scholarly journals The Performance of the Diurnal Cycle of Precipitation from Blended Satellite Techniques over Brazil

2021 ◽  
Vol 13 (4) ◽  
pp. 734
Author(s):  
Ricardo Almeida de Siqueira ◽  
Daniel Alejandro Vila ◽  
João Maria de Sousa Afonso
Keyword(s):  
Diurnal Cycle ◽  
Temporal Distribution ◽  
Absolute Error ◽  
Rain Gauge ◽  
Rainfall Events ◽  
Surface Precipitation ◽  
Critical Success ◽  
Precipitation Regimes ◽  
Diurnal Cycle Of Precipitation ◽  
Critical Success Index

The knowledge of the diurnal cycle of precipitation is of extreme relevance to understanding the physical/dynamic processes associated with the spatial and temporal distribution of precipitation. The main difficulty of this task is the lack of surface precipitation information over certain regions on an hourly time scale and the low spatial representativeness of these data (normally surface gauges). In order to overcome these difficulties, the main objective of this study is to create a 3-h precipitation accumulation database from the gauge-adjusted daily regional precipitation products to resolve the diurnal cycle properly. This study also proposes to evaluate different methodologies for partitioning gauge-adjusted daily precipitation products, i.e., a product made by the combination of satellite estimates and surface gauge observations, into 3-h precipitation accumulation. Two methodologies based on the calculation of a conversion factor F between a daily gauge-adjusted product, combined scheme (CoSch, hereafter), and a non-gauge-adjusted one, the integrated multi-satellite retrievals for GPM (IMERG)-Early (IMERG, hereafter) were tested for this research. Hourly rain gauge stations for the period of 2015–2018 over Brazil were used to assess the performance of the proposed methodologies over the whole region and five sub-regions with homogeneous precipitation regimes. Standard statistical metrics and categorical indices related with the capability to detect rainfall events were used to compare the ability of each product to represent the diurnal cycle. The results show that the new 3-h CoSch products show better agreement with rainfall gauge stations when compared with IMERG, better capturing the diurnal cycle of precipitation. The biggest improvement was over northeastern region close to the coast, where IMERG was not able to capture the diurnal cycle properly. One of the proposed methodologies (CoSchB) performed better on the critical success index and equitable threat score metrics, suggesting that this is the best product over the two. The downside, when compared with the other methodology (CoSchA), was a slight increase in the values of bias and mean absolute error, but still at acceptable levels.

scholarly journals Seasonal Variation of the Diurnal Cycle of Rainfall in Southern Contiguous China

2008 ◽  
Vol 21 (22) ◽  
pp. 6036-6043 ◽  
Author(s):  
Jian Li ◽  
Rucong Yu ◽  
Tianjun Zhou
Keyword(s):  
Seasonal Variation ◽  
Diurnal Cycle ◽  
Radiative Forcing ◽  
Early Morning ◽  
Rain Gauge ◽  
Rainfall Events ◽  
Late Afternoon ◽  
Long Duration ◽  
China Region ◽  
Afternoon Peak

Abstract Hourly station rain gauge data are employed to study the seasonal variation of the diurnal cycle of rainfall in southern contiguous China. The results show a robust seasonal variation of the rainfall diurnal cycle, which is dependent both on region and duration. Difference in the diurnal cycle of rainfall is found in the following two neighboring regions: southwestern China (region A) and southeastern contiguous China (region B). The diurnal cycle of annual mean precipitation in region A tends to reach the maximum in either midnight or early morning, while precipitation in region B has a late-afternoon peak. In contrast with the weak seasonal variation of the diurnal phases of precipitation in region A, the rainfall peak in region B shifts sharply from late afternoon in warm seasons to early morning in cold seasons. Rainfall events in south China are classified into short- (1–3 h) and long-duration (more than 6 h) events. Short-duration precipitation in both regions reaches the maximum in late afternoon in warm seasons and peaks in either midnight or early morning in cold seasons, but the late-afternoon peak in region B exists during February–October, while that in region A only exists during May–September. More distinct differences between regions A and B are found in the long-duration rainfall events. The long-duration events in region A show dominant midnight or early morning peaks in all seasons. But in region B, the late-afternoon peak exists during July–September. Possible reasons for the difference in the diurnal cycle of rainfall between the two regions are discussed. The different cloud radiative forcing over regions A and B might contribute to this difference.

