Sept 23-28 GSD scientist Georg Grell will present at the 18th AeroCom meeting in Barcelona, Spain. AeroCom is an open international initiative of scientists interested in the advancement of the understanding of global aerosol properties and aerosol impacts on climate, weather, and air quality. A central goal is to more strongly tie and constrain modeling efforts to observational data from satellite, ground-based, and aircraft observations. A major element for exchanges between data and modeling groups are annual meetings of AeroCom together with the satellite data oriented initiative AeroSAT. In addition to the comparisons among models and between models and data, AeroCom initiates and coordinates model experiments to target particular research topics, leading to joint research papers of synthesizing character.
Grid operators responsible for making decisions on what kind of power generation to use to keep the grid in balance (conventional versus weather dependent, such as wind or solar) need a reliable numerical weather prediction (NWP) model to ensure grid stability. A statistically significant improvement of the ramp event forecast skill is found through the assimilation of the special WFIP data in two different study areas, and variations in model skill between up‐ramp versus down‐ramp events are found.
The spatiotemporal variability of the atmospheric boundary layer regulates the atmosphere's ability to generate and sustain severe thunderstorms. Boundary layer evolution poses significant challenges for numerical weather prediction because both its vertical and horizontal inconsistencies are not handled by most operational models. Using a ground-based vertically pointing radar can reveal additional details about the evolution and character of the boundary layer. Researchers developed an algorithm for observations collected during the Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX) by a vertically-pointing radar. The algorithm automatically separated observations of precipitation and non-precipitation, and allows for further identification of important boundary layer features of interest to the VORTEX-SE community.
This study used 20 years of Oklahoma Mesonet data to investigate the changes of near surface water vapor mixing ratio (qv) during the afternoon to evening transition (AET). Similar to past studies, increases in qv are found to occur near sunset. Next to known changes in low-level wind shear, these changes in instability and moisture demonstrate new ways the AET can modify the presence of the key ingredients relevant to explaining the climatological increase in severe convective storm hazards around sunset.
Evaluation of numerical weather prediction (NWP) is critical for both forecasters and researchers. Through such evaluation, forecasters can understand the strengths and weaknesses of NWP guidance, and researchers can work to improve NWP models. However, evaluating high-resolution convection-allowing models (CAMs) requires unique verification metrics tailored to high-resolution output, particularly when considering extreme events. Metrics used and fields evaluated often differ between verification studies, hindering the effort to broadly compare CAMs. The purpose of this article is to summarize the development and initial testing of a CAM-based scorecard, which is intended for broad use across research and operational communities and is similar to scorecards currently available within the enhanced Model Evaluation Tools package (METplus) for evaluating coarser models.
AMS Weather and Forecasting journal
Due to lack of high spatial and temporal resolution boundary layer (BL) observations, the rapid changes in near storm environment are not well represented in current convective-scale numerical models. Better representation of the near storm environment in model initial conditions will likely further improve the forecasts of severe convective weather. This study investigates the impact of assimilating high temporal resolution BL retrievals from two ground-based remote sensing instruments for short-term forecasts of a tornadic supercell event on 13 July 2015 during the Plains Elevated Convection at Night field campaign. Results indicate a positive impact of Atmospheric Emitted Radiance Interferometer (AERI) and Doppler Lidar observations in forecasting Convective Initiation (CI) and early evolution of the supercell storm. The experiment that employed the AI technique to assimilate BL observations in DA enhances the humidity in near storm environment and low-level convergence, which in turn helps forecasting CI. The forecast improvement is most pronounced during the first ~3-h. Results also indicate that the AERI observations have a larger impact compared to DL in predicting CI.
Observations of near-surface vertical wind profiles and vertical momentum fluxes obtained from a Doppler lidar and instrumented towers deployed during VORTEX-SE in the spring of 2017 are analyzed. In particular, departures from the predictions of Monin–Obukhov similarity theory (MOST) are documented on thunderstorm days, both in the warm air masses ahead of storms and within the cool outflow of storms, where MOST assumptions (e.g., horizontal homogeneity and a steady state) are least credible. In these regions, it is found that the non-dimensional vertical wind shear near the surface commonly exceeds predictions by MOST. The departures from MOST have implications for the specification of the lower boundary condition in numerical simulations of convective storms. Documenting departures from MOST is a necessary first-step toward improving the lower boundary condition and parameterization of near-surface turbulence (“wall models”) in storm simulations.
Researchers leveraged a multi-scale dataset of observations from the second Wind Forecast Improvement Project field campaign in the northwest U.S. to diagnose and quantify systematic forecast errors in the operational High-Resolution Rapid Refresh (HRRR) model during weather events of particular concern to wind energy forecasting. Examples of such events are cold pools, gap flows, thermal troughs/marine pushes, mountain waves, and topographic wakes. This study describes the model development and testing undertaken during WFIP2, and demonstrates forecast improvements. Specifically, WFIP2 found that mean absolute errors in rotor-layer wind speed forecasts could be reduced by 5-20% in winter by improving the turbulent mixing lengths, horizontal diffusion, and gravity wave drag. The model improvements made in WFIP2 are also shown to be applicable to regions outside of complex terrain. Ongoing and future challenges in model development will also be discussed.
September 11-13: GSD Model Development Branch Chief Georg Grell is a Lead Chair for the biennial Meteorology and Climate – Modeling for Air Quality Conference (MAC-MAQ) hosted by the University of California, Davis. The biennial three day conference brings together research scientists, experts, and professionals from around the world to discuss a wide range of topics related to meteorology for air quality applications. The primary focus is on understanding and improving meteorological modeling, understanding what is “under the hood” in the models, how experimental data can be used to improve them, and the importance of meteorology in air quality modeling applications.
September 19-20: Researchers from GSD, CIRES, and CIRA will present research progress at the annual Developmental Testbed Center (DTC) Science Advisory Board Meeting. The DTC is a distributed facility where the Numerical Weather Prediction (NWP) community can test and evaluate new models and techniques for use in research and operations. The DTC is a NOAA/NCAR collaboration, and the board is made of members of the U.S. NWP community including GSD's Curtis Alexander.