Identifying Extreme Precipitation in GPMfor Evaluating Climate ModelsBrian Medeiros, Kevin Reed, Erica Bower, Angeline Pendergrass, Julie Caron

Total annual meanprecipitation [mm/yr] (left),annual mean precipitationfrom Tropical Cyclones (TC)[mm/yr] (middle), andpercentage of the annualmean precipitation that isdue to TCs (right). Uppertwo rows showobservations, 3rd row is ahigh-resolution CESM1simulation (similar toHighResMIP models), 4throw is a low-resolutionCESM1 simulation (similar toCMIP models).

Annual maximum 5-dayaccumulated precipitation

(Rx5day) [mm/yr] (left),TC-related Rx5day

[mm/yr] (middle), andpercentage of Rx5day

events due to TCs (right).

OrganizedSystemsrole inclimatology

OrganizedSystemsrole in

extremes

Identify organized precipitation events from the GPM andTRMM products using a precipitation-focused approach

Classify organized precipitation events based on overlapbetween precipitation- and dynamically-based trackingalgorithms

Confront standard- and high-resolution models withobservations of organized precipitation

What are the characteristics of convective organization, includingfrequency, duration, location and spatial extent as observed bysatellites? How do organized events, including extreme forms ofweather, contribute to the probability distribution of precipitation,especially its extreme tail?

How are extreme precipitation events related to dynamically-driven weather phenomena?

Do high-resolution climate model simulations capture theobserved relationships between extreme precipitation andorganized convection better than conventional-resolutionsimulations?

TASKSQUESTIONS

non-

MCSP

recip

itatio

nMC

SPrecip

itatio

n PRESENT (1991-2005) FUTURE (2070-2099)

mm d-180°W100°W120°W80°W100°W120°W

30°N

40°N

50°N

30°N

20°N

40°N

50°N8

20

46

24

6

0

12

18

Composite May precipitation from CESM1 at 0.25°,separately for Mesoscale Convective Systems (MCS), andother. On the left is present, and on the right is a projectionof the late 21st Century.

High-resolution models

60

1 10−60

−30

0

30

1 10 1 10 100 0

0.05

0.1

0.15

0.2GPCP GPM TRMM

Three views of observed rain distributions. Note GPM &TRMM both have rain rates >50 mm d-1, while GPCPdoes not.

Contrast the observed rain distribution with CMIP5models. Most of these models have grid spacing around100 km. There is a large diversity among models, withmost being skewed toward lighter rain rates. Is this biasbecause of a lack of organized convection?

Rainamount(mm d-1)Rain rate [mm d-1]

Latit

ude

BCC−CSM1.1

−60−30

0

3060

BNU−ESM CCSM4 CESM1−BGC

CMCC−CESM

−60−30

0

3060

CMCC−CMS CNRM−CM5 CSIRO−Mk3−6−0

CanESM2

−60−30

0

3060

FGOALS−g2 GFDL−CM3 GFDL−ESM2G

GFDL−ESM2M

−60−30

0

3060

INM−CM4 IPSL−CM5A−LR IPSL−CM5B−LR

MIROC−ESM

−60−30

0

3060

MIROC−ESM−CHEM

1 10 100

MIROC5

1 10 100

MPI−ESM−LR

1 10 1001 10 100

Rain distributions:Models & Observations

SANDY

24 OCTOBER2012

40mm d-1

Tracking individual storms (upper: Sandy, lower:Irene) using TempestExtremes to find storm centersfrom ERA5 pressure. Compare tracks with the EPIC-ORCA tracked 95th percentile IMERGE rainfall.

High-impact events

IRENE

24 AUGUST2011