A5008739354- Climate variability and models
- Meteorological Phenomena and Simulations
- Cryospheric studies and observations
- Atmospheric and Environmental Gas Dynamics
- Geology and Paleoclimatology Research
- Astro and Planetary Science
- Hydrological Forecasting Using AI
- Tropical and Extratropical Cyclones Research
- Flood Risk Assessment and Management
- Hydrology and Watershed Management Studies
- Oceanographic and Atmospheric Processes
- Planetary Science and Exploration
- Atmospheric chemistry and aerosols
- Stellar, planetary, and galactic studies
- Climate change and permafrost
- Astrophysics and Star Formation Studies
- Precipitation Measurement and Analysis
- Landslides and related hazards
- Arctic and Antarctic ice dynamics
- Granular flow and fluidized beds
- Groundwater flow and contamination studies
- Geotechnical Engineering and Soil Mechanics
- Ecosystem dynamics and resilience
- Statistical Methods and Applications
- Environmental and Agricultural Sciences
University of California, Los Angeles
2018-2024
Pacific Northwest National Laboratory
2023
Stony Brook University
2023
State University of New York
2023
Scripps Institution of Oceanography
2023
NSF National Center for Atmospheric Research
2023
Lawrence Berkeley National Laboratory
2023
University of California, San Diego
2023
University of California, Davis
2023
University of California, Berkeley
2023
Abstract. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is an international collaborative effort to understand and quantify the uncertainties in atmospheric river (AR) science based on detection algorithm alone. Currently, there are many AR identification tracking algorithms literature with a wide range of techniques conclusions. ARTMIP strives provide community information different methodologies guidance most appropriate for given question or region interest. All...
Abstract Atmospheric rivers (ARs) are now widely known for their association with high‐impact weather events and long‐term water supply in many regions. Researchers within the scientific community have developed numerous methods to identify track of ARs—a necessary step analyses on gridded data sets, objective attribution impacts ARs. These different been answer specific research questions hence use criteria (e.g., geometry, threshold values key variables, time dependence). Furthermore,...
The intensification of extreme precipitation under anthropogenic forcing is robustly projected by global climate models, but highly challenging to detect in the observational record. Large internal variability distorts this signal. Models produce diverse magnitudes response forcing, largely due differing schemes for parameterizing subgrid-scale processes. Meanwhile, multiple datasets daily exist, developed using varying techniques and inhomogeneously sampled data space time. Previous...
Abstract Dynamical downscaling remains a powerful tool for studying regional climate processes, and the genesis of high‐resolution historical future data. This technique is particularly important over areas complex terrain, such as western United States (WUS), where global models are especially limited in representing climate. After identifying suite WRF options that best simulate snow precipitation an average water year (2010) WUS, we evaluate performance dynamically downscaled European...
Abstract Polarization surrounding bias correction (BC) in creating climate projections arises from its lack of physicality. Here, we perform and analyze 18 dynamical downscaling simulations (with without BC) to better understand the physical impacts BC, applied before downscaling, on regional output across western United States. Without downscaled precipitation is systematically unrealistically wet biased compared a hierarchy observationally based datasets over 1980–2014 period due cascading...
Abstract. Predicting future climate change over a region of complex terrain, such as the western United States (US), remains challenging due to low resolution global models (GCMs). Yet extremes recent years in this region, floods, wildfires, and drought, are likely intensify further warms, underscoring need for high-quality high-resolution predictions. Here, we present an ensemble dynamically downscaled simulations US from 1980–2100 at 9 km grid spacing, driven by 16 latest-generation GCMs....
Abstract In the coastal mountains of western North America, most extreme precipitation is associated with atmospheric rivers (ARs), narrow bands moisture originating in tropics. Here we quantify how interannual variability influences snowpack United States observations and a model. We simulate historical climate Model for Prediction Across Scales (MPAS) physics from Community Atmosphere Model, version 5 [CAM5 (MPAS-CAM5)], using prescribed sea surface temperatures. global variable-resolution...
* CURRENT AFFILIATIONS: T. A. O'Brien—Earth and Atmospheric Sciences, Indiana University, Bloomington, Indiana; Patricola—Geological Iowa State Ames, Iowa; J. O'Brien—National Center for Research, Boulder, Colorado© 2020 American Meteorological Society. For information regarding reuse of this content general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).Corresponding author: Travis O'Brien, obrienta@iu.edu
Abstract In this study, we calibrate a regional climate model’s (RCM) underlying land surface model (LSM). addition to providing realistic representation of runoff across the hydroclimatically diverse western United States, is done take advantage RCM’s ability physically resolve meteorological forcing data in ungauged regions, and prepare calibrated hydrologic for tight coupling, or represent surface–atmosphere interactions, with RCM. Specifically, use 9-km resolution dataset from fifth...
Abstract The Colorado River Basin is an important natural resource for the semi‐arid southwestern United States (US), where it provides water to more than 40 million people. While nearly 1.5°C of anthropogenic warming has occurred across this region from 1880s 2021, climate models show little agreement in precipitation change during same historical period, with no trend mean latest (sixth) generation Global Climate Models. As such, here we focus on how CO 2 increase and associated over...
Abstract Dynamical downscaling is a crucial process for providing regional climate information broad uses, using coarser-resolution global models to drive higher-resolution simulations. The pool of (GCMs) the fields needed dynamical has increased from previous generations Coupled Model Intercomparison Project (CMIP). However, with limited computational resources, need prioritizing GCMs subsequent studies remains. GCM selection should focus on evaluating processes relevant boundary conditions...
