Comparison of TRMM and water district rain rates over New Mexico

Chiu, Long S.; Liu, Zhong; Vongsaard, J.; Morain, S. A.; Budge, Amelia; Neville, Paul; Bales, Chandra

doi:10.1007/s00376-006-0001-x

Cited by 48 publications

(24 citation statements)

References 18 publications

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“…To ensure high quality and continuity of observed rainfall data, a series of quality control and maintenance procedures were implemented, such as the preliminary visual inspection and a programming detection (see [8] for a detailed description). To further reduce the scale errors produced by direct comparison between the grid-scale satellite estimates and the point-scale gauge data, in this study we only selected gridboxes that contained at least three gauges and then used the mean value of all gauges inside each gridbox as the ground truth, as practiced by many previous studies [8][9][10][11][12]. Thus, thirty-two 0.25° × 0.25° gridboxes corresponding to the TRMM combined product pixel resolution were selected over the entire basin (see Figure 1).…”

Section: Study Area and Data Sourcesmentioning

confidence: 99%

Impact of Missing Passive Microwave Sensors on Multi-Satellite Precipitation Retrieval Algorithm

Yong

Hong

et al. 2015

Remote Sensing

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The impact of one or two missing passive microwave (PMW) input sensors on the end product of multi-satellite precipitation products is an interesting but obscure issue for both algorithm developers and data users. On 28 January 2013, the Version-7 TRMM Multi-satellite Precipitation Analysis (TMPA) products were reproduced and re-released by National Aeronautics and Space Administration (NASA) Goddard Space Flight Center because the Advanced Microwave Sounding Unit-B (AMSU-B) and the Special Sensor Microwave Imager-Sounder-F16 (SSMIS-F16) input data were unintentionally disregarded in the prior retrieval. Thus, this study investigates the sensitivity of TMPA algorithm results to missing PMW sensors by intercomparing the "early" and "late" Version-7 TMPA real-time (TMPA-RT) precipitation estimates (i.e., without and with AMSU-B, SSMIS-F16 sensors) with an independent high-density gauge network of 200 tipping-bucket rain gauges over the Chinese Jinghe river basin (45,421 km 2 ). The retrieval counts and retrieval frequency of various PMW and Infrared (IR) sensors incorporated into the TMPA system were also OPEN ACCESS

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Section: Study Area and Data Sourcesmentioning

confidence: 99%

Impact of Missing Passive Microwave Sensors on Multi-Satellite Precipitation Retrieval Algorithm

Yong

Hong

et al. 2015

Remote Sensing

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“…For quantitative comparison, only the grids that cover two and more rain gauges have been used to compute the statistics metrics. Such a grid-based comparison technique has been reported in many previous studies [1,[27][28][29][30]. A total of 5086 gauge abnormal measurements were removed during the quality control.…”

Section: Statistics Metricsmentioning

confidence: 99%

“…We assumed that rain gauge measurements represent the precipitation truth within the corresponding pixel of satellite data. This kind of assumption is a common way to evaluate remote sensing products and has been widely applied by the remote sensing community [1,[27][28][29][30][31]. Considering that the TRMM products to be evaluated have the same spatio-temporal resolution, to better address the differences for these TRMM products, the uncertainty analysis associated with the NUBF effect has not been included in the current study.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Version-7 TRMM Multi-Satellite Precipitation Analysis Product during the Beijing Extreme Heavy Rainfall Event of 21 July 2012

