Contrasting Tropical Rainfall Regimes Using TRMM and Ground-Based Polarimetric Radar Steven A. Rutledge, Robert Cifelli, Timothy J. Lang

Colorado State University, Fort Collins

Steven W. NesbittUniversity of Illinois at Urbana-Champaign

Contact Info: Steven A. Rutledge, CSU Atmospheric Science,Ft Collins, CO 80523; (970) 491-8283, rutledge@atmos.colostate.edu

This research is supported by NASA PMM Grant NNX07AD51G and NSF Grant ATM-0733396. Larry Carey contributed some of the LBA plots.

1. Introduction 2. NAME (July-August 2004) 3. TRMM-LBA (January-February 1999)

                   > 1500 m   500-1500 m  < 500 m   Ocean/Gulf

Mean a      173.297      185.151      208.575    176.801

a    20.216 28.721 49.254 45.943

Mean b     1.5379 1.5421 1.5474 1.5527

b  0.0044 0.0055 0.0085 0.0129

Mean Unc     0.146 0.138 0.116 0.0410  R (mm/hr)

Unc R 0.089 0.111 0.104 0.058

Mean Cond   9.37 9.05 8.56 7.38R (mm/hr)

Cond R      2.24 2.98 3.30 5.58

Mean Freq   0.015 0.014 0.013 0.005

R Freq    0.007 0.009 0.010 0.005

S-Pol Near-Sfc D0 via D0 = 1.529*(ZDR)0.467 S-Pol Liquid & Ice Water Mass*

S-Pol a in Z=aR1.5**

TRMM PR StatisticsJuly-August 1998-2007

TRMM PR (JA 98-07)ReflectivityCFADs

TRMM PR (JA 98-07)a in Z=aRb

Domain:10x10 deg boxCenter at S-Pol

N1 N2

N5 N6

N7

Over the water, S-Pol observed a lower frequency of large median volume diameters (D0) than over land (N1). This was associated with less ice mass aloft (N2). However, liquid water mass was large, suggesting the relative importance of warm rain processes over the Gulf. Over land, the lowest elevations had the highest frequencies of large D0 and more ice mass, and these tended to decrease with increasing elevation. High rainfall rates were more frequent over the low terrain and water (N3) This was consistent with upscale growth of convection toward lower elevations (Lang et al. 2007).

The net result was increasing a in Z=aR1.5 from water to high elevations (N4). But this was not observed by TRMM (N5, N6), which showed an opposite trend, except for the ocean/gulf region. However, TRMM found the over-water a to be larger near the coast, so this average was misleading. TRMM conditional rain rate was found to decrease with elevation, which was completely inconsistent with S-Pol. Given the more frequent heavy S-Pol rain rates at low elevations, how well did the TRMM attenuation correction handle these extreme events? Reflectivity intercomparisons between TRMM and S-Pol showed good agreement for a handful of available overpasses (Lang et al. 2008), but these did not include strong events. TRMM did observe more vertically intense echoes over the low-elevation land (N7), like S-Pol. In addition, TRMM’s ocean/gulf CFAD was consistent with the S-Pol’s inference of smaller drop sizes (i.e., lower reflectivities despite heavy rainfall) over the water.

The TRMM satellite has provided unprecedented data for over 10 years. TRMM precipitation products have advanced our understanding of tropical precipitation considerably. There are many studies underway that seek to refine the precipitation products from the TRMM Precipitation Radar (PR). In this work we build on previously identified influences on tropical precipitation in Amazonia and in Mexico, the latter associated with the N. American Monsoon system.

Precipitation in Amazonia is strongly influenced by pronounced reversals in the low-level flow regime (easterly and westerly regimes, or continental-like vs. maritime-like) (I1, I2). In Mexico, precipitation characteristics vary markedly with terrain (I3), ranging from frequent showery rain over the high terrain of the Sierra Madre Occidental to more persistent, heavier rain over the coastal plains (I4). An even broader contrast exists between land-based convection and convection over the adjacent Gulf of California.

We used polarimetric radar data from two field projects, TRMM-LBA and NAME (North American Monsoon Experiment), to characterize the physical nature of precipitation in these regions. We contrasted these structures with 10-yr statistics from the PR. It will be demonstrated that using regime-specific Z-R estimators could lead to improved rainfall estimates derived from the PR. In addition, the results demonstrate the possibility of uncorrected PR attenuation in heavy rainfall events.

TRMM-LBA

Precipitation variability as a function of meteorological regime

NAME

Precipitation variability as a function of terrain

I1. Easterly and westerly regimes in TRMM-LBA, showing higher lightning flash rates in the east regime compared to the west regime. Mean CAPE was higher in the east regime compared to the west regime.

I2. Diurnal cycle of rainfall for the easterly and westerly regimes during TRMM-LBA.

I3. Terrain map for the NAME domain. Adapted from Lang et al. (2007).

I4. Diurnal cycle of convective rain rate for the NAME domain. Results are plotted as a function of elevation band and over water.

* Methodology described in Cifelli et al. (2002)** Methodology described in Bringi et al. (2004)

S-Pol Liquid Water Mass*

S-Pol Ice Water Mass*

Easterly regime convective precipitation was characterized by larger D0 compared to the westerly regime (L1). Easterly regime convective precipitation also contained larger liquid and ice water mass compared to the westerly regime (L2), consistent with the more frequent occurrence of vertically intense reflectivities in the easterly regime (L3), and heavier rainfall overall.

The larger drops observed in the easterly regime were manifested in a slightly higher “a” coefficient for the Z=aR1.5 relation in convective precipitation (L4). This indicated that different Z-Rs were required to accurately estimate the rainfall in each regime. TRMM did capture this relative variability in a between regimes (L5), although TRMM’s mode was shifted toward larger values (L6). However, TRMM conditional rain rates were completely at odds with the S-Pol results, and the reflectivity CFADs showed little difference between easterly and westerly regimes (L7). As in NAME, TRMM PR attenuation in extreme rainfall events may have played a role in biasing the easterly regime results low.

S-Pol reflectivity cumulative frequency distributions and mean profiles

Hei

ght (

km)

East

West

L3

>|0.5 m/s| wind criteria

Easterly Westerly No Regime

number of days 193 536 163

number of convective pixels

31041 104741 29568

number of sampled pixels

2112463 5666049 1799237

mean a in Z=aR^b 175.0 170.9 170.1

σ(a) 33.6 18.5 27.4

mean b in Z=aR^b 1.546 1.546 1.546

σ(b) .007 .005 .007

mean convective rain rate

2.96 3.59 3.16

mean convective conditional rain rate

7.50 7.89 7.14

convective precipitation frequency

0.011 0.007 0.013

N3

L1

N4

L4

L2

Frequency Distribution of S-Pol Rain Rate

L5

L7

L6

S-Pol Near-Sfc D0 via D0 = 1.529*(ZDR)0.467

S-Pol a in Z=aR1.5**

TRMM PR (DJF 98-07)a and b in Z=aRb

TRMM PR (DJF 98-07)ReflectivityCFADs

TRMM PR StatisticsDJF 1998-2007

800 hPa winds derived from NCEP/NCAR reanalysisTRMM used 7.5x7.5 deg box centered on S-Pol