Changes in Future Flash Flood–Producing Storms in the United States

2020 ◽  
Vol 21 (10) ◽  
pp. 2221-2236 ◽  
Author(s):  
Erin Dougherty ◽  
Kristen L. Rasmussen
Keyword(s):  
United States ◽  
Climate Models ◽  
Flash Flood ◽  
Global Climate ◽  
The United States ◽  
Flash Floods ◽  
Global Climate Models ◽  
Future Climate ◽  
South Central ◽  
Rain Rates

AbstractFlash floods are high-impact events that can result in massive destruction, such as the May 2010 flash floods in the south-central United States that resulted in over $2 billion of damage. While floods in the current climate are already destructive, future flood risk is projected to increase based on work using global climate models. However, global climate models struggle to resolve precipitation structure, intensity, and duration, which motivated the use of convection-permitting climate models that more accurately depict these precipitation processes on a regional scale due to explicit representation of convection. These high-resolution convection-permitting simulations have been used to examine future changes to rainfall, but not explicitly floods. This study aims to fill this gap by examining future changes to rainfall characteristics and runoff in flash flood–producing storms over the United States using convection-permitting models under a pseudo–global warming framework. Flash flood accumulated rainfall increases on average by 21% over the United States in a future climate. Storm-generated runoff increases by 50% on average, suggesting increased runoff efficiency in future flash flood–producing storms. In addition to changes in nonmeteorological factors, which were not explored in this study, increased future runoff is possible due to the 7.5% K−1 increase in future hourly maximum rain rates. Though this median change in rain rates is consistent with Clausius–Clapeyron theory, some storms exhibit increased future rain rates well above this, likely associated with storm dynamics. Overall, results suggest that U.S. cities might need to prepare for more intense flash flood–producing storms in a future climate.

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.

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 Diagnosing Moisture Sources for Flash Floods in the United States. Part I: Kinematic Trajectories

2019 ◽  
Vol 20 (8) ◽  
pp. 1495-1509 ◽  
Author(s):  
Jessica M. Erlingis ◽  
Jonathan J. Gourley ◽  
Jeffrey B. Basara
Keyword(s):  
United States ◽  
Flash Flood ◽  
The United States ◽  
Flash Floods ◽  
Reanalysis Data ◽  
Front Range ◽  
Flow Paths ◽  
South Central ◽  
Central Texas ◽  
Regional Reanalysis

Abstract This study uses backward trajectories derived from North American Regional Reanalysis data for 19 253 flash flood reports during the period 2007–13 published by the National Weather Service to assess the origins of air parcels for flash floods in the conterminous United States. The preferred flow paths for parcels were evaluated seasonally and for six regions of interest: the West Coast, Arizona, the Front Range of the Rocky Mountains, Flash Flood Alley in south-central Texas, the Missouri Valley, and the Appalachians. Parcels were released from vertical columns in the atmosphere at times and locations where there were reported flash floods; these were traced backward in time for 5 days. The temporal and seasonal cycles of flood events in these regions are also explored. The results show the importance of trajectories residing for long periods over oceanic regions such as the Gulf of Mexico and the Caribbean Sea. The flow is generally unidirectional with height in the lower layers of the atmosphere. The trajectory paths from oceanic genesis regions to inland hotspots and their orientation with height provide clues that can assist in the diagnosis of impending flash floods. Part II of this manuscript details the land–atmosphere interactions along the trajectory paths.

scholarly journals Spatial–Temporal Patterns of Historical, Near-Term, and Projected Drought in the Conterminous United States

Hydrology ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 136
Author(s):  
Susan M. Kotikot ◽  
Olufemi A. Omitaomu
Keyword(s):  
United States ◽  
Spatial Scale ◽  
Climate Models ◽  
Global Climate ◽  
Severity Index ◽  
The United States ◽  
Global Climate Models ◽  
Drought Severity ◽  
Near Term ◽  
Local Variability

Major droughts in the United States have heavily impacted the hydrologic system, negatively effecting energy and food production. Improved understanding of historical drought is critical for accurate forecasts. Data from global climate models (GCMs), commonly used to assess drought, cannot effectively evaluate local patterns because of their low spatial scale. This research leverages downscaled (~4 km grid spacing) temperature and precipitation estimates from nine GCMs’ data under the business-as-usual scenario (Representative Concentration Pathway 8.5) to examine drought patterns. Drought severity is estimated using the Palmer Drought Severity Index (PDSI) with the Thornthwaite evapotranspiration method. The specific objectives were (1) To reproduce historical (1966–2005) drought and calculate near-term to future (2011–2050) drought patterns over the conterminous USA. (2) To uncover the local variability of spatial drought patterns in California between 2012 and 2018 using a network-based approach. Our estimates of land proportions affected by drought agree with the known historical drought events of the mid-1960s, late 1970s to early 1980s, early 2000s, and between 2012 and 2015. Network analysis showed heterogeneity in spatial drought patterns in California, indicating local variability of drought occurrence. The high spatial scale at which the analysis was performed allowed us to uncover significant local differences in drought patterns. This is critical for highlighting possible weak systems that could inform adaptation strategies such as in the energy and agricultural sectors.

