scholarly journals SPREAD: A high-resolution daily gridded precipitation dataset for Spain

2017 ◽  
Author(s):  
Roberto Serrano-Notivoli ◽  
Santiago Beguería ◽  
Miguel Ángel Saz ◽  
Luis Alberto Longares ◽  
Martín de Luis
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Original Data ◽  
Extreme Precipitation Events ◽  
Complete Dataset ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices

Abstract. A high-resolution daily gridded precipitation dataset was built from raw data of 12,858 observatories covering a period from 1950 to 2012 in peninsular Spain and 1971 to 2012 in Balearic and Canary Islands. The original data were quality controlled and gaps were filled on each day and location independently. Using the serially-complete dataset, a grid with a 5 x 5 kilometres spatial resolution was constructed by estimating daily precipitation amounts and their corresponding uncertainty at each grid node. Daily precipitation estimations were compared to original observations to assess the quality of the gridded dataset. Four daily precipitation indices were computed to characterize the spatial distribution of daily precipitation and nine extreme precipitation indices were used to describe the frequency and intensity of extreme precipitation events. The use of the total available data in Spain, the independent estimation of precipitation for each day and the high spatial resolution of the grid allowed for a precise spatial and temporal assessment of daily precipitation that are difficult to achieve when using other methods, pre- selected long-term stations or global gridded datasets. SPREAD dataset is publicly available at http://dx.doi.org/10.20350/digitalCSIC/7393.

scholarly journals SPREAD: a high-resolution daily gridded precipitation dataset for Spain – an extreme events frequency and intensity overview

2017 ◽  
Vol 9 (2) ◽  
pp. 721-738 ◽  
Author(s):  
Roberto Serrano-Notivoli ◽  
Santiago Beguería ◽  
Miguel Ángel Saz ◽  
Luis Alberto Longares ◽  
Martín de Luis
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Extreme Events ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Mediterranean Coast ◽  
Extreme Precipitation Events ◽  
Precipitation Indices ◽  
Peninsular Spain ◽  
Wet Spells

Abstract. A high-resolution daily gridded precipitation dataset was built from raw data of 12 858 observatories covering a period from 1950 to 2012 in peninsular Spain and 1971 to 2012 in Balearic and Canary islands. The original data were quality-controlled and gaps were filled on each day and location independently. Using the serially complete dataset, a grid with a 5 × 5 km spatial resolution was constructed by estimating daily precipitation amounts and their corresponding uncertainty at each grid node. Daily precipitation estimations were compared to original observations to assess the quality of the gridded dataset. Four daily precipitation indices were computed to characterise the spatial distribution of daily precipitation and nine extreme precipitation indices were used to describe the frequency and intensity of extreme precipitation events. The Mediterranean coast and the Central Range showed the highest frequency and intensity of extreme events, while the number of wet days and dry and wet spells followed a north-west to south-east gradient in peninsular Spain, from high to low values in the number of wet days and wet spells and reverse in dry spells. The use of the total available data in Spain, the independent estimation of precipitation for each day and the high spatial resolution of the grid allowed for a precise spatial and temporal assessment of daily precipitation that is difficult to achieve when using other methods, pre-selected long-term stations or global gridded datasets. SPREAD dataset is publicly available at https://doi.org/10.20350/digitalCSIC/7393.

scholarly journals Trend in Extreme Precipitation Indices Based on Long Term In Situ Precipitation Records over Pakistan

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 797 ◽  
Author(s):  
Asher Samuel Bhatti ◽  
Guojie Wang ◽  
Waheed Ullah ◽  
Safi Ullah ◽  
Daniel Fiifi Tawia Hagan ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Temporal Trend ◽  
Daily Precipitation ◽  
Heavy Precipitation ◽  
Precipitation Extremes ◽  
Study Region ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
Extreme Indices

Assessing the long-term precipitation changes is of utmost importance for understanding the impact of climate change. This study investigated the variability of extreme precipitation events over Pakistan on the basis of daily precipitation data from 51 weather stations from 1980-2016. The non-parametric Mann–Kendall, Sen’s slope estimator, least squares method, and two-tailed simple t-test methods were used to assess the trend in eight precipitation extreme indices. These indices were wet days (R1 ≥1 mm), heavy precipitation days (R10 ≥ 10 mm), very heavy precipitation days (R20 ≥ 20 mm), severe precipitation (R50 ≥ 50 mm), very wet days (R95p) defining daily precipitation ≥ 95 percentile, extremely wet days (R99p) defining daily precipitation ≥ 99 percentile, annual total precipitation in wet days (PRCPTOT), and mean precipitation amount on wet days as simple daily intensity index (SDII). The study is unique in terms of using high stations’ density, extended temporal coverage, advanced statistical techniques, and additional extreme indices. Furthermore, this study is the first of its kind to detect abrupt changes in the temporal trend of precipitation extremes over Pakistan. The results showed that the spatial distribution of trends in different precipitation extreme indices over the study region increased as a whole; however, the monsoon and westerlies humid regions experienced a decreasing trend of extreme precipitation indices during the study period. The results of the sequential Mann–Kendall (SqMK) test showed that all precipitation extremes exhibited abrupt dynamic changes in temporal trend during the study period; however, the most frequent mutation points with increasing tendency were observed during 2011 and onward. The results further illustrated that the linear trend of all extreme indices showed an increasing tendency from 1980- 2016. Similarly, for elevation, most of the precipitation extremes showed an inverse relationship, suggesting a decrease of precipitation along the latitudinal extent of the country. The spatiotemporal variations in precipitation extremes give a possible indication of the ongoing phenomena of climate change and variability that modified the precipitation regime of Pakistan. On the basis of the current findings, the study recommends that future studies focus on underlying physical and natural drivers of precipitation variability over the study region.

