scholarly journals Tropical Precipitation Extremes

2013 ◽  
Vol 26 (4) ◽  
pp. 1457-1466 ◽  
Author(s):  
William B. Rossow ◽  
Ademe Mekonnen ◽  
Cindy Pearl ◽  
Weber Goncalves
Keyword(s):  
Large Scale ◽  
Accumulation Rate ◽  
Deep Convection ◽  
Circulation Model ◽  
Grid Cell ◽  
Precipitation Intensity ◽  
Convective Systems ◽  
Tropical Precipitation ◽  
Cloud Properties ◽  
Deep Convective Systems

Abstract Classifying tropical deep convective systems by the mesoscale distribution of their cloud properties and sorting matching precipitation measurements over an 11-yr period reveals that the whole distribution of instantaneous precipitation intensity and daily average accumulation rate is composed of (at least) two separate distributions representing distinctly different types of deep convection associated with different meteorological conditions (the distributions of non-deep-convective situations are also shown for completeness). The two types of deep convection produce very different precipitation intensities and occur with very different frequencies of occurrence. Several previous studies have shown that the interaction of the large-scale tropical circulation with deep convection causes switching between these two types, leading to a substantial increase of precipitation. In particular, the extreme portion of the tropical precipitation intensity distribution, above 2 mm h−1, is produced by 40% of the larger, longer-lived mesoscale-organized type of convection with only about 10% of the ordinary convection occurrences producing such intensities. When average precipitation accumulation rates are considered, essentially all of the values above 2 mm h−1 are produced by the mesoscale systems. Yet today’s atmospheric models do not represent mesoscale-organized deep convective systems that are generally larger than current-day circulation model grid cell sizes but smaller than the resolved dynamical scales and last longer than the typical physics time steps. Thus, model-based arguments for how the extreme part of the tropical precipitation distribution might change in a warming climate are suspect.

Deep Convective Systems Observed by A-Train in the Tropical Indo-Pacific Region Affected by the MJO

2013 ◽  
Vol 70 (2) ◽  
pp. 465-486 ◽  
Author(s):  
Jian Yuan ◽  
Robert A. Houze
Keyword(s):  
Large Scale ◽  
Deep Convection ◽  
Active Phase ◽  
Maximum Height ◽  
Pacific Region ◽  
Convective Envelope ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
Deep Convective Systems ◽  
Cloud Tops

Abstract In the Indo-Pacific region, mesoscale convective systems (MCSs) occur in a pattern consistent with the eastward propagation of the large-scale convective envelope of the Madden–Julian oscillation (MJO). MCSs are major contributors to the total precipitation. Over the open ocean they tend to be merged or connected systems, while over the Maritime Continent area they tend to be separated or discrete. Over all regions affected by the MJO, connected systems increase in frequency during the active phase of the MJO. Characteristics of each type of MCS (separated or connected) do not vary much over MJO-affected regions. However, separated and connected MCSs differ in structure from each other. Connected MCSs have a larger size and produce less but colder-topped anvil cloud. For both connected and separated MCSs, larger systems tend to have colder cloud tops and less warmer-topped anvil cloud. The maximum height of MCS precipitating cores varies only slightly, and the variation is related to sea surface temperature. Enhanced large-scale convection, greater frequency of occurrence of connected MCSs, and increased midtroposphere moisture coincide, regardless of the region, season, or large-scale conditions (such as the concurrent phase of the MJO), suggesting that the coexistence of these phenomena is likely the nature of deep convection in this region. The increase of midtroposphere moisture observed in all convective regimes during large-scale convectively active phases suggests that the source of midtroposphere moisture is not local or instantaneous and that the accumulation of midtroposphere moisture over MJO-affected regions needs to be better understood.

A Low-Level Circulation in the Tropics

2008 ◽  
Vol 65 (3) ◽  
pp. 1019-1034 ◽  
Author(s):  
Ian Folkins ◽  
S. Fueglistaler ◽  
G. Lesins ◽  
T. Mitovski
Keyword(s):  
Mass Flux ◽  
Large Scale ◽  
Deep Convection ◽  
Lower Troposphere ◽  
Shallow Convection ◽  
Vertical Variation ◽  
Convective Systems ◽  
Clear Sky ◽  
Deep Convective Systems ◽  
The Tropics

