scholarly journals Evaluation of Three-Hourly TMPA Rainfall Products Using Telemetric Rain Gauge Observations at Lai Nullah Basin in Islamabad, Pakistan

2018 ◽  
Vol 10 (12) ◽  
pp. 2040 ◽  
Author(s):  
Asid Rehman ◽  
Farrukh Chishtie ◽  
Waqas Qazi ◽  
Sajid Ghuffar ◽  
Imran Fatima
Keyword(s):  
Time Scale ◽  
Rain Gauge ◽  
Mean Bias Error ◽  
Bias Error ◽  
Rainfall Analysis ◽  
Light Rain ◽  
Post Monsoon ◽  
Statistical Measures ◽  
Rain Rates ◽  
Daily Time

Flash floods which occur due to heavy rainfall in hilly and semi-hilly areas may prove deleterious when they hit urban centers. The prediction of such localized and heterogeneous phenomena is a challenge due to a scarcity of in-situ rainfall. A possible solution is the utilization of satellite-based precipitation products. The current study evaluates the efficacy of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) three-hourly products, i.e., 3B42 near-real-time (3B42RT) and 3B42 research version (3B42V7) at a sub-daily time scale. Various categorical indices have been used to assess the capability of products in the detection of rain/no-rain. Hourly rain rates are assessed by employing the most commonly used statistical measures, such as correlation coefficients (CC), mean bias error (MBE), mean absolute error (MAE), and root-mean-square error (RMSE). Further, a diurnal analysis is performed to authenticate TMPA’s performance in specific hours of the day. In general, the results show the good capability of both TMPA products in the detection of rain/no-rain events in all seasons except winter. Specifically, 3B42V7 performed better than 3B42RT. Moreover, both products detect a high number of rainy days falsely in light rain ranges. Regarding rainfall measurements, TMPA products exhibit an overall underestimation. Seasonally, 3B42V7 underestimates rainfall in monsoon and post-monsoon, and overestimates in winter and pre-monsoon. 3B42RT, on the other hand, underestimates rainfall in all seasons. A greater MBE and RMSE are found with both TMPA rain measurements in monsoon and post-monsoon seasons. Overall, a weak correlation and high MBE between the TMPA (3B42RT, 3B42V7) and reference gauge hourly rain rates are found at a three-hourly time scale (CC = 0.41, 0.38, MBE = −0.92, −0.70). The correlation is significant at decadal (CC = 0.79, 0.77) and monthly (CC = 0.91, 0,90) timescales. Furthermore, diurnal rainfall analysis indicates low credibility of 3B42RT to detect flash flooding. Within the parameters of this study, we conclude that the TMPA products are not the best choice at a three-hourly time scale in hilly/semi-hilly areas of Pakistan. However, both products can be used at daily, yet more reliably above daily, time scales, with 3B42V7 preferable due to its consistency.

scholarly journals An assessment of IMERG rainfall products over Bali at multiple time scale

2020 ◽  
Vol 153 ◽  
pp. 02001
Author(s):  
I Wayan Andi Yuda ◽  
Rakhmat Prasetia ◽  
Abd. Rahman As-syakur ◽  
Takahiro Osawa ◽  
Masahiko Nagai
Keyword(s):  
Time Scale ◽  
Rain Gauge ◽  
Probability Of Detection ◽  
Mean Bias Error ◽  
Bias Error ◽  
Correction Coefficient ◽  
Multiple Time ◽  
Observation Data ◽  
Wet Season ◽  
Rainfall Variation

Evaluation of first five years of the Global Precipitation Measurement - Integrated Multi-satellitE Retrievals for GPM (IMERG) final preciptitation product was performed over Bali – Indonesia using surface observation data which derived from The Agency for Meteorology, Climatology, and Geophysics of the Republic of Indonesia (BMKG) as a reference. This study evaluated IMERG’s performance in describing the temporal characteristics of rainfall variation over various time periods (including daily, monthly, and seasonal). The analysis concentrated on the period of April 2014 to April 2019. The results of statistical measurements consisted Probability of Detection (POD), linear correction coefficient (r), Mean Bias Error (MBE), and Root Mean Square Error (RMSE). In general, the results showed that IMERG rainfall estimation value was lower than rain gauges data. The statistical assesment indicated IMERG data was highly accurate on monthly to seasonal timescales. However, a moderate correlation was shown between the daily data comparison from IMERG to ground references. IMERG Performed better in wet season period (November -April) than in dry season period (May – Oktober). The probability of detection rain events on daily time scale was good. Overall, data from IMERG has the potential to be useful as a complement to rain gauge data in areas where rainfall observations are not available in the field.

