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All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Stress distribution and topography of Tellus Regio, Venus

The Tellus Regio area of Venus represents a subset of a narrow latitude band where Pioneer Venus Orbiter (PVO) altimetry data, line-of-sight (LOS) gravity data, and Venera 15/16 radar images have all been obtained with good resolution. Tellus Regio also has a wide variety of surface morphologic features, elevations ranging up to 2.5 km, and a relatively low LOS gravity anomaly. This area was therefore chosen in order to examine the theoretical stress distributions resulting from various models of compensation of the observed topography. These surface stress distributions are then compared with the surface morphology revealed in the Venera 15/16 radar images. Conclusions drawn from these comparisons will enable constraints to be put on various tectonic parameters relevant to Tellus Regio. The stress distribution is calculated as a function of the topography, the equipotential anomaly, and the assumed model parameters. The topography data is obtained from the PVO altimetry. The equipotential anomaly is estimated from the PVO LOS gravity data. The PVO LOS gravity represents the spacecraft accelerations due to mass anomalies within the planet. These accelerations are measured at various altitudes and angles to the local vertical and therefore do not lend themselves to a straightforward conversion. A minimum variance estimator of the LOS gravity data is calculated, taking into account the various spacecraft altitudes and LOS angles and using the measured PVO topography as an a priori constraint. This results in an estimated equivalent surface mass distribution, from which the equipotential anomaly is determined.

Williams, David R.↗
DOE OSTI2022

Early arrival waveform inversion using data uncertainties and matching filters with application to near-surface seismic refraction data

We develop an early arrival waveform inversion (EAWI) technique for high-resolution near-surface velocity estimation by iteratively updating the P-wave velocity model to minimize the difference between the observed and calculated seismic refraction data. Traditional EAWI uses a least-squares penalty function and an acoustic forward-modeling engine. Conventional least-squares error is sensitive to data with low signal-to-noise ratio (S/N) and iterations of EAWI stop at a local-minimum data misfit or at the preassigned maximum number of iterations. These stopping criteria can result in overfitting the data. In addition, fitting the elastic field data with an acoustic modeling engine can introduce artifacts in velocity estimation, especially in land data with significant elastic effects. To overcome these challenges, we develop a robust EAWI (REAWI) method by (1) incorporating the data uncertainties into the penalty function and (2) mitigating the elastic effects using a matching filter workflow. The data uncertainties are estimated from waveform reciprocal errors. When full-waveform reciprocity is not available, trace interpolation is applied. The proposed method prevents closely fitting data with low S/N, avoids overall overfitting by stopping the iterations when a normalized chi-square ([Formula: see text]) waveform misfit of one is achieved, and is less affected by elastic effects. Numerical examples and application to near-surface refraction data at a groundwater contamination site suggest that the final REAWI models are more accurate than the corresponding EAWI models, at the same level of misfit. This is the first known application of a matching filter workflow to real land data. The final REAWI models satisfy an appropriate misfit between the real data and predicted elastic P-wave data, making this approach in this respect equivalent to elastic waveform inversion. We also develop a method to analyze model constraint by examining the energy of the wavefield Fréchet derivative thereby avoiding the influence of the data residuals in traditional Fréchet kernels.

Geochemistry & Geophysics↗
NASA NTRS1984

The Draco Nebula, a Molecular Cloud Associated with a High Velocity Cloud?

Extended and very faint bright nebulae are found in high galactic latitudes at the Palomar Observatory Sky Survey. Such a nebula, located in the constellation Draco and called Draco Nebula or Dracula, was found to be in detailed positional coincidence with a 21 cm emission line feature. Estimates of the minimum visual extinction from star counts ON and OFF Dracula and an estimated visual surface brightness indicate that Dracula fits the relation SBV = 24.2 - 2.5 log AV for dust clouds located above the galactic plane and reflecting the integrated starlight of the galactic disk. Hence Dracula is probably a reflection nebula. Indicators of molecular hydrogen in Dracula, molecules such as CO, were searched for by using a 2.5-m mm-telescope. Molecular hydrogen column densities were estimated. The dynamics of CO clumps was studied. Dracula has a close positional and possibly even astrophysical relationship to the high velocity cloud phenomenon.

