scholarly journals Evaluation and Hydrological Utility of the Latest GPM IMERG V5 and GSMaP V7 Precipitation Products over the Tibetan Plateau

2018 ◽  
Vol 10 (12) ◽  
pp. 2022 ◽  
Author(s):  
Dekai Lu ◽  
Bin Yong
Keyword(s):  
Tibetan Plateau ◽  
The Tibetan Plateau ◽  
Mountain Areas ◽  
Hydrological Simulation ◽  
Satellite Precipitation ◽  
Precipitation Measurement ◽  
Winter Snow ◽  
Comparable Performance ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Satellite precipitation products provide alternative precipitation data in mountain areas. This study aimed to assess the performance of the latest Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) version 5 (IMERG V5) and Global Satellite Mapping of Precipitation version 7 (GSMaP V7) products and their hydrological utilities over the Tibetan Plateau (TP). Here, two IMERG Final Run products (uncalibrated IMERG (IMERG-UC) and gauge-calibrated IMERG (IMEEG-C)) and two GSMaP products (GSMaP Moving Vector with Kalman Filter (GSMaP-MVK) and gauge-adjusted GSMaP (GSMaP-Gauge)) were evaluated from April 2014 to March 2017. Results show that all four satellite precipitation products could generally capture the spatial patterns of precipitation over the TP. The two gauge-adjusted products were more consistent with the ground measurements than the satellite-only products in terms of statistical assessment. For hydrological simulation, IMERG-UC and GSMaP-MVK showed unsatisfactory performance for hydrological utility, while GSMaP-Gauge demonstrated comparable performance with gauge reference data, suggesting that GSMaP-Gauge can be selected for hydrological application in the TP. Our study also indicates that accurately measuring light rainfall and winter snow is still a challenging task for the current satellite precipitation retrievals.

scholarly journals Comprehensive Characteristics of Summer Deep Convection over Tibetan Plateau and Its South Slope from the Global Precipitation Measurement Core Observatory

Atmosphere ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 9 ◽  
Author(s):  
Guolu Gao ◽  
Quanliang Chen ◽  
Hongke Cai ◽  
Yang Li ◽  
Zhenglin Wang
Keyword(s):  
Tibetan Plateau ◽  
Diurnal Variation ◽  
Vertical Structure ◽  
Deep Convection ◽  
Low Frequency ◽  
The Tibetan Plateau ◽  
Precipitation Measurement ◽  
South Slope ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Observational data from the Global Precipitation Measurement (GPM) Core Observatory during four summers (2014–2017) has been used to investigate deep convection systems (DCSs) over the Tibetan Plateau (TP) and its south slope (SS). The frequency, geographical distribution diurnal variation, and vertical structure of DCSs over the TP and SS are compared among these two regions. The frequency of DCSs over the SS (0.98%) was far higher than over the TP (0.15%), suggesting that stronger DCSs occur to the east and south of the TP. The maximum number of DCS occurred in July and August. A clear diurnal variation in DCS was found over the whole region, DCSs over the TP and SS both have a greatest amplitude in the afternoon. The probability of DCSs from 1200 to 1800 local time (LT) was 76.3% and 44.1% over TP and SS respectively, whereas the probability of DCSs being generated from 2200 (LT) to 0600 on the next day LT was 0.03% and 33.1% over the TP and SS respectively. There was a very low frequency of DCSs over the TP during the night. Five special echo top heights were used to investigate the vertical structure of DCSs. DCSs over the TP were both weaker and smaller than those over the SS.

scholarly journals Precipitation Retrieval over the Tibetan Plateau from the Geostationary Orbit—Part 2: Precipitation Rates with Elektro-L2 and Insat-3D

2020 ◽  
Vol 12 (13) ◽  
pp. 2114
Author(s):  
Christine Kolbe ◽  
Boris Thies ◽  
Nazli Turini ◽  
Zhiyu Liu ◽  
Jörg Bendix
Keyword(s):  
Tibetan Plateau ◽  
Rain Gauge ◽  
The Tibetan Plateau ◽  
Precipitation Measurement ◽  
Precipitation Estimates ◽  
Geo Satellites ◽  
Spatio Temporal ◽  
Model Training ◽  
Global Precipitation Measurement ◽  
Global Precipitation

