ORCID Profile
0000-0002-5635-2457
Current Organisation
University of New South Wales
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Publisher: Springer Science and Business Media LLC
Date: 17-06-2017
Publisher: Springer Science and Business Media LLC
Date: 11-12-2010
Publisher: Frontiers Media SA
Date: 04-12-2019
Publisher: Springer Science and Business Media LLC
Date: 28-05-2016
Publisher: American Geophysical Union (AGU)
Date: 07-09-2017
DOI: 10.1002/2017JD027345
Publisher: Elsevier BV
Date: 2013
Publisher: Springer Science and Business Media LLC
Date: 04-03-2019
Publisher: American Meteorological Society
Date: 06-01-2023
Abstract: Robust conclusions regarding changes in the temperature distribution rely on the accuracy and reliability of the input datasets used. Differences between methodologies and datasets in previous studies add uncertainty when comparing and quantifying findings. Here, the authors investigate the sensitivity of assessing global and regional temperature variability and extremes over 1980–2014 in gridded datasets of daily temperature anomalies. A gridded in situ–based dataset, Hadley Centre Global Historical Climatology Network–Daily (HadGHCND), is compared against several commonly used reanalysis products by assessing both the entire distribution and the tails of the distribution. Empirical probability distribution functions show sensitivity to the input dataset when estimating aspects such as standard deviation and skewness, with the mean showing robust results for most regions, irrespective of dataset choice. Standard deviation is especially sensitive, with larger disagreements between datasets for some regions more than others, such as Africa and the Mediterranean region, and with larger differences in minimum temperatures compared with maximum temperatures. Estimates of extreme parameters also show sensitivity to dataset choice, particularly in the lower tails and for daily minimum temperature anomalies. Comparing changes in the means and the extremes of the temperature distributions, the cold extremes in the lower tails have been warming at a faster rate than the mean of the entire distribution for much of the Northern Hemisphere extratropics, with warm extremes warming at a faster rate than the mean in some subtropical regions. These documented sensitivities call for caution when assessing changes in temperature variability and extremes, as dataset choice can have substantial effects on results.
Publisher: American Meteorological Society
Date: 12-2015
DOI: 10.1175/JCLI-D-14-00753.1
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.
Publisher: Springer Science and Business Media LLC
Date: 16-09-2009
Publisher: Copernicus GmbH
Date: 27-02-2020
Abstract: Abstract. We present a new global land-based daily precipitation dataset from 1950 using an interpolated network of in situ data called Rainfall Estimates on a Gridded Network – REGEN. We merged multiple archives of in situ data including two of the largest archives, the Global Historical Climatology Network – Daily (GHCN-Daily) hosted by National Centres of Environmental Information (NCEI), USA, and one hosted by the Global Precipitation Climatology Centre (GPCC) operated by Deutscher Wetterdienst (DWD). This resulted in an unprecedented station density compared to existing datasets. The station time series were quality-controlled using strict criteria and flagged values were removed. Remaining values were interpolated to create area-average estimates of daily precipitation for global land areas on a 1∘ × 1∘ latitude–longitude resolution. Besides the daily precipitation amounts, fields of standard deviation, kriging error and number of stations are also provided. We also provide a quality mask based on these uncertainty measures. For those interested in a dataset with lower station network variability we also provide a related dataset based on a network of long-term stations which interpolates stations with a record length of at least 40 years. The REGEN datasets are expected to contribute to the advancement of hydrological science and practice by facilitating studies aiming to understand changes and variability in several aspects of daily precipitation distributions, extremes and measures of hydrological intensity. Here we document the development of the dataset and guidelines for best practices for users with regards to the two datasets.
Publisher: Wiley
Date: 12-05-2017
DOI: 10.1002/JOC.4769
Publisher: American Geophysical Union (AGU)
Date: 15-03-2019
DOI: 10.1029/2018JD029541
Publisher: American Meteorological Society
Date: 31-05-2013
DOI: 10.1175/JCLI-D-12-00502.1
Abstract: This study investigates the presence of trends in annual maximum daily precipitation time series obtained from a global dataset of 8326 high-quality land-based observing stations with more than 30 years of record over the period from 1900 to 2009. Two complementary statistical techniques were adopted to evaluate the possible nonstationary behavior of these precipitation data. The first was a Mann–Kendall nonparametric trend test, and it was used to evaluate the existence of monotonic trends. The second was a nonstationary generalized extreme value analysis, and it was used to determine the strength of association between the precipitation extremes and globally averaged near-surface temperature. The outcomes are that statistically significant increasing trends can be detected at the global scale, with close to two-thirds of stations showing increases. Furthermore, there is a statistically significant association with globally averaged near-surface temperature, with the median intensity of extreme precipitation changing in proportion with changes in global mean temperature at a rate of between 5.9% and 7.7% K−1, depending on the method of analysis. This ratio was robust irrespective of record length or time period considered and was not strongly biased by the uneven global coverage of precipitation data. Finally, there is a distinct meridional variation, with the greatest sensitivity occurring in the tropics and higher latitudes and the minima around 13°S and 11°N. The greatest uncertainty was near the equator because of the limited number of sufficiently long precipitation records, and there remains an urgent need to improve data collection in this region to better constrain future changes in tropical precipitation.
Publisher: Wiley
Date: 17-11-2021
Publisher: American Meteorological Society
Date: 16-07-2019
Abstract: Trends in mean and extreme annual and seasonal temperature and precipitation over the 1951–2015 period were calculated for 57 stations in 20 western Pacific Ocean island countries and territories. The extremes indices are those of the World Meteorological Organization Expert Team on Sector-Specific Climate Indices. The purpose of the expert team and indices is to promote the use of globally consistent climate indices to highlight variability and trends in climate extremes that are of particular interest to socioeconomic sectors and to help to characterize the climate sensitivity of various sectors. Prior to the calculation of the monthly means and indices, the data underwent quality control and homogeneity assessment. A rise in mean temperature occurred at most stations, in all seasons, and in both halves of the study period. The temperature indices also showed strong warming, which for the majority was strongest in December–February and weakest in June–August. The absolute and percentile-based indices show the greatest warming at the upper end of the distribution. While changes in precipitation were less consistent and trends were generally weak at most locations, declines in both total and extreme precipitation were found in southwestern French Polynesia and the southern subtropics. There was a decrease in moderate- to high-intensity precipitation events, especially those experienced over multiple days, in southwestern French Polynesia from December to February. Strong drying trends have also been identified in the low- to moderate-extreme indices in the June–August and September–November periods. These negative trends contributed to an increase in the magnitude of meteorological drought in both subregions.
