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NASA NTRS2012

The Effect of ENSO on Phytoplankton Composition in the Pacific Ocean

The effect of climate variability on phytoplankton communities was assessed for the tropical and sub-tropical Pacific Ocean between 1998 and 2005 using an established biogeochemical assimilation model. The phytoplankton communities exhibited wide range of responses to climate variability, from radical shifts in the Equatorial Pacific, to changes of only a couple of phytoplankton groups in the North Central Pacific, to no significant changes in the South Pacific. In the Equatorial Pacific, climate variability dominated the variability of phytoplankton. Here, nitrate, chlorophyll and all but one of the 4 phytoplankton types (diatoms, cyanobacteria and coccolithophores) were strongly correlated (p less than 0.01) with the Multivariate El Nino Southern Oscillation Index (MEI). In the North Central Pacific, MEI and chlorophyll were significantly (p<0.01) correlated along with two of the phytoplankton groups (chlorophytes and coccolithophores). Ocean biology in the South Pacific was not significantly correlated with MEI. During La Ni a events, diatoms increased and expanded westward along the cold tongue (correlation with MEI, r=-0.81), while cyanobacteria concentrations decreased significantly (r=0.78). El Nino produced the reverse pattern, with cyanobacteria populations increasing while diatoms plummeted. The diverse response of phytoplankton in the different major basins of the Pacific suggests the different roles climate variability can play in ocean biology.

Rousseaux, Cecile↗

DOE OSTI2021

Local summer insolation and greenhouse gas forcing drove warming and glacier retreat in New Zealand during the Holocene

Geological climate archives from the Holocene Epoch provide baseline information concerning natural climate variability. Temperate mountain glacier extent is sensitive to summer air temperature, thus geological records of past glacier length changes are a useful proxy for this climatic variable. Here we present a new cosmogenic 10 Be chronology of glacier length changes at Dart Glacier in the Southern Alps, New Zealand. Prominent moraines deposited 321 ± 44 yr ago (n = 11) and 7.8 ± 0.3 ka (n = 5) show glaciers during the Little Ice Age were less extensive than during the early Holocene. This pattern of net Holocene glacier retreat is consistent with emerging data from other catchments in New Zealand and across the southern mid-latitudes. Using the physical framework of a transient global climate model simulation, we suggest that cool summers in the early Holocene were promoted by the local summer insolation minimum, together with low atmospheric greenhouse gas concentrations, causing an early Holocene austral glacial maximum. An insolation-driven reduction in seasonality at southern mid-latitudes may reconcile differences between early Holocene temperature reconstructions where climate proxies have different seasonal sensitivities. Furthermore, we suggest that rising greenhouse gas concentrations after 7 ka caused regional-scale glacier retreat and appear to be the dominant driver of multi-millennial summer temperature trends in the southern mid-latitudes during the present interglacial.

58 GEOSCIENCES↗

NASA NTRS1982

Linear trends in Northern Hemisphere tropospheric geopotential height and temperature patterns

Gridded National Meteorological Center data for 500 mb geopotential height and 300-500 mb and 500-700 mb thickness for the period 1951-1978 are subjected to linear trend analyses. The analyses are carried out for each calendar month. Significant geographical and seasonal distributions of cooling and warming patterns are found. An atmospheric cooling trend over the North Pacific during the winter months is seen in a region where oceanic cooling has also been observed, but planetary-wave adjustments rather than ocean-atmosphere feedback mechanisms appear to be dominant in the atmospheric cooling on climatic time scales. Consistently large temperature trends are also seen over the continent of Asia. Comparisons between thickness trends in the layer 300-500 mb and those in the layer 500-700 mb reveal pronounced patterns of stabilization and destabilization.