We present the new Precipitation REtrieval covering the TIbetan Plateau (PRETIP) as a feasibility study using the two geostationary (GEO) satellites Elektro-L2 and Insat-3D with reference to the GPM (Global Precipitation Measurement Mission) IMERG (Integrated Multi-satellitE Retrievals for GPM) product. The present study deals with the assignment of the rainfall rate. For precipitation rate assignment, the best-quality precipitation estimates from the gauge calibrated microwave (MW) within the IMERG product were combined with the GEO data by Random Forest (RF) regression. PRETIP was validated with independent MW precipitation information not considered for model training and revealed a good performance on 30 min and 11 km spatio-temporal resolution with a correlation coefficient of R = 0.59 and outperforms the validation of the independent MW precipitation with IMERG’s IR only product (R = 0.18). A comparison of PRETIP precipitation rates in 4 km resolution with daily rain gauge measurements from the Chinese Ministry of Water Resources revealed a correlation of R = 0.49. No differences in the performance of PRETIP for various elevation ranges or between the rainy (July, August) and the dry (May, September) season could be found.

Precipitation Retrieval over the Tibetan Plateau from the Geostationary Orbit

2020 ◽  
Author(s):  
Christine Kolbe ◽  
Boris Thies ◽  
Nazli Turini ◽  
Jörg Bendix
Keyword(s):  
Tibetan Plateau ◽  
The Tibetan Plateau ◽  
Cloud Properties ◽  
Spectral Bands ◽  
Precipitation Measurement ◽  
High Asia ◽  
Precipitation Estimates ◽  
Optimization Schemes ◽  
Global Precipitation Measurement ◽  
Global Precipitation

<p>The distribution of precipitation on the Tibetan Plateau (TiP) is not yet understood due to various factors. Satellite-based precipitation retrieval can provide comprehensive information in a high spatial-temporal resolution. The aim of this feasibility study is to retrieve precipitation rates over High Asia using multi-spectral data from the two geostationary (GEO) satellites Elektro-L2 and Insat-3D in a 30 minutes and 4 km resolution. The variety of spectral bands from both satellites provides an insight into the cloud properties which are associated with precipitation. In the first step, the precipitation area is delineated, and in a second step, the rates are retrieved. To this end, we use a machine learning approach (Random Forest, RF) and a precipitation product of the Global Precipitation Measurement Mission (GPM IMERG) as a reference. From this product, we use the best quality gauge calibrated microwave (MW) precipitation estimates. We validate our results with independent gauge calibrated MW precipitation. To improve the RF models, we tested various optimization schemes. The results of this study will provide information about the precipitation processes in High Asia.</p>

scholarly journals Systematical Evaluation of GPM IMERG and TRMM 3B42V7 Precipitation Products in the Huang-Huai-Hai Plain, China

2019 ◽  
Vol 11 (6) ◽  
pp. 697 ◽  
Author(s):  
Fenglin Xu ◽  
Bin Guo ◽  
Bei Ye ◽  
Qia Ye ◽  
Huining Chen ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Accurate Estimation ◽  
Detection Capability ◽  
Satellite Precipitation ◽  
Precipitation Measurement ◽  
Daily Precipitation Data ◽  
Precipitation Estimates ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Precipitation Events

Accurate estimation of high-resolution satellite precipitation products like Global Precipitation Measurement (GPM) and Tropical Rainfall Measuring Mission (TRMM) is critical for hydrological and meteorological research, providing a benchmark for the continued development and future improvement of these products. This study aims to comprehensively evaluate the Integrated Multi-Satellite Retrievals for GPM (IMERG) and TRMM 3B42V7 products at multiple temporal scales from 1 January 2015 to 31 December 2017 over the Huang-Huai-Hai Plain in China, using daily precipitation data from 59 meteorological stations. Three commonly used statistical metrics (CC, RB, and RMSE) are adopted to quantitatively verify the accuracy of two satellite precipitation products. The assessment also takes into account the precipitation detection capability (POD, FAR, CSI, and ACC) and frequency of different precipitation intensities. The results show that the IMERG and 3B42V7 present strong correlation with meteorological stations observations at annual and monthly scales (CC > 0.90), whereas moderate at the daily scale (CC = 0.76 and 0.69 for IMERG and 3B42V7, respectively). The spatial variability of the annual and seasonal precipitation is well captured by these two satellite products. And spatial patterns of precipitation gradually decrease from south to north over the Huang-Huai-Hai Plain. Both IMERG and 3B42V7 products overestimate precipitation compared with the station observations, of which 3B42V7 has a lower degree of overestimation. Relative to the IMERG, annual precipitation estimates from 3B42V7 show lower RMSE (118.96 mm and 142.67 mm, respectively), but opposite at the daily, monthly, and seasonal scales. IMERG has a better precipitation detection capability than 3B42V7 (POD = 0.83 and 0.67, respectively), especially when detecting trace and solid precipitation. The two precipitation products tend to overestimate moderate (2–10 mm/d) and heavy (10–50 mm/d) precipitation events, but underestimate violent (>50 mm/d) precipitation events. The IMERG is not found capable to detecting precipitation events of different frequencies more precisely. In general, the accuracy of IMERG is better than 3B42V7 product in the Huang-Huai-Hai Plain. The IMERG satellite precipitation product with higher temporal and spatial resolutions can be regarded a reliable data sources in studying hydrological and climatic research.

