scholarly journals Early warning of drought in Europe using the monthly ensemble system from ECMWF

2015 ◽  
Vol 19 (7) ◽  
pp. 3273-3286 ◽  
Author(s):  
C. Lavaysse ◽  
J. Vogt ◽  
F. Pappenberger
Keyword(s):  
Large Scale ◽  
Standardized Precipitation Index ◽  
Seasonal Forecast ◽  
Cumulative Distribution ◽  
False Alarms ◽  
Negative Effects ◽  
European Continent ◽  
Probabilistic Forecasts ◽  
Extended Range ◽  
The Standardized Precipitation Index

Abstract. Timely forecasts of the onset or possible evolution of droughts are an important contribution to mitigate their manifold negative effects. In this paper we therefore analyse and compare the performance of the first month of the probabilistic extended range forecast and of the seasonal forecast from the European Centre for Medium-range Weather Forecasts (ECMWF) in predicting droughts over the European continent. The Standardized Precipitation Index (SPI-1) is used to quantify the onset or likely evolution of ongoing droughts for the next month. It can be shown that on average the extended range forecast has greater skill than the seasonal forecast, whilst both outperform climatology. No significant spatial or temporal patterns can be observed, but the scores are improved when focussing on large-scale droughts. In a second step we then analyse several different methods to convert the probabilistic forecasts of SPI into a Boolean drought warning. It can be demonstrated that methodologies which convert low percentiles of the forecasted SPI cumulative distribution function into warnings are superior in comparison with alternatives such as the mean or the median of the ensemble. The paper demonstrates that up to 40 % of droughts are correctly forecasted one month in advance. Nevertheless, during false alarms or misses, we did not find significant differences in the distribution of the ensemble members that would allow for a quantitative assessment of the uncertainty.

scholarly journals Early warning of drought in Europe using the monthly ensemble system from ECMWF

2015 ◽  
Vol 12 (2) ◽  
pp. 1973-2009
Author(s):  
C. Lavaysse ◽  
J. Vogt ◽  
F. Pappenberger
Keyword(s):  
Large Scale ◽  
Standardized Precipitation Index ◽  
Seasonal Forecast ◽  
Cumulative Distribution ◽  
False Alarms ◽  
Negative Effects ◽  
European Continent ◽  
Probabilistic Forecasts ◽  
Extended Range ◽  
The Standardized Precipitation Index

Abstract. Timely forecasts of the onset or possible evolution of droughts are an important contribution to mitigate their manifold negative effects. In this paper we therefore analyse and compare the performance of the first month of the probabilistic extended range forecast and of the seasonal forecast from ECMWF in predicting droughts over the European continent. The Standardized Precipitation Index (SPI) is used to quantify the onset and severity of droughts. It can be shown that on average the extended range forecast has greater skill than the seasonal forecast whilst both outperform climatology. No significant spatial or temporal patterns can be observed but the scores are improved when focussing on large-scale droughts. In a second step we then analyse several different methods to convert the probabilistic forecasts of SPI into a Boolean drought warning. It can be demonstrated that methodologies which convert low percentiles of the forecasted SPI cumulative distribution function into warnings are superior in comparison with alternatives such as the mean or the median of the ensemble. The paper demonstrates that up to 40% of droughts are correctly forecasted one month in advance. Nevertheless, during false alarms or misses, we did not find significant differences in the distribution of the ensemble members that would allow for a quantitative assessment of the uncertainty.

scholarly journals Meteorological Drought Analysis and Return Periods over North and West Africa and Linkage with El Niño–Southern Oscillation (ENSO)

2021 ◽  
Vol 13 (23) ◽  
pp. 4730
Author(s):  
Malak Henchiri ◽  
Tertsea Igbawua ◽  
Tehseen Javed ◽  
Yun Bai ◽  
Sha Zhang ◽  
...  
Keyword(s):  
West Africa ◽  
Large Scale ◽  
Southern Oscillation ◽  
Standardized Precipitation Index ◽  
Joint Probability ◽  
Meteorological Drought ◽  
Socioeconomic Impacts ◽  
The North ◽  
The Standardized Precipitation Index ◽  
The North Atlantic Oscillation

