Atmospheric & Oceanic Science Research Works

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Formerly known as the Department of Meteorology.


Recent Submissions

Now showing 1 - 5 of 11
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    Assimilation of NASA's Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF-Hydro System
    (Wiley, 2022-03-14) Lahmers, Timothy M.; Kumar, Sujay V.; Rosen, Daniel; Dugger, Aubrey; Gochis, David J.; Santanello, Joseph A.; Gangodagamage, Chandana; Dunlap, Rocky
    The NASA LIS/WRF-Hydro system is a coupled modeling framework that combines the modeling and data assimilation (DA) capabilities of the NASA Land Information System (LIS) with the multi-scale surface hydrological modeling capabilities of the WRF-Hydro model, both of which are widely used in both operations and research. This coupled modeling framework builds on the linkage between land surface models (LSMs), which simulate surface boundary conditions in atmospheric models, and distributed hydrologic models, which simulate horizontal surface and sub-surface flow, adding new land DA capabilities. In the present study, we employ this modeling framework in the Tuolumne River basin in central California. We demonstrate the added value of the assimilation of NASA Airborne Snow Observatory (ASO) snow water equivalent (SWE) estimates in the Tuolumne basin. This analysis is performed in both LIS as an LSM column model and LIS/WRF-Hydro, with hydrologic routing. Results demonstrate that ASO DA in the basin reduced snow bias by as much as 30% from an open-loop (OL) simulation compared to three independent datasets. It also reduces downstream streamflow runoff biases by as much as 40%, and improves streamflow skill scores in both wet and dry years. Analysis of soil moisture and evapotranspiration (ET) also reveals the impacts of hydrologic routing from WRF-Hydro in the simulations, which would otherwise not be resolved in an LSM column model. By demonstrating the beneficial impact of SWE DA on the improving streamflow forecasts, the article outlines the importance of such observational inputs for reservoir operations and related water management applications.
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    A CloudSat and CALIPSO-based evaluation of the effects of thermodynamic instability and aerosol loading on Amazon Basin deep convection and lightning
    (2023-08-14) Allen, Dale
    The Amazon Basin, which plays an important role in the carbon and water cycle, is under stress due to changes in climate, agricultural practices, and deforestation. The Basin includes a rainforest in the northwest and a mix of deforested areas, savannah-type vegetation, and agriculture in the southeast. The effects of instability and aerosol loading on thunderstorms in the Basin (75-45° W, 0-15° S) were examined during mid-August through mid-December, a period with large variations in aerosols, intense convective storms, and plentiful flashes. The analysis used measurements of radar reflectivity, ice water content (IWC), and aerosol type from instruments aboard the CloudSat and CALIPSO satellites, flash rates from the ground-based STARNET network, and aerosol optical depth (AOD) from a surface network and a meteorological re-analysis. After controlling for convective available potential energy (CAPE), a measure of instability, it was found that thunderstorms that developed under dirty (high-AOD) conditions were approximately 1.5 km deeper, had 50% more IWC, and more than two times as many flashes as storms that developed under clean (low-AOD) conditions. Flash rates were also found to be larger during periods when smoke rather than dust was common in the lower troposphere, likely because these periods were less stable.
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    Wood Vault: remove atmospheric CO2 with trees, store wood for carbon sequestration for now and as biomass, bioenergy and carbon reserve for the future
    (Springer Nature, 2022-04-01) Zeng, Ning; Hausmann, Henry
    Wood harvesting and storage (WHS) is a hybrid Nature-Engineering combination method to combat climate change by harvesting wood sustainably and storing it semi-permanently for carbon sequestration. To date, the technology has only been purposefully tested in small-scale demonstration projects. This study aims to develop a concrete way to carry out WHS at large-scale. We describe a method of constructing a wood storage facility, named Wood Vault, that can bury woody biomass on a mega-tonne scale in specially engineered enclosures to ensure anaerobic environments, thus preventing wood decay. The buried wood enters a quasi-geological reservoir that is expected to stay intact semi-permanently. Storing wood in many environments is possible, leading to seven versions of Wood Vault: (1) Burial Mound (Tumulus or Barrow), (2) Underground (Pit, Quarry, or Mine), (3) Super Vault, (4) Shelter, (5) AquaOpen or AquaVault with wood submerged under water, (6) DesertOpen or DesertVault in dry regions, (7) FreezeVault in cold regions such as Antarctica. Smaller sizes are also possible, named Baby Vault. A prototype Wood Vault Unit (WVU) occupies 1 hectare (ha, 100 m by 100 m) of surface land, 20 m tall, stores up to 100,000 m3 of wood, sequestering 0.1 MtCO2. A 1 MtCO2 y−1 sequestration rate can be achieved by collecting currently unused wood residuals (WR) on an area of 25,000 km2, the size of 10 typical counties in the eastern US, corresponding to an average transportation distance of less than 100 km. After 30 years of operation, such a Wood Vault facility would have sequestered 30 MtCO2, stored in 300 WVUs, occupying a land surface of 300 ha. The cost is estimated at $10–50/tCO2 with a mid-point price of $30/tCO2. To sequester 1 GtCO2 y−1, wood can be sourced from currently unexploited wood residuals on an area of 9 Mkm2 forested land (9 million square kilometers, size of the US), corresponding to a low areal harvesting intensity of 1.1 tCO2 ha−1 y−1. Alternatively, giga-tonne scale carbon removal can be achieved by harvesting wood at a medium harvesting intensity of 4 tCO2 ha−1 y−1 on 3 Mkm2 of