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At least 145 records · Page 8

Science Writers' Guide to TERRA

The launch of NASA's Terra spacecraft marks a new era of comprehensive monitoring of the Earth's atmosphere, oceans, and continents from a single space-based platform. Data from the five Terra instruments will create continuous, long-term records of the state of the land, oceans, and atmosphere. Together with data from other satellite systems launched by NASA and other countries, Terra will inaugurate a new self-consistent data record that will be gathered over the next 15 years. The science objectives of NASAs Earth Observing System (EOS) program are to provide global observations and scientific understanding of land cover change and global productivity, climate variability and change, natural hazards, and atmospheric ozone. Observations by the Terra instruments will: provide the first global and seasonal measurements of the Earth system, including such critical functions as biological productivity of the land and oceans, snow and ice, surface temperature, clouds, water vapor, and land cover; improve our ability to detect human impacts on the Earth system and climate, identify the "fingerprint" of human activity on climate, and predict climate change by using the new global observations in climate models; help develop technologies for disaster prediction, characterization, and risk reduction from wildfires, volcanoes, floods, and droughts, and start long-term monitoring of global climate change and environmental change.

Source record↗

TOPEX Press Conference (2 of 2)

Footage shows the continuation of the TOPEX Press Conference. The panelists are seen answering questions from the participating audience as well as from NASA Centers. Answers address Kelvin waves, pulses of warm water, sea surface temperature, and the direction in which the project is heading. Also presented are TOPEX/POSEIDON playbacks of the topography and currents of the World Ocean. The video also shows stills of the Central Pacific Ocean from Nov. 1992 to Jan. 1993 and observations of the El Nino events.

Source record↗

The validation of AIRS retrievals

The initial validation of Atmospheric Infrared Sounder (SIRS) experiment retrievals were completed in August 2003 as part of public release of version 3.0 data. The associated analyses are reported at http://daac.gsfc.nasa.gov/atmodyn/airs/, where data may be accessed. Here we describe some of those analyses, with an emphasis on cloud cleared radiances, atmospheric temperature profiles, sea surface temperature, total water vapor and atmospheric water vapor profiles. The results are applicable over ocean in the latitude band +/-40 degrees.

meterology↗

AIRS Level 2 Status

The Atmospheric Infrared Sounder (AIRS) is a facility instrument onboard EOS Aqua. Major level 2 products are highlighted including temperature profile; water vapor profile; surface skin temperature and other surface parameters; and, cloud friction and top cloud pressure. Level 2 files and data availability are discussed.

AIRS↗

An Integrated Examination of AMSR2 Products over Ocean

Integrated processing and analysis are presented for oceanic retrievals of precipitation, sea ice concentration, columnar water vapor and cloud water, sea surface temperature, and near surface wind from the advanced microwave scanning radiometer-2 (AMSR2) sensor. By developing a common algorithmic framework and permitting iterative interaction between historically separate science algorithms, ambiguous and contradictory retrieval results are minimized. The integration also serves to improve each algorithm individually, decreasing reliance on ancillary datasets. Case studies are presented that exemplify both ongoing challenges for these retrievals and potential research uses of such an integrated satellite product. Two cases are presented each for precipitation at high latitudes and marginal sea ice detection, with analysis supplemented by satellite data from CloudSat profiles and Himawari-8 imagery. Detection and retrieval of snowfall remains a challenge, while light rainfall detection can be aided by a variational algorithm. Sea ice concentrations below 20% cause disagreements, but the algorithms otherwise agree well on the sea ice edge. Potential mitigation strategies for ambiguous areas of light rainfall and marginal sea ice are discussed. The analysis demonstrates potential avenues for future algorithm development, but also some physical limitations of remote sensing with the AMSR2 frequencies.

variational methods↗

Diagnosing Changes In Earth's Top-Of-Atmosphere Radiation Budget Since 2000

Earth’s radiation budget (ERB) is a key indicator of the climate system as it describes the delicate balance between how much of the sun’s energy reaching Earth is absorbed and how much thermal infrared radiation is emitted back to space. It is now well established that there is a positive net imbalance in ERB of 0.5-1 Wm-2. This imbalance, referred to as Earth’s Energy Imbalance (EEI), is shaped by natural and anthropogenic climate forcings and the climate system’s response to the forcing.When averaged over a long period, a positive EEI leads to an increase in surface temperature, sea levelrise, ocean heat content, melting of snow and sea-ice, and an acceleration of the hydrological cycle.EEI is also influenced by internal climate variability at interannual (e.g., El Niño/Southern Oscillation(ENSO)) and longer timescales (e.g., Pacific Decadal Oscillation (PDO)). Here we use CERES data toshow that since 2000, EEI has been increasing at a rate of 0.04+-0.03 Wm-2 per yr, corresponding to 0.8 Wm-1 over the 20-year CERES record. To understand the underlying causes for this increase, we analyze the CERES data in the context of internal climate variability indices and regional pattern changes. We also perform a partial radiative perturbation analysis that decomposes the TOA SW and LW radiation variations in terms of contributions by clouds, aerosols, surface albedo, temperature,water vapor and other gases (e.g., ozone, carbon dioxide, methane, etc.).

