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

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Presentation on theme: "Contrasting Tropical Rainfall Regimes Using TRMM and Ground-Based Polarimetric Radar Steven A. Rutledge, Robert Cifelli, Timothy J. Lang Colorado State."— Presentation transcript:

1 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. Nesbitt University of Illinois at Urbana-Champaign Contact Info: Steven A. Rutledge, CSU Atmospheric Science, Ft Collins, CO 80523; (970) , This research is supported by NASA PMM Grant NNX07AD51G and NSF Grant ATM Larry Carey contributed some of the LBA plots. 1. Introduction2. NAME (July-August 2004)3. TRMM-LBA (January-February 1999) > 1500 m m < 500 m Ocean/Gulf Mean a  a Mean b  b Mean Unc R (mm/hr)  Unc R Mean Cond R (mm/hr)  Cond R Mean Freq  R Freq S-Pol Near-Sfc D 0 via D 0 = 1.529*(Z DR ) S-Pol Liquid & Ice Water Mass* S-Pol a in Z=aR 1.5 ** TRMM PR Statistics July-August TRMM PR (JA 98-07) Reflectivity CFADs TRMM PR (JA 98-07) a in Z=aR b Domain: 10x10 deg box Center at S-Pol N1 N2 N5 N6 N7 Over the water, S-Pol observed a lower frequency of large median volume diameters (D 0 ) 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 D 0 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=aR 1.5 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 D 0 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=aR 1.5 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 Height (km) East West L3 >|0.5 m/s| wind criteria EasterlyWesterlyNo Regime number of days number of convective pixels number of sampled pixels mean a in Z=aR^b σ(a) mean b in Z=aR^b1.546 σ(b) mean convective rain rate mean convective conditional rain rate convective precipitation frequency N3 L1 N4 L4 L2 Frequency Distribution of S-Pol Rain Rate L5 L7 L6 S-Pol Near-Sfc D 0 via D 0 = 1.529*(Z DR ) S-Pol a in Z=aR 1.5 ** TRMM PR (DJF 98-07) a and b in Z=aR b TRMM PR (DJF 98-07) Reflectivity CFADs TRMM PR Statistics DJF hPa winds derived from NCEP/NCAR reanalysis TRMM used 7.5x7.5 deg box centered on S-Pol


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