Trends In Extreme Indices Research Articles

Impact of the dynamic vegetation on climate extremes during the wheat growing period over China

Extreme temperature and precipitation indices have important implications for the crop growing season. Whether a coupled regional model with carbon–nitrogen cycling (CN) and vegetation dynamics (DV) can better represent these indices during the growing season compared with a model without these modules remains unknown. This study evaluates the performance of extreme indices in three wheat planting regions (including northeast spring wheat, north winter wheat and south winter wheat regions) over China in the period of 1990–2009 using the Regional Climate Model (RegCM) coupled with the Community Land Model (CLM), which include CN and DV. The results show that relative to the RegCM-CLM, both the RegCM-CLM-CN and RegCM-CLM-CN-DV perform better in simulating summer days (SU), consecutive dry days (CDD), consecutive wet days (CWD), and the interannual variability in all the extreme indices in the three regions but produce larger biases on frost days (FD). The trends of extreme indices in the high-impact risk region of wheat are also better captured by the RegCM-CLM with CN or CN-DV compared with the model without these modules. In the northeast spring wheat and southern winter wheat regions, the greater cold bias of mean daily minimum temperature between RegCM-CLM-CN-DV and RegCM-CLM is consistent with the leaf area index (LAI) difference, which may increase evaporative cooling and thus increasing FD biases. Overestimation of the LAI may have a weaker effect than the surface albedo on the mean daily maximum temperature, leading to decreased SU biases in RegCM-CLM-CN-DV relative to RegCM-CLM.

Evaluation of Temperature and Precipitation Simulations in CMIP6 Models Over the Tibetan Plateau

AbstractThis study presents a comprehensive evaluation of the mean and extreme surface air temperature and precipitation in the Coupled Model Intercomparison Project Phase 6 (CMIP6) multimodel ensemble simulations over the Tibetan Plateau. Simulations from 29 climate models are compared against gridded observations for the period 1961–2012. Results show that models reasonably reproduce the overall spatial patterns of the 1961–2012 averages of seasonal mean temperature and precipitation. Nevertheless, models tend to underestimate mean temperature and overestimate precipitation accumulations. To be specific, the multimodel mean estimates of seasonal average temperatures over the plateau are 0.5°C–2.6°C colder than observed, while the corresponding estimates of seasonal precipitation accumulations are 218% (spring: March–May), 76% (summer: June–August), 129% (autumn: September–November), and 533% (winter: December–February) of those observed. As in observations, models also well capture increasing trend of mean temperature and precipitation in all seasons but underestimate the rates of increasing trends for both variables in all seasons. Models’ ability to simulate temperature and precipitation extremes is also evaluated in terms of a set of chosen extreme indices defined by the Expert Team on Climate Change Detection and Indices. On average, models tend to underestimate the averages of annual maximum daily maximum temperature, annual minimum daily minimum temperature, frost days, warm nights, and consecutive dry days but overestimate the corresponding averages of annual maximum 5‐day precipitation accumulations and simply daily intensity. Generally, models are able to simulate the signs of the trends in extreme indices but underestimate their magnitudes and misrepresent spatial patterns.

Characterization of future climate extremes over Tamil Nadu, India, using high-resolution regional climate model simulation

