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DOE OSTI2026

Assessing Photovoltaic Capacity Factor Variability Using Long-Term Satellite Derived Solar Resource Data Under Brazilian Climate

Accurate estimation of photovoltaic (PV) energy yield and its variability is essential for reducing financial risk and supporting reliable system planning for rapidly expanding PV markets. In Brazil, high solar adoption and increasing levels of distributed energy resources are beginning to introduce operational challenges such as curtailment and evolving grid requirements. Understanding how natural variability in solar resource propagates into PV system performance is therefore increasingly important for both project design and grid integration. Modern PV yield assessments commonly rely on multi-year meteorological datasets and probabilistic exceedance metrics (e.g., P50/P90) to quantify energy yield uncertainty for project financing. However, the implications of long-term solar resource variability for PV system design choices and high-adoption grid conditions remain less well characterized for rapidly expanding markets such as Brazil. In particular, understanding how weather-driven variability propagates into PV production distributions and capacity factor expectations is important for evaluating curtailment exposure, deployment strategies, and storage requirements in regions experiencing rapid growth of distributed and utility-scale PV. Seasonal and interannual variability in atmospheric conditions can produce substantial fluctuations in monthly PV energy production, which propagate into uncertainty in annual energy yield and capacity factor expectations. Characterizing this variability using long-term meteorological datasets allows probabilistic estimation of PV system performance and provides improved insight into the range of expected PV energy outcomes. This study explores the use of long-term satellite-derived meteorological data from the National Solar Radiation Database (NSRDB) to evaluate the variability of photovoltaic system performance across multiple locations in Brazil. Using a 27-year dataset (1998-2024), PV system simulations are performed to characterize the distribution of annual and seasonal capacity factors and energy yield outcomes, while propagating key sources of meteorological variability and model uncertainty through the PV modeling chain. The analysis also investigates the sensitivity of PV performance outcomes to key system design assumptions within the PV modeling chain, including tracking configuration and system sizing parameters. The resulting probabilistic performance characterization provides insight into how weather-driven variability influences PV production expectations and capacity factor distributions. These results provide a foundation for evaluating how weather-driven variability interacts with high PV adoption and potential storage or curtailment mitigation strategies.

14 SOLAR ENERGY↗

NASA NTRS2019

Long-Term Ozone Variability and Trends from Reanalyses: Can It Be Done?

Stratospheric ozone concentrations have begun to show early signs of recovery following the implementation of the Montreal Protocol and its amendments as well as in response to decreasing upper-stratospheric temperatures. Secular trends in stratospheric ozone are modulated by considerable interannual variability and systematic changes in transport patterns that are expected under increasing concentrations of greenhouse gases, especially in the lower stratosphere. These factors necessitate the continued close monitoring of stratospheric ozone in upcoming decades, with a special focus on the lower stratosphere.As highly resolved data sets combining a plethora of observations with model simulations atmospheric reanalyses are, in principle, well suited for the task. All major reanalyses generate ozone output. However, significant spurious discontinuities that arise from step changes in the observing systems prevent a straightforward analysis of ozone trends and long-term variability. Building on our recent work, in this presentation we will demonstrate that trend detection is nonetheless possible using the ozone record from NASA's MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, Version 2) reanalysis bias-corrected using a chemistry model simulation as a transfer function. Next, we will outline several strategies to reduce artificial discontinuities in the ozone record in future NASA reanalyses. This discussion will be illustrated by an example of joint assimilation of bias-corrected ozone profiles from the Microwave Limb Sounder (MLS) on the Aura satellite (2004 to present) and the Ozone Mapping Profiler Suite Limb Profiler (OMPS-LP) sensors that are expected to operate on future NOAA platforms.

