scholarly journals Persistent Nature of Secondary Diurnal Modes of Precipitation over Oceanic and Continental Regimes

2008 ◽  
Vol 21 (16) ◽  
pp. 4115-4131 ◽  
Author(s):  
Song Yang ◽  
Kwo-Sen Kuo ◽  
Eric A. Smith
Keyword(s):  
Microwave Radiometer ◽  
Tropical Rainfall Measuring Mission ◽  
Radar Data ◽  
Early Morning ◽  
Global Scale ◽  
Fourier Decomposition ◽  
Identification Scheme ◽  
Fourier Harmonic ◽  
Clear Cut ◽  
Physically Based

Abstract This investigation seeks a better understanding of the assorted mechanisms controlling the global distribution of diurnal precipitation variability based on the use of the Tropical Rainfall Measuring Mission (TRMM) microwave radiometer and radar data. The horizontal distributions of precipitation’s diurnal cycle are derived from 8 yr of TRMM Microwave Imager (TMI) and Precipitation Radar (PR) measurements involving three TRMM standard rain retrieval algorithms; the resultant distributions are analyzed at various spatiotemporal scales. The results reveal both the prominent and expected late-evening (LE) to early-morning (EM) precipitation maxima over oceans and the counterpart prominent and expected mid- to late-afternoon (MLA) maxima over continents. Moreover, and not generally recognized, the results reveal a widespread distribution of secondary maxima, which generally mirror their counterpart regime’s behavior, occurring over both oceans and continents. That is, many ocean regions exhibit clear-cut secondary MLA precipitation maxima, while many continental regions exhibit just as evident secondary LE–EM maxima. This investigation is the first comprehensive study of these globally prevalent secondary maxima and their widespread nature, a type of study only made possible when the analysis procedure is applied to a high-quality global-scale precipitation dataset. The characteristics of the secondary maxima are mapped and described on global grids using an innovative clock-face format, while a current study that is to be published at a later date provides physically based explanations of the seasonal regional distributions of the secondary maxima. In addition to a primary “explicit” maxima identification scheme, a secondary “Fourier decomposition” maxima identification scheme is used as a cross-check to examine the amplitude and phase properties of the multimodal maxima. Accordingly, the advantages and ambiguities resulting from the use of a Fourier harmonic analysis are investigated.

Incorporating NASA Spaceborne Radar Data into NOAA National Mosaic QPE System for Improved Precipitation Measurement: A Physically Based VPR Identification and Enhancement Method

2013 ◽  
Vol 14 (4) ◽  
pp. 1293-1307 ◽  
Author(s):  
Yixin Wen ◽  
Qing Cao ◽  
Pierre-Emmanuel Kirstetter ◽  
Yang Hong ◽  
Jonathan J. Gourley ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Radar Data ◽  
Cold Season ◽  
Dual Frequency ◽  
Surface Precipitation ◽  
Precipitation Measurement ◽  
Trmm Pr ◽  
Physically Based ◽  
Precipitation Estimation ◽  
Enhancement Method

Abstract This study proposes an approach that identifies and corrects for the vertical profile of reflectivity (VPR) by using Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) measurements in the region of Arizona and southern California, where the ground-based Next Generation Weather Radar (NEXRAD) finds difficulties in making reliable estimations of surface precipitation amounts because of complex terrain and limited radar coverage. A VPR identification and enhancement (VPR-IE) method based on the modeling of the vertical variations of the equivalent reflectivity factor using a physically based parameterization is employed to obtain a representative VPR at S band from the TRMM PR measurement at Ku band. Then the representative VPR is convolved with ground radar beam sampling properties to compute apparent VPRs for enhancing NEXRAD quantitative precipitation estimation (QPE). The VPR-IE methodology is evaluated with several stratiform precipitation events during the cold season and is compared to two other statistically based correction methods, that is, the TRMM PR–based rainfall calibration and a range ring–based adjustment scheme. The results show that the VPR-IE has the best overall performance and provides much more accurate surface rainfall estimates than the original ground-based radar QPE. The potential of the VPR-IE method could be further exploited and better utilized when the Global Precipitation Measurement Mission's dual-frequency PR is launched in 2014, with anticipated accuracy improvements and expanded latitude coverage.

