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Overview. Scientific Advisory Committee Meeting 26 September 2011. SAC members and agency colleagues - Welcome!. Special Welcome! Dennis Lettenmaier New SAC Member. Congratulations! Tim Palmer Elected President, Royal Meteorological Society.

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Overview

Overview

Scientific Advisory Committee Meeting

26 September 2011


Sac members and agency colleagues welcome

SAC membersand agency colleagues - Welcome!


Special welcome dennis lettenmaier new sac member

Special Welcome!Dennis LettenmaierNew SAC Member


Congratulations tim palmer elected president royal meteorological society

Congratulations!Tim Palmer Elected President, Royal Meteorological Society


Congratulations jim hurrell selected director ncar earth system laboratory

Congratulations!Jim Hurrell Selected Director, NCAR Earth System Laboratory


Sac meeting goals

SAC Meeting Goals

Highlight COLA progress since last SAC meeting (April 2010)

Get SAC advice on current and future plans for COLA research and broader engagement activities


Overview 1958423

Vision and Mission

VISION

Global society benefits

from basic and applied research and education

on climate variability and predictability

and the free access to data and research tools

MISSION

Explore, establish and quantify

the predictability and prediction

of intra-seasonal to decadal variability

in a changing climate


And in a probabilistic framework

… and in a probabilistic framework

The laws of probability, so true in general, so fallacious in particular. - Edward Gibbon


Cola uniqueness

COLA Uniqueness

  • Critical mass of excellent climate scientists working together

  • Experimentation with multiple national climate models

  • Stable, multi-agency funding and external expert advice

  • Scientific leadership in national/international I-S-I climate research

  • Co-sponsorship with GMU of PhD program in Climate Dynamics

  • Highly-valued, widely-used software: GrADS

  • High-capacity in-house computing facility

  • Building global capacity: creating weather & climate research institutions


Cola uniqueness1

COLA Uniqueness

  • Critical mass of excellent climate scientists working together

  • Experimentation with multiple national climate models

  • Stable, multi-agency funding and external expert advice

  • Scientific leadership in national/international I-S-I climate research

  • Co-sponsorship with GMU of PhD program in Climate Dynamics

  • Highly-valued, widely-used software: GrADS

  • High-capacity in-house computing facility

  • Building global capacity: creating weather & climate research institutions


Overview 1958423

Pres., IGES (1993-present)

Dir. COLA (1993-2004)

Exec. Dir. COLA (1993-2004)

Dir. COLA (2005-present)

Your most precious possessions are the people you have working there, and what they carry around in their heads, and their ability to work together.

- Robert Reich


Cola uniqueness2

COLA Uniqueness

  • Critical mass of excellent climate scientists working together

  • Experimentation with multiple national climate models

  • Stable, multi-agency funding and external expert advice

  • Scientific leadership in national/international I-S-I climate research

  • Co-sponsorship with GMU of PhD program in Climate Dynamics

  • Highly-valued, widely-used software: GrADS

  • High-capacity in-house computing facility

  • Building global capacity: creating weather & climate research institutions


Experimentation with the nation s climate models

Experimentation with the Nation’s Climate Models

NCAR

CAM4

GFDL

AM2

GSFC

GEOS5

NCEP

GFS2

POP4

MOM4

MOM4

MOM4

CCSM4

CESM1

CFSv2

(CFSv1)

GEOS_CM

CM2.x

Multi-Model Ensemble


Cola uniqueness3

COLA Uniqueness

  • Critical mass of excellent climate scientists working together

  • Experimentation with multiple national climate models

  • Stable, multi-agency funding and external expert advice

  • Scientific leadership in national/international I-S-I climate research

  • Co-sponsorship with GMU of PhD program in Climate Dynamics

  • Highly-valued, widely-used software: GrADS

  • High-capacity in-house computing facility

  • Building global capacity: creating weather & climate research institutions


Overview 1958423

“Omnibus” Funding

COLA is a private, non-profit research institute supported by NSF (lead), NOAA and NASA through a single jointly-peer-reviewed *, jointly-funded five-year proposal.

