The Distribution of Rainfall over Oceans from Spaceborne Radars

2010 ◽  
Vol 49 (3) ◽  
pp. 535-543 ◽  
Author(s):  
Wesley Berg ◽  
Tristan L’Ecuyer ◽  
John M. Haynes
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Precipitable Water ◽  
Rainfall Regime ◽  
Tropical Regions ◽  
Light Rain ◽  
Convective Storms ◽  
Relative Contribution ◽  
Rainfall Frequency ◽  
Subtropical Oceans ◽  
Rain Rates

Abstract A combination of rainfall estimates from the 13.8-GHz Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and the 94-GHz CloudSat Cloud Profiling Radar (CPR) is used to assess the distribution of rainfall intensity over tropical and subtropical oceans. These two spaceborne radars provide highly complementary information: the PR provides the best information on the total rain volume because of its ability to estimate the intensity of all but the lightest rain rates while the CPR’s higher sensitivity provides superior rainfall detection as well as estimates of drizzle and light rain. Over the TRMM region between 35°S and 35°N, rainfall frequency from the CPR is around 9%, approximately 2.5 times that detected by the PR, and the CPR estimates indicate a contribution by light rain that is undetected by the PR of around 10% of the total. Stratifying the results by total precipitable water (TPW) as a proxy for rainfall regime indicates dramatic differences over stratus-dominated subsidence regions, with nearly 20% of the total rain occurring as light rain. Over moist tropical regions, the CPR substantially underestimates rain from intense convective storms because of large attenuation and multiple-scattering effects while the PR misses very little of the total rain volume because of a lower relative contribution from light rain. Over low-TPW regions, however, inconsistencies between estimates from the PR and the CPR point to uncertainties in the algorithm assumptions that remain to be understood and addressed.

Investigation of PR and TMI Version 6 and Version 7 Rainfall Algorithms in Landfalling Tropical Cyclones Relative to the NEXRAD Stage-IV Multisensor Precipitation Estimate Dataset

2013 ◽  
Vol 52 (12) ◽  
pp. 2809-2827 ◽  
Author(s):  
Joseph P. Zagrodnik ◽  
Haiyan Jiang
Keyword(s):  
Tropical Cyclones ◽  
Stage Iv ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Rain ◽  
Light Rain ◽  
Hourly Rainfall ◽  
Wide Range ◽  
Landfalling Tropical Cyclones ◽  
Rain Rates ◽  
Rainfall Estimates

AbstractRainfall estimates from versions 6 (V6) and 7 (V7) of the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) 2A25 and Microwave Imager (TMI) 2A12 algorithms are compared relative to the Next Generation Weather Radar (NEXRAD) Multisensor Precipitation Estimate stage-IV hourly rainfall product. The dataset consists of 252 TRMM overpasses of tropical cyclones from 2002 to 2010 within a 230-km range of southeastern U.S. Weather Surveillance Radar-1988 Doppler (WSR-88D) sites. All rainfall estimates are averaged to a uniform 1/7° square grid. The grid boxes are also divided by their TMI surface designation (land, ocean, or coast). A detailed statistical analysis is undertaken to determine how changes to the TRMM rainfall algorithms in the latest version (V7) are influencing the rainfall retrievals relative to ground reference data. Version 7 of the PR 2A25 is the best-performing algorithm over all three surface types. Over ocean, TMI 2A12 V7 is improved relative to V6 at high rain rates. At low rain rates, the new ocean TMI V7 probability-of-rain parameter creates ambiguity in differentiating light rain (≤0.5 mm h−1) and nonraining areas. Over land, TMI V7 underestimates stage IV more than V6 does at a wide range of rain rates, resulting in an increased negative bias. Both versions of the TMI coastal algorithm are also negatively biased at both moderate and heavy rain rates. Some of the TMI biases can be explained by uncertain relationships between rain rate and 85-GHz ice scattering.

scholarly journals Comparison of TMPA-3B42 Versions 6 and 7 Precipitation Products with Gauge-Based Data over India for the Southwest Monsoon Period