scholarly journals Features of weather types involving heavy rainfall along the southern Spanish Mediterranean

2020 ◽  
Author(s):  
J.M. Senciales-González ◽  
J.D. Ruiz-Sinoga
Keyword(s):  
Heavy Rainfall ◽  
Temporal Distribution ◽  
Heavy Rain ◽  
Rain Gauge ◽  
Weather Types ◽  
Seasonal Incidence ◽  
Rainfall Events ◽  
Synoptic Conditions ◽  
The Mediterranean ◽  
Heavy Rainfall Events

Heavy rainfall events in the Mediterranean can be of high intensity, commonly exceeding 100 mm day-1, and have irregular spatio-temporal distribution. Such events can have significant impacts both on soils and human structures. The aim of this paper is to highlight a systematic comparison of synoptic conditions with heavy rainfall events in Mediterranean Southern Spain, assessing the weather types responsible for meteorological risk in specific locations of this mountainous region. To do this, we analyzed the maximum intensity of rainfall in observational periods ranging from 10 min to 24 h using a database from 132 rain gauge stations across the study area since 1943; then, the heavy rain has been associated with the weather type which triggers it. This analysis identified a pattern of heavy rainfall which differs from that previously reported in the Mediterranean area. Thus, in this research, the maximum number of heavy rainfall events uses to come from a dominant pattern of low pressures associated to front systems and East-Northeast winds; but the maximum volumes use to be associated to Cold Drops and the same winds; in addition, there are differences throughout the territory, showing several patterns and seasonal incidence when analyzing sub-zones, which may be related with different erosive conditions according to its position with respect to Atlantic or Mediterranean sea, and the entity of its relief.

scholarly journals Verification of APHRODITE Precipitation Data Set in Bangladesh

2021 ◽  
Vol 12 (1) ◽  
pp. 51-56
Author(s):  
Md Atiqul Islam ◽  
Asif Ahmed ◽  
Md Munirujjaman Munir ◽  
Zarif Zaman Khandakar
Keyword(s):  
Extreme Rainfall ◽  
Absolute Error ◽  
Rain Gauge ◽  
Probability Of Detection ◽  
False Alarms ◽  
Data Set ◽  
Study Region ◽  
Rainfall Events ◽  
Rain Gauges ◽  
Precipitation Threshold

We investigated the preformance of Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) of water resources precipitation products in Bangladesh taking rain gauge data as reference for a 3-year period (2003-2005). Various statistical and categorical indices such as coefficient of correlation (CC), bias, relative bias (RB), mean absolute error (MAE), root mean square error (RMSE), probability of detection (POD), and false alarm ratio (FAR), were applied to measure the performance of the product. With CC value of 0.85, bias of 0.91, RB of -9.5%, MAE of 7.7 mm, and RMSE of 15.2 mm the product tended to underestimate rainfall values during the study period. Although, the POD score of 1.00 demonstrated very good skill in detecting the occurrence of rainfall events, FAR value of 0.25 indicated a considerable amount of false alarms. Moreover, as the precipitation threshold increased, the underestimation became more prominent over the study region. Analysis on the basis of location of the rain gauges also showed that APHRODITE consistently underestimated rainfall values with the increase of extreme rainfall thresholds. Journal of Engineering Science 12(1), 2021, 51-56

scholarly journals A comparison between high-resolution satellite precipitation estimates and gauge measured data: case study of Gorganrood basin, Iran

