AGU Advances最新文献

In the Subantarctic Southern Ocean, primary productivity is predominantly limited by seasonal changes in light and iron (Fe) availability, shaping the phytoplankton community and impacting the magnitude of the biological carbon pump. However, quantifying the seasonal iron cycle is challenging, as observations of bioavailable, dissolved iron (DFe) from individual campaigns rarely span a full seasonal cycle. Here, we present a composite seasonal cycle constructed from 27 years of DFe observations at the subantarctic Southern Ocean Time Series (SOTS) south of Australia. Iron measurements are paired with time series data to explain the iron cycle contextualized to broader Southern Ocean biogeochemistry. Three distinct phases were revealed with clear coupling between iron and productivity in the first two phases. In the first phase, light limitation initially controls spring to summer primary production with shoaling of the mixed layer, accounting for around half of annual net community production (ANCP). In the second phase and remaining half of ANCP, rapid biomass increases and near-complete drawdown of DFe drive iron limitation, evidenced by maximum fluorescence-to-chlorophyll ratios. A subset of this period covering a third of ANCP exhibits a mean Fe:C uptake ratio of 31.08 ± 8.88 μmol:mol. During the third phase, iron is weakly coupled to productivity as the system transitions to net heterotrophy and biomass declines despite increased Fe supply associated with the east Australian current system. Together, 27 years of continuous monitoring draws a comprehensive picture of how and when iron fuels subantarctic productivity, providing a critical baseline for model validation and continued monitoring in a rapidly changing climate.

Global warming results from anthropogenic greenhouse gas emissions which upset the delicate balance between the incoming sunlight, and the reflected and emitted radiation from Earth. The imbalance leads to energy accumulation in the atmosphere, oceans and land, and melting of the cryosphere, resulting in increasing temperatures, rising sea levels, and more extreme weather around the globe. Despite the fundamental role of the energy imbalance in regulating the climate system, as known to humanity for more than two centuries, our capacity to observe it is rapidly deteriorating as satellites are being decommissioned.

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 (OC_petro) from OC-bearing (meta-)sedimentary bedrock. To our knowledge, no soil carbon model accounts for the inputs of OC_petro to soils, resulting in significant gaps in our understanding about the roles OC_petro plays in soils. Here, we call for cross-disciplinary research to investigate the transport and stability of OC_petro across the bedrock–soil continuum. We pose four key questions as motivation for this effort. Ignoring the inputs of OC_petro to soils has significant implications, including overestimating biospheric carbon stocks and turnover times. Furthermore, we lack information on the role that OC_petro may play in priming microbial communities, as well as the impacts of land management on OC_petro 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 $��{\text{km}}^2�$ over an 18 year period. Increasing hazard detection capabilities and expanding existing definitions of hazards using daily satellite data increases the temporal and spatial resolutions at which multi-hazard events are detected. Having more complete data sets of all relevant hazard extents improves our ability to track global trends and more accurately determine the magnitude of hazard exposure inequities.

Unlike declines of pH in the open ocean on the total scale (pH_T), coastal systems have shown complex long-term trends in pH_T due to a multitude of global and regional drivers. These drivers include changes in nutrient loading, human-accelerated chemical weathering of watersheds, acid-rain and land-use changes, and ocean acidification due to atmospheric CO₂ increase. We lack understanding of how these co-occurring processes have influenced long-term pH_T changes in coastal waters. To address this knowledge gap, a coupled hydrodynamic-biogeochemical-carbonate chemistry model was used to conduct a hindcast simulation and scenario analyses of carbonate chemistry in the Chesapeake Bay between 1951 and 2010. Trend analysis reveals increasing pH_T in the upper Bay due to river alkalinization but decreasing pH_T in the bottom waters of the mid-and lower Bay due to ocean acidification. No trend is detected in the surface waters of the mid- and lower Bay due to competition between the two drivers. The effect of river alkalinization on the acidic volume in the estuary is twice that of ocean acidification. Our findings show that river alkalinization provides an important buffer against acidification while eutrophication plays a secondary role. Our results also suggest ocean alkalinity enhancement could be effective in mitigating acidification in coastal waters.

Sub-Antarctic Mode Waters (SAMWs) form to the north of the Antarctic Circumpolar Current in the Indo-Pacific Ocean, whence they ventilate the ocean's lower pycnocline and play an important role in the climate system. With a backward Lagrangian particle-tracking experiment in a data-assimilative model of the Southern Ocean (B-SOSE), we address the long-standing question of the extent to which SAMWs originate from densification of southward-flowing subtropical waters versus lightening of northward-flowing Antarctic waters sourced by Circumpolar Deep Water (CDW) upwelling. Our analysis evidences the co-occurrence of both sources in all SAMW formation areas, and strong inter-basin contrasts in their relative contributions. Subtropical waters are the main precursor of Indian Ocean SAMWs (70%–75% of particles) but contribute a smaller amount (40% of particles) to Pacific SAMWs, which are mainly sourced from the upwelled CDW. By tracking property changes along particle trajectories, we show that SAMW formation from northern and southern sources involves contrasting drivers: subtropical source waters are cooled and densified by surface heat fluxes, and freshened by ocean mixing. Southern source waters are warmed and lightened by surface heat and freshwater fluxes, and they are made either saltier by mixing in the case of Indian SAMWs, or fresher by surface fluxes in the case of Pacific SAMWs. Our results underscore the distinct climatic impact of Indian and Pacific SAMWs formation, involving net release of atmospheric heat and uptake of atmospheric freshwater, respectively; a role that is conferred by the relative contributions of subtropical and Antarctic sources to their formation.