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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.

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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Constraints on Variability of Brightness and Surface Magnetism on Time Scales of Decades to Centuries in the Sun and Sun-Like Stars: A Source of Potential Terrestrial Climate Variability

These four points summarize our work to date. (1) Conciliation of solar and stellar photometric variability. Previous research by us and colleagues suggested that the Sun might at present be showing unusually low photometric variability compared to other sun-like stars. Those early results would question the suitability of the technique of using sun-like stars as proxies for solar irradiance change on time scales of decades to centuries. However, our results indicate the contrary: the Sun's observed short-term (seasonal) and longterm (year-to-year) brightness variations closely agree with observed brightness variations in stars of similar mass and age. (2) We have demonstrated an inverse correlation between the global temperature of the terrestrial lower troposphere, inferred from the NASA Microwave Sounding Unit (MSU) radiometers, and the total area of the Sun covered by coronal holes from January 1979 to present (up to May 2000). Variable fluxes of either solar charged particles or cosmic rays, or both, may influence the terrestrial tropospheric temperature. The geographical pattern of the correlation is consistent with our interpretation of an extra-terrestrial charged particle forcing. (3) Possible climate mechanism amplifying the impact of solar ultraviolet irradiance variations. The key points of our proposed climate hypersensitivity mechanism are: (a) The Sun is more variable in the UV (ultraviolet) than in the visible. However, the increased UV irradiance is mainly absorbed in the lower stratosphere/upper troposphere rather than at the surface. (b) Absorption in the stratosphere raises the temperature moderately around the vicinity of the tropopause, and tends to stabilize the atmosphere against vertical convective/diffusive transport, thus decreasing the flux of heat and moisture carried upward from surface. (c) The decrease in the upward convection of heat and moisture tends to raise the surface temperature because a drier upper atmosphere becomes less cloudy, which in turn allows more solar radiation to reach the Earth's surface. (4) Natural variability in an ocean-atmosphere climate model. We use a 14-region, 6-layer, global thermo-hydrodynamic ocean-atmosphere model to study natural climate variability. All the numerical experiments were performed with no change in the prescribed external boundary conditions (except for the seasonal cycle of the Sun's tilt angle). Therefore, the observed inter-annual variability is of an internal kind. The model results are helpful toward the understanding of the role of nonlinearity in climate change. We have demonstrated a range of possible climate behaviors using our newly developed ocean-atmosphere model. These include climate configurations with no interannual variability, with multi-year periodicities, with continuous chaos, or with chaotically occuring transitions between two discrete substrates. These possible modes of climate behavior are all possible for the real climate, as well as the model. We have shown that small temporary climate influences can trigger shifts both in the mean climate, and among these different types of behavior. Such shifts are not only theoretically plausible, as shown here and elsewhere; they are omnipresent in the climate record on time scales from several years to the age of the Earth. This has two apparently opposite implications for the possibility of anthropogenic global warming. First, any warming which might occur as a result of human influence would be only a fraction of the small-to-large unpredictable natural changes and changes which result from other external causes. On the other hand, small temporary influences such as human influence do have the potential of causing large permanent shifts in mean climate and interannual variability.

Baliunas, Sallie L.↗
NASA NTRS2018

Constraining the Models' Response of Tropical Clouds to SST Forcings Using CALIPSO Observations

