10th International Aerosol Conference September 2 - September 7, 2018 America's Center Convention Complex St. Louis, Missouri, USA
Abstract View
Forecasting Smoke Transport and Its Impact on Weather in High-Resolution (3km) HRRR-Smoke Model over the US
RAVAN AHMADOV, Eric James, Georg Grell, Curtis Alexander, Steven Albers, Ivan Csiszar, Marina Tsidulko, Rick Graw, Stuart McKeen, Shobha Kondragunta, Gabriel Pereira, Brad Pierce, Saulo Freitas, CU CIRES- NOAA ESRL
Abstract Number: 1574 Working Group: Aerosol Modeling
Abstract We present a new smoke modeling system, the High-Resolution Rapid Refresh with smoke (HRRR-Smoke) to simulate biomass burning (BB) emissions, plume rise and smoke transport in real time. The HRRR model (without smoke) is run operationally at the National Weather Service with 3km spacing for numerical weather prediction (NWP) over the contiguous US. One of the novelties of this model is the use of the double moment aerosol aware microphysics scheme. This scheme enables a computationally efficient coupling between smoke and model meteorology. HRRR-Smoke simulates fine particulate matter (PM2.5 or smoke) emitted by wildfires and prescribed burns. The model ingests fire radiative power data from various satellite sensors to calculate the BB emissions in real time. Here, we present simulations of HRRR-Smoke for the August-September 2017 time period that is associated with one of the worst fire seasons in the northwestern US.
In this study we evaluate the HRRR-Smoke predictions of 3D distributions of smoke concentrations by using hourly PM2.5 measurements from the ground-based network and VIIRS satellite AOD data for this case study. The emissions of smoke near the surface and aloft (plume rise) and its transport on a regional scale in the model are analyzed in detail. We also evaluate the ability of the high-resolution model to capture the transport of smoke over complex terrain in the northwestern US.
Additional sensitivity simulations are conducted by enabling the smoke impact on radiation and microphysics in HRRR-Smoke. These sensitivity simulations allow us to estimate the impact of smoke on air temperature across the region, for example. We present an extensive verification of the HRRR-Smoke forecasts for meteorology by comparing the modeled temperature, moisture, cloudiness and precipitation over the CONUS domain for the case study. A new visibility parameterization, which accounts for smoke extinction, is used here to improve the visibility forecasts when high levels of smoke are present. In addition to the improvement of air quality and visibility forecasting, this study also helps to demonstrate the importance of the inclusion of aerosol within NWP models.