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NASA NTRS2018

Recent Rainfall Decline in West Africa Due to Enhanced Biomass Burning and Dust Emission

Rainfall in West Africa during boreal summer is primarily controlled by the low-level southerly monsoon flow that transports moisture from the Gulf of Guinea to the region and the African Easterly Jet that modulates the convective systems. However, the role of aerosols in rainfall variability of this region, despite the large emissions of dust and black carbon in Africa, is not well-understood. Our study reveals a decline in precipitation over Southern West Africa (SWA) in the past two decades that its trend and interannual variability present an indirect relationship with the aerosols loadings. Examining the local and remote sources of aerosols, we found that the latter have a larger contribution. We have used MERRA-2 large scale atmospheric dynamics and physics data to determine the mechanisms responsible for aerosol-rainfall interactions in the region. Our results have important implications for the people and ecosystem as the increasing rates of land use change, deforestation and urbanization in the continent are expected to enhance the aerosols. This will result in an increase in the frequency and intensity of the extreme events including droughts.

Dezfuli, Amin↗

DOE OSTI2026

How Well Can CMIP6 Models Represent the Observed Influence of the Pacific and Indian Oceans on the Indian Summer Monsoon Rainfall?

This study evaluates the ability of CMIP6 climate models to simulate the observed effects of tropical Pacific and Indian Ocean sea surface temperature anomalies (SSTAs) on Indian summer monsoon rainfall (ISMR) variability. Using observational data and the large ensemble historical simulations of seven CMIP6 models from 1950 to 2014, we applied a cyclostationary linear inverse model (CS-LIM) to isolate the impacts of tropical Pacific SSTAs, Indian Ocean SSTAs and their interaction on the interannual variability of ISMR. Overall, CMIP6 models well reproduced the observed enhanced (reduced) ISMR variability from Pacific SSTAs (Indian Ocean SSTAs and the Indo-Pacific interaction), but with varying spatial patterns and magnitudes. While CESM2 and E3SM-2-0 showed the best agreement with observations for the effects of Pacific SSTAs and the Indo-Pacific interaction, respectively, CMIP6 models showed mixed results for the impacts from Indian Ocean SSTAs. Composite analysis of ISMR anomalies during the developing phases of pure and co-occurring El Niño-Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) events revealed that the impacts from Pacific SSTAs were captured reasonably well by E3SM-2-0, CESM2, MIROC6, and MPI-ESM1-2-LR, while E3SM-2-0 also showed the best agreement with observations for the effects from the Indo-Pacific interaction. However, all models showed substantial biases in simulating the Indian Ocean SSTA impacts on ISMR, especially for pure El Niño events. Overall, this study provides new insights into how individual CMIP6 models simulate the isolated impacts from the tropical Pacific and Indian Oceans, which has important applications for improving ISMR predictions and interpreting ISMR future projections.

monsoon↗

NASA NTRS1999

The Tropical Upper Troposphere and Lower Stratosphere in the GEOS-2 GCM

The structure of the tropical upper troposphere and lower stratosphere in the GEOS-2 General Circulation Model (GCM) is discussed. The emphasis of this study is on the reality of monthly-mean temperature and water vapor distributions in the model, compared to reasonable observational estimates. It is shown that although the zonal-mean temperature is in good agreement with observations, the GCM supports an excessive zonal asymmetry near the tropopause compared to the ECMWF Reanalyses. In reality there is a QBO-related variability in the zonally averaged lower stratospheric temperature which is not captured by the model. The observed upper tropospheric temperature and humidity fields show variations related to those in the sea surface temperature, which are not incorporated in the GCM; nevertheless, there is some interannual variability in the GCM, indicating a component arising from internal processes. The model is too moist in the middle troposphere (500 hPa) but too dry in the upper troposphere, suggesting that there is too little vertical transport or too much drying in the GCM. Transport into the stratosphere shows a pronounced annual cycle, with drier air entering the tropical stratosphere when the tropopause is coldest in northern winter; while the alternating dry and moist air masses can be traced ascending through the tropical lower stratosphere, the progression of the anomalies is too rapid.