Here we present preliminary results from the analysis of the low cloud cover (LCC) and cloud radiative effect (CRE) interannual changes in response to sea surface temperature (SST) forcings in two GISS climate models, and 12 other climate models. We further classify them as a function of their ability to reproduce the vertical structure of the cloud response to SST change against 10 years of CALIPSO observations: “the constrained models, which match the observation constraint, and the unconstrained models”. The constrained models replicate the observed interannual LCC change particularly well (ΔLCC(sub con)=-3.49 ±1.01 %/K vs. ΔLCC(sub obs)=-3.59 ±0.28 %/K) as opposed to the unconstrained models, which largely underestimate it (ΔLCC(sub unc) = -1.32 ± 1.28 %/K). As a result, the amount of short-wave warming simulated by the constrained models (ΔCRE(sub con)=2.60 ±1.13 W/m2/K) is in better agreement with the observations (ΔCRE(sub obs)=3.05 ±0.28 W/m2/K) than the unconstrained models (ΔCRE(sub con)=0.87 ±2.63 W/m2/K). Depending on the type of low cloud, the observed relationship between cloud/radiation and surface temperature varies. Over the stratocumulus regions, increasing SSTs generate higher cloud top height along with a large decrease of the cloud fraction below as opposed to a slight decrease of the cloud fraction at each level over the trade cumulus regions. Our results suggest that the models must generate sustainable stratocumulus decks and moist processes in the planetary boundary layer to reproduce these observed features. Future work will focus on defining a method to objectively discriminate these cloud types that can be applied consistently in both the observations and the models.

Cesana, Gregory↗
NASA NTRS2012

The GEOS-5 Atmospheric General Circulation Model: Mean Climate and Development from MERRA to Fortuna

This report is a documentation of the Fortuna version of the GEOS-5 Atmospheric General Circulation Model (AGCM). The GEOS-5 AGCM is currently in use in the NASA Goddard Modeling and Assimilation Office (GMAO) for simulations at a wide range of resolutions, in atmosphere only, coupled ocean-atmosphere, and data assimilation modes. The focus here is on the development subsequent to the version that was used as part of NASA s Modern-Era Retrospective Analysis for Research and Applications (MERRA). We present here the results of a series of 30-year atmosphere-only simulations at different resolutions, with focus on the behavior of the 1-degree resolution simulation. The details of the changes in parameterizations subsequent to the MERRA model version are outlined, and results of a series of 30-year, atmosphere-only climate simulations at 2-degree resolution are shown to demonstrate changes in simulated climate associated with specific changes in parameterizations. The GEOS-5 AGCM presented here is the model used for the GMAO s atmosphere-only and coupled CMIP-5 simulations.

Molod, Andrea↗
NASA NTRS2023

Considering Soil Moisture in Models of Climate Impacts on Child Health in Farming-Centric Countries

Soil moisture reflects the amount of water available to crops in the top layer of soil. As such, considering soil moisture provides important insight into water availability and ultimately crop yields in agricultural settings. In studies of climate change, food security, and health, however, soil moisture is rarely empirically considered despite its connection to crop health and yields. In this project, we aim to advance understanding of climate impacts on food security by incorporating soil moisture into quantitative models of child health. Combining spatially referenced health survey data from the Demographic and Health Surveys for 2005 and 2010 in Senegal and 2007, 2011, and 2014 in Bangladesh, with soil moisture data from the Famine Early Warning System Network Land Data Assimilation System, we explore the linkages between sub-annual and sub-seasonal climate conditions and child malnutrition in two rainfed agriculture dependent countries—Bangladesh and Senegal. Results suggest that soil moisture, measured on very short time scales, may be associated with reductions in anthropometric weight-for-height z-scores, but the relationship is highly dependent upon geographic context.

Child health↗
NASA NTRS2021

The MJO-QBO Relationship in a GCM with Stratospheric Nudging

Observational studies show a strong connection between the intraseasonal Madden-Julian oscillation (MJO) and the stratospheric quasi-biennial oscillation (QBO): the boreal winter MJO is stronger, more predictable, and has different teleconnections when the QBO in the lower stratosphere is easterly versus westerly. Despite the strength of the observed connection, global climate models do not produce an MJO-QBO link. Here the authors use a current-generation ocean-atmosphere coupled NASA Goddard Institute for Space Studies global climate model (Model E2.1) to examine the MJO-QBO link. To represent the QBO with minimal bias, the model zonal mean stratospheric zonal and meridional winds are relaxed to reanalysis fields from 1980-2017. The model troposphere, including the MJO, is allowed to freely evolve. The model with stratospheric nudging captures QBO signals well, including QBO temperature anomalies. However, an ensemble of nudged simulations still lacks an MJO-QBO connection.

Madden-Julian oscillation (MJO)↗
NASA NTRS2015

The Mars Dust and Water Cycles: Investigating the Influence of Clouds on the Vertical Distribution and Meridional Transport of Dust and Water.

