scholarly journals Development of an Aerosol Retrieval Method: Description and Preliminary Tests

2008 ◽  
Vol 47 (11) ◽  
pp. 2760-2776 ◽  
Author(s):  
G. G. Carrió ◽  
W. R. Cotton ◽  
D. Zupanski ◽  
M. Zupanski
Keyword(s):  
Boundary Layer ◽  
Cloud Condensation Nuclei ◽  
Coupled Model ◽  
Nonlinear Problems ◽  
Atmospheric Modeling ◽  
Arctic Boundary Layer ◽  
Retrieval Method ◽  
Aerosol Retrieval ◽  
Highly Nonlinear ◽  
Microscale Model

Abstract A cloud-nucleating aerosol retrieval method was developed. It allows the estimation of ice-forming nuclei and cloud condensation nuclei (IFN and CCN) for regions in which boundary layer clouds prevail. The method is based on the assumption that the periodical assimilation of observations into a microscale model leads to an improved estimation of the model state vector (that contains the cloud-nucleating aerosol concentrations). The Colorado State University Cloud Resolving Model (CRM) version of the Regional Atmospheric Modeling System (RAMS@CSU) and the maximum likelihood ensemble filter algorithm (MLEF) were used as the forecast model and the assimilation algorithm, respectively. On the one hand, the microphysical modules of this CRM explicitly consider the nucleation of IFN, CCN, and giant CCN. On the other hand, the MLEF provides an important advantage because it is defined to address highly nonlinear problems, employing an iterative minimization of a cost function. This paper explores the possibility of using an assimilation technique with microscale models. These initial series of experiments focused on isolating the model response and showed that data assimilation enhanced its performance in simulating a mixed-phase Arctic boundary layer cloud. Moreover, the coupled model was successful in reproducing the presence of an observed polluted air mass above the inversion.

Impact of Aerosol Intrusions on Arctic Boundary Layer Clouds. Part I: 4 May 1998 Case

2005 ◽  
Vol 62 (9) ◽  
pp. 3082-3093 ◽  
Author(s):  
G. G. Carrió ◽  
H. Jiang ◽  
W. R. Cotton
Keyword(s):  
Boundary Layer ◽  
Sea Ice ◽  
National Laboratory ◽  
Atmospheric Modeling ◽  
Mixed Phase ◽  
Radiative Properties ◽  
Arctic Boundary Layer ◽  
Water Fraction ◽  
Boundary Layer Clouds ◽  
The Impact

Abstract The objective of this paper is to assess the impact of the entrainment of aerosol from above the inversion on the microphysical structure and radiative properties of boundary layer clouds. For that purpose, the Los Alamos National Laboratory sea ice model was implemented into the research and real-time versions of the Regional Atmospheric Modeling System at Colorado State University. A series of cloud-resolving simulations have been performed for a mixed-phase Arctic boundary layer cloud using a new microphysical module that considers the explicit nucleation of cloud droplets. Different aerosol profiles based on observations were used for initialization. When more polluted initial ice-forming nuclei (IFN) profiles are assumed, the liquid water fraction of the cloud decreases while the total condensate path, the residence time of the ice particles, and the downwelling infrared radiation monotonically increase. Results suggest that increasing the aerosol concentrations above the boundary layer may increase sea ice melting rates when mixed-phase clouds are present.

Impact of Aerosol Intrusions on Arctic Boundary Layer Clouds. Part II: Sea Ice Melting Rates

2005 ◽  
Vol 62 (9) ◽  
pp. 3094-3105 ◽  
Author(s):  
G. G. Carrió ◽  
H. Jiang ◽  
W. R. Cotton
Keyword(s):  
Sea Ice ◽  
Heat Budget ◽  
Cloud Condensation Nuclei ◽  
National Laboratory ◽  
Arctic Basin ◽  
Atmospheric Modeling ◽  
Surface Energy Budget ◽  
The Arctic ◽  
Ice Melting ◽  
Arctic Boundary Layer

Abstract The potential impact of intrusions of polluted air into the Arctic basin on sea ice melting rates and the surface energy budget is examined. This paper extends a previous study to cloud-resolving simulations of the entire spring season during the 1998 Surface Heat Budget of the Arctic (SHEBA) field campaign. For that purpose, the Los Alamos National Laboratory sea ice model is implemented into the research and real-time versions of the Regional Atmospheric Modeling System at Colorado State University (RAMS@CSU). This new version of RAMS@CSU also includes a new microphysical module that considers the explicit nucleation of cloud droplets and a bimodal representation of their spectrum. Different aerosol profiles based on 4 May 1998 observations were used to characterize the polluted upper layer and the 2–3 daily SHEBA soundings were utilized to provide time-evolving boundary conditions to the model. Results indicate that entrainment of ice-forming nuclei (IFN) from above the inversion increases the sea ice melting rates when mixed-phase clouds are present. An opposite although less important effect is associated with cloud condensation nuclei (CCN) entrainment when liquid-phase clouds prevail.

