Maximum Dry Spell Length Research Articles

Assessment of future precipitation indices in the Shikoku region using a statistical downscaling model

In this study, we used the statistical downscaling model (SDSM) to estimate mean and extreme precipitation indices under present and future climate conditions for Shikoku, Japan. Specifically, we considered the following mean and extreme precipitation indices: mean daily precipitation, R10 (number of days with precipitation >10 mm/day), R5d (annual maximum precipitation accumulated over 5 days), maximum dry-spell length (MaDSL), and maximum wet-spell length (MaWSL). Initially, we calibrated the SDSM model using the National Center for environmental prediction (NCEP) reanalysis dataset and daily time series of precipitation for ten locations in Shikoku which were acquired from the surface weather observation point dataset. Subsequently, we used the validated SDSM, using data from NCEP and outputs form general circulation models (GCM), to predict future precipitation indices. Specifically, the HadCM3 GCM was run under the special report on emissions scenarios (SRES) A2 and B2 scenarios, and the CGCM3 GCM was run under the SRES A2 and A1B scenarios. The results showed that: (1) the SDSM can reasonably be used to simulate mean and extreme precipitation indices in the Shikoku region; (2) the values of annual R10 were predicated to decrease in the future in northern Shikoku under all climate scenarios; conversely, the values of annual R10 were predicted to increase in the future in the range of 0–15 % in southern and western Shikoku. The values of annual MaDSL were predicted to increase in northern Shikoku, and the values of annual MaWSL were predicted to decrease in northeastern Shikoku; (3) the spatial variation of precipitation indices indicated the potential for an increased occurrence of drought across northeastern Shikoku and an increased occurrence of flood events in the southwestern part of Shikoku, especially under the A2 and A1B scenarios; (4) characteristics of future precipitation may differ between the northern and southern sides of the Shikoku Mountains. Regional variations in extreme precipitation indices were not notably evident in the B2 scenario compared to the other scenarios.

Long-term trends and variability of rainfall extremes in the Philippines

Owing to the increasing concerns about climate change due to the recent extreme rainfall events in the Philippines, long-term trends and variability in rainfall extremes in the country are investigated using 60-year (1951–2010) daily rainfall data from 35 meteorological stations. Rainfall extremes are described using seven extreme precipitation indices (EPI) that characterize daily rainfall in terms of intensity, accumulation, and duration on a seasonal perspective. The nonparametric Mann–Kendall test is employed in combination with the moving blocks bootstrapping technique to detect significant trends in EPI. The results suggest a tendency toward a drying condition for the dry season, January–March (JFM), as indicated by statistically significant decreasing trends in seasonal wet days total rainfall (PCPTOT) associated with increasing trends in maximum length of dry spell (LDS). In contrast, statistically significant increasing trends in maximum 5-day rainfall (RX5day) and decreasing trends in LDS denote a wetting condition during the July–September (JAS) season, particularly at stations located in the northwest and central Philippines. The trends obtained are further assessed by examining the longer time series of EPI at four meteorological stations (Aparri, Dagupan, Iloilo, and Masbate) that have rainfall data from 1911 to 2010. The longer historical data revealed that the trends obtained in the shorter period (1951–2010) could either be consistent with the continuous long-term trends, as observed in RX5day during JAS at Aparri and Masbate, or represent interdecadal variability as was observed at Dagupan and Iloilo. The long-term (1911–2010) southwestward extension of the western North Pacific subtropical high associated with a weakening of the 850-hPa westerly wind over the South China Sea partly provides a possible cause of the trends in EPI during JAS, whereas the weakening of the East Asian winter monsoon contributed somewhat to the trends obtained during JFM. Furthermore, interannual variations in EPI are found to be influenced greatly by the El Niño–Southern Oscillation (ENSO). Composite analyses suggest that El Niño (La Niña) events are associated with statistically significant drier (wetter) conditions over the Philippines, especially during the seasons close to ENSO mature stage.