Pawson, S.↗

NASA NTRS1993

Circulation and rainfall climatology of a 10-year (1979 - 1988) integration with the Goddard Laboratory for atmospheres general circulation model

A 10-year (1979-1988) integration of Goddard Laboratory for Atmospheres (GLA) general circulation model (GCM) under Atmospheric Model Intercomparison Project (AMIP) is analyzed and compared with observation. The first momentum fields of circulation variables and also hydrological variables including precipitation, evaporation, and soil moisture are presented. Our goals are (1) to produce a benchmark documentation of the GLA GCM for future model improvements; (2) to examine systematic errors between the simulated and the observed circulation, precipitation, and hydrologic cycle; (3) to examine the interannual variability of the simulated atmosphere and compare it with observation; and (4) to examine the ability of the model to capture the major climate anomalies in response to events such as El Nino and La Nina. The 10-year mean seasonal and annual simulated circulation is quite reasonable compared to the analyzed circulation, except the polar regions and area of high orography. Precipitation over tropics are quite well simulated, and the signal of El Nino/La Nina episodes can be easily identified. The time series of evaporation and soil moisture in the 12 biomes of the biosphere also show reasonable patterns compared to the estimated evaporation and soil moisture.

Kim, J.-H.↗

DOE OSTI2018

Effective Quantification of Wind-Speed Variability at Different Temporal Scales

RCoV, a statistically robust and resistant metric, effectively characterizes and correlates the spreads of the distributions of wind resources and wind-energy productions. Using RCoV, a wind farm with high wind-speed fluctuations possesses high variations in wind-energy generation and vice versa. Because the long-term correlations between the wind-speed and energy-production interannual variabilities are weak and decrease with the length of data, we do not recommend calculating variabilities with yearly mean data. Skewness and kurtosis drastically change with averaging time frames. Nonzero skewness and kurtosis illustrate that the Gaussian assumption is principally inadequate in most of the United States for all averaging time frames of wind speeds.

17 WIND ENERGY↗

DOE OSTI2017

Global variation of transpiration and soil evaporation and the role of their major climate drivers

Although global variation in actual evapotranspiration has been widely investigated, it remains unclear how its two major components, transpiration and soil evaporation, are driven by climate drivers across global land surface. This paper uses a well-validated, process-based model that estimates transpiration and soil evaporation, and for the first time investigates and quantifies how the main global drivers, associated to vegetation process and the water and energy cycle, drive the spatiotemporal variation of the two components. The results show that transpiration and soil evaporation dominate the variance of actual evapotranspiration in wet and dry regions, respectively. Dry southern hemisphere from 13°S to 27°S is highlighted since it contributes to 21% global soil evaporation variance, with only 11% global land area. In wet regions, particularly in the humid tropics, there are strong correlations between transpiration, actual evapotranspiration, and potential evapotranspiration, with precipitation playing a relatively minor role, and available radiative energy is the major contributor to the interannual variability in transpiration and actual evapotranspiration in Amazonia. Conversely in dry regions, there are strong correlations between soil evaporation, actual evapotranspiration, and precipitation. Lastly, our findings highlight that ecohydrological links are highly related to climate regimes, and the small region such as Australia has important contribution to interannual variation in global soil evaporation and evapotranspiration, and anthropogenic activities strongly influence the variances in irrigation regions

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Evaluation of the National Solar Radiation Database (NSRDB): 1998-2015