Tamil Nadu, an agriculturally important state in India, is recurrently exposed to floods, cyclones, and droughts that have devastating effects on human, agriculture, and economy. This persuades the study to focus on future climate extremities of the state. The future climate extremes are examined using daily temperature and rainfall simulations developed by Hadley Center’s Regional Climate Model termed PRECIS (Providing REgional Climates for Impacts Studies) at a horizontal resolution of 25 km. The study uses the simulations that are driven by the lateral boundary condition of HadCM3Q0 (Hadley Centre Coupled Model-Q0) generated by a Perturbed Physical Ensemble of 17 ensembles under A1B scenario for the period of 2005 to 2095. Extreme indices have been acquired from the simulations using RClimDex. The trends of extreme indices are computed and verified for statistical significance using Mann–Kendall and Sen’s slope test. The changes in extreme indices with respect to baseline (1970–2000) reveal that almost all temperature indices denote a highly significant trend. The minimum temperature indices have shown prominent increase compared with maximum temperature indices, which is also upheld by the significant decrease in the diurnal temperature range trend. The summer days above 40 °C have indicated a substantial increase with a stronger slope of 0.77. However, the rainfall indices depict the insignificant trend. The changes in extreme wet days (R99p) and very wet days (R95p) exhibit a positive shift, and the increase of maximum 1-day rainfall is projected to be higher than maximum 5-day rainfall. Furthermore, the probability of rainfall indices exemplifies the increase of intense rainfall by the end of the century. The overall results of indices intimate that Tamil Nadu will be shifted to the extreme warmer and wetter condition by 2080s (2065–2095). Such information will act as a baseline to study the future impact assessment on different sectors thereby supporting policymakers and stakeholders to formulate suitable adaptation and mitigation strategies.

Assessment of changing trends of daily precipitation and temperature extremes in Bamako and Ségou in Mali from 1961- 2014

Abstract In Mali the annual rainfall is highly variable, ranging from less than 200 mm–1 300 mm and its distribution is unevenly spread between north and south. Climate change threatens to increase air temperatures and evapotranspiration, increase the risk of intense rainstorms, and increase the risk of heat waves associated with drought. The objective of this study is to assess the change trends of daily temperature and precipitation extremes in Bamako and Segou in Mali during the period between 1961 and - 2014. Analyses of the changes in trends of daily temperature and precipitation extremes in two regions were studied by calculated extreme climate extreme indices series in RClimdex software. Trends in extreme indices were studied for 5 temperature and 4 precipitation series. Results showed a positive significant decrease of warming trends in cool days, cool nights, whereas warm extreme nights, day times and warm spells on the contrary showed positive significant increasing warming throughout the Segou region. In Bamako, temperature extreme showed an insignificant trend for negative extremes decreasing warming trends for cold nights and cold days while warm nights, warm days and warm spells showed insignificant positive trends over the period from 1961 to 2014. The results of precipitation extremes for Segou showed positive significant decrease in consecutive wet day and in extremely wet, whereas Maximum 5 day's precipitation showed positive insignificant increase and the total annual precipitation showed a positive insignificant decrease. In Bamako consecutive wet day, Maximum 5 day's precipitation and total annual precipitation showed positive insignificant decrease. Despite the small number of homogenous temperature and rainfall indices series, the study could present a proportion of significant extremes in Segou station averages trends. The study provided evidence that during the last 53 years; Segou was particularly affected by warm extremes based on night time indices rather than cold extremes based on day time indices.

GRIMs-RMP를 이용한 지역기후모형의 동아시아 극한지수 모의 성능 검증

GRIMs-RMP를 이용한 지역기후모형의 동아시아 극한지수 모의 성능 검증

A 133-Year Record of Climate Change and Variability from Sheffield, England

A 133-year length (1883–2015) daily climate record from Sheffield, England (53.38°N, 1.49°W) is analysed. Across the entire length of the record, there are significant warming trends annually and for all seasons, whereas precipitation shows a significant annual increase but the seasonal trends, whilst all positive, are not significant. Trends in extreme indices mirror the mean long-term warming and wetting signal. Record hot and cold daily temperatures and precipitation amounts are associated with summer anticyclonic conditions, an anomalous easterly winter jet stream and summer cyclonic activity, respectively. Whilst there are large uncertainties surrounding the calculation of return periods for the daily maximum, minimum and precipitation records from a single record, our best estimates suggest that in the current climate (2015), the existing records have return periods of 38, 529 and 252 years, respectively. The influence of several climate indices on mean and extreme indices are considered on seasonal scales, with the North Atlantic Oscillation displaying the strongest relationship. Future mean maximum temperature and precipitation alongside extreme indices representing the warmest and wettest day of the year are analysed from two downscaled climate model output archives under analysis periods of a 1.5 and 2 degree warmer world and the 2080–2099 end of 21st century period. For this mid-latitude location, there is minimal difference in model projections between a 1.5 and 2 degree world, but a significant difference between the 1.5/2 degree world and the end of century 2080–2099 period under the most severe climate warming scenarios.

