A 21-yr gridded monthly fire-starts and acres-burned dataset from U.S. Forest Service, Bureau of Land Management, National Park Service, and Bureau of Indian Affairs fire reports recreates the seasonality and interannual variability of wild fire in the western United States. Despite pervasive human influence in western fire regimes, it is striking how strongly these data reveal a fire season responding to variations in climate. Correlating anomalous wildfire frequency and extent with the Palmer Drought Severity Index illustrates the importance of prior and accumulated precipitation anomalies for future wildfire season severity. This link to antecedent seasons' moisture conditions varies widely with differences in predominant fuel type. Furthermore, these data demonstrate that the relationship between wildfire season severity and observed moisture anomalies from antecedent seasons is strong enough to forecast fire season severity at lead times of one season to a year in advance.

Fluctuations in spring climate in the western United States over the last 4–5 decades are described by examining changes in the blooming of plants and the timing of snowmelt–runoff pulses. The two measures of spring's onset that are employed are the timing of first bloom of lilac and honeysuckle bushes from a long-term cooperative phenological network, and the timing of the first major pulse of snowmelt recorded from high-elevation streams. Both measures contain year-to-year fluctuations, with typical year-to-year fluctuations at a given site of one to three weeks. These fluctuations are spatially coherent, forming regional patterns that cover most of the west. Fluctuations in lilac first bloom dates are highly correlated to those of honeysuckle, and both are significantly correlated with those of the spring snowmelt pulse. Each of these measures, then, probably respond to a common mechanism. Various analyses indicate that anomalous temperature exerts the greatest influence upon both interannual and secular changes in the onset of spring in these networks. Earlier spring onsets since the late 1970s are a remarkable feature of the records, and reflect the unusual spell of warmer-than-normal springs in western North America during this period. The warm episodes are clearly related to larger-scale atmospheric conditions across North America and the North Pacific, but whether this is predominantly an expression of natural variability or also a symptom of global warming is not certain.

Abstract

The variability of precipitation and water supply along the U.S. West Coast creates major challenges to the region’s economy and environment, as evidenced by the recent California drought. This variability is strongly influenced by atmospheric rivers (ARs), which deliver much of the precipitation along the U.S. West Coast and can cause flooding, and by aerosols (from local sources and transported from remote continents and oceans) that modulate clouds and precipitation. A better understanding of these processes is needed to reduce uncertainties in weather predictions and climate projections of droughts and floods, both now and under changing climate conditions.

To address these gaps, a group of meteorologists, hydrologists, climate scientists, atmospheric chemists, and oceanographers have created an interdisciplinary research effort, with support from multiple agencies. From 2009 to 2011 a series of field campaigns [California Water Service (CalWater) 1] collected atmospheric chemistry, cloud microphysics, and meteorological measurements in California and associated modeling and diagnostic studies were carried out. Based on the remaining gaps, a vision was developed to extend these studies offshore over the eastern North Pacific and to enhance land-based measurements from 2014 to 2018 (CalWater-2). The dataset and selected results from CalWater-1 are summarized here. The goals of CalWater-2, and measurements to date, are then described.

CalWater is producing new findings and exploring new technologies to evaluate and improve global climate models and their regional performance and to develop tools supporting water and hydropower management. These advances also have potential to enhance hazard mitigation by improving near-term weather prediction and subseasonal and seasonal outlooks.

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.

Abstract

California experienced a historic run of nine consecutive landfalling atmospheric rivers (ARs) in three weeks’ time during winter 2022/23. Following three years of drought from 2020 to 2022, intense landfalling ARs across California in December 2022–January 2023 were responsible for bringing reservoirs back to historical averages and producing damaging floods and debris flows. In recent years, the Center for Western Weather and Water Extremes and collaborating institutions have developed and routinely provided to end users peer-reviewed experimental seasonal (1–6 month lead time) and subseasonal (2–6 week lead time) prediction tools for western U.S. ARs, circulation regimes, and precipitation. Here, we evaluate the performance of experimental seasonal precipitation forecasts for winter 2022/23, along with experimental subseasonal AR activity and circulation forecasts during the December 2022 regime shift from dry conditions to persistent troughing and record AR-driven wetness over the western United States. Experimental seasonal precipitation forecasts were too dry across Southern California (likely due to their overreliance on La Niña), and the observed above-normal precipitation across Northern and Central California was underpredicted. However, experimental subseasonal forecasts skillfully captured the regime shift from dry to wet conditions in late December 2022 at 2–3 week lead time. During this time, an active MJO shift from phases 4 and 5 to 6 and 7 occurred, which historically tilts the odds toward increased AR activity over California. New experimental seasonal and subseasonal synthesis forecast products, designed to aggregate information across institutions and methods, are introduced in the context of this historic winter to provide situational awareness guidance to western U.S. water managers.