scholarly journals Comparison of Precipitation Derived from the ECMWF Operational Forecast Model and Satellite Precipitation Datasets

2013 ◽  
Vol 14 (5) ◽  
pp. 1463-1482 ◽  
Author(s):  
Chris Kidd ◽  
Erin Dawkins ◽  
George Huffman
Keyword(s):  
Hydrological Modeling ◽  
Model Simulation ◽  
Model Performance ◽  
Tropical Rainfall Measuring Mission ◽  
Forecast Model ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
Diurnal Rainfall ◽  
The Tropics ◽  
Ecmwf Model

Abstract Precipitation is an important component of the climate system, and the accurate representation of the diurnal rainfall cycle is a key test of model performance. Although the modeling of precipitation in the cooler midlatitudes has improved, in the tropics substantial errors still occur. Precipitation from the operational ECMWF forecast model is compared with satellite-derived products from the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) and TRMM Precipitation Radar (PR) to assess the mean annual and seasonal diurnal rainfall cycles. The analysis encompasses the global tropics and subtropics (40°N–40°S) over a 7-yr period from 2004 to 2011. The primary aim of the paper is to evaluate the ability of an operational numerical model and satellite products to retrieve subdaily rainfall. It was found that during the first half of the analysis period the ECMWF model overestimated precipitation by up to 15% in the tropics, although after the implementation of a new convective parameterization in November 2007 this bias fell to about 4%. The ECMWF model poorly represented the diurnal cycle, simulating rainfall too early compared to the TMPA and TRMM PR products; the model simulation of precipitation was particularly poor over Indonesia. In addition, the model did not appear to simulate mountain-slope breezes well or adequately capture many of the characteristics of mesoscale convective systems. The work highlights areas for further study to improve the representation of subgrid-scale processes in parameterization schemes and improvements in model resolution. In particular, the proper representation of subdaily precipitation in models is critical for hydrological modeling and flow forecasting.

Storm Morphology and Rainfall Characteristics of TRMM Precipitation Features

2006 ◽  
Vol 134 (10) ◽  
pp. 2702-2721 ◽  
Author(s):  
Stephen W. Nesbitt ◽  
Robert Cifelli ◽  
Steven A. Rutledge
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Annual Rainfall ◽  
Size Spectrum ◽  
Regional Variability ◽  
Rain Area ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
Trmm Precipitation ◽  
Microwave Imager ◽  
Almost All

Abstract Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), TRMM Microwave Imager (TMI), and Visible and Infrared Scanner (VIRS) observations within the Precipitation Feature (PF) database have been analyzed to examine regional variability in rain area and maximum horizontal extent of rainfall features, and role of storm morphology on rainfall production (and thus modes where vertically integrated heating occurs). Particular attention is focused on the sampling geometry of the PR and the resulting impact on PF statistics across the global Tropics. It was found that 9% of rain features extend to the edge of the PR swath, with edge features contributing 42% of total rainfall. However, the area (maximum dimension) distribution of PR features is similar to the wider-swath TMI up until a truncation point of nearly 30 000 km2 (250 km), so a large portion of the feature size spectrum may be examined using the PR as with past ground-based studies. This study finds distinct differences in land and ocean storm morphology characteristics, which lead to important differences in rainfall modes regionally. A larger fraction of rainfall comes from more horizontally and vertically developed PFs over land than ocean due to the lack of shallow precipitation in both relative and absolute frequency of occurrence, with a trimodal distribution of rainfall contribution versus feature height observed over the ocean. Mesoscale convective systems (MCSs) are found to be responsible for up to 90% of rainfall in selected land regions. Tropicswide, MCSs are responsible for more than 50% of rainfall in almost all regions with average annual rainfall exceeding 3 mm day−1. Characteristic variability in the contribution of rainfall by feature type is shown over land and ocean, which suggests new approaches for improved convective parameterizations.

scholarly journals Regional Characteristics of Extreme Rainfall Extracted from TRMM PR Measurements

