Search NASA⌕ Search

SEARCH · Search NASA

Results for “Atmospheric river”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Effects of Resolution and Spectral Nudging in Simulation the Effects of Wintertime Atmospheric River Landfalls in the Western US

Landfalling atmospheric rivers (ARs) play a crucial role in the climate of the US Pacific coast region as they are frequently related with heavy precipitation and flash flooding events. Thus, the capability of climate models to accurately simulate AR landfalls and their key hydrologic effects is an important practical concern for WUS, from flood forecasting to future water resources projections. In order to examine the effects of model configuration, including the resolution and spectral nudging, in simulating the climatology of key weather events in the conterminous US, a NASA team has performed a hindcast experiment using the GEOS5 global and the NU-WRF regional models for Nov 1999 - Oct 2010. This study examines the skill of these hindcasts, with different models and their configurations, in simulating key footprints of landfalling ARs in the WUS region. Using an AR-landfall chronology based on the vertically-integrated water vapor flux calculated from the MERRA2 reanalysis, we have analyzed the observed and simulated precipitation and temperature anomalies associated with wintertime AR landfalls along the US Pacific coast. Model skill is measured using metrics including regional means, a skill score based on correlations and mean-square errors, and Taylor diagrams in four WUS Bukovsky regions. Results show that the AR-related anomalies of precipitation is more reliable than of surface temperatures. Model skill also varies according to regions. The AR temperature anomalies are well simulated in most of the WUS region except PNW. For precipitation, simulations with finer spatial resolution tend to generate larger spatial variability and agree better with the PRISM data in most regions. Such a resolution dependence of spatial variability is not found for temperatures; e.g., the MERRA2 reanalysis often outperforms, with similar spatial variability and higher pattern correlations with the PRISM data, finer-resolution NU-WRF runs in simulating temperature variations within subregions. Results from this study will be summarized to assist future (regional) climate experiments for climate change impact assessments and developing adaptationmitigation strategies, the key elements of the National Climate Assessment.

Simulation↗
NASA NTRSDate not supplied

A Strong Atmospheric River Responsible for the 2019 Record Floods in the Middle East

Atmospheric rivers (ARs) cause some of the weather-related disasters around the world. While many studies have shown the contribution of ARs to precipitation in the coastal regions such as western Europe and the U.S. West Coast, little is known about their mechanisms and impacts on flooding in the Middle East. This study shows that an AR was responsible for the record floods during March 2019 across the Middle East. Iran in particular was hit hardest with the floods that left a death toll of at least 76 and an early estimate of $2.5 billion (U.S. dollars) damage to its infrastructures. The heavy precipitation produced by this AR made the 2018/19 rainy season the wettest in the past four decades. By contrast, the prior year (2017/18) was the driest over the same period. This is a compelling example of rapid dry-to-wet transitions that may enhance the chance of landslides and impose challenges to water resources management. The AR originated in the Atlantic Ocean and propagated across North Africa and the Arabian Peninsula before its final landfall over the Zagros Mountains. On its nearly 9000 km journey, the AR received additional moisture from the Mediterranean, Red, and Arabian Seas, and the Persian Gulf. Moisture transport by this AR during 24-25 March 2019 is estimated at more than 150times the aggregated discharge of the four major rivers in the region, that is, the Tigris, Euphrates, Karun, and Karkheh. Anomalously warm sea surface temperatures in all surrounding basins and coincidence of a midlatitude system and a subtropical jet provided the necessary ingredients for formation of this strong AR. This work underlines the fact that the impacts of rain-producing ARs are not limited to the coastal regions. Such ARs can travel very long distances away from the oceans and affect remote arid and semi-arid regions like the Middle East. This study examined an individual AR, though one associated with record floods. However, it attempts to draw attention to the need for more AR-related research over the Middle East.