Decadal trends in convection from satellite microwave observations of near-surface wind and deep precipitating clouds

2020 ◽  
Author(s):  
Ziad Haddad ◽  
Svetla Hristova-Veleva ◽  
Nobuyuki Utsumi
Keyword(s):  
Microwave Radiometer ◽  
Surface Wind ◽  
Longwave Radiation ◽  
Hadley Circulation ◽  
Tropical Rainfall Measuring Mission ◽  
Direct Analysis ◽  
Radar Data ◽  
Near Surface ◽  
Temporal Sampling ◽  
The Tropics

<p>Since the past decade, evidence derived from model reanalysis (including outgoing longwave radiation, tropopause height, the latitude where zonal mean precipitation exceeds evaporation, and the latitude where the zonal mean 500-hPa meridional streamfunction crosses from positive to negative) indicate that the tropics have been expanding since at least 1979, by a very approximate one degree per decade. To the reanalysis evidence, we have added our direct analysis of near-surface wind estimated from satellite radar scatterometty. These show a widening of the Hadley circulation, with a distinct poleward migration of the zonally-averaged crossing latitudes (from easterly trade winds in the tropics to the mid-latitude westerly winds) by about 1 degree per decade. This begs the question: are the precipitation patterns changing accordingly? The brief answer, derived from analysis of the Tropical Rainfall Measuring Mission radar data, is that deep storm top heights in the tropics showed a monotone increase over the 16-year TRMM record, but their occurrences became steadily less frequent. This will be described in more detail, along with a method to increase the sample size from the rather poor temporal sampling by the TRMM radar to a 50-fold larger sample from the microwave radiometer constellation.</p>

scholarly journals Quantifying Global Uncertainties in a Simple Microwave Rainfall Algorithm

2006 ◽  
Vol 23 (1) ◽  
pp. 23-37 ◽  
Author(s):  
Christian Kummerow ◽  
Wesley Berg ◽  
Jody Thomas-Stahle ◽  
Hirohiko Masunaga
Keyword(s):  
A Priori ◽  
Simple Algorithm ◽  
Tropical Rainfall Measuring Mission ◽  
Radar Data ◽  
Global Scale ◽  
Time And Space ◽  
Validation Data ◽  
Brightness Temperatures ◽  
Time Domains ◽  
Imperfect Knowledge

Abstract While a large number of methods exist in the literature for retrieving rainfall from passive microwave brightness temperatures, little has been written about the quantitative assessment of the expected uncertainties in these rainfall products at various time and space scales. The latter is the result of two factors: sparse validation sites over most of the world’s oceans, and algorithm sensitivities to rainfall regimes that cause inconsistencies against validation data collected at different locations. To make progress in this area, a simple probabilistic algorithm is developed. The algorithm uses an a priori database constructed from the Tropical Rainfall Measuring Mission (TRMM) radar data coupled with radiative transfer computations. Unlike efforts designed to improve rainfall products, this algorithm takes a step backward in order to focus on uncertainties. In addition to inversion uncertainties, the construction of the algorithm allows errors resulting from incorrect databases, incomplete databases, and time- and space-varying databases to be examined. These are quantified. Results show that the simple algorithm reduces errors introduced by imperfect knowledge of precipitation radar (PR) rain by a factor of 4 relative to an algorithm that is tuned to the PR rainfall. Database completeness does not introduce any additional uncertainty at the global scale, while climatologically distinct space/time domains add approximately 25% uncertainty that cannot be detected by a radiometer alone. Of this value, 20% is attributed to changes in cloud morphology and microphysics, while 5% is a result of changes in the rain/no-rain thresholds. All but 2%–3% of this variability can be accounted for by considering the implicit assumptions in the algorithm. Additional uncertainties introduced by the details of the algorithm formulation are not quantified in this study because of the need for independent measurements that are beyond the scope of this paper. A validation strategy for these errors is outlined.

