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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Seasonal changes in GPP/SIF ratios and their climatic determinants across the Northern Hemisphere

Satellite-derived sun-induced chlorophyll fluorescence (SIF) has been increasingly used for estimating gross primary production (GPP). However, the relationship between SIF and GPP has not been well defined, impeding the translation of satellite observed SIF to GPP. Previous studies have generally assumed a linear relationship between SIF and GPP at daily and longer time scales, but support for this assumption is lacking. Here, we used the GPP/SIF ratio to investigate seasonal variations in the relationship between SIF and GPP over the Northern Hemisphere (NH). Based on multiple SIF products and MODIS and FLUXCOM GPP data, we found strong seasonal hump-shaped patterns for the GPP/SIF ratio over northern latitudes, with higher values in the summer than in the spring or autumn. This hump-shaped GPP/SIF seasonal variation was confirmed by examining different SIF products and was evident for most vegetation types except evergreen broadleaf forests. The seasonal amplitude of the GPP/SIF ratio decreased from the boreal/arctic region to drylands and the tropics. For most of the NH, the lowest GPP/SIF values occurred in October or September, while the maximum GPP/SIF values were evident in June and July. The most pronounced seasonal amplitude of GPP/SIF occurred in intermediate temperature and precipitation ranges. GPP/SIF was positively related to temperature in the early and late parts of the growing season, but not during the peak growing months. These shifting relationships between temperature and GPP/SIF across different months appeared to play a key role in the seasonal dynamics of GPP/SIF. Several mechanisms may explain the patterns we observed, and future research encompassing a broad range of climate and vegetation settings is needed to improve our understanding of the spatial and temporal relationships between SIF and GPP. Nonetheless, the strong seasonal variation in GPP/SIF we identified highlights the importance of incorporating this behavior into SIF-based GPP estimations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

The Role of Internal Variability in Springtime Arctic Amplification from 1980 to 2022

Arctic amplification (AA) refers to the enhanced warming of the Arctic relative to the global average due to rising greenhouse gases, measured as the ratio of Arctic-mean to global-mean surface air temperature (SAT) trends. From 1980 to 2022, annual-mean AA reached 4.2 (Arctic defined as north of 70°N). Climate models simulate AA but fail to reproduce its magnitude. Sweeney et al. attributed much of this model–observation discrepancy to internal variability. AA shows seasonality and so does the discrepancy. Spring (March–May) shows the largest gap: Observed AA is 4.2, while the multimodel mean is 2.7. This raises several questions: 1) What role does internal variability play in observed spring AA? 2) How does simulated spring AA compare to observations when internal variability is removed? 3) If internal variability is significant, what mechanisms drive it? To address these, we adapted the machine learning algorithm from Sweeney et al., training on simulated multidecadal spring SAT and sea level pressure (SLP) trend maps. Our results show that internal variability enhanced spring Arctic warming by 37% and reduced global warming by 10%. Removing internal variability reconciles the spring AA discrepancy. The estimated internal contribution to Arctic spring warming is supported by an independent dynamical adjustment approach. We identify an atmospheric circulation pattern in observations associated with this internal warming. Observed internal Siberian SAT and SLP trends follow the simulated SAT–SLP relationship but lie at the distribution’s extreme, suggesting models generally underestimate internal variability unless the observed configuration reflects a rare real-world realization.

Arctic↗
DOE OSTI2023

Divergent Metabolic Changes in Rhizomes of Lowland and Upland Switchgrass (Panicum virgatum) from Early Season through Dormancy Onset

High-biomass-yielding southerly adapted switchgrasses (Panicum virgatum L.) frequently suffer from unpredictable winter hardiness at more northerly sites arising from damage to rhizomes that prevent effective spring regrowth. Previously, changes occurring over the growing season in rhizomes sampled from a cold-adapted tetraploid upland cultivar, Summer, demonstrated a role for abscisic acid (ABA), starch accumulation, and transcriptional reprogramming as drivers of dormancy onset and potential keys to rhizome health during winter dormancy. Here, rhizome metabolism of a high-yielding southerly adapted tetraploid switchgrass cultivar, Kanlow—which is a significant source of genetics for yield improvement—was studied over a growing season at a northern site. Metabolite levels and transcript abundances were combined to develop physiological profiles accompanying greening through the onset of dormancy in Kanlow rhizomes. Next, comparisons of the data to rhizome metabolism occurring in the adapted upland cultivar Summer were performed. These data revealed both similarities as well as numerous differences in rhizome metabolism that were indicative of physiological adaptations unique to each cultivar. Similarities included elevated ABA levels and accumulation of starch in rhizomes during dormancy onset. Notable differences were observed in the accumulation of specific metabolites, the expression of genes encoding transcription factors, and several enzymes linked to primary metabolism.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Iowa’s agriculture is losing its Goldilocks climate

