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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Temperature Trends in the Tropical Upper Troposphere and Lower Stratosphere: Connections with Sea Surface Temperatures and Implications for Water Vapor and Ozone

Satellite observations and chemistry-climate model experiments are used to understand the zonal structure of tropical lower stratospheric temperature, water vapor, and ozone trends. The warming in the tropical upper troposphere over the past 30 years is strongest near the Indo-Pacific warm pool, while the warming trend in the western and central Pacific is much weaker. In the lower stratosphere, these trends are reversed: the historical cooling trend is strongest over the Indo-Pacific warm pool and is weakest in the western and central Pacific. These zonal variations are stronger than the zonal-mean response in boreal winter. Targeted experiments with a chemistry-climate model are used to demonstrate that sea surface temperature (hereafter SST) trends are driving the zonal asymmetry in upper tropospheric and lower stratospheric tropical temperature trends. Warming SSTs in the Indian Ocean and in the warm pool region have led to enhanced moist heating in the upper troposphere, and in turn to a Gill-like response that extends into the lower stratosphere. The anomalous circulation has led to zonal structure in the ozone and water vapor trends near the tropopause, and subsequently to less water vapor entering the stratosphere. The radiative impact of these changes in trace gases is smaller than the direct impact of the moist heating. Projected future SSTs appear to drive a temperature and water vapor response whose zonal structure is similar to the historical response. In the lower stratosphere, the changes in water vapor and temperature due to projected future SSTs are of similar strength to, though slightly weaker than, that due directly to projected future CO2, ozone, and methane.

water vapor↗
NASA NTRS1993

AVHRR Surface Temperature and Narrow-Band Albedo Comparison with Ground Measurements for the Greenland Ice Sheet

An ice-surface temperature retrieval algorithm for the Greenland ice sheet was developed using NOAA 11 thermal radiances from channels 4 and 5. Temperature, pressure and humidity profiles, cloud observations and skin temperatures from the Swiss Federal Institute of Technology (ETH) camp, located at the equilibrium line altitude at 49 deg17 min W, 69 deg 34 min N, were used in the LOWTRAN 7 model. Through a statistical analysis of daily clear sky profiles, the coefficients that correct for the atmospheric effects were determined for the ETH-Camp field season (May to August). Surface temperatures retrieved by this method were then compared against the in situ observations with a maximum difference of 0.6 K. The NOAA 11 narrow-band planetary albedo values for channels 1 and 2 were calculated using pre-launch calibration coefficients. Scattering and absorption by the atmosphere were modelled with LOWTRAN 7. Then, narrow-band albedo values for the AVHRR visible and near infrared channels were compared with in situ high resolution spectral reflectance measurements. In the visible band (580-680 nm), AVHRR-derived narrow-band albedo and the in situ measurements corrected with radiative transfer model LOWTRAN 7 showed a difference of less than 2%. For the near infrared channel (725-1100 nm) the difference between the measured and modelled narrow-band albedo was 14%. These discrepancies could be either the result of inaccurate aerosol scattering modelling (lack of the in situ observation), or the result of sensor drift due to degradation.

Haefliger, M.↗
NASA NTRS1999

Satellite Derived Land Surface Temperature for Model Assimilation

Studies have shown that land surface temperature (LST) tendencies are sensitive to the surface moisture availability which is a function of soil moisture and vegetation. The assimilation of satellite derived LST tendencies into the surface energy budget of mesoscale models has shown promise in improving the representation of the complex effects of both soil moisture and vegetation within the models for short term simulations. LST derived from geostationary satellites has the potential of providing the temporal and spatial resolution needed for an LST assimilation process. This paper presents an analysis comparing the LST derived from GOES-8 infrared measurements with LST calculated by the MM5 numerical model. The satellite derived LSTs are calculated using a physical split window approach using channels 4 and 5 of GOES-8. The differences in the LST data sets, especially the tendencies, are presented and examined. Quantifying the differences between the data sets provide insight of possible weaknesses in the model parameterizations affecting the surface energy budget calculations and an indication of the potential effectiveness o f assimilating LST into the models.

