L Ruby Leung
Biographic Data
| ID | 6818143 |
|---|---|
| NAME | L Ruby Leung |
| GIVEN NAMES | L Ruby |
| FAMILY NAME | Leung |
| SIGNATURE | LEUNG L R |
| AFFILIATIONS | Pacific Northwest National Laboratory |
| ORCID | 0000-0002-3221-9467 |
| VERIFIED | Yes |
| TOTAL WORKS | 16 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 16 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Improving tropical cyclone rapid intensification forecasts with satellite measurements of sea surface salinity and calibrated machine learning
Forecasting rapid intensification (RI) of tropical cyclones (TC) is a mission known for large errors. One under-researched factor that affects TC intensification is salinity, which is important for density stratification in certain ocean regions and can affect the surface enthalpy flux under a strengthening hurricane. To investigate the impact and efficacy of using salinity information in state-of-the-art forecasting, we use a statistical model c…
Projecting U.S. coastal storm surge risks and impacts with deep learning
Storm surge is one of the deadliest hazards posed by tropical cyclones (TCs), yet assessing its current and future risk is difficult due to the phenomenon’s rarity and physical complexity. Recent advances in artificial intelligence applications to natural hazard modeling suggest a new avenue for addressing this problem. We develop a deep learning storm surge model to efficiently estimate coastal surge risk in the United States from 900 000 synthe…
More high-impact atmospheric river-induced extreme precipitation events under warming in a high-resolution model
Is land use producing robust signals in future projections from Earth system models, all else being equal
We use six Earth system models (ESMs) run under SSP3-7.0, a scenario characterized by a relatively large land use change (LUC) over the 21st century, and under a variant of the same scenario where a significantly different pattern of LUC, taken from SSP1-2.6, was used, all else being equal. Our goal is to identify changes in climate extremes between the two scenarios that are statistically significant and robust across the ESMs. The motivation fo…
Evolution of global snow drought characteristics from 1850 to 2100
Seasonal snow is an integral part of the global water supply and storage system. Snow droughts impact ecological, agricultural, and urban systems by altering the amount and timing of meltwater delivery. These droughts are characterized by a lack of on-the-ground snow (snow water equivalent, SWE) that can be caused by low total precipitation (dry drought) or low proportion of precipitation falling as snowfall (warm drought), often combined with an…
A simple framework to characterize land aridity based on surface energy partitioning regimes
Land aridity is often characterized by the aridity index (AI), which does not account for land surface water-energy interactions that are crucially important in determining regional climate. Such interactions can be captured by the evaporative fraction (EF, ratio of evapotranspiration to available energy) regimes. As EF is subject to energy and water limitations in humid and dry areas, respectively, EF regimes may be used to characterize land ari…
Disentangling the mechanism of temperature and water vapor modulation on ozone under a warming climate
Temperature and water vapor have been considered as important factors affecting ozone concentrations, however, their synergistic effect on ozone, as well as its response to a warming climate remains unclear. Here, numerical experiments with different combinations of climate and emissions highlighted opposite changes of annual ozone over the contiguous U.S. under scenarios with high vs. low ozone precursor emissions in the future with warming. Com…
Isolating the modulation of mean warming and higher-order temperature changes on ozone in a changing climate over the contiguous United States
Surface ozone is substantially affected by climate change through the modulation of key meteorological parameters such as temperature. While the changes in temperature under a warming climate manifest in changes of both the mean and higher-order statistical moments, their individual role in ozone concentration changes has not been broadly investigated. To address this gap, we use a novel approach to isolate the impacts of mean warming and changes…
Metrics as tools for bridging climate science and applications
In climate science and applications, the term “metric” is used to describe the distillation of complex, multifaceted evaluations to summarize the overall quality of a model simulation, or other data product, and/or as a means to quantify some response to climate change. Metrics provide insights into the fidelity of processes and outcomes from climate models and can assist with both differentiating models' representation of variables or processes …
Increased extreme rains intensify erosional nitrogen and phosphorus fluxes to the northern Gulf of Mexico in recent decades
Soil erosion delivers enormous amounts of macro-nutrients including nitrogen (N) and phosphorus (P) from land to rivers, potentially sustaining water column bioavailable nutrient levels for decades. In this study, we represent erosional N and P fluxes in the Energy Exascale Earth System Model (E3SM) and apply the model to the continental United States. We estimate that during 1991–2019 soil erosion delivers 775 Gg yr −1 (1 Gg = 10 9 g) of particu…
Changes in temporal variability of precipitation over land due to anthropogenic forcings
