scholarly journals Understanding the Sensitivity of Different Drought Metrics to the Drivers of Drought under Increased Atmospheric CO2

2011 ◽  
Vol 12 (6) ◽  
pp. 1378-1394 ◽  
Author(s):  
Eleanor J. Burke
Keyword(s):  
Soil Moisture ◽  
Standard Deviation ◽  
Climate Model ◽  
Relative Sensitivity ◽  
Severity Index ◽  
Atmospheric Co2 ◽  
Drought Severity ◽  
Available Energy ◽  
The Mean ◽  
Hadley Centre

Abstract A perturbed physics Hadley Centre climate model ensemble was used to study changes in drought on doubling atmospheric CO2. The drought metrics analyzed were based on 1) precipitation anomalies, 2) soil moisture anomalies, and 3) the Palmer drought severity index (PDSI). Drought was assumed to occur 17% of the time under single CO2. On doubling CO2, in general, PDSI drought occurs more often than soil moisture drought, which occurs more often than precipitation drought. This paper explores the relative sensitivity of each drought metric to changes in the main drivers of drought, namely precipitation and available energy. Drought tends to increase when the mean precipitation decreases, the mean available energy increases, the standard deviation of precipitation increases, and the standard deviation of available energy decreases. Simple linear approximations show that the sensitivity of drought to changes in mean precipitation is similar for the three different metrics. However, the sensitivity of drought to changes in the mean available energy (which is projected to increase under increased atmospheric CO2) is highly dependent on metric: with PDSI drought the most sensitive, soil moisture less sensitive, and precipitation independent of available energy. Drought metrics are only slightly sensitive to changes in the variability of the drivers. An additional driver of drought is the response of plants to increased CO2. This process reduces evapotranspiration and increases soil moisture, and generally causes less soil moisture drought. In contrast, the associated increase in available energy generally causes an increase in PDSI drought. These differing sensitivities need to be taken into consideration when developing adaptation strategies.

scholarly journals Evaluating Uncertainties in the Projection of Future Drought

2008 ◽  
Vol 9 (2) ◽  
pp. 292-299 ◽  
Author(s):  
Eleanor J. Burke ◽  
Simon J. Brown
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Climate Modeling ◽  
Standardized Precipitation Index ◽  
Severity Index ◽  
Ensemble Member ◽  
Drought Indices ◽  
Drought Severity ◽  
Hadley Centre ◽  
The Standardized Precipitation Index

Abstract The uncertainty in the projection of future drought occurrence was explored for four different drought indices using two model ensembles. The first ensemble expresses uncertainty in the parameter space of the third Hadley Centre climate model, and the second is a multimodel ensemble that additionally expresses structural uncertainty in the climate modeling process. The standardized precipitation index (SPI), the precipitation and potential evaporation anomaly (PPEA), the Palmer drought severity index (PDSI), and the soil moisture anomaly (SMA) were derived for both a single CO2 (1×CO2) and a double CO2 (2×CO2) climate. The change in moderate drought, defined by the 20th percentile of the relevant 1×CO2 distribution, was calculated. SPI, based solely on precipitation, shows little change in the proportion of the land surface in drought. All the other indices, which include a measure of the atmospheric demand for moisture, show a significant increase with an additional 5%–45% of the land surface in drought. There are large uncertainties in regional changes in drought. Regions where the precipitation decreases show a reproducible increase in drought across ensemble members and indices. In other regions the sign and magnitude of the change in drought is dependent on index definition and ensemble member, suggesting that the selection of appropriate drought indices is important for impact studies.