Assessment of climatic variability in the catchments of Himalayan Lake, Jammu & Kashmir

The present investigation was conducted to analyse the trends in hydrometeorological data to addresses how these trends impacted on the water extent of Wular Lake, Kashmir. Temporal changes in the lake surface area have been analysed, using the Landsat satellite data. The nonparametric Mann–Kendall and Sen’s methods were used to determine trends in hydrometeorological data. In addition, trends in extreme indices of frost days (FD), summer days, days with rainfall > 10 mm (R10), days with rainfall > 20 mm (R20) and dry spell for temperature and precipitation were also analysed. The results suggest an overall decrease in extreme rainfall events, R10 and R20, and annual precipitation pattern with increase in maximum and minimum annual average temperatures. Furthermore, the analysis of extreme temperature events suggests warming trend with increased number of warm days and decreased number of FD. With regard to water extent of the lake, an intense decreasing trend was observed.

Analyses of Observed and Anticipated Changes in Extreme Climate Events in the Northwest Himalaya

In this study, past (1970-2005) as well as future long term (2011-2099) trends in various extreme events of temperature and precipitation have been investigated over selected hydro-meteorological stations in the Sutlej river basin. The ensembles of two Coupled Model Intercomparison Project (CMIP3) models: third generation Canadian Coupled Global Climate Model and Hadley Centre Coupled Model have been used for simulation of future daily time series of temperature (maximum and minimum) and precipitation under A2 emission scenario. Large scale atmospheric variables of both models and National Centre for Environmental Prediction/National Centre for Atmospheric Research reanalysis data sets have been downscaled using statistical downscaling technique at individual stations. A total number of 25 extreme indices of temperature (14) and precipitation (11) as specified by the Expert Team of the World Meteorological Organization and Climate Variability and Predictability are derived for the past and future periods. Trends in extreme indices are detected over time using the modified Mann-Kendall test method. The stations which have shown either decrease or no change in hot extreme events (i.e., maximum TMax, warm days, warm nights, maximum TMin, tropical nights, summer days and warm spell duration indicators) for 1970–2005 and increase in cold extreme events (cool days, cool nights, frost days and cold spell duration indicators) are predicted to increase and decrease respectively in the future. In addition, an increase in frequency and intensity of extreme precipitation events is also predicted.

Regional climate change trends and uncertainty analysis using extreme indices: A case study of Hamilton, Canada

This study aims to provide a deeper understanding of the level of uncertainty associated with the development of extreme weather frequency and intensity indices at the local scale. Several different global climate models, downscaling methods, and emission scenarios were used to develop extreme temperature and precipitation indices at the local scale in the Hamilton region, Ontario, Canada. Uncertainty associated with historical and future trends in extreme indices and future climate projections were also analyzed using daily precipitation and temperature time series and their extreme indices, calculated from gridded daily observed climate data along with and projections from dynamically downscaled datasets of CanRCM4 and PRECIS, and the statistically downscaled CIMP5 ensemble. A bias correction technique was applied to all raw daily temperature and precipitation time series prior to calculation of the indices.All climate models predicted increasing trends for extreme temperature indices, maximum 1-day and 5-day precipitation (RX1day and RX5day), total wet day precipitation (PRCPTOT), very heavy precipitation days (R20mm), Summer Days (SU), and Tropical Nights (TR) and decreasing trend for Forest Days (FD) and Ice Days (ID) in 2020s, 2050s, and 2080s compared to present. CanRCM4 model did consistently project values in the upper range of the CMIP5 ensemble while the PRECIS ensemble was more in-line with the CMIP5 mean values. This difference may however be a function of different emission scenarios used.

