In this report we present an assessment of the use of atmospheric observations in the Arctic, and
their impact on the ECMWF analysis and short-range forecasts, for recent summer and winter
periods. This is based on a number of available diagnostics from the ECMWF operational data
assimilation system, such as analysis increments, observation departures, Forecast Sensitivity to
Observations (FSOI) and Ensemble of Data Assimilation (EDA) spread-skill relationship. This work
was carried out in the context of the APPLICATE Horizon-2020 project with the aim of guiding the
design and complementing the results of Arctic Observing System Experiments (OSEs).
This assessment has highlighted both the impact of Arctic atmospheric observations and the
challenges related to their use. The polar regions are a particularly data-rich area in terms of satellite
sounding observations from polar-orbiting satellites, whereas conventional observations are sparse
north of 70N. However, the assimilation of lower tropospheric sounding satellite channels from
polar orbiting satellites is more challenging in the Arctic region, especially during winter. This is
due to the fact that model errors are larger and that there are larger errors in the radiative transfer
model used to assimilate the satellite radiances over snow and sea-ice. For instance, mean
differences between surface-sensitive microwave observations (including AMSU-A channel 5 and
all MHS channels) and short-range forecasts are larger over snow and sea-ice. A proportion of this
can be linked to errors in the specification of the surface characteristics in the radiative transfer
model, even though model biases also contribute. Fewer observations are therefore assimilated from
these channels in winter periods, and when these data are assimilated the forward model has a higher
uncertainty. Uncertainties in the specification of surface contributions in the radiative transfer also
affect the infrared observations, leading to a more difficult detection of clouds.
In addition, our assessment shows that background errors used in the analysis over the Arctic are
likely to be under-estimated for the lower troposphere and the upper-troposphere lower-stratosphere
during the winter season. To improve the use of satellite data in the troposphere, improvements in
the forward model and/or cloud detection would be needed, whereas to improve the use of nearsurface
data, it would be necessary to increase the background errors to avoid limiting the
adjustments observations can make to the short-range forecasts in this area during the assimilation.
Overcoming the challenges relating to the use of Arctic observations in winter, which are not
insurmountable but require a sustained effort, would lead to better analyses and weather forecasts,
but also better atmospheric reanalyses.
An initial assessment of the impact of Arctic atmospheric observations on global short-range
forecasts has been performed using adjoint-based techniques (FSOI). This suggests that
conventional Arctic observations appear to contribute the most to reducing the global short-range
forecast error during winter, while microwave observations from polar orbiting satellites contribute
the most in summer. A separate report will summarise results from observing system experiments
that assess the impact of withdrawing selected observing systems from the polar regions.
In this report we present an assessment of the use of atmospheric observations in the Arctic, and
their impact on the ECMWF analysis and short-range forecasts, for recent summer and winter
periods. This is based on a number of available diagnostics from the ECMWF operational data
assimilation system, such as analysis increments, observation departures, Forecast Sensitivity to
Observations (FSOI) and Ensemble of Data Assimilation (EDA) spread-skill relationship. This work
was carried out in the context of the APPLICATE Horizon-2020 project with the aim of guiding the
design and complementing the results of Arctic Observing System Experiments (OSEs).
This assessment has highlighted both the impact of Arctic atmospheric observations and the
challenges related to their use. The polar regions are a particularly data-rich area in terms of satellite
sounding observations from polar-orbiting satellites, whereas conventional observations are sparse
north of 70N. However, the assimilation of lower tropospheric sounding satellite channels from
polar orbiting satellites is more challenging in the Arctic region, especially during winter. This is
due to the fact that model errors are larger and that there are larger errors in the radiative transfer
model used to assimilate the satellite radiances over snow and sea-ice. For instance, mean
differences between surface-sensitive microwave observations (including AMSU-A channel 5 and
all MHS channels) and short-range forecasts are larger over snow and sea-ice. A proportion of this
can be linked to errors in the specification of the surface characteristics in the radiative transfer
model, even though model biases also contribute. Fewer observations are therefore assimilated from
these channels in winter periods, and when these data are assimilated the forward model has a higher
uncertainty. Uncertainties in the specification of surface contributions in the radiative transfer also
affect the infrared observations, leading to a more difficult detection of clouds.
In addition, our assessment shows that background errors used in the analysis over the Arctic are
likely to be under-estimated for the lower troposphere and the upper-troposphere lower-stratosphere
during the winter season. To improve the use of satellite data in the troposphere, improvements in
the forward model and/or cloud detection would be needed, whereas to improve the use of nearsurface
data, it would be necessary to increase the background errors to avoid limiting the
adjustments observations can make to the short-range forecasts in this area during the assimilation.
Overcoming the challenges relating to the use of Arctic observations in winter, which are not
insurmountable but require a sustained effort, would lead to better analyses and weather forecasts,
but also better atmospheric reanalyses.
An initial assessment of the impact of Arctic atmospheric observations on global short-range
forecasts has been performed using adjoint-based techniques (FSOI). This suggests that
conventional Arctic observations appear to contribute the most to reducing the global short-range
forecast error during winter, while microwave observations from polar orbiting satellites contribute
the most in summer. A separate report will summarise results from observing system experiments
that assess the impact of withdrawing selected observing systems from the polar regions.