A climatic dipole drives short- and long-term patterns of postfire forest recovery in the western United States
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Caitlin E. Littlefield↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Observations of Local Positive Low Cloud Feedback Patterns and Their Role in Internal Variability and Climate Sensitivity
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Tianle Yuan↗
Sea-surface temperature pattern effects have slowed global warming and biased warming-based constraints on climate sensitivity
The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR)—key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO 2 forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed warming is consistent with wide ranges of ECS and TCR extending to higher values than previously recognized. These findings are corroborated by energy balance model simulations and coupled model (CESM1-CAM5) simulations that better replicate observed patterns via tropospheric wind nudging or Antarctic meltwater fluxes. Because CMIP5/6 models fail to simulate observed warming patterns, proposed warming-based constraints on ECS, TCR, and projected global warming are biased low. The results reinforce recent findings that the unique pattern of observed warming has slowed global-mean warming over recent decades and that how the pattern will evolve in the future represents a major source of uncertainty in climate projections.
58 GEOSCIENCES↗
Lagrangian Characterization of Surface Transport From the Equatorial Atlantic to the Caribbean Sea Using Climatological Lagrangian Coherent Structures and Self‐Organizing Maps
Abstract This study presents an assessment of the transport of suspended material by surface ocean currents, which have a critical role in determining the connectivity and distribution of living and non‐living material. Lagrangian experiments reveal pathways from the Equatorial Atlantic to 10 strategic regions within the Caribbean Sea, determined by considering the space‐time variability of climatological Lagrangian Coherent Structures, which act as recurrent attracting pathways and transport barriers. Due to windage or Stokes drift, wind forcing is a significant factor in determining the spatial locations where particles cluster and the time needed to reach the Caribbean from the Equatorial Atlantic. Pathways shift westward within the Caribbean and take less time to arrive with increasing wind influence. Depending on the wind effect, the particles show higher confluence in different areas of the Caribbean. A case study is presented for the Mexican Caribbean nearshore area, isolated from ocean‐current trajectories. Here, wind weakens the transport barrier responsible for this isolation and causes particle confluence toward that region. Spatial patterns of the Eulerian velocity identified through Self‐Organizing Maps, with time dependence given by their best matching units, can reproduce the characteristic Lagrangian patterns of surface current climate variability. Our study demonstrates the application of tools from dynamical systems and unsupervised neural networks to understand Lagrangian patterns and identify the processes that drive them. These findings improve our understanding of transport mechanisms of suspended material by surface ocean currents in the Western Atlantic and the Caribbean Sea, which is essential for managing and conserving marine ecosystems.
Allende‐Arandía, Ma. Eugenia↗
Effects of Climate Change on Capacity Expansion Decisions of an Electricity Generation Fleet in the Southeast U.S.
The electric power sector in the United States faces many challenges related to climate change. On the demand side, climate change could shift demand patterns due to increased air temperatures. On the supply side, climate change could lead to deratings of thermal units due to changes in air temperature, water temperature, and water availability. Past studies have typically analyzed these risks separately. Here, we developed an integrated, multimodel framework to analyze how compounding risks of climate-change impacts on demand and supply affect long-term planning decisions in the power system. In the southeast U.S., we found that compounding climate-change impacts could result in a 35% increase in installed capacity by 2050 relative to the reference case. Participation of renewables, particularly solar, in the fleet increased, driven mostly by the expected increase in summertime peak demand. Such capacity requirements would increase investment costs by approximately 31 billion (USD 2015) over the next 30 years, compared to the reference case. These changes in investment decisions align with carbon emission mitigation strategies, highlighting how adaptation and mitigation strategies can converge.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Ubiquity and Causes of Soil Water Preferential Flow Across 17 Ecoregions