Mebold, U.↗
NASA NTRS1999

Path Radiance Techniques for Retrieving Aerosol Optical Thickness over Land

The key issue in retrieving aerosol optical thickness over land from shortwave satellite radiances is to identify and separate the signal due to scattering by a largely transparent aerosol layer from the noise due to reflection by the background surface, where the signal is relatively uniform compared to the highly inhomogeneous surface contribution. Sensitivity studies in aerosol optical thickness retrievals reveal that the apparent reflectance at the top of the atmosphere is very susceptible to the surface reflectance, especially when aerosol optical thickness is small. Uncertainties associated with surface reflectance estimation can greatly amplify the error of the aerosol optical thickness retrieval. To reduce these uncertainties, we have developed a "path radiance" method to retrieve aerosol optical thickness over land by extending the traditional technique that uses the "dark object" approach to extract the aerosol signal. This method uses the signature of the correlation of visible and mid-IR reflectance at the surface, and couples the correlation with the atmospheric effect. We have applied this method to a TM (Landsat Thematic Mapper) image acquired over the Oklahoma Southern Great Plains (SGP) site of DoE's ARM (Atmospheric Radiation Measurement) program on September 27, 1997, a very clear day during the first Landsat IOP (Intensive Observation Period). The retrieved mean aerosol optical thickness for TM band 1 at 0.49 micrometers and band 3 at 0.66 micrometers agree very well with the ground-based sun-photometer measurements at the ARM site. The ability to retrieve small aerosol optical thickness (such as 0.07 at 0.5 micrometers as in the example considered here) makes this path radiance technique promising. More importantly, the path radiance is relatively insensitive to surface inhomogeneity. The retrieved mean path radiances in reflectance units have very small standard deviations for both TM blue and red bands. This small variability of path radiance further supports the current aerosol retrieval method.

Wen, Guoyong↗
NASA NTRS1999

Path Radiance Technique for Retrieving Aerosol Optical Thickness over Land

The key issue in retrieving aerosol optical thickness over land from short-wave satellite radiances is to identify and separate the signal due to scattering by a largely transparent aerosol layer from the noise due to reflection by the background surface, where the signal is relatively uniform compared to the highly inhomogeneous surface contribution. Sensitivity studies in aerosol optical thickness retrievals reveal that the apparent reflectance at the top of the atmosphere is very susceptible to the surface reflectance, especially when aerosol optical thickness is small. Uncertainties associated with surface reflectance estimation can greatly amplify the error of the aerosol optical thickness retrieval. To reduce these uncertainties, we have developed a "path radiance" method to retrieve aerosol optical thickness over land by extending the traditional technique that uses the "dark object" approach to extract the aerosol signal. This method uses the signature of the correlation of visible and mid-IR reflectance at the surface, and couples the correlation with the atmospheric effect. We have applied this method to a Landsat TM (Thematic Mapper) image acquired over the Oklahoma Southern Great Plains (SGP) site of DoE's ARM (Department of Energy's Atmospheric Radiation Measurement) program on September 27, 1997, a very clear day (aerosol optical thickness of 0.07 at 0.5 pm) during the first Landsat IOP (Intensive Observation Period). The retrieved mean aerosol optical thickness for TM band 1 at 0.49 pm and band 3 at 0.66 pm agree very well with the ground-based sun-photometer measurements at the ARM site. The ability to retrieve small aerosol optical thickness makes this path radiance technique promising. More importantly, the path radiance is relatively insensitive to surface inhomogeneity. The retrieved mean path radiances in reflectance units have very small standard deviations for both TM blue and red bands. This small variability of path radiance further supports the current aerosol retrieval method.

