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CW3E Publication Notice: Multi-Model Subseasonal Prediction Skill Assessment of Water Vapor Transport Associated with Atmospheric Rivers over the Western U.S.

CW3E Publication Notice

Multi-Model Subseasonal Prediction Skill Assessment of Water Vapor Transport Associated with Atmospheric Rivers over the Western U.S.

March 24, 2023

A new paper entitled “Multi-Model Subseasonal Prediction Skill Assessment of Water Vapor Transport Associated with Atmospheric Rivers over the Western U.S.” was recently published in the Journal of Geophysical Research: Atmospheres and authored by CW3E researcher Zhenhai Zhang, Michael DeFlorio (CW3E), Luca Delle Monache (CW3E), Aneesh Subramanian (University of Colorado Boulder), Martin Ralph (CW3E), Duane Waliser (NASA JPL), Minghua Zheng (CW3E), Bin Guan (NASA JPL), Alexander Goodman (NASA JPL), Andrea Molod (NASA GMAO), Frederic Vitart (ECMWF), Arun Kumar (NCEP CPC), and Hai Lin (ECCC). As part of CW3E’s 2019-2024 Strategic Plan, CW3E seeks to improve atmospheric river (AR) prediction at subseasonal to seasonal (S2S; 2-week to 6-month) lead times. This work contributes to that specific goal and provides an assessment of subseasonal prediction skill of weekly water vapor transport associated with ARs over the Western U.S. in four dynamical model hindcast systems.

More skillful S2S forecasts of ARs are in high demand in the water supply management and flood control communities. This study aims to provide a multi-model S2S prediction skill assessment for the accumulated water vapor transport associated with ARs, which is closely related to wintertime extreme precipitation over the western U.S. The subseasonal prediction skill is evaluated at 1–4 weeks lead time in four dynamical model hindcast datasets from National Centers for Environmental Prediction (NCEP), European Centre for Medium‐Range Weather Forecasts (ECMWF), Environment and Climate Change Canada (ECCC), and Global Modeling and Assimilation Office (GMAO) at National Aeronautics and Space Administration (NASA). Three reanalysis datasets, including NCEP CFSR, ECMWF ERA5, and NASA MERRA2, are used to evaluate the sensitivity of the prediction skill to the choice of reference dataset.

This study shows that the AR-related water vapor transport is underestimated in ECMWF and ECCC over most of the investigated region, while its maximum has a southeastward shift in NCEP and GMAO at 3–4 weeks lead time. The root mean square error, anomaly correlation coefficient, and Brier skill score are calculated to quantify the prediction skill in both a deterministic and probabilistic sense. At week-3 lead time, the models have significant skill near the lower latitudes (< 40N) of the eastern North Pacific, extending northeastward to the California coastal area (Figure 1). Models have higher skills in forecasting no and strong AR-related water vapor transport cases than weak cases at weeks 1–4 lead time. The impacts of the Madden-Julian Oscillation (MJO) on the prediction skill are also explored. The results show that the MJO’s impact at week-3 lead time is larger than at week-1 and week-2 lead. At week-3 lead, the modulation of prediction skill by MJO mainly occurs over Central and Southern California. However, the impacts have large uncertainties across models, which might be caused by the different model performances in predicting the MJO and the relevant teleconnections.

This work is supported by the California Department of Water Resources Atmospheric River Program. It provides scientific support to the CW3E Subseasonal AR Experimental Forecasts, which are developed via a close collaboration between CW3E and NASA JPL.

Figure 1: (a)-(d): Anomaly correlation coefficients (ACCs) of the AR T-IVT for the four models with respect to ERA5 at week-1 lead time during the cool seasons of the hindcast periods. (e)-(h), (i)-(l), and (m)-(p) are the same as (a)-(d) but for week-2, week-3, and week-4 lead times, respectively. Only ACC values at 95% confidence level based on a 1000-resampling bootstrap statistical significance test are plotted.

Zhang, Z., DeFlorio, M. J., Delle Monache, L., Subramanian, A. C., Ralph, F. M., Waliser, D. E., … & Lin, H. Multi‐Model Subseasonal Prediction Skill Assessment of Water Vapor Transport Associated with Atmospheric Rivers over the Western US. Journal of Geophysical Research: Atmospheres, e2022JD037608. http://doi.org/10.1029/2022JD037608

CW3E AR Update: 5 April 2023 Outlook

April 5, 2023

Click here for a pdf of this information.

