scholarly journals Correlations between components of the water balance and burned area reveal new insights for predicting forest fire area in the southwest United States

2015 ◽  
Vol 24 (1) ◽  
pp. 14 ◽  
Author(s):  
A. Park Williams ◽  
Richard Seager ◽  
Alison K. Macalady ◽  
Max Berkelhammer ◽  
Michael A. Crimmins ◽  
...  
Keyword(s):  
United States ◽  
Land Cover ◽  
Water Balance ◽  
Climate Models ◽  
Vapour Pressure Deficit ◽  
Cold Season ◽  
Positive Influence ◽  
Burned Area ◽  
Southwest United States ◽  
Complicating Factors

We related measurements of annual burned area in the southwest United States during 1984–2013 to records of climate variability. Within forests, annual burned area correlated at least as strongly with spring–summer vapour pressure deficit (VPD) as with 14 other drought-related metrics, including more complex metrics that explicitly represent fuel moisture. Particularly strong correlations with VPD arise partly because this term dictates the atmospheric moisture demand. Additionally, VPD responds to moisture supply, which is difficult to measure and model regionally due to complex micrometeorology, land cover and terrain. Thus, VPD appears to be a simple and holistic indicator of regional water balance. Coupled with the well-known positive influence of prior-year cold season precipitation on fuel availability and connectivity, VPD may be utilised for burned area forecasts and also to infer future trends, though these are subject to other complicating factors such as land cover change and management. Assuming an aggressive greenhouse gas emissions scenario, climate models predict mean spring–summer VPD will exceed the highest recorded values in the southwest in nearly 40% of years by the middle of this century. These results forewarn of continued increases in burned forest area in the southwest United States, and likely elsewhere, when fuels are not limiting.

scholarly journals A prognostic pollen emissions model for climate models (PECM1.0)

2017 ◽  
Author(s):  
Matthew C. Wozniak ◽  
Allison Steiner
Keyword(s):  
United States ◽  
Land Cover ◽  
Climate Models ◽  
Climate Model ◽  
Vegetation Type ◽  
Global Climate ◽  
The United States ◽  
Global Climate Models ◽  
Pollen Counts ◽  
Surface Pollen

Abstract. We develop a prognostic model of Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus), evergreen needleleaf trees (Cupressaceae, Pinaceae), grasses (Poaceae; C3, C4), and ragweed (Ambrosia). This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in a regional climate model (RegCM4) over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model: (1) using a taxa-specific land cover database, phenology and emission potential, and (2) a PFT-based land cover, phenology and emission potential. The resulting surface concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model, however we note that the PFT-based version provides a useful and climate-flexible emissions model for the general representation of the pollen phenology over the United States.

scholarly journals A prognostic pollen emissions model for climate models (PECM1.0)

2017 ◽  
Vol 10 (11) ◽  
pp. 4105-4127 ◽  
Author(s):  
Matthew C. Wozniak ◽  
Allison L. Steiner
Keyword(s):  
United States ◽  
Land Cover ◽  
Climate Models ◽  
Climate Model ◽  
Vegetation Type ◽  
The United States ◽  
Global Climate Models ◽  
Pollen Counts ◽  
Surface Pollen ◽  
Pollen Concentrations

Abstract. We develop a prognostic model called Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type, and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus), evergreen needleleaf trees (Cupressaceae, Pinaceae), grasses (Poaceae; C3, C4), and ragweed (Ambrosia). This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in the Regional Climate Model version 4 (RegCM4) over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model using (1) a taxa-specific land cover database, phenology, and emission potential, and (2) a plant functional type (PFT) land cover, phenology, and emission potential. The simulated surface pollen concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model; however, we note that the PFT-based version provides a useful and climate-flexible emissions model for the general representation of the pollen phenology over the United States.

scholarly journals The Uneven Response of Different Snow Measures to Human-Induced Climate Warming

2013 ◽  
Vol 26 (12) ◽  
pp. 4148-4167 ◽  
Author(s):  
David W. Pierce ◽  
Daniel R. Cayan
Keyword(s):  
United States ◽  
Water Content ◽  
Climate Warming ◽  
Climate Models ◽  
Linear Trend ◽  
Cold Season ◽  
Winter Precipitation ◽  
Global Climate Models ◽  
Western United States ◽  
Significant Linear Trend

Abstract The effect of human-induced climate warming on different snow measures in the western United States is compared by calculating the time required to achieve a statistically significant linear trend in the different measures, using time series derived from regionally downscaled global climate models. The measures examined include the water content of the spring snowpack, total cold-season snowfall, fraction of winter precipitation that falls as snow, length of the snow season, and fraction of cold-season precipitation retained in the spring snowpack, as well as temperature and precipitation. Various stakeholders may be interested in different sets of these variables. It is found that temperature and the fraction of winter precipitation that falls as snow exhibit significant trends first, followed in 5–10 years by the fraction of cold-season precipitation retained in the spring snowpack, and later still by the water content of the spring snowpack. Change in total cold-season snowfall is least detectable of all the measures, since it is strongly linked to precipitation, which has large natural variability and only a weak anthropogenic trend in the western United States. Averaging over increasingly wider areas monotonically increases the signal-to-noise ratio of the 1950–2025 linear trend from 0.15 to 0.37, depending on the snow measure.

scholarly journals Spatial and Seasonal Variations in Aridification across Southwest North America

2016 ◽  
Vol 29 (12) ◽  
pp. 4637-4649 ◽  
Author(s):  
Shannon M. Jones ◽  
David S. Gutzler
Keyword(s):  
United States ◽  
North America ◽  
Warm Season ◽  
Cold Season ◽  
Base Flow ◽  
First Century ◽  
Strongly Correlated ◽  
Southwest United States ◽  
The North ◽  
Twenty First Century

Abstract Southwestern North America (SWNA) is projected to become drier in the twenty-first century as both precipitation (P) and evaporation (E) rates change with increasing greenhouse gas concentration. The authors diagnose the relative contributions of changes in P and E to the local surface moisture balance (P − E) in cold and warm halves of the year across SWNA. Trends in P − E vary spatially between the arid southern subregion (mostly northern Mexico) and the more temperate northern subregion (southwest United States), although both subregions exhibit a negative trend in P − E (trending toward more arid conditions) in CMIP5 projections for the twenty-first century. The P − E trend is biggest in the cold season, when much of the base flow to rivers in the southwest United States is generated. The downward trend in cold season P − E across SWNA is caused primarily by increasing E in the north and decreasing P in the south. Decreasing P is the primary contributor to modest warm season drying trends in both northern and southern subregions. Also, P accounts for most of the interannual variability in SWNA P − E and is strongly correlated with modes of oceanic natural variability during the cold season. SWNA aridification is therefore most readily distinguished from the region’s large natural climate variability in the cold season in the northern subregion, where the projected temperature-driven increase in E is greater than the projected decrease in P.

scholarly journals RANGES improves satellite-based information and land cover assessments in southwest United States

Eos ◽  
2002 ◽  
Vol 83 (51) ◽  
pp. 601 ◽  
Author(s):  
Jiaguo Qi ◽  
Robin Marsett ◽  
Philip Heilman ◽  
Sharon Bieden-bender ◽  
Susan Moran ◽  
...  
Keyword(s):  
United States ◽  
Land Cover ◽  
Southwest United States
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