REGIONAL CLIMATE AND VARIABILITY OF THE SUMMERTIME CONTINENTAL UNITED STATES IN REANALYSES

Michael G. Bosilovich (GSFC), Franklin R. Robertson (MSFC)

Motivation Global reanalyses assimilate many

observations, and the state fields can depict well the associated large scale circulation and weather variations

The background model produces many fields that are not observed regularly, if at all

How well are precipitation and temperature interannual variations represented in sub-continental regions? Focus on U.S. summer, when there are concerns

on extremes and when forecasts are most difficult

Modern-Era Retrospective analysis for Research and Applications (MERRA) 1979-Present (will not continue, depending on

remotely sensed observations) ½° lat x ⅔° lon, 42 pressure levels (derived from

72 terrain following model levels) 1 Hourly Surface/2D fields, 3 and 6 hourly 3D

fields; over 300 variables NCEP GSI analysis (~2008) GEOS5 GCM (~2008) New offline land and ocean reprocessing

products Gridded Innovations and Observations (GIO)

Additional Data

NCEP CFSR (Saha et al. 2010) Includes obs precipitation forcing in land analysis cycle

ERA Interim (Dee et al. 2011) Includes surface meteorology data assimilation

CPC Gauge Analysis (Chen et al. 2008) CRU 3.1 Surface Temperature (Mitchell and

Jones, 2005)

Regions

Regions track those defined For the USGCRP National Climate Assessment

• A first order approximation • Not optimal for some regional

climate features • Many results are also reflected

in basin scale evaluation (e.g. Mississippi River)

Summer Seasonal Precipitation

For MERRA dry southern plains, wet

northern Correlations are high or

comparable St Dev lean low, esp MW

0

1

2

3

4

5

NE SE MW GP SGP NGP NW SW US

Regional Precipitation JJA 79-08

CPC MERRA Interim CFSR

0.40.50.60.70.80.91.0

NE SE MW GP SGP NGP NW SW US

Regions Correlation JJA 79-08

MERRA Interim CFSR

0

0.2

0.4

0.6

0.8

1

NE SE MW GP SGP NGP NW SW US

Regional Precip JJA St Dev 79-08

CPC MERRA Interim CFSR

mm

day

-1

Regional Precipitation All reanalyses

agree well in NW In MW MERRA

underestimates anomaly magnitude

CFSR completely misses some anomalies

Interim has a persistent trend

-0.8

-0.4

0.0

0.4

0.8

1.2

1979

1980

1981

1982

1983

1984

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1986

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1989

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1991

1992

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1994

1995

1996

1997

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2000

2001

2002

2003

2004

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2007

2008

2009

2010

2011

NW JJA Precip Anomalies (mm day-1)

Gauge MERRA Interim CFSR

-1.5-1.0-0.50.00.51.01.52.0

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

MW JJA Precip Anomalies (mm day-1)

Gauge MERRA Interim CFSR

MERRA – Gauge Correlation

Barlow et al show some correlation of NW precipitation to ENSO

ENSO Connection

CPC ERA-I

CFSR MERRA

JJA Precipitation Correlation with MAM Niño34

Summer P and T Trends SE Pr – CFSR

discontinuity in 1998 ERA-I Pr – Systematic

decreasing trend over much of US

T – All have warming trends (MERRA largest)

Obs – new corrections may increase trends (Vose et al 2012)

00.10.20.30.40.50.6

NE SE MW GP SGP NGP NW SW US

79-08 JJA Temp Trend (K/Dec)

CRU31 MERRA Interim CFSR

-0.7-0.6-0.5-0.4-0.3-0.2-0.1

00.10.20.3

NE SE MW GP SGP NGP NW SW US

NCA Regions Trend JJA 79-08

Gauge MERRA Interim CFSR

Heat Wave Duration Index

5K above climatology for 5 day stretches Not exactly warming, but affected by warming Identifying an appropriate daily temperature

data set for comparisons

Max Precip in a Season

Largest precip occurrence each season at each grid point

Hurricane Season (Jun-Nov) shows increases along East Coast and SE US

MERRA represents the variability of the extreme precipitation well

Max Precip SLP/Ts Composite Anomaly

Compositing the most extreme years to show the supporting large scale environment

Low pressure in tropical Atlantic, with weaker westerly flow

SST Shows warm Atlantic, including off the east coast and La Niña Pacific pattern

Max vs Mean Precip Composite Anomaly

Daily Composites of Extremes

Choose days when mean T2m exceeds 90th% JAN days in the Northeastern US Strong southerly flow ahead of low pressure

to the west

Summary

MW weakness in precip variability seems a good target to learn about the system

Is the strong ENSO a feature of global reanalysis, or perhaps a weakness in the ability to generate local feedback or circulations?

EC surface station analysis has clear benefit for the near surface state representation (what about fluxes?) Developing satellite surface temperature assimilation

for GMAO systems