scholarly journals CDRD and PNPR satellite passive microwave precipitation retrieval algorithms: EuroTRMM/EURAINSAT origins and H-SAF operations

2013 ◽  
Vol 13 (4) ◽  
pp. 887-912 ◽  
Author(s):  
A. Mugnai ◽  
E. A. Smith ◽  
G. J. Tripoli ◽  
B. Bizzarri ◽  
D. Casella ◽  
...  
Keyword(s):  
National Research Council ◽  
Tropical Rainfall Measuring Mission ◽  
Passive Microwave ◽  
Neural Net ◽  
Initial Development ◽  
Atmospheric Sciences ◽  
Rainfall Analysis ◽  
Technological Advances ◽  
Retrieval Algorithms ◽  
Physically Based

Abstract. Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) is a EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) program, designed to deliver satellite products of hydrological interest (precipitation, soil moisture and snow parameters) over the European and Mediterranean region to research and operations users worldwide. Six satellite precipitation algorithms and concomitant precipitation products are the responsibility of various agencies in Italy. Two of these algorithms have been designed for maximum accuracy by restricting their inputs to measurements from conical and cross-track scanning passive microwave (PMW) radiometers mounted on various low Earth orbiting satellites. They have been developed at the Italian National Research Council/Institute of Atmospheric Sciences and Climate in Rome (CNR/ISAC-Rome), and are providing operational retrievals of surface rain rate and its phase properties. Each of these algorithms is physically based, however, the first of these, referred to as the Cloud Dynamics and Radiation Database (CDRD) algorithm, uses a Bayesian-based solution solver, while the second, referred to as the PMW Neural-net Precipitation Retrieval (PNPR) algorithm, uses a neural network-based solution solver. Herein we first provide an overview of the two initial EU research and applications programs that motivated their initial development, EuroTRMM and EURAINSAT (European Satellite Rainfall Analysis and Monitoring at the Geostationary Scale), and the current H-SAF program that provides the framework for their operational use and continued development. We stress the relevance of the CDRD and PNPR algorithms and their precipitation products in helping secure the goals of H-SAF's scientific and operations agenda, the former helpful as a secondary calibration reference to other algorithms in H-SAF's complete mix of algorithms. Descriptions of the algorithms' designs are provided including a few examples of their performance. This aspect of the development of the two algorithms is placed in the context of what we refer to as the TRMM era, which is the era denoting the active and ongoing period of the Tropical Rainfall Measuring Mission (TRMM) that helped inspire their original development. In 2015, the ISAC-Rome precipitation algorithms will undergo a transformation beginning with the upcoming Global Precipitation Measurement (GPM) mission, particularly the GPM Core Satellite technologies. A few years afterward, the first pair of imaging and sounding Meteosat Third Generation (MTG) satellites will be launched, providing additional technological advances. Various of the opportunities presented by the GPM Core and MTG satellites for improving the current CDRD and PNPR precipitation retrieval algorithms, as well as extending their product capability, are discussed.

scholarly journals Investigating Hector Convective Development and Microphysical Structure Using High-Resolution Model Simulations, Ground-Based Radar Data, and TRMM Satellite Data

2014 ◽  
Vol 71 (4) ◽  
pp. 1353-1370 ◽  
Author(s):  
Sabrina Gentile ◽  
Rossella Ferretti ◽  
Frank Silvio Marzano
Keyword(s):  
High Resolution ◽  
Conceptual Model ◽  
Vertical Structure ◽  
Mesoscale Model ◽  
Tropical Rainfall Measuring Mission ◽  
Sea Breeze ◽  
Radar Data ◽  
Full Life Cycle ◽  
Resolution Model ◽  
High Resolution Model

