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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Direct Air Capture Using Aqueous Amino Acid Solvents in a Crossflow Absorber

Carbon dioxide (CO 2 ) is the most abundant of all greenhouse gases (GHGs). CO 2 levels in the atmosphere are 50% higher than in the preindustrial era, trapping heat. CO 2 removal from the atmosphere by direct air capture (DAC) is needed to achieve the internationally agreed global temperature goals. The most common CO 2 capture technology is absorption by aminebased solvents in packed columns. Amino acid solutions have recently gained attention due to their advantages over traditional amine solvents. To be implemented effectively, DAC industrial processes need to handle large airflow rates in separation absorbers. The large air and solvent flow rates preclude the use of countercurrent columns due to high-pressure drops and the occurrence of flooding. Crossflow air−liquid absorbers are used to handle large air and liquid volumes due to their lower-pressure drop. The objective of this work is to study the influence of crossflow absorber geometric parameters and operating conditions on product formation and process efficiency. An already derived theoretical model for countercurrent absorbers has been modified to simulate the operation of a crossflow DAC absorber. The predictive model was implemented into a computer code that was used to study the efficiency of the processes as geometric equipment dimensions and operating parameters vary. Practical suggestions are made to design more efficient DAC processes.

Absorption↗
NASA NTRS2016

A Satellite Data-Driven, Client-Server Decision Support Application for Agricultural Water Resources Management

Water cycle extremes such as droughts and floods present a challenge for water managers and for policy makers responsible for the administration of water supplies in agricultural regions. In addition to the inherent uncertainties associated with forecasting extreme weather events, water planners need to anticipate water demands and water user behavior in a typical circumstances. This requires the use decision support systems capable of simulating agricultural water demand with the latest available data. Unfortunately, managers from local and regional agencies often use different datasets of variable quality, which complicates coordinated action. In previous work we have demonstrated novel methodologies to use satellite-based observational technologies, in conjunction with hydro-economic models and state of the art data assimilation methods, to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, and land allocation. These methods create an opportunity for new, cost-effective analysis tools to support policy and decision-making over large spatial extents. The methods can be driven with information from existing satellite-derived operational products, such as the Satellite Irrigation Management Support system (SIMS) operational over California, the Cropland Data Layer (CDL), and using a modified light-use efficiency algorithm to retrieve crop yield from the synergistic use of MODIS and Landsat imagery. Here we present an integration of this modeling framework in a client-server architecture based on the Hydra platform. Assimilation and processing of resource intensive remote sensing data, as well as hydrologic and other ancillary information occur on the server side. This information is processed and summarized as attributes in water demand nodes that are part of a vector description of the water distribution network. With this architecture, our decision support system becomes a light weight 'app' that connects to the server to retrieve the latest information regarding water demands, land use, yields and hydrologic information required to run different management scenarios. Furthermore, this architecture ensures all agencies and teams involved in water management use the same, up-to-date information in their simulations.

Agricultural↗
NASA NTRS2005

Forecasting of Storm Surge Floods Using ADCIRC and Optimized DEMs

Increasing the accuracy of storm surge flood forecasts is essential for improving preparedness for hurricanes and other severe storms and, in particular, for optimizing evacuation scenarios. An interactive database, developed by WorldWinds, Inc., contains atlases of storm surge flood levels for the Louisiana/Mississippi gulf coast region. These atlases were developed to improve forecasting of flooding along the coastline and estuaries and in adjacent inland areas. Storm surge heights depend on a complex interaction of several factors, including: storm size, central minimum pressure, forward speed of motion, bottom topography near the point of landfall, astronomical tides, and most importantly, maximum wind speed. The information in the atlases was generated in over 100 computational simulations, partly by use of a parallel-processing version of the ADvanced CIRCulation (ADCIRC) model. ADCIRC is a nonlinear computational model of hydrodynamics, developed by the U.S. Army Corps of Engineers and the US Navy, as a family of two- and three-dimensional finite element based codes. It affords a capability for simulating tidal circulation and storm surge propagation over very large computational domains, while simultaneously providing high-resolution output in areas of complex shoreline and bathymetry. The ADCIRC finite-element grid for this project covered the Gulf of Mexico and contiguous basins, extending into the deep Atlantic Ocean with progressively higher resolution approaching the study area. The advantage of using ADCIRC over other storm surge models, such as SLOSH, is that input conditions can include all or part of wind stress, tides, wave stress, and river discharge, which serve to make the model output more accurate.