Suggs, Ronnie J.↗
NASA NTRS1997

Satellite Sensed Skin Sea Surface Temperature

Quantitative predictions of spatial and temporal changes the global climate rely heavily on the use of computer models. Unfortunately, such models cannot provide the basis for climate prediction because key physical processes are inadequately treated. Consequently, fine tuning procedures are often used to optimize the fit between model output and observational data and the validation of climate models using observations is essential if model based predictions of climate change are to be treated with any degree of confidence. Satellite Sea Surface Temperature (SST) observations provide high spatial and temporal resolution data which is extremely well suited to the initialization, definition of boundary conditions and, validation of climate models. In the case of coupled ocean-atmosphere models, the SST (or more correctly the 'Skin' SST (SSST)) is a fundamental diagnostic variable to consider in the validation process. Daily global SST maps derived from satellite sensors also provide adequate data for the detection of global patterns of change which, unlike any other SST data set, repeatedly extend into the southern hemisphere extra-tropical regions. Such data are essential to the success of the spatial 'fingerprint' technique, which seeks to establish a north-south asymmetry where warming is suppressed in the high latitude Southern Ocean. Some estimates suggest that there is a greater than 80% chance of directly detecting significant change (97.5 % confidence level) after 10-12 years of consistent global observations of mean sea surface temperature. However, these latter statements should be qualified with the assumption that a negligible drift in the observing system exists and that biases between individual instruments required to derive a long term data set are small. Given that current estimates for the magnitude of global warming of 0.015 K yr(sup -1) - 0.025 K yr(sup -1), satellite SST data sets need to be both accurate and stable if such a warming trend is to be confidently detected. Some of these activities are focussed to develop and deploy instrumentation suitable for the collection of precise in situ measurements of the SSST which can be used to improve the accuracy of satellite measurements, while others develop techniques to generate improved global analyses of sea surface temperature using historical data.

Donlon, Craig↗
NASA NTRS2021

The Influence of Direct Radiative Forcing Versus Indirect Sea Surface Temperature Warming on Southern Hemisphere Subtropical Anticyclones Under Global Warming

Southern hemisphere subtropical anticyclones are projected to change in a warmer climate during both austral summer and winter. A recent study of CMIP 5 & 6 projections found a combination of local diabatic heating changes and static-stability-induced changes in baroclinic eddy growth as the dominant drivers. Yet the underlying mechanisms forcing these changes still remain uninvestigated. This study aims to enhance our mechanistic understanding of what drives these Southern Hemisphere anticyclones changes during both seasons. Using an AGCM, we decompose the response to CO2-induced warming into two components: (1) the fast atmospheric response to direct CO2 radiative forcing, and (2) the slow atmospheric response due to indirect sea surface temperature warming. Additionally, we isolate the influence of tropical diabatic heating with AGCM added heating experiments. As a complement to our numerical AGCM experiments, we analyze the Atmospheric and Cloud Feedback Model Intercomparison Project experiments. Results from sensitivity experiments show that slow subtropical sea surface temperature warming primarily forces the projected changes in subtropical anticyclones through baroclinicity change. Fast CO2 atmospheric radiative forcing on the other hand plays a secondary role, with the most notable exception being the South Atlantic subtropical anticyclone in austral winter, where it opposes the forcing by sea surface temperature changes resulting in a muted net response. Lastly, we find that tropical diabatic heating changes only significantly influence Southern Hemisphere subtropical anticyclone changes through tropospheric wind shear changes during austral winter.

Subtropical anticyclone↗
NASA NTRS1979

The effect of paleoatmospheric ozone on surface temperature

Photochemical and radiative-convective calculations are performed to evaluate the influence of ozone in determining the surface temperature of the paleoatmosphere prior to the buildup of molecular oxygen to its present atmospheric level. Possible effects of atmospheric dynamics on the photochemistry and thermal structure of the paleoatmosphere are neglected, and the present atmospheric values are assumed for the tropospheric water-vapor relative-humidity distribution and lapse rate as well as for the fractional cloud amount and cloud reflectivity. It is found that the radiative effects (at IR and solar wavelengths) of ozone for a molecular oxygen level of one-tenth the present atmospheric level resulted in a globally averaged surface-temperature increase of about 4.5 K for the present solar constant. Implications of the results for paleoclimate are briefly considered.

