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At least 19 records

An atlas of monthly mean distributions of SSMI surface wind speed, AVHRR/2 sea surface temperature, AMI surface wind velocity, TOPEX/POSEIDON sea surface height, and ECMWF surface wind velocity during 1993

The following monthly mean global distributions for 1993 are presented with a common color scale and geographical map: 10-m height wind speed estimated from the Special Sensor Microwave Imager (SSMI) on a United States (U.S.) Air Force Defense Meteorological Satellite Program (DMSP) spacecraft; sea surface temperature estimated from the Advanced Very High Resolution Radiometer (AVHRR/2) on a U.S. National Oceanic and Atmospheric Administration (NOAA) satellite; 10-m height wind speed and direction estimated from the Active Microwave Instrument (AMI) on the European Space Agency (ESA) European Remote Sensing (ERS-1) satellite; sea surface height estimated from the joint U.S.-France Topography Experiment (TOPEX)/POSEIDON spacecraft; and 10-m height wind speed and direction produced by the European Center for Medium-Range Weather Forecasting (ECMWF). Charts of annual mean, monthly mean, and sampling distributions are displayed.

Halpern, D.↗

Seasat performance evaluation - The first two steps

Seasat, the satellite dedicated to the study of the oceans using microwave sensors, collected a data set containing information on sea surface winds, sea surface temperatures, wave heights, wave directions, internal waves, currents, tides, the marine geoid, and atmospheric water content. The first two steps of the performance evaluation of the satellite have been completed: (1) the engineering assessment and (2) the sensor evaluation. The results are encouraging for the performance of the instruments and the first level of data processing algorithms.

Lame, D. B.↗

Overview of US AID-World Bank-NASA Collaboration to Address Water Management Issues in the MENA Region

The World Bank, USAID and NASA have recently established a joint project to study multiple issues pertaining to water related applications in the Middle East North Africa (MENA) region. The main concentration of the project is on utilization of remote sensing data and hydrological models to address crop irrigation and mapping, flood mapping and forecasting, evapotranspiration and drought problems prevalent in this large geographic area. Additional emphases are placed on understanding the climate impact on these areas as well. Per IPCC 2007 report, by the end of this century MENA region is projected to experience an increase of 3 C to 5 C rise in mean temperatures and a 20% decline in precipitation. This poses a serious problem for this geographic zone especially when majority of the hydrological consumption is for the agriculture sector and the remaining amount is for domestic consumption. The remote sensing data from space is one of the best ways to study such complex issues and further feed into the decision support systems. NASA's fleet of Earth Observing satellites offer a great vantage point from space to look at the globe and provide vital signs necessary to maintain healthy and sustainable ecosystem. These observations generate multiple products such as soil moisture, global precipitation, aerosols, cloud cover, normalized difference vegetation index, land cover/use, ocean altimetry, ocean salinity, sea surface winds, sea surface temperature, ozone and atmospheric gases, ice and snow measurements, and many more. All of the data products, models and research results are distributed-via the Internet freely through out the world. This project will utilize several NASA models such as global Land Data Assimilation System (LDAS) to generate hydrological states and fluxes in near real time. These LDAS products will then be further compared with other NASA satellite observations (MODIS, VIIRS, TRMM, etc.) and other discrete models to compare and optimize evapotranspiration, soil moisture and crop irrigation, droUght assessment and water balance. The floods being a critical disaster in many of the MENA countries, NASA's global flood mapping and modeling framework (CREST) will be customized for country specific needs and delivered to the remote sensing organizations for their future use. Finally, capacity building is a critical part of this project and NASA will assist in this effort as well.

Habib, Shahid↗

Customizing NASA's Earth Science Research Products for addressing MENA Water Challenges

