ALBERT

Description: Historical in situ sub-daily rainfall observations are essential for the understanding of short-duration rainfall extremes but records are typically not readily accessible and data are often subject to errors and inhomogeneities. Furthermore, these events are poorly quantified in projections of future climate change making adaptation to the risk of flash flooding problematic. Consequently, knowledge of the processes contributing to intense, short-duration rainfall is less complete compared with those on daily timescales. The INTENSE project is addressing this global challenge by undertaking a data collection initiative that is coupled with advances in high-resolution climate modelling to better understand key processes and likely future change. The project has so far acquired data from over 23 000 rain gauges for its global sub-daily rainfall dataset (GSDR) and has provided evidence of an intensification of hourly extremes over the US. Studies of these observations, combined with model simulations, will continue to advance our understanding of the role of local-scale thermodynamics and large-scale atmospheric circulation in the generation of these events and how these might change in the future.

Description: We compare the latest observational land surface humidity dataset, HadISDH, with the latest generation of climate models extracted from the CMIP5 archive and the ERA-Interim reanalysis over the period 1973 to present. The globally averaged behaviour of HadISDH and ERA-Interim are very similar in both humidity measures and air temperature, on decadal and interannual timescales. The global average relative humidity shows a gradual increase from 1973 to 2000, followed by a steep decline in recent years. The observed specific humidity shows a steady increase in the global average during the early period but in the later period it remains approximately constant. None of the CMIP5 models or experiments capture the observed behaviour of the relative or specific humidity over the entire study period. When using an atmosphere-only model, driven by observed sea surface temperatures and radiative forcing changes, the behaviour of regional average temperature and specific humidity are better captured, but there is little improvement in the relative humidity. Comparing the observed climatologies with those from historical model runs shows that the models are generally cooler everywhere, are drier and less saturated in the tropics and extra-tropics, and have comparable moisture levels but are more saturated in the high latitudes. The spatial pattern of linear trends is relatively similar between the models and HadISDH for temperature and specific humidity, but there are large differences for relative humidity, with less moistening shown in the models over the tropics and very little at high latitudes. The observed drying in mid-latitudes is present at a much lower magnitude in the CMIP5 models. Relationships between temperature and humidity anomalies (T–q and T–rh) show good agreement for specific humidity between models and observations, and between the models themselves, but much poorer for relative humidity. The T–q correlation from the models is more steeply positive than the observations in all regions, and this over-correlation may be due to missing processes in the models. The observed temporal behaviour appears to be a robust climate feature rather than observational error. It has been previously documented and is theoretically consistent with faster warming rates over land compared to oceans. Thus, the poor replication in the models, especially in the atmosphere-only model, leads to questions over future projections of impacts related to changes in surface relative humidity. It also precludes any formal detection and attribution assessment.

Description: With the ongoing warming of the globe, it is important to quantify changes in the recent behaviour of extreme events given their impacts on human health, infrastructure and the natural environment. We use the sub-daily, multivariate, station-based HadISD dataset to study the changes in the statistical distributions of temperature, dew point temperature and wind speeds. Firstly, we use zonally averaged quantities to show that the lowest temperatures during both day and night are changing more rapidly than the highest, with the effect more pronounced in the northern high latitudes. Along with increases in the zonally averaged mean temperature, the standard deviation has decreased and the skew increased (increasing positive tail, decreasing negative tail) over the last 45 years, again with a stronger, more robust signal at higher latitudes. Changes in the distribution of dew point temperature are similar to those of temperature. However, changes in the distribution of wind speeds indicate a more rapid change at higher speeds than at lower. Secondly, to assess in more detail the spatial distribution of changes as well as changes across seasons and hours of the day we study each station individually. For stations which show clear indications of change in the statistical moments, the higher the statistical moment, generally the more spatially heterogenous the patterns of change. The standard deviations of temperatures are increasing in a band stretching from Europe through China but are decreasing across North America and in the high northern latitudes, indicating broadening and narrowing of the distributions, respectively. Large seasonal differences are found in the change of standard deviations of temperatures over North America and eastern China. Temperatures in eastern Asia also have increasing skew in the winter in contrast to the remainder of the year. The dew point temperatures show smaller variation in all of the moments but similar patterns to the temperatures. For wind speeds, apart from the USA, standard deviations are decreasing across the world, indicating a decrease in variability. Finally, we use quantile regression to show changes in the percentiles of distributions over time. These show an increase in high quantiles of temperature in eastern Europe during the summer and also in northern Europe for low quantiles in the winter, also indicating broadening and narrowing of the distributions, respectively. In North America, the largest changes are at the lower quantiles in northern latitudes for autumn and winter. Quantiles of dew point temperature are changing most in the autumn and winter, especially in the northern parts of Europe.

