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At least 559 records · Page 31

Equilibrium Climate Sensitivity Estimated by Equilibrating Climate Models

The methods to quantify equilibrium climate sensitivity are still debated. We collect millennial length simulations of coupled climate models and show that the global mean equilibrium warming is higher than those obtained using extrapolation methods from shorter simulations. Specifically, 27 simulations with 15 climate models forced with a range of CO2 concentrations show a median 17% larger equilibrium warming than estimated from the first 150 years of the simulations. The spatial patterns of radiative feedbacks change continuously, in most regions reducing their tendency to stabilizing the climate. In the equatorial Pacific, however, feedbacks become more stabilizing with time. The global feedback evolution is initially dominated by the tropics, with eventual substantial contributions from the midlatitudes. Time dependent feedbacks underscore the need of a measure of climate sensitivity that accounts for the degree of equilibration, so that models, observations, and paleo proxies can be adequately compared and aggregated to estimate future warming.

Maria Rugenstein↗

Advanced Materials Testing for Lunar Landing & Launch Pad Construction

Five candidate lunar landing and launch pad candidate materials were evaluated in relevant Oxygen/Methane rocket engine plume environment exposure tests. The performance trends were modeled, observed, measured (to the extent possible), and testing results were evaluated. A total of fifteen high temperature plume tests were performed in two test campaigns: five in December 2020 and ten in March 2021. The results indicate that several of the selected materials are promising for future consideration in designing and building lunar landing and launch pads, although further development work is needed for all of them.

landing pad↗

NASA Health and Air Quality Applications

There is a growing body of evidence that the environment can affect human health in ways that are both complex and global in scope. To address some of these complexities, NASA maintains a diverse constellation of Earth observing research satellites, and sponsors research in developing satellite data applications across a wide spectrum of areas. These include environmental health; infectious disease; air quality standards, policies, and regulations; and the impact of climate change on health and air quality in a number of interrelated efforts. The Health and Air Quality Applications fosters the use of observations, modeling systems, forecast development, application integration, and the research to operations transition process to address environmental health effects. NASA has been a primary partner with Federal operational agencies over the past nine years in these areas. This talk presents the background of the Health and Air Quality Applications program, recent accomplishments, and a plan for the future.

Air Quality Remote Sensing↗

Observation of a Magnetic Switchback in the Solar Corona

Switchbacks are sudden, large radial deflections of the solar wind magnetic field, widely revealed in interplanetary space by the Parker Solar Probe. The switchbacks’ formation mechanism and sources are still unresolved, although candidate mechanisms include Alfvénic turbulence, shear-driven Kelvin–Helmholtz instabilities, interchange reconnection, and geometrical effects related to the Parker spiral. This Letter presents observations from the Metis coronagraph on board a Solar Orbiter of a single large propagating S-shaped vortex, interpreted as the first evidence of a switchback in the solar corona. It originated above an active region with the related loop system bounded by open-field regions to the east and west. Observations, modeling, and theory provide strong arguments in favor of the interchange reconnection origin of switchbacks. Metis measurements suggest that the initiation of the switchback may also be an indicator of the origin of slow solar wind.

Solar corona↗

Impact of Size Distribution Assumption on PM2.5 Simulation

Aerosol particles, especially those with diameter that is smaller than 2.5um, i.e. PM2.5, have detrimental impact on public health. As a regulated criteria air pollutant, PM2.5 is monitored by ground networks using various instruments. At the same time aerosol assimilation modeling system is developed to simulate the aerosol distribution with continuous global coverage. In this study we compared the PM2.5 simulated by NASA’s MERRA-2 modeling system with the measurements made at US Embassy sites around the globe on diurnal cycle, monthly average, and interannual variabilities. We focused the comparison in the places that are significantly impacted by the desert dust. Simulations based on both aerodynamic and geometric diameters are compared with available measurements. Aerodynamic diameter assumption shows better model-observation agreements over several dust belt stations.

