# Presentation: 452023

## - 2

***-****** ******2***

**The 2****nd**** phase of the **
**Global Land-Atmosphere Coupling Experiment**

- Randal Koster
- GMAO, NASA/GSFC
- randal.d.koster@nasa.gov

## GLACE-1 was a successful international modeling project that looked at soil moisture impacts on precipitation... 

- GLACE-1 was a successful international modeling project that looked at soil moisture impacts on precipitation...

- Where precipitation responds to variations in soil moisture, according to the 12 GLACE models.

## Motivation for GLACE-2

- For soil moisture initialization to add to subseasonal or seasonal _**forecast skill**_, two criteria must be satisfied:

- An initialized anomaly must be “remembered” into the forecast period, and
- The atmosphere must be able to respond to the remembered anomaly.

**Addressed**
**by GLACE**

**Addressed**
**by GLACE2:**
**the full**
**initialization**
**forecast **
**problem**

## Outline of Talk

**Outline of Talk**

- Experiment overview
- Technical issues
- Diagnostic output
- Analyses
- Encouraged supplemental runs
- Status

## GLACE-2:

**Experiment Overview**

- Perform ensembles of retrospective seasonal forecasts

- Initialize land states
- with “observations”, using GSWP approach

- Prescribed, observed SSTs or the use of a coupled ocean model

- Initialize atmosphere with “observations”, via reanalysis

- Evaluate forecasts against observations

_**Step 1:**_

## GLACE-2:

**Experiment Overview**

- Perform ensembles of retrospective seasonal forecasts

- Initialize land states
- with “observations”, using GSWP approach

- Prescribed, observed SSTs or the use of a coupled ocean model

- Initialize atmosphere with “observations”, via reanalysis

- Evaluate forecasts against observations

_**Step 2:**_

**“****Randomize” land**
**initialization!**

## GLACE-2:

**Experiment Overview**

_**Step 3:**_**  **Compare skill; isolate contribution of realistic land initialization.

- Forecast skill obtain in experiment using realistic land initialization

- Forecast skill obtained in identical experiment, except that land is not initialized to realistic values

- Forecast skill due to land initialization

## FORECAST START DATES

- Apr 1

- 1986

- 1987

- 1988

- 1989

- 1990

- 100 different 10-member forecast ensembles.
- Each ensemble consists of 10 simulations, each running for 2 months.

- 1991

- 1992

- 1993

- 1994

- 1995

- Apr 15

- May 1

- May 15

- Jun 1

- Jun 15

- Jul 1

- Jul 15

- Aug 1

- Aug 15

## 100

- forecast
- start
- dates

- 10
- ensemble
- members
- per
- forecast

- 1/6
- years
- (2 months)
- per
- simulation

- 2
- experiments
- (including
- control)

- X

- X

- X

- =  333 years of simulation

## LSM

- precipitation

- Wind speed, humidity, air temperature, etc.
- from reanalysis

- Observed
- radiation

- A decade of LSM initial conditions for seasonal forecasts

- The resulting LSM initial conditions reflect observed antecedent atmospheric forcing.

**LAND STATE INITIALIZATION**
- via offline simulations, a la GSWP

- A decade of offline integration

## Outline of Talk

**Outline of Talk**

- Experiment overview
- Technical issues
- Diagnostic output
- Analyses
- Encouraged supplemental runs
- Status

## Model resolution:  Decided by participating groups.

_**Land initialization:**_  Best to be generated independently by each group using existing GSWP experimental design.  *Could* be provided by GLACE-2 organizers, if proper scaling is performed.
_**Atmospheric initialization:**_  Reanalysis.
_**Ocean boundary condition:**_  GLACE-2 organizers will provide SST fields (persisted anomalies), or groups may use coupled ocean model.

## Outline of Talk

**Outline of Talk**

- Experiment overview
- Technical issues
- Diagnostic output
- Analyses
- Encouraged supplemental runs
- Status

## Required output diagnostics (to be provided to GLACE data center):

- 1.  For each of the 4 15-day periods of each forecast simulation, provide global fields of:
- 15-day total precipitation
- 15-day average near-surface air temperature (in the lowest AGCM level)
- 15-day total evaporation
- 15-day average net radiation
- 15-day average vertically-integrated soil moisture content.
- 15-day average near-surface relative humidity

## Required output diagnostics (to be provided to GLACE data center):

- 2.  For each day of the first 30 days of certain forecast simulations, provide global fields of:
- vertically-integrated soil moisture content.

- This will allow us to analyze the decay with lead time of the information provided by soil moisture initialization.
- The forecast simulations chosen for this output are:
- Apr. 1, May 1, June 1, July 1, and Aug. 1 of 1986, 1988, 1990, 1992, and 1994.

## Outline of Talk

**Outline of Talk**

- Experiment overview
- Technical issues
- Diagnostic output
- Analyses
- Encouraged supplemental runs
- Status

## 1. Determine maximum level of precipitation (and air temperature) predictability associated with land initialization.

**1. Determine maximum level of precipitation (and air temperature) predictability associated with land initialization.**

- Results from pilot study of Koster et al. 2004

## 2. Determine forecast skill for precipitation (and air temperature) associated with land initialization.

- Regress full forecast against actual observations to retrieve r2.

