Search NASA⌕ Search

SEARCH · Search NASA

Results for “Climate process”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Discovery of Carbonate-Rich Outcrops in the Gusev Crater Columbia Hills by the MER Rover Spirit

The chemical composition, global abundance, distribution, and formation pathways of carbonates are central to understanding aqueous processes, climate, and habitability of early Mars. The Mars Exploration Rover (MER) Spirit analyzed a series of olivine-rich outcrops while descending from the summit region of Husband Hill into the Inner Basin of the Columbia Hills of Gusev Crater to the eastern edge of the El Dorado ripple field in late 2005. Reanalysis of Spirit s mineralogical data from the Moessbauer Spectrometer (MB) and the Miniature Thermal Emission Spectrometer (Mini-TES) and chemical data from the Alpha Particle X-Ray Spectrometer (APXS) in 2010, coupled with new laboratory data for carbonate-bearing samples, lead to identification of carbonate in one of the outcrops (Comanche) [Morris, R.V., et al., Science, 329, 421-424]. The carbonate is rich in magnesium and iron (Mc62Sd25Cc11Rh2, assuming all Ca and Mn is associated with the carbonate) and is a major component of the Comanche outcrops (16 to 34 wt.%). The mineralogical, chemical, and abundance data are constrained in multiple, mutually consistent ways by the MER analyses. For example, a low-Ca carbonate is required by the MB and APXS data and is consistent with Mini-TES data. Three spectral features attributable to fundamental infrared vibrational modes of low-Ca carbonate are present in the Mini-TES spectra of Comanche outcrops. The average composition of Comanche carbonate approximates the average composition of the carbonate globules in Martian meteorite ALH 84001. Analogy with ALH 84001, terrestrial, and synthetic carbonate globules suggests that Comanche carbonate precipitated from aqueous solutions under hydrothermal conditions at near neutral pH in association with volcanic activity during the Noachian era. Comanche outcrop morphology suggests they are remnants of a larger carbonate-bearing formation that evolved in ultramafic rock and then preferentially eroded by a combination of aeolian abrasion and chemical decomposition by exposure to acid-sulfate vapors/solutions. The high carbonate concentration in the Comanche outcrops supports climate models involving a CO2 greenhouse gas on a wet and warm early Mars and subsequent sequestering of at least part of that atmosphere in carbonate minerals.

Morris, Richard V.↗
NASA NTRS2011

Atmospheric Constituents in GEOS-5: Components for an Earth System Model

The GEOS-S model is being developed for weather and climate processes, including the implementation of "Earth System" components. While the stratospheric chemistry capabilities are mature, we are presently extending this to include predictions of the tropospheric composition and chemistry - this includes CO2, CH4, CO, nitrogen species, etc. (Aerosols are also implemented, but are beyond the scope of this paper.) This work will give an overview of our chemistry modules, the approaches taken to represent surface emissions and uptake of chemical species, and some studies of the sensitivity of the atmospheric circulation to changes in atmospheric composition. Results are obtained through focused experiments and multi-decadal simulations.

Pawson, Steven↗
NASA NTRS2013

Analysis of CrIS-ATMS Data Using an AIRS Science Team Version 6 - Like Retrieval Algorithm

CrIS/ATMS is flying on NPP and is scheduled to fly on JPSS-1. CrIS/ATMS has roughly equivalent capabilities to AIRS/AMSU. The AIRS Science Team Version 6 retrieval algorithm is currently producing very high quality level-3 Climate Data Records (CDR's) that will be critical for understanding climate processes AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrIS/ATMS is the only scheduled follow on to AIRS AMSU. I have been asked by Ramesh Kakar if CrIS/ATMS can be counted on to adequately continue the AIRS/AMSU CDRs beyond 2020, or is something better needed? This research is being done to answer that question. A minimum requirement to obtain a yes answer is that CrIS/ATMS be analyzed using an AIRS Version 6 - like algorithm. NOAA is currently generating CrIS/ATMS products using 2 algorithms: IDPS and NUCAPS

Retrieval Algorithm↗
NASA NTRS2015

A Bispectral Composite Threshold Approach for Automatic Cloud Detection in VIIRS Imagery

