Evaluation of the PERSIANN-CDR Daily Rainfall Estimates in Capturing the Behavior of Extreme Precipitation Events over China

2015 ◽  
Vol 16 (3) ◽  
pp. 1387-1396 ◽  
Author(s):  
Chiyuan Miao ◽  
Hamed Ashouri ◽  
Kuo-Lin Hsu ◽  
Soroosh Sorooshian ◽  
Qingyun Duan
Keyword(s):  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Eastern China ◽  
Absolute Threshold ◽  
The Tibetan Plateau ◽  
Climate Data ◽  
Extreme Precipitation Events ◽  
Data Record ◽  
Climate Data Record ◽  
Precipitation Events

Abstract This study evaluates the performance of a newly developed daily precipitation climate data record, called Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR), in capturing the behavior of daily extreme precipitation events in China during the period of 1983–2006. Different extreme precipitation indices, in the three categories of percentile, absolute threshold, and maximum indices, are studied and compared with the same indices from the East Asia (EA) ground-based gridded daily precipitation dataset. The results show that PERSIANN-CDR depicts similar precipitation behavior as the ground-based EA product in terms of capturing the spatial and temporal patterns of daily precipitation extremes, particularly in the eastern China monsoon region, where the intensity and frequency of heavy rainfall events are very high. However, the agreement between the datasets in dry regions such as the Tibetan Plateau in the west and the Taklamakan Desert in the northwest is not strong. An important factor that may have influenced the results is that the ground-based stations from which EA gridded data were produced are very sparse. In the station-rich regions in eastern China, the performance of PERSIANN-CDR is significant. PERSIANN-CDR slightly underestimates the values of extreme heavy precipitation.

scholarly journals Annual and Seasonal Precipitation and Their Extremes over the Tibetan Plateau and Its Surroundings in 1963–2015

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 620
Author(s):  
Jin Ding ◽  
Lan Cuo ◽  
Yongxin Zhang ◽  
Cunjie Zhang ◽  
Liqiao Liang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
The Tibetan Plateau ◽  
Opposite Pattern ◽  
Westerly Jet ◽  
Extreme Precipitation Events ◽  
Daily Precipitation Data ◽  
Moisture Transports ◽  
Precipitation Events

Based on daily precipitation data from 115 climate stations, seasonal and annual precipitation and their extremes over the Tibetan Plateau and its surroundings (TPS) in 1963–2015 are investigated. There exists a clear southeast-northwest gradient in precipitation and extreme daily precipitation but an opposite pattern for the consecutive dry days (CDDs). The wet southeast is trending dry while the dry center and northwest are trending wet in 1963–2015. Correspondingly, there is a drying tendency over the wet basins in the southeast and a wetting tendency over the dry and semi-dry basins in the center and northwest in summer, which will affect the water resources in the corresponding areas. The increase (decrease) in precipitation tends to correspond to the increase (decrease) in maximum daily precipitation but the decrease (increase) in CDDs. Extreme precipitation events with 20-year, 50-year, 100-year, and 200-year recurrence occurred frequently in the past decades especially in the 1980s. The greatest extreme precipitation events tend to occur after the late 1990s and in the southeastern TPS. The ERA5 reanalysis and climate system indices reveal that (1) decreased moisture transports to the southeast in summer due to the weakening of the summer monsoons and the East Asian westerly jet; (2) increased moisture transports to the center in winter due to the strengthening of the winter westerly jet and north Atlantic oscillation; and (3) decreased instability over the southeast thus suppressing precipitation and increased instability over the northwest thus promoting precipitation. All these are conducive to the drying trends in the southeast and the wetting trends in the center.

scholarly journals Recognizing the Aggregation Characteristics of Extreme Precipitation Events Using Spatio-Temporal Scanning and the Local Spatial Autocorrelation Model

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 218
Author(s):  
Changjun Wan ◽  
Changxiu Cheng ◽  
Sijing Ye ◽  
Shi Shen ◽  
Ting Zhang
Keyword(s):  
Spatial Autocorrelation ◽  
Extreme Precipitation ◽  
Eastern China ◽  
Temporal Aggregation ◽  
Global Changes ◽  
Percentile Method ◽  
Extreme Precipitation Events ◽  
Spatio Temporal ◽  
Precipitation Events ◽  
Local Spatial Autocorrelation

