Monthly Palmer Drought Severity Research Articles

Drought variation recorded by growth rings of the shrub Sabina vulgaris in the middle Qilian Mountains, northwest China

The evergreen coniferous creeping shrub, Sabina vulgaris, is widely distributed in China, from high and cold mountain sites to low-elevation arid desert areas. This paper performed dendroclimatological analysis of the samples of S. vulgaris from three sampling sites (2700–2900 m a.s.l.) at sites in the northern border of the middle Qilian Mountains, Northwest China. We found that the radial growth of S. vulgaris was mainly limited by rainfall during the growing season, especially in May and June, but was also limited by low temperatures in the late growing season. It presents the regional differention of the climate response of the shrub radial growth from the other distributed areas, such as the sandland and mountains. We constructed a 274-year drought record by calibrating growth-ring data and relating this data to the regional monthly Palmer Drought Severity Index (PDSI56), which represents regional moisture conditions. The PDSI56 reconstruction accounted for 35.5 % of the variation of the actual May to June PDSI56 during the period for which meteorological data was available (1950–2014). The most severe drought occurred during the 1920s, followed by the 1950s, 1740s, and the period from the 1870s to the 1880s; the wettest years were during the 1980s, followed by the 2010s, 1770s, and 1750. The changes between drought, normal, and wet periods were consistent with the reconstructed results from previous conifer ring series for Sabina przewalskii and Picea crassifolia in the study area. Our results demonstrate the value of S. vulgaris in dendrochronology.

Drought indices for the Zagreb-Grič Observatory with an overview of drought damage in agriculture in Croatia

The Standardized Precipitation Index (SPI) for different time scales of n = 1, 2, 3, 6, 9, 12, and 24 months and the monthly Palmer Drought Severity Index (PDSI) were calculated for the Zagreb-Gric Observatory, located in North-Western Croatia, for the period 1862–2012. The PDSI exhibits a stronger long-term negative trend than the SPI due to the influence of the global warming, which corresponds with the global scale results published in the 4th IPCC (Intergovernmental Panel on Climate Change) report. The SPI for a 9-month scale was compared with the PDSI for a monthly scale because the correlation between them is the highest in comparison with other SPI time scales. The Chapman percentile classification regarding dryness/wetness severity was used instead of the “originally” proposed classes. Thirty-year moving averages indicate that long-term variation in dryness/wetness severity is more clearly emphasised for the PDSI than for the SPI, showing the last 30-year period to be the driest on record. Autoregressive function analysis indicates that the SPI for a 1-month scale has serialy independent values, while the SPI for the 9-month scale and the monthly PDSI are close to a Markov process. A significant correlation was established between the SPI and PDSI indices and crop damages in Croatia.

Seasons of Drought in Slovakia During the Period from 1957 to 2016

Abstract The aim of the paper was to describe the occurrence of dry seasons in Slovakia. Dry seasons in the period from 1957 to 2016 were determined according to the monthly Palmer Drought Severity Index (PDSI). For this purpose, ten sites based on limit climatic parameters were chosen – Bratislava, Piešťany, Hurbanovo, Čadca, Sliač, Boľkovce, Poprad, Košice, Milhostov, and Kamenica nad Cirochou. The results showed the alternation of dry and wet episodes and the variability of weather not only over time, but also over space. The analysis of linear trends showed that the arid trend was identified on most sites (9 localities).