Qian Tan↗

Towards Assimilation of Satellite Derived Aerosol Optical Centroid Height in the NASA’s Goddard Earth Observing System (GEOS) Model: Case Studies

Aerosol vertical distribution plays an important role in determining aerosol effects on the weather, climate and air quality, but is one of the largest uncertainties in current global chemistry transport models. Operational datasets of global aerosol vertical distribution from observational sources that could constrain models are not adequate.

Santiago Gasso↗

Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications

This technical report presents Prithvi-EO-2.0, a new geospatial foundation model that offers significant improvements over its predecessor, Prithvi-EO-1.0. Trained on 4.2M global time series samples from NASA’s Harmonized Landsat and Sentinel-2 data archive at 30m resolution, the new 300M and 600M parameter models incorporate temporal and location embeddings for enhanced performance across various geospatial tasks. Through extensive benchmarking with GEOBench, the 600M version outperforms the previous Prithvi-EO model by 8% across a range of tasks. It also outperforms six other geospatial foundation models when benchmarked on remote sensing tasks from different domains and resolutions (i.e. from 0.1m to 15m). The results demonstrate the versatility of the model in both classical earth observation and high-resolution applications. Early involvement of end-users and subject matter experts (SMEs) are among the key factors that contributed to the project’s success. In particular, SME involvement allowed for constant feedback on model and dataset design, as well as successful customization for diverse SME-led applications in disaster response, land use and crop mapping, and ecosystem dynamics monitoring. Prithvi-EO-2.0 is available on Hugging Face and IBM terratorch, with additional resources on GitHub. The project exemplifies the Trusted Open Science approach embraced by all involved organizations.

Daniela Szwarcman↗

Mesosphere and Lower Thermosphere Temperatures Simulated by WACCM‐X With NAVGEM‐HA Meteorological Analyses and Compared to SABER Observations

Realistic modeling of the dynamics and variability in the upper mesosphere and lower thermosphere (UMLT) is critical to understand the coupling between different layers of the whole atmosphere system. Here we present simulations of the UMLT temperatures at ∼100 km altitude for one year during 2014 by the Whole Atmosphere Community Climate Model with thermosphere-ionosphere extension (WACCM-X) constrained below ∼90 km using meteorological analysis products of the high-altitude version of Navy Global Environmental Model (NAVGEM-HA). The model results are sampled at the same times and latitudes and longitudes as the satellite observations from Thermosphere Ionosphere and Mesosphere Electric Dynamics/Sounding of the Atmosphere using Broadband Emission Radiometry (TIMED/SABER). Comparisons show that the observed and modeled daily zonal mean temperatures are correlated (r ∼0.5–0.7) at most latitudes between ±50°. Both the observations and simulations show an annual variation at mid-latitudes in two hemispheres with the temperature maximum in summer and the minimum in winter, and at lower latitudes the semiannual variation becomes stronger having the temperature maximums at equinoxes and the minimums during solstices. However, the temperatures observed are on average ∼5–10 K (3%–5%) smaller than the model and the observations show a larger variability. Moreover, migrating tidal amplitudes are mostly overestimated by the model. Though differences are noticed, the WACCM-X simulations with NAVGEM-HA meteorological analyses are overall consistent with the SABER observations. These results support that whole atmosphere models informed by high altitude observations would help to simulate the UMLT variability and the atmosphere and ionosphere coupling.

Guiping Liu↗

Inverse Modeling of Texas NOx Emissions Using Space-Based and Ground-Based NO2 Observations

Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite observed NO2 over rural regions. Satellitebased top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with Decoupled Direct Method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2 based DKF inversion. The DKF inversions yield conflicting results: the satellite based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3-55% increase in modeled NO2 column densities and 1-7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.

Nitrogen dioxide↗

What is data assimilation really solving, and how is the calculation actually done?

