scholarly journals Adequacy of Using a 1/3-Degree Special Sensor Microwave Imager Dataset to Estimate Climate-Scale Rainfall

2000 ◽  
Vol 39 (5) ◽  
pp. 680-685 ◽  
Author(s):  
Qihang Li ◽  
Ralph Ferraro ◽  
Norman Grody
Keyword(s):  
Data Processing ◽  
Spatial Resolution ◽  
Information Service ◽  
Global Precipitation Climatology Project ◽  
Spatial Density ◽  
Tropical Ocean ◽  
Full Resolution ◽  
Toga Coare ◽  
Microwave Imager ◽  
Climate Scale

Abstract Until recently, monthly rainfall products using the National Oceanic and Atmospheric Administration National Environmental Satellite, Data, and Information Service Office of Research and Applications Special Sensor Microwave Imager (SSM/I) rainfall algorithm have been generated on a global 2.5° × 2.5° grid. The rainfall estimates are based on a subsampled set of the full-resolution SSM/I data, with a resulting spatial density of about one-third of what is possible at SSM/I’s highest spatial resolution. The reduction in the spatial resolution was introduced in 1992 as a compromise dictated by data processing capabilities. Currently, daily SSM/I data processing at full resolution has been established and is being operated in parallel with the subsampled set. Reprocessing of the entire SSM/I time series based on the full-resolution data is plausible but requires the reprocessing of over 10 yr of retrospective data. Because the Global Precipitation Climatology Project is considering the generation of a daily 1° × 1° rainfall product, it is important that the effects of using the reduced spatial resolution be reexamined. In this study, error due to using the reduced-resolution versus the full-resolution SSM/I data in the gridded products at 2.5° and 1° grid sizes is examined. The estimates are based on statistics from radar-derived rain data and from SSM/I data taken over the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) radar site. SSM/I data at full resolution were assumed to provide rain estimates with 12.5-km spacing. Subsampling with spacings of 25, 37.5 (which corresponds to the present situation of ⅓° latitude–longitude spatial resolution), and 50 km were considered. For the instantaneous 2.5° × 2.5° product, the error due to subsampling, expressed as a percentage of the gridbox mean, was estimated using radar-derived data and was 6%, 10%, and 15% at these successively poorer sampling densities. For monthly averaged products on a 2.5° × 2.5° grid, it was substantially lower: 3%, 4%, and 7%, respectively. Subsampling errors for monthly averages on a 1° × 1° grid were 8%, 16%, and 23%, respectively. Estimates based on SSM/I data at full resolution gave errors that were somewhat larger than those from radar-based estimates. It was concluded that a rain product of monthly averages on a 1° × 1° grid must use the full-resolution SSM/I data. More work is needed to determine how applicable these estimates are to other areas of the globe with substantially different rain statistics.

scholarly journals An Updated TRMM Composite Climatology of Tropical Rainfall and Its Validation

2014 ◽  
Vol 27 (1) ◽  
pp. 273-284 ◽  
Author(s):  
Jian-Jian Wang ◽  
Robert F. Adler ◽  
George J. Huffman ◽  
David Bolvin
Keyword(s):  
Pacific Ocean ◽  
Tropical Rainfall Measuring Mission ◽  
Global Precipitation Climatology Project ◽  
Mean Value ◽  
Passive Microwave ◽  
Control Measures ◽  
Tropical Ocean ◽  
Tropical Rainfall ◽  
Uncertainty Estimates ◽  
Microwave Imager