As projected by IPCC 2007 report, by the end of this century the Middle East North Mrica (MENA) region is projected to experience an increase of 3 C to 5 C rise in mean temperatures and a 20% decline in precipitation. This poses a serious problem for this geographic zone especially when majority of the hydrological consumption is for the agriculture sector and the remaining amount is for domestic consumption. In late 2011, the World Bank, USAID and NASA have joined hands to establishing integrated, modem, up to date NASA developed capabilities for various countries in the MENA region for addressing water resource issues and adapting to climate change impacts for improved decision making for societal benefits. The main focus of this undertaking is to address the most pressing societal issues which can be modeled and solved by utilizing NASA Earth Science remote sensing data products and hydrological models. The remote sensing data from space is one of the best ways to study such complex issues and further feed into the decision support systems. NASA's fleet of Earth Observing satellites offer a great vantage point from space to look at the globe and provide vital signs necessary to maintain healthy and sustainable ecosystem. NASA has over fifteen satellites and thirty instruments operating on these space borne platforms and generating over 2000 different science products on a daily basis. Some of these products are soil moisture, global precipitation, aerosols, cloud cover, normalized difference vegetation index, land cover/use, ocean altimetry, ocean salinity, sea surface winds, sea surface temperature, ozone and atmospheric gasses, ice and snow measurements, and many more. All of the data products, models and research results are distributed via the Internet freely through out the world. This project will utilize several NASA models such as global Land Data Assimilation System (LDAS) to generate hydrological states and fluxes in near real time. These LDAS products will then be further compared with other NASA satellite observations (MODIS, VIIRS, TRMM, etc.) and other discrete models to compare and optimize evapotranspiration, soil moisture and crop irrigation, drought assessment and water balance. The floods being a critical disaster in many of the MENA countries, NASA's global flood mapping and modeling framework (CREST) will be customized for country specific needs and delivered to the remote sensing organizations for their future use. Training is an important component under this activity and adequate level of training will be offered to build basic capacity to work with NASA provided data products, models for their future use. This paper provides a comprehensive introduction to NASA's Earth Science mission for understanding the behavior of our home Planet, projecting its health for future generations and applying research results solving societal issues.

Habib, Shahid↗

Multisensor satellite data integration for sea surface wind speed and direction determination

Techniques to integrate meteorological data from various satellite sensors to yield a global measure of sea surface wind speed and direction for input to the Navy's operational weather forecast models were investigated. The sensors were launched or will be launched, specifically the GOES visible and infrared imaging sensor, the Nimbus-7 SMMR, and the DMSP SSM/I instrument. An algorithm for the extrapolation to the sea surface of wind directions as derived from successive GOES cloud images was developed. This wind veering algorithm is relatively simple, accounts for the major physical variables, and seems to represent the best solution that can be found with existing data. An algorithm for the interpolation of the scattered observed data to a common geographical grid was implemented. The algorithm is based on a combination of inverse distance weighting and trend surface fitting, and is suited to combing wind data from disparate sources.

Glackin, D. L.↗

Short pulse radar used to measure sea surface wind speed and SWH

A joint airborne measurement program is being pursued by NRL and NASA Wallops Flight Center to determine the extent to which wind speed and sea surface significant wave height (SWH) can be measured quantitatively and remotely with a short pulse (2 ns), wide-beam (60 deg), nadir-looking 3-cm radar. The concept involves relative power measurements only and does not need a scanning antenna, Doppler filters, or absolute power calibration. The slopes of the leading and trailing edges of the averaged received power for the pulse limited altimeter are used to infer SWH and surface wind speed. The interpretation is based on theoretical models of the effects of SWH on the leading edge shape and rms sea-surface slope on the trailing-edge shape. The models include the radar system parameters of antenna beam width and pulsewidth.

Hammond, D. L.↗

A review of satellite altimeter measurement of sea surface wind speed - With a proposed new algorithm

The scheduled February 1985 launch of a radar altimeter aboard the U.S. Navy satellite Geosat has motivated an in-depth investigation of wind speed retrieval from satellite altimeters. The accuracy of sea surface wind speed estimated by the Seasat altimeter is examined by comparison with wind speed estimated by the Seasat scatterometer. The intercomparison is based on globally distributed spatial and temporal averages of the estimated wind speed. It is shown that there are systematic differences between altimeter and scatterometer wind speed estimates. These differences are traced to errors in the Seasat altimeter geophysical data record wind speed algorithm. A new algorithm is proposed which yields consistent estimates from the two satellite sensors. Using this new algorithm, the rms difference between spatial and temporal averages of the two wind speed estimates is less than 1 m/s, and their correlation is greater than 0.9.

Chelton, D. B.↗

Comparison of sea surface wind speed fields by SEASAT radar altimeter, scatterometer and scanning multichannel microwave radiometer with an emphasis on the Southern Ocean

The SEASAT altimeter (ALT), scatterometer (SASS), and scanning microwave multichannel radiometer (SMMR) measured sea surface wind speed. During the satellite lifetime from June to October 1978, the Austral winter, the highest wind speeds were recorded in the Southern Ocean. Three-month, monthly, and three-day surface wind speed fields deduced from the three Seasat wind speed sensors are compared. The monthly and three-day fields show a pronounced mesoscale (1000 km) variability in wind speed. At all space and time scales analyzed, differences of 40% are found in the magnitude of the wind speed features, with the ALT consistently yielding the lowest wind speed and the SMMR the highest.