2009-2014Predictability of the Physical Climate System

Funding: ~$3.6 M / yr

Principal Investigator:Kinter

Co-Investigators:Cash, DelSole, Dirmeyer, Huang, Jin, Klinger,

Krishnamurthy, Schneider, Shukla, Straus

“Science is a wonderful thing

if one does not have to earn one's living at it.” - Albert Einstein

2004-2008Predictability of Earth’s Climate

Funding: ~$3.25M / yr (NSF - 46%; NOAA - 39%; NASA - 15%)

Principal Investigator:Shukla

Co-Investigators:DelSole, Dirmeyer, Huang, Kinter, Kirtman, Klinger, Krishnamurthy, Misra, Schneider, Schopf, Straus

1999-2003Predictability and Variability of the Present Climate

Funding: ~$2.75M / yr

Principal Investigator:J. Shukla

Co-PIs:J. Kinter, E. Schneider, P. Schopf, D. Straus

Co-investigators:P. Dirmeyer, B. Huang, B. Kirtman

1994-1998Predictability and Variability of the Present Climate

Funding: $2.25M /yr

Principal Investigator:J. Shukla

Co-PIs:J. Kinter, E. Schneider, D. Straus

* Thanks to our peers and the agencies


Overview 1958423

“Omnibus” Funding

COLA is viewed as a major interagency National center of excellence:

  • Box 5-1 Major Interagency Programs

  • U.S. Climate Change Science Program (CCSP)

  • U.S. Weather Research Program (USWRP)

  • National Space Weather Program (NSWP)

  • Center for Ocean-Land-Atmosphere Studies (COLA)

2006


Cola uniqueness4

COLA Uniqueness

  • Critical mass of excellent climate scientists working together

  • Experimentation with multiple national climate models

  • Stable, multi-agency funding and externalexpert advice

  • Scientific leadership in national/international I-S-I climate research

  • Co-sponsorship with GMU of PhD program in Climate Dynamics

  • Highly-valued, widely-used software: GrADS

  • High-capacity in-house computing facility

  • Building global capacity: creating weather & climate research institutions


Cola scientific advisory committee

COLA Scientific Advisory Committee

THANK YOU!


Cola scientific advisory committee1

COLA Scientific Advisory Committee


Advice from sac 2010

Advice from SAC 2010

  • COLA should maintain its role as “honest broker”

  • COLA management should provide emphasis on, and coordination and prioritization of core activities

  • COLA should focus on its niche (I-S-I) and avoid mission creep, e.g. overemphasis on Decadal, Athena projects

  • COLA should coordinate closely with NCAR, NCEP

  • COLA should maintain its independence in transition to GMU


Cola involvement with ncep ncar nmme and cfsv3

COLA Involvement with NCEP, NCAR: NMME and CFSv3

  • NMME – National Multi-Model Ensemble

    • Real-time seasonal forecast ensembles with CCSM3beinggiven to NCEP

      (in collaboration with U. Miami)

    • Proposal to CPO FY12 AO: real-time seasonal forecast ensembles with CCSM4

      • collaboration with ESRL, GFDL, GMAO, U. Miami, NCAR, IRI, Princeton, and NCEP

    • Heavy leveraging of COLA I-S-I project and results

  • Design of next generation operational I-S-I prediction model

    • COLA and CTB spearheading groundbreaking R2O activity

      • Involving research scientists from outside NCEP and including private sector input

      • Very successful workshop on 25-26 August 2011


Experimentation with nation al models

Experimentation with National Models

Real-time NMME as of August 2011:

NCAR

CAM4

GFDL

AM2

GSFC

GEOS5

NCEP

GFS2

POP4

MOM4

MOM4

MOM4

CCSM4

CESM1

CFSv2

(CFSv1)

GEOS_CM

CM2.x

Multi-Model Ensemble


Cola involvement with ncep ncar nmme and cfsv31

COLA Involvement with NCEP, NCAR: NMME and CFSv3

  • NMME – National Multi-Model Ensemble

    • Real-time seasonal forecast ensembles with CCSM3 being given to NCEP

      (in collaboration with U. Miami)

    • Proposal to CPO FY12 AO: real-time seasonal forecast ensembles with CCSM4

      • collaboration with ESRL, GFDL, GMAO, U. Miami, NCAR, IRI, Princeton, and NCEP

    • Heavy leveraging of COLA I-S-I project and results

  • Design of next generation operational I-S-I prediction model

    • COLA and CTB spearheading groundbreaking R2O activity

      • Involving research scientists from outside NCEP and including private sector input

