scholarly journals Characterizing the Spatial Scales of Extreme Daily Precipitation in the United States

2018 ◽  
Vol 31 (19) ◽  
pp. 8023-8037 ◽  
Author(s):  
Danielle Touma ◽  
Anna M. Michalak ◽  
Daniel L. Swain ◽  
Noah S. Diffenbaugh
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Spatial Scales ◽  
The United States ◽  
Spatial Extent ◽  
Precipitation Event ◽  
Length Scales ◽  
Precipitation Records ◽  
Northwest Region

The spatial extent of an extreme precipitation event can be important for a basin’s hydrologic response and subsequent flood risk, and may yield insights into underlying atmospheric processes. Using a relaxed moving-neighborhood approach, we develop indicator semivariograms based on precipitation records from the Global Historical Climatology Network–Daily (GHCN-D) station network to directly quantify the climatological length scales of extreme daily precipitation over the United States during 1965–2014. We find that the length scales of extreme (90th percentile) daily precipitation events vary both regionally and seasonally. Over the eastern half of the United States, daily extreme precipitation length scales reach 400 km during the winter months, but are approximately half as large during the summer months. The Northwest region, on the other hand, exhibits little seasonal variation, with extreme precipitation length scales of approximately 150 km throughout the year. By leveraging in situ station measurements, our study avoids some of the uncertainties associated with satellite or interpolated precipitation data, and provides the longest climatological assessment of length scales of extreme daily precipitation over the United States to date. Although the length scales that we calculate can be sensitive to station density, neighborhood size, and neighborhood relaxation, we find that the interregional and interseasonal differences in length scales are relatively robust. Our method could be extended to quantify changes in the spatial extent of extreme daily precipitation in the recent past, and to investigate the underlying causes of any changes that are detected.

scholarly journals Simulation of Daily Extreme Precipitation over the United States in the CMIP5 30-Yr Decadal Prediction Experiment

2019 ◽  
Vol 58 (4) ◽  
pp. 875-886 ◽  
Author(s):  
Steve T. Stegall ◽  
Kenneth E. Kunkel
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
The United States ◽  
Natural Variability ◽  
Return Level ◽  
Historical Period ◽  
Regional Variability ◽  
Anthropogenic Forcing ◽  
Near Term

AbstractThe CMIP5 decadal hindcast (“Hindcast”) and prediction (“Predict”) experiment simulations from 11 models were analyzed for the United States with respect to two metrics of extreme precipitation: the 10-yr return level of daily precipitation, derived from the annual maximum series of daily precipitation, and the total precipitation exceeding the 99.5th percentile of daily precipitation. Both Hindcast simulations and observations generally show increases for the 1981–2010 historical period. The multimodel-mean Hindcast trends are statistically significant for all regions while the observed trends are statistically significant for the Northeast, Southeast, and Midwest regions. An analysis of CMIP5 simulations driven by historical natural (“HistoricalNat”) forcings shows that the Hindcast trends are generally within the 5th–95th-percentile range of HistoricalNat trends, but those outside that range are heavily skewed toward exceedances of the 95th-percentile threshold. Future projections for 2006–35 indicate increases in all regions with respect to 1981–2010. While there is good qualitative agreement between the observations and Hindcast simulations regarding the direction of recent trends, the multimodel-mean trends are similar for all regions, while there is considerable regional variability in observed trends. Furthermore, the HistoricalNat simulations suggest that observed historical trends are a combination of natural variability and anthropogenic forcing. Thus, the influence of anthropogenic forcing on the magnitude of near-term future changes could be temporarily masked by natural variability. However, continued observed increases in extreme precipitation in the first decade (2006–15) of the “future” period partially confirm the Predict results, suggesting that incorporation of increases in planning would appear prudent.

Evaluating the Reliability of the U.S. Cooperative Observer Program Precipitation Observations for Extreme Events Analysis Using the LTAR Network

2019 ◽  
Vol 36 (3) ◽  
pp. 317-332
Author(s):  
Eleonora M. C. Demaria ◽  
David C. Goodrich ◽  
Kenneth E. Kunkel
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Warm Season ◽  
The United States ◽  
Observation Time ◽  
Dense Networks ◽  
Rain Gauges ◽  
Detection And Attribution ◽  
Precipitation Characteristics

