Browsing by Author "Randall, David, committee member"

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Open Access
A parametric optimal estimation retrieval of the non-precipitating parameters over the global oceans
(Colorado State University. Libraries, 2006) Elsaesser, Gregory S., author; Kummerow, Chris, advisor; Reising, Steven C., committee member; Randall, David, committee member
There are a multitude of spacebome microwave sensors in orbit, including the TRMM Microwave Imager (TMI), the Special Sensor Microwave/lmager (SSM/I) onboard the DMSP satellites, the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E), SSMIS, WINDSAT, and others. Future missions, such as the planned Global Precipitation Measurement (GPM) Mission, will incorporate additional spacebome microwave sensors. The need for consistent geophysical parameter retrievals among an ever-increasing number of microwave sensors requires the development of a physical retrieval scheme independent of any particular sensor and flexible enough so that future microwave sensors can be added with relative ease. To this end, we attempt to develop a parametric retrieval algorithm currently applicable to the non-precipitating atmosphere with the goal of having consistent non-precipitating geophysical parameter products. An algorithm of this nature makes is easier to merge separate products, which, when combined, would allow for additional global sampling or longer time series of the retrieved global geophysical parameters for climate purposes. This algorithm is currently applied to TMI, SSM/I and AMSR-E with results that are comparable to other independent microwave retrievals of the non-precipitating parameters designed for specific sensors. The physical retrieval is developed within the optimal estimation framework. The development of the retrieval within this framework ensures that the simulated radiances corresponding to the retrieved geophysical parameters will always agree with observed radiances regardless of the sensor being used. Furthermore, a framework of this nature allows one to easily add additional physics to describe radiation propagation through raining scenes, thus allowing for the merger of cloud and precipitation retrievals, if so desired. Additionally, optimal estimation provides error estimates on the retrieval, a product often not available in other algorithms, information on potential forward model/sensor biases, and a number of useful diagnostics providing information on the validity and significance of the retrieval (such as Chi-Square, indicative of the general "fit" between the model and observations and the A-Matrix, indicating the sensitivity of the model to a change in the geophysical parameters). There is an expected global response of these diagnostics based on the scene being observed, such as in the case of a raining scene. Fortunately, since TRMM has a precipitation radar (TRMM PR) in addition to a radiometer (TMI) flying on-board, the expected response of the retrieval diagnostics to rainfall can be evaluated. It is shown that a potentially powerful rainfall screen can then be developed for use in passive microwave rainfall and cloud property retrieval algorithms with the possibility of discriminating between precipitating and nonprecipitating scenes, and further indicating the possible contamination of rainfall in cloud liquid water path microwave retrievals.
Open Access
A performance evaluation of the coupling infrastructure within the Community Earth System Model™
(Colorado State University. Libraries, 2018) Mickelson, Sheri A., author; Pouchet, Louis-Noel, advisor; Rajopadhye, Sanjay, committee member; Randall, David, committee member
Earth System models (ESMs) are complex software packages comprised of millions of lines of code used to simulate many different Earth processes. ESMs simulate the dynamical and physical states of the atmosphere, land, ocean, sea ice, rivers, and glaciers and coordinate the interactions between them. Many computational challenges exist within these models and future systems are putting more pressure on these challenges. In order to alleviate some of the pressure, it is important to study the performance challenges that exist within the models in order to understand the optimizations that need to be performed as we move to exascale systems. This work studies the performance of the coupling infrastructure between the modeling components within the Community Earth System Model. The coupler is responsible for the data exchanges between the different modeling components and while it has a small computational footprint, it has the potential to have a large impact on performance if the component resources are dispersed in incorrect proportions. This work explains and addresses this issue and provides easy solutions for users to save thousands of core cpu hours.
Open Access
Biophysical behavior in tropical South America
(Colorado State University. Libraries, 2011) Baker, Ian Timothy, author; Denning, A. Scott, advisor; Randall, David, committee member; Coughenour, Michael, committee member; Gao, Wei, committee member; Estep, Donald, committee member
To view the abstract, please see the full text of the document.