Regional extreme‐dry‐spell frequency analysis using the L‐moments method in the middle reaches of the Yellow River Basin, China

AbstractIn this research, the regional extreme‐dry‐spell frequency in the middle reaches of the Yellow River Basin (YRB) is studied by the L‐moments method. The research area has been divided into three subregions (regions 1, 2 and 3), which have been identified as homogenous regions. The results of a goodness‐of‐fit test indicate that a generalized normal distribution is the optimal regional model for regions 1 and 2 whereas a generalized Pareto distribution is the optimal regional model for region 3. The return period analysis figures out that the maximum length‐of‐dry‐spell (MxDS) values increase from south to north in the southern part and increase from northeast to southwest in the northern part of the middle reaches of the YRB under different return periods. The increments of quantiles of dry spell under different return levels indicate that drought risk in region 1 is higher than that in regions 2 and 3. The analysis of the occurrence day of MxDS shows that MxDS mostly occurred during winter of 1998 and spring of 1999 in most stations during the considered period. By comparing summer MxDS events, it can be found that mean MxDS values have slightly increased in regions 1 and 2 during the last five decades. The maximum mean MxDS values appeared in the 2000s for regions 1 and 2 and in the 1990s for region 3. The atmospheric circulation shows that the positive anomaly centre in the west of North China, negative anomaly centre in the east of North China and the strong western Pacific subtropical high led to the decrease of precipitation in North China during the summer of 1997. Copyright © 2013 John Wiley & Sons, Ltd.

Regional frequency analysis and spatial pattern characterization of Dry Spells in Iran

ABSTRACTThis paper presents a methodology for regional frequency analysis and spatial pattern features of the Annual Maximum Dry Spell Length (AMDSL) as an indicator of drought conditions using the well‐known L‐moments approach and statistical‐based methods. Applying Ward's cluster‐analysis method identifies eight regions with distinctive AMDSL behaviours for Iran. Homogeneity testing indicates that most of these regions are homogenous. The goodness‐of‐fit test ZDist shows that Generalized Logistic; Generalized Extreme Value and Pearson type III, distributions fit best for most regions. The spatial pattern of L‐Moment statistics demonstrates that although the northwestern and northern parts of the country experience short dry spells, these periods are inconstant, and extreme dry spell events may happen in these areas. Almost all spatial mapping of AMDSLs at different probabilistic levels demonstrates that dry spells increase gradually from west to east and from north to south, and the southern parts (especially along the Persian Gulf and Oman Sea) and central areas, including most agricultural lands, stand out as the most sensitive to soil moisture deficits, because of longer lasting droughts. © 2013 Royal Meteorological Society

Assessment of RegCM4 simulated inter-annual variability and daily-scale statistics of temperature and precipitation over Mexico

The skill of a regional climate model (RegCM4) in capturing the mean patterns, interannual variability and extreme statistics of daily-scale temperature and precipitation events over Mexico is assessed through a comparison of observations and a 27-year long simulation driven by reanalyses of observations covering the Central America CORDEX domain. The analysis also includes the simulation of tropical cyclones. It is found that RegCM4 reproduces adequately the mean spatial patterns of seasonal precipitation and temperature, along with the associated interannual variability characteristics. The main model bias is an overestimation of precipitation in mountainous regions. The 5 and 95 percentiles of daily temperature, as well as the maximum dry spell length are realistically simulated. The simulated distribution of precipitation events as well as the 95 percentile of precipitation shows a wet bias in topographically complex regions. Based on a simple detection method, the model produces realistic tropical cyclone distributions even at its relatively coarse resolution (dx = 50 km), although the number of cyclone days is underestimated over the Pacific and somewhat overestimated over the Atlantic and Caribbean basins. Overall, it is assessed that the performance of RegCM4 over Mexico is of sufficient quality to study not only mean precipitation and temperature patterns, but also higher order climate statistics.

