Aerosol Complexity and Implications for Predictability and Short-Term Forecasting
There are clear NWP and climate impacts from including aerosol radiative and cloud interactions. Changes in dynamics and cloud fields affect aerosol lifecycle, plume height, long-range transport, overall forcing of the climate system, etc. Inclusion of aerosols in NWP systems has benefit to surface field biases (e.g., T2m, U10m). Including aerosol affects has impact on analysis increments and can have statistically significant impacts on, e.g., tropical cyclogenesis. Above points are made especially with respect to aerosol radiative interactions, but aerosol-cloud interaction is a bigger signal on the global system. Many of these impacts are realized even in models with relatively simple (bulk) aerosol schemes (approx.10 -20 tracers). Simple schemes though imply simple representation of aerosol absorption and importantly for aerosol-cloud interaction particle-size distribution. Even so, more complex schemes exhibit a lot of diversity between different models, with issues such as size selection both for emitted particles and for modes. Prospects for complex sectional schemes to tune modal (and even bulk) schemes toward better selection of size representation. I think this is a ripe topic for more research -Systematic documentation of benefits of no vs. climatological vs. interactive (direct and then direct+indirect) aerosols. Document aerosol impact on analysis increments, inclusion in NWP data assimilation operator -Further refinement of baseline assumptions in model design (e.g., absorption, particle size distribution). Did not get into model resolution and interplay of other physical processes with aerosols (e.g., moist physics, obviously important), chemistry