Quantifying the Direct Radiative Effect of Absorbing Aerosols for Numerical Weather Prediction: A Case Study

We conceptualize aerosol radiative transfer processes arising from the hypothetical coupling of a global aerosol transport model and a global numerical weather prediction model by applying the US Naval Research Laboratory Navy Aerosol Analysis and Prediction System (NAAPS) and the Navy Global Environmental Model (NAVGEM) meteorological and surface reflectance fields. A unique experimental design during the 2013 NASA Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) field mission allowed for collocated airborne sampling by the high spectral resolution Lidar (HSRL), the Airborne Multi-angle SpectroPolarimetric Imager (AirMSPI), up/down shortwave (SW) and infrared (IR) broadband radiometers, as well as NASA A-Train support from the Moderate Resolution Imaging Spectroradiometer (MODIS), to attempt direct aerosol forcing closure. The results demonstrate the sensitivity of modeled fields to aerosol radiative fluxes and heating rates, specifically in the SW, as induced in this event from transported smoke and regional urban aerosols. Limitations are identified with respect to aerosol attribution, vertical distribution, and the choice of optical and surface polarimetric properties, which are discussed within the context of their influence on numerical weather prediction output that is particularly important as the community propels forward towards inline aerosol modeling within global forecast systems

Conceptualizing the impact of dust-contaminated infrared radiances on data assimilation for numerical weather prediction

Numerical weather prediction systems depend on Hyperspectral Infrared Sounder (HIS) data, yet the impacts of dust-contaminated HIS radiances on weather forecasts has not been quantified. To determine the impact of dust aerosol on HIS radiance assimilation, we use a modified radiance assimilation system employing a one-dimensional variational assimilation system (1DVAR) developed under the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Numerical Weather Prediction–Satellite Application Facility (NWP-SAF) project, which uses the Radiative Transfer for TOVS (RTTOV). Dust aerosol impacts on analyzed temperature and moisture fields are quantified using synthetic HIS observations from rawinsonde, Micropulse Lidar Network (MPLNET), and Aerosol Robotic Network (AERONET). Specifically, a unit dust aerosol optical depth (AOD) contamination at 550 nm can introduce larger than 2.4 and 8.6 K peak biases in analyzed temperature and dewpoint, respectively, over our test domain. We hypothesize that aerosol observations, or even possibly forecasts from aerosol predication models, may be used operationally to mitigate dust induced temperature and moisture analysis biases through forward radiative transfer modeling.This study is supported by the NASA ROSES Science of Terra and Aqua program (T. Lee; 80HQTR18T0085). The MPLNET project is funded by the NASA Radiation Sciences Program and Earth Observing System. MPLNET observations at the Santa Cruz de Tenerife site are supported by the INTA Grant IGE03004

Unusually Deep Wintertime Cirrus Clouds Observed over the Alaskan Sub-Arctic

Unusually deep wintertime cirrus clouds at altitudes exceeding 13.0 km above mean sea level (AMSL) were observed at Fairbanks, Alaska (64.86 N, 147.85 W, 0.300 km AMSL) over a twelve hour period, beginning near 1200 UTC 1 January 2017. Such elevated cirrus cloud heights are far more typical of warmer latitudes, and in many instances associated with convective outflow, as opposed to early winter over the sub-Arctic on a day featuring barely four hours of local sunlight. In any other context, they could have been confused for polar stratospheric clouds, which are a more common regional/seasonal occurrence at elevated heights. The mechanics of this unique event are documented, including the thermodynamic and synoptic environments that nurtured and sustained cloud formation. The impact of an unusually deep and broad anticyclone over the wintertime Alaskan sub-Arctic is described. Comparisons with climatological datasets illustrate how unusual these events are regionally and seasonally. The event proves a relatively uncharacteristic confluence of circulatory and dynamic features over the wintertime Alaskan sub-Arctic. Our goal is to document the occurrence of this event within the context of a growing understanding for how cirrus cloud incidence and their physical characteristics vary globally. Cirrus clouds are unique within the earth-atmosphere system. Formed by the freezing of submicron haze particles in the upper troposphere, they are the last primary cloud mechanism contributing to the large scale exchange of the terrestrial water cycle. Accordingly, cirrus clouds are observed globally at all times of the year, exhibiting an instantaneous global occurrence rate near 40%. Radiatively, however, they are even more distinct. During daylight hours, cirrus are the only cloud genus that can induce either positive or negative top-of-the-atmosphere forcing (i.e., heating or cooling; all other clouds induce a negative sunlit cooling effect). Though diffuse compared with low-level liquid water clouds, their significance radiatively and thus within climate, is borne out of their overwhelming relative occurrence rate. This emerging recognition makes understanding cirrus cloud occurrence and physical cloud properties an innovative and exciting element of current climate study. The observations described here contribute to this knowledge, and the apparent potential for anomalous wintertime radiative characteristics exhibited along sub-Arctic latitudes

Implementation of a Global Dust Physical Sea Surface Temperature Retrieval For Numerical Weather Prediction Applications

This works presents the results for the first study to ever attempt to analyze the full potential and limitations of incorporating aerosols within a truly physical SST retrieval for operational weather forecasting purposes. This is accomplished through the application of a satellite sea surface temperature (SST) physical retrieval for satellite split-window and hyperspectral infrared (IR) sensors that allows a better representation of the atmospheric state under aerosol-laden conditions. The new algorithm includes 1) accurate specification of the surface emissivity that characterizes the surface leaving radiance and 2) transmittance and physical characterization of the atmosphere by using the Community Radiative transfer model (CRTM). This project includes application of the NEMS-Global Forecasting System Aerosol Component (NGAC) fields, which corresponds to the first global interactive atmosphere-aerosol forecast system ever implemented at NOAA’s National Center for Environmental Prediction (NCEP). A number of limiting factors were identified by analysing brightness temperatures and SST outputs biases as a function of latitude, zenith angle, wind and moisture for cases in January and November 2013. SST ouputs are validated against a bulk SST (Reynolds SST) and a parameterized SST derived from operational products and partly against observed measurements from the eastern Atlantic Ocean, which is dominated by Saharan dust throughout most of the year and that is also a genesis region for Atlantic tropical cyclones. These observations are obtained from the NOAA Aerosols and Ocean Science Expeditions (AEROSE). The improved physical SST methodology has the potential to allow for improved representation of the geophysical state under dust-laden conditions