Multiple Atmospheric Rivers Forecast to Impact Pacific Northwest Though the Weekend

A series of atmospheric rivers (ARs) are forecast to develop over the North Pacific Ocean and make landfall over the Pacific Northwest during the next several days
The first AR is forecast to make landfall tonight and bring AR2 conditions (based on the Ralph et al. 2019 AR Scale) to coastal Washington and Oregon
Another AR is forecast to make landfall this weekend, bringing AR2 conditions to coastal Washington and Oregon and AR1 conditions to coastal Northern California
There is still considerable uncertainty in the timing, duration, and intensity of the second landfalling AR
The NWS Weather Prediction Center (WPC) is forecasting at least 3–7 inches of precipitation in the Cascades and Coast Ranges in Washington and Oregon during the next 7 days, with more than 10 inches possible in the Olympic Mountains
The NWS WPC has issued a marginal risk of rainfall exceeding flash flood guidance along the coast from Northern California to the Olympic Peninsula tomorrow into Friday morning
Several rivers in Washington and Oregon are forecast to rise above monitor stage during the next 7 days
A majority of the precipitation is forecast to fall as rain in most watersheds due to higher freezing levels during these AR events

Click images to see loops of GFS IVT and IWV forecasts Valid 1200 UTC 5 April – 1200 UTC 10 April 2023

Summary provided by C. Castellano, S. Bartlett, and S. Roj; 5 April 2023

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*Outlook products are considered experimental

CW3E S2S Outlook: 3 April 2023

April 3, 2023

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Summary provided by C. Castellano, J. Wang, M. DeFlorio, and J. Kalansky; 3 April 2023

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*Outlook products are conside

CW3E Welcomes Dr. Zhiqi Yang

April 3, 2023

Zhiqi Yang joined CW3E’s subseasonal-to-seasonal (S2S) team as a Postdoctoral Scholar in April 2023. She graduated with a Ph.D. from the Civil and Environmental Engineering Department at the University of Iowa in 2021. Prior to CW3E, her research focused on extreme precipitation, climate change, numerical climate modeling (WRF-CHEM), developing and maintaining the Euro-Mediterranean Center on Climate Change (CMCC) seasonal forecast system, and evaluating seasonal forecasted TCs activities.

At CW3E, Zhiqi’s research interests are centered on enhancing the deterministic and probabilistic S2S prediction of weather parameters, particularly precipitation and atmospheric river (AR)-related parameters, over the western United States. She aims to develop an innovative experimental S2S forecast product that will greatly benefit water management in the region. Zhiqi is also keenly interested in exploring diverse research topics such as extreme weather, climate change, hydrometeorology, and Tropical cyclones (TCs)!

CW3E Welcomes Joseph Bursey

March 28, 2023

Joseph Bursey joined CW3E as a research project manager in March 2023. He received his BS in Biology from Winthrop University in Rock Hill, SC and then became manager for a plankton ecology research lab at NC State. Here, Joseph went on to also earn his Masters in Marine Science (2016) with research focusing on seasonal differences plankton in biodiversity, trophic cascades, and carbon energy transfer to upper trophic levels. Essentially who’s there seasonally, who’s eating who, and carbon energy movement through the food web in Bogue Sound, North Carolina.

After completing his masters degree, he became facility manager for an aquaculture research lab at NC State. Here, he worked on numerous larvae culture rearing projects with the scope to reduce overfishing by providing sustainable alternatives. He worked with PIs to meet their research needs at the facility and handled all facility maintenance and repairs. From here, he traveled across the country to become hatchery manager for a fish enhancement program at Hubbs Seaworld, San Diego where he managed a team to spawn and release thousands of fish.

Joseph is an avid wildlife photographer and musician and has a deep personal interest in mitigating human impacts on the environment. He has long aspired to join the Scripps Institution of Oceanographer to further his goal at a like-minded organization.