Tsay, S.-C.↗
NASA NTRS1999

Path Radiance Technique for Retrieving Aerosol Optical Thickness Over Land

The key issue in retrieving aerosol optical thickness over land from shortwave satellite radiances is to identify and separate the signal due to scattering by a largely transparent aerosol layer from the noise due to reflection by the background surface, where the signal is relatively uniform compared to the highly inhomogeneous surface contribution. Sensitivity studies in aerosol optical thickness retrievals reveal that the apparent reflectance at the top of the atmosphere is very susceptible to the surface reflectance, especially when aerosol optical thickness is small. Uncertainties associated with surface reflectance estimation can greatly amplify the error of the aerosol optical thickness retrieval. To reduce these uncertainties, we have developed a "path radiance" method to retrieve aerosol optical thickness over land by extending the traditional technique that uses the "dark object" approach to extract the aerosol signal. This method uses the signature of the correlation of visible and mid-IR reflectance at the surface, and couples the correlation with the atmospheric effect. We have applied this method to a Landsat TM (Thematic Mapper) image acquired over the Oklahoma Southern Great Plains (SGP) site of DoE's ARM (Department of Energy's Atmospheric Radiation Measurement) program on September 27,1997, a very clear day (aerosol optical thickness of 0.07 at 0.5 microns) during the first Landsat Intensive Observation Period (IOP). The retrieved mean aerosol optical thickness for TM band 1 at 0.49 micron and band 3 at 0.66 micron agree very well with the ground-based sun-photometer measurements at the ARM site. The ability to retrieve small aerosol optical thickness makes this path radiance technique promising. More importantly, the path radiance is relatively insensitive to surface inhomogeneity. The retrieved mean path radiances in reflectance units have very small standard deviations for both TM blue and red bands. This small variability of path radiance further supports the current aerosol retrieval method.

Tsay, S.-C.↗
NASA NTRS1991

A theory of photometric stereo for a class of diffuse non-Lambertian surfaces

A theory of photometric stereo is proposed for a large class of non-Lambertian reflectance maps. The authors review the different reflectance maps proposed in the literature for modeling reflection from real-world surfaces. From this, they obtain a mathematical class of reflectance maps to which the maps belong. They show that three lights can be sufficient for a unique inversion of the photometric stereo equation for the entire class of reflectance maps. They also obtain a constraint on the positions of light sources for obtaining this solution. They investigate the sufficiency of three light sources to estimate the surface normal and the illuminant strength. The issue of completeness of reconstruction is addressed. They shown that if k lights are sufficient for a unique inversion, 2k lights are necessary for a complete inversion.

Tagare, Hemant D.↗
NASA NTRS2007

Improvement of Risk Assessment from Space Radiation Exposure for Future Space Exploration Missions

Protecting astronauts from space radiation exposure is an important challenge for mission design and operations for future exploration-class and long-duration missions. Crew members are exposed to sporadic solar particle events (SPEs) as well as to the continuous galactic cosmic radiation (GCR). If sufficient protection is not provided the radiation risk to crew members from SPEs could be significant. To improve exposure risk estimates and radiation protection from SPEs, detailed variations of radiation shielding properties are required. A model using a modern CAD tool ProE (TM), which is the leading engineering design platform at NASA, has been developed for this purpose. For the calculation of radiation exposure at a specific site, the cosine distribution was implemented to replicate the omnidirectional characteristic of the 4 pi particle flux on a surface. Previously, estimates of doses to the blood forming organs (BFO) from SPEs have been made using an average body-shielding distribution for the bone marrow based on the computerized anatomical man model (CAM). The development of an 82-point body-shielding distribution at BFOs made it possible to estimate the mean and variance of SPE doses in the major active marrow regions. Using the detailed distribution of bone marrow sites and implementation of cosine distribution of particle flux is shown to provide improved estimates of acute and cancer risks from SPEs.