Precipitation is an essential climate variable in the hydrologic cycle. Its abnormal change would have a serious impact on the social economy, ecological development and life safety. In recent decades, many studies about extreme precipitation have been performed on spatio-temporal variation patterns under global changes; little research has been conducted on the regionality and persistence, which tend to be more destructive. This study defines extreme precipitation events by percentile method, then applies the spatio-temporal scanning model (STSM) and the local spatial autocorrelation model (LSAM) to explore the spatio-temporal aggregation characteristics of extreme precipitation, taking China in July as a case. The study result showed that the STSM with the LSAM can effectively detect the spatio-temporal accumulation areas. The extreme precipitation events of China in July 2016 have a significant spatio-temporal aggregation characteristic. From the spatial perspective, China’s summer extreme precipitation spatio-temporal clusters are mainly distributed in eastern China and northern China, such as Dongting Lake plain, the Circum-Bohai Sea region, Gansu, and Xinjiang. From the temporal perspective, the spatio-temporal clusters of extreme precipitation are mainly distributed in July, and its occurrence was delayed with an increase in latitude, except for in Xinjiang, where extreme precipitation events often take place earlier and persist longer.

scholarly journals ENSO and Wintertime Extreme Precipitation Events over the Contiguous United States

2008 ◽  
Vol 21 (1) ◽  
pp. 22-39 ◽  
Author(s):  
Siegfried D. Schubert ◽  
Yehui Chang ◽  
Max J. Suarez ◽  
Philip J. Pegion
Keyword(s):  
United States ◽  
West Coast ◽  
Extreme Precipitation ◽  
East Coast ◽  
Daily Precipitation ◽  
Precipitation Variability ◽  
The West ◽  
Extreme Precipitation Events ◽  
The Impact ◽  
Precipitation Events

Abstract In this study the authors examine the impact of El Niño–Southern Oscillation (ENSO) on precipitation events over the continental United States using 49 winters (1949/50–1997/98) of daily precipitation observations and NCEP–NCAR reanalyses. The results are compared with those from an ensemble of nine atmospheric general circulation model (AGCM) simulations forced with observed SST for the same time period. Empirical orthogonal functions (EOFs) of the daily precipitation fields together with compositing techniques are used to identify and characterize the weather systems that dominate the winter precipitation variability. The time series of the principal components (PCs) associated with the leading EOFs are analyzed using generalized extreme value (GEV) distributions to quantify the impact of ENSO on the intensity of extreme precipitation events. The six leading EOFs of the observations are associated with major winter storm systems and account for more than 50% of the daily precipitation variability along the West Coast and over much of the eastern part of the country. Two of the leading EOFs (designated GC for Gulf Coast and EC for East Coast) together represent cyclones that develop in the Gulf of Mexico and occasionally move and/or redevelop along the East Coast producing large amounts of precipitation over much of the southern and eastern United States. Three of the leading EOFs represent storms that hit different sections of the West Coast (designated SW for Southwest coast, WC for the central West Coast, and NW for northwest coast), while another represents storms that affect the Midwest (designated by MW). The winter maxima of several of the leading PCs are significantly impacted by ENSO such that extreme GC, EC, and SW storms that occur on average only once every 20 years (20-yr storms) would occur on average in half that time under sustained El Niño conditions. In contrast, under La Niña conditions, 20-yr GC and EC storms would occur on average about once in 30 years, while there is little impact of La Niña on the intensity of the SW storms. The leading EOFs from the model simulations and their connections to ENSO are for the most part quite realistic. The model, in particular, does very well in simulating the impact of ENSO on the intensity of EC and GC storms. The main model discrepancies are the lack of SW storms and an overall underestimate of the daily precipitation variance.

scholarly journals Impacts of Atmospheric Rivers in Extreme Precipitation on the European Macaronesian Islands