This paper validates the performance of the physics-based Physical Solar Model (PSM) data set in the National Solar Radiation Data Base (NSRDB) to quantify the accuracy of the magnitude and the spatial and temporal variability of the solar radiation data. Achieving higher penetrations of solar energy on the electric grid and reducing integration costs requires accurate knowledge of the available solar resource. Understanding the impacts of clouds and other meteorological constituents on the solar resource and quantifying intra-/inter-hour, seasonal, and interannual variability are essential for accurately designing utility-scale solar energy projects. Solar resource information can be obtained from ground-based measurement stations and/or from modeled data sets. The availability of measurements is scarce, both temporally and spatially, because it is expensive to maintain a high-density solar radiation measurement network that collects good quality data for long periods of time. On the other hand, high temporal and spatial resolution gridded satellite data can be used to estimate surface radiation for long periods of time and is extremely useful for solar energy development. Because of the advantages of satellite-based solar resource assessment, the National Renewable Energy Laboratory developed the PSM. The PSM produced gridded solar irradiance -- global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance -- for the NSRDB at a 4-km by 4-km spatial resolution and half-hourly temporal resolution covering the 18 years from 1998-2015. The NSRDB also contains additional ancillary meteorological data sets, such as temperature, relative humidity, surface pressure, dew point, and wind speed. Details of the model and data are available at https://nsrdb.nrel.gov. The results described in this paper show that the hourly-averaged satellite-derived data have a systematic (bias) error of approximately +5% for GHI and less than +10% for DNI; however, the scatter (root mean square error [RMSE]) difference is higher for the hourly averages.

14 SOLAR ENERGY↗

DOE OSTI2017

Evaluation of the National Solar Radiation Database (NSRDB): 1998-2015

14 SOLAR ENERGY↗

DOE OSTI2025

Aerosol hygroscopicity over the South-East Atlantic Ocean during the biomass burning season – Part 2: Influence of sea salt and burning conditions on CCN hygroscopicity

Biomass burning (BB) significantly influences cloud condensation nuclei (CCN) concentrations over the southeastern Atlantic; however, aerosol hygroscopicity (κ) – a key factor for CCN activation – remains poorly constrained during the BB season. This study investigates κ variability using in situ measurements from Ascension Island during the 2016 and 2017 BB seasons. Results show substantial monthly variability, with κ values lowest in August and increasing through October. On average, κ was significantly higher in 2017 (∼ 0.55) than in 2016 (∼ 0.33), suggesting that the aerosols in 2017 were more hygroscopic and more easily activated as CCN. Sulfate and sea salt were the two dominant contributors to κ and the primary drivers of its interannual variability. During the 2017 BB season, sulfate – the major inorganic component – accounted for ∼ 34 % of the submicron aerosol mass, while sea salt, estimated via κ-closure analysis, contributed ∼ 17 %. The higher κ in 2017 was largely attributed to increased sea salt, likely driven by stronger marine winds. Approximately 67 % of sulfate was linked to BB emissions. Variations in BB combustion efficiency, modulated by regional meteorology, influenced sulfate fraction and thus κ values. Specifically, higher relative humidity and lower wind speeds over BB source regions in 2017 favored smoldering combustion, explaining the higher sulfate fraction. Overall, the observed interannual differences in aerosol hygroscopicity reflect the combined impacts of BB combustion characteristics and sea salt emissions, underscoring the critical roles of both BB and marine aerosol sources in regulating aerosol-cloud interactions over the southeastern Atlantic.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

New Particle Formation Event Dataset at the Southern Great Plains (SGP) Observatory from 2018 to 2023

This data set contains observations of new particle formation (NPF) events collected at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory from 2018 to 2023. Measurements include particle number size distributions, radiance measurements, and associated meteorological variables from onsite instrumentation relevant for identifying and characterizing NPF events. Events were identified using standardized criteria and documented to support investigations of aerosol nucleation, growth dynamics, and their interactions with local atmospheric conditions. The data set provides a multi-year record that enables evaluation of seasonal and interannual variability in NPF occurrence and intensity at a mid-continental site. These data are intended to support studies of aerosol-cloud-climate interactions and model evaluation within both ARM and the broader atmospheric science community. More information can be found within the README_NPF_SGP_2018_2023.docx file.

