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 Prediction of Summer Maximum and Minimum Temperature over the Central and Western United States: The Roles of Soil Moisture and Sea Surface Temperature

2006 ◽  
Vol 19 (8) ◽  
pp. 1407-1421 ◽  
Author(s):  
Eric J. Alfaro ◽  
Alexander Gershunov ◽  
Daniel Cayan
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Short Range ◽  
Large Scale ◽  
Severity Index ◽  
Time Frame ◽  
Western United States ◽  
Drought Severity ◽  
Explanatory Variables ◽  
Predictive Skill

Abstract A statistical model based on canonical correlation analysis (CCA) was used to explore climatic associations and predictability of June–August (JJA) maximum and minimum surface air temperatures (Tmax and Tmin) as well as the frequency of Tmax daily extremes (Tmax90) in the central and western United States (west of 90°W). Explanatory variables are monthly and seasonal Pacific Ocean SST (PSST) and the Climate Division Palmer Drought Severity Index (PDSI) during 1950–2001. Although there is a positive correlation between Tmax and Tmin, the two variables exhibit somewhat different patterns and dynamics. Both exhibit their lowest levels of variability in summer, but that of Tmax is greater than Tmin. The predictability of Tmax is mainly associated with local effects related to previous soil moisture conditions at short range (one month to one season), with PSST providing a secondary influence. Predictability of Tmin is more strongly influenced by large-scale (PSST) patterns, with PDSI acting as a short-range predictive influence. For both predictand variables (Tmax and Tmin), the PDSI influence falls off markedly at time leads beyond a few months, but a PSST influence remains for at least two seasons. The maximum predictive skill for JJA Tmin, Tmax, and Tmax90 is from May PSST and PDSI. Importantly, skills evaluated for various seasons and time leads undergo a seasonal cycle that has maximum levels in summer. At the seasonal time frame, summer Tmax prediction skills are greatest in the Midwest, northern and central California, Arizona, and Utah. Similar results were found for Tmax90. In contrast, Tmin skill is spread over most of the western region, except for clusters of low skill in the northern Midwest and southern Montana, Idaho, and northern Arizona.

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 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 Juniper Tree-Ring Data from the Kuramin Range (Northern Tajikistan) Reveals Changing Summer Drought Signals in Western Central Asia

Forests ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 505 ◽  
Author(s):  
Feng Chen ◽  
Tongwen Zhang ◽  
Andrea Seim ◽  
Shulong Yu ◽  
Ruibo Zhang ◽  
...  
Keyword(s):  
Central Asia ◽  
Tree Ring ◽  
Large Scale ◽  
Southern Oscillation ◽  
Severity Index ◽  
Drought Severity ◽  
Summer Drought ◽  
Tree Ring Chronology ◽  
Tree Ring Data ◽  
June July

Coniferous forests cover the mountains in many parts of Central Asia and provide large potentials for dendroclimatic studies of past climate variability. However, to date, only a few tree-ring based climate reconstructions exist from this region. Here, we present a regional tree-ring chronology from the moisture-sensitive Zeravshan juniper (Juniperus seravschanica Kom.) from the Kuramin Range (Tajikistan) in western Central Asia, which is used to reveal past summer drought variability from 1650 to 2015 Common Era (CE). The chronology accounts for 40.5% of the variance of the June–July self-calibrating Palmer Drought Severity Index (scPDSI) during the instrumental period (1901 to 2012). Seven dry periods, including 1659–1696, 1705–1722, 1731–1741, 1758–1790, 1800–1842, 1860–1875, and 1931–1987, and five wet periods, including 1742–1752, 1843–1859, 1876–1913, 1921–1930, and 1988–2015, were identified. Good agreements between drought records from western and eastern Central Asia suggest that the PDSI records retain common drought signals and capture the regional dry/wet periods of Central Asia. Moreover, the spectral analysis indicates the existence of centennial (128 years), decadal (24.3 and 11.4 years), and interannual (8.0, 3.6, 2.9, and 2.0 years) cycles, which may be linked with climate forces, such as solar activity and El Niño-Southern Oscillation (ENSO). The analysis between the scPDSI reconstruction and large-scale atmospheric circulations during the reconstructed extreme dry and wet years can provide information about the linkages of extremes in our scPDSI record with the large-scale ocean–atmosphere–land circulation systems.

