Adjoint sensitivity of global cloud droplet number to aerosol and dynamical parameters
We present the development of the adjoint of a comprehensive cloud\ndroplet formation parameterization for use in aerosol-cloud-climate\ninteraction studies. The adjoint efficiently and accurately calculates\nthe sensitivity of cloud droplet number concentration (CDNC) to all\nparameterization inputs (e. g., updraft velocity, water uptake\ncoefficient, aerosol number and hygroscopicity) with a single execution.\nThe adjoint is then integrated within three dimensional (3-D) aerosol\nmodeling frameworks to quantify the sensitivity of CDNC formation\nglobally to each parameter. Sensitivities are computed for year-long\nexecutions of the NASA Global Modeling Initiative (GMI) Chemical\nTransport Model (CTM), using wind fields computed with the Goddard\nInstitute for Space Studies (GISS) Global Circulation Model (GCM) II',\nand the GEOS-Chem CTM, driven by meteorological input from the Goddard\nEarth Observing System (GEOS) of the NASA Global Modeling and\nAssimilation Office (GMAO). We find that over polluted (pristine) areas,\nCDNC is more sensitive to updraft velocity and uptake coefficient\n(aerosol number and hygroscopicity). Over the oceans of the Northern\nHemisphere, addition of anthropogenic or biomass burning aerosol is\npredicted to increase CDNC in contrast to coarse-mode sea salt which\ntends to decrease CDNC. Over the Southern Oceans, CDNC is most sensitive\nto sea salt, which is the main aerosol component of the region.\nGlobally, CDNC is predicted to be less sensitive to changes in the\nhygroscopicity of the aerosols than in their concentration with the\nexception of dust where CDNC is very sensitive to particle\nhydrophilicity over arid areas. Regionally, the sensitivities differ\nconsiderably between the two frameworks and quantitatively reveal why\nthe models differ considerably in their indirect forcing estimates.