Abstract Preferential flow (PF) in soil causes the rapid transport of water, nutrients, and contaminants into the subsurface, influencing groundwater recharge and streamflow. Data scarcity has hindered the quantification of PF occurrence and the identification of its drivers across diverse ecoregions. We address this gap by analyzing high‐frequency, multi‐depth soil moisture data across 17 ecoregions in the USA, using ∼1,500 sensors at 40 sites. We discovered that PF is widespread, with sites experiencing PF in up to 60% of rainfall events ≥2 mm. Multiple approaches consistently show that PF is more likely to occur with increased peak rainfall intensity, finer textured material, low soil moisture variability, humid climate, and higher net primary productivity. This suggests that PF patterns could shift with projected climate changes, increasing uncertainty in predictions of groundwater recharge, water quality, and streamflow generation. Plain Language Summary Water can bypass part of the soil's matrix through a process called preferential flow (PF). This quick transport of water through the soil brings with it nutrients and contaminants and eventually makes it to groundwater and streams. To ensure ample amounts of good quality groundwater and surface water we need to understand when and where PF occurs. We inferred when PF occurred at 40 different sites across 17 ecoregions in the USA using soil moisture and rainfall data. We found that PF happened at all sites and in up to 60% of rainfall events ≥2 mm. Preferential flow was most likely at sites with high rainfall intensities, high clay content in soils, low variability in soil moisture, and high vegetation productivity. As rainfall intensities are predicted to increase due to climate change and vegetation becomes more productive, PF occurrence becomes more important for predicting groundwater recharge, water quality, and streamflow generation. Key Points Preferential flow (PF) is ubiquitous across the USA and occurs in up to 60% of all rainfall events ≥2 mm Rainfall intensity, soil texture, and antecedent soil moisture emerge as critical in generating PF across diverse ecoregions Two different PF detection approaches show similar relationships between key drivers and occurrence of PF
Li, Bonan↗
Projected evolution of droughts and human exposure in the contiguous United States under SSP5-8.5: a regional downscaling perspective
The increasingly unpredictable and extreme weather patterns under a warming climate underscore the urgency of accurate regional assessments of future drought risk. This study evaluates the projected drought evolution in the contiguous United States under the high-emission shared socioeconomic pathway 5–8.5 climate scenario for the coming decades. Using a multi-model ensemble of six Coupled Model Intercomparison Project Phase 6 global climate models combined with dynamical downscaling techniques, we analyzed near-term (2020–2039) and mid-term (2040–2059) drought patterns using the self-calibrating palmer drought severity index (ScPDSI), the standardized precipitation index (SPI-12), and the Standardized Precipitation-Evapotranspiration Index (SPEI-12). Results reveal a widespread increase in abnormally dry (D0) and moderate drought (D1) conditions, particularly in urban areas, while severe (D2), extreme (D3), and exceptional (D4) droughts are expected to become less common in many regions. Meanwhile, persistent and intensifying droughts are projected in the western and southwestern U.S., driven by long-term soil moisture deficits. The ScPDSI projects that 1.1 million urban residents will be affected by D0 conditions in 2050, while SPI-12 suggests a decrease in the total affected populations after 2040. ScPDSI indicates prolonged droughts in the West, and SPI-12 captures transient variability. Although the total drought-exposed population is expected to decrease, urban areas will continue to bear a greater burden, particularly for mild droughts (D0, D1). These findings highlight a shift toward more frequent mild droughts, fewer severe droughts, and persistent drying in the Southwest, emphasizing the need for region-specific adaptation strategies.
CMIP6↗
Statistical Downscaling and Bias Correction of Climate Model Outputs for Climate Change Impact Assessment in the U.S. Northeast
Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1∕8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.
extreme climate index↗
More frequent central Pacific El Niño and stronger eastern pacific El Niño in a warmer climate
El Niño events exhibit rich diversity in their spatial patterns, which can lead to distinct global impacts. Therefore, how El Niño pattern diversity will change in a warmer climate is one of the most critical issues for future climate projections. Based on the sixth Coupled Model Intercomparison Project simulations, we report an inter-model consensus on future El Niño diversity changes. Central Pacific (CP) El Niño events are projected to occur more frequently compared to eastern Pacific (EP) El Niño events. Concurrently, EP El Niño events are projected to increase in amplitude, leading to higher chances of extreme EP El Niño occurrences. We suggest that enhanced upper-ocean stability due to greenhouse warming can lead to a stronger surface-layer response for increasing positive feedbacks, more favorable excitation of CP El Niño. Whereas, enhanced nonlinear atmospheric responses to EP sea surface temperatures can lead to a higher probability of extreme EP El Niño.