2015 ◽  
Vol 16 (1) ◽  
pp. 346-362 ◽  
Author(s):  
Satya Prakash ◽  
Ashis K. Mitra ◽  
Imranali M. Momin ◽  
D. S. Pai ◽  
E. N. Rajagopal ◽  
...  
Keyword(s):  
Monsoon Rainfall ◽  
Central India ◽  
Tropical Rainfall Measuring Mission ◽  
Southwest Monsoon ◽  
Summer Monsoon Rainfall ◽  
Monsoon Period ◽  
Light Rain ◽  
Rainfall Frequency ◽  
India Summer Monsoon ◽  
Marginal Improvement

Abstract The upgraded version 7 (V7) of the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) products is available to the user community. In this paper, two successive versions of the TMPA-3B42 research monitoring product, version 6 (V6) and V7, at the daily scale are evaluated over India during the southwest monsoon with gauge-based data for a 13-yr (1998–2010) period. Over typical monsoon rainfall zones, biases are improved by 5%–10% in V7 over the regions of higher rainfall like the west coast, northeastern, and central India. A similar reduced bias is seen in V7 over the rain-shadow region located in southeastern India. In terms of correlation, anomaly correlation, and RMSE, a marginal improvement is seen in V7. Additionally, in all-India summer monsoon rainfall amounts, mean, interannual values, and standard deviation show an overall improvement in V7. Different skill metrics over typical subregions within India show an improvement of the monsoon rainfall representation in V7. Rainfall frequency in different categories also indicates an overall improvement in V7 across all scales and subregions. Over central India regions associated with the monsoon transients, the sign of the bias has changed toward a positive bias. Even if the bias in the frequency of the occurrence of light rain has improved in V7, the values still show a large difference compared to observations. Though both V6 and V7 are able to represent the anomalous dry/wet regions during contrasting monsoon years, V7 shows some improvement in amplitude of those anomalies over V6. In general, V7 has considerably improved over V6 and will continue to be in demand from various sectors of observed rainfall data users.

scholarly journals Warm Rain Rates from AMSR-E 89-GHz Brightness Temperatures Trained Using CloudSat Rain-Rate Observations

2019 ◽  
Vol 36 (6) ◽  
pp. 1033-1051 ◽  
Author(s):  
Ryan Eastman ◽  
Matthew Lebsock ◽  
Robert Wood
Keyword(s):  
Rain Rate ◽  
Sea Surface ◽  
Training Dataset ◽  
Light Rain ◽  
Brightness Temperatures ◽  
Warm Rain ◽  
Confounding Variables ◽  
The Mean ◽  
Subtropical Oceans ◽  
Rain Rates

AbstractCollocated CloudSat rain rates and Advanced Microwave Scanning Radiometer for EOS (AMSR-E) 89-GHz brightness temperature Tb retrievals allow for the development of an algorithm to estimate light, warm rain statistics as a function of AMSR-E 89-GHz Tb for shallow marine clouds. Four statistics are calculated from CloudSat rainfall rate estimates within each 4 km × 6 km Tb pixel sampled by both sensors: the probability of rainfall, the mean rain rate, the mean rate when raining, and the maximum rain rate. Observations with overlying cold clouds are removed from the analysis. To account for confounding variables that modify Tb, curves are fit to the mean relationships between Tb and these four statistics within bins of constant column-integrated water vapor from AMSR-E, and sea surface temperature and wind speed from reanalysis grids. The coefficients that define these curves are then applied to all available AMSR-E Tb retrievals to estimate rain rate throughout the eastern subtropical oceans. A preliminary analysis shows strong agreement between AMSR-E rain rates and the CloudSat training dataset. Comparison with an existing microwave precipitation product shows that the new statistical product has an improved sensitivity to light rain. A climatology for the year 2007 shows that precipitation rates tend to be heavier where the sea surface is warmer and that rain is most frequent where stratocumulus transitions to trade cumulus in the subtropics.

scholarly journals Contribution of Extreme Convective Storms to Rainfall in South America

2015 ◽  
Vol 17 (1) ◽  
pp. 353-367 ◽  
Author(s):  
K. L. Rasmussen ◽  
M. M. Chaplin ◽  
M. D. Zuluaga ◽  
R. A. Houze
Keyword(s):  
South America ◽  
Amazon Basin ◽  
Austral Summer ◽  
Tropical Rainfall Measuring Mission ◽  
Life Cycles ◽  
High Resolution Data ◽  
Tropical Regions ◽  
Convective Storms ◽  
La Plata ◽  
La Plata Basin