forest (equivalent to increasing current world wood harvest rate by 25%), or harvest on 0.8 Mkm2 forest restored from past Amazon deforestation at high harvest intensity, or many combinations of these and other possibilities. It takes 1000 facilities as discussed above to store 1 GtCO2 y−1, compared to more than 6000 landfills currently in operation in the US. After full closure of a Wood Vault, the land can be utilized for recreation, agriculture, solar farm, or agrivoltaics. A more distributed small operator model (Baby Vault) has somewhat different operation and economic constraints. A 10 giga-tonne sequestration rate siphons off only 5% of total terrestrial net primary production, thus possible with WHS, but extreme caution needs to be taken to ensure sustainable wood sourcing. Our technical and economic analysis shows that Wood Vault can be a powerful tool to sequester carbon reliably, using a variety of wood sources. Most pieces of the technology already exist, but they need to be put together efficiently in practice. Some uncertainties need to be addressed, including how durability of buried wood depends on detailed storage methods and burial environment, but the science and technology are known well enough to believe the practicality of the method. The high durability, verifiability and low-cost makes it already an attractive option in the current global carbon market. Woody biomass stored in Wood Vaults is not only a carbon sink to combat current climate crisis, but also a valuable resource for the future that can be used as biomass/bioenergy and carbon supply. The quantity of this wood utilization can be controlled carefully to maintain a desired amount of CO2 in the atmosphere to keep the Earth’s climate from diving into the next ice age, acting as a climate thermostat. The CO2 drawdown time is on the order of 100 years while the ramp-up time is a decade. A sense of urgency is warranted because the CO2 removal rate is limited by biosphere productivity, thus delayed action means a loss of opportunity. In conclusion, WHS provides a tool for managing our Earth system, which will likely remain forever in the Anthropocene.
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    Full Results Accompanying A Machine Learning Examination of Hydroxyl Radical Differences Among Model Simulations for CCMI-1
    (2020) Nicely, Julie M.; Duncan, Bryan N.; Hanisco, Thomas F.; Wolfe, Glenn M.; Salawitch, Ross J.; Deushi, Makoto; Haslerud, Amund S.; Jöckel, Patrick; Josse, Béatrice; Kinnison, Douglas E.; Klekociuk, Andrew; Manyin, Michael E.; Marécal, Virginie; Morgenstern, Olaf; Murray, Lee T.; Myhre, Gunnar; Oman, Luke D.; Pitari, Giovanni; Pozzer, Andrea; Quaglia, Ilaria; Revell, Laura E.; Rozanov, Eugene; Stenke, Andrea; Stone, Kane; Strahan, Susan; Tilmes, Simone; Tost, Holger; Westervelt, Daniel M.; Zeng, Guang
    The hydroxyl radical (OH) plays critical roles within the troposphere, such as determining the lifetime of methane (CH4), yet is challenging to model due to its fast cycling and dependence on a multitude of sources and sinks. As a result, the reasons for variations in OH and the resulting methane lifetime, both between models and in time, are difficult to diagnose. We apply a neural network (NN) approach to address this issue within a group of models that participated in the Chemistry-Climate Model Initiative (CCMI). Analysis of the historical specified dynamics simulations performed for CCMI indicates that the primary drivers of methane lifetime differences among ten models are the flux of UV light to the troposphere (indicated by the photolysis frequency JO1D), the mixing ratio of tropospheric ozone (O3), the abundance of nitrogen oxides (NOx=NO+NO2), and details of the various chemical mechanisms that drive OH. Water vapor, carbon monoxide (CO), the ratio of NO:NOx, and formaldehyde (HCHO) explain moderate differences in methane lifetime, while isoprene, methane, the photolysis frequency of NO2 by visible light (JNO2), overhead ozone column, and temperature account for little-to-no model variation in methane lifetime. We also apply the NNs to analysis of temporal trends in OH from 1980 to 2015. All models that participated in the specified dynamics historical simulation for CCMI demonstrate a decline in methane lifetime during the analysed timeframe. The significant contributors to this trend, in order of importance, are tropospheric O3, JO1D, NOx, and H2O, with CO also causing substantial interannual variability in OH burden. Finally, the identified trends in methane lifetime are compared to calculated trends in the tropospheric mean OH concentration from previous work, based on analysis of observations. The comparison reveals a robust result for the effect of rising water vapor on OH and methane lifetime, imparting an increasing and decreasing trend of about 0.5 % per decade, respectively. The responses due to NOx, ozone column, and temperature are also in reasonably good agreement between the two studies.
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    Climate model shows large-scale wind and solar farms in the Sahara increase rain and vegetation
    (Science, 2018-09-07) Li, Yan; Kalnay, Eugenia; Motesharrei, Safa; Rivas, Jorge; Kucharski, Fred; Kirk-Davidoff, Daniel; Bach, Eviatar; Zeng, Ning
    Wind and solar farms offer a major pathway to clean, renewable energies. However, these farms would significantly change land surface properties, and, if sufficiently large, the farms may lead to unintended climate consequences. In this study, we used a climate model with dynamic vegetation to show that large-scale installations of wind and solar farms covering the Sahara lead to a local temperature increase and more than a twofold precipitation increase, especially in the Sahel, through increased surface friction and reduced albedo. The resulting increase in vegetation further enhances precipitation, creating a positive albedo–precipitation–vegetation feedback that contributes ~80% of the precipitation increase for wind farms. This local enhancement is scale dependent and is particular to the Sahara, with small impacts in other deserts.