Quasi-Global and Regional Water Vapor and Rainfall Rate

Climatologies for a 35 Month Period

Kelly HowellMS Thesis Defense

July 9, 2010

2

Acknowledgements• Tom Vonder Haar and Stan Kidder, advisor and co-

advisor, for their many suggestions on the direction of this project and confidence in my success

• Chris Kummerow and Jorge Ramírez, committee members, for their time in reviewing this work

• Eric Guillot and Jessica Ram, officemates, for their continual encouragement, suggestions, and distractions

• Family and friends for their support and readiness to listen

• DoD Center for Geosciences/Atmospheric Research at CSU under Cooperative Agreement W911NF-06-2-0015 with the Army Research Laboratory for funding this research

3

Introduction

Motivation

• Use new datasets to create total precipitable water (TPW) and rainfall rate (RR) climatologies

• Further investigate the relationship between TPW and RR with the hopes of improving rain forecasting techniques:– In areas lacking adequate forecasting

capabilities– In areas that may experience flood-inducing

rainfall

5

September 5, 2008 at 00 UTC

Areas with elevated TPW

are often associated

with instances of rainfall.

Hurricane Ike

6

Domain

• Spatially, the data cover 60o S to 60o N at all longitudes at 0.25o×0.25o resolution.

• CMORPH covers the entire domain; bTPW covers the oceans. Over the continental US, bTPW is supplemented by GPS TPW estimates.

• Temporally, both datasets were sampled 6-hourly from February 2006 to December 2008 and used at 00, 06, 12, and 18 UTC.

• In all, 3928 time periods were used in this analysis, or approximately 92% of the temporal domain.

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Data• Total precipitable water (TPW) is the total

atmospheric water vapor in a vertical column, measured in mm. Data in this study come from the CIRA blended TPW product (bTPW), which combines TPW measurements from 6 instruments (Kidder and Jones 2007).

• Rainfall rate (RR) is the amount of rain that falls during a given amount of time. The data in this study come from the CPC morphing method product (CMORPH), which combines RR measurements from 7 instruments and uses an IR-based advection technique to fill in missing data (Joyce et al. 2004).

• In this project, ‘rainfall’ implies a RR≥0.1 mm hr-1.

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Satellite Instruments

Data type

Satellites

Sensor

Channels Used

Scan Type

Source

TPW

DMSP F-13, -14, -15

SSM/I 19, 22, 37 GHz

Conical Ferraro et al. 1996

NOAA-15, -16, -17

AMSU-A2

23.8, 31.4 GHz

Cross-track

Ferraro et al. 2005

RR

DMSP F-13, -14, -15

SSM/I 19, 22, 37, 85.5 GHz

Conical Ferraro 1997

NOAA-15, -16, -17

AMSU-B

89, 150, 183 GHz

Cross-track

Ferraro et al. 2005

TRMM TMI 10, 19, 21, 37, 85 GHz

Conical Kummerow et al. 1996

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Total Precipitable

Water Climatology

10

Annual Mean TPW (Trenberth 1998)

Mean global TPW is 24.52 mm (Trenberth et al. 2003).TPW maximizes north of the equator around 45 mm.

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Annual Mean TPW

The global mean TPW is 24.94 mm, with a maximum

of approximately 45 mm north of the equator.

West Pacific

Warm Pool

SPCZ ITCZ

Oceanic Deserts

12

Seasonal Mean TPW (Ferraro et al. 1996)

The seasonal changes in TPW are evident, particularly in the west Pacific warm pool during the JJA monsoon period and in the

eastward advancement of the SPCZ during DJF. In addition, the northernmost latitudes display their highest TPW values during JJA

and the southernmost latitudes display their highest TPW values during DJF, following the seasonal changes in solar insolation.

13

Seasonal Mean TPW

The seasonal TPW distributions are similar to previous findings, with the SPCZ extending its farthest eastward during DJF and TPW highs

around southeast Asia during the JJA monsoon period. The presence of a double ITCZ can be detected in the eastern tropical Pacific during

MAM. However, TPW values in the ITCZ are lower than the findings by Ferraro et al. (1996).

