Editing IPCC:AR6/WGI/Chapter-11 (section)

=== 11.2.2 Data ===

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Studies of past and future changes in weather and climate extremes, and in the mean state of the climate, use the same original sources of weather and climate observations, including in situ observations, remotely sensed data, and derived data products such as reanalyses. Sections 2.3 and 10.2 assess various aspects of these data sources and data products from the perspective of their general use, and in the analysis of changes in the mean state of the climate in particular. Building on these previous chapters, this subsection highlights particular aspects that are related to extremes and are most relevant to the assessment of this Chapter. The SREX (Chapter 3, [[#Seneviratne--2012|Seneviratne et al., 2012]] ) and AR5 (Chapter 2, [[#Hartmann--2013|Hartmann et al., 2013]] ) addressed critical issues regarding the quality and availability of observed data and their relevance for the assessment of changes in extremes.

Extreme weather and climate events occur on time scales of hours (e.g., convective storms that produce heavy precipitation) to days (e.g., tropical cyclones, heatwaves), to seasons and years (e.g., droughts). A robust determination of long-term changes in these events can have different requirements for the spatial and temporal scales and sample size of the data. In general, it is more difficult to determine long-term changes for events of fairly large temporal duration, such as ‘megadroughts’ that last several years or longer (e.g., [[#Ault--2014|Ault et al., 2014]] ), because of the limitations of the observational sample size. Literature that studies changes in extreme precipitation and temperature often uses indices representing specifics of extremes that are derived from daily precipitation and temperature values. Station-based indices would have the same issues as those for the mean climate regarding the quality, availability, and homogeneity of the data. For the purpose of constructing regional information and/or for comparison with model outputs, such as model evaluation, and detection and attribution, these station-based indices are often interpolated onto regular grids. Two different approaches, involving two different orders of operation, have been used in producing such gridded datasets.

In some cases, such as for the HadEX3 dataset ( [[#Dunn--2020|Dunn et al., 2020]] ), indices of extremes are computed using time series directly derived from stations first, and are then gridded over the space. As the indices are computed at the station level, the gridded data products represent point estimates of the indices averaged over the spatial scale of the grid box. In other instances, daily values of station observations are first gridded (e.g., [[#Contractor--2020a|Contractor et al., 2020a]] ), and the interpolated values can then be used to compute various indices. Depending on the station density, values for extremes computed from data gridded this way represent extremes of spatial scales anywhere from the size of the grid box to a point. In regions with high station density (e.g., North America, Europe), the gridded values are closer to extremes of area means and are thus more appropriate for comparisons with extremes estimated from climate model output, which is often considered to represent areal means ( [[#Chen--2008|Chen and Knutson, 2008]] ; [[#Gervais--2014|Gervais et al., 2014]] ; [[#Avila--2015|Avila et al., 2015]] ; [[#Di%20Luca--2020b|Di Luca et al., 2020b]] ). In regions with very limited station density (e.g., Africa), the gridded values are closer to point estimates of extremes. The difference in spatial scales among observational data products and model simulations needs to be carefully accounted for when interpreting the comparison among different data products. For example, the average annual maximum daily maximum temperature (TXx) over land computed from the original ERA-Interim reanalysis (at 0.75° resolution) is about 0.4°C warmer than that computed when the ERA-Interim dataset is upscaled to the resolution of 2.5° × 3.75° ( [[#Di%20Luca--2020|Di Luca et al., 2020]] ).

Extreme indices computed from various reanalysis data products have been used in some studies, but reanalysis extreme statistics have not been rigorously compared to observations ( [[#Donat--2016a|Donat et al., 2016a]] ).

In general, changes in temperature extremes from various reanalyses were most consistent with gridded observations after about 1980, but larger differences were found during the pre-satellite era ( [[#Donat--2014b|Donat et al., 2014b]] ). Overall, lower agreement across reanalysis datasets was found for extreme precipitation changes, although temporal and spatial correlations against observations were found to be still significant. In regions with sparse observations (e.g., Africa and parts of South America), there is generally less agreement for extreme precipitation between different reanalysis products, indicating a consequence of the lack of an observational constraint in these regions ( [[#Donat--2014b|Donat et al., 2014b]] , 2016a). More recent reanalyses, such as ERA5 ( [[#Hersbach--2020|Hersbach et al., 2020]] ), seem to have improved over previous products, at least over some regions (e.g., [[#Mahto--2019|Mahto and Mishra, 2019]] ; [[#Gleixner--2020|Gleixner et al., 2020]] ; [[#Sheridan--2020|Sheridan et al., 2020]] ). Caution is needed when reanalysis data products are used to provide additional information about past changes in these extremes in regions where observations are generally lacking.