Abstract One event of a tropical thunderstorm typically observed in northern Australia, known as Hector, is investigated using high-resolution model output from the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) observations from a ground-based weather radar located in Berrimah (Australia) and data from the Tropical Rainfall Measuring Mission (TRMM) satellite. The analysis is carried out by tracking the full life cycle of Hector from prestorm stage to the decaying stage. In both the prestorm stage, characterized by nonprecipitating cells, and the triggering stage, when the Hector storm is effectively initiated, an analysis is performed with the aid of high-spatial-and-temporal-resolution MM5 output and the Berrimah ground-based radar imagery. During the mature (“old”) stage of Hector, considering the conceptual model for tropical convection suggested by R. Houze, TRMM Microwave Imager satellite-based data were added to ground-based radar data to analyze the storm vertical structure (dynamics, thermodynamics, and hydrometeor contents). Model evaluation with respect to observations (radar reflectivity and TRMM data) suggests that MM5 performed fairly well in reproducing the dynamics of Hector, providing support to the assertion that the strength of convection, in terms of vertical velocity, largely contributes to the vertical distribution of hydrometeors. Moreover, the stages of the storm and its vertical structure display good agreement with Houze’s aforementioned conceptual model. Finally, it was found that the most important triggering mechanisms for this Hector event are topography, the sea breeze, and a gust front produced by previous convection.

The CIMR mission and its unique capabilities for soil moisture sensing

2021 ◽  
Author(s):  
Maria Piles ◽  
Roberto Fernandez-Moran ◽  
Luis Gómez-Chova ◽  
Gustau Camps-Valls ◽  
Dara Entekhabi ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Spatial Scales ◽  
Microwave Radiometer ◽  
Critical Time ◽  
Global Scale ◽  
The Arctic ◽  
Temporal Perspective ◽  
Microwave Radiometers ◽  
Moisture Sensing

<p>The Copernicus Imaging Microwave Radiometer (CIMR) mission is currently being developed as a High Priority Copernicus Mission to support the Integrated European Policy for the Arctic. Due to its measurement characteristics, CIMR has exciting capabilities to enable a unique set of land surface products and science applications at a global scale. These characteristics go beyond what previous microwave radiometers (e.g. AMSR series, SMAP and SMOS) provide, and therefore allow for entirely new approaches to the estimation of bio-geophysical products from brightness temperature observations. Most notably, CIMR channels (L-,C-,X-,Ka-,Ku-bands) are very well fit for the simultaneous retrieval of soil moisture and vegetation properties, like biomass and moisture of different plant components such as leaves, stems or trunks. Also, the distinct spatial resolution of each frequency band allows for the development of approaches to cascade information and obtain these properties at multiple spatial scales. From a temporal perspective, CIMR has a higher revisit time than previous L-band missions dedicated to soil moisture monitoring (about 1 day global, sub-daily at the poles). This improved temporal resolution could allow resolving critical time scales of water processes, which is relevant to better model and understand land-atmosphere exchanges and feedbacks. In this presentation, new opportunities for soil moisture remote sensing made possible by the CIMR mission, as well as synergies and cross-sensor opportunities will be discussed.  </p>

scholarly journals Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations

2016 ◽  
Vol 20 (2) ◽  
pp. 903-920 ◽  
Author(s):  
W. Qi ◽  
C. Zhang ◽  
G. Fu ◽  
C. Sweetapple ◽  
H. Zhou
Keyword(s):  
Hydrological Model ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Precipitation ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Precipitation Product ◽  
Physically Based ◽  
Precipitation Estimation ◽  
Discharge Simulation ◽  
Fine Resolution

