An upgraded version of the Hadley Centre’s monthly historical mean sea level pressure (MSLP) dataset (HadSLP2) is presented. HadSLP2 covers the period from 1850 to date, and is based on numerous terrestrial and marine data compilations. Each terrestrial pressure series used in HadSLP2 underwent a series of quality control tests, and erroneous or suspect values were either corrected, where possible, or removed. Marine observations from the International Comprehensive Ocean Atmosphere Data Set were quality controlled (assessed against climatology and near neighbors) and then gridded. The final gridded form of HadSLP2 was created by blending together the processed terrestrial and gridded marine MSLP data. MSLP fields were made spatially complete using reduced-space optimal interpolation. Gridpoint error estimates were also produced.HadSLP2 was found to have generally stronger subtropical anticyclones and higher-latitude features across the Northern Hemisphere than an earlier product (HadSLP1). During the austral winter, however, it appears that the pressures in the southern Atlantic and Indian Ocean midlatitude regions are too high; this is seen in comparisons with both HadSLP1 and the 40-yr ECMWF Re-Analysis (ERA-40). Over regions of high altitude, HadSLP2 and ERA-40 showed consistent differences suggestive of potential biases in the reanalysis model, though the region over the Himalayas in HadSLP2 is biased compared with HadSLP1 and improvements are required in this region. Consistent differences were also observed in regions of sparse data, particularly over the higher latitudes of the Southern Ocean and in the southeastern Pacific. Unlike the earlier HadSLP1 product, error estimates are available with HadSLP2 to guide the user in these regions of low confidence.An evaluation of major phenomena in the climate system using HadSLP2 provided further validation of the dataset. Important climatic features/indices such as the North Atlantic Oscillation, Arctic Oscillation, North Pacific index, Southern Oscillation index, Trans-Polar index, Antarctic Oscillation, Antarctic Circumpolar Wave, East Asian Summer Monsoon index, and the Siberian High index have all been resolved in HadSLP2, with extensions back to the mid-nineteenth century.
19 August 2020 in Journal of Geophysical Research: Atmospheres
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.
22 October 2008 in International Journal of Climatology
Protracted droughts lasting years to decades constitute severe threats to human welfare across the Indian subcontinent. Such events are, however, rare during the instrumental period (ca. since 1871 CE). In contrast, the historic documentary evidence indicates the repeated occurrences of protracted droughts in the region during the preinstrumental period implying that either the instrumental observations underestimate the full spectrum of monsoon variability or the historic accounts overestimate the severity and duration of the past droughts. Here we present a temporally precise speleothem-based oxygen isotope reconstruction of the Indian summer monsoon precipitation variability from Mawmluh cave located in northeast India. Our data reveal that protracted droughts, embedded within multidecadal intervals of reduced monsoon rainfall, frequently occurred over the past millennium. These extreme events are in striking temporal synchrony with the historically documented droughts, famines, mass mortality events, and geopolitical changes in the Indian subcontinent. Our findings necessitate reconsideration of the region’s current water resources, sustainability, and mitigation policies that discount the possibility of protracted droughts in the future.
Global gridded data sets of observed extremes indices underpin assessments of changes in climate extremes. However, similar efforts to enable the assessment of indices relevant to different sectors of society have been missing. Here we present a data set of sector‐specific indices, based on daily station data, that extends the HadEX3 data set of climate extremes indices. These additional indices, which can be used singly or in combinations, have been recommended by the World Meteorological Organization and are intended to empower decision makers in different sectors with accurate historical information about how sector‐relevant measures of the climate are changing, especially in regions where in situ daily temperature and rainfall data are hard to come by. The annual and/or monthly indices have been interpolated on to a 1.875° × 1.25° longitude‐latitude grid for 1901–2018. We show changes in globally‐averaged time series of these indices in comparison with reanalysis products. Changes in temperature‐based indices are consistent with global scale warming, with days with Tmax > 30°C (TXge30) increasing virtually everywhere with potential impacts on crop fertility. At the other end of the scale, the number of days with Tmin < −2°C (TNltm2) are reducing, decreasing potential damage from frosts. Changes in heat wave characteristics show increases in the number, duration and intensity of these extreme events in most places. The gridded netCDF files and, where possible, the underlying station indices are available from https://www.metoffice.gov.uk/hadobs/hadex3 and https://www.climdex.org.
The rescue, digitization, quality control, preservation, and utilization of long and high quality meteorological and climate records, particularly related to historical marine data, are crucial for advancing our understanding of the Earth’s climate system. In combination with land and air measurements, historical marine records serve as foundational pillars in linking present and past weather and climate information, offering essential insights into natural climate variability, extreme events in marine areas, baseline data for assessing current changes, and inputs for enhancing predictive climate models and reanalyses. This paper provides an overview of rescue activities covering marine weather data over the past centuries and presents and highlights several ongoing projects across the world and how the data are used in an integrative and international framework. Current and future continuous efforts in data rescue, digitization, quality control, and the development of temporally high-resolution meteorological and climatological observations from oceans, will greatly help to further complete our understanding and knowledge of the Earth’s climate system, including extremes, as well as improve the quality of reanalysis.