scholarly journals Improving the Identification of Extreme Precipitation Trends in the U.S.

Eos ◽  
2016 ◽  
Vol 97 ◽  
Author(s):  
Terri Cook
Keyword(s):  
Extreme Precipitation ◽  
Rare Events ◽  
Seasonal Forecasting ◽  
New Model ◽  
The U.S ◽  
Precipitation Trends

By greatly reducing the associated uncertainty, a new model is better able to discern statistically significant trends, offering the potential to improve the seasonal forecasting of rare events.

A New Model for Virtual Radiometers

2012 ◽  
Author(s):  
Isaac L. Hunsaker ◽  
David J. Glaze ◽  
Jeremy N. Thornock ◽  
Philip J. Smith
Keyword(s):  
High Accuracy ◽  
Radiative Fluxes ◽  
New Model ◽  
Nuclear Security ◽  
Wholly Owned Subsidiary ◽  
Structured Meshes ◽  
Tracing Algorithm ◽  
Validation Testing ◽  
The U.S ◽  
Good Agreement

There exists a general need to compare radiative fluxes from experimental radiometers with fluxes computed in Thermal/Fluid simulations. Unfortunately, typical numerical simulation suites lack the ability to predict fluxes to objects with small view angles thus preventing validation of simulation results. A new model has been developed that allows users to specify arbitrary view angles, orientations, and locations of multiple radiometers, and receive as the output, high-accuracy radiative fluxes to these radiometers. This virtual radiometer model incorporates a reverse monte-carlo ray tracing algorithm adapted to meet these user specifications and runs on both unstructured and structured meshes. Verification testing of the model demonstrated the expected order of convergence. Validation testing showed good agreement between calculated fluxes from the model and measured fluxes from radiometers used in propellant fires. Sandia National Laboratories is a multiprogram laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy’s National Nuclear Security Administration under contract DEAC0494AL85000.

Mean versus Extreme Precipitation Trends in Iran over the Period 1960–2017

2019 ◽  
Vol 176 (8) ◽  
pp. 3717-3735 ◽  
Author(s):  
Mohammad Rahimi ◽  
Samira Sadat Fatemi
Keyword(s):  
Extreme Precipitation ◽  
Precipitation Trends

A districtwide commitment to arts integration

2017 ◽  
Vol 98 (7) ◽  
pp. 29-33
Author(s):  
Eileen Mackin ◽  
Robert Mackin ◽  
John Obremski ◽  
Katherine McKie
Keyword(s):  
School District ◽  
Visual Arts ◽  
Middle Grades ◽  
Arts Integration ◽  
Department Of Education ◽  
School Systems ◽  
Regular Instruction ◽  
New Model ◽  
The U.S

Like many school systems in economically stressed parts of the country, the Everett, Mass., school district had cut back on arts instruction over the years, to the point where most students were getting only a single art class per week. But since 2013, and thanks to a grant from the U.S. Department of Education, Everett has designed and implemented a new model of arts integration in its elementary and middle grades, providing teachers with intensive support and coaching to help them combine their regular instruction with serious lessons in theater, the visual arts, design, and more.

Extreme Precipitation and Temperature over the U.S. Pacific Northwest: A Comparison between Observations, Reanalysis Data, and Regional Models*

2011 ◽  
Vol 24 (7) ◽  
pp. 1950-1964 ◽  
Author(s):  
Valérie Dulière ◽  
Yongxin Zhang ◽  
Eric P. Salathé
Keyword(s):  
Pacific Northwest ◽  
Extreme Precipitation ◽  
Global Climate Model ◽  
Extreme Temperature ◽  
Reanalysis Data ◽  
Grid Spacing ◽  
Regional Models ◽  
Temperature Indices ◽  
The U.S ◽  
Precipitation And Temperature

Abstract Extreme precipitation and temperature indices in reanalysis data and regional climate models are compared to station observations. The regional models represent most indices of extreme temperature well. For extreme precipitation, finer grid spacing considerably improves the match to observations. Three regional models, the Weather Research and Forecasting (WRF) at 12- and 36-km grid spacing and the Hadley Centre Regional Model (HadRM) at 25-km grid spacing, are forced with global reanalysis fields over the U.S. Pacific Northwest during 2003–07. The reanalysis data represent the timing of rain-bearing storms over the Pacific Northwest well; however, the reanalysis has the worst performance at simulating both extreme precipitation indices and extreme temperature indices when compared to the WRF and HadRM simulations. These results suggest that the reanalysis data and, by extension, global climate model simulations are not sufficient for examining local extreme precipitations and temperatures owing to their coarse resolutions. Nevertheless, the large-scale forcing is adequately represented by the reanalysis so that regional models may simulate the terrain interactions and mesoscale processes that generate the observed local extremes and frequencies of extreme temperature and precipitation.

