Improvement in the Accuracy of Back Trajectories Using WRF to Identify Pollen Sources in Southern Iberian Peninsula

Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1 ° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness

Response of London's urban heat island to a marine air intrusion in an easterly wind regime

Numerical simulations are conducted using the Weather Research and Forecast numerical model to examine the effects of a marine air intrusion (including a sea-breeze front), in an easterly wind regime on 7 May 2008, on the structure of London's urban heat island (UHI). A sensitivity study is undertaken to assess how the representation of the urban area of London in the model, with a horizontal grid resolution of 1 km, affects its performance characteristics for the near-surface air temperature, dewpoint depression, and wind fields. No single simulation is found to provide the overall best or worst performance for all the near-surface fields considered. Using a multilayer (rather than single layer or bulk) urban canopy model does not clearly improve the prediction of the intensity of the UHI but it does improve the prediction of its spatial pattern. Providing surface-cover fractions leads to improved predictions of the UHI intensity. The advection of cooler air from the North Sea reduces the intensity of the UHI in the windward suburbs and displaces it several kilometres to the west, in good agreement with observations. Frontal advection across London effectively replaces the air in the urban area. Results indicate that there is a delicate balance between the effects of thermal advection and urbanization on near-surface fields, which depend, inter alia, on the parametrization of the urban canopy and the urban land-cover distribution.Peer reviewedFinal Accepted Versio

The ongoing need for high-resolution regional climate models: Process understanding and stakeholder information The ongoing need for high-resolution regional climate models: Process understanding and stakeholder information

Regional climate modeling addresses our need to understand and simulate climatic processes and phenomena unresolved in global models. This paper highlights examples of current approaches to and innovative uses of regional climate modeling that deepen understanding of the climate system. High-resolution models are generally more skillful in simulating extremes, such as heavy precipitation, strong winds, and severe storms. In addition, research has shown that finescale features such as mountains, coastlines, lakes, irrigation, land use, and urban heat islands can substantially influence a region's climate and its response to changing forcings. Regional climate simulations explicitly simulating convection are now being performed, providing an opportunity to illuminate new physical behavior that previously was represented by parameterizations with large uncertainties. Regional and global models are both advancing toward higher resolution, as computational capacity increases. However, the resolution and ensemble size necessary to produce a sufficient statistical sample of these processes in global models has proven too costly for contemporary supercomputing systems. Regional climate models are thus indispensable tools that complement global models for understanding physical processes governing regional climate variability and change. The deeper understanding of regional climate processes also benefits stakeholders and policymakers who need physically robust, high-resolution climate information to guide societal responses to changing climate. Key scientific questions that will continue to require regional climate models, and opportunities are emerging for addressing those questions