Reiter, E. R.↗

DOE OSTI2017

Exploring a Variable-Resolution Approach for Simulating Regional Climate in the Rocky Mountain Region Using the VR-CESM: VR-CESM Simulation in the Rocky Mountains

The reliability of climate simulations and projections, particularly in the regions with complex terrains, is greatly limited by the model resolution. Here, we evaluate the variable-resolution Community Earth System Model (VR-CESM) with a high-resolution (0.125°) refinement over the Rocky Mountain region. The VR-CESM results are compared with observations, as well as CESM simulation at a quasi-uniform 1° resolution (UNIF) and Canadian Regional Climate Model version 5 (CRCM5) simulation at a 0.11° resolution. We find that VR-CESM is effective at capturing the observed spatial patterns of temperature, precipitation, and snowpack in the Rocky Mountains with the performance comparable to CRCM5, while UNIF is unable to do so. VR-CESM and CRCM5 simulate better the seasonal variations of precipitation than UNIF, although VR-CESM still overestimates winter precipitation whereas CRCM5 and UNIF underestimate it. All simulations distribute more winter precipitation along the windward (west) flanks of mountain ridges with the greatest overestimation in VR-CESM. VR-CESM simulates much greater snow water equivalent peaks than CRCM5 and UNIF, although the peaks are still 10–40% less than observations. Moreover, the frequency of heavy precipitation events (daily precipitation ≥ 25 mm) in VR-CESM and CRCM5 is comparable to observations, whereas the same events in UNIF are an order of magnitude less frequent. In addition, VR-CESM captures the observed occurrence frequency and seasonal variation of rain-on-snow days and performs better than UNIF and CRCM5. Lastly, these results demonstrate the VR-CESM's capability in regional climate modeling over the mountainous regions and its promising applications for climate change studies.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1999

Interdisciplinary Determination of Ice Sheet Accumulation Patterns: Combined Atmospheric Modeling and Field and Remote Sensing Studies

This research is focusing on two related areas that are fundamental to the NASA PARCA (Program for Arctic Regional Climate Assessment) program. The primary research area is the determination of the amount, rate, and timing of accumulation at distributed sites in the dry snow zone of Greenland and evaluation of these results in light of accumulation modeling results. The secondary research area is the calibration of the isotope "thermometer" at these ice sheet sites as well as the determination of long-term temperature trends in Greenland.

Shuman, C. A.↗

DOE OSTI2020

Evaluation of Mesoscale Convective Systems in Climate Simulations: Methodological Development and Results from MPAS-CAM over the U.S.

In this study, a process-oriented approach is developed to evaluate warm-season mesoscale convective system (MCS) precipitation and their favorable large-scale meteorological patterns (FLSMPs) over the U.S. This approach features a novel observation-driven MCS-tracking algorithm using infrared brightness temperature and precipitation feature at 12, 25 and 50 km resolution and metrics to evaluate the model large-scale environment favorable for MCS initiation. The tracking algorithm successfully reproduces the observed MCS statistics from a reference 4-km radar MCS database. To demonstrate the utility of the new methodologies in evaluating MCS in climate simulations with mesoscale resolution, the process-oriented approach is applied to two climate simulations produced by the Variable-Resolution Model for Prediction Across Scales coupled to the Community Atmosphere Model physics, with refined horizontal grid spacing at 50 km and 25 km over North America. With the tracking algorithm applied to simulations and observations at equivalent resolutions, the simulated number of MCS and associated precipitation amount, frequency and intensity are found to be consistently underestimated in the Central U.S., particularly from May to August. The simulated MCS precipitation shows little diurnal variation and lasts too long, while MCS precipitation area is too large and intensity is too weak. The model is able to simulate four types of observed FLSMP associated with frontal systems and low-level jets (LLJ) in spring, but the frequencies are underestimated because of low-level dry bias and weaker LLJ. Precipitation simulated under different FLSMPs peak during daytime, in contrast to the observed nocturnal peak. Implications of these findings for future model development and diagnostics are discussed.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2016