Spatio-temporal variation and statistical characteristic of extreme dry spell in Yellow River Basin, China

Drought is one of the most detrimental natural hazards in Yellow River Basin (YRB). In this research, spatio-temporal variation and statistical characteristic of drought in YRB is studied by using dry spell. Two extreme series, including annual maximum series (AMS) and partial duration series (PDS), are used and simulated with generalized extreme value (GEV), generalized Pareto (GP), and Pearson type III (PE3) distributions. The results show that the northern part is drier than the southern part of YRB. Besides, the maximum dry spell usually starts in October, November, and December. According to the trend analysis, mean maximum length of dry spell (MxDS) shows a negative trend in most stations. From the L-moments and Kolmogorov–Smirnov test method, it can be found that GEV model can better fit AMS while GP and PE3 can better fit PDS. Moreover, the quantiles from optimal model of AMS and PDS depict a similar distribution with values increases from south to north. The spatial distribution of scale and location parameters of GEV model for AMS shows a south-to-north gradient, while the distribution of shape parameter is a little irregularity. Furthermore, based on the linear correlation analysis, there is an evident linear relation between location and scale parameters with mean and standard variation of MxDS, respectively.

Non-stationary analysis of dry spells in monsoon season of Senegal River Basin using data from Regional Climate Models (RCMs)

Summary The Senegal River Basin, located in West Africa, has been affected by several droughts since the end of the 1960s. In its valley, which is densely populated and highly vulnerable to climate variability and water availability, agricultural activities provide the livelihood for thousands of people. Increasing the knowledge about plausible trends of drought events will allow to improve the adaptation and mitigation measures in order to build “adaptive capacity” to climate change in West Africa. An innovative methodology for the non-stationary analysis of droughts events, which allows the prediction of regional trends associated to several return periods, is presented. The analyses were based on Regional Climate Models (RCMs) provided by the European ENSEMBLES project for West Africa, together with observed data. A non-stationary behaviour of the annual series of maximum length of dry spells (AMDSL) in the monsoon season is reflected in temporal changes in mean and variance. The non-stationary nature of hydrometeorological series, due to climate change and anthropogenic activities, is the main criticism to traditional frequency analysis. Therefore, in this paper, the modelling tool GAMLSS (Generalized Additive Models for Location, Scale and Shape), is applied to develop regional probability density functions (pdfs) fitted to AMDSL series for the monsoon season in the Senegal River Basin. The skills of RCMs in the representation of maximum length of dry spells observed for the period 1970–1990, are evaluated considering observed data. Based on the results obtained, a first selection of the RCMs with which to apply GAMLSS to the AMDSL series identified, for the time period 1970–2050, is made. The results of GAMLSS analysis exhibit divergent trends, with different value ranges for parameters of probability distributions being detected. Therefore, in the second stage of the paper, regional pdfs are constructed using bootstrapping distributions based on probabilistic models. In general, an increase in the mean and variance statistics of AMDSL at regional level are predicted, thereby increasing the lengths of dry spells associated with a low probability of occurrence (related to high return period) in the monsoon season.

Trends in frequency indices of daily precipitation over the Iberian Peninsula during the last century

[1] This study provides the first long-term assessment of changes in precipitation associated with different rainfall categories over the Iberian Peninsula (IP). Using recently digitized data from 27 stations in Portugal and Spain, we have examined trends of precipitation indices for the complete period 1903–2003 and the two subperiods 1903–1953 and 1954–2003. These indices were evaluated seasonally according to five rainfall categories: total rainfall (≥0.2 mm), light rainfall (≥0.2 and <2.5 mm), moderate rainfall (≥2.5 and <7.5 mm), intense rainfall (≥7.5 mm), and very intense rainfall (≥15 mm). For the complete period 1903–2003, we have found that the total number of rainy days and that of light rainfall are increasing at many observatories over the IP for all seasons (except in the western zone of Portugal and the Cadiz gulf, where they are decreasing). Both subperiods show opposite behaviors in fall and spring. During the first (second) subperiod spanning 1903–1953 (1954–2003), we can find a generalized decrease (increase) in the number of rainy days in fall in all rainfall categories. In spring, an increase in the number of rainy days is found mainly for total, moderate, and intense categories for the first subperiod, and a slight decrease during the second. In winter, we have verified a decrease in the number of rainy days mainly for total, moderate, and intense rainfall categories in the second subperiod. Finally in relation to the maximum length of dry spells for both subperiods, most observatories show significant trends opposite those of the total number of rainy days. It is worth noticing that the contrasting evolution of trends found between the first and second halves of the twentieth century could only be characterized in this work following a recent comprehensive digitization of historical Iberian precipitation data from the first decades of the twentieth century.

