PIRCSPIRCS

Project to Intercompare Regional Climate Simulations:Contributions to Transferability

Ninth SessionGEWEX Hydrometeorology Panel

Lüneburg, GermanySeptember 2003

http://www.pircs.iastate.edu/

Gene TakleBill Gutowski, Ray Arritt

OutlineOutline

• What is PIRCS

• Lessons learned relating to hydrological cycle

• PIRCS 1c and beyond

• Contributions to transferability and GHP objectives

To provide a common framework for evaluating strengths and

weaknesses of regional climate models and their component

procedures through systematic, comparative simulations

PIRCS Mission

Domain PIRCS Experiments 1a and 1b

GCM grid: red points RCM grid: green, blue points

Domain PIRCS Experiments 1a and 1b

GCM grid: red points RCM grid: green, blue points

UpperMiss.

PIRCS Experiment 1PIRCS Experiment 1

Experiment 1a1988 drought

Experiment 1b1993 flood

Heat Wave

Jet Stream

Cool

Warm & Moist Southerly Flow

Flood

Jet Stream

Cool &Damp

Weak & Dry Southerly Flow

Heat Wave

Danish Met. Inst. (HIRHAM4; J.H. Christensen, O.B. Christensen)Danish Met. Inst. (HIRHAM4; J.H. Christensen, O.B. Christensen)Université du Québec à Montréal (D. Caya, S. Biner)Université du Québec à Montréal (D. Caya, S. Biner)Scripps Institution of Oceanography (RSM; J. Roads, S. Chen)Scripps Institution of Oceanography (RSM; J. Roads, S. Chen)NCEP (RSM; S.-Y. Hong) NCEP (RSM; S.-Y. Hong) NASA - Marshall (MM5/BATS; W. Lapenta)NASA - Marshall (MM5/BATS; W. Lapenta)CSIRO (DARLAM; J. McGregor, J. Katzfey)CSIRO (DARLAM; J. McGregor, J. Katzfey)Colorado State University (ClimRAMS; G. Liston)Colorado State University (ClimRAMS; G. Liston)Iowa State University (RegCM2; Z. Pan)Iowa State University (RegCM2; Z. Pan)Iowa State University (MM5/LSM; D. Flory)Iowa State University (MM5/LSM; D. Flory)Univ. of Maryland / NASA-GSFC (GEOS; M. Fox-Rabinovitz)Univ. of Maryland / NASA-GSFC (GEOS; M. Fox-Rabinovitz)SMHI / Rossby Centre (RCA; M. Rummukainen, C. Jones)SMHI / Rossby Centre (RCA; M. Rummukainen, C. Jones)NOAA (RUC2; G. Grell)NOAA (RUC2; G. Grell)ETH (D. Luethi)ETH (D. Luethi)Universidad Complutense Madrid (PROMES; M.Gaertner)Universidad Complutense Madrid (PROMES; M.Gaertner)Université Catholique du Louvain (P. Marbaix)Université Catholique du Louvain (P. Marbaix)Argnonne National Lab (MM5 V3; J. Taylor, J. Larson)Argnonne National Lab (MM5 V3; J. Taylor, J. Larson)

PIRCS Participating GroupsPIRCS Participating Groups

500 hPa Heights (1993-1988)500 hPa Heights (1993-1988)

<== Reanalysis

Mean of 7 models ==>

500 hPa Heights:500 hPa Heights: Root Mean Square Difference from ReanalysisRoot Mean Square Difference from Reanalysis

PIRCS Expt 1a (1988)PIRCS Expt 1a (1988)

500 hPa RMSD

0

20

40

60

80

100

136 141 146 151 156 161 166 171 176 181 186 191 196

Julian Day

RegCM2RAMSDARLAMHIRHAMScripps RSMNCEP RSMMM5-BATS

Daily Precipitation HistoryDaily Precipitation HistoryPIRCS Expt 1a (1988 Drought)PIRCS Expt 1a (1988 Drought)

Precipitation over Upper Mississippi River Basin

0

2

4

6

8

10

12

14

136 141 146 151 156 161 166 171 176 181 186 191 196

Julian Day

Observed

MM5-BATS

RSM-Scripps

RSM-NCEP

DARLAM

HIRHAM

RegCM2

RAMS

Lessons Learned - 1aLessons Learned - 1a

• Models generally capture the large-scale fields for extreme events

• Models generally capture the timing and spatial location of precipitation events far from boundaries and long after initialization for synoptically driven precipitation

• Models show wide differences(but realistic behavior) during periods of strong mesoscale forcing

• From these experiences, we assert that simulated climate is a sequence of actual climate events

Spatially Averaged RMSD 500 hPa Geopotential Height1 June - 31 July 1993

0

10

20

30

40

50

60

70

80

1-Jun 11-Jun 21-Jun 1-Jul 11-Jul 21-Jul 31-Jul

Date

RMSD (m)

DARLAM RSM - ScrippsHIRHAM MM5-BATSRSM-NCEP RegCM2Model Mean

500 hPa Heights:500 hPa Heights: Root Mean Square Difference from ReanalysisRoot Mean Square Difference from Reanalysis

PIRCS Expt1b (1993)PIRCS Expt1b (1993)

Ensemble of Cumulative Precipitation for PIRCS 1bP

rec

ipit

ati

on

(m

m)

Upper Mississippi River Basin

Daily Cycle of Water Vapor in Daily Cycle of Water Vapor in Upper Mississippi River BasinUpper Mississippi River Basin