      • Very successful workshop on 25-26 August 2011


Cola uniqueness5

COLA Uniqueness

  • Critical mass of excellent climate scientists working together

  • Experimentation with multiple national climate models

  • Stable, multi-agency funding and external expert advice

  • Scientific leadership in national/international I-S-I climate research

  • Co-sponsorship with GMU of PhD program in Climate Dynamics

  • Highly-valued, widely-used software: GrADS

  • High-capacity in-house computing facility

  • Building global capacity: creating weather & climate research institutions


Overview 1958423

Panels and Working Groups

COLA


Cola leadership current examples

COLA Leadership – Current Examples

Editors: Adv. Atmospheric Science (Huang)

Climate Dynamics(Schneider)

J. Climate(DelSole)

IPCC AR5 (DelSole, Lu, contributing authors)

Climate change assessement; also contributions from others (e.g. ZOD and FOD reviewers)

International Advisory Panel for Weather and Climate, India (Shukla, chair; Palmer, Uccellini, members)

Advise Indian government on weather forecasting and climate prediction (research and operations)

NRC BASC Panel on Advancing Climate Modeling (Kinter, member)

Advise US government on climate modeling strategy for 10-20 year horizon

UCAR Community Advisory Committee for NCEP (Kinter, co-chair)

Advise NCEP on strategic direction for 5-10 year horizon

US CLIVAR PPAI Panel (Stan, member)

Set agenda for Predictability, Predictions and Applications Interface

World Climate Modeling Summit(Shukla, chair; Kinter, member)

Very successful meeting in May 2008  multiple BAMS articles in 2010


Cola uniqueness6

COLA Uniqueness

  • Critical mass of excellent climate scientists working together

  • Experimentation with multiple national climate models

  • Stable, multi-agency funding and external expert advice

  • Scientific leadership in national/international I-S-I climate research

  • Co-sponsorship with GMU of PhD program in Climate Dynamics

  • Highly-valued, widely-used software: GrADS

  • High-capacity in-house computing facility

  • Building global capacity: creating weather & climate research institutions


Overview 1958423

Education

COLAand George Mason University (GMU) established (2003) a new Ph.D. Program in Climate Dynamics in the School of Computational Sciences (SCS). Became Climate Dynamics Department in College of Sciences in 2006. Now part of Department of Atmospheric, Oceanic and Earth Sciences.

  • Current Graduate Students

    • K. Arsenault (Shukla/Dirmeyer/Houser)

    • A. Badger (Jin)

    • G. Bucher (Boybeyi)

    • H. Chen (Schneider)

    • I. Colfescu (Schneider)

    • X. Feng (Lu)

    • A. Garuba (Klinger)

  • A. Hazra (Klinger)

  • Y. Jang (Straus)

  • L. Jia(DelSole)

  • L. Krishnamurthy (Krishnamurthy)

  • E. Lajoie (DelSole)

  • J. Li (Huang)

  • J. Nattala (Kinter)

  • E. Palipane (Lu)

  • M. Scafonas (Lu)

  • B. Singh (Krishnamurthy)

  • A. Srivastava (Shukla)

  • E. Stofferahn (Boybeyi)

  • E. Swenson (Straus)

  • L. Xu(Shukla)

  • X. Yan (DelSole)

  • Climate Dynamics Faculty

    • Faculty (0.5 FTE): Boybeyi, Chiu, DelSole, Huang,Jin, Kinter, Klinger, Lu, Schneider, Schopf, Shukla (Director, CLIM), Stan, Straus(chair, AOES)

    • Adjunct:Dirmeyer (selected for 2012 appointment), Doty, Krishnamurthy

  • Bold = 2011 graduate


2002 2010 gmu cd ph d s

2002-2010 GMU-CD Ph.D.s

DeepthiRole of the Indian and Pacific Oceans in Indian Summer Monsoon Variability

Achuthavarier(post-doctoral associate, COLA)

Whit AndersonOceanic Sill - Overflow Systems: Investigation and Simulation with the Poseidon OGCM

(post-doctoral associate, NOAA GFDL)

Susan BatesThe Role of the Annual Cycle in the Coupled Ocean-Atmosphere Variability in the Tropical Atlantic Ocean

(research scientist, NCAR)

Robert BurgmanENSO Decadal Variability in a Tropically-Forced Hybrid Coupled Model

(faculty member, Florida International University)

Carlos CruzGlobal Ocean Circulation Variability Induced by Southern Ocean Winds

(research scientist, NASA Goddard)

Meizhu FanLow Frequency North Atlantic SST Variability: Weather Noise Forcing and Coupled Response