scholarly journals Validation of rainfall data estimated by GPM satellite on Southern Amazon region

2019 ◽  
Vol 14 (1) ◽  
pp. 1
Author(s):  
Luiz Octavio Fabricio dos Santos ◽  
Carlos Alexandre Santos Querino ◽  
Juliane Kayse Albuquerque da Silva Querino ◽  
Altemar Lopes Pedreira Junior ◽  
Aryanne Resende de Melo Moura ◽  
...  
Keyword(s):  
Pearson Correlation ◽  
Absolute Error ◽  
High Rate ◽  
Satellite Precipitation ◽  
Precipitation Measurement ◽  
Surface Data ◽  
Precipitation Estimates ◽  
Amazonas State ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Rainfall is a meteorological variable of great importance for hydric balance and for weather studies. Rainfall estimation, carried out by satellites, has increased the climatological dataset related to precipitation. However, the accuracy of these data is questionable. This paper aimed to validate the estimates done by the Global Precipitation Measurement (GPM) satellite for the mesoregion of Southern Amazonas State, Brazil. The surface data were collected by the National Water Agency – ANA and National Institute of Meteorology – INMET, and is available at both institutions’ websites. The satellite precipitation data were accessed directly from the NASA webpage. Statistical analysis of Pearson correlation was used, as well as the Willmott’s “d” index and errors from the MAE (Mean Absolute Error) and RMSE (Root Mean Square Error). The GPM satellite satisfactorily estimated the precipitation, once it had correlations above 73% and high Willmott coefficients (between 0.86 and 0.97). The MAE and RMSE showed values that varied from 36.50 mm to 72.49 mm and 13.81 mm to 71.76 mm, respectively. Seasonal rain variations are represented accordingly. In some cases, either an underestimation or an overestimation of the rain data was observed. In the yearly totals, a high rate of similarity between the estimated and measured values was observed. We concluded that the GPM-based multi-satellite precipitation estimates can be used, even though they are not 100% reliable. However, adjustments in calibration for the region are necessary and recommended.

scholarly journals Seasonal Effect on Spatial and Temporal Consistency of the New GPM-Based IMERG-v5 and GSMaP-v7 Satellite Precipitation Estimates in Brazil’s Central Plateau Region

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 668 ◽  
Author(s):  
Leandro Salles ◽  
Frédéric Satgé ◽  
Henrique Roig ◽  
Tati Almeida ◽  
Diogo Olivetti ◽  
...  
Keyword(s):  
Daily Basis ◽  
Seasonal Effect ◽  
Temporal Consistency ◽  
Time Step ◽  
Central Plateau ◽  
Satellite Precipitation ◽  
Precipitation Measurement ◽  
Precipitation Estimates ◽  
Global Precipitation Measurement ◽  
Global Precipitation

This study assesses the performance of the new Global Precipitation Measurement (GPM)-based satellite precipitation estimates (SPEs) datasets in the Brazilian Central Plateau and compares it with the previous Tropical Rainfall Measurement Mission (TRMM)-era datasets. To do so, the Integrated Multi-satellitE Retrievals for GPM (IMERG)-v5 and the Global Satellite Mapping of Precipitation (GSMaP)-v7 were evaluated at their original 0.1° spatial resolution and for a 0.25° grid for comparison with TRMM Multi-satellite Precipitation Analysis (TMPA). The assessment was made on an annual, monthly, and daily basis for both wet and dry seasons. Overall, IMERG presents the best annual and monthly results. In both time steps, IMERG’s precipitation estimations present bias with lower magnitudes and smaller root-mean-square error. However, GSMaP performs slightly better for the daily time step based on categorical and quantitative statistical analysis. Both IMERG and GSMaP estimates are seasonally influenced, with the highest difficulty in estimating precipitation occurring during the dry season. Additionally, the study indicates that GPM-based SPEs products are capable of continuing TRMM-based precipitation monitoring with similar or even better accuracy than obtained previously with the widely used TMPA product.