Mognard, N. M.↗

An atlas of monthly mean distributions of GEOSAT sea surface height, SSMI surface wind speed, AVHRR/2 sea surface temperature, and ECMWF surface wind components during 1988

Monthly mean global distributions for 1988 are presented with a common color scale and geographical map. Distributions are included for sea surface height variation estimated from GEOSAT; surface wind speed estimated from the Special Sensor Microwave Imager on the Defense Meteorological Satellite Program spacecraft; sea surface temperature estimated from the Advanced Very High Resolution Radiometer on NOAA spacecrafts; and the Cartesian components of the 10m height wind vector computed by the European Center for Medium Range Weather Forecasting. Charts of monthly mean value, sampling distribution, and standard deviation value are displayed. Annual mean distributions are displayed.

Halpern, D.↗

Accuracy Assessment of Aqua-MODIS Aerosol Optical Depth Over Coastal Regions: Importance of Quality Flag and Sea Surface Wind Speed

Coastal regions around the globe are a major source for anthropogenic aerosols in the atmosphere, but the underlying surface characteristics are not favorable for the Moderate Resolution Imaging Spectroradiometer (MODIS) algorithms designed for retrieval of aerosols over dark land or open-ocean surfaces. Using data collected from 62 coastal stations worldwide from the Aerosol Robotic Network (AERONET) from approximately 2002-2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from MODIS aboard Aqua satellite. It is found that coastal AODs (at 550 nm) characterized respectively by the MODIS Dark Land (hereafter Land) surface algorithm, the Open-Ocean (hereafter Ocean) algorithm, and AERONET all exhibit a log-normal distribution. After filtering by quality flags, the MODIS AODs respectively retrieved from the Land and Ocean algorithms are highly correlated with AERONET (with R(sup 2) is approximately equal to 0.8), but only the Land algorithm AODs fall within the expected error envelope greater than 66% of the time. Furthermore, the MODIS AODs from the Land algorithm, Ocean algorithm, and combined Land and Ocean product show statistically significant discrepancies from their respective counterparts from AERONET in terms of mean, probability density function, and cumulative density function, which suggest a need for future improvement in retrieval algorithms. Without filtering with quality flag, the MODIS Land and Ocean AOD dataset can be degraded by 30-50% in terms of mean bias. Overall, the MODIS Ocean algorithm overestimates the AERONET coastal AOD by 0.021 for AOD less than 0.25 and underestimates it by 0.029 for AOD greater than 0.25. This dichotomy is shown to be related to the ocean surface wind speed and cloud contamination effects on the satellite aerosol retrieval. The Modern Era Retrospective-Analysis for Research and Applications (MERRA) reveals that wind speeds over the global coastal region 25 (with a mean and median value of 2.94 meters per second and 2.66 meters per second, respectively) are often slower than 6 meters per second assumed in the MODIS Ocean algorithm. As a result of high correlation (R(sup 2) greater than 0.98) between the bias in binned MODIS AOD and the corresponding binned wind speed over the coastal sea surface, an empirical scheme for correcting the bias of AOD retrieved from the MODIS Ocean algorithm is formulated and is shown to be effective over the majority of the coastal AERONET stations, and hence can be used in future analysis of AOD trend and MODIS AOD data assimilation.

Anderson, J. C.↗

Skylab S-193 Radscat microwave measurements of sea surface winds

The S-193 Radscat made extensive measurements of many sea conditions. Measurements were taken in a tropical hurricane (Ava), a tropical storm (Christine), and in portions of extratropical cyclones. Approximately 200 scans of ocean data at 105 kilometer spacings were taken during the first two Skylab missions and another 200 during the final mission when the characteristics of the measurements changed due to damage of the antenna. Backscatter with four transmit/receive polarization combinations and emissions with horizontal and vertical receive polarizations were measured. Other surface parameters investigated for correlation with the measurements included sea temperature, air/sea temperature difference, and gravity-wave spectrum. Methods were developed to correct the microwave measurements for atmospheric effects. The radiometric data were corrected accurately for clear sky and light cloud conditions only. The radiometer measurements were used to recover the surface scattering characteristics for all atmospheric conditions excluding rain. The radiometer measurements also detected the presence of rain which signaled when the scattering measurement should not be used for surface wind estimation. Regression analysis was used to determine empirically the relation between surface parameters and the microwave measurements, after correction for atmospheric effects. Results indicate a relationship approaching square-law at 50 deg between differential scattering coefficient and wind speed with horizontally polarized scattering data showing slightly more sensitivity to wind speed than vertically polarized data.