(research scientist: NOAA NESDIS)

Xia FengNew Methods For Estimating Seasonal Potential Climate Predictability

(post-doctoral associate, GMU)

Laura FeudaleExtreme Events in Europe & N. America During 1950-2003: An Observational & Modeling Study

(research scientist, ARPA/OSMER)

Daeho JinThe Impact of ENSO on the Extratropics

(post-doctoral associate, University of Maryland)

Julia ManganelloThe Influence of SST Anomalies on Low-Frequency Variability of the North Atlantic Oscillation

(research scientist, COLA)

BalaNarapusettyImpact Of Tropical Instability Waves In The Eastern Equatorial Pacific

(post-doctoral associate, COLA)

Xiaohua PanImpact of Mean Climate on ENSO Simulation and Prediction

(post-doctoral associate, UMBC/GEST)

Kathy PegionPotential Predictability of Tropical Intraseasonal Variability in the NCEP CFS

(research scientist, CIRES, University of Colorado)

Mary Ellen VeronaObservational Analysis and Numerical Simulation of 1997-1998 El Niño

(deceased)

Yuri VikhliaevDecadal Extra-Tropical Pacific Variability

(post-doctoral associate, NASA Goddard)

TugrulYilmazImproving Land Data Assimilation Performance With A Water Budget Constraint

(research scientist, USDA)


Overview 1958423

Xu Badger Swenson JiaArsenaultGarubaHazraColfescu

NarapusettyLaJoieCruzLiFeng Krishna- NattalaChen

murthy

Current students and recent graduates not pictured: Bucher, Jang, Palipane, Scafonas, Singh, Srivastava, Stofferahn, Yan, and Yilmaz


Overview 1958423

CLIM 101: Global Warming - Weather, Climate and Society

The signs of global climate change can be seen all over the Earth. Some regions are already experiencing dramatic changes and more changes are expected in the future. The costs to society and ecosystems may be huge. Information about climate change is immensely valuable, and a public educated about the scientific basis for these changes is essential.

This course provides a survey of the scientific and societal issues associated with weather and climate variability and change. It will enable students to critically examine arguments being discussed by policy makers, corporations, and the public at large. The current debate on climate change will be discussed from a scientific point of view, with a focus on those aspects that have the largest potential impact on global society.

CLIM 101 is open to all undergraduate students

and fulfills the General Education Natural Science

(non-laboratory) requirement.

Instructors:

Jim Kinter and JagadishShukla

Offered since 2008.

47 students

enrolled in 2011


Cola uniqueness7

COLA Uniqueness

  • Critical mass of excellent climate scientists working together

  • Experimentation with multiple national climate models

  • Stable, multi-agency funding and external expert advice

  • Scientific leadership in national/international I-S-I climate research

  • Co-sponsorship with GMU of PhD program in Climate Dynamics

  • Highly-valued, widely-used software: GrADS

  • High-capacity in-house computing facility

  • Building global capacity: creating weather & climate research institutions


Overview 1958423

GrADS

  • GrADS is an essential tool for COLA research and data management (at COLA and at NCAR) and essential to the COLA "brand".

  • GrADS has over 75,000 users worldwide

    • We know of no other university-based, PI-driven geoscience software in use by more than just a few people.

    • COLA’s long-term, stable, multi-agency funding enables GrADSto be both nimbly responsive to user needs and dedicated to long-term design and planning.

  • GrADS figures are frequently found in weather and climate journals

  • GrADS is used to generate images on many weather and climate web pages hosted by NOAA, NASA, Universities, and a variety of International Agencies (http://iges.org/grads/gotw.html)

  • Funded at a minimal level by COLA Omnibus and intermittent external grants (NASA & NOAA)


Grads is used worldwide

GrADS is Used Worldwide

77,500 downloads

February 2010 - Present


Data management at cola

Data Management at COLA

  • New, more cost-effective design

    • Isolate and curate frequently used static data (shared)

    • Good metadata, logical organization

    • Automated catalogue

    • Scientists make data management decisions

    • Design builds on collaboration with NCAR-CISL

  • Promote best practices among data curators, users


Selected past cola achievements

Selected Past COLA Achievements

  • Established scientific basis for dynamical S-I prediction

  • Established critical role of land surface in climate predictability

  • Established feasibility of reanalysis

  • Organized DSP project (in connection with PROVOST)