Kim, Myung-Hee Y.↗
NASA NTRS1990

The analysis of polar clouds from AVHRR satellite data using pattern recognition techniques

The cloud cover in a set of summertime and wintertime AVHRR data from the Arctic and Antarctic regions was analyzed using a pattern recognition algorithm. The data were collected by the NOAA-7 satellite on 6 to 13 Jan. and 1 to 7 Jul. 1984 between 60 deg and 90 deg north and south latitude in 5 spectral channels, at the Global Area Coverage (GAC) resolution of approximately 4 km. This data embodied a Polar Cloud Pilot Data Set which was analyzed by a number of research groups as part of a polar cloud algorithm intercomparison study. This study was intended to determine whether the additional information contained in the AVHRR channels (beyond the standard visible and infrared bands on geostationary satellites) could be effectively utilized in cloud algorithms to resolve some of the cloud detection problems caused by low visible and thermal contrasts in the polar regions. The analysis described makes use of a pattern recognition algorithm which estimates the surface and cloud classification, cloud fraction, and surface and cloudy visible (channel 1) albedo and infrared (channel 4) brightness temperatures on a 2.5 x 2.5 deg latitude-longitude grid. In each grid box several spectral and textural features were computed from the calibrated pixel values in the multispectral imagery, then used to classify the region into one of eighteen surface and/or cloud types using the maximum likelihood decision rule. A slightly different version of the algorithm was used for each season and hemisphere because of differences in categories and because of the lack of visible imagery during winter. The classification of the scene is used to specify the optimal AVHRR channel for separating clear and cloudy pixels using a hybrid histogram-spatial coherence method. This method estimates values for cloud fraction, clear and cloudy albedos and brightness temperatures in each grid box. The choice of a class-dependent AVHRR channel allows for better separation of clear and cloudy pixels than does a global choice of a visible and/or infrared threshold. The classification also prevents erroneous estimates of large fractional cloudiness in areas of cloudfree snow and sea ice. The hybrid histogram-spatial coherence technique and the advantages of first classifying a scene in the polar regions are detailed. The complete Polar Cloud Pilot Data Set was analyzed and the results are presented and discussed.

Smith, William L.↗
DOE OSTI2023

Towards operational atmospheric correction of airborne hyperspectral imaging spectroscopy: Algorithm evaluation, key parameter analysis, and machine learning emulators

Atmospheric correction of airborne hyperspectral imaging spectroscopy (AHIS) to obtain high-quality surface reflectance is the prerequisite for remote sensing applications. Over the last decades, different atmospheric correction methods have been developed based on radiative transfer models (RTMs), however, the relative performances of different algorithms are unclear. Automated operational atmospheric correction methods to process large-volume AHIS data in a high-accurate and high-throughput manner are still lacking. Therefore, this study proposed an operational atmospheric correction pipeline for deriving surface reflectance from AHIS data. To ensure the accuracy and efficiency of the pipeline, we focused on three specific aspects: (1) selecting a suitable RTM for the development of atmospheric lookup tables (LUTs) by comparing the commercial MODerate resolution atmospheric TRANsmission (MODTRAN) and open-sourced Library for Radiative TRANsfer (LibRadTRAN) models, where the widely-used software, Atmospheric/Topographic Correction for Airborne Imagery (ATCOR), was used as benchmarks; (2) identifying key atmospheric correction parameters and determining suitable sources for parameter retrievals including AHIS, Moderate Resolution Imaging Spectroradiometer (MODIS), and AErosol RObotic NETwork (AERONET); and (3) testing the performance of using machine learning emulators to speed up the RTM-based atmospheric correction. Results indicate that (1) atmospheric correction based on MODTRAN LUTs can produce surface reflectance accurately with mean absolute errors < 0.05 and cosine similarities > 0.98 compared to field measurements, which is comparable to the software ATCOR and slightly outperforms the LibRadTRAN LUTs; (2) sobol global sensitivity analysis demonstrates that in the atmospheric correction, visibility and water vapor are two key parameters that can be accurately derived from AHIS in contrast to MODIS or AERONET data; and (3) Random Forest emulators can produce accurate estimations of surface reflectance with mean absolute errors < 0.03 and cosine similarities > 0.98 for higher processing efficiency and determine a suitable set of wavelengths for retrieving atmospheric visibility and water vapor. In conclusion, the proposed atmospheric correction pipeline also improved the four-stream radiative transfer theory for airborne applications by considering adjacent effects from airborne surrounding pixels and can also be applied for atmospheric correction of hyperspectral data from spaceborne missions.

