Rooting depth is an ecosystem trait that determines the extent of soil development and carbon (C) and water cycling. Recent hypotheses propose that human-induced changes to Earth’s biogeochemical cycles propagate deeply due to rooting depth changes from agricultural and climate-induced land cover changes. Yet, the lack of a global-scale quantification of rooting depth responses to human activity limits knowledge of hydrosphere-atmosphere-lithosphere feedbacks in the Anthropocene. Here we use land cover datasets to demonstrate that root depth distributions are changing globally as a consequence of agricultural expansion truncating depths above which 99% of root biomass occurs (D99) by ~60 cm, and woody encroachment linked to anthropogenic climate change extending D99 in other regions by ~38 cm. The net result of these two opposing drivers is a global reduction of D99 by 5%, or ~8 cm, representing a loss of ~11,600 km3 of rooted volume. Projected land cover scenarios in 2100 suggest additional future D99 shallowing of up to 30 cm, generating further losses of rooted volume of ~43,500 km3, values exceeding root losses experienced to date and suggesting that the pace of root shallowing will quicken in the coming century. Losses of Earth’s deepest roots — soil-forming agents — suggest unanticipated changes in fluxes of water, solutes, and C. Two important messages emerge from our analyses: dynamic, human-modified root distributions should be incorporated into earth systems models, and a significant gap in deep root research inhibits accurate projections of future root distributions and their biogeochemical consequences.

The intraseasonal variation of the Tibetan Plateau summer monsoon (TPSM) during 1979–2011 is investigated. The TPSM shows a dominant quasi-biweekly oscillation (QBWO) in most summer seasons, and its active/break phases are closely related to more/less precipitation over the Tibetan Plateau. We suggest that the TPSM QBWO is associated with a southeastward propagating nonstationary wave train in the middle and upper troposphere. It shows equivalent barotropic vertical structures over the midlatitudes and a baroclinic structure over the eastern Tibetan Plateau. Wave activity flux analysis indicates that it originates from northern Europe, which is an active center of the summertime Arctic Oscillation (AO). The AO also shows significant QBWO signals and leads TPSM QBWO by about 13 days. Phase composite and wave activity flux analyses of AO QBWO confirmed that the wave train influences TPSM QBWO, suggesting that AO plays an important role in the TPSM on a 10- to 20-day timescale.

The vertical distribution of plant roots in the soil profile is a key trait modulating plant contributions to soil carbon storage, drought and nutrient stress resistance, yield, and fitness. However, direct sampling of deep roots requires massive effort, so existing data are sparse and many researchers have adopted modeling approaches to fill data gaps and generate hypotheses about how soil properties change the biogeochemical, agricultural, ecological, and hydrologic consequences of root depth. Such models are useful only if they correctly represent the processes of interest and give accurate predictions of the root systems they simulate. Most current root growth models represent soil as a uniform and unrestrictive medium. This is often a reasonable simplification when modeling roots grown in pots or artificial media, but is less so for field soils which often increase in density, hardness, and heterogeneity with depth. To better predict the effect of soil hardness on root distribution, we updated the structural-functional root growth model OpenSimRoot to explicitly predict soil hardness from soil bulk density, water content, porosity, and depth. Root growth impedance is curently represented by linear scaling of the root elongation rate according to soil hardness. Future work will incorporate configurable growth responses and allow hardness to control changes in root diameter and growth direction, thus allowing the model to examine the fitness implications of carbon reallocation in complex structured soils. Our updated OpenSimRoot captured >50% of observed variation in penetrometer resistance from field soils. When we incorporated soil hardness into simulations of maize growth, we observed a substantial reduction in the predicted root:shoot ratio that overwhelmed previous model predictions of increased water uptake from steeper root angles. These findings reinforce that models considering costs and benefits of deep rooting should routinely consider soil hardess.

Rangelands cover over 50% of the land surface area in the western US, providing important economic, social and environmental benefits. The resilience of western rangelands, however, is threatened by climate change, including altered phenology and precipitation patterns, increased frequency and intensity of drought and forest fires, heightened pressure from invasive plants, and reduced water storage in winter snowpack. Climate adaptation strategies are available to ranchers, yet uptake varies substantially. Rancher decision-making is a complex function of their beliefs, knowledge, skill level, risk perceptions, and the institutions supporting them. Semi-structured interviews, focus groups and workshops will be utilized to examine how ranchers in Idaho, Montana, Wyoming perceive and respond to climate change, and the opportunities and barriers these social processes create for climate change adaptation.