Wargan, Krzysztof↗

DOE OSTI2024

Climate, Hydrology, and Nutrients Control the Seasonality of Si Concentrations in Rivers

Abstract The seasonal behavior of fluvial dissolved silica (DSi) concentrations, termedDSi regime, mediates the timing of DSi delivery to downstream waters and thus governs river biogeochemical function and aquatic community condition. Previous work identified five distinct DSi regimes across rivers spanning the Northern Hemisphere, with many rivers exhibiting multiple DSi regimes over time. Several potential drivers of DSi regime behavior have been identified at small scales, including climate, land cover, and lithology, and yet the large‐scale spatiotemporal controls on DSi regimes have not been identified. We evaluate the role of environmental variables on the behavior of DSi regimes in nearly 200 rivers across the Northern Hemisphere using random forest models. Our models aim to elucidate the controls that give rise to (a) average DSi regime behavior, (b) interannual variability in DSi regime behavior (i.e., Annual DSi regime), and (c) controls on DSi regime shape (i.e., minimum and maximum DSi concentrations). Average DSi regime behavior across the period of record was classified accurately 59% of the time, whereas Annual DSi regime behavior was classified accurately 80% of the time. Climate and primary productivity variables were important in predicting Average DSi regime behavior, whereas climate and hydrologic variables were important in predicting Annual DSi regime behavior. Median nitrogen and phosphorus concentrations were important drivers of minimum and maximum DSi concentrations, indicating that these macronutrients may be important for seasonal DSi drawdown and rebound. Our findings demonstrate that fluctuations in climate, hydrology, and nutrient availability of rivers shape the temporal availability of fluvial DSi.

Environmental Sciences & Ecology↗

NASA NTRS2004

Trend and Variability of China Precipitation in Spring and Summer: Linkage to Sea Surface Temperatures

Observational records in the past 50 years show an upward trend of boreal-summer precipitation over central eastern China and a downward trend over northern China. During boreal spring, the trend is upward over southeastern China and downward over central eastern China. This study explores the forcing mechanism of these trends in association with the global sea-surface temperature (SST) variations on the interannual and inter-decadal timescales. Results based on Singular Value Decomposition analyses (SVD) show that the interannual variability of China precipitation in boreal spring and summer can be well defined by two centers of actions for each season, which are co-varying with two interannual modes of SSTs. The first SVD modes of precipitation in spring and summer, which are centered in southeastern China and northern China, respectively, are linked to an ENSO-like mode of SSTs. The second SVD modes of precipitation in both seasons are confined to central eastern China, and are primarily linked to SST variations over the warm pool and Indian Ocean. Features of the anomalous 850-hPa winds and 700-Wa geopotential height corresponding to these modes support a physical mechanism that explains the causal links between the modal variations of precipitation and SSTs. On the decadal and longer timescale, similar causal links are found between the same modes of precipitation and SSTs, except for the case of springtime precipitation over central eastern China. For this case, while the interannual mode of precipitation is positively correlated with the interannual variations of SSTs over the warm pool and Indian Ocean; the inter-decadal mode is negatively correlated with a different SST mode, the North Pacific mode. The later is responsible for the observed downward trend of springtime precipitation over central eastern China. For all other cases, both the interannual and inter-decadal variations of precipitation can be explained by the same mode of SSTs. The upward trend of springtime precipitation over southeastern China and downward trend of summertime precipitation over northern China are attributable to the warming trend of the ENSO-like mode. The recent frequent summertime floods over central eastern China are linked to the warming trend of SSTs over the warm pool and Indian Ocean.

Yang, Fanglin↗

DOE OSTI2024

Investigating the Relative Contribution from Tropical Indo-Pacific SST to Asian Monsoon Precipitation Variability Using LIM