Data assimilation is a procedure in which observations are combined with models. The observations correct model errors on the one hand, and the models extrapolate the data information in space, time, and among different properties on the other. The result of assimilation is generally a more complete and more accurate description of the state of the modeled system than those obtained by either observations or model simulations alone. However, data assimilation is not a panacea for correcting every model error or for compensating all deficiencies of observations.

smoother↗

Spatial Scaling of Snow Observations and Microwave Emission Modeling During CLPX and Appropriate Satellite Sensor Resolution

Accurate estimates of snow water equivalent and other properties play an important role in weather, natural hazard, and hydrological forecasting and climate modeling over a range of scales in space and time. Remote sensing-derived estimates have traditionally been of the "snapshot" type, but techniques involving models with assimilation are also being explored. In both cases, forward emission models are useful to understand the observed passive microwave signatures and developing retrieval algorithms. However, mismatches between passive microwave sensor resolutions and the scales of processes controlling subpixel heterogeneity can affect the accuracy of the estimates. Improving the spatial resolution of new passive microwave satellite sensors is a major desire in order to (literally) resolve such subpixel heterogeneity, but limited spacecraft and mission resources impose severe constraints and tradeoffs. In order to maximize science return while mitigating risk for a satellite concept, it is essential to understand the scaling behavior of snow in terms of what the sensor sees (brightness temperature) as well as in terms of the actual variability of snow. NASA's Cold Land Processes Experiment-1 (CLPX-1: Colorado, 2002 and 2003) was designed to provide data to measure these scaling behaviors for varying snow conditions in areas with forested, alpine, and meadow/pasture land cover. We will use observations from CLPX-1 ground, airborne, and satellite passive microwave sensors to examine and evaluate the scaling behavior of observed and modeled brightness temperatures and observed and retrieved snow parameters across scales from meters to 10's of kilometers. The conclusions will provide direct examples of the appropriate spatial sampling scales of new sensors for snow remote sensing. The analyses will also illustrate the effects and spatial scales of the underlying phenomena (e.g., land cover) that control subpixel heterogeneity.

Kim, Edward J.↗

Cold air outbreak during MASEX - Lidar observations and boundary-layer model test

Lidar observations of boundary-layer development during a cold air outbreak over the Atlantic Ocean were examined. Very rapid rise rates were measured in the first 20 km off the coast. A large region of partial cloudiness was found to exist between the totally clear region near shore and the overcast region far from the coast. As the layer became overcast, rise rate of the boundary layer tripled, suggesting a direct relation between cloudiness and entrainment. Boundary-layer evolution was reasonably well simulated by a simple slab model. The model was not capable of predicting the area of partial cloudiness, nor the region of rapid entrainment near the coast.

Boers, R.↗

Observational constraints on model atmospheres for Uranus and Neptune

We have re-examined the visible and near-IR regions of the spectra of Uranus and Neptune to provide additional data for constructing atmospheric models. We find that a true continuum exists only at wavelengths below 4700 A, that the 6420 A absorption previously attributed to hydrogen is probably caused by methane, that there is no evidence for ammonia, ethylene or ethane absorptions in our spectra, and that the abundance of methane is probably much higher than previous estimates suggest. This last finding implies that the value of H/C in the atmospheres of both planets is much less than 1/10 the solar (or Jovian) value. Clear, Rayleigh-scattering model atmospheres are not compatible with the observations, but more work is needed to establish viable alternatives.

Encrenaz, T.↗

Quantifying the benefits of improved satellite remote-sensing observations for inverse modeling of NOx and NMVOC emissions

This study aims to demonstrate the benefits of using novel high spatiotemporal retrieval products from newer satellites for top-down emission estimates of nitrogen oxides (NO x ) and non-methane volatile organic compounds (NMVOCs) for the summer of 2019 over the contiguous United States. Recent satellite retrievals have not only advanced spatiotemporal resolution but also greatly reduced error and uncertainty due to reduced noise in the retrievals compared to spaceborne sensors launched in the past. We applied inverse modeling techniques using tropospheric nitrogen dioxide (NO 2 ) and formaldehyde (H-CHO) column retrieval products from the Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) in conjunction with the Weather Research Forecast and Community Multiscale Air Quality Modeling system (WRF-CMAQ). In order to provide a better representation of background chemical composition and avoid misalignment of emission adjustment, we applied monthly scaling factors for ozone (O 3 ) and CO boundary concentrations in addition to the inclusion of lightning and aviation emissions. Satellite-constrained NO x and NMVOCs posterior emissions showed a mitigated discrepancy between observed and modeled columns. The improvement in the model performance was greater when using TROPOMI, primarily benefiting from reduced errors/biases of the satellite retrievals that enabled us to explore corresponding changes in O 3 concentrations and production sensitivity regimes using the ratio of H-CHO and NO 2 .