The Iowa landscape is endowed with rich, deep, dark soils that have high water-holding capacity. Because most of the state’s land is flat or gently rolling, agriculture can be practiced with large, efficient machinery. Historically, Iowa’s average climate is characterized by a growing season of about five to six months with favorable sunshine and warm temperatures. Its crop-dormant season has low enough temperatures to prevent overwintering of detrimental pests and pathogens. The seasonal cycle of precipitation has a spring–summer maximum and a winter minimum that generally provide a sufficient and timely supply of water to support high crop densities without the need for irrigation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Life Cycle Analysis of Growing Canola for Biofuel Production in the United States

This study quantifies and compares the life cycle greenhouse gas (GHG) emissions of renewable diesel (RD), sustainable aviation fuel (SAF), and biodiesel (BD) produced from two U.S. canola production systems: 1) emerging intermediate winter canola, typically grown in double- or relay-cropping systems between the growing seasons of main crops, and 2) main canola, mostly spring canola but also including winter canola, which are grown as primary crops occupying the field for a full growing season. Using the Research and Development version of the Greenhouse gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) model and the most up-to-date life cycle inventory data─field trial data for intermediate winter canola (>37,000 acres) and recent national survey data for spring canola─this life cycle analysis (LCA) estimates the direct emissions from canola cultivation and harvest, the conversion of canola into fuels, fuel transportation, and combustion. In addition, we account for market-mediated emissions associated with a scenario of 0.5 billion gallons per year of spring canola-based biofuels, including induced land use change (ILUC), induced other crop (nonfeedstock) production changes, and induced livestock production changes. For intermediate winter canola, these market-mediated effects were not modeled, as ILUC is expected to be negligible due to its integration into existing rotations, and data are currently insufficient to reliably quantify other market-mediated changes. The estimated life cycle direct emissions of RD/SAF derived from intermediate winter canola and main spring canola are about 32 and 33 g of CO2-equivalent per megajoule of fuel (g CO 2 e/MJ), respectively. Corresponding emissions for BD from intermediate winter canola and main spring canola are about 30 and 31 g of CO 2 e/MJ, respectively. Farming is the dominant emissions source for both canola systems, with intermediate winter canola and main spring canola emitting about 19 and 20 g of CO 2 e/MJ, respectively. ILUC and other induced changes increase emissions of main spring canola-derived RD/SAF and BD by about 18 and 17 g of CO 2 e/MJ, respectively. These results indicate that the GHG emissions of biofuels produced from the two canola systems may differ substantially due to the different land use dynamics of the systems.

biodiesel↗
DOE OSTI2024

Recent increases in annual, seasonal, and extreme methane fluxes driven by changes in climate and vegetation in boreal and temperate wetland ecosystems