Variations in Flash Flood-Producing Storm Characteristics Associated with Changes in Vertical Velocity in a Future Climate in the Mississippi River Basin

2021 ◽  
Author(s):  
Erin Dougherty ◽  
Kristen L. Rasmussen
Keyword(s):  
United States ◽  
River Basin ◽  
Vertical Velocity ◽  
Mississippi River ◽  
Flash Flood ◽  
The United States ◽  
Flash Floods ◽  
Future Climate ◽  
Mississippi River Basin ◽  
Storm Characteristics

AbstractThe Mississippi River Basin (MRB) is a flash flood hotspot receiving the most frequent flash floods and highest average rainfall accumulation of any region in the United States. Given the destruction flash floods cause in the current climate in the MRB, it is critical to understand how they will change in a future, warmer climate in order to prepare for these impacts. Recent work utilizing convection-permitting climate simulations to analyze future precipitation changes in flash flood-producing storms in the United States shows that the MRB experiences the greatest future increase in flash flood rainfall. This result motivates the goal of the present study to better understand the changes to precipitation characteristics and vertical velocity in flash flood-producing storms in the MRB. Specifically, the variations in flash flood-producing storm characteristics related to changes in vertical velocity in the MRB are examined by identifying 484 historical flash flood-producing storms from 2002–2013 and studying how they change in a future climate using 4-km convection-permitting simulations under a pseudo-global warming framework. In a future climate, precipitation and runoff increase by 17% and 32%, respectively, in flash flood-producing storms in the MRB. While rainfall increases in all flash flood-producing storms due to similar increases in moisture, it increases the most in storms with the strongest vertical velocity, suggesting that storm dynamics might modulate future changes in rainfall. These results are necessary to predict and prepare for the multifaceted impacts of climate change on flash flood-producing storms in order to create more resilient communities.

Using convection-permitting climate models and a high-resolution distributed hydrological model to assess future changes in Alpine flash floods.

2021 ◽  
Author(s):  
Marjanne Zander ◽  
Pety Viguurs ◽  
Frederiek Sperna Weiland ◽  
Albrecht Weerts
Keyword(s):  
High Resolution ◽  
Natural Hazards ◽  
Climate Models ◽  
Flash Flood ◽  
Regional Climate ◽  
Flash Floods ◽  
Flood Frequency ◽  
Climate Dynamics ◽  
Future Climate ◽  
European Climate

<p>Flash Floods are damaging natural hazards which often occur in the European Alps. Precipitation patterns and intensity may change in a future climate affecting their occurrence and magnitude. For impact studies, flash floods can be difficult to simulate due the complex orography and limited extent & duration of the heavy rainfall events which trigger them. The new generation convection-permitting regional climate models improve the intensity and frequency of heavy precipitation (Ban et al., 2021).</p><p>Therefore, this study combines such simulations with high-resolution distributed hydrological modelling to assess changes in flash flood frequency and occurrence over the Alpine terrain. We use the state-of-the-art Unified Model (Berthou et al., 2018) to drive a high-resolution distributed hydrological wflow_sbm model (e.g. Imhoff et al., 2020) covering most of the Alpine mountain range on an hourly resolution. Simulations of the future climate RCP 8.5 for the end-of-century (2096-2105) and current climate (1998-2007) are compared.</p><p>First, the wflow_sbm model was validated by comparing ERA5 driven simulation with streamflow observations (across Rhone, Rhine, Po, Adige and Danube). Second, the wflow_sbm simulation driven by UM simulation of the current climate was compared to a dataset of historical flood occurrences (Paprotny et al., 2018, Earth Syst. Sci. Data) to validate if the model can accurately simulate the location of the flash floods and to determine a suitable threshold for flash flooding. Finally, the future run was used to asses changes in flash flood frequency and occurrence. Results show an increase in flash flood frequency for the Upper Rhine and Adige catchments. For the Rhone the increase was less pronounced. The locations where the flash floods occur did not change much.</p><p>This research is embedded in the EU H2020 project EUCP (EUropean Climate Prediction system) (https://www.eucp-project.eu/), which aims to support climate adaptation and mitigation decisions for the coming decades by developing a regional climate prediction and projection system based on high-resolution climate models for Europe.</p><p> </p><p>N. Ban, E. Brisson, C. Caillaud, E. Coppola, E. Pichelli, S. Sobolowski, …, M.J. Zander (2021): “The first multi-model ensemble of regional climate simulations at the kilometer-scale resolution, Part I: Evaluation of precipitation”, manuscript accepted for publication in Climate Dynamics.</p><p>S. Berthou, E.J. Kendon, S. C. Chan, N. Ban, D. Leutwyler, C. Schär, and G. Fosser, 2018, “Pan-european climate at convection-permitting scale: a model intercomparison study.” Climate Dynamics, pages 1–25, DOI: 10.1007/s00382-018-4114-6</p><p>Imhoff, R.O., W. van Verseveld, B. van Osnabrugge, A.H. Weerts, 2020. “Scaling point-scale pedotransfer functions parameter estimates for seamless large-domain high-resolution distributed hydrological modelling: An example for the Rhine river.” Water Resources Research, 56. Doi: 10.1029/2019WR026807</p><p>Paprotny, D., Morales Napoles, O., & Jonkman, S. N., 2018. "HANZE: a pan-European database of exposure to natural hazards and damaging historical floods since 1870". Earth System Science Data, 10, 565–581, https://doi.org/10.5194/essd-10-565-2018</p>