Abstract The contribution of extreme convective storms to rainfall in South America is investigated using 15 years of high-resolution data from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). Precipitation from three specific types of storms with extreme horizontal and vertical dimensions have been calculated and compared to the climatological rain. The tropical and subtropical regions of South America differ markedly in the influence of storms with extreme dimensions. The tropical regions, especially the Amazon basin, have aspects similar to oceanic convection. Convection in the subtropical regions, centered on La Plata basin, exhibits patterns consistent with storm life cycles initiating in the foothills of the Andes and growing into larger mesoscale convective systems that propagate to the east. In La Plata basin, convective storms with a large horizontal dimension contribute ~44% of the rain and the accumulated influence of all three types of storms with extreme characteristics produce ~95% of the total precipitation in the austral summer.

scholarly journals Exploring the Transient Behavior of Z–R Relationships: Implications for Radar Rainfall Estimation

2009 ◽  
Vol 48 (10) ◽  
pp. 2127-2143 ◽  
Author(s):  
Olivier P. Prat ◽  
Ana P. Barros
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Transient Behavior ◽  
Warm Pool ◽  
Rainfall Regime ◽  
Rainfall Estimation ◽  
Radar Rainfall ◽  
Microphysical Process ◽  
Transient Nature ◽  
Microphysical Processes ◽  
Rain Rates

Abstract The objective of this study is to characterize the signature of dynamical microphysical processes on reflectivity–rainfall (Z–R) relationships used for radar rainfall estimation. For this purpose, a bin model with explicit microphysics was used to perform a sensitivity analysis of the shape parameters of the drop size distribution (DSD) as a function of time and rainfall regime. Simulations show that coalescence is the dominant microphysical process for low to moderate rain intensity regimes (R < 20 mm h−1) and that the rain rate in this regime is strongly dependent on the spectral properties of the DSD (i.e., the shape). The time to equilibrium for light rainfall is at least twice as long as in the case of heavy rainfall (1 h for stratiform vis-à-vis 30 min for thunderstorms). For high-intensity rainfall (R > 20 mm h−1), collision–breakup dynamics dominate the evolution of the raindrop spectra. The time-dependent Z–R relationships produced by the model converge to a universal Z–R relationship for heavy intensity rainfall (A = 1257; b ∼ 1) centered on the region of Z–R space defined by the ensemble of over 100 empirical Z–R relationships. Given the intrinsically transient nature of the DSD for light rainfall, it is proposed that the vertical raindrop spectra and corresponding rain rates should be modeled explicitly by a microphysical model. A demonstration using a multicolumn simulation of a Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) overpass over Darwin for a stratiform event during the Tropical Warm Pool–International Cloud Experiment (TWP-ICE) is presented.

scholarly journals Validation of TRMM Precipitation Radar through Comparison of Its Multiyear Measurements with Ground-Based Radar

2009 ◽  
Vol 48 (4) ◽  
pp. 804-817 ◽  
Author(s):  
Liang Liao ◽  
Robert Meneghini
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Heavy Rain ◽  
Radar Data ◽  
Precipitation Radar ◽  
Convective Storms ◽  
Conditional Mean ◽  
Conditional Basis ◽  
Trmm Precipitation ◽  
Rain Rates ◽  
Overlap Area

Abstract A procedure to accurately resample spaceborne and ground-based radar data is described and then is applied to the measurements taken from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and the ground-based Weather Surveillance Radar-1988 Doppler (WSR-88D or WSR) for the validation of the PR measurements and estimates. Through comparisons with the well-calibrated, nonattenuated WSR at Melbourne, Florida, for the period 1998–2007, the calibration of the PR aboard the TRMM satellite is checked using measurements near the storm top. Analysis of the results indicates that the PR, after taking into account differences in radar reflectivity factors between the PR and WSR, has a small positive bias of 0.8 dB relative to the WSR, implying a soundness of the PR calibration in view of the uncertainties involved in the comparisons. Comparisons between the PR and WSR reflectivities are also made near the surface for evaluation of the attenuation-correction procedures used in the PR algorithms. It is found that the PR attenuation is accurately corrected in stratiform rain but is underestimated in convective rain, particularly in heavy rain. Tests of the PR estimates of rainfall rate are conducted through comparisons in the overlap area between the TRMM overpass and WSR scan. Analyses of the data are made both on a conditional basis, in which the instantaneous rain rates are compared only at those pixels at which both the PR and WSR detect rain, and an unconditional basis, in which the area-averaged rain rates are estimated independently for the PR and WSR. Results of the conditional rain comparisons show that the PR-derived rain is about 9% greater and 19% less than the WSR estimates for stratiform and convective storms, respectively. Overall, the PR tends to underestimate the conditional mean rain rate by 8% for all rain categories, a finding that conforms to the results of the area-averaged rain (unconditional) comparisons.