2018 ◽  
Vol 67 (3) ◽  
pp. 236-251 ◽  
Author(s):  
Donya Dezfooli ◽  
Banafsheh Abdollahi ◽  
Seyed-Mohammad Hosseini-Moghari ◽  
Kumars Ebrahimi
Keyword(s):  
Pearson Correlation ◽  
Absolute Error ◽  
Probability Of Detection ◽  
Critical Success ◽  
Precipitation Estimates ◽  
Seasonal Basis ◽  
Precipitation Gauge ◽  
Critical Success Index ◽  
Trmm 3B42

Abstract The aim of this paper is to evaluate the accuracy of the precipitation data gathered from satellites including PERSIANN, TRMM-3B42V7, TRMM-3B42RTV7, and CMORPH, over Gorganrood basin, Iran. The data collected from these satellites (2003–2007) were then compared with precipitation gauge observations at six stations, namely, Tamar, Ramiyan, Bahlakeh-Dashli, Sadegorgan, Fazel-Abad, and Ghaffar-Haji. To compare these two groups, mean absolute error (MAE), bias, root mean square error (RMSE), and Pearson correlation coefficient criteria were calculated on daily, monthly, and seasonal basis. Furthermore, probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) were calculated for these datasets. Results indicate that, on a monthly scale, the highest correlation between observed and satellite-gathered data calculated is 0.404 for TRMM-3B42 at Bahlakeh-Dashli station. At a seasonal scale, the highest correlation is calculated for winter data and using PERSIANN data, while for the other seasons, TRMM-3B42 data showed the best correlation with observed data. The high values of RMSE and MAE for winter data showed that the satellites provided poor estimations at this season. The best and the worst values of RMSE for studied satellites belonged to Sadegorgan and Ramiyan stations, respectively. Furthermore, the PERSIANN gains a better CSI and POD while TRMM-3B42V7 showed a better FAR.

scholarly journals The Quantile-Matching Approach to Improving Radar Quantitative Precipitation Estimation in South China

2021 ◽  
Vol 13 (23) ◽  
pp. 4956
Author(s):  
Linye Song ◽  
Shangfeng Chen ◽  
Yun Li ◽  
Duo Qi ◽  
Jiankun Wu ◽  
...  
Keyword(s):  
South China ◽  
Weather Radar ◽  
Absolute Error ◽  
Rain Gauge ◽  
Observation Data ◽  
Matching Method ◽  
Study Region ◽  
Surface Precipitation ◽  
Quantitative Precipitation Estimation ◽  
Precipitation Estimation

Weather radar provides regional rainfall information with a very high spatial and temporal resolution. Because the radar data suffer from errors from various sources, an accurate quantitative precipitation estimation (QPE) from a weather radar system is crucial for meteorological forecasts and hydrological applications. In the South China region, multiple weather radar networks are widely used, but the accuracy of radar QPE products remains to be analyzed and improved. Based on hourly radar QPE and rain gauge observation data, this study first analyzed the QPE error in South China and then applied the Quantile Matching (Q-matching) method to improve the radar QPE accuracy. The results show that the rainfall intensity of the radar QPE is generally larger than that determined from rain gauge observations but that it usually underestimates the intensity of the observed heavy rainfall. After the Q-matching method was applied to correct the QPE, the accuracy improved by a significant amount and was in good agreement with the rain gauge observations. Specifically, the Q-matching method was able to reduce the QPE error from 39–44%, demonstrating performance that is much better than that of the traditional climatological scaling method, which was shown to be able to reduce the QPE error from 3–15% in South China. Moreover, after the Q-matching correction, the QPE values were closer to the rainfall values that were observed from the automatic weather stations in terms of having a smaller mean absolute error and a higher correlation coefficient. Therefore, the Q-matching method can improve the QPE accuracy as well as estimate the surface precipitation better. This method provides a promising prospect for radar QPE in the study region.

scholarly journals Evaluation of Precipitation Estimates CMORPH-CRT on Regions of Mexico with Different Climates