As the sea level rises, it is alarming that the threat from flooding induced by tropical cyclones would cause more severe damages to coastal regions worldwide. In order to address this threat, optimizing coastal protective or mitigation strategies is necessary, given limited resources. The optimization methodology must incorporate feedback from stakeholders for practical use. Multiple interviews were conducted by engineering model developers and social scientists with stakeholders who have first-hand knowledge and varied backgrounds in New York. The protective strategies have been tuned to the critical infrastructure's particular and contextual risks due to flood hazards by engaging and integrating stakeholders' knowledge on the interdependency of the infrastructures and other aspects after the first interview. The second interview was conducted for further model improvement.

Some of the Earth system data products such as those from NASA airborne and field investigations (a.k.a. campaigns), are highly heterogeneous and cross-disciplinary, making the data extremely challenging to manage. For example, airborne and field campaign measurements tend to be sporadic over a period of time, with large gaps. Data products generated are of various processing levels and utilized for a wide range of inter- and cross-disciplinary research and applications. Data and derived products have been historically stored in a variety of domain-specific standard (and some non-standard) formats and in various locations such as NASA Distributed Active Archive Centers (DAACs), NASA airborne science facilities, field archives, or even individual scientists’ computer hard drives. As a result, airborne and field campaign data products have often been managed and represented differently, making it onerous for data users to find, access, and utilize campaign data. Some difficulties in discovering and accessing the campaign data originate from the incomplete data product and contextual metadata that may contain details relevant to the campaign (e.g. campaign acronym and instrument deployment locations), but tend to lack other significant information needed to understand conditions surrounding the data. Such details can be burdensome to locate after the conclusion of a campaign. Utilizing consistent terminology, essential for improved discovery and reuse, is also challenging due to the variety of involved disciplines. To help address the aforementioned challenges faced by many repositories and data managers handling airborne and field data, this presentation will describe stewardship practices developed by the Airborne Data Management Group (ADMG) within the Interagency Implementation and Advanced Concepts Team (IMPACT) under the NASA’s Earth Science Data systems (ESDS) Program.

This study investigates trends in global tropical cyclone (TC) activity from 1990–2020, a period where observational platforms are mostly consistent. Several global TC metrics have decreased during this period, with significant decreases in hurricanes and Accumulated Cyclone Energy (ACE). Most of this decrease has been driven by significant downward trends in the western North Pacific. Globally, short-lived named storms, 24-hr intensification periods of >=50 kt day-1 and TC-related damage have increased significantly. The increase in short-lived named storms is likely due to technological improvements, while rapidly intensifying TC increases may be fueled by higher potential intensity. Damage increases are largely due to increased coastal assets. The decreasing trends in hurricane numbers and global ACE are likely due to the trend towards a more La Niña-like base state from 1990–2020, favoring TC activity in the North Atlantic and suppressing TC activity in the eastern and western North Pacific.

Studies of intraseasonal and annual cycles of meteorological variables, using projections of climate change, are nowadays extremely important to improve regional socio-economic planning for countries. This is particularly true in Costa Rica, as Central America has been identified as a climate change hot spot. Today many of the economic activities in the region, especially those related to agriculture, tourism and hydroelectric power generation are linked to the seasonal cycle of precipitation. Changes in rainfall (mm/day) and in the diurnal temperature range ($^{\circ}$C) for the periods 1970-1999 and 2070-2099 were investigated using the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) constructed using the CMIP5 (Coupled Model Intercomparison Project version 5) data. Differences between the multi-model ensembles of the two prospective scenarios (RCP 4.5 and RCP 8.5) and the retrospective baseline scenario were computed. This study highlights Costa Rica as an inflexion point of the climate change in the region and also suggests an early onset of the rainy season and future drying conditions.