Improving cold season precipitation prediction by the nested CWRF-CFS system

[1] This study uses the newly developed Climate extension of Weather Research and Forecasting (CWRF) model nested in the National Centers for Environmental Prediction (NCEP) operational Climate Forecast System (CFS) to improve interannual prediction of cold season precipitation over the United States. An ensemble of 5 retrospective forecasts for 27-cold seasons (December–April) during 1982–2008 has been conducted to assess the predictive skill. The CWRF downscaling reduces CFS forecast errors of seasonal mean precipitation by 22% on average, increases the equitable threat score by 0.08–0.15, and produces greater skill for heavy rainfall events. The CWRF simulates more accurate number of rainy days than the CFS over the northern and western U.S. due to the refined representation of orographic effect, shallow convection, and terrestrial hydrology. The CWRF also more realistically captures the broad region of extreme rainfall over the Gulf States and maximum dry spell length along the Great Plains, as well as their contrasts between El Niño and La Niña events. The results demonstrate the significant advantage of the CWRF downscaling for regional precipitation prediction, especially during years with weak planetary anomalies.

Observed changes in extreme weather indices in Hong Kong

AbstractPast trends of the occurrences of extreme temperature and rainfall events in Hong Kong from 1885 to 2008 were examined using a suite of 27 extreme indices adopted from the core indices developed by the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI) under the auspices of the World Meteorological Organization (WMO), with appropriate modification to suit the sub‐tropical climate of Hong Kong. Results showed that the extreme daily maximum and minimum temperatures, annual numbers of very hot days (daily maximum temperature ≥ 33.0 °C) and hot nights (daily minimum temperature ≥ 28.0 °C) as well as the warm spell duration index (WSDI) in Hong Kong exhibited statistically significant long‐term rising trends, whereas the annual number of cold days (daily minimum temperatures ≤ 12.0 °C) and cold spell duration (CSDI) index had a statistically significant decreasing trend. Regarding rainfall, the frequency of occurrence of extreme hourly, 2‐ and 3‐hourly rainfall amounts increased significantly. The fraction of annual total precipitation due to events exceeding the daily 95th percentile of the climatological normal (1971–2000) increased by 22 mm per decade in the same period, indicating that the contribution of heavy rain to the annual rainfall amount was increasing with time. However, the maximum length of dry spell in the summer months from April to September increased at a rate of 0.3 days per decade from 1885 to 2008. Using the time‐dependent generalized extreme value (GEV) distribution technique, the return period for the daily minimum temperature of 4 °C or lower had significantly lengthened from 6 years in 1900 to 163 years in 2000. The return period for an hourly rainfall of 100 mm or more had shortened from 37 years in 1900 to 18 years in 2000. Copyright © 2010 Royal Meteorological Society

Consistency of projected drought over the Sahel with changes in the monsoon circulation and extremes in a regional climate model projections

As a step toward an increased understanding of climate change over West Africa, in this paper we analyze the relationship between rainfall changes and monsoon dynamics in high‐resolution regional climate model experiments performed using the Regional Climate Model (RegCM3). Multidecadal simulations are carried out for present‐day and future climate conditions under increased greenhouse gas forcing driven by the global climate model European Center/Hamburg 5 (ECHAM5). Compared to the present day, the future scenario simulation produces drier conditions over the Sahel and wetter conditions over orographic areas. The Sahel drying is accompanied by a weaker monsoon flow, a southward migration and strengthening of the African Easterly Jet, a weakening of the Tropical Easterly Jet, a decrease of the deep core of ascent between the jets, and reduced African Easterly Wave activity. These circulation changes are characteristics of dry periods over the Sahel and are similar to the conditions found in the late twentieth century observed drought over the region. Changes in extreme events suggest that the drier conditions over the Sahel are associated with more frequent occurrences of drought periods. The projected drought over the Sahel is thus physically consistent with changes in the monsoon circulation and the extreme indices (maximum dry spell length and 5 day precipitation).