Satellite Observations of Regional Drought Severity in the Continental United States Using GRACE-Based Terrestrial Water Storage Changes

Drought monitoring is important for characterizing the timing, extent, and severity of drought for effective mitigation and water management. Presented here is a novel satellite-based drought severity index (DSI) for regional monitoring derived using time-variable terrestrial water storage changes from the Gravity Recovery and Climate Experiment (GRACE). The GRACE-DSI enables drought feature comparison across regions and periods, it is unaffected by uncertainties associated with soil water balance models and meteorological forcing data, and it incorporates water storage changes from human impacts including groundwater withdrawals that modify land surface processes and impact water management. Here, the underlying algorithm is described, and the GRACE-DSI performance in the continental United States during 2002–14 is evaluated. It is found that the GRACE-DSI captures documented regional drought events and shows favorable spatial and temporal agreement with the monthly Palmer Drought Severity Index (PDSI) and the U.S. Drought Monitor (USDM). The GRACE-DSI also correlates well with a satellite-based normalized difference vegetation index (NDVI), indicating sensitivity to plant-available water supply changes affecting vegetation growth. Because the GRACE-DSI captures changes in total terrestrial water storage, it complements more traditional drought monitoring tools such as the PDSI by providing information about deeper water storage changes that affect soil moisture recharge and drought recovery. The GRACE-DSI shows potential for globally consistent and effective drought monitoring, particularly where sparse ground observations (especially precipitation) limit the use of traditional drought monitoring methods.

A Viable and Cost-Effective Weather Index Insurance for Rice in Indonesia

The potentially adverse effects of droughts on agricultural output are obvious. Indonesian rice farmers have no financial protection from climate risk via catastrophic weather risk transfer tools. Done well, a weather index insurance (WII) program can not only provide resources that enable recovery, but can also facilitate the adoption of prevention and adaptation measures and incentivise risk reduction. Here, we quantify the applicability, viability, and likely cost of introducing a WII for droughts for rice production in Indonesia. To reduce basis risk, we construct district specific indices that are based on the estimation of Panel Geographically Weighted Regressions models. With these spatial tools, and detailed district level data on past agricultural productivity and weather conditions, we present an algorithm that generates an effective and actuarially sound WII, and measure its effectiveness in reducing income volatility for farmers. We use data on annual paddy production in 428 Indonesian districts, reported over the period 1990-2013, and climate data from 1950-2015. We use the monthly Palmer Drought Severity Index and identify district-specific trigger and exit points for the insurance plan. We quantify the impact of this hypothetical insurance product using past production data to calculate an actuarially-robust and welfare-enhancing price for this scheme.

Reconstruction of the March–August PDSI since 1703 AD based on tree rings of Chinese pine (<i>Pinus tabulaeformis</i> Carr.) in the Lingkong Mountain, southeast Chinese loess Plateau

Abstract. We utilised tree-ring cores, collected from three sites at Lingkong Mountain located in the southeast part of the Chinese Loess Plateau (CLP), to develope a regional ring-width chronology. Significant positive correlations between the tree-ring index and the monthly Palmer drought severity index (PDSI) were identified, indicating that the radial growth of trees in this region was moisture-limited. The March–August mean PDSI was quantitatively reconstructed from 1703 to 2008 with an explained variance of 46.4%. Seven dry periods during 1719–1726, 1742–1748, 1771–1778, 1807–1818, 1832–1848, 1867–1932 and 1993–2008 and six wet periods during 1727–1741, 1751–1757, 1779–1787, 1797–1805, 1853–1864 and 1934–1957 were revealed in our reconstruction. Among them, 1867–1932 and 1934–1957 were identified as the longest dry and wet periods, respectively. On the centennial scale, the 19th century was recognised as the driest century. The drying tendency since 1960s was evident. However, recent drought in 1993–2008 was still within the frame of natural climate variability based on the 306 yr PDSI reconstruction. The dry and wet phases of Lingkong Mountain were in accordance with changes in the summer Asian-Pacific oscillation (IAPO) and sunspot numbers, they also showed strong similarity to other tree-ring based moisture indexes in large areas in and around the CLP, indicating the moisture variability in the CLP was almost synchronous and closely related with large-scale land–ocean–atmospheric circulation and solar activity. Spatial correlation analysis suggested that this PDSI reconstruction could represent the moisture variations for most parts of the CLP, and even larger area of northern China and east Mongolia. Multi-taper spectral analysis revealed significant cycles at the inter-annual (2–7 yr), inter-decadal (37.9 yr) and centennial (102 yr) scales. Results of this study are very helpful for us to improve the knowledge of past climate change in the CLP and enable us to prevent and manage future natural disasters.