Norman G Loeb↗

The Application of Remote Sensing using NASA Earth Observations paired with Sociodemographic Indicators to Identify Communities Most Susceptible to Urban Heat Exposure in Austin, Texas

In recent years, Austin, Texas has experienced an increase in population and urban development. Additionally, the City’s climate—already characterized by periods of extreme heat and drought—continues to change. As temperatures and demand for utilities and cooling resources rise, the number of heat-related deaths and illnesses in socially vulnerable populations (e.g., older, lower-income populations) is expected to increase. The City of Austin, The University of Texas at Austin (UT Austin), and The University of Texas Health Science Center at Houston (UT Health) partnered with NASA DEVELOP to examine the distribution of urban heat throughout the City. This project used land surface temperature, greenness, plant water content, and urban surface material analysis parameters derived from NASA Earth observations from Landsat 8 Operational Land Imager (OLI), Landsat 8 Thermal Infrared Sensor (TIRS), and Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS). The project team produced three different indices to create a spatial analysis for the study area including a social vulnerability index (SoVI), heat exposure index (HEI), and an overall heat priority index (HPI) score. This overall score was determined with a weighted analysis of heat-related environmental variables from NASA Earth observations and socioeconomic data from the 2019 American Community Survey. Based on the HPI score, the project team identified 121 census block groups out of 605 total that are designated as being most at risk of adverse impacts from extreme heat events. To test the sensitivity of the HPI, the team used a Monte Carlo analysis using different approaches for geographic scale, variable inclusion, census uncertainty, and index aggregation. Based on the sensitivity analysis, the resulting HPI score showed the metric was consistent with the baseline HPI. This provided increased confidence the score can be used as a tool to make informed infrastructure improvement plans in targeted areas (e.g., siting of cooling centers) and ensure equitable sustainable development.

Ryan Hammock↗

Lake Chad Total Surface Water Area as Derived from Land Surface Temperature and Radar Remote Sensing Data

Lake Chad, located in the middle of the African Sahel belt, underwent dramatic decreases in the 1970s and 1980s leaving less than ten percent of its 1960s surface water extent as open water. In this paper, we present an extended record (dry seasons 1988-2016) of the total surface water area of the lake (including both open water and flooded vegetation) derived using Land Surface Temperature (LST) data (dry seasons 2000-2016) from the NASA Terra MODIS sensor and EUMETSAT Meteosat-based LST measurements (dry seasons 1988-2001) from an earlier study. We also examine the total surface water area for Lake Chad using radar data (dry seasons 2015-2016) from the ESA Sentinel-1a mission. For the limited number of radar data sets available to us (18 data sets), we find on average a close match between the estimates from these data and the corresponding estimates from LST, though we find spatial differences in the estimates using the two types of data. We use these spatial differences to adjust the record (dry seasons 2000-2016) from MODIS LST. Then we use the adjusted record to remove the bias of the existing LST record (dry seasons 1988-2001) derived from Meteosat measurements and combine the two records. From this composite, extended record, we plot the total surface water area of the lake for the dry seasons of 1988-1989 through 2016-2017. We find for the dry seasons of 1988-1989 to 2016-2017 that the maximum total surface water area of the lake was approximately 16,800 sq. km (February and May, 2000), the minimum total surface water area of the lake was approximately 6400 sq. km (November, 1990), and the average was approximately 12,700 sq. km. Further, we find the total surface water area of the lake to be highly variable during this period, with an average rate of increase of approximately 143 sq. km per year.

Policelli, Frederick↗

Assessing the Impacts of Two Averaging Methods on AIRS Level 3 Monthly Products and Multi-Year Monthly Means

The Atmospheric Infrared Sounder (AIRS) onboard NASA’s Aqua satellite provides more than 16 years of data. Its monthly gridded (Level 3) product has been widely used for climate research and applications. Since counts of successful soundings in a grid cell are used to derive monthly averages, this “Averaged By Observations (ABO)” approach effectively gives equal importance to all participating soundings within a month. It is conceivable, then, that days with more observations due to day-to-day orbit shift and regimes with better retrieval skills, will contribute disproportionately to the monthly average within a cell. Alternatively, the AIRS Level 3 monthly product can be produced through an "Averaged By Days (ABD)” approach, where the monthly mean in a grid cell is a simple average of the daily means. The effects of these averaging methods on the AIRS version 6 monthly product are assessed quantitatively using temperature and water vapor at surface and 500hPa. The ABO method results in a warmer (slightly colder) global mean temperature at surface (500hPa) and a drier global mean water vapor than ABD method. The AIRS multi-year monthly mean temperature and water vapor from both methods are also compared with the Modern-Era Retrospective analysis for Research and Applications – 2 (MERRA-2) product and evaluated with a simulation experiment, indicating the ABD method has less error and is more closely correlated with MERRA-2. In summary, the ABD method is recommended for future versions of the AIRS Level 3 monthly product and more data services supporting Level 3 aggregation are needed.