Using precipitation effectiveness variables in indexing drought in semi-arid regions

This study proposes a new drought index based on several precipitation-based parameters to quantify drought hazard in semi arid region. In addition to the practice of using only rainfall volume for indexing drought, the proposed index verifies the potentials of nine other precipitation effectiveness variables (PEVs) onset of rain, cessation of rain, length of rainy and dry season, wet days and dry days within a wet season, dry days within the year, maximum dry spell length within a wet season and mean seasonal rainfall depth (MAR) in quantifying the drought conditions over a place. The conjunctive Precipitation Effectiveness Index (CPEI), as proposed in this study, utilizes a mathematical model, which algebraically combines “standardized seasonal PEV difference or deficit in each prevailing PEV” and terms of their sequent higher powers to define a single numerical value for this “at-site” drought index approach. Some statistical comparison tests were employed to determine the most appropriate set of PEV that can be employed in the CPEI model to quantify the drought conditions at each study location. The daily rainfall data obtained from seven synoptic stations in the semi-arid region of Nigeria were obtained, tested and then used to verify the effectiveness of this new method. Results obtained showed that the optimum no of PEVs that can be effectively combined to get the optimum CPEI values for indexing the drought in the study area is three PEVs for Gusau and Kano, five PEVs for Sokoto and Maiduguri and four for the rest stations under study. The trends observed in drought values obtained using the CPEI models employing these optimum PEVs also clearly earmarks the 1970 -73 and 1983 -1987 historical drought years within the study area. This approach seems to be significant for the specific area in the Sudano-Sahelian Region of Nigeria but would need to be verified in a wider regional context in similar future study. Key words: Drought indexing, precipitation effectiveness variables, semi arid regions.

Regional Dry Spells Frequency Analysis by L-Moment and Multivariate Analysis

The spatial variation of the statistical characteristics of the extreme dry events, such as the annual maximum dry spell length (AMDSL), is a key practice for regional drought analysis and mitigation management. For arid and semi arid regions, where the data set is short and insufficient, the regionalization methods are applied to transfer at-site data to a region. The spatial variation and regional frequency distribution of annual maximum dry spell length for Isfahan Province, located in the semi arid region of Iran, was investigated using a daily database compiled from 31 rain gauges and both L-moment and multivariate analysis. The use of L-moment method showed a homogeneous region over entire province with generalized logistic distribution (GLOG) as the regional frequency distribution. However, the cluster analysis performed two regions in west and east of the province where L-moment method demonstrated the homogeneity of the regions and GLOG and Pearson Type III (PIII) distributions as regional frequency distributions for each region, respectively. The principal component analysis was applied on at-site statistics of AMDSL and found the L-coefficient of skewness (LCs) and maximum AMDSL the main variables describing the spatial variation of AMDSL over the Isfahan Province. The comparison of two homogeneous regions also proved the difference between two regions. Therefore, this study indicates the advantage of the use of multivariate methods with L-moment method for hydrologic regionalization and spatial variation of drought statistical characteristics.

Dry spell trend analysis of Isfahan Province, Iran

AbstractIn the present study the spatiotemporal trend analysis of the annual maximum dry spell length (AMDSL) and the annual number of dry spell periods (ANDSPs) of Isfahan Province in the center of Iran has been conducted based on daily rainfall records taken from 17 rain gauge stations. The autocorrelation functions (ACFs) of dry spell time series showed the randomness of dry spells. The use of Mann‐Kendall test for trend revealed two stations with significant negative trend of the AMDSL located in east and west of the province. The trend analysis of the ANDSP showed three stations with significant upward trend in east and one station with significant negative trend in the west of the province. The sequential Mann‐Kendall test showed an evidence of an individual abrupt change in the magnitudes of dry spells from 1980s, especially in eastern arid and semi‐arid regions of the province. However, the binomial and uniform distribution of Mann‐Kendall statistics reveals that individual trend in a region is not strong enough to conclude the large‐scale regional climatic effects on dry spell characteristics in the entire Isfahan Province. Copyright © 2008 Royal Meteorological Society

