scholarly journals Are Temperature and Precipitation Extremes Increasing over the U.S. High Plains?

2012 ◽  
Vol 16 (16) ◽  
pp. 1-20 ◽  
Author(s):  
Di Long ◽  
Bridget R. Scanlon ◽  
D. Nelun Fernando ◽  
Lei Meng ◽  
Steven M. Quiring

Abstract Large-scale environmental, social, and economic impacts of recent weather and climate extremes are raising questions about whether the frequency and intensity of these extremes have been increasing. Here, the authors evaluate trends in climate extremes during the past half century using the U.S. High Plains as a case study. A total of eight different extreme indices and the standardized precipitation index (SPI) were evaluated using daily maximum and minimum temperature and precipitation data from 207 stations and 0.25° gridded data. The 1958–2010 time period was selected to exclude the 1950s and 2011 droughts. Results show general consistency between the station data and gridded data. The annual extreme temperature range (ETR) decreased significantly (p < 0.05) in ~54% of the High Plains, with a spatial mean rate of −0.7°C decade−1. Decreases in ETR result primarily from increases in annual lowest temperature in ~63% of the stations at a mean rate of ~0.9°C decade−1, whereas increases in annual highest temperature were much less. Approximately 43% of the stations showed increasing warm nights (Tmin90) with a spatial mean rate of 0.5% decade−1. Precipitation intensity generally did not vary significantly in most grid cells and stations. Significant decreasing trends in consecutive dry days (CDD) were restricted to 21% of the stations in the northern High Plains with a spatial mean of −0.8 days decade−1. Areas experiencing severe dry periods (1-month SPI < −1.5) decreased over time from 8% to 4%. The number of dry months (SPI < 0) in each year also decreased. In summary, the ETR is decreasing and low temperatures are increasing. Precipitation extremes are generally not changing in the High Plains; however, high natural climatic variability in this semiarid region makes it difficult to assess climate extremes.

2016 ◽  
Vol 55 (5) ◽  
pp. 1169-1182 ◽  
Author(s):  
Lei Wang ◽  
Zhi-Jun Yao ◽  
Li-Guang Jiang ◽  
Rui Wang ◽  
Shan-Shan Wu ◽  
...  

AbstractThe spatiotemporal changes in 21 indices of extreme temperature and precipitation for the Mongolian Plateau from 1951 to 2012 were investigated on the basis of daily temperature and precipitation data from 70 meteorological stations. Changes in catastrophic events, such as droughts, floods, and snowstorms, were also investigated for the same period. The correlations between catastrophic events and the extreme indices were examined. The results show that the Mongolian Plateau experienced an asymmetric warming trend. Both the cold extremes and warm extremes showed greater warming at night than in the daytime. The spatial changes in significant trends showed a good homogeneity and consistency in Inner Mongolia. Changes in the precipitation extremes were not as obvious as those in the temperature extremes. The spatial distributions in changes of precipitation extremes were complex. A decreasing trend was shown for total precipitation from west to east as based on the spatial distribution of decadal trends. Drought was the most serious extreme disaster, and prolonged drought for longer than 3 yr occurred about every 7–11 yr. An increasing trend in the disaster area was apparent for flood events from 1951 to 2012. A decreasing trend was observed for the maximum depth of snowfall from 1951 to 2012, with a decreased average maximum depth of 10 mm from the 1990s.


2018 ◽  
Author(s):  
Kishore Pangaluru ◽  
Isabella Velicogna ◽  
Tyler C. Sutterley ◽  
Yara Mohajerani ◽  
Enrico Ciraci ◽  
...  

Abstract. Changes in extreme temperature and precipitation may give some of the largest significant societal and ecological impacts. For changes in the magnitude of extreme temperature and precipitation over India, we used a statistical model of generalized extreme value (GEV) distribution. The GEV statistical distribution is a time-dependent distribution with different time scales of variability bounded by a precipitation, maximum (Tmax), and minimum (Tmin) temperature extremes and also assessed their possibility changes are evaluated and quantified over India is presented. The GEV-based method is applied on both precipitation and temperature extremes over India during the 20th and 21st centuries using multiple coupled climate models taking an interest in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and observational datasets. The regional means of historical warm extreme temperatures are 34.89, 36.42, and 38.14 °C for three different (10, 20, and 50-year) periods, respectively; whereas the cold extreme mean temperatures are 7.75, 4.19, and −1.57 °C. It indicates that 20th century cold extreme temperatures have relatively larger variations than the warm extremes. As for the future, the CMIP5 models of warm extreme regional mean values increase from 0.33 to 0.75 °C in all return periods (10-, 20-, and 50-year periods), while in the case of cold extreme means values vary between 0.58 and 2.29 °C. In the future, cold extreme values have a larger increasing rate over the northwest, northeast, some parts of north-central, and Inter Peninsula regions. The CRU precipitation extremes are larger than the historical extreme precipitation in all three (10, 20, and 50-year) return-periods.