Satellite remote sensing data have been used to provide information about precipitation extremes because several products provide data at sub-daily resolution for precipitation, for example, Tropical Rainfall Measuring Mission (TRMM; [[#Maggioni--2016|Maggioni et al., 2016]] ) and clouds, for example, Himawari (Bessho et al., 2016; [[#Chen--2019|Chen et al., 2019]] ). However, satellites do not observe the primary atmospheric state variables directly and polar orbiting satellites do not observe any given place at all times. Hence, their utility as a substitute for high-frequency (i.e., daily) ground-based observations is limited. For instance, [[#Timmermans--2019|Timmermans et al. (2019)]] found little relationship between the timing of extreme daily and five-day precipitation in satellite and gridded station data products over the USA.

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Box 11.3 | Extremes in Paleoclimate Archives Compared to Instrumental Records

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Examining extremes in pre-instrumental information can help to put events occurring in the instrumental record (referred to as ‘observed’) in a longer-term context. This box focuses on extremes in the Common Era (CE, the last 2000 years), because there is generally higher confidence in pre-instrumental information gathered from the more recent archives from the Common Era than from earlier evidence. It addresses evidence of extreme events in paleoreconstructions, documentary evidence (such as grape harvest data, religious documents, newspapers, and logbooks) and model-based analyses, and whether observed extremes have or have not been exceeded in the Common Era. This box provides overviews of: (i) AR5 assessments; (ii) types of evidence assessed here; evidence of: (iii) droughts; (iv) temperature extremes; (v) paleofloods; and (vi) paleotempests; and (vii) a summary.

( [[IPCC:Wg1:Chapter:Chapter-5|Chapter 5]] of AR5 ( [[#Masson-Delmotte--2013|Masson-Delmotte et al., 2013]] ) concluded with ''high confidence'' that droughts of greater magnitude and of longer duration than those observed in the instrumental period occurred in many regions during the preceding millennium. There was ''high confidence'' in evidence that floods during the past five centuries in northern and Central Europe, the western Mediterranean region, and eastern Asia were of a greater magnitude than those observed instrumentally, and ''medium confidence'' in evidence that floods in the Near East, India and Central North America were comparable to modern observed floods. While AR5 assessed 20th century summer temperatures compared to those reconstructed in the Common Era, it did not assess shorter duration temperature extremes.

Many factors affect confidence in information on pre-instrumental extremes. First, the geographical coverage of paleoclimate reconstructions of extremes is not spatially uniform ( [[#Smerdon--2016|Smerdon and Pollack, 2016]] ) and depends on both the availability of archives and records, which are environmentally dependent, and also the differing attention and focus from the scientific community. In Australia, for example, the paleoclimate network is sparser than for other regions, such as Asia, Europe and North America, and synthesized products rely on remote proxies and assumptions about the spatial coherence of precipitation between remote climates ( [[#Cook--2016c|Cook et al., 2016c]] ; [[#Freund--2017|Freund et al., 2017]] ). Second, pre-instrumental evidence of extremes may be focused on understanding archetypal extreme events, such as the climatic consequences of the 1815 eruption of Mount Tambora, Indonesia (Veale and Endfield, 2016). These studies provide narrow evidence of extremes in response to specific forcings (M. [[#Li--2017|]] [[#Li--2017|]] [[#Li--2017|]] [[#Li--2017|Li et al., 2017]] ) for specific epochs. Third, natural archives may provide information about extremes in one season only and may not represent all extremes of the same types.