A supermodel connects different models interactively so that their systematic errors compensate and achieve a model with superior performance. It differs from the standard non-interactive multi-model ensembles (NI), which combines model outputs a-posteriori. We formulate the first supermodel framework for Earth System Models (ESMs) and use data assimilation to synchronise models. The ocean of three ESMs is synchronised every month by assimilating pseudo sea surface temperature (SST) observations generated from them. Discrepancies in grid and resolution are handled by constructing the synthetic pseudo-observations on a common grid. We compare the performance of two supermodel approaches to that of the NI for 1980—2006. In the first (EW), the models are connected to the equal-weight multi-model mean, while in the second (SINGLE), they are connected to a single model. Both versions achieve synchronisation in locations where the ocean drives the climate variability. The time variability of the supermodel multi-model mean SST is reduced compared to the observed variability; most where synchronisation is not achieved and is bounded by NI. The damping is larger in EW than in SINGLE because EW yields additional damping of the variability in the individual models. Hence, under partial synchronisation, the part of variability that is not synchronised gets damped in the multi-model average pseudo-observations, causing a deflation during the assimilation. The SST bias in individual models of EW is reduced compared to that of NI, and so is its multi-model mean in the synchronised regions. The performance of a trained supermodel remains to be tested.

Volcanism is the dominant natural source of mercury (Hg) to the atmosphere, biosphere, ocean and sediments. In recent years, sedimentary Hg contents have emerged as a tool to reconstruct volcanic activity, and particularly activity of (subaerially emplaced) large igneous provinces (LIP) in geological deep time. More specifically, Hg has shown potential as a useful proxy to illuminate the previously elusive impact of such large-scale volcanism on marine and terrestrial paleo-environments. While Hg is now widely applied as volcanism tracer, non-volcanic factors controlling sedimentary Hg content are generally not well constrained. Part of this uncertainty stems from our inability to directly observe a natural unperturbed “steady-state” environment as a baseline, as the modern Hg cycle is heavily influenced by anthropogenic activity. Here we focus on the effects of ambient redox conditions in the water column and shallow sediments (early diagenesis), quantify their influence on the geological Hg record and thereby constrain their potential impact on the use of Hg as a proxy for deep-time volcanic activity. Constraining these factors is of critical importance for the application of Hg as a proxy. Many periods in the geological past for which records have been generated, such as the Mesozoic Oceanic Anoxic Events, are marked by a variety of high-amplitude environmental perturbations, including widespread deoxygenation and deposition of organic-rich sediments. We estimate the impact of redox changes and early diagenesis on the geological Hg record using a suite of (sub)recent–Pleistocene and Upper Cretaceous sediments representing oxic to euxinic marine conditions. Our sample set includes a transect through an oxygen minimum zone and cores that record transient shifts in oxygenation state, as well as post-depositional effects – all unrelated to volcanism, to the best of our knowledge. We find substantial alterations to the Hg record and the records of organic carbon and total sulfur, which are typically assumed to be the most common carrier phases of Hg in marine sediments. Moreover, these biases can lead to signal-alterations on a par with those interpreted to result from volcanic activity. Geochemical modifications are ubiquitous and their potential magnitude implies that the factors leading to biases in the geological record warrant careful consideration before interpretation. Factors of particular concern to proxy application are (1) the disproportionate loss of organic carbon and sulfur compounds relative to Hg during oxidation that strongly modulates normalized Hg records, (2) the evasion of Hg in anoxic and mildly euxinic sediments and (3) sharp focusing of Hg during post-depositional oxidation of organic matter.

Recent worldwide heatwaves have shattered temperature records in many regions. In this study, we applied a dynamical downscaling method on the high-resolution version of the Max Planck Institute Earth System Model (MPI-ESM-1-2-HR) to obtain projections of the summer thermal environments and heatwaves in the Pearl River Delta (PRD) considering three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5) in the middle and late 21st century. Results indicated that relative to the temperatures in the 2010s, the mean increases in the summer daytime and nighttime temperatures in the 2040s will be 0.7–0.8 °C and 0.9–1.1 °C, respectively. In the 2090s, they will be 0.5–3.1 °C and 0.7–3.4 °C, respectively. SSP1-2.6 is the only scenario in which the temperatures in the 2090s are expected to be lower than those in the 2040s. Compared with those in the 2010s, hot extremes are expected to be more frequent, more intense, more extensive, and longer-lasting in the future in the SSP2-4.5 and SSP5-8.5 scenarios. In the 2010s, a heatwave occurred in the PRD lasted for 6 days on average, with a mean daily maximum temperature of 34.4 °C. In the 2040s, the heatwave duration and intensity are expected to increase by 2–3 days and 0.2–0.4 °C in all three scenarios. In the 2090s, the increase in these values will be 23 days and 36.0 °C in SSP5-8.5. Moreover, a 10-year extreme high temperature in the 2010s is expected to occur at a monthly frequency from June to September.