AIRS↗

Large-scale paleo water-table rise in a deep desert aquifer recorded by dissolved noble gases

Illuminating past hydrological and climatological conditions in arid regions may provide insights into future trends in groundwater availability. The main objective of this study is to explore paleorecharge processes in the deep regional Nubian Sandstone Aquifer (NSA), which stretches below the hyperarid deserts of the Sinai Peninsula (Egypt) and the Negev (Israel), using dissolved noble gas data. Extremely high amounts of dissolved excess air (Ne concentrations up to 4 × solubility equilibrium) were observed in the ancient ( 81 Kr-depleted) groundwater that was recharged during past pluvial epochs in the basin. Here, the observed unique excess air signal and the clear spatiotemporal structure of the noble gas compositions in the aquifer are hypothesized to reflect two major characteristics of the groundwater system: (a) large-scale, long-term rises in the water table that facilitate the entrapment and dissolution of air bubbles under increased hydrostatic pressure, and (b) the geological settings in the southern recharge area in Sinai, including an almost horizontal position of the layers and intercalation of low-permeability rock formations within the aquifer, which inefficiently reject air bubbles from groundwater, thereby allowing for substantial entrapment of bubbles that dissolve as the water table rises. Enhanced dissolution of entrapped air was also observed in other paleo-groundwater-containing regional sandstone aquifers across North Africa, which, together with the recent findings from the NSA, suggest that largescale water table fluctuations have likely extensively occurred during past pluvial periods over these (and possibly other) arid regions. A preliminary assessment of noble gas recharge temperatures (NGTs) indicates an apparent decoupling of surface and water table temperatures in the case of deep aquifers with a thick (hundreds of m) unsaturated zone. This observed decoupling calls for a re-evaluation of previously obtained NGT records and a need for future work to consider the modification of NGTs due to soil air fractionation and geothermal heating of the underlying deep unsaturated zones.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of the Radiometric Quality of the TM Data Using Clustering, Linear Transformations and Multispectral Distance Measures

The radiometric quality of LANDSAT 4 TM data for the classification and identification of Earth surface features was evaluated. Techniques employed in the evaluation included clustering, data compression (linear transformations), multispectral distance measures, and hierarchical classification methods. TM and MSS data for the Chicago, Illinois test site were studied. In order to determine the radiometric quality of the TM thermal data for temperature mapping of surface water, a test site was selected within the area covered by the TM scene (Scene ID: 40101-16025) gathered over Illinois. This site was chosen because it includes a surface water body with a large range of temperatures, i.e., a cooling pond for the Dresden nuclear power plant and the junction of two rivers.

Bartolucci, L. A.↗

Sensitivity of Wide Bandwidth Radiometer for Remote Sensing of Ocean Salinity

Passive microwave remote sensing of sea surface salinity from space is currently being done with measurements in the 27 MHz wide spectral window at 1.413 GHz (L-band) protected for passive use. Modern L-band instruments, such as the radiometers on SMOS and Aquarius, have demonstrated the feasibility of monitoring surface salinity from space, and they have also demonstrated the need for better accuracy, especially in cold water. Proposals to improve accuracy have largely involved adding measurement at more frequencies. For example, adding lower frequencies to improve the sensitivity to salinity in cold water and adding higher frequencies to enable simultaneous retrieval of sea surface temperature which is needed in the retrieval of salinity. These strategies involve trade-offs, some obvious such as the effects of interference from anthropogenic sources of radio frequency radiation (RFI) when operating outside the protected band and the loss of spatial resolution at lower frequencies. But, some are more subtle and arise because of the dependence of the retrieval of salinity on other parameters of the ocean surface, in particular, water temperature and roughness (wind speed). The effect of these interdependencies on the potential accuracy of salinity remote sensing in the frequency range 0.3 – 3.0 GHz is examined here to gain insight into the potential for future wide bandwidth instruments for remote sensing of salinity and the optimization of their design. There is benefit including the low frequencies, especially for cold water, but a danger of increased error including frequencies above 1.5 - 2.0 GHz depending on temperature.