Climate warming is expected to increase global methane (CH 4 ) emissions from wetland ecosystems. Although in situ eddy covariance (EC) measurements at ecosystem scales can potentially detect CH 4 flux changes, most EC systems have only a few years of data collected, so temporal trends in CH 4 remain uncertain. Here, we use established drivers to hindcast changes in CH 4 fluxes (FCH 4 ) since the early 1980s. We trained a machine learning (ML) model on CH 4 flux measurements from 22 [methane-producing sites] in wetland, upland, and lake sites of the FLUXNET-CH 4 database with at least two full years of measurements across temperate and boreal biomes. The gradient boosting decision tree ML model then hindcasted daily FCH 4 over 1981-2018 using meteorological reanalysis data. We found that, mainly driven by rising temperature, half of the sites (n = 11) showed significant increases in annual, seasonal, and extreme FCH 4 , with increases in FCH 4 of ca. 10% or higher found in the fall from 1981–1989 to 2010–2018. The annual trends were driven by increases during summer and fall, particularly at high-CH 4 -emitting fen sites dominated by aerenchymatous plants. We also found that the distribution of days of extremely high FCH 4 (defined according to the 95th percentile of the daily FCH 4 values over a reference period) have become more frequent during the last four decades and currently account for 10–40% of the total seasonal fluxes. The share of extreme FCH 4 days in the total seasonal fluxes was greatest in winter for boreal/taiga sites and in spring for temperate sites, which highlights the increasing importance of the non-growing seasons in annual budgets. Our results shed light on the effects of climate warming on wetlands, which appears to be extending the CH 4 emission seasons and boosting extreme emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Wind ramp events validation in NWP forecast models during the second Wind Forecast Improvement Project (WFIP2) using the Ramp Tool and Metric (RT&M)

The second Wind Forecast Improvement Project (WFIP2) is a multi-agency field campaign held in the Columbia Gorge area (October 2015 - March 2017). The main goal of the project is to understand and improve the forecast skill of numerical weather prediction (NWP) models in complex terrain, particularly beneficial for the wind energy industry. This region is well-known for its excellent wind resource. One of the biggest challenges for wind power production is the accurate forecasting of wind ramp events (large changes of generated power over short periods of time). Poor forecasting of the ramps requires large and sudden adjustments in conventional power generation, ultimately increasing the costs of power. A Ramp Tool and Metric (RT&M) was developed during the first WFIP experiment, held in the U.S. Great Plains (September 2011 - August 2012). The RT&M was designed to explicitly measure the skill of NWP models at forecasting wind ramp events. Here we apply the RT&M to 80-m (turbine hub-height) wind speeds measured by 19 sodars and 3 lidars, and to forecasts from the High Resolution Rapid Refresh (HRRR), 3-km, and from the High Resolution Rapid Refresh Nest (HRRRNEST), 750-m horizontal grid spacing, models. The diurnal and seasonal distribution of ramp events are analyzed, finding a noticeable diurnal variability for spring and summer but less for fall and especially winter. Also, winter has fewer ramps compared to the other seasons. The model skill at forecasting ramp events, including the impact of the modification to the model physical parameterizations, was finally investigated.

Djalalova, Irina V.↗
DOE OSTI2022

Interannual consistency of migration phenology is season- and breeding region-specific in North American Golden Eagles

Abstract Interannual consistency (an indicator of the strength of adjustments) in migration phenology of Golden Eagles (Aquila chrysaetos) in North America is most strongly associated with the breeding region, the season, and with late-season temperature on breeding and wintering grounds. Consistency was greatest in boreal spring migration and the breeding regions of eastern Canada. Using multi-year GPS tracks of 83 adults breeding in 3 spatially distant regions (Alaska, northeast Canada, and southeast Canada), we quantified the interannual consistency of migration phenology and wintering latitude within and among individuals tracked across multiple years and the repeatability (r) by breeding regions and seasons. By comparing regions and seasons, we found that consistency was highest (r > 0.85) for boreal spring migration in eastern Canada while Alaska had the lowest value (r < 0.15). Because seasonal consistency of migration phenology was only detected in eastern Canada, we conclude that seasonal features are not a primary constraint. While regional differences in consistency were not related to differences in migratory distances, they could be the result of genetic or habitat differences. We also found that temperatures warmer than the decadal average at the region of departure delayed the start of boreal spring migration by ~10 days and advanced boreal autumn migration by ~20 days. These results suggest that warmer temperatures would reduce residence time on breeding grounds, contrary to expectations and trends found in other studies. Wide variations in migratory strategies across a species distribution can add to the list of challenges for conservation but may give migrants the capacity to acclimate to environmental changes.