The dust and water cycles are critical to the current Martian climate, and they interact with each other through cloud formation. Dust modulates the thermal structure of the atmosphere and thus greatly influences atmospheric circulation. Clouds provide radiative forcing and control the net hemispheric transport of water through the alteration of the vertical distributions of water and dust. Recent advancements in the quality and sophistication of both climate models and observations enable an increased understanding of how the coupling between the dust and water cycles (through cloud formation) impacts the dust and water cycles. We focus here on the effects of clouds on the vertical distributions of dust and water and how those vertical distributions control the net meridional transport of water. We utilize observations of temperature, dust and water ice from the Mars Climate Sounder (MCS) on the Mars Reconnaissance Orbiter (MRO) and the NASA ARC Mars Global Climate Model (MGCM) to show that the magnitude and nature of the hemispheric exchange of water during NH summer is sensitive to the vertical structure of the simulated aphelion cloud belt. Further, we investigate how clouds influence atmospheric temperatures and thus the vertical structure of the cloud belt. Our goal is to isolate and understand the importance of radiative/dynamic feedbacks due to the physical processes involved with cloud formation and evolution on the current climate of Mars.

NASA ARC Mars Global Climate Model (MGCM)↗
DOE OSTI2025

A review of future weather data for assessing climate change impacts on buildings and energy systems

The effectiveness of climate change impact assessments and the development of adaptation strategies depend on the availability of high-quality future weather data. However, significant gaps exist between the needs of the energy research community and the focus of the climate modeling community, primarily due to a historical lack of communication and collaboration between the two groups. Here, to address this issue, this work provides a comprehensive overview of the critical aspects involved in creating future weather data for building and energy system modeling, including emissions scenarios, general circulation models, downscaling methods, categories of future weather data, and uncertainties in climate simulations. Moreover, it critically evaluates the applicability and suitability of various types of future weather data in five key application scenarios: energy use analysis, resilience analysis, HVAC design, utility-scale analysis, and renewable energy analysis. Finally, this work presents recommendations for high-level actions and research directions to foster collaboration between the energy research and climate modeling communities and to promote the integration of future weather data into energy codes and the design practices of buildings and energy systems.

Climate change↗
NASA NTRS1998

Atmospheric Solar Heating in Minor Absorption Bands

Solar radiation is the primary source of energy driving atmospheric and oceanic circulations. Concerned with the huge computing time required for computing radiative transfer in weather and climate models, solar heating in minor absorption bands has often been neglected. The individual contributions of these minor bands to the atmospheric heating is small, but collectively they are not negligible. The solar heating in minor bands includes the absorption due to water vapor in the photosynthetically active radiation (PAR) spectral region from 14284/cm to 25000/cm, the ozone absorption and Rayleigh scattering in the near infrared, as well as the O2 and CO2 absorption in a number of weak bands. Detailed high spectral- and angular-resolution calculations show that the total effect of these minor absorption is to enhance the atmospheric solar heating by approximately 10%. Depending upon the strength of the absorption and the overlapping among gaseous absorption, different approaches are applied to parameterize these minor absorption. The parameterizations are accurate and require little extra time for computing radiative fluxes. They have been efficiently implemented in the various atmospheric models at NASA/Goddard Space Flight Center, including cloud ensemble, mesoscale, and climate models.

Chou, Ming-Dah↗
DOE OSTI2024

Steric Sea Level Rise and Relationships with Model Drift and Water Mass Representation in GFDL CM4 and ESM4