Abstract Deep convective tropical systems are strongly convergent in the midtroposphere. Horizontal wind measurements from a variety of rawinsonde arrays in the equatorial Pacific and Caribbean are used to calculate the mean dynamical divergence profiles of large-scale arrays (≥1000 km in diameter) in actively convecting regions. Somewhat surprisingly, the magnitude of the midtropospheric divergence calculated from these arrays is usually small. In principle, the midlevel convergence of deep convective systems could be balanced on larger scales either by a vertical variation in the radiative mass flux of the background clear sky atmosphere, or by a divergence from shallow cumuli. The vertical variation of the clear sky mass flux in the midtroposphere is small, however, so that the offsetting divergence must be supplied by shallow cumuli. On spatial scales of ∼1000 km, the midlevel convergent inflow toward deep convection appears to be internally compensated, or “screened,” by a divergent outflow from surrounding precipitating shallow convection. Deep convective systems do not induce a large-scale inflow of midlevel air toward actively convecting regions from the rest of the tropics, but instead help generate a secondary low-level circulation, in which the net downward mass flux from mesoscale and convective-scale downdrafts is balanced by a net upward mass flux from precipitating shallow cumuli. The existence of this circulation is consistent with observational evidence showing that deep and shallow convection are spatiotemporally coupled on a wide range of both spatial and temporal scales. One of the mechanisms proposed for coupling shallow convection to deep convection is the tendency for deep convection to cool the lower troposphere. The authors use radiosonde temperature profiles and the Tropical Rainfall Measuring Mission (TRMM) 3B42 gridded rainfall product to argue that the distance over which deep convection cools the lower troposphere is approximately 1000 km.

scholarly journals Extinction coefficients retrieved in deep tropical ice clouds from lidar observations using a CALIPSO-like algorithm compared to in-situ measurements from the Cloud Integrated Nephelometer during CRYSTAL-FACE

2006 ◽  
Vol 6 (5) ◽  
pp. 10649-10672 ◽  
Author(s):  
V. Noel ◽  
D. M. Winker ◽  
T. J. Garrett ◽  
M. McGill
Keyword(s):  
Spatial Scales ◽  
Deep Convection ◽  
Retrieval Algorithm ◽  
Crystal Face ◽  
Ice Clouds ◽  
Extinction Coefficients ◽  
Convective Systems ◽  
Lidar Ratio ◽  
Deep Convective Systems

Abstract. This paper presents a comparison of lidar ratios and volume extinction coefficients in tropical ice clouds, retrieved using observations from two instruments: the 532-nm Cloud Physics Lidar (CPL), and the in-situ Cloud Integrating Nephelometer (CIN) probe. Both instruments were mounted on airborne platforms during the CRYSTAL-FACE campaign and took measurements up to 17 km. Coincident observations from two cases of ice clouds located on top of deep convective systems are compared. First, lidar ratios are retrieved from CPL observations of attenuated backscatter, using a retrieval algorithm for opaque cloud similar to one used in the soon-to-be launched CALIPSO mission, and compared to results from the regular CPL algorithm. These lidar ratios are used to retrieve extinction coefficient profiles, which are compared to actual observations from the CIN in-situ probe, putting the emphasis on their vertical variability. When observations coincide, retrievals from both instruments are very similar. Differences are generally variations around the average profiles, and general trends on larger spatial scales are usually well reproduced. The two instruments agree well, with an average difference of less than 11% on optical depth retrievals. Results suggest the CALIPSO Deep Convection algorithm can be trusted to deliver realistic estimates of the lidar ratio, leading to good retrievals of extinction coefficients.

scholarly journals On the discretization of the ice thickness distribution in the NEMO3.6-LIM3 global ocean–sea ice model

2019 ◽  
Vol 12 (8) ◽  
pp. 3745-3758 ◽  
Author(s):  
François Massonnet ◽  
Antoine Barthélemy ◽  
Koffi Worou ◽  
Thierry Fichefet ◽  
Martin Vancoppenolle ◽  
...  
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Large Scale ◽  
Thickness Distribution ◽  
Circulation Model ◽  
Grid Cell ◽  
The Arctic ◽  
Global Ocean ◽  
Ice Thickness ◽  
Ice Model

