Search Results

You are looking at 1 - 4 of 4 items for

  • Author or Editor: E. G. Njoku x
  • Refine by Access: All Content x
Clear All Modify Search
E. G. Njoku
and
L. Swanson

Abstract

Satellite microwave measurements of sea surface temperature (SST), sea surface wind speed, atmospheric water vapor and cloud liquid water have been analyzed for the three-month period from July to October 1978. During this period the Scanning Multichannel Microwave Radiometer (SMMR) on the Seasat satellite provided continuous orbital coverage of the world's oceans. Monthly contour maps and zonal averages of the SMMR measurements have been produced to examine the consistency of the Seasat data over longer temporal and spatial scales than has hitherto been investigated. With small (∼0.5°C) bias corrections to the SST estimates, the SMMR appears capable of detecting SST anomalies of ≲1°C, except where radio frequency inteference occurs. The SMMR wind speed and water vapor distributions indicate large-scale atmospheric circulation patterns, and provide complete coverage in regions of sparse ship and radiosonde data. The SMMR cloud liquid water measurements show features similar to those observed in measurements of cloud cover by visible and IR sensors, but indicate the greater SMMR sensitivity to liquid rather than ice content. These SMMR results indicate the potential for future use of microwave radiometry in ocean, weather and climate applicationss.

Full access
P. C. Pandey
,
E. G. Njoku
, and
J. W. Waters

Abstract

The Scanning Multichannel Microwave Radiometer (SMMR) on the Seasat and Nimbus-7 satellite measured microwave radiation at 6.6, 10.69, 18.0, 21.0 and 37.0 GHz with both horizontal and vertical polarizations. Numerical simulations have been performed to explore the potential of using the 18.0, 21.0 and 37.0 GHZ SMMR channels with simultaneous infrared measurements of cloud top height for retrieving cloud temperature differential and thickness over the ocean. The results suggest it is possible to infer cloud vertical thickness to ∼0.4 km rms accuracy and cloud temperature differential to ∼3°C rms. These accuracies are approximately half the a prior variances.

Full access
A. Chehbouni
,
E. G. Njoku
,
J-P. Lhomme
, and
Y. H. Kerr

Abstract

Successful prediction of possible climate change depends on realistic parameterization of land surface processes in climate models. Such parameterizations must take appropriate account of the heterogeneities that are found in most earth surfaces. In this study, different average strategies for aggregating patch-scale heterogeneities to scales that are appropriate for mesoscale and climate model gods have been explored. A simple model for estimating area-average “effective” surface flux parameters is evaluated. The model satisfies the energy balance equation and leads to a set of relationships between local and effective parameters in the governing equations for the surface energy balance. One outcome is that the resulting effective surface temperature is not a simple area-weighted average of component temperatures, but is a function of a specific combination of different resistance of the individual surface elements. A set of heterogeneous surfaces has been simulated to study the effective fluxes obtained using the described model. A comparison with results obtained by other investigators using different averaging methods is also performed.

Full access
Molly E. Brown
,
Vanessa Escobar
,
Susan Moran
,
Dara Entekhabi
,
Peggy E. O'Neill
,
Eni G. Njoku
,
Brad Doorn
, and
Jared K. Entin
Full access