Abstract An updated 15-yr Tropical Rainfall Measuring Mission (TRMM) composite climatology (TCC) is presented and evaluated. This climatology is based on a combination of individual rainfall estimates made with data from the primary TRMM instruments: the TRMM Microwave Imager (TMI) and the precipitation radar (PR). This combination climatology of passive microwave retrievals, radar-based retrievals, and an algorithm using both instruments simultaneously provides a consensus TRMM-based estimate of mean precipitation. The dispersion of the three estimates, as indicated by the standard deviation σ among the estimates, is presented as a measure of confidence in the final estimate and as an estimate of the uncertainty thereof. The procedures utilized by the compositing technique, including adjustments and quality-control measures, are described. The results give a mean value of the TCC of 4.3 mm day−1 for the deep tropical ocean belt between 10°N and 10°S, with lower values outside that band. In general, the TCC values confirm ocean estimates from the Global Precipitation Climatology Project (GPCP) analysis, which is based on passive microwave results adjusted for sampling by infrared-based estimates. The pattern of uncertainty estimates shown by σ is seen to be useful to indicate variations in confidence. Examples include differences between the eastern and western portions of the Pacific Ocean and high values in coastal and mountainous areas. Comparison of the TCC values (and the input products) to gauge analyses over land indicates the value of the radar-based estimates (small biases) and the limitations of the passive microwave algorithm (relatively large biases). Comparison with surface gauge information from western Pacific Ocean atolls shows a negative bias (~16%) for all the TRMM products, although the representativeness of the atoll gauges of open-ocean rainfall is still in question.

scholarly journals Comparison of the GPCP and CMAP Merged Gauge–Satellite Monthly Precipitation Products for the Period 1979–2001

2004 ◽  
Vol 5 (6) ◽  
pp. 1207-1222 ◽  
Author(s):  
Xungang Yin ◽  
Arnold Gruber ◽  
Phil Arkin
Keyword(s):  
Spatial Correlation ◽  
Input Data ◽  
Sampling Error ◽  
Global Precipitation Climatology Project ◽  
Monthly Precipitation ◽  
Tropical Ocean ◽  
Microwave Sounding Unit ◽  
Microwave Sounding ◽  
Microwave Imager ◽  
Global Precipitation

Abstract The two monthly precipitation products of the Global Precipitation Climatology Project (GPCP) and the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) are compared on a 23-yr period, January 1979–December 2001. For the long-term mean, major precipitation patterns are clearly demonstrated by both products, but there are differences in the pattern magnitudes. In the tropical ocean the CMAP is higher than the GPCP, but this is reversed in the high-latitude ocean. The GPCP–CMAP spatial correlation is generally higher over land than over the ocean. The correlation between the global mean oceanic GPCP and CMAP is significantly low. It is very likely because the input data of the two products have much less in common over the ocean; in particular, the use of atoll data by the CMAP is disputable. The decreasing trend in the CMAP oceanic precipitation is found to be an artifact of input data change and atoll sampling error. In general, overocean precipitation represented by the GPCP is more reasonable; over land the two products are close, but different merging algorithms between the GPCP and the CMAP can sometimes produce substantial discrepancy in sensitive areas such as equatorial West Africa. EOF analysis shows that the GPCP and the CMAP are similar in 6 out of the first 10 modes, and the first 2 leading modes (ENSO patterns) of the GPCP are nearly identical to their counterparts of the CMAP. Input data changes [e.g., January 1986 for Geostationary Operational Environmental Satellite (GOES) precipitation index (GPI), July 1987 for Special Sensor Microwave Imager (SSM/I), May 1994 for Microwave Sounding Unit (MSU), and January 1996 for atolls] have implications in the behavior of the two datasets. Several abrupt changes identified in the statistics of the two datasets including the changes in overocean precipitation, spatial correlation time series, and some of the EOF principal components, can be related to one or more input data changes.

Radar Measurement of Rainfall with and without Polarimetry

2008 ◽  
Vol 47 (7) ◽  
pp. 1929-1939 ◽  
Author(s):  
Carlton W. Ulbrich ◽  
David Atlas
Keyword(s):  
A Priori ◽  
Structural Features ◽  
Size Distributions ◽  
Tropical Ocean ◽  
Convective Storms ◽  
Toga Coare ◽  
Median Volume ◽  
Raindrop Size ◽  
Differential Reflectivity ◽  
R Relation