scholarly journals A comparison of rainfall measurements from multiple instruments

2013 ◽  
Vol 6 (7) ◽  
pp. 1585-1595 ◽  
Author(s):  
X. C. Liu ◽  
T. C. Gao ◽  
L. Liu
Keyword(s):  
Rain Rate ◽  
Rain Gauge ◽  
Measurement Range ◽  
Light Rain ◽  
Large Size ◽  
Drop Size Distributions ◽  
Rain Rates ◽  
Effect Of Light ◽  
Good Agreement

Abstract. Simultaneous observations of rainfall collected by a tipping bucket rain gauge (TBRG), a weighing rain gauge (WRG), an optical rain gauge (ORG), a present weather detector (PWD), a Joss–Waldvogel disdrometer (JWD), and a 2-D video disdrometer (2DVD) during January to October 2012 were analyzed to evaluate how accurately they measure rainfall and drop size distributions (DSDs). For the long-term observations, there were different discrepancies in rain amounts from six instruments on the order of 0% to 27.7%. The TBRG, WRG, and ORG have a good agreement, while the PWD and 2DVD record higher and the JWD lower rain rates when R > 20 mm h−1, the ORG agrees well with JWD and 2DVD, while the TBRG records higher and the WRG lower rain rates when R > 20 mm h−1. Compared with the TBRG and WRG, optical and impact instruments can measure the rain rate accurately in the light rain. The overall DSDs of JWD and 2DVD agree well with each other, except for the small raindrops (D < 1 mm). JWD can measure more moderate-size raindrops (0.3 mm < D < 1.5 mm) than 2DVD, but 2DVD can measure more small-size raindrops (D < 0.3 mm). 2DVD has a larger measurement range; more overall raindrops can be measured by 2DVD than by JWD in different rain rate regimes. But small raindrops might be underestimated by 2DVD when R > 15 mm h−1. The small raindrops tend to be omitted in the more large-size raindrops due to the shadow effect of light. Therefore, the measurement accuracy of small raindrops in the heavy rainfall from 2DVD should be handled carefully.

scholarly journals Evaluation of Two Global Rainfall Models for Water Resources Planning and Management in Nigeria

2020 ◽  
Vol 5 (2) ◽  
Author(s):  
Ajayi J Oloruntade ◽  
Philip G Oguntunde ◽  
Kehinde O Mogaji
Keyword(s):  
Numerical Models ◽  
Research Unit ◽  
Rain Gauge ◽  
Mean Bias Error ◽  
Bias Error ◽  
University Of Delaware ◽  
Spatial And Temporal Patterns ◽  
Time Series Plot ◽  
Alternative Sources ◽  
Resources Planning

Given the sparseness of weather stations in Nigeria, there is an increasing need for alternative sources of rainfall data such as satellite measurements, numerical models and reanalysis. Nevertheless, the complexity of such data requires proper evaluation and validation. Therefore, this study evaluated two globally available rainfall products from Climate Research Unit (CRU) and University of Delaware (UNIDEL) using rain gauge data obtained from Nigerian Meteorological Agency (NIMET), over a period of twenty years (1980-1999) covering 24 stations. Time series plot and statistical tools were used to evaluate the products on annual, seasonal and zonal basis. The results show that the two products demonstrated comparable ability and sufficiently captured the spatial and temporal patterns of rainfall over the country. However, the products overestimated and underestimated during the dry and rainy seasons, respectively. Although, correlation was comparatively high between 0.3 and 0.8, but negative in few instances, mean bias error (MBE) and root mean square error (RMSE) were generally high depicting high random error. The performance of the products was best in the Sahel, followed by the Savannah and Forest zones, with UNIDEL showing better performance in most cases. Consequently, we recommend further studies to validate the present results on the use of gridded data in the country.Keywords— evaluation, CRU, UNIDEL, rain gauge, rainfall products

scholarly journals Evaluation of the GEM-AQ model in the context of the AQMEII Phase 1 project