Understanding Precipitation Characteristics of Afghanistan at Provincial Scale

2021 ◽  
Author(s):  
Shakti Suryavanshi ◽  
Nitin Joshi ◽  
Hardeep Kumar Maurya ◽  
Divya Gupta ◽  
Keshav Kumar Sharma
Keyword(s):  
Extreme Precipitation ◽  
Asian Country ◽  
Annual Precipitation ◽  
Precipitation Pattern ◽  
Precipitation Trend ◽  
Extreme Precipitation Events ◽  
Changing Patterns ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
Precipitation Events

Abstract This study examines the pattern and trend of seasonal and annual precipitation along with extreme precipitation events in a data scare, south Asian country, Afghanistan. Seven extreme precipitation indices were considered based upon intensity, duration and frequency of precipitation events. The study revealed that precipitation pattern of Afghanistan is unevenly distributed at seasonal and yearly scales. Southern and Southwestern provinces remain significantly dry whereas, the Northern and Northeastern provinces receive comparatively higher precipitation. Spring and winter seasons bring about 80% of yearly precipitation in Afghanistan. However, a notable declining precipitation trend was observed in these two seasons. An increasing trend in precipitation was observed for the summer and autumn seasons, however; these seasons are the lean periods for precipitation. A declining annual precipitation trend was also revealed in many provinces of Afghanistan. Analysis of extreme precipitation indices reveals a general drier condition in Afghanistan. Large spatial variability was found in precipitation indices. In many provinces of Afghanistan, a significantly declining trends were observed in intensity-based (Rx1-day, RX5-day, SDII and R95p) and frequency-based (R10) precipitation indices. The duration-based precipitation indices (CDD and CWD) also infer a general drier climatic condition in Afghanistan. This study will assist the agriculture and allied sectors to take well-planned adaptive measures in dealing with the changing patterns of precipitation, and additionally, facilitating future studies for Afghanistan.

scholarly journals Vegetation Dynamics and Diverse Responses to Extreme Climate Events in Different Vegetation Types of Inner Mongolia

Atmosphere ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 394 ◽  
Author(s):  
Li Na ◽  
Risu Na ◽  
Jiquan Zhang ◽  
Siqin Tong ◽  
Yin Shan ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Inner Mongolia ◽  
Climate Changes ◽  
Extreme Temperature ◽  
Vegetation Growth ◽  
Extreme Climate ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
The Relationship

As the global climate has changed, studies on the relationship between vegetation and climate have become crucial. We analyzed the long-term vegetation dynamics and diverse responses to extreme climate changes in Inner Mongolia, based on long-term Global Inventory Monitoring and Modelling Studies (GIMMS) NDVI3g datasets, as well as the eight extreme precipitation indices and six extreme temperature indices that are highly correlated with the occurrence of droughts or floods, heat or cold temperature disasters, and vegetation growth in Inner Mongolia. These datasets were analyzed using linear regression analysis, the Hurst exponent index, residual analysis, and the Pearson correlation analysis. The results showed the following: (1) The vegetation dynamical changes exhibited trends of improvement during 1982 to 2015, and 68% of the vegetation growth changes in Inner Mongolia can be explained by climate changes. (2) The extreme precipitation indices exhibited a slight change, except for the annual total wet–day precipitation (PRCPTOT). The occurrence of extreme cold temperatures showed a significant decline, while the occurrence of extreme warm temperatures showed an upward trend in Inner Mongolia. (3) The typical steppe, desert steppe, and forest steppe regions are more sensitive to extreme large precipitation, and the forest regions are more sensitive to extreme warm temperatures. (4) Extreme precipitation exhibits a one-month lagged effect on vegetation that is larger than the same-month effects on the grassland system. Extreme temperature exhibits same-month effects on vegetation, which are larger than the one-month lagged effects on the forest system. Therefore, studies of the relationship between extreme climate indices and vegetation are important for performing risk assessments of droughts, floods, and other related natural disasters.