Access to groundwater leaves riparian plants in drylands resistant to atmospheric drought but vulnerable to changes in climate or water use that reduce streamflow and groundwater tables. Despite the vulnerability of riparian vegetation to water balance changes few extensible methods have been developed to automatically map riparian plants at the scale of individual stands or stream reaches, to assess their response to changes in moisture due to drought and climate change, and to contrast those responses across plant functional types. We used LiDAR and a sub-annual timeseries of NDVI to map vegetation and then assessed drought response by comparing a drought index to variation in a remotely sensed metric of plant health. First, a random forest model was built to classify vegetation communities based on phenological changes in Sentinel-2 NDVI. This model produced community classes with an overall accuracy of 97.9%; accuracy for the riparian vegetation class was 98.9%. Following this initial classification, LiDAR measurements of vegetation height were used to split the riparian class into structural subclasses. Multiple Endmember Spectral Mixture Analysis was applied to a timeseries of Landsat imagery from 1984 to 2018, producing annual sub-pixel fractions of green vegetation, non-photosynthetic vegetation, and soil. Relationships were assessed within structural subclasses between mid-summer green vegetation fraction (GV) and the Standardized Precipitation-Evapotranspiration Index (SPEI), a measure of soil moisture drought. Among riparian vegetation subclasses, all groups showed significant positive correlations between SPEI and GV, indicating an increase in healthy plant material during wetter years. However, the relationship was strongest for herbaceous plants (R^2=0.509, m=0.0278), intermediate for shrubs (R^2=0.339, m=0.0262), and weakest for the largest trees (R^2=0.1373, m=0.0145). This implies decoupling of larger riparian plants from the impacts of atmospheric drought due to subsidies provided by groundwater resources. Our method was extended successfully to multiple climatically-dissimilar dryland systems in the American Southwest, and the results provide a basis for ongoing studies on the fine-scale drought response and climatic vulnerability of riparian woodlands.

The Late Miocene Biogenic Bloom (LMBB) is a late Miocene to early Pliocene oceanographic event characterized by high accumulation rates of opal from diatoms and calcite from calcareous nannofossils and planktic foraminifera. This multi-million year event has been recognized in sediment cores from the Pacific, Atlantic and Indian Oceans. The numerous studies discussing the LMBB lead us to believe that this event is omnipresent in all oceans, although this hypothesis need to be tested. Moreover, the origin of this event is still widely discussed. In this study we aim to provide a comprehensive overview of the geographical and temporal aspects of the LMBB by compiling published ocean drilling (DSDP, ODP and IODP) records of sedimentation rates, CaCO\textsubscript{3} and opal and terrigenous accumulation rates that cover the late Miocene and early Pliocene interval. Our data compilation shows that traces of the LMBB are present in many different locations but in a very heterogeneous way, highlighting that the LMBB is not a pervasive event. The compilation in addition shows that the sites where the LMBB is recorded are mainly located in areas with a high productivity regime (i.e. upwelling systems). We suggest that the most likely hypothesis to explain the LMBB is a global increase in upwelling intensity due to an increase in wind strength or an increase in deep water formation, ramping up global thermohaline circulation.

In response to north-south pressure gradients set by the annual march of the Sun, a cross-equatorial flow that turns to become a low-level Somali jet at around $10^{\circ}$ N is established in the lower troposphere over the Indian ocean. This flow plays a fundamental role in the Indian monsoon. A mechanistic understanding of drivers of this flow is lacking. Here we present a seasonal-mean analysis of the Kinetic Energy (KE) budget of the low-level flow using high spatiotemporal resolution ERA5 reanalysis to identify sources and sinks of KE. We find that the largest KE generation occurs around east African orography where the Somali jet forms while a significant KE is also generated over western Ghats and the Madagascar Island (‘hot spots’). These regions are distant from core monsoon precipitation regions, suggesting that local circulations driven by condensation do not directly produce the bulk of KE during monsoons. A unique KE balance supports the generation of Somali jet, with KE generation balanced by nonlinear KE advection as it forms. Over oceans, KE generation occurs mainly due to cross-isobaric meridional winds in the boundary layer. In contrast, over east African highlands and western Ghats KE generation maximizes just above the boundary layer and mainly occurs due to interaction of flow with orography. We propose a simple decomposition of lower tropospheric KE generation into contributions from surface pressure, orography and free-tropospheric gradients that corroborates the important role played by surface pressure gradients once adjusted for effects of orography.