Open Access
Drought tolerance and implications for vegetation-climate interactions in the Amazon forest
(Colorado State University. Libraries, 2012) Harper, Anna Biagi, author; Denning, Alan Scott, advisor; Randall, David, committee member; Kummerow, Christian, committee member; Cotrufo, Francesca, committee member
On seasonal and annual timescales, the Amazon forest is resistant to drought, but more severe droughts can have profound effects on ecosystem productivity and tree mortality. The majority of climate models predict decreased rainfall in tropical South America over this century. Until recently, land surface models have not included mechanisms of forest resistance to seasonal drought. In some coupled climate models, the inability of tropical forest to withstand warming and drying leads to replacement of forest by savanna by 2050. The main questions of this research are: What factors affect forest drought tolerance, and what are the implications of drought tolerance mechanisms for climate? Forest adaptations to drought, such as development of deep roots, enable Amazon forests to withstand seasonal droughts, and the maintenance of transpiration during dry periods can affect regional climate. At high levels of water stress, such as those imposed during a multiyear rainfall exclusion experiment or during interannual drought, trees prevent water loss by closing their stomata. We examine forest response to drought in an ecosystem model (SiB3 - the Simple Biosphere model) compared to two rainfall exclusion experiments in the Amazon. SiB3 best reproduces the observed drought response using realistic soil parameters and annual LAI, and by adjusting soil depth. SiB3's optimal soil depth at each site serves as a proxy for forest drought resistance. Based on the results at the exclusion sites, we form the hypothesis that forests with periodic dry conditions are more adapted to drought. We parameterize stress resistance as a function of precipitation climatology, soil texture, and percent forest cover. The parameterization impacts carbon and moisture fluxes during extreme drought events. The loss of productivity is of similar magnitude as plot-based measurements of biomass loss during the 2005 drought. Changing stress resistance in SiB3 also affects surface evapotranspiration during dry periods, which has the potential to affect climate through changing sensible and latent heat fluxes. We examine the effects of forest stress resistance on climate through coupled experiments of SiB3 in a GCM. In a single column model, we find evidence for a more active hydrologic cycle due to increased stress resistance. The boundary layer responds through changes in its depth, relative humidity, and turbulent kinetic energy, and the changes feed back to influence wet season onset and intensity. In a full global GCM, increased stress resistance often decreases drought intensity through enhanced ET and changes to circulation. The circulation responds to changes in atmospheric latent heating and can affect precipitation in the South Atlantic Convergence Zone.
Open Access
Estimating the likelihood of significant climate change with the NCAR 40-member ensemble
(Colorado State University. Libraries, 2014) Foust, William Eliott, author; Thompson, David, advisor; Randall, David, committee member; Barnes, Elizabeth, committee member; Cooley, Daniel, committee member
Increasing greenhouse gas concentrations are changing the radiative forcing on the climate system, and this forcing will be the key driver of climate change over the 21st century. One of the most pressing questions associated with climate change is whether certain aspects of the climate system will change significantly. Climate ensembles are often used to estimate the probability of significant climate change, but they struggle to produce accurate estimates of significant climate change because they sometimes require more realizations than what is feasible to produce. Additionally, the ensemble mean suggests how the climate will respond to an external forcing, but since it filters out the variability, it cannot determine if the response is significant. In this study, the NCAR CCSM 40-member ensemble and a lag-1 autoregressive model (AR1 model) are used to estimate the likelihood that climate trends will be significant. The AR1 model generates an analytic solution for what the distribution of trends should be if the NCAR model was run an infinite number of times. The analytical solution produced by the AR1 model is used to assess the significance of future climate trends. The results of this study demonstrate that an AR1 model can aid in making a probabilistic forecast. Additionally, the results give insight into the certainty of the trends in the surface temperature field, precipitation field, and atmospheric circulation, the probability of climate trends being significant, and whether the significance of climate trends is dependent on the internal variability or anthropogenic forcing.
Open Access
Evaluation of inter-annual variability and trends of cloud liquid water path in climate models using a multi-decadal record of passive microwave observations
(Colorado State University. Libraries, 2016) Manaster, Andrew, author; Kummerow, Christian, advisor; O'Dell, Christopher W., advisor; Randall, David, committee member; Reising, Steven, committee member
Long term satellite records of cloud changes have only been available for the past several decades and have just recently been used to diagnose cloud-climate feedbacks. However, due to issues with satellite drift, calibration, and other artifacts, the validity of these cloud changes has been called into question. It is therefore pertinent that we look for other observational datasets that can help to diagnose changes in variables relevant to cloud-radiation feedbacks. One such dataset is the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP), which blends cloud liquid water path (LWP) observations from 12 different passive microwave sensors over the past 27 years. In this study, observed LWP trends from the MAC-LWP dataset are compared to LWP trends from 16 models in the Coupled Model Intercomparison Project 5 (CMIP5) in order to assess how well the models capture these trends and thus related radiative forcing variables (e.g., cloud radiative forcing). Mean state values of observed LWP are compared to those of previous observed climatologies and are found to have relatively good quantitative and qualitative agreements. Mean state observed LWP variables are compared both qualitatively and quantitatively to our suite of CMIP5 models. These models tend to capture mean state and mean seasonal cycle LWP features, but the magnitudes exhibit large variations from model to model. Several metrics were used to compare observed mean state LWP and mean seasonal cycle amplitude and the mean state LWP and mean seasonal cycle amplitude in each model. However, the models' performance in regards to these metrics is found to not be indicative of their abilities to accurately reproduce trends on a regional or global scale. Global trends in the observations and the model means are compared. It is found that observational trends are roughly 2-3 times larger in magnitude in most regions globally when compared to the model mean although this is thought to be at least partly caused by cancellation effects due to differing inter-annual variability and physics between models. Several regions (e.g., the Southern Ocean) have consistent signs in trends between the observations and the model mean while others do not due to spatial inconsistencies in certain trend features in the model mean relative to the observations. Trends are examined in individual regions. In four of the six regions analyzed, the observational trends are statistically different from zero, while, in most regions, very few models have trends that are statistically significant. In certain regions, the majority of modeled trends are statistically consistent with the observed trends although this is typically due to large estimated errors in the observations and/or models, most likely caused by large inter-annual variability. The Southern Ocean and globally averaged trends show the strongest similarities to the observed trends. Almost all Southern Ocean trends are robustly positive and statistically significant with the majority of models being statistically consistent with the observations. Similarly, the observed and global trends are all positive with the majority being statistically significant and statistically consistent. We discuss why a large positive Southern Ocean trend is unlikely to be due to a trend in cloud phase. CMIP5 model mean and observational LWP trends are compared regionally to Atmospheric Model Intercomparison Project (AMIP) and ERA-interim reanalysis trends. It is found that AMIP model mean and ERA LWPs are better than the CMIP5 model mean at capturing the inter-annual variability in the observed time series in most of the regions examined. The AMIP model mean better replicates the observed trends when the inter-annual variability is better captured. The ERA reanalysis tends to better reproduce the observed inter-annual variability when compared to the AMIP model mean in almost every region, but, surprisingly, it is either worse or roughly the same in regards to matching observed trends. Our results suggest that observed trends are due to a combination of inter-annual and decadal-scale internal variability, in addition to external forced trends due to anthropogenic influences on the climate system. With a record spanning three decades, many modeled trends are statistically consistent with the observed trends, but a true climatically forced signal is not yet apparent in the models that agrees with the observations. The primary exception to this is in the Southern Ocean, where virtually all models and observations indicate an increasing amount of cloud liquid water path.