The detection of clouds in satellite imagery has a number of important applications in weather and climate studies. The presence of clouds can alter the energy budget of the Earth‐atmosphere system through scattering and absorption of shortwave radiation and the absorption and re‐emission of infrared radiation at longer wavelengths. The scattering and absorption characteristics of clouds vary with the microphysical properties of clouds, hence the cloud type. Thus, detecting the presence of clouds over a region in satellite imagery is important in order to derive atmospheric or surface parameters that give insight into weather and climate processes. For many applications however, clouds are a contaminant whose presence interferes with retrieving atmosphere or surface information. In these cases, is important to isolate cloud‐free pixels, used to retrieve atmospheric thermodynamic information or surface geophysical parameters, from cloudy ones. This abstract describes an application of a two‐channel bispectral composite threshold (BCT) approach applied to VIIRS imagery. The simplified BCT approach uses only the 10.76 and 3.75 micrometer spectral channels from VIIRS in two spectral tests; a straight‐forward infrared threshold test with the longwave channel and a shortwave - longwave channel difference test. The key to the success of this approach as demonstrated in past applications to GOES and MODIS data is the generation of temporally and spatially dependent thresholds used in the tests from a previous number of days at similar observations to the current data. The paper and subsequent presentation will present an overview of the approach and intercomparison results with other satellites, methods, and against verification data.

LaFontaine Frank J.↗
NASA NTRS2010

Seven Years of Observations of Mid-Tropospheric CO2 from the Atmospheric Infrared Sounder

The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft was launched on May 4, 2002. AIRS acquires hyperspectral infrared radiances in the 3.7-15.4 um spectral region with spectral resolution of better than 1200. The AIRS was designed to measure temperature and water vapor profiles and cloud properties for improvement in weather forecast and improved parameterization of climate processes. Currently the AIRS Level 1B Radiance Products are assimilated by NWP centers and have shown considerable forecast improvement. Scientists have also demonstrated accurate retrievals of minor gases from AIRS including Carbon Monoxide, Methane, and Ozone. The excellent sensitivity and stability of the AIRS instrument has recently allowed the AIRS team to successfully retrieve Carbon Dioxide (CO2) concentrations in the mid-troposphere (8-10 km) with a horizontal resolution of 100 km and accuracy of 1-2 ppm. The AIRS retrieves over 15,000 measurements per day and can achieve full global coverage in 30 days. The AIRS CO2 accuracy has been validated against a variety of aircraft measurements in the mid-troposphere and upward looking interferometers. Findings from the AIRS data include higher than expected variability in the mid-troposphere, the presence of a belt of CO2 in the southern hemisphere, and numerous observations of atmospheric circulation including the effects of El Nino/La Nina on the CO2 concentrations in the mid-troposphere. The full mid-tropospheric AIRS CO2 data set is now available at the NASA GES/DISC for almost eight years since AIRS has been operational.

carbon dioxide↗
NASA NTRS2012

CARVE: The Carbon in Arctic Reservoirs Vulnerability Experiment

The Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) is a NASA Earth Ventures (EV-1) investigation designed to quantify correlations between atmospheric and surface state variables for the Alaskan terrestrial ecosystems through intensive seasonal aircraft campaigns, ground-based observations, and analysis sustained over a 5-year mission. CARVE bridges critical gaps in our knowledge and understanding of Arctic ecosystems, linkages between the Arctic hydrologic and terrestrial carbon cycles, and the feedbacks from fires and thawing permafrost. CARVE's objectives are to: (1) Directly test hypotheses attributing the mobilization of vulnerable Arctic carbon reservoirs to climate warming; (2) Deliver the first direct measurements and detailed maps of CO2 and CH4 sources on regional scales in the Alaskan Arctic; and (3) Demonstrate new remote sensing and modeling capabilities to quantify feedbacks between carbon fluxes and carbon cycle-climate processes in the Arctic (Figure 1). We describe the investigation design and results from 2011 test flights in Alaska.