Ocean-Atmosphere Interactions Modulate Irrigation's Climate Impacts

Numerous studies have focused on the local and regional climate effects of irrigated agriculture and other land cover and land use change (LCLUC) phenomena, but there are few studies on the role of ocean- atmosphere interaction in modulating irrigation climate impacts. Here, we compare simulations with and without interactive sea surface temperatures of the equilibrium effect on climate of contemporary (year 2000) irrigation geographic extent and intensity. We find that ocean-atmosphere interaction does impact the magnitude of global-mean and spatially varying climate impacts, greatly increasing their global reach. Local climate effects in the irrigated regions remain broadly similar, while non-local effects, particularly over the oceans, tend to be larger. The interaction amplifies irrigation-driven standing wave patterns in the tropics and mid-latitudes in our simulations, approximately doubling the global-mean amplitude of surface temperature changes due to irrigation. The fractions of global area experiencing significant annual-mean surface air temperature and precipitation change also approximately double with ocean-atmosphere interaction. Subject to confirmation with other models, these findings imply that LCLUC is an important contributor to climate change even in remote areas such as the Southern Ocean, and that attribution studies should include interactive oceans and need to consider LCLUC, including irrigation, as a truly global forcing that affects climate and the water cycle over ocean as well as land areas.

Air water interactioins↗

DOE OSTI2023

Advances in understanding the changes of tropical rainfall annual cycle: a review

Abstract Aided by progress in the theoretical understanding, new knowledge on tropical rainfall annual cycle changes under a global warming background has been advanced in the past decade. In this review, we focus on recent advances in understanding the changes of tropical rainfall annual cycle, including its four distinct features: amplitude, spatial pattern shift, phase and wet/dry season length changes. Here, amplitude refers to the local summer-winter rainfall contrast and phase refers to the timing of rainfall annual cycle. In a warming climate, the amplitude is enhanced, more evidently over ocean, while the phase is delayed, mainly over land. The former is explained by the wet-get-wetter mechanism and the latter is explained by the enhanced effective atmospheric heat capacity and increased convective barrier. The phase delay over land has already emerged in the past four decades. The spatial pattern shift under warming is marked by two features: equatorward shift of the ITCZ throughout the year and the land-to-ocean precipitation shift in the rainy season. The former is explained by the upped-ante mechanism and/or related to the enhanced equatorial warming in a warmer world. The latter may be caused by the opposite land and ocean surface temperature annual cycle changes in the tropics. Over tropical rainforest regions such as Amazon and Congo Basin, the dry season has lengthened in the recent decades, but the fundamental reason is still unclear. Despite the notable progress in the research of tropical rainfall annual cycle change, many gaps remain in understanding its mechanisms, quantifying and attributing its historical emergence, narrowing the inter-model uncertainty of its future projections, and evaluating its global impact, motivating future work guided by some directions proposed in this review.

Song, Fengfei (ORCID:0000000230041749)↗

DOE OSTI2017

Future changes in the climatology of the Great Plains low-level jet derived from fine resolution multi-model simulations

The southerly Great Plains low-level jet (GPLLJ) is one of the most significant circulation features of the central U.S. linking large-scale atmospheric circulation with the regional climate. GPLLJs transport heat and moisture, contribute to thunderstorm and severe weather formation, provide a corridor for the springtime migration of birds and insects, enhance wind energy availability, and disperse air pollution. We also assess future changes in GPLLJ frequency using an eight member ensemble of dynamically-downscaled climate simulations for the mid-21st century. Nocturnal GPLLJ frequency is projected to increase in the southern plains in spring and in the central plains in summer, whereas current climatological patterns persist into the future for daytime and cool season GPLLJs. The relationship between future GPLLJ frequency and the extent and strength of anticyclonic airflow over eastern North America varies with season. Most simulations project a westward shift of anticyclonic airflow in summer, but uncertainty is larger for spring with only half of the simulations suggesting a westward expansion. Furthemore, the choice of regional climate model and the driving lateral boundary conditions have a large influence on the projected future changes in GPLLJ frequency and highlight the importance of multi-model ensembles to estimate the uncertainty surrounding the future GPLLJ climatology.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Static Energy Deserves Greater Emphasis in the Meteorology Community