Publisher: Pleiades Publishing Ltd
Date: 06-2009
Publisher: Springer Science and Business Media LLC
Date: 09-11-2020
DOI: 10.1038/S41598-020-75445-3
Abstract: Prolonged high-temperature extreme events in the ocean, marine heatwaves, can have severe and long-lasting impacts on marine ecosystems, fisheries and associated services. This study applies a marine heatwave framework to analyse a global sea surface temperature product and identify the most extreme events, based on their intensity, duration and spatial extent. Many of these events have yet to be described in terms of their physical attributes, generation mechanisms, or ecological impacts. Our synthesis identifies commonalities between marine heatwave characteristics and seasonality, links to the El Niño-Southern Oscillation, triggering processes and impacts on ocean productivity. The most intense events preferentially occur in summer, when climatological oceanic mixed layers are shallow and winds are weak, but at a time preceding climatological maximum sea surface temperatures. Most subtropical extreme marine heatwaves were triggered by persistent atmospheric high-pressure systems and anomalously weak wind speeds, associated with increased insolation, and reduced ocean heat losses. Furthermore, the most extreme events tended to coincide with reduced chlorophyll- a concentration at low and mid-latitudes. Understanding the importance of the oceanic background state, local and remote drivers and the ocean productivity response from past events are critical steps toward improving predictions of future marine heatwaves and their impacts.
Publisher: American Meteorological Society
Date: 08-2007
Publisher: American Geophysical Union (AGU)
Date: 07-2005
DOI: 10.1029/2005GL022371
Publisher: Copernicus GmbH
Date: 10-02-2020
Abstract: Abstract. Cold extremes are anticipated to warm at a faster rate than both hot extremes and average temperatures for much of the Northern Hemisphere. Anomalously warm cold extremes can affect numerous sectors, including human health, tourism and various ecosystems that are sensitive to cold temperatures. Using a selection of global climate models, this paper explores the accelerated warming of seasonal cold extremes relative to seasonal mean temperatures in the Northern Hemisphere extratropics. The potential driving physical mechanisms are investigated by assessing conditions on or prior to the day when the cold extreme occurs to understand how the different environmental fields are related. During winter, North America, Europe and much of Eurasia show lified warming of cold extremes projected for the late 21st century, compared to the mid-20th century. This is shown to be largely driven by reductions in cold air temperature advection, suggested as a likely consequence of Arctic lification. In spring and autumn, cold extremes are expected to warm faster than average temperatures for most of the Northern Hemisphere mid-latitudes to high latitudes, particularly Alaska, northern Canada and northern Eurasia. In the shoulder seasons, projected decreases in snow cover and associated reductions in surface albedo are suggested as the largest contributor affecting the accelerated rates of warming in cold extremes. The key findings of this study improve our understanding of the environmental conditions that contribute to the accelerated warming of cold extremes relative to mean temperatures.
Publisher: American Meteorological Society
Date: 2008
Abstract: The authors estimate the change in extreme winter weather events over Europe that is due to a long-term change in the North Atlantic Oscillation (NAO) such as that observed between the 1960s and 1990s. Using ensembles of simulations from a general circulation model, large changes in the frequency of 10th percentile temperature and 90th percentile precipitation events over Europe are found from changes in the NAO. In some cases, these changes are comparable to the expected change in the frequency of events due to anthropogenic forcing over the twenty-first century. Although the results presented here do not affect anthropogenic interpretation of global and annual mean changes in observed extremes, they do show that great care is needed to assess changes due to modes of climate variability when interpreting extreme events on regional and seasonal scales. How changes in natural modes of variability, such as the NAO, could radically alter current climate model predictions of changes in extreme weather events on multidecadal time scales is also discussed.
Publisher: Springer Science and Business Media LLC
Date: 20-03-2023
DOI: 10.1007/S00382-023-06751-5
Abstract: This study focuses on future seasonal changes in daily precipitation using Regional Climate Models (RCMs) from the Coordinated Regional Climate Downscaling Experiments-Southeast Asia ensemble (CORDEX-SEA). Projections using this RCM ensemble generally show a larger inter-model spread in winter than in summer, with higher significance and model agreement in summer over most land areas. We evaluate how well the RCMs simulate climatological precipitation using two skill metrics. To extract reliable projections, two sub-ensembles of ‘better’ and ‘worse’ performing models are selected and their respective projections compared. We find projected intensification of summer precipitation over northern SEA, which is robust across RCMs. On the contrary, in the southern part of SEA, the ‘worse’ ensemble projects a significant and widespread decrease in summer rainfall intensity whereas a slight intensification is projected by the ‘better’ ensemble. Further exploration of inter-model differences in future changes reveals that these are mainly explained by changes in moisture supply from large-scale sources (i.e., moisture convergence) with enhanced effects from local sources (i.e., evapotranspiration). The ‘worse’ models project greater changes in atmospheric circulation compared with the ‘better’ models, which can explain part of the uncertainty in projections for daily precipitation over the CORDEX-SEA domain. Hence, our findings might help assess more reliable projections over the SEA region by selecting models based on a two-step model evaluation: the ability of models to simulate historical daily precipitation and their performance in reproducing key physical processes of the regional climate.
Publisher: Springer Science and Business Media LLC
Date: 07-03-2016
DOI: 10.1038/NCLIMATE2941
Publisher: IOP Publishing
Date: 23-04-2020
Abstract: A range of in situ , satellite and reanalysis products on a common daily 1° × 1° latitude/longitude grid were extracted from the Frequent Rainfall Observations on Grids database to help facilitate intercomparison and analysis of precipitation extremes on a global scale. 22 products met the criteria for this analysis, namely that daily data were available over global land areas from 50°S to 50°N since at least 2001. From these daily gridded data, 10 annual indices that represent aspects of extreme precipitation frequency, duration and intensity were calculated. Results were analysed for in idual products and also for four cluster types: (i) in situ , (ii) corrected satellite, (iii) uncorrected satellite and (iv) reanalyses. Climatologies based on a common 13-year period (2001–2013) showed substantial differences between some products. Timeseries (which ranged from 13 years to 67 years) also highlighted some substantial differences between products. A coefficient of variation showed that the in situ products were most similar to each other while reanalysis products had the largest variations. Reanalyses however agreed better with in situ observations over extra-tropical land areas compared to the satellite clusters, although reanalysis products tended to fall into ‘wet’ and ‘dry’ c s overall. Some indices were more robust than others across products with daily precipitation intensity showing the least variation between products and days above 20 mm showing the largest variation. In general, the results of this study show that global space-based precipitation products show the potential for climate scale analyses of extremes. While we recommend caution for all products dependent on their intended application, this particularly applies to reanalyses which show the most ergence across results.