Abstract. The presence of light-absorbing aerosol particles deposited on arctic snow and sea ice influences the surface albedo, causing greater shortwave absorption, warming, loss ice, lowering albedo further. Community Earth System Model version 1 (CESM1) now includes radiative effects in land itself. We investigate model response to deposition black carbon dust both ice. For these purposes we employ a slab ocean CESM1, using Atmosphere 4 (CAM4), run equilibrium for year 2000 levels CO2...
Abstract In climate science and applications, the term “metric” is used to describe distillation of complex, multifaceted evaluations summarize overall quality a model simulation, or other data product, and/or as means quantify some response change. Metrics provide insights into fidelity processes outcomes from models can assist with both differentiating models' representation variables informing whether are “fit for purpose.” also valuable reference point co‐production knowledge between...
Abstract Localized projections of 21st‐century hydroclimate variables obtained from downscaling Global Climate Model (GCM) output are central to informing regional impact assessments and infrastructure planning. Regional GCM biases can be significant and, for dynamical downscaling, addressed either before (a priori) or after posteriori) downscaling. However, a priori bias correction (APBC) has generally unexplored effects on climate change signals. Here we analyze dynamically downscaled...
We present the results of a HST WFPC2 search for substellar companions to members star-forming cluster IC 348. The detection limits low-mass stars and brown dwarfs in PC images are dm_791=0, 2.5, 5.5 at separations 0.05", 0.1", 0.3", respectively, which correspond M_2/M_1=1, 0.3, 0.1 15, 30, 90 AU. Meanwhile, heavily saturated solar-mass primaries WFC images, dm_791=0 6 (M_2/M_1=1 0.04) 0.2" 0.4". sky limiting magnitude m_791~26 large from primary corresponds mass ~0.006 M_sun. For two...
Abstract The serial occurrence of atmospheric rivers (ARs) along the US West Coast can lead to prolonged and exacerbated hydrologic impacts, threatening flood‐control water‐supply infrastructure due soil saturation diminished recovery time between storms. Here a statistical approach for quantifying subseasonal temporal clustering among extreme events is applied 41‐year (1979–2019) wintertime AR catalog across western United States (US). Observed occurrence, compared against randomly...
Abstract. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is an international collaborative effort to understand and quantify the uncertainties in atmospheric river (AR) science based on detection algorithm alone. Currently, there are many AR identification tracking algorithms literature with a wide range of techniques conclusions. ARTMIP strives provide community information different methodologies guidance most appropriate for given question or region interest. All...
Abstract How do ocean initial states impact historical and future climate projections in Earth system models? To answer this question, we use the 50-member Canadian System Model (CanESM2) large ensemble, which individual ensemble members are initialized using a combination of different oceanic atmospheric microperturbations. We show that global heat content anomalies associated with states, particularly differences deep due to drift, persist from initialization at year 1950 through end...
We present experimental measurements of a granular slope under horizontal vibration. use optical particle tracking to measure the motion surface beads as fails. find that for all but largest inclination angles, initial bead leads strengthening rather than an avalanche. The is usually intermittent and evolves differently different preparations, rates increase in vibration amplitude. When specific criterion chosen define failure, Coulomb friction model adequately describes average acceleration...
The 3rd ARTMIP Workshop What: Over 30 participants from multiple universities and research insititutions met to discuss new results the Atmospheric River Tracking Method Intercomparison Project. Where: Lawrence Berkeley National Lab, Berkeley, CA, USA When: 16-18 October 2019
Abstract Because of internal variability in both the real‐world and global climate models, it is unclear whether disagreement between models observations reflects true systematic differences, or different phasing short observational period. Here, we address this issue through an examination moderate‐to‐heavy precipitation large ensembles models. We find that model inconsistency with a product lowest for extratropical northern hemisphere winter. The systematically greater southern winter, but...
Abstract Internal variability in the climate system can contribute substantial uncertainty projections, particularly at regional scales. be quantified using large ensembles of simulations that are identical but for perturbed initial conditions. Here we compare methods quantifying internal variability. Our study region spans west coast North America, which is strongly influenced by El Niño and other large‐scale dynamics through their contribution to Using a statistical framework...
Abstract The hydrologic cycle in California is strongly influenced by wet‐season (November–April) precipitation. Here, we demonstrate the existence of an influential mode North Pacific atmospheric pressure variability that regulates precipitation over both northern and southern California. This mode, named as “California mode” (CPM), statistically distinct from other well‐known modes such Pacific‐North American pattern. In addition to controlling mean precipitation, positive days CPM...
Abstract. Predicting future climate change over a region of complex terrain, such as the western United States (U.S.), remains challenging due to low resolution global models (GCMs). Yet extremes recent years in this region, floods, wildfires, and drought, are likely intensify further warms, underscoring need for high-quality predictions. Here, we present an ensemble dynamically downscaled simulations U.S. from 1980–2100 at 9-km grid spacing, driven by sixteen latest-generation GCMs. This...
A radiative‐conductive balance calculation is presented to predict dust temperatures in the Mars atmosphere and evaluate assumption that gas are thermal equilibrium. Mie theory used calculate absorption scattering properties of dust, important for heating by sunlight; neglected treatment infrared emission grains. Besides radiating infrared, grains cool via collisions with molecules, at a rate proportional density. We find equilibrium atmospheric near surface. At predictable pressure, which...