Tropical Moisture Exports and Extreme Rainfall

Mengqian Lu and Upmanu LallEarth and Environmental Engineering, Columbia University, NY, NY, United States.

Columbia Water Center: Global Flood Initiative

Flood Risk and Changing Climate Typical Hypothesis: Since the water holding

capacity of the atmosphere increases with warming, extreme rain events will become more frequent

But where … and in which seasons? Are most extreme floods over large basins due to

local convection or large scale moisture transport? What aspects of circulation are important for

floods? Specifically, what role is played by organized

tropical moisture exports (TME)?

AV. ATMOSPHERIC MOISTURE TRANSPORT ASSOCIATED WITH THE TOP 10 FLOODS AT DIFFERENT LOCATIONS

Source: Hyun-Han Kwon

Columbia Water Center Global Flood Initiative

Major TME Source regions and their seasonality for N Hemisphere1979-2011

Knippertz & Wernli 2010, 2013

50˚N

45˚N

46˚N

47˚N

48˚N

49˚N

3˚W4˚W5˚W 2˚W 1˚W

High:420Low:-81 (m)

Brittany

A Flood in France & Germany in January 1995 Lu et al 2013

The TME Train Day by DayLu et al 2013

0

100

200

300

400

500

600

0

100

200

300

400

500

600

700

800

900

1st 6th 11th 16th 21st 26th 31st

No. of TracksΔQ (g/kg)

TME birth date in January 1995

No. of Tracks entered the areaTotal Specific Humidity Released

Daily TME’s entering the French region and associated Specific Humidity release for the French region

Lu et al 2013

17 Jan 1995 to 28 Jan 1995 mid-latitude daily SLP anomaly field evolution Lu et al 2013

(a)

(b)

Leading PC modes of mid-latitude daily January Sea Level Pressure fields that are correlated with January rain in the French regionDiagnosed from MERRA January data excluding 1995

GLM based prediction of area averaged daily rainfall using SLP PC’s Model built without using January 1995 data 53% variance explained in out of sample prediction

Lu et al 2013

Back to the USA…………

Where do the storm tracks for the N. E. USA come from?

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

Monthly Correlation with number of tracks entering Northeast USA

Days with Rain>90%Days with Rain<10%Monthly DQ

Corre

latio

n

1989-2010 data

Major TME Source regions and their seasonality for N Hemisphere1979-2011

Knippertz & Wernli 2010, 2013

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

-0.10

0.00

0.10

0.20

0.30

0.40

0.50

0.60 Probability of a Track entering the NE from a given source by Month

P(NE|PE)P(NE|WP)P(NE|GS)P(NE|GP)

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

Probability that a track entering the NE came from a particular source by month

P(PE|NE)P(WP|NE)P(GP|NE)P(GS|NE)

FLOODS EXCEEDING THE 10 YEAR FLOOD ACROSS OHIO RIVER SUB-BASINS

Robertson et al, 2013

(a) Vertically integrated 600 mb - surface moisture flux in kg m s-1 (strongest 20 percent of values shown as arrows) and moisture convergence in gm-2s-1 (contours) for drainage basins (size > 103 km2) within the Ohio Valley averaged over the nine days leading to the 10-year flood.

Full field Anomaly

Nakamura et al, 2013

Large-scale anti-cyclonic moisture flow & convergence (Bermuda High)

700 mb geopotential height anomalies (in m) in contours and vertical pressure velocity (in mb day-1) colors (blue/purple is upward motion).Left: 20 event averageRight: April 2011

Nakamura et al, 2013

The dipole pattern of a significant positive geopotential high anomaly to the east of the flooded basins together with a weaker but negative anomaly to the west, are established on day -9 and persist throughout the days leading to the flood event.

Summary• Our exploratory analyses suggest that persistent, consistent

anomalous circulation and moisture transport patterns may determine large floods in a specific region implications for climate scenario “downscaling” and prediction.

• Tropical Ocean moisture sources and associated circulation patterns that focus meridional transport into the US Midwest, along the East coast, and into N. Europe can be identified even across event composites. flood determinism ?

• For such events, persistent wave like patterns and synoptic circulation types potentially related to ENSO and MJO activity may be identified Tropical SST/OLR Anomalies?

• Short to medium range probabilistic forecasts of the extreme events, as well as seasonal stochastic simulation may be feasible, and are being explored.

Columbia Water Center Global Flood Initiative