  • Advanced the multi-model ensemble

  • Helped quantify limits of climate predictability associated with L-A and O-A interactions

  • Initiated development of framework for climate predictability and prediction

  • Showed that model fidelity determines model predictability


Highlights of today s presentations

Highlights of Today’s Presentations

  • ISI prediction – predictability rebound

    • Develops as a result of coupling of climate system components, e.g., L-A, O-A

    • Consistent with “predictability in the midst of chaos”

  • Seamless prediction

    • Applying NWP technology for climate prediction: higher resolution is necessary but not sufficient for improving climate model fidelity

    • Weather predictability ≈ error growth || Climate predictability ≈ signal/noise

  • Decadal predictability and prediction

    • Rigorous scientific basis for decadal predictability. Evidence for multi-decadal modes of variability; however, we don’t know how to initialize those modes

    • Decadal predictions with CFSv2 (CMIP5)

      • Detected predictability due to changing GHG forcing and ENSO; nothing in between

  • Hypothesis-based experimentation

    • To provide feedback to model development, need experiments to test hypotheses


Predictability from l a coupling

Predictability from L-A Coupling

  • Top: CCSM4 (1850) correlation between initial ½ day soil moisture perturbations and 1-day T2m anomalies.

  • Bottom: GSWP2 seasonal index of coupling between soil moisture and evaporation.

  • Red shading links high land IC impacts on atmosphere (top) to strong land-atmosphere coupling (bottom).


Impact of land and ocean on precipitation prediction

Impact of Land and Ocean on Precipitation Prediction

GLACE-2: COLA AGCM 10-member ensemble hindcasts for 1986-1995

signal/total ratio 80% for land (green), specified SST (blue), and both (purple)

dots indicate 95% significance


Ensemble mean ic improves signal to noise ratio

Ensemble Mean IC Improves Signal-to-noise Ratio

Ensemble initialization from multiple ocean initial states

may be the key to predicting the tropical Atlantic

6 ODA Products:

ORA-S3 (ECMWF)

NEMO-Var (ECMWF)

GODAS (NCEP)

CFS-R (NCEP)

SODA (UMCP)

ECDA (GFDL)

Initializing 1 Model:

CFSv2


Decadal nino3 4 ssta hindcasts cmip5 with cfsv2 nemo var ocean ics

Obs

Decadal NINO3.4 SSTA Hindcasts (CMIP5)with CFSv2 (NEMO-Var ocean ICs)

Model (ens 4)


Most predictable component

Scientific Basis for Decadal Prediction

Autocorrelation squared

5% significance

Time Lag (years)

Most Predictable Component

Most predictable component of annual average SST in CMIP3 control simulations, projected onto 300-year control simulations of individual models  some models show skillful prediction to ~10-year lead-time

DelSole, Tippett and Shukla (2011)


The athena project 2009 2011 revolutionizing climate modeling

The Athena Project, 2009-2011:Revolutionizing Climate Modeling

  • Exploring hypothesis that high spatial resolution and process-resolving models can dramatically improve simulation of climate


Basis for seamless prediction

Basis for Seamless Prediction

  • WCRP, 2005:  The world climate research programmestrategic framework2005-2015. WMO/TD-No. 1291.

  • Palmer, T. N.and co-authors, 2008: Toward seamlessprediction: Calibration of climate change projections using seasonal forecasts. Bull. Amer. Meteor. Soc., 89, 459–470.

  • Dole, R., 2008: Linking weather and climate. Synoptic-Dynamic Meteorology and Weather Analysis and Forecasting. Meteor. Monogr., 55, Amer. Meteor. Soc., 297-348.

  • Hurrell, J., and co-authors, 2009: A unifiedmodeling approach to climate system prediction. Bull. Amer. Meteor. Soc., 90, 1819-1832.

  • Brunet, G., and co-authors, 2010: Collaboration of the weather and climate communitiesto advance subseasonal-to-seasonal prediction. Bull. Amer. Meteor. Soc., 91, 1397-1406.

  • Hazeleger, W., and co-authors, 2010: EC-Earth: A seamlessEarth-system predictionapproach in action. Bull. Amer. Meteor. Soc., 91, 1357-1364.

  • Shukla, J., and co-authors, 2010: Toward a new generation of world climate research and computing facilities. Bull. Amer. Meteor. Soc., 91, 1407–1412.