Publisher: American Meteorological Society
Date: 27-02-2015
Abstract: The Australian east coast low (ECL) is both a major cause of damaging severe weather and an important contributor to rainfall and dam inflow along the east coast, and is of interest to a wide range of groups including catchment managers and emergency services. For this reason, several studies in recent years have developed and interrogated databases of east coast lows using a variety of automated cyclone detection methods and identification criteria. This paper retunes each method so that all yield a similar event frequency within the ECL region, to enable a detailed intercomparison of the similarities, differences, and relative advantages of each method. All methods are shown to have substantial skill at identifying ECL events leading to major impacts or explosive development, but the choice of method significantly affects both the seasonal and interannual variation of detected ECL numbers. This must be taken into consideration in studies on trends or variability in ECLs, with a subcategorization of ECL events by synoptic situation of key importance.
Publisher: Springer Science and Business Media LLC
Date: 26-02-2014
DOI: 10.1038/NCLIMATE2145
Publisher: IOP Publishing
Date: 06-12-2019
Publisher: Springer Science and Business Media LLC
Date: 10-04-2018
DOI: 10.1038/S41467-018-03732-9
Abstract: Heatwaves are important climatic extremes in atmospheric and oceanic systems that can have devastating and long-term impacts on ecosystems, with subsequent socioeconomic consequences. Recent prominent marine heatwaves have attracted considerable scientific and public interest. Despite this, a comprehensive assessment of how these ocean temperature extremes have been changing globally is missing. Using a range of ocean temperature data including global records of daily satellite observations, daily in situ measurements and gridded monthly in situ-based data sets, we identify significant increases in marine heatwaves over the past century. We find that from 1925 to 2016, global average marine heatwave frequency and duration increased by 34% and 17%, respectively, resulting in a 54% increase in annual marine heatwave days globally. Importantly, these trends can largely be explained by increases in mean ocean temperatures, suggesting that we can expect further increases in marine heatwave days under continued global warming.
Publisher: Springer Science and Business Media LLC
Date: 06-05-2015
Publisher: Wiley
Date: 12-06-2022
DOI: 10.1002/GDJ3.163
Abstract: Millions of sub‐daily sea‐level pressure observations taken between 1919 and 1960 over the British and Irish Isles were transcribed from paper records in the early 2000s but were not published and subsequently forgotten. A chance discussion led to the rediscovery of the transcribed data and 5.47 million observations from 160 locations are now made available, although the data have not been fully quality‐controlled. Much of the data are 3‐hourly, allowing for detailed examinations of synoptic weather variations for this region and time period, and will be invaluable for constraining future reanalyses. We illustrate the value of the data using a stormy period during October and November 1928 and discuss the remaining quality‐control issues.
Publisher: American Meteorological Society
Date: 07-2013
DOI: 10.1175/JCLI-D-12-00383.1
Abstract: Despite their adverse impacts, definitions and measurements of heat waves are ambiguous and inconsistent, generally being endemic to only the group affected, or the respective study reporting the analysis. The present study addresses this issue by employing a set of three heat wave definitions, derived from surveying heat-related indices in the climate science literature. The definitions include three or more consecutive days above one of the following: the 90th percentile for maximum temperature, the 90th percentile for minimum temperature, and positive extreme heat factor (EHF) conditions. Additionally, each index is studied using a multiaspect framework measuring heat wave number, duration, participating days, and the peak and mean magnitudes. Observed climatologies and trends computed by Sen's Kendall slope estimator are presented for the Australian continent for two time periods (1951–2008 and 1971–2008). Trends in all aspects and definitions are smaller in magnitude but more significant for 1951–2008 than for 1971–2008. Considerable similarities exist in trends of the yearly number of days participating in a heat wave and yearly heat wave frequency, suggesting that the number of available heat wave days drives the number of events. Larger trends in the hottest part of a heat wave suggest that heat wave intensity is increasing faster than the mean magnitude. Although the direct results of this study cannot be inferred for other regions, the methodology has been designed as such that it is widely applicable. Furthermore, it includes a range of definitions that may be useful for a wide range of systems impacted by heat waves.
Publisher: Wiley
Date: 22-10-2008
DOI: 10.1002/JOC.1765
Publisher: SAGE Publications
Date: 02-2007
Abstract: In 1990 and 1992 the Intergovernmental Panel on Climate Change (IPCC), in its first assessment of climate change and its supplement, did not consider whether extreme weather events had increased in frequency and/or intensity globally, because data were too sparse to make this a worthwhile exercise. In 1995 the IPCC, in its second assessment, did examine this question, but concluded that data and analyses of changes in extreme events were ‘not comprehensive’and thus the question could not be answered with any confidence. Since then, concerted multinational efforts have been undertaken to collate, quality control, and analyse data on weather and climate extremes. A comprehensive examination of the question of whether extreme events have changed in frequency or intensity is now more feasible than it was 15 years ago. The processes that have led to this position are described, along with current understanding of possible changes in some extreme weather and climate events.
Publisher: Wiley
Date: 07-2000
Publisher: Wiley
Date: 10-06-2019
DOI: 10.1002/JOC.6138
Publisher: American Meteorological Society
Date: 03-11-2016
Abstract: The skill of eight climate models in simulating the variability and trends in the observed areal extent of daily temperature and precipitation extremes is evaluated across five large-scale regions, using the climate extremes index (CEI) framework. Focusing on Europe, North America, Asia, Australia, and the Northern Hemisphere, results show that overall the models are generally able to simulate the decadal variability and trends of the observed temperature and precipitation components over the period 1951–2005. Climate models are able to reproduce observed increasing trends in the area experiencing warm maximum and minimum temperature extremes, as well as, to a lesser extent, increasing trends in the areas experiencing an extreme contribution of heavy precipitation to total annual precipitation for the Northern Hemisphere regions. Using simulations performed under different radiative forcing scenarios, the causes of simulated and observed trends are investigated. A clear anthropogenic signal is found in the trends in the maximum and minimum temperature components for all regions. In North America, a strong anthropogenically forced trend in the maximum temperature component is simulated despite no significant trend in the gridded observations, although a trend is detected in a reanalysis product. A distinct anthropogenic influence is also found for trends in the area affected by a much-above-average contribution of heavy precipitation to annual precipitation totals for Europe in a majority of models and to varying degrees in other Northern Hemisphere regions. However, observed trends in the area experiencing extreme total annual precipitation and extreme number of wet and dry days are not reproduced by climate models under any forcing scenario.