Flash Drought Characteristics by Different Severities in Humid Subtropical Basins: A Case Study in the Gan River Basin, China

2021 ◽  
pp. 1-44
Author(s):  
Yuqing Zhang ◽  
Qinglong You ◽  
Guangxiong Mao ◽  
Changchun Chen ◽  
Xin Li ◽  
...  
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Vapour Pressure Deficit ◽  
Severity Index ◽  
Drought Severity ◽  
Rapid Decline ◽  
Drought Risk ◽  
Drought Event ◽  
Drought Period ◽  
Drought Intensity

AbstractIt is essential to assess flash drought risk based on a reliable flash drought intensity (severity) index incorporating comprehensive information of the rapid decline (“flash”) in soil moisture towards drought conditions and soil moisture thresholds belonging to the “drought” category. In this study, we used the Gan River Basin as an example to define a flash drought intensity index that can be calculated for individual time steps (pentads) during a flash drought period over a given grid (or station). The severity of a complete flash drought event is the sum of the intensity values during the flash drought. We explored the spatial and temporal characteristics of flash droughts with different grades based on their respective severities. The results show that decreases in total cloud cover, precipitation, and relative humidity, as well as increases in 500 hPa geopotential height, convective inhibition, temperature, vapour pressure deficit, and wind speed can create favorable conditions for the occurrence of flash droughts. Although flash droughts are relatively frequent in the central and southern parts of the basin, the severity is relatively high in the northern part of the basin due to longer duration. Flash drought severity shows a slightly downward trend due to decreases in frequency, duration, and intensity from 1961 to 2018. Extreme and exceptional flash droughts decrease significantly while moderate and severe flash droughts trend slightly upward. Flash drought severity appears to be more affected by the interaction between duration and intensity as the grade increases from mild to severe. The frequency and duration of flash droughts are higher in July to October. The southern part of the basin is more prone to moderate and severe flash droughts, while the northern parts of the basin are more vulnerable to extreme and exceptional flash droughts due to longer durations and greater severities than other parts. Moderate, severe, extreme, and exceptional flash droughts occurred approximately every 3-6, 5-15, 10-50, and 30-200 year intervals, respectively, based on the copula analysis.

scholarly journals Projected Spatiotemporal Dynamics of Drought under Global Warming in Central Asia

2019 ◽  
Vol 11 (16) ◽  
pp. 4421 ◽  
Author(s):  
Zhang ◽  
Zhao ◽  
Ma ◽  
Brindha ◽  
Han ◽  
...  
Keyword(s):  
Global Warming ◽  
Central Asia ◽  
Social Life ◽  
Climate Model ◽  
Severity Index ◽  
Drought Severity ◽  
Warming Scenario ◽  
Intercomparison Project ◽  
Marked Decline ◽  
Human Social Life

Drought, one of the most common natural disasters that have the greatest impact on human social life, has been extremely challenging to accurately assess and predict. With global warming, it has become more important to make accurate drought predictions and assessments. In this study, based on climate model data provided by the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), we used the Palmer Drought Severity Index (PDSI) to analyze and project drought characteristics and their trends under two global warming scenarios—1.5 °C and 2.0 °C—in Central Asia. The results showed a marked decline in the PDSI in Central Asia under the influence of global warming, indicating that the drought situation in Central Asia would further worsen under both warming scenarios. Under the 1.5 °C warming scenario, the PDSI in Central Asia decreased first and then increased, and the change time was around 2080, while the PDSI values showed a continuous decline after 2025 in the 2.0 °C warming scenario. Under the two warming scenarios, the spatial characteristics of dry and wet areas in Central Asia are projected to change significantly in the future. In the 1.5 °C warming scenario, the frequency of drought and the proportion of arid areas in Central Asia were significantly higher than those under the 2.0 °C warming scenario. Using the Thornthwaite (TH) formula to calculate the PDSI produced an overestimation of drought, and the Penman–Monteith (PM) formula is therefore recommended to calculate the index.

scholarly journals Drought Analysis in the Yellow River Basin Based on a Short-Scalar Palmer Drought Severity Index

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1526 ◽  
Author(s):  
Ye Zhu ◽  
Yi Liu ◽  
Xieyao Ma ◽  
Liliang Ren ◽  
Vijay Singh
Keyword(s):  
Soil Moisture ◽  
Time Scale ◽  
Palmer Drought Severity Index ◽  
Yellow River ◽  
Severity Index ◽  
Yellow River Basin ◽  
Drought Severity ◽  
The Yellow River ◽  
The Yellow River Basin ◽  
Drought Severity Index

