Understanding the recent increase in multiyear La Niñas

Nature Portfolio (Springer Nature) | September 18th, 2023

Understanding Uncertainties in Future Colorado River Streamflow

American Meteorological Society (AMS) | January 1st, 2014

The Colorado River is the primary water source for more than 30 million people in the United States and Mexico. Recent studies that project streamf low changes in the Col

The Colorado River is the primary water source for more than 30 million people in the United States and Mexico. Recent studies that project streamf low changes in the Colorado River all project annual declines, but the magnitude of the projected decreases range from less than 10% to 45% by the mid-twenty-first century. To understand these differences, we address the questions the management community has raised: Why is there such a wide range of projections of impacts of future climate change on Colorado River streamflow, and how should this uncertainty be interpreted? We identify four major sources of disparities among studies that arise from both methodological and model differences. In order of importance, these are differences in 1) the global climate models (GCMs) and emission scenarios used; 2) the ability of land surface and atmospheric models to simulate properly the high-elevation runoff source areas; 3) the sensitivities of land surface hydrology models to precipitation and temperature changes; and 4) the methods used to statistically downscale GCM scenarios. In accounting for these differences, there is substantial evidence across studies that future Colorado River streamflow will be reduced under the current trajectories of anthropogenic greenhouse gas emissions because of a combination of strong temperature-induced runoff curtailment and reduced annual precipitation. Reconstructions of preinstrumental streamflows provide additional insights; the greatest risk to Colorado River streamf lows is a multidecadal drought, like that observed in paleoreconstructions, exacerbated by a steady reduction in flows due to climate change. This could result in decades of sustained streamflows much lower than have been observed in the ~100 years of instrumental record.

User’s Manual for the Draper Climate-Distribution Software Suite with Data-Evaluation Tools

U.S. Geological Survey (USGS) | March 20th, 2019

Development of a time series of spatially distributed climate data is an important step in the process of developing physically based environmental models requiri

Development of a time series of spatially distributed climate data is an important step in the process of developing physically based environmental models requiring distributed inputs of climate data beyond what is available from observations collected at climate stations. To prepare inputs required for model-mapping units across the study area, climate data (temperature and precipitation) are distributed by combining data from gridded surfaces of mean-monthly climate-data values with (often) widely spaced daily pointobservations. Examples of climate-data files used to develop PRMS-formatted input files for the Merced River Basin Precipitation-Runoff Modeling System (PRMS) are includedin this manual. The Draper Climate-Distribution Software Suite (Draper Suite) consists of the Draper climate-distribution program (Draper) and several supporting pre- and post-processing applications. Draper combines spatially distributed input in the form of monthly averaged values for precipitation, maximum temperature, and minimum temperature with daily observed data from climate stations to estimate distributed climate-data values at predefined locations across a study area (typically adrainage basin) on a daily time step. Alternative methods are used when station data are limited or missing for a particular day. Draper uses a set of required and optional input andoutput files with defined formats and naming conventions. Ashell application also is available to manage multiple runs of the Draper application. Other applications in the Draper Suite include (1) a toolto find and interactively remove outliers in the input data, (2) atool to check and enforce a minimum daily temperature range, and (3) a tool to view output diagnostic information as time- series graphs. These tools can be used iteratively to evaluate and improve the results from Draper as part of a work flow involving physically-based environmental models, such as the Precipitation-Runoff Modeling System (PRMS).