  • Shapiroand co-authors 2010: An Earth-system predictioninitiativefor the twenty-first century. Bull. Amer. Meteor. Soc., 91, 1377-1388.


Collaborating groups

Collaborating Groups

  • COLA– USA (NSF-funded 1.0 FTE)

  • CrayInc.– USA (in-kind support)

  • ECMWF– EU (in-kind support)

  • JAMSTEC– Japan (in-kind support)

  • NICS University of Tennessee – USA (NSF-funded 6 months supercomputing)

  • RIKEN– Japan (in-kind support; data archival support)

  • University of Tokyo– Japan (in-kind support)

Codes

  • IFS: ECMWF Integrated Forecast System (T159 – T2047)

  • NICAM: Nonhydrostatic Icosahedral Atmospheric Model (7 km)

Supercomputers

  • Athena: Cray XT4 - 4512 quad-core Opteron nodes (18048)

    • #30 on Top500 list (November 2009) – dedicated Oct’09 – Mar’10

  • Kraken: Cray XT5 - 8256 dual hex-core Opteron nodes (99072)

  • Total: ~80 million core-hours; 1.2 PB output


Mean precipitation change in europe s growing season 21 st c minus 20 th c

Mean Precipitation Change inEurope’s Growing Season: 21st C minus 20th C

T159 (128-km)

T1279 (16-km)

“Time-slice” runs of the ECMWF IFS with observed SST for the 20th century and CMIP3 projections of SST for the 21st century at two different model resolutions.


Athena publications

Athena Publications

  • Dirmeyerand 15 co-authors, 2011a: Hydrologic Diurnal Cycle.Climate Dyn., (submitted; accepted).

  • Dirmeyerand 12 co-authors, 2011b: Land-Atmosphere Feedback in a Warming Climate. J. Hydrometeorology(submitted).

  • Jung and 12 co-authors, 2011: Experimental Design, Model Climate and Seasonal Forecast Skill. J. Climate (submitted; accepted).

  • Kinterand 29 co-authors, 2011: Revolutionizing Climate Modeling. Bull. Amer. Met. Soc. (submitted, March 2011).

  • Manganello and 13 co-authors, 2011: Tropical Cyclones: Toward Weather-Resolving Climate Modeling. J. Climate(submitted; minor revision).

  • Sato and 12 co-authors, 2011: ISO and Tropical Cyclones. Climate Dyn. (submitted; major revision).


Overview 1958423

COLA Publications

> 500 peer-reviewed publications since 1993


Today and tomorrow

Today and Tomorrow …

  • Dirmeyer: Land-Atmosphere Interactions

  • Straus: I-S-I Prediction and Predictability

  • Huang: Ocean Prediction and Predictability

  • Schneider: Decadal Prediction and Predictability

  • DelSole: Predictability Framework – A Synthesis

  • Wakefield: COLA Computing

  • Adams: GrADS

  • POSTER SESSION

  • Tomorrow - Future plans


Cola sac poster session

COLA SAC Poster Session

  • Achuthavarier– Impact of horizontal resolution on tropical intraseasonal variability (Project Athena)

  • Doty– GrADS demo

  • Lu– Role of ocean dynamical feedback in the climate response to global warming

  • Manganello,Hodges, Kinter, Cash, Marx, Jung, Achuthavarier, Adams, Altshuler, Huang, Jin, Stan, Towers and Wedi – Tropical cyclone climatology in a 10-km global AGCM: toward weather-resolving climate modeling

  • Wei– Impact of different land or atmospheric models on climate simulation

  • Zhu– The tropical Atlantic zonal mode, meridional mode, and their interaction

  • Arsenault(‘11) – Snow cover fraction data assimilation impacts on modeled energy and moisture budgets

  • Chen(GRA) – Does SST-forced CAM reproduce the CCSM forced response?

  • Jang(‘11) – A new look at the influence of tropical waves on the Indian summer monsoon

  • Jia(‘11) – The limits of detecting forced responses on seasonal and continental scales

    Robust multi-year predictability on continental scales

  • Krishnamurthy (Lakshmi, GRA) – Influence of decadal variability of oceans on south Asian monsoon

  • Lajoie(GRA) – Are some climate models outliers?

  • Li(‘11) and Huang - SST diurnal variability in the CFS and its influence on low frequency variability

  • Narapusetty(‘10), Stan, Zhu, Marx, Lu, and Kumar – Role of atmospheric noise in the predictability of PDV


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