Evidence of shorter duration extreme event types, such as floods and tropical storms, is further restricted by the comparatively low chronological controls and temporal resolution (e.g., monthly, seasonal, yearly, multiple years) of most archives compared to the events (e.g., minutes to days). Natural archives may be sensitive only to intense environmental disturbances, and so only sporadically record short-duration or small spatial-scale extremes. Interpreting sedimentary records as evidence of past short-duration extremes is also complex and requires a clear understanding of natural processes (Wilhelm et al. , 2019) . For example, paleoflood reconstructions of flood recurrence and intensity produced from geological evidence (e.g., river and lake sediments), speleothems ( [[#Denniston--2017|Denniston and Luetscher, 2017]] ), botanical evidence (e.g., flood damage to trees, or tree ring reconstructions), and floral and faunal evidence (e.g., diatom fossil assemblages) require understanding of sediment sources and flood mechanisms. Pre-instrumental records of tropical storm intensity and frequency (also called paleotempest records) derived from overwash deposits of coastal lake and marsh sediments are difficult to interpret. Many factors have an impact on whether disturbances are deposited in archives ( [[#Muller--2017|Muller et al., 2017]] ) and deposits may provide sporadic and incomplete preservation histories (e.g., [[#Tamura--2018|Tamura et al., 2018]] ).

Overall, the most complete pre-instrumental evidence of extremes occurs for long-duration, large spatial-scale extremes, such as for multi-year meteorological droughts or seasonal- and regional-scale temperature extremes. Additionally, more precise insights into recent extremes emerge where multiple studies have been undertaken, compared to the confidence in extremes reported at single sites or in single studies, which may not necessarily be representative of large-scale changes, or for reconstructions that synthesize multiple proxies over large areas (e.g., drought atlases). Multiproxy synthesis products combine paleoclimate temperature reconstructions and cover sub-continental- to hemispheric-scale regions to provide continuous records of the Common Era (e.g., Ahmed et al. , 2013; Neukom et al. , 2014 fo r temperature).

There is ''high confidence'' in the occurrence of long-duration and severe drought events during the Common Era for many locations, although their severity compared to recent drought events differs between locations and the lengths of reconstruction provided. Recent observed drought extremes in some regions – such as the eastern Mediterranean Levant ( [[#Cook--2016a|Cook et al., 2016a]] ), California in the USA( [[#Cook--2014b|Cook et al., 2014b]] ; [[#Griffin--2014|Griffin and Anchukaitis, 2014]] ), and in the Andes (Garreaud et al. , 2017; Domínguez-Castro et al. , 2018) – do not have precedents within the multi-century periods reconstructed in these studies, in terms of duration and/or severity. In some regions (in south-western North America ( [[#Asmerom--2013|Asmerom et al., 2013]] ; [[#Cook--2015|Cook et al., 2015]] ), the Great Plains region ( [[#Cook--2004|Cook et al., 2004]] ), the Middle East ( [[#Kaniewski--2012|Kaniewski et al., 2012]] ), and China ( [[#Gou--2015|Gou et al., 2015]] )), recent drought extremes may have been exceeded in the Common Era. In further locations, there is conflicting evidence for the severity of pre-instrumental droughts compared to observed extremes, depending on the length of the reconstruction and the seasonal perspective provided (see Cook et al. , 2016c; Freund et al. , 2017 for Australia). There can also be differing conclusions for the severity, or even the occurrence, of specific individual pre-instrumental droughts when different evidence is compared (e.g., [[#Wetter--2014|Wetter et al., 2014]] ; [[#Büntgen--2015|Büntgen et al., 2015]] ).

There is ''medium confidence'' that the magnitudes of large-scale, seasonal-scale extreme high temperatures in observed records exceed those reconstructed over the Common Era in some locations, such as Central Europe. In one example, multiple studies have examined the unusualness of present-day European summer temperature records in a long-term context, particularly in comparison to the exceptionally warm year of 1540 CE in Central Europe. Several studies indicate that recent extreme summers (2003 and 2010) in Europe have been unusually warm in the context of the last 500 years ( [[#Barriopedro--2011|Barriopedro et al., 2011]] ; [[#Wetter--2013|Wetter and Pfister, 2013]] ; [[#Wetter--2014|Wetter et al., 2014]] ; [[#Orth--2016b|Orth et al., 2016b]] ), or longer ( [[#Luterbacher--2016|Luterbacher et al., 2016]] ). Others studies show that summer temperatures in Central Europe in 1540 were warmer than the present-day (1966–2015) mean, but note that it is difficult to assess whether or not the 1540 summer was warmer than observed record extreme temperatures ( [[#Orth--2016b|Orth et al., 2016b]] ).