Open Access
Features based assessments of warm season convective precipitation forecasts from the high resolution rapid refresh model
(Colorado State University. Libraries, 2017) Bytheway, Janice L., author; Kummerow, Christian, advisor; Schumacher, Russ, committee member; Randall, David, committee member; Chandrasekar, V., committee member; Alexander, Curtis, committee member
Forecast models have seen vast improvements in recent years, via increased spatial and temporal resolution, rapid updating, assimilation of more observational data, and continued development and improvement of the representation of the atmosphere. One such model is the High Resolution Rapid Refresh (HRRR) model, a 3 km, hourly-updated, convection-allowing model that has been in development since 2010 and running operationally over the contiguous US since 2014. In 2013, the HRRR became the only US model to assimilate radar reflectivity via diabatic assimilation, a process in which the observed reflectivity is used to induce a latent heating perturbation in the model initial state in order to produce precipitation in those areas where it is indicated by the radar. In order to support the continued development and improvement of the HRRR model with regard to forecasts of convective precipitation, the concept of an assessment is introduced. The assessment process aims to connect model output with observations by first validating model performance then attempting to connect that performance to model assumptions, parameterizations and processes to identify areas for improvement. Observations from remote sensing platforms such as radar and satellite can provide valuable information about three-dimensional storm structure and microphysical properties for use in the assessment, including estimates of surface rainfall, hydrometeor types and size distributions, and column moisture content. A features-based methodology is used to identify warm season convective precipitating objects in the 2013, 2014, and 2015 versions of HRRR precipitation forecasts, Stage IV multisensor precipitation products, and Global Precipitation Measurement (GPM) core satellite observations. Quantitative precipitation forecasts (QPFs) are evaluated for biases in hourly rainfall intensity, total rainfall, and areal coverage in both the US Central Plains (29-49N, 85-105W) and US Mountain West (29-49N, 105-125W). Features identified in the model and Stage IV were tracked through time in order to evaluate forecasts through several hours of the forecast period. The 2013 version of the model was found to produce significantly stronger convective storms than observed, with a slight southerly displacement from the observed storms during the peak hours of convective activity (17-00 UTC). This version of the model also displayed a strong relationship between atmospheric water vapor content and cloud thickness over the central plains. In the 2014 and 2015 versions of the model, storms in the western US were found to be smaller and weaker than the observed, and satellite products (brightness temperatures and reflectivities) simulated using model output indicated that many of the forecast storms contained too much ice above the freezing level. Model upgrades intended to decrease the biases seen in early versions include changes to the reflectivity assimilation, the addition of sub-grid scale cloud parameterizations, changes to the representation of surface processes and the addition of aerosol processes to the microphysics. The effects of these changes are evident in each successive version of the model, with reduced biases in intensity, elimination of the southerly bias, and improved representation of the onset of convection.