2014 ◽  
Vol 27 (21) ◽  
pp. 8151-8169 ◽  
Author(s):  
Atsushi Hamada ◽  
Yuki Murayama ◽  
Yukari N. Takayabu
Keyword(s):  
Regional Differences ◽  
Tropical Rainfall Measuring Mission ◽  
Extreme Rainfall ◽  
Horizontal Resolution ◽  
Mesoscale Convective Systems ◽  
Extreme Rainfall Events ◽  
Near Surface ◽  
Rainfall Events ◽  
Convective Systems ◽  
Mesoscale Convective

Abstract Characteristics and global distribution of regional extreme rainfall are presented using 12 yr of the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) measurements. By considering each rainfall event as a set of contiguous PR rainy pixels, characteristic values for each event are obtained. Regional extreme rainfall events are defined as those in which maximum near-surface rainfall rates are higher than the corresponding 99.9th percentile on a 2.5° × 2.5° horizontal-resolution grid. The geographical distribution of extreme rainfall rates shows clear regional differences. The size and volumetric rainfall of extreme events also show clear regional differences. Extreme rainfall rates show good correlations with the corresponding rain-top heights and event sizes over oceans but marginal or no correlation over land. The time of maximum occurrence of extreme rainfall events tends to be during 0000–1200 LT over oceans, whereas it has a distinct afternoon peak over land. There are also clear seasonal differences in which the occurrence over land is largely coincident with insolation. Regional extreme rainfall is classified by extreme rainfall rate (intensity) and the corresponding event size (extensity). Regions of “intense and extensive” extreme rainfall are found mainly over oceans near coastal areas and are likely associated with tropical cyclones and convective systems associated with the establishment of monsoons. Regions of “intense but less extensive” extreme rainfall are distributed widely over land and maritime continents, probably related to afternoon showers and mesoscale convective systems. Regions of “extensive but less intense” extreme rainfall are found almost exclusively over oceans, likely associated with well-organized mesoscale convective systems and extratropical cyclones.

scholarly journals Atmospheric Rivers and Rainfall during NASA’s Iowa Flood Studies (IFloodS) Campaign*

2015 ◽  
Vol 17 (1) ◽  
pp. 257-271 ◽  
Author(s):  
Munir A. Nayak ◽  
Gabriele Villarini ◽  
A. Allen Bradley
Keyword(s):  
Stage Iv ◽  
Major Axis ◽  
Extratropical Cyclones ◽  
Rainfall Events ◽  
Atmospheric Rivers ◽  
Convective Systems ◽  
Central United States ◽  
Mesoscale Convective ◽  
The Tropics ◽  
Heavy Rainfall Events

Abstract Atmospheric rivers (ARs) play a major role in causing extreme precipitation and flooding over the central United States (e.g., Midwest floods of 1993 and 2008). The goal of this study is to characterize rainfall associated with ARs over this region during the Iowa Flood Studies (IFloodS) campaign that took place in April–June 2013. Total precipitation during IFloodS was among the five largest accumulations recorded since the mid-twentieth century over most of this region, with three of the heavy rainfall events associated with ARs. As a preliminary step, the authors evaluate how well different remote sensing–based precipitation products captured the rainfall associated with the ARs and find that stage IV is the product that shows the closest agreement to the reference data. Two of the three ARs during IFloodS occurred within extratropical cyclones, with the moist ascent associated with the presence of cold fronts. In the third AR, mesoscale convective systems resulted in intense rainfall at many locations. In all the three cases, the continued supply of warm water vapor from the tropics and subtropics helped sustain the convective systems. Most of the rainfall during these ARs was concentrated within ~100 km of the AR major axis, and this is the region where the rainfall amounts were highly positively correlated with the vapor transport intensity. Rainfall associated with ARs tends to be larger as these events mature over time. Although no major diurnal variation is detected in the AR occurrences, rainfall amounts during nocturnal ARs were higher than for ARs that occurred during the daytime.