Potential temperature and static energy are both useful quantities for understanding our atmosphere, yet static energy receives much less attention in weather science relative to climate science. Bridging this conceptual gap is important, as there is a pressing need for our communities to work together to understand and predict changing weather patterns in a warming world. Here we provide evidence for this gap in usage in American Meteorological Society journal publications and in introductory textbooks. We then describe key benefits of static energy for explaining basic concepts in atmospheric science. We encourage scientists and educators unfamiliar with static energy to familiarize themselves with the concept and consider incorporating it into their science and teaching.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2023

Global and Zonal-Mean Hydrological Response to Early Eocene Warmth

Earth's hydrological cycle is expected to intensify in response to global warming, with a “wet-gets-wetter, dry-gets-drier” response anticipated over the ocean. Subtropical regions (∼15°–30°N/S) are predicted to become drier, yet proxy evidence from past warm climates suggests these regions may be characterized by wetter conditions. Here we use an integrated data-modeling approach to reconstruct global and zonal-mean rainfall patterns during the early Eocene (∼56–48 million years ago). The Deep-Time Model Intercomparison Project (DeepMIP) model ensemble indicates that the mid- (30°–60°N/S) and high-latitudes (>60°N/S) are characterized by a thermodynamically dominated hydrological response to warming and overall wetter conditions. The tropical band (0°–15°N/S) is also characterized by wetter conditions, with several DeepMIP models simulating narrowing of the Inter-Tropical Convergence Zone. However, the latter is not evident from the proxy data. The subtropics are characterized by negative precipitation-evaporation anomalies (i.e., drier conditions) in the DeepMIP models, but there is surprisingly large inter-model variability in mean annual precipitation (MAP). Intriguingly, we find that models with weaker meridional temperature gradients (e.g., CESM, GFDL) are characterized by a reduction in subtropical moisture divergence, leading to an increase in MAP. These model simulations agree more closely with our new proxy-derived precipitation reconstructions and other key climate metrics and imply that the early Eocene was characterized by reduced subtropical moisture divergence. If the meridional temperature gradient was even weaker than suggested by those DeepMIP models, circulation-induced changes may have outcompeted thermodynamic changes, leading to wetter subtropics. This highlights the importance of accurately reconstructing zonal temperature gradients when reconstructing past rainfall patterns.

Margot J. Cramwinckel↗

DOE OSTI2026

Semi‐Volatile Organic Partitioning Improves Simulation of Biomass Burning Aerosol Mixing State Evolution

Biomass burning aerosols significantly contribute to atmospheric composition and radiative forcing, with black carbon (BC) mixing states critically influencing optical properties and climate impacts. Recent field observations reveal a systematic three‐phase evolution in BC coating thickness during plume aging: rapid initial growth, quasi‐equilibrium, and gradual coating loss. Current models misrepresent this evolution due to oversimplified treatment of organic aerosol volatility. Here we demonstrate that incorporating semi‐volatile organic partitioning through the MATRIX‐VBS model fundamentally improves simulation accuracy compared to traditional non‐volatile approaches. Evaluation against four field campaigns spanning fresh to aged plumes shows MATRIX‐VBS successfully captures the observed three‐phase pattern, and global application reveals universal three‐phase evolution with substantial regional variations. These advances address critical gaps in aerosol mixing state representation and provide essential improvements for climate model predictions in wildfire‐affected regions.

