Model intercomparison of COSMO 5.0 and IFS 45r1 at kilometer-scale grid spacing

The increase in computing power and recent model developments allow for the use of global kilometer-scale weather and climate models for routine forecasts. At these scales, deep convective processes can be partially resolved explicitly by the model dynamics. Next to horizontal resolution, other aspects such as the applied numerical methods, the use of the hydrostatic approximation, and time step size are factors that might influence a model's ability to resolve deep convective processes. In order to improve our understanding of the role of these factors, a model intercomparison between the nonhydrostatic COSMO model and the hydrostatic Integrated Forecast System (IFS) from ECMWF has been conducted. Both models have been run with different spatial and temporal resolutions in order to simulate 2 summer days over Europe with strong convection. The results are analyzed with a focus on vertical wind speed and precipitation. Results show that even at around 3 km horizontal grid spacing the effect of the hydrostatic approximation seems to be negligible. However, time step proves to be an important factor for deep convective processes, with a reduced time step generally allowing for higher updraft velocities and thus more energy in vertical velocity spectra, in particular for shorter wavelengths. A shorter time step is also causing an earlier onset and peak of the diurnal cycle. Furthermore, the amount of horizontal diffusion plays a crucial role for deep convection with more diffusion generally leading to larger convective cells and higher precipitation intensities. The study also shows that for both models the parameterization of deep convection leads to lower updraft and precipitation intensities and biases in the diurnal cycle with a precipitation peak which is too early.

Mixed-Convective Processes Within Seafloor Sediments Arising From Fresh Groundwater Discharge

The dependence of near-shore ecosystems on the freshwater component of submarine groundwater discharge (SFGD) is well recognized. Previous studies of SFGD have typically assumed that SFGD occurs through aquitards that are in direct contact with seawater. These studies provide no guidance on the distribution of freshwater discharge to the seafloor where SFGD occurs through sandy sediments, even though in most situations, seabed sediments are permeable. We find that SFGD may occur in unconfined, seafloor sediments as density-driven flow in the form of fingers, or otherwise, diffusive freshwater discharge is also possible. Unstable, buoyancy-driven flow within seabed sediments follows similar patterns (except inverted) to the downward free convection of unstable (dense over less-dense groundwater) situations. Consequently, the same theoretical controlling factors as those developed for downward mixed-convective flow are expected to apply. Although, there are important differences, in particular the boundary conditions, between subsea freshwater-seawater interactions and previous mixed-convective problems. Simplified numerical experiments in SEAWAT indicate that the behavior of fresh buoyant plumes depends on the aquifer lower boundary, which in turn controls the rate and pattern of SFGD to the seafloor. This article provides an important initial step in the understanding of SFGD behavior in regions of sandy seafloor sediments and analyses for the first time the mixed-convective processes that occur when freshwater rises into an otherwise saline groundwater body.

Model intercomparison of COSMO 5.0 and IFS 45r1 at kilometer-scale grid spacing

The increase in computing power and recent model developments allow the use of global kilometer-scale weather and climate models for routine forecasts. At these scales, deep convective processes can be partially resolved explicitly by the model dynamics. Next to horizontal resolution, other aspects such as the applied numerical methods, the use of the hydrostatic approximation, and timestep size are factors that might influence a model's ability of resolving deep convective processes. In order to improve our understanding of the role of these factors, a model intercomparison between the nonhydrostatic COSMO model and the hydrostatic Integrated Forecast System (IFS) from ECMWF has been conducted. Both models have been run with different spatial and temporal resolutions in order to simulate two summer days over Europe with strong convection. The results are analyzed with focus on vertical wind speed and precipitation. Results show that even at around 3 km horizontal grid spacing the effect of the hydrostatic approximation seems to be negligible. However, timestep proves to be an important factor for deep convective processes, with a reduced timestep generally allowing for higher updraft velocities and thus more energy in vertical velocity spectra, in particular for smaller wavelengths. A shorter timestep is also causing an earlier onset and peak of the diurnal cycle. Furthermore, the amount of horizontal diffusion plays a crucial role for deep convection with more diffusion generally leading to larger convective cells and higher precipitation intensities. The study also shows that for both models the parameterization of deep convection leads to lower updraft and precipitation intensities and biases in the diurnal cycle with a precipitation peak which is too early.

WRF model moisture adjustment method; a case study with winter-time cloudy biases in Xinjiang, China.

For most locations on Earth the ability of a Numerical Weather Prediction (NWP) model to accurately simulate surface irradiance relies heavily on the NWP model being able to resolve cloud coverage and thickness. At horizontal resolutions at or below a few kilometres NWP models begin to explicitly resolve convection and the clouds that arise from convective processes. However, even at high resolutions, biases may remain in the model and result in under- or over-prediction of surface irradiance. In this study we explore the correction of such systematic biases using a moisture adjustment method in tandem with the Weather Research and Forecasting model (WRF) for a location in Xinjiang, China. After extensive optimisation of the configuration of the WRF model we show that systematic biases still exist—in particular for wintertime in Xinjiang. We then demonstrate the moisture adjustment method with cloudy days for January 2019. Adjusting the relative humidity by 12% through the vertical led to a Root Mean Square Error (RMSE) improvement of 57.8% and a 90.5% reduction in bias for surface irradiance.

Assimilation of DAWN Doppler Wind Lidar Data During the 2017 Convective Processes Experiment (CPEX): Impact on the Precipitation and Flow Structure

An improved representation of the 3-D air motion and precipitation structure through forecast models and assimilation of observations is vital for improvements in weather forecasting capabilities. However, there is little independent data to properly validate a model forecast of precipitation structure when the underlying dynamics are evolving on short convective times scales. Using data from the JPL Ku/Ka-band Airborne Precipitation Radar (APR-2) and the 2-um Doppler Aerosol Wind (DAWN) lidar collected during the 2017 Convective Processes Experiment (CPEX), the NASA Unified Weather Research and Forecasting (WRF) Ensemble Data Assimilation System (EDAS) modeling system was used to quantify the impact of the high resolution, sparsely-sampled DAWN measurements on the analyzed variables and on the forecast when the DAWN winds were assimilated. Overall, the assimilation of the DAWN wind profiles had a discernible impact to the wind field and the evolution and timing of the 3-D precipitation structure. Analysis of individual variables revealed that the assimilation of the DAWN winds resulted in important and coherent modifications of the environment. It led to increase of the near surface convergence, temperature and water vapor, creating more favorable conditions for the development of convection exactly where it was observed (but not present in the control run). Comparison to APR-2 and observations by the Global Precipitation Measurement (GPM) satellite shows a much-improved forecast after the assimilation of the DAWN winds – development of precipitation where there was none, more organized precipitation where there was some, and a much more intense and organized cold pool, similar to the analysis of the dropsonde data. Onset of the vertical evolution of the precipitation showed similar radar-derived cloud top heights, but delayed in time. While this investigation was limited to a single CPEX flight date, the investigation design is appropriate for further investigation of the impact of airborne Doppler wind lidar observations upon short-term convective precipitation forecasts.