47 OTHER INSTRUMENTATION↗
NASA NTRS1985

The First International Satellite Land-Surface Climatology Project (ISLSCP) Field Experiment (FIFE)

The International Satellite Land Surface Climatology Project (ISLSCP) will verify the use of satellite data for the estimation of land-surface properties through field experiments using point measurements on the ground and areal measurements from aircraft overflights. In addition to validating satellite estimates of surface properties, it studies approaches for obtaining areal averages of the radiation, moisture and heat fluxes made using remotely sensed data. The procedure suggested combines the surface point measurements of the fluxes with the aircraft areal observations using a surface energy balance model to interpolate between the point estimates of these fluxes and calculate area-averaged quantities. The surface parameters to be estimated from aircraft observations include: surface radiation temperature, albedo, land cover or vegetation index, and surface soil moisture (the latter to be obtained using passive and active microwave approaches). The area-averages of the surface properties are compared with satellite data where possible. The First ISLSCP Field Experiment is planned for l987 at a site having relatively uniform vegetation cover in the central great plains of the USA. for 1987 at a site having relatively uniform vegetation cover in the central great plains of the USA.

Schmugge, T. J.↗
NASA NTRS2016

Atmospheric Drivers of Greenland Surface Melt Revealed by Self-Organizing Maps

Recent acceleration in surface melt on the Greenland ice sheet (GrIS) has occurred concurrently with a rapidly warming Arctic and has been connected to persistent, anomalous atmospheric circulation patterns over Greenland. To identify synoptic setups favoring enhanced GrIS surface melt and their decadal changes, we develop a summer Arctic synoptic climatology by employing self-organizing maps. These are applied to daily 500 hPa geopotential height fields obtained from the Modern Era Retrospective Analysis for Research and Applications reanalysis, 1979-2014. Particular circulation regimes are related to meteorological conditions and GrIS surface melt estimated with outputs from the Modèle Atmosphérique Régional. Our results demonstrate that the largest positive melt anomalies occur in concert with positive height anomalies near Greenland associated with wind, temperature, and humidity patterns indicative of strong meridional transport of heat and moisture. We find an increased frequency in a 500 hPa ridge over Greenland coinciding with a 63% increase in GrIS melt between the 1979-1988 and 2005-2014 periods, with 75.0% of surface melt changes attributed to thermodynamics, 17% to dynamics, and 8.0% to a combination. We also confirm that the 2007-2012 time period has the largest dynamic forcing relative of any period but also demonstrate that increased surface energy fluxes, temperature, and moisture separate from dynamic changes contributed more to melt even during this period. This implies that GrIS surface melt is likely to continue to increase in response to an ever warmer future Arctic, regardless of future atmospheric circulation patterns.