event↗

NASA NTRS1990

Surface winds from tropical Pacific islands - Climatological statistics

Variability space- and time-scales are presently investigated on the basis of multidecadal time series of surface wind observations from islands in the tropical Pacific. The frequency distribution of variance, derived from daily-averaged data, exhibits considerable geographical variation. Poleward of about 5 deg of latitude, the interannual variability in zonal wind diminishes sharply and the zonal and meridional wind variances become increasingly comparable. The zonal wind energy level in the 3- to 60-day band decreases with distance from the equator.

Harrison, D. E.↗

NASA NTRS2010

Comparing Global Atmospheric CO2 Flux and Transport Models with Remote Sensing (and Other) Observations

We report recent progress derived from comparison of global CO2 flux and transport models with new remote sensing and other sources of CO2 data including those from satellite. The overall objective of this activity is to improve the process models that represent our understanding of the workings of the atmospheric carbon cycle. Model estimates of CO2 surface flux and atmospheric transport processes are required for initial constraints on inverse analyses, to connect atmospheric observations to the location of surface sources and sinks, to provide the basic framework for carbon data assimilation, and ultimately for future projections of carbon-climate interactions. Models can also be used to test consistency within and between CO2 data sets under varying geophysical states. Here we focus on simulated CO2 fluxes from terrestrial vegetation and atmospheric transport mutually constrained by analyzed meteorological fields from the Goddard Modeling and Assimilation Office for the period 2000 through 2009. Use of assimilated meteorological data enables direct model comparison to observations across a wide range of scales of variability. The biospheric fluxes are produced by the CASA model at 1x1 degrees on a monthly mean basis, modulated hourly with analyzed temperature and sunlight. Both physiological and biomass burning fluxes are derived using satellite observations of vegetation, burned area (as in GFED-3), and analyzed meteorology. For the purposes of comparison to CO2 data, fossil fuel and ocean fluxes are also included in the transport simulations. In this presentation we evaluate the model's ability to simulate CO2 flux and mixing ratio variability in comparison to remote sensing observations from TCCON, GOSAT, and AIRS as well as relevant in situ observations. Examples of the influence of key process representations are shown from both forward and inverse model comparisons. We find that the model can resolve much of the synoptic, seasonal, and interannual variability in the observations, although reasons for persistent discrepancies in northern hemisphere vegetation uptake are examined. At this time, we do not find any serious shortcomings in the model transport representation, but this is still the subject of close scrutiny. In general, the fidelity of these simulations leads us to anticipate incorporation of real-time, highly resolved remote sensing and other observations into quantitative analyses that will reduce uncertainty in CO2 fluxes and revolutionize our understanding of the key processes controlling atmospheric CO2 and its evolution with time.

Kawa, S. R.↗

NASA NTRSDate not supplied

Estimating Future Changes of Energy Demand for Heating and Cooling Buildings at NASA Centers GC23J-1198

With its unique and trusted earth observations, NASA is a critical source in informing decisions that will help achieve the U.S. goal of Net-Zero Greenhouse Gas (GHG) Emissions by 2050. NASA’s Prediction of Worldwide Energy Resource (POWER) project facilitates the use of NASA Earth Science data holdings within the energy, agricultural, and building heating/cooling design industries. POWER packages solar and meteorological data from several NASA projects in a user friendly GIS-enabled web services system (https://power.larc.nasa.gov). As part of the development of new data products to support the energy and building heating/cooling design communities, we estimate the changes in energy required to heat and cool buildings in the future climate at 14 different NASA site locations spread throughout the continental United States, as projected by CMIP6 climate models under different emissions scenarios. Bias-corrected downscaled time series of meteorological variables are taken from NASA Earth Exchange (NEX) Global Daily Downscaled Projections (GDDP-CMIP6) downscaled climate model data. The spread between the different model projections is accounted for by analyzing both the ensemble average of 22 CMIP6 models and 6 representative models with different climate sensitivities and different interannual variability. Changes in energy use are estimated in two ways. First, changes in the total annual heating and cooling degree days (HDD and CDD, respectively) are calculated relative to the current climate. This is done at all 14 sites. Second, the downscaled time series are used as inputs into RETScreen(R), a clean energy management decision tool, to give an estimate of heating/cooling energy use for a typical office building. We use this estimation method with model data at Langley Research Center. In the next 50 years, the annual total of HDD (CDD) is projected to decrease by 8-38% (increase by 5-28%) at all sites, with the increase in CDD typically a larger magnitude the decrease in HDD. For a typical small office building at Langley Research Center, the amount of energy needed to cool increases by 33-54% and the amount of energy to heat decreases by 29-40%. POWER is working to develop long term climate data services based on these results to include in future data products to provide to users.

