scholarly journals Predicted Changes in the Frequency of Extreme Precipitable Water Vapor Events

2015 ◽  
Vol 28 (18) ◽  
pp. 7057-7070 ◽  
Author(s):  
Jacola Roman ◽  
Robert Knuteson ◽  
Steve Ackerman ◽  
Hank Revercomb
Keyword(s):  
United States ◽  
Water Vapor ◽  
Climate Models ◽  
Global Climate ◽  
Precipitable Water ◽  
Heavy Precipitation ◽  
Precipitable Water Vapor ◽  
Global Climate Models ◽  
Eastern United States ◽  
Mean Trend

Abstract A high amount of precipitable water vapor (PWV) is a necessary requirement for heavy precipitation and extreme flooding events. This study determined the predicted shift in extreme PWV from a set of CMIP5 global climate models using the highest emission scenario over three different spatial resolutions (global, zonal, and regional) and four different case regions (India, China, Europe, and eastern United States). For the globe, the frequency of the extreme 1% of PWV events between 2006 and 2030 was predicted to increase by a median factor (herein called an X factor) of 9 by 2075–99. Areas of high PWV, like the tropics, tended toward higher factors. The annual median X factor for India, China, central Europe, and the eastern United States was 24, 17, 15, and 16, respectively. For India, the minimum median X factor was 10 during December–February (DJF) and the maximum was 48 during June–August (JJA). In China, the minimum median X factor (8) occurred during DJF, and the maximum was 42 in JJA. For Europe, DJF and September–November (SON) had the smallest median X factor of 15, whereas JJA had the largest median X factor of 30. The smallest median X factor for the eastern United States (11) occurred during March–May (MAM), whereas the largest median X factor (32) occurred in JJA. Regional X factors were significantly larger than global (1.5–2 times larger), illustrating the importance of regional assessments of extreme PWV. The mean trend in the extreme PWV was approximately linear for all regions with a slope of about 3% decade−1. Observations for 10 (20) years are needed for the extreme PWV to change by an amount that exceeds a 3% (5%) measurement error.

scholarly journals Using AIRS to assess the precipitable water vapor in global climate models (GCMs) with regional validation from SuomiNet

2013 ◽  
Author(s):  
Jacola Roman ◽  
Robert Knuteson ◽  
Steve Ackerman ◽  
David Tobin ◽  
William Smith ◽  
...  
Keyword(s):  
Water Vapor ◽  
Climate Models ◽  
Global Climate ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Global Climate Models

scholarly journals Climate change projected to reduce prescribed burning opportunities in the south-eastern United States

2020 ◽  
Vol 29 (9) ◽  
pp. 764
Author(s):  
John A. Kupfer ◽  
Adam J. Terando ◽  
Peng Gao ◽  
Casey Teske ◽  
J. Kevin Hiers
Keyword(s):  
United States ◽  
Prescribed Burning ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Global Climate ◽  
Management Strategies ◽  
Global Climate Models ◽  
Eastern United States ◽  
The South ◽  
South Eastern

Prescribed burning is a critical tool for managing wildfire risks and meeting ecological objectives, but its safe and effective application requires that specific meteorological criteria (a ‘burn window’) are met. Here, we evaluate the potential impacts of projected climatic change on prescribed burning in the south-eastern United States by applying a set of burn window criteria that capture temperature, relative humidity and wind speed to projections from an ensemble of Global Climate Models under two greenhouse gas emission scenarios. Regionally, the percentage of suitable days for burning changes little during winter but decreases substantially in summer owing to rising temperatures by the end of the 21st century compared with historical conditions. Management implications of such changes for six representative land management units include seasonal shifts in burning opportunities from summer to cool-season months, but with considerable regional variation. We contend that the practical constraints of rising temperatures on prescribed fire activities represent a significant future challenge and show that even meeting basic burn criteria (as defined today) will become increasingly difficult over time, which speaks to the need for adaptive management strategies to prepare for such changes.

scholarly journals Time-to-Detect Trends in Precipitable Water Vapor with Varying Measurement Error

2014 ◽  
Vol 27 (21) ◽  
pp. 8259-8275 ◽  
Author(s):  
Jacola Roman ◽  
Robert Knuteson ◽  
Steve Ackerman
Keyword(s):  
Water Vapor ◽  
Measurement Error ◽  
Measurement Errors ◽  
Climate Model ◽  
Global Climate ◽  
Spatial Scales ◽  
Global Climate Model ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Eastern United States

Abstract This study determined the theoretical time-to-detect (TTD) global climate model (GCM) precipitable water vapor (PWV) 100-yr trends when realistic measurement errors are considered. Global trends ranged from 0.055 to 0.072 mm yr−1 and varied minimally from season to season. Global TTDs with a 0% measurement error ranged from 3.0 to 4.8 yr, while a 5% measurement error increased the TTD by almost 6 times, ranging from 17.6 to 22.0 yr. Zonal trends were highest near the equator; however, zonal TTDs were nearly independent of latitude when 5% measurement error was included. Zonal TTDs are significantly reduced when the trends are analyzed by season. Regional trends (15° × 30°) show TTDs close to those in the 15° latitude zones (15° × 360°). Detailed case study analysis of four selected regions with high population density—eastern United States, Europe, China, and India—indicated that trend analysis on regional spatial scales may provide the most timely information regarding highly populated regions when comparing detection time scales to global and zonal analyses.

