Hydrometeorological characteristics of rain-on-snow events associated with atmospheric rivers

American Geophysical Union (AGU) | March 29th, 2016

Atmospheric rivers (ARs) are narrow, elongated, synoptic corridors of enhanced water vapor transport that play an important role in regional weather/hydrology. Rain-on-s

Atmospheric rivers (ARs) are narrow, elongated, synoptic corridors of enhanced water vapor transport that play an important role in regional weather/hydrology. Rain-on-snow (ROS) events during ARs present enhanced flood risks due to the combined effects of rainfall and snowmelt. Focusing onCalifornia’s Sierra Nevada, the study identifies ROS occurrences and their connection with ARs during the 1998–2014 winters. AR conditions, which occur during 17% of all precipitation events, are associated with 50% of ROS events (25 of 50). Composite analysis shows that compared to ARs without ROS, ARs with ROS areon average warmer by ~2 K, with snow water equivalent loss of ~0.7 cm/d (providing 20% of the combined water available for runoff) and ~50% larger streamflow/precipitation ratios. Atmospheric Infrared Sounderretrievals reveal distinct offshore characteristics of the two types of ARs. The results highlight the potential value of observing these events for snow, rain, and flood prediction.

Improved Bias Correction Techniques for Hydrological Simulations of Climate Change

American Meteorological Society (AMS) | December 13th, 2015

Global climate model (GCM) output typically needs to be bias corrected before it can be used for climate change impact studies. Three existing bias correction met

Global climate model (GCM) output typically needs to be bias corrected before it can be used for climate change impact studies. Three existing bias correction methods, and a new one developed here, are applied to daily maximum temperature and precipitation from 21 GCMs to investigate how different methods alter the climate change signal of the GCM. The quantile mapping (QM) and cumulative distribution function transform (CDF-t) bias correction methods can significantly alter the GCM’s mean climate change signal, with differences of up to 28C and 30% points for monthly mean temperature and precipitation, respectively. Equidistant quantile matching (EDCDFm) bias correction preserves GCM changes in mean daily maximum temperature but not precipitation. An extension to EDCDFm termed PresRat is introduced, which generally preserves the GCM changes in mean precipitation. Another problem is that GCMs can have difficulty simulating variance as a function of frequency. To address this, a frequency-dependent bias correction method is introduced that is twice as effective as standard bias correction in reducing errors in the models’ simulation of variance as a function of frequency, and it does so without making any locations worse, unlike standard bias correction. Last, a preconditioning technique is introduced that improves the simulation of the annual cycle while still allowing the bias correction to take account of an entire season’s values at once.

Incomplete Determination of the 2020 Groundwater Sustainability Plans Submitted for the San Joaquin Valley – Kern County Subbasin

California Department of Water Resources (DWR) | January 28th, 2022

Department management has reviewed the enclosed Staff Report, which recommends that the deficiencies identified should preclude approval of the Plan. Based on its review

Department management has reviewed the enclosed Staff Report, which recommends that the deficiencies identified should preclude approval of the Plan. Based on its review of the Staff Report, Department management is satisfied that staff have conducted a thorough evaluation and assessment of the Plan and concurs with, and hereby adopts, staff’s recommendation and all the corrective actions provided. The Department thus deems the Plan incomplete based on the Staff Report and the findings contained herein. A. The GSPs do not establish undesirable results that are consistent for the entire Subbasin. 1. While the Coordination Agreement presents Subbasin-wide undesirable results, the Subbasin’s fragmented approach towards establishing management criteria that define undesirable conditions in various parts of the Subbasin does not satisfy SGMA’s requirement to use same data and methodologies. B. The Subbasin’s chronic lowering of groundwater levels sustainable management criteria do not satisfy the requirements of SGMA and the GSP Regulations. 1. The GSPs relied on disparate methods to develop groundwater level minimum thresholds across the numerous GSPs and management areas. 2. The GSPs do not consistently and sufficiently document the effects of their selected minimum thresholds on beneficial uses and users in the Subbasin, nor explain how the minimum thresholds and measurable objectives that are set below historical lows will impact other applicable sustainability indicators, specifically water quality, land subsidence, and reduction of groundwater storage. C. The Subbasin’s land subsidence sustainable management criteria do not satisfy the requirements of SGMA and the GSP Regulations. 1. The Plan lacks a Subbasin-wide, coordinated approach to establishing land subsidence sustainable management criteria. 2. The GSPs and management areas that use their minimum thresholds for the chronic lowering of groundwater levels as proxy criteria for subsidence do not sufficiently demonstrate that groundwater levels (specifically groundwater levels below historical lows) are a reasonable proxy to avoid land subsidence that would substantially interfere with surface land uses.

