.55178443, 0.58067442, 0.60872709, 0.63585388, 0.66197911, 0.68703898, 0.71098036, 0.73375964, 0.5534143, 0.77569737, 0.79480486, 0.81264598, 0.82920633, 0.84454000, 0.85875505, 0.87191802, 0.88409276, 0.89534045,  0.90571965, 0.91528643, 0.92409452, 0.93219549, 0.93963895, 0.94647277, 0.95274328, 0.95849551, 0.96377340, 0.96862008, 0.97307803, 0.97718944, 0.98099640, 0.98454132, 0.98786727, 0.99102462, 0.99406510, 0.99703923, 1.00000000

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