HadISDH.land Update Document version 4.2.0.2019f

HadISDH.land update document covering the latest changes in version 4.2.0.2019f from previous versions

HadISDH Data Format

Format description for the netCDF and ASCII HadISDH data products

Investigation and quality assessment of the Past Weather Code from the Integrated Surface Database

Quantitative SYNOP Code weather variables such as rainfall amount, although of high societal and environmental importance, are frequently subject to recording errors and inhomogeneities resulting in uncertain conclusions. Here we assess the viability of the more qualitative Past Weather Code (PWC) for its use in robust climate analysis in the belief that it is less prone to both random and systematic errors. The Past Weather Code data, from a selection of the National Oceanographic and Atmospheric Administration’s Integrated Surface Database (ISD) (4731 sufficiently long stations), is quality assessed by searching for inhomogeneities in station PWC time series, removing the offending stations and averaging the remaining stations into a global gridded dataset. PWCs 6 (Rainfall), 7 (Snowfall) and 9 (Thunderstorms) are found to robustly exhibit seasonal features, e.g. the Indian monsoon and peak Northern Hemispheric winter snowfall. Precipitation responses to the North Atlantic Oscillation are also detected in winter PWC 6 data over Europe

HadISDH.marine Update Document version 1.1.0.2020f

Update notes for HadISDH.marine

HadISDH.land Update Document version 4.3.1.2020f

Update notes for HadISDH land

HadISDH.marine Update Document version 1.0.0.2019f

HadISDH.marine update document covering the latest changes in version 1.0.0.2019f from previous versions

Homogenization of daily temperature and humidity series in the UK

Building on previous experience with continental and global data sets, we use a quantile-matching approach to homogenize temperature and humidity series measured by a network of 220 stations in the United Kingdom (UK). The data set spans 160 years at daily resolution, although data coverage varies greatly in time, space, and across variables. We use the homogenized data to analyse trends of the mean values as well as the lowest and highest quantiles of the distribution over the last 100 and 50 years. For the latter period, we find large regional differences, particularly between the southeastern and the northern part of the UK. The southeast has seen a faster warming, particularly for maximum temperatures in spring and summer, and a reduction of relative humidity; the northern mainland has become more humid and only slightly warmer. These differences become more evident for the highest quantiles and reflect a well-known pattern of climate change affecting the extra-tropics. Among the studied variables, the increases of wet bulb temperature and specific humidity are the most spatially homogeneous and are statistically significant for most stations in all seasons except winter

HadISD: a quality-controlled global synoptic report database for selected variables at long-term stations from 1973--2011

[Abridged] This paper describes the creation of HadISD: an automatically quality-controlled synoptic resolution dataset of temperature, dewpoint temperature, sea-level pressure, wind speed, wind direction and cloud cover from global weather stations for 1973--2011. The full dataset consists of over 6000 stations, with 3427 long-term stations deemed to have sufficient sampling and quality for climate applications requiring sub-daily resolution. As with other surface datasets, coverage is heavily skewed towards Northern Hemisphere mid-latitudes. The dataset is constructed from a large pre-existing ASCII flatfile data bank that represents over a decade of substantial effort at data retrieval, reformatting and provision. These raw data have had varying levels of quality control applied to them by individual data providers. The work proceeded in several steps: merging stations with multiple reporting identifiers; reformatting to netCDF; quality control; and then filtering to form a final dataset. Particular attention has been paid to maintaining true extreme values where possible within an automated, objective process. Detailed validation has been performed on a subset of global stations and also on UK data using known extreme events to help finalise the QC tests. Further validation was performed on a selection of extreme events world-wide (Hurricane Katrina in 2005, the cold snap in Alaska in 1989 and heat waves in SE Australia in 2009). Although the filtering has removed the poorest station records, no attempt has been made to homogenise the data thus far. Hence non-climatic, time-varying errors may still exist in many of the individual station records and care is needed in inferring long-term trends from these data. A version-control system has been constructed for this dataset to allow for the clear documentation of any updates and corrections in the future.Comment: Published in Climate of the Past, www.clim-past.net/8/1649/2012/. 31 pages, 23 figures, 9 pages. For data see http://www.metoffice.gov.uk/hadobs/hadis

Development of the HadISDH.marine humidity climate monitoring dataset

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

Challenges in quantifying changes in the global water cycle

Human influences have likely already impacted the large-scale water cycle but natural variability and observational uncertainty are substantial. It is essential to maintain and improve observational capabilities to better characterize changes. Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time-series over land but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols, and due to large climate variability presently limits confidence in attribution of observed changes