Valenti, Elizabeth↗
NASA NTRS2015

New York City Panel on Climate Change 2015 Report: Climate Observations and Projections - Chapter 1

During 2013 and 2014, numerous international (IPCC, 2013) and national (Melillo et al., 2014; Gordon, 2014) reports have concluded that human activities are changing the climate, leading to increased vulnerability and risk. Since the industrial revolution, fossil fuel burning, industrial activity, and land use changes have led to a 40% increase in heat-trapping carbon dioxide (CO2), and an approximately 150% increase in methane (CH4), another powerful greenhouse gas (GHG), has been observed. Global temperatures have increased by close to 1 C since 1880 as the upper oceans have warmed and polar ice has retreated. These and other climate changes are projected to accelerate as greenhouse gas concentrations continue to rise. In the coming decades, climate change is extremely likely to bring warmer temperatures in the New York metropolitan region (see Box. 1.1 and Fig.1.1 for key definitions and terms). Heat waves are very likely to increase; total annual precipitation will likely increase and brief, intense rainstorms are very likely to increase. Because of incomplete knowledge about exactly how much climate change will occur, choosing among policies for reducing future damages requires prudent risk management (Yohe and Leichenko, 2010; Kunreuther et al., 2013). Given differing risk tolerances among stakeholders, a risk management approach allows for a range of possible climate change outcomes to be examined with associated uncertainties surrounding their likelihoods. The New York City Panel on Climate Change 2 (NPCC2) projections can be used to inform planning across multiple governmental scales (e.g., city, county, state) in the New York metropolitan region. Such coordinated efforts can serve as test cases for successful local, state, and federal coordination for integrated climate adaptation initiatives. This chapter describes the global climate system, and presents observed temperature and precipitation trends and projections for the region. Chapter 2 (NPCC, 2015) focuses on sea level rise and possible changes in coastal storms. Chapter 3 and Chapter 4 (NPCC, 2015) describe efforts to better understand the region's vulnerability to coastal flooding during coastal storms. The treatment of likelihood related to the NPCC projections is similar to that developed by the Intergovernmental Panel on Climate Change Fourth and Fifth Assessment Reports (IPCC, 2007; 2013), with six likelihood categories (Box 1.1 and Fig. 1.1). The assignment of climate hazards to these categories is based on observed data, global climate model simulations, published literature, and expert judgment.

climate change↗
NASA NTRS2010

Use the High-Resolution Numerical Model to Simulate Typhoon Morakot 2009

Typhoon Morakot struck Taiwan on the night of Friday August 7th, 2009 as a category 2 storm with sustained winds of 85 knots (92 mph). Although the center made landfall in Hualien county along the central cast coast of Taiwan and passed over the central northern part of the island, it was southern Taiwan that received the worst effects of the storm where locally as Much as 2200 mm (2.2 m) of rain were reported, resulting in the worst flooding there in 50 years. The result of the enormous amount of rain has been massive flooding and devastating mudslides. More than 600 people are confirmed dead. In this paper, we will present the results from high-resolution (2-km) WRF for this typhoon case. The results showed that the model captured both in terms of maximum rainfall area and intensity. The model results also showed that the heavy amounts of rain over the southern portion of the island is due to persistent southwesterly flow associated with Morakot and it's circulation was able to draw up copious amounts of moisture from the South China Sea into southern Taiwan where it was able to interact with the steep topography. In the paper, we will also present results from sensitivity test of terrain heights and SST on the precipitation processes (rainfall) associated with Typhoon Morakot (2009), In addition, we will present high-resolution visualization (36 second and 2-km) to show the evolution of Typhoon Morakot.