Publisher: American Geophysical Union (AGU)
Date: 17-03-2022
DOI: 10.1029/2021GL097002
Abstract: Marine cold‐spell (MCS) metrics—such as frequency and intensity—are decreasing globally, while marine heatwave (MHW) metrics are increasing due to sea surface temperature (SST) warming. However, the concomitant changes in MHW and MCS metrics, and whether SST warming can similarly explain the decreasing MCS metrics remain unclear. Here, we provide a comparative global assessment of these changes based on satellite SST observations over 1982–2020. Across the globe, we find distinct differences in mean MHW and MCS metrics. Furthermore, decreasing trends in MCS metrics are not necessarily aligned with increasing trends in MHW metrics. While differences in intensity trends are mainly explained by SST variance trends, differences in trends of annual days are less clear. Overall, decreasing MCS days and intensities are found to be largely driven by warming SST, rather than SST variance changes. Therefore, it is expected that MCS days and intensity will continue diminishing under global warming.
Publisher: American Meteorological Society
Date: 29-07-2014
DOI: 10.1175/JCLI-D-13-00715.1
Abstract: Leading patterns of observed monthly extreme rainfall variability in Australia are examined using an empirical orthogonal teleconnection (EOT) method. Extreme rainfall variability is more closely related to mean rainfall variability during austral summer than in winter. The leading EOT patterns of extreme rainfall explain less variance in Australia-wide extreme rainfall than is the case for mean rainfall EOTs. The authors illustrate that, as with mean rainfall, the El Niño–Southern Oscillation (ENSO) has the strongest association with warm-season extreme rainfall variability, while in the cool season the primary drivers are atmospheric blocking and the subtropical ridge. The Indian Ocean dipole and southern annular mode also have significant relationships with patterns of variability during austral winter and spring. Leading patterns of summer extreme rainfall variability have predictability several months ahead from Pacific sea surface temperatures (SSTs) and as much as a year in advance from Indian Ocean SSTs. Predictability from the Pacific is greater for wetter-than-average summer months than for months that are drier than average, whereas for the Indian Ocean the relationship has greater linearity. Several cool-season EOTs are associated with midlatitude synoptic-scale patterns along the south and east coasts. These patterns have common atmospheric signatures denoting moist onshore flow and strong cyclonic anomalies often to the north of a blocking anticyclone. Tropical cyclone activity is observed to have significant relationships with some warm-season EOTs. This analysis shows that extreme rainfall variability in Australia can be related to remote drivers and local synoptic-scale patterns throughout the year.
Publisher: Springer Science and Business Media LLC
Date: 08-04-2015
Publisher: Hindawi Limited
Date: 2015
DOI: 10.1155/2015/325718
Abstract: Daily gridded precipitation data are needed for investigating spatiotemporal variability of precipitation, including extremes however, uncertainties related to daily precipitation products are large. Here, we compare a range of precipitation grids for Australia. These datasets include products derived solely from in situ observations (interpolated datasets) and two products that combine both remote sensed data and in situ observations. We find that all precipitation grids have similar climatologies for annual aggregated precipitation totals and annual maximum precipitation. The temporal correlations of daily precipitation values are higher between the interpolated datasets, but the correlations between the most widely used interpolated product (AWAP) and the two remotely sensed products (TRMM and GPCP) are still reasonable. Our results, however, point to distinct structural uncertainties between those datasets gridding in situ observations and those datasets deriving precipitation estimates primarily from satellite measurements. All datasets analysed agree well for low to moderate daily precipitation amounts up to about 20 mm but erge at upper quantiles, indicating that substantial uncertainty exists in gridded precipitation extremes over Australia.
Publisher: American Geophysical Union (AGU)
Date: 19-01-2017
DOI: 10.1002/2016JD025842
Publisher: American Geophysical Union (AGU)
Date: 14-04-2017
DOI: 10.1002/2016JD026256
Publisher: Ubiquity Press, Ltd.
Date: 27-11-2015
DOI: 10.1016/J.AOGH.2015.07.003
Abstract: Many studies have explored the relationship between temperature and health in the context of a changing climate, but few have considered the effects of humidity, particularly in tropical locations, on human health and well-being. To investigate this potential relationship, this study assessed the main and interacting effects of daily temperature and humidity on hospital admission rates for selected heat-relevant diagnoses in Darwin, Australia. Univariate and bivariate Poisson generalized linear models were used to find statistically significant predictors and the admission rates within bins of predictors were compared to explore nonlinear effects. The analysis indicated that nighttime humidity was the most statistically significant predictor (P < 0.001), followed by daytime temperature and average daily humidity (P < 0.05). There was no evidence of a significant interaction between them or other predictors. The nighttime humidity effect appeared to be strongly nonlinear: Hot days appeared to have higher admission rates when they were preceded by high nighttime humidity. From this analysis, we suggest that heat-health policies in tropical regions similar to Darwin need to accommodate the effects of temperature and humidity at different times of day.
Publisher: MDPI AG
Date: 13-02-2014
Publisher: Elsevier BV
Date: 09-2016
Publisher: IOP Publishing
Date: 05-2019
Abstract: Climate extremes, such as droughts or heat waves, can lead to harvest failures and threaten the livelihoods of agricultural producers and the food security of communities worldwide. Improving our understanding of their impacts on crop yields is crucial to enhance the resilience of the global food system. This study analyses, to our knowledge for the first time, the impacts of climate extremes on yield anomalies of maize, soybeans, rice and spring wheat at the global scale using sub-national yield data and applying a machine-learning algorithm. We find that growing season climate factors—including mean climate as well as climate extremes—explain 20%–49% of the variance of yield anomalies (the range describes the differences between crop types), with 18%–43% of the explained variance attributable to climate extremes, depending on crop type. Temperature-related extremes show a stronger association with yield anomalies than precipitation-related factors, while irrigation partly mitigates negative effects of high temperature extremes. We developed a composite indicator to identify hotspot regions that are critical for global production and particularly susceptible to the effects of climate extremes. These regions include North America for maize, spring wheat and soy production, Asia in the case of maize and rice production as well as Europe for spring wheat production. Our study highlights the importance of considering climate extremes for agricultural predictions and adaptation planning and provides an overview of critical regions that are most susceptible to variations in growing season climate and climate extremes.