Open Access
Large-eddy simulation of compressible flows using the stretched-vortex model and a fourth-order finite volume scheme on adaptive grids
(Colorado State University. Libraries, 2022) Walters, Sean, author; Guzik, Stephen, advisor; Gao, Xinfeng, advisor; Randall, David, committee member; Yalin, Azer, committee member
State-of-the-art engineering workflows are becoming increasingly dependent on accurate large-eddy simulations (LES) of compressible, turbulent flows for off-design conditions. Traditional CFD algorithms for compressible flows rely on numerical stabilization to handle unresolved physics and/or steep gradient flow features such as shockwaves. To reach higher levels of physical-fidelity than previously attainable, more accurate turbulence models must be properly incorporated into existing, high-order CFD codes in a manner that preserves the stability of the underlying algorithm while fully realizing the benefits of the turbulence model. As it stands, casually combining turbulence models and numerical stabilization degrades LES solutions below the level achievable by using numerical stabilization alone. To effectively use high-quality turbulence models and numerical stabilization simultaneously in a fourth-order-accurate finite volume LES algorithm, a new method based on scale separation is developed using adaptive grid technology for the stretched-vortex subgrid-scale (SGS) LES model. This method successfully demonstrates scheme-independent and grid-independent LES results at very-high-Reynolds numbers for the inviscid Taylor-Green vortex, the temporally-evolving double-shear-flow, and decaying, homogeneous turbulence. Furthermore, the method clearly demonstrates quantifiable advantages of high-order accurate numerical methods. Additionally, the stretched-vortex LES wall-model is extended to curvilinear mapped meshes for compressible flow simulations using adaptive mesh refinement. The capabilities of the wall-model combined with the stretched-vortex SGS LES model are demonstrated using the canonical zero-pressure-gradient flat-plate turbulent boundary layer. Finally, the complete algorithm is applied to simulate flow-separation and reattachment over a smooth-ramp, showing high-quality solutions on extremely coarse meshes.
Open Access
Links between climate feedbacks and the large-scale circulation across idealized and complex climate models
(Colorado State University. Libraries, 2023) Davis, Luke L. B., author; Thompson, David W. J., advisor; Maloney, Eric, committee member; Randall, David, committee member; Pinaud, Olivier, committee member; Gerber, Edwin, committee member
The circulation response to anthropogenic forcing is typically considered in one of two distinct frameworks: One that uses radiative forcings and feedbacks to investigate the thermodynamics of the response, and another that uses circulation feedbacks and thermodynamic constraints to investigate the dynamics of the response. In this thesis, I aim to help bridge the gap between these two frameworks by exploring direct links between climate feedbacks and the atmospheric circulation across ensembles of experiments from idealized and complex general circulation models (GCMs). I first demonstrate that an existing, widely-used type of idealized GCM — the dynamical core model — has climate feedbacks that are explicitly prescribed and determined by a single parameter: The thermal relaxation timescale. The dynamical core model may thus help to fill gaps in the model hierarchies commonly used to study climate forcings and climate feedbacks. I then perform two experiments: One that explores the influence of prescribed feedbacks on the unperturbed, climatological circulation; and a second that explores their influence on the circulation response to a horizontally uniform, global warming-like forcing perturbation. The results indicate that more stabilizing climate feedbacks are associated with 1) a more vigorous climatological circulation with increased thermal diffusivity, and 2) a weaker poleward displacement of the circulation in response to the global warming-like forcing. Importantly, since the most commonly-used relaxation timescale field resembles the real-world clear-sky feedback field, the uniform forcing perturbations produce realistic warming patterns, with amplified warming in the tropical upper troposphere and polar lower troposphere. The warming pattern and circulation response disappear when the relaxation timescale field is instead spatially uniform, demonstrating the critical role of spatially-varying feedback processes on shaping the response to anthropogenic forcing. I next explore circulation-feedback relationships in more complex GCMs using results from the most recent Coupled Model Intercomparison Projects (CMIP5 and CMIP6). Here, I estimate climate feedbacks by regressing top-of-atmosphere radiation against surface temperature for both 1) an unperturbed pre-industrial control experiment and 2) a perturbed global warming experiment forced by an abrupt quadrupling of CO2 concentrations. I find that across both ensembles, the cloud component of the perturbed climate feedback is closely related to the cloud component of the unperturbed climate feedback. Critically, the relationship is much stronger in CMIP6 than CMIP5, contrasting with many previously proposed constraints on the perturbation response. The relationship also explains the slow part of the CO2 response better than the fast, transient response. In general, the strength of the relationship depends on the degree to which the spatial pattern of the response resembles ENSO-dominated internal variability, with "El Niño-like" East Pacific warming and related tropical cloud changes. This is consistent with fluctuation-dissipation theory: Regions with stronger deep ocean heat exchange and weaker net feedbacks must always dominate both 1) internal fluctuations in the global energy budget, and 2) the slow part of the response to forcing perturbations. The stronger CMIP6 inter-model relationships are due to both an amplification of this mechanism and higher inter-model correlations between tropical cloud changes and extratropical cloud changes. Finally, I present emergent constraints on the slow response using a recent observational estimate of the unperturbed cloud feedback. I conclude by discussing some implications of these results. I consider how the relaxation feedback framework might be further developed and reconciled with traditional climate feedbacks to provide future research opportunities with climate model hierarchies.