Tao, Wei-Kuo↗
DOE OSTI2021

Changes in Future Precipitation Mean and Variability across Scales

Changes in precipitation variability can have large societal consequences, whether at the short time scales of flash floods or the longer time scales of multiyear droughts. Recent studies have suggested that in future climate projections, precipitation variability rises more steeply than does its mean, leading to concerns about societal impacts. Here we evaluate changes in mean precipitation over a broad range of spatial and temporal scales using a range of models from high-resolution regional simulations to millennial-scale global simulations. Results show that changes depend on the scale of aggregation and involve strong regional differences. On local scales that resolve individual rainfall events (hours and tens of kilometers), changes in precipitation distributions are complex and variances rise substantially more than means, as is required given the well-known disproportionate rise in precipitation intensity. On scales that aggregate across many events, distributional changes become simpler and variability changes smaller. At regional scale, future precipitation distributions can be largely reproduced by a simple transformation of present-day precipitation involving a multiplicative shift and a small additive term. The “extra” broadening is negatively correlated with changes in mean precipitation: in strongly “wetting” areas, distributions broaden less than expected from a simple multiplicative mean change; in “drying” areas, distributions narrow less. Precipitation variability changes are therefore of especial concern in the subtropics, which tend to dry under climate change. Outside the tropics, variability changes are similar on time scales from days to decades (i.e., show little frequency dependence). This behavior is highly robust across models, suggesting it may stem from some fundamental constraint.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

Forecasting of Storm-Surge Floods Using ADCIRC and Optimized DEMs

Increasing the accuracy of storm-surge flood forecasts is essential for improving preparedness for hurricanes and other severe storms and, in particular, for optimizing evacuation scenarios. An interactive database, developed by WorldWinds, Inc., contains atlases of storm-surge flood levels for the Louisiana/Mississippi gulf coast region. These atlases were developed to improve forecasting of flooding along the coastline and estuaries and in adjacent inland areas. Storm-surge heights depend on a complex interaction of several factors, including: storm size, central minimum pressure, forward speed of motion, bottom topography near the point of landfall, astronomical tides, and, most importantly, maximum wind speed. The information in the atlases was generated in over 100 computational simulations, partly by use of a parallel-processing version of the ADvanced CIRCulation (ADCIRC) model. ADCIRC is a nonlinear computational model of hydrodynamics, developed by the U.S. Army Corps of Engineers and the US Navy, as a family of two- and three-dimensional finite-element-based codes. It affords a capability for simulating tidal circulation and storm-surge propagation over very large computational domains, while simultaneously providing high-resolution output in areas of complex shoreline and bathymetry. The ADCIRC finite-element grid for this project covered the Gulf of Mexico and contiguous basins, extending into the deep Atlantic Ocean with progressively higher resolution approaching the study area. The advantage of using ADCIRC over other storm-surge models, such as SLOSH, is that input conditions can include all or part of wind stress, tides, wave stress, and river discharge, which serve to make the model output more accurate. To keep the computational load manageable, this work was conducted using only the wind stress, calculated by using historical data from Hurricane Camille, as the input condition for the model. Hurricane storm-surge simulations were performed on an eight-node Linux computer cluster. Each node contained dual 2-GHz processors, 2GB of memory, and a 40GB hard drive. The digital elevation model (DEM) for this region was specified using a combination of Navy data (over water), NOAA data (for the coastline), and optimized Interferometric Synthetic Aperture Radar data (over land). This high-resolution topographical data of the Mississippi coastal region provided the ADCIRC model with improved input with which to calculate improved storm-surge forecasts.