Publisher: American Thoracic Society
Date: 05-2018
Publisher: IOP Publishing
Date: 26-05-2016
Publisher: American Geophysical Union (AGU)
Date: 03-2006
DOI: 10.1029/2005JD006280
Publisher: Wiley
Date: 10-2002
DOI: 10.1002/JOC.773
Publisher: American Geophysical Union (AGU)
Date: 27-08-2014
DOI: 10.1002/2014RG000464
Publisher: American Geophysical Union (AGU)
Date: 09-2006
DOI: 10.1029/2006GL026131
Publisher: Springer Science and Business Media LLC
Date: 26-03-2019
Publisher: American Geophysical Union (AGU)
Date: 27-10-2012
DOI: 10.1029/2012GL053361
Publisher: American Geophysical Union (AGU)
Date: 07-06-2019
DOI: 10.1029/2019GL081898
Publisher: Elsevier BV
Date: 09-2018
Publisher: American Meteorological Society
Date: 15-01-2015
DOI: 10.1175/JCLI-D-14-00645.1
Abstract: The climate of the eastern seaboard of Australia is strongly influenced by the passage of low pressure systems over the adjacent Tasman Sea due to their associated precipitation and their potential to develop into extreme weather events. The aim of this study is to quantify differences in the climatology of east coast lows derived from the use of six global reanalyses. The methodology is explicitly designed to identify differences between reanalyses arising from differences in their horizontal resolution and their structure (type of forecast model, assimilation scheme, and the kind and number of observations assimilated). As a basis for comparison, reanalysis climatologies are compared with an observation-based climatology. Results show that reanalyses, specially high-resolution products, lead to very similar climatologies of the frequency, intensity, duration, and size of east coast lows when using spatially smoothed (about 300-km horizontal grid meshes) mean sea level pressure fields as input data. Moreover, at these coarse horizontal scales, monthly, interannual, and spatial variabilities appear to be very similar across the various reanalyses with a generally stronger agreement between winter events compared with summer ones. Results also show that, when looking at cyclones using reanalysis data at their native resolution (approaching 50-km grid spacing for the most recent products), uncertainties related to the frequency, intensity, and size of lows are very large and it is not clear which reanalysis, if any, gives a better description of cyclones. Further work is needed in order to evaluate the usefulness of the finescale information in modern reanalyses and to better understand the sources of their differences.
Publisher: MDPI AG
Date: 03-12-2015
Publisher: Springer Science and Business Media LLC
Date: 09-01-2016
Publisher: Wiley
Date: 31-10-2011
DOI: 10.1002/WCC.147
Abstract: Indices for climate variability and extremes have been used for a long time, often by assessing days with temperature or precipitation observations above or below specific physically‐based thresholds. While these indices provided insight into local conditions, few physically based thresholds have relevance in all parts of the world. Therefore, indices of extremes evolved over time and now often focus on relative thresholds that describe features in the tails of the distributions of meteorological variables. In order to help understand how extremes are changing globally, a subset of the wide range of possible indices is now being coordinated internationally which allows the results of studies from different parts of the world to fit together seamlessly. This paper reviews these as well as other indices of extremes and documents the obstacles to robustly calculating and analyzing indices and the methods developed to overcome these obstacles. Gridding indices are necessary in order to compare observations with climate model output. However, gridding indices from daily data are not always straightforward because averaging daily information from many stations tends to d en gridded extremes. The paper describes recent progress in attribution of the changes in gridded indices of extremes that demonstrates human influence on the probability of extremes. The paper also describes model projections of the future and wraps up with a discussion of ongoing efforts to refine indices of extremes as they are being readied to contribute to the IPCC's Fifth Assessment Report. WIREs Clim Change 2011, 2:851–870. doi: 10.1002/wcc.147 This article is categorized under: Paleoclimates and Current Trends Modern Climate Change
Publisher: Springer Science and Business Media LLC
Date: 14-06-2019
DOI: 10.1038/S41467-019-10206-Z
Abstract: Marine heatwaves (MHWs) can cause devastating impacts to marine life. Despite the serious consequences of MHWs, our understanding of their drivers is largely based on isolated case studies rather than any systematic unifying assessment. Here we provide the first global assessment under a consistent framework by combining a confidence assessment of the historical refereed literature from 1950 to February 2016, together with the analysis of MHWs determined from daily satellite sea surface temperatures from 1982–2016, to identify the important local processes, large-scale climate modes and teleconnections that are associated with MHWs regionally. Clear patterns emerge, including coherent relationships between enhanced or suppressed MHW occurrences with the dominant climate modes across most regions of the globe – an important exception being western boundary current regions where reports of MHW events are few and ocean-climate relationships are complex. These results provide a global baseline for future MHW process and prediction studies.
Publisher: American Meteorological Society
Date: 07-2013
Publisher: American Geophysical Union (AGU)
Date: 16-10-2012
DOI: 10.1029/2012GL053409
Publisher: American Geophysical Union (AGU)
Date: 07-07-2020
DOI: 10.1029/2019JD032184
Publisher: American Geophysical Union (AGU)
Date: 24-09-2009
DOI: 10.1029/2009JD012301
Publisher: Springer Science and Business Media LLC
Date: 03-2019
DOI: 10.1007/S00484-019-01697-Y
Abstract: The authors of the article would like to bring the following correction/corrigendum to attention: When recently investigating future changes in heat stress indices, we discovered an error in the use of the heatwave indices we compared in Goldie et al. (2017).
Publisher: Elsevier BV
Date: 03-2017
Publisher: Wiley
Date: 15-04-2011
DOI: 10.1002/JOC.2118
Publisher: Wiley
Date: 28-06-2017
DOI: 10.1002/JOC.4812
Publisher: American Meteorological Society
Date: 03-2018
Abstract: The sparse nature of observational records across the mid- to high latitudes of the Southern Hemisphere limits the ability to place late-twentieth-century environmental changes in the context of long-term (multidecadal and centennial) variability. Historical records from subantarctic islands offer considerable potential for developing highly resolved records of change. In 1905, a whaling and meteorological station was established at Grytviken on subantarctic South Georgia in the South Atlantic (54°S, 36°W), providing near-continuous daily observations through to present day. This paper reports a new, daily observational record of temperature and precipitation from Grytviken, which is compared to regional datasets and historical reanalysis. The authors find a shift toward increasingly warmer daytime extremes commencing from the mid-twentieth century and accompanied by warmer nighttime temperatures, with an average rate of temperature rise of 0.13°C decade −1 over the period 1907–2016 ( p 0.0001). Analysis of these data and reanalysis products suggest a change of pervasive synoptic conditions across the mid- to high latitudes since the mid-twentieth century, characterized by stronger westerly airflow and associated warm föhn winds across South Georgia. This rapid rate of warming and associated declining habitat suitability has important negative implications for bio ersity, including the survival of key marine biota in the region.
