An issue of global concern is how climate change forcing is transmitted to ecosystems. Forest ecosystems in mountain landscapes may demonstrate buffering and perhaps decoupling of long-term rates of temperature change, because vegetation, topography, and local winds (e.g., cold air pooling) influence temperature and potentially create microclimate refugia (areas which are relatively protected from climate change). We tested these ideas by comparing 45-year regional rates of air temperature change to unique temporal and spatial air temperature records in the understory of regionally representative stable old forest at the H.J. Andrews Experimental Forest, Oregon, USA. The 45-year seasonal patterns and rates of warming were similar throughout the forested landscape and matched regional rates observed at 88 standard meteorological stations in Oregon and Washington, indicating buffering, but not decoupling of long-term climate change rates. Consideration of the energy balance explains these results: while shading and airflows produce spatial patterns of temperature, these processes do not counteract global increases in air temperature driven by increased downward, longwave radiation forced by increased anthropogenic greenhouse gases in the atmosphere. In some months, the 45-year warming in the forest understory equaled or exceeded spatial differences of air temperature between the understory and the canopy or canopy openings and was comparable to temperature change over 1,000 m elevation, while in other months there has been little change. These findings have global implications because they indicate that microclimate refugia are transient, even in this forested mountain landscape.
Extratropical storms dominate midlatitude climate and weather and are known to grow baroclinically and decay barotropically. Traditionally, quantitative climatic measures of storm activity have been mostly based on Eulerian measures, taking into account the mean state of the atmosphere and how those affect Eulerian eddy activity, but they do not consider the Lagrangian growth of the storms themselves. Here, using ERA-5 reanalysis data and tracking all extratropical storms (cyclones and anticyclones) from 83 years of data, we examine the actual growth of the storms and compare it to the Eulerian characteristics of the background state as the storms develop. In the limit of weak baroclinicity, we find that baroclinicity provides a good measure for storm maximum intensity. However, this monotonic relationship breaks for high baroclinicity levels. We show that although the actual growth rate of individual storms monotonically increases with baroclinicity, the reduction in maximum intensity at high baroclinicity is caused by a decrease in storm growth time. Based on the Lagrangian analysis, we suggest a nonlinear correction to the traditional linear connection between baroclinicity and storms' activity. Then, we show that a simplified model of storm growth, incorporating the baroclinicity effect on the vertical tilt of anomalies, reproduces the observed nonlinear relationship. Expanding the analysis to include the mean flow's barotropic properties highlights their marginal effect on storm growth rate, but the crucial impact on growth time. Our results emphasize the potential of Lagrangianly studying storm dynamics to advance understanding of the midlatitude climate.
The Amazon has experienced extensive deforestation in recent decades, causing substantial impacts on local and regional climate. However, the precipitation response to this recent forest cover change remains unclear. Here, we examined biophysical effects of forest cover change in the Brazilian Amazon on dry season precipitation using a regional coupled climate model with embedded water vapor tracers. We find that the 3.2% mean reduction in forest cover that occurred in Rondônia and Mato Grosso during 2002–2015 caused a 3.5 ± 0.8% reduction in evapotranspiration and a 5.4 ± 4.4% reduction in precipitation. The reduction in evapotranspiration warmed and dried the lower atmosphere reducing convection and precipitation. Reductions in incoming moisture, dominated by reduced moisture inflow in the mid-troposphere, accounted for 25% of the total reduction in moisture and amplified the precipitation response to forest loss. The reduction in precipitation efficiency explains 84.5% of the reduction in precipitation with the remainder due to reductions in precipitable water. The reduced precipitation sourced from water vapor inflow accounts for 76.9% of the simulated precipitation reduction, with the remaining 23.1% due to reduced local evapotranspiration. Our study demonstrates substantial reductions in dry season precipitation due to recent forest cover change in the Amazon, highlighting the importance of atmospheric responses to land cover change in this region.
Intensifying effects of global climate change have spurred efforts to enhance carbon sequestration and the long-term storage of soil organic carbon (OC). Current soil carbon models predominantly assume that inputs of OC are biospheric, that is, primarily derived from plant decomposition. However, these overlook the contribution of OC from soil parent material, including petrogenic organic carbon (OCpetro) from OC-bearing (meta-)sedimentary bedrock. To our knowledge, no soil carbon model accounts for the inputs of OCpetro to soils, resulting in significant gaps in our understanding about the roles OCpetro plays in soils. Here, we call for cross-disciplinary research to investigate the transport and stability of OCpetro across the bedrock–soil continuum. We pose four key questions as motivation for this effort. Ignoring the inputs of OCpetro to soils has significant implications, including overestimating biospheric carbon stocks and turnover times. Furthermore, we lack information on the role that OCpetro may play in priming microbial communities, as well as the impacts of land management on OCpetro stocks.
The co-occurrence of multiple hazards is of growing concern globally as the frequency and magnitude of extreme climate events increases. Despite studies examining the spatial distribution of such events, there has been little work in examining if all relevant life threatening and damaging hazards are captured in existing hazard databases and by common hazard metrics. For example, local/regional flash flooding events are seldom captured by optical satellite instruments and are subsequently excluded from global hazard databases. Similarly, the heat hazard definitions most frequently used in multi-hazard studies inherently fail to capture events that are life-threatening but climatologically within an expected range. Our goal is to determine the potential for increasing multi-hazard event detection capabilities by inferring additional hazard footprints from widely accessible satellite data. We use daily precipitation and temperature satellite data to develop an open-source framework that infers additional hazard footprints that are not included in traditional methods. With the state of Texas as our study area, we detected 2.5 times as many flood hazards, equivalent to $320 million in property and crop damages. Furthermore, our expanded heat hazard definition increases the impacted area by 56.6%, equivalent to 91.5 million