2015 ◽  
Vol 15 (2) ◽  
pp. 1471-1522
Author(s):  
J. Struzewska ◽  
M. Zdunek ◽  
J. W. Kaminski ◽  
L. Lobocki ◽  
M. Porebska ◽  
...  
Keyword(s):  
Pearson Correlation ◽  
Phase 1 ◽  
Surface Ozone ◽  
Data Uncertainty ◽  
Mean Bias Error ◽  
Bias Error ◽  
European Continent ◽  
Statistical Measures ◽  
The Mean ◽  
The Impact

Abstract. In the scope of the AQMEII Phase 1 project the GEM-AQ model was run over Europe for the year 2006. The modelling domain was defined using a global variable resolution grid with a rotated equator and uniform resolution of 0.2° × 0.2° over the European continent. Spatial distribution and temporal variability of the GEM-AQ model results were analysed for surface ozone and PM10 concentrations. Model results were compared with measurements available in the ENSEMBLE database. Statistical measures were used to evaluate performance of the GEM-AQ model. The mean bias error, the mean absolute gross error and the Pearson correlation coefficient were calculated for the maximum 8 h running average ozone concentrations and daily mean PM10 concentrations. The GEM-AQ model performance was characterised for station types, European climatic regions, and seasons. The best performance for ozone was obtained at suburban stations and the worst performance was obtained for rural stations where the model tends to underestimate. The best results for PM10 were calculated for urban stations, while over most of Europe concentrations at rural sites were too high. Discrepancies between modelled and observed concentrations were discussed in the context of emission data uncertainty as well as the impact of large scale dynamics and circulation of air masses. Presented analyses suggest that interpretation of modelling results is enhanced when regional climate characteristics are ta ken into consideration.

scholarly journals Polarimetric Estimates of a 1-Month Accumulation of Light Rain with a 3-cm Wavelength Radar

2011 ◽  
Vol 12 (5) ◽  
pp. 1024-1039 ◽  
Author(s):  
L. Borowska ◽  
D. Zrnić ◽  
A. Ryzhkov ◽  
P. Zhang ◽  
C. Simmer
Keyword(s):  
Rain Rate ◽  
Rain Gauge ◽  
Light Rain ◽  
Differential Phase ◽  
Rain Gauges ◽  
Bright Band ◽  
X Band ◽  
Wet Snow ◽  
Composite Estimator ◽  
Rain Rates

Abstract The authors evaluate rainfall estimates from the new polarimetric X-band radar at Bonn, Germany, for a period between mid-November and the end of December 2009 by comparison with rain gauges. The emphasis is on slightly more than 1-month accumulations over areas minimally affected by beam blockage. The rain regime was characterized by reflectivities mainly below 45 dBZ, maximum observed rain rates of 47 mm h−1, a mean rain rate of 0.1 mm h−1, and brightband altitudes between 0.6 and 2.4 km above the ground. Both the reflectivity factor and the specific differential phase are used to obtain the rain rates. The accuracy of rain total estimates is evaluated from the statistics of the differences between radar and rain gauge measurements. Polarimetry provides improvement in the statistics of reflectivity-based measurements by reducing the bias and RMS errors from −25% to 7% and from 33% to 17%, respectively. Essential to this improvement is separation of the data into those attributed to pure rain, those from the bright band, and those due to nonmeteorological scatterers. A type-specific (rain or wet snow) relation is applied to obtain the rain rate by matching on the average the contribution by wet snow to the radar-measured rainfall below the bright band. The measurement of rain using specific differential phase is the most robust and can be applied to the very low rain rates and still produce credible accumulation estimates characterized with a standard deviation of 11% but a bias of −25%. A composite estimator is also tested and discussed.

scholarly journals Performance of the CMORPH and GPM IMERG Products over the United Arab Emirates

2020 ◽  
Vol 12 (9) ◽  
pp. 1426 ◽  
Author(s):  
Tareefa S. Alsumaiti ◽  
Khalid Hussein ◽  
Dawit T. Ghebreyesus ◽  
Hatim O. Sharif
Keyword(s):  
United Arab Emirates ◽  
Spatial Scales ◽  
Rain Gauge ◽  
Light Rain ◽  
Rain Gauges ◽  
Statistical Measures ◽  
Quantitative Accuracy ◽  
Highly Correlated ◽  
Global Precipitation Mission ◽  
Global Precipitation