Levine, J. S.↗
NASA NTRS2002

Spatial Patterns of Variability in Antarctic Surface Temperature: Connections to the Southern Hemisphere Annular Mode and the Southern Oscillation

The 17-year (1982-1998) trend in surface temperature shows a general cooling over the Antarctic continent, warming of the sea ice zone, with moderate changes over the oceans. Warming of the peripheral seas is associated with negative trends in the regional sea ice extent. Effects of the Southern Hemisphere Annular Mode (SAM) and the extrapolar Southern Oscillation (SO) on surface temperature are quantified through regression analysis. Positive polarities of the SAM are associated with cold anomalies over most of Antarctica, with the most notable exception of the Antarctic Peninsula. Positive temperature anomalies and ice edge retreat in the Pacific sector are associated with El Nino episodes. Over the past two decades, the drift towards high polarity in the SAM and negative polarity in the SO indices couple to produce a spatial pattern with warmer temperatures in the Antarctic Peninsula and peripheral seas, and cooler temperatures over much of East Antarctica.

Kwok, Ron↗
NASA NTRS2022

Spatial Downscaling of GOES-R Land Surface Temperature over Urban Regions: A Case Study for New York City

The surface urban heat island (SUHI) effect is among the major environmental issues encountered in urban regions. To better predict the dynamics of the SUHI and its impacts on extreme heat events, an accurate characterization of the surface energy balance in urban regions is needed. However, the ability to improve understanding of the surface energy balance is limited by the heterogeneity of surfaces in urban areas. This study aims to enhance the understanding of the urban surface energy budget through an innovation in the use of land surface temperature (LST) observations from remote sensing satellites. A LST database with 5–min temporal and 30–m spatial resolution is developed by spatial downscaling of the Geostationary Operational Environmental Satellites—R (GOES–R) series LST product over New York City (NYC). The new downscaling method, known as the Spatial Downscaling Method (SDM), benefits from the fine spatial resolution of Landsat–8 and high temporal resolution of GOES–R, and considers the temporal variation in LST for each land cover type separately. Preliminary results show that the SDM can reproduce the temporal and spatial variability of LST over NYC reasonably well and the downscaled LST has a spatial root mean square error (RMSE) of the order of 2 K as compared to the independent Landsat–8 observations. The SDM shows smaller RMSE of 1.93 K over the tree canopy land cover, whereas RMSE is 2.19 K for built–up areas. The overall results indicate that the SDM has potential to estimate LST at finer spatial and temporal scales over urban regions.

land surface temperature↗
NASA NTRS2022

Multisensor Machine Learning to Retrieve High Spatiotemporal Resolution Land Surface Temperature

Climate change is making heat waves more frequent, long-lasting, and severe. While multiple satellite types provide data to monitor surface temperature, geostationary (GEO) sensors provide near-continuous, continental-scale observations which can better capture the diurnal variability of land surface temperature (LST) than intermittent observations from low-earth orbit (LEO) sensors. However, standard products from GEO satellites are available at coarsened spatial and temporal resolutions compared to the native sensor resolution. Using datasets from the NASA Earth Exchange, we leveraged co-located, co-temporal observations from LEO and GEO satellites to learn a data-driven mapping using a convolutional neural network. The resulting NASA Earth eXchange Artificial Intelligence LST (NEXAI-LST) achieved a mean absolute error of 1.73 K relative to the target LEO product and improves on both spatial and temporal resolution [2 km, 10 minute] compared to the GEO full disk standard product [10 km, hourly]. In validation against measurements from a ground-based sensor network, NEXAI-LST achieves similar or better fit than both LEO and GEO standard products, while depending none of the prior knowledge of land surface and atmospheric states required by physical-statistical models. Further, application of the model to unseen LEO and GEO satellites demonstrates robust generalization of the model across spatial region, time of day, and sensor. In support of NASA’s open-source science initiative, we make our NEXAI-LST product, model, and codes available to facilitate data exploration and further studies.

Kate Marie Duffy↗
NASA NTRS2015

Surface Temperature Measurements from a Stator Vane Doublet in a Turbine Engine Afterburner Flame Using a YAG:Tm Thermographic Phosphor