Variability and Trends in Precipitation, Temperature and Drought Indices in the State of California

Hydrology (MDPI) | March 28th, 2016

This study presents a comprehensive assessment of the variability and trends of the precipitation and temperature along with the trends in drought indices over the State

This study presents a comprehensive assessment of the variability and trends of the precipitation and temperature along with the trends in drought indices over the State of California. The non-parametric Mann–Kendall trend test is applied with a trend-free pre-whitening procedure in trend identification. A dataset containing 120-year (water years 1896–2015) monthly precipitation, average temperature, maximum temperature, minimum temperature and the Palmer Index for seven climatic regions of the state is used for this purpose. The results confirm previous work indicating that no clear trends are observed in precipitation, while a distinct warming trend is evident in temperature over the state. New findings of this study include: (1) in general, the variability of annual, winter (December–February) and spring (March–May) precipitation shows an increasing tendency, implying intensified frequency of the occurrence of dry or wet extremes; (2) on the annual scale and in the summer, statewide meteorological, hydrological and agricultural drought indices all have decreasing trends, indicating the more frequent occurrence of drought events; and (3) among seven regions, the South Coast Drainage region generally has the most significant warming trend, as well as the most significant declining trends in drought indices. Overall, these findings are highly meaningful from both theoretical and practical perspectives, in the context of providing critical information in developing prediction models and guiding water resources management practices, respectively.

Water Demand Projection Accuracy and Demand Management Trends in California Cities

American Geophysical Union (AGU) | November 21st, 2025

This study investigates the accuracy of long-term water demand projections and tracks the evolution of water demand management incentives across 61 California water suppl

This study investigates the accuracy of long-term water demand projections and tracks the evolution of water demand management incentives across 61 California water suppliers from 2000 to 2020. Through a systematic analysis of Urban Water Management Plans, we find that water suppliers consistently overestimated future demand by an average of 25% for 5-year projections and 74% for 20-year projections. This overestimation stems primarily from assumptions about per capita water demand rather than population growth estimates. While suppliers generally projected stable or increasing per capita demand, actual water demand per capita declined by 1.9% annually between 2000 and 2020, leading to a decoupling of water demand from population growth. Concurrently, we document a substantial increase in water demand management incentives, with non-voluntary regulations emerging as the dominant demand management approach by 2020, largely driven by state policies like the Model Water Efficient Landscape Ordinance and California Green Building Standards. Demand management efforts have evolved from primarily indoor and educational initiatives toward outdoor-focused non-voluntary regulations and rebates. This shift appears closely linked to the reduction in per capita demand that suppliers failed to fully capture in their water demand projections. Our findings underscore the importance of incorporating dynamic conservation trends into demand projections and suggest that suppliers should develop more sophisticated forecasting methods that account for the continuing evolution of water efficiency incentives. This research provides valuable insights for water resource planners seeking to improve the accuracy of water demand projections in an era of increasing conservation and climate uncertainty.

Water Supply Forecasting

U.S. Department of Agriculture (USDA) | March 9th, 2011

Chapter 7: Part 622 Snow Survey and Water Supply Forecasting from the National Engineering Handbook The U.S. Department of Agriculture (USDA) Natural Resources Conser

Chapter 7: Part 622 Snow Survey and Water Supply Forecasting from the National Engineering Handbook The U.S. Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) Snow Survey and Water Supply Forecasting Program issues water supply forecasts for hundreds of points in the Western United States. The primary forecast product is a seasonal volume for a specified period of months (e.g., April–July). These forecasts are issued near the first of the month between January and June. Mid-month updates are also issued for selected forecast points. In addition, daily guidance forecasts are issued for a subset of forecast points using an automated procedure. This chapter describes the essential features of water supply forecasting as practiced in the NRCS. The topics are presented in a roughly chronological sequence of activities, from forecasting point establishment, to data gathering, to model development, to operations, and finally to verification. Citations of foundational professional literature and NRCS technical notes are given to provide sources of details on mathematical procedures and other technical information not explicitly described in this chapter.

Water Year 2023: Weather Whiplash, from Drought to Deluge

California Department of Water Resources (DWR) | October 4th, 2023

Water Year 2023 demonstrated California’s high climate variability, ending the state’s driest consecutive three-year period with one of the snowiest years of record.

Water Year 2023 demonstrated California’s high climate variability, ending the state’s driest consecutive three-year period with one of the snowiest years of record. Even though California has been experiencing a theme of aridity in the 21st century (the statewide droughts of 2007-2009, 2012-2019, and 2020-2022), Water Year 2017 was the state’s second wettest in terms of statewide precipitation. Climate change is expected to amplify naturally occurring variability in the long term, potentially result in a shorter wet season for California but one with more extreme atmospheric river storms and hence potentially greater flood damage risk.

