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Huang, Xingying

Publications and source records attributed to Huang, Xingying.

13 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Examining Tropical Convection Features at Storm-Resolving Scales Over the Maritime Continent Region

Global Storm Resolving Models (GSRMs) provide a way to understand weather and climate events across scales for better-informed climate impacts. In this work, we apply the recently developed and validated CAM (Community Atmosphere Model)—MPAS (Model for Prediction Across Scales) modeling framework, based on the open-source Community Earth System Model (CESM2), to examine the tropical convection features at the storm resolving scale over the Maritime Continent region at 3 km horizontal spacing. We target two global numerical experiments during the winter season of 2018 for comparison with observation in the region. Here we focus on the investigation of the representations of the convective systems, precipitation statistics, and tropical cyclone behaviors. We found that regional-refined experiments show more accurate precipitation distributions, diurnal cycles, and better agreement with observations for tropical cyclone features in terms of intensity and strength statistics. We expect the exploration of this work will further advance the development and use of the storm-resolving model in precipitation predictions across scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Enhancing Extreme Precipitation Predictions With Dynamical Downscaling: A Convection‐Permitting Modeling Study in Texas and Oklahoma

Precipitation in the Southern Plains of the United States is relatively well depicted by the Community Earth System Model (CESM). However, despite its ability to capture seasonal mean precipitation anomalies, CESM consistently underestimates extreme pluvial and drought events, rendering it an insufficient tool for extending simulation lead times for exceptional events, such as the abnormally dry May 2011, which helped drive Texas into its worst period of drought in more than a century, and the abnormally wet May 2015, which led to widespread flooding in that state. Ensemble‐based regional climate experiments are completed for the two extreme years using Weather Research and Forecasting model (WRF) and downscaled from CESM. WRF simulations are at convection‐permitting grid resolution for improved physical representation of simulated precipitation over the Southern Great Plains. By integrating convection‐permitting models (CPMs) into each individual member of a CESM ocean data assimilation ensemble, this study demonstrates that high‐resolution dynamical downscaling can improve model skillfulness at capturing these two events and is thus a potentially useful tool for forecasting extremely high and extremely low precipitation events at subseasonal or even seasonal lead times.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Ensemble Spread Behavior in Coupled Climate Models: Insights From the Energy Exascale Earth System Model Version 1 Large Ensemble

AbstractAssessing uncertainty in future climate projections requires understanding both internal climate variability and external forcing. For this reason, single‐model initial condition large ensembles (SMILEs) run with Earth System Models (ESMs) have recently become popular. Here we present a new 20‐member SMILE with the Energy Exascale Earth System Model version 1 (E3SMv1‐LE), which uses a “macro” initialization strategy choosing coupled atmosphere/ocean states based on inter‐basin contrasts in ocean heat content (OHC). The E3SMv1‐LE simulates tropical climate variability well, albeit with a muted warming trend over the twentieth century due to overly strong aerosol forcing. The E3SMv1‐LE's initial climate spread is comparable to other (larger) SMILEs, suggesting that maximizing inter‐basin ocean heat contrasts may be an efficient method of generating ensemble spread. We also compare different ensemble spread across multiple SMILEs, using surface air temperature and OHC. The Community Earth system Model version 1, the only ensemble which utilizes a “micro” initialization approach perturbing only atmospheric initial conditions, yields lower spread in the first ∼30 years. The E3SMv1‐LE exhibits a relatively large spread, with some evidence for anthropogenic forcing influencing spread in the late twentieth century. However, systematic effects of differing “macro” initialization strategies are difficult to detect, possibly resulting from differing model physics or responses to external forcing. Notably, the method of standardizing results affects ensemble spread: control simulations for most models have either large background trends or multi‐centennial variability in OHC. This spurious disequlibrium behavior is a substantial roadblock to understanding both internal climate variability and its response to forcing.