There is ''high confidence'' that the magnitude of floods over the Common Era exceeded observed records in some locations, including Central Europe and eastern Asia. Recent literature supports the AR5 assessments of floods ( [[#Masson-Delmotte--2013|Masson-Delmotte et al., 2013]] ). For example, high temporally resolved records provide evidence of Common Era floods exceeding the probable maximum flood levels in the Upper Colorado River, USA ( [[#Greenbaum--2014|Greenbaum et al., 2014]] ) and peak discharges that are double gauge levels along the middle Yellow River, China ( [[#Liu--2014|Liu et al., 2014]] ). Further studies demonstrate pre-instrumental or early instrumental differences in flood frequency compared to the instrumental period, including reconstructions of high and low flood frequency in the European Alps (e.g., [[#Swierczynski--2013|Swierczynski et al., 2013]] ; [[#Amann--2015|Amann et al., 2015]] ) and Himalayas ( [[#Ballesteros%20Cánovas--2017|Ballesteros Cánovas et al., 2017]] ). The combination of extreme historical flood episodes determined from documentary evidence also increases confidence in the determination of flood frequency and magnitude, compared to using geomorphological archives alone ( [[#Kjeldsen--2014|Kjeldsen et al., 2014]] ). In regions, such as Europe and China, that have rich historical flood documents, there is strong evidence of high-magnitude flood events over pre-instrumental periods (Kjeldsen et al., 2014; [[#Benito--2015|Benito et al., 2015]] ; [[#Macdonald--2017|Macdonald and Sangster, 2017]] ). A key feature of paleoflood records is variability in flood recurrence at centennial timescales ( [[#Wilhelm--2019|Wilhelm et al., 2019]] ), although constraining climate-flood relationships remains challenging. Pre-instrumental floods often occurred in considerably different contexts in terms of land use, irrigation, and infrastructure, and may not provide direct insight into modern river systems, which further prevents long-term assessments of flood changes being made based on these sources.

There is ''medium confidence'' that periods of both more and less tropical cyclone activity (frequency or intensity) than observed occurred over the Common Era in many regions. Paleotempest studies cover a limited number of locations that are predominantly coastal, and hence provide information on specific locations that cannot be extrapolated basin-wide (see [[#Muller--2017|Muller et al., 2017]] ). In some locations, such as the Gulf of Mexico and the New England, USA, coast, similarly intense storms to those observed recently have occurred multiple times over centennial timescales ( [[#Donnelly--2001|Donnelly et al., 2001]] ; [[#Bregy--2018|Bregy et al., 2018]] ). Further research focused on the frequency of tropical storm activity. Extreme storms occurred considerably more frequently in particular periods of the Common Era, compared to the instrumental period in north-east Queensland, Australia ( [[#Nott--2009|Nott et al., 2009]] ; [[#Haig--2014|Haig et al., 2014]] ), and the Gulf Coast (e.g., [[#Brandon--2013|Brandon et al., 2013]] ; [[#Lin--2014|Lin et al., 2014]] ).

The probability of finding an unprecedented extreme event increases with a longer length of past record-keeping, in the absence of longer-term trends. Thus, as a record is extended to the past based on paleoreconstruction, there is a higher chance of very rare extreme events having occurred at some time prior to instrumental records. Such an occurrence is not, in itself, evidence of a change, or lack of a change, in the magnitude or the likelihood of extremes in the past or in the instrumental period at regional and local scales. Yet, the systematic collection of paleoclimate records over wide areas may provide evidence of changes in extremes. In one study, extended evidence of the last millennium from observational data and paleoclimate reconstructions using tree rings indicates that human activities affected the worldwide occurrence of droughts as early as the beginning of the 20th century ( [[#Marvel--2019|Marvel et al., 2019]] ).

In summary, there is ''low confidence'' in overall changes in extremes derived from paleo-archives. There is ''high confidence'' that long-duration and severe drought events occurred at many locations during the last 2000 years. There is also ''high confidence'' that high-magnitude flood events occurred at some locations during the last 2000 years, but overall changes in infrastructure and human water management make the comparison with present-day records difficult. But these isolated paleo-drought and paleo-flood events are not evidence of a change, or lack of a change, in the magnitude or the likelihood of relevant extremes.

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