Atmosphere ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 325 ◽  
Author(s):  
Alexandre M. Ramos ◽  
Ricardo M. Trigo ◽  
Ricardo Tomé ◽  
Margarida L. R. Liberato
Keyword(s):  
Canary Islands ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Comprehensive Assessment ◽  
Atmospheric Rivers ◽  
Extreme Precipitation Events ◽  
Macaronesian Islands ◽  
Weather Stations ◽  
The Relationship ◽  
Precipitation Events

The European Macaronesia Archipelagos (Azores, Madeira and Canary Islands) are struck frequently by extreme precipitation events. Here we present a comprehensive assessment on the relationship between atmospheric rivers and extreme precipitation events in these three Atlantic Archipelagos. The relationship between the daily precipitation from the various weather stations located in the different Macaronesia islands and the occurrence of atmospheric rivers (obtained from four different reanalyses datasets) are analysed. It is shown that the atmospheric rivers’ influence over extreme precipitation (above the 90th percentile) is higher in the Azores islands when compared to Madeira or Canary Islands. In Azores, for the most extreme precipitation days, the presence of atmospheric rivers is particularly significant (up to 50%), while for Madeira, the importance of the atmospheric rivers is reduced (between 30% and 40%). For the Canary Islands, the occurrence of atmospheric rivers on extreme precipitation is even lower.

PERSIANN-CDR: Daily Precipitation Climate Data Record from Multisatellite Observations for Hydrological and Climate Studies

2015 ◽  
Vol 96 (1) ◽  
pp. 69-83 ◽  
Author(s):  
Hamed Ashouri ◽  
Kuo-Lin Hsu ◽  
Soroosh Sorooshian ◽  
Dan K. Braithwaite ◽  
Kenneth R. Knapp ◽  
...  
Keyword(s):  
Daily Precipitation ◽  
Radar Data ◽  
Climate Data ◽  
Data Record ◽  
Global Precipitation ◽  
Climate Data Record ◽  
Climate Studies ◽  
Rainfall Estimates ◽  
Good Agreement

Abstract A new retrospective satellite-based precipitation dataset is constructed as a climate data record for hydrological and climate studies. Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) provides daily and 0.25° rainfall estimates for the latitude band 60°S–60°N for the period of 1 January 1983 to 31 December 2012 (delayed present). PERSIANN-CDR is aimed at addressing the need for a consistent, long-term, high-resolution, and global precipitation dataset for studying the changes and trends in daily precipitation, especially extreme precipitation events, due to climate change and natural variability. PERSIANN-CDR is generated from the PERSIANN algorithm using GridSat-B1 infrared data. It is adjusted using the Global Precipitation Climatology Project (GPCP) monthly product to maintain consistency of the two datasets at 2.5° monthly scale throughout the entire record. Three case studies for testing the efficacy of the dataset against available observations and satellite products are reported. The verification study over Hurricane Katrina (2005) shows that PERSIANN-CDR has good agreement with the stage IV radar data, noting that PERSIANN-CDR has more complete spatial coverage than the radar data. In addition, the comparison of PERSIANN-CDR against gauge observations during the 1986 Sydney flood in Australia reaffirms the capability of PERSIANN-CDR to provide reasonably accurate rainfall estimates. Moreover, the probability density function (PDF) of PERSIANN-CDR over the contiguous United States exhibits good agreement with the PDFs of the Climate Prediction Center (CPC) gridded gauge data and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) product. The results indicate high potential for using PERSIANN-CDR for long-term hydroclimate studies in regional and global scales.

scholarly journals Climatology of Daily Precipitation and Extreme Precipitation Events in the Northeast United States

2015 ◽  
Vol 16 (6) ◽  
pp. 2537-2557 ◽  
Author(s):  
Laurie Agel ◽  
Mathew Barlow ◽  
Jian-Hua Qian ◽  
Frank Colby ◽  
Ellen Douglas ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Seasonal Cycle ◽  
Large Scale ◽  
Daily Precipitation ◽  
Warm Season ◽  
Extreme Precipitation Events ◽  
Tail Distribution ◽  
Hourly Data ◽  
Early Fall ◽  
Precipitation Events