The Diurnal Cycle of Rainfall and Convective Intensity according to Three Years of TRMM Measurements

2003 ◽  
Vol 16 (10) ◽  
pp. 1456-1475 ◽  
Author(s):  
Stephen W. Nesbitt ◽  
Edward J. Zipser
Keyword(s):  
Diurnal Cycle ◽  
Tropical Rainfall Measuring Mission ◽  
Early Morning ◽  
Convective Systems ◽  
Rain Gauges ◽  
Mesoscale Convective ◽  
Late Evening ◽  
Microwave Imager ◽  
Trmm Microwave Imager ◽  
Rain Rates

Abstract The Tropical Rainfall Measuring Mission (TRMM) satellite measurements from the precipitation radar and TRMM microwave imager have been combined to yield a comprehensive 3-yr database of precipitation features (PFs) throughout the global Tropics (±36° latitude). The PFs retrieved using this algorithm (which number nearly six million Tropicswide) have been sorted by size and intensity ranging from small shallow features greater than 75 km2 in area to large mesoscale convective systems (MCSs) according to their radar and ice scattering characteristics. This study presents a comprehensive analysis of the diurnal cycle of the observed precipitation features' rainfall amount, precipitation feature frequency, rainfall intensity, convective–stratiform rainfall portioning, and remotely sensed convective intensity, sampled Tropicswide from space. The observations are sorted regionally to examine the stark differences in the diurnal cycle of rainfall and convective intensity over land and ocean areas. Over the oceans, the diurnal cycle of rainfall has small amplitude, with the maximum contribution to rainfall coming from MCSs in the early morning. This increased contribution is due to an increased number of MCSs in the nighttime hours, not increasing MCS areas or conditional rain rates, in agreement with previous works. Rainfall from sub-MCS features over the ocean has little appreciable diurnal cycle of rainfall or convective intensity. Land areas have a much larger rainfall cycle than over the ocean, with a marked minimum in the midmorning hours and a maximum in the afternoon, slowly decreasing through midnight. Non-MCS features have a significant peak in afternoon instantaneous conditional rain rates (the mean rain rate in raining pixels), and convective intensities, which differs from previous studies using rain rates derived from hourly rain gauges. This is attributed to enhancement by afternoon heating. MCSs over land have a convective intensity peak in the late afternoon, however all land regions have MCS rainfall peaks that occur in the late evening through midnight due to their longer life cycle. The diurnal cycle of overland MCS rainfall and convective intensity varies significantly among land regions, attributed to MCS sensitivity to the varying environmental conditions in which they occur.

Morphology, Intensity, and Rainfall Production of MJO Convection: Observations from DYNAMO Shipborne Radar and TRMM

2015 ◽  
Vol 72 (2) ◽  
pp. 623-640 ◽  
Author(s):  
Weixin Xu ◽  
Steven A. Rutledge
Keyword(s):  
Mesoscale Convective System ◽  
Tropical Rainfall Measuring Mission ◽  
Radar Data ◽  
Convective System ◽  
Precipitation Radar ◽  
Convective Systems ◽  
Trmm Pr ◽  
Mesoscale Convective ◽  
Trmm Precipitation

Abstract This study uses Dynamics of the Madden–Julian Oscillation (DYNAMO) shipborne [Research Vessel (R/V) Roger Revelle] radar and Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) datasets to investigate MJO-associated convective systems in specific organizational modes [mesoscale convective system (MCS) versus sub-MCS and linear versus nonlinear]. The Revelle radar sampled many “climatological” aspects of MJO convection as indicated by comparison with the long-term TRMM PR statistics, including areal-mean rainfall (6–7 mm day−1), convective intensity, rainfall contributions from different morphologies, and their variations with MJO phase. Nonlinear sub-MCSs were present 70% of the time but contributed just around 20% of the total rainfall. In contrast, linear and nonlinear MCSs were present 10% of the time but contributed 20% and 50%, respectively. These distributions vary with MJO phase, with the largest sub-MCS rainfall fraction in suppressed phases (phases 5–7) and maximum MCS precipitation in active phases (phases 2 and 3). Similarly, convective–stratiform rainfall fractions also varied significantly with MJO phase, with the highest convective fractions (70%–80%) in suppressed phases and the largest stratiform fraction (40%–50%) in active phases. However, there are also discrepancies between the Revelle radar and TRMM PR. Revelle radar data indicated a mean convective rain fraction of 70% compared to 55% for TRMM PR. This difference is mainly due to the reduced resolution of the TRMM PR compared to the ship radar. There are also notable differences in the rainfall contributions as a function of convective intensity between the Revelle radar and TRMM PR. In addition, TRMM PR composites indicate linear MCS rainfall increases after MJO onset and produce similar rainfall contributions to nonlinear MCSs; however, the Revelle radar statistics show the clear dominance of nonlinear MCS rainfall.