Publisher: Copernicus GmbH
Date: 12-12-2014
Abstract: Abstract. We assess the effects of different methodological choices made during the construction of gridded data sets of climate extremes, focusing primarily on HadEX2. Using global land-surface time series of the indices and their coverage, as well as uncertainty maps, we show that the choices which have the greatest effect are those relating to the station network used or that drastically change the values for in idual grid boxes. The latter are most affected by the number of stations required in or around a grid box and the gridding method used. Most parametric changes have a small impact, on global and on grid box scales, whereas structural changes to the methods or input station networks may have large effects. On grid box scales, trends in temperature indices are very robust to most choices, especially in areas which have high station density (e.g. North America, Europe and Asia). The precipitation indices, being less spatially correlated, can be more susceptible to methodological choices, but coherent changes are still clear in regions of high station density. Regional trends from all indices derived from areas with few stations should be treated with care. On a global scale, the linear trends over 1951–2010 from almost all choices fall within the 5–95th percentile range of trends from HadEX2. This demonstrates the robust nature of HadEX2 and related data sets to choices in the creation method.
Publisher: Springer Science and Business Media LLC
Date: 27-06-2016
Publisher: American Meteorological Society
Date: 07-2014
DOI: 10.1175/JCLI-D-13-00405.1
Abstract: 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.
Publisher: IOP Publishing
Date: 09-2015
Publisher: Springer Science and Business Media LLC
Date: 09-01-2017
DOI: 10.1038/NCLIMATE3201
Publisher: American Geophysical Union (AGU)
Date: 07-2011
DOI: 10.1029/2011GL047995
Publisher: American Geophysical Union (AGU)
Date: 28-08-2018
DOI: 10.1029/2018GL078875
Publisher: Springer Science and Business Media LLC
Date: 11-04-2016
Publisher: American Geophysical Union (AGU)
Date: 24-11-2005
DOI: 10.1029/2005JD006181
Publisher: Wiley
Date: 21-07-2008
DOI: 10.1002/JOC.1730
Publisher: Elsevier BV
Date: 02-2016
Publisher: Wiley
Date: 27-11-2013
DOI: 10.1002/JOC.3874
Publisher: Elsevier BV
Date: 03-2016
Publisher: Wiley
Date: 22-11-2013
DOI: 10.1002/JOC.3861
Publisher: Wiley
Date: 2020
Publisher: Elsevier BV
Date: 09-2015
Publisher: Elsevier BV
Date: 08-2017
Abstract: To find appropriate regression model specifications for counts of the daily hospital admissions of a Sydney cohort and determine which human heat stress indices best improve the models' fit. We built parent models of eight daily counts of admission records using weather station observations, census population estimates and public holiday data. We added heat stress indices models with lower Akaike Information Criterion scores were judged a better fit. Five of the eight parent models demonstrated adequate fit. Daily maximum Simplified Wet Bulb Globe Temperature (sWBGT) consistently improved fit more than most other indices temperature and heatwave indices also modelled some health outcomes well. Humidity and heat-humidity indices better fit counts of patients who died following admission. Maximum sWBGT is an ideal measure of heat stress for these types of Sydney hospital admissions. Simple temperature indices are a good fallback where a narrower range of conditions is investigated. Implications for public health: This study confirms the importance of selecting appropriate heat stress indices for modelling. Epidemiologists projecting Sydney hospital admissions should use maximum sWBGT as a common measure of heat stress. Health organisations interested in short-range forecasting may prefer simple temperature indices.
Publisher: American Geophysical Union (AGU)
Date: 28-07-2012
DOI: 10.1029/2012GL052459
Publisher: American Meteorological Society
Date: 03-2010
Abstract: A high-quality daily dataset of in situ mean sea level pressure was collated for Australia for the period from 1907 to 2006. This dataset was used to assess changes in daily synoptic pressure patterns over Australia in winter using the method of self-organizing maps (SOMs). Twenty patterns derived from the in situ pressure observations were mapped to patterns derived from ERA-40 data to create daily synoptic pressure fields for the past century. Changes in the frequencies of these patterns were analyzed. The patterns that have been decreasing in frequency were generally those most strongly linked to variations in the southern annular mode (SAM) index, while patterns that have increased in frequency were more strongly correlated with variations in the positive phase of El Niño–Southern Oscillation. In general, there has been a reduction in the rain-bearing systems affecting southern Australia since the beginning of the twentieth century. Over the past century, reductions in the frequencies of synoptic patterns with a marked trough to the south of the country were shown to be linked to significant reductions in severe storms in southeast Australia and decreases in rainfall at four major Australian cities: Sydney, Melbourne, Adelaide, and Perth. Of these, Perth showed the most sustained decline in both the mean and extremes of rainfall linked to changes in the large-scale weather systems affecting Australia over the past century. The results suggest a century-long decline in the frequency of low pressure systems reaching southern Australia, consistent with the southward movement of Southern Hemisphere storm tracks. While most of these trends were not significant, associated changes in rainfall and storminess appear to have had significant impacts in the region.
Publisher: American Geophysical Union (AGU)
Date: 23-05-2013
DOI: 10.1002/GRL.50427
Publisher: American Geophysical Union (AGU)
Date: 25-02-2012
DOI: 10.1029/2011JD016382
Publisher: American Geophysical Union (AGU)
Date: 17-07-2003
DOI: 10.1029/2002JD002670
Publisher: Wiley
Date: 08-06-2009
DOI: 10.1002/JOC.1965
Publisher: Elsevier BV
Date: 12-2017
Publisher: American Geophysical Union (AGU)
Date: 15-03-2006
DOI: 10.1029/2005JD006290
Publisher: Wiley
Date: 11-09-2013
DOI: 10.1002/JOC.3588
Publisher: American Meteorological Society
Date: 03-07-2019
Abstract: Extreme short-duration rainfall can cause devastating flooding that puts lives, infrastructure, and natural ecosystems at risk. It is therefore essential to understand how this type of extreme rainfall will change in a warmer world. A significant barrier to answering this question is the lack of sub-daily rainfall data available at the global scale. To this end, a global sub-daily rainfall dataset based on gauged observations has been collated. The dataset is highly variable in its spatial coverage, record length, completeness and, in its raw form, quality. This presents significant difficulties for many types of analyses. The dataset currently comprises 23 687 gauges with an average record length of 13 years. Apart from a few exceptions, the earliest records begin in the 1950s. The Global Sub-Daily Rainfall Dataset (GSDR) has wide applications, including improving our understanding of the nature and drivers of sub-daily rainfall extremes, improving and validating of high-resolution climate models, and developing a high-resolution gridded sub-daily rainfall dataset of indices.