Abstract This study examines U.S. Northeast daily precipitation and extreme precipitation characteristics for the 1979–2008 period, focusing on daily station data. Seasonal and spatial distribution, time scale, and relation to large-scale factors are examined. Both parametric and nonparametric extreme definitions are considered, and the top 1% of wet days is chosen as a balance between sample size and emphasis on tail distribution. The seasonal cycle of daily precipitation exhibits two distinct subregions: inland stations characterized by frequent precipitation that peaks in summer and coastal stations characterized by less frequent but more intense precipitation that peaks in late spring as well as early fall. For both subregions, the frequency of extreme precipitation is greatest in the warm season, while the intensity of extreme precipitation shows no distinct seasonal cycle. The majority of Northeast precipitation occurs as isolated 1-day events, while most extreme precipitation occurs on a single day embedded in 2–5-day precipitation events. On these extreme days, examination of hourly data shows that 3 h or less account for approximately 50% of daily accumulation. Northeast station precipitation extremes are not particularly spatially cohesive: over 50% of extreme events occur at single stations only, and 90% occur at only 1–3 stations concurrently. The majority of extreme days (75%–100%) are related to extratropical storms, except during September, when more than 50% of extremes are related to tropical storms. Storm tracks on extreme days are farther southwest and more clustered than for all storm-related precipitation days.

scholarly journals Investigations into the development of a satellite-based aerosol climate data record using ATSR-2, AATSR and AVHRR data over north-eastern China from 1987 to 2012

2019 ◽  
Vol 12 (7) ◽  
pp. 4091-4112 ◽  
Author(s):  
Yahui Che ◽  
Jie Guang ◽  
Gerrit de Leeuw ◽  
Yong Xue ◽  
Ling Sun ◽  
...  
Keyword(s):  
Eastern China ◽  
Data Sets ◽  
Climate Data ◽  
Data Set ◽  
North Eastern ◽  
Data Record ◽  
Single Sensor ◽  
Sun Photometer ◽  
Climate Data Record ◽  
Better Than

Abstract. Satellites provide information on the temporal and spatial distributions of aerosols on regional and global scales. With the same method applied to a single sensor all over the world, a consistent data set is to be expected. However, the application of different retrieval algorithms to the same sensor and the use of a series of different sensors may lead to substantial differences, and no single sensor or algorithm is better than any other everywhere and at all times. For the production of long-term climate data records, the use of multiple sensors cannot be avoided. The Along Track Scanning Radiometer (ATSR-2) and the Advanced ATSR (AATSR) aerosol optical depth (AOD) data sets have been used to provide a global AOD data record over land and ocean of 17 years (1995–2012), which is planned to be extended with AOD retrieved from a similar sensor. To investigate the possibility of extending the ATSR data record to earlier years, the use of an AOD data set from the Advanced Very High Resolution Radiometer (AVHRR) is investigated. AOD data sets used in this study were retrieved from the ATSR sensors using the ATSR Dual View algorithm ADV version 2.31, developed by Finnish Meteorological Institute (FMI), and from the AVHRR sensors using the aerosol optical depth over land (ADL) algorithm developed by RADI/CAS. Together, these data sets cover a multi-decadal period (1987–2012). The study area includes two contrasting areas, both in regards to aerosol content and composition and surface properties, i.e. a region over north-eastern China, encompassing a highly populated urban/industrialized area (Beijing–Tianjin–Hebei) and a sparsely populated mountainous area. Ground-based AOD observations available from ground-based sun photometer AOD data in AERONET and CARSNET are used as a reference, together with broadband extinction method (BEM) data at Beijing to cover the time before sun photometer observations became available in the early 2000s. In addition, MODIS-Terra C6.1 AOD data are used as a reference data set over the wide area where no ground-based data are available. All satellite data over the study area were validated against the reference data, showing the qualification of MODIS for comparison with ATSR and AVHRR. The comparison with MODIS shows that AVHRR performs better than ATSR in the north of the study area (40∘ N), whereas further south ATSR provides better results. The validation against sun photometer AOD shows that both AVHRR and ATSR underestimate the AOD, with ATSR failing to provide reliable results in the wintertime. This is likely due to the highly reflecting surface in the dry season, when AVHRR-retrieved AOD traces both MODIS and reference AOD data well. However, AVHRR does not provide AOD larger than about 0.6 and hence is not reliable when high AOD values have been observed over the last decade. In these cases, ATSR performs much better for AOD up to about 1.3. AVHRR-retrieved AOD compares favourably with BEM AOD, except for AOD higher than about 0.6. These comparisons lead to the conclusion that AVHRR and ATSR AOD data records each have their strengths and weaknesses that need to be accounted for when combining them in a single multi-decadal climate data record.