Satellite-based precipitation products are becoming available at very high temporal and spatial resolutions, which has accelerated their use in various hydro-meteorological and hydro-climatological applications. Because the quantitative accuracy of such products is affected by numerous factors related to atmospheric and terrain properties, validating them over different regions and environments is needed. This study investigated the performance of two high-resolution global satellite-based precipitation products: the climate prediction center MORPHing technique (CMORPH) and the latest version of the Integrated Multi-SatellitE Retrievals for the Global Precipitation Mission (GPM) algorithm (IMERG), V06, over the United Arab Emirates from 2010 through 2018. The estimates of the products and that of 71 in situ rain gauges distributed across the country were compared by employing several common quantitative, categorical, and graphical statistical measures at daily, event-duration, and annual temporal scales, and at the station and study area spatial scales. Both products perform quite well in rainfall detection (above 70%), but report rainfall not observed by the rain gauges at an alarming rate (more than 30%), especially for light rain (lower quartile). However, for moderate and intense (upper quartiles) rainfall rates, performance is much better. Because both products are highly correlated with rain gauge observations (mostly above 0.7), the satellite rainfall estimates can probably be significantly improved by removing the bias. Overall, the CMORPH and IMERG estimates demonstrate great potential for filling spatial gaps in rainfall observations, in addition to improving the temporal resolution. However, further improvement is required, regarding the overestimation and underestimation of small and large rainfall amounts, respectively.

scholarly journals Evaluation of the GEM-AQ model in the context of the AQMEII Phase 1 project

2015 ◽  
Vol 15 (8) ◽  
pp. 3971-3990 ◽  
Author(s):  
J. Struzewska ◽  
M. Zdunek ◽  
J. W. Kaminski ◽  
L. Łobocki ◽  
M. Porebska ◽  
...  
Keyword(s):  
Pearson Correlation ◽  
Phase 1 ◽  
Surface Ozone ◽  
Data Uncertainty ◽  
Mean Bias Error ◽  
Bias Error ◽  
European Continent ◽  
Statistical Measures ◽  
The Mean ◽  
The Impact

Abstract. In the scope of the AQMEII Phase 1 project the GEM-AQ model was run over Europe for the year 2006. The modelling domain was defined using a global variable resolution grid with a rotated equator and uniform resolution of 0.2° × 0.2° over the European continent. Spatial distribution and temporal variability of the GEM-AQ model results were analysed for surface ozone and PM10 concentrations. Model results were compared with measurements available in the ENSEMBLE database. Statistical measures were used to evaluate performance of the GEM-AQ model. The mean bias error, the mean absolute gross error and the Pearson correlation coefficient were calculated for the maximum 8 h running average ozone concentrations and daily mean PM10 concentrations. The GEM-AQ model performance was characterized for station types, European climatic regions and seasons. The best performance for ozone was obtained at suburban stations, and the worst performance was obtained for rural stations where the model tends to underestimate. The best results for PM10 were calculated for urban stations, while over most of Europe concentrations at rural sites were too high. Discrepancies between modelled and observed concentrations were discussed in the context of emission data uncertainty as well as the impact of large-scale dynamics and circulation of air masses. Presented analyses suggest that interpretation of modelling results is enhanced when regional climate characteristics are taken into consideration.

scholarly journals Comparsion of TRMM Precipitation Satellite Data over Central Java Region – Indonesia

2018 ◽  
Vol 37 (3) ◽  
pp. 97-114 ◽  
Author(s):  
Andung Bayu Sekaranom ◽  
Emilya Nurjani ◽  
M. Pramono Hadi ◽  
Muh Aris Marfai
Keyword(s):  
Rainy Season ◽  
Tropical Rainfall Measuring Mission ◽  
Satellite Observation ◽  
High Elevation ◽  
Rain Gauge ◽  
Mean Bias Error ◽  
Bias Error ◽  
Precipitation Data ◽  
Central Java ◽  
Trmm Precipitation

Abstract This research aims to compare precipitation data derived from satellite observation and ground measurements through a dense station network over Central Java, Indonesia. A precipitation estimate from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 Version 7 are compared with precipitation data from interpolated rain gauge stations. Correlation analysis, mean bias error (MBE), and root mean square error (RMSE) were utilized in the analysis for each thee-monthly seasonal statistics. The result shows that the 3B42 products often estimate lower rainfall than observed from weather stations in the peak of the rainy season (DJF). Further, it is revealed that the 3B42 product are less robust in estimating rainfall at high elevation, especially when humid environment, which is typical during the rainy season peak, are involved.

scholarly journals Correction of Eddy Covariance Based Crop ET Considering the Heat Flux Source Area