Abstract. The ice thickness distribution (ITD) is one of the core constituents of modern sea ice models. The ITD accounts for the unresolved spatial variability of sea ice thickness within each model grid cell. While there is a general consensus on the added physical realism brought by the ITD, how to discretize it remains an open question. Here, we use the ocean–sea ice general circulation model, Nucleus for European Modelling of the Ocean (NEMO) version 3.6 and Louvain-la-Neuve sea Ice Model (LIM) version 3 (NEMO3.6-LIM3), forced by atmospheric reanalyses to test how the ITD discretization (number of ice thickness categories, positions of the category boundaries) impacts the simulated mean Arctic and Antarctic sea ice states. We find that winter ice volumes in both hemispheres increase with the number of categories and attribute that increase to a net enhancement of basal ice growth rates. The range of simulated mean winter volumes in the various experiments amounts to ∼30 % and ∼10 % of the reference values (run with five categories) in the Arctic and Antarctic, respectively. This suggests that the way the ITD is discretized has a significant influence on the model mean state, all other things being equal. We also find that the existence of a thick category with lower bounds at ∼4 and ∼2 m for the Arctic and Antarctic, respectively, is a prerequisite for allowing the storage of deformed ice and therefore for fostering thermodynamic growth in thinner categories. Our analysis finally suggests that increasing the resolution of the ITD without changing the lower limit of the upper category results in small but not negligible variations of ice volume and extent. Our study proposes for the first time a bi-polar process-based explanation of the origin of mean sea ice state changes when the ITD discretization is modified. The sensitivity experiments conducted in this study, based on one model, emphasize that the choice of category positions, especially of thickest categories, has a primary influence on the simulated mean sea ice states while the number of categories and resolution have only a secondary influence. It is also found that the current default discretization of the NEMO3.6-LIM3 model is sufficient for large-scale present-day climate applications. In all cases, the role of the ITD discretization on the simulated mean sea ice state has to be appreciated relative to other influences (parameter uncertainty, forcing uncertainty, internal climate variability).

Structure of the Madden–Julian Oscillation in the Superparameterized CAM

2009 ◽  
Vol 66 (11) ◽  
pp. 3277-3296 ◽  
Author(s):  
James J. Benedict ◽  
David A. Randall
Keyword(s):  
Boundary Layer ◽  
General Circulation ◽  
Deep Convection ◽  
Circulation Model ◽  
Grid Cell ◽  
Atmospheric Model ◽  
Space Time ◽  
Madden Julian Oscillation ◽  
Moist Convection ◽  
Time Structures

Abstract The detailed dynamic and thermodynamic space–time structures of the Madden–Julian oscillation (MJO) as simulated by the superparameterized Community Atmosphere Model version 3.0 (SP-CAM) are analyzed. Superparameterization involves substituting conventional boundary layer, moist convection, and cloud parameterizations with a configuration of cloud-resolving models (CRMs) embedded in each general circulation model (GCM) grid cell. Unlike most GCMs that implement conventional parameterizations, the SP-CAM displays robust atmospheric variability on intraseasonal space and time (30–60 days) scales. The authors examine a 19-yr SP-CAM simulation based on the Atmospheric Model Intercomparison Project protocol, forced by prescribed sea surface temperatures. Overall, the space–time structures of MJO convective disturbances are very well represented in the SP-CAM. Compared to observations, the model produces a similar vertical progression of increased moisture, warmth, and heating from the boundary layer to the upper troposphere as deep convection matures. Additionally, important advective and convective processes in the SP-CAM compare favorably with those in observations. A deficiency of the SP-CAM is that simulated convective intensity organized on intraseasonal space–time scales is overestimated, particularly in the west Pacific. These simulated convective biases are likely due to several factors including unrealistic boundary layer interactions, a lack of weakening of the simulated disturbance over the Maritime Continent, and mean state differences.

scholarly journals Quantitative Sensitivity Analysis of Physical Parameterizations for Cases of Deep Convection in the NASA GEOS-5

2016 ◽  
Vol 29 (2) ◽  
pp. 455-479 ◽  
Author(s):  
Derek J. Posselt ◽  
Bruce Fryxell ◽  
Andrea Molod ◽  
Brian Williams
Keyword(s):  
General Circulation ◽  
Process Model ◽  
Large Scale ◽  
Climate Models ◽  
Deep Convection ◽  
Input Parameter ◽  
Circulation Model ◽  
Parameter Sensitivity ◽  
Global Climate Models ◽  
Simulation Code

