In February 2017, a 5‐day sequence of atmospheric river storms in California, USA, resulted in extreme inflows to Lake Oroville, the state's second‐largest reservoir. Damage to the reservoir's ...spillway infrastructure necessitated evacuation of 188,000 people; subsequent infrastructure repairs cost $1 billion. We assess the atmospheric conditions, snowmelt, and runoff against major historical events. The event generated exceptional runoff volumes (second largest in a 30‐yr record) partially at odds with the event precipitation totals (ninth largest). We explain the discrepancy with observed record melt of deep antecedent snowpack, heavy rainfall extending to unusually high elevations, and high water vapor transport during the atmospheric river storms. An analysis of distributed snow water equivalent indicates that snowmelt increased water available for runoff watershed‐wide by 37% (25–52% at 90% confidence). The results highlight potential threats to public safety and infrastructure associated with a warmer and more variable climate.
Plain Language Summary
In February 2017, extreme runoff into California's second‐largest reservoir, Lake Oroville, and cracks in the reservoir's spillways resulted in evacuations of thousands of people and major repair costs. We analyzed to what extent the atmospheric river storms that caused the extreme runoff were unusual in terms of precipitation, snowmelt, temperature, and moisture in the air. We found that the precipitation amounts were less unusual than the runoff amounts, suggesting that other factors were involved. We also found that snowmelt in the Sierra Nevada mountains above the reservoir was the heaviest on record at many locations, driven by unusually warm temperatures and deep preexisting snowpack before the storms began. Thus, the warm temperatures and record melt likely increased the water available for runoff by about a third during the spillways incident. Our findings are consistent with other studies that suggest that unusually warm temperatures during winter atmospheric river storms in the Western United States are associated with flood risk due to substantial rainfall and snowmelt. Other studies show that climate change is expected to increase the type of flood risk in the 2017 incident.
Key Points
The atmospheric river event causing the 2017 Oroville Dam spillways incident was more exceptional for runoff than precipitation totals
High rain‐snow elevations, deep antecedent snowpack, and unprecedented snowmelt are shown to explain the discrepancy
We highlight the importance of considering snowmelt, rain‐snow elevations, and climate change in assessing current and future flood risk
Atmospheric rivers (ARs) are elongated narrow bands of enhanced water vapor that can cause intense rainfall and flooding. ARs only appeared in the literature the last 30 years, and there has been ...much debate about how to define ARs and how to identify them. As a result, a wide range of AR identification algorithms have been produced with variations in the conditions required for an object to be classified as an AR and differences in the input data. One of the key conditions in most AR identification algorithms is a minimum threshold of water vapor flux, along with geometric criteria. The aim of this study is to explore uncertainties in global AR identification based on a single integrated water vapor transport (IVT)‐based identification method. We conduct a sensitivity analysis under one algorithmic framework to explore the effects of different IVT thresholds, input data resolutions, and regridding methods during the Years of Tropical Convection operational analysis (May 2008 to April 2010). We found that the resolution and regridding method affects the number of ARs identified but the seasonal cycle is maintained. AR identification is highly sensitive to the choice of IVT threshold; importantly, the commonly used 250 kg m−1 s−1 IVT threshold is not appropriate for global studies with detection methods that also include a restrictive geometric condition as this combination can lead to the strongest systems failing to be identified. The uncertainties within a single AR detection method and input data parameters may be as large as uncertainties across AR detection methodologies.
Plain Language Summary
Atmospheric rivers (ARs) are large corridors of increased moisture flow in the lower atmosphere. ARs can cause hazards such as heavy rainfall, damaging winds, landslides, and flash flooding. Recently, there has been a lot of discussion about how scientists should define these weather phenomena; for example, what is the minimum amount of water needed for a weather system to be considered an AR? In order to study ARs, scientists often look at large data sets over multiple decades. So instead of searching for ARs manually in these huge data sets, they create computer algorithms that identify ARs automatically. As a result, there has been a large variety of different algorithms developed. Using a single algorithm, we answer the following question: How do small differences between data sets and moisture content of ARs affect the detection results? We found that when ARs are defined using lower thresholds of vapor transport and geometric conditions, algorithms may fail to identify the strongest ARs. Additionally, we quantified some of the uncertainty associated with using data sets of different fidelity. These results are useful for helping scientists choose the best threshold and data sets for their study.