scholarly journals Investigating Temporal and Spatial Precipitation Patterns in the Southern Mid-Atlantic United States

2022 ◽  
Vol 3 ◽  
Author(s):  
Ishrat Jahan Dollan ◽  
Viviana Maggioni ◽  
Jeremy Johnston
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Flood Control ◽  
Regional Scale ◽  
Population Projections ◽  
Positive Trend ◽  
Significance Level ◽  
Relative Contribution ◽  
Extreme Precipitation Events ◽  
Precipitation Trends

The investigation of regional vulnerability to extreme hydroclimatic events (e.g., floods and hurricanes) is quite challenging due to its dependence on reliable precipitation estimates. Better understanding of past precipitation trends is crucial to examine changing precipitation extremes, optimize future water demands, stormwater infrastructure, extreme event measures, irrigation management, etc., especially if combined with future climate and population projections. The objective of the study is to investigate the spatial-temporal variability of average and extreme precipitation at a sub-regional scale, specifically in the Southern Mid-Atlantic United States, a region characterized by diverse topography and is among the fastest-growing areas in North America. Particularly, this work investigates past precipitation trends and patterns using the North American Land Data Assimilation System, Version 2 (NLDAS-2, 12 km/1 h resolution) reanalysis dataset during 1980–2018. Both parametric (linear regression) and non-parametric (e.g., Theil-Sen) robust statistical tools are employed in the study to analyze trend magnitudes, which are tested for statistical significance using the Mann-Kendall test. Standard precipitation indices from ETCCDI are also used to characterize trends in the relative contribution of extreme events to precipitation in the area. In the region an increasing trend (4.3 mm/year) is identified in annual average precipitation with ~34% of the domain showing a significant increase (at the 0.1 significance level) of +3 to +5 mm/year. Seasonal and sub-regional trends are also investigated, with the most pronounced increasing trends identified during summers along the Virginia and Maryland border. The study also finds a statistically significant positive trend (at a 0.05 significance level) in the annual maximum precipitation. Furthermore, the number of daily extremes (daily total precipitation higher than the 95th and 99th percentiles) also depicts statistically significant increases, indicating the increased frequency of extreme precipitation events. Investigations into the proportion of annual precipitation occurring on wet days and extremely wet days (95th and 99th percentile) also indicate a significant increase in their relative contribution. The findings of this study have the potential to improve local-scale decision-making in terms of river basin management, flood control, irrigation scheme scheduling, and stormwater infrastructure planning to address urban resilience to hydrometeorological hazards.

Scale-dependent representation of extreme precipitation processes in regional and CPM scale simulations for the greater Alpine region

2021 ◽  
Author(s):  
Alberto Caldas-Alvarez ◽  
Hendrik Feldmann ◽  
Joaquim G. Pinto
Keyword(s):  
Extreme Precipitation ◽  
Rare Events ◽  
Potential Temperature ◽  
Low Pressure ◽  
Scale Dependency ◽  
Data Set ◽  
Extreme Precipitation Events ◽  
Spatial Coverage ◽  
Precipitation Processes ◽  
Precipitation Events