Study of Daily Extreme Temperature Indices over Sutlej Basin, N-W Himalayan Region, India

<div> <p>A detailed analysis of extreme temperature indices for the period of 1970-2005 is conducted over Sutlej river basin located in North-West Himalayan region. For this purpose, daily records of maximum and minimum temperature data were procured from Bhakara Beas Management Board, India for four stations. These stations are installed at varying height from 518m to 976m under different physiographic and climatic conditions. Fourteen extreme indices for temperature as specified by the World Meteorological Organization (WMO) Commission for Climatology (CCL)/Climate Variability and Predictability (CLIVAR) Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI) are derived with the aid of RClimDex software.  Linear Regression (LR) method is employed for detecting annual as well as monthly trends in extreme indices of temperature over the period of thirty six years (1970-2005). Large spatial and inter-annual variability in trends of extreme indices is observed. However, a rise in diurnal temperature range is observed for the basin as a whole. This may be attributed to the decrease observed in maximum T<sub>Min</sub> (TXn) and warm nights (TN90p) coupled with the increase in maximum T<sub>Max</sub> (TXx).</p> </div> <p> </p>

Trends in Extreme Indices and Seasonal Analysis of Precipitation and Temperature in the Northwest Region of Rio Grande do Sul, Brazil

Probably the most important environmental challenge of this century is to adapt to climate change and develop strategies to minimize its effects. This study aims to conduct an investigation to detect changes in temperature and precipitation in the northwest region of Rio Grande do Sul with the use of different general and regional circulation models (GCMs and RCMs, respectively). Seven distinct locations in the region were considered, for which there were ten different climate projections. Additionally, we investigated the frequency and intensity of extreme rainfall events using different extreme precipitation indices. These projections indicate an increase of mean annual temperature of almost 3°C till the end of the century, as well as an increase in annual precipitation. The seasonal analysis has demonstrated that the largest increases of temperature are projected for winter and early spring and do not coincide with the summer months of the main crop cultivation (soybean) in the region. Additionally, it is expected high amounts of rain during these same months. In general, trends in extreme precipitation indices were detected for the RCM projections in most of locations. It can also be concluded that it is possible that the spatial distribution of the impacts of climate change on agriculture will not be uniform.

Wintertime circulation types over the Iberian Peninsula: long-term variability and relationships with weather extremes

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 53:205-227 (2012) - DOI: https://doi.org/10.3354/cr01095 Wintertime circulation types over the Iberian Peninsula: long-term variability and relationships with weather extremes S. Fernández-Montes1*, S. Seubert2, F. S. Rodrigo1, E. Hertig2 1Department of Applied Physics, University of Almería, La Cañada de San Urbano, s/n, 04120 Almería, Spain 2Institute of Geography, University of Augsburg. Universitätsstrasse 10, 86135 Augsburg, Germany *Email: soniafm@ual.es ABSTRACT: This paper analyses atmospheric surface circulation and climatic extremes in the Iberian Peninsula in winter (December–February). Sea level pressure grids (1850–2003) are classified through a simulated annealing clustering into 7 characteristic circulation types (CTs). Daily series of temperature (29 stations) and precipitation (44 stations) started between 1905 and 1950. We investigate which CTs are conducive to extremes at each station by means of their contribution to extreme days compared to non-extremes days, with significance based on a Monte Carlo resampling. Regional features arise in the relationship between CTs and extremes and, taking them into account, some trends in extreme indices from 1950–2003 (period shared by all stations) agree with trends in the frequency of the CTs. Thus, increases in warm days in northern and central stations are consistent with a positive trend in Anticyclone over North Iberia/France; and negative trends in extreme precipitation in the East Cantabrian coast are consistent with a negative trend in the north-westerly flow. Furthermore, low-frequency temporal analyses reveal large (small) changes in extreme temperature (precipitation) days within the CTs. From the mid-1940s onwards, the extreme cold character of the northerly and north-easterly flows diminished, i.e. the frequency of cold nights within these CTs decreased from ~25 to ~15%, whereas from the 1920s to mid-1940s an opposite behaviour occurred (towards a higher frequency of cold nights). Throughout the 20th century, the frequency of warm days within the CTs has increased, especially for the south-westerly and westerly flows from the 1920s to 1950s and since the mid-1970s. Westerly flow was less frequent in the 1980s and 1990s but connected with a higher percentage of extreme precipitation days in West Iberia. This changing frequency of extremes within the CTs indicates that, apart from circulation types, other physical forcings have influenced the occurrence of extremes. KEY WORDS: Winter circulation types · Iberian Peninsula · Daily extremes · Temperature · Precipitation · Within-type changes Full text in pdf format PreviousNextCite this article as: Fernández-Montes S, Seubert S, Rodrigo FS, Hertig E (2012) Wintertime circulation types over the Iberian Peninsula: long-term variability and relationships with weather extremes. Clim Res 53:205-227. https://doi.org/10.3354/cr01095 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 53, No. 3. Online publication date: July 19, 2012 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2012 Inter-Research.