• Nocturnal water vapor flux convergence (not in NNR)• Nocturnal precipitation maximum (not in NNR)• Temporal separation of evap max and precip max• Nocturnal precipitation max created by mesoscale

convective systems • Region lacks major orographic forcing (e.g., no

mountains, no coasts, no major lakes) to spatially constrain precip events

Daily Cycle of Water Vapor in Daily Cycle of Water Vapor in Upper Mississippi River BasinUpper Mississippi River Basin

• Nocturnal water vapor flux convergence (not in NNR)• Nocturnal precipitation maximum (not in NNR)• Temporal separation of evap max and precip max• Nocturnal precipitation max created by mesoscale

convective systems • Region lacks major orographic forcing (e.g., no

mountains, no coasts, no major lakes) to spatially constrain precip events

• We are a boring place to visit…

Daily Cycle of Water Vapor in Daily Cycle of Water Vapor in Upper Mississippi River BasinUpper Mississippi River Basin

• Nocturnal water vapor flux convergence (not in NNR)• Nocturnal precipitation maximum (not in NNR)• Temporal separation of evap max and precip max• Nocturnal precipitation max created by mesoscale

convective systems • Region lacks major orographic forcing (e.g., no

mountains, no coasts, no major lakes) to spatially constrain precip events

• We are a boring place to visit unless you bring your RCM!

Lessons Learned - 1bLessons Learned - 1b

• As much difference among models using NNR bc as between models using NNR and ER bc. But this may not be the case where bc are in data-sparse regions.

• Extended period of saturated soils allowed examination of evaporation schemes (independent of soil moisture values).

• Diurnal separation of C and P from E.• Lack of precip south of frontal boundary shows

failure to simulate MCCs

Lessons Learned - 2Lessons Learned - 2

• All models get P-E > 0, as observed, even though this is not the normal climatological occurrence for this region.

• Convective (vs. stable precip): 37 - 97%. Three models using K-F scheme differ widely in conv. fraction.

• Conv fraction not correlated with total precip.• E (models) = 3.9 mm/d; E (clim) ~ 4 mm/d; 3 models markedly

different: model deficiencies exposed.• Water recycling ratio similar in 10 of 13 and within the expected

range. • Importance of vertical and horizontal resolution of and time evolution

of the LLJ• Common model faults and relation to parentage

PIRCS 1c and BeyondPIRCS 1c and Beyond

• 1986- present• Domain same as 1a and 1b with expansion to

south and west• Participants sought• See PIRCS homepage: http://www.pircs.iastate.edu• Revisit PIRCS 1b?• PIRCS 2, South America??

What have been the benefits What have been the benefits of transferability?of transferability?

• Application to different regions severely tests different model components

• Convection, interaction of convection with PBL and turbulence representation of the LLJ

• Linkage of convective activity to convective cloudiness to test surface energy budget

Colin Jones, Rossby Center

u, v, w u, v, w u, v, w u, v, w u, v, wu, v, w

Constraining boundary

T, w T, w T, w T, w T, w

Regional models, with boundaries constrained by observations,allow for more realistic parameterizations of model physics for use in global models

Concept suggested by Colin Jones, sketch by EST

RCM is a bridge between 1-D and GCMs for parameterizations

PIRCS PublicationsPIRCS Publications

PIRCS 1a

Takle, E. S., W. J. Gutowski, R. A. Arritt, Z. Pan, C. J. Anderson, R. R. da Silva, D. Caya, S.-C. Chen, J. H. Christensen, S.-Y. Hong, H.-M. H. Juang, J. Katzfey, W. M. Lapenta, R. Laprise, P. Lopez, J. McGregor and J. O. Roads, 1999: Project to Intercompare Regional Climate Simulations (PIRCS): Description and initial results.   J. Geophys. Res., 104, 19,443-19,461.

PIRCS 1b

Anderson, C. J., R. W. Arritt, E. S. Takle, Z. Pan, W. J. Gutowski, Jr., R. da Silva, D. Caya, J. H. Christiansen, D. Luthi, M. A. Gaertner, C. Gallardo, F. Giorgi, S.-Y. Hong, Colin Jones, H.-M. J. Juang, Jack J. Katzfey, W. M. Lapenta, R. Laprise, J. W. Larson, G. E. Liston, J. L. McGregor, R. A. Pielke, Sr., J. O. Roads, and J. A. Taylor, 2002: Hydrologic processes in regional climate model simulations of the central United States flood of June-July 1993.  J. Hydrometeor., 4, 584-598.

15 Conference Presentations15 Conference Presentations

• American Meteorological Society meetings

• International Association of Meteorological and Atmospheric Sciences

• European Geophysical Society• American Geophysical Union

Invited PresentationsInvited Presentations

• Working Group on Numerical Experimentation, WCRP

• Workshop on Climate Modeling• Clivar Meeting• Regional Climate Model Intercomparsion

Project for China• Arctic Model Intercomparison Project• Workshop on Regional Climate Prediction

and Downscaling Techniques for South America

Contributions of RCM Contributions of RCM Intercomparisons to GHP Intercomparisons to GHP

Objectives Objectives

• Offer opportunities for better understanding of how the water and energy cycles contribute to climate feedbacks (up-scaling issues)

• Suggest specific areas and strategies for improving parameterizations

• PIRCS represented in the IPCC TAR and offers opportunity to interact with the broader WCRP community on predictability

PIRCS Program OfficePIRCS Program Office

Project Leaders:Ray Arritt rwarritt@iastate.eduBill Gutowski gutowski@iastate.eduGene Takle gstakle@iastate.edu

Project Scientists:Chris AndersonDave Flory

Computations and Communications Consultant:

Daryl Herzmann

Scientific Consultant:

Zaitao Pan