remote sensing↗

A model of the Venus atmosphere from radio, radar, and occultation observations

A model is presented of the atmosphere and surface of Venus which best fits in the least-squares sense the available radio-brightness, radar cross-section, radio interferometric, and Mariner 5 and 10 radio occultation observations. The determinations of the radius of the planet obtained by others from radar time-delay measurements are included in the data set. The values of the adjusted parameters are: molar fraction of CO2 = 95 plus or minus 3%; fraction of combined nitrogen and argon = 5 plus or minus 3%; total atmospheric opacity at a wavelength of 1 cm = 19.4 plus or minus 1.3; mean radius of the surface = 6050.7 plus or minus 0.8 km; mean dielectric constant of the surface = 4.1 plus or minus 0.2, and percentage of total opacity due to chemical species other than CO2 = 45 plus or minus 12. The model temperature and pressure at the mean surface are 755 K and 91.4 atm, respectively.

Muhleman, D. O.↗

A theoretical model study of observed correlations between whistler mode waves and energetic electron precipitation events in the magnetosphere

A recently extended test particle computer model of the gyroresonance wave-particle interaction in the magnetosphere is applied to previously reported cases of observed correlations between whistler mode waves and ionospheric responses to particle precipitation. Three different ionospheric effects, namely, X-ray bursts, photoemissions, and D region perturbations, all correlated with VLF waves and believed to be caused by precipitated particles, are considered. The precipitation flux level, the pulse shape, and the associated time delays are computed for the parameters relevant to each case and are compared with values deduced from the data. The results demonstrate that the existing theoretical model can be useful for interpreting experimental results of this kind. Furthermore, the model results and observations, used together, provide a basis for additional diagnostics of the various parameters of the cold and energetic particle distributions in the magnetosphere. For example, when applied to the observed photoemission case (Helliwell et al., 1980) the model results imply that the trapped energetic particle distribution function at the time could be modeled as proportional to E exp -n/2 with n about 3.5 to 6, where E is the particle energy.

Chang, H. C.↗

Excessive Subsidence of the Southeast Atlantic Biomass Burning Aerosol Plume in the NASA Goddard Earth Observing System (GEOS) Model

Global models struggle to accurately represent the meteorological environment over the Southeast Atlantic Ocean, as evidenced by the poor representation of persistent marine stratocumulus decks off the west coast of southern Africa. This complex regime also experiences significant seasonal biomass burning aerosol plumes that are transported from southern Africa over the Atlantic Ocean, which gradually descend via large scale subsidence and interact radiatively and microphysically with the cloudy environment of the region. In comparisons to space borne lidar and aircraft observations we find that the NASA Goddard Earth Observing System (GEOS) model’s MERRA-2 aerosol and meteorology reanalysis shows that the aerosol plume descends too rapidly due to exaggerated large-scale downward vertical motion. This complicates the evaluation of aerosol properties utilizing aircraft observations collected throughout the ORACLES campaign as well as the model’s representation of the heating rate profiles due to the aerosol itself and its radiative interaction with the semi-permanent cloud deck typically located lower in altitude than the smoke. Two types of modeling experiments using GEOS will be presented to diagnose deficiencies in the model related to the excessive subsidence. Ensembles of free-running model simulations with and without radiatively active biomass burning aerosol will be used to quantify the impact of smoke on the atmospheric circulation. It will be demonstrated that heating within the aerosol layer results in self lofting through a reduction of the subsidence but did not alter the vertical placement or speed of the African Easterly jet. The amount of aerosol absorption required to eliminate the bias in the height of the aerosol plume through self-lofting will then be quantified. Finally, a second type of modeling experiment will be discussed in which the meteorology is constrained to observations. This will allow for biases in the height of the aerosol plume due to the general circulation model to be distinguished from biases that may be induced through the data assimilation process.

Allison Collow↗