**2. Determine forecast skill for precipitation (and air temperature) associated with land initialization.**

## Contributions of land moisture initialization to the skill of subseasonal (one-month) forecasts of P and T

**Contribution to skill: **
**P forecasts**

**Contributions of land moisture initialization to the skill of subseasonal (one-month) forecasts of P and T**

**Contribution to skill:**
** ****T forecasts**

- Koster et al., *Journal of Hydrometeorology,5*, pp. 1049-1063, 2004

- Results from pilot study of Koster et al. 2004

## Outline of Talk

**Outline of Talk**

- Experiment overview
- Technical issues
- Diagnostic output
- Analyses
- Encouraged supplemental runs
- Status

## Repeat Series 1 and Series 2 over a lengthier time period.

*Selected start dates from 50 years, using land conditions produced offline with Sheffield et al. (2006) data.*

- Apr 1

- 1950

- 1951

- 1952

- 1953

- 1998

- 1999

- 2000

- Apr 15

- May 1

- May 15

- Jun 1

- Jun 15

- Jul 1

- Jul 15

- Aug 1

- Aug 15

- Choose dates of forecasts based on presence of large initial anomaly in region known to have high predictability.

## ALSO...      

- Austral summer forecasts.  By shifting the GLACE-2 start dates by 6 months, participants may redo the experiment(s) for Austral summer.  Data will be analyzed at the GLACE-2 data center.
- Idealized predictability analysis in absence of observations-based initializaiton.

## Outline of Talk

**Outline of Talk**

- Experiment overview
- Technical issues
- Diagnostic output
- Analyses
- Encouraged supplemental runs
- Status

## Timeline

**Spring, 2007:** 		**Obtained funding for GLACE-2!**
- Summer 2007:		Finish identifying interested
- 			     modeling groups
- Summer 2007:		Provide data to participants 				     (meteorological forcing data,
- 			     atmospheric initialization, SST
- 			     conditions)
- Summer/Fall 2008:	Simulations due
- Fall/Winter 2008: 	First analyses performed

## Interested participants (so far)

- _Model / Group_				_Contact  _
- _   _
- 1.  GMAO (NASA/GSFC) 			R. Koster
-                   (old system and new system)
- 2.  COLA					P. Dirmeyer
- 3.  NCEP GFS/CFS				E. Wood, L. Luo
- 4.  U. Tokyo					T. Yamada
- 5.  ECHAM5					S. Seneviratne
- 6.  ECMWF IFS				B. van den Hurk,
- 							     H. Camargo
- 7.  BMRC					B. McAvaney

## Do you want to participate?

- If so, contact Randy Koster at randal.d.koster@nasa.gov

## Do you want to participate?

- If so, contact Randy Koster at randal.d.koster@nasa.gov

- Thank you!

## Slide 28

## Back-up slides

## 1. GLACE-2 will first perform an idealized analysis:

- For a given ensemble forecast, assume that the first ensemble member represents “nature”.

**STEP 1:**

- Assume that the remaining ensemble members represent the “forecast”.

**STEP 2:**

- Forecasted
- precipitation
- anomaly
- (mm/day)

- 0

- 1

- 2

- 3

- 4

- -1

- -2

- -3

- -4

- Ensemble member

- 1

- 2

- 3

- 4

- 5

- 6

- 7

- 8

- 9

- 10

## STEP 1:

**STEP 1:**

- Assume that the remaining ensemble members represent the “forecast”.

**STEP 2:**

**STEP 3:**

- Determine the degree to which the “forecast” agrees with the assumed “nature”.

- Precipitation
- anomaly
- (mm/day)

- 0

- 1

- 2

- 3

- 4

- -1

- -2

- -3

- -4

- Ensemble member

- 1

- 2

- 3

- 4

- 5

- 6

- 7

- 8

- 9

- To what extent does this anomaly...

- ... agree with the average of these anomalies?

- 10

- 1. GLACE-2 will first perform an _idealized analysis_:

## Regress “forecast” against “observations” to retrieve r2, a measure of forecast skill. 

- Regress “forecast” against “observations” to retrieve r2, a measure of forecast skill.

## STEP 1:

**STEP 1:**

- Assume that the remaining ensemble members represent the “forecast”.

**STEP 2:**

**STEP 3:**

- Determine the degree to which the “forecast” agrees with the assumed “nature”.

- This analysis effectively determines the degree to which atmospheric chaos foils the forecast, under the assumptions of “perfect” initialization, “perfect” validation data, and “perfect” model physics.

**STEP 4:**

- Repeat multiple times, with each ensemble member in turn taken as “nature”.  Average the resulting skill diagnostics.

- 1. GLACE-2 will first perform an _idealized analysis_:

## 100     x    10    x    4    x     6    x    2   =   48000

- # of start dates

- # of ensemble
- members

- # of periods

- # of variables

- experiment
- and control

## WI values for 7 different GSWP-2 models over a point in the U.S. Great Plains.

**WI values for 7 different GSWP-2 models over a point in the U.S. Great Plains.**

- 1988 drought

- 1993 drought

**The unprocessed soil water diagnostics (shown here as degree of saturation) are not nearly as model-independent.**

- 1986

- 1987

- 1988

- 1989

- 1991

- 1990

- 1992

-   1994

- 1993

- 1995

- 1986

- 1987

- 1988

- 1989

- 1991

- 1990

- 1992

-   1994

- 1993

- 1995