AbstractThe detection and attribution of changes in precipitation characteristics relies on dense networks of rain gauges. In the United States, the COOP network is widely used for such studies even though there are reported inconsistencies due to changes in instruments and location, inadequate maintenance, dissimilar observation time, and the fact that measurements are made by a group of dedicated volunteers. Alternately, the Long-Term Agroecosystem Research (LTAR) network has been consistently and professionally measuring precipitation since the early 1930s. The purpose of this study is to compare changes in extreme daily precipitation characteristics during the warm season using paired rain gauges from the LTAR and COOP networks. The comparison, done at 12 LTAR sites located across the United States, shows underestimation and overestimation of daily precipitation totals at the COOP sites compared to the reference LTAR observations. However, the magnitude and direction of the differences are not linked to the underlying precipitation climatology of the sites. Precipitation indices that focus on extreme precipitation characteristics match closely between the two networks at most of the sites. Our results show consistency between the COOP and LTAR networks with precipitation extremes. It also indicates that despite the discrepancies at the daily time steps, the extreme precipitation observed by COOP rain gauges can be reliably used to characterize changes in the hydrologic cycle due to natural and human causes.

scholarly journals Contrasting scaling relationships of extreme precipitation and streamflow to temperature across the United States

2021 ◽  
Author(s):  
Mingxi Shen ◽  
Ting Fong May Chui
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Temporal Evolution ◽  
Extreme Event ◽  
The United States ◽  
Scaling Analysis ◽  
Southern Plains ◽  
Scaling Relationships ◽  
Warming Climate

Abstract Recent studies have reached inconsistent conclusions from scaling analysis about whether flood or extreme precipitation is more sensitive to warming climate. To explain the reasons behind the inconsistency, here we first used scaling analysis to illustrate how extreme daily precipitation and streamflow scale with daily air temperature across the Continental United States (CONUS). We found both similar and opposite scaling in extreme precipitation and streamflow. It indicates based on scaling analysis, the sensitivity of extreme streamflow to warming climate can be either similar, higher or lower to that of extreme precipitation. We further explored why there are contrasting scaling relationships in the CONUS. Generally, the similar scaling was found in regions where the timing of extreme precipitation and streamflow is correspondent, as well as with similar temporal evolution in extreme event timing and magnitude, e.g., the west coast and southern plains, implying extreme precipitation is the dominant driver of local floods. However, for regions with dissimilar scaling in extreme precipitation and streamflow (e.g., Rocky Mountains, southern plains), the characteristics of extreme streamflow show large difference to those of extreme precipitation, and the temporal evolution of extreme streamflow timing and magnitude are more correlated with factors/processes such as soil moisture and snowmelt. This study reflects that the contrasting scaling relationships of extreme precipitation and streamflow are oriented from the local hydro-climatological specifics. Using scaling analysis to compare the sensitivity of extreme precipitation and streamflow to warming climate is not suitable. Instead, we should focus more on local flood generating mechanisms or flood drivers when investigating floods in the changing climate.

scholarly journals Who Received the Most Rain Today?: An Analysis of Daily Precipitation Extremes in the Contiguous United States Using CoCoRaHS and COOP Reports

2020 ◽  
Vol 101 (6) ◽  
pp. E710-E719 ◽  
Author(s):  
Peter E. Goble ◽  
Nolan J. Doesken ◽  
Imke Durre ◽  
Russ S. Schumacher ◽  
Abigail Stewart ◽  
...  
Keyword(s):  
United States ◽  
Gulf Stream ◽  
Temporal Variability ◽  
Extreme Precipitation ◽  
Seasonal Cycle ◽  
Daily Precipitation ◽  
The United States ◽  
Precipitation Extremes ◽  
The Past ◽  
The U.S

Abstract Every day, thousands of volunteers across the United States report the amount of precipitation they have received in the past 24 hours. This study focuses on the largest of these volunteer-submitted reports for each day, using precipitation measurements from the Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) from January 2010 to December 2017 as well as observations from the U.S. Cooperative Observer Program (COOP) network from January 1981 through December 2017. Results provide clarity on spatial variability, temporal variability, and seasonal cycle of contiguous U.S daily precipitation extremes (DPEs). During 2010–17, the DPEs ranged from 11 mm on 28 March 2013 in Oregon to 635 mm on 27 August 2017 in Texas during Hurricane Harvey. Coastal states are most prone to high daily precipitation totals, especially those bordering the Gulf of Mexico or Atlantic Gulf Stream. The average DPE value varies with season; it is greater than 175 mm in late August and less than 100 mm through meteorological winter. These observations also show that location of the DPE varies with season as well. For example, 28.5% of February extremes fall in Pacific states, whereas all August extremes occur east of that region. Perhaps most importantly, these findings demonstrate strength in numbers. The large daily sample size of CoCoRaHS and COOP networks forms a basis for monitoring, mapping, and categorizing DPEs, and other aspects of extreme precipitation, with considerable spatial detail.