Abstract Density-driven steric seawater changes are a leading-order contributor to global mean sea level rise. However, intermodel differences in the magnitude and spatial patterns of steric sea level rise exist at regional scales and often emerge during the spinup and preindustrial control integrations of climate models. Steric sea level results from an eddy-permitting climate model, GFDL CM4, are compared with a lower-resolution counterpart, GFDL-ESM4. The results from both models are examined through basin-scale heat budgets and watermass analysis, and we compare the patterns of ocean heat uptake, redistribution, and sea level differ in ocean-only [i.e., Ocean Model Intercomparison Project (OMIP)] and coupled climate configurations. After correcting for model drift, both GFDL CM4 and GFDL-ESM4 simulate nearly equivalent ocean heat content change and global sea level rise during the historical period. However, the GFDL CM4 model exhibits as much as a 40% increase in surface ocean heat uptake in the Southern Ocean and subsequent increases in horizontal export to other ocean basins after bias correction. The results suggest regional differences in the processes governing Southern Ocean heat export, such as the formation of Antarctic Intermediate Water (AAIW), Subpolar Mode Water (SPMW), and gyre transport between the two models, and that sea level changes in these models cannot be fully bias-corrected. Since the process-level differences between the two models are evident in the preindustrial control simulations of both models, these results suggest that the control simulations are important for identifying and correcting sea level–related model biases.

Krasting, John P. [a NOAA/OAR/Geophysical Fluid Dy↗
NASA NTRS2012

Projections of Declining Surface-Water Availability for the Southwestern United States

16 of the CMIP5 models had all the data needed for this work for at least one simulation that was continuous from 1950 to 2040. Details of the models analyzed here are provided in Table S1. The model data analyzed here are available at http://strega.ldeo.columbia.edu:81/expert/home/.naomi/.AR5/.v2/.historical:rcp85/.mmm16/ a. Assessing the climatology of the models Despite increases in horizontal resolution of many models compared to their CMIP3 counterparts none of these models can adequately resolve the topography of the south west United States, such as the Sierra Nevada and Rocky Mountains and the associated orographic precipitation. This requires that caution be used when interpreting the results presented here. To assess the ability of the models to simulate the current hydroclimate, in Figure S1 we show the observed (from the Global Precipitation Climatology Centre gridded rain gauge data, (1)) monthly climatology of precipitation and the same for all the models and the multimodel mean for the California-Nevada, Colorado headwaters and Texas regions. The GPCC data uses rain gauges only and interpolates to regular grids of which we used the 1◦ by 1◦ one. Details of the data set can be found in (2). While the models apparently overestimate precipitation in California and Nevada the seasonal cycle with wet winters and dry summers is very well represented. It is also possible that the rain gauge observations are biased low by inadequately sampling the higher mountain regions. How ever the models might also be expected to underestimate orographic precipitation due to inadequate horizontal resolution. The 25 models are also too wet in the Colorado headwaters region but correctly represent the quite even distribution though the year. The bimodal distribution of precipitation in Texas, with peaks in May and September, and the absolute amounts, are well modeled but with the September peak too weak. The positive precipitation bias translates into a positive runoff bias for the Colorado headwaters as also shown in Figure S1. Here the observed runoff values are taken from simulations of the Variable Infiltration Capacity (VIC) land surface-hydrology model (3) forced by observed meteorology (5) that were conducted as part of the North American Land Data Assimilation System project phase 2 ( (NLDAS-2), http://www.emc.ncep.noaa.gov/mmb/nldas/. Runoff for California-Nevada is better simulated but there is a positive bias over Texas despite no strong precipitation bias. To check whether regional climate models better simulate P and runoff in these regions we analyzed the historical simulation with the Regional Climate Model version 3 driven by the National Centers for Environmental Prediction-Department of Energy Reanalysis 2 available from the North American Regional Climate Change Assessment Program (http://www.narccap.ucar.edu). This model configuration retained these biases in P and runoff although they were reduced in amplitude. Given these varying biases we plot P and P − E changes in actual values but apply the simplest bias correction possible to the runoff and soil moisture values and show the modeled changes in terms of percentages of the 20th Century model climatologies. A thorough assessment of the simulation of North American climate in CMIP5 models is conducted in Sheffield at al. (North American Climate in CMIP5 Experiments. Part I: Evaluation of 20th Century Continental and Regional Climatology, manuscript submit ted to J. Climate, available at http://www.climate.noaa.gov/index.jsp?pg=./cpo pa/ mapp/cmip5 publications.html). Sheffield et al. analyze the climatology of precipitation, surface air temperature, low level winds, moisture fluxes, runoff etc. and conclude that the main features of the hydrological cycle, including characteristics of the atmospheric moisture balance and its seasonality, are captured in the CMP5 models subject to biases in total precipitation amounts. We chose to use all available models instead of selecting some and rejecting others based on an assessment of model realism. This is in accord with the suggestions of Mote et al. for CMIP3 (4) but future work needs to revisit this matter for the case of the CMIP5 ensemble.