Why Seasonal Prediction of California Winter Precipitation is Challenging

American Meteorological Society (AMS) | December 7th, 2022

Despite an urgent demand for reliable seasonal prediction of precipitation in California (CA) due to the recent recurrent and severe drought conditions, our predictive sk

Despite an urgent demand for reliable seasonal prediction of precipitation in California (CA) due to the recent recurrent and severe drought conditions, our predictive skill for CA winter precipitation remains limited. October hindcasts by the coupled dynamical models typically show a correlation skill of about 0.3 for CA winter (November–March) precipitation. In this study, an attempt is made to understand the underlying processes that limit seasonal prediction skill for CA winter precipitation. It is found that only about 25% of interannual variability of CA winter precipitation can be attributed to influences by El Niño–Southern Oscillation (ENSO). Instead, the year-to-year CA winter precipitation variability is primarily due to circulation anomalies independent from ENSO, featuring a circulation center over the west coast United States as a portion of a short Rossby wave train pattern over the North Pacific. Analyses suggest that dynamical models show nearly no skill in predicting these ENSO-independent circulation anomalies, thus leading to limited predictive skill for CA winter precipitation. Low predictability of these ENSO-independent circulation anomalies is further demonstrated by a large ensemble of atmospheric-only climate model simulations. While low predictability of the ENSO-independent circulation anomalies could be due to chaotic internal atmospheric processes over the mid- to high latitudes, possible underexploited predictability sources for CA precipitation in models are also discussed. This study pinpoints an urgent need for improved understanding of the formation mechanisms of ENSO-independent circulation anomalies over the U.S. West Coast for a breakthrough in seasonal prediction of CA winter precipitation.

Widening of the tropical belt in a changing climate

Nature Portfolio (Springer Nature) | December 2nd, 2007

Some of the earliest unequivocal signs of climate change have been the warming of the air and ocean, thawing of land and melting of ice in the Arctic. But recent studies

Some of the earliest unequivocal signs of climate change have been the warming of the air and ocean, thawing of land and melting of ice in the Arctic. But recent studies are showing that the tropics are also changing. Several lines of evidence show that over the past few decades the tropical belt has expanded. This expansion has potentially important implications for subtropical societies and may lead to profound changes in the global climate system. Most importantly, poleward movement of large-scale atmospheric circulation systems, such as jet streams and storm tracks, could result in shifts in precipitation patterns affecting natural ecosystems, agriculture, and water resources. The implications of the expansion for stratospheric circulation and the distribution of ozone in the atmosphere are as yet poorly understood. The observed recent rate of expansion is greater than climate model projections of expansion over the twenty-first century, which suggests that there is still much to be learned about this aspect of global climate change.

Winter melt trends portend widespread declines in snow water resources

Nature Portfolio (Springer Nature) | April 5th, 2021

In many mountainous regions, winter precipitation accumulates as snow that melts in the spring and summer, which provides water to one billion people globally. Climate wa

In many mountainous regions, winter precipitation accumulates as snow that melts in the spring and summer, which provides water to one billion people globally. Climate warming and earlier snowmelt compromise this natural water storage. Although snowpack trend analyses commonly focus on the snow water equivalent (SWE), we propose that trends in the accumulation season snowmelt serve as a critical indicator of hydrological change. Here we compare long-term changes in the snowmelt and SWE from snow monitoring stations in western North America and find 34% of stations exhibit increasing winter snowmelt trends (P < 0.05), a factor of three larger than the 11% showing SWE declines (P < 0.05). Snowmelt trends are highly sensitive to temperature and an underlying warming signal, whereas SWE trends are more sensitive to precipitation variability. Thus, continental-scale snow water resources are in steeper decline than inferred from SWE trends alone. More winter snowmelt will complicate future water resource planning and management.