scholarly journals Validation and Error Characterization of the GPCP-1DD Precipitation Product over the Contiguous United States

2005 ◽  
Vol 6 (4) ◽  
pp. 441-459 ◽  
Author(s):  
James McPhee ◽  
Steven A. Margulis
Keyword(s):  
United States ◽  
Daily Precipitation ◽  
Ground Truth ◽  
Global Precipitation Climatology Project ◽  
The United States ◽  
Precipitation Event ◽  
Precipitation Product ◽  
The North ◽  
Error Characterization ◽  
Environmental Prediction

Abstract A validation and error characterization study of the Global Precipitation Climatology Project, 1 degree daily (GPCP-1DD) precipitation product over the contiguous United States is presented. Daily precipitation estimates over a 1° grid are compared against aggregated precipitation values obtained from the forcing field of the North American Land Data Assimilation System (LDAS). LDAS daily values are consistent with the National Centers for Environmental Prediction Climate Prediction Center (CPC) gauge-based daily precipitation product and hence are regarded as realistic ground-truth values with full coverage of the United States. Continuous and categorical measures of skill are presented, so that both the ability of GPCP-1DD to identify a precipitation event and its accuracy in determining cumulative precipitation amounts are evaluated. Daily values are aggregated into seasonal averages, and spatial averages are computed for five arbitrarily defined zones that cover most of the study area. Results show that in general there is good agreement between GPCP-1DD and LDAS values, except for areas where GPCP-1DD is unable to identify high-intensity events, particularly the Pacific coast north of parallel 40°N. Computation of continuous statistics shows that average bias is negligible in most areas of the United States except for humid regions north of parallel 40°N. However, the rmse statistics shows that differences in estimated precipitation for individual 1° cells can be significant, exceeding in most cases the magnitude of the average precipitation. Beyond the validation, the error characterization presented here can significantly enhance the utility of the GPCP-1DD product by providing necessary inputs for ensemble hydrologic modeling and forecasting.

scholarly journals ENSO and Wintertime Extreme Precipitation Events over the Contiguous United States

2008 ◽  
Vol 21 (1) ◽  
pp. 22-39 ◽  
Author(s):  
Siegfried D. Schubert ◽  
Yehui Chang ◽  
Max J. Suarez ◽  
Philip J. Pegion
Keyword(s):  
United States ◽  
West Coast ◽  
Extreme Precipitation ◽  
East Coast ◽  
Daily Precipitation ◽  
Precipitation Variability ◽  
The West ◽  
Extreme Precipitation Events ◽  
The Impact ◽  
Precipitation Events

Abstract In this study the authors examine the impact of El Niño–Southern Oscillation (ENSO) on precipitation events over the continental United States using 49 winters (1949/50–1997/98) of daily precipitation observations and NCEP–NCAR reanalyses. The results are compared with those from an ensemble of nine atmospheric general circulation model (AGCM) simulations forced with observed SST for the same time period. Empirical orthogonal functions (EOFs) of the daily precipitation fields together with compositing techniques are used to identify and characterize the weather systems that dominate the winter precipitation variability. The time series of the principal components (PCs) associated with the leading EOFs are analyzed using generalized extreme value (GEV) distributions to quantify the impact of ENSO on the intensity of extreme precipitation events. The six leading EOFs of the observations are associated with major winter storm systems and account for more than 50% of the daily precipitation variability along the West Coast and over much of the eastern part of the country. Two of the leading EOFs (designated GC for Gulf Coast and EC for East Coast) together represent cyclones that develop in the Gulf of Mexico and occasionally move and/or redevelop along the East Coast producing large amounts of precipitation over much of the southern and eastern United States. Three of the leading EOFs represent storms that hit different sections of the West Coast (designated SW for Southwest coast, WC for the central West Coast, and NW for northwest coast), while another represents storms that affect the Midwest (designated by MW). The winter maxima of several of the leading PCs are significantly impacted by ENSO such that extreme GC, EC, and SW storms that occur on average only once every 20 years (20-yr storms) would occur on average in half that time under sustained El Niño conditions. In contrast, under La Niña conditions, 20-yr GC and EC storms would occur on average about once in 30 years, while there is little impact of La Niña on the intensity of the SW storms. The leading EOFs from the model simulations and their connections to ENSO are for the most part quite realistic. The model, in particular, does very well in simulating the impact of ENSO on the intensity of EC and GC storms. The main model discrepancies are the lack of SW storms and an overall underestimate of the daily precipitation variance.

