# Presentation: 556254

## Summer Season Predictions with the Next NCEP CFS Using 

**Summer Season Predictions with the Next NCEP CFS Using **
**Different Land Models and Different Initial Land States**

**Assistance from other EMC members:**
**Suru Saha, Cathy Thiaw, Shrinivas Moorthi**

- NOAA 32nd Climate Diagnostics and Prediction Workshop (CDPW)
- 22-26 October 2007

## Outline

**Operational CFS**
- CONUS summer season forecast skill: precip, 2m-T, Pacific SST
**Next-generation CFS**
- Analysis & physics upgrades: Atmos, Ocean, Land, Sea-Ice
- Double horizontal resolution
- CO2 trend
**CFS Experiment Design: ****Land & Summer Emphasis**
- Land Models: Two models (Noah LSM, OSU LSM)
- Land initial states: Two sources (Global Reanal 2, GLDAS)
**CFS Experiment Results:**
- CONUS precipitation & 2-m air temperature
- Pacific SST
**Conclusions & Future Work**
- Future Work: winter runs

## Performance of Currently Operational CFS:(shown in next four frames)

- -- SST (high correlation skill in tropical Pacific),
- -- CONUS precipitation (low correlation skill in summer)
- -- CONUS 2-m air temperature (low correlation skill in summer)

## 15-member CFS reforecasts

**15-member CFS reforecasts**

**CFS Tropical Pacific SST skill is very competitive with **
**empirical methods & their composite**

## Ops CFS Seasonal SST Forecast Skill:Correlation of CFS SST forecast with observed SST over 1982-2003For April initial conditions: 15-member ensemble mean

- More examples at: http://www.cpc.ncep.noaa.gov/products/people/wwang/cfs_skills/

**1-Month Lead**

**6-Month Lead**

- Correlation skill of SST prediction for central and eastern tropical Pacific is rather high

## Ops CFS Seasonal Precipitation Forecast Skill:Correlation of CFS precip forecast with observed precip: 1982-2003For April initial conditions: 15-member ensemble mean

- More examples at: http://www.cpc.ncep.noaa.gov/products/people/wwang/cfs_skills/

**1-Month Lead ****(valid **_**summer**_**)**

**6-Month Lead ****(valid **_**winter**_**)**

**Short-lead summer forecast correlation skill is low across bulk of CONUS **
**(lower than longer-lead winter forecast)**

## Ops CFS Seasonal Temperature Fcst Skill over CONUS:Correlation of forecast with observed 2mT over 22-year hindcastFor April initial conditions: 15-member ensemble mean

- More examples at: http://www.cpc.ncep.noaa.gov/products/people/wwang/cfs_skills/

**Short-lead summer forecast correlation skill is low across majority of CONUS**** **

## Experimental CFS versus Ops CFS:See workshop Monday presentation by Hua-Lu Pan et al.

- Upgrades to CFS physics
- Atmosphere, ocean, land, sea-ice
- Double the CFS resolution
- T126 / L64 versus T62 / L28
- New CFS vertical coordinate
- Hybrid sigma-pressure versus sigma
- New analysis systems
- Atmosphere, ocean, land

**The CFS experiments presented below incorporate the**
** ****upgrades highlighted above in red, with a focus on the land upgrades.**

## Experimental CFS: Land Model Upgrade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
- Other

**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

**Noah LSM replaced OSU LSM in operational NCEP medium-range**
**Global Forecast System (GFS) in **_**late May 2005**_

## Annual mean biases in surface energy fluxes:

**Annual mean biases in surface energy fluxes:**
**In five operational GCMs during 2003-2004**
**w.r.t. nine flux-station sites distributed world-wide**
**from K. Yang et al. (2007, J. Meteor. Soc. Japan)**

- _Mean Bias Error (MBE)_

***lE – Latent Heat Flux***
***H – Sensible Heat Flux***
***Rn – Net Radiation***
***μ – Global mean**** *

**Pre-May 2005 NCEP GFS had large positive bias**
**in surface latent heat flux and corresponding**
**large negative bias in surface sensible heat flux.**

## Mean GFS surface latent heat flux: 09-25 May 2005:

**Pre-May 05 GFS: with OSU LSM**

**Post-May 05 GFS: with new Noah LSM**

**Mean GFS surface latent heat flux: 09-25 May 2005:**
**Upgrade to Noah LSM significantly reduced the GFS surface latent heat flux**
**(especially in non-arid regions)**

## CFS Land Experiments: 4 configurations  Experiments of T126 CFS with CFS/Noah and CFS/OSU25-year summer reforecasts (10 member ensembles) from April initial conditions of 1980-2004