Bradley M. Hegyi↗

DOE OSTI2018

How Would the Twenty-First-Century Warming Influence Pacific Decadal Variability and Its Connection to North American Rainfall: Assessment Based on a Revised Procedure for the IPO/PDO

Decadal climate variability of sea surface temperature (SST) over the Pacific Ocean can be characterized by interdecadal Pacific oscillation (IPO) or Pacific decadal oscillation (PDO) based on empirical orthogonal function (EOF) analysis. Although the procedures to derive the IPO and PDO indices differ in their regional focuses and filtering methods to remove interannual variability, the IPO and PDO are highly correlated in time and are often used interchangeably. Studies have shown that the IPO and PDO conjointly (IPO/PDO for conciseness) play a vital role in modulating the pace of global warming. It is less clear, however, how externally forced global warming may, in turn, affect the IPO/PDO. One obstacle to revealing this effect is that the conventional definitions of the IPO/PDO fail to account for the spatial heterogeneity of the background warming trend, which causes the IPO/PDO to be conflated with the warming trend, especially for the twenty-first-century simulation when the forced change is likely to be more dominant. Using a large-ensemble simulation in the Community Earth System Model, version 1 (CESM1), it is shown here that a better practice of detrending prior to EOF analysis is to remove the local and nonlinear trend, defined as the ensemble-mean time series at each grid box (or simply as the quadratic fit of the local time series if such an ensemble is not available). The revised IPO/PDO index is purely indicative of internal decadal variability. In the twenty-first-century warmer climate, the IPO/PDO has a weaker amplitude in space, a higher frequency in time, and a muted impact on global and North American temperature and rainfall.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Interannual to Decadal Variability in Subarctic Atlantic Ocean Primary Productivity Historical Variability, Dynamics, and Response to Warming

Phytoplankton primary productivity in the Subarctic Atlantic Ocean sustains valuable fisheries and exports anthropogenic atmospheric carbon dioxide, but multiple Earth system models show that this productivity declines substantially in 21st century global warming scenarios. Prior studies have investigated the spatial and temporal dynamics of the seasonal cycle of the phytoplankton, which exhibit a prominent but spatially variable spring bloom that is caused by the closely related seasonal cycles in solar radiation and vertical mixing that modulate both phytoplankton growth and loss rates. However, recent work indicates that multi-decade declines in this spring bloom with global warming in multiple Earth system models are driven by reductions in circulation of nutrients from the subtropical and tropical thermocline, rather than local changes in vertical mixing or shortwave radiation in the Subarctic. It is unclear if current models of how phytoplankton productivity varies seasonally or over a century in global warming can be interpolated to explain the interannual to decadal variability. In this poster, I will quantify the interannual to decadal variability of phytoplankton chlorophyll using historical satellite ocean color observations and model simulations with the Community Earth System Model. I will then use the observations and model simulations to elucidate the mechanisms of interannual to decadal variability and how that variability is restructured in 21st century global warming scenarios.