scholarly journals Representing Extremes in a Daily Gridded Precipitation Analysis over the United States: Impacts of Station Density, Resolution, and Gridding Methods

2014 ◽  
Vol 27 (14) ◽  
pp. 5201-5218 ◽  
Author(s):  
Melissa Gervais ◽  
L. Bruno Tremblay ◽  
John R. Gyakum ◽  
Eyad Atallah
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
The United States ◽  
Low Resolution ◽  
Spatial Homogeneity ◽  
Precipitation Analysis ◽  
Precipitation Station ◽  
Density Resolution ◽  
Analysis Point ◽  
Station Density

Abstract This study focuses on errors in extreme precipitation in gridded station products incurred during the upscaling of station measurements to a grid, referred to as representativeness errors. Gridded precipitation station analyses are valuable observational data sources with a wide variety of applications, including model validation. The representativeness errors associated with two gridding methods are presented, consistent with either a point or areal average interpretation of model output, and it is shown that they differ significantly (up to 30%). An experiment is conducted to determine the errors associated with station density, through repeated gridding of station data within the United States using subsequently fewer stations. Two distinct error responses to reduced station density are found, which are attributed to differences in the spatial homogeneity of precipitation distributions. The error responses characterize the eastern and western United States, which are respectively more and less homogeneous. As the station density decreases, the influence of stations farther from the analysis point increases, and therefore, if the distributions are inhomogeneous in space, the analysis point is influenced by stations with very different precipitation distributions. Finally, ranges of potential percent representativeness errors of the median and extreme precipitation across the United States are created for high-resolution (0.25°) and low-resolution areal averaged (0.9° lat × 1.25° lon) precipitation fields. For example, the range of the representativeness errors is estimated, for annual extreme precipitation, to be from +16% to −12% in the low-resolution data, when station density is 5 stations per 0.9° lat × 1.25° lon grid box.

Changes in Observed Daily Precipitation over the United States between 1950–79 and 1980–2009

2013 ◽  
Vol 14 (1) ◽  
pp. 105-121 ◽  
Author(s):  
R. W. Higgins ◽  
V. E. Kousky
Keyword(s):  
United States ◽  
Great Plains ◽  
El Niño ◽  
Daily Precipitation ◽  
El Nino ◽  
Southern Oscillation ◽  
Heavy Precipitation ◽  
The United States ◽  
Enso Cycle ◽  
Precipitation Events

Abstract Changes in observed daily precipitation over the conterminous United States between two 30-yr periods (1950–79 and 1980–2009) are examined using a 60-yr daily precipitation analysis obtained from the Climate Prediction Center (CPC) Unified Raingauge Database. Several simple measures are used to characterize the changes, including mean, frequency, intensity, and return period. Seasonality is accounted for by examining each measure for four nonoverlapping seasons. The possible role of the El Niño–Southern Oscillation (ENSO) cycle as an explanation for differences between the two periods is also examined. There have been more light (1 mm ≤ P < 10 mm), moderate (10 mm ≤ P < 25 mm), and heavy (P ≥ 25 mm) daily precipitation events (P) in many regions of the country during the more recent 30-yr period with some of the largest and most spatially coherent increases over the Great Plains and lower Mississippi Valley during autumn and winter. Some regions, such as portions of the Southeast and the Pacific Northwest, have seen decreases, especially during the winter. Increases in multiday heavy precipitation events have been observed in the more recent period, especially over portions of the Great Plains, Great Lakes, and Northeast. These changes are associated with changes in the mean and frequency of daily precipitation during the more recent 30-yr period. Difference patterns are strongly related to the ENSO cycle and are consistent with the stronger El Niño events during the more recent 30-yr period. Return periods for both heavy and light daily precipitation events during 1950–79 are shorter during 1980–2009 at most locations, with some notable regional exceptions.

scholarly journals Fine-Scale Population Genetic Structure and Within-Tree Distribution of Mating Types of Venturia effusa, Cause of Pecan Scab in the United States