54 ENVIRONMENTAL SCIENCES↗
Dataset for "Climatic and socioeconomic drivers of water use and their spatio-temporal patterns for small and mid-sized cities in the Contiguous United States"
This dataset contains all code for calibrating and analyzing machine learning models for "Climatic and socioeconomic drivers of water use and their spatio-temporal patterns for small and mid-sized cities in the Contiguous United States". Please unzip the folders and follow the instructions from 'README.txt'. Required python modulessklearn=1.2.2numpy=1.23.3xgboost=2.0.2joblib=1.2.0 Required R libraryshapFlex:devtools::install_github("nredell/shapFlex")library(shapFlex)
Dave, Hari [Civil and Environmental Engineering De↗
What Does Global Land Climate Look Like at 2°C Warming?
Constraining an increase in global mean temperature below 2°C compared to pre-industrial levels is critical to limiting dangerous and cascading impacts of anthropogenic climate change. Understanding future climatic changes and their spatial heterogeneity at 2°C warming is thus important for policy makers to prepare actionable adaptation and mitigation plans by identifying where and to what extent lives and livelihoods will be impacted. This study uses the recently released NASA Earth eXchange Global Daily Downscaled Projections (NEX-GDDP) CMIP6 data to provide a broad overview of projected changes in six key climate variables and two climate impact indicators at a time when warming exceeds 2°C. Analysis of global mean temperature changes indicates the 2040s as the decade when most CMIP6 models reach 2°C warming with respect to a pre-industrial period (1850–1900). During the 2040s, we find that global mean temperature, precipitation, relative humidity, downwelling shortwave and longwave radiation, and wind speed over land under the high emission scenario are projected to change by +2.8°C, +22.4 mm/year, −0.73%, −2.23 , +15.9 W/m 2 , and −0.04 m/s, respectively. Many of the future changes are expected to exacerbate climate impacts including heat stress and fire danger. Our analysis shows geographic patterns of policy-relevant climatic changes, as parts of the globe will experience significant climate impacts even if the goal to keep warming below 2°C goal is achieved. Our results highlight the urgent need for further studies focused on identifying key hotspots and advancing region-specific actionable adaptation and mitigation plans.
GDDP↗
Future projections of wind patterns in California with the variable-resolution CESM: a clustering analysis approach
Wind energy production is expected to be affected by shifts in wind patterns that will accompany climate change. However, many questions remain on the magnitude and character of this impact, especially on regional scales. In this study, clustering is used to group and analyze large-scale wind patterns in California using model simulations from the variable-resolution Community Earth System Model (VR-CESM). Specifically, simulations have been produced that cover historical (1980–2000), mid-century (2030–2050), and end-of-century (2080–2100) time periods. Once clustered, observed changes to wind patterns can be analyzed in terms of both the change in frequency of those clusters and changes to winds within-clusters. Statistically significant capacity factors changes have been found at all five wind plant sites. Further, decomposition of the capacity factor changes into frequency changes and within-cluster changes enables a better understanding of their drivers. A further examination of the synoptic-scale fields associated with each cluster then provides a better understanding of how changes to large-scale meteorological fields are important for driving changes in localized wind speeds.
17 WIND ENERGY↗
Cold climate mapping using satellite high resolution thermal imagery
In an attempt to improve cold climate mapping and freeze forecasting techniques, thermal imagery from the NOAA-2 and -3 satellites and the Synchronous Meteorological Satellite (SMS) were obtained and analyzed. Enhanced image transparencies showed detailed temperature patterns over the peninsula of Florida. The analysis was superior to hand-drawn isotherms drawn from the 300 to 500 thermograph stations presently in use. Satellite data on several cold nights with similar synoptic conditions showed that similar cold patterns existed. Thus, cold climate mapping is possible.
Bartholic, J. F.↗
Large-Scale Circulation and Climate Variability
The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.