His role at CW3E will be serving as research project manager to help support Forecast Informed Reservoir Operations (FIRO). He looks forward to bringing his varied experience, managerial skills, and passion to CW3E research efforts to enhance CW3E’s ability to provide 21st Century water cycle science, technology and outreach to support effective policies and practices that address the impacts of extreme weather and water events on the environment, people and the economy of Western North America.

Undergraduates of AR Recon

March 27, 2023

CW3E would like to highlight two UC San Diego undergraduate students who were instrumental in the success of the annual CW3E-led Atmospheric River Reconnaissance effort. Both served in the role of flight track coordinator under the leadership of CW3E scientist Shawn Roj.

Kyle Hurley, originally from Crofton, Maryland, enlisted into the United States Marine Corps in 2016 where he deployed two times within four years and was honorably discharged in 2020. Since then, Kyle has achieved an associate’s degree in both Biology and Chemistry with honors. In April of 2022, Kyle Hurley was then accepted into UC San Diego to pursue a bachelor’s degree in Oceanic and Atmospheric Sciences. Kyle has high hopes of becoming a meteorologist, working in the field of severe weather. Kyle joined the CW3E team back in November of 2022.

Jackson Ludtke, of Silver Spring, Maryland, enrolled in UC San Diego in the fall of 2021. He is majoring in Urban Studies and Planning with minors in Geosciences and Climate Change Studies. After earning his private pilot’s license in the summer of 2021, Jackson plans on pursuing a career in aviation and hopes of flying for NOAA or the Coast Guard one day. The late Professor Jane Teranes helped Jackson realize how much he enjoys helping out on the logistical side of science. He has been working at the Center since December of 2021.

Kyle and Jackson have quickly learned how to work with the flight planning tool and develop flight tracks during the morning briefings. They have both served as the lead flight planning coordinator. It took a large, dedicated team to cover CW3E’s longest and most active AR Recon season, and Kyle and Jackson are looking forward to contributing next season.

New CW3E Award Represented at the Colorado River District’s State of the River Event

March 27, 2023

Colorado River District hosted the State of the River – Upper Yampa event on March 23, 2023, in Steamboat Springs, Colorado, with roughly 100 attendees. Madison Muxworthy, of Yampa Valley Sustainability Council, spoke on behalf of the project team working on Enhancing Soil Moisture Observations to Support Water Resource Management in the Upper Yampa River Basin. This project is led by PI Dr. Martin Ralph and includes staff from the Center for Western Weather and Water Extremes, Yampa Valley Sustainability Council, Colorado Mountain College, and Upper Yampa Water Conservancy District. The presentation focused on the future expansion of the Yampa Basin soil moisture monitoring network over the next three years, made possible by recent grant funding from Colorado River District’s Community Funding Partnership, Colorado Water Conservation District’s Water Plan Grant, and Upper Yampa Water Conservancy District. CW3E is really excited to be working with a group of stellar partners on such an impactful project to support robust monitoring in the region.

CW3E and Colorado Partners secure funding for soil moisture network expansion

March 27, 2023

CW3E, Yampa Valley Sustainability Council (YVSC) and key partners Upper Yampa Water Conservancy District (UYWCD) and Colorado Mountain College (CMC) have secured funding for the project, “Enhancing Soil Moisture Observations to Support Water Resource Management in the Upper Yampa River Basin.” This funding enables the project team to expand upon the first soil moisture monitoring station that was installed in the Yampa River Basin in September 2022 and install eight more stations over the next two years.

The expanding Yampa Basin soil moisture network measures moisture concentrations in the soil as well as soil and air temperature, precipitation, snow depth, fuel moisture, and other key climatic variables. Soil moisture data is key to understanding how snowpack relates to spring runoff and river flows. Snow-to-flow dynamics – or how much water is delivered to our rivers from our snowpack – are mediated by soil moisture. Drier soils in upland areas function like dry sponges and absorb water, reducing the amount of water delivered to rivers and thus reducing flows. The Yampa Basin is already experiencing changes in snow-to-flow dynamics, where normal snowpack years are followed by low spring and summer flows.

“The timing for the launch of the network is key,” said Dr. Michelle Stewart, Executive Director of YVSC. “Our snow-to-flow patterns have been changing considerably in recent years and monitoring soil moisture data is an important step towards a better understanding of how water in our basin is changing due to changing climate.”