Comparison of Simulated and Observed Continental Tropical Anvil Clouds and Their Radiative Heating Profiles

2012 ◽  
Vol 69 (9) ◽  
pp. 2662-2681 ◽  
Author(s):  
Scott W. Powell ◽  
Robert A. Houze ◽  
Anil Kumar ◽  
Sally A. McFarlane
Keyword(s):  
Mesoscale Model ◽  
Model Performance ◽  
Radar Data ◽  
Radiative Heating ◽  
Radar Observations ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
Atmospheric Radiation Measurement ◽  
Stringent Test ◽  
Heating Profiles

Abstract Vertically pointing millimeter-wavelength radar observations of anvil clouds extending from mesoscale convective systems (MCSs) that pass over an Atmospheric Radiation Measurement Program (ARM) field site in Niamey, Niger, are compared to anvil structures generated by the Weather Research and Forecasting (WRF) mesoscale model using six different microphysical schemes. The radar data provide the statistical distribution of the radar reflectivity values as a function of height and anvil thickness. These statistics are compared to the statistics of the modeled anvil cloud reflectivity at all altitudes. Requiring the model to be statistically accurate at all altitudes is a stringent test of the model performance. The typical vertical profile of radiative heating in the anvil clouds is computed from the radar observations. Variability of anvil structures from the different microphysical schemes provides an estimate of the inherent uncertainty in anvil radiative heating profiles. All schemes underestimate the optical thickness of thin anvils and cirrus, resulting in a bias of excessive net anvil heating in all of the simulations.

scholarly journals A Simple Model of the Life Cycle of Mesoscale Convective Systems Cloud Shield in the Tropics

2017 ◽  
Vol 30 (11) ◽  
pp. 4283-4298 ◽  
Author(s):  
R. Roca ◽  
T. Fiolleau ◽  
D. Bouniol
Keyword(s):  
Life Cycle ◽  
Simple Model ◽  
Large Scale ◽  
Morphological Characteristics ◽  
Mesoscale Convective Systems ◽  
Boreal Summer ◽  
Maximum Extent ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
The Tropics

Abstract Mesoscale convective systems (MCSs) are important to the water and energy budget of the tropical climate and are essential ingredients of the tropical circulation. MCSs are readily observed in satellite infrared geostationary imagery as cloud clusters that evolve in time from small structures to well-organized large patches of cloud shield before dissipating. The MCS cloud shield is the result of a large ensemble of mesoscale dynamical, thermodynamical, and microphysical processes. This study shows that a simple parametric model can summarize the time evolution of the morphological characteristics of the cloud shield during the life cycle of the MCS. It consists of a growth–decay linear model of the cloud shield and is based on three parameters: the time of maximum extent, the maximum extent, and the duration of the MCS. It is shown that the time of maximum is frequently close to the middle of the life cycle and that the correlation between maximum extent and duration is strong all over the tropics. This suggests that 1 degree of freedom is left to summarize the life cycle of the MCS cloud shield. Such a model fits the observed MCS equally well, independent of the duration, size, location, and propagation characteristics, and its relevance is assessed for a large number of MCSs over three boreal summer periods over the whole tropical belt. The scaling of this simple model exhibits weak (strong) regional variability for the short- (long-) lived systems indicative of the primary importance of the internal dynamics of the systems to the large-scale environment for MCS sustainability.