Droughts are one of the world’s most destructive natural disasters. In large regions of Africa, droughts can have strong environmental and socioeconomic impacts. Understanding the mechanism that drives drought and predicting its variability is important for enhancing early warning and disaster risk management. Taking North and West Africa as the study area, this study adopted multi-source data and various statistical analysis methods, such as the joint probability density function (JPDF), to study the meteorological drought and return years across a long term (1982–2018). The standardized precipitation index (SPI) was used to evaluate the large-scale spatiotemporal drought characteristics at 1–12-month timescales. The intensity, severity, and duration of drought in the study area were evaluated using SPI–12. At the same time, the JPDF was used to determine the return year and identify the intensity, duration, and severity of drought. The Mann-Kendall method was used to test the trend of SPI and annual precipitation at 1–12-month timescales. The pattern of drought occurrence and its correlation with climate factors were analyzed. The results showed that the drought magnitude (DM) of the study area was the highest in 2008–2010, 2000–2003, and 1984–1987, with the values of 5.361, 2.792, and 2.187, respectively, and the drought lasting for three years in each of the three periods. At the same time, the lowest DM was found in 1997–1998, 1993–1994, and 1991–1992, with DM values of 0.113, 0.658, and 0.727, respectively, with a duration of one year each time. It was confirmed that the probability of return to drought was higher when the duration of drought was shorter, with short droughts occurring more regularly, but not all severe droughts hit after longer time intervals. Beyond this, we discovered a direct connection between drought and the North Atlantic Oscillation Index (NAOI) over Morocco, Algeria, and the sub-Saharan countries, and some slight indications that drought is linked with the Southern Oscillation Index (SOI) over Guinea, Ghana, Sierra Leone, Mali, Cote d’Ivoire, Burkina Faso, Niger, and Nigeria.

scholarly journals Application of the Hidden Markov Bayesian Classifier and Propagation Concept for Probabilistic Assessment of Meteorological and Hydrological Droughts in South Korea

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 1000
Author(s):  
Muhammad Nouman Sattar ◽  
Muhammad Jehanzaib ◽  
Ji Eun Kim ◽  
Hyun-Han Kwon ◽  
Tae-Woong Kim
Keyword(s):  
Hydrological Cycle ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Bayesian Classifier ◽  
Hydrological Drought ◽  
Data Availability ◽  
Negative Effects ◽  
The Standardized Precipitation Index ◽  
Hydrological Droughts ◽  
Drought Classes

Drought is one of the most destructive natural hazards and results in negative effects on the environment, agriculture, economics, and society. A meteorological drought originates from atmospheric components, while a hydrological drought is influenced by properties of the hydrological cycle and generally induced by a continuous meteorological drought. Several studies have attempted to explain the cross dependencies between meteorological and hydrological droughts. However, these previous studies did not consider the propagation of drought classes. Therefore, in this study, to consider the drought propagation concept and to probabilistically assess the meteorological and hydrological drought classes, characterized by the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI), respectively, we employed the Markov Bayesian Classifier (MBC) model that combines the procedure of iteration of feature extraction, classification, and application for assessment of drought classes for both SPI and SRI. The classification results were compared using the observed SPI and SRI, as well as with previous findings, which demonstrated that the MBC was able to reasonably determine drought classes. The accuracy of the MBC model in predicting all the classes of meteorological drought varies from 36 to 76% and in predicting all the classes of hydrological drought varies from 33 to 70%. The advantage of the MBC-based classification is that it considers drought propagation, which is very useful for planning, monitoring, and mitigation of hydrological drought in areas having problems related to hydrological data availability.

scholarly journals A hybrid downscaling approach for the estimation of climate change effects on droughts using a geo-information tool. Case study: Thessaly, Central Greece