Seager, Richard↗
NASA NTRS2016

The Pliocene Model Intercomparison Project (PlioMIP) Phase 2: Scientific Objectives and Experimental Design

The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, as well as their potential relevance in the context of future climate change. PlioMIP examines the consistency of model predictions in simulating Pliocene climate and their ability to reproduce climate signals preserved by geological climate archives. Here we provide a description of the aim and objectives of the next phase of the model intercomparison project (PlioMIP Phase 2), and we present the experimental design and boundary conditions that will be utilized for climate model experiments in Phase 2. Following on from PlioMIP Phase 1, Phase 2 will continue to be a mechanism for sampling structural uncertainty within climate models. However, Phase 1 demonstrated the requirement to better understand boundary condition uncertainties as well as uncertainty in the methodologies used for data-model comparison. Therefore, our strategy for Phase 2 is to utilize state-of-the-art boundary conditions that have emerged over the last 5 years. These include a new palaeogeographic reconstruction, detailing ocean bathymetry and land-ice surface topography. The ice surface topography is built upon the lessons learned from offline ice sheet modelling studies. Land surface cover has been enhanced by recent additions of Pliocene soils and lakes. Atmospheric reconstructions of palaeo-CO2 are emerging on orbital timescales, and these are also incorporated into PlioMIP Phase 2. New records of surface and sea surface temperature change are being produced that will be more temporally consistent with the boundary conditions and forcings used within models. Finally we have designed a suite of prioritized experiments that tackle issues surrounding the basic understanding of the Pliocene and its relevance in the context of future climate change in a discrete way.

climate models↗
DOE OSTI2024

An overview of the E3SM version 2 large ensemble and comparison to other E3SM and CESM large ensembles

Abstract. This work assesses a recently produced 21-member climate model large ensemble (LE) based on the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) version 2 (E3SM2). The ensemble spans the historical era (1850 to 2014) and 21st century (2015 to 2100), using the SSP370 pathway, allowing for an evaluation of the model's forced response. A companion 500-year preindustrial control simulation is used to initialize the ensemble and estimate drift. Characteristics of the LE are documented and compared against other recently produced ensembles using the E3SM version 1 (E3SM1) and Community Earth System Model (CESM) versions 1 and 2. Simulation drift is found to be smaller, and model agreement with observations is higher in versions 2 of E3SM and CESM versus their version 1 counterparts. Shortcomings in E3SM2 include a lack of warming from the mid to late 20th century, likely due to excessive cooling influence of anthropogenic sulfate aerosols, an issue also evident in E3SM1. Associated impacts on the water cycle and energy budgets are also identified. Considerable model dependence in the response to both aerosols and greenhouse gases is documented and E3SM2's sensitivity to variable prescribed biomass burning emissions is demonstrated. Various E3SM2 and CESM2 model benchmarks are found to be on par with the highest-performing recent generation of climate models, establishing the E3SM2 LE as an important resource for estimating climate variability and responses, though with various caveats as discussed herein. As an illustration of the usefulness of LEs in estimating the potential influence of internal variability, the observed CERES-era trend in net top-of-atmosphere flux is compared to simulated trends and found to be much larger than the forced response in all LEs, with only a few members exhibiting trends as large as observed, thus motivating further study.