The Yampa Basin soil moisture network stands to benefit forecasters, water managers, and water users to better understand water supply by increasing the understanding of soils, which Dr. Marty Ralph, Principal Investigator on the project and Director of CW3E, calls the “fourth reservoir” in
water planning. The primary types of reservoirs water managers think about are snow, rivers/streams, and reservoirs, but soils have been a missing part of the puzzle. The project goals are to reduce uncertainty in seasonal snowmelt runoff predictions and work with stakeholders in the Yampa Valley to appropriately integrate these data into water management decision support, including at sub-seasonal to seasonal forecast lead times ranging from weeks, months, and seasons. The network will be critical to establishing a baseline for long-term monitoring of new trends in soil moisture expected due to greater evapotranspiration – the cumulative transfer of moisture from soils and plants to the atmosphere – related to warming as climate changes.
The funding is an exciting development for the Basin because it allows for investments in infrastructure that increase resilience to water changes in the basin. According to Andy Rossi, General Manager of the UYWCD, “the data will be invaluable to UYWCD in forecasting runoff and assisting with reservoir and water resource management decisions,” and the hope is that, “this network will help close a data gap in the Yampa River Basin and serve as a useful tool for water managers in our basin and beyond.” UYWCD’s initial funding has been instrumental to the successful installation of this first station and an important anchor for building out the network.

Colorado Mountain College, which will partner to provide student career training in climate monitoring and instrument maintenance, sees the expansion of the network as an important contribution to regional workforce development. Dr. Nathan Stewart, Professor of Ecosystem Science and Sustainability, identifies this funding as integral to student career pathways in water. “Expansion of our region’s Soil Moisture monitoring network will provide us with a state-of-the-art platform for technical training in meteorology, hydrology, and ecosystem science,” he said. “Student engagement with this network is essential to the recruitment and development of our future western water workforce.”

The Yampa Basin soil moisture network began in 2021 when extreme drought conditions led CW3E and YVSC to partner with the UYWCD to identify critical areas for soil moisture monitoring in the basin through a basin analysis. In 2022, UYWCD funded the installation of the first soil moisture and surface meteorological monitoring station near Stagecoach Reservoir and the development of an online data portal site for project partners and public use.

This three year project was funded through a joint grant from the Colorado Water Conservation Board (CWCB) Water Plan Grants, Colorado River District’s (CRD) Community Funding Partnership and support from UYWCD.

“It is an exciting opportunity for our Center and key partners YVSC and CMC to pull together and create this network,” says Ralph. “It is envisioned as a pathfinder for the future. We are excited to be working closely with UYWCD, CRD, and CWCB to develop this capability and apply it to the special water management needs in the Yampa, from local to state and regional scales.”

This collaborative effort between CW3E, YVSC, CMC, and UYWCD includes additional project partners at Aspen Global Change Institute and Natural Resources Conservation Service.

CW3E Publication Notice: Deep Learning Forecast Uncertainty for Precipitation over Western US

CW3E Publication Notice

Deep Learning Forecast Uncertainty for Precipitation over Western US

March 24, 2023

The growing popularity of deep learning does not miss the numerical weather prediction community. CW3E researcher Weiming Hu, along with the co-authors Mohammadvaghef Ghazvinian, William E. Chapman (NCAR/UCAR Climate & Global Dynamics Lab), Agniv Sengupta, F. Martin Ralph, and Luca Delle Monache, recently published a paper titled “Deep Learning Forecast Uncertainty for Precipitation over Western US” in the Monthly Weather Review. The work contributes to the goals of CW3E’s 2019-2024 Strategic Plan to support Atmospheric River (AR) Research and Applications through the use of Emerging Technologies, namely Deep Learning-based post-processing algorithms.