Climate variability and projected change in the western United States: regional downscaling and drought statistics

Climate change in the twenty-first century, projected by a large ensemble average of global coupled models forced by a mid-range (A1B) radiative forcing scenario, is downscaled to Climate Divisions across the western United States. A simple empirical downscaling technique is employed, involving model-projected linear trends in temperature or precipitation superimposed onto a repetition of observed twentieth century interannual variability. This procedure allows the projected trends to be assessed in terms of historical climate variability. The linear trend assumption provides a very close approximation to the time evolution of the ensemble-average climate change, while the imposition of repeated interannual variability is probably conservative. These assumptions are very transparent, so the scenario is simple to understand and can provide a useful baseline assumption for other scenarios that may incorporate more sophisticated empirical or dynamical downscaling techniques. Projected temperature trends in some areas of the western US extend beyond the twentieth century historical range of variability (HRV) of seasonal averages, especially in summer, whereas precipitation trends are relatively much smaller, remaining within the HRV. Temperature and precipitation scenarios are used to generate Division-scale projections of the monthly palmer drought severity index (PDSI) across the western US through the twenty-first century, using the twentieth century as a baseline. The PDSI is a commonly used metric designed to describe drought in terms of the local surface water balance. Consistent with previous studies, the PDSI trends imply that the higher evaporation rates associated with positive temperature trends exacerbate the severity and extent of drought in the semi-arid West. Comparison of twentieth century historical droughts with projected twenty-first century droughts (based on the prescribed repetition of twentieth century interannual variability) shows that the projected trend toward warmer temperatures inhibits recovery from droughts caused by decade-scale precipitation deficits.

Statistical Modeling of the Monthly Palmer Drought Severity Index

This paper presents a new approach for the modeling of dry period interarrival times. The new model targets dry period interarrival times directly and uses a combination of the empirical model and results from extreme-value theory to achieve good fits. Existing approaches initially model dry period duration and successive wet period duration, then get a model for dry period interarrival times as a by-product. We perform a statistical study and analyze various duration characteristics of dry and wet periods based on monthly Palmer drought severity indices for climate divisions in the United States. Data from the states of Nebraska, Nevada, Arizona, and Florida are used to show that previous models are often inadequate. We also estimate return periods showing that our proposed approach for modeling dry period interarrival times is necessary and that designs and actuarial calculations based on the results produced by fitting previously published models would be severely flawed.

Tree-ring based PDSI reconstruction since AD 1842 in the Ortindag Sand Land, east Inner Mongolia

Based on three Chinese pine (Pinus tabulaeformis Carr.) and one Meyer spruce (Picea meyeri Rehd. et Wils.) ring-width chronologies, a 163-year drought history was reconstructed in the eastern Ortindag Sand Land. All tree-ring chronologies show large inter-annual variations and strong common signals and fairly consistent variation between different chronologies, indicating that they are excellent proxy of regional climate. A regional chronology (RC) was established by averaging the four standard chronologies and further employed for the analysis and climatic reconstruction. The analysis revealed that tree growth is primarily limited by low precipitation in February–March and June–July and high temperature in May–July. In addition, RC has high correlations with the monthly Palmer drought severity index (PDSI) prior to and during the growing season because the PDSI considers the accumulation of the droughts. Response function analysis revealed that RC only exhibits significant correlations with the PDSI in June and July (close to the 95% significance level in May). Because May–July is a critical period for tree growth, the average May–July PDSI (PDSI5–7) was reconstructed back to 1842 using RC in the Ortindag Sand Land. The reconstruction can explain 52% of the PDSI variance and the equation was rather stable over time. It agrees well with the variation of the average dryness/wetness indices in North China, and captures the decline process of the East Asian summer monsoon since the mid-1960s. It is worth noting that the Ortindag Sand Land has experienced the most severe drought in the recent 40 years based on the 163-year drought reconstruction. Like summer precipitation in North China the reconstructed PDSI5–7 also displays a 20-year oscillation.