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Rainfall Climatology

15

Global Mean RR in mm day-1

(Legates and Willmott 1990)

Source Surface Typ

e

RR [mm day-

1]

CMAP Ocean 3.02

Land 1.86

Globe 2.69

Jaeger (1976

)

Ocean 2.91

Land 2.01

Globe 2.66

LW (1990

)

Ocean 3.15

Land 1.97

Globe 2.82Over land, rainfall maximizes over the Amazon Basin and the African rainforests. Over the

ocean, the most rainfall occurs in the ITCZ, the west Pacific warm pool, and the SPCZ. This plot was constructed based on rain gauge

measurements.

On average, ocean surfaces receive the

most rainfall while land surfaces receive the

least. Source: Xie and Arkin (1997).

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Annual Mean RR in mm day-1

Surface Type

RR [mm day-1]

Ocean 2.68

Land 2.57

All Surfaces

2.63

The oceans receive more rainfall than land

surfaces. The ITCZ receives the most

rainfall; the oceanic deserts receive the least.

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Annual Mean RR in mm year-1

(Ferraro et al. 1996)

Over land, rainfall maximizes just south of the equator. Over the oceans, there is a double peak in the tropics,

maximizing north of the equator.

The solid lines indicate Ferraro et al.’s (1996) findings; the dashed lines indicate findings from Legates and Willmott (1990).

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Annual Mean RR in mm year-1

The zonal mean RR distributions over ocean and land display similar trends to the findings by Ferraro et al. (1996), although these estimations are slightly higher.

Latitude (degrees N)

RR (m

m y

r-1)

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Annual Mean Rainfall Frequency

The zonal distributions of rainfall frequency are analogous to the zonal distributions of rainfall.

Overall, the oceans receive rain more frequently (11.04 %)

than land surfaces (8.58 %).

Latitude Zone

Ocean Frequency

Land Frequency

60-45o N 10.99 % 4.68 %

45-30o N 12.72 % 5.65 %

30-15o N 7.56 % 5.15 %

15-0o N 16.48 % 13.91 %

0-15o S 11.02 % 16.41 %

15-30o S 7.63 % 6.90 %

30-45o S 11.32 % 5.91 %

45-60o S 10.23 % 5.19 %

Latitude (degrees N)

Rainf

all F

requ

ency

[%]

Rainfall frequency = 100×

0.0

1.0

RR

RR

20

Seasonal Mean RR in mm month-1

(Ferraro et al. 1996)

Seasonal mean rainfall tends to follow the patterns of seasonal mean TPW, with the SPCZ extending its farthest eastward in DJF and monsoonal rains occurring over southeast Asia during JJA. Also notable is the presence of a southern branch of the ITCZ

during MAM.

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Seasonal Mean RR in mm month-1

Seasonal mean rainfall estimates from CMORPH are similar to the findings by Ferraro et al. (1996). The NH and SH land areas show large changes between DJF and JJA: the winter hemisphere’s land

areas receive very little rainfall.

22

Seasonal Mean Rainfall Frequency

(Ferraro et al. 1996)

Seasonal rainfall frequency patterns mimic rainfall patterns, with more frequent rain occurring over the areas that typically receive

more rainfall.

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Seasonal Mean Rainfall Frequency

Season

0.1 mm hr-1

0.5 mm hr-1

1.0 mm hr-1

DJF 10.31 % 4.88 % 2.76 %

MAM 10.30 % 4.79 % 2.76 %

JJA 10.17 % 5.00 % 2.92 %

SON 10.09 % 4.95 % 2.88 %

The global frequency distribution estimates are much higher than

those found by Ferraro et al. (1996), although the same patterns are present. Using the 0.1 mm hr-1

threshold, global frequencies hover around 10%.

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Regional Studies

25

TPW Threshold for Rainfall?

Average rainfall rate versus column water vapor for the eastern Pacific at various

tropospheric temperatures. 25% of the rainfall occurs for TPW values above a ‘critical value.’