2016 ◽  
Vol 8 (1) ◽  
pp. 728-746 ◽  
Author(s):  
John Tzabiras ◽  
Athanasios Loukas ◽  
Lampros Vasiliades
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Standardized Precipitation Index ◽  
Historical Period ◽  
Monthly Precipitation ◽  
Max Planck ◽  
Climate Change Effects ◽  
Geostatistical Approach ◽  
The Standardized Precipitation Index ◽  
Stochastic Time Series

AbstractMultiple linear regression is used to downscale large-scale outputs from CGCM2 (second generation CGCM of Canadian centre for climate monitoring and analysis) and ECHAM5 (developed at the Max Planck Institute for Meteorology), statistically to regional precipitation over the Thessaly region, Greece. Mean monthly precipitation data for the historical period Oct.1960-Sep.2002 derived from 79 rain gauges were spatially interpolated using a geostatistical approach over the region of Thessaly, which was divided into 128 grid cells of 10 km × 10 km. The methodology is based on multiple regression of large scale GCM predictant variables with observed precipitation and the application of a stochastic time series model for precipitation residuals simulation (white noise). The methodology was developed for historical period (Oct.1960–Sep.1990) and validated against observed monthly precipitation for period (Oct.1990–Sep.2002). The downscaled proposed methodology was used to calculate the standardized precipitation index (SPI) at various timescales (3-month, 6-month, 9-month, 12-month, 24-month) in order to estimate climate change effects on droughts. Various evaluation statistics were calculated in order to validate the process and the results showed that the method is efficient in SPI reproduction but the level of uncertainty is quite high due to its stochastic component.

scholarly journals Jointly Modeling Drought Characteristics with Smoothed Regionalized SPI Series for a Small Island

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2489 ◽  
Author(s):  
Luis Angel Espinosa ◽  
Maria Manuela Portela ◽  
João Dehon Pontes Filho ◽  
Ticiana Marinho de Carvalho Studart ◽  
João Filipe Santos ◽  
...  
Keyword(s):  
Moving Average ◽  
Standardized Precipitation Index ◽  
Cumulative Distribution ◽  
Interarrival Time ◽  
Small Island ◽  
Drought Duration ◽  
Rain Gauges ◽  
Duration Magnitude ◽  
The Standardized Precipitation Index ◽  
Homogeneous Regions

The paper refers to a study on droughts in a small Portuguese Atlantic island, namely Madeira. The study aimed at addressing the problem of dependent drought events and at developing a copula-based bivariate cumulative distribution function for coupling drought duration and magnitude. The droughts were identified based on the Standardized Precipitation Index (SPI) computed at three and six-month timescales at 41 rain gauges distributed over the island and with rainfall data from January 1937 to December 2016. To remove the spurious and short duration-dependent droughts a moving average filter (MA) was used. The run theory was applied to the smoothed SPI series to extract the drought duration, magnitude, and interarrival time for each drought category. The smoothed series were also used to identify homogeneous regions based on principal components analysis (PCA). The study showed that MA is necessary for an improved probabilistic interpretation of drought analysis in Madeira. It also showed that despite the small area of the island, three distinct regions with different drought temporal patterns can be identified. The copulas approach proved that the return period of droughts events can differ significantly depending on the way the relationship between drought duration and magnitude is accounted for.

scholarly journals Drought Variability and Characteristics in the Muda River Basin of Malaysia from 1985 to 2019

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1210
Author(s):  
Zibeon bin Luhaim ◽  
Mou Leong Tan ◽  
Fredolin Tangang ◽  
Zed Zulkafli ◽  
Kwok Pan Chun ◽  
...  
Keyword(s):  
River Basin ◽  
Large Scale ◽  
Response Rate ◽  
Southern Oscillation ◽  
Standardized Precipitation Index ◽  
Kendall Test ◽  
Dry Period ◽  
The Indian Ocean ◽  
The Standardized Precipitation Index ◽  
Almost All