Luminescence-based surface temperature measurements were obtained from a YAG:Tm-coated stator vane doublet exposed to the afterburner flame of a J85 test engine at University of Tennessee Space Institute (UTSI). The objective of the testing was to demonstrate that reliable surface temperatures based on luminescence decay of a thermographic phosphor producing short-wavelength emission could be obtained from the surface of an actual engine component in a high gas velocity, highly radiative afterburner flame environment. YAG:Tm was selected as the thermographic phosphor for its blue emission at 456 nm (1D23F4 transition) and UV emission at 365 nm (1D23H6 transition) because background thermal radiation is lower at these wavelengths, which are shorter than those of many previously used thermographic phosphors. Luminescence decay measurements were acquired using a probe designed to operate in the afterburner flame environment. The probe was mounted on the sidewall of a high-pressure turbine vane doublet from a Honeywell TECH7000 turbine engine coated with a standard electron-beam physical vapor deposited (EB-PVD) 200-m-thick TBC composed of yttria-stabilized zirconia (YSZ) onto which a 25-m-thick YAG:Tm thermographic phosphor layer was deposited by solution precursor plasma spray (SPPS). Spot temperature measurements were obtained by measuring luminescence decay times at different afterburner power settings and then converting decay time to temperature via calibration curves. Temperature measurements using the decays of the 456 and 365 nm emissions are compared. While successful afterburner environment measurements were obtained to about 1300C with the 456 nm emission, successful temperature measurements using the 365 nm emission were limited to about 1100C due to interference by autofluorescence of probe optics at short decay times.

thermographic phosphor↗
NASA NTRS1989

The annual and interannual variabilities of precipitable water, surface wind speed, and sea surface temperature over the tropical Pacific

The Nimbus-7 Scanning Multichannel Microwave Radiometer (SSMR) provided simultaneous measurements of three geophysical parameters, each of which describing a certain aspect of the evolution of the 1982-1983 ENSO: the sea-surface temperature (T), precipitable water (W), and surface-wind speed (U). In this paper, values derived from the SSMR were compared with in situ measurements from ships, research buoys, and operational island stations in the tropical Pacific between January 1980 and October 1983, demonstrating the temporal and spatial coherence of the SSMR measurements. The results show that the variabilities of the surface convergence, sea surface temperature, and precipitable water are related. It was found that W anomalies were not always colocated with T anomalies, and that W anomalies were often associated with negative U anomalies, interpreted as surface convergence.

Liu, W. Timothy↗
NASA NTRS2000

A New Neural Network Approach Including First-Guess for Retrieval of Atmospheric Water Vapor, Cloud Liquid Water Path, Surface Temperature and Emissivities Over Land From Satellite Microwave Observations

The analysis of microwave observations over land to determine atmospheric and surface parameters is still limited due to the complexity of the inverse problem. Neural network techniques have already proved successful as the basis of efficient retrieval methods for non-linear cases, however, first-guess estimates, which are used in variational methods to avoid problems of solution non-uniqueness or other forms of solution irregularity, have up to now not been used with neural network methods. In this study, a neural network approach is developed that uses a first-guess. Conceptual bridges are established between the neural network and variational methods. The new neural method retrieves the surface skin temperature, the integrated water vapor content, the cloud liquid water path and the microwave surface emissivities between 19 and 85 GHz over land from SSM/I observations. The retrieval, in parallel, of all these quantities improves the results for consistency reasons. A data base to train the neural network is calculated with a radiative transfer model and a a global collection of coincident surface and atmospheric parameters extracted from the National Center for Environmental Prediction reanalysis, from the International Satellite Cloud Climatology Project data and from microwave emissivity atlases previously calculated. The results of the neural network inversion are very encouraging. The r.m.s. error of the surface temperature retrieval over the globe is 1.3 K in clear sky conditions and 1.6 K in cloudy scenes. Water vapor is retrieved with a r.m.s. error of 3.8 kg/sq m in clear conditions and 4.9 kg/sq m in cloudy situations. The r.m.s. error in cloud liquid water path is 0.08 kg/sq m . The surface emissivities are retrieved with an accuracy of better than 0.008 in clear conditions and 0.010 in cloudy conditions. Microwave land surface temperature retrieval presents a very attractive complement to the infrared estimates in cloudy areas: time record of land surface temperature will be produced.

Aires, F.↗
NASA NTRS1985

Sea surface temperature from satellites: The impact of FGGE

Spacecraft instruments first launched at the beginning of the FGGE year are now producing sea surface temperature data accurate to about 1 C. At larger scales, the errors are dominated by systematic effects, some of which are instrumental, but most are geophysical, i.e., correlated with volcanic aerosols, atmospheric water vapor, clouds, and surface wind. Progress is being made to identify and eliminate such errors and thereby provide sea surface temperature data on a global basis consistently accurate to 0.5 C, which will be needed for studies of climate variability.