Regional expression of the 1988 U.S. Midwest drought in seasonal δ13C of tree rings

This study analyzes δ13C of subdivisions of the 1988 and 1989 growth rings from three conifer species (Pinus resinosa, Pinus strobus, and Picea glauca) across a network of nine sites over four states in the upper U.S. Midwest to infer seasonal and interannual environmental moisture conditions. Both years were characterized by different spatial patterns of drought (expressed through rainfall and Palmer Drought Indices), with the area of 1989 drought being smaller and shifting westward relative to 1988. Rings were subdivided into four equal segments from which holocellulose was separated. The range of δ13C variation within each ring was typically 1–2‰ for both years, and the single site where all three species co‐occurred revealed coherent seasonal δ13C patterns for the pines but no correlation of the spruce δ13C patterns with those of the pines. Various averaged combinations of monthly Palmer Drought Severity Index (PDSI) and precipitation assigned to each subdivision versus both δ13C and discrimination (Δ ≈ δ13Cair − δ13Cplant) yielded significant correlations (generally higher with PDSI) and even stronger correlations when the spruce data were removed. The fraction of average monthly cumulative precipitation (relative to 1900–2001 means) for these 2 years was more strongly related to δ13C than either monthly precipitation or monthly fraction of average precipitation, but was not as strongly related to δ13C as was PDSI. Furthermore, the pattern of increasing δ13C in 1988 observed at several sites is an indicator of the increasing moisture stress of that year, and the difference between the 1988 and 1989 average isotopic compositions of the third and fourth subdivisions matched the regional moisture shift well.

The Palmer Drought Severity Index (PDSI) as an indicator of soil moisture

Detailed observation of soil moisture time series has of practical importance either in strategic preparing of researches or in professional planning. Meteorological-related spatial and temporal connections of soil moisture were investigated on monthly Palmer Drought Severity Index (PDSI) time series of five meteorological stations in Eastern Hungary (Miskolc, Nyı́regyháza, Debrecen, Kecskemét and Szeged) for the period 1901–1999. The calculated PDSI values were compared with the soil moisture content of the upper one meter soil layer. The measured soil moisture time series come from the authors ([Dunkel, Z., 1994; Lambert, K., et al., 1993 (in Hungarian)]). Both the used soil moisture time series and the Pálfai-index, expressing numerically daily hydrological extremes ([Pálfai, I.,1991]), confirmed our result independently of each other according to which PDSI is a good indicator of the soil moisture fluctuations in the upper one meter soil layer of the Great Hungarian Plain. On the basis of the regression coefficients of the linear connection, the index values can be expressed in physical unit of the water content in the upper one meter soil layer, as well. As a result of our examinations, the index has favourable statistical features; namely, the distribution of monthly samples is normal. Analysing spatial and temporal connections of the varied hydrometeorological relations of the selected region, average spatial and strong temporal correlations were established and these results are functions of intra-annual variability of precipitation.

Climatic forcing of droughts: a Central European example

A fuzzy rule-based technique is used for modelling the relationship between climatic forcing and droughts in a Central/Eastern European country, Hungary. Two types of climatic forcing'called premises'are considered: atmospheric circulation patterns (CP) and El Niño Southern Oscillation (ENSO). Both the Hess-Brezowsky CP types and ENSO events influence the occurrence of droughts, but the ENSO signal is relatively weak in a statistical sense. The fuzzy rule-based approach is able to learn the high space—time variability of monthly Palmer Drought Severity Index (PDSI) and results in a proper reproduction of the empirical frequency distributions. The “engine” of the approach, the fuzzy rules, are ascertained from a subset called the learning set of the observed time series of premises (monthly CP frequencies and Southern Oscillation Index) and PDSI response. Then an independent subset, the validation set, is used to check how the application of fuzzy rules reproduces the observed PDSI.

