[1] A two-dimensional cloud-resolving model with detailed spectral bin microphysics is used to examine the effect of aerosols on three different deep convective cloud systems that developed in different geographic locations: south Florida, Oklahoma, and the central Pacific. A pair of model simulations, one with an idealized low cloud condensation nuclei (CCN) (clean) and one with an idealized high CCN (dirty environment), is conducted for each case. In all three cases, rain reaches the ground earlier for the low-CCN case. Rain suppression is also evident in all three cases with high CCN. However, this suppression only occurs during the early stages of the simulations. During the mature stages of the simulations the effects of increasing aerosol concentration range from rain suppression in the Oklahoma case to almost no effect in the Florida case to rain enhancement in the Pacific case. The model results suggest that evaporative cooling in the lower troposphere is a key process in determining whether high CCN reduces or enhances precipitation. Stronger evaporative cooling can produce a stronger cold pool and thus stronger low-level convergence through interactions with the low-level wind shear. Consequently, precipitation processes can be more vigorous. For example, the evaporative cooling is more than two times stronger in the lower troposphere with high CCN for the Pacific case. Sensitivity tests also suggest that ice processes are crucial for suppressing precipitation in the Oklahoma case with high CCN. A comparison and review of other modeling studies are also presented.
[1] A three-dimensional (3-D) cloud-scale chemical transport model that includes a parameterized source of lightning NO x on the basis of observed flash rates has been used to simulate six midlatitude and subtropical thunderstorms observed during four field projects. Production per intracloud (P IC ) and cloud-to-ground (P CG ) flash is estimated by assuming various values of P IC and P CG for each storm and determining which production scenario yields NO x mixing ratios that compare most favorably with in-cloud aircraft observations. We obtain a mean P CG value of 500 moles NO (7 kg N) per flash. The results of this analysis also suggest that on average, P IC may be nearly equal to P CG , which is contrary to the common assumption that intracloud flashes are significantly less productive of NO than are cloud-to-ground flashes. This study also presents vertical profiles of the mass of lightning NO x after convection based on 3-D cloud-scale model simulations. The results suggest that following convection, a large percentage of lightning NO x remains in the middle and upper troposphere where it originated, while only a small percentage is found near the surface. The results of this work differ from profiles calculated from 2-D cloud-scale model simulations with a simpler lightning parameterization that were peaked near the surface and in the upper troposphere (referred to as a ''C-shaped'' profile). The new model results (a backward C-shaped profile) suggest that chemical transport models that assume a C-shaped vertical profile of lightning NO x mass may place too much mass near the surface and too little in the middle troposphere.
SUMMARYThis paper investigates daytime convective development over land and its representation in single-column models (SCMs) and cloud-resolving models (CRMs). A model intercomparison case is developed based on observations of the diurnal cycle and convection during the rainy season in Amazonia. The focus is on the 6 h period between sunrise and early afternoon which was identified in previous studies as critical for the diurnal cycle over summertime continents in numerical weather prediction and climate models. This period is characterized by the formation and growth of a well-mixed convective boundary layer from the early morning temperature and moisture profiles as the surface sensible-and latent-heat fluxes increase after sunrise. It proceeds with the formation of shallow convective clouds as the convective boundary layer deepens, and leads to the eventual transition from shallow to deep precipitating convection around local noon. To provide a benchmark for other models, a custom-designed set of simulations, applying increasing in time computational domain and decreasing spatial resolution, was executed. The SCMs reproduced the previously identified problem with premature development of deep convection, less than two hours after sunrise. The benchmark simulations suggest a possible route to improve SCMs by considering a time-evolving cumulus entrainment rate as convection evolves from shallow to deep and the cloud width increases up to an order of magnitude. The CRMs featuring horizontal grid length around 500 m are capable of capturing the qualitative aspects of the benchmark simulations, but there are significant differences among the models. Two-dimensional CRMs tend to simulate too rapid a transition from shallow to deep convection and too high a cloud cover.
The 3D Goddard Cumulus Ensemble model is used to simulate two convective events observed during the Tropical Rainfall Measuring Mission Large-Scale Biosphere-Atmosphere (TRMM LBA) experiment in Brazil. These two events epitomized the type of convective systems that formed in two distinctly different environments observed during TRMM LBA. The 26 January 1999 squall line formed within a sheared low-level easterly wind flow. On 23 February 1999, convection developed in weak low-level westerly flow, resulting in weakly organized, less intense convection. Initial simulations captured the basic organization and intensity of each event. However, improvements to the model resolution and microphysics produced better simulations as compared to observations. More realistic diurnal convective growth was achieved by lowering the horizontal grid spacing from 1000 to 250 m. This produced a gradual transition from shallow to deep convection that occurred over a span of hours as opposed to an abrupt appearance of deep convection. Eliminating the dry growth of graupel in the bulk microphysics scheme effectively removed the unrealistic presence of high-density ice in the simulated anvil. However, comparisons with radar reflectivity data using contoured-frequency-with-altitude diagrams (CFADs) revealed that the resulting snow contents were too large. The excessive snow was reduced primarily by lowering the collection efficiency of cloud water by snow and resulted in further agreement with the radar observations. The transfer of cloud-sized particles to precipitation-sized ice appears to be too efficient in the original scheme. Overall, these changes to the microphysics lead to more realistic precipitation ice contents in the model. However, artifacts due to the inability of the one-moment scheme to allow for size sorting, such as excessive low-level rain evaporation, were also found but could not be resolved without moving to a two-moment or bin scheme. As a result, model rainfall histograms underestimated the occurrence of high rain rates compared to radar-based histograms. Nevertheless, the improved precipitation-sized ice signature in the model simulations should lead to better latent heating retrievals as a result of both better convective-stratiform separation within the model as well as more physically realistic hydrometeor structures for radiance calculations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.