This study aimed to analyze the spatiotemporal changes of historical droughts over the Muda River basin (MRB), Malaysia, from 1985 to 2019 using the Standardized Precipitation Index (SPI) and the Standardized Streamflow Index (SSI). The Mann–Kendall test and Sens’ slope were used to evaluate the trends and magnitude changes in the droughts, respectively, while Spearman’s rho was applied to understand the relationships of the droughts with large-scale atmospheric circulations, such as the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), and the Madden–Julian Oscillation (MJO). The results show that the intense droughts in the MRB mostly occurred in 1991–1992, 1995, 1998, 2002–2003, 2005–2006, 2008, 2012–2013, and 2016. In addition, a declining SPI trend was found from May to December at most of the stations. About 80% of the stations experienced about 10 severely dry droughts, while almost all stations experienced at least 5 extremely dry events. Moreover, a higher response rate of the SSI than the SPI was found during low-rainfall months from January to May. Lastly, ENSO had a larger impact on the drought formations over the MRB compared to the IOD and MJO, especially during the dry period.

scholarly journals Drought Assessment Based on Fused Satellite and Station Precipitation Data: An Example from the Chengbi River Basin, China

2022 ◽  
Vol 11 (1) ◽  
pp. 48
Author(s):  
Chongxun Mo ◽  
Xuechen Meng ◽  
Yuli Ruan ◽  
Yafang Wang ◽  
Xingbi Lei ◽  
...  
Keyword(s):  
River Basin ◽  
Cumulative Distribution Function ◽  
Standardized Precipitation Index ◽  
Cumulative Distribution ◽  
Precipitation Data ◽  
Drought Assessment ◽  
Lack Of Information ◽  
Complex Calculation ◽  
The Standardized Precipitation Index

Drought poses a significant constraint on economic development. Drought assessment using the standardized precipitation index (SPI) uses only precipitation data, eliminating other redundant and complex calculation processes. However, the sparse stations in southwest China and the lack of information on actual precipitation measurements make drought assessment highly dependent on satellite precipitation data whose accuracy cannot be guaranteed. Fortunately, the Chengbi River Basin in Baise City is rich in station precipitation data. In this paper, based on the evaluation of the accuracy of IMERG precipitation data, geographically weighted regression (GWR), geographic difference analysis (GDA), and cumulative distribution function (CDF) are used to fuse station precipitation data and IMERG precipitation data, and finally, the fused precipitation data with the highest accuracy are selected to evaluate the drought situation. The results indicate that the accuracy of IMERG precipitation data needs to be improved, and the quality of CDF-fused precipitation data is higher than the other two. The drought analysis indicated that the Chengbi River Basin is in a cyclical drought and flood situation, and from October to December 2014, the SPI was basically between +1 and −1, showing a spatial pattern of slight flooding, normal conditions, and slight drought.

scholarly journals Characterization of the climatic drought indices application to the Mellah catchment, North-East of Algeria

2019 ◽  
Vol 43 (1) ◽  
pp. 28-40 ◽  
Author(s):  
Lina Bendjema ◽  
Kamila Baba-Hamed ◽  
Abderrazak Bouanani
Keyword(s):  
Statistical Tests ◽  
Standardized Precipitation Index ◽  
Drought Indices ◽  
Negative Effects ◽  
Temperature Index ◽  
North East ◽  
The Standardized Precipitation Index ◽  
Annual Scale ◽  
Social Sectors

AbstractDrought is one of the important phenomena resulting from variability and climate change. It has negative effects on all economic, agricultural and social sectors. The objective of this study is to rapidly detect climate dryness situations on an annual scale at the Mellah catchment (Northeast Algeria) for periods ranging from 31 years through the calculation of: the standardized precipitation index (SPI), the standardized Streamflow index (SSFI), the standardized temperature index (STI). Calculations made it possible to locate periods of drought more precisely by their intensity, duration and frequency, and detect years of breaks using the tests of Pettitt, rang, Lee and Heghinian, Hubert and Buishand. The use of the statistical tests for the rainfall series analyzed show all breaks, the majority of which are in 1996/1997 and 2001/2002. For the temperatures the breaks are situated in 1980/1981.

