Rongqian Yang, Ken Mitchell, Jesse Meng

Impact of Different Land Models & Different Initial Land States

on CFS Summer and Winter Reforecasts

Acknowledgment to : S. Saha, S. Moorthi, W. Wang, C. Thiaw

This development is sponsored by CPPA Program of the NOAA Climate Program Office

4th Annual Climate Test Bed Science Advisory Board Meeting11-12 September 2008

Project Sponsorship

This work is funded by the Climate Prediction Program for the Americas (CPPA) of the NOAA Climate Program Office.

No funding was received from the Climate Test Bed (CTB) program for this work, but the experimental design and importance was evaluated positively by CTB technical advisory group.

The CFS experiments were executed in the CTB partition of the NOAA Research Computer at NCEP.

Objective of this project:

Upgrade the land physics and initial land states of the CFS and assess the impact on T126 CFS summer and winter season reforecasts.

Motivation: While SST anomalies are believed to be the foremost source of seasonal predictability in coupled global models, land surface anomalies are generally believed to be the second most important source of seasonal predictability (e.g. anomalies of soil moisture, snowpack, vegetation cover)

Land Model Upgrade: In CFS experimentsNoah LSM (new) versus OSU LSM (old):

• Noah LSM– 4 soil layers (10, 30, 60, 100 cm)– Frozen soil physics included– Surface fluxes weighted by snow

cover fraction– Improved seasonal cycle of

vegetation cover– Spatially varying root depth– Runoff and infiltration account for

sub-grid variability in precipitation & soil moisture

– Improved soil & snow thermal conductivity

– Higher canopy resistance– More

• OSU LSM– 2 soil layers (10, 190 cm)– No frozen soil physics– Surface fluxes not weighted by

snow fraction– Vegetation fraction never less than

50 percent– Spatially constant root depth– Runoff & infiltration do not account

for subgrid variability of precipitation & soil moisture

– Poor soil and snow thermal conductivity, especially for thin snowpack and moist soils

Noah LSM replaced OSU LSM in operational NCEP medium-rangeGlobal Forecast System (GFS) in late May 2005

Initial Land States: Two Sources GLDAS/Noah & Global Reanalysis 2 (GR2/OSU):

• GLDAS: an uncoupled land assimilation system driven by observed precipitation analyses (CPC CMAP analyses)– Executed using same grid, land mask, terrain field and

four-layer Noah LSM as in experimental CFS forecasts– Non-precipitation land forcing is from GR2– Executed retrospectively from 1979-2006 (after spin-up)

• GR2: a coupled atmosphere/land assimilation system wherein land component is driven by model predicted precipitation– applies the OSU LSM with two soil layers– nudges soil moisture based on differences between

model and CPC CMAP precipitation

Observed 90-dayPrecipitation Anomaly(mm) valid 30 April 99

GLDAS/Noah (top ) versus GR2/OSU (bottom)

2-meter soil moisture (% volume)

May 1st Climatology 01 May 1999 Anomaly

Left column: GLDAS/Noah soil moisture climo is generally higher then GR2/OSUMiddle column: GLDAS/Noah soil moisture anomaly pattern agrees betterthan that of GR2/OSU with observed precipitation anomaly (right column: top)

GLDAS/Noah GLDAS/Noah

GR2/OSU GR2/OSU

Monthly Time Series (1985-2004) of Area-mean

Illinois 2-meter Soil Moisture [mm]:

Observations (black), GLDAS/Noah (purple), GR2/OSU (green)

Climatology

The climatology of GLDAS/Noah soil moisture is higher and closer to the observed climatology than that of GR2/OSU.

Choice of Land Model

Choice of

LandInitial

Conditions

GR2/OSU (CONTROL)GLDAS/Noah

GLDAS/Noah--CLIMO

GR2/OSU

CFS/Noah CFS/OSU

Summer CFS Experiments: all 4 configurations above (A, B, C, D) 25-year (1980-2004) summer reforecasts (10 member ensembles) from mid April and early May initial conditions

Winter Land Related Experiments: top 2 configurations in table (A & C) 24-year (1981-2004) winter reforecasts (10 member ensembles) from late Nov and Dec initial conditions

Four configurations of T126 CFS:A) CFS/OSU/GR2: - OSU LSM, initial land states from GR2 (CONTROL)B) CFS/Noah/GR2: - Noah LSM, initial land states from GR2C) CFS/Noah/GLDAS: - Noah LSM, initial land states from T126 GLDAS/NoahD) CFS/Noah/GLDAS-Climo: - Noah LSM, initial land states from GLDAS/Noah climo

CFS Experiment Design: four configurations

Summer Results

25-year (1980-2004) summer reforecasts (10 member ensembles) from mid April and early May initial conditions

Partition 25 summers (80-04) intoNeutral & Non-neutral samples

using MJJ Nino3.4 SST anomaly0.7C as a threshold

10 non-neutral summers:82,83,87,88,91,92,93,97,99,02 (red: warm, blue: cold)

15 neutral summers:80,81,84,85,86,89,90,94,95,96,98,00,01,03,04

10 non-neutral years: CONUS JJA precipitation AC score

WorstCase

15 neutral years: CONUS JJA precipitation AC score

WorstCase

Significance test (T-statistic) shows differences wrt third bar arenot significant at 90% confidence.

Significance test (T-statistic) showsdifferences wrt third bar aresignificant at 90% confidence.

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

OSU/GR2 Noah/GR2 Noah/GLDAS Noah/GLDAS C

Non-Neutral Years

-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0

0.01

0.02

0.03

0.04

OSU/GR2 Noah/GR2 Noah/GLDAS Noah/GLDAS C

Neutral Years

CONUS-average JJA precipitation AC score

0.18

0

0.04

-0.06

Winter Results

Only two of four configurations were executed:

-- OSU/GR2 (Control)-- Noah/GLDAS

24-year (1981-2004) winter reforecasts (10 member ensembles) from late Nov and Dec initial conditions

Partition 24 winters (1981-2004) intoNeutral & Non-neutral samples

using JFM Nino3.4 SST anomaly0.5C as a threshold

14 non-neutral winters:83, 85, 86, 87, 88, 89, 92, 95, 96, 98, 99, 00, 01, 03

10 neutral winters:81, 82, 84, 90, 91, 93, 94, 97, 02, 04

14 Non-neutral Years: CONUS JFM Precipitation AC Score:83, 85, 86, 87, 88, 89, 92, 95, 96, 98, 99, 00, 01, 03

10 Neutral Years: CONUS Domain JFM Precip AC Score:81, 82, 84, 90, 91, 93, 94, 97, 02, 04

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

Noah/GLDAS OSU/GR2

CONUS-average JFM precipitation AC scoreNon-neutral Years

I

Significance test (T-statistic) shows differences are not significant at 90% confidence

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

Noah/GLDAS OSU/GR2

Neutral Years

Significance test (T-statistic) shows differences are not significant at 90% confidence

0.2

0.2

0

0

Conclusions• When upgrading land surface model of coupled CFS, it is

imperative to upgrade to the same land surface model in the supporting data assimilation system

• Positive impact of land surface upgrade on CFS seasonal forecast skill for precipitation is very modest– Significant only for summer season in neutral ENSO years (and

then only very small positive impact)– Essentially neutral impact for winter season and non-neutral

ENSO summers

• For a given land configuration, differences in CONUS precipitation skill between neutral and non-neutral years appears larger than differences between two different land configurations for given sample of years– Confirming that impact of SST anomaly is indeed substantially

greater than impact of land surface configuration