Key Points
An IVT‐based identification method was used to perform extensive sensitivity tests on IVT threshold and data set parameters (resolution and regridding)
IVT thresholds below 350 kg m−1 s−1 may miss the strongest ARs when combined with a geometric criterion
Simple methodological changes to resolution, order of operations, regridding methods, and IVT threshold can result in considerable changes to the detection results
With the highest population density in China, eastern China has an unshakable position in Chinese socioeconomic development. To understand the precipitation changes and the related mechanisms is of ...great significance for regional management of water resources and agricultural irrigation. In this study, the impacts of western North Pacific subtropical high (WNPSH) on precipitation changes in eastern China and the underlying processes are investigated. The results indicate that the strength and location of WNPSH are in close relations with the changes of summer precipitation in eastern China, and their influences vary across both space and time. In particular, WNPSH exerts remarkable impacts on precipitation in June and July in Jiang‐Huai region and precipitation in June in South China such as the Pearl River basin. The interannual variations of WNPSH exhibit significant correlations with water vapor flux in East Asia, and the variations of the location and direction of the west flank of the WNPSH are well corroborated with the influences of the East Asian summer monsoon (EASM) on precipitation in eastern China. The westward extension of WNPSH tends to favor the strong moisture transport to East Asia, intensify the EASM, and thus increase water vapor flux in East Asia, which greatly benefits the occurrence of Meiyu regimes in Jiang‐Huai region. Besides, analysis results also show that the westward extension of WNPSH drives tropical cyclones southward so as to increase the occurrence of extreme precipitation in South China. This study helps to bridge the knowledge gap in the relationship between WNPSH, tropical cyclones, and summer precipitation events in eastern China.
Key Points
Novel insights into relations between WNPSH and summer extreme precipitation
First investigation of relations between CT and summer extreme precipitation
Clarifying physical mechanisms behind summer extreme precipitation
Accurate representation of soil and snow state variables in the land surface model is crucial for good simulation results. In order to investigate the potential impacts of the overestimated snow ...cover over the Tibetan Plateau (TP) on precipitation over China, we designed comparative experiments over TP with and without updated soil texture data, soil hydrological parameters, and the fresh snow density scheme to address this issue with the Weather Research and Forecasting Model (WRF). The results show that snow cover fraction (SCF) and surface albedo in winter on the TP were overestimated in the WRF control experiment (CTL), with albedo bias exceeding 0.4 in the western TP. The SCF in the WRF improved experiment (WRFIM) is about 8% lower than that of the CTL, and the bias is decreased to 0.2–0.3 in the interior of the TP. The thermal and dynamic effects of the TP in winter have a significant impact on the weather and climate of East Asia during summer. Thus, the simulated summer rainfall bias is significantly reduced by WRFIM in North China, and the mid-lower reaches of the Yangtze River, along with the spatial correlation coefficient between the observed-based and WRF-simulated rainfall increased from 0.76 in CTL to 0.88 in WRFIM. The WRFIM-simulated reductions in snow cover and albedo cause a decrease in upward shortwave radiation and eventually increase net surface radiation. The horizontal temperature gradient of the atmosphere is increased in the WRFIM compared to the CTL, and the increased temperature in the lower and middle layers accommodates more water vapor, which is not conducive to precipitation formation. Correspondingly, the Western Pacific Subtropical High at 500 hPa in the middle troposphere weakened. The low-level anticyclonic circulation at 850 hPa also weakened to the east, affecting water vapor transport in eastern China. It leads to a decrease in the water vapor transported northward by southeasterly from the western Pacific Ocean and a decrease in the water vapor flux reaching North China. This work indicates that accurate characterization of soil properties and snow cover on the TP is crucial for improving the simulation bias of summer rainfall in China.
In situ measurements in the climatically important upper troposphere–lower stratosphere (UTLS) are critical for understanding controls on cloud formation, the entry of water into the stratosphere, ...and hydration–dehydration of the tropical tropopause layer.
Accurate in situ measurement of water vapor in the UTLS however is difficult because of low water vapor concentrations (<5 ppmv) and a challenging low temperature–pressure environment.
The StratoClim campaign out of Kathmandu, Nepal, in July and August 2017, which made the first high-altitude aircraft measurements in the Asian Summer Monsoon (ASM), also provided an opportunity to intercompare three in situ hygrometers mounted on the M-55 Geophysica: ChiWIS (Chicago Water Isotope Spectrometer), FISH (Fast In situ Stratospheric Hygrometer), and FLASH (Fluorescent Lyman-α Stratospheric Hygrometer).
Instrument agreement was very good, suggesting no intrinsic technique-dependent biases: ChiWIS measures by mid-infrared laser absorption spectroscopy and FISH and FLASH by Lyman-α induced fluorescence.