Time series of (a) RR in mm hr-1,

(b) TPW in mm, and (c) global solar radiation at the Koto Tabang GPS station during JJA 2001. Rainfall does not tend to occur at times with

relatively low TPW.

Source: Wu et al. (2003) Source: Neelin et al. (2009)

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Regional Studies

Location Longitude

Latitude

East of Florida 70o W 30o N

Indian Ocean 75o E 8o S

East of Japan 142o E 35o N

South of Panama 83o W 4o N

South Atlantic Ocean

22o W 45o S

North Atlantic Ocean

30o W 50o N

West Pacific 155o E 6o N

Southeastern Pacific

120o W 8o S

SPCZ 170o E 10o S

The following plots were constructed using the data at

each of these grid points analyzed over all 35 months.

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TPW Distributions

Annual mean TPW is highly variable in the midlatitude location, relatively high in the tropical location, and

relatively low in the oceanic desert location.

Location Mean TPW

East of Florida 30.66 mm

West Pacific 54.28 mm

Southeastern Pacific

29.62 mm

TPW (mm)

Prop

ortio

n of

Tot

al O

ccur

renc

es

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RR Distributionst

oeEtE

)(

Location Slope of Fit

Rainfall Frequency

East of Florida

-0.58

11.11 %

West Pacific

-0.516

31.20 %

Southeastern Pacific

-1.556

2.29 %

Equation of exponential decay. A more negative slope indicates a faster rate of decay (i.e., there are relatively few heavy

rain events).

More negative slopes tend to be associated with lower rainfall frequencies.RR [mm hr-1]

Prop

ortio

n of

Tot

al O

ccur

renc

es

ln(P

ropo

rtio

n of

Tot

al O

ccur

renc

es)

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RR vs TPW

The shapes of these distributions approximate the TPW distributions. In general, the higher RRs occur at the

more frequently occurring TPW values. However, this is not the case

in the southeastern Pacific, where the highest RRs occur at higher TPW

values.

TPW (mm)

RR [m

m h

r-1]

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Probability of RainfallRR ≥ 0.1 mm hr-1

RR ≥ 3.0 mm hr-1

As rain intensity increases, rainfall

becomes less likely at lower TPW values.

TPW (mm)

Prob

abili

ty o

f Rainf

all [

%]

31

RR Distributions by TPW Range

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RR Distribution by TPW Range

TPW Range

Probability of Rainfall

0-15 mm 2.34 %

15-30 mm 7.64 %

30-45 mm 16.59 %

45-60 mm 29.89 %

60-75 mm 45.89 %

At higher TPW values, rainfall is

more probable and there is a higher

proportion of heavier rainfall.

RR [mm hr-1]

Prop

ortio

n of

Tot

al O

ccur

renc

es

33

RR Distribution by TPW Range

The RR distributions are not strictly exponential, but an

exponential fit is a consistent representation of the

distribution. Steeper slopes are associated with drier

environments.

TPW Range

Slope of RR Distribution

0-15 mm -1.01

15-30 mm -0.90

30-45 mm -0.70

45-60 mm -0.59

60-75 mm -0.49

ln(P

ropo

rtio

n of

Tot

al O

ccur

renc

es)

RR [mm hr-1]

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Conclusions

• The bTPW and CMORPH datasets result in climatologies that are comparable to those from previous studies. TPW, rainfall, and rainfall frequency are the highest in the ITCZ, SPCZ, and west Pacific warm pool, and the lowest in oceanic desert regions.

• Quasi-global mean TPW is 24.94 mm. • Quasi-global mean RR is 2.63 mm day-1. • The ocean receives rainfall in greater quantities

and more frequently compared with land surfaces.

• In a global mean sense, rainfall is more probable and higher RRs are more frequent at higher TPW values.

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Future Work

• Extend this study over land areas when an accurate TPW dataset over land becomes available.

• Incorporate CloudSat estimates into the RR results in order to better measure lighter rainfall events.

• Because TPW may not be detected when rain is present, estimate missing the TPW values in order to create more robust statistics.

• Use TPW anomaly data to compare with occurrences of rainfall.

• Incorporate regional TPW and RR characteristics into forecast and climate models.

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Questions?