58 GEOSCIENCES↗
NASA NTRS2015

Interannual Variability of Tropospheric Trace Gases and Aerosols: The Role of Biomass Burning Emissions

Fires are responsible for a range of gaseous and aerosol emissions. However, their influence on the interannual variability of atmospheric trace gases and aerosols has not been systematically investigated from a global perspective. We examine biomass burning emissions as a driver of interannual variability of large-scale abundances of short-lived constituents such as carbon monoxide (CO), hydroxyl radicals (OH), ozone and aerosols using the GISS ModelE composition-climate model and a range of observations, with an emphasis on satellite information. Our model captures the observed variability of the constituents examined in most cases, but with substantial underestimates in boreal regions. The strongest interannual variability on a global scale is found for carbon monoxide (10 for its global annual burden), while the lowest is found for tropospheric ozone (10 for its global annual burden). Regionally, aerosol optical depth shows variability that exceeds 50. Areas of strong variability include the tropical land regions and northern high latitudes, while even regions in the northern midlatitudes experience substantial inteannual variability of aerosols. Ozone variability peaks over Equatorial Asia in boreal autumn, partly due to varying biomass burning emissions, and over the western and central Pacific in the rest of the year, mainly due to meteorological fluctuations. We find that biomass burning emissions are almost entirely responsible for global CO interannual variability, and similarly important for OH variability. The same is true for global and regional aerosol variability, especially when not taking into account dust and sea-salt particles. We show that important implications48 can arise from such interannual influences for regional climate and air quality.

aerosols↗
DOE OSTI2024

An Evaluation of Dynamical Downscaling Methods Used to Project Regional Climate Change

In the past decade, dynamical downscaling using “pseudo-global-warming” (PGW) techniques has been applied frequently to project regional climate change. Such techniques generate signals by adding mean global climate model (GCM)-simulated climate change signals in temperature, moisture, and circulation to lateral and surface boundary conditions derived from reanalysis. An alternative to PGW is to downscale GCM data directly. This technique should be advantageous, especially for simulation of extremes, since it incorporates the GCM's full spectrum of changing synoptic-scale dynamics in the regional solution. Here, we test this assumption, by comparing simulations in Europe and Western North America. We find that for warming and changes in temperature extremes, PGW often produces similar results to direct downscaling in both regions. For mean and extreme precipitation changes, PGW generally also performs surprisingly well in many cases. Moisture budget analysis in the Western North America domain reveals why. Large fractions of the downscaled hydroclimate changes arise from mean changes in large-scale thermodynamics and circulation, that is, increases in temperature, moisture, and winds, included in PGW by design. The one component PGW may have difficulty with is the contribution from changes in synoptic-scale variability. When this component is large, PGW performance could be degraded. Global analysis of GCM data shows there are regions where it is large or dominant. Hence, our results provide a road map to identify, through GCM analyses, the circumstances when PGW would not be expected to accurately regionalize GCM climate signals.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Obliquity variation in a Mars climate evolution model

The existence of layered terrain in both polar regions of Mars is strong evidence supporting a cyclic variation in climate. It has been suggested that periods of net deposition have alternated with periods of net erosion in creating the layered structure that is seen today. The cause for this cyclic climatic behavior is variation in the annually averaged latitudinal distribution of solar insolation in response to obliquity cycles. For Mars, obliquity variation leads to major climatological excursion due to the condensation and sublimation of the major atmospheric constituent, CO2. The atmosphere will collapse into the polar caps, or existing caps will rapidly sublimate into the atmosphere, dependent upon the polar surface heat balance and the direction of the change in obliquity. It has been argued that variations in the obliquity of Mars cause substantial departures from the current climatological values of the surface pressure and the amount of CO2 stored in both the planetary regolith and polar caps. In this new work we have modified the Haberle et al. model to incorporate variable obliquity by allowing the polar and equatorial insolation to become functions of obliquity, which we assume to vary sinusoidally in time. As obliquity varies in the model, there can be discontinuities in the time evolution of the model equilibrium values for surface pressure, regolith, and polar cap storage. The time constant, tau r, for the regolith to find equilibrium with the climate is estimated--depending on the depth, thermal conductivity, and porosity of the regolith--between 10(exp 4) and 10(exp 6) yr. Thus, using 2000-yr timesteps to move smoothly through the 0.1250 m.y. obliquity cycles, we have an atmosphere/regolith system that cannot be assumed in equilibrium. We have dealt with this problem by limiting the rate at which CO2, can move between the atmosphere and regolith, mimicking the diffusive nature and effects of the temperature and pressure waves, by setting the time rate of change of regolith storage proportional to the difference between equilibrium storage and current storage.