Abstract A critical issue is determining the factors that control the year-to-year variability in precipitation over southern Asia. In this study, we employ a cyclostationary linear inverse model (CS-LIM) to quantify the relative contribution of tropical Pacific and Indian Ocean sea surface temperature anomalies (SSTAs) to the interannual variability of the Asian monsoon, especially Indian summer monsoon rainfall (ISMR). Through a series of CS-LIM experiments, we isolate the impacts of the direct forcing from Pacific SSTAs, Indian Ocean SSTAs, and their interaction on Asian monsoon rainfall variability. Our results reveal distinct patterns of influence with the direct forcing from the Pacific (Indian) Ocean tending to enhance (reduce) the magnitude of precipitation variability, while the Indo-Pacific interaction acts to strongly damp the variability of Asian monsoon precipitation, especially over India. We further investigate these specific impacts on ISMR by analyzing the relationship between tropical Indo-Pacific SSTAs and the leading three empirical orthogonal functions (EOFs) of ISMR. The results from our CS-LIM experiments indicate that the direct forcing from El Niño–Southern Oscillation (ENSO) enhances the variability of the first and third EOFs, while the Indian Ocean SSTA opposes ENSO’s effects, which is consistent with previous studies. Our new results show that the tropical Indo-Pacific interaction strongly damps ISMR variability, which is due to the ENSO-induced Indian Ocean dipole (IOD) opposing the direct impacts from ENSO on ISMR. Additionally, reduced ENSO amplitude and duration associated with the Indo-Pacific interaction may also contribute to the damping effect on ISMR, but this requires further study to understand the relevant mechanisms.

Meteorology & Atmospheric Sciences↗

NASA NTRSDate not supplied

Variability and Trends in Dates of the Last Spring Freeze and the First Fall Freeze over the United States

The timing of the last freeze of the spring and the first freeze in the fall have implications for agriculture and ecosystems in a region, and changes in theses dates are expected with a changing climate. In this study, indices used to represent these dates are computed from the Modern Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). The indices are analyzed over the United States to assess the climatology, trends, and variability over 1980-2023. In general, the last spring freeze date has trended earlier, and the first fall freeze date has trended later over this period; regional variations in these trends are investigated. We explore drivers of interannual variability in the timing of the last spring freeze and first fall freeze for different regions of the United States.

Natalie Thomas↗

DOE OSTI2020

Rainfall manipulation experiments as simulated by terrestrial biosphere models: Where do we stand?

Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model-data intercomparison project, where we tested the ability of 10 terrestrial biosphere models to reproduce the observed sensitivity of ecosystem productivity to rainfall changes at 10 sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are as follows: (a) Inter-model variation is generally large and model agreement varies with timescales. In severely water-limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent on gross primary productivity. In more mesic sites, model agreement for both water and carbon fluxes is typically higher on fine (daily–monthly) timescales and reduces on longer (seasonal–annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter-model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. Finally, the relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Carbon fluxes and interannual drivers in a temperate forest ecosystem assessed through comparison of top-down and bottom-up approaches

Despite decades of research, gaining a comprehensive understanding of carbon (C) cycling in forests remains a considerable challenge. Uncertainties stem from persistent methodological limitations and the difficulty of resolving top-down estimates of ecosystem C exchange with bottom-up measurements of individual pools and fluxes. To address this, we derived estimates and associated uncertainties of ecosystem C fluxes for a 100–125 year old mixed temperate forest stand at the Bartlett Experimental Forest, New Hampshire, USA, using three different approaches: (1) tower-based eddy covariance, (2) a biometric approach involving C flux measurements of individual ecosystem subcomponents, and (3) an inventory approach involving changes in major C stocks over time. Our analysis made use of 13 years of data, collected over the period from 2004 to 2016. Estimates of mean annual net ecosystem production (NEP) ranged from 120 to 133 g C m -2 , demonstrating strong agreement among methods and suggesting that this aging forest acts as a moderate C sink. The use of multiple approaches to measure C fluxes and their uncertainties helped place constraints on difficult-to-measure processes such as aboveground contributions to ecosystem respiration and belowground allocation to mycorrhizal fungal biomass (which was estimated at 20% of net primary production). Analysis of interannual variability in C fluxes revealed a decoupling between annual wood growth and either current year or lagged NEP or GPP, suggesting that source limitation (C supply) is likely not controlling rates of wood production, at least on an interannual scale. Results also demonstrated a strong association between the maximum rate of C uptake during the growing season (Amax) and the length of the vernal window, defined as the period of time between soil thaw and the onset of photosynthesis. This suggests an important, but poorly understood, influence of winter and spring climate on mid-summer canopy physiology. Efforts to resolve the mechanisms responsible should be prioritized in light of ongoing and predicted changes in climate for the northeastern U.S. region, particularly during the winter and winter-spring transition period.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2000