Stevenson, Samantha↗
DOE OSTI2023

Contributions of Climate Change and ENSO Variability to Future Precipitation Extremes Over California

The El Niño/Southern Oscillation (ENSO) affects the occurrence frequency and intensity of extreme precipitation through modulations of regional heat and moisture fluxes. California experiences particularly strong ENSO influences and models project different to its extreme precipitation. It remains unclear how diverse projections of future precipitation extremes relate to inter-model differences for those changing signals. Here, we use “large ensemble” simulations with multiple climate models along with the Coupled Model Intercomparison Project Phase 5 to investigate the range of precipitation extreme changes over California and the influences from ENSO-related teleconnections. We found that precipitation amount increases are much larger during El Niño relative to La Niña years, mainly caused by the differences in frequency of extreme events during different phases. The ENSO-driven effect is even larger than the overall climate change signal for the most extreme events, implying uncertainties from inter-model differences in ENSO-related SST variability for extreme precipitation changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Climate change increases risk of extreme rainfall following wildfire in the western United States

Post-wildfire extreme rainfall events can have destructive impacts in the western United States. Using two climate model large ensembles, we assess the future risk of extreme fire weather events being followed by extreme rainfall in this region. By mid-21st century, in a high warming scenario (RCP8.5), we report large increases in the number of extreme fire weather events followed within 1 year by at least one extreme rainfall event. By 2100, the frequency of these compound events increases by 100% in California and 700% in the Pacific Northwest in the Community Earth System Model v1 Large Ensemble. We further project that more than 90% of extreme fire weather events in California, Colorado, and the Pacific Northwest will be followed by at least three spatially colocated extreme rainfall events within five years. Our results point to a future with substantially increased post-fire hydrologic risks across much of the western United States.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Connections Between Mean North Pacific Circulation and Western US Precipitation Extremes in a Warming Climate

Abstract Extreme precipitation has widespread impacts over the western US (WUS), which are expected to be exacerbated in the future given thermodynamically driven increases in atmospheric moisture and shifts in atmospheric circulation patterns. However, internal climate variability complicates how these factors affect future projections of precipitation changes. In this study, we investigate late 21st‐century changes in mean‐state responses over the North Pacific Ocean and associated WUS precipitation extremes using the Multi‐Model Large Ensemble Archive, which is a recent and valuable resource to disentangle the effects of model structural differences from internal variability. We found that inter‐model differences in precipitation extremes over the WUS are large: from south to north (here, from California to Washington), models show different levels of increases for both the frequency and intensity of heavy precipitation. In general, the Pacific Northwest sees a more consistent signal than California. We show that wet‐season mean circulation influences extreme precipitation, by using a decomposition of the relative contributions of thermodynamic (atmospheric humidity) and dynamic (large‐scale circulation) driven changes. The thermodynamic contribution dominates, however, the dynamic contribution varies with latitude and differs substantially between model ensembles. Inter‐model differences affect the spread in not only the magnitude, but also the sign of the dynamic contribution. This implies that mean circulation changes contribute to uncertainty in quantifying the regional structure of concentrated moisture flux and future extreme events. This result highlights the need to more accurately constrain projected North Pacific coupled circulation changes to narrow the spread in projections of future precipitation extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Future Warming and Intensification of Precipitation Extremes: A “Double Whammy” Leading to Increasing Flood Risk in California

This study focuses on quantifying future anthropogenic changes in surface runoff associated with extreme precipitation in California's Sierra Nevada. The method involves driving a land surface model with output from a high resolution regional atmospheric simulation of the most extreme atmospheric rivers (ARs). AR events were selected from an ensemble of global climate model simulations of historical and late 21st century climate under the “high-emission” RCP8.5 scenario. Average precipitation during the future ARs increases by ~25% but a much lower proportion falls as snow. The resulting future runoff increase is dramatic—nearly 50%, reflecting both the precipitation increase and simultaneous conversion of snow to rain. The “double whammy” impact on runoff is largest in the 2,000–2,500 m elevation band, where the snowfall loss and precipitation increase are both especially large. Overall, this huge increase in runoff during the most extreme AR events could present major flood control challenges for the region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Simulating and Evaluating Atmospheric River-Induced Precipitation Extremes Along the U.S. Pacific Coast: Case Studies From 1980–2017