This study investigated the anthropogenic influence on the temporal variability of annual precipitation for the period 1950–2005 as simulated by the CMIP5 models. The temporal variability of both annual precipitation amount (PRCPTOT) and intensity (SDII) was first measured using a metric of statistical dispersion called the Gini coefficient. Comparing simulations driven by both anthropogenic and natural forcing (ALL) with simulations of natural f…
Emergence of new hydrologic regimes of surface water resources in the conterminous United States under future warming
Despite the importance of surface water to people and ecosystems, few studies have explored detectable changes in surface water supply in a changing climate, given its large natural variability. Here we analyze runoff projections from the Variable Infiltration Capacity hydrological model driven by 97 downscaled and bias-corrected Coupled Model Intercomparison Project Phase 5 climate projections over the conterminous United States (CONUS). Our res…
Influence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4)
Land carbon sensitivity to atmospheric CO 2 concentration (β L ) and climate warming (γ L ) is a crucial part of carbon-climate feedbacks in the earth system. Using the Community Land Model version 4 with a coupled carbon-nitrogen cycle, we examine whether the inclusion of a dynamic global vegetation model (CNDV) significantly changes the land carbon sensitivity from that obtained with prescribed vegetation cover (CN). For decadal timescale in th…
Aridity changes in the Tibetan Plateau in a warming climate
Desertification in the Tibetan Plateau (TP) has drawn increasing attention in the recent decades. It has been postulated as a consequence of climate aridity due to the observed warming. This study quantifies the aridity changes in the TP and attributes the changes to different climatic factors. Using the ratio of P/PET (precipitation to potential evapotranspiration) as an aridity index to indicate changes in dryness and wetness in a given area, P…
Persistent cold air outbreaks over North America in a warming climate
This study examines future changes of cold air outbreaks (CAOs) using a multi-model ensemble of global climate simulations from the Coupled Model Intercomparison Project Phase 5 and high resolution regional climate simulations. Overall, climate models agree on a dip in CAO duration across North America, but the percentage change is consistently smaller from western Canada to the upper mid-western US with historically more frequent CAO. By decompo…
Oceanic control of Northeast Pacific hurricane activity at interannual timescales
Sea surface temperature (SST) is not the only oceanic parameter that can play a key role in the interannual variability of Northeast Pacific hurricane activity. Using several observational data sets and the statistical technique of multiple linear regression analysis, we show that, along with SST, the thermocline depth (TD) plays an important role in hurricane activity at interannual timescales in this basin. Based on the parameter that dominates…
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Oceanic control of Northeast Pacific hurricane activity at interannual timescales
Sea surface temperature (SST) is not the only oceanic parameter that can play a key role in the interannual variability of Northeast Pacific hurricane activity. Using several observational data sets and the statistical technique of multiple linear regression analysis, we show that, along with SST, the thermocline depth (TD) plays an important role in hurricane activity at interannual timescales in this basin. Based on the parameter that dominates…
Aridity changes in the Tibetan Plateau in a warming climate
Desertification in the Tibetan Plateau (TP) has drawn increasing attention in the recent decades. It has been postulated as a consequence of climate aridity due to the observed warming. This study quantifies the aridity changes in the TP and attributes the changes to different climatic factors. Using the ratio of P/PET (precipitation to potential evapotranspiration) as an aridity index to indicate changes in dryness and wetness in a given area, P…
Persistent cold air outbreaks over North America in a warming climate
This study examines future changes of cold air outbreaks (CAOs) using a multi-model ensemble of global climate simulations from the Coupled Model Intercomparison Project Phase 5 and high resolution regional climate simulations. Overall, climate models agree on a dip in CAO duration across North America, but the percentage change is consistently smaller from western Canada to the upper mid-western US with historically more frequent CAO. By decompo…
Emergence of new hydrologic regimes of surface water resources in the conterminous United States under future warming
Despite the importance of surface water to people and ecosystems, few studies have explored detectable changes in surface water supply in a changing climate, given its large natural variability. Here we analyze runoff projections from the Variable Infiltration Capacity hydrological model driven by 97 downscaled and bias-corrected Coupled Model Intercomparison Project Phase 5 climate projections over the conterminous United States (CONUS). Our res…
Influence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4)
Land carbon sensitivity to atmospheric CO 2 concentration (β L ) and climate warming (γ L ) is a crucial part of carbon-climate feedbacks in the earth system. Using the Community Land Model version 4 with a coupled carbon-nitrogen cycle, we examine whether the inclusion of a dynamic global vegetation model (CNDV) significantly changes the land carbon sensitivity from that obtained with prescribed vegetation cover (CN). For decadal timescale in th…
Changes in temporal variability of precipitation over land due to anthropogenic forcings