Abstract. The applicability of six fine-resolution precipitation products, including precipitation radar, infrared, microwave and gauge-based products, using different precipitation computation recipes, is evaluated using statistical and hydrological methods in northeastern China. In addition, a framework quantifying uncertainty contributions of precipitation products, hydrological models, and their interactions to uncertainties in ensemble discharges is proposed. The investigated precipitation products are Tropical Rainfall Measuring Mission (TRMM) products (TRMM3B42 and TRMM3B42RT), Global Land Data Assimilation System (GLDAS)/Noah, Asian Precipitation – Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and a Global Satellite Mapping of Precipitation (GSMAP-MVK+) product. Two hydrological models of different complexities, i.e. a water and energy budget-based distributed hydrological model and a physically based semi-distributed hydrological model, are employed to investigate the influence of hydrological models on simulated discharges. Results show APHRODITE has high accuracy at a monthly scale compared with other products, and GSMAP-MVK+ shows huge advantage and is better than TRMM3B42 in relative bias (RB), Nash–Sutcliffe coefficient of efficiency (NSE), root mean square error (RMSE), correlation coefficient (CC), false alarm ratio, and critical success index. These findings could be very useful for validation, refinement, and future development of satellite-based products (e.g. NASA Global Precipitation Measurement). Although large uncertainty exists in heavy precipitation, hydrological models contribute most of the uncertainty in extreme discharges. Interactions between precipitation products and hydrological models can have the similar magnitude of contribution to discharge uncertainty as the hydrological models. A better precipitation product does not guarantee a better discharge simulation because of interactions. It is also found that a good discharge simulation depends on a good coalition of a hydrological model and a precipitation product, suggesting that, although the satellite-based precipitation products are not as accurate as the gauge-based products, they could have better performance in discharge simulations when appropriately combined with hydrological models. This information is revealed for the first time and very beneficial for precipitation product applications.

scholarly journals Comparison of MODIS and VIIRS cloud properties with ARM ground-based observations over Finland

2016 ◽  
Vol 9 (7) ◽  
pp. 3193-3203 ◽  
Author(s):  
Moa K. Sporre ◽  
Ewan J. O'Connor ◽  
Nina Håkansson ◽  
Anke Thoss ◽  
Erik Swietlicki ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Microwave Radiometer ◽  
Single Layer ◽  
Radar Data ◽  
Liquid Water Path ◽  
Cloud Parameters ◽  
Cloud Properties ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Biogenic Aerosols ◽  
Cloud Mask

Abstract. Cloud retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the satellites Terra and Aqua and the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument aboard the Suomi-NPP satellite are evaluated using a combination of ground-based instruments providing vertical profiles of clouds. The ground-based measurements are obtained from the Atmospheric Radiation Measurement (ARM) programme mobile facility, which was deployed in Hyytiälä, Finland, between February and September 2014 for the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) campaign. The satellite cloud parameters cloud top height (CTH) and liquid water path (LWP) are compared with ground-based CTH obtained from a cloud mask created using lidar and radar data and LWP acquired from a multi-channel microwave radiometer. Clouds from all altitudes in the atmosphere are investigated. The clouds are diagnosed as single or multiple layer using the ground-based cloud mask. For single-layer clouds, satellites overestimated CTH by 326 m (14 %) on average. When including multilayer clouds, satellites underestimated CTH by on average 169 m (5.8 %). MODIS collection 6 overestimated LWP by on average 13 g m−2 (11 %). Interestingly, LWP for MODIS collection 5.1 is slightly overestimated by Aqua (4.56 %) but is underestimated by Terra (14.3 %). This underestimation may be attributed to a known issue with a drift in the reflectance bands of the MODIS instrument on Terra. This evaluation indicates that the satellite cloud parameters selected show reasonable agreement with their ground-based counterparts over Finland, with minimal influence from the large solar zenith angle experienced by the satellites in this high-latitude location.

scholarly journals The Ice Water Paths of Small and Large Ice Species in Hurricanes Arthur (2014) and Irene (2011)

2017 ◽  
Vol 56 (5) ◽  
pp. 1383-1404 ◽  
Author(s):  
Evan A. Kalina ◽  
Sergey Y. Matrosov ◽  
Joseph J. Cione ◽  
Frank D. Marks ◽  
Jothiram Vivekanandan ◽  
...  
Keyword(s):  
Small Particle ◽  
Large Particle ◽  
Radar Data ◽  
Particle Identification ◽  
Convective Precipitation ◽  
Ratio Distribution ◽  
Identification Scheme ◽  
Ice Particles ◽  
Precipitation Type ◽  
Ice Water