Open Access
Moist synoptic transport of CO2 along midlatitude storm tracks, transport uncertainty, and implications for flux estimation
(Colorado State University. Libraries, 2011) Parazoo, Nicholas C., author; Denning, A. Scott, advisor; Randall, David, committee member; Maloney, Eric, committee member; Kawa, Randy, committee member; Paustian, Keith, committee member
Mass transport along moist isentropic surfaces on baroclinic waves represents an important component of the atmospheric heat engine that operates between the equator and poles. This is also an important vehicle for tracer transport, and is correlated with ecosystem metabolism because large-scale baroclinicity and photosynthesis are both driven seasonally by variations in solar radiation. In this research, I pursue a dynamical framework for explaining atmospheric transport of CO2 by synoptic weather systems at middle and high latitudes. A global model of atmospheric tracer transport, driven by meteorological analysis in combination with a detailed description of surface fluxes, is used to create time varying CO2 distributions in the atmosphere. Simulated mass fluxes of CO2 are then decomposed into a zonal monthly mean component and deviations from the monthly mean in space and time. Mass fluxes of CO2 are described on moist isentropic surfaces to represent frontal transport along storm tracks. Forward simulations suggest that synoptic weather systems transport large amounts of CO2 north and south in northern mid-latitudes, up to 1 PgC/month during winter when baroclinic wave activity peaks. During boreal winter when northern plants respire, warm moist air, high in CO2, is swept upward and poleward along the east side of baroclinic waves and injected into the polar vortex, while cold dry air, low in CO2, that had been transported into the polar vortex earlier in the year is advected equatorward. These synoptic eddies act to strongly reduce seasonality of CO2 in the biologically active mid-latitudes by 50% of that implied by local net ecosystem exchange while correspondingly amplifying seasonality in the Arctic. Transport along stormtracks is correlated with rising, moist, cloudy air, which systematically hides this CO2 transport from satellite observing systems. Meridional fluxes of CO2 are of comparable magnitude as surface exchange of CO2 in mid-latitudes, and thus require careful consideration in (inverse) modeling of the carbon cycle. Because synoptic transport of CO2 by frontal systems and moist processes is generally unobserved and poorly represented in global models, it may be a source of error for inverse flux estimates. Uncertainty in CO2 transport by synoptic eddies is investigated using a global model driven by four reanalysis products from the Goddard EOS Data Assimilation System for 2005. Eddy transport is found to be highly variable between model analysis, with significant seasonal differences of up to 0.2 PgC, which represents up to 50% of fossil fuel emissions. The variations are caused primarily by differences in grid spacing and vertical mixing by moist convection and PBL turbulence. To test for aliasing of transport bias into inverse flux estimates, synthetic satellite data is generated using a model at 50 km global resolution and inverted using a global model run with coarse grid transport. An ensemble filtering method called the Maximum Likelihood Ensemble Filter (MLEF) is used to optimize fluxes. Flux estimates are found to be highly sensitive to transport biases at pixel and continental scale, with errors of up to 0.5 PgC/year in Europe and North America.
Open Access
On the evaluation of exact-match and range queries over multidimensional data in distributed hash tables
(Colorado State University. Libraries, 2012) Malensek, Matthew, author; Pallickara, Shrideep, advisor; Draper, Bruce, committee member; Randall, David, committee member
The quantity and precision of geospatial and time series observational data being collected has increased alongside the steady expansion of processing and storage capabilities in modern computing hardware. The storage requirements for this information are vastly greater than the capabilities of a single computer, and are primarily met in a distributed manner. However, distributed solutions often impose strict constraints on retrieval semantics. In this thesis, we investigate the factors that influence storage and retrieval operations on large datasets in a cloud setting, and propose a lightweight data partitioning and indexing scheme to facilitate these operations. Our solution provides expressive retrieval support through range-based and exact-match queries and can be applied over massive quantities of multidimensional data. We provide benchmarks to illustrate the relative advantage of using our solution over a general-purpose cloud storage engine in a distributed network of heterogeneous computing resources.
Open Access
Separating implementation concerns in stencil computations for semiregular grids
(Colorado State University. Libraries, 2013) Stone, Andrew, author; Strout, Michelle Mills, advisor; Massey, Daniel, committee member; Pallickara, Shrideep, committee member; Randall, David, committee member
In atmospheric and ocean simulation programs, stencil computations occur on semiregular grids where subdomains of the grid are regular (i.e. stored in an array), but boundaries between subdomains connect in an irregular fashion. Implementations of stencils on semiregular grids often have grid connectivity details tangled with stencil computation code. When grid connectivity concerns tangle with stencil code it becomes difficult for programmers to modify the code. This is because any change made will have to account for grid connectivity. In this dissertation we introduce programming abstractions for the class of semiregular grids and describe a prototype Fortran 90+ library called GridWeaver that implements these abstractions. Implementing these abstractions requires determining the communication schedule given an orthogonal specification of the grid decomposition and solving nodes in the grid with a non-standard number of neighbors. We present solutions to these issues that work within the context of grids used in atmospheric and ocean simulations. We also show that to maintain the performance while still providing a separation of concerns, it is necessary for a source-to source translator to perform inlining between user code and the GridWeaver runtime library code. We present performance results for stencil computations extracted from the Parallel Ocean Program and Global Cloud-Resolving Model.
