El Niño and Atmospheric Water Vapor: Observations from Nimbus 7 SMMR

Prabhakara, C.; Short, David; Vollmer, Bruce

doi:10.1175/1520-0450(1985)024<1311:enaawv>2.0.co;2

Cited by 49 publications

(31 citation statements)

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“…4) exhibit a similar spatial pattern as the SST anomalies, showing a moistening center in the equatorial central and eastern Pacific but drying anomalies in the western equatorial Pacific and the off-equator tropical latitudes in both hemispheres. This feature is consistent with the results of Prabhakara et al (1985) and Takahashi et al (2013). The horizontal pattern of atmospheric water vapor anomalies remains largely unchanged throughout the troposphere but its amplitude decreases gradually with height in the lower troposphere and diminishes in the upper troposphere.…”

Section: An Overview Of the Key Features Of Atmospheric Anomalies Of supporting

confidence: 91%

Delineation of thermodynamic and dynamic responses to sea surface temperature forcing associated with El Niño

Hu¹,

Cai²,

Yang³

et al. 2017

Clim Dyn

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a result, air temperature induced thermal radiative cooling anomalies would balance out most of the radiative heating anomalies in the lower troposphere. The remaining part of the radiative heating anomalies is then taken away by an enhancement (a reduction) of upward energy transport in the central-eastern (western) Pacific basin, a secondary contribution to the air temperature anomalies in the lower troposphere. Above the middle troposphere, radiative effect due to water vapor feedback is weak. Thermal radiative cooling anomalies are mainly in balance with the sum of latent heating anomalies, vertical and horizontal energy transport anomalies associated with atmospheric dynamic response and the radiative heating anomalies due to changes in cloud. The pattern of Gill-type response is attributed mainly to the non-radiative heating anomalies associated with convective and large-scale energy transport. The radiative heating anomalies associated with the anomalies of high clouds also contribute positively to the Gill-type response. This sheds some light on why the Gilltype atmospheric response can be easily identifiable in the upper atmosphere.

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Section: An Overview Of the Key Features Of Atmospheric Anomalies Of supporting

confidence: 91%

Delineation of thermodynamic and dynamic responses to sea surface temperature forcing associated with El Niño

Hu¹,

Cai²,

Yang³

et al. 2017

Clim Dyn

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“…Results of this work are compared with a previous analysis (using the Australian data) of the water vapor flux divergence field (Howarth, 1986) for the period June 1973 through May 1978 and with other independent estimates of the differences between evaporation and precipitation for the southern hemisphere published by Sellers (1965), Starr, Peixoto, and McKean (1969), Peixoto (1970Peixoto ( , 1972, Peixoto and Oort (1983), Bryan and Oort (1984), and Savijarvi (1988). Additional information about water vapor content and movement, which can be used to assess the current analyses, is found in Chen (1985), Prabhakara et al (1985), Kayano, Rao and Moura (1989), and Stephens (1990). This analysis thus extends the work of Howarth (1986), providing a basis for comparison with calculations for an earlier period and permitting an assessment of the impact of the 1982-1983 El Niño on the atmospheric water balance over the hemisphere.…”

Section: Introductionmentioning

confidence: 61%

“…With the introduction of operational numerical forecasting, however, it became necessary to generate three-dimemional fields of atmospheric variables over the hemisphere. Recent advances in modeling and in data assimilation procedures (Kinter and Shukla, 1990), along with the use of satellite-based remote sensing (Prabhakara, Short, and Vollmer, 1985), have provided information that has greatly increased our knowledge of the distribution and flow of water vapor over the hemisphere. Hence, despite some shortcomings (cf., Trenberth, Christy, and Olson, 1987), the analyses from numerical prediction centers constitute some of the best estimates of the state of the atmosphere currently available.…”

Section: Introductionmentioning

confidence: 99%

An Analysis of the Atmospheric Water Balance Over the Southern Hemisphere

Howarth

Rayner

1993

Physical Geography

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An analysis of the atmospheric water balance over the Southern Hemi sphere is conducted for the time period June 1980 through May 1984 that includes the 1982-1983 El Niño event. Notable spatial and temporal variations are evident in the moisture flux divergence fields, in the mean meridional transport of water vapor, and in the moisture content of portions of the tropical atmosphere that are attributable to the 1982-1983 ENSO event. Estimates of the net gain/loss of atmospheric water are provided for 10° latitude belts; although the magnitudes of the differences between evaporation and precipitation fall within the range of previous estimates, they are most probably underestimated. [Key words: atmospheric water balance, El Niño, hydrologic cycle, southern hemisphere, water vapor flux.]

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“…From earlier studies (Chang and Wilheit 1979;Prabhakara et al 1985), we know the combination (T 21V -T 19V ) reflects the water vapor content in the atmosphere over the oceans in the absence of rain. Furthermore, over the clear skies T 21V is greater than T 19V .…”

Section: B Parameter ωmentioning

confidence: 99%

A Method to Estimate Rain Rate over Tropical Oceans with the TRMM Microwave Imager Radiometer

Prabhakara

Iacovazzi

Yoo

et al. 2008

Journal of the Meteorological Society of Japan

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In this preliminary study, we have developed a method to retrieve rain rate on a scale of 20 km from the brightness temperatures measured by the TRMM microwave imaging radiometer (TMI) over the tropical oceans, using the estimates of rain rate R PR made by the TRMM Precipitation Radar (PR) as a benchmark. The purpose of this study is to demonstrate with a limited amount of PR and TMI data the feasibility of improving the TRMM operational rain retrieval method V6 over the tropical oceans. This study utilizes the TMI-measured brightness temperatures T 19H , T 37H , and T 85H of horizontally polarized microwave radiances at 19, 37 and 85 GHz, respectively, to deduce a salient non-linear parameter ζ that is highly correlated with R PR over the oceans. Two additional parameters generated from TMI data, ω and Γ, add significant amounts of rain information to our retrieval method. The parameter ω is based on T 19V and T 21V , the brightness temperatures measured by TMI for vertically polarized microwave radiances at 19 and 21 GHz respectively. This parameter takes advantage of the independent information contained in T 21V . The parameter Γ depends on the average horizontal gradient of the TMI-measured T 85V (vertically-polarized 85 GHz radiance) in a 20 km footprint.Initially our TMI rain retrieval algorithm is tuned with the help of R PR for seven cases of 2°×3° area over tropical oceans. Then it is applied to 13 other independent tropical ocean cases. For these independent cases, the rain rate R* estimated from our method correlates better with R PR than the rain rate R V6 retrieved from the present TMI V6 operational retrieval method. On a 20 km scale, the correlation between R PR and R* is better by about 6% compared to that between R PR and R V6 . The slope of the regression line between the rain rates R PR and R V6 is about 0.5. With respect to R PR , the rain rate R V6 retrieved from operational V6 method tends to underestimate high rain rates and overestimate low rain rates. The slope of the regression line between

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El Niño and Atmospheric Water Vapor: Observations from Nimbus 7 SMMR

Cited by 49 publications

References 0 publications

Delineation of thermodynamic and dynamic responses to sea surface temperature forcing associated with El Niño

Delineation of thermodynamic and dynamic responses to sea surface temperature forcing associated with El Niño

An Analysis of the Atmospheric Water Balance Over the Southern Hemisphere

A Method to Estimate Rain Rate over Tropical Oceans with the TRMM Microwave Imager Radiometer

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