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Variability of the total solar irradiance (TSI) is a ptential contributor to changes in global mean temperature on time scales longer than the relaxation time of the upper ocean (i.e. a few years).
As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.
In this paper we carried out a numerical experiment using the Specified Dynamics mode of the Whole Atmosphere Community Climate Model with thermosphere and ionosphere eXtension (SD-WACCM-X). One SD-WACCM-X run was with realistic Kp and F10.7 and the other with constant Kp and F10.7. By comparing the day-to-day variability of thermosphere mass density at 300 km (low earth orbit, LEO) and 120 km (reentry level) in these two runs, we find that the density variation at 300 km is mainly driven by geomagnetic and solar forcing while at 120 km it is exclusively controlled by the lower atmosphere. At LEO altitudes, during solar minimum and geomagnetic quiet days, the impact from the lower atmosphere is much smaller than the effect of solar and geomagnetic variations but is not negligible (5–10% vs 20%).
The "global warming hiatus" since the 1998 El Nino, highlighted by Meehl et al., and the resulting "missing energy" problem highlighted by Trenberth et al., has opened the door to a more fundamental view of climate change than mere surface air temperature. That new view is based on two variables which are strongly correlated: the rate of change of ocean heat content d(OHC)/dt; and Earth Radiation Imbalance (ERI) at the top of the atmosphere, whose guesstimated range is 0.4 to 0.9 Watts per square meters (this imbalance being mainly due to increasing CO2). The Argo float array is making better and better measurements of OHC. But existing satellite systems cannot measure ERI to even one significant digit. So, climate model predictions of ERI are used in place of real measurements of it, and the satellite data are tuned to the climate model predictions. Some oceanographers say "just depend on Argo for understanding the global warming hiatus and the missing energy", but we don't think this is a good idea because d(OHC)/dt and ERI have different time scales and are never perfectly correlated. We think the ERB community needs to step up to measuring ERI correctly, just as oceanographers have deployed Argo to measure OHC correctly. This talk will overview a proposed constellation of 66 Earth radiation budget instruments, hosted on Iridium satellites, that will actually be able to measure ERI to at least one significant digit, thus enabling a crucial test of climate models. This constellation will also be able to provide ERI at two-hourly time scales and 500-km spatial scales without extrapolations from uncalibrated narrowband geostationary instruments, using the highly successful methods of GRACE to obtain spatial resolution. This high time resolution would make ERI a synoptic variable like temperature, and allow studies of ERI's response to fast-evolving phenomena like dust storms and hurricanes and even brief excursions of Total Solar Irradiance. Time permitting, we will also discuss the emerging view of clear vs. cloudy and its implications for the traditional ERB approach.
The TROPspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor (Sentinel-5P) is the first of the Atmospheric Composition Sentinels by the European Space Agency (ESA) that provides measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions. The early afternoon orbit of Sentinel-5P mission provides a strong synergy with the U.S. Suomi National Polar-orbiting Partnership (S-NPP) satellite, especially in that the S-NPP Ozone Monitoring and Profiling Suite (OMPS) facilitates high vertically resolved stratospheric and lower mesospheric ozone profiles. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) supports over a thousand data collections in the Focus Areas of Atmospheric Composition, Water & Energy Cycles, and Climate Variability and it is the Distributed Active Archive Center (DAAC) that is curating both offline Sentinel-5P TROPOMI and S-NPP OMPS Level-1B (L1B) and Level-2 (L2) products. Through its convenient and enhanced tools/services such as OPeNDAP and L2 Subsetting, GES DISC offers air quality remote sensing user communities facile solutions for complex Earth science data and applications. This presentation will demonstrate TROPOMI and OMPS products including earthview radiance, solar irradiance, and currently available L2 datasets, as well as easy ways to access, visualize and subset data. The implementation of the End User License Agreement (EULA) between NASA GES DISC and all data users accessing data at GES DISC will be emphasized as well.
Hydroclimate extremes in North America, Europe, and the Mediterranean are linked to ocean and atmospheric circulation anomalies in the Atlantic, but the limited length of the instrumental record prevents complete identification and characterization of these patterns of covariability especially at decadal to centennial timescales. Here we analyze the coupled patterns of drought variability on either side of the North Atlantic Ocean basin using independent climate field reconstructions spanning the last millennium in order to detect and attribute epochs of coherent basin-wide moisture anomalies to ocean and atmosphere processes. A leading mode of broad-scale moisture variability is characterized by distinct patterns of North Atlantic atmosphere circulation and sea surface temperatures. We infer a negative phase of the North Atlantic Oscillation and colder Atlantic sea surface temperatures in the middle of the 15th century, coincident with weaker solar irradiance and prior to strong volcanic forcing associated with the early Little Ice Age.