Abstract Parameterization of processes that occur on length scales too small to resolve on a computational grid is a major source of uncertainty in global climate models. This study investigates the relative importance of a number of parameters used in the Goddard Earth Observing System Model, version 5 (GEOS-5), atmospheric general circulation model, focusing on cloud, convection, and boundary layer parameterizations. Latin hypercube sampling is used to generate a few hundred sets of 19 candidate physics parameters, which are subsequently used to generate ensembles of single-column model realizations of cloud content, precipitation, and radiative fluxes for four different field campaigns. A Gaussian process model is then used to create a computationally inexpensive emulator for the simulation code that can be used to determine a measure of relative parameter sensitivity by sampling the response surface for a very large number of input parameter sets. Parameter sensitivities are computed for different geographic locations and seasons to determine whether the intrinsic sensitivity of the model parameterizations changes with season and location. The results indicate the same subset of parameters collectively control the model output across all experiments, independent of changes in the environment. These are the threshold relative humidity for cloud formation, the ice fall speeds, convective and large-scale autoconversion, deep convection relaxation time scale, maximum convective updraft diameter, and minimum ice effective radius. However, there are differences in the degree of parameter sensitivity between continental and tropical convective cases, as well as systematic changes in the degree of parameter influence and parameter–parameter interaction.

The vertical moisture structure and precipitation intensity distributions associated with tropical convective systems

2020 ◽  
Author(s):  
Kathleen Schiro ◽  
Sylvia Sullivan ◽  
Jiabo Yin ◽  
Pierre Gentine
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Probability Distributions ◽  
Reanalysis Data ◽  
Precipitation Intensity ◽  
Maximum Precipitation ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
Environmental Relative Humidity ◽  
Relative Gains

<p>In the tropics, the majority of high-intensity precipitation comes from the organization of multiple convective cells into mesoscale convective systems (MCS). Here, we use a synthesis of multi-decade satellite and reanalysis data to investigate relationships between the column water vapor content (CWVC), instability (CAPE), and precipitation from MCS. We find a linear relationship between MCS maximum precipitation intensity and CAPE and a sharp, nonlinear relationship between this maximum precipitation intensity and CWVC. The latter suggests that a deep layer of inflow to the MCS dominates buoyancy and precipitation production. From these multidecade data, we can also illustrate robust shifts in the probability distributions of precipitation intensity with the El Niño Southern Oscillation. El Niño-La Niña relative gains and losses in precipitation intensity can be understood with a vertical momentum budget and the role of environmental relative humidity and large-scale circulation therein. Understanding the associated vertical moisture structure and instability is essential to better predict future variability in tropical precipitation.</p>

scholarly journals Cloud and Radiative Characteristics of Tropical Deep Convective Systems in Extended Cloud Objects from CERES Observations

2009 ◽  
Vol 22 (22) ◽  
pp. 5983-6000 ◽  
Author(s):  
Zachary A. Eitzen ◽  
Kuan-Man Xu ◽  
Takmeng Wong
Keyword(s):  
Optical Depth ◽  
Large Scale ◽  
Radiant Energy ◽  
Radiative Properties ◽  
Cloud Optical Depth ◽  
Water Path ◽  
Convective Systems ◽  
Joint Histogram ◽  
Deep Convective Systems ◽  
Cloud Top Temperature

Abstract The physical and radiative properties of tropical deep convective systems for the period from January to August 1998 are examined with the use of Clouds and the Earth’s Radiant Energy System Single-Scanner Footprint (SSF) data from the Tropical Rainfall Measuring Mission satellite. Deep convective (DC) cloud objects are contiguous regions of satellite footprints that fulfill the DC criteria (i.e., overcast footprints with cloud optical depths >10 and cloud-top heights >10 km). Extended cloud objects (ECOs) start with the original cloud object but include all other cloudy footprints within a rectangular box that completely covers the original cloud object. Most of the non-DC footprints are overcast but have optical depths and/or cloud-top heights that are too low to fit the DC criteria. The histograms of cloud physical and radiative properties are analyzed according to the size of the ECO and the SST of the underlying ocean. Larger ECOs are associated with greater magnitudes of large-scale upward motion, which supports stronger convection for larger sizes of ECOs. This leads to shifts toward higher values in the DC distributions of cloud-top height, albedo, condensate water path, and cloud optical depth. However, non-DC footprints become less reflective with increasing ECO size, as the longer-lived large convective systems have more time to develop thin cirrus anvils. The proportion of DC footprints remains fairly constant with size. The proportion of DC footprints also remains nearly constant with SST within a given size class, although the number of footprints per object increases with SST for large objects. As SSTs increase, there is a decrease in the proportion of updraft water that goes into detrainment, causing the non-DC distributions of albedo, condensate water path, and cloud optical depth to shift toward lower values. The all-cloud distributions of cloud-top temperature and outgoing longwave radiation (OLR) shift toward lower values as SST increases owing to the increase in convective instability with SST. Both the DC and non-DC distributions of cloud-top temperature do not change much with satellite precession cycle, supporting the fixed anvil temperature hypothesis of Hartmann and Larson. When a joint histogram is formed from the cloud-top pressures and cloud optical depths of the ECOs, it is very similar to the corresponding histogram of the deep convective weather state obtained by cluster analysis of International Satellite Cloud Climatology Project data.