Arctic Carbon Cycle↗
NASA NTRS2015

Joint Projections of US East Coast Sea Level and Storm Surge

Future coastal flood risk will be strongly influenced by sea-level rise (SLR) and changes in the frequency and intensity of tropical cyclones. These two factors are generally considered independently. Here, we assess twenty-first century changes in the coastal hazard for the US East Coast using a flood index (FI) that accounts for changes in flood duration and magnitude driven by SLR and changes in power dissipation index (PDI, an integrated measure of tropical cyclone intensity, frequency and duration). Sea-level rise and PDI are derived from representative concentration pathway (RCP) simulations of 15 atmosphere- ocean general circulation models (AOGCMs). By 2080-2099, projected changes in the FI relative to 1986-2005 are substantial and positively skewed: a 10th-90th percentile range 4-75 times higher for RCP 2.6 and 35-350 times higher for RCP 8.5. High-end Fl projections are driven by three AOGCMs that project the largest increases in SLR, PDI and upper ocean temperatures. Changes in PDI are particularly influential if their intra-model correlation with SLR is included, increasing the RCP 8.5 90th percentile FI by a further 25%. Sea-level rise from other, possibly correlated, climate processes (for example, ice sheet and glacier mass changes) will further increase coastal flood risk and should be accounted for in comprehensive assessments.

cyclones↗
NASA NTRS2016

Comparative Results of AIRS/AMSU and CrIS/ATMS Retrievals Using a Scientifically Equivalent Retrieval Algorithm

The AIRS Science Team Version-6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRS/AMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrIS/ATMS is the only scheduled follow on to AIRS/AMSU. The objective of this research is to prepare for generation of long term CrIS/ATMS CDRs using a retrieval algorithm that is scientifically equivalent to AIRS/AMSU Version-7.

AIRS AMSU↗
NASA NTRS2016

Early Spring Post-Fire Snow Albedo Dynamics in High Latitude Boreal Forests Using Landsat-8 OLI Data

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (less than 100 m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high-burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500 m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems.

Landsat-8 snow albedo↗
NASA NTRS2015

Improving AIRS Radiance Spectra in High Contrast Scenes Using MODIS

The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft was launched on May 4, 2002. AIRS acquires hyperspectral infrared radiances in 2378 channels ranging in wavelength from 3.7-15.4 microns with spectral resolution of better than 1200, and spatial resolution of 13.5 km with global daily coverage. The AIRS is designed to measure temperature and water vapor profiles for improvement in weather forecast accuracy and improved understanding of climate processes. As with most instruments, the AIRS Point Spread Functions (PSFs) are not the same for all detectors. When viewing a non-uniform scene, this causes a significant radiometric error in some channels that is scene dependent and cannot be removed without knowledge of the underlying scene. The magnitude of the error depends on the combination of non-uniformity of the AIRS spatial response for a given channel and the non-uniformity of the scene, but is typically only noticeable in about 1% of the scenes and about 10% of the channels. The current solution is to avoid those channels when performing geophysical retrievals. In this effort we use data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument to provide information on the scene uniformity that is used to correct the AIRS data. For the vast majority of channels and footprints the technique works extremely well when compared to a Principal Component (PC) reconstruction of the AIRS channels. In some cases where the scene has high inhomogeneity in an irregular pattern, and in some channels, the method can actually degrade the spectrum. Most of the degraded channels appear to be slightly affected by random noise introduced in the process, but those with larger degradation may be affected by alignment errors in the AIRS relative to MODIS or uncertainties in the PSF. Despite these errors, the methodology shows the ability to correct AIRS radiances in non-uniform scenes under some of the worst case conditions and improves the ability to match AIRS and MODIS radiances in non-uniform scenes.

spatial↗
NASA NTRS2018

Evaluation of the Land Surface Reflectance Fundamental Climate Data Record

The land surface reflectance is a fundamental climate data record at the basis of the derivation of other climate data records (Albedo, LAI/Fpar, Vegetation indices) and has been recognized as a key parameter in the understanding of the land-surface-climate processes. In this presentation, we present the validation of the Land surface reflectance used for MODIS, VIIRS, Landsat 8 and Sentinel 2 data. This methodology uses the 6SV Code and data from the AERONET network. The overall accuracy clearly reaches the satellite specifications. To understand how to improve the validation, we developed an exhaustive error budget. Results show an impact of the absorption of aerosol and of the fine mode volume concentration.

Atmospheric correction↗
NASA NTRSDate not supplied

A Study of Past, Present, and Future Mars Rotorcraft

Interest in utilizing rotorcraft to explore Mars is expected to increase following the anticipated successful technical demonstration of the Mars Helicopter, Ingenuity, during the Mars 2020 mission. Previously, science investigations have been limited by either the instrumentation resolution on orbiters or the roughness/accessibility of terrain a rover can traverse. Rotorcraft can enable low-altitude flight over and on-surface exploration at previously inaccessible locations. This paper describes potential mission concepts designed to utilize the unique capabilities of rotorcraft to advance the science performed in extraterrestrial environments. This includes missions tailored for investigating if Mars ever supported life, understanding climate processes and history, determining the evolution of Martian geology, and preparing for human exploration. The Mars rotorcraft mission concepts described in this paper can be divided into two categories: rover-assisted missions and independent (rotorcraft-only) missions. A number of concept vehicles, consistent with these proposed missions, are also discussed.