Bernstein, R. L.↗
NASA NTRS1994

The classification of the Arctic Sea ice types and the determination of surface temperature using advanced very high resolution radiometer data

The accurate quantification of new ice and open water areas and surface temperatures within the sea ice packs is a key to the realistic parameterization of heat, moisture, and turbulence fluxes between ocean and atmosphere in the polar regions. Multispectral NOAA advanced very high resolution radiometer/2 (AVHRR/2) satellite images are analyzed to evaluate how effectively the data can be used to characterize sea ice in the Bering and Greenland seas, both in terms of surface type and physical temperature. The basis of the classification algorithm, which is developed using a late wintertime Bering Sea ice cover data, is that frequency distributions of 10.8- micrometers radiances provide four distinct peaks, represeting open water, new ice, young ice, and thick ice with a snow cover. The results are found to be spatially and temporally consistent. Possible sources of ambiguity, especially associated with wider temporal and spatial application of the technique, are discussed. An ice surface temperature algorithm is developed for the same study area by regressing thermal infrared data from 10.8- and 12.0- micrometers channels against station air temperatures, which are assumed to approximate the skin temperatures of adjacent snow and ice. The standard deviations of the results when compared with in situ data are about 0.5 K over leads and polynyas to about 0.5-1.5 K over thick ice. This study is based upon a set of in situ data limited in scope and coverage. Cloud masks are applied using a thresholding technique that utilizes 3.74- and 10.8- micrometers channel data. The temperature maps produced show coherence with surface features like new ice and leads, and consistency with corresponding surface type maps. Further studies are needed to better understand the effects of both the spatial and temporal variability in emissivity, aerosol and precipitable atmospheric ice particle distribution, and atmospheric temperature inversions.

Massom, Robert↗
NASA NTRS1991

Analysis of normalized difference and surface temperature observations over southeastern Australia

Relations between radiative surface temperature (TR) and visible and near-IR reflectances expressed as the normalized difference (ND) from a Landsat Thematic Mapper scene are analyzed to examine the heat balance of agriculture and native evergreen forests in southeastern Australia. Factors determining the residual scatter about, and slope of, the TR/ND relationships were analyzed using a coupled two-layer soil-vegetation model of the surface heat balance. Inverse linear relationships were observed between TR and ND for agriculture, but not for forests. This was due to a wide range of ND and TR values in agricultural regions caused by wide variations in fractional vegetation cover.

Smith, R. C. G.↗
NASA NTRS1981

Seasat SMMR observations of ocean surface temperature and wind speed in the North Pacific

The Scanning Multichannel Microwave Radiometer (SMMR), aboard both the SEASAT and Nimbus-7 satellites, was designed primarily to determine global sea surface temperatures and wind speeds over an extended range of atmospheric conditions. The Seasat mission lasted approximately three months from July to October 1978, during which time sufficient data was acquired to enable an assessment of SMMR measurement capabilities under a variety of conditions. This paper reports some results of initial Seasat SMMR assessments in the North Pacific area. A brief description is given of retrieval techniques used to derive the geophysical parameters. SMMR-derived sea surface temperatures and winds are compared with surface truth point measurements from XBT's and buoys, and with surface truth fields derived from point measurements. Accuracies of approximately 1.5 C and 2.5 m/s rms are obtained in these comparisons.

Njoku, E. G.↗
NASA NTRS2010

The Evolution of Remnant Ice at the Lunar South Pole from Diviner Surface Temperature Results

The Diviner lunar radiometer instrument aboard the Lunar Reconnaissance Orbiter mission has revealed large areas of lunar polar terrain with surface temperatures well below 100K. At these temperatures, the sublimation rate of water ice is well below 1 mm per billion years. In contrast, the loss rate at 120K is more than 1 meter of ice in that time consequently volatiles delivered to the coldest locations can be trapped for over 1 Ga, but will be quickly lost from warmer locales. Here we investigate the loss or retention of a layer of ice-bearing regolith at the lunar south poe, assuming contemporary surface temperature conditions and no other loss processes. We use an analytic solution for the one-dimensional diffusion equation of water ice, assuming an isothermal regolith with pore space comparable to mean grain size, 75 micrometers. Only the top meter of soil is assumed to be ice-bearing. We can then calculate the history of ice content with time based on local temperature, and predict what the epithermal neutron output would be in the presence of such a concentration of hydrogen. We compare the present, observed distribution of hydrogen with what one would expect from the temperature-dependent loss or retention of ice for various times since emplacement.

Elphic, Richard C.↗