Rongqian Yang, Kenneth Mitchell, Jesse Meng NCEP Environmental Modeling Center (EMC) Summer and Winter Season Reforecast Experiments with the NCEP Coupled Forecast System (CFS) using Different Land Models and Different Initial Land States Acknowledgment to : S. Saha, S. Moorthi, W. Wang, C. Thiaw This development is sponsored by CPPA Program of the NOAA Climate Program Office 33 rd Annual Climate Diagnostics and Prediction Workshop 21 October 2008

Objective of this project: Upgrade the land physics and initial land states of the NCEP Climate Forecast System (CFS) and assess the impact on 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 experiments: Noah 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-range Global Forecast System (GFS) in late May 2005 Many Noah LSM upgrades & assessments were result of collaborations with CPPA PIs

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

Monthly Time Series ( ) Area-average 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.

Observed 90-day Precipitation Anomaly (mm) valid 30 April 99 GLDAS/Noah (top ) versus GR2/OSU (bottom) 2-meter soil moisture (% volumetric) May 1 st Climatology 01 May 1999 Anomaly Left column: GLDAS/Noah soil moisture climo is generally higher then GR2/OSU Middle column: GLDAS/Noah soil moisture anomaly pattern agrees better than that of GR2/OSU with observed precipitation anomaly (right column: top) GLDAS/Noah GR2/OSU

Choice of Land Model Choice of Land Initial Conditions GR2/OSU (CONTROL)GLDAS/Noah GLDAS/Noah--CLIMO GR2/OSU CFS/NoahCFS/OSU Summer CFS Experiments: all 4 configurations above (A, B, C, D) 25-year ( ) 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 ( ) 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 GR2 C) CFS/Noah/GLDAS: - Noah LSM, initial land states from T126 GLDAS/Noah D) CFS/Noah/GLDAS-Climo: - Noah LSM, initial land states from GLDAS/Noah climo CFS Experiment Design: four configurations

Summer Results 25-year ( ) CFS summer reforecasts (10 members) from mid April and early May initial conditions

Partition 25 summers (80-04) into ENSO Neutral & Non-neutral samples using MJJ Nino3.4 SST anomaly 0.7C as a threshold magnitude 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 ENSO years: JJA precipitation AC score Worst Case

15 neutral ENSO years: JJA precipitation AC score Worst Case Next Worst Case

Significance test (T-statistic) shows differences wrt third bar are not significant at 90% confidence. Significance test (T-statistic) shows differences wrt third bar are significant at 90% confidence. Non-Neutral Years Neutral Years CONUS-average JJA precipitation AC score

Winter Results Only two of four configurations were executed: -- OSU/GR2 (Control) -- Noah/GLDAS 24-year ( ) winter reforecasts (10 members) from late Nov and Dec initial conditions

Partition 24 winters ( ) into ENSO Neutral & Non-neutral samples using JFM Nino3.4 SST anomaly 0.5C as a threshold magnitude 14 non-neutral winters: 83, 85, 86, 87, 88, 89, 92, 95, 96, 98, 99, 00, 01, neutral winters: 81, 82, 84, 90, 91, 93, 94, 97, 02, 04

14 Non-neutral Years: JFM Precipitation AC Score: 10 Neutral Years: JFM Precipitation AC Score:

CONUS-average JFM precipitation AC score Non-neutral Years I Significance test (T-statistic) shows differences are not significant at 90% confidence Neutral Years Significance test (T-statistic) shows differences are not significant at 90% confidence

Conclusions When upgrading the land surface model of the 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 modest –Significant only for summer season and only in neutral ENSO years (and then only small positive impact) –Essentially neutral impact for winter season and non-neutral ENSO summers Differences in CFS precipitation skill over CONUS between neutral and non-neutral ENSO years is larger than the skill differences between two different land configurations for same sample of years –Indicates that impact of SST anomaly is greater than impact of land surface configuration