We examine measurement strategies for reducing uncertainties in aerosol direct radiative forcing by focused experiments that combine surface, air, and space measurements. Particularly emphasized are closure experiments, which test the degree of agreement among different measurements and calculations of aerosol properties and radiative effects. By combining results from previous measurements of large-scale smokes, volcanic aerosols, and anthropogenic aerosols with models of aerosol evolution, we estimate the spatial and temporal variability in optical depth spectra to be expected in the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX, planned for summer 1996 off the Eastern U.S. seaboard). In particular, we examine the expected changes in the wavelength dependence of optical depth as particles evolve through nucleation, growth by condensation and coagulation, and removal via sedimentation. We then calculate the expected radiative climate forcing (i.e. change in net radiative flux) for typical expected aerosols and measurement conditions (e.g. solar elevations, surface albedos, radiometer altitudes). These calculations use new expressions for flux and albedo changes, which account not only for aerosol absorption, but also for instantaneous solar elevation angles and the dependence of surface albedo on solar elevation. These factors, which are usually ignored or averaged in calculations of global aerosol effects, can have a strong influence on fluxes measured in closure experiments, and hence must be accounted for in calculations if closure is to be convincingly tested. We compare the expected measurement signal to measurement uncertainties expected for various techniques in various conditions. Thereby we derive recommendations for measurement strategies that combine surface, airborne, and spaceborne measurements.
We present the first direct measurements of the infrared and solar heating rates of a tropical subvisible cirrus (SVC) cloud sampled off the east coast of Nicaragua on 25 July 2007 by the NASA ER-2 aircraft during the Tropical Composition, Cloud and Climate Coupling Experiment (TC4). On this day a persistent thin cirrus layer, with mostly clear skies underneath, was detected in real time by the cloud lidar on the ER-2, and the aircraft was directed to profile down through the SVC. Measurements of the net broadband infrared irradiance and spectrally integrated solar irradiance above, below, and through the SVC are used to determine the infrared and solar heating rates of the cloud. The lidar measurements show that the variable SVC layer was located between approximately 13 and 15 km. Its midvisible optical depth varied from 0.01 to 0.10 with a mean of 0.034 +/- 0.033. Its depolarization ratio was approximately 0.4, indicative of ice clouds. From the divergence of the measured net irradiances the infrared heating rate of the SVC was determined to be approximately 2.50 - 3.24 K/d and the solar heating rate was found to be negligible. These values are consistent with previous indirect observations of other SVC and with model-generated heating rates of SVC with similar optical depths. This study illustrates the utility and potential of the profiling sampling strategy employed here. A more fully instrumented high-altitude aircraft that also included in situ cloud and aerosol probes would provide a comprehensive data set for characterizing both the radiative and microphysical properties of these ubiquitous tropical clouds
Satellite measurements of the effect of clouds on the top of atmosphere radiative energy budget are used to validate model simulations from the National Center for Atmospheric Research Community Climate Model (NCAR CCM). The ability of the NCAR CCM to reproduce the monthly mean global distribution and temporal variability on both daily and seasonal time scales is assessed. The comparison reveals several deficiencies in the CCM cloud representation. Most notable are the difficulties in properly simulating the effect of clouds on the planetary albedo. This problem arises from discrepancies in the model's portrayal of low-level cloudiness and leads to significant errors in the absorbed solar radiation simulated by the model. The CCM performs much better in simulating the effect of clouds on the longwave radiation emitted to space, indicating its relative success in capturing the vertical distribution of cloudiness. The daily variability of the radiative effects of clouds in both the shortwave and longwave spectral regions is systematically overestimated. Analysis of the seasonal variations illustrates a distinct lack of coupling in the seasonal changes in the radiative effects of cloudiness between the tropics and mid-latitudes and between the Northern and Southern Hemisphere. Much of this problem also arises from difficulties in simulating low-level cloudiness, placing further emphasis on the need for better model parameterizations of boundary layer clouds.
A study of stable periodic solutions to a simple nonlinear model of the ocean-atmosphere-ice system is presented. The model has two dependent variables: ocean-atmosphere temperature and latitudinal extent of the ice cover. No explicit dependence on latitude is considered in the model. Hence all variables depend only on time and the model consists of a coupled set of nonlinear ordinary differential equations. The globally averaged ocean-atmosphere temperature in the model is governed by the radiation balance. The reflectivity to incoming solar radiation, i.e., the planetary albedo, includes separate contributions from sea ice and from continental ice sheets. The major physical mechanisms active in the model are (1) albedo-temperature feedback, (2) continental ice-sheet dynamics and (3) precipitation-rate variations. The model has three-equilibrium solutions, two of which are linearly unstable, while one is linearly stable. For some choices of parameters, the stability picture changes and sustained, finite-amplitude oscillations obtain around the previously stable equilibrium solution. The physical interpretation of these oscillations points to the possibility of internal mechanisms playing a role in glaciation cycles.