Microwave Remote Sensing↗

Microwave emission measurements of sea surface roughness, soil moisture, and sea ice structure

In order to demonstrate the feasibility of the microwave radiometers to be carried aboard the Nimbus 5 and 6 satellites and proposed for one of the earth observatory satellites, remote measurements of microwave radiation at wavelengths ranging from 0.8 to 21 cm have been made of a variety of the earth's surfaces from the NASA CV-990 A/C. Brightness temperatures of sea water surfaces of varying roughness, of terrain with varying soil moisture, and of sea ice of varying structure were observed. In each case, around truth information was available for correlation with the microwave brightness temperature. The utility of passive microwave radiometry in determining ocean surface wind speeds, at least for values higher than 7 meters/second has been demonstrated. In addition, it was shown that radiometric signatures can be used to determine soil moisture in unvegetated terrain to within five percentage points by weight. Finally, it was demonstrated that first year thick, multi-year, and first year thin sea ice can be distinguished by observing their differing microwave emissivities at various wavelengths.

Gloersen, P.↗

Riverbed and Near-Surface Water Quality Data, Hanford Reach, Columbia River, February 2021 - April 2022

This dataset contains longitudinal profiles of natural groundwater tracers (temperature, electrical conductivity (EC), and Radon-222 (Rn)) collected to identify locations of hydrologic exchange flows along a 75-km reach of the Columbia River near Richland, Washington.A jetboat was used to tow a 30 foot long, weighted tether that had one set of temperature and EC sensors just below the water surface and one set of temperature and EC sensors on the end (just above the river bed). The dataset contains profiles of temperature/EC data (resolution: 1 second) collected along the left and right banks during three different sampling events. During the final sampling event, we revisited some "deep holes" where the river was more than 30 feet deep with a weighted tether that was 75 feet long. The dataset has been processed to remove data collected when the sensors were not in the water, or when the water was too deep to keep the tether on the riverbed. We collected grab samples of water for analysis of dissolved Rn in places where the temperature/EC was different from the background river water. The Rn data was joined to the temperature/EC profiles based on the sample times.This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) installation methods; (4) February 2021 data; (5) July 2021 data; (6) April 2022 data; and (7) April 2022 deep hole data. All files are .csv format and can be opened with a spreadsheet program (such as Microsoft Excel or OpenOffice).

54 ENVIRONMENTAL SCIENCES↗

Numerical simulation of VTPR temperature retrievals in a severe storm environment

Environmental conditions prior to convective development on the Great Plains of the U.S. on one case study day were investigated using the high-resolution infrared radiation sounder (HIRS) on Nimbus 6. A dual-retrieval scheme was developed to retrieve both lower tropospheric moisture and temperature parameters from the HIRS radiances. Total precipitable water, surface dew point temperatures, and stability indices were analyzed at a resolution of up to 30 Km on this day. Correlations with interpolated NES rawinsonde values were high and intrinsic noise levels were low. The true quality of the mesoscale analyses, however, is only seen by examining the small scale features at a scale of approximately 100 Km. Perturbations on the dry line feature for this day were seen in the satellite data, although the dry line position was just as easily picked up by surface observations. Convective development 2 1/2 hours later did seem to correlate well with the local maxima of moisture and instability seen in the satellite analyses.

Vonderhaar, T. H.↗

Land surface temperature measurements from EOS MODIS data

A generalized split-window method for retrieving land-surface temperature (LST) from AVHRR and MODIS data has been developed. Accurate radiative transfer simulations show that the coefficients in the split-window algorithm for LST must depend on the viewing angle, if we are to achieve a LST accuracy of about 1 K for the whole scan swath range (+/-55.4 deg and +/-55 deg from nadir for AVHRR and MODIS, respectively) and for the ranges of surface temperature and atmospheric conditions over land, which are much wider than those over oceans. We obtain these coefficients from regression analysis of radiative transfer simulations, and we analyze sensitivity and error by using results from systematic radiative transfer simulations over wide ranges of surface temperatures and emissivities, and atmospheric water vapor abundance and temperatures. Simulations indicated that as atmospheric column water vapor increases and viewing angle is larger than 45 deg it is necessary to optimize the split-window method by separating the ranges of the atmospheric column water vapor and lower boundary temperature, and the surface temperature into tractable sub-ranges. The atmospheric lower boundary temperature and (vertical) column water vapor values retrieved from HIRS/2 or MODIS atmospheric sounding channels can be used to determine the range where the optimum coefficients of the split-window method are given. This new LST algorithm not only retrieves LST more accurately but also is less sensitive than viewing-angle independent LST algorithms to the uncertainty in the band emissivities of the land-surface in the split-window and to the instrument noise.

Wan, Zhengming↗