Atmospheric Rivers↗
DOE OSTI2023

Synoptic Drivers of Atmospheric River Induced Precipitation Near Dronning Maud Land, Antarctica

Atmospheric rivers (ARs) that reach the Antarctic Ice Sheet (AIS) transport anomalous moisture from lower latitudes and can impact the AIS via extreme precipitation and increased downward longwave radiation. ARs contribute significantly to the interannual variability of precipitation over the AIS and thus are likely to play a key role in understanding future changes in the surface mass balance of the AIS. Dronning Maud Land (DML) is one of four maxima in AR frequency over coastal East Antarctica, with AR precipitation explaining 77% of the interannual variability in precipitation for this region. We employ a 16-node self-organizing map (SOM) trained with MERRA-2 sea-level pressure anomalies to identify synoptic-scale environments associated with landfalling ARs in and around DML. Node composites of atmospheric variables reveal common drivers of precipitation associated with ARs reaching DML including anomalous high-low surface pressure couplets, anomalously high integrated water vapor, and coastal barrier jets. Using a quasi-geostrophic framework, we find that upward vertical motion associated with the occlusion process of attendant cyclones dominates atmospheric lift in AR environments. We further identify mechanisms that explain the variability in AR precipitation intensity across nodes, such as the lift associated with the occlusion process of attendant cyclones and the spatial coincidence of ascent induced by the occlusion process and frontogenesis. Here, the latter suggests that ARs making landfall during the mature phase of cyclogenesis result in higher precipitation intensity compared to landfalling ARs that occur during the occluded phase.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Ocean fronts and eddies force atmospheric rivers and heavy precipitation in western North America

Atmospheric rivers (ARs) are responsible for over 90% of poleward water vapor transport in the mid-latitudes and can produce extreme precipitation when making landfall. However, weather and climate models still have difficulty simulating and predicting landfalling ARs and associated extreme precipitation, highlighting the need to better understand AR dynamics. Here, using high-resolution climate models and observations, we demonstrate that mesoscale sea-surface temperature (SST) anomalies along the Kuroshio Extension can exert a remote influence on landfalling ARs and related heavy precipitation along the west coast of North America. Inclusion of mesoscale SST forcing in the simulations results in approximately a 40% increase in landfalling ARs and up to a 30% increase in heavy precipitation in mountainous regions and this remote impact occurs on two-week time scales. The asymmetrical response of the atmosphere to warm vs. cold mesoscale SSTs over the eddy-rich Kuroshio Extension region is proposed as a forcing mechanism that results in a net increase of moisture flux above the planetary boundary layer, prompting AR genesis via enhancing moisture transport into extratropical cyclones in the presence of mesoscale SST forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Uncertainties in Atmospheric River Lifecycles by Detection Algorithms: Climatology and Variability

Atmospheric rivers (ARs) are long and narrow filaments of vapor transport that are responsible for most poleward moisture transport outside of the tropics. Many AR detection algorithms have been developed to automatically identify ARs in climate data. The diversity of these algorithms has introduced appreciable uncertainties in quantitative measures of AR properties and thereby impedes the construction of a unified and internally consistent climatology of ARs. This paper compares nine global AR detection algorithms from the perspective of AR lifecycles following the propagation of ARs from origin to termination in the MERRA2 reanalysis over the period 1980–2017. Uncertainties in AR lifecycle characteristics, including event number, lifetime, intensity, and frequency distribution are discussed. Notably, the number of AR events per year in the Northern Hemisphere can vary by a factor of 5 with different algorithms. Although all algorithms show that the maximum AR origin (termination) frequency is located over the western (eastern) portion of ocean basins, significant disagreements appear in regional distribution. Spreads are large in AR lifetime and intensity. Here, the number of landfalling AR events produced by the algorithms can vary from 16 to 80 events per year, although the agreement improves for stronger ARs. By examining the ARs' connections with the Madden-Julian Oscillation and El Niño Southern Oscillation, we find that the overall responses of ARs (such as changes in AR frequency, origin, and landfall activity) to climate variability are consistent among algorithms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Sources of Subseasonal-To-Seasonal Predictability of Atmospheric Rivers and Precipitation in the Western United States

Atmospheric rivers (ARs) account for a large portion of winter precipitation in the western US. To evaluate the sources of AR and precipitation predictability at subseasonal-to-seasonal timescales, we examine the relationships between two climate modes, the El Niño/Southern Oscillation (ENSO) and Madden-Julian oscillation (MJO), and winter hydroclimate in the western US. Our analysis uses a large ensemble of the Weather Research and Forecast (WRF) model simulations from 1981 to 2017, facilitating the assessment of uncertainty in climate mode-AR relationship due to climate variability and short length of observations. Over the North Pacific basin, we find ENSO-related latitudinal shifts of ARs, but ENSO has little effect on basin-wide averaged AR frequency. Over the western US, there is some uncertainty in the ENSO-AR connection due to the impacts of ENSO indices and datasets. However, extreme El Niño events defined by the ENSO longitude index are consistently linked to increased landfalling AR activity. The MJO can lead to significantly enhanced or suppressed landfalling AR activity in the large-ensembles, depending on the phase of MJO and time lag, while observations are too short in length to robustly show this signal. ENSO substantially modulates the MJO-AR relationship, triggering variegated responses of landfalling ARs and AR precipitation in La Niña and El Niño years. Our findings highlight the need to evaluate concurrent effects of different climate modes on ARs and precipitation, and may shed light on a path toward more accurate subseasonal-to-seasonal prediction of ARs and precipitation over the western US.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Rare Atmospheric River Caused Record Floods Across the Middle East