Moore, R. K.↗

An Overview of CMIP5 and CMIP6 Simulated Cloud Ice, Radiation Fields, Surface Wind Stress, Sea Surface Temperatures and Precipitation over Tropical and Subtropical Oceans

The potential links between ice water path (IWP), radiation, circulation, sea surface temperature (SST) and precipitation over the Pacific and Atlantic Oceans resulting from the falling ice radiative effects (FIREs) are examined from present day model outputs of CMIP5 and CMIP6. The latter is divided into two subsets with (SON6) and without FIREs (NOS6) as more models with FIREs are included in CMIP6 than in CMIP5. Improvement in floating cloud ice (~20 g m-2) is noticeable over convective regions in CMIP6 relative to CMIP5. The inclusion of FIREs in SON6 subset may contribute to reduce biases of overestimated outgoing longwave radiation and downward surface shortwave and overestimated reflected shortwave at the top of the atmosphere (TOA) by magnitudes of 4?8 W m-2 over convective regions against CERES, compared to NOS6 subset. The reduced biases in radiative fluxes in convective regions stabilize the atmosphere and lead to circulation, SST, cloud and precipitation changes over the trade-wind regions, as seen from improved radiative fluxes (4?15 W m-2), surface wind stress biases, SST (0.2?0.8 K) and precipitation (1 mm day-1) biases. The significant improvement from NOS6 to SON6 leads to improved multi-model means for CMIP6 relative to CMIP5 for radiation fields over the trade wind regions but the degradation over convective zones is attributed to NOS6 subset. The results suggest that other sources of uncertainty and deficiencies in climate models may play significant roles for reducing discrepancies although FIREs, via radiation-circulation coupling, may be one of the factors that help to reduce regional biases.

Jui-Lin F Li↗

Active microwave measurement from space of sea-surface winds

Radar backscatter measurements from the ocean were made at 13.9 GHz from Skylab. The radar signal increased rapidly with wind speed over the entire range of winds encountered, and for angles of incidence of 30 deg larger. Signals observed were normalized to a nominal incidence angle and to a nominal upwind observation direction, using a theoretical model that has been verified as approximately true with aircraft experiments. Observations during the summer and winter Skylab missions were treated separately because of possible differences caused by an accident to the antenna between the two sets of observations. The results are in general agreement with the theory in all cases. The objective analysis method used for determining surface-truth winds in the Skylab experiment was tested by comparing results obtained at weather ships with the observations made by the weather ships themselves. In most cases, the variance about the regression line between objective analysis and weather-ship data actually exceeded that about the regression line between objective analysis and backscatter data

Young, J. D.↗

Studies of the dependence of L-band backscatter on sea surface winds using the synthetic aperture radar

Airborne and Seasat-1 SAR measurements of over-ocean winds through the use of L-band frequencies is described. A consistent dependence has been found between the wind speeds and the microwave backscattering coefficient. Measurements were obtained for cells a few kilometers across and at an incidence angle of 20 deg from nadir. Surface measurements were included in the analyses whenever possible, including data for surface temperatures and current variations, such as in the Gulf Stream. Higher radar cross-sections have been observed from the Gulf Stream than in nearby continental shelf waters. The eye-wall of Hurricane Gloria in Sept. 1976 displayed the largest backscatter of the storm. Wind speed backscatter exponents of 0.5 for winds below 18 m/sec, and 0.58 for winds above 20 m/sec have been determined for the Seasat L-band backscatter. The same wind speeds hold true for 0.05 and 0.50, respectively, for the wind direction component.

Weissman, D. E.↗

Altimeter Estimation of Sea Surface Wind Stress for Light to Moderate Winds

Aircraft altimeter and in situ measurements are used to examine relationships between altimeter backscatter and the magnitude of near-surface wind and friction velocities. Comparison of altimeter radar cross section with wind speed is made through the modified Chelton-Wentz algorithm. Improved agreement is found after correcting 10-m winds for both surface current and atmospheric stability. An altimeter friction velocity algorithm is derived based on the wind speed model and an open-ocean drag coefficient. Close agreement between altimeter- and in situ-derived friction velocities is found. For this dataset, quality of the altimeter inversion to surface friction velocity is comparable to that for adjusted winds and clearly better than the inversion to true 10-m wind speed.

Vandemark, Douglas↗