Browsing by Subject "Numerical modeling"

Now showing 1 - 4 of 4
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    Constraining Regional Evapotranspiration in the Upper Midwestern United States Using In Situ Observations and Numerical Modeling
    (2023-08) Xiao, Ke
    Evapotranspiration (ET) is a critical component in the global water cycle and water resource management. The Upper Midwestern United States (US), a major agricultural production region with large areas of lake and cropland, is facing challenges related to extreme variations in precipitation, increasing irrigation water usage, and large fluctuations in water budgets. Lake evaporation and cropland ET represent two significant components of the regional water budget. However, regional ET estimates from these two sources contain large uncertainties due to their complex interactions with atmospheric conditions (e.g. precipitation) and land surface processes (e.g. ice/plant phenology, atmospheric demand), affected by climate change and anthropogenic activities. This dissertation combines in situ observations and modeling to better constrain the regional ET, focusing on lake evaporation, local water recycling, and cropland ET in the Upper Midwest US.Evaporation from a temperate closed-basin lake, White Bear Lake (WBL), was estimated using the eddy covariance method and an optimized lake model CLM4-LISSS. The annual evaporation totals from 2014 to 2016 were 559 ± 22 mm, 779 ± 81 mm, and 766 ± 11 mm, respectively. The combined effects of smaller average daily evaporation and a shorter ice-free season caused lower evaporation in 2014. Retrospective analyses indicated that WBL evaporation increased by 3.8 mm/year during 1979–2016, which was driven by increased wind speed and lake-surface vapor pressure gradient. Lake evaporation is expected to increase by 1.4 mm/year from 2017 to 2100 under the business-as-usual greenhouse gas emission scenario, largely driven by extended ice-free periods. These results imply that the water level of WBL is closely coupled to evaporation and consequently impacted by the large-scale synoptic and climatic conditions. The contribution of ET to regional precipitation, known as “local water recycling”, is a key process in the water cycle. An idealized two-layer equilibrium planetary boundary layer model was coupled with a stable isotope module that included HDO and H218O in water to constrain the local water recycling ratio (LRR) by isotope observations. The regional value of the summer LRR was estimated to be 0.29 ± 0.12. The summer LRR values for the years 2006–2010 varied between 0.17 and 0.36. The smallest value of LRR was in 2008 which corresponded to a drought year. Cropland has likely changed the regional LRR by −7.6 to 19.5% under different pre-agriculture land cover scenarios. The model also implies that local water recycling is expected to be weakened under drought conditions, but it will be enhanced if irrigation is applied more intensely. In humid continental climates, forecasting cropland ET is challenging due to the variable precipitation and plant phenology. An ET forecast system (ETool) was built upon the Weather Research and Forecasting (WRF) model with the Noah land surface scheme to forecast the weekly ET at 3-km resolution in Minnesota, US. The near real-time leaf area index (LAI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) product was used in ETool to improve the representation of plant phenology. At a cropland site, the LAI improvement led to a 17.7% reduction in the weekly ET forecast bias, with an R2 value of 0.82 and a root-mean-square error of 0.64 mm/day. Using the predicted difference between precipitation and ET, ETool can inform irrigation scheduling to balance the tradeoff between safeguarding yields and conserving water usage. Collectively, this dissertation also revealed the feedback processes between ET and climate under the influence of anthropogenic activities in the Upper Midwest US. As the climate continues to warm, the regional lake evaporation is expected to increase with lengthening ice-free periods. The regional cropland ET and local water recycling are expected to be weakened due to an increased likelihood of drought events. However, irrigation is anticipated to increase in response to the more frequent drought events, which will conversely enhance ET and local water recycling. Furthermore, more intense groundwater usage and greater fluctuations in lake water levels within the region are expected with increased use of irrigation.
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    Modeling marine dissolved organic carbon response to climate change
    (2022-06) Gilchrist, Maya
    At 662 Pg C, the marine reservoir of dissolved organic carbon (DOC) represents the ocean’s largest pool of reduced carbon, holding over 200 times the carbon contained in marine biomass and rivaling the atmospheric carbon inventory. Recent work has suggested that the size of the DOC reservoir may respond to future changes in sea temperatures and global overturning circulation strength. Moreover, mobilization of marine DOC has been implicated in several paleoclimate change events. Despite these suggestions, however, the temporal dynamics of the marine DOC reservoir are poorly understood, and previous carbon cycle modeling work has generally assumed this reservoir to be static. In this study, we utilized an Earth system model of intermediate complexity calibrated with respect to DOC observations to assess the response of the marine DOC reservoir to climate changes representative of the last glacial maximum climate state, reduced ocean overturning circulation strength, and future warming scenarios. Our results indicate that the marine DOC reservoir is mobile in response to climate forcings and may shrink or expand depending on changes in its production rate. Moreover, variability in the ocean’s DOC reservoir was directly linked to changes in atmospheric CO2 concentrations, explaining a significant portion of CO2 drawdown or ventilation by the ocean across three sets of climate change experiments. These findings point to an integral role of marine DOC in the global carbon cycle and indicate that consideration of this reservoir is critical in improving our understanding of the connection between ocean processes and global climate of the past, present, and future.
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    Numerical Modeling of the Metal Cutting Process in the Plasma Arc Cutting
    (2015-11) Park, Hunkwan
    The process of cutting metal with a plasma arc cutting tool is investigated and discussed. Focus is on the metal cutting process at the inside surface of the kerf. This is an important region that is not well documented due to the difficulty of experiments and the complexity of computation needed to characterize this process. In the present work, a three-dimensional numerical simulation using a plasma model combined with a melting process model is conducted and results are discussed, leading to a better understanding of the physical phenomena within the kerf region of a commercial plasma arc cutting tool. The modeling includes three different phenomena: 1) the plasma jet flow, 2) the Volume of Fluid (VoF) method in identify the gas to molten metal interface, and 3) the phase change model for computing the melting process. The model is implemented in the open source CFD software, OpenFOAM. Thermodynamic and transport properties, calculated by kinetic theory of gases and statistical mechanics, are implemented for accurate simulation in the high temperature regions. The simulation results show the transient cutting process including the physical phenomena for melting of the work piece as well as the plasma flow. The simulated kerf shape is compared to measured kerf under same operations. Additionally, the temperature, velocity, and current density distributions are discussed to understand the plasma characteristics during the cutting process. In an attempt to make a more reasonable kerf shape, the swirl component of the jet, the surface tension and the phase change model are investigated for improvement and discussed. Effects of metal vapor and oxidation reaction are also discussed. This work is a first attempt simulation of the plasma flow, melting, and molten metal flow in the plasma arc cutting process. As the model approaches physical reality, it gives increasingly useful insight into the relationships among operating conditions, providing very helpful directions to improve performance, and providing useful data for designing the plasma arc cutting process.
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    Supporting Data for "A novel machine learning method for accelerated modeling of the downwelling irradiance field in the upper ocean"
    (2022-04-27) Hao, Xuanting; Shen, Lian; haoxx081@umn.edu; Hao, Xuanting; University of Minnesota Fluid Mechanics Lab
    The training data are generated from the Monte Carlo simulation of oceanic irradiance field. They can be used for training a neural network that significantly accelerates the prediction of irradiance in the upper ocean.