Atmospheric rivers (ARs) are responsible for a majority of extreme precipitation and floodevents along the U.S. West Coast. To better understand the present-day characteristics of AR-relatedprecipitation extremes, a selection of nine most intense historical AR events during 1980–2017 is simulatedusing a dynamical downscaling modeling framework based on the Weather Research and ForecastingModel. We find that the chosen framework and Weather Research and Forecasting Model configurationreproduces both large-scale atmospheric features—including parent synoptic-scale cyclones—as well asthe filamentary corridors of integrated vapor transport associated with the ARs themselves. The accuracyof simulated extreme precipitation maxima, relative to in situ and interpolated gridded observations,improves notably with increasing model resolution, with improvements as large as 40–60% for fine scale(3 km) relative to coarse-scale (27 km) simulations. A separate set of simulations using smoothedtopography suggests that much of these gains stem from the improved representation of complex terrain.Additionally, using the 12 December 1995 storm in Northern California as an example, we demonstratethat only the highest-resolution simulations resolve important fine-scale features—such as localizedorographically forced vertical motion and powerful near hurricane-force boundary layer winds. Given thedemonstrated ability of a targeted dynamical downscaling framework to capture both local extremeprecipitation and key fine-scale characteristics of the most intense ARs in the historical record, we arguethat such a configuration may be highly conducive to understanding AR-related extremes and associatedchanges in a warming climate

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Anthropogenic Warming Impacts on Today's Sierra Nevada Snowpack and Flood Risk: WARMING IMPACTS ON SNOWPACK AND FLOOD RISK

This study investigates temperature impacts to snowpack and runoff-driven flood risk over the Sierra Nevada during the extremely wet year of 2016–2017, which followed the extraordinary California drought of 2011–2015. By perturbing near-surface temperatures from a 9-km dynamically downscaled simulation, a series of offline land surface model experiments explore how Sierra Nevada hydrology has already been impacted by historical anthropogenic warming and how these impacts evolve under future warming scenarios. Results show that historical warming reduced 2016–2017 Sierra Nevada snow water equivalent by 20% while increasing early-season runoff by 30%. An additional one third to two thirds loss of snowpack is projected by the end of the century, depending on the emission scenario, with middle elevations experiencing the most significant declines. Notably, the number of days in the future with runoff exceeding 20 mm nearly doubles under a mitigation emission scenarios and triples under a business-as-usual scenario. A smaller snow-to-rain ratio, as opposed to increased snowmelt, is found to be the primary mechanism of temperature impacts to Sierra snowpack and runoff. These findings are consequential to the prevalence of early-season floods in the Sierra Nevada. In the Feather River Watershed, historical warming increased runoff by over one third during the period of heaviest precipitation in February 2017. This suggests that historical anthropogenic warming may have exacerbated runoff conditions underlying the Oroville Dam spillway overflow that occurred in this month. As warming continues in the future, the potential for runoff-based flood risk may rise even higher.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

The Changing Character of Twenty-First-Century Precipitation over the Western United States in the Variable-Resolution CESM