This study investigated the anthropogenic influence on the temporal variability of annual precipitation for the period 1950–2005 as simulated by the CMIP5 models. The temporal variability of both annual precipitation amount (PRCPTOT) and intensity (SDII) was first measured using a metric of statistical dispersion called the Gini coefficient. Comparing simulations driven by both anthropogenic and natural forcing (ALL) with simulations of natural f…
Increased extreme rains intensify erosional nitrogen and phosphorus fluxes to the northern Gulf of Mexico in recent decades
Soil erosion delivers enormous amounts of macro-nutrients including nitrogen (N) and phosphorus (P) from land to rivers, potentially sustaining water column bioavailable nutrient levels for decades. In this study, we represent erosional N and P fluxes in the Energy Exascale Earth System Model (E3SM) and apply the model to the continental United States. We estimate that during 1991–2019 soil erosion delivers 775 Gg yr −1 (1 Gg = 10 9 g) of particu…
A simple framework to characterize land aridity based on surface energy partitioning regimes
Land aridity is often characterized by the aridity index (AI), which does not account for land surface water-energy interactions that are crucially important in determining regional climate. Such interactions can be captured by the evaporative fraction (EF, ratio of evapotranspiration to available energy) regimes. As EF is subject to energy and water limitations in humid and dry areas, respectively, EF regimes may be used to characterize land ari…
Disentangling the mechanism of temperature and water vapor modulation on ozone under a warming climate
Temperature and water vapor have been considered as important factors affecting ozone concentrations, however, their synergistic effect on ozone, as well as its response to a warming climate remains unclear. Here, numerical experiments with different combinations of climate and emissions highlighted opposite changes of annual ozone over the contiguous U.S. under scenarios with high vs. low ozone precursor emissions in the future with warming. Com…
Isolating the modulation of mean warming and higher-order temperature changes on ozone in a changing climate over the contiguous United States
Surface ozone is substantially affected by climate change through the modulation of key meteorological parameters such as temperature. While the changes in temperature under a warming climate manifest in changes of both the mean and higher-order statistical moments, their individual role in ozone concentration changes has not been broadly investigated. To address this gap, we use a novel approach to isolate the impacts of mean warming and changes…
Metrics as tools for bridging climate science and applications
In climate science and applications, the term “metric” is used to describe the distillation of complex, multifaceted evaluations to summarize the overall quality of a model simulation, or other data product, and/or as a means to quantify some response to climate change. Metrics provide insights into the fidelity of processes and outcomes from climate models and can assist with both differentiating models' representation of variables or processes …
Is land use producing robust signals in future projections from Earth system models, all else being equal
We use six Earth system models (ESMs) run under SSP3-7.0, a scenario characterized by a relatively large land use change (LUC) over the 21st century, and under a variant of the same scenario where a significantly different pattern of LUC, taken from SSP1-2.6, was used, all else being equal. Our goal is to identify changes in climate extremes between the two scenarios that are statistically significant and robust across the ESMs. The motivation fo…
Evolution of global snow drought characteristics from 1850 to 2100
Seasonal snow is an integral part of the global water supply and storage system. Snow droughts impact ecological, agricultural, and urban systems by altering the amount and timing of meltwater delivery. These droughts are characterized by a lack of on-the-ground snow (snow water equivalent, SWE) that can be caused by low total precipitation (dry drought) or low proportion of precipitation falling as snowfall (warm drought), often combined with an…
More high-impact atmospheric river-induced extreme precipitation events under warming in a high-resolution model
Improving tropical cyclone rapid intensification forecasts with satellite measurements of sea surface salinity and calibrated machine learning
Forecasting rapid intensification (RI) of tropical cyclones (TC) is a mission known for large errors. One under-researched factor that affects TC intensification is salinity, which is important for density stratification in certain ocean regions and can affect the surface enthalpy flux under a strengthening hurricane. To investigate the impact and efficacy of using salinity information in state-of-the-art forecasting, we use a statistical model c…
Projecting U.S. coastal storm surge risks and impacts with deep learning
Storm surge is one of the deadliest hazards posed by tropical cyclones (TCs), yet assessing its current and future risk is difficult due to the phenomenon’s rarity and physical complexity. Recent advances in artificial intelligence applications to natural hazard modeling suggest a new avenue for addressing this problem. We develop a deep learning storm surge model to efficiently estimate coastal surge risk in the United States from 900 000 synthe…
Environmental Science (16 works) · Climatology (14 works) · Geography (13 works) · Geology (13 works) · Climate variability and models (12 works) · Meteorology (11 works) · Climate change (10 works) · Ecology (10 works) · Atmospheric sciences (9 works) · Oceanography (6 works)