Atmospheric rivers (ARs) are responsible for some of the hydroclimatic extremes around the world. Their mechanisms and contribution to flooding in the Middle East are relatively poorly understood. This study shows that the record floods during March 2019 across the Middle East were caused by a powerful AR, originated from the North Atlantic Ocean. Iran, in particular, was substantially affected by the floods. The nearly 9000 km long AR propagated across North Africa and the Middle-East, and was fed by additional moisture from several other sources on its pathway. Simultaneous presence of a mid-latitude system and a subtropical jet facilitated the moisture supply. The AR, as passing over the Zagros Mountains, produced record rainfall induced by the orographic forcing. The resulting floods caused widespread damage to infrastructures and left a death toll of at least 76 in Iran.

Amin Dezfuli↗
DOE OSTI2024

Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0

Abstract. Using the regionally refined mesh (RRM) configuration of the US Department of Energy's Simple Cloud-Resolving Energy Exascale Earth System Model (E3SM) Atmosphere Model (SCREAM), we simulate and evaluate four meteorologically distinct atmospheric river events over California. We test five different RRM configurations, each differing in terms of the areal extent of the refined mesh and the resolution (ranging from 800 m to 3.25 km). We find that SCREAM RRM generally has a good representation of the AR-generated precipitation in CA, even for the control simulation which has a very small 3 km refined patch, and is able to capture the fine-scale regional distributions that are controlled largely by the fine-scale topography of the state. It is found that SCREAM generally has a wet bias over topography, most prominently over the Sierra Nevada mountain range, with a corresponding dry bias on the lee side. We find that refining the resolution beyond 3 km (specifically 1.6 km and 800 m) has virtually no benefit towards reducing systematic precipitation biases but that improvements can be found when increasing the areal extent of the upstream refined mesh. However, these improvements are relatively modest and only realized if the size of the refined mesh is expanded to the scale where employing RRM no longer achieves the substantial cost benefit it was intended for.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Atmospheric River Frequency-Category Characteristics Shape U.S. West Coast Runoff

Abstractrunoff response to atmospheric rivers (ARs) over the U.S. West Coast. We focused on runoff time series variations impacted by AR characteristics (e.g., category and frequency) and land preconditions during Northern Hemisphere cool seasons in the period of 1940–2023. Results show that high-category ARs significantly increase local runoff with higher hourly precipitation rates leading to a greater incremental rate and peak runoff. Extreme runoff increases greatly with the AR category with an increase rate up to 12.5 times stronger than non-extreme runoff. Besides the AR category, land preconditions such as soil moisture and snowpack also play crucial roles in modulating runoff response. We found that runoff induced by weak-category ARs is more sensitive to land preconditions than high-category ARs, with high peak runoff occurring when soil is nearly saturated. Additionally, more than 50% of high-peak-runoff events in snow-covered grid cells are associated with rain-on-snow events particularly for the events associated with weaker ARs. Regression analysis reveals that AR precipitation and land preconditions jointly influence runoff, emphasizing the importance of including soil moisture and snowpack levels in AR impact assessments. The study also highlights the intensified runoff response to back-to-back ARs with short intervals, which may become more frequent with climate warming, posing increased flood risks via facilitating wet soil conditions. Our findings have significant implications for AR risk predictions and the development of prediction models for AR-induced runoff.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Examination of Global Midlatitude Atmospheric River Lifecycles Using an Object-Oriented Methodology