scholarly journals Effects of Explicit Convection on Future Projections of Mesoscale Circulations, Rainfall, and Rainfall Extremes over Eastern Africa

2020 ◽  
Vol 33 (7) ◽  
pp. 2701-2718 ◽  
Author(s):  
Declan L. Finney ◽  
John H. Marsham ◽  
David P. Rowell ◽  
Elizabeth J. Kendon ◽  
Simon O. Tucker ◽  
...  
Keyword(s):  
Climate Change ◽  
Spatial Heterogeneity ◽  
Extreme Rainfall ◽  
Sea Breeze ◽  
Eastern Africa ◽  
Tropical Regions ◽  
Rainfall Frequency ◽  
Humidity Change ◽  
Parameterized Model ◽  
Rain Rates

AbstractEastern Africa’s fast-growing population is vulnerable to changing rainfall and extremes. Using the first pan-African climate change simulations that explicitly model the rainfall-generating convection, we investigate both the climate change response of key mesoscale drivers of eastern African rainfall, such as sea and lake breezes, and the spatial heterogeneity of rainfall responses. The explicit model shows widespread increases at the end of the century in mean (~40%) and extreme (~50%) rain rates, whereas the sign of changes in rainfall frequency has large spatial heterogeneity (from −50% to over +90%). In comparison, an equivalent parameterized simulation has greater moisture convergence and total rainfall increase over the eastern Congo and less over eastern Africa. The parameterized model also does not capture 1) the large heterogeneity of changes in rain frequency; 2) the widespread and large increases in extreme rainfall, which result from increased rainfall per humidity change; and 3) the response of rainfall to the changing sea breeze, even though the sea-breeze change is captured. Consequently, previous rainfall projections are likely inadequate for informing many climate-sensitive decisions—for example, for infrastructure in coastal cities. We consider the physics revealed here and its implications to be relevant for many other vulnerable tropical regions, especially those with coastal convection.

scholarly journals Estimating Rain Rates from Tipping-Bucket Rain Gauge Measurements

2008 ◽  
Vol 25 (1) ◽  
pp. 43-56 ◽  
Author(s):  
Jianxin Wang ◽  
Brad L. Fisher ◽  
David B. Wolff
Keyword(s):  
Rain Rate ◽  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Radar Reflectivity ◽  
Time Shift ◽  
Estimation Errors ◽  
Rate Estimation ◽  
Reflectivity Data ◽  
Rain Rates ◽  
Event Definition

Abstract This paper describes the cubic spline–based operational system for the generation of the Tropical Rainfall Measuring Mission (TRMM) 1-min rain-rate product 2A-56 from tipping-bucket (TB) gauge measurements. A simulated TB gauge from a Joss–Waldvogel disdrometer is employed to evaluate the errors of the TB rain-rate estimation. These errors are very sensitive to the time scale of rain rates. One-minute rain rates suffer substantial errors, especially at low rain rates. When 1-min rain rates are averaged over 4–7-min intervals or longer, the errors dramatically reduce. Estimated lower rain rates are sensitive to the event definition whereas the higher rates are not. The median relative absolute errors are about 22% and 32% for 1-min rain rates higher and lower than 3 mm h−1, respectively. These errors decrease to 5% and 14% when rain rates are used at the 7-min scale. The radar reflectivity–rain-rate distributions drawn from the large amount of 7-min rain rates and radar reflectivity data are mostly insensitive to the event definition. The time shift due to inaccurate clocks can also cause rain-rate estimation errors, which increase with the shifted time length. Finally, some recommendations are proposed for possible improvements of rainfall measurements and rain-rate estimations.

scholarly journals Constant Raindrop Fall Speed Profiles Derived from Doppler Radar Data Analyses for Steady Nonconvective Precipitation