Climatology of the Finite-Volume CCM and Sensitivity Studies

A new model has been developed in the Data Assimilation Office at NASA Goddard Space Flight Center. It is intended for data assimilation and general circulation modeling, including representations of radiatively active trace gases such as stratospheric ozone. The model is based on the flux-form semi-Lagrangian' dynamical core, developed by Lin and Rood. In collaboration with the National Center for Atmospheric Research, the physical parametrization package from the Community Climate model, Version 3, has been included. This paper will discuss the climatology of a multi-year integration of the model, with observed boundary conditions (sea-surface temperature, sea ice, and incoming solar radiation). The standard model version has a resolution of 2.5 degrees longitude, 2 degrees latitude and has 55 levels between the surface and 80km. The mean climate and interannual variability of this model will be discussed, with emphasis on the middle atmosphere. The sensitivity to horizontal resolution will be examined, as will the impact of increasing and decreasing the vertical resolution. Changes which differ significantly from the interannual variations of the control run will be highlighted. Impacts of using long-term mean boundary conditions or values which vary from year to year will be discussed. Changes in the tropospheric circulation induced by lowering the upper boundary of the model will be discussed. The emphasis of the paper is on the climatology of the middle atmosphere and its impacts on the troposphere, with particular attention given to the climatologically important region near the tropopause.

Pawson, Steven↗

DOE OSTI2023

Southern Himalayas rainfall as a key driver of interannual variation of pre-monsoon aerosols over the Tibetan Plateau

The Tibetan Plateau (TP) is one of the most climate-sensitive regions around the world. Aerosols imported from adjacent regions reach their peak during the pre-monsoon season and play a vital role in the TP environment. However, the strong interannual variation in aerosols transported to the TP has not been fully understood. Here, we show that the interannual variability of pre-monsoon aerosols transported to the TP is influenced more by rainfall over the southern Himalayas than near-surface wind. Rainfall modulates fire events and biomass burning emissions and reduces aerosols over the TP by wet scavenging. Contrary to the role of wind in increasing aerosol transport, the positive correlation between wind and aerosols in the TP reported in previous studies is contributed by the negative interannual correlations between wind and rainfall and between rainfall and fire events over the southern Himalayas. This study highlights the co-variability of wind and rainfall and their confounding impacts on aerosols in the southern Himalayas and over the TP. With pre-monsoon rainfall projected to increase in adjacent regions of southern TP, aerosol transport to the TP may be mitigated in the future.

Liu, Weichien↗

NASA NTRS1988

Analysis of sea ice dynamics

The ongoing work has established the basis for using multiyear sea ice concentrations from SMMR passive microwave for studies of largescale advection and convergence/divergence of the Arctic sea ice pack. Comparisons were made with numerical model simulations and buoy data showing qualitative agreement on daily to interannual time scales. Analysis of the 7-year SMMR data set shows significant interannual variations in the total area of multiyear ice. The scientific objective is to investigate the dynamics, mass balance, and interannual variability of the Arctic sea ice pack. The research emphasizes the direct application of sea ice parameters derived from passive microwave data (SMMR and SSMI) and collaborative studies using a sea ice dynamics model. The possible causes of observed interannual variations in the multiyear ice area are being examined. The relative effects of variations in the large scale advection and convergence/divergence within the ice pack on a regional and seasonal basis are investigated. The effects of anomolous atmospheric forcings are being examined, including the long-lived effects of synoptic events and monthly variations in the mean geostrophic winds. Estimates to be made will include the amount of new ice production within the ice pack during winter and the amount of ice exported from the pack.