Tyler, D.↗
DOE OSTI2025

Warming induces unexpectedly high soil respiration in a wet tropical forest

Abstract Tropical forests are a dominant regulator of the global carbon cycle, exchanging more carbon dioxide with the atmosphere than any other terrestrial biome. Climate models predict unprecedented climatic warming in tropical regions in the coming decades; however, in situ field warming studies are severely lacking in tropical forests. Here we present results from an in situ warming experiment in Puerto Rico, where soil respiration responses to + 4 o C warming were assessed half-hourly for a year. Soil respiration rates were 42-204% higher in warmed relative to ambient plots, representing some of the highest soil respiration rates reported for any terrestrial ecosystem. While respiration rates were significantly higher in the warmed plots, the temperature sensitivity (Q 10 ) was 71.7% lower, pointing to a mechanistic shift. Even with reduced Q 10 , if observed soil respiration rates persist in a warmer world, the feedback to future climate could be considerably greater than previously predicted or observed.

Science & Technology - Other Topics↗
NASA NTRS1979

Use of global atmospheric data sets to test quasi-geostrophic eddy momentum flux convergence

The quasi-geostrophic relation between the fluxes of momentum, potential vorticity, and potential temperature is tested with global sets of atmospheric wind and temperature data by computing the convergence of momentum flux as a residual of the potential temperature and potential vorticity flux and comparing it to the momentum flux convergence computed directly. It is shown that in the troposphere between 18 N and 74 N the observed momentum flux convergence differs from the quasi-geostrophic convergence by 25%-60%, with the larger errors only occurring where the convergence is small. These results indicate that momentum flux convergence obtained from quasi-geostrophic theory is adequate for qualitative studies of the general circulation, and is comparable in accuracy to values obtained in general circulation models. For simple climate models and qualitative process studies, it can thus provide a useful approach.

Heck, W. J.↗
NASA NTRS2004

A GEO Hyperspectral Mission For Continental-Scale Carbon Cycle Observations

For both terrestrial and ocean carbon cycle science objectives, a hyperspectral geostationary sensor should enable the development of new remote sensing measurements for important but as yet unobservable variables, and with the overall goal of linking both terrestrial and ocean carbon cycle processes to climate variability. For terrestrial research, accurate estimates of carbon, water and energy (CWE) exchange between the terrestrial biosphere and atmosphere are needed to identify the geographical locations of carbon sources/sinks and to improve regional climate models and global climate change assessments. It is an enormous challenge to estimate CWE exchange from the infrequent temporal coverage provided by most polar-orbiting satellites, and without benefit of spectral indices that capture vegetation responses to stress conditions that down-regulate photosynthesis. Physiological status can be better assessed with spectral indices based on continuous, narrow (5 nm) bands, as can seasonal and annual terrestrial productivity. For coastal and ocean constituents, narrow-band observations in the ultraviolet and visible are essential to investigate the variability, dynamics and biogeochemical cycles of the world s coastal and open ocean regions, which will in turn help in measuring ocean productivity and predicting the variability of Ocean carbon uptake and its role in climate change scenarios. The GSFC Carbon Team has been pursuing a geostationary hyperspectral instrument, which would revolutionize our knowledge of biological processes on land, in the ocean, and along the coast by providing multiple, diurnal coverage. Preliminary studies in Goddard's Instrument Synthesis and Analysis Laboratory (ISAL) indicate that we can meet many of our science requirements: full spectral coverage (360-1000 nm); narrow bandwidths (5-10 nm); adequate ground resolution (100-200 m); and continental-scale coverage 4-6 times per day; all the while achieving a signal to noise ratio of between 500 and 1000 to 1. However, an innovative and bold focal plane design and a large mirror (1.8 meter diameter) would be required. The development of our science requirements and the results of the initial design study will be presented as well as our most recent technological developments.

Gervin, Janette C.↗