AbstractDual-polarization scanning radar measurements, air temperature soundings, and a polarimetric radar-based particle identification scheme are used to generate maps and probability density functions (PDFs) of the ice water path (IWP) in Hurricanes Arthur (2014) and Irene (2011) at landfall. The IWP is separated into the contribution from small ice (i.e., ice crystals), termed small-particle IWP, and large ice (i.e., graupel and snow), termed large-particle IWP. Vertically profiling radar data from Hurricane Arthur suggest that the small ice particles detected by the scanning radar have fall velocities mostly greater than 0.25 m s−1 and that the particle identification scheme is capable of distinguishing between small and large ice particles in a mean sense. The IWP maps and PDFs reveal that the total and large-particle IWPs range up to 10 kg m−2, with the largest values confined to intense convective precipitation within the rainbands and eyewall. Small-particle IWP remains mostly <4 kg m−2, with the largest small-particle IWP values collocated with maxima in the total IWP. PDFs of the small-to-total IWP ratio have shapes that depend on the precipitation type (i.e., intense convective, stratiform, or weak-echo precipitation). The IWP ratio distribution is narrowest (broadest) in intense convective (weak echo) precipitation and peaks at a ratio of about 0.1 (0.3).

scholarly journals Investigating the Applicability of Error Correction Ensembles of Satellite Rainfall Products in River Flow Simulations

2013 ◽  
Vol 14 (4) ◽  
pp. 1194-1211 ◽  
Author(s):  
Viviana Maggioni ◽  
Humberto J. Vergara ◽  
Emmanouil N. Anagnostou ◽  
Jonathan J. Gourley ◽  
Yang Hong ◽  
...  
Keyword(s):  
Error Propagation ◽  
River Flow ◽  
Tropical Rainfall Measuring Mission ◽  
Global Scale ◽  
Hydrologic Model ◽  
Runoff Simulation ◽  
Stochastic Error ◽  
Precipitation Estimation ◽  
Satellite Rainfall ◽  
The Impact

Abstract This study uses a stochastic ensemble-based representation of satellite rainfall error to predict the propagation in flood simulation of three quasi-global-scale satellite rainfall products across a range of basin scales. The study is conducted on the Tar-Pamlico River basin in the southeastern United States based on 2 years of data (2004 and 2006). The NWS Multisensor Precipitation Estimator (MPE) dataset is used as the reference for evaluating three satellite rainfall products: the Tropical Rainfall Measuring Mission (TRMM) real-time 3B42 product (3B42RT), the Climate Prediction Center morphing technique (CMORPH), and the Precipitation Estimation from Remotely Sensed Imagery Using Artificial Neural Networks–Cloud Classification System (PERSIANN-CCS). Both ground-measured runoff and streamflow simulations, derived from the NWS Research Distributed Hydrologic Model forced with the MPE dataset, are used as benchmarks to evaluate ensemble streamflow simulations obtained by forcing the model with satellite rainfall corrected using stochastic error simulations from a two-dimensional satellite rainfall error model (SREM2D). The ability of the SREM2D ensemble error corrections to improve satellite rainfall-driven runoff simulations and to characterize the error variability of those simulations is evaluated. It is shown that by applying the SREM2D error ensemble to satellite rainfall, the simulated runoff ensemble is able to envelope both the reference runoff simulation and observed streamflow. The best (uncorrected) product is 3B42RT, but after applying SREM2D, CMORPH becomes the most accurate of the three products in the prediction of runoff variability. The impact of spatial resolution on the rainfall-to-runoff error propagation is also evaluated for a cascade of basin scales (500–5000 km2). Results show a doubling in the bias from rainfall to runoff at all basin scales. Significant dependency to catchment area is exhibited for the random error propagation component.

Sign in / Sign up

Export Citation Format

Share Document