On the utility of individual tendency output: Revealing interactions between parameterized processes during a marine cold air outbreak

Forecasts of marine cold air outbreaks critically rely on the interplay of multiple parameterization schemes to represent subgrid-scale processes, including shallow convection, turbulence, and microphysics. Even though such an interplay has been recognized to contribute to forecast uncertainty, a quantification of this interplay is still missing. Here, we investigate the tendencies of temperature and specific humidity contributed by individual parameterization schemes in the operational weather prediction model AROME-Arctic. From a case study of an extensive marine cold air outbreak over the Nordic seas, we find that the type of planetary boundary layer assigned by the model algorithm modulates the contribution of individual schemes and affects the interactions between different schemes. In addition, we demonstrate the sensitivity of these interactions to an increase or decrease in the strength of the parameterized shallow convection. The individual tendencies from several parameterizations can thereby compensate each other, sometimes resulting in a small residual. In some instances this residual remains nearly unchanged between the sensitivity experiments, even though some individual tendencies differ by up to an order of magnitude. Using the individual tendency output, we can characterize the subgrid-scale as well as grid-scale responses of the model and trace them back to their underlying causes. We thereby highlight the utility of individual tendency output for understanding process-related differences between model runs with varying physical configurations and for the continued development of numerical weather prediction models.publishedVersio

A well-observed polar low analysed with a regional and a global weather-prediction model

The capability of a regional (AROME‐Arctic) and a global (ECMWF HRES) weather‐prediction model are compared for simulating a well‐observed polar low (PL). This PL developed on 3–4 March 2008 and was measured by dropsondes released from three flights during the IPY‐THORPEX campaign. Validation against these measurements reveals that both models simulate the PL reasonably well. AROME‐Arctic appears to represent the cloud structures and the high local variability more realistically. The high local variability causes standard error statistics to be similar for AROME‐Arctic and ECMWF HRES. A spatial verification technique reveals that AROME‐Arctic has improved skills at small scales for extreme values. However, the error growth of the forecast, especially in the location of the PL, is faster in AROME‐Arctic than in ECMWF HRES. This is likely associated with larger convection‐induced perturbations in the former than the latter model. Additionally, the PL development is analysed. This PL has two stages, an initial baroclinic and a convective mature stage. Sensible heat flux and condensational heat release both contribute to strengthen the initial baroclinic environment. In the mature stage, latent heat release appears to maintain the system. At least two conditions must be met for this stage to develop: (a) the sensible heat flux sufficiently destabilises the local environment around the PL, and (b) sufficient moisture is available for condensational heat release. More than half of the condensed moisture within the system originates from the surroundings. The propagation of the PL is “pulled” towards the area of strongest condensational heating. Finally, the sensitivity of the PL to the sea‐surface temperature is analysed. The maximum near‐surface wind speed connected to the system increases by 1–2 m·s−1 per K of surface warming and a second centre develops in cases of highly increased temperature

On the utility of individual tendency output: Revealing interactions between parameterized processes during a marine cold air outbreak

Forecasts of marine cold air outbreaks critically rely on the interplay of multiple parameterization schemes to represent subgrid-scale processes, including shallow convection, turbulence, and microphysics. Even though such an interplay has been recognized to contribute to forecast uncertainty, a quantification of this interplay is still missing. Here, we investigate the tendencies of temperature and specific humidity contributed by individual parameterization schemes in the operational weather prediction model AROME-Arctic. From a case study of an extensive marine cold air outbreak over the Nordic seas, we find that the type of planetary boundary layer assigned by the model algorithm modulates the contribution of individual schemes and affects the interactions between different schemes. In addition, we demonstrate the sensitivity of these interactions to an increase or decrease in the strength of the parameterized shallow convection. The individual tendencies from several parameterizations can thereby compensate each other, sometimes resulting in a small residual. In some instances this residual remains nearly unchanged between the sensitivity experiments, even though some individual tendencies differ by up to an order of magnitude. Using the individual tendency output, we can characterize the subgrid-scale as well as grid-scale responses of the model and trace them back to their underlying causes. We thereby highlight the utility of individual tendency output for understanding process-related differences between model runs with varying physical configurations and for the continued development of numerical weather prediction models

Evaluation of a sub-kilometre NWP system in an Arctic fjord-valley system in winter

Terrain challenges the prediction of near-surface atmospheric conditions, even in kilometre-scale numerical weather prediction (NWP) models. In this study, the ALADIN-HIRLAM NWP system with 0.5 km horizontal grid spacing and an increased number of vertical levels is compared to the 2.5-km model system similar to the currently operational NWP system at the Norwegian Meteorological Institute. The impact of the increased resolution on the forecasts’ ability to represent boundary-layer processes is investigated for the period from 12 to 16 February 2018 in an Arctic fjord-valley system in the Svalbard archipelago. Model simulations are compared to a wide range of observations conducted during a field campaign. The model configuration with sub-kilometre grid spacing improves both the spatial structure and overall verification scores for the near-surface temperature and wind forecasts compared to the 2.5-km experiment. The sub-kilometre experiment successfully captures the wind channelling through the valley and the temperature field associated with it. In a situation of a cold-air pool development, the sub-kilometre experiment has a particularly high near-surface temperature bias at low elevations. The use of measurement campaign data, however, reveals some encouraging results, e.g. the sub-kilometre system has a more realistic vertical profile of temperature and wind speed, and the surface temperature sensitivity to the net surface energy is closer to the observations. This work demonstrates the potential of sub-kilometre NWP systems for forecasting weather in complex Arctic terrain, and also suggests that the increase in resolution needs to be accompanied with further development of other parts of the model system