Increased Interannual Precipitation Extremes over California under Climate Change

American Meteorological Society (AMS) | August 10th, 2015

Changes to mean and extreme wet season precipitation over California on interannual time scales are analyzed using twenty-first-century precipitation data from 34

Changes to mean and extreme wet season precipitation over California on interannual time scales are analyzed using twenty-first-century precipitation data from 34 global climate models. Models disagree on the sign of projected changes in mean precipitation, although in most models the change is very small compared to historical and simulated levels of interannual variability. For the 2020/21–2059/60 period, there is no projected increase in the frequency of extremely dry wet seasons in the ensemble mean. Wet extremes are found to increase to around 2 times the historical frequency, which is statistically significant at the 95% level. Stronger signals emerge in the 2060/61–2099/2100 period. Across all models, extremely dry wet seasons are roughly 1.5 to 2 times more common, and wet extremes generally triple in their historical frequency (statistically significant). Large increases in precipitation variability in most models account for the modest increases to dry extremes. Increases in the frequency of wet extremes can be ascribed to equal contributions from increased variability and increases to the mean. These increases in the frequency of interannual precipitation extremes will create severe water management problems in a region where coping with large interannual variability in precipitation is already a challenge. Evidence from models and observations is examined to understand the causes of the low precipitation associated with the 2013/14 drought in California. These lines of evidence all strongly indicate that the low 2013/14 wet season precipitation total can be very likely attributed to natural variability, in spite of the projected future changes in extremes.

Increasing precipitation volatility in twenty-first-century California

Nature Portfolio (Springer Nature) | April 23rd, 2018

Mediterranean climate regimes are particularly susceptible to rapid shifts between drought and flood—of which, California’s rapid transition from record multi-yea

Mediterranean climate regimes are particularly susceptible to rapid shifts between drought and flood—of which, California’s rapid transition from record multi-year dryness between 2012 and 2016 to extreme wetness during the 2016–2017 winter provides a dramatic example. Projected future changes in such dry-to-wet events, however, remain inadequately quantified, which we investigate here using the Community Earth System Model Large Ensemble of climate model simulations. Anthropogenic forcing is found to yield large twenty-first-century increases in the frequency of wet extremes, including a more than threefold increase in sub-seasonal events comparable to California’s ‘Great Flood of 1862’. Smaller but statistically robust increases in dry extremes are also apparent. As a consequence, a 25% to 100% increase in extreme dry-to-wet precipitation events is projected, despite only modest changes in mean precipitation. Such hydrological cycle intensification would seriously challenge California’s existing water storage, conveyance and flood control infrastructure.

Increasing water cycle extremes in California and in relation to ENSO cycle under global warming

Nature Portfolio (Springer Nature) | October 21st, 2015

Since the winter of 2013–2014, California has experienced its most severe drought in recorded history, causing statewide water stress, severe economic loss and

Since the winter of 2013–2014, California has experienced its most severe drought in recorded history, causing statewide water stress, severe economic loss and an extraordinary increase in wildfires. Identifying the effects of global warming on regional water cycle extremes, such as the ongoing drought in California, remains a challenge. Here we analyse large-ensemble and multi-model simulations that project the future of water cycle extremes in California as well as to understand those associations that pertain to changing climate oscillations under global warming. Both intense drought and excessive flooding are projected to increase by at least 50% towards the end of the twenty-first century; this projected increase in water cycle extremes is associated with a strengthened relation to El Niño and the Southern Oscillation (ENSO)—in particular, extreme El Niño and La Niña events that modulate California’s climate not only through its warm and cold phases but also its precursor patterns.