anomalies↗
NASA NTRS1995

Remote sensing of flooding in the U.S. upper Midwest during the summer of 1993

The U.S. upper Midwest was subjected to severe flooding during the summer of 1993. Heavy rainfall in the Mississippi River basin from April through July caused flooding on many Midwest rivers, including the Mississippi, Illinois, Missouri, and Kansas Rivers. The flood crest of 15.1 m at St. Louis, Missouri, on 1 August 1993 was the highest ever measured, surpassing the previous record of 13.2 m set on 28 April 1973. Damage estimates include at least 47 flood-related deaths and a total damage cost of $12 billion. Remotely sensed imagery of severe flooding in the U.S. Midwest was obtained under cloud-free skies on 29 July 1993 by the MODIS (Moderate Resolution Imaging Spectroradiometer) Airborne Simulator (MAS). The MAS is a newly developed scanning spectrometer with 50 spectral bands in the wavelength range 0.55-14.3 micrometers. Estimation of the total flooded area in the MAS scene acquired near St. Louis was accomplished by comparing the MAS scene to a Landsat-5 thematic mapper (TM) scene of the same area acquired on 14 April 1984 in nonflood conditions. For comparison, the MAS band centered at 0.94 micrometers and the TM band centered at 1.65 micrometers were selected because of the high contrast seen in these bands between land and water-covered surfaces. An estimate of the area covered by water in the MAS and TM scenes was obtained by developing land/water brightness thresholds from histograms of the MAS and TM digital image data. Afetr applying the thresholds, the difference between the area covered by water in the MAS and TM scenes, and hence the flooded area in the MAS scene, was found to be about 396 sq km, or about 153 square miles.

Gumley, Liam E.↗
DOE OSTI2025

Evaluation and calibration of MERRA-2 and CAMS reanalysis for PM 2.5 in a semi-urbanized area in the south of the Amazon

Air pollution has significant implications for the climate and poses irreversible risks to human health. The Amazon region of Brazil is severely affected by biomass burning (BB) emissions, yet air quality monitoring remains highly inadequate. Given the scarcity of surface-based observations, reanalysis models have become essential tools for assessing air pollution. Although MERRA-2 and CAMS PM 2.5 products are widely utilized, their validation and comprehensive evaluation for the Amazon Basin remain limited. Here, this study assesses the performance of these products in a semi-urbanized region in the southern Amazon. The calibrated time series was employed to analyze PM 2.5 concentrations from 2003 to 2023. Our results showed satisfactory performance of both products for the 24-h averages of PM 2.5 , with linear correlations above 0.76. However, it was found that both products overestimate surface concentrations. MERRA-2 performed better, with approximately 30% lower bias than CAMS. Time series analysis showed that the study area is strongly impacted by emissions BB in the dry period, mainly in August and September. Furthermore, our findings indicate a positive trend in increasing PM 2.5 concentrations, with a notable rise observed since 2014. The average PM 2.5 levels frequently exceed the daily air quality guidelines established by the WHO in 2021. It has been estimated that the population of this region is exposed to concentrations above 15 μg.m -3 , on average, more than 30 days per year. Our results contribute to the evaluation of MERRA-2 and CAMS products for Amazon and provide a corrected estimate for surface PM 2.5 . Recent concerns about air quality and the implementation of new surface monitoring networks may improve the evaluation of reanalysis products. In the short term, the need for this information makes our assessments indispensable.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

An integrated research program for TOPEX/Poseidon with emphasis on the Pacific Ocean

There are four distinct but related tasks in this investigation. First, we want to combine estimates of the surface dynamic topography derived independently from altimetry and from hydrography in an optimal way (weighted least squares with a priori estimates) to produce an optimal estimate (with error bounds) of the large-scale circulation. Second, we want to study the large-scale (as opposed to the mesoscale) variability using crossover differences as well as exact repeat tracks. The third task involves the study of mesoscale variability in the Kuroshio Extension, the California Current, and eventually the Pacific Ocean and the whole globe, wherein surface transport estimates are provided for both the Kuroshio Extension and the Gulf Stream. The final task is a study of how altimeter data and other data can be assimilated into numerical models.