Abstract Raindrop size distributions (DSDs) for tropical convective storms are used to examine the relationships between the parameters of a gamma DSD, with special emphasis on their variation with the stage of the storm. Such a distinction has rarely been made before. Several storms from a variety of tropical locations are divided into storm stages according to the temporal dependence of their reflectivity factor Z, rainfall rate R, and median volume diameter D0. In most cases it is found that the DSD parameter D0 is approximately constant in time during the convective, or C, stage, which leads to a Z–R relation of the form Z = AR, that is, a linear relationship between Z and R. This finding implies the existence of equilibrium DSDs during the C stage. The convective stage is sometimes marked by pulsations in draft strength so that D0, R, and Z and associated values of the shape parameter μ decrease in a quasi-transition stage before increasing once more. Theoretical relations between the differential reflectivity ZDR and the ratio Z/R as functions of the DSD parameter μ are derived by assuming a gamma DSD and an accurate raindrop fall speed law. It is found that data derived from disdrometer observations lie along a μ = 5 isopleth for tropical continental C stages (Puerto Rico and Brazil) and along a μ = 12 isopleth for tropical maritime C stages [Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE)]. Small values of μ that occur in the weak updraft intervals do not impact the rainfall measurements because they correspond to relatively small R. The latter features imply that the measurement of rainfall for the convective stages can be performed with standard polarimetry involving only two measurables rather than three, provided knowledge of μ is available a priori. A new rain parameter diagram is presented in which isopleths of the generalized number concentration and D0 are superimposed on the Z–R plot. It is proposed that it is possible to estimate D0 from climatological and observable storm structural features, which, with Z, provide estimates of R. Such an approach is necessary for use with conventional radars until polarimetric radars are more widely available.

scholarly journals Water vapor mapping by fusing InSAR and GNSS remote sensing data and atmospheric simulations

2015 ◽  
Vol 19 (12) ◽  
pp. 4747-4764 ◽  
Author(s):  
F. Alshawaf ◽  
B. Fersch ◽  
S. Hinz ◽  
H. Kunstmann ◽  
M. Mayer ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Vapor ◽  
Data Fusion ◽  
Spatial Resolution ◽  
Heterogeneous Data ◽  
Spatial Density ◽  
Data Sets ◽  
Data Set ◽  
Fixed Rank Kriging ◽  
Fixed Rank

Abstract. Data fusion aims at integrating multiple data sources that can be redundant or complementary to produce complete, accurate information of the parameter of interest. In this work, data fusion of precipitable water vapor (PWV) estimated from remote sensing observations and data from the Weather Research and Forecasting (WRF) modeling system are applied to provide complete grids of PWV with high quality. Our goal is to correctly infer PWV at spatially continuous, highly resolved grids from heterogeneous data sets. This is done by a geostatistical data fusion approach based on the method of fixed-rank kriging. The first data set contains absolute maps of atmospheric PWV produced by combining observations from the Global Navigation Satellite Systems (GNSS) and Interferometric Synthetic Aperture Radar (InSAR). These PWV maps have a high spatial density and a millimeter accuracy; however, the data are missing in regions of low coherence (e.g., forests and vegetated areas). The PWV maps simulated by the WRF model represent the second data set. The model maps are available for wide areas, but they have a coarse spatial resolution and a still limited accuracy. The PWV maps inferred by the data fusion at any spatial resolution show better qualities than those inferred from single data sets. In addition, by using the fixed-rank kriging method, the computational burden is significantly lower than that for ordinary kriging.

scholarly journals Enhancement of the Performance and Data Processing Rate of an Optical Frequency Domain Reflectometer Distributed Sensing System Using A Limited Swept Wavelength Range

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3480 ◽  
Author(s):  
Kunpeng Feng ◽  
Jiwen Cui ◽  
Yihua Jin ◽  
Xun Sun ◽  
Dong Jiang ◽  
...  
Keyword(s):  
Data Processing ◽  
Frequency Domain ◽  
Spatial Resolution ◽  
Wavelength Range ◽  
Distributed Sensing ◽  
Optical Frequency ◽  
Local Similarity ◽  
Processing Rate ◽  
Spectrum Range ◽  
Measurable Range

A novel optical frequency domain reflectometer (OFDR) processing algorithm is proposed to enhance the measurable range and data processing rate using a narrow swept spectrum range and reducing the time consuming of the process distributed sensing results. To reduce the swept wavelength range and simultaneously enhance strain measurable range, the local similarity characteristics of Rayleigh scattering fingerprint spectrum is discovered and a new similarity evaluation function based on least-square method is built to improve the data processing rate and sensing performance. By this method, the strain measurable range is raised to 3000 µε under a highest spatial resolution of 3 mm when the swept spectrum range is only 10 nm and the data processing rate is improved by at least 10 times. Experimental results indicate that a nonlinearity of less than 0.5%, a strain resolution of better than 10 µε, a repeatability at zero strain of below ±0.4 GHz and a full-scale accuracy is lower than 0.85 GHz under a highest spatial resolution of 3 mm can be achieved. Advantages of this method are fast processing rate, large strain measurable range, high SNR, and applicability with current OFDR systems.