Daily precipitation‐downscaling techniques in three Chinese regions

Four methods of statistical downscaling of daily precipitation were evaluated on three catchments located in southern, eastern, and central China. The evaluation focused on seasonal variation of statistical properties of precipitation and indices describing the precipitation regime, e.g., maximum length of dry spell and maximum 5‐day precipitation, as well as interannual and intra‐annual variations of precipitation. The predictors used in this study were mean sea level pressure, geopotential heights at 1000, 850, 700, and 500 hPa, and specific humidity as well as horizontal winds at 850, 700, and 500 hPa levels from the NCEP/NCAR reanalysis with 2.5° × 2.5° resolution for 1961–2000. The predictand was daily precipitation from 13 stations. Two analogue methods, one using principal components analysis (PCA) and the other Teweles‐Wobus scores (TWS), a multiregression technique with a weather generator producing precipitation (SDSM) and a fuzzy‐rule‐based weather‐pattern‐classification method (MOFRBC), were used. Temporal and spatial properties of the predictors were carefully evaluated to derive the optimum setting for each method, and MOFRBC and SDSM were implemented in two modes, with and without humidity as predictor. The results showed that (1) precipitation was most successfully downscaled in the southern and eastern catchments located close to the coast, (2) winter properties were generally better downscaled, (3) MOFRBC and SDSM performed overall better than the analogue methods, (4) the modeled interannual variation in precipitation was improved when humidity was added to the predictor set, and (5), the annual precipitation cycle was well captured with all methods.

IMPACT OF CLIMATE CHANGE ON AGRICULTURAL PRODUCTION IN THE SAHEL - PART 2. CASE STUDY FOR GROUNDNUT AND COWPEA IN NIGER

During the last 30 years, the climate of the West African Sahel has undergone various changes, especially in terms of rainfall. This has large consequences for the poor-resource farmers depending mainly on rainfed agriculture. This paper investigates the impacts of current climate variability and future climate change on groundnut and cowpea production in Niger for three major agricultural regions, including the groundnut basin.Niger was one of the largest West African groundnut producing and exporting countries. Groundnut production – as a cash crop – dropped fromabout 312,000 tons in the mid 1960s (about 68% exported) to as low as 13,000tons in 1988 and increased again to 110,000 tons in 2000. Cowpea, a food crop, showsa different tendency, going from 4,000 tons in the mid fifties to a maximum of 775,000 tons in 1997, and its cultivated area is still increasing. It is also a cash crop in local economies (especially for women).To highlight the impact of climate change on groundnut and cowpea production (significantly determined by rainfall in July, August and September), the following components of the rainfall regime were calculated for the period 1951–1998: mean annual and monthly rainfall, beginning, end and lengthof the rainy season, number of rainy days per month, amount of rainfall per rainy day and the maximum length of dry spell per month. Three sub-periods whose duration varied per region were defined: for Dosso 1951–1968,1969–1984 and 1985–1998; for Maradi 1951–1970, 1971–1987 and1988–1998; and for Zinder 1951–1966, 1967–1984 and 1985–1998. A change in rainfallregime components was observed between the three sub-periods, which were characterized in chronological order by wet, dry and intermediate conditions. To assess the impact of climate variability and change on groundnut and cowpea production, a statistical modeling approach has been followed, based on thirteen predictors as described and discussed in the preceding paper. Climate change is mimicked in terms of reduced total amount of rainfall for the three main rainfall months and an increased temperature, while maintaining other significant predictors at a constant level. In 2025,production of groundnut is estimated to be between 11 and 25% lower, while cowpeayield will fall maximally 30%. Various strategies to compensate thispotential loss are presented for the two crops.