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.

scholarly journals Identifying hydro-meteorological events from precipitation extremes indices and other sources over northern Namibia, Cuvelai Basin

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Frans C. Persendt ◽  
Christopher Gomez ◽  
Peyman Zawar-Reza
Keyword(s):  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Economic Losses ◽  
Precipitation Data ◽  
Rainfall Station ◽  
Extreme Precipitation Events ◽  
Daily Precipitation Data ◽  
Dry Spell ◽  
Flood Disasters ◽  
Precipitation Indices

Worldwide, more than 40% of all natural hazards and about half of all deaths are the result of flood disasters. In northern Namibia flood disasters have increased dramatically over the past half-century, along with associated economic losses and fatalities. There is a growing concern to identify these extreme precipitation events that result in many hydro-meteorological disasters. This study presents an up to date and broad analysis of the trends of hydrometeorological events using extreme daily precipitation indices, daily precipitation data from the Grootfontein rainfall station (1917–present), regionally averaged climatologies from the gauged gridded Climate Research Unit (CRU) product, archived disasters by global disaster databases, published disaster events in literature as well as events listed by Mendelsohn, Jarvis and Robertson (2013) for the data-sparse Cuvelai river basin (CRB). The listed events that have many missing data gaps were used to reference and validate results obtained from other sources in this study. A suite of ten climate change extreme precipitation indices derived from daily precipitation data (Grootfontein rainfall station), were calculated and analysed. The results in this study highlighted years that had major hydro-meteorological events during periods where no data are available. Furthermore, the results underlined decrease in both the annual precipitation as well as the annual total wet days of precipitation, whilst it found increases in the longest annual dry spell indicating more extreme dry seasons. These findings can help to improve flood risk management policies by providing timely information on historic hydro-meteorological hazard events that are essential for early warning and forecasting.

scholarly journals Long term changes of the sub-daily precipitation extremes in Hungary

2021 ◽  
Author(s):  
Monika Lakatos ◽  
Olivér Szentes
Keyword(s):  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Heavy Precipitation ◽  
Data Series ◽  
Precipitation Frequency ◽  
Maximum Rainfall ◽  
Extreme Precipitation Events ◽  
Digital Database ◽  
Precipitation Changes

<p>The warming climate evokes increasing frequency of extreme precipitation in some region. Analysis of long-term measurements could support the better understanding of the processes that cause extreme precipitation events.</p><p>Automatic stations replaced the ombrometer in many places in Hungary, particularly from the late 1990s. The change of the measurement practice do not allow simply merging the data recorded form the registering paper in the past and the recent 10 minutes measurements.   The most intense 5, 10, 20, 30, 60, 180 min sub-totals per rainfall events were recorded from the ombrometer registering paper before atomization, typically until 1993. By contrast, the 10 min precipitation sum from the AWSs are stored in the meteorological database of the Hungarian Meteorological Service from automatization. In order to join together the older and the AWS measurements it was necessary to develop a method to make this possible. Therefore we downscaled the 10 min data in time. The sampling of the AWSs is one minute, although the 1-minute data are available only for some stations in the digital database.  We applied a linear regression model to downscale the 10-miniute data for 1 min. After this, we can derive the most intense sub-totals per events from the AWS data as if they have been measured with the ombrometers.</p><p>Thereby a set of sub-daily precipitation indices defined in the INTENSE project (https://research.ncl.ac.uk/intense/aboutintense/ can be computed for longer data series. Some of the indices specified in INTENSE project describes the maximum rainfall totals and timing, the intensity, duration and frequency of heavy precipitation, frequency of rainfall above specific thresholds and some of them is related to diurnal cycle. A few of these indices are analysed for long data series to detect the sub-daily precipitation changes in Hungary.</p>

scholarly journals Spatiotemporal Trend Analysis of Precipitation Extremes in Ho Chi Minh City, Vietnam During 1980–2017

2020 ◽  
Author(s):  
Nguyen Trong Quan ◽  
Dao Nguyen Khoi ◽  
Nguyen Xuan Hoan ◽  
Nguyen Ky Phung ◽  
Thanh Duc Dang
Keyword(s):  
Extreme Precipitation ◽  
Southern Oscillation ◽  
Precipitation Extremes ◽  
Spatiotemporal Variability ◽  
Ho Chi Minh City ◽  
Annual Rainfall ◽  
Extreme Precipitation Events ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
The City

Abstract In this study, the spatiotemporal variability of trends in extreme precipitation events in Ho Chi Minh City during the period 1980–2017 was analyzed based on several core extreme precipitation indices (Rx1day, Rx5day, CDD, CWD, R20mm, R25mm, R95p, and SDII). The non-parametric Mann–Kendall and Sen’s slope methods were used to compute the statistical strength, stability, and magnitude of trends in annual rainfall, as well as the extreme precipitation indices. We found that 64% of the stations had statistically significant upward trends in yearly rainfall, with high magnitudes frequently observed in the northern and southern regions of the city. For the extreme precipitation indices, only SDII and R25mm showed dominantly significant trends. Additionally, there were increasing trends in the frequency and duration at the southern and central regions of the city during the study period. Furthermore, El Niño-Southern Oscillation and Pacific Decadal Oscillation positively correlated with the duration and negatively correlated with the intensity and frequency of extreme precipitation. Thus, water management plans should be adjusted appropriately to reduce the severe impacts of precipitation extremes on communities and ecosystems.

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