Open Access
Testing eddy compensation and eddy saturation in the Southern Ocean
(Colorado State University. Libraries, 2013) Jones, Daniel C., author; Ito, Takamitsu, advisor; Birner, Thomas, committee member; Lovenduski, Nicole, committee member; Randall, David, committee member; Tavener, Simon, committee member
The Southern Ocean (SO) is a unique and dynamic component of the climate system. Due in part to its cold temperatures and large surface area, the SO is an important region for the transfer of heat, momentum, and climatically relevant gases between the atmosphere and the interior ocean. The strong westerly winds above the SO help drive a powerful current (i.e. the Antarctic Circumpolar Current or ACC) that connects Earth's ocean basins in a global overturning circulation. In recent decades, these winds have strengthened and shifted poleward. Despite this change in surface forcing, no clear observational signal of the oceanic density structure's response has yet been detected. The eddy compensation hypothesis posits that changes in the direct wind-driven overturning circulation are balanced by changes in the eddy-induced meridional circulation, effectively rendering SO stratification insensitive to wind stress. The closely related (but not identical) eddy saturation hypothesis suggests that the ACC is also insensitive to increased wind stress, since additional energy ends up in the mesoscale eddy field instead of in the zonal mean circulation. In this work, we examine the viability of the eddy compensation and saturation hypotheses on interannual, decadal, and centennial timescales. Using a combination of theory and idealized numerical simulations, we show that it may take the Southern Ocean many decades to centuries to fully equilibrate with the world ocean following a change in wind stress. As such, it may be difficult to detect changes in isopycnal slope using the few decades of available observational data. We also explore the characteristics of eddy-driven interannual variability and examine how this variability may affect the decadal-scale adjustment of the global ocean. Our results suggest that departures from the eddy compensation regime may be important on decadal and centennial timescales, on which the interaction between regional Southern Ocean circulation and global ocean circulation is significant. As such, we suggest that Southern Ocean overturning circulation is likely to strengthen in response to recent and future climate change, with implications for the global carbon cycle and climate.
Open Access
The contribution of clouds to global surface temperature variability on monthly to decadal timescales
(Colorado State University. Libraries, 2022) Boehm, Chloe, author; Thompson, David W. J., advisor; Randall, David, committee member; McGrath, Daniel, committee member
Cloud radiative effects (CREs) have well documented impacts on the mean climate, and have recently been found to play a key role in climate variability in the tropics. This thesis expands on previous work to probe the role of CREs on extratropical surface temperature variability. The impact of CREs on climate variability is isolated using the 'cloud-locking' method run on the Max Planck Earth System Model. This method involves comparing the output from two climate simulations: one in which clouds are coupled to the atmospheric circulation, and another in which clouds are prescribed and thus decoupled from the flow. Results show that coupling between CREs and the atmospheric circulation leads to widespread increases in extratropical surface temperature variability, particularly over the North Atlantic and North Pacific. This work then explores on what timescales surface temperature variability is increased. In general, CREs play an increasingly large role in surface temperature variability at increasingly long timescales. Importantly, cloud-circulation coupling leads to enhanced decadal temperature variability of ~25–45% over most of the Northern Hemisphere oceans and ~10–15% over most of the land areas. Finally, using a simple expression for temperature variance in terms of the surface energy balance, the mechanisms driving these variability changes are identified. This variability enhancement derives from 'reddening' of surface temperature variability by cloud shortwave radiative effects. These results demonstrate the dominant effect that cloud-circulation coupling has on interannual and decadal temperature variability across much of the globe. This work has implications for the interpretation of observed decadal variability, and for the importance of cloud-circulation coupling in climate model simulations.
Open Access
The hydrometeorological sustainability of Miscanthus × giganteus as a biofuel crop in the US Midwest
(Colorado State University. Libraries, 2016) Roy, Gavin R., author; Kummerow, Christian, advisor; Randall, David, committee member; Barnes, Elizabeth, committee member; Niemann, Jeffrey, committee member; Peters-Lidard, Christa, committee member
Miscanthus × giganteus (M. × giganteus) is a dense, 3-5 m tall, productive perennial grass that has been suggested to replace corn as the principal source of biofuel for the US transportation industry. However, cultivating a regime of this water-intensive rhizomatous crop across the US Midwest may not be agronomically realistic if it is unable to survive years of low precipitation or extreme cold wintertime soil temperatures, both of which have previously killed experimental crops. The goal of this research was to use a third-generation land surface model (LSM) to provide a new assessment of the hypothetical biogeophysical sustainability of a regime of M. × giganteus across the US Midwest given that, for the first time, a robust and near-complete dataset over a large area of mature M. × giganteus was available for model validation. Modifications to the local hydrology and microclimate would necessarily occur in areas where M. × giganteus is adapted, but a switch to this biofuel crop can only occur where its intense growing season water usage (up to 600 mm) and wintertime soil temperature requirements (no less than -6° C) are feasibly sustainable without irrigation. The first step was to interpret the observed turbulent and ecosystem flux behavior over an extant area of mature M. × giganteus and replicate this behavior within the SiB3 third-generation LSM (Simple Biosphere Model, version 3). A new vegetation parameterization was developed in SiB3 using several previous empirical studies of M. × giganteus as a foundation. The simulation results were validated against a new, robust series of turbulent and ecosystem flux data taken over a four-hectare experimental crop of M. × giganteus in Champaign, IL, USA from 2011-2013. Wintertime mortality of M. × giganteus was subsequently assessed. It was proposed that areas with higher seasonal snowfall in the US Midwest may be favorable for M. × giganteus sustainability and expansion due to the significant insulating effect of snow cover. Observations of snow cover and air and soil temperatures from small experimental plots of M. × giganteus in Illinois, Wisconsin, and the lake effect snowbelt of southern Michigan were analyzed during several anomalously cold winters. While a large insulating effect was observed, shallow soil temperatures were still observed to drop below laboratory mortality temperature thresholds of M. × giganteus during periods of snow cover. Despite this, M. × giganteus often survived these low temperatures, and it is hypothesized that the rate of soil temperature decrease might play a role in wintertime rhizome survival. The domain was expanded in SiB3 to cover the US Midwest, and areas defined as cropland were replaced with the developed M. × giganteus surface parameterization. A 14-year uncoupled simulation was carried out and compared to an unmodified simulation in order to gauge the first-order hydrometeorological sustainability of a large-scale M. × giganteus regime in this area in terms of simulated productivity, evapotranspiration, soil water content, and wintertime cold soil temperature. It was found that M. × giganteus was biogeophysically sustainable and productive in a relatively small portion of the domain in southern Indiana and Ohio, consistent with a small set of previous studies and ultimately in disagreement with the theory that M. × giganteus could reliably replace corn in areas such as Illinois and Iowa as a profitable and sustainable biofuel crop.