Zwally, J.↗

NASA NTRS2000

Meteorological Characterization of Global Dust Sources

The global distribution of absorbing aerosols index (AI) derived from Nimbus 7 Total Ozone Mapping Spectrometer (TOMS) measurements has been used to identify the major sources of atmospheric dust particles [Prospero, et al., 2000]. In this presentation, we will show that the TOMS aerosol index can also be used to the meteorological characterization of the source areas. We found a huge "dust belt" with a strong correlation between the TOMS index and the sea-level pressure wrapping all the major dust sources. To handle the difficulty of using quantitatively the TOMS Al and its strong dependency on the aerosol layer altitude, the Al has been correlated to the planetary boundary layer depth (PBL) and the surface wind speed. The strongest correlation is obtained with the product of these two variables and at the precise location of the dust sources identified by Prospero et al. The relation between the TOMS Al and the product of the PBL height and the surface wind speed has been used to study the interannual variability of the North-Africa dust sources in relation with the North Atlantic Oscillation (NAO). Finally, we will show that even on a short time base the variability of the TOMS Al can be related to the surface wind speed and PBL height.

Ginoux, Paul↗

NASA NTRS2002

Subtropical Gyre Variability Observed by Ocean Color Satellites

The subtropical gyres of the world are extensive, coherent regions that occupy about 40% of the surface of the earth. Once thought to be homogeneous and static habitats, there is increasing evidence that mid-latitude gyres exhibit substantial physical and biological variability on a variety of time scales. While biological productivity within these oligotrophic regions may be relatively small, their immense size makes their total contribution significant. Global distributions of dynamic height derived from satellite altimeter data, and chlorophyll concentration derived from satellite ocean color data, show that the dynamic center of the gyres, the region of maximum dynamic height where the thermocline is deepest, does not coincide with the region of minimum chlorophyll concentration. The physical and biological processes by which this distribution of ocean properties is maintained, and the spatial and temporal scales of variability associated with these processes, are analyzed using global surface chlorophyll-a concentrations, sea surface height, sea surface temperature and surface winds from operational satellite and meteorological sources, and hydrographic data from climatologies and individual surveys. Seasonal and interannual variability in the areal extent of the subtropical gyres are examined using 8 months (November 1996 - June 1997) of OCTS and nearly 5 years (September 1997 - June 02) of SeaWiFS ocean color data and are interpreted in the context of climate variability and measured changes in other ocean properties (i.e., wind forcing, surface currents, Ekman pumping, and vertical mixing). The North Pacific and North Atlantic gyres are observed to be shrinking over this period, while the South Pacific, South Atlantic, and South Indian Ocean gyres appear to be expanding.

McClain, Charles R.↗

NASA NTRS2003

Collaborative Research: Atlantic Ocean Tropical/Subtropical Processes from Seasonal to Decadal Time Scales: Model/Data, Model/Model Comparison and Model/Data Synthesis Through Assimilation

The effort of this first year of research has been focused on the assimilation of TOPEX/Poseidon altimetric data into a primitive equation model of the Atlantic tropical/subtropical circulation. A reduced-rank, stationary Kalman filter has been constructed to assimilate the altimetric sea surface height anomaly (SHA) into the model. The goal is to assess how the inter-hemispheric transports between the Atlantic subtropics and tropics are affected by the assimilation and how the subsurface thermocline structure , and its variability ,is dynamically constrained by the SHA. The model is a reduced-gravity primitive equation GCM of the upper Atlantic Ocean between 30 S and 30 N. The assimilation scheme is an approximation to the extended Kalman filter in which the error covariances of the state estimates are calculated only in a reduced- dimension subspace. The subspace is defined by the leading empirical orthogonal functions calculated from an unconstrained model calculation. Both an identical twin experiment using simulated SHA observations and assimilation of the real TOPEX data were performed. Results from the twin experiments demonstrate the ability of the method to constrain the ocean circulation and the subsurface temperature structure. The impact on the subsurface temperature structure of TOPEX assimilation was assessed using data from expandable bathythermographs. This showed a substantial improvement in the estimated temperature variability only within 13 degrees in latitude around the equator. The impact of TOPEX SHA assimilation on zonally integrated meridional transport across different latitudes was also estimated. Again within 13 degrees from the equator both the mean amplitude and interannual variability of the surface and subsurface transports were significantly enhanced, while the transports were insensitive to the assimilation in the subtropics.