scholarly journals Climate change will increase potential hydropower production in six Arctic Council member countries based on probabilistic hydrological projections

2018 ◽  
Author(s):  
Elena Shevnina ◽  
Karoliina Pilli-Sihvola ◽  
Riina Haavisto ◽  
Timo Vihma ◽  
Andrey Silaev
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
The United States ◽  
Annual Runoff ◽  
Global Climate Models ◽  
Exceedance Probability ◽  
Arctic Council ◽  
Pearson Type ◽  
Hydropower Production ◽  
Runoff Rate

Abstract. Potential hydropower production for 2020–2050 is calculated for 173 catchments located over the territories of Finland, Sweden, Norway, the Russian Federation, Canada and the United States. The results are based on hydrological river runoff projections assessed together with their exceedance probabilities. The annual runoff rate of particular exceedance probability was modelled with the Pearson type 3 distribution from three parameters (mean values, coefficient of variation and coefficient of skewness) simulated by the probabilistic hydrological MARcov Chain System (MARCS) model. The probabilistic projections of annual runoff were simulated from outputs of four global climate models under three Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5). The future potential hydropower production was evaluated based on annual runoff of low and high exceedance probabilities, and then aggregated at a country level. Under forcing from climate models that project a large increase in precipitation (CaEMS2 and MPI-EMS-LM), the expected potential hydropower production in the six countries increased by 14.0 to 18.0 % according to the projected values of annual runoff rate on exceedance probabilities of 10 and 90 %. This increase in water resources allows for 10–15 % more hydropower energy generation by rivers located in Russia, Finland, Norway, and Sweden. For the USA and Canada, the potential hydropower production is projected to increases by 4.0–9.0 %. Under forcing from climate models that project a smaller increase in precipitation (HadGEM2-ES and INMCM4), the increase of potential hydropower production by 2050 was predicted to be 2.1–8.4 % over the six countries considered.

Drivers of Twenty-First Century U.S. Winter Precipitation Trends in CMIP6 Models: A Storyline-Based Approach

2021 ◽  
pp. 1-48
Author(s):  
Daniel F. Schmidt ◽  
Kevin M. Grise
Keyword(s):  
Climate Models ◽  
Southern Oscillation ◽  
Global Climate ◽  
The United States ◽  
Winter Precipitation ◽  
Global Climate Models ◽  
First Century ◽  
Precipitation Trend ◽  
Twenty First Century ◽  
Precipitation Trends

AbstractClimate change during the twenty-first century has the potential to substantially alter geographic patterns of precipitation. However, regional precipitation changes can be very difficult to project, and in some regions, global climate models do not even agree on the sign of the precipitation trend. Since some of this uncertainty is due to internal variability rather than model bias, models cannot be used to narrow the possibilities to a single outcome, but they can usefully quantify the range of plausible outcomes and identify the combination of dynamical drivers that would be likely to produce each.This study uses a storylines approach—a type of regression-based analysis—to identify some of the key dynamical drivers that explain the variance in 21st century U.S. winter precipitation trends across CMIP6 models under the SSP3-7.0 emissions scenario. This analysis shows that the spread in precipitation trends is not primarily driven by differences in modeled climate sensitivity. Key drivers include global-mean surface temperature, but also tropical upper-troposphere temperature, the El Niño-Southern Oscillation (ENSO), the Pacific-North America (PNA) pattern, and the East Pacific (EP) dipole (a dipole pattern in geopotential heights over North America’s Pacific coast). Combinations of these drivers can reinforce or cancel to produce various high- or low-impact scenarios for winter precipitation trends in various regions of the United States. For example, the most extreme winter precipitation trends in the southwestern U.S. result from opposite trends in ENSO and EP, whereas the wettest winter precipitation trends in the midwestern U.S. result from a combination of strong global warming and a negative PNA trend.

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