Publisher: American Geophysical Union (AGU)
Date: 05-2007
DOI: 10.1029/2007GL029539
Publisher: American Geophysical Union (AGU)
Date: 28-05-2017
DOI: 10.1002/2017GL073231
Publisher: American Geophysical Union (AGU)
Date: 10-2016
DOI: 10.1002/2016JD025480
Abstract: Knowledge about long‐term changes in climate extremes is vital to better understand multidecadal climate variability and long‐term changes and to place today's extreme events in a historical context. While global changes in temperature and precipitation extremes since the midtwentieth century are well studied, knowledge about century‐scale changes is limited. This paper analyses a range of largely independent observations‐based data sets covering 1901–2010 for long‐term changes and interannual variability in daily scale temperature and precipitation extremes. We compare across data sets for consistency to ascertain our confidence in century‐scale changes in extremes. We find consistent warming trends in temperature extremes globally and in most land areas over the past century. For precipitation extremes we find global tendencies toward more intense rainfall throughout much of the twentieth century however, local changes are spatially more variable. While global time series of the different data sets agree well after about 1950, they often show different changes during the first half of the twentieth century. In regions with good observational coverage, gridded observations and reanalyses agree well throughout the entire past century. Simulations with an atmospheric model suggest that ocean temperatures and sea ice may explain up to about 50% of interannual variability in the global average of temperature extremes, and about 15% in the global average of moderate precipitation extremes, but local correlations are mostly significant only in low latitudes.
Publisher: American Geophysical Union (AGU)
Date: 09-2022
DOI: 10.1029/2021EF002645
Abstract: This study focuses on the projections and time of emergence (TOE) for temperature extremes over Australian regions in the phase 6 of Coupled Model Intercomparison Project (CMIP6) models. The model outputs are based on the Shared Socioeconomic Pathways (SSPs) from the Tier 1 experiments (i.e., SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5) in the Scenario Model Intercomparison Project (ScenarioMIP), which is compared with the Representative Concentration Pathways (RCPs) in CMIP5 (i.e., RCP2.6, RCP4.5, and RCP8.5). Furthermore, two large ensembles (LEs) in CMIP6 are used to investigate the effects of internal variability on the projected changes and TOE. As shown in the temporal evolution and spatial distribution, the strongest warming levels are projected under the highest future scenario and the changes for some extremes follow a “warm‐get‐warmer” pattern over Australia. Over subregions, tropical Australia usually shows the highest warming. Compared to the RCPs in CMIP5, the multi‐model medians in SSPs are higher for some indices and commonly exhibit wider spreads, likely related to the different forcings and higher climate sensitivity in a subset of the CMIP6 models. Based on a signal‐to‐noise framework, we confirm that the emergence patterns differ greatly for different extreme indices and the large uncertainty in TOE can result from the inter‐model ranges of both signal and noise, for which internal variability contributes to the determination of the signal. We further demonstrate that the internally generated variations influence the noise. Our findings can provide useful information for mitigation strategies and adaptation planning over Australia.
Publisher: Springer Science and Business Media LLC
Date: 30-09-2018
DOI: 10.1007/S00484-017-1451-9
Abstract: Various human heat stress indices have been developed to relate atmospheric measures of extreme heat to human health impacts, but the usefulness of different indices across various health impacts and in different populations is poorly understood. This paper determines which heat stress indices best fit hospital admissions for sets of cardiovascular, respiratory, and renal diseases across five Australian cities. We hypothesized that the best indices would be largely dependent on location. We fit parent models to these counts in the summers (November-March) between 2001 and 2013 using negative binomial regression. We then added 15 heat stress indices to these models, ranking their goodness of fit using the Akaike information criterion. Admissions for each health outcome were nearly always higher in hot or humid conditions. Contrary to our hypothesis that location would determine the best-fitting heat stress index, we found that the best indices were related largely by health outcome of interest, rather than location as hypothesized. In particular, heatwave and temperature indices had the best fit to cardiovascular admissions, humidity indices had the best fit to respiratory admissions, and combined heat-humidity indices had the best fit to renal admissions. With a few exceptions, the results were similar across all five cities. The best-fitting heat stress indices appear to be useful across several Australian cities with differing climates, but they may have varying usefulness depending on the outcome of interest. These findings suggest that future research on heat and health impacts, and in particular hospital demand modeling, could better reflect reality if it avoided "all-cause" health outcomes and used heat stress indices appropriate to specific diseases and disease groups.
Publisher: American Geophysical Union (AGU)
Date: 09-01-2016
DOI: 10.1002/2015GL066615
Publisher: Springer Science and Business Media LLC
Date: 28-03-2016
Publisher: IOP Publishing
Date: 21-02-2020
Abstract: Observational evidence of precipitation extremes is vital to better understand how these events might change in a future warmer climate. Over the terrestrial regions of a quasi-global domain, we assess the representation of annual maxima of daily precipitation (Rx1day) in 22 observational products gridded at 1° × 1° resolution and clustered into four categories: station-based in situ , satellite observations with or without a correction to rain gauges, and reanalyses (5, 8, 4 and 5 datasets, respectively). We also evaluate the interproduct spread across the ensemble and within the four clusters, as a measure of observational uncertainty. We find that reanalyses present a heterogeneous representation of Rx1day in particular over the tropics, and their interproduct spread is the highest compared to any other cluster. Extreme precipitation in satellite data broadly compares well with in situ -based data. We find a general better agreement with in situ -based observations and less interproduct spread for the satellite products with a correction to rain gauges compared to the uncorrected products. Given the level of uncertainties associated with the estimation of Rx1day in the observations, none of the datasets can be thought of as the best estimate. Our recommendation is to avoid using reanalyses as observational evidence and to consider in situ and satellite data (the corrected version preferably) in an ensemble of products for a better estimation of precipitation extremes and their observational uncertainties. Based on this we choose a subs le of 10 datasets to reduce the interproduct spread in both the representation of Rx1day and its timing throughout the year, compared to all 22 datasets. We emphasize that the recommendations and selection of datasets given here may not be relevant for different precipitation indices, and other grid resolutions and time scales.
