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1 Spatio-temporal Distribution Spatio-temporal Distribution of of Latent Heating in the Latent Heating in the Southeast Southeast Asian Monsoon Region Asian Monsoon Region School of Earth and Atmospheric Sciences Georgia Institute of Technology Graduate Student Symposium November 2, 2007 Manuel Zuluaga, Carlos Hoyos and Peter Manuel Zuluaga, Carlos Hoyos and Peter Webster Webster

Spatio-temporal Distribution of Latent Heating in the Southeast Asian Monsoon Region

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Spatio-temporal Distribution of Latent Heating in the Southeast Asian Monsoon Region. Manuel Zuluaga, Carlos Hoyos and Peter Webster. School of Earth and Atmospheric Sciences Georgia Institute of Technology Graduate Student Symposium November 2, 2007. Why study Latent Heating?. - PowerPoint PPT Presentation

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Page 1: Spatio-temporal Distribution of  Latent Heating in the Southeast  Asian Monsoon Region

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Spatio-temporal Distribution of Spatio-temporal Distribution of Latent Heating in the Southeast Latent Heating in the Southeast

Asian Monsoon RegionAsian Monsoon Region

School of Earth and Atmospheric SciencesGeorgia Institute of Technology

Graduate Student SymposiumNovember 2, 2007

Manuel Zuluaga, Carlos Hoyos and Peter WebsterManuel Zuluaga, Carlos Hoyos and Peter Webster

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Why study Latent Heating?

• The total diabatic heat absorbed and released is the primary agent of the vertical energy transport… fuel of tropical motions.

• Response of a tropical atmosphere to a heating as forcing

After Gill, 1982

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After Schumacher et al, 2004

Latent heating in model parameterizations

• Vertical heating variations have been received few attention in the physical and model parameterizations.

• Model assumptions: geographically uniform vertical LH and no large-scale variability

• Difficulties in estimation due to the lack of high-resolution data over extended spatio-temporal scales.

• Data from satellite derived information is trying to help to fulfill this deficiency.

• Examine and produce 3D LH structures.• Explore differences with Inter-annual and

Intraseasonal variability.• Produce a diagnostic dataset to parameterize

an atmospheric circulation model

Objectives

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Data

• Convective and Stratiform Heating (CSH) algorithm. (TRMM mission).

• Monthly mean values for a tropical band (37°N - 37°S) and 2.5x2.5 pixel size were used.

• The algorithm compute LH using several runs of a Cloud Resolving Model and then normalizing by precipitation.

• Information of surface precipitation rates, percentage of its stratiform rain component and the type and location of the observed cloud system is used to compute LH values.

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Latent Heating average for 1998-2006

• Higher values of heating related with cloudiness and precipitation regions (Monsoon regions, warm pool, ITCZ, SPCZ).

• Lower values over winter hemisphere and desertic regions

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Vertical profiles of LH

• In general heating distribution is related with cloud characteristics.• Different inter-annual variability for different regions.

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South Asian Monsoon region

After Hoyos and Webster, 2007

• Special region with a conjunction of warm SST and high and spatially complex distribution of mean precipitation.

• Propagation characteristics of intra-seasonal oscillations.

• A well representation of the circulation and its associated precipitation has been elusive in model results.

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Inter-annual LH variability

• High amount of heating in some special regions (Bay of Bengal, BoB and Equatorial Indian Ocean, EIO) in special over ocean

• Lower values over land regions.

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Vertical LH profiles

• Profile shapes related with type of cloudiness

• Interannual variability showing years with less and higher release of LH

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Vertical LH profiles

• Profiles showing relation with orographic precipitation

• Different inter-annual variability also through the vertical profile

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Intra-seasonal relationships

• The monsoon ISO is the dominant large-scale feature of the monsoon region.

• Highest pattern of ISO is shown over the EIO and BoB regions within period of 25-80 days.

• Monsoon ISO considerably alters the entire monsoon circulation

• Active phase is defined as time intervals where rainfall anomalies in the 25-80 day band are positive. Summer averaged wavelet spectra for GPCP

rainfall. After Hoyos and Webster, 2007

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• ISO signal over EIO through the entire year.

• Positive LH anomalies for EIO and Bangladesh region on active phase and for BoB on break phase.

• Dipole-like structure due to the northward wave propagation in the summer period.

Intra-seasonal LH variations

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• Northward propagation of the ISO wave• Amplitude of variability within ISO activity appears stronger as

in the inter-annual variability

Active phase Break phase

N

Intra-seasonal variations

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Conclusions and Future work

• Satellite LH retrievals used as model parameterization can improve physical response of GCM.

• LH retrievals in agreement with precipitative cloud system.

• This CSH data diagnostic shows good representation of intrinsic temporal LH variability (inter-annual and intra-seasonal).

• Next step: this datasets will be used as input parameter to force a GCM.

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Intra-seasonal LH variations

• ISO signal over EIO through the entire year.

• Positive LH anomalies for EIO and Bangladesh region on active phase and for BoB on break phase.

• Dipole “like” structure due to the northward wave propagation in the summer period.

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Intra-seasonal variations

• Northward dipole structure• Amplitude of variability within ISO activity appears stronger than the

inter-annual variability