<p>Extreme precipitation events with return periods above 100-years (Most Extreme Precipitation Events; MEPE) are rare events by definition, as the observational record covers very few of such events. Therefore, our knowledge is insufficient to assess their potential intensities and physical processes on different scales. To fill this gap, large regional climate ensembles, like the one provided by the German Decadal Climate Predictions (MiKlip) project (> 10.000 years), are of great value as they provide a larger sample size of such rare events. The RCM ensemble samples present day climate conditions multiple times (Ehmele et al., 2020) with a resolution of 25 km, and thus it does not resolve the convection permitting scales (CPM).</p><p>In this study, we aim to combine the large RCM ensemble with episodic CPM-scale downscaling simulations to derive a better statistical and process related representation of MEPEs for Central Europe. As a first step, we evaluate two re-analysis driven long-term simulations with COSMO-CLM (CCLM) from MiKlip and CORDEX-FPS Convection with respect to their scale-dependent representation.</p><p>The simulations span the period 1971 to 2016 with the 25 km simulation and are forced by ERA40 until 1979 and by ERA-interim afterwards. The CPM simulation (~3 km) is forced by ERA-40 between 1971 and 1999 and by ERA-interim between 2000 and 2016. We validate the simulations against E-OBS (25 km) and the unique HYdrologische RASterdatensätze (HYRAS) precipitation data set (5 km). The investigation area is the greater Alpine area. We employ a Precipitation Severity Index (PSI) adapted from extreme wind detection (Leckebusch et al., 2008; Pinto et al., 2012) for extreme precipitation cases. The advantage of the PSI is its ability to account for extreme grid point precipitation as well as spatial coverage and event duration. The events are categorized objectively into composite Weather Types (WT) to enable further generalization of the findings.</p><p>The results show a clear overestimation of precipitation for the analysed period and area by the RCMs at both resolutions. However, large differences exist the representation of extreme precipitation. Compared to observations, the 3 km (25km) resolution overestimates (underestimates) precipitation intensity for extreme cases. This agrees with previous literature. Five different WTs are identified for the analysed period, with Autumn-Winter WT being the most common, followed by convective summer WT. The Autumn-Winter WT is characterized by deep, cold, low-pressure areas located over Northern Europe. Summer WT cases are characterized by stable high-pressure situations affected by incurring small low-pressure systems on its western flank (convective-prone situations). Regarding the scale dependency of precipitation processes, the coarse resolution tends to overestimate surface moisture in situations of heavy precipitation, leading to larger latent instability (CAPE) in the 25 km resolution than in its 3 km counterpart. Furthermore, a large-scale dependency is found in summer extreme precipitation cases for two stability-related variables, Equivalent Potential Temperature (θ<sub>e</sub><sup>850</sup>) at 850 hPa and moisture flux at the Lower Free Troposphere (LFT-moisture). In these cases, the overestimation (underestimation) of  and LFT-moisture by either resolution is in line with their precipitation overestimation (underestimation).</p>

Extreme Precipitation Events in Northern California during Winter 2016–17: Multiscale Analysis and Climatological Perspective

2020 ◽  
Vol 148 (3) ◽  
pp. 1049-1074
Author(s):  
Benjamin J. Moore ◽  
Allen B. White ◽  
Daniel J. Gottas ◽  
Paul J. Neiman
Keyword(s):  
Bering Sea ◽  
Extreme Precipitation ◽  
Wave Breaking ◽  
Multiscale Analysis ◽  
Large Scale ◽  
Northern California ◽  
Extreme Precipitation Events ◽  
The U.S ◽  
Precipitation Events ◽  
The Bering Sea

Abstract A multiscale analysis is presented of extreme precipitation events (EPEs) in Northern California during winter 2016–17, which caused flooding and contributed substantially to highly anomalous seasonal precipitation totals. The EPEs were characterized by long durations (≥7 days) and involved persistent large-scale flow patterns. The three largest EPEs involved blocking over the Bering Sea–Alaska region. A detailed investigation of the largest EPE, occurring on 2–10 February 2017, reveals that extreme precipitation was produced as four discrete cyclones moved across the eastern North Pacific equatorward of a high-amplitude blocking ridge and impacted the U.S. West Coast in rapid succession. The latter three cyclones developed and moved in conjunction with elongated negatively tilted troughs or PV streamers resulting from repeated episodes of baroclinic development and cyclonic Rossby wave breaking on the upstream flank of the block. Each of the four cyclones interacted with a PV streamer and an associated baroclinic zone established by anticyclonic wave breaking on the downstream flank of the block and, thereby, tracked into the U.S. West Coast. The serial clustering of the cyclones during the 9-day event resulted in persistent water vapor flux and lifting that supported extreme precipitation totals in Northern California. A climatological analysis for 1979–2017 reveals a significant statistical relationship between blocking over the Bering Sea–Alaska region and EPEs in Northern California, indicating that this type of blocking pattern represents a favorable large-scale scenario for extreme precipitation in Northern California.

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