Publisher: American Geophysical Union (AGU)
Date: 06-01-2016
DOI: 10.1002/2015GL067267
Publisher: American Meteorological Society
Date: 09-2013
Publisher: American Geophysical Union (AGU)
Date: 21-03-2017
DOI: 10.1002/2016JD025878
Publisher: American Geophysical Union (AGU)
Date: 05-2020
DOI: 10.1029/2019EF001469
Publisher: Copernicus GmbH
Date: 10-07-2019
DOI: 10.5194/ESSD-11-1017-2019
Abstract: Abstract. We introduce the Frequent Rainfall Observations on GridS (FROGS) database (Roca et al., 2019). It is composed of gridded daily-precipitation products on a common 1∘×1∘ grid to ease intercomparison and assessment exercises. The database includes satellite, ground-based and reanalysis products. As most of the satellite products rely on rain gauges for calibration, unadjusted versions of satellite products are also provided where available. Each product is provided over its length of record and up to 2017 if available. Quasi-global, quasi-global land-only, ocean-only and tropical-only as well as regional products (over continental Africa and South America) are included. All products are provided on a common netCDF format that is compliant with Climate and Forecast (CF) Convention and Attribute Convention for Dataset Discovery (ACDD) standards. Preliminary investigations of this large ensemble indicate that while many features appear robust across the products, the characterization of precipitation extremes exhibits a large spread calling for careful selection of the products used for scientific applications. All datasets are freely available via an FTP server and identified thanks to the DOI: 0.14768/06337394-73A9-407C-9997-0E380DAC5598.
Publisher: American Geophysical Union (AGU)
Date: 12-2022
DOI: 10.1029/2022EF002979
Abstract: Atmospheric warming results in an intensification of annual precipitation over the globe but large uncertainties remain regionally and at seasonal scales, especially for extremes. Using 29 models from the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), we investigate future seasonal changes in extreme precipitation (under the scenario SSP5‐8.5) and how it compares to changes in mean precipitation. Over land, we find a strong intensification of the wettest day in all seasons over the mid and high latitudes of the Northern Hemisphere and over India during the monsoon. Extreme intensity decreases in the subtropics for some seasons, including over large regions around the Mediterranean basin and Southern Africa, and these drying patterns are not apparent in annual results. The key finding is that the CMIP6 multi‐model mean always shows that seasonal changes in mean and extreme precipitation align where there is high model agreement. That is, in all seasons by the end of the 21st century, extremes intensify in regions where mean precipitation increases and decline where mean precipitation decreases. This should not hide inherent uncertainties associated, namely the large range of changes intensity that can be found across the models, and an important modulation of the changes by internal variability. Yet, this study shows that the multi‐model mean shows broad consistency such that future seasonal changes in mean precipitation could be used to infer future changes in extremes (and vice versa), thus providing valuable information for risk planning and mitigation strategies.
Publisher: Wiley
Date: 17-08-2018
DOI: 10.1002/JOC.5665
Publisher: Wiley
Date: 26-12-2016
DOI: 10.1002/JOC.4971
Publisher: American Meteorological Society
Date: 10-2004
Publisher: Wiley
Date: 10-10-2015
DOI: 10.1002/JOC.4174
Publisher: American Geophysical Union (AGU)
Date: 17-05-2016
DOI: 10.1002/2015JD024584
Publisher: American Geophysical Union (AGU)
Date: 19-08-2020
DOI: 10.1029/2019JD032263
Abstract: We present the second update to a data set of gridded land‐based temperature and precipitation extremes indices: HadEX3. This consists of 17 temperature and 12 precipitation indices derived from daily, in situ observations and recommended by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). These indices have been calculated at around 7,000 locations for temperature and 17,000 for precipitation. The annual (and monthly) indices have been interpolated on a 1.875°×1.25° longitude‐latitude grid, covering 1901–2018. We show changes in these indices by examining ”global”‐average time series in comparison with previous observational data sets and also estimating the uncertainty resulting from the nonuniform distribution of meteorological stations. Both the short and long time scale behavior of HadEX3 agrees well with existing products. Changes in the temperature indices are widespread and consistent with global‐scale warming. The extremes related to daily minimum temperatures are changing faster than the maximum. Spatial changes in the linear trends of precipitation indices over 1950–2018 are less spatially coherent than those for temperature indices. Globally, there are more heavy precipitation events that are also more intense and contribute a greater fraction to the total. Some of the indices use a reference period for calculating exceedance thresholds. We present a comparison between using 1961–1990 and 1981–2010. The differences between the time series of the temperature indices observed over longer time scales are shown to be the result of the interaction of the reference period with a warming climate. The gridded netCDF files and, where possible, underlying station indices are available from www.metoffice.gov.uk/hadobs/hadex3 and www.climdex.org .
Publisher: American Geophysical Union (AGU)
Date: 25-11-2016
DOI: 10.1002/2016JD025495
Publisher: IOP Publishing
Date: 28-10-2013
Publisher: IOP Publishing
Date: 12-04-2019
Publisher: American Geophysical Union (AGU)
Date: 15-11-2002
DOI: 10.1029/2002JD002251
Publisher: IOP Publishing
Date: 29-10-2019
Abstract: This study examines wet season droughts using eight products from the Frequent Rainfall Observations on GridS database. The study begins by evaluating wet season precipitation totals and wet day counts at seasonal and decadal time scales. While we find a high level of agreement among the products at a seasonal time scale, evaluations of 10 year variability indicate substantial non-stationary inter-product differences that make the assessment of low-frequency changes difficult, especially in data-sparse regions. Some products, however, appear more reliable than others on decadal time scales. Global time series of dry, middle, and wet region standardized precipitation index time series indicate little coherent change. There is substantial coherence in year-to-year variations in these time series for the better-performing products, likely indicative of skill for monitoring variations at large spatial scales. During the wet season, the data do not appear to indicate widespread global changes in precipitation, reference evapotranspiration (RefET) or Standardized Precipitation Evapotranspiration Index (SPEI) values. These data also do not indicate a global shift towards increasing aridity. Focusing on SPEI values for dry regions during droughts, however, we find modest increases in RefET and decreases in SPEI when wet season precipitation is below normal. Dry region SPEI values during droughts have decreased by −0.2 since the 1990s. The cause of these RefET increases is unclear, and more detailed analysis will be needed to confirm these results. For wet regions, however, the majority of products appear to indicate increases in wet season precipitation, although many products perform poorly in these regions due to limited observation networks, and estimated increases vary substantially. Synopsis: Our analysis indicates a lack of increasing aridity at global scales, issues associated with non-stationary systematic errors, and concerns associated with increases in reference evapotranspiration in global dry regions during droughts.
Publisher: IOP Publishing
Date: 03-2017
Publisher: Springer Science and Business Media LLC
Date: 12-12-2011
DOI: 10.1038/NGEO1045
Publisher: American Geophysical Union (AGU)
Date: 04-03-2013
DOI: 10.1002/JGRD.50150
Publisher: Wiley
Date: 16-02-2009
DOI: 10.1002/JOC.1861
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Lisa Alexander.