Valenti, Elizabeth↗
DOE OSTI2025

Effect of Rocky Mountains and Tibetan Plateau 1998 Spring Land Temperature on N. American and East Asian Summer Precipitation Anomalies

This work follows up on the GEWEX/LS4P Phase I (LS4P-I) experiments, a community effort highlighting the spring land surface temperature anomalies in the Tibetan Plateau (TP) as a useful source for subseasonal to seasonal (S2S) prediction of summer precipitation in global hot spot regions, particularly in East Asia and North America. This paper extends the investigation to both the US Rocky Mountain (RM) region and the TP, considering the 1998 summer drought/flood event in North America/East Asia, respectively, as a case study. A previously developed initialization method for land surface temperature/subsurface temperature (LST/SUBT) is used in the NCEP Global Forecast System, coupled with a land model, SSiB2 (GFS/SSiB2), to produce observed RM cold May temperature anomaly. Forward simulation yields June precipitation anomalies at five remote locations. Likewise, the TP warm May temperature anomaly also produces June precipitation anomalies at these five locations. The effects of RM (cold) and TP (warm) temperature anomalies are consistent in the US South Coastal regions and the south Yangtze River Basin, yielding 49% (42%) of observed drought and 34% (44%) of observed flood, respectively. These LST/SUBT effects in RM and TP induce a global large-scale wave train linking North America with the TP, affecting the subtropical westerly jet and thereby modulating summer precipitation. Global SST effect is examined for comparison but does not yield statistically significant June precipitation anomalies in GFS/SSiB2. Furthermore, this study adds to evidence that high-mountain LST effects in the RM and TP are first-order sources of S2S precipitation predictability in summer months.

Nayak, Hara Prasad [University of California, Los ↗
NASA NTRS2012

Integrated Modeling of Aerosol, Cloud, Precipitation and Land Processes at Satellite-Resolved Scales

In this talk, I will present recent results from a project led at NASA/GSFC, in collaboration with NASA/MSFC and JHU, focused on the development and application of an observation-driven integrated modeling system that represents aerosol, cloud, precipitation and land processes at satellite-resolved scales. The project, known as the NASA Unified WRF (NU-WRF), is funded by NASA's Modeling and Analysis Program, and leverages prior investments from the Air Force Weather Agency and NASA's Earth Science Technology Office (ESTO). We define "satellite-resolved" scales as being within a typical mesoscale atmospheric modeling grid (roughly 1-25 km), although this work is designed to bridge the continuum between local (microscale), regional (mesoscale) and global (synoptic) processes. NU-WRF is a superset of the standard NCAR Advanced Research WRF model, achieved by fully integrating the GSFC Land Information System (LIS, already coupled to WRF), the WRF/Chem enabled version of the Goddard Chemistry Aerosols Radiation Transport (GOCART) model, the Goddard Satellite Data Simulation Unit (SDSU), and boundary/initial condition preprocessors for MERRA and GEOS-5 into a single software release (with source code available by agreement with NASA/GSFC). I will show examples where the full coupling between aerosol, cloud, precipitation and land processes is critical for predicting local, regional, and global water and energy cycles, including some high-impact phenomena such as floods, hurricanes, mesoscale convective systems, droughts, and monsoons.

Peters-Lidard, Christa↗
NASA NTRS2005

Outflow Channels Influencing Martian Climate: Global Circulation Model Simulations with Emplaced Water

The existence of surface water on Mars in past geologic epochs is inferred on the basis of geomorphologic interpretation of spaceflight images, and is supported by the recent Mars Odyssey identification of ice-rich soils [1]. The Mars Exploration Rovers have provided further chemical evidence for past surface hydrologic activity [2]. One issue is whether this water-rich climate ever existed in a steady state, or whether it was triggered by catastrophic events such as large impacts [3], and/ or catastrophic outburst floods, the topic of consideration here.