Correction of Radar QPE Errors for Non-Uniform VPRs Using TRMM Observations

2013 ◽  
Vol 726-731 ◽  
pp. 3391-3396
Author(s):  
Man Zhang ◽  
You Cun Qi
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Tropical Rainfall Measuring Mission ◽  
Cool Season ◽  
Convective Systems ◽  
Freezing Level ◽  
Stratiform Region ◽  
Stratiform Precipitation ◽  
Precipitation Estimation ◽  
Mesoscale Convective

Mesoscale Convective Systems (MCSs) contain both regions of convective and stratiform precipitation, and a bright band (BB) or equivalent high-reflectivity region is often found in the stratiform precipitation. Inflated reflectivity intensities in the BB often cause positive biases in radar quantitative precipitation estimation (QPE), and a vertical profile of reflectivity (VPR) correction is necessary to reduce the error. VPR corrections of the radar QPE is more difficult for MCSs than for a widespread cool season stratiform precipitation because of the spatial non-homogeneity of MCSs. Further, microphysical processes in the MCS stratiform region are more complicated than in the large-scale cool season stratiform precipitation. A clearly defined BB bottom, which is critical for accurate VPR corrections, is often not found in ground radar VPRs from MCSs. This is a big challenge when the stratiform region of MCSs is far away from the radar where the radar beam is too high or too wide to resolve the BB bottom. Further, variations of reflectivity below the freezing level are much more significant in MCSs than in a large-scale cool season precipitation, requiring high-resolution radar observations near the ground for an effective VPR correction. The current study seeks to use the vertical precipitation structure observed from Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR) to aid VPR corrections of the ground radar QPE in MCSs. High-resolution VPRs are derived from TRMM data for MCSs and then applied for the correction of ground radar QPEs.

scholarly journals Basis for a Rainfall Estimation Technique Using IR–VIS Cloud Classification and Parameters over the Life Cycle of Mesoscale Convective Systems

2008 ◽  
Vol 47 (5) ◽  
pp. 1500-1517 ◽  
Author(s):  
G. Delgado ◽  
Luiz A. T. Machado ◽  
Carlos F. Angelis ◽  
Marcus J. Bottino ◽  
Á. Redaño ◽  
...  
Keyword(s):  
Life Cycle ◽  
Empirical Relationship ◽  
Estimation Method ◽  
Tropical Rainfall Measuring Mission ◽  
Rainfall Rate ◽  
Mesoscale Convective Systems ◽  
Rainfall Estimation ◽  
Convective Systems ◽  
Cloud Classification ◽  
Mesoscale Convective

Abstract This paper discusses the basis for a new rainfall estimation method using geostationary infrared and visible data. The precipitation radar on board the Tropical Rainfall Measuring Mission satellite is used to train the algorithm presented (which is the basis of the estimation method) and the further intercomparison. The algorithm uses daily Geostationary Operational Environmental Satellite infrared–visible (IR–VIS) cloud classifications together with radiative and evolution properties of clouds over the life cycle of mesoscale convective systems (MCSs) in different brightness temperature (Tb) ranges. Despite recognition of the importance of the relationship between the life cycle of MCSs and the rainfall rate they produce, this relationship has not previously been quantified precisely. An empirical relationship is found between the characteristics that describe the MCSs’ life cycle and the magnitude of rainfall rate they produce. Numerous earlier studies focus on this subject using cloud-patch or pixel-based techniques; this work combines the two techniques. The algorithm performs reasonably well in the case of convective systems and also for stratiform clouds, although it tends to overestimate rainfall rates. Despite only using satellite information to initialize the algorithm, satisfactory results were obtained relative to the hydroestimator technique, which in addition to the IR information uses extra satellite data such as moisture and orographic corrections. This shows that the use of IR–VIS cloud classification and MCS properties provides a robust basis for creating a future estimation method incorporating humidity Eta field outputs for a moisture correction, digital elevation models combined with low-level moisture advection for an orographic correction, and a nighttime cloud classification.

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