Focusing on the shortages of moisture estimation and time scale in the self-calibrating Palmer drought severity index (scPDSI), this study proposed a new Palmer variant by introducing the Variable Infiltration Capacity (VIC) model in hydrologic accounting module, and modifying the standardization process to make the index capable for monitoring droughts at short time scales. The performance of the newly generated index was evaluated over the Yellow River Basin (YRB) during 1961–2012. For time scale verification, the standardized precipitation index (SPI), and standardized precipitation evapotranspiration index (SPEI) at a 3-month time scale were employed. Results show that the new Palmer variant is highly correlated with SPI and SPEI, combined with a more stable behavior in drought frequency than original scPDSI. For drought trend detection, this new index is more inclined to reflect comprehensive moisture conditions and reveals a different spatial pattern from SPI and SPEI in winter. Besides, two remote sensing products of soil moisture and vegetation were also employed for comparison. Given their general consistent behaviors in monitoring the spatiotemporal evolution of the 2000 drought, it is suggested that the new Palmer variant is a good indicator for monitoring soil moisture variation and the dynamics of vegetation growth.

scholarly journals Commonly Used Drought Indices as Indicators of Soil Moisture in China

2015 ◽  
Vol 16 (3) ◽  
pp. 1397-1408 ◽  
Author(s):  
Hongshuo Wang ◽  
Jeffrey C. Rogers ◽  
Darla K. Munroe
Keyword(s):  
Soil Moisture ◽  
Time Scales ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Severity Index ◽  
Agricultural Drought ◽  
Weather Data ◽  
Drought Indices ◽  
Drought Severity ◽  
Better Than

Abstract Soil moisture shortages adversely affecting agriculture are significantly associated with meteorological drought. Because of limited soil moisture observations with which to monitor agricultural drought, characterizing soil moisture using drought indices is of great significance. The relationship between commonly used drought indices and soil moisture is examined here using Chinese surface weather data and calculated station-based drought indices. Outside of northeastern China, surface soil moisture is more affected by drought indices having shorter time scales while deep-layer soil moisture is more related on longer index time scales. Multiscalar drought indices work better than drought indices from two-layer bucket models. The standardized precipitation evapotranspiration index (SPEI) works similarly or better than the standardized precipitation index (SPI) in characterizing soil moisture at different soil layers. In most stations in China, the Z index has a higher correlation with soil moisture at 0–5 cm than the Palmer drought severity index (PDSI), which in turn has a higher correlation with soil moisture at 90–100-cm depth than the Z index. Soil bulk density and soil organic carbon density are the two main soil properties affecting the spatial variations of the soil moisture–drought indices relationship. The study may facilitate agriculture drought monitoring with commonly used drought indices calculated from weather station data.

Long lead statistical forecasts of area burned in western U.S. wildfires by ecosystem province

2002 ◽  
Vol 11 (4) ◽  
pp. 257 ◽  
Author(s):  
Anthony L. Westerling ◽  
Alexander Gershunov ◽  
Daniel R. Cayan ◽  
Tim P. Barnett
Keyword(s):  
Soil Moisture ◽  
Large Scale ◽  
Forecast Model ◽  
Severity Index ◽  
Fire Season ◽  
Drought Severity ◽  
Canonical Correlations ◽  
Area Burned ◽  
Wildfire Season ◽  
Random Guess

A statistical forecast methodology exploits large-scale patterns in monthly U.S. Climatological Division Palmer Drought Severity Index (PDSI) values over a wide region and several seasons to predict area burned in western U.S. wildfires by ecosystem province a season in advance. The forecast model, which is based on canonical correlations, indicates that a few characteristic patterns determine predicted wildfire season area burned. Strong negative associations between anomalous soil moisture (inferred from PDSI) immediately prior to the fire season and area burned dominate in most higher elevation forested provinces, while strong positive associations between anomalous soil moisture a year prior to the fire season and area burned dominate in desert and shrub and grassland provinces. In much of the western U.S., above- and below-normal fire season forecasts were successful 57% of the time or better, as compared with a 33% skill for a random guess, and with a low probability of being surprised by a fire season at the opposite extreme of that forecast.