Malannotte-Rizzoli, Paola↗

NASA NTRS1984

Low frequency variability and tropical-extratropical interactions

In this investigation of relationships between mid-latitude 500 mb anomalies and tropical heating anomalies on the time scales of weeks to seasons are studied using outgoing IR to characterize the tropical convection heating. The data are first used to form 5-day means and the mean seasonal cycle and the interannual variability of seasonal means are then removed. The time scales considered are then between about 10 days and 90 days. By correlating the mid-latitude height anomalies with the tropical precipitation anomalies it can be shown that, on the time scales considered here, the predominant correlation patterns are those associated with Rossby waves propagating from mid-latitudes into the tropics and influencing the tropical convection. The mid-latitude Rossby waves can significantly influence convection to within 5 degrees of the equator.

Hartmann, D. L.↗

NASA NTRS2015

Groundwater Variability Across Temporal and Spatial Scales in the Central and Northeastern U.S.

Depth-to-water measurements from 181 monitoring wells in unconfined or semi-confined aquifers in nine regions of the central and northeastern U.S. were analyzed. Groundwater storage exhibited strong seasonal variations in all regions, with peaks in spring and lows in autumn, and its interannual variability was nearly unbounded, such that the impacts of droughts, floods, and excessive pumping could persist for many years. We found that the spatial variability of groundwater storage anomalies (deviations from the long term mean) increases as a power function of extent scale (square root of area). That relationship, which is linear on a log-log graph, is common to other hydrological variables but had never before been shown with groundwater data. We describe how the derived power function can be used to determine the number of wells needed to estimate regional mean groundwater storage anomalies with a desired level of accuracy, or to assess uncertainty in regional mean estimates from a set number of observations. We found that the spatial variability of groundwater storage anomalies within a region often increases with the absolute value of the regional mean anomaly, the opposite of the relationship between soil moisture spatial variability and mean. Recharge (drainage from the lowest model soil layer) simulated by the Variable Infiltration Capacity (VIC) model was compatible with observed monthly groundwater storage anomalies and month-to-month changes in groundwater storage.

Groundwater↗

NASA NTRS2015

Groundwater Variability Across Temporal and Spatial Scales in the Central and Northeastern U.S.

water cycle↗

NASA NTRS1984

Numerical Simulation of North Atlantic Sea Ice Variability, 1951 - 1980

A two-level dynamic-thermodynamic sea ice model is used to simulate the growth, drift and decay of sea ice in the Northern Hemisphere during a 30-year period, 1951 to 1980. The model is run with a daily timestep on a 222 km grid and is forced by interanually varying fields of geostrophic wind and temperature-derived thermodynamic fluxes. The objective is a quantitative description of large-scale sea ice variability in terms of the dynamic and thermodynamic processes responsible for the fluctuations, especially in the North Atlantic where sea ice represents a substantial input of fresh water. The fields of ice velocity and thickness contain strong seasonal as well as interannual variability. The mean drift pattern results in thicknesses of 4 to 5 m offshore of northern Canada and Greenland, while winter thicknesses of approximately 2 m are typical of Alaskan. Eurasian and East Greenland coastal waters. The 30-year mean fields are characterized by ecessive ice in the North Atlantic during winter and by a summer retreat that is more rapid than observed.

Walsh, J. E.↗