## Slide 13

## GLDAS versus Global Reanalysis 2 (GR2):Land Treatment

- GLDAS:  an _uncoupled_ land simulation system _driven by observed precipitation_ analyses (CPC CMAP analyses)
- Executed using same grid, land mask, terrain field and _Noah LSM_ as GFS in experimental CFS
- 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_
- _nudges soil moisture_ based on differences between model and CPC CMAP precipitation

## GLDAS/Noah (top ) versus GR2/OSU (bottom) 2-meter soil moisture (% volume)

**Observed 90-day**
**Precipitation Anomaly**
**(mm) valid 30 April 99**

**GLDAS/Noah (**_**top **_**)**** versus ****GR2/OSU (**_**bottom**_**)** **2-meter soil moisture** (% volume)
**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**

**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)

**The climatology of GLDAS/Noah soil moisture is higher and closer to the observed climatology than that of GR2/OSU**, while the anomlies of all three show generally better agreement with each other (though some exceptions)

## Results of CFS Experiments:

- All remaining frames

## JJA Precipitation Correlation Skill

- From hindcasts for years 1981-2004. Ten-member ensemble mean shown for each panel.

_**JJA**_** ****Precipitation Correlation Skill**

**CFS/Noah/GR2 case is clearly worst case** (least spatial extent of positive correlation).
- Remaining three cases appear to have similar spatial extent of positive correlation, but
- distributed differently among sub-regions. Still disappointingly small spatial extent of
- correlations above 0.5 in all four configurations.

## JJA Precipitation Correlation Skill

_**JJA**_** Precipitation Correlation Skill**

- As in previous frame, except Ops CFS result now shown in upper right panel.  Compared
- to Ops CFS, the three viable experimental CFS configurations do not show notably higher
- spatial extent of positive correlation nor notably higher values of positive correlation.
- Still disappointingly small spatial extent of correlations above 0.5 in all four configurations.

## OSU/GR2 somewhat better over CONUS & Noah/GLDAS worst over Canada

**  ****Noah/**
**GLDAS**

** ****Noah/**
**GLDAS**
** ****Climo**

**OSU/**
** ****GR2**

**Noah/**
**GR2**

**10 Members each case (same initial dates)**

**OSU/GR2 somewhat better over CONUS & Noah/GLDAS worst over Canada**

## All experimental configurations better than Ops CFS, mostly likely due to 

**  ****Noah/**
**GLDAS**

** ****Noah/**
**GLDAS**
** ****Climo**

**Noah/**
**GR2**

**All experimental configurations better than Ops CFS, mostly likely due to **
**CO2 trend included in experimental CFS but absent in ops CFS**

- This Frame same as previous, except Ops CFS (from 15 members) shown in lower right.

## JJA SST Correlation Skill

**CFS Noah/GLDAS**

**CFS Noah/GLDAS Climo**

**CFS Noah/GR2**

**CFS OSU/GR2**

_**JJA**_** SST Correlation Skill**

**All four configurations yield similar SST correlation patterns**

## JJA SST Correlation Skill

**CFS Noah/GLDAS Climo**

**CFS Noah/GLDAS**

**CFS Noah/GR2**

**Ops CFS**

- This Frame same as previous, except Ops CFS (from 15 members) shown in lower right.

_**JJA**_** SST Correlation Skill**

**Ops CFS (lower right) better in Nino 3.4 but worse over western warm pool**

## Conclusions & Future Work

- The relatively low CFS seasonal prediction skill for summer precipitation over CONUS is not materially improved by the tested upgrade in land surface physics and land data assimilation
- An upgrade to the land surface model of a GCM can possibly degrade GCM performance if the upgraded land model is not also incorporated into the data assimilation suite that supplies the initial land states
- The addition of a CO2 trend to the experimental CFS is likely the major source of the improvement in experimental CFS summer season surface temperature forecasts relative to the currently operational CFS
- The land model and land assimilation upgrades did not appear to materially increase the summer season surface temperature prediction skill of the CFS
- The use of initial soil moisture states with instantaneous soil moisture anomalies did not appear to provide an advantage over climatological soil moisture states, provided the soil moisture climatology was produced by the same land model being tested in the GCM
- The Tuesday workshop poster by Soo-Hyun Yoo et al. evaluated these same CFS experiments over the Asian-Australian Monsoon, showing modestly positive impact over that region from the land model upgrades presented here
- Future work will carry out this same suite of experiments for winter season hindcasts.