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1722
Author(s):  
José L. Bruster-Flores ◽  
Ruperto Ortiz-Gómez ◽  
Adrian L. Ferriño-Fierro ◽  
Víctor H. Guerra-Cobián ◽  
Dagoberto Burgos-Flores ◽  
...  
Keyword(s):  
Absolute Error ◽  
Probability Of Detection ◽  
Rain Gauges ◽  
Critical Success ◽  
Lack Of Information ◽  
Precipitation Estimates ◽  
Global Coverage ◽  
Climate Prediction Center ◽  
Critical Success Index ◽  
Precipitation Events

Satellite-based precipitation (SBP) products with global coverage have the potential to overcome the lack of information in places where there are no rain gauges to perform hydrological analyses; however, it is necessary to evaluate the reliability of the SBP products. In this study, we evaluated the performance of the Climate Prediction Center morphing technique with corrected bias (CMORPH-CRT) product in 14 sites in Mexico. The evaluation was carried out using two approaches: (1) using categorical metrics that include indicators of probability of detection (POD), false alarm rate (FAR), critical success index (CSI), and frequency bias index (FBI); and (2) through statistical indicators such as the mean absolute error (MAE), root mean square error (RMSE), relative bias (RB), and correlation coefficient (CC). The analysis was carried out with two levels of temporal aggregation: 30 min and daily. The results indicate that the CMORPH-CRT product overestimates the number of precipitation events in most cases since FBI values greater than 1 in 78.6% of analyzed stations were obtained. Also, we obtained CC values in the range of 0.018 to 0.625, which implied weak to moderate correlations, and found that in all stations, the CMORPH-CRT product overestimates the precipitation (RB > 0).

scholarly journals Spatial Pattern of Precipitation in GPM-Era Satellite Products against Rain Gauge Measurements over Nepal

Jalawaayu ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 39-56
Author(s):  
Bharat Badayar Joshi ◽  
Munawar Ali ◽  
Dibit Aryal ◽  
Laxman Paneru ◽  
Bhaskar Shrestha
Keyword(s):  
High Elevation ◽  
Rain Gauge ◽  
Probability Of Detection ◽  
Precipitation Pattern ◽  
Critical Success ◽  
Precipitation Estimates ◽  
Critical Success Index ◽  
Precipitation Events ◽  
Selection Of ◽  
Better Than

Precipitation in a mountainous region is highly variable due to the complex terrain. Satellite-based precipitation estimates are potential alternatives to gauge measurements in these regions, as these typical measurements are not available or are scarce in high elevation areas. However, the accuracy of these gridded precipitation datasets need to be addressed before further usage. In this study, an evaluation of the spatial precipitation pattern in satellite-based precipitation products is provided, including satellite-only (Integrated Multi satellite Retrievals for GPM IMERG-UCORR and Global Satellite Mapping of Precipitation (GSMaP-MVK) and gauge calibrated (IMERG-CORR and GSMaP-Gauge) products, with a spatial resolution of 0.1°, which is compared to 387-gauge measurements in Nepal from April 2014 to December 2016. The major results are as follows: (1) The gauge calibrated version 5 IMERG-CORR and version 6 GSMaP-Gauge are relatively better than the satellite-only datasets, although they all underestimate the observed precipitation. (2) The daily gauge calibrated GSMaP-Gauge performs fairly well in low and mid-elevation areas, whereas the monthly gauge calibrated IMERG-C performs better in high-elevation areas. (3) For the daily time scale, IMERG-CORR shows a better ability to detect the true precipitation (higher Probability of Detection (POD)) and (lowest False Alarm Ratio (FAR)) events among all datasets. However, all four satellite-based precipitation datasets accurately detect (Critical Success Index (CSI) >40%) precipitation and no-precipitation events. The results of this work provide the systematic quantification of IMERG and GSMaP of satellite precipitation products over Nepal using station observations and delivers a helpful statistical basis for the selection of these datasets for future scientific research.

scholarly journals Characteristics of Precipitation Diurnal Cycle over a Mountainous Area of Sumatra Island including MJO and Seasonal Signatures Based on the 15-Year Optical Rain Gauge Data, WRF Model and IMERG

