Diurnal Cycle of Precipitation Based on CMORPH

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Diurnal Cycle of Precipitation Based on CMORPH. Vernon E. Kousky, John E. Janowiak and Robert Joyce Climate Prediction Center, NOAA. Motivation. The diurnal cycle is fundamentally important throughout the Tropics and Subtropics (and in middle latitudes in summer). - PowerPoint PPT Presentation

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Diurnal Cycle of Precipitation Based on CMORPH

Vernon E. Kousky, John E. Janowiak

and

Robert Joyce

Climate Prediction Center, NOAA

Motivation• The diurnal cycle is fundamentally important

throughout the Tropics and Subtropics (and in middle latitudes in summer).

• A better understanding of the diurnal cycle, and its variability, will lead to better short-range forecasts.

• There is a need to develop a benchmark for evaluating the diurnal cycle in numerical models.

Uses IR data along with passive microwave data to create global rainfall analyses (60N-60S) at high spatial and temporal resolution.

CMORPH uses IR only as a transport vehicle, i.e. IR data are NOT used to make estimates of rainfall when passive microwave data are not available.

The underlying assumption is that the error in using IR to transport precipitation features is less than the error in using IR to estimate precipitation.

CMORPH (CPC Morphing technique)

Rationale

• Passive microwave (PMW) data provide much better rainfall estimates than IR but these data are spatially and temporally incomplete (instruments on polar orbiting platforms)

• IR data are abundant both in space & time (polar & geostationary platforms)

• CMORPH combines the superior quality of the PMW-derived precipitation estimates with the excellent sampling characteristics of the IR data

Specifics

• Spatial Grid: 0.0728o lat/lon (8 km at equator)

• Temporal Resolution: 30 minutes

• Domain: Global (60o N - 60o S)

• Period of record: Dec. 2002 – present

For more information about CMORPH:

http://www.cpc.ncep.noaa.gov/products/janowiak/cmorph.html

Methodology• The seasonal mean precipitation rates, from CMORPH, are

computed for each time interval (1-h or 3-h).

• The mean daily precipitation rates are computed by summing the 1-h rates.

• In the absence of any diurnal variability, the same amount of rainfall would be expected during each time interval (e.g., 100/24 = 4.2% for 1-h intervals and 100/8 = 12.5% for 3-h intervals).

• Brown (green) colors are used to depict times when the observed % is less (more) than the expected values (precipitation uniformly distributed throughout the 24-h period).

Global: June-August

Land Areas

Many land areas experience a late night/ early morning minimum and a late afternoon/ early evening maximum in precipitation.

(Add 5-8 hs for LST)Southeast Asia, India, Malaysia & Indonesia

Ocean Areas

Many ocean areas experience a late night/ early morning maximum and a late afternoon/ early evening minimum in precipitation.

(Add 5-8 hs for LST)Southeast Asia, India, Malaysia & Indonesia

Southeast Asia, India & Indonesia

Animation India

Indonesian region

Animation Malaysia/Indonesia/Phili

ppines

Many land areas experience a late night-early morning minimum and a late afternoon-early evening maximum in precipitation.

(5-8 LT)

(18-21 LT)

North & Central

America: Land Areas

North & Central

America: Ocean Areas

(5-8 LT)

(18-21 LT)

Many nearby ocean areas experience a late night-early morning maximum and a late afternoon-early evening minimum in precipitation.

North & Central America: JJA 0304 (1mm/d mask)

South America:December-February

Comparison: CMORPH and Gridded Analyses (DJF

0203+0304)CMORPH Gridded

CMORPH over estimates precipitation by 40-50% over Brazil.

The bias is being corrected using station observations.

Land Areas Many land areas experience a late night-early morning minimum and a late afternoon-early evening maximum in precipitation.

(6-9 LT)

(18-21 LT)

However, some land areas experience a late night-early morning maximum and a late afternoon-early evening minimum in precipitation.

Ocean Areas

(6-9 LT)

(18-21 LT)

Many nearby ocean areas experience a late night-early morning maximum and a late afternoon-early evening minimum in precipitation.

South America: DJF 0203-0405 (1mm/d mask)

Diurnal Cycle DJF 0203-0405

South America: DJF 02-03+03-04 (1mm/d mask)

DJF - South America (1mm mask)

DJF - South America (1mm mask)

Diurnal Cycle DJF 02-03

Diurnal Cycle DJF 02-03 +

03-04

Seasonal variations of the Diurnal Cycle of

Precipitation over the Amazon

Basin

Time-Longitude Diurnal Cycle EQ DJF 2002-03 +2003-04

Coast

Mean diurnal cycle Repeated four times

Maximum over the ocean ~ 12Z.

Minimum over the ocean ~00Z.

Minimum over the land ~ 12Z.

Maximum over the land ~00Z.

Time-Longitude Diurnal Cycle 10S DJF 2002-03 +2003-04

Time-Longitude Diurnal Cycle 20S DJF 2002-03 +2003-04

Coast

Time-Longitude Diurnal Cycle 30S DJF 2002-03 +2003-04

Coast

Eastward-propagating precipitation systems between the Andes Mts. and southern Brazil.

MAM Mean Diurnal Cycle – EQ-5N

East CoastWest Coast

Convective rainfall systems start along east coast on day-1 propagate westward, reaching western Amazon on day-3.

Southeast Brazil

Southeast Brazil (cont.)

Seasonally varying diurnal cycle: 27S, top, and area averaged (2x2

degrees), bottom.

Seasonally varying diurnal cycle of preciitation (area averaged 2x2

degrees), 24S (top) and 27S (bottom).

24S

27S

Seasonally varying diurnal cycle of preciitation (area averaged 2x2

degrees), 2S.

55W 52W 49W 46W

Westward propagating lines occur primarily during February-May.

Conclusions• CMORPH precipitation analyses are useful in

obtaining a detailed description of the diurnal cycle.• A pronounced diurnal cycle in precipitation is found

in many areas of South America.–Daytime peak over high terrain (e.g., Andes Mts.,

Brazilian Planalto).

–Daytime peak near the coast, especially NE South America, associated with the sea breeze.

–Nocturnal peak in the central La Plata Basin, over oceanic regions, and over portions of the Amazon Basin (affected by westward propagating sea breeze-induced convection).

Future Work

• There is a need to document the regional and large-scale atmospheric circulation features that contribute to the formation of westward-propagating lines over the Amazon Basin.

• Studies should be developed to evaluate the ability of numerical prediction models to simulate and predict the occurrence of these westward-propagating lines.