Description: We compare the latest observational land-surface humidity dataset, HadISDH, with the latest generation of climate models extracted from the CMIP5 archive and the ERA-Interim reanalysis over the period 1973 to present. The globally averaged behaviour of HadISDH and ERA-Interim are very similar in both humidity measures and air temperature, at decadal and interannual timescales. The global average relative humidity shows a gradual increase from 1973 to 2000, followed by a steep decline in recent years. The observed specific humidity shows a steady increase in the global average during the early period but in the later period it remains approximately constant. None of the CMIP5 models or experiments capture the observed behaviour of the relative or specific humidity over the entire study period. When using an atmosphere-only model, driven by observed sea-surface temperatures and radiative forcing changes, the behaviour of regional average temperature and specific humidity are better captured, but there is little improvement in the relative humidity. Comparing the observed and historical model climatologies show that the models are generally cooler everywhere, are drier and less saturated in the tropics and extra tropics, and have comparable moisture levels but are more saturated in the high latitudes. The spatial pattern of linear trends are relatively similar between the models and HadISDH for temperature and specific humidity, but there are large differences for relative humidity, with less moistening shown in the models over the Tropics, and very little at high latitudes. The observed drying in mid-latitudes is present at a much lower magnitudes. Relationships between temperature and humidity anomalies (T–q and T–rh) show good agreement for specific humidity between models and observations, and between the models themselves, but much poorer for relative humidity. The T–q correlation from the models is more steeply positive in all regions than the observations, and this over-correlation may be due to missing processes in the models. The observed temporal behaviour appears to be a robust climate feature rather than observational error. It has been previously documented and is theoretically consistent with faster warming rates over land compared to oceans. Thus, the poor replication in the models, especially in the atmosphere only model, leads to questions over future projections of impacts related to changes in surface relative humidity. It also precludes any formal detection and attribution assessment.

Description: HadISD is a sub-daily, station-based, quality-controlled dataset designed to study past extremes of temperature, pressure and humidity and allow comparisons to future projections. Herein we describe the first major update to the HadISD dataset. The temporal coverage of the dataset has been extended to 1931 to present, doubling the time range over which data are provided. Improvements made to the station selection and merging procedures result in 7677 stations being provided in version 2.0.0.2015p of this dataset. The selection of stations to merge together making composites has also been improved and made more robust. The underlying structure of the quality control procedure is the same as for HadISD.1.0.x, but a number of improvements have been implemented in individual tests. Also, more detailed quality control tests for wind speed and direction have been added. The data will be made available as NetCDF files at http://www.metoffice.gov.uk/hadobs/hadisd and updated annually.

Description: With the ongoing warming of the globe, it is important to quantify changes in the recent behaviour of extreme events given their impacts on human health, infrastructure and the natural environment. We use the sub-daily, multi-variate, station-based HadISD dataset to study the changes in the statistical distributions of temperature, dewpoint temperature and wind speeds. Firstly, we use zonally averaged quantities to show that the lowest temperatures during both day and night are changing more rapidly than the highest, with the effect more pronounced in the northern high latitudes. Along with an increases in the zonally-averaged mean temperature, the standard deviation has decreased and the skew increased (increasing positive tail/decreasing negative tail) over the last 45 years, again with a stronger, more robust signal at higher latitudes. Changes in the distribution of dewpoint temperature are similar to those of temperature. However, changes in the distribution of wind speeds indicate a more rapid change at higher speeds than at lower. Secondly, to assess in more detail the spatial distribution of changes as well as across seasons and hours of the day we study each station individually. For stations which show clear indications of change in the statistical moments, the higher the statistical moment, generally the more spatially heterogenous the patterns of change. The standard deviation of temperatures are increasing in a band stretching from Europe through to China, but are decreasing across North America and in the high northern latitudes, indicating broadening and narrowing of the distributions respectively. Large seasonal differences are found in the change of standard deviations of temperatures over North America and eastern China. Temperatures in Eastern Asia also have increasing skew in the winter in contrast to the remainder of the year. The dewpoint temperatures show smaller variation in all of the moments, but similar patterns to the temperatures. For wind speeds, apart from the USA, standard deviations are decreasing across the world, indicating a decrease in variability. Finally, we use quantile regression to show changes in the percentiles of distributions over time. These show an increase of high quantiles of temperature in eastern Europe during the summer, and also in northern Europe for low quantiles in the winter, also indicating broadening and narrowing of the distributions respectively. In North America, the largest changes are at the lower quantiles in northern latitudes for autumn and winter. Quantiles of dewpoint temperature are changing most in the autumn and winter, especially in the northern parts of Europe.

Description: Atmospheric humidity plays an important role in climate analyses. Here we describe the production and key characteristics of a new quasi-global marine humidity product intended for climate monitoring, HadISDH.marine. It is an in situ multivariable marine humidity product, gridded monthly at a 5∘×5∘ spatial resolution from January 1973 to December 2018 with annual updates planned. Currently, only reanalyses provide up-to-date estimates of marine surface humidity, but there are concerns over their long-term stability. As a result, this new product makes a valuable addition to the climate record and will help address some of the uncertainties around recent changes (e.g. contrasting land and sea trends, relative-humidity drying). Efforts have been made to quality-control the data, ensure spatial and temporal homogeneity as far as possible, adjust for known biases in non-aspirated instruments and ship heights, and also estimate uncertainty in the data. Uncertainty estimates for whole-number reporting and for other measurement errors have not been quantified before for marine humidity. This is a companion product to HadISDH.land, which, when combined, will provide methodologically consistent land and marine estimates of surface humidity. The spatial coverage of HadISDH.marine is good over the Northern Hemisphere outside of the high latitudes but poor over the Southern Hemisphere, especially south of 20∘ S. The trends and variability shown are in line with overall signals of increasing moisture and warmth over oceans from theoretical expectations and other products. Uncertainty in the global average is larger over periods where digital ship metadata are fewer or unavailable but not large enough to cast doubt over trends in specific humidity or air temperature. Hence, we conclude that HadISDH.marine is a useful contribution to our understanding of climate change. However, we note that our ability to monitor surface humidity with any degree of confidence depends on the continued availability of ship data and provision of digitized metadata. HadISDH.marine data, derived diagnostics, and plots are available at http://www.metoffice.gov.uk/hadobs/hadisdh (last access: June 2019) and https://doi.org/10.5285/463b2fcd6a264a39b1e3249dab16c177 (Willett et al., 2020).