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Abstract Recent record-breaking wildfire seasons in California prompt an investigation into the climate patterns that typically precede anomalous summer burned forest area. Using burned-area data from the U.S. Forest Service’s Monitoring Trends in Burn Severity (MTBS) product and climate data from the fifth major global reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ERA5) over 1984–2018, relationships between the interannual variability of antecedent climate anomalies and July California burned area are spatially and temporally characterized. Lag correlations show that antecedent high vapor pressure deficit (VPD), high temperatures, frequent extreme high temperature days, low precipitation, high subsidence, high geopotential height, low soil moisture, and low snowpack and snowmelt anomalies all correlate significantly with July California burned area as far back as the January before the fire season. Seasonal regression maps indicate that a global midlatitude atmospheric wave train in late winter is associated with anomalous July California burned area. July 2018, a year with especially high burned area, was to some extent consistent with the general patterns revealed by the regressions: low winter precipitation and high spring VPD preceded the extreme burned area. However, geopotential height anomaly patterns were distinct from those in the regressions. Extreme July heat likelymore »contributed to the extent of the fires ignited that month, even though extreme July temperatures do not historically significantly correlate with July burned area. While the 2018 antecedent climate conditions were typical of a high-burned-area year, they were not extreme, demonstrating the likely limits of statistical prediction of extreme fire seasons and the need for individual case studies of extreme years. Significance Statement The purpose of this study is to identify the local and global climate patterns in the preceding seasons that influence how the burned summer forest area in California varies year-to-year. We find that a dry atmosphere, high temperatures, dry soils, less snowpack, low precipitation, subsiding air, and high pressure centered west of California all correlate significantly with large summer burned area as far back as the preceding January. These climate anomalies occur as part of a hemispheric scale pattern with weak connections to the tropical Pacific Ocean. We also describe the climate anomalies preceding the extreme and record-breaking burned-area year of 2018, and how these compared with the more general patterns found. These results give important insight into how well and how early it might be possible to predict the severity of an upcoming summer wildfire season in California.« less

The trends over recent decades in tropical Pacific sea surface and upper ocean temperature are examined in observations-based products, an ocean reanalysis and the latest models from the Coupled Model Intercomparison Project phase six and the Multimodel Large Ensembles Archive. Comparison is made using three metrics of sea surface temperature (SST) trend—the east–west and north–south SST gradients and a pattern correlation for the equatorial region—as well as change in thermocline depth. It is shown that the latest generation of models persist in not reproducing the observations-based SST trends as a response to radiative forcing and that the latter are at the far edge or beyond the range of modeled internal variability. The observed combination of thermocline shoaling and lack of warming in the equatorial cold tongue upwelling region is similarly at the extreme limit of modeled behavior. The persistence over the last century and a half of the observed trend toward an enhanced east–west SST gradient and, in four of five observed gridded datasets, to an enhanced equatorial north–south SST gradient, is also at the limit of model behavior. It is concluded that it is extremely unlikely that the observed trends are consistent with modeled internal variability. Instead, themore »results support the argument that the observed trends are a response to radiative forcing in which an enhanced east–west SST gradient and thermocline shoaling are key and that the latest generation of climate models continue to be unable to simulate this aspect of climate change.

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Abstract During the summer, the Midwest United States, which covers the main US corn belt, has a net loss of surface water as evapotranspiration exceeds precipitation. The net moisture gain into the atmosphere is transported out of the region to northern high latitudes through transient eddy moisture fluxes. How this process may change in the future is not entirely clear despite the fact that the corn belt region is responsible for a large portion of the global supply of corn and soybeans. We find that increased CO2 and the associated warming increases evapotranspiration. while precipitation reduces in the region leading to further reduction in precipitation minus evaporation (P-E) in the future. At the same time, the poleward transient moisture flux increases leading to enhanced atmospheric moistures export from the corn belt region. However, storm track intensity is generally weakened in the summer due to reduced north-south temperature gradient associated with amplified warming in the midlatitudes. The intensified transient eddy moisture transport as storm track weakens can be reconciled by the stronger mean moisture gradient in the future. This is found to be caused by the climatological low-level jet transporting more moisture into the Great Plains region due to the thermodynamicmore »mechanism under warmer conditions. Our results, for the first time, show that in the future, the US Midwest corn belt will experience more hydrological stress due to intensified transient eddy moisture export leading to drier soils in the region.« less

Abstract Persistent multiyear cold states of the tropical Pacific Ocean drive hydroclimate anomalies worldwide, including persistent droughts in the extratropical Americas. Here, the atmosphere and ocean dynamics and thermodynamics of multiyear cold states of the tropical Pacific Ocean are investigated using European Centre for Medium-Range Weather Forecasts reanalyses and simplified models of the ocean and atmosphere. The cold states are maintained by anomalous ocean heat flux divergence and damped by increased surface heat flux from the atmosphere to ocean. The anomalous ocean heat flux divergence is contributed to by both changes in the ocean circulation and thermal structure. The keys are an anomalously shallow thermocline that enhances cooling by upwelling and anomalous westward equatorial currents that enhance cold advection. The thermocline depth anomalies are shown to be a response to equatorial wind stress anomalies. The wind stress anomalies are shown to be a simple dynamical response to equatorial SST anomalies as mediated by precipitation anomalies. The cold states are fundamentally maintained by atmosphere-ocean coupling in the equatorial Pacific. The physical processes that maintain the cold states are well approximated by linear dynamics for ocean and atmosphere and simple thermodynamics.

Abstract Over the last century, the increase in snow accumulation has partly mitigated the total dynamic Antarctic Ice Sheet mass loss. However, the mechanisms behind this increase are poorly understood. Here we analyze the Antarctic Ice Sheet atmospheric moisture budget based on climate reanalysis and model simulations to reveal that the interannual variability of regional snow accumulation is controlled by both the large-scale atmospheric circulation and short-lived synoptic-scale events (i.e. storm systems). Yet, when considering the entire continent at the multi-decadal scale, only the synoptic-scale events can explain the recent and expected future snow accumulation increase. In a warmer climate induced by climate change, these synoptic-scale events transport air that can contain more humidity due to the increasing temperatures leading to more precipitation on the continent. Our findings highlight that the multi-decadal and interannual snow accumulation variability is governed by different processes, and that we thus cannot rely directly on the mechanisms driving interannual variations to predict long-term changes in snow accumulation in the future.