2018 ◽  
Vol 108 (11) ◽  
pp. 1326-1336 ◽  
Author(s):  
Clive H. Bock ◽  
Carolyn A. Young ◽  
Katherine L. Stevenson ◽  
Nikki D. Charlton
Keyword(s):  
United States ◽  
Genetic Diversity ◽  
Asexual Reproduction ◽  
Population Genetic ◽  
Spatial Scales ◽  
The United States ◽  
Source Population ◽  
Mating Types ◽  
Fine Scale ◽  
Scale Population

Scab (caused by Venturia effusa) is the major disease of pecan in the southeastern United States. There is no information available on the fine-scale population genetic diversity or the occurrence of clonal types at small spatial scales that provides insight into inoculum sources and dispersal mechanisms, and potential opportunity for sexual reproduction. To investigate fine-scale genetic diversity, four trees of cultivar Wichita (populations) were sampled hierarchically: within each tree canopy, four approximately evenly spaced terminals (subpopulations) were selected and up to six leaflets (sub-subpopulations) were sampled from different compound leaves on each terminal. All lesions (n = 1 to 8) on each leaflet were sampled. The isolates were screened against a panel of 29 informative microsatellite markers and the resulting multilocus genotypes (MLG) subject to analysis. Mating type was also determined for each isolate. Of 335 isolates, there were 165 MLG (clonal fraction 49.3%). Nei’s unbiased measure of genetic diversity for the clone-corrected data were moderate to high (0.507). An analysis of molecular variance demonstrated differentiation (P = 0.001) between populations on leaflets within individual terminals and between terminals within trees in the tree canopies, with 93.8% of variance explained among isolates within leaflet populations. Other analyses (minimum-spanning network, Bayesian, and discriminant analysis of principal components) all indicated little affinity of isolate for source population. Of the 335 isolates, most unique MLG were found at the stratum of the individual leaflets (n = 242), with similar total numbers of unique MLG observed at the strata of the terminal (n = 170), tree (n = 166), and orchard (n = 165). Thus, the vast majority of shared clones existed on individual leaflets on a terminal at the scale of 10s of centimeters or less, indicating a notable component of short-distance dispersal. There was significant linkage disequilibrium (P < 0.001), and an analysis of Psex showed that where there were multiple encounters of an MLG, they were most probably the result of asexual reproduction (P < 0.05) but there was no evidence that asexual reproduction was involved in single or first encounters of an MLG (P > 0.05). Overall, the MAT1-1-1 and MAT1-2-1 idiomorphs were at equilibrium (73:92) and in most populations, subpopulations, and sub-subpopulations. Both mating types were frequently observed on the same leaflet. The results provide novel information on the characteristics of populations of V. effusa at fine spatial scales, and provide insights into the dispersal of the organism within and between trees. The proximity of both mating idiomorphs on single leaflets is further evidence of opportunity for development of the sexual stage in the field.

DNA-based quantification of Fusarium oxysporum f. sp. vasinfectum in environmental soils to describe spatial variation in inoculum density

Plant Disease ◽  
2022 ◽  
Author(s):  
Roy Davis ◽  
Thomas Isakeit ◽  
Thomas Chappell
Keyword(s):  
United States ◽  
Fusarium Oxysporum ◽  
Spatial Scales ◽  
The United States ◽  
Inoculum Density ◽  
Root Knot Nematode ◽  
West Texas ◽  
Sudden Appearance ◽  
Digital Polymerase Chain Reaction ◽  
Race 4

Fusarium wilt of cotton, caused by the soilborne fungal pathogen Fusarium oxysporum f. sp. vasinfectum (FOV), occurs in regions of the United States where cotton (Gossypium spp.) is grown. Race 4 of this pathogen (FOV4) is especially aggressive and does not require the co-occurrence of the root knot nematode (Meloidogyne incognita) to infect cotton. Its sudden appearance in far-west Texas in 2016 after many years of being restricted to California is of great concern, as is the threat of its continued spread through the cotton-producing regions of the United States. The aim of this research was to analyze the spatial variability of FOV4 inoculum density in the location where FOV4 is locally emerging, using quantitative and droplet digital polymerase chain reaction (qPCR and ddPCR) methods. Soil samples collected from a field with known FOV4 incidence in Fabens, Texas were analyzed. Appreciable variation in inoculum density was found to occur at spatial scales smaller than the size of plots involved in cultivar trial research, and was spatially autocorrelated (Moran’s I, Z = 17.73, p < 0.0001). These findings indicate that for cultivar trials, accounting for the spatial distribution of inoculum either by directly quantifying it or through the use of densely-distributed “calibration checks” is important to the interpretation of results.

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