Huang

Chen

Cao

et al. 2013

Water

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Abstract:The latest Version-7 (V7) Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) products were released by the National OPEN ACCESSWater 2014, 6 33Aeronautics and Space Administration (NASA) in December of 2012. Their performance on different climatology, locations, and precipitation types is of great interest to the satellite-based precipitation community. This paper presents a study of TMPA precipitation products (3B42RT and 3B42V7) for an extreme precipitation event in Beijing and its adjacent regions (from 00:00 UTC 21 July 2012 to 00:00 UTC 22 July 2012). Measurements from a dense rain gauge network were used as the ground truth to evaluate the latest TMPA products. Results are summarized as follows. Compared to rain gauge measurements, both 3B42RT and 3B42V7 generally captured the rainfall spatial and temporal pattern, having a moderate spatial correlation coefficient (CC, 0.6) and high CC values (0.88) over the broader Hebei, Beijing and Tianjin (HBT) regions, but the rainfall peak is 6 h ahead of gauge observations. Overall, 3B42RT showed higher estimation than 3B42V7 over both HBT and Beijing. At the storm center, both 3B42RT and 3B42V7 presented a relatively large deviation from the temporal variation of rainfall and underestimated the storm by 29.02% and 36.07%, respectively. The current study suggests that the latest TMPA products still have limitations in terms of resolution and accuracy, especially for this type of extreme event within a latitude area on the edge of coverage of TRMM precipitation radar and microwave imager. Therefore, TMPA users should be cautious when 3B42RT and 3B42V7 are used to model, monitor, and forecast both flooding hazards in the Beijing urban area and landslides in the mountainous west and north of Beijing.

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“…Comparisons by Chiu et al (2006) of TRMM retrievals (TRMM Precipitation Radar (PR), 2A25, TRMM Microwave Imager (TMI) 2A12, TRMM Combined Instrument (TCI) 2B31, TRMM 3B42, V5 & V6, TRMM, 3B43, V5 & V6) with Water District (WD) Rain-Gauge rates over New Mexico showed high biases for satellite-only algorithms. Merged satellite-gauge products (3B43 or 3B42) were found to be better correlated with WD gauge data.…”

Section: Review Of the Other Validation Studiesmentioning

confidence: 99%

Evaluation of Multi-Satellite TRMM Derived Rainfall Estimates over a Western State of India

Nair¹,

Srinivasan

Nemani

2009

Journal of the Meteorological Society of Japan

122

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The Tropical Rainfall Measuring Mission (TRMM) blended rainfall product (3B42-V6 data set) has been used for inter-comparison with observations from a high density rain-gauge network over the western state of Maharashtra, India. The state of Maharashtra was chosen for the inter-comparison exercise primarily because of its diverse rainfall regime. The rain distribution over Maharashtra, characterized by a pronounced longitudinal gradient is closely linked to the north-south oriented orography of the region known as the Western Ghats. The validation exercise was carried out for 7 monsoon seasons from June to September from 1998 to 2004 at various space and time scales. The results are consistent at daily, monthly and seasonal timescales. The comparisons among stations and over geographically similar climatic zones demonstrated that the performance of 3B42-V6 product varies over the di¤erent climatic regimes. In terms of spatial reproductivity, the existence of the westeast rainfall gradient along the west coast is captured by the satellite product, but the orographic e¤ect (rainfall maxima is over the Western Ghats as captured by the rain-gauge) is not reflected by 3B42-V6 product. The 3B42-V6 product shows rainfall maxima at the coast. The satellite estimates of rainfall amounts over the state were found to be most accurate over regions of moderate rainfall and mainly inaccurate in regions of sharp rainfall gradient. In terms of magnitude of the rainfall amounts, over the windward side of the Western Ghats the 3B42-V6 product was unable to resolve the heavy orographic rainfall amounts and over the leeward side the rainfall amounts in the immediate rain-shadow region were overestimated. One of the key results obtained from the daily rainfall intercomparison exercise is the ability of the 3B42-V6 estimates to detect the wet and dry phases of monsoon over most parts of the state (except the leeward side). Though the rainfall amounts estimated by the satellite product were sometimes under/over estimated, the timing of the rain events as estimated by the satellite product was generally coincident with the gauge observations over most of the regions except in the immediate rainshadow region of the state. The TRMM 3B42-V6 estimates therefore could have tremendous potential to be used for intraseasonal studies over most regions of the state.

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Comparison of TRMM and water district rain rates over New Mexico

Cited by 48 publications

References 18 publications

Impact of Missing Passive Microwave Sensors on Multi-Satellite Precipitation Retrieval Algorithm

Impact of Missing Passive Microwave Sensors on Multi-Satellite Precipitation Retrieval Algorithm

Evaluation of Version-7 TRMM Multi-Satellite Precipitation Analysis Product during the Beijing Extreme Heavy Rainfall Event of 21 July 2012

Evaluation of Multi-Satellite TRMM Derived Rainfall Estimates over a Western State of India

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