scholarly journals Quasi-Global Evaluation of IMERG and GSMaP Precipitation Products over Land Using Gauge Observations

Water ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 243 ◽  
Author(s):  
Wang ◽  
Yong
Keyword(s):  
Climate Models ◽  
Input Parameter ◽  
Poor Performance ◽  
Global Evaluation ◽  
Satellite Precipitation ◽  
Precipitation Product ◽  
Precipitation Measurement ◽  
Highly Correlated ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Understanding the error distribution of satellite precipitation products is conducive to obtaining accurate precipitation data, which is a very important input parameter in hydrological models and climate models. The error characteristics of Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) and Global Satellite Mapping of Precipitation (GSMaP) uncalibrated products on quasi-global land and six continents are evaluated, and the effects of latitude, elevation, and season on satellite precipitation product accuracy are analyzed. In order to be consistent with the Climate Prediction Center (CPC), the selected products are resampled at 0.5° and daily resolutions from 1 January 2015 to 31 August 2018. We find out that (1) GSMaP performs worse than IMERG mainly due to systematic errors and poor performance at high latitudes; (2) overestimation is obvious in high latitude areas of the northern hemisphere and also in areas with low rainfall intensity; (3) IMERG and GSMaP show good performance in summer and poor performance in winter; (4) where elevation is lower than 1500 m, the error metrics are highly correlated with the elevation; (5) the correlation coefficient is relatively high in areas with high rainfall, and the dispersion of satellite data and gauge data is also high. IMERG is a high-quality satellite precipitation product in the GPM era, but some uncertainties mentioned above are still worthy of attention by product developers and users.

scholarly journals Evaluation and Application of Satellite Precipitation Products in Studying the Summer Precipitation Variations over Taiwan

2020 ◽  
Vol 12 (3) ◽  
pp. 347 ◽  
Author(s):  
Wan-Ru Huang ◽  
Pin-Yi Liu ◽  
Ya-Hui Chang ◽  
Chian-Yi Liu
Keyword(s):  
Summer Precipitation ◽  
Tropical Rainfall Measuring Mission ◽  
Temporal Variations ◽  
Rain Gauge ◽  
Satellite Precipitation ◽  
Reference Base ◽  
Precipitation Measurement ◽  
June July ◽  
Global Precipitation Measurement ◽  
Global Precipitation

In March 2019, Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG)-Final v6 (hereafter IMERG6) was released, with data concerning precipitation dating back to June 2000. The National Aeronautics and Space Administration (NASA) has suggested that researchers use IMERG6 to replace the frequently used Tropical Rainfall Measuring Mission (TRMM)-3B42 v7 (hereafter TRMM7), which is expected to cease operation in December 2019. This study aims to evaluate the performance of IMERG6 and TRMM7 in depicting the variations of summer (June, July, and August) precipitation over Taiwan during the period 2000–2017. Data used for the comparison also includes IMERG-Final v5 (hereafter IMERG5) and Global Satellite Mapping of Precipitation for Global Precipitation Measurement (GSMaP)-Gauge v7 (hereafter GSMaP7) during the summers of 2014–2017. Capabilities to apply the four satellite precipitation products (SPPs) in studying summer connective afternoon rainfall (CAR) events, which are the most frequently observed weather patterns in Taiwan, are also examined. Our analyses show that when using more than 400 local rain-gauge observations as a reference base for comparison, IMERG6 outperforms TRMM7 quantitatively and qualitatively, more accurately depicting the variations of the summer precipitation over Taiwan at multiple timescales (including mean status, daily, interannual, and diurnal). IMERG6 also performs better than TRMM7 in capturing the characteristics of CAR activities in Taiwan. These findings highlight that using IMERG6 to replace TRMM7 adds value in studying the spatial-temporal variations of summer precipitation over Taiwan. Furthermore, the analyses also indicated that IMERG6 outperforms IMERG5 and GSMaP7 in the examination of most of the features of summer precipitation over Taiwan during 2014–2017.

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