NAME Climate Process and Modeling Team/Issues for Warm Season Prediction

J. Schemm and D. GutzlerCPC/NCEP/NWS/NOAA

University of New Mexico

The 30th Climate Diagnostics and Prediction workshop

The Pennsylvania State University

October 24-28, 2005

Acknowledgements: Myong-In Lee, Soo-Hyun Yoo and Lindsey Williams

NAME Climate Process and Modeling Team- supported by NOAA/OGP CPPA program

Team members:

David Gutzler, University of New MexicoWayne Higgins, CPC/NCEP/NWS/NOAABrian Mapes, University of MiamiKingtse Mo, CPC/NCEP/NWS/NOAAShrinivas Moorthi, EMC/NCEP/NWS/NOAAJae-Kyung Schemm, CPC/NCEP/NWS/NOAASiegfried Schubert, GMAO/GSFC/NASAGlenn White, EMC/NCEP/NWS/NOAA

Project Objectives:

1. Implementation of the second phase of NAME Model Assessment Project (NAMAP2) focused on the 2004

season.

2. Coordinated efforts with the current NAME Diurnal Cycle Experiment Project in GCM diagnostics.

3. Implementation of their findings to the NCEP GFS/CFS operational forecast system - NOAA Climate Test Bed.

4. Serve as a primary mechanism for collaboration andtechnology transfer between research communities andoperational centers.

NAMAP Analysis: Metrics for model development

• Improved simulation of monsoon onset, especially in global models

• Goals for improvement of precipitation (total amount and diurnal variability) and surface flux simulations, tied to improvements in ground truth to be achieved from NAME 2004 field observations

• Questions regarding the structure of low-level jet circulations and their importance for proper precipitation simulation

NAMAP2 - A coordinated exercise in global and regional atmospheric modeling

of NAMS.

- Summer 2004 is the simulation target.

- Simulation protocols have been developed and announced among potential participants.

- Focus on uncertainties identified in NAMAP, with additional emphasis on verification using enhanced observations from the NAME 2004 field campaign.

- Results based on the first NAMAP published in BAMS, Oct. 2005.

NAMAP2

- Will re-examine the metrics proposed by the first NAMAP.

- For proper specification of SSTs in the Gulf of California, a new SST analysis has been developed by W. Wang and P. Xie of CPC.

Simulation Period 15 May- 30 September 2004

Domain of I nterest 15°N- 45°N 125°W- 75°W

Lateral Boundary Conditions (f or regional models)

NOAA CDAS2 (to be supplied)

Surf ace Boundary Conditions/ oceanic

Multiple- Platf orm- Merged Analysis (to be supplied; see description below)

Surf ace Boundary Conditions/ continental

Chosen by each modeling group

NAMAP2 Protocols

abbrv field abbrv field

Ms sfc soil moisture Ts temperature (surface)

Msub subsfc soil moisture T2m temperature (2m)

Msca sfc soil moisture cap T850 temperature (850 hPa)

Msub subsfc soil mois. cap T500 temperature (500 hPa)

Rs sfc runoff T300 temperature (300 hPa)

Rsub subsfc runoff Zs geopot ht (surface)

Veg Vegetation stress Z850 geopot ht (850 hPa)

SWs net sfc SW flux (+dn) Z500 geopot ht (500 hPa)

LWs net sfc LW flux (+up) Z300 geopot ht (300 hPa)

LHs sfc latent flux (+up) Q10m specific humid (2m)

SHs sfc sensible flux (+up) Q850 specific humid (850 hPa)

As albedo (surface) Q500 specific humid (500 hPa)

Ap albedo (planetary) Q300 specific humid (300 hPa)

SLP sea level pressure U10m zonal wind (10m)

OLR outgoing LW flux (TOA) U850 zonal wind (850 hPa)

Topo surface elevation (ASL) U500 zonal wind (500 hPa)

CWco column condensed H2O U300 zonal wind (300 hPa)

Qco column specific humid V10m merid wind (10m)

QUco vert integrated QU V850 merid wind (850 hPa)

QVco vert integrated QV V500 merid wind (500 hPa)

CWlt sfc- 700hPa cond H2O V300 merid wind (300 hPa)

Qlt sfc- 700hPa spec hum Pcon precip (convective)

QUlt sfc- 700hPa cond QU Pres precip (resolved)

QVlt sfc- 700hPa cond QV CAPE convective available PE

CWut 700hPa- top cond H2O Cin convective inhibition

Qut 700hPa- top spec hum

QUut 700hPa- top cond QU

QVut 700hPa- top cond QV

a) For spatial analysis:Archive lat-lon fields covering the NAMAP2domain every 3 hours (8/day) during simulation period. Fields to archive:

Output Archiving Protocols

site lat lon site lat lon

NAME sounding sites US, Cent Amer. raobs

Puerto Penasco (ISS 2) 31.18N 113.33W Tucson (NWS) 32.12N 110.92W

Bahia Kino (ISS 3) 28.81N 111.93W Las Vegas (NWS) 36.62N 116.02W

Los Mochis (ISS 4) 25.41N 109.05W San Diego (NWS) 32.85N 117.12W

Loreto (GLASS) 26.01N 111.21W Flagstaff (NWS) 35.23N 111.82W

RV Altair (CSU) 21.49N 106.07W Albuquerque (NWS) 35.05N 106.62W

SMN sites El Paso (NWS) 31.87N 106.70W

Empalme 27.95N 110.77W Amarillo (NWS) 35.23N 101.70W

Mazatlan 23.20N 106.42W Midland (NWS) 31.95N 102.18W

Chihuahua 28.63N 106.08W Del Rio (NWS) 29.37N 100.92W

Torreon 25.53N 103.45W Yuma (ARMY) 32.51N 114.00W

Monterrey 25.87N 100.23W Phoenix (SRP) 33.45N 111.95W

Zacatecas/Guadalupe 22.75N 102.51W Belize City, Belize 17.53N 88.3W

La Paz 24.17N 110.30W

Mexico City 19.4N 99.2W

b) For high-resolution temporal analysis:

Archive "MOLTS"-style time series (at least hourly in time and full vertical resolution). We will consider surface fluxes and profiles of humidity, T, u, v, w, p, resolved and convective precipitation, cloud fraction, radiation, and turbulence at model grid points corresponding to the following NAME sounding sites: 

Output Archiving Protocols

A Multi-Platform-Merged (MPM) SST Analysis over the NAME Domain

Wanqiu Wang and Pingping Xie

Climate Prediction Center

NCEP/NWS/NOAA

To create a fine-resolution SST analysis with desirable resolutions and accuracy for NAME Projects

Resolution: 0.25o in space, 3-hour in time

Domain: 180o – 30oW, 30oS – 60oN

Target Period:2001 – present

Input data: All available in-situ and advanced satellite observations

Quality control: Cross verification to ensure data quality

Bias correction: Removal of large-scale/low-frequency bias in satellite observations

OI analysis: Combining SST data from all observations through the Optimal Interpolation (OI)

Input Data In-situ observations

Buoys and ships

Satellite ObservationsGOES: 3-hourly / clear sky

TMI: twice daily / all skyAMSR: twice daily / all sky

NOAA16: twice daily / clear sky

NOAA17: twice daily / clear sky

MODIS: Not included yet.

Input SST for AMJ 2004

Similar Spatial distribution Pattern;

Differences in small-scale features and in magnitude

Current Status

Developed prototype algorithm to define the analysis

Produced analysis for 2004

Conducted preliminary comparison with existing analyses (OI and RTG)

Some quick analysis statistics

OI RTG MPM0.70 K 0.60 K 0.48 K

OI: Weekly Optimum Interpolation

RTG: Real-Time Global analysis (2DVAR)

MPM: Multi-Platform-Merged Analysis

Magnitude of accuracy: RMS difference in daily mean between analyses and moored buoy (May 15 to Sep 30, 2004)

Magnitude of mean bias: RMS difference in seasonal mean between analyses and all in situ (Jun 1 to Aug 31, 2004)

OI RTG MPM0.44 K 0.32 K 0.19 K

Mean difference (K) between analyses

and in situ observations(Jun 1 to Aug 31, 2004)

MPM shows smaller bias

Note: In situ observations were used in all analyses. However, MPM is probably less dependent on the in situ because the use of much larger amount of satellite observations.

Issues involved in warm season predictability over NAME area

Model sensitivity on1. Horizontal resolution2. Continental boundary conditions3. Oceanic boundary condition

Physical processes1. Vertical sounding analysis - test for model convection schemes. 2. Surface flux and PBL formulations

Coordinated activities with the NAME Diurnal Cycle Experiment Project (S. Schubert, PI)

1. Collaborative effort among NASA, GFDL and NCEP.

2. GCM diagnostics focused on diurnal cycle over NAME domain.

3. Findings of this project to be tested on NCEP GFSand CFS GCMs.

ObsGFDLNCEPNASANARR

Figure 1

GFS Resolution and Precipitation in the Core Monsoon RegionPrecipitation (mm day-1) Seasonal Cycle (1981-2000)

T62

obs

T126

month

P (JAS) & T2m from observations, AMIP126 and SIMU126

In comparison with observations:

The AMIP is too hot (2 C higher) and too dry (2 mm/day less ) over the Great Plains ;

The SIMU ensemble means are closer to the observations

Area Mean of Climatological Precipitation

Anomaly Correlation Scores of 2m Temperatureover US Region; RNL2

Summary• NAMAP2 protocols have been developed and posted at

UCAR/JOSS website. A special SST analysis provided by Wang and Xie of CPC

• Coordinated with the NAME Diurnal Cycle Project, impact of GCM horizontal resolution on warm season precipitation over NA has been examined.

• Initial soil moisture is important in reducing systematic error and seasonal progression of precipitation and surface temperature.

• Role of ocean boundary condition will be examined with

the new improved SST analysis.