In clear-sky UTLS conditions (H2O<10 ppmv), mean and standard deviations of differences in paired observations between ChiWIS and FLASH were only (-1.4±5.9) % and those between FISH and FLASH only (-1.5±8.0) %.
Agreement between ChiWIS and FLASH for in-cloud conditions is even tighter, at (+0.7±7.6) %.
Estimated realized instrumental precision in UTLS conditions was 0.05, 0.2, and 0.1 ppmv for ChiWIS, FLASH, and FISH, respectively.
This level of accuracy and precision allows the confident detection of fine-scale spatial structures in UTLS water vapor required for understanding the role of convection and the ASM in the stratospheric water vapor budget.
Abstract
It has been suggested that summer rainfall over central Asia (CA) is significantly correlated with the summer thermal distribution of the Tibetan Plateau (TP) and the Indian summer monsoon ...(ISM). However, relatively few studies have investigated their synergistic effects of different distribution. This study documents the significant correlations between precipitation in CA and the diabatic heating of TP and the ISM in summer based on the results of statistical analysis and numerical simulation. Summer precipitation in CA is dominated by two water vapor transport branches from the south that are related to the two primary modes of anomalous diabatic heating distribution contributed by the TP and ISM precipitation, that is, the “+−” dipole mode in the southeastern TP and the Indian subcontinent (IS), and the “+−+” tripole mode in the southeastern TP, the IS, and southern India. Both modes exhibit obvious midlatitude Silk Road pattern (SRP) wave trains with cyclone anomalies over CA, but with different transient and stationary eddies over South Asia. The different locations of anomalous anticyclones over India govern two water vapor transport branches to CA, which are from the Arabian Sea and the Bay of Bengal. The water vapor flux climbs while being transported northward and can be transported to CA with the cooperation of cyclonic circulation. The convergent water vapor and ascending motion caused by cyclonic anomalies favor the precipitation in CA. Further analysis corroborates the negative south Indian Ocean dipole in February could affect the tripole mode distribution of TP heating and ISM via the atmospheric circulation, water vapor transport, and anomalous Hadley cell circulation. The results indicate a reliable prediction reference for summer precipitation in CA.
During droughts, soil evaporation is often constrained by water vapor transport through an air‐dry soil layer (DSL). Fick's water vapor diffusion is widely regarded as the only process for such ...transport; however, field studies conducted in arid and semi‐arid conditions showed measured evaporation rates higher than those predicted by diffusion. Therefore, transport processes other than diffusion could be relevant. To study the evaporation through a DSL, the same lysimeter column with 70 cm thick DSL as earlier applied in laboratory in Balugani et al. (2021), was installed in the field in Spain applying an original weighing setup to measure evaporation. The correlation between the measured evaporation and possible drivers of the water vapor transport were evaluated. With the DSL thickness of 70 cm in 2012 and 12 cm in 2015, the lysimeter recorded similar groundwater evaporation rates: 1.25 and 1.05 mm days−1, respectively; these rates were much larger than the laboratory recorded rates (0.3 mm days−1) and those estimated in this study using Hydrus1D accounting for non‐isothermal liquid water fluxes and water vapor diffusion. The main forcing driver of the field lysimeter evaporation was the soil profile temperature fluctuation, which concealed other less important forcing factors, that is, atmospheric pressure fluctuations and diffusion. A multivariate regression model to estimate evaporation was proposed, based on the profile temperature fluctuation, that, when added to the atmospheric pressure fluctuations, yielded reliable estimates of the cumulative evaporation measured in both 2012 and 2015.
Key Points
Development of an original lysimeter setup allowing for separate measurements of evaporation (E $E$) and groundwater evaporation (Eg ${E}_{g}$)
Under dry soil layer condition, lysimeter E=Eg $E={E}_{g}$, ∼1.25 mm days−1 in 2012 and 1.05 mm days−1 in 2015
Lysimeter evaporation correlated with profile soil temperature measurements and solar radiation changes; vapor diffusion was negligible
Abstract An analysis of atmospheric rivers (ARs) as defined by an automated AR detection tool based on integrated water vapor transport (IVT) and the connection to heavy precipitation in the ...southeast United States (SEUS) is performed. Climatological water vapor and water vapor transport fields are compared between the U.S. West Coast (WCUS) and the SEUS, highlighting stronger seasonal variation in integrated water vapor in the SEUS and stronger seasonal variation in IVT in the WCUS. The climatological analysis suggests that IVT values above ~500 kg m −1 s −1 (as incorporated into an objective identification tool such as the AR detection tool used here) may serve as a sensible threshold for defining ARs in the SEUS. Atmospheric river impacts on heavy precipitation in the SEUS are shown to vary on an annual cycle, and a connection between ARs and heavy precipitation during the nonsummer months is demonstrated. When identified ARs are matched to heavy precipitation days (>100 mm day −1 ), an average match rate of ~41% is found. Results suggest that some aspects of an AR identification framework in the SEUS may offer benefit in forecasting heavy precipitation, particularly at medium- to longer-range forecast lead times. However, the relatively high frequency of SEUS heavy precipitation cases in which an AR is not identified necessitates additional careful consideration and incorporation of other critical aspects of heavy precipitation environments such that significant predictive skill might eventually result.