2020 ◽  
Author(s):  
Bridget Scanlon ◽  
Ashraf Rateb ◽  
Alexander Sun ◽  
Himanshu Save

<p>There is considerable concern about water depletion caused by climate extremes (e.g., drought) and human water use in the U.S. and globally. Major U.S. aquifers provide an ideal laboratory to assess water storage changes from GRACE satellites because the aquifers are intensively monitored and modeled. The objective of this study was to assess the relative importance of climate extremes and human water use on GRACE Total Water Storage Anomalies in 14 major U.S. aquifers and to evaluate the reliability of the GRACE data by comparing with groundwater level monitoring (~-23,000 wells) and regional and global models. We quantified total water and groundwater storage anomalies over 2002 – 2017 from GRACE satellites and compared GRACE data with groundwater level monitoring and regional and global modeling results.  </p> <p>The results show that water storage changes were controlled primarily by climate extremes and amplified or dampened by human water use, primarily irrigation. The results were somewhat surprising, with stable or rising long-term trends in the majority of aquifers with large scale depletion limited to agricultural areas in the semi-arid southwest and southcentral U.S. GRACE total water storage in the California Central Valley and Central/Southern High Plains aquifers was depleted by drought and amplified by groundwater irrigation, totaling ~70 km<sup>3</sup> (2002–2017), about 2× the capacity of Lake Mead, the largest surface reservoir in the U.S. In the Pacific Northwest and Northern High Plains aquifers, lower drought intensities were partially dampened by conjunctive use of surface water and groundwater for irrigation and managed aquifer recharge, increasing water storage by up to 22 km<sup>3</sup> in the Northern High Plains over the 15 yr period. GRACE-derived total water storage changes in the remaining aquifers were stable or slightly rising throughout the rest of the U.S.</p> <p>GRACE data compared favorably with composite groundwater level hydrographs for most aquifers except for those with very low signals, indicating that GRACE tracks groundwater storage dynamics. Comparison with regional models was restricted to the limited overlap periods but showed good correspondence for modeled aquifers with the exception of the Mississippi Embayment, where the modeled trend is 4x the GRACE trend. The discrepancy is attributed to uncertainties in model storage parameters and groundwater/surface water interactions. Global hydrologic models (WGHM-2d and PCR-GLOBWB-5.0 overestimated trends in groundwater storage in heavily exploited aquifers in the southwestern and southcentral U.S. Land surface models (CLSM-F2.5 and NOAH-MP) seem to track GRACE TWSAs better than global hydrologic models but underestimated TWS trends in aquifers dominated by irrigation.</p> <p>Intercomparing GRACE, traditional hydrologic monitoring, and modeling data underscore the importance of considering all data sources to constrain water storage changes.  GRACE satellite data have critical implications for many nationally important aquifers, highlighting the importance of conjunctively using surface-water and groundwater and managed aquifer recharge to enhance sustainable development.</p>


2019 ◽  
Vol 45 (1) ◽  
pp. 393 ◽  
Author(s):  
F. Ferrelli ◽  
A.S. Brendel ◽  
V.S. Aliaga ◽  
M.C. Piccolo ◽  
G.M.E. Perillo

