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Kaycee Frederick and Courtney Schumacher

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The Tropical Pacific Warm Pool International Cloud Experiment (TWP-ICE) took place in Darwin, Australia, in early 2006. C-band radar data were used to characterize tropical anvil (i.e., thick, nonprecipitating cloud associated with deep convection) areal coverage, height, and thickness during the monthlong field campaign. The morphology, evolution, and longevity of the anvil were analyzed, as was the relationship of the anvil to the rest of the precipitating system.

The anvil was separated into mixed (i.e., echo base below 6 km) and ice-only categories. The average areal coverage for each anvil type was between 4% and 5% of the radar grid. Ice anvil thickness averaged 2.8 km and mixed anvil thickness averaged 6.7 km. Areal peaks show that mixed anvil typically formed out of the stratiform rain region. Peak production in ice anvil usually followed the mixed anvil peak by 1–3 h. Anvil typically lasted 4–10 h after the initial convective rain area peak. TWP-ICE experienced three distinct regimes: an active monsoon, a dry monsoon, and a break period. During the experiment (except the active monsoon period) there was a strong negative correlation between ice anvil thickness and ice anvil height, a strong positive correlation between ice anvil area and thickness, and a greater variance in ice anvil bottom than ice anvil top. These results have important implications for understanding how anvil affects the tropical atmosphere.

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Christopher Dupuis and Courtney Schumacher

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The Lomb–Scargle discrete Fourier transform (LSDFT) is a well-known technique for analyzing time series. In this study, a solution for empirical orthogonal functions (EOFs) based on irregularly sampled data is derived from the LSDFT. It is demonstrated that this particular algorithm has no hard limit on its accuracy and yields results comparable to those of complex Hilbert EOF analysis. Two LSDFT algorithms are compared in terms of their performance in evaluating EOFs for precipitation observations from the Tropical Rainfall Measuring Mission satellite. Both are shown to be able to capture the pattern of the diurnal cycle of rainfall over the complex topography and diverse land cover of South America, and both also show other consistent features in the 0–12-day frequency band.

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Wei Li and Courtney Schumacher

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This study investigates anvils from thick, nonprecipitating clouds associated with deep convection as observed in the tropics by the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) during the 10-yr period, 1998–2007. Anvils observable by the PR occur, on average, 5 out of every 100 days within grid boxes with 2.5° resolution and with a conditional areal coverage of 1.5%. Unconditional areal coverage is only a few tenths of a percent. Anvils also had an average 17-dBZ echo top of ∼8.5 km and an average thickness of ∼2.7 km. Anvils were usually higher and thicker over land compared to ocean, and occurred most frequently over Africa, the Maritime Continent, and Panama. Anvil properties were intimately tied to the properties of the parent convection. In particular, anvil area and echo-top heights were highly correlated to convective rain area. The next best predictor for anvil areal coverage and echo tops was convective echo tops, while convective reflectivities had the weakest correlation. Strong upper-level wind shear also may be associated with anvil occurrence over land, especially when convection regularly attains echo-top heights greater than 7 km. Some tropical land regions, especially those affected by monsoon circulations, experience significant seasonal variability in anvil properties—strong interannual anvil variability occurs over the central Pacific because of the El Niño–Southern Oscillation. Compared to the CloudSat Cloud Profiling Radar, the TRMM PR underestimates anvil-top height by an average of ∼5 km and underestimates their horizontal extent by an average factor of 4.

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Christian Jakob and Courtney Schumacher

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An objective tropical cloud regime classification based on daytime averaged cloud-top pressure and optical thickness information from the International Satellite Cloud Climatology Project (ISCCP) is combined with precipitation and latent heating characteristics derived using the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). TRMM precipitation information is stratified into the ISCCP regimes in the tropical western Pacific (TWP), revealing the following three major precipitation regimes: a heavy (12 mm day−1) precipitation regime dominated by stratiform precipitation and top-heavy latent heating; a regime with moderate (5 mm day−1) precipitation amounts, mostly convective in nature with more midlevel latent heating; and a low (2 mm day−1) precipitation regime with a relatively large rain contribution from shallow convection, compared to the other regimes. Although three of the ISCCP cloud regimes are linked to the more convective, moderate precipitation regime, only one of the cloud regimes is associated with the more stratiform, top-heavy latent heating regime, making the ISCCP regimes a potentially useful tool for the further study of this dynamically important tropical weather state. Similarly, only one cloud regime is associated with the more shallow convective precipitation regime.