We have developed a compact Doppler lidar concept which utilizes recent developments in semiconductor diode laser technology in order to be considered suitable for wind and dust opacity profiling in the Mars lower atmosphere from a surface location. The current understanding of the Mars global climate and meteorology is very limited, with only sparse, near-surface data available from the Viking and Mars Pathfinder landers, supplemented by long-range remote sensing of the Martian atmosphere. The in situ measurements from a lander-based Doppler lidar would provide a unique dataset particularly for the boundary layer. The coupling of the radiative properties of the lower atmosphere with the dynamics involves the radiative absorption and scattering effects of the wind-driven dust. Variability in solar irradiance, on diurnal and seasonal time scales, drives vertical mixing and PBL (planetary boundary layer) thickness. The lidar data will also contribute to an understanding of the impact of wind-driven dust on lander and rover operations and lifetime through an improvement in our understanding of Mars climatology. In this paper we discuss the Mars lidar concept, and the development of a laboratory prototype for performance studies, using, local boundary layer and topographic target measurements.
Evapotranspiration (ET) is the water lost to the atmosphere by evaporation and transpiration. ET is a shared component in the energy and water budget, therefore, a critical variable for global energy and water cycle and climate change studies. However, direct ET measurements and data acquisition are difficult and expensive, especially at the global level. Therefore, modeling is one common alternative for estimating ET. With the goal to generate optimal fields of land surface states and fluxes, the Global Land Data Assimilation System (GLDAS) has been generating quality-controlled, spatially and temporally consistent, terrestrial hydrologic data, including ET and other variables that affect evaporation and transpiration, such as temperature, precipitation, humidity, wind, soil moisture, heat flux, and solar radiation. This poster presents the long-term ET climatology (mean and monthly), derived from the 61-year GLDAS-2 monthly 1.0 deg x 1.0 deg. NOAH model Experiment-1 data, and describes the basic characteristics of spatial and seasonal variations of the climatology. The time series of GLDAS-2 precipitation and radiation, and ET are also discussed to show the improvement of GLDAS-2 forcing data and model output over those from GLDAS-1.
The Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) mission will provide the science community with high-vertical resolution and nearly global observations of ozone, aerosols, water vapor, nitrogen dioxide, and other trace gas species in the stratosphere and upper-troposphere. SAGE III/ISS measurements will extend the long-term Stratospheric Aerosol Measurement (SAM) and SAGE data record begun in the 1970s. The multi-decadal SAGE ozone and aerosol data sets have undergone intense scrutiny and are considered the international standard for accuracy and stability. SAGE data have been used to monitor the effectiveness of the Montreal Protocol. Key objectives of the mission are to assess the state of the recovery in the distribution of ozone, to re-establish the aerosol measurements needed by both climate and ozone models, and to gain further insight into key processes contributing to ozone and aerosol variability. The space station mid-inclination orbit allows for a large range in latitude sampling and nearly continuous communications with payloads. The SAGE III instrument is the fifth in a series of instruments developed for monitoring atmospheric constituents with high vertical resolution. The SAGE III instrument is a moderate resolution spectrometer covering wavelengths from 290 nm to 1550 nm. Science data is collected in solar occultation mode, lunar occultation mode, and limb scatter measurement mode. A SpaceX Falcon 9 launch vehicle will provide access to space. Mounted in the unpressurized section of the Dragon trunk, SAGE III will be robotically removed from the Dragon and installed on the space station. SAGE III/ISS will be mounted to the ExPRESS Logistics Carrier-4 (ELC-4) location on the starboard side of the station. To facilitate a nadir view from this location, a Nadir Viewing Platform (NVP) payload was developed which mounts between the carrier and the SAGE III Instrument Payload (IP).
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.