The south of Pampas (36° 32’-40° 44’ S; 63° 24’-60° 30’ W), as most of Argentina, is a semiarid region. Its economy is based on rain-fed agriculture and livestock. Traditionally, the climate has been studied considering the analyses of monthly and annual climate parameters, but there is evidence that in this type of areas, the short-term climatic events have a substantial impact on the climate. Therefore, this study aimed at developing a climate regionalization from the analysis of daily temperature and precipitation extremes in the south of the Pampas for the period 1970-2017. Subsequently, it focuses on analyzing both trends and breakpoints of these events in the different sub-climates. To do so, we applied a Cluster-based Principal Component Analyses with a Ward hierarchical supervised method to generate a climate regionalization considering 29 daily extreme climatic indices and the elevation. We identify four sub-regions, and we analyzed trends during 1970-2017, and in the two-time series defined by applying breakpoints. Both minimum and maximum temperatures and precipitation had structural changes in the last 15 years, exposing the region to warming and dryness trends. The maximum temperature increases 0.5ºC, while precipitation decreases 30 mm. The short-term climate variability allows us to identify areas climatically more detailed and to conclude that the south of the Pampas is characterized by its high dependency on short-term climatic events.


Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2535
Author(s):  
Jintao Zhang ◽  
Fang Wang

Limiting the global temperature increase to a level that would prevent “dangerous anthropogenic interference with the climate system” is the focus of intergovernmental climate negotiations, and the cost-benefit analysis to determine this level requires an understanding of how the risk associated with climate extremes varies with different warming levels. We examine daily extreme temperature and precipitation variances with continuous global warming using a non-stationary extreme value statistical model based on the Coupled Model Intercomparison Project Phase 5 (CMIP5). Our results show the probability of extreme warm and heavy precipitation events over East Asia (EA) will increase, while that of cold extremes over EA will decrease as global warming increases. A present-day 1-in-20-year heavy precipitation extreme in EA is projected to increase to 1.3, 1.6, 2.5, and 3.4 times more frequently of the current climatology, at the global mean warming levels of 1.5 °C, 2 °C, 3 °C, and 4 °C above the preindustrial era, respectively. Moreover, the relative changes in probability are larger for rarer events. These results contribute to an improved understanding of the future risk associated with climate extremes, which helps scientists create mitigation measures for global warming and facilitates policy-making.


2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Karin van der Wiel ◽  
Richard Bintanja

AbstractThe frequency of climate extremes will change in response to shifts in both mean climate and climate variability. These individual contributions, and thus the fundamental mechanisms behind changes in climate extremes, remain largely unknown. Here we apply the probability ratio concept in large-ensemble climate simulations to attribute changes in extreme events to either changes in mean climate or climate variability. We show that increased occurrence of monthly high-temperature events is governed by a warming mean climate. In contrast, future changes in monthly heavy-precipitation events depend to a considerable degree on trends in climate variability. Spatial variations are substantial however, highlighting the relevance of regional processes. The contributions of mean and variability to the probability ratio are largely independent of event threshold, magnitude of warming and climate model. Hence projections of temperature extremes are more robust than those of precipitation extremes, since the mean climate is better understood than climate variability.


2021 ◽  
Vol 168 (1-2) ◽  
Author(s):  
Dipesh Chapagain ◽  
Sanita Dhaubanjar ◽  
Luna Bharati

AbstractExisting climate projections and impact assessments in Nepal only consider a limited number of generic climate indices such as means. Few studies have explored climate extremes and their sectoral implications. This study evaluates future scenarios of extreme climate indices from the list of the Expert Team on Sector-specific Climate Indices (ET-SCI) and their sectoral implications in the Karnali Basin in western Nepal. First, future projections of 26 climate indices relevant to six climate-sensitive sectors in Karnali are made for the near (2021–2045), mid (2046–2070), and far (2071–2095) future for low- and high-emission scenarios (RCP4.5 and RCP8.5, respectively) using bias-corrected ensembles of 19 regional climate models from the COordinated Regional Downscaling EXperiment for South Asia (CORDEX-SA). Second, a qualitative analysis based on expert interviews and a literature review on the impact of the projected climate extremes on the climate-sensitive sectors is undertaken. Both the temperature and precipitation patterns are projected to deviate significantly from the historical reference already from the near future with increased occurrences of extreme events. Winter in the highlands is expected to become warmer and dryer. The hot and wet tropical summer in the lowlands will become hotter with longer warm spells and fewer cold days. Low-intensity precipitation events will decline, but the magnitude and frequency of extreme precipitation events will increase. The compounding effects of the increase in extreme temperature and precipitation events will have largely negative implications for the six climate-sensitive sectors considered here.