Gao, Chloe Yuchao [Fudan Univ., Shanghai (China); ↗

DOE OSTI2020

Simulations of Winter Arctic Clouds and Associated Radiation Fluxes Using Different Cloud Microphysics Schemes in the Polar WRF: Comparisons With CloudSat, CALIPSO, and CERES

Clouds are important for the Arctic climate, but simulating such clouds with numerical models is still challenging. The accuracy of model clouds has not been sufficiently examined due to the harsh Arctic environment obstructing cloud observations, especially during Arctic winters experiencing polar nights. This study compares the Arctic winter clouds simulated by a weather forecast model to cloud observations from active (lidar and radar) satellite instruments. The model successfully produced cloud patterns similar to the satellite observations. However, the choice of the cloud physics module in the model can modify the amount of cloud water significantly enough to affect the simulated surface climate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

A stochastic model of future extreme temperature events for infrastructure analysis

Applying extreme temperature events for future conditions is not straightforward for infrastructure resilience analyses. This work introduces a stochastic model that fills this gap. The model uses at least 50 years of daily extreme temperature records, climate normals with 10%-90% confidence intervals, and shifts/offsets for increased frequency and intensity of heat wave events. Intensity and frequency are shifted based on surface temperature anomaly from 1850-1900 for 32 models from CMIP6. A case study for Worcester, Massachusetts passed 85% of cases using the two-sided Kolmogorov-Smirnov -value test with 95% confidence for both temperature and duration. Future shifts for several climate scenarios to 2020, 2040, 2060, and 2080 had acceptable errors between the shifted model and 10- and 50-year extreme temperature event thresholds with the largest error being 2.67 degrees C. The model is likely to be flexible enough for other patterns of extreme weather such as extreme precipitation and hurricanes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

Global reconstructed daily surge levels from the 20th Century Reanalysis (1871–2010)

Studying the effect of global patterns of wind and pressure gradients on the sea level variation (storm surge) is a key issue in understanding the recent climate change effect on the dynamical state of the ocean. The analysis of the spatial and temporal variability of storm surges from observations is a difficult task to accomplish since observations are not homogeneous in time, scarce in space, and moreover, their temporal coverage is limited. A recent global surge database developed by AVISO (DAC, Dynamic Atmospheric Correction) fulfilled the lack of data in terms of spatial coverage, but not regarding time extent, since it only includes the last two decades (1992–2014). In this work, we use the 20th Century Reanalysis V2 (20CR), which spans the years 1871 to 2010, to statistically reconstruct daily maximum surge levels at a global scale. A multivariate linear regression model is fitted between daily mean ERA-interim sea level pressure fields and daily maximum surge levels from DAC. Following, the statistical model is used to reconstruct daily surges using mean sea level pressure fields from 20CR. The verification of the statistical model shows good agreements between DAC levels and the reconstructed surge levels from the 20CR. The validation of the reconstructed surge with tide gauges, distributed throughout the domain, shows good accuracy both in terms of high correlations and small errors. A time series comparison is also depicted at specific tide gauges for the beginning of the 20th century, showing a high concordance. Therefore, this work provides to the scientific community, a daily database of maximum surge levels; which correspond to an extension of the DAC database, from 1871 to 2010. This database can be used to improve the knowledge on historical storm surge conditions, allowing the study of their temporal and spatial variability.

Geology↗

DOE OSTI2022

Decoupling of greenness and gross primary productivity as aridity decreases

Ecosystem primary productivity is a key ecological process influencing many ecosystem services, including carbon storage. Thus, clarifying how primary productivity in terrestrial ecosystems responds to climatic variability can reveal key mechanisms that will drive future changes in the global carbon budget. Satellite products of canopy greenness are widely used as proxies for vegetation productivity to evaluate how ecosystems respond to climate variability. However, to what degree inter-annual variations in productivity are consistent with greenness and how this relationship varies spatially remains unclear. Here we investigated the strength of the coupling between inter-annual variations in leaf area index (LAI, a measure of greenness) and ecosystem gross primary productivity (GPP) derived from eddy covariance towers, i.e., the r2 of the LAI-GPP relationship. Overall, inter-annual GPP and LAI were highly coupled (i.e., high r2) in arid grasslands, but were fully decoupled in mesic evergreen broadleaf forests, indicating that this relationship varies strongly along aridity gradients. A possible mechanism of the spatial variation in the LAI-GPP relationship is that the tradeoff between ecosystem structure (LAI) and physiology (photosynthesis per unit leaf area) becomes stronger in more humid climates. Land models overestimated the r2 of LAI-GPP correlation for most ecosystem types and failed to capture the spatial pattern along aridity gradients. We conclude that relying on greenness products for evaluating inter-annual changes in vegetation productivity may bias assessments, especially in tropical rainforest ecosystems. Our findings may also reconcile observed disparities between responses in greenness and GPP during drought in Amazon forests.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Adaptive variation and plasticity in non‐structural carbohydrate storage in a temperate tree species