2005 ◽  
Vol 62 (1) ◽  
pp. 220-230 ◽  
Author(s):  
Robert Nissen ◽  
Roland List ◽  
David Hudak ◽  
Greg M. McFarquhar ◽  
R. Paul Lawson ◽  
...  
Keyword(s):  
Doppler Radar ◽  
Free Fall ◽  
Radar Data ◽  
Measuring System ◽  
Doppler Velocity ◽  
Light Rain ◽  
Fall Speed ◽  
Air Speed ◽  
Velocity Moments ◽  
Rain Rates

Abstract For nonconvective, steady light rain with rain rates <5 mm h−1 the mean Doppler velocity of raindrop spectra was found to be constant below the melting band, when the drop-free fall speed was adjusted for pressure. The Doppler radar–weighted raindrop diameters varied from case to case from 1.5 to 2.5 mm while rain rates changed from 1.2 to 2.9 mm h−1. Significant changes of advected velocity moments were observed over periods of 4 min. These findings were corroborated by three independent systems: a Doppler radar for establishing vertical air speed and mean terminal drop speeds [using extended Velocity Azimuth Display (EVAD) analyses], a Joss–Waldvogel disdrometer at the ground, and a Particle Measuring System (PMS) 2-DP probe flown on an aircraft. These measurements were supported by data from upper-air soundings. The reason why inferred raindrop spectra do not change with height is the negligible interaction rate between raindrops at low rain rates. At low rain rates, numerical box models of drop collisions strongly support this interpretation. It was found that increasing characteristic drop diameters are correlated with increasing rain rates.

scholarly journals Hydrology of inland tropical lowlands: the Kapuas and Mahakam wetlands

2017 ◽  
Vol 21 (5) ◽  
pp. 2579-2594 ◽  
Author(s):  
Hidayat Hidayat ◽  
Adriaan J. Teuling ◽  
Bart Vermeulen ◽  
Muh Taufik ◽  
Karl Kastner ◽  
...  
Keyword(s):  
Time Series ◽  
Groundwater Recharge ◽  
Potential Evapotranspiration ◽  
Southern Oscillation ◽  
Tropical Rainfall Measuring Mission ◽  
Threshold Level ◽  
Phase Array ◽  
Catchment Scale ◽  
Tropical Regions ◽  
Rainfall Estimates

Abstract. Wetlands are important reservoirs of water, carbon and biodiversity. They are typical landscapes of lowland regions that have high potential for water retention. However, the hydrology of these wetlands in tropical regions is often studied in isolation from the processes taking place at the catchment scale. Our main objective is to study the hydrological dynamics of one of the largest tropical rainforest regions on an island using a combination of satellite remote sensing and novel observations from dedicated field campaigns. This contribution offers a comprehensive analysis of the hydrological dynamics of two neighbouring poorly gauged tropical basins; the Kapuas basin (98 700 km2) in West Kalimantan and the Mahakam basin (77 100 km2) in East Kalimantan, Indonesia. Both basins are characterised by vast areas of inland lowlands. Hereby, we put specific emphasis on key hydrological variables and indicators such as discharge and flood extent. The hydroclimatological data described herein were obtained during fieldwork campaigns carried out in the Kapuas over the period 2013–2015 and in the Mahakam over the period 2008–2010. Additionally, we used the Tropical Rainfall Measuring Mission (TRMM) rainfall estimates over the period 1998–2015 to analyse the distribution of rainfall and the influence of El-Niño – Southern Oscillation. Flood occurrence maps were obtained from the analysis of the Phase Array type L-band Synthetic Aperture Radar (PALSAR) images from 2007 to 2010. Drought events were derived from time series of simulated groundwater recharge using time series of TRMM rainfall estimates, potential evapotranspiration estimates and the threshold level approach. The Kapuas and the Mahakam lake regions are vast reservoirs of water of about 1000 and 1500 km2 that can store as much as 3 and 6.5 billion m3 of water, respectively. These storage capacity values can be doubled considering the area of flooding under vegetation cover. Discharge time series show that backwater effects are highly influential in the wetland regions, which can be partly explained by inundation dynamics shown by flood occurrence maps obtained from PALSAR images. In contrast to their nature as wetlands, both lowland areas have frequent periods with low soil moisture conditions and low groundwater recharge. The Mahakam wetland area regularly exhibits low groundwater recharge, which may lead to prolonged drought events that can last up to 13 months. It appears that the Mahakam lowland is more vulnerable to hydrological drought, leading to more frequent fire occurrences than in the Kapuas basin.

Sign in / Sign up

Export Citation Format

Share Document