Zoology↗
DOE OSTI2021

The Phase-Locking of Tropical North Atlantic and the Contribution of ENSO

The Tropical North Atlantic (TNA) is characterized by significant interannual variability in sea surface temperature (SST), which is phase-locked to the boreal spring. In this study, the phase-locking of TNA is investigated by adopting a linear stochastic-dynamical model (SDM) using seasonally modulated TNA feedbacks together with the seasonal modulation of ENSO forcing. In the observations, the role of local TNA feedbacks and ENSO forcing in TNA phase-locking are equivalently important with both preferring the peak of TNA variability to appear in the boreal spring. Besides, the seasonal modulation of TNA feedbacks and ENSO forcing strength are both mainly controlled by thermodynamic processes. In most climate models, the contribution of ENSO on TNA phase-locking is weaker than that in observations. The strength of ENSO-related TNA phase-locking is highly correlated with the relationship between ENSO and TNA, which is mainly determined by the amplitude of ENSO and its teleconnection patterns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Detection and attribution of long-term and fine-scale changes in spring phenology over urban areas: A case study in New York State

Spring phenology plays an essential role in climate change, terrestrial ecosystem, and public health. Field-based monitoring and understanding of changes in spring phenology for long periods and in large regions are challenging due to the limited in-site observations. Space-based remotely sensed observations offer great potentials for monitoring decadal spring phenology changes from regional to global scales. However, the coarse-scale remotely sensed observations are insufficient to capture fine-scale spring phenology dynamics, especially in urban areas, and this makes it challenging for understanding the combined effects of climate change and urbanization on spring phenology. We derived the start of phenology season (SOS) in New York State using 30 m Landsat observations from 1990 to 2015 to understand the impact of the environment and urbanization on SOS. The results show that SOS for different years reveals heterogeneous spatial distribution. Most regions of New York State have been experiencing significant spring phenology changes in form of earlier onset of vegetation greening, ranging from 0.2 to 0.6 day/year during 1990 to 2015, and this trend varies slightly with latitudes and urbanization levels. Further, spatial correlation analysis shows that the increase in temperature and urbanization could both promote the advancement of SOS. However, the effect of urbanization (partial correlation coefficient (R) ranges from −0.289 to −0.542) on SOS is greater than the effect of temperature (R ranges from 0.006 to −0.192). The study generates a high spatio-temporal resolution spring phenology dataset for ecological, environmental and public health studies, especially in urban areas, and reveals the importance of better accounting for the urbanization effects when quantifying the SOS dynamics in phenology models.

Landsat↗
DOE OSTI2022

Latitudinal shifts of soil microbial biomass seasonality

Soil microbes ultimately drive the mineralization of soil organic carbon and thus ecosystem functions. We compiled a dataset of the seasonality of microbial biomass carbon (MBC) and developed a semi-mechanistic model to map monthly MBC across the globe. MBC exhibits an equatorially symmetric seasonality between the Northern and Southern Hemispheres. In the Northern Hemisphere, MBC peaks in autumn and is minimal in spring at low latitudes (<25°N), peaks in the spring and is minimal in autumn at mid-latitudes (25°N to 50°N), while peaks in autumn and is minimal in spring at high latitudes (>50°N). This latitudinal shift of MBC seasonality is attributed to an interaction of soil temperature, soil moisture, and substrate availability. The MBC seasonality is inconsistent with patterns of heterotrophic respiration, indicating that MBC as a proxy for microbial activity is inappropriate at this resolution. This study highlights the need to explicitly represent microbial physiology in microbial models. The interactive controls of environments and substrate on microbial seasonality provide insights for better representing microbial mechanisms in simulating ecosystem functions at the seasonal scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Climatic Drivers for the Variation of Gross Primary Productivity Across Terrestrial Ecosystems in the United States

Abstract Temperature and water stress are important factors limiting the gross primary productivity (GPP) in terrestrial ecosystems, yet the extent of their influence across ecosystems remains uncertain. This study examines how surface air temperature, soil water availability (SWA) and vapor pressure deficit (VPD) influence ecosystem light use efficiency (LUE), a critical metric for assessing GPP, across different ecosystems and climatic zones at 80 flux tower sites based on in situ measurements and data assimilation products. Results indicate that LUE increases with temperature in spring, with higher correlation coefficients in colder regions (0.79–0.82) than in warmer regions (0.68–0.78). LUE reaches a plateau earlier in the season in warmer regions. LUE variations in summer are mainly driven by SWA, exhibiting a positive correlation indicative of a water‐limited regime. The relationship between the daily LUE and daytime temperature shows a clear seasonal hysteresis at many sites, with a higher LUE in spring than in fall under the same temperature, likely resulting from younger leaves being more efficient in photosynthesis. Drought stress influences LUE through SWA in all ranges of water availability; VPD variation under moderate conditions does not have a clear influence on LUE, but extremely high VPD (exceeding the threshold of 1.6 kPa, often observed during extreme drought‐heat events) causes a dramatic reduction of LUE. Our findings provide insight into how ecosystem productivities respond to climate variability and how they may change under the influence of more frequent and severe heat and drought events projected for the future.