Study↗
NASA NTRS2022

Intercalibration of the reflective solar bands of MODIS and MISR instruments on the Terra platform

As a part of NASA’s Earth Observing System (EOS), the Terra spacecraft was launched on December 18, 1999, with the goal of understanding the changes of the Earth, by examining the Earth’s hydrological, geophysical, and climatic processes. The MODIS and MISR instruments on the Terra platform, combined with their continuous operation, broad spectral coverage, and different spatial resolutions, have played an important role to achieve the goals of the EOS. Over two decades of successful operations, these multispectral imaging instruments have benefited a variety of scientific applications. Being on the same platform, the two sensors complement each other in terms of spatial coverage (and target viewing geometry) and facilitate synergistic applications using multispectral data. A consistent radiometric calibration between these sensors is a prerequisite for creating high quality science products from their observations. Both instruments underwent intensive prelaunch characterization and their on-orbit calibrations are monitored using their onboard calibrators. In this paper, we perform a calibration inter-comparison of the spectrally matching bands of the two instruments using vicarious techniques. These techniques include multiyear simultaneous views of the North African desert, North Atlantic Ocean, and Dome Concordia, therefore covering different reflectance regimes. Also included in this work are the near-simultaneous top-of-atmosphere (TOA) reflectance measurements from Railroad Valley, USA, as provided by the RadCalNet (converted to TOA), that are used as a calibration reference to compare the on-orbit observations between MODIS and MISR. Simultaneous overpasses from desert, ocean, Dome C, and RadCalNet over Railroad Valley reveal that the agreement between the four spectrally matching bands is within 3% for the time-period between 2014 and 2020. Also, observed are some long-term drifts in the TOA reflectance time-series from MISR for the red and NIR band that are expected to be corrected in a future calibration reprocess.

MODIS↗
NASA NTRS2022

Technical Note: On Seasonal Variability of the M2 Tide

Seasonal variability of the M2 ocean tide can be detected at many ports, perhaps most. Examination of the cluster of tidal constituents residing within the M2 tidal group can shed light on the physical mechanisms underlying seasonality. In the broadest terms these are astronomical, frictional–advective interactions, and climate processes; some induce annual modulations and some semiannual, in amplitude, phase, or both. This note reviews how this occurs and gives an example from each broad category. Phase conventions and their relationship with causal mechanisms, as well as nomenclature, are also addressed.

Richard D Ray↗
DOE OSTI2025

Warming Permafrost Model Intercomparision Project (WrPMIP): Pan-Arctic Perturbation Warming Simulations

Title: Warming Permafrost Model Intercomparision Project (WrPMIP): Pan-Arctic Perturbation Warming Simulations Description: WrPMIP Pan-Arctic simulations including historial baseline and two warming simulations. Models were perturbed similarly to known experimental warming trials that have been implemented across the Pan-Arctic over the last several decades. More information about the dataset can be found at the following links: https://warmingpermafrost.nau.edu/ The dataset is available at: https://esgf-node.ornl.gov/search/project=WrPMIP&mip_era=CMIP6&activity_id=WrPMIP

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Sensitivity of Arctic Clouds to Ice Microphysical Processes in the NorESM2 Climate Model