Tracking atmospheric rivers (ARs) across their lifecycles is a field of recent interest with a multitude of emerging methodologies. The CONNected-objECT (CONNECT) algorithm is adapted for the tracking of global midlatitude AR lifecycles and associated precipitation by implementing a seeded region growing segmentation algorithm, creating the AR-CONNECT algorithm. To facilitate the permissiveness of the methodology, AR-CONNECT is without hard-coded geometric criteria yet is still shown to extract synoptic-scale elongated objects >99.99% of the time. One of the consequences of the methodology is the ability to occasionally track atmospheric water vapor anomalies before evolving into AR geometries, effectively tracking AR genesis further back than other studies. With the aid of subdaily satellite-derived rain data, we investigate the climatology, trends, and patterns of AR lifecycles from 1983–2016 and compare with other AR tracking studies. We find that AR frequency, genesis, and terminus locations are in generally good agreement with other AR tracking methodologies, though with key differences, and that AR frequencies in each hemisphere are determined by the number of AR hotspots. Furthermore, we uncover evidence that certain AR characteristics, such as frequency, areal extent, and duration, show evidence of increasing trends. Midlatitude precipitation uncovered by AR-CONNECT shows contributions up to 50% over land and 65% over the ocean. Trend analysis of AR precipitation shows an increase in precipitation associated with ARs propagated by the Southern Jet Stream and ARs that traverse over the Sahara Desert, among others, but is determined not to be a driver of changes in global precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Multiscale drivers of extreme southern California flooding: ENSO, MJO, North Pacific jet, and atmospheric rivers

Extreme rainfall and flooding, driven by a powerful atmospheric river (AR) and a persistent Madden-Julian Oscillation (MJO), hit Southern California in February 2024 during the 2023–2024 El Niño, affecting over 10 million people. ARs are key contributors to extreme rainfall and flooding along the U.S. West Coast. Although the AR-MJO link has been documented, its spatio-temporal variability remains a major forecasting and risk-management challenge. Combining precipitation, stream gauge and demographic data, we quantify the physical drivers and population exposure to this extreme event. Leveraging a Lagrangian MJO precipitation tracking algorithm, we unravel the multiscale interactions responsible for the AR’s development. El Niño favored a large, long-lived MJO that interacted with the North Pacific Jet (NPJ) over more than three weeks. The MJO convective outflow modulated the NPJ by inducing negative potential vorticity advection along the tropopause. The ensuing NPJ extension and acceleration induced explosive cyclogenesis, whose AR-driven moisture transport resulted in extreme rainfall.

Atmospheric dynamics↗
DOE OSTI2021

Constraining and Characterizing the Size of Atmospheric Rivers: A Perspective Independent From the Detection Algorithm

Abstract Atmospheric rivers (AR) are large and narrow filaments of poleward horizontal water vapor transport. Because of its direct relationship with horizontal vapor transport, extreme precipitation, and overall AR impacts over land, the AR size is an important characteristic that needs to be better understood. Current AR detection and tracking algorithms have resulted in large uncertainty in estimating AR sizes, with areas varying over several orders of magnitude among different detection methods. We develop and implement five independent size estimation methods to characterize the size of ARs that make landfall over the west coast of North America in the 1980–2017 period and reduce the range of size estimation from ARTMIP. ARs that originate in the Northwest Pacific (WP) (100°−180°E) have larger sizes and are more zonally oriented than those from the Northeast Pacific (EP) (180°−240°E). ARs become smaller through their life cycle, mainly due to reductions in their width. They also become more meridionally oriented toward the end of their life cycle. Overall, the size estimation methods proposed in this study provide a range of AR areas (between 7 × 10 11 and 10 13 m 2 ), that is, several orders of magnitude narrower than current methods estimation. This methodology can provide statistical constraints in size and geometry for the AR detection and tracking algorithms, and an objective insight for future studies about AR size changes under different climate scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Improved Simulations of Atmospheric River Climatology and Variability in High-Resolution CESM

Atmospheric rivers (ARs) can trigger extreme rainfall and snowfall events, causing high risk of flooding. Meanwhile, they are sometimes responsible for the occurrence and break of drought events. So, it is of great importance for weather and climate forecast models to accurately represent ARs. Studies have shown that AR variability is linked to various climate modes, such as El Niño/Southern Oscillation, Pacific Decadal Oscillation, Pacific-North America pattern, providing the potential for predicting ARs at subseasonal-to-decadal timescales. In this study, we examine the impact of climate model resolution on AR simulations and their relationship with major climate modes by comparing a pair of high-resolution and a low-resolution (LR) Community Earth System Model (CESM) simulations against the observations. The results reveal major deficiencies in LR that include underestimated climatological AR strength and associated precipitation, and inaccurate representations of ARs relationships with climate modes. Significant improvements are observed by increasing CESM horizontal resolution, suggesting a path for more accurate prediction of ARs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Detection of atmospheric rivers with inline uncertainty quantification: TECA-BARD v1.0.1