Abstract The changing characters of precipitation frequency and intensity have been comprehensively investigated from the recent historical period to the end of the twenty-first century over the western United States. Variable-resolution Community Earth System Model (VR-CESM) ensemble simulations are applied with a fine grid resolution of ~0.25° over the study area. Simulations are forced with prescribed sea surface temperatures, sea ice extent, and greenhouse gas concentrations from the representative concentration pathway 8.5 (RCP8.5) scenario. VR-CESM is shown to be effective at accurately capturing the spatial patterns of the historical precipitation climatology. The results of VR-CESM output provide significantly regional details with crucial enhancement of precipitation representations over complex terrain. In the Intermountain West and U.S. Southwest, a statistically significant increase in mean precipitation and rainy days through midcentury is observed, although this trend is tempered by the end of the century in response to a decrease in relative humidity. Over the Pacific Northwest, extreme precipitation events are observed to increase significantly as a result of increased cool season integrated vapor transport associated with a moistening of the cool seasons and drying through the warm seasons. In particular, extreme precipitation in this region appears to increase more rapidly than would be predicted by the Clausius–Clapeyron relationship. No clear climate signal emerges in mean precipitation or extreme events in the majority of California, where the precipitation climatology is attributed to large interannual variabilities that are tied closely to ENSO patterns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

An evaluation of the variable-resolution CESM for modeling California's climate

In this paper, the recently developed variable-resolution option within the Community Earth System Model (VR-CESM) is assessed for long-term regional climate modeling of California at 0.25° (~ 28 km) and 0.125° (~ 14 km) horizontal resolutions. The mean climatology of near-surface temperature and precipitation is analyzed and contrasted with reanalysis, gridded observational data sets, and a traditional regional climate model (RCM)—the Weather Research and Forecasting (WRF) model. Statistical metrics for model evaluation and tests for differential significance have been extensively applied. VR-CESM tended to produce a warmer summer (by about 1–3°C) and overestimated overall winter precipitation (about 25%–35%) compared to reference data sets when sea surface temperatures were prescribed. Increasing resolution from 0.25° to 0.125° did not produce a statistically significant improvement in the model results. By comparison, the analogous WRF climatology (constrained laterally and at the sea surface by ERA-Interim reanalysis) was ~1–3°C colder than the reference data sets, underestimated precipitation by ~20%–30% at 27 km resolution, and overestimated precipitation by ~ 65–85% at 9 km. Overall, VR-CESM produced comparable statistical biases to WRF in key climatological quantities. Moreover, this assessment highlights the value of variable-resolution global climate models (VRGCMs) in capturing fine-scale atmospheric processes, projecting future regional climate, and addressing the computational expense of uniform-resolution global climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Characterizing Sierra Nevada Snowpack Using Variable-Resolution CESM

The location, timing, and intermittency of precipitation in California make the state integrally reliant on winter-season snowpack accumulation to maintain its economic and agricultural livelihood. Of particular concern is that winter-season snowpack has shown a net decline across the western United States over the past 50 years, resulting in major uncertainty in water-resource management heading into the next century. Cutting-edge tools are available to help navigate and preemptively plan for these uncertainties. This paper uses a next-generation modeling technique-variable-resolution global climate modeling within the Community Earth System Model (VR-CESM)-at horizontal resolutions of 0.125° (14 km) and 0.25° (28 km). VR-CESM provides the means to include dynamically large-scale atmosphere-ocean drivers, to limit model bias, and to provide more accurate representations of regional topography while doing so in a more computationally efficient manner than can be achieved with conventional general circulation models. This paper validates VR-CESM at climatological and seasonal time scales for Sierra Nevada snowpack metrics by comparing them with the "Daymet," "Cal-Adapt," NARR, NCEP, and North American Land Data Assimilation System (NLDAS) reanalysis datasets, the MODIS remote sensing dataset, the SNOTEL observational dataset, a standard-practice global climate model (CESM), and a regional climate model (WRF Model) dataset. Overall, given California's complex terrain and intermittent precipitation and that both of the VR-CESM simulations were only constrained by prescribed sea surface temperatures and data on sea ice extent, a 0.68 centered Pearson product-moment correlation, a negative mean SWE bias of < 7 mm, an interquartile range well within the values exhibited in the reanalysis datasets, and a mean December-February extent of snow cover that is within 7% of the expected MODIS value together make apparent the efficacy of the VR-CESM framework.

54 ENVIRONMENTAL SCIENCES↗