This study focuses on uncertainty quantification for daily precipitation forecasts using a Deep Learning architecture, Unet, under the model output post-processing framework. For training, it leverages CW3E’s 34-year Reforecast dataset based on the West Weather Research and Forecasting (West-WRF) model available at a 3 km spatial resolution. Precipitation ground truth is obtained from the Parameter Elevation Regression on Independent Slopes Model (PRISM), which is a daily gridded precipitation dataset over the continental US at a 4 km spatial resolution. The Unet is trained to learn the non-linear relationship between the West-WRF and PRISM to calibrate precipitation forecasts. Unet has been tested for four water years conditioned on the state of the ENSO, namely 1997 (an El Niño year), 2011 (a La Niña year), 2013, and 2016 (ENSO neutral years) and compared with other benchmark methods involving parametric methods (censored, shifted Gamma distribution and mixed-type meta Gaussian distribution) and non-parametric methods (Analog Ensemble).

The main contribution of this work is the generation of probabilistic forecasts up to 4-day local lead times from a deterministic model, like West-WRF, with improved accuracy and reliability. Fig. 1 shows the study region (panel a), the deterministic (panels b and c), and probabilistic (panel d) skills of the proposed Unet model. Two metrics are used for deterministic verification – the Root Mean Square Error (RMSE) and the Pearson correlation. The Continuous Ranked Probability Score (CRPS) is used as the probabilistic metric. For all metrics, their skill scores are calculated against climatology with the higher being better. Unet consistently shows outperformance over other benchmark methods across all lead days.

Figure 1: (a) shows the study domain. (b, c, d) show deterministic (RMSE, correlation) and probabilistic (CRPS) verification aggregated from four test years and all grid points from the study region.

Fig. 2 presents the verification over space using the Brier score which is a metric that measures the accuracy of probabilistic forecasts. The skill score is compared with three different benchmark methods. Positive values (in green shading) indicate skill improvement in the Unet compared to the benchmark. Panels (a, b, c) reflect the model skill for detecting rain events (>1 mm). More importantly, panels (d ~ i) illustrate how Unet produces more accurate forecasts for extreme events (the 95-th and 99-th percentiles) over areas that are typically susceptible to strong precipitation.

Figure 2: Brier skill scores of Unet averaged from all lead days for three thresholds, 1 𝑚𝑚 (first row), 95% (second row), and 99% (third row) of the location-specific climatological distribution, against MMGD (first column), CSGD (second column), AnEn (third column); the fourth column is generated from PRISM. (j) shows a map of PoP using 1 𝑚𝑚 as the threshold, whereas (k) and (i) show the precipitation map for the 95-th and 99-th percentiles, respectively.

We also investigated the performance sensitivity to data volume sizes and found that Unet continues to learn non-linear relationships better than traditional methods and improves its performance as more data becomes available.

Hu, W., M. Ghazvinian, W. E. Chapman, A. Sengupta, F. M. Ralph, and L. Delle Monache, 2023: Deep Learning Forecast Uncertainty for Precipitation over Western US. Mon. Wea. Rev., https://doi.org/10.1175/MWR-D-22-0268.1, in press.

CW3E Event Summary: 20-22 March 2023

23 March 2023

Click here for a pdf of this information.

Atmospheric River Brings More Rain and Flooding to California and Arizona

An atmospheric river (AR) formed over the subtropical Northeast Pacific and made landfall in Southern California on 20 Mar
A surface cyclone developed on the cold side of the AR and underwent rapid intensification as it approached the Bay Area
AR2 conditions were observed in coastal San Diego County and southern Arizona
The AR produced at least 1–3 inches of precipitation across coastal Southern CA and North Central AZ, with the highest amounts (> 4 inches) observed in the San Gabriel Mountains, CA and Coconino County, AZ
Rainbands wrapping around the low-pressure center produced > 4 inches of precipitation in a 24-hour period in portions of San Mateo and Santa Cruz Counties
Lower snow levels during this storm (compared to the two previous storms) allowed for significant snowfall accumulations (> 12 inches) in the higher terrain of the Transverse Ranges
Two weak tornadoes were reported in California during this storm; an EF0 on 21 March in a trailer park near Carpinteria, CA and an EF1 on 22 March in an industrial area of Montebello, CA, both causing structural damage to multiple buildings
According to ABC7 News Bay Area, at least 5 people died during this storm, all struck by falling trees. Two fatalities were reported in San Francisco and one in Oakland, Portola Valley, and Rossmoor respectively. (Link to ABC7 News Bay Area Reporting)
Damage due to high winds, heavy rain, and flooding were reported across Southern California and in parts of Arizona