Santiago, D. L.↗
DOE OSTI2021

Earth System Model Improvement Pipeline via Uncertainty Attribution and Active Learning

Primary focal area: 2 (Predictive Modeling via AI): We develop methods to formally quantify uncertainties in Earth System models for the land-atmosphere coupled system. Science Challenge: Earth system models still have significant biases in historical predictions of the intensity and frequency of water cycling extremes (e.g., droughts and flood events), leading to low confidence in future projections. Uncertainties arise from incomplete understanding of land and atmospheric processes, and insufficient observational constraints on model parameters. Many observations, including those from key DOE investments such as ARM and AmeriFlux, are used to evaluate model performance but have not been used to formally quantify model uncertainty because of the expense of running ESM simulations. An efficient pipeline engaging cutting-edge machine learning (ML) and uncertainty quantification (UQ) methods is needed to improve the predictive understanding of water cycle extremes in the Earth system.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

Effect of the Trendelenburg position on the distribution of arterial air emboli in dogs

The effect of Trendelenburg position (TP) on the distribution of arterial air emboli in dogs was examined in a two-part investigation. In the first part, the effects of the bubble size and the vessel angle on the bubble velocity and the direction of flow were investigated in vitro, using a simulated carotid artery preparation. It was found that larger bubbles increased in velocity in the same direction as the blood flow at 0-, 10-, and 30-deg vessel angles, and decreased when the vessel was positioned at 90 deg. Smaller bubbles did not change velocity from 0 to 30 deg, but acted to increase the velocity, in the same direction as the flood flow, at 90 deg. The second series of experiments examined the effect of 0 to 30 deg TP on carotid-artery distribution of gas bubbles injected into the left ventricle or ascending aorta of anesthetized dogs. It was found that, regardless of the degree of the TP, the bubbles passed into the carotid artery simultaneously with the passage into the abdominal aorta. It is concluded that the TP does not prevent arterial bubbles from reaching the brain.

Butler, Bruce D.↗
DOE OSTI2024

Stress Testing California's Hydroclimatic Whiplash: Potential Challenges, Trade‐Offs and Adaptations in Water Management and Hydropower Generation

Abstract Inter‐annual precipitation in California is highly variable, and future projections indicate an increase in the intensity and frequency of hydroclimatic “whiplash.” Understanding the implications of these shocks on California's water system and its degree of resiliency is critical from a planning perspective. Therefore, we quantify the resilience of reservoir services provided by water and hydropower systems in four basins in the western Sierra Nevada. Using downscaled runoff from 10 climate model outputs, we generated 200 synthetic hydrologic whiplash sequences of alternating dry and wet years to represent a wide range of extremes and transitional conditions used as inputs to a water system simulation model. Sequences were derived from upper (wet) and lower (dry) quintiles of future streamflow projections (2030–2060). Results show that carryover storage was negatively affected in all basins, particularly in those with lower storage capacity. All basins experienced negative impacts on hydropower generation, with losses ranging from 5% to nearly 90%. Reservoir sizes and inflexible operating rules are a particular challenge for flood control, as in extremely wet years spillage averaged nearly the annual basins' total discharge. The reliability of environmental flows and agricultural deliveries varied depending on the basin, intensity, and duration of whiplash sequences. Overall, wet years temporarily rebound negative drought effects, and greater storage capacity results in higher reliability and resiliency, and lesser volatility in services. We highlight potential policy changes to improve flexibility, increase resilience, and better equip managers to face challenges posed by whiplash while meeting human and environmental needs.

Environmental Sciences & Ecology↗
DOE OSTI2024

Methane-cycling microbial communities from Amazon floodplains and upland forests respond differently to simulated climate change scenarios

Seasonal floodplains in the Amazon basin are important sources of methane (CH 4 ), while upland forests are known for their sink capacity. Climate change effects, including shifts in rainfall patterns and rising temperatures, may alter the functionality of soil microbial communities, leading to uncertain changes in CH 4 cycling dynamics. To investigate the microbial feedback under climate change scenarios, we performed a microcosm experiment using soils from two floodplains (i.e., Amazonas and Tapajós rivers) and one upland forest. We employed a two-factorial experimental design comprising flooding (with non-flooded control) and temperature (at 27 °C and 30 °C, representing a 3 °C increase) as variables. We assessed prokaryotic community dynamics over 30 days using 16S rRNA gene sequencing and qPCR. These data were integrated with chemical properties, CH 4 fluxes, and isotopic values and signatures. In the floodplains, temperature changes did not significantly affect the overall microbial composition and CH 4 fluxes. CH 4 emissions and uptake in response to flooding and non-flooding conditions, respectively, were observed in the floodplain soils. By contrast, in the upland forest, the higher temperature caused a sink-to-source shift under flooding conditions and reduced CH 4 sink capability under dry conditions. The upland soil microbial communities also changed in response to increased temperature, with a higher percentage of specialist microbes observed. Floodplains showed higher total and relative abundances of methanogenic and methanotrophic microbes compared to forest soils. Isotopic data from some flooded samples from the Amazonas river floodplain indicated CH 4 oxidation metabolism. This floodplain also showed a high relative abundance of aerobic and anaerobic CH 4 oxidizing Bacteria and Archaea. Taken together, our data indicate that CH 4 cycle dynamics and microbial communities in Amazonian floodplain and upland forest soils may respond differently to climate change effects. We also highlight the potential role of CH 4 oxidation pathways in mitigating CH 4 emissions in Amazonian floodplains.