Influence of temperature and precipitation variability on near-term snow trends

Climatic Change (Springer) | October 17th, 2014

Snow is a vital resource for a host of natural and human systems. Global warming is projected to drive widespread decreases in snow accumulation by the end of the century

Snow is a vital resource for a host of natural and human systems. Global warming is projected to drive widespread decreases in snow accumulation by the end of the century, potentially affecting water, food, and energy supplies, seasonal heat extremes, and wildfire risk. However, over the next few decades, when the planning and implementation of current adaptation responses are most relevant, the snow response is more uncertain, largely because of uncertainty in regional and local precipitation trends. We use a large (40-member) single-model ensemble climate model experiment to examine the influence of precipitation variability on the direction and magnitude of near-term Northern Hemisphere snow trends. We find that near-term uncertainty in the sign of regional precipitation change does not cascade into uncertainty in the sign of regional snow accumulation change. Rather, temperature increases drive statistically robust consistency in the sign of future near-term snow accumulation trends, with all regions exhibiting reductions in the fraction of precipitation falling as snow, along with mean decreases in late-season snow accumulation. However, internal variability does create uncertainty in the magnitude of hemispheric and regional snow changes, including uncertainty as large as 33 % of the baseline mean. In addition, within the 40-member ensemble, many mid-latitude grid points exhibit at least one realization with a statistically significant positive trend in net snow accumulation, and at least one realization with a statistically significant negative trend. These results suggest that the direction of near-term snow accumulation change is robust at the regional scale, but that internal variability can influence the magnitude and direction of snow accumulation changes at the local scale, even in areas that exhibit a high signal-to-noise ratio.

Intensification of hydrological drought in California by human water management

American Geophysical Union (AGU) | January 25th, 2017

Interpreting Water Supply Forecasts

U.S. Bureau of Reclamation (USBR) | January 24th, 2012

For each Central Valley Project (CVP) allocation announcement, two forecasts are issued for each contract type by location within the CVP. Unless otherwise specified, all

For each Central Valley Project (CVP) allocation announcement, two forecasts are issued for each contract type by location within the CVP. Unless otherwise specified, all runoff forecasts are based on runoff volumes that would occur naturally without any upstream influences. For the February through May period, the runoff volume estimates are based on the observed inflow to date and current snow pack measurements made at the end of each preceding month. Water users need to know what the different forecasts represent if they are to use the information appropriately when making operational decisions. Following are explanations of each of the forecasts.

Investigating the Role of Snow Water Equivalent on Streamflow Predictability during Drought

American Meteorological Society (AMS) | October 20th, 2022

Snowpack provides the majority of predictive information for water supply forecasts (WSFs) in snow-dominated basins across the western United States. Drought conditions t

Snowpack provides the majority of predictive information for water supply forecasts (WSFs) in snow-dominated basins across the western United States. Drought conditions typically accompany decreased snowpack and lowered runoff efficiency, negatively impacting WSFs. Here, we investigate the relationship between snow water equivalent (SWE) and April–July streamflow volume (AMJJ-V) during drought in small headwater catchments, using observations from 31 USGS streamflow gauges and 54 SNOTEL stations. A linear regression approach is used to evaluate forecast skill under different historical climatologies used for model fitting, as well as with different forecast dates. Experiments are constructed in which extreme hydrological drought years are withheld from model training, that is, years with AMJJ-V below the 15th percentile. Subsets of the remaining years are used for model fitting to understand how the climatology of different training subsets impacts forecasts of extreme drought years. We generally report overprediction in drought years. However, training the forecast model on drier years, that is, below-median years (P15, P57.5], minimizes residuals by an average of 10%in drought year forecasts, relative to a baseline case, with the highest median skill obtained in mid- to late April for colder regions. We report similar findings using a modified National Resources Conservation Service (NRCS) procedure in nine large Upper Colorado River basin (UCRB) basins, highlighting the importance of the snowpack–streamflow relationship in streamflow predictability. We propose an “adaptive sampling” approach of dynamically selecting training years based on antecedent SWE conditions, showing error reductions of up to 20% in historical drought years relative to the period of record. These alternate training protocols provide opportunities for addressing the challenges of future drought risk to water supply planning.