Tai, Chang-Kou↗
NASA NTRSDate not supplied

U.S. IMERG Status

The U.S. Science Team’s Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) product provides estimates of surface precipitation rate and related information on a global 0.1° half-hour grid. It is run three times at increasingly longer latency and higher information input to serve different communities. This presentation will briefly summarize the major upgrades included in Version 07. The Goddard Profiling (GPROF) algorithm (applied to passive microwave sensor data from the GPM virtual constellation) and the Combined Radar-Radiometer Algorithm (CORRA) that provide input to IMERG V07 are both improved, and the new Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Dynamic Infrared Rain Rate (PDIR) algorithm is being applied to infrared data, which employs an additional, warmer infrared temperature threshold than the previous infrared scheme and a deep neural network. V07 has improved bias performance as a result of calibrations that now employ the entire swath widths of CORRA and GPROF GPM Microwave Imager precipitation estimates. As well, time continuity in precipitation features is improved as a result of changes to the Kalman filter that approximately preserve the local histogram of precipitation rates (Scheme for Histogram Adjustment with Ranked Precipitation Estimates in the Neighborhood, or SHARPEN), and that better account for differences in sensor performance. A long-standing bug in the geolocation that shifted grid values 0.1° to the east in the latitude band 70°N-S has been corrected. Other changes in V07 include a hierarchical selection among motion vector sources to address deficiencies in the precipitation propagation near orography, an update to the precipitation phase specification for improved consistency with current inputs, and a renewed effort to implement climatological gauge adjustment to the near-real-time Runs. Early evaluations of V07 IMERG show interesting behavior across the TRMM orbit boost that is highly relevant to the planned orbit boost for the GPM Core observatory.

GPM↗
NASA NTRS2001

Tropical Ocean Evaporation/SST Sensitivity and It's Link to Water and Energy Budget Variations During ENSO

The continuing debate over feedback mechanisms governing tropical sea surface temperatures (SSTs) and tropical climate in general has highlighted the diversity of potential checks and balances within the climate system. Competing feedbacks due to changes in surface evaporation, water vapor, and cloud long- and shortwave radiative properties each may serve critical roles in stabilizing or destabilizing the climate system. It is also intriguing that even those climate variations having origins internal to the climate system - changes in ocean heat transport for example, apparently require complementary equilibrating effects by changes in atmospheric energy fluxes. Perhaps the best observational evidence of this is the relatively invariant nature of tropically averaged net radiation exiting the top-of-atmosphere (TOA) as measured by broadband satellite sensors over the past two decades. Thus, analyzing how these feedback mechanisms are operating within the context of current interannual variability may offer considerable insight for anticipating future climate change. In this paper we focus primarily on interannual variations of ocean evaporative fluxes and their significance for coupled water and energy cycles within the tropical climate system. In particular, we use both the da Silva estimates of surface fluxes (based on the Comprehensive Ocean Atmosphere Data Set, COADS) and numerical simulations from several global climate models to examine evaporation sensitivity to perturbations in SST associated with warm and cold ENSO events. The specific questions we address are as follows: (1) What recurring patterns of surface wind and humidity anomalies are present during ENSO and how do they combine to yield systematic evaporation anomalies?, (2) What is the resulting tropical ocean mean evaporation-SST sensitivity associated with this climate perturbation?, and (3) What role does this evaporation play in tropical heat and water balance over tropical oceanic regions? We use the da Silva ocean flux data to identify composite structure of departures of latent heat flux from climatology. We also show how these patterns arise out of associated wind and humidity anomaly distributions. Our preliminary work shows that evaporation sensitivity estimates from the da Silva / COADS data, computed for the tropical oceans (30 degrees N/S) are in the neighborhood of 5 to 6 W/square m K. Model estimates are also quite close to this figure. This rate is only slightly less than a rate corresponding to constant relative humidity; however, substantial regional departures from constant relative humidity are present. These patterns are robust and we relate the associated wind and humidity fluctuations noted in previous investigations to the derived evaporation anomalies. Finally, these results are interpreted with other data from the Earth radiation Budget Experiment (ERBE), Global Precipitation Climatology Project (GPCP) and NASA's Surface Radiation Budget (SRB) data set to characterize the tropical energetics of ENSO-related climate variability.

Robertson, Franklin R.↗