Environmental Sciences & Ecology↗
DOE OSTI2023

Amplified drought trends in Nepal increase the potential for Himalayan wildfires

Here we report in the spring 2021, Nepal underwent a record wildfire season in which active fires were detected at a rate 10 times greater than the 2002–2020 average. Prior to these major wildfire events, the country experienced a prolonged precipitation deficit and extreme drought during the post-monsoon period (starting in October 2020). An analysis using observational, reanalysis, and climate model ensemble data indicates that both climate variability and climate change-induced severe drought conditions were at play. Further analysis of climate model outputs suggests the likely reoccurrence of drought conditions, thus favoring active wildfire seasons in Nepal throughout the twenty-first century. While the inter-model uncertainty is large and direct modeling of wildfire spread and suppression has not been completed, the demonstrated relationship between a drought index (the standardized precipitation and evapotranspiration index) and subsequent fire activity may offer actionable opportunities for forest managers to employ the monitoring and projection of climate anomalies at sub-seasonal to decadal timescales to inform their management strategies for Nepal’s wildlands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Strong temporal variability in methane fluxes from natural gas well pad soils

We measured methane and carbon dioxide fluxes at natural gas well pad soils and undisturbed soils in the Rocky Mountain and Gulf Coast regions of the United States, including producing and gas storage wells. We collected both short-term (15 min) and multi-day (between 3 and 8), continuous measurements at 47 well pads and two undisturbed locations. Methane fluxes varied by more than an order of magnitude over periods as short as 30 min (e.g., 19–593 mg m -2 h -1 in one instance), and diurnal and seasonal variability was also significant (e.g., spring-to-fall change from 509 to 14174 mg m -2 h -1 ). We hypothesize that short-term flux variability was caused by pulsed flow of methane during its migration through the subsurface. Barometric pressure and well conditions likely impacted fluxes, but we found only weak evidence for this. Bacterial methanotrophy appeared to impact methane flux magnitude and variability. We injected methane into the subsurface at one well, and we found that, while fluxes of methane and carbon dioxide, and combustible soil gas concentrations, increased in response to the injection, the response was not uniform, and fluxes exhibited high hourly-scale variability, in spite of a constant injection rate. Methane fluxes tended to be higher at well pad soils compared to background soils (often much higher), and fluxes tended to be higher at well pad locations closer to the well head.

03 NATURAL GAS↗
DOE OSTI2025

Seasonal stabilization effects slowed the greening of the Northern Hemisphere over the last two decades

Rising atmospheric CO₂ and warming spring temperatures increase vegetation growth and the terrestrial carbon sink. However, drought, heat stress, phenology, and resource limitations may stabilize or limit theses projected increases. We investigate the balance between these amplifying and stabilizing ecological factors by asking whether enhanced early-season growth leads to continued late-season growth. Using the Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) dataset, we identify three seasonal growth patterns based on early- and peak-season positive LAI anomalies: (1) amplification, where late-season LAI anomalies exceed earlier ones; (2) weak stabilization, where late-season anomalies remain similar or slightly lower; and (3) strong stabilization, where late-season anomalies become negative. Weak and strong stabilization events dominate across 67% and 26% of Northern Hemisphere ecosystems above 30°N, respectively. The absence of any trend in amplifying or stabilizing events suggests stabilizing factors seasonally offset CO₂ and temperature-induced spring greening. Terrestrial biosphere models underestimate strong stabilization and overestimate amplification events. This inconsistency arises from the models’ underestimation late-season LAI sensitivity to precipitation in water-limited regions; overlook negative legacy effects of early enhanced LAI on late-season soil moisture via evapotranspiration losses in energy-limited regions. Our findings suggest water/heat stress and resource limitations limit greening and the land carbon sink.