Atmosphere ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 63
Author(s):  
Marzuki Marzuki ◽  
Helmi Yusnaini ◽  
Ravidho Ramadhan ◽  
Fredolin Tangang ◽  
Abdul Azim Bin Amirudin ◽  
...  
Keyword(s):  
Diurnal Cycle ◽  
Precipitation Amount ◽  
Wrf Model ◽  
Rain Gauge ◽  
Mountainous Area ◽  
Peak Time ◽  
Rain Event ◽  
Northeast Monsoon ◽  
Sumatra Island ◽  
Diurnal Cycle Of Precipitation

In this study we investigate the characteristics of the diurnal precipitation cycle including the Madden–Julian oscillation (MJO) and seasonal influences over a mountainous area in Sumatra Island based on the in situ measurement of precipitation using the optical rain gauge (ORG). For comparison with ORG data, the characteristics based on the Global Precipitation Measurement (GPM) mission (IMERG) and Weather Research and Forecasting (WRF) simulations were also investigated. Fifteen years of ORG data over a mountainous area of Sumatra, namely, at Kototabang (100.32° E, 0.20° S), were analyzed to obtain the characteristics of the diurnal cycle of precipitation in this region. The diurnal cycle of precipitation presented a single peak in the late afternoon, and the peak time difference was closely related to the rain event duration. The MJO acts to modulate the diurnal amplitude but not the diurnal phase. A high precipitation amount (PA) and frequency (PF) were observed during phases 2, 3, and 4, along with an increase in the number of longer-duration rain events, but the diurnal phase was similar in all MJO phases. In terms of season, the highest PA and PF values were observed during pre-southwest and pre-northeast monsoon seasons. WRF simulation reproduced the diurnal phase correctly and more realistically than the IMERG products. However, it largely overestimated the amplitude of the diurnal cycle in comparison with ORG. These disagreements could be related to the resolution and quality of IMERG and WRF data.

scholarly journals A Unified Convection Scheme (UNICON). Part II: Simulation

2014 ◽  
Vol 71 (11) ◽  
pp. 3931-3973 ◽  
Author(s):  
Sungsu Park
Keyword(s):  
Diurnal Cycle ◽  
Radiative Forcing ◽  
Deep Convection ◽  
The United States ◽  
Convection Scheme ◽  
Near Surface ◽  
Surface Precipitation ◽  
Early Afternoon ◽  
Single Column ◽  
Diurnal Cycle Of Precipitation

Abstract A unified convection scheme (UNICON) is implemented into the Community Atmosphere Model, version 5 (CAM5), and tested in single-column and global simulations forced by observed sea surface temperature. Compared to CAM5, UNICON substantially improves the single-column simulations of stratocumulus-to-cumulus transition and shallow and deep convection cases. The global performance of UNICON is similar to CAM5 with a relative spatiotemporal root-mean-square error (RMSE) of 0.777 (0.755 in CAM5) against the earlier version of the model (CCSM3.5). The notable improvements in the UNICON-simulated climatologies over CAM5 are seasonal precipitation patterns (i.e., monsoon) over the western Pacific and South Asia, reduced biases of cloud radiative forcing in the tropical deep convection regions, aerosol optical depth in the tropical and subtropical regions, and cumulus fraction and in-cumulus condensate. One notable degradation is that UNICON simulates warmer near-surface air temperature over the United States during summer. In addition to the climatology, UNICON significantly improves the simulation of the diurnal cycle of precipitation and the Madden–Julian oscillation (MJO). The surface precipitation simulated by UNICON is a maximum in the late afternoon (early afternoon in CAM5) over the summer continents and in the early morning (predawn in CAM5) over the ocean with a fairly realistic amplitude of the diurnal cycle. Sensitivity simulations indicate that the key for successful MJO simulation in UNICON is a seamless parameterization of the updraft plume dilution rate as convection evolves from shallow to deep convection. The mesoscale perturbation of the vertical velocity and the thermodynamic scalars of convective updrafts is an additional requirement for simulating the observed diurnal cycle of precipitation.

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