pacs/gapp research overview: warm season precipitation david s. gutzler dept. of earth &...

PACS/GAPP Research Overview: Warm Season Precipitation

David S. Gutzler

Dept. of Earth & Planetary Sciences

University of New Mexico

Albuquerque, NM 87131

gutzler@unm.edu

David J. Gochis

National Center for Atmospheric Research

RAP / ASP

Boulder, CO 80303

gochis@rap.ucar.edu

What is PACS/GAPP Warm Season Precipitation Initiative ?

• Determine the sources and limits of predictability of warm season precipitation over N. America with emphasis on the intraseasonal-to-interannual timescales.

• Explicit emphasis on the role of the land surface in modulating warm season precipitation

• Conduct field observations, diagnostic analyses and modeling studies to improve the prediction of warm season precipitation

PACS/GAPP Warm Season Precipitation Research: Motivating Questions

• How can PACS/GAPP research drive improvements in simulating warm season precipitation?

• What is the PACS/GAPP strategy for improvements in operational climate prediction of warm season precipitation anomalies?

... empirical vs dynamical prediction?... relative importance of land/ocean boundary conditions?

... temporal stability of empirical correlations?

• What are top priorities for improvements in the observing and information dissemination system?

Modeling Studies: Re-affirming a persistent

problem

Sensitivity of NCEP RSM-simulated precipitationto choice of physics/surface parameterizations

Kanamitsu & Mo (J. Climate 2003)

USGS physics

SiB physics

AZNM obsJuly 1999

Sensitivity of MM5-simulated precipitationto choice of convective parameterization (I)

Gochis et al. (Mon. Wea. Rev. 2002)

Kain-Fritsch

PERSIANN(observed)

B-M-J

Grell

Sensitivity of MM5-simulated precipitation to choice of convective parameterization (III)

Ritchie & Gutzler (2002)

Grell & Kain-Fritsch parameterizations have opposite sensitivities over land & ocean

No obs here! What is the “true” diurnal cycle? All models show convective max between 21Z-04Z How much nocturnal rain should be falling?

Observations:

NAME

North American Monsoon Observed Precipitation

NAME Higgins & Shi Gochis et al. 2003 11 gridded fields

5b

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

0 2 4 6 8 10 12 14 16 18 20 22 24

Time of Day (LST- Local Solar Time)

Prec

ipita

tion

Rat

e (m

m/h

r)

Network Mean (n=47)

0-500 (n=14)

500-1000 (n=10)

1000-1500 (n=1)

1500-2000 (n=9)

2000-2500 (n=11)

2500-3000 (n=2)

The NAME Field Campaign

Intraseasonal to InterannualVariations:

An “ephemeral” courtship

Empirical studies of decade-scale

predictability variations (I)

winter precip summer precip lag correlations

correlations most pronounced pre-1930 and post-1965

Hu & Feng (J Climate 2002)

Emergent Successes:

Simulation of moisture surges & low-level jets

Berbery & Fox-Rabinowitz (J. Climate 2003)

surge no-surgeprecip: NAMS, Great Plains

Simulation of heavy precipitation events

Kunkel et al. (J. Hydromet. 2002)

timing of intense eventsinterannual variability

of intense events

interannual envelope of intense precip holds promise;

precise timing is elusive

Seattle Working Group Questions:

• What guidance can be derived from PACS/GAPP science to improve simulation of convective precipitation in climate models?

• What are the highest priorities for improvements in sustained observations, derived products, and/or information dissemination, to achieve PACS/GAPP science goals?

• What is the best strategy for improvements in operational climate prediction of warm season precipitation?

• What is the optimum role for dynamical models?