It has become increasingly common for researchers to utilize methods that identify weather features in climate models. There is an increasing recognition that the uncertainty associated with choice of detection method may affect our scientific understanding. For example, results from the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) indicate that there are a broad range of plausible atmospheric river (AR) detectors and that scientific results can depend on the algorithm used. There are similar examples from the literature on extratropical cyclones and tropical cyclones. It is therefore imperative to develop detection techniques that explicitly quantify the uncertainty associated with the detection of events. We seek to answer the following question: given a “plausible” AR detector, how does uncertainty in the detector quantitatively impact scientific results? We develop a large dataset of global AR counts, manually identified by a set of eight researchers with expertise in atmospheric science, which we use to constrain parameters in a novel AR detection method. We use a Bayesian framework to sample from the set of AR detector parameters that yield AR counts similar to the expert database of AR counts; this yields a set of “plausible” AR detectors from which we can assess quantitative uncertainty. This probabilistic AR detector has been implemented in the Toolkit for Extreme Climate Analysis (TECA), which allows for efficient processing of petabyte-scale datasets. We apply the TECA Bayesian AR Detector, TECA-BARD v1.0.1, to the MERRA-2 reanalysis and show that the sign of the correlation between global AR count and El Niño–Southern Oscillation depends on the set of parameters used.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Atmospheric River Response to Arctic Sea Ice Loss in the Polar Amplification Model Intercomparison Project

The atmospheric river (AR) response to Arctic sea ice loss in the Northern hemisphere winter is investigated using simulations from the Polar Amplification Model Intercomparison Project. Results have shown that the midlatitude responses are dominated by dynamic effects. Poleward of around 60°N, the dynamic and thermodynamic effects cancel each other, resulting in relatively small responses. The response uncertainty can be characterized by leading uncertainty modes, with the responses over the Pacific and Atlantic projecting onto the northeastward extension and equatorward shift mode, respectively. In addition, the responses seem to be mean state-dependent: under the same forcing, models with more poleward-located climatological ARs tend to show stronger equatorward shifts over the Atlantic; over the Pacific, models with more westward-located climatological AR core tend to show stronger northeastward extensions. Finally, these relationships highlight the importance of improving the AR climatology representation on reducing the response uncertainty to Arctic sea ice loss.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Applications of MERRA-2 data for avian migration, biomass burning, and dusty atmospheric rivers

Three different applications of MERRA-2 data are presented. 1) Using radar data, we introduced a new concept for spatial patterns of bird migration across the contiguous U.S. This approach allowed us to use MERRA-2 data and learn that remote forcing in the tropical Pacific—through a chain of processes including atmospheric Rossby wave trains— controls the climatic conditions, associated with bird migration in North America. 2) We showed that emissions from biomass burning in the Congo Basin are partly controlled by the low-level winds, which are in turn associated with the intensity of the subtropical high in the Indian Ocean. Using back-trajectory analysis, we found that these emissions combined with their transport mechanism explain the interannual variability of black carbon in West Africa. 3) Our analysis showed that atmospheric rivers in the Middle East contribute to both heavy flood and dust transport within their corridor. We also found that warm advection and rain-on-snow effect of dusty atmospheric rivers further enhance the chance of flood through rapid snowmelt processes.

Amin Dezfuli↗
NASA NTRSDate not supplied

Applications of MERRA-2 Data for Avian Migration, Biomass Burning, and Dusty Atmospheric Rivers

Three different applications of MERRA-2 data are presented. 1) Using radar data, we introduced a new concept for spatial patterns of bird migration across the contiguous U.S. This approach allowed us to use MERRA-2 data and learn that remote forcing in the tropical Pacific—through a chain of processes including atmospheric Rossby wave trains— controls the climatic conditions, associated with bird migration in North America. 2) We showed that emissions from biomass burning in the Congo Basin are partly controlled by the low-level winds, which are in turn associated with the intensity of the subtropical high in the Indian Ocean. Using back-trajectory analysis, we found that these emissions combined with their transport mechanism explain the interannual variability of black carbon in West Africa. 3) Our analysis showed that atmospheric rivers in the Middle East contribute to both heavy flood and dust transport within their corridor. We also found that warm advection and rain-on-snow effect of dusty atmospheric rivers further enhance the chance of flood through rapid snowmelt processes.

Amin Dezfuli↗