scholarly journals Extended-Range Forecasts of Atlantic Tropical Cyclone Events during 2012 Using the ECMWF 32-Day Ensemble Predictions*

2014 ◽  
Vol 29 (2) ◽  
pp. 271-288 ◽  
Author(s):  
Russell L. Elsberry ◽  
Hsiao-Chung Tsai ◽  
Mary S. Jordan
Keyword(s):  
Tropical Cyclone ◽  
False Alarm ◽  
North Pacific ◽  
Western North Pacific ◽  
False Alarms ◽  
Surprising Result ◽  
Wave Type ◽  
Weather Forecasts ◽  
Probabilistic Forecasts ◽  
Extended Range

Abstract Previous studies have demonstrated the capability of the European Centre for Medium-Range Weather Forecasts (ECMWF) 51-member, 32-day ensemble to forecast tropical cyclone (TC) events (formation and tracks) in the western North Pacific on the extended range (5–30 days). In this study, the performance of the ECMWF ensemble in extended-range forecasting of Atlantic TCs during May–December 2012 is evaluated using similar approaches. The conclusion from this evaluation is that Atlantic TC events have lower forecastability using the ECMWF ensemble than in the western North Pacific. Hurricanes Kirk and Leslie and Tropical Storms (TSs) Joyce and Oscar were successfully forecast in weeks 1–4 and, thus, are labeled as highly forecastable. Somewhat forecastable storms that are only forecast in three of the four weeks include Hurricanes Ernesto, Isaac, Nadine, and Sandy plus TS Florence. The limited forecastable storms that were successful in only the first two weeks include Hurricanes Gordon and Rafael plus TS Debby. The surprising result was that two hurricanes (Chris and Michael) and three TSs (Helene, Patty, and Tony) were not even forecast in week 1 before the starting time in the National Hurricane Center working best track (WBT) for these storms. As was the case in the western North Pacific, a substantial number of false alarm storms (no matches with any WBT) are predicted, with about 35% occurring in the first week. Except for the African wave–type false alarms, three other false alarm types may be easily recognized. A larger sample will be required to statistically verify the reliability of the probabilistic forecasts for the African wave–type ensemble storms.

scholarly journals Utilizing Objective Drought Severity Thresholds to Improve Drought Monitoring

2020 ◽  
Vol 59 (3) ◽  
pp. 455-475 ◽  
Author(s):  
Zachary T. Leasor ◽  
Steven M. Quiring ◽  
Mark D. Svoboda
Keyword(s):  
Standardized Precipitation Index ◽  
Region Of Interest ◽  
Cumulative Distribution ◽  
Drought Severity ◽  
Study Region ◽  
South Central ◽  
Central United States ◽  
Systematic Biases ◽  
The Standardized Precipitation Index ◽  
Western Portion

AbstractDrought is a prominent climatic hazard in the south-central United States. Drought severity is frequently classified using the categories established by the U.S. Drought Monitor (USDM). This study evaluates whether the thresholds for the standardized precipitation index (SPI) used by the USDM accurately classify drought severity. This study uses the SPI based on PRISM precipitation data from 1900 to 2015 to evaluate drought severity in Texas, Oklahoma, and Kansas. The results show that the fixed SPI thresholds for the USDM drought categories may lead to a systematic underestimation of drought severity in arid regions. To address this issue, objective drought thresholds were developed at each location by fitting a cumulative distribution function at each location to ensure that the observed frequency of drought in each severity category (D0–D4) matched the theoretical expectations of the USDM. This approach reduces the systematic biases in drought severity across the western portion of the study region. Therefore, we recommend developing objective drought thresholds for each location and SPI time scale (e.g., 1, 3, and 6 months). This method can be used to develop objective drought thresholds for any drought index and climate region of interest.

Sign in / Sign up

Export Citation Format

Share Document