Abstract Ice formation remains one of the most poorly represented microphysical processes in climate models. While primary ice production (PIP) parameterizations are known to have a large influence on the modeled cloud properties, the representation of secondary ice production (SIP) is incomplete and its corresponding impact is therefore largely unquantified. Furthermore, ice aggregation is another important process for the total cloud ice budget, which also remains largely unconstrained. In this study, we examine the impact of PIP, SIP, and ice aggregation on Arctic clouds, using the Norwegian Earth System Model, version 2 (NorESM2). Simulations with both prognostic and diagnostic PIP show that heterogeneous freezing alone cannot reproduce the observed cloud ice content. The implementation of missing SIP mechanisms (collisional breakup, drop shattering, and sublimation breakup) in NorESM2 improves the modeled ice properties, while improvements in liquid content occur only in simulations with prognostic PIP. However, results are sensitive to the description of collisional breakup. This mechanism, which dominates SIP in the examined conditions, is very sensitive to the treatment of the sublimation correction factor, a poorly constrained parameter that is included in the utilized parameterization. Finally, variations in ice aggregation treatment can also significantly impact cloud properties, mainly through their impact on collisional breakup efficiency. Overall, enhancement in ice production through the addition of SIP mechanisms and the reduction in ice aggregation (in line with radar observations of shallow Arctic clouds) result in enhanced cloud cover and decreased TOA radiation biases, compared to satellite measurements, especially during the cold months. Significance Statement Arctic clouds remain a large source of uncertainty in projections of the future climate due to the poor representation of the microphysical processes that govern their life cycle. Ice formation is among the least understood processes. While it is widely recognized that better constraints on primary ice production (PIP) are needed to improve existing parameterizations, we show that secondary ice production (SIP) and ice aggregation can have also a significant impact on ice number concentrations. Constraining ice formation through the addition of missing SIP mechanisms and reducing ice aggregation can improve the representation of the cloud macrophysical properties and enhance total cloud cover in the Arctic region, which in turn contributes to decreased TOA radiation biases in the cold months.

Meteorology & Atmospheric Sciences↗
NASA NTRS2008

Climate Model Evaluation using New Datasets from the Clouds and the Earth's Radiant Energy System (CERES)

There are some in the science community who believe that the response of the climate system to anthropogenic radiative forcing is unpredictable and we should therefore call off the quest . The key limitation in climate predictability is associated with cloud feedback. Narrowing the uncertainty in cloud feedback (and therefore climate sensitivity) requires optimal use of the best available observations to evaluate and improve climate model processes and constrain climate model simulations over longer time scales. The Clouds and the Earth s Radiant Energy System (CERES) is a satellite-based program that provides global cloud, aerosol and radiative flux observations for improving our understanding of cloud-aerosol-radiation feedbacks in the Earth s climate system. CERES is the successor to the Earth Radiation Budget Experiment (ERBE), which has widely been used to evaluate climate models both at short time scales (e.g., process studies) and at decadal time scales. A CERES instrument flew on the TRMM satellite and captured the dramatic 1998 El Nino, and four other CERES instruments are currently flying aboard the Terra and Aqua platforms. Plans are underway to fly the remaining copy of CERES on the upcoming NPP spacecraft (mid-2010 launch date). Every aspect of CERES represents a significant improvement over ERBE. While both CERES and ERBE measure broadband radiation, CERES calibration is a factor of 2 better than ERBE. In order to improve the characterization of clouds and aerosols within a CERES footprint, we use coincident higher-resolution imager observations (VIRS, MODIS or VIIRS) to provide a consistent cloud-aerosol-radiation dataset at climate accuracy. Improved radiative fluxes are obtained by using new CERES-derived Angular Distribution Models (ADMs) for converting measured radiances to fluxes. CERES radiative fluxes are a factor of 2 more accurate than ERBE overall, but the improvement by cloud type and at high latitudes can be as high as a factor of 5. Diurnal cycles are explicitly resolved by merging geostationary satellite observations with CERES and MODIS. Atmospheric state data are provided from a frozen version of the Global Modeling and Assimilation Office- Data Assimilation System at the NASA Goddard Space Flight Center. In addition to improving the accuracy of top-of-atmosphere (TOA) radiative fluxes, CERES also produces radiative fluxes at the surface and at several levels in the atmosphere using radiative transfer modeling, constrained at the TOA by CERES (ERBE was limited to the TOA). In all, CERES uses 11 instruments on 7 spacecraft all integrated to obtain climate accuracy in TOA to surface fluxes. This presentation will provide an overview of several new CERES datasets of interest to the climate community (including a new adjusted TOA flux dataset constrained by estimates of heat storage in the Earth system), show direct comparisons between CERES ad ERBE, and provide a detailed error analysis of CERES fluxes at various time and space scales. We discuss how observations can be used to reduce uncertainties in cloud feedback and climate sensitivity and strongly argue why we should NOT "call off the quest".

Loeb, Norman G.↗
NASA NTRS1991

Global climate change

Present processes of global climate change are reviewed. The processes determining global temperature are briefly described and the concept of effective temperature is elucidated. The greenhouse effect is examined, including the sources and sinks of greenhouse gases.

Levine, Joel S.↗