The satellite ocean color data record spans multiple decades and, like most long-term satellite observations of the Earth, comes from many sensors. Unfortunately, global and regional chlorophyll estimates from the overlapping missions show substantial biases, limiting their use in combination to construct consistent data records. SeaWiFS and MODIS-Aqua differed by 13% globally in overlapping time segments, 2003-2007. For perspective, the maximum change in annual means over the entire Sea WiFS mission era was about 3%, and this included an El NinoLa Nina transition. These discrepancies lead to different estimates of trends depending upon whether one uses SeaWiFS alone for the 1998-2007 (no significant change), or whether MODIS is substituted for the 2003-2007 period (18% decline, P less than 0.05). Understanding the effects of climate change on the global oceans is difficult if different satellite data sets cannot be brought into conformity. The differences arise from two causes: 1) different sensors see chlorophyll differently, and 2) different sensors see different chlorophyll. In the first case, differences in sensor band locations, bandwidths, sensitivity, and time of observation lead to different estimates of chlorophyll even from the same location and day. In the second, differences in orbit and sensitivities to aerosols lead to sampling differences. A new approach to ocean color using in situ data from the public archives forces different satellite data to agree to within interannual variability. The global difference between Sea WiFS and MODIS is 0.6% for 2003-2007 using this approach. It also produces a trend using the combination of SeaWiFS and MODIS that agrees with SeaWiFS alone for 1998-2007. This is a major step to reducing errors produced by the first cause, sensor-related discrepancies. For differences that arise from sampling, data assimilation is applied. The underlying geographically complete fields derived from a free-running model is unaffected by solar zenith angle requirements and obscuration from clouds and aerosols. Combined with in situ dataenhanced satellite data, the model is forced into consistency using data assimilation. This approach eliminates sampling discrepancies from satellites. Combining the reduced differences of satellite data sets using in situ data, and the removal of sampling biases using data assimilation, we generate consistent data records of ocean color. These data records can support investigations of long-term effects of climate change on ocean biology over multiple satellites, and can improve the consistency of future satellite data sets.
The activity cavity radiometer irradiance monitor is supplying the first high precision data on solar total irradiance at the Earth. Thee classes of variability were discovered: large variations of amplitudes up to 0.2%; small high frequency variations in the form of a continuum in the periodogram, extending up to the Nyquist frequency; and sharp spikes at frequencies corresponding to the individual p modes already known from radial velocity measurements. The observed variations (up to 0.3%, on time scales of several days) were identified with sunspot darkness. The data analysis is expected to give information about the solar interior, as well as about the solar input to the terrestrial climate.
Recent satellite observations of the solar total irradiance confirm that it is varying at least on the 11 year time scale. Both blocking by sunspots and re-emission by faculae are components in this variation, but changes in the temperature of the solar photosphere may also be a contributing component. The satellite observations are as yet of insufficient length to answer the question of whether the sun is varying in luminosity on time scales longer than the 11 year sunspot cycle. Examined here are proxy methods of re-constructing these longer term luminosity variations, with an examination of secular changes in sunspot structure as one tool. Solar rotation changes and solar diameter changes are other parameters which may reveal information about solar luminosity variations. All three variables give remarkably similar conclusions. Over the last century the Earth's surface temperatures and the structure of sunspots have varied in a parallel manner. It is hypothesized that sunspots have varied in a convective medium which itself is varying over long time periods. These variations in convective strength alter the boundary conditions on sunspots and hence cause their structure to vary. Simultaneous with the variations in convective strength, the solar luminosity will vary as well. This, in turn, leads to changes in the climate of the Earth. Variations in solar diameter and solar rotation support the hypothesis that solar luminosity has varied over the last century and reached a peak around 1925 to 1935. This evidence is reviewed along with a possible model of why sunspot structure may provide a good proxy measure of solar luminosity changes.
This annual report covers August 2000 - August 2001 under NASA contract NASW-0032, entitled "Continuation of the NVAP (NASA's Water Vapor Project) Global Water Vapor Data Sets for Pathfinder Science Analysis". NASA has created a list of Earth Science Research Questions which are outlined by Asrar, et al. Particularly relevant to NVAP are the following questions: (a) How are global precipitation, evaporation, and the cycling of water changing? (b) What trends in atmospheric constituents and solar radiation are driving global climate? (c) How well can long-term climatic trends be assessed or predicted? Water vapor is a key greenhouse gas, and an understanding of its behavior is essential in global climate studies. Therefore, NVAP plays a key role in addressing the above climate questions by creating a long-term global water vapor dataset and by updating the dataset with recent advances in satellite instrumentation. The NVAP dataset produced from 1988-1998 has found wide use in the scientific community. Studies of interannual variability are particularly important. A recent paper by Simpson, et al. that examined the NVAP dataset in detail has shown that its relative accuracy is sufficient for the variability studies that contribute toward meeting NASA's goals. In the past year, we have made steady progress towards continuing production of this high-quality dataset as well as performing our own investigations of the data. This report summarizes the past year's work on production of the NVAP dataset and presents results of analyses we have performed in the past year.