Regional Climate Simulations of summer precipitation over the

United States and Mexico

Kingtse Mo, Jae Schemm, Wayne Higgins, and H. K. Kim

GoalsWhat is the best way to make

summer precipitation forecasts ?

a) Model resolution: Regional dependent

What is the horizontal/vertical resolution needed to have skillful forecasts?

b) Importance of the initial conditions

Is this just soil moisture ?

ExperimentsModel : T126L28 GFS simulations with observed SSTs

Two sets of experiments:

1) 2 AMIP runs from 1981-2000: SAS and RAS convection schemes;

2) Ensemble seasonal simulations from June 29/30 each year and run through 30 September from 1990-2001. 5- member ensemble

Model: T62L64 GFS simulations

Two sets of experiments

1). AMIP runs from 1950-2001: SAS convection scheme;

2). Ensemble seasonal simulations from June 29/30 each year and run through 30 September from 1990-2001. 5- member ensemble

The AMIP run does not have information on initial conditions , but ensemble simulations do

GFS Resolution and Precipitation in the Core Monsoon Region

Precipitation (mm day-1) (1981-2000)

month

Kim et al(2004)

T62

obs

T126

AMIP

200 hPa streamline for CDAS, T62 and T126 ensemble for 1988 and 1993 as examples.

The T62 does not recognize the Gulf of California

no moisture surges,

too dry over the SW,

circulation change leads to unrealistic monsoon circulation

negative feedback to monsoon rainfall

obsT62

T126

AMIP(90-100W,36-48N)

P observed, SIMU and AMIP

1) AMIP126 is too dry, AMIP62 is wetter, but has no skill.

2) Both SIMU126 and SIMU62 give reasonable amounts of P.

3) Corr (obs, SIMU62)=0.57

Corr(obs,SIMU126)=0.58

Near the 5% statistical significant level.

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

P (JAS) and T2m from observations, AMIP62 and SIMU62

The T62L64 model is less drier and cooler over southern Texas, but it is too dry over

the Southwest.

The differences between

SIMU126 and SIMU62 are small comparing to the differences between AMIP126 and AMIP62

Ensemble SIMU - AMIP 1990-2000 for T126L28

1. Over the central US: In comparison with AMIP, the ensemble SIMU has

High soil moisture from the top level more E less sensible heat cooler T2m

2. More E more P, (DQ is small )

More E more P

3. Relationship is also true for the T62L64 model, but the E (and P) over the central US is 1 mm/day less.

Does the AMIP126 dry out when the model runs forward?

The comparison of SM (JAS) averaged from 1981-2000 between the regional reanalysis and AMIP shows

1. After winter, the May SM shows only 5% difference between the RR and the AMIP;

2. This rate is nearly the same as summer progresses, the

AMIP126 does not dry out when summer progresses.

The AMIP126 produces less E when the summer progresses

The AMIP126 does not sustain E:

It is 0.5-1 mm/day less in May, but in August, the E difference increases to almost 2 mm/day or higher.

The model does not lose SM that much, but it loses E badly

Soil10cm and E for 1950-2001 for AMIP62

Soil10cm from AMIP62 and AMIP126 are similar, but AMIP62 has 1mm/day more E over the central US in comparison with T126

Over the Southwest, no P no E

Mean soil10cm and E over the Northern Plains (90-100W,36-48W)

Soil10cm E

Black (Jul) Red (August) Green (sep)

Soil 10CM

• AMIPs lacks variability in Soil 10cm

• Simulations have more Soil10cm, but the difference is only 0.03

E:

• Large similarity between SIMU126 and SIMU62;

• T62 gives higher level of E for the same Soil10cm

• AMIPs lack of variability in E

RR

AMIP126

SIMU126

AMIP62

SIMU62

For AMIP (Blue) and the RR (Green), each summer month (June-September) is one dot,For SIMU (Red), each summer month (July-September) each member in the ensemble is one red cross

E is not only a function of soil moisture, it also depends on other energy terms and circulations

The mean SM is around 0.21 soAMIP: E=1.75 +22.6*(SM-0.21)RR: E=3.28+27.5*(SM-0.21)SIMU: E= 1.73+25.1*(SM-0,21)

Importance of initial conditions on P fcsts over central US

• Vertical resolution improves the E/SM relationship.

• Accurate initial conditions are important not just because realistic soil moisture. They give realistic circulation anomalies and energy balance terms to take advantage of soil conditions,

• AMIP is not upper limit of forecast skill.• Improve of surface data set like using satellite

derived weekly vegetation fraction may help

Conclusions• Seasonal forecast is not just a boundary

condition problem. The initial conditions are also important;

• Initial SM gives interannual variability and increase fcst skill

Can we improve simulations by downscaling?

Experiments: Season forecasts for 4 cases based on

• A) T126L28 GFS Model (approx 80 km)

• B) T62L28 GFS model (approx 200 km)

• C) T62 with RSM80 downscaling (80km) Impact of downscaling: T126 vs T62/RSM80

CASES shown :1988JJA, 1993 JAS, 1999JAS and 2000JAS with observed SSTs

Observed Precipitation

1988 : Drought;

1993: Floods

Difference: classic 3 cell pattern

1999: wet SW monsoon;

2000: dry SW

Seasonal mean P from unified P data

1993-1988 1999-2000

T62 ensemble mean ( 8 members)

1993-1988 1999-2000 T62 model

It captures P over the Central

US, but it is too coarse to

simulate monsoon rainfall

over the SW.

Ensemble P simulations from the T126 GFS

The T126 model captures the 1988 drought and the 1993 floods and gives more realistic monsoon rainfall over the SW.

Season mean P from T126 ensemble simulations

1993-1988 1999-2000

RSM80/T62 simulationsOverall P simulation improves by downscaling, but RSM can not correct errors from T62 and improve

P over the NAME region.

RSM/T62 enesmble

Conclusions

• If the global forecast is good, the RSM is better

• If the global forecast is not realistic, then the RSM downscaling will not correct the global model errors and improve fcsts.

RSM simulations SIB

The Southwest & Texas are way too dry

July 1999

SIB

USGS

USGS has more E over AZNM and stronger LLJ from G. of Calif

2 0-km RSM nested into 50-km RSM outputs

USGS-USGS

USGS surface conditions

USGS 50-km bdry conditions

Downscaling from the 50-km RSM

USGS-SIB

USGS surface conditions

SIB 50-km bdry conditions

More local E but weak Qflux into the SW

SIB-USGS

SIB surface conditions

USGS 50-km bdry conditions

Less local E, but strong Qflux into the SW

Conclusions

• Over the Southwest,the impact of E to P is not large. E and P can not sustain locally.

• It depends on the large scale circulation.

• The horizontal resolution has to be ;large enough to resolve the Gulf of California, the LLJ and moisture transport