Open Access
Tropical deep convection, entrainment, and dilution during the DYNAMO field campaign
(Colorado State University. Libraries, 2014) Hannah, Walter, author; Maloney, Eric, advisor; Randall, David, committee member; Johnson, Richard, committee member; Venayagamoorthy, Karan, committee member
This dissertation presents a study of outstanding questions in tropical meteorology relating to tropical deep convection, entrainment, and dilution. Much of the discussion in this study will focus on an important convectively-coupled phenomenon in the tropical atmosphere known as the Madden-Julian Oscillation (MJO), which is an eastward propagating atmospheric disturbance over the Indian and West Pacific Oceans that dominates the tropical variability on intraseasonal timescales (30-90 days). The MJO is most active during the Northern Hemisphere winter season and is characterized by alternating periods of enhanced and suppressed convective activity. A field campaign known as the "Dynamics of the MJO" (DYNAMO) was conducted in the boreal winter months from October 2011 through February 2012 to study the initialization of the MJO with in-situ observations. The first part of this study examines hindcast simulations of the first two MJO events during DYNAMO in a general circulation model (GCM). The model used for this is the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM5) version 5, which uses parameterized convection. In these simulations, an entrainment rate parameter is varied to test its effects on the representation of the MJO, following previous studies. Hindcast simulations with CAM5 reveal that the entrainment parameter can improve the representation of the MJO. However, analysis of the column integrated moist static energy (MSE) budget reveals that this improvement is the right answer for the wrong reason. CAM5 incorrectly enhances vertical MSE advection, which compensates for cloud radiative feedbacks that are too weak. A promising theory for the MJOs fundamental dynamics is that of a moisture mode. The gross moist stability (GMS) describes the ratio of advective MSE import to a measure of convective activity. Negative GMS, and specifically the vertical component of GMS (VGMS), is thought to be a necessary condition for the destabilization of a moisture mode. In CAM5, VGMS becomes negative when the entrainment parameter is increased, indicating that the model can more easily destabilize moisture modes. However, this is inconsistent with re-analysis data, which exhibits positive VGMS. The second part of the study examines hindcasts using the super-parameterized version of CAM5 (SP-CAM) that uses embedded cloud-resolving models (CRM) to explicitly simulate convection on the sub-grid scale. SP-CAM was used for these hindcast simulations because previous studies have shown this type of model can reproduce the MJO much better than conventional GCMs. SP-CAM hindcasts yield a more robust MJO representation than CAM5, as expected. SP-CAM has an interesting systematic drift away from the initial conditions that projects well on the Real-time Multivariate MJO index (RMM), which negatively impacts the RMM skill scores. Analysis of the column MSE budget shows that SP-CAM has more realistic cloud-radiative feedbacks when compared to CAM5. SP-CAM also has a bias towards stronger import by vertical MSE advection that is similar CAM5 and inconsistent with re-analysis data. VGMS in SP-CAM is also found to be negative, which is similar to CAM5 and inconsistent with re-analysis data. The results from the first part of this study highlight a paradox surrounding entrainment. Although, previous studies have shown that entrainment rates should be larger than typical values used in parameterizations, increasing the entrainment rate does not make global model simulations more realistic. This prompted a detailed investigation into entrainment processes in high-resolution CRM simulations. A series of simulations are conducted where deep convection is initiated with a warm humid bubble. The bubble simulations are compared to a more realistic field of deep convection driven by forcing derived from the DYNAMO northern sounding array data. Entrainment and detrainment are found to be associated with toroidal circulations, consistent with recent studies. Analysis of the directly measured fractional entrainment rates does support an inverse relationship between entrainment and cloud radius, as is often assumed in simple models of deep convection. A method for quantifying the dilution by entrainment is developed and tested. Dilution and entrainment are generally not synonymous, but dilution is found to have a weak inverse relationship to cloud core radius. Sensitivity experiments show that entrainment and total water dilution are enhanced with environmental humidity is increased, contrary to the assumptions of some parameterizations. More vigorous convection in a more humid environment is better explained by a reduction of buoyancy dilution. An additional sensitivity experiment shows that entrainment and dilution are enhanced when convection is organized by the presence of vertical wind shear. The enhanced dilution is associated with entrainment of drier air on average.