Spatial and temporal patterns of soil moisture variations in a sub-catchment of River Tisza

Monthly Palmer drought severity index (PDSI) series are computed in a vulnerable sub-catchment of River Tisza (36,000 km 2) in East Hungary. An objective regional classification, based on spatial factor analysis of 18 stations, identifies mainly two sub-regions (three in autumn), that are likely determined rather by the variable meteorological conditions than by constant geographical ones. Location of the sub-regions are not constant, hence five stations are selected for longer-term temporal analysis (1901–1999). Since the PDSI is based on monthly temperature and precipitation data that exhibit inhomogeneities, both the original and homogenised series of PDSI are further used, although, effects of homogenisation do not appear too strongly. Cluster analysis of intra-annual PDSI-anomalies, applied for hydrological years (November–October), yields characteristically different wet, medium and dry year-types compressing the overall within-group variance to 48% of the total variance. Frequency of the year-types exhibits marked long-term variation, demonstrating unequivocal drying tendency, despite some variations among the stations. To correlate this inclination to the global climate development of the recent century, a special regression technique (Idöjárás 92 (1988) 178 (in Hungarian)) is applied for every second month of the growing season (April, June, August and October). The regression coefficients between the regional PDSI-values and the hemispherical temperature characteristics are mainly negative in the 1901–1988 basic sample. The most recent decade, however, did not support this relation, since positive precipitation anomalies prevailed in the second part of the decade. This means, that either new factors appeared in the climate system, or, more simply, the statistical connections of these different space-scales are not strong enough to delimit individual few-years’ anomalies of the water balance in the given region.

Long term climate deviations: an alternative approach and application on the Palmer drought severity index in Hungary

A new statistical test (Makra-test), applicable for long time series, is introduced to identify extended sub-periods, namely, “breaks”, average of which is significantly higher or lower than the mean of the entire time series. In order to apply this test, normal distribution of the time series being examined is a sufficient condition. In another case, if the number of elements increases in the time series, its distribution is near normal and the test can be applied, as well (according to the Central Limit Theorem). The method is demonstrated on monthly Palmer drought severity index (PDSI) data sets, computed for five stations of East Hungary in 1901–1999. Due to strongly recursive (auto-correlative) nature of PDSI every second month of the warm season (April, June, August and October) is analysed and treated as independent samples. Normality of the time series, which is a sufficient condition of the Makra-test, is validated by Kolmogorov–Smirnov test and χ 2-test. Analysis of the PDSI time series indicates that separate treatment of the months is important not only to ensure the normality, but also to consider the existing slight seasonal differences in standard deviation and skewness of the index in the East-Hungarian region. The Makra-test delimits one or more (maximum 4) significant sub-periods of the PDSI in every station and month (not considering the sub-intervals within the significant breaks, although most of them are also significant). Since the PDSI is based on monthly temperature and precipitation data that exhibit considerable inhomogeneities ( Szentimry, 1999), the test is applied both for the original and the homogeneous time series. Effect of the inhomogeneity on long term variations of PDSI is strong: about the half of the significant breaks in the original time series disappear or become totally different from the time series based on homogenised data. All negative (dry) breaks of each month and station, however, occurred in more recent decades of the 20th century, according to both homogeneous and original series.

The dendroecology and climatic impacts for old-growth white pine and hemlock on the extreme slopes of the Berkshire Hills, Massachusetts, U.S.A.

