Arastoo Pour-Biazar

Response and sensitivity of the nocturnal boundary layer over land to added longwave radiative forcing

[1] One of the most significant signals in the thermometer-observed temperature record since 1900 is the decrease in the diurnal temperature range over land, largely due to rising of the minimum temperatures. Generally, climate models have not well replicated this change in diurnal temperature range. Thus, the cause for night-time warming in the observed temperatures has been attributed to a variety of external causes. We take an alternative approach to examine the role that the internal dynamics of the stable nocturnal boundary layer (SNBL) may play in affecting the response and sensitivity of minimum temperatures to added downward longwave forcing. As indicated by previous nonlinear analyses of a truncated two-layer equation system, the SNBL can be very sensitive to changes in greenhouse gas forcing, surface roughness, heat capacity, and wind speed. A new singlecolumn model growing out of these nonlinear studies is used to examine the SNBL. Specifically, budget analyses of the model are provided that evaluate the response of the boundary layer to forcing and sensitivity to mixing formulations. Based on these model analyses, it is likely that part of the observed long-term increase in minimum temperature is reflecting a redistribution of heat by changes in turbulence and not by an accumulation of heat in the boundary layer. Because of the sensitivity of the shelter level temperature to parameters and forcing, especially to uncertain turbulence parameterization in the SNBL, there should be caution about the use of minimum temperatures as a diagnostic global warming metric in either observations or models.

Summertime tropospheric ozone enhancement associated with a cold front passage due to stratosphere‐to‐troposphere transport and biomass burning: Simultaneous ground‐based lidar and airborne measurements

Stratosphere-to-troposphere transport (STT) and biomass burning (BB) are two important natural sources for tropospheric ozone that can result in elevated ozone and air-quality episode events. High-resolution observations of multiple related species are critical for complex ozone source attribution. In this article, we present an analysis of coinciding ground-based and airborne observations, including ozone lidar, ozonesonde, high spectral resolution lidar (HSRL), and multiple airborne in situ measurements, made on 28 and 29 June 2013 during the Southeast Nexus field campaign. The ozone lidar and HSRL reveal detailed ozone and aerosol structures as well as the temporal evolution associated with a cold front passage. The observations also captured two enhanced (+30 ppbv) ozone layers in the free troposphere (FT), which were determined from this study to be caused by a mixture of BB and stratospheric sources. The mechanism for this STT is tropopause folding associated with a cutoff upper level low-pressure system according to the analysis of its potential vorticity structure. The depth of the tropopause fold appears to be shallow for this case compared to events observed in other seasons; however, the impact on lower tropospheric ozone was clearly observed. This event suggests that strong STT may occur in the southeast United States during the summer and can potentially impact lower troposphere during these times. Statistical analysis of the airborne observations of trace gases suggests a coincident influence of BB transport in the FT impacting the vertical structure of ozone during this case study.

Improving Cloud Simulation for Air Quality Studies Through Assimilation of Geostationary Satellite Observations in Retrospective Meteorological Modeling

AbstractDevelopment of clouds in space and time within numerical meteorological models as observed in nature is essential for producing an accurate representation of the physical atmosphere for input into air quality models. In this study, a new technique was developed to assimilate Geostationary Operational Environmental Satellite (GOES)-derived cloud fields into the Weather Research and Forecasting (WRF) meteorological model to improve the placement of clouds in space and time within the model. The simulations were performed on 36-, 12-, and 4-km grid-size domains covering the contiguous United States, the south-southeastern United States, and eastern Texas, respectively. The technique was tested over the month of August 2006. The results indicate that the assimilation technique significantly improves the agreement between the model-predicted and GOES-derived cloud fields. The daily average percentage increase in the cloud agreement was determined to be 14.02%, 11.29%, and 4.96% for the 36-, 12-, and 4-...

Examination of the Physical Atmosphere in the Great Lakes Region and its Potential Impact on Air Quality - Over-Water Stability and Satellite Assimilation

AbstractHigh mixing ratios of ozone along the shores of Lake Michigan have been a recurring theme over the last 40 years. Models continue to have difficulty in replicating ozone behavior in the reg...