Open Access
Using neural networks to learn the forced response of the jet-stream to tropospheric temperature tendencies
(Colorado State University. Libraries, 2023) Connolly, Charlotte, author; Barnes, Elizabeth, advisor; Randall, David, committee member; Anderson, Chuck, committee member
Two distinct features of anthropogenic climate change, warming in the tropical upper troposphere and warming at the Arctic surface, have competing effects on the midlatitude jet-stream's latitudinal position, often referred to as a "tug-of-war". Many previous studies have investigated the strength of the jet response to these thermal forcings, as well as many others, and have shown that the jet response is sensitive to model type, season, initial atmospheric conditions, and the shape and magnitude of the forcing. Here, we explore the potential for training a convolutional neural network (CNN) on internal variability alone to examine possible nonlinear jet responses to a variety of thermal forcings. Our approach thus makes use of the fluctuation-dissipation theorem, which relates the internal variability of a system to its forced response. We train a CNN on data from a long control run of the CESM dry dynamical core, thereby providing it with ample data to learn relationships between the temperature forcing and the jet movement over the coming days. Then, we use the CNN to explore the jet response to a wide range of tropospheric temperature tendencies. Despite being trained on the jet-stream response to internal variability alone, we show that the trained CNN is able to skillfully predict the nonlinear response of the jet-stream to sustained external forcing. The trained CNN provides a quick method for exploring the jet-stream sensitivity to a wide range of tropospheric temperature tendencies and, considering that this method can likely be applied to any model with a long control run, could lend itself useful for early stage experiment design.
Open Access
Vertically resolved weak temperature gradient analysis of the Madden-Julian Oscillation
(Colorado State University. Libraries, 2017) Wolding, Brandon, author; Maloney, Eric, advisor; Randall, David, committee member; van den Heever, Susan, committee member; Kiladis, George, committee member; Ham, Jay, committee member
Interactions between moisture, convection, and large-scale circulations are thought to play an important role in destabilizing the Madden-Julian Oscillation (MJO). A simplified framework for understanding such interactions is developed, building upon the work of Chikira (2014). Tropical weak temperature gradient (WTG) balance is used to diagnose intraseasonal variations in large-scale vertical velocity from variations in apparent heating, allowing intraseasonal variations in large-scale vertical moisture advection to be decomposed into contributions from various apparent heating processes (e.g. radiative heating, microphysical processes). The WTG diagnosis captures the vertical structure and magnitude of large-scale vertical velocity and vertical moisture advection with exceptional accuracy throughout the free troposphere. Moisture and moisture variance budgets are used to investigate the MJO in ERA-interim (ERAi) reanalysis and the Superparameterized Community Earth System Model (SP-CESM). Moisture budgets indicate that, during the enhanced phase of the MJO, anomalous moistening by large-scale vertical moisture advection exceeds anomalous drying by microphysical processes and sub-grid scale (SGS) eddy fluxes, such that the net effect of these large and opposing processes (hereafter the column process) is to further moisten regions that are anomalously moist. Moisture variance budgets indicate that the column process helps grow moisture variance, acting to destabilize the MJO. Horizontal advective damping of moisture variance, associated with the modulation of higher frequency convective variability on intraseasonal timescales, acts to stabilize the MJO. The vertically resolved WTG balance framework is used to assess the contribution various apparent heating processes make to the column process, and its ability to destabilize the MJO. Intraseasonal variations in longwave radiative heating enhance variations in large-scale vertical moisture advection at low and mid levels, strongly supporting destabilization of the MJO in both ERAi and SP-CESM. The effect of convection alone (i.e. without radiative and surface flux feedbacks) is to weakly grow moisture variance in SP-CESM, and weakly damp moisture variance in ERAi, suggesting that the MJO is unrealistically unstable in the former. Surface flux feedbacks appear to play a more important role in destabilizing the real world MJO. Moisture variance budget analysis of periods of weak, moderate, and strong MJO activity suggests that changes in the vertical structure of apparent heating do not play a dominant role in limiting the amplitude of the MJO in SP-CESM in the current climate. WTG balance provides a useful framework for investigating how the MJO, and its impacts, may change as the climate system warms. Two simulations of SP-CESM, one at pre-industrial levels of CO2 (280 ppm, hereafter PI) and one where CO2 levels have been quadrupled (1120 ppm, hereafter 4xCO2), were analyzed. MJO convective variability increases considerably in the 4xCO2 simulation, a consequence of more favorable mean state moist thermodynamic conditions. A steepened mean state vertical moisture gradient allows MJO convective heating to drive stronger variations in large-scale vertical moisture advection, helping to support enhanced MJO convective variability in the 4xCO2 simulation. The dynamical response to MJO convective heating weakens in the warmer climate, a result of increased tropical static stability. One consequence of this weakened dynamical response is that the MJO's ability to influence the extratopics, which is closely tied to the strength of its associated divergence, is reduced considerably in the 4xCO2 simulation.