Dendrochronological techniques were used to investigate the dynamics of an old-growth forest on the extreme slope (65%) at Ice Glen Natural Area in southwestern Massachusetts. The site represented a rare opportunity to study the disturbance history, successional development, and responses to climatic variation of an old-growth hemlock (Tsuga canadensis (L.) Carr) - white pine (Pinus strobus L.) - northern hardwood forest in the northeastern United States. Hemlock is the oldest species in the forest, with maximum tree ages of 305-321 years. The maximum ages for white pine and several hardwood species are 170-200 years. There was continuous recruitment of hemlock trees from 1677 to 1948. All of the existing white pine was recruited in the period between 1800 and 1880, forming an unevenly aged population within an unevenly aged, old-growth hemlock canopy. This was associated with large increases in the Master tree-ring chronologies, indicative of major stand-wide disturbances, for both hemlock and white pine. Nearly all of the hardwood species were also recruited between 1800 and 1880. After 1900, there was a dramatic decline in recruitment for all species, including hemlock, probably as a result of intensive deer browsing. White pine and hemlock tree-ring growth during the 20th century was positively correlated with the annual Palmer drought severity index (r = 0.61 and 0.39, respectively). This included reduced growth during periods of low Palmer drought severity index values, the drought years of 1895-1922, and dramatic increases during periods of high Palmer drought severity index values in the 1970s and 1990s. Significant positive and negative correlations of certain monthly Palmer drought severity index values with 20th century tree-ring chronologies also exist for white pine and hemlock using response function analysis. The results of this study suggest that old-growth forests on extreme sites in the eastern United States may be particularly sensitive to direct and indirect allogenic factors and climatic variations and represent an important resource for studying long-term ecological and climatic history.Key words: age structure, radial growth analysis, disturbance, climate, fire, tree rings.

Drought and Regional Hydrologic Variation in the United States: Associations with the El Niño‐Southern Oscillation

Using 94 years of monthly Palmer Drought Severity Index (PDSI) data for 344 climate divisions, this study investigates the hydroclimatic response in the United States to the extreme phases of the Southern Oscillation (El Niño and La Nina). Several regions of coherent response to El Niño‐Southern Oscillation (ENSO) are identified. The strongest relationship between El Niño and extreme drought years is found in the Pacific Northwest. A strong relationship is also noticed in the southern United States, where dry conditions occur consistently during La Niña events. Next, the conditional response in PDSI is evaluated based on the extreme phases of the Southern Oscillation. The PDSI results were compared to similar analyses on 41 years of station temperature, precipitation, and streamflow data. A consistent response is seen in the other hydroclimatic variables, though the most filtered response is seen in PDSI data and streamflow data. The major contribution to the understanding of the ENSO–United States climate relationship is the evaluation of the general form of drought )nd comparison of these results to the fundamental hydrologic processes (precipitation, temperature, and streamflow).

The Use of Time Series Analysis Techniques in Forecasting Meteorological Drought

Using an exponential smoothing procedure and an autoregressive-moving average process; forecasts for the monthly Palmer Drought Severity Index were calculated. The autocorrelation and partial autocorrelation functions of severity index values were used as a starting point for the autoregressive-moving average model selection process. Of the many possible autoregressive-moving average models, the one that was selected provided the best forecasts based on the mean square error. Monthly data for the period 1929–1969 were utilized in a nonlinear least-squares computer routine to arrive at estimated parameter values for the autoregressive-moving average model. Monthly forecasts with a lead time of one month were generated using the exponential smoothing and autoregressive-moving average procedures for the period 1970–1972. These forecasts were compared with the myopic (persistence) forecasts, Xt+1=Xt. The mean square errors of the forecasts were 0.63 for the autoregressive-moving average model, 0.65 for the myopic model, and 0.79 for the exponential smoothing model. From the mean-square-error calculations, it appears that there is no statistically significant difference between the forecasts given by the Box-Jenkins and myopic models; however, the 95% confidence intervals for these two models overlap only slightly during the first part of the forecast period indicating that there may be some advantage to using the Box-Jenkins model instead of the myopic model. Both of these models are superior to the exponential smoothing model. These results demonstrate the usefulness of the relatively new autoregressive-moving average time series analysis procedures.