Further Developments in Estimating Cloud Liquid Water over Land Using Microwave and Infrared Satellite Measurements

Greenwald, Thomas J.; Combs, Cynthia L.; Jones, Andrew S.; Randel, David L.; Haar, Thomas H. Vonder

doi:10.1175/1520-0450(1997)036<0389:fdiecl>2.0.co;2

Cited by 32 publications

(17 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The algorithm developed by Jones and Vonder[I] found largest errors for the lowest-level clouds. Greenwald et al [2] showed small radiometric response to CL W when the clouds were situated between 2 -3 km altitudes. But if the same clouds were moved to a greater height (4-5 km), the brightness temperatures for both polarizations at 85.5 GHz showed changes in response to CL W. This phenomenon is primarily caused by interplay between the cloud emission and T a; e.g., when cloud emission occurs at a temperature T close to a calculated under a clear-sky, then the presence of the cloud layer results in little radiometric response.…”

Section: Theoretical Basis For Derivation Of CL W Retrieval Algomentioning

confidence: 98%

“…Thus, they can provide means for the development of viable techniques to retrieve geophysical parameters for global energy and water cycle researches. Some previous investigations have demonstrated the capability of satellite microwave radiometers to retrieve reasonable values of CLW over land [1][2][3]. However, the currently existing CL W retrieval algorithms depend heavi Iy on ancillary data.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Estimating of atmospheric parameters on land using AMSR-E, part II: Inferring cloud liquid water

Wang

Shi

Liu

et al. 2012

2012 Second International Workshop on Earth Observation and Remote Sensing Applications

View full text Add to dashboard Cite

This paper presents a new scheme to retrieve cloud liquid water (CLW) over land using AMSR-E brightness temperatures (TB) without the help of ancillary data. A surface emission model, Advanced Integral Equation Model (AIEM) and an one-dimensional atmosphere transfer model (IDRTM) were combined to generate a database. Through analysis of the simulated dataset, it is found that the ratio of the polarization difference obtained from 36.5 and 89 GHz (!1Ts(36.5)/ !1Ts(89), called PDR_CLW later) is sensitive to CLW. The algorithm was validated using AMSR-E observations over the Southern Great Plains. The CLW data retrieved by five ground based microwave radiometers (MWR) were used to validate the algorithm, with RMS error of 0.11 mm.

show abstract

Section: Theoretical Basis For Derivation Of CL W Retrieval Algomentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Estimating of atmospheric parameters on land using AMSR-E, part II: Inferring cloud liquid water

Wang

Shi

Liu

et al. 2012

2012 Second International Workshop on Earth Observation and Remote Sensing Applications

View full text Add to dashboard Cite

show abstract

“…Although LWP can be retrieved over land from passive microwave imager measurements (Jones and Haar, 1990;Greenwald et al, 1997;Deeter and Vivekanandan, 2006), it cannot be retrieved from AMSU-A data that are often available from the same polar-orbiting satellite. It is thus necessary to develop a land index to capture MHS data pixels affected not only by clouds of ice phase, which can be retrieved from two MHS window channels, but also by clouds of a pure liquid phase over land.…”

Section: A Modified Qc Check For Cloud Detectionmentioning

confidence: 99%

Development and initial assessment of a new land index for microwave humidity sounder cloud detection

Qin

Zou

2016

J Meteorol Res

View full text Add to dashboard Cite

This paper describes a new quality control (QC) scheme for microwave humidity sounder (MHS) data assimilation. It consists of a cloud detection step and an O-B (i.e., differences of brightness temperatures between observations and model simulations) check. Over ocean, cloud detection can be carried out based on two MHS window channels and two Advanced Microwave Sounding Unit-A (AMSU-A) window channels, which can be used for obtaining cloud ice water path (IWP) and liquid water path (LWP), respectively. Over land, cloud detection of microwave data becomes much more challenging due to a much larger emission contribution from land surface than that from cloud. The current MHS cloud detection over land employs an O-B based method, which could fail to identify cloudy radiances when there is mismatch between actual clouds and model clouds. In this study, a new MHS observation based index is developed for identifying MHS cloudy radiances over land. The new land index for cloud detection exploits the large variability of brightness temperature observations among MHS channels over different clouds. It is shown that those MHS cloudy radiances that were otherwise missed by the current O-B based QC method can be successfully identified by the new land index. An O-B check can then be employed to the remaining data after cloud detection to remove additional outliers with model simulations deviated greatly from observations. It is shown that MHS channel correlations are significantly reduced by the newly proposed QC scheme.Citation: Qin Zhengkun and Zou Xiaolei, 2016: Development and initial assessment of a new land index for microwave humidity sounder cloud detection.

show abstract

“…The algorithm de vel oped by J ones a nd V onder[l] found largest errors for the lowest-level clouds. Greenwald et a\' [2] showed small radiometric response t 0 C L W whe n t he c louds were situated between 2 -3 km altitudes. Bu t if t he s arne clouds were m oved t 0 a g reater h eight ( 4-5 km), t he br ightness temperatures for both polarizations a t 85.…”

Section: Retri Eval Algorithmmentioning

confidence: 99%

“…Thus, they can provide means for the de velopment of viable techniques to retrieve geophysical pa rameters f or gl obal energy and water cycle researches. Some previous investigations have demonstrated the capability of sa tellite mi crowave ra diometers to retrieve reasonable values of C LW ove r I and [1][2][3]. However, the currently existing C L W retrieval a 19orithms de pend heavily on ancillary da ta.…”

Section: Introductionmentioning

confidence: 99%

A physically based parameterized method to estimate cloud liquid water over land using satellite passive microwave sensor AMSR-E

Wang

Shi

Liu

et al. 2011

Proceedings of 2011 Cross Strait Quad-Regional Radio Science and Wireless Technology Conference

View full text Add to dashboard Cite

This paper presents a new scheme to retrieve cloud liquid water (CLW) over land using AMSR-E brightness temperatures (TB) without the help of ancillary data. A surface emission model, Advanced Integral Equation Model (AIEM) and an one-dimensional atmosphere transfer model (lDRTM) were combined to generate a database. Through analysis of the simulated dataset, it is found that the ratio of the polarization difference obtained from 36.5 and 89 GHz ('�� TB ( 3 6 .5 ) 1 dTB ( 89 ) , called PDR_CLW later) is sensitive to CLW. The algorithm was validated using AMSR-E observations over the Southern Great Plains. The CLW data retrieved by five ground based microwave radiometers (MWR) were used to validate the algorithm, with RMS error of 0.11 mm.

show abstract

Further Developments in Estimating Cloud Liquid Water over Land Using Microwave and Infrared Satellite Measurements

Cited by 32 publications

References 20 publications

Estimating of atmospheric parameters on land using AMSR-E, part II: Inferring cloud liquid water

Estimating of atmospheric parameters on land using AMSR-E, part II: Inferring cloud liquid water

Development and initial assessment of a new land index for microwave humidity sounder cloud detection

A physically based parameterized method to estimate cloud liquid water over land using satellite passive microwave sensor AMSR-E

Contact Info

Product

Resources

About