A Comprehensive Investigation of Ensembles of Gaussian-Based and Gradient-Based Transformed Reliability Analyses: When and How to Use Them

2016 ◽  
Author(s):  
Po Ting Lin ◽  
Wei-Hao Lu ◽  
Shu-Ping Lin
Keyword(s):  
Design Optimization ◽  
Design Space ◽  
Optimization Problems ◽  
Nonlinear Problems ◽  
Kernel Functions ◽  
Sensitivity Analyses ◽  
Normal Space ◽  
Highly Nonlinear ◽  
Standard Normal ◽  
Gradient Based

In the past few years, researchers have begun to investigate the existence of arbitrary uncertainties in the design optimization problems. Most traditional reliability-based design optimization (RBDO) methods transform the design space to the standard normal space for reliability analysis but may not work well when the random variables are arbitrarily distributed. It is because that the transformation to the standard normal space cannot be determined or the distribution type is unknown. The methods of Ensemble of Gaussian-based Reliability Analyses (EoGRA) and Ensemble of Gradient-based Transformed Reliability Analyses (EGTRA) have been developed to estimate the joint probability density function using the ensemble of kernel functions. EoGRA performs a series of Gaussian-based kernel reliability analyses and merged them together to compute the reliability of the design point. EGTRA transforms the design space to the single-variate design space toward the constraint gradient, where the kernel reliability analyses become much less costly. In this paper, a series of comprehensive investigations were performed to study the similarities and differences between EoGRA and EGTRA. The results showed that EGTRA performs accurate and effective reliability analyses for both linear and nonlinear problems. When the constraints are highly nonlinear, EGTRA may have little problem but still can be effective in terms of starting from deterministic optimal points. On the other hands, the sensitivity analyses of EoGRA may be ineffective when the random distribution is completely inside the feasible space or infeasible space. However, EoGRA can find acceptable design points when starting from deterministic optimal points. Moreover, EoGRA is capable of delivering estimated failure probability of each constraint during the optimization processes, which may be convenient for some applications.

Mesoscale Variability in the Summer Arctic Boundary Layer

2009 ◽  
Vol 130 (3) ◽  
pp. 383-406 ◽  
Author(s):  
Michael Tjernström ◽  
Thorsten Mauritsen
Keyword(s):  
Boundary Layer ◽  
Mesoscale Variability ◽  
Arctic Boundary Layer

Observation of coinciding arctic boundary layer ozone depletion and snow surface emissions of nitrous acid

2006 ◽  
Vol 40 (11) ◽  
pp. 1949-1956 ◽  
Author(s):  
Antonio Amoroso ◽  
Harry J. Beine ◽  
Roberto Sparapani ◽  
Marianna Nardino ◽  
Ivo Allegrini
Keyword(s):  
Boundary Layer ◽  
Ozone Depletion ◽  
Nitrous Acid ◽  
Snow Surface ◽  
Arctic Boundary Layer ◽  
Boundary Layer Ozone

Idealized large-eddy simulations of stratocumulus advecting over cold water. Part 1: Boundary layer decoupling

2021 ◽  
Author(s):  
Youtong Zheng ◽  
Haipeng Zhang ◽  
Daniel Rosenfeld ◽  
Seoung-Soo Lee ◽  
Tianning Su ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Surface Temperature ◽  
Cold Water ◽  
Temperature Inversion ◽  
Atmospheric Modeling ◽  
Sea Surface ◽  
Entrainment Rate ◽  
Surface Cooling ◽  
Near Surface ◽  
Large Eddy

AbstractWe explore the decoupling physics of a stratocumulus-topped boundary layer (STBL) moving over cooler water, a situation mimicking the warm air advection (WADV). We simulate an initially well-mixed STBL over a doubly periodic domain with the sea surface temperature decreasing linearly over time using the System for Atmospheric Modeling large-eddy model. Due to the surface cooling, the STBL becomes increasingly stably stratified, manifested as a near-surface temperature inversion topped by a well-mixed cloud-containing layer. Unlike the stably stratified STBL in cold air advection (CADV) that is characterized by cumulus coupling, the stratocumulus deck in the WADV is unambiguously decoupled from the sea surface, manifested as weakly negative buoyancy flux throughout the sub-cloud layer. Without the influxes of buoyancy from the surface, the convective circulation in the well-mixed cloud-containing layer is driven by cloud-top radiative cooling. In such a regime, the downdrafts propel the circulation, in contrast to that in CADV regime for which the cumulus updrafts play a more determinant role. Such a contrast in convection regime explains the difference in many aspects of the STBLs including the entrainment rate, cloud homogeneity, vertical exchanges of heat and moisture, and lifetime of the stratocumulus deck, with the last being subject to a more thorough investigation in part 2. Finally, we investigate under what conditions a secondary stratus near the surface (or fog) can form in the WADV. We found that weaker subsidence favors the formation of fog whereas a more rapid surface cooling rate doesn’t.

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