scholarly journals Kinematic and Precipitation Characteristics of Convective Systems Observed by Airborne Doppler Radar during the Life Cycle of a Madden–Julian Oscillation in the Indian Ocean

2014 ◽  
Vol 142 (4) ◽  
pp. 1385-1402 ◽  
Author(s):  
Nick Guy ◽  
David P. Jorgensen
Keyword(s):  
Indian Ocean ◽  
Doppler Radar ◽  
Convective System ◽  
Dynamical Structure ◽  
Madden Julian Oscillation ◽  
Tropical Ocean ◽  
Convective Systems ◽  
Toga Coare ◽  
Stratiform Precipitation ◽  
The Indian Ocean

Abstract This study presents characteristics of convective systems observed during the Dynamics of the Madden–Julian oscillation (DYNAMO) experiment by the instrumented NOAA WP-3D aircraft. Nine separate missions, with a focus on observing mesoscale convective systems (MCSs), were executed to obtain data in the active and inactive phase of a Madden–Julian oscillation (MJO) in the Indian Ocean. Doppler radar and in situ thermodynamic data are used to contrast the convective system characteristics during the evolution of the MJO. Isolated convection was prominent during the inactive phases of the MJO, with deepening convection during the onset of the MJO. During the MJO peak, convection and stratiform precipitation became more widespread. A larger population of deep convective elements led to a larger area of stratiform precipitation. As the MJO decayed, convective system top heights increased, though the number of convective systems decreased, eventually transitioning back to isolated convection. A distinct shift of echo top heights and contoured frequency-by-altitude diagram distributions of radar reflectivity and vertical wind speed indicated that some mesoscale characteristics were coupled to the MJO phase. Convective characteristics in the climatological initiation region (Indian Ocean) were also apparent. Comparison to results from the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) in the western Pacific indicated that DYNAMO MCSs were linearly organized more parallel to the low-level shear and without strong cold pools than in TOGA COARE. Three-dimensional MCS airflow also showed a different dynamical structure, with a lack of the descending rear inflow present in shear perpendicularly organized TOGA COARE MCSs. Weaker, but deeper updrafts were observed in DYNAMO.

scholarly journals Relating Passive 37-GHz Scattering to Radar Profiles in Strong Convection

2011 ◽  
Vol 50 (1) ◽  
pp. 233-240 ◽  
Author(s):  
Daniel J. Cecil
Keyword(s):  
Central Africa ◽  
Tropical Rainfall Measuring Mission ◽  
The United States ◽  
Phase Layer ◽  
Tropical Ocean ◽  
Convective Systems ◽  
Freezing Level ◽  
Brightness Temperatures ◽  
Microwave Imager ◽  
Ice Water

Abstract Tropical Rainfall Measuring Mission (TRMM) Microwave Imager and precipitation radar measurements are examined for strong convective systems. Storms having similar values of minimum 37-GHz polarization-corrected temperature (PCT) are grouped together, and their vertical profiles of maximum radar reflectivity are composited. Lower 37-GHz PCT corresponds to stronger radar profiles (high reflectivity through a deep layer), but characteristic profiles for a given 37-GHz PCT are different for deep tropical ocean, deep tropical land, subtropical ocean, and subtropical land regions. Tropical oceanic storms have a sharper decrease of reflectivity just above the freezing level than storms from other regions with the same brightness temperature. Storms from subtropical land regions have the slowest decrease of reflectivity with height and the greatest mixed-phase-layer ice water content (IWC). Linear fits of 37-GHz PCT versus IWC for each region are used to scale the brightness temperatures. Counts of storms with these scaled brightness temperatures below certain thresholds suggest that not as many of the strongest storms occur in central Africa as in subtropical parts of South America, the United States, and central Asia.

scholarly journals Modeling Diurnal and Intraseasonal Variability of the Ocean Mixed Layer