16S rRNA sequencing↗
NASA NTRS2002

Mesoscale Convective Systems During SCSMEX: Simulations with a Regional Climate Model and a Cloud-Resolving Model

The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China (Lau et al. 2000). Multiple observation platforms (e.g., soundings, Doppler radar, ships, wind seafarers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convection and circulation changes, associated with monsoons over the South China Sea region. SCSMEX also provided precipitation derived from atmospheric budgets (Johnson and Ciesielski 2002) and comparison to those obtained from the Tropical Rainfall Measuring Mission (TRMM). In this paper, a regional climate model and a cloud-resolving model are used to perform multi-day integrations to understand the precipitation processes associated with the summer monsoon over Southeast Asia and southern China. The regional climate model is used to understand the soil - precipitation interaction and feedback associated with a flood event that occurred in and around China's Atlantic River during SCSMEX. Sensitivity tests on various land surface models, cumulus parameterization schemes (CASE), sea surface temperature (SST) variations and midlatitude influences are also performed to understand the processes associated with the onset of the monsoon over the S. China Sea during SCSMEX. Cloud-resolving models (CRMs) use more sophisticated and physically realistic parameterizations of cloud microphysical processes with very fine spatial and temporal resolution. One of the major characteristics of CRMs is an explicit interaction between clouds, radiation and the land/ocean surface. It is for this reason that GEWEX (Global Energy and Water Cycle Experiment) has formed the GCSS (GEWEX Cloud System Study) expressly for the purpose of improving the representation of the moist processes in large-scale models using CRMs. The Goddard Cumulus Ensemble (GCE) model is a CRM and is used to simulate convective systems associated with the onset of the South China Sea monsoon in 1998. The BRUCE model includes the same land surface model, cloud physics, and radiation scheme used in the regional climate model. A comparison between the results from the GCE model and regional climate model is performed.

Tao, W. K.↗
DOE OSTI2022

Future changes in extreme precipitation over the San Francisco Bay Area: Dependence on atmospheric river and extratropical cyclone events

Extreme precipitation poses a major challenge for local governments, including the City and County of San Francisco, California, as flooding can damage and destroy infrastructure and property. As the climate continues to warm, reliable future precipitation projections are needed to provide the best possible information to decision makers. However, future changes in the magnitude of extreme precipitation are uncertain, as current state-of-the-art global climate models are typically run at relatively coarse horizontal resolutions that require the use of convective parameterization and have difficulty simulating observed extreme rainfall rates. Here, we performed ensembles of convection-permitting regional climate model simulations to investigate how five historically impactful extreme precipitation events over the San Francisco Bay Area could change if similar events occurred in future climates. We found that changes in storm-total precipitation depend strongly on storm type. Precipitation associated with an atmospheric river (AR) accompanied by an extratropical cyclone (ETC) is projected to increase at a rate exceeding (by up to 1.5 times) the theoretical Clausius Clapeyron scaling of 6–7% per °C warming. On the other hand, future precipitation changes are weak or negative for events characterized by an AR only, despite increases in precipitable water and integrated vapor transport that are similar to those of the co-occurring AR and ETC events. The differences in the sign of future precipitation change between AR-only events and co-occurring AR and ETC events is instead linked with changes in mid-tropospheric vertical velocity. Given that the majority of observed ARs are associated with an ETC, this research has important implications for future precipitation impacts over the Bay Area, as it indicates that storm-total precipitation associated with the most common type of storm event may increase by up to 26–37% in 2100 relative to historical.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Projected changes in cross-equatorial northerly surges and their hydrological impacts in the near future