Perlwitz, J.↗
Wintertime East Asian Jet Stream and Its Association with the Asian-Pacific Climate
Interannual variability of the wintertime East Asian westerly jet stream and the linkage between this variability and the Asian-Pacific climate are investigated. The study emphasizes on the variability of the jet core and its association with the Asian winter monsoon, tropical convection, upper tropospheric wave patterns, and the teleconnection of the jet with other climate systems. The relationship between the jet and North Pacific sea surface temperature pattern (SST) is also explored. NCEP/NCAR reanalysis, NASA GISS surface temperature, NASA GEOS reanalysis, NOAA reconstructed SST, GPCP precipitation, and NOAA snow cover data sets are analyzed in this study. An index of the East Asian jet has been defined by the December-February means of the 200 mb zonal winds that are averaged within a box enclosing the jet maximum, which shifts only moderately from one year to another especially in the south-north direction. The jet links to a teleconnection pattern whose major climate anomalies appear over the Asian continent and western Pacific (west of the dateline). This pattern differs distinctly from the teleconnection pattern associated with El Nino/Southern Oscillation (ENSO), which causes the Pacific/North American pattern to the east of the dateline. A strong jet is accompanied clearly by an increase in the intensity of the atmospheric circulation over Asia and the Pacific. In particular, the winter monsoon strengthens over East Asia, leading to cold climate in the region, and convection intensifies over the tropical Asia-Australia sector. Changes in the jet are associated with broad-scale modification in the upper tropospheric wave patterns that leads to downstream climate anomalies over the eastern Pacific. Through this downstream influence, the East Asian jet causes climate signals in North America as well. A strong jet gives rise to warming and less snow cover in the western United States but reverse climate anomalies in the eastern part of the country, although these signals are relatively weaker than the jet-related anomalies in East Asia. There is a strong association between the East Asian jet and the North Pacific SST (NPSST). A strong jet is accompanied by a cooling in the extratropical Pacific and a warming in the tropical-subtropical Pacific. Evidence also indicates that the extratropical NPSST pattern plays a role in modulating the intensity of the jet stream. ENSO, the jet, and the NPSST are mutually interactive on certain time scales and such an interaction links closely to the climate anomalies in the Asian-Pacific-American regions.
Yang, Song↗
Surface-to-Interior Transport Timescales and Ventilation Patterns in a Time-Dependent Circulation Driven by Sustained Climate Warming
Abstract The effect of climate warming in response to rising atmospheric CO 2 on the ventilation of the ocean remains uncertain. Here we make theoretical advances in elucidating the relationship between ideal age and transit time distribution (TTD) in a time-dependent flow. Subsequently, we develop an offline tracer-transport model to characterize the ventilation patterns and time scales in the time-evolving circulation for the 1850–2300 period as simulated with the Community Earth System Model version 1 (CESMv1) under a business-as-usual warming scenario. We found that by 2300 2.1% less water originates from the high-latitude deep water formation regions (both hemispheres) compared to 1850. In compensation, there is an increase in the water originating from the subantarctic. We also found that slowing meridional overturning circulation causes a gradual increase in mean age during the 1850–2300 period, with a globally averaged mean-age increase of ∼110 years in 2300. Where and when the water will be re-exposed to the atmosphere depends on the post-2300 circulation. For example, if we assume that the circulation persists in its year-2300 state (scenario 1), the mean interior-to-surface transit time in year 1850 is ∼1140 years. In contrast, if we assume that the circulation abruptly recovers to its year-1850 state (scenario 2), the mean interior-to-surface transit time in 1850 is only ∼740 years. By 2300, these differences become even larger; in scenario 1, the mean interior-to-surface transit time increases by ∼200 years, whereas scenario 2 decreases by ∼80 years. The dependence of interior-to-surface transit time on the future ocean circulation produces an additional unavoidable uncertainty in the long-term durability of marine carbon dioxide removal strategies. Significance Statement The ocean’s circulation, when altered by climate warming, can affect its capacity to absorb heat and CO 2 , which are crucial for the global climate. In our study, we investigated how global warming, caused by rising CO 2 levels, might impact the ocean circulation—the way water moves from deep ocean to the surface and vice versa. We discovered that by 2300, if we continue on our current warming trajectory, the origins of water within the ocean will shift, with less coming from deep, cold zones near the poles and more from subantarctic regions. As a result, deep water will take longer time before it resurfaces than shallow water. How quickly this water travels from deep regions to the surface could change, depending on the state of future ocean circulation. If the circulation remains as predicted in 2300, this journey will take longer. Conversely, if it reverts to the pattern in 1850, the process will be quicker. This variability introduces added uncertainty to strategies aimed at mitigating climate change by storing CO 2 in the ocean. Our work highlights the intricate ways in which climate change can influence our oceans, potentially affecting our plans to mitigate global warming.
54 ENVIRONMENTAL SCIENCES↗
Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes
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Weiqing Han↗