Statistical Model for Forecasting Monthly Large Wildfire Events in Western United States

2007 ◽  
Vol 46 (7) ◽  
pp. 1020-1030 ◽  
Author(s):  
Haiganoush K. Preisler ◽  
Anthony L. Westerling
Keyword(s):  
United States ◽  
Statistical Model ◽  
Spatial Scales ◽  
Severity Index ◽  
Fire Danger ◽  
Western United States ◽  
Drought Severity ◽  
Large Fire ◽  
Confidence Bounds ◽  
Regression Techniques

Abstract The ability to forecast the number and location of large wildfire events (with specified confidence bounds) is important to fire managers attempting to allocate and distribute suppression efforts during severe fire seasons. This paper describes the development of a statistical model for assessing the forecasting skills of fire-danger predictors and producing 1-month-ahead wildfire-danger probabilities in the western United States. The method is based on logistic regression techniques with spline functions to accommodate nonlinear relationships between fire-danger predictors and probability of large fire events. Estimates were based on 25 yr of historic fire occurrence data (1980–2004). The model using the predictors monthly average temperature, and lagged Palmer drought severity index demonstrated significant improvement in forecasting skill over historic frequencies (persistence forecasts) of large fire events. The statistical models were particularly amenable to model evaluation and production of probability-based fire-danger maps with prespecified precisions. For example, during the 25 yr of the study for the month of July, an area greater than 400 ha burned in 3% of locations where the model forecast was low; 11% of locations where the forecast was moderate; and 76% of locations where the forecast was extreme. The statistical techniques may be used to assess the skill of forecast fire-danger indices developed at other temporal or spatial scales.

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.

scholarly journals Influence of the Pacific Decadal Oscillation on Winter Precipitation and Drought during Years of Neutral ENSO in the Western United States

2007 ◽  
Vol 22 (1) ◽  
pp. 116-124 ◽  
Author(s):  
Gregory B. Goodrich
Keyword(s):  
United States ◽  
Pacific Northwest ◽  
Pacific Decadal Oscillation ◽  
Severity Index ◽  
Winter Precipitation ◽  
Western United States ◽  
Drought Severity ◽  
The Pacific ◽  
Area Of Influence ◽  
Hydroclimatic Variables

Abstract The influence of the Pacific decadal oscillation (PDO) on important hydroclimatic variables during years of neutral ENSO for 84 climate divisions in the western United States is analyzed from 1925 to 1998. When the 34 neutral ENSO years are split by cold (12 yr) and warm (22 yr) PDOs, the resulting winter precipitation patterns are spatially similar to those that occur during years of La Niña–cold PDO and, to a lesser extent, years of El Niño–warm PDO, respectively, although the characteristic ENSO dipole is not evident. The PDO influence is similar when the winter Palmer drought severity index is analyzed, although the core area of influence moves from the Southwest to the northern Rockies. Correlations between Niño-3.4 SSTs and the hydroclimatic variables reverse sign when the neutral ENSO years are split by PDO phase. The greatest difference between correlations occurs in the characteristic dipole between the Pacific Northwest and the desert Southwest. Since seasonal forecast guidance based on ENSO conditions in the tropical Pacific often yields a forecast of “equal chances” during years of neutral ENSO, forecasters may be able to improve their forecasts for the southwestern United States depending on if the PDO is known to be in the cold (drier than normal) or warm (wetter than normal) phase. However, this can be difficult to implement considering the current uncertainty of the phase of the PDO.

scholarly journals Variability of Cloudiness over Mountain Terrain in the Western United States

2017 ◽  
Vol 18 (5) ◽  
pp. 1227-1245 ◽  
Author(s):  
Edwin Sumargo ◽  
Daniel R. Cayan
Keyword(s):  
United States ◽  
Large Scale ◽  
Spatial Scales ◽  
High Elevation ◽  
Empirical Orthogonal Functions ◽  
Western United States ◽  
Spatial And Temporal Variability ◽  
Regional Patterns ◽  
Cloud Albedo

Abstract This study investigates the spatial and temporal variability of cloudiness across mountain zones in the western United States. Daily average cloud albedo is derived from a 19-yr series (1996–2014) of half-hourly Geostationary Operational Environmental Satellite (GOES) images. During springtime when incident radiation is active in driving snowmelt–runoff processes, the magnitude of daily cloud variations can exceed 50% of long-term averages. Even when aggregated over 3-month periods, cloud albedo varies by ±10% of long-term averages in many locations. Rotated empirical orthogonal functions (REOFs) of daily cloud albedo anomalies over high-elevation regions of the western conterminous United States identify distinct regional patterns, wherein the first five REOFs account for ~67% of the total variance. REOF1 is centered over Northern California and Oregon and is pronounced between November and March. REOF2 is centered over the interior northwest and is accentuated between March and July. Each of the REOF/rotated principal components (RPC) modes associates with anomalous large-scale atmospheric circulation patterns and one or more large-scale teleconnection indices (Arctic Oscillation, Niño-3.4, and Pacific–North American), which helps to explain why anomalous cloudiness patterns take on regional spatial scales and contain substantial variability over seasonal time scales.

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

2000 ◽  
Vol 78 (7) ◽  
pp. 851-861 ◽  
Author(s):  
Marc D Abrams ◽  
Saskia van de Gevel ◽  
Ryan C Dodson ◽  
Carolyn A Copenheaver
Keyword(s):  
United States ◽  
20Th Century ◽  
Tree Ring ◽  
Palmer Drought Severity Index ◽  
Severity Index ◽  
Drought Severity ◽  
White Pine ◽  
Old Growth ◽  
Hardwood Species ◽  
Drought Severity Index

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.

scholarly journals The relationship of large fire occurrence with drought and fire danger indices in the western USA, 1984–2008: the role of temporal scale

2013 ◽  
Vol 22 (7) ◽  
pp. 894 ◽  
Author(s):  
Karin L. Riley ◽  
John T. Abatzoglou ◽  
Isaac C. Grenfell ◽  
Anna E. Klene ◽  
Faith Ann Heinsch
Keyword(s):  
Primary Objective ◽  
Fire Danger ◽  
Drought Severity ◽  
Monthly Precipitation ◽  
Fire Occurrence ◽  
Large Fire ◽  
Short Term ◽  
Area Burned ◽  
Standardised Precipitation Index ◽  
The Relationship

The relationship between large fire occurrence and drought has important implications for fire prediction under current and future climates. This study’s primary objective was to evaluate correlations between drought and fire-danger-rating indices representing short- and long-term drought, to determine which had the strongest relationships with large fire occurrence at the scale of the western United States during the years 1984–2008. We combined 4–8-km gridded drought and fire-danger-rating indices with information on fires greater than 404.7ha (1000acres). To account for differences in indices across climate and vegetation assemblages, indices were converted to percentile conditions for each pixel. Correlations between area burned and short-term indices Energy Release Component and monthly precipitation percentile were strong (R2=0.92 and 0.89), as were correlations between number of fires and these indices (R2=0.94 and 0.93). As the period of time tabulated by indices lengthened, correlations with fire occurrence weakened: Palmer Drought Severity Index and 24-month Standardised Precipitation Index percentile showed weak correlations with area burned (R2=0.25 and –0.01) and number of large fires (R2=0.3 and 0.01). These results indicate associations between short-term indices and moisture content of dead fuels, the primary carriers of surface fire.

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.

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