scholarly journals Moisture and Temperature Covariability over the Southeastern Tibetan Plateau during the Past Nine Centuries

2020 ◽  
Vol 33 (15) ◽  
pp. 6583-6598
Author(s):  
Jianglin Wang ◽  
Bao Yang ◽  
Fredrik Charpentier Ljungqvist
Keyword(s):  
Tibetan Plateau ◽  
Climate Model ◽  
Severity Index ◽  
Early Summer ◽  
Convective Precipitation ◽  
Drought Severity ◽  
The Tibetan Plateau ◽  
Low Frequencies ◽  
The Past ◽  
Spatial Coverage

AbstractAccurate projections of moisture variability across the Tibetan Plateau (TP) are crucial for managing regional water resources, ecosystems, and agriculture in densely populated downstream regions. Our understanding of how moisture conditions respond to increasing temperatures over the TP is still limited, due to the short length of instrumental data and the limited spatial coverage of high-resolution paleoclimate proxy records in this region. This study presents a new, early-summer (May–June) self-calibrating Palmer drought severity index (scPDSI) reconstruction for the southeastern TP (SETP) covering 1135–2010 CE using 14 tree-ring records based on 1669 individual width sample series. The new reconstruction reveals that the SETP experienced the longest period of pluvial conditions in 1154–75 CE, and the longest droughts during the periods 1262–80 and 1958–76 CE. The scPDSI reconstruction shows stable and significant in-phase relationships with temperature at both high and low frequencies throughout the past 900 years. This supports the hypothesis that climatic warming may increase moisture by enhancing moisture recycling and convective precipitation over the SETP; it is also consistent with climate model projections of wetter conditions by the late twenty-first century in response to global warming.

scholarly journals The impact of climate mitigation on projections of future drought

2013 ◽  
Vol 17 (6) ◽  
pp. 2339-2358 ◽  
Author(s):  
I. H. Taylor ◽  
E. Burke ◽  
L. McColl ◽  
P. D. Falloon ◽  
G. R. Harris ◽  
...  
Keyword(s):  
Climate Model ◽  
Severity Index ◽  
Baseline Period ◽  
Drought Indices ◽  
Drought Severity ◽  
Climate Mitigation ◽  
Climate Projections ◽  
Standardised Precipitation Index ◽  
The Impact ◽  
Future Emissions

Abstract. Drought is a cumulative event, often difficult to define and involving wide-reaching consequences for agriculture, ecosystems, water availability, and society. Understanding how the occurrence of drought may change in the future and which sources of uncertainty are dominant can inform appropriate decisions to guide drought impacts assessments. Our study considers both climate model uncertainty associated with future climate projections, and future emissions of greenhouse gases (future scenario uncertainty). Four drought indices (the Standardised Precipitation Index (SPI), Soil Moisture Anomaly (SMA), the Palmer Drought Severity Index (PDSI) and the Standardised Runoff Index (SRI)) are calculated for the A1B and RCP2.6 future emissions scenarios using monthly model output from a 57-member perturbed parameter ensemble of climate simulations of the HadCM3C Earth System model, for the baseline period 1961–1990, and the period 2070–2099 ("the 2080s"). We consider where there are statistically significant increases or decreases in the proportion of time spent in drought in the 2080s compared to the baseline. Despite the large range of uncertainty in drought projections for many regions, projections for some regions have a clear signal, with uncertainty associated with the magnitude of change rather than direction. For instance, a significant increase in time spent in drought is generally projected for the Amazon, Central America and South Africa whilst projections for northern India consistently show significant decreases in time spent in drought. Whilst the patterns of changes in future drought were similar between scenarios, climate mitigation, represented by the RCP2.6 scenario, tended to reduce future changes in drought. In general, climate mitigation reduced the area over which there was a significant increase in drought but had little impact on the area over which there was a significant decrease in time spent in drought.

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