Recommendations:

Priorities for Ongoing & Future Research Activities: Short Term

• Encourage organization of dynamical prediction efforts:– Focus on establishing predictors & predictands– Ascertain time scales of predictability

• Develop new diagnostics and forecasts metrics:– Utilize the diurnal cycle as a principal focal point of

diagnostic and simulation research– Improve characterization of intraseasonal and seasonal

regimes which generate warm season precipitation– Advance understanding of local-remote forcing

linkages

Priorities for Ongoing & Future Research Activities: Short Term

• Demonstrate critical components of enhanced observing systems:– Link EOP projects to future long-term observing

network enhancements (e.g. TAO array)

– Improve a priori coordination of EOP’s with operational centers (e.g. NAME-NCEP)

– Continue and improve coordination of single EOPs with variety of programmatic research goals (GEWEX, DOE, CLIVAR, etc.)

Priorities for Ongoing & Future Research Activities: Long Term

• Explore focused engagement of observational-diagnostic-model development communities to think about improved techniques for simulating warm season precipitation

• Improve ties with operational communities to define the time-scales of predictability and elucidate avenues of significant opportunity

Priorities for Ongoing & Future Research Activities: Obs. & Data

• Motivate data mining as a priority to enhance longer term records

• Improve and implement metadata requirements for PACS/GAPP datasets

• Cloud microphysics and aerosols currently underrepresented in warm season precipitation research priorities

Priorities for Ongoing & Future Research Activities: Linkages

• Strengthen ties to NASA’s Global Precipitation Monitoring Project

• Improve ties with groups studying warm season precip. over oceans (e.g. CLIVAR-EPIC)

• Improve linkages to NOAA RISA’s program to explore fruitful applications of PACS/GAPP research

• Improve connections to other monsoon-related programs (CLIVAR-VAMOS; S. America, GEWEX; Asia)

THE END!

Sensitivity of a JAS precip in a global GCM to interannually varying SST

Farrara & Yu (J. Climate 2002)

... not much

Empirical studies of decade-scale predictability

variations (III) spring snow summer precip

lag correlations

negative correlation most pronounced during the 1975-1985

period

Lo & Clark (J Climate 2002)

Diagnostics of snow-summer precip relationship

Matsui et al. (J. Climate 2003)

... but Tsfc is poorly correlated with summer precip to the south

April snow cover is inversely related with southern Rockies Tsfc through June (though not with later Tsfc) ...

SST in the Gulf of California modulatingNorth American monsoon precipitation

Mitchell et al. (J Climate 2002)

NAME Model Assessment Project Surface Temperature simulations

Sensitivity of MM5 to choice of model physics/ convective parameterization (II)

Xu & Small (JGR 2002)

Kain-Fritsch: too wet, not enough interannual variabilityGrell: superior, but also sensitive to choice of radiation code

Empirical studies of decade-scale predictability

variations (II)

winter summer precip lag correlations

negative correlation most pronounced during the 1963-

1994 period

Kim (J Climate 2002)

Discussion [1]: Modeling Deep Convection• GAPP research has explored the large sensitivity of

current dynamical models to choices of surface treatment, convective parameterization and physics packages

• These sensitivities are surely important for modeling efforts outside GAPP, e.g. IPCC climate change simulations

so ...

What guidance can be derived from GAPP science to improve simulation of convective precipitation in climate models?

Discussion [2]: Observations• Warm season precipitation is poorly sampled (in time

and space) relative to the principal time/space scales of variability

• Simulations of warm season precipitation are sensitive to surface conditions that are sampled even more poorly (e.g. land surface fluxes)

so ...

What are the highest priorities for improvements in sustained observations, derived products, and/or information dissemination, to achieve GAPP science goals?

Discussion [3]: Predictability• Operational seasonal predictability of warm season precipitation

is close to zero• GAPP empirical research on seasonal prediction has suggested

new pathways to predictability, but also demonstrated that observed interannual lead/lag relationships are not temporally stationary

• Current global model sensitivity to prescribed summer SST anomalies is problematic

so ... What is the best strategy for improvements in operational climate prediction of warm season precipitation?

What is the optimum role for dynamical models?