Abstract Trees' total amount of non‐structural carbohydrate (NSC) stores and the proportion of these stores residing as insoluble starch are vital traits for individuals living in variable environments. However, our understanding of how stores vary in response to environmental stress is poorly understood as the genetic component of storage is rarely accounted for in studies. Here, we quantified variation in NSC traits in branch samples taken from over 600 clonally transplanted black cottonwood ( Populus trichocarpa) trees grown in two common gardens. We found heritable variation in both total NSC stores and the proportion of stores in starch (H 2 TNC = 0.19, H 2 PropStarch = 0.31), indicating a substantial genetic component of variation. In addition, we found high amounts of plasticity in both traits in response to cold temperatures and significant genotype‐by‐environment (GxE) interactions in the total amount of NSC stored (54% of P is GxE). This finding of high GxE indicates extensive variation across trees in their response to environment, which may explain why previous studies of carbohydrate stores' responses to stress have failed to converge on a consistent pattern. Overall, we found high amounts of environmental and genetic variation in NSC storage concentrations, which may bolster species against future climate change.

Blumstein, Meghan↗

DOE OSTI2025

Amplified Mesoscale and Submesoscale Variability and Increased Concentration of Precipitation under Global Warming over Western North America

Abstract Cold-season precipitation statistics in simulations from the storm-resolving WRF Model at 6-km and 1-h resolution over western North America are analyzed. Pseudo–global warming future simulations for the 2041–80 period, constrained by GCMs under the RCP8.5 scenario, are compared to the 1981–2020 historical simulation. The analysis focuses on the dynamical properties of precipitation time series at subdaily scales and on the morphology of storms. The statistical distribution of precipitation intensities in each pixel of the simulation domain is characterized through nonparametric statistical indicators: frequency of wet hours, mean wet-hour precipitation intensity, and Gini coefficient as a measure of the temporal concentration of the precipitation volume. Additionally, the temporal and spatial Fourier power spectra of precipitation time series and precipitation fields are analyzed. The half-power period (HPP) and half-power wavelength (HPW) are defined as spectral measures of the characteristic scales of precipitation’s temporal and spatial patterns. The results show statistically significant increases in the mean wet-hour precipitation intensity and in the Gini coefficient in 99% of the pixels, indicating that the seasonal precipitation volume becomes more concentrated within a smaller number of hours with higher precipitation intensity. The statistics of change in the frequency of wet hours are more contrasted across the simulation domain. The changes are also reflected in the power spectra, which show the spatial and temporal variability increasing proportionally more with finer spatial and temporal scales and the HPW and HPP decreasing. These projected changes are expected to have consequences, not only in terms of hydrologic impacts but also in terms of the predictability of precipitation patterns. Significance Statement The precipitation characteristics of winter storms over the western United States and southwestern Canada are analyzed in future climate simulations for the 2041–80 period. As compared to present-day climate, the most intense parts of the storms are projected to produce a higher rainfall volume, with increased concentration over smaller areas and shorter time intervals. The propensity of rainfall intensity to vary rapidly over time will be enhanced in the future according to the simulations. These model predictions imply an increased risk of rapid flooding in small basins. They also suggest that predicting several hours ahead the time and location at which a storm will produce maximum rainfall may become more challenging in the future.

Climate change↗