In terms of the TWP, precipitation and latent heating are dominated by the relatively infrequent (15%) occurrence of the strongly precipitating top-heavy latent heating state and by the frequent (>30%) occurrence of one of the more moderately precipitating convective states. The low precipitation/shallow cumulus regime occurs often (i.e., 25% of the time) but does not contribute strongly to the overall precipitation and latent heating. Each of these regimes also shows distinct geographical patterns in the TWP, thus providing insight into the distribution of convective and stratiform rain across the tropics. This study confirms the potential usefulness of the objective regime classification based on ISCCP, and it opens several new avenues for studying the interaction of convection with the large-scale tropical circulation.

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Hedanqiu Bai and Courtney Schumacher

Abstract

A nocturnal Amazonian low-level jet (ALLJ) was recently diagnosed using reanalysis data. This work assesses the ability of CESM1.2.2 to reproduce the jet and explores the mechanisms by which the ALLJ influences convection in the Amazon. The coupled CESM simulates the nocturnal ALLJ realistically, while CAM5 does not. A low-level cold air temperature bias in the eastern Amazon exists in CAM5, and thus the ALLJ is weaker than observed. However, a cold SST bias over the equatorial North Atlantic in the coupled model offsets the cold air temperature bias, producing a realistic ALLJ. Climate models significantly underestimate March–May (MAM) precipitation over the eastern Amazon. We ran two sensitivity experiments using the coupled CESM by adding bottom-heavy diabatic heating at noon and midnight for 2.5 h along the coastal Amazon during MAM to mimic the occurrence of shallow precipitating convection. When heating is added during the early afternoon, coastal convection deepens and the ALLJ transports moisture inland from the ocean, preconditioning the environment for deep convective development during the ensuing hours. The increased convection over the eastern Amazon also moderately alleviates the equatorial Atlantic westerly wind bias, leading to deepening of the east Atlantic thermocline in the following months and partially improving the simulated June–August (JJA) Atlantic cold tongue in the coupled model. When heating is added at night, coastal convection does not strengthen as much and the ALLJ transports less moisture. Improvements in the simulated Atlantic winds and SST are negligible. Therefore, diurnal circulations matter to the organization of convection and rain across the Amazon, with impacts over the equatorial Atlantic.

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Fiaz Ahmed and Courtney Schumacher

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Positive feedbacks between the cloud population and the environmental moisture field are central to theoretical expositions on the Madden–Julian oscillation (MJO). This study investigates the statistical incidence of positive moisture–convection feedbacks across multiple space and time scales over the tropical Indian Ocean. This work uses vertically integrated moisture budget terms from the ECMWF interim reanalysis [ERA-Interim (ERA-I)] in a framework proposed by Hannah et al. Positive moisture–convection feedbacks are primarily a low-frequency, low-wavenumber phenomenon with significant spectral signatures in the 32–48-day time scale. The efficacy of these feedbacks, however, is subject to horizontal moisture advection variations, whose relative importance varies with scale. Wave-filtered Tropical Rainfall Measuring Mission (TRMM) satellite precipitation is used to show that these moisture–convection feedbacks contribute more to moisture increases in the MJO than in other equatorial waves. A moving-window correlation analysis suggests that instances of moisture–convection feedbacks are more frequent in drier conditions, when column water vapor (CWV) is below its climatological mean value, with the implication that positive moisture–convection feedbacks shape the mean CWV field by moistening drier air columns, but that they are less effective in moistening already moist environments. Ground radar observations show that stratiform rain damps local CWV increases on short time scales (<2 days) and therefore precludes positive moisture–convection feedbacks in high-CWV environments. Vertical coherence structures from ERA-I confirm that relatively bottom-heavy cloud ensembles (i.e., peaks between 700 and 850 hPa) are more effective in inducing low-frequency positive moisture–convection feedbacks than ensembles with other vertical structures. Low-frequency horizontal advective drying damps moisture increases and is strongly coherent with upper-level rising motion.

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Elinor R. Martin and Courtney Schumacher

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Based on 12 years of daily satellite precipitation data and reanalysis winds, intraseasonal (30–90 days) variability in Caribbean precipitation is linked to phases of the Madden–Julian oscillation (MJO). Intraseasonal variability is largest during September–November (SON), but some modulation of precipitation by the MJO appears throughout all seasons. Precipitation anomalies up to 50% above (below) the annual mean are observed in phases 1 and 2 (5 and 6) of the MJO. The changes in Caribbean precipitation associated with the MJO are shown to be related to changes in the low-level (925 hPa) winds. When precipitation anomalies are above (below) average in phases 1 and 2 (5 and 6), wind anomalies act to decrease (increase) the strength of the prevailing easterly trade winds. The changes in the low-level winds are most apparent in the region of the Caribbean low-level jet (CLLJ), and divergence anomalies associated with the entrance and exit regions of the CLLJ precede the precipitation anomalies. The CLLJ itself is also shown to be subject to intraseasonal variability, and its magnitude varies with the phase of the MJO. Again, intraseasonal variability in the CLLJ associated with the MJO is observed in all seasons and shows a significant coherence with intraseasonal variability in the precipitation. Extreme rainfall events over islands in the Caribbean show a strong relationship with the MJO phase, with extreme events being most common in phases 1 and 2 of an MJO event. This relationship between the MJO and extreme events has important implications for the predictability of precipitation extremes in the Caribbean.