Zhang, Wen↗
DOE OSTI2023

The Future of Supercells in the United States

A supercell is a distinct type of intense, long-lived thunderstorm that is defined by its quasi-steady, rotating updraft. Supercells are responsible for most damaging hail and deadly tornadoes, causing billions of dollars in losses and hundreds of casualties annually. This research uses high-resolution, convection-permitting climate simulations across 15-yr epochs that span the twenty-first century to assess how supercells may change across the United States. Specifically, the study explores how late-twentieth-century supercell populations compare with their late-twenty-first-century counterparts for two—intermediate and pessimistic—anthropogenic climate change trajectories. An algorithm identifies, segments, and tracks supercells in the simulation output using updraft helicity, which measures the magnitude of corkscrew flow through a storm’s updraft and is a common proxy for supercells. Results reveal that supercells will be more frequent and intense in future climates, with robust spatiotemporal shifts in their populations. Supercells are projected to become more numerous in regions of the eastern United States, while decreasing in frequency in portions of the Great Plains. Supercell risk is expected to escalate outside of the traditional severe storm season, with supercells and their perils likely to increase in late winter and early spring months under both emissions scenarios. Conversely, the latter part of the severe storm season may be curtailed, with supercells expected to decrease midsummer through early fall. These results suggest the potential for more significant tornadoes, hail, and extreme rainfall that, when combined with an increasingly vulnerable society, may produce disastrous consequences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

RNA-seq and metabolomic analyses of beneficial plant phenol biochemical pathways in red alder

Red alder ( Alnus rubra ) has highly desirable wood, dye pigment, and (traditional) medicinal properties which have been capitalized on for thousands of years, including by Pacific West Coast Native Americans. A rapidly growing tree species native to North American western coastal and riparian regions, it undergoes symbiosis with actinobacterium Frankia via their nitrogen-fixing root nodules. Red alder’s desirable properties are, however, largely attributed to its bioactive plant phenol metabolites, including for plant defense, for its attractive wood and bark coloration, and various beneficial medicinal properties. Integrated transcriptome and metabolome data analyses were carried out using buds, leaves, stems, roots, and root nodules from greenhouse grown red alder saplings with samples collected during different time-points (Spring, Summer, and Fall) of the growing season. Pollen and catkins were collected from field grown mature trees. Overall plant phenol biochemical pathways operative in red alder were determined, with a particular emphasis on potentially identifying candidates for the long unknown gateway entry points to the proanthocyanidin (PA) and ellagitannin metabolic classes, as well as in gaining better understanding of the biochemical basis of diarylheptanoid formation, i.e. that help define red alder’s varied medicinal uses, and its extensive wood and dye usage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Impacts of the Large Seasonal Cycle of Upwelling Zone Sea Surface Temperatures on the Atmosphere

Abstract The amplitude of the annual cycle of sea surface temperatures (SSTs) within the tropics is the largest in the eastern Atlantic and Pacific Oceans. Upwelling activity in these regions is maximum during late boreal summer and autumn, resulting in cool SSTs, and minimum in spring, leading to warm SSTs. The fundamental question of how this large seasonal cycle affects the atmosphere has received relatively little scientific attention. In this study, we use perturbed-SST experiments in an atmosphere model to identify the effects of the seasonal cycle of upwelling zone SSTs on the atmospheric state. Although annual-mean upwelling zone SSTs are cool, preventing their convective coupling with the free troposphere for much of the year, their boreal spring warmth can activate precipitating convection. We find that in this season, upwelling zone SSTs affect the atmosphere by 1) altering the intensity and position of the local intertropical convergence zone and 2) inducing a thermally forced Matsuno–Gill response, altering subtropical winds. On the seasonal time scale, the Atlantic upwelling zone is more effective than the Pacific in inducing this response. We also find that, consistent with prior work, the Pacific upwelling zone excites extratropical modes of internal atmospheric variability. Upwelling zone SSTs have remained poorly simulated through generations of climate models; our experiments allow us to diagnose the atmospheric biases that arise in response to upwelling zone SST biases. Our experiments show that upwelling zone SST biases are most impactful in boreal spring, particularly over the Atlantic.

Ramesh, Nandini↗