scholarly journals Assessing the Use of Satellite-Based Estimates and High-Resolution Precipitation Datasets for the Study of Extreme Precipitation Events over the Iberian Peninsula

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1688 ◽  
Author(s):  
Riccardo Hénin ◽  
Margarida Liberato ◽  
Alexandre Ramos ◽  
Célia Gouveia
Keyword(s):  
High Resolution ◽  
Iberian Peninsula ◽  
Real Time ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Weather Forecast ◽  
Winter Period ◽  
Medium Range Weather Forecast ◽  
Extreme Precipitation Events ◽  
Precipitation Events

An assessment of daily accumulated precipitation during extreme precipitation events (EPEs) occurring over the period 2000–2008 in the Iberian Peninsula (IP) is presented. Different sources for precipitation data, namely ERA-Interim and ERA5 reanalysis by the European Centre for Medium-Range Weather Forecast (ECMWF) and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), both in near-real-time and post-real-time releases, are compared with the best ground-based high-resolution (0.2° × 0.2°) gridded precipitation dataset available for the IP (IB02). In this study, accuracy metrics are analysed for different quartiles of daily precipitation amounts, and additional insights are provided for a subset of EPEs extracted from an objective ranking of extreme precipitation during the extended winter period (October to March) over the IP. Results show that both reanalysis and multi-satellite datasets overestimate (underestimate) daily precipitation sums for the least (most) extreme events over the IP. In addition, it is shown that the TRMM TMPA precipitation estimates from the near-real-time product may be considered for EPEs assessment over these latitudes. Finally, it is found that the new ERA5 reanalysis accounts for large improvements over ERA-Interim and it also outperforms the satellite-based datasets.

Climatology of Extreme Daily Precipitation in Colorado and Its Diverse Spatial and Seasonal Variability

2015 ◽  
Vol 16 (2) ◽  
pp. 781-792 ◽  
Author(s):  
Kelly Mahoney ◽  
F. Martin Ralph ◽  
Klaus Wolter ◽  
Nolan Doesken ◽  
Michael Dettinger ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Daily Rainfall ◽  
High Elevation ◽  
Colorado Front Range ◽  
Front Range ◽  
Regional Variability ◽  
Extreme Precipitation Events ◽  
Continental Divide ◽  
Precipitation Events

Abstract The climatology of Colorado’s historical extreme precipitation events shows a remarkable degree of seasonal and regional variability. Analysis of the largest historical daily precipitation totals at COOP stations across Colorado by season indicates that the largest recorded daily precipitation totals have ranged from less than 60 mm day−1 in some areas to more than 250 mm day−1 in others. East of the Continental Divide, winter events are rarely among the top 10 events at a given site, but spring events dominate in and near the foothills; summer events are most common across the lower-elevation eastern plains, while fall events are most typical for the lower elevations west of the Divide. The seasonal signal in Colorado’s central mountains is complex; high-elevation intense precipitation events have occurred in all months of the year, including summer, when precipitation is more likely to be liquid (as opposed to snow), which poses more of an instantaneous flood risk. Notably, the historic Colorado Front Range daily rainfall totals that contributed to the damaging floods in September 2013 occurred outside of that region’s typical season for most extreme precipitation (spring–summer). That event and many others highlight the fact that extreme precipitation in Colorado has occurred historically during all seasons and at all elevations, emphasizing a year-round statewide risk.

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