Recent decades have witnessed unprecedented extreme precipitation and catastrophic flooding in some of the most populated regions in Southeast Asia during boreal winter. These extreme events are often influenced by the cross-equatorial northerly surge (CENS), characterized by a strengthening of northerly moist monsoon winds south of the equator in the western Maritime Continent. However, the potential future changes in CENS and its hydrological impacts remain underexplored. Here, using an ensemble of high-resolution climate model simulations (CMIP6 HighResMIP), we show that the regional impacts of CENS on the intensity and frequency of extreme precipitation events are projected to significantly increase in the near future (2030–2050), particularly over the adjacent coastal regions of southern Indonesia and northwestern Australia. More specifically, the risk of CENS-related extreme precipitation is projected to increase by up to 39 ± 1.2% relative to the seasonal probability, despite no apparent changes in the CENS characteristics in the near future. Such stronger impact is attributed to the enhanced moistening efficiency and moist static instability due to a more humid and warmer environment, which leads to more intense CENS convection. Our results suggest the need for effective monitoring and disaster managements to respond to the increasing severity of such events in the near future.

Climate sciences↗
DOE OSTI2025

Monthly averages of ED2 model simulations initialized with airborne lidar structure, Jan 1981-Dec 2018, Brazilian Amazon

Deforestation and forest degradation (selective logging, fires, fragmentation) have impacted nearly 40% of the original extent of the Brazilian Amazon, and have markedly impacted forest structure across the region. To date, few studies analysed how shifts in forest structure from degradation influence the forest sensitivity to climate extremes, because of the complex interactions between forest structure and micro-environmental conditions. To address this knowledge gap, we carried out a series of simulations across the Brazilian Amazon using the Ecosystem Demography Model (ED2), using observed forest structure derived from 541 airborne lidar transects (375 ha each) and two scenarios representing forest recovery and expansion of degradation to investigate how shifts in forest structure impact ecosystem function under near-average and extreme climate conditions, as part of the manuscript Longo et al 2025 "Degradation and Deforestation Increase the Sensitivity of the Amazon Forest to Climate Extremes". This dataset provides the output results from the ED2 model simulations for the three simulations at monthly time scales, in NetCDF format. For all simulations, we used bias-corrected hourly reanalyses (WFDE5) for most meteorological drivers, except for precipitation, which was obtained from CHIRPS. The meteorological drivers used in the study span 38 years (Jan 1981–Dec 2018). The output results correspond to the last 38 years of simulation (one full cycle of meteorological drivers), in which ED2 simulations used static stand structure (i.e., the forest structure was held constant). The following files are provided:ED2_emean_Global_R004_BrAmaz_s1c0t0l0f0.nc. This corresponds to the Control simulation. The forest structure was obtained from the airborne lidar.ED2_emean_Global_R005_BrAmaz_s1c0t1l1f0.nc. This corresponds to the Degraded simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that expanded deforestation and selective logging across the Amazon.ED2_emean_Global_R006_BrAmaz_s1c0t1l0f0.nc. This corresponds to the Recovery simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that completely halted deforestation and degradation, allowing degraded forests to recover for 38 years.We also provide file ED2_zones_R004_BrAmaz_s1c0t0l0f0.nc, which classifies each grid cell into zones used in the reference manuscript: 1: Southeast. 2: South. 3: West. 4: Central. 5: Northeast. 6: North. 7: Northwest". Index 0 corresponds to grid cells excluded from sub-region analyses because they were dominated by flooded forests, deforestation, and naturally non-forest vegetation.

54 ENVIRONMENTAL SCIENCES↗