Impact of altitude and latitude on changes in temperature extremes over South Asia during 1971–2000

AbstractSouth Asia covers more than 30° of latitude with weather observation stations situated from 6°N at Galle, Sri Lanka, to 36°N at Chitral in Pakistan. Moreover, the South Asian station network ranges in altitude from sea level to nearly 4000 m above sea level. This paper uses time series of 11 objectively defined indices of daily temperature extremes at 197 stations in Bangladesh, India, Nepal, Pakistan and Sri Lanka to examine the possible impacts of elevation and latitude on changes in temperature extremes over the period of 1971–2000. Trends in extreme indices are consistent with general warming only at low altitudes and latitudes. Stations at high altitudes and latitudes show both positive and negative trends in extreme temperature indices. As a notable example, the Diurnal Temperature Range (DTR), which has been known to decrease in most parts of the globe, has increasing trends over many high altitude stations in South Asia. Trends in extreme temperature indices at stations in South Asia higher than 2000 m above sea level are mostly in disagreement with those reported over the Tibetan Plateau. Observed trends at low altitude locations in South Asia suggest that these sites can generally expect future changes in temperature extremes that are consistent with broad‐scale warming. High‐elevation sites appear to be more influenced by local factors and, hence, future changes in temperature extremes may be less predictable for these locations. Copyright © 2012 Royal Meteorological Society

The temporal and spatial structures of recent and future trends in extreme indices over Korea from a regional climate projection

AbstractThe temporal and spatial characteristics of trends in extreme indices over Korea between 1971 and 2100 are investigated using daily minimum (Tmin) and maximum (Tmax) temperature and precipitation data from a regional climate projection at 20 km grid spacing. Five temperature–based indices and five precipitation–based indices are selected to comprehensively consider the frequency, intensity, and persistence of extreme events. In addition, Mann–Kendall tests are used to detect the statistical significance of trends in these indices. For validation during the reference period (1971–2000), the model reasonably simulates the temporal and spatial pattern of the trend. The model captures observed direction and magnitude well in various types of extremes. Indices based on Tmin show a considerable change towards warmer climate conditions while indices based on Tmax do not reveal any distinct trend, implying an asymmetric response of Tmin and Tmax to global warming. Indices of the frequency and intensity of heavy precipitation show a significant increase, whereas the duration of dry and wet consecutive days shows no change. For future projections, the temperature–based indices exhibit a much more significant and consistent trend than the precipitation–based indices, with statistical significance at the 95% confidence level for all indices. The frequency and intensity of heavy precipitation are projected to increase in the 21st century, continuing the trend of the reference climate. Although the future projected changes in the duration of consecutive dry and wet days are not statistically significant, the signal becomes more pronounced with respect to the reference simulation. Copyright © 2010 Royal Meteorological Society

The survey of linkage between climate changes and desertification using extreme climate index software (case study: Kashan).

Climate is the most important factor which control desertification .In order to detect climate changes in desert zones, time trend analysis is applied to extreme indices in Kashan station using extreme climate index software (ECIS). Results show significant trends in extreme indices during the past decade 1995-2004 and the pronounced warming is associated with a negative trend in cold extremes. The finding revealed that the frequency of warm (cold) extreme indices is increased (decreased) and probability, the problem of desertification in Kashan region will be extended. Keywords: Climate change; Desertification; Extreme Climate Indices; Trend, Return Period.