2005 ◽  
Vol 18 (8) ◽  
pp. 1190-1202 ◽  
Author(s):  
D. J. Bernie ◽  
S. J. Woolnough ◽  
J. M. Slingo ◽  
E. Guilyardi
Keyword(s):  
Mixed Layer ◽  
Diurnal Cycle ◽  
Intraseasonal Variability ◽  
Western Pacific ◽  
Madden Julian Oscillation ◽  
Ocean Mixed Layer ◽  
Tropical Ocean ◽  
Toga Coare ◽  
The Impact ◽  
The Western Pacific

Abstract The intraseasonal variability of SST associated with the passage of the Madden–Julian oscillation (MJO) is well documented; yet coupled model integrations generally underpredict the magnitude of this SST variability. Observations from the Improved Meteorological Instrument (IMET) mooring in the western Pacific during the intensive observing period (IOP) of the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) showed a large diurnal signal in SST that is modulated by the passage of the MJO. In this study, observations from the IOP of the TOGA COARE and a one-dimensional (1D) ocean mixed layer model incorporating the K-Profile Parameterization (KPP) vertical mixing scheme have been used to investigate the rectification of the intraseasonal variability of SST by the diurnal cycle and the implied impact of the absence of a representation of this process on the modeled intraseasonal variability in coupled GCMs. Analysis of the SST observations has shown that the increase of the daily mean SST by the diurnal cycle of SST accounts for about one-third of the magnitude of intraseasonal variability of SST associated with the Madden–Julian oscillation in the western Pacific warm pool. Experiments from the 1D model forced with fluxes at a range of temporal resolutions and with differing vertical resolution of the model have shown that to capture 90% of the diurnal variability of SST, and hence 95% of the intraseasonal variability of SST, requires a 3-h or better temporal resolution of the fluxes and a vertical grid with an upper-layer thickness of the order of 1 m. In addition to the impact of the representation of the diurnal cycle on the intraseasonal variability of SST, the strength of the mixing across the thermocline was found to be enhanced by the proper representation of the nighttime deep mixing in the ocean, implying a possible impact of the diurnal cycle onto the mean climate of the tropical ocean.

Research of Personalized Information Service Based on Association Rules

2013 ◽  
Vol 760-762 ◽  
pp. 1800-1803 ◽  
Author(s):  
Qing Song Zhang ◽  
Xin Yu Wang
Keyword(s):  
Data Processing ◽  
Association Rules ◽  
Information Service ◽  
Processing Technology ◽  
Demand Model ◽  
Library Service ◽  
Mining Technology ◽  
Association Rules Mining ◽  
Transaction Data ◽  
Information Demand

Association rules mining technology is a new data processing technology. Its algorithm and application play a very important role in the library. Obtaining personalized information of readers effectively and automatically is the key to carry out individualized service of university library. By using association rules technology, the library mine transaction data generated in the process of library service. And it also can have an access to various types of readers' information demand model, thus can provide accurate service for readers.

scholarly journals A data processing approach with built-in spatial resolution reduction methods to construct energy system models

2021 ◽  
Vol 1 ◽  
pp. 36
Author(s):  
Christian Etienne Fleischer
Keyword(s):  
Data Processing ◽  
Open Source ◽  
Spatial Resolution ◽  
Input Data ◽  
Energy System ◽  
System Modelling ◽  
System Models ◽  
Processing Approach ◽  
Open Source Data ◽  
Reduction Methods

Introduction: Data processing is a crucial step in energy system modelling which prepares input data from various sources into a format needed to formulate a model. Multiple open-source web-hosted databases offer pre-processed input data within the European context. However, the number of documented open-source data processing workflows that allow for the construction of energy system models with specified spatial resolution reduction methods is still limited. Methods: This paper presents a novel data processing approach to construct sector-coupled energy system models for European countries while maximising the use of existing web-hosted pre-processed data. Three power and heat optimisation models of Germany were constructed using different spatial resolution reduction methods. Results: Significant variation in generation, transmission and storage capacity of electricity were observed between the optimisation results of the energy system models. The results of the model that used administrative state boundaries to define regions were found to be sensitive to the omission of solar rooftop photovoltaic availability. Conclusions: This paper uses the proposed data processing approach to demonstrate the importance of spatial context when building and analysing power and heat optimisation models.

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