Placing heavy rainfall events in context using long time series: An example from the North York Moors

Weather ◽  
2010 ◽  
Vol 65 (4) ◽  
pp. 88-94 ◽  
Author(s):  
Jonathan Hopkins ◽  
Jeff Warburton ◽  
Tim Burt
Keyword(s):  
Time Series ◽  
Heavy Rainfall ◽  
Rainfall Events ◽  
Long Time Series ◽  
The North ◽  
Long Time ◽  
Heavy Rainfall Events

Cloud Properties over the North Slope of Alaska: Identifying the Prevailing Meteorological Regimes

2012 ◽  
Vol 25 (23) ◽  
pp. 8238-8258 ◽  
Author(s):  
Johannes Mülmenstädt ◽  
Dan Lubin ◽  
Lynn M. Russell ◽  
Andrew M. Vogelmann
Keyword(s):  
Time Series ◽  
Climate Model ◽  
North Slope ◽  
Test Cases ◽  
Synoptic Scale ◽  
Long Time Series ◽  
The North ◽  
Cloud Properties ◽  
North Slope Of Alaska ◽  
Long Time

Abstract Long time series of Arctic atmospheric measurements are assembled into meteorological categories that can serve as test cases for climate model evaluation. The meteorological categories are established by applying an objective k-means clustering algorithm to 11 years of standard surface-meteorological observations collected from 1 January 2000 to 31 December 2010 at the North Slope of Alaska (NSA) site of the U.S. Department of Energy Atmospheric Radiation Measurement Program (ARM). Four meteorological categories emerge. These meteorological categories constitute the first classification by meteorological regime of a long time series of Arctic meteorological conditions. The synoptic-scale patterns associated with each category, which include well-known synoptic features such as the Aleutian low and Beaufort Sea high, are used to explain the conditions at the NSA site. Cloud properties, which are not used as inputs to the k-means clustering, are found to differ significantly between the regimes and are also well explained by the synoptic-scale influences in each regime. Since the data available at the ARM NSA site include a wealth of cloud observations, this classification is well suited for model–observation comparison studies. Each category comprises an ensemble of test cases covering a representative range in variables describing atmospheric structure, moisture content, and cloud properties. This classification is offered as a complement to standard case-study evaluation of climate model parameterizations, in which models are compared against limited realizations of the Earth–atmosphere system (e.g., from detailed aircraft measurements).

scholarly journals An investigation of atmospheric rivers impacting heavy rainfall events in the North‐Central Mississippi River Valley

2019 ◽  
Vol 39 (10) ◽  
pp. 4091-4106
Author(s):  
Jordan L. Rabinowitz ◽  
Anthony R. Lupo ◽  
Patrick S. Market ◽  
Patrick E. Guinan
Keyword(s):  
Mississippi River ◽  
Heavy Rainfall ◽  
River Valley ◽  
Mississippi River Valley ◽  
North Central ◽  
Rainfall Events ◽  
Atmospheric Rivers ◽  
The North ◽  
Heavy Rainfall Events

scholarly journals Effect of Heavy Rainfall Events on the Dry Matter Yield Trend of Whole Crop Maize (Zea mays L.)

Agriculture ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 75 ◽  
Author(s):  
Kim ◽  
Chemere ◽  
Sung
Keyword(s):  
Time Series ◽  
Zea Mays ◽  
Dry Matter ◽  
Heavy Rainfall ◽  
Zea Mays L ◽  
Republic Of Korea ◽  
Dry Matter Yield ◽  
Rainfall Events ◽  
One Year ◽  
Heavy Rainfall Events

The objective of this study was to detect the historical dry matter yield (DMY) trend and to evaluate the effects of heavy rainfall events on the observed DMY trend of whole crop maize (WCM, Zea mays L.) using time-series analysis in Suwon, Republic of Korea. The climatic variables corresponding to the seeding to harvesting period, including the growing degree days, mean temperature, etc., of WCM along with the DMY data (n = 543) during 1982–2011, were used in the analysis. The DMY trend was detected using Autoregressive Integrated Moving Average with the explanatory variables (ARIMAX) form of time-series trend analysis. The optimal DMY model was found to be ARIMAX (1, 1, 1), indicating that the DMY trend follows the mean DMY of the preceding one year and the residual of the preceding one year with an integration level of 1. Furthermore, the SHGDD and SHHR were determined to be the main variables responsible for the observed trend in the DMY of WCM. During heavy rainfall events, the DMY was found to be decreasing by 4745.27 kg/ha (p < 0.01). Our analysis also revealed that both the intensity and frequency of heavy rainfall events have been increasing since 2005. The forecasted DMY indicates the potential decrease, which is expected to be 11,607 kg/ha by 2045. This study provided us evidence for the correlation between the DMY and heavy rainfall events that opens the way to provide solutions for challenges that summer forage crops face in the Republic of Korea.

scholarly journals 2DVD Data Revisited: Multifractal Insights into Cuts of the Spatiotemporal Rainfall Process

2015 ◽  
Vol 16 (2) ◽  
pp. 548-562 ◽  
Author(s):  
Auguste Gires ◽  
Ioulia Tchiguirinskaia ◽  
Daniel Schertzer ◽  
Alexis Berne
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Empirical Evidence ◽  
Heavy Rainfall ◽  
Resolution Time ◽  
Time Step ◽  
Measuring Device ◽  
Rainfall Events ◽  
Heavy Rainfall Events ◽  
Very High

Abstract Data collected during four heavy rainfall events that occurred in Ardèche (France) with the help of a 2D video disdrometer (2DVD) are used to investigate the structure of the raindrop distribution in both space and time. A first type of analysis is based on the reconstruction of 36-m-height vertical rainfall columns above the measuring device. This reconstruction is obtained with the help of a ballistic hypothesis applied to 1-ms time step series. The corresponding snapshots are analyzed with the help of universal multifractals. For comparison, a similar analysis is performed on the time series with 1-ms time steps, as well as on time series of accumulation maps of N consecutive recorded drops (therefore with variable time steps). It turns out that the drop distribution exhibits a good scaling behavior in the range 0.5–36 m during the heaviest portion of the events, confirming the lack of empirical evidence of the widely used homogenous assumption for drop distribution. For smaller scales, drop positions seem to be homogeneously distributed. The notion of multifractal singularity is well illustrated by the very high-resolution time series.

scholarly journals The Relationship between the Pacific–North American Teleconnection Pattern, the Great Plains Low-Level Jet, and North Central U.S. Heavy Rainfall Events*

2015 ◽  
Vol 28 (17) ◽  
pp. 6729-6742 ◽  
Author(s):  
Keith J. Harding ◽  
Peter K. Snyder
Keyword(s):  
United States ◽  
Great Plains ◽  
Heavy Rainfall ◽  
Teleconnection Pattern ◽  
North Central ◽  
Rainfall Events ◽  
The North ◽  
The Pacific ◽  
Central United States ◽  
Heavy Rainfall Events

Abstract This study demonstrates the relationship between the Pacific–North American (PNA) teleconnection pattern and the Great Plains low-level jet (GPLLJ). The negative phase of the PNA, which is associated with lower heights over the Great Plains and ridging in the southeastern United States, enhances the GPLLJ by increasing the pressure gradient within the GPLLJ on 6-hourly to monthly time scales. Strong GPLLJ events predominantly occur when the PNA is negative. Warm-season strong GPLLJ events with a very negative PNA (&lt;−1) are associated with more persistent, longer wavelength planetary waves that increase the duration of GPLLJ events and enhance precipitation over the north central United States. When one considers the greatest 5-day north central U.S. precipitation events, a large majority occur when the PNA is negative, with most exhibiting a very negative PNA. Stronger moisture transport during heavy rainfall events with a very negative PNA decreases the precipitation of locally derived moisture compared to events with a very positive PNA. The PNA becomes negative 2–12 days before heavy rainfall events and is very negative within two weeks of 78% of heavy rainfall events in the north central United States, a finding that could be used to improve medium-range forecasts of heavy rainfall events.

scholarly journals Assessment of parameters and distribution of extremely heavy-rainfall events that occur several times per year

2019 ◽  
Vol 46 (4) ◽  
pp. 438-446
Author(s):  
D. E. Klimenko ◽  
E. S. Cherepanova ◽  
A. Yu. Kuzminykh
Keyword(s):  
Time Series ◽  
Heavy Rainfall ◽  
Ural Mountains ◽  
Reliable Determination ◽  
Rainfall Events ◽  
Use Of Data ◽  
Storm Rainfall ◽  
Short Time ◽  
Heavy Rainfall Events

Applied analyses of a number of datasets containing several highwater-forming storm rainfall events (intense rain for short time periods) per year are examined. The use of data containing several events per year is demonstrated as justified for reliable determination of statistical properties of time series derived from short observation periods. The statistics of time series containing one to several events per year in the Ural Mountains are shown to be well correlated with the frequency of the observed events. Recommendations for recalculation of the time-series statistics containing several events per year versus statistics for one event per year were developed, and a brief comparative analysis of the methods used in Russia is provided.

Low-frequency ambient sound in the North Pacific: Long time series observations

1999 ◽  
Vol 106 (6) ◽  
pp. 3189-3200 ◽  
Author(s):  
Keith R. Curtis ◽  
Bruce M. Howe ◽  
James A. Mercer
Keyword(s):  
Time Series ◽  
North Pacific ◽  
Low Frequency ◽  
Long Time Series ◽  
The North ◽  
Ambient Sound ◽  
Long Time ◽  
The North Pacific

scholarly journals Evaluating Linkages between Atmospheric Blocking Patterns and Heavy Rainfall Events across the North-Central Mississippi River Valley for Different ENSO Phases

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Jordan L. Rabinowitz ◽  
Anthony R. Lupo ◽  
Patrick E. Guinan
Keyword(s):  
Mississippi River ◽  
Heavy Rainfall ◽  
Atmospheric Blocking ◽  
Atmospheric Flow ◽  
Rainfall Events ◽  
The North ◽  
Strong Focus ◽  
Central United States ◽  
The Relationship ◽  
Heavy Rainfall Events

Over the last six to seven decades, there has been a substantial increase in atmospheric research to better understand the dynamics and evolution of atmospheric blocking events. It is well known that atmospheric blocking serves as a catalyst for increasing the frequency of atmospheric flow regime stagnation and forecast unpredictability. This study built upon the results of previous work by expanding upon the findings of various climatologies and case studies. This work analyzes specific trends observed in association with atmospheric blocking predominantly across the central and eastern Pacific Ocean. Such trends include the relationship between the size, duration, and onset position of atmospheric blocking events and the frequency, duration, and intensity of heavy rainfall events across the central United States. A strong focus is placed on examining the duration and spatial extent of atmospheric blocking which has been found to influence the intensity of heavy rainfall events. The goal is to further bridge the gap between the location and duration of blocking highs and the intensity, duration, and frequency of heavy rainfall events which occur downstream of such blocking events.

Sign in / Sign up

Export Citation Format

Share Document