scholarly journals Enhancing Dynamical Seasonal Predictions through Objective Regionalization

2017 ◽  
Vol 56 (5) ◽  
pp. 1431-1442 ◽  
Author(s):  
Saleh Satti ◽  
Benjamin F. Zaitchik ◽  
Hamada S. Badr ◽  
Tsegaye Tadesse
Keyword(s):  
East Africa ◽  
General Circulation ◽  
Large Scale ◽  
Rainfall Variability ◽  
Circulation Model ◽  
Grid Cell ◽  
Ocean General Circulation Model ◽  
Seasonal Forecasts ◽  
Interannual Rainfall Variability ◽  
Local Grid

AbstractImproving seasonal forecasts in East Africa has great implications for food security and water resources planning in the region. Dynamically based seasonal forecast systems have much to contribute to this effort, as they have demonstrated ability to represent and, to some extent, predict large-scale atmospheric dynamics that drive interannual rainfall variability in East Africa. However, these global models often exhibit spatial biases in their placement of rainfall and rainfall anomalies within the region, which limits their direct applicability to forecast-based decision-making. This paper introduces a method that uses objective climate regionalization to improve the utility of dynamically based forecast-system predictions for East Africa. By breaking up the study area into regions that are homogenous in interannual precipitation variability, it is shown that models sometimes capture drivers of variability but misplace precipitation anomalies. These errors are evident in the pattern of homogenous regions in forecast systems relative to observation, indicating that forecasts can more meaningfully be applied at the scale of the analogous homogeneous climate region than as a direct forecast of the local grid cell. This regionalization approach was tested during the July–September (JAS) rain months, and results show an improvement in the predictions from version 4.5 of the Max Plank Institute for Meteorology’s atmosphere–ocean general circulation model (ECHAM4.5) for applicable areas of East Africa for the two test cases presented.

scholarly journals Effects of Cloud Microphysics on Tropical Atmospheric Hydrologic Processes and Intraseasonal Variability

2005 ◽  
Vol 18 (22) ◽  
pp. 4731-4751 ◽  
Author(s):  
K. M. Lau ◽  
H. T. Wu ◽  
Y. C. Sud ◽  
G. K. Walker
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Water Cycle ◽  
Deep Convection ◽  
Intraseasonal Variability ◽  
Lower Troposphere ◽  
Circulation Model ◽  
Cloud Microphysics ◽  
Hydrologic Processes ◽  
Warm Rain

Abstract The sensitivity of tropical atmospheric hydrologic processes to cloud microphysics is investigated using the NASA Goddard Earth Observing System (GEOS) general circulation model (GCM). Results show that a faster autoconversion rate leads to (a) enhanced deep convection in the climatological convective zones anchored to tropical land regions; (b) more warm rain, but less cloud over oceanic regions; and (c) an increased convective-to-stratiform rain ratio over the entire Tropics. Fewer clouds enhance longwave cooling and reduce shortwave heating in the upper troposphere, while more warm rain produces more condensation heating in the lower troposphere. This vertical differential heating destabilizes the tropical atmosphere, producing a positive feedback resulting in more rain and an enhanced atmospheric water cycle over the Tropics. The feedback is maintained via secondary circulations between convective tower and anvil regions (cold rain), and adjacent middle-to-low cloud (warm rain) regions. The lower cell is capped by horizontal divergence and maximum cloud detrainment near the freezing–melting (0°C) level, with rising motion (relative to the vertical mean) in the warm rain region connected to sinking motion in the cold rain region. The upper cell is found above the 0°C level, with induced subsidence in the warm rain and dry regions, coupled to forced ascent in the deep convection region. It is that warm rain plays an important role in regulating the time scales of convective cycles, and in altering the tropical large-scale circulation through radiative–dynamic interactions. Reduced cloud–radiation feedback due to a faster autoconversion rate results in intermittent but more energetic eastward propagating Madden–Julian oscillations (MJOs). Conversely, a slower autoconversion rate, with increased cloud radiation produces MJOs with more realistic westward-propagating transients embedded in eastward-propagating supercloud clusters. The implications of the present results on climate change and water cycle dynamics research are discussed.

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