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 Simulating Hydrological Drought Properties at Different Spatial Units in the United States Based on Wavelet–Bayesian Regression Approach

2012 ◽  
Vol 16 (17) ◽  
pp. 1-23 ◽  
Author(s):  
Ashok K. Mishra ◽  
Vijay P. Singh
Keyword(s):  
United States ◽  
Regression Model ◽  
Climate Models ◽  
Global Climate ◽  
The United States ◽  
Hydrological Drought ◽  
Bayesian Regression ◽  
Global Climate Models ◽  
Meteorological Variables ◽  
The Relationship

Abstract Because of their stochastic nature, droughts vary in space and time, and therefore quantifying droughts at different time units is important for water resources planning. The authors investigated the relationship between meteorological variables and hydrological drought properties using the Palmer hydrological drought index (PHDI). Twenty different spatial units were chosen from the unit of a climatic division to a regional unit across the United States. The relationship between meteorological variables and PHDI was investigated using a wavelet–Bayesian regression model, which enhances the modeling strength of a simple Bayesian regression model. Further, the wavelet–Bayesian regression model was tested for the predictability of global climate models (GCMs) to simulate PHDI, which will also help understand their role for downscaling purposes.

Moisture flux convergence in regional and global climate models: Implications for droughts in the southwestern United States under climate change

2012 ◽  
Vol 39 (9) ◽  
pp. n/a-n/a ◽  
Author(s):  
Yanhong Gao ◽  
L. Ruby Leung ◽  
Eric P. Salathé ◽  
Francina Dominguez ◽  
Bart Nijssen ◽  
...  
Keyword(s):  
Climate Change ◽  
United States ◽  
Climate Models ◽  
Global Climate ◽  
Moisture Flux ◽  
Global Climate Models ◽  
Southwestern United States ◽  
Moisture Flux Convergence

scholarly journals A Method for Detection and Attribution of Regional Precipitation Change Using Granger Causality Application to the United States Historical Record

2021 ◽  
Author(s):  
Mark Risser ◽  
William Collins ◽  
Michael Wehner ◽  
Travis O'Brien ◽  
Christopher Paciorek ◽  
...  
Keyword(s):  
United States ◽  
Climate Models ◽  
Water Cycle ◽  
Global Climate ◽  
Internal Variability ◽  
The United States ◽  
Historical Record ◽  
Global Climate Models ◽  
Detection And Attribution ◽  
Observational Uncertainty

Abstract Despite the emerging influence of anthropogenic climate change on the global water cycle, at regional scales the combination of observational uncertainty, large internal variability, and modeling uncertainty undermine robust statements regarding the human influence on precipitation. Here, we propose a novel approach to regional detection and attribution (D&A) for precipitation, starting with the contiguous United States (CONUS) where observational uncertainty is minimized. In a single framework, we simultaneously detect systematic trends in mean and extreme precipitation, attribute trends to anthropogenic forcings, compute the effects of forcings as a function of time, and map the effects of individual forcings. We use output from global climate models in a perfect-data sense to conduct a set of tests that yield a parsimonious representation for characterizing seasonal precipitation over the CONUS for the historical record (1900 to present day). In doing so, we turn an apparent limitation into an opportunity by using the diversity of responses to short-lived climate forcers across the CMIP6 multi-model ensemble to ensure our D&A is insensitive to structural uncertainty. Our framework is developed using a Pearl-causal perspective, but forthcoming research now underway will apply the framework to in situ measurements using a Granger-causal perspective. While the hypothesis-based framework and accompanying generalized D&A formula we develop should be widely applicable, we include a strong caution that the hypothesis-guided simplification of the formula for the historical climatic record of CONUS as described in this paper will likely fail to hold in other geographic regions and under future warming.

scholarly journals Regional Perspective on Mechanisms for Tropical Precipitation Frequency and Intensity under Global Warming

2012 ◽  
Vol 25 (24) ◽  
pp. 8487-8501 ◽  
Author(s):  
Chao-An Chen ◽  
Chia Chou ◽  
Cheng-Ta Chen
Keyword(s):  
Global Warming ◽  
Climate Models ◽  
Global Climate ◽  
Longwave Radiation ◽  
Heavy Precipitation ◽  
Point Of View ◽  
Global Climate Models ◽  
Main Process ◽  
Precipitation Frequency ◽  
Horizontal Advection

Abstract From a global point of view, a shift toward more intense precipitation is often found in observations and global warming simulations. However, similar to changes in mean precipitation, these changes associated with precipitation characters, such as intensity and frequency, should vary with space. Based on the classification of the subregions for the tropics in Chou et al., changes in precipitation frequency and intensity and their association with changes in mean precipitation are analyzed on a regional basis in 10 coupled global climate models. Furthermore, mechanisms for these changes are also examined, via the thermodynamic and dynamic contributions. In general, the increase (decrease) of mean precipitation is mainly attributed to increases (decreases) in the frequency and intensity of almost all strengths of precipitation: that is, light to heavy precipitation. The thermodynamic contribution, which is associated with increased water vapor, is positive to both precipitation frequency and intensity, particularly for precipitation extremes, and varies little with space. On the other hand, the dynamic contribution, which is related to changes in the tropical circulation, is the main process for inducing the spatial variation of changes in precipitation frequency and intensity. Among mechanisms that induce the dynamic contribution, the rich-get-richer mechanism (the dynamic part), ocean feedback, and warm horizontal advection increase precipitation frequency and intensity, while the upped-ante mechanism, the deepening of convection, longwave radiation cooling, and cold horizontal advection tend to reduce precipitation frequency and intensity.

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