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.

scholarly journals Malawi’s Shire River Fluctuations and Climate

2014 ◽  
Vol 15 (5) ◽  
pp. 2039-2049 ◽  
Author(s):  
Mark R. Jury
Keyword(s):  
Large Scale ◽  
River Flow ◽  
Potential Evapotranspiration ◽  
Global Climate ◽  
Severity Index ◽  
Early Warning Systems ◽  
Climatic Research Unit ◽  
Climate Index ◽  
Drought Severity ◽  
High Pressure Cell

Abstract Hydrological fluctuations of Malawi’s Shire River and climatic drivers are studied for a range of time and space scales. The annual cycles of basin rainfall and river flow peak in summer and autumn, respectively. Satellite and model products at <50-km resolution resolve the water deficit in this narrow valley. The leading climate index fitting Shire River flow anomalies is the Climatic Research Unit (CRU) Palmer drought severity index, based on interpolated gauge rainfall minus Penman–Monteith potential evapotranspiration. Climate variables anticipate lake level changes by 2 months, while weather variables anticipate river flow surges by 2 days. Global climate patterns related to wet years include a Pacific La Niña cool phase and low pressure over northeastern Africa. Shire River floods coincide with a cyclonic looping wind pattern that amplifies the equatorial trough and draws monsoon flow from Tanzania. Hot spells are common in spring: daytime surface temperatures can reach 60°C causing rapid desiccation. An anticyclonic high pressure cell promotes evaporation losses of ~20 mm day−1 over brief periods. Flood and drought in Malawi are shown to be induced by the large-scale atmospheric circulation and rainfall in the surrounding highlands. Hence, early warning systems should consider satellite and radar coverage of the entire basin.

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 How Wet and Dry Spells Evolve across the Conterminous United States Based on 555 Years of Paleoclimate Data

2018 ◽  
Vol 31 (16) ◽  
pp. 6633-6647 ◽  
Author(s):  
Michelle Ho ◽  
Upmanu Lall ◽  
Edward R. Cook
Keyword(s):  
United States ◽  
Large Scale ◽  
Viterbi Algorithm ◽  
Severity Index ◽  
Climate Forcing ◽  
Drought Severity ◽  
Spatial Features ◽  
Dry Spells ◽  
Temporal And Spatial ◽  
Wet Spells

Abstract Evolving patterns of droughts and wet spells in the conterminous United States (CONUS) are examined over 555 years using a tree-ring-based paleoclimate reconstruction of the modified Palmer drought severity index (PDSI). A hidden Markov model is used as an unsupervised method of classifying climate states and quantifying the temporal evolution from one state to another. Modeling temporal variability in spatial patterns of drought and wet spells provides the ability to objectively assess and simulate historical persistence and recurrence of similar patterns. The Viterbi algorithm reveals the probable sequence of states through time, enabling an examination of temporal and spatial features and associated large-scale climate forcing. Distinct patterns of sea surface temperature that are known to enhance or inhibit rainfall are associated with some states. Using the current CONUS PDSI field the model can be used to simulate the space–time PDSI pattern over the next few years, or unconditional simulations can be used to derive estimates of spatially concurrent PDSI patterns and their persistence and intensity across the CONUS.

scholarly journals Evaluating the Performance of Palmer Drought Severity Index (PDSI) In Various Vegetation Regions of the Ethiopian Highlands

2021 ◽  
Vol 4 (2) ◽  
pp. 14-31
Author(s):  
Polina Lemenkova
Keyword(s):  
Soil Moisture ◽  
Wind Speed ◽  
Palmer Drought Severity Index ◽  
Environmental Parameters ◽  
Severity Index ◽  
Drought Severity ◽  
Topographic Effects ◽  
Vegetation Monitoring ◽  
Ethiopian Highlands ◽  
Drought Severity Index

Abstract This paper focuses on the environment of Ethiopia, a country highly sensitive to droughts severely affecting vegetation. Vegetation monitoring of Ethiopian Highlands requires visualization of environmental parameters to assess droughts negatively influencing agricultural sustainable management of crops. Therefore, this study presented mapping of several climate and environmental variables including Palmer Drought Severity Index (PDSI). The data were visualized and interpreted alongside the topographic data to evaluate the environmental conditions for vegetation. The datasets included WorldClim and GEBCO and Digital Chart of the World (DCW). Research has threefold objectives: i) environmental mapping; ii) technical cartographic scripting; iii) data processing. Following variables were visualized on seven new maps: 1) topography; 2) soil moisture; 3) T °C minimum; 4) T °C maximum; 5) Wind speed; 6) Precipitation; 7) Palmer Drought Severity Index (PDSI). New high-resolution thematic environmental maps are presented and the utility of GMT for mapping multi-source datasets is described. With varying degrees of soil moisture (mean value of 15.0), min T°C (−1.8°C to 24°C), max T°C (14.4°C to 40.2°C) and wind speed (0.1 to 6.1 m/s), the maps demonstrate the variability of the PDSI fields over the country area (from −11.7 to 2.3) induced by the complex sum of these variables and intensified by the topographic effects notable over the Ethiopian Highlands which can be used for vegetation analysis. The paper presents seven new maps and contributes to the environmental studies of Ethiopia.

Sign in / Sign up

Export Citation Format

Share Document