The spatial and temporal distribution of tropospheric water vapour in the South Indian Ocean (SIO) basin is investigated using observations collected from twelve GNSS stations spanning the basin. The ...comparison of GNSS‐derived integrated water vapour (IWV) content against radiosoundings and satellite‐borne microwave radiometer data shows good agreement, with global uncertainties ranging from 0.76 to 1.17 kg·m−2, depending on GNSS station locations. GNSS‐derived IWV contents show a strong seasonal cycle, characterized by higher water vapour content during the austral summer, when the InterTropical Convergence Zone (ITCZ) is located in the Southern Hemisphere. At the seasonal time‐scale, the observed annual IWV amplitude varies from 10 to 15 kg·m−2 near the Equator to 20 to 30 kg·m−2 in the Subtropics. The GNSS IWV signature of the Madden–Julian Oscillation (MJO) is hardly noticeable during the Austral winter, but varies from 1–2 to 4 kg·m−2 between the active and suppressed phases of the MJO during austral summer. At diurnal time‐scales, GNSS IWV shows larger diurnal amplitude over land (2–3 kg·m−2) than over open ocean (1–2 kg·m−2), with highest amplitudes (up to 7 kg·m−2) observed over large and mountainous islands. The phase analysis of the IWV diurnal cycle indicates that the diurnal maximum (minimum) is reached in the late afternoon/evening (morning) over land, at night (mid‐day) over ocean and in the early morning (late afternoon) at coastal locations. A comparison of GNSS‐derived IWV contents against fifth‐generation European Centre for Medium‐range Weather Forecasts (ECMWF) Reanalysis (ERA5) data shows that ERA5 generally correctly reproduces the IWV content at both seasonal, intra‐seasonal and diurnal time‐scales, although some discrepancies can be noticed over small islands characterised by steep orography. The signature of the MJO in ERA5 also shows good agreement with GNSS observations at most studied locations.
Location of the twelve ground‐based GNSS stations (circles) and the five radiosonde stations (triangles) used in this study. Insert shows the locations of new GNSS research stations recently deployed in the southwest Indian Ocean basin in the framework of the Indian Ocean GNSS Applications for Meteorology (IOGA4MET) research program. Red, blue and green colours indicate the three transects discussed in the paper.
A recent study presented nearly two decades of airborne atmospheric river (AR) observations and concluded that, on average, an individual AR transports ∼5 × 10⁸ kg s−1 of water vapor. The study here ...compares those cases to ARs independently identified in reanalyses based on a refined algorithm that can detect less well-structured ARs, with the dual-purpose of validating reanalysis ARs against observations and evaluating dropsonde representativeness relative to reanalyses. The first comparison is based on 21 dropsonde-observed ARs in the northeastern Pacific and those closely matched, but not required to be exactly collocated, in ERA-Interim (MERRA-2), which indicates a mean error of −22% (−8%) in AR width and +3% (−1%) in total integrated water vapor transport (TIVT) and supports the effectiveness of the AR detection algorithm applied to the reanalyses. The second comparison is between the 21 dropsonde ARs and ∼6000 ARs detected in ERA-Interim (MERRA-2) over the same domain, which indicates a mean difference of 5% (20%) in AR width and 5% (14%) in TIVT and suggests the limited number of dropsonde observations is a highly (reasonably) representative sampling of ARs in the northeastern Pacific. Sensitivities of the comparison to seasonal and geographical variations in AR width/TIVT are also examined. The results provide a case where dedicated observational efforts in specific regions corroborate with global reanalyses in better characterizing the geometry and strength of ARs regionally and globally. The results also illustrate that the reanalysis depiction of ARs can help inform the selection of locations for future observational and modeling efforts.
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