Browsing UA Graduate and Undergraduate Research by Subjects
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North American Monsoon Variability from Paleoclimate Era to Climate Change Projection: A Multiple Dataset PerspectiveIn the southwestern United States, the North American monsoon (NAM) is the main driver of severe weather and accounts for nearly half the annual precipitation. How the monsoon has behaved in the past and how it will change in the future is a question of major importance for natural resource management and infrastructural planning. In this dissertation, I present the results of three studies that have investigated North American monsoon variability and change from the perspective of paleoclimate records, future climate change projections, and simulation of the low-frequency variability with the longest retrospective atmospheric reanalysis. In the first study, a monsoon-sensitive network of tree-ring chronologies is evaluated within its ability to reproduce NAM variability during the past four centuries. Matrix methods are used to detect the low-frequency spatiotemporal variability. The treering chronologies can reasonable characterizes the dominant modes of NAM climate variability. The monsoon tree-ring network is able to reproduce the interannual variability of cool and warm season precipitation, in a manner similar to the period of the instrumental record. Earlywood and latewood adjusted chronologies reveal low frequency climate variability at decadal and longer timescales that is beyond the ability of the instrumental record to temporally well resolve. This low-frequency climate variability seems to be part of a much larger cycle that coincides with the occurrence of multiyear persistent droughts. In the second study, we consider the modes of natural climate variability identified in the previous study to objectively assess the degree of physical uncertainty in climate change projections for NAM from Regional Climate Models (RCMs) used in the North American Regional Climate Change Assessment Program (NARCCAP). Climate change projection models are evaluated mainly on their ability to represent warm season driven by quasi-stationary Rossby wave trains and El Niño Southern Oscillation – Pacific Decadal Variability (ENSO-PDV). It is concluded that use of the NARCCAP model ensemble mean for NAM climate projections is probably not suitable. NARCCAP RCMs are largely a slave to their driving global models and their error in the specification of large-scale atmospheric circulation. Only one out of eight NARCCAP RCMs has a reasonable representation of the seasonal cycle of monsoon precipitation and ENSOdriven interannual variability in both the 20th and 21st centuries. No decadal variability was observed in any of the NARCCAP RCMs. In the third study, the low-frequency drought signal found with tree-ring chronologies is further explored within the framework of a regional climate modeling. Version 2 of the Twentieth-Century Reanalysis (DD-20CR) is dynamically downscaled over a contiguous U.S.-Mexico domain. Statistic analysis of the DD-20CR suggests that the low-frequency drought signal in the Southwest is driven by atmospheric circulation changes on global to continental scales that affect precipitation in Central American as well. DD-20CR reproduces the spatial patterns of precipitation associated with climate variability at decadal and longer timescales in a manner that compares well with observational records and tree-ring chronologies. Low-frequency climate variability is therefore likely responsible for the multiyear persistent droughts in the last four centuries, as independently evaluated from the tree-ring monsoon-sensitive network.
Severe Weather during the North American Monsoon and Its Response to Rapid Urbanization and a Changing Global Climate within the Context of High Resolution Regional Atmospheric ModelingThe North American monsoon (NAM) is the principal driver of summer severe weather in the Southwest U.S. With sufficient atmospheric instability and moisture, monsoon convection initiates during daytime in the mountains and later may organize, principally into mesoscale convective systems (MCSs). Most monsoon-related severe weather occurs in association with organized convection, including microbursts, dust storms, flash flooding and lightning. The overarching theme of this dissertation research is to investigate simulation of monsoon severe weather due to organized convection within the use of regional atmospheric modeling. A commonly used cumulus parameterization scheme has been modified to better account for dynamic pressure effects, resulting in an improved representation of a simulated MCS during the North American monsoon experiment and the climatology of warm season precipitation in a long-term regional climate model simulation. The effect of urbanization on organized convection occurring in Phoenix is evaluated in model sensitivity experiments using an urban canopy model (UCM) and urban land cover compared to pre-settlement natural desert land cover. The presence of vegetation and irrigation makes Phoenix a "heat sink" in comparison to its surrounding desert, and as a result the modeled precipitation in response to urbanization decreases within the Phoenix urban area and increase on its periphery. Finally, analysis of how monsoon severe weather is changing in association with observed global climate change is considered within the context of a series of retrospectively simulated severe weather events during the period 1948-2010 in a numerical weather prediction paradigm. The individual severe weather events are identified by favorable thermodynamic conditions of instability and atmospheric moisture (precipitable water). Changes in precipitation extremes are evaluated with extreme value statistics. During the last several decades, there has been intensification of organized convective precipitation, but these events occur with less frequency. A more favorable thermodynamic environment for monsoon thunderstorms is the driver of these changes, which is consistent with the broader notion that anthropogenic climate change is presently intensifying weather extremes worldwide.