nterannual↗

DOE OSTI2025

The global Sahel monsoon ocean-pressure index reconciles its regional and large-scale features

Monitoring Sahelian rainfall variability is increasingly critical as climate extremes intensify across the region. Here, we develop the Sahelian Monsoon Ocean-Pressure Index (SMOPI), a novel global synthetic indicator constructed from five dynamically coherent sea-level pressure regions statistically linked to June-September Sahel monsoon rainfall. SMOPI captures intra-seasonal and interannual variability, and crucially, reflects the influence of both regional processes and large-scale teleconnections on monsoon dynamics. It aligns with the dominant rainfall variability mode in reanalyses and 29 CMIP6 models. Strong/positive SMOPI phases coincide with wet years and are associated with enhanced convergence, favorable jet configurations, and robust Pacific, Atlantic, and Indian Ocean teleconnections. Conversely, weak/negative SMOPI phases correspond to drought conditions and divergent moisture fluxes. SMOPI exposes model failures in reproducing historical droughts and offers new physical insights into rainfall-driving mechanisms. It stands out as a scalable, potentially transferable diagnostic tool for monitoring/forecasting and evaluating Sahelian monsoon rainfall under global warming.

Tamoffo, Alain T. [Helmholtz-Zentrum Hereon GmbH, ↗

NASA NTRS2000

Development and Validation of Water Vapor Tracers as Diagnostics for the Atmospheric Hydrologic Cycle

Understanding of the local and remote sources of water vapor can be a valuable diagnostic in understanding the regional atmospheric hydrologic cycle. In the present study, we have implemented passive tracers as prognostic variables to follow water vapor evaporated in predetermined regions until the water tracer precipitates. The formulation of the sources and sinks of tracer water is generally proportional to the prognostic water vapor variable. Because all water has been accounted for in tracers, the water vapor variable provides the validation of the tracer water and the formulation of the sources and sinks. The tracers have been implemented in a GEOS General Circulation Model (GCM) simulation consisting of several summer periods to determine the source regions of precipitation for the United States and India. The recycling of water and interannual variability of the sources of water will be examined. Potential uses in GCM sensitivity studies, predictability studies and data assimilation will be discussed.

Bosilovich, Michael G.↗

NASA NTRS2017

Atmospheric Form Drag Coefficients Over Arctic Sea Ice Using Remotely Sensed Ice Topography Data, Spring 2009-2015

Sea ice topography significantly impacts turbulent energy/momentum exchange, e.g., atmospheric (wind) drag, over Arctic sea ice. Unfortunately, observational estimates of this contribution to atmospheric drag variability are spatially and temporally limited. Here we present new estimates of the neutral atmospheric form drag coefficient over Arctic sea ice in early spring, using high-resolution Airborne Topographic Mapper elevation data from NASA's Operation IceBridge mission. We utilize a new three-dimensional ice topography data set and combine this with an existing parameterization scheme linking surface feature height and spacing to form drag. To be consistent with previous studies investigating form drag, we compare these results with those produced using a new linear profiling topography data set. The form drag coefficient from surface feature variability shows lower values [less than 0.5-1 × 10(exp. −3)] in the Beaufort/Chukchi Seas, compared with higher values [greater than 0.5-1 ×10(exp. −3)] in the more deformed ice regimes of the Central Arctic (north of Greenland and the Canadian Archipelago), which increase with coastline proximity. The results show moderate interannual variability, including a strong increase in the form drag coefficient from 2013 to 2014/2015 north of the Canadian Archipelago. The form drag coefficient estimates are extrapolated across the Arctic with Advanced Scatterometer satellite radar backscatter data, further highlighting the regional/interannual drag coefficient variability. Finally, we combine the results with existing parameterizations of form drag from floe edges (a function of ice concentration) and skin drag to produce, to our knowledge, the first pan-Arctic estimates of the total neutral atmospheric drag coefficient (in early spring) from 2009 to 2015.

sea ice↗