2015 ◽  
Vol 28 (23) ◽  
pp. 9206-9220 ◽  
Author(s):  
Andrea J. Dittus ◽  
David J. Karoly ◽  
Sophie C. Lewis ◽  
Lisa V. Alexander

Abstract This study examines trends in the area affected by temperature and precipitation extremes across five large-scale regions using the climate extremes index (CEI) framework. Analyzing changes in temperature and precipitation extremes in terms of areal fraction provides information from a different perspective and can be useful for climate monitoring. Trends in five temperature and precipitation components are analyzed, calculated using a new method based on standard extreme indices. These indices, derived from daily meteorological station data, are obtained from two global land-based gridded extreme indices datasets. The four continental-scale regions of Europe, North America, Asia, and Australia are analyzed over the period from 1951 to 2010, where sufficient data coverage is available. These components are also computed for the entire Northern Hemisphere, providing the first CEI results at the hemispheric scale. Results show statistically significant increases in the percentage area experiencing much-above-average warm days and nights and much-below-average cool days and nights for all regions, with the exception of North America for maximum temperature extremes. Increases in the area affected by precipitation extremes are also found for the Northern Hemisphere regions, particularly Europe and North America.


2014 ◽  
Vol 27 (13) ◽  
pp. 5019-5035 ◽  
Author(s):  
Markus G. Donat ◽  
Jana Sillmann ◽  
Simon Wild ◽  
Lisa V. Alexander ◽  
Tanya Lippmann ◽  
...  

Changes in climate extremes are often monitored using global gridded datasets of climate extremes based on in situ observations or reanalysis data. This study assesses the consistency of temperature and precipitation extremes between these datasets. Both the temporal evolution and spatial patterns of annual extremes of daily values are compared across multiple global gridded datasets of in situ observations and reanalyses to make inferences on the robustness of the obtained results. While normalized time series generally compare well, the actual values of annual extremes of daily data differ systematically across the different datasets. This is partly related to different computational approaches when calculating the gridded fields of climate extremes. There is strong agreement between extreme temperatures in the different in situ–based datasets. Larger differences are found for temperature extremes from the reanalyses, particularly during the presatellite era, indicating that reanalyses are most consistent with purely observational-based analyses of changes in climate extremes for the three most recent decades. In terms of both temporal and spatial correlations, the ECMWF reanalyses tend to show greater agreement with the gridded in situ–based datasets than the NCEP reanalyses and Japanese 25-year Reanalysis Project (JRA-25). Extreme precipitation is characterized by higher temporal and spatial variability than extreme temperatures, and there is less agreement between different datasets than for temperature. However, reasonable agreement between the gridded observational precipitation datasets remains. Extreme precipitation patterns and time series from reanalyses show lower agreement but generally still correlate significantly.


2019 ◽  
Vol 139 (3-4) ◽  
pp. 1137-1149 ◽  
Author(s):  
Dong An ◽  
Yiheng Du ◽  
Ronny Berndtsson ◽  
Zuirong Niu ◽  
Linus Zhang ◽  
...  

AbstractTemperature and precipitation extremes are the dominant causes of natural disasters. In this study, seven indices of extreme temperature and precipitation events in Gansu Province, China, were analysed for the period 1961–2017. An abrupt climate shift was recorded during 1980–1981. Thus, the study period was divided into a preshift (before the climate shift) period 1961–1980 and an aftshift (after the climate shift) period 1981–2017. Comparison of mean extreme indices for preshift and aftshift periods was performed for the purpose of exploring possible increasing/decreasing patterns. Generalized extreme value (GEV) distribution was applied spatially to fit the extreme indices with return periods up to 100 years for preshift/aftshift periods. Singular value decomposition (SVD) was adopted to investigate possible correlation between the extreme climate events and indices of large-scale atmospheric circulation. The results indicate that changes in mean and return levels between the preshift and aftshift periods vary significantly in time and space for different extreme indices. Increase in extreme temperature regarding magnitude and frequency for the aftshift period as compared with the preshift period suggests a change to a warmer and more extreme climate during recent years. Changes in precipitation extremes were different in southern and northern parts of Gansu. The precipitation extremes in the north have increased that can result in more serious floods and droughts in the future. SVD analyses revealed a complex pattern of correlation between climate extremes and indices of large-scale atmospheric circulation. Strengthening of westerlies and weakening of the south summer monsoon contribute to the complex changing patterns of precipitation extremes. Results in this study will contribute to disaster risk prevention and better water management in this area.


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