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 281
Author(s):  
Stuart L. Joy ◽  
José L. Chávez
Keyword(s):  
Heat Flux ◽  
Eddy Covariance ◽  
Agricultural Land ◽  
Flux Measurement ◽  
Source Area ◽  
Mean Bias Error ◽  
Bias Error ◽  
Crop Water ◽  
The Past ◽  
Measurement Results

Eddy covariance (EC) systems are being used to measure sensible heat (H) and latent heat (LE) fluxes in order to determine crop water use or evapotranspiration (ET). The reliability of EC measurements depends on meeting certain meteorological assumptions; the most important of such are horizontal homogeneity, stationarity, and non-advective conditions. Over heterogeneous surfaces, the spatial context of the measurement must be known in order to properly interpret the magnitude of the heat flux measurement results. Over the past decades, there has been a proliferation of ‘heat flux source area’ (i.e., footprint) modeling studies, but only a few have explored the accuracy of the models over heterogeneous agricultural land. A composite ET estimate was created by using the estimated footprint weights for an EC system in the upwind corner of four fields and separate ET estimates from each of these fields. Three analytical footprint models were evaluated by comparing the composite ET to the measured ET. All three models performed consistently well, with an average mean bias error (MBE) of about −0.03 mm h−1 (−4.4%) and root mean square error (RMSE) of 0.09 mm h−1 (10.9%). The same three footprint models were then used to adjust the EC-measured ET to account for the fraction of the footprint that extended beyond the field of interest. The effectiveness of the footprint adjustment was determined by comparing the adjusted ET estimates with the lysimetric ET measurements from within the same field. This correction decreased the absolute hourly ET MBE by 8%, and the RMSE by 1%.

scholarly journals CO2 Flux over the Contiguous United States in 2016 Inverted by WRF-Chem/DART from OCO-2 XCO2 Retrievals

2021 ◽  
Vol 13 (15) ◽  
pp. 2996
Author(s):  
Qinwei Zhang ◽  
Mingqi Li ◽  
Maohua Wang ◽  
Arthur Paul Mizzi ◽  
Yongjian Huang ◽  
...  
Keyword(s):  
United States ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Co2 Flux ◽  
Total Carbon ◽  
Mean Bias Error ◽  
Bias Error ◽  
Parallel Experiment ◽  
Concentration Measurements ◽  
Global Stocktake

High spatial resolution carbon dioxide (CO2) flux inversion systems are needed to support the global stocktake required by the Paris Agreement and to complement the bottom-up emission inventories. Based on the work of Zhang, a regional CO2 flux inversion system capable of assimilating the column-averaged dry air mole fractions of CO2 (XCO2) retrieved from Orbiting Carbon Observatory-2 (OCO-2) observations had been developed. To evaluate the system, under the constraints of the initial state and boundary conditions extracted from the CarbonTracker 2017 product (CT2017), the annual CO2 flux over the contiguous United States in 2016 was inverted (1.08 Pg C yr−1) and compared with the corresponding posterior CO2 fluxes extracted from OCO-2 model intercomparison project (OCO-2 MIP) (mean: 0.76 Pg C yr−1, standard deviation: 0.29 Pg C yr−1, 9 models in total) and CT2017 (1.19 Pg C yr−1). The uncertainty of the inverted CO2 flux was reduced by 14.71% compared to the prior flux. The annual mean XCO2 estimated by the inversion system was 403.67 ppm, which was 0.11 ppm smaller than the result (403.78 ppm) simulated by a parallel experiment without assimilating the OCO-2 retrievals and closer to the result of CT2017 (403.29 ppm). Independent CO2 flux and concentration measurements from towers, aircraft, and Total Carbon Column Observing Network (TCCON) were used to evaluate the results. Mean bias error (MBE) between the inverted CO2 flux and flux measurements was 0.73 g C m−2 d−1, was reduced by 22.34% and 28.43% compared to those of the prior flux and CT2017, respectively. MBEs between the CO2 concentrations estimated by the inversion system and concentration measurements from TCCON, towers, and aircraft were reduced by 52.78%, 96.45%, and 75%, respectively, compared to those of the parallel experiment. The experiment proved that CO2 emission hotspots indicated by the inverted annual CO2 flux with a relatively high spatial resolution of 50 km consisted well with the locations of most major metropolitan/urban areas in the contiguous United States, which demonstrated the potential of combing satellite observations with high spatial resolution CO2 flux inversion system in supporting the global stocktake.

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