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Elinor R. Martin and Courtney Schumacher

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A regime sorting analysis is used to identify Caribbean and western Pacific precipitation, sea surface temperature, and large-scale vertical circulation relationships and biases within coupled and uncoupled Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) general circulation models. This analysis shows that an oversensitivity of precipitation to both SST and vertical circulation (as represented by ω 500) is inherent in the atmospheric models in both regions, with models using a spectral-type convective parameterization performing best in the Caribbean, but less separation between convective parameterization groups is seen in the western Pacific. The error in magnitude of precipitation for a given SST and vertical circulation causes uncoupled models to overestimate Caribbean and western Pacific mean precipitation. In coupled models, however, errors in the frequency of occurrence of SSTs (the distribution is cold biased in both regions) and deep convective vertical circulations (reduced frequency) lead to an underestimation of Caribbean and western Pacific mean precipitation. In the western Pacific, increased frequency of subsidence regimes in coupled models leads to an overestimation of precipitation at ω 500 values above 0 hPa day−1. The varied ability of convective parameterization groups in the two warm pool regions suggests that deficiencies in parameterization groups differ between the two regions, with improvements needed particularly in the deep convective regime in the Caribbean and subsidence regimes in the western Pacific.

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Elinor R. Martin and Courtney Schumacher

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A census of 19 coupled and 12 uncoupled model runs from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) shows that all models have the ability to simulate the location and height of the Caribbean low-level jet (CLLJ); however, the observed semiannual cycle of the CLLJ magnitude was a challenge for the models to reproduce. In particular, model means failed to capture the strong July CLLJ peak as a result of the lack of westward and southward expansion of the North Atlantic subtropical high (NASH) between May and July. The NASH was also found to be too strong, particularly during the first 6 months of the year in the coupled model runs, which led to increased meridional sea level pressure gradients across the southern Caribbean and, hence, an overly strong CLLJ. The ability of the models to simulate the correlation between the CLLJ and regional precipitation varied based on season and region. During summer months, the negative correlation between the CLLJ and Caribbean precipitation anomalies was reproduced in the majority of models, with uncoupled models outperforming coupled models. The positive correlation between the CLLJ and the central U.S. precipitation during February was more challenging for the models, with the uncoupled models failing to reproduce a significant relationship. This may be a result of overactive convective parameterizations raining out too much moisture in the Caribbean meaning less is available for transport northward, or due to incorrect moisture fluxes over the Gulf of Mexico. The representation of the CLLJ in general circulation models has important consequences for accurate predictions and projections of future climate in the Caribbean and surrounding regions.

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Larry J. Hopper Jr. and Courtney Schumacher

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Divergence structures associated with the spectrum of precipitating systems in the subtropics and midlatitudes are not well documented. A mesoscale model is used to quantify the relative importance different baroclinic environments have on divergence profiles for storms primarily caused by upper-level disturbances in southeastern Texas, a subtropical region. The divergence profiles simulated for a subset of the modeled storms are consistent with those calculated from an S-band Doppler radar. Realistic convective and stratiform divergence signals are also generated when applying a two-dimensional convective–stratiform separation algorithm to reflectivities derived from the mesoscale model, although the model appears to underestimate stratiform rain area. Divergence profiles from the modeled precipitating systems vary in magnitude and structure across the wide range of baroclinicities common in southeastern Texas. Barotropic storms more characteristic of the tropics generate the most elevated divergence (and thus diabatic heating) structures with the largest magnitudes. In addition, stratiform rain regions in barotropic storms contain thicker, more elevated midlevel convergence signatures than more baroclinic storms. As the degree of baroclinicity increases, stratiform area fractions generally increase while the levels of nondivergence (LNDs) decrease. However, some weakly baroclinic storms contain stratiform area fractions and/or divergence profiles with magnitudes and LNDs that are similar to barotropic storms, despite having lower tropopause heights and less deep convection. Additional convection forms after the passage of barotropic and weakly baroclinic storms that contain elevated divergence signatures, circumstantially suggesting that heating at upper levels may cause diabatic feedbacks that help to drive regions of persistent convection in the subtropics.

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