K. M. Willett

Attribution of observed surface humidity changes to human influence

Water vapour is the most important contributor to the natural greenhouse effect, and the amount of water vapour in the atmosphere is expected to increase under conditions of greenhouse-gas-induced warming, leading to a significant feedback on anthropogenic climate change. Theoretical and modelling studies predict that relative humidity will remain approximately constant at the global scale as the climate warms, leading to an increase in specific humidity. Although significant increases in surface specific humidity have been identified in several regions, and on the global scale in non-homogenized data, it has not been shown whether these changes are due to natural or human influences on climate. Here we use a new quality-controlled and homogenized gridded observational data set of surface humidity, with output from a coupled climate model, to identify and explore the causes of changes in surface specific humidity over the late twentieth century. We identify a significant global-scale increase in surface specific humidity that is attributable mainly to human influence. Specific humidity is found to have increased in response to rising temperatures, with relative humidity remaining approximately constant. These changes may have important implications, because atmospheric humidity is a key variable in determining the geographical distribution and maximum intensity of precipitation, the potential maximum intensity of tropical cyclones, and human heat stress, and has important effects on the biosphere and surface hydrology.

Recent Changes in Surface Humidity: Development of the HadCRUH Dataset

Water vapor constitutes the most significant greenhouse gas, is a key driver of many atmospheric processes, and hence, is fundamental to understanding the climate system. It is a major factor in human “heat stress,” whereby increasing humidity reduces the ability to stay cool. Until now no truly global homogenized surface humidity dataset has existed with which to assess recent changes. The Met Office Hadley Centre and Climatic Research Unit Global Surface Humidity dataset (HadCRUH), described herein, provides a homogenized quality controlled near-global 5° by 5° gridded monthly mean anomaly dataset in surface specific and relative humidity from 1973 to 2003. It consists of land and marine data, and is geographically quasicomplete over the region 60°N–40°S. Between 1973 and 2003 surface specific humidity has increased significantly over the globe, tropics, and Northern Hemisphere. Global trends are 0.11 and 0.07 g kg 1 (10 yr) 1 for land and marine components, respectively. Trends are consistently larger in the tropics and in the Northern Hemisphere during summer, as expected: warmer regions exhibit larger increases in specific humidity for a given temperature change under conditions of constant relative humidity, based on the Clausius–Clapeyron equation. Relative humidity trends are not significant when averaged over the landmass of the globe, tropics, and Northern Hemisphere, although some seasonal changes are significant. A strong positive bias is apparent in marine humidity data prior to 1982, likely owing to a known change in reporting practice for dewpoint temperature at this time. Consequently, trends in both specific and relative humidity are likely underestimated over the oceans.

A comparison of large scale changes in surface humidity over land in observations and CMIP3 general circulation models

Observed changes in the HadCRUH global land surface specific humidity and CRUTEM3 surface temperature from 1973 to 1999 are compared to CMIP3 archive climate model simulations with 20th Century forcings. Observed humidity increases are proportionately largest in the Northern Hemisphere, especially in winter. At the largest spatio-temporal scales moistening is close to the Clausius–Clapeyron scaling of the saturated specific humidity (~7% K − 1). At smaller scales in water-limited regions, changes in specific humidity are strongly inversely correlated with total changes in temperature. Conversely, in some regions increases are faster than implied by the Clausius–Clapeyron relation. The range of climate model specific humidity seasonal climatology and variance encompasses the observations. The models also reproduce the magnitude of observed interannual variance over all large regions. Observed and modelled trends and temperature–