A 1-D model to retrieve the vertical profiles of minor atmospheric constituents for cloud microphysical modeling: I. Formulation and validation

Determining the number concentration of minor constituents in the atmosphere is very important as it determines the whole tropospheric chemistry process. These constituents may act as cloud condensation nuclei (CCN) and ice nuclei (IN), impacting heterogeneous nucleation inside the cloud. However, the estimations of the number concentration of CCN/IN in cloud microphysical parameters are associated with uncertainties. In the present work, a hybrid Monte Carlo Gear solver has been developed to retrieve profiles of CH₄, N₂O, and SO₂. The idealized experiments have been carried out using this solver for retrieving vertical profiles of these constituents over four megacities, viz., Delhi, Mumbai, Chennai, and Kolkata. Community Long-term Infrared Microwave Coupled Atmospheric Product System (CLIMCAPS) dataset around 0800 UTC (2000UTC) has been used for initializing the number concentration of CH₄, N₂O, and SO₂ for daytime (nighttime). The daytime (nighttime) retrieved profiles have been validated using 2000 UTC (next day 0800 UTC) CLIMCAPS products. ERA5 temperature dataset has been used to estimate the kinematic rate of reactions with 1000 perturbations determined using Maximum Likelihood Estimation (MLE). The retrieved profiles and CLIMCAPS products are in very good agreement, as evidenced by the percentage difference between them within the range of 1.3 × 10^-5-60.8 % and the coefficient of determination mainly within the range between 81 and 97 %. However, during the passage of tropical cyclone and western disturbance, its value became as low as 27 and 65 % over Chennai and Kolkata, respectively. The enactment of synoptic scale systems such as western disturbances, tropical cyclone Amphan, and easterly waves caused disturbed weather over these megacities-the retrieved profiles during disturbed weather cause large deviations of vertical profiles of N₂O. However, the profiles of CH₄ and SO₂ have less deviation. It is inferred that incorporating this methodology in the dynamical model will be useful to simulate the realistic vertical profiles of the minor constituents in the atmosphere.

Predicting Vertical Concentration Profiles in the Marine Atmospheric Boundary Layer With a Markov Chain Random Walk Model

In an effort to better represent aerosol transport in mesoscale and global-scale models, large eddy simulations (LES) from the National Center for Atmospheric Research (NCAR) Turbulence with Particles (NTLP) code are used to develop a Markov chain random walk model that predicts aerosol particle profiles in a cloud-free marine atmospheric boundary layer (MABL). The evolution of vertical concentration profiles are simulated for a range of aerosol particle sizes and in a neutral and an unstable boundary layer. For the neutral boundary layer we find, based on the LES statistics and a specific model time step, that there exist significant correlation for particle positions, meaning that particles near the bottom of the boundary are more likely to remain near the bottom of the boundary layer than being abruptly transported to the top, and vice versa. For the unstable boundary layer, a similar time interval exhibits a weaker tendency for an aerosol particle to remain close to its current location compared to the neutral case due to the strong nonlocal convective motions. In the limit of a large time interval, particles have been mixed throughout the MABL and virtually no temporal correlation exists. We leverage this information to parameterize a Markov chain random walk model that accurately predicts the evolution of vertical concentration profiles. The new methodology has significant potential to be applied at the subgrid level for coarser-scale weather and climate models, the utility of which is shown by comparison to airborne field data and global aerosol models.

Evaluations of tropospheric aerosol properties simulated by the community earth system model with a sectional aerosol microphysics scheme

A sectional aerosol model (CARMA) has been developed and coupled with the Community Earth System Model (CESM1). Aerosol microphysics, radiative properties, and interactions with clouds are simulated in the size-resolving model. The model described here uses 20 particle size bins for each aerosol component including freshly nucleated sulfate particles, as well as mixed particles containing sulfate, primary organics, black carbon, dust, and sea salt. The model also includes five types of bulk secondary organic aerosols with four volatility bins. The overall cost of CESM1-CARMA is approximately ∼2.6 times as much computer time as the standard three-mode aerosol model in CESM1 (CESM1-MAM3) and twice as much computer time as the seven-mode aerosol model in CESM1 (CESM1-MAM7) using similar gas phase chemistry codes. Aerosol spatial-temporal distributions are simulated and compared with a large set of observations from satellites, ground-based measurements, and airborne field campaigns. Simulated annual average aerosol optical depths are lower than MODIS/MISR satellite observations and AERONET observations by ∼32%. This difference is within the uncertainty of the satellite observations. CESM1/CARMA reproduces sulfate aerosol mass within 8%, organic aerosol mass within 20%, and black carbon aerosol mass within 50% compared with a multiyear average of the IMPROVE/EPA data over United States, but differences vary considerably at individual locations. Other data sets show similar levels of comparison with model simulations. The model suggests that in addition to sulfate, organic aerosols also significantly contribute to aerosol mass in the tropical UTLS, which is consistent with limited data.