scholarly journals Extreme Precipitation in the Great Lakes Region: Trend Estimation and Relation With Large-Scale Circulation and Humidity

2021 ◽  
Vol 3 ◽  
Author(s):  
Andrew Paxton ◽  
Justin T. Schoof ◽  
Trent W. Ford ◽  
Jonathan W. F. Remo
Keyword(s):  
Great Lakes ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Ordinary Least Squares ◽  
Specific Humidity ◽  
Great Lakes Region ◽  
Self Organizing Map ◽  
Precipitation Frequency ◽  
Urban Floods ◽  
The U.S

Extreme precipitation contributes to widespread impacts in the U.S. Great Lakes region, ranging from agricultural losses to urban floods and associated infrastructure costs. Previous studies have reported historical increases in the frequency of extreme precipitation in the region and downscaled model projections indicate further changes as the climate system continues to warm. Here, we conduct trend analysis on the 5 km NOAA NClimDiv data for the U.S. Great Lakes region using both parametric (Ordinary Least Squares) and non-parametric methods (Theil-Sen/Mann-Kendall) and accounting for temporal autocorrelation and field significance to produce robust estimates of extreme precipitation frequency trends in the region. The approaches provide similar overall results and reflect an increase in extreme precipitation frequency in parts of the U.S. Great Lakes region. To relate the identified trends to large scale drivers, a bivariate self-organizing map (SOM) is constructed using standardized values of 500 hPa geo-potential height and 850 hPa specific humidity obtained from the ECMWF ERA-5 reanalysis. Using a Monte Carlo approach, we identify six SOM nodes that account for only 25.4% of all days, but 50.5% of extreme precipitation days. Composites of days with and without extreme precipitation for each node indicate that extreme events are associated with stronger features (height gradient and background humidity) than their non-extreme counterparts. The analysis also identifies a significant increase in the frequency of one SOM node often associated with extreme precipitation (accounting for 8.5% of all extreme precipitation days) and a significant increase in the frequency of extreme precipitation days relative to all days across the six extreme precipitation nodes collectively. Our results suggest that changes in atmospheric circulation and related moisture transport and convergence are major contributors to changes in extreme precipitation in the U.S. Great Lakes region.

scholarly journals Geospatial Analysis of Extreme Weather Events in Nigeria (1985–2015) Using Self-Organizing Maps

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Adeoluwa Akande ◽  
Ana Cristina Costa ◽  
Jorge Mateu ◽  
Roberto Henriques
Keyword(s):  
Extreme Precipitation ◽  
Large Scale ◽  
Northern Region ◽  
Extreme Weather Events ◽  
Self Organizing Map ◽  
Spatial And Temporal Patterns ◽  
Self Organizing Maps ◽  
The North ◽  
Precipitation Regimes ◽  
Self Organizing

The explosion of data in the information age has provided an opportunity to explore the possibility of characterizing the climate patterns using data mining techniques. Nigeria has a unique tropical climate with two precipitation regimes: low precipitation in the north leading to aridity and desertification and high precipitation in parts of the southwest and southeast leading to large scale flooding. In this research, four indices have been used to characterize the intensity, frequency, and amount of rainfall over Nigeria. A type of Artificial Neural Network called the self-organizing map has been used to reduce the multiplicity of dimensions and produce four unique zones characterizing extreme precipitation conditions in Nigeria. This approach allowed for the assessment of spatial and temporal patterns in extreme precipitation in the last three decades. Precipitation properties in each cluster are discussed. The cluster closest to the Atlantic has high values of precipitation intensity, frequency, and duration, whereas the cluster closest to the Sahara Desert has low values. A significant increasing trend has been observed in the frequency of rainy days at the center of the northern region of Nigeria.

Implications of the 2012 U.S. Election for U.S. Policy in Africa’s Great Lakes Region

2013 ◽  
Vol 56 (2) ◽  
pp. 185-191
Author(s):  
Georges Nzongola-Ntalaja
Keyword(s):  
United States ◽  
Natural Resources ◽  
Great Lakes ◽  
Democratic Republic ◽  
The United States ◽  
Great Lakes Region ◽  
Security Sector ◽  
White House ◽  
Republic Of The Congo ◽  
The U.S

Abstract:While Africans are generally satisfied that a person of African descent was reelected to the White House following a campaign in which vicious and racist attacks were made against him, the U.S. Africa policy under President Barack Obama will continue to be guided by the strategic interests of the United States, which are not necessarily compatible with the popular aspirations for democracy, peace, and prosperity in Africa. Obama’s policy in the Great Lakes region provides an excellent illustration of this point. Since Rwanda and Uganda are Washington’s allies in the “war against terror” in Darfur and Somalia, respectively, the Obama administration has done little to stop Kigali and Kampala from destabilizing the Democratic Republic of the Congo (DRC) and looting its natural resources, either directly or through proxies. Rwanda and Uganda have even been included in an international oversight mechanism that is supposed to guide governance and security sector reforms in the DRC, but whose real objective is to facilitate Western access to the enormous natural wealth of the Congo and the Great Lakes region.

scholarly journals Evaluation of SMAP Level 2, 3, and 4 Soil Moisture Datasets over the Great Lakes Region

2020 ◽  
Vol 12 (22) ◽  
pp. 3785
Author(s):  
Xiaoyong Xu
Keyword(s):  
Soil Moisture ◽  
Great Lakes ◽  
Root Zone ◽  
Evaluation Studies ◽  
Reference Network ◽  
Great Lakes Region ◽  
Sparse Network ◽  
Level 2 ◽  
The U.S

Satellite sensor systems for soil moisture measurements have been continuously evolving. The Soil Moisture Active Passive (SMAP) mission represents one of the latest advances in this regard. Thus far, much of our knowledge of the accuracy of SMAP soil moisture over the Great Lakes region of North America has originated from evaluation studies using in situ data from the U.S. Department of Agriculture (USDA) Natural Resources Conservation Service Soil Climate Analysis Network and/or the U.S. Climate Reference Network, which provide only several in situ sensor stations for this region. As such, these results typically underrepresent the accuracy of SMAP soil moisture in this region, which is characterized by a relatively large soil moisture variability and is one of the least studied regions. In this work, SMAP Level 2‒4 soil moisture products: SMAP/Sentinel-1 L2 Radiometer/Radar Soil Moisture (SPL2SMAP_S), SMAP Enhanced L3 Radiometer Soil Moisture (SPL3SMP_E), and SMAP L4 Surface and Root-Zone Soil Moisture Analysis Update (SPL4SMAU) are evaluated over the southern portion of the Great Lakes region using in situ measurements from Michigan State University’s Enviro-weather Automated Weather Station Network. The unbiased root-mean-square error (ubRMSE) values for both SPL4SMAU surface and root zone soil moisture estimates are below 0.04 m3 m−3 at the 36-km scale, with an average ubRMSE of 0.045 m3 m−3 (0.037 m3 m−3) for the surface (root-zone) soil moisture against the sparse network. The ubRMSE values for SPL3SMP_E a.m. (i.e., descending overpasses) soil moisture retrievals are close to or below 0.04 m3 m−3 at the 36-km scale, with an average ubRMSE of ~0.06 m3 m−3 against the sparse network. The average ubRMSE values are ~0.05‒0.06 m3 m−3 for high-resolution SPL2SMAP_S soil moisture retrievals against the sparse network, with the skill of the baseline algorithm-based soil moisture retrievals exceeding that of the optional algorithm-based counterparts. Clearly, the skill of SPL4SMAU surface soil moisture exceeds that of the SPL3SMP_E and SPL2SMAP_S soil moisture retrievals.

A 1400-Year Bølling-Allerød Tree-Ring Record from the U.S. Great Lakes Region

2017 ◽  
Vol 73 (2) ◽  
pp. 102-112 ◽  
Author(s):  
Irina P. Panyushkina ◽  
Steven W. Leavitt ◽  
William N. Mode
Keyword(s):  
Great Lakes ◽  
Tree Ring ◽  
Great Lakes Region ◽  
The U.S

scholarly journals Genetic population structure of fishers (Pekania pennanti) in the Great Lakes region: remnants and reintroductions

2017 ◽  
Vol 95 (11) ◽  
pp. 869-876 ◽  
Author(s):  
Paul Hapeman ◽  
Emily K. Latch ◽  
Olin E. Rhodes ◽  
Brad Swanson ◽  
C. William Kilpatrick
Keyword(s):  
Population Structure ◽  
Genetic Structure ◽  
Great Lakes ◽  
Large Scale ◽  
Spatial Scales ◽  
Genetic Population Structure ◽  
Great Lakes Region ◽  
Eastern United States ◽  
Genetic Population ◽  
Pekania Pennanti

Reintroduction programs have been pivotal in augmenting populations of fishers (Pekania pennanti (Erxleben, 1777)) and re-establishing them to their former range in North America. The majority of reintroduction efforts in fishers have been considered demographically successful, but reintroductions can alter genetic population structure and success has rarely been evaluated in fishers from a genetic standpoint. We used microsatellite data (n = 169) to examine genetic population structure of fishers in the Great Lakes region and comment on the success of past reintroductions at two different spatial scales. We found significant genetic population structure among source and reintroduced populations within the Great Lakes region and large-scale genetic structure between fisher populations located in two geographically distant regions (Great Lakes and Northeast) in the eastern United States. Reintroductions associated with the Great Lakes produced results that were largely consistent with other studies of fisher reintroductions in the Northeast. However, our data are the first to support a measurable impact on genetic population structure in Pekania pennanti pennanti (Erxleben, 1777) from a reintroduction using geographically distant source and reintroduced populations. When feasible, we strongly recommend that reintroduction programs include an investigation of the underlying genetic structure to better define intended goals and supplement measures of demographic success.

scholarly journals Correction: Responses of deposition and bioaccumulation in the Great Lakes region to policy and other large-scale drivers of mercury emissions

2019 ◽  
Vol 21 (6) ◽  
pp. 1065-1066
Author(s):  
J. A. Perlinger ◽  
N. R. Urban ◽  
A. Giang ◽  
N. E. Selin ◽  
A. N. Hendricks ◽  
...  
Keyword(s):  
Great Lakes ◽  
Large Scale ◽  
Great Lakes Region ◽  
Mercury Emissions

Correction for ‘Responses of deposition and bioaccumulation in the Great Lakes region to policy and other large-scale drivers of mercury emissions’ by J. A. Perlinger et al., Environ. Sci.: Processes Impacts, 2018, 20, 195–209.

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.

Climate Change and Waterborne Disease Risk in the Great Lakes Region of the U.S.

2008 ◽  
Vol 35 (5) ◽  
pp. 451-458 ◽  
Author(s):  
Jonathan A. Patz ◽  
Stephen J. Vavrus ◽  
Christopher K. Uejio ◽  
Sandra L. McLellan
Keyword(s):  
Climate Change ◽  
Great Lakes ◽  
Disease Risk ◽  
Great Lakes Region ◽  
Waterborne Disease ◽  
The U.S

scholarly journals Application to NWP Models Verification of an Atmospheric Circulation Patterns Classification

2021 ◽  
Author(s):  
Raffaele Salerno ◽  
Laura Bertolani
Keyword(s):  
Large Scale ◽  
Precipitation Forecast ◽  
Specific Humidity ◽  
Forecast Errors ◽  
Self Organizing Map ◽  
Model Ensemble ◽  
Climate Services ◽  
Global Models ◽  
Circulation Patterns ◽  
Synoptic Circulation

<p>At Meteo Expert, a Italian private organization providing weather and climate services and formerly known as Epson Meteo Centre, we are using the Self Organizing Map (SOM) algorithm to study synoptic circulation over Southern Europe, evaluating the capability of five NWP global models and one multi-model ensemble to predict its variability in order to relate synoptic circulation patterns to temperature and precipitation forecast’s quality over Italy. SOM is an iterative algorithm that ‘learns’ the patterns of the input data vectors and organizes them into nodes within the SOM space, arranging like patterns in neighboring nodes and the most unlike patterns in nodes farthest from each other. Daily observed and predicted weather types from the five NWP global models and the multi-model ensemble were recognized and classified by the SOM. The SOM-based classification built for our purposes produces a 12-weather-type set using daily 500 hPa and 700 hPa geopotential, sea level pressure, 850 hPa temperature and 700 hPa specific humidity. The five global models are GFS from National Centers for Environmental Prediction, IFS from European Centre for Medium-Range Weather (ECMWF), Arpege from Meteo France, GEM from Canadian Meteorological Centre, ICON from Deutscher Wetterdienst, together with MIX, our multi-model ensemble. Here we would like to present some examples of this operational activity in the one-year-period, also showing how much the source of forecast errors may depend on large-scale dynamics rather than model's physical parameterisations. A quality index has been used to quantify the overall ability of models in predicting the circulation patterns, showing that MIX and ECMWF reached the best performance within 96 hours of forecast.</p>

scholarly journals Twenty-First-Century Changes in U.S. Regional Heavy Precipitation Frequency Based on Resolved Atmospheric Patterns

2017 ◽  
Vol 30 (7) ◽  
pp. 2501-2521 ◽  
Author(s):  
Xiang Gao ◽  
C. Adam Schlosser ◽  
Paul A. O’Gorman ◽  
Erwan Monier ◽  
Dara Entekhabi
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Heavy Precipitation ◽  
First Century ◽  
Specific Humidity ◽  
Atmospheric Conditions ◽  
Precipitation Frequency ◽  
Model Based ◽  
Twenty First Century ◽  
Precipitation Events

Precipitation-gauge observations and atmospheric reanalysis are combined to develop an analogue method for detecting heavy precipitation events based on prevailing large-scale atmospheric conditions. Combinations of atmospheric variables for circulation (geopotential height and wind vector) and moisture (surface specific humidity, column and up to 500-hPa precipitable water) are examined to construct analogue schemes for the winter [December–February (DJF)] of the “Pacific Coast California” (PCCA) region and the summer [June–August (JJA)] of the Midwestern United States (MWST). The detection diagnostics of analogue schemes are calibrated with 1979–2005 and validated with 2006–14 NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA). All analogue schemes are found to significantly improve upon MERRA precipitation in characterizing the occurrence and interannual variations of observed heavy precipitation events in the MWST. When evaluated with the late twentieth-century climate model simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5), all analogue schemes produce model medians of heavy precipitation frequency that are more consistent with observations and have smaller intermodel discrepancies than model-based precipitation. Under the representative concentration pathways (RCP) 4.5 and 8.5 scenarios, the CMIP5-based analogue schemes produce trends in heavy precipitation occurrence through the twenty-first century that are consistent with model-based precipitation, but with smaller intermodel disparity. The median trends in heavy precipitation frequency are positive for DJF over PCCA but are slightly negative for JJA over MWST. Overall, the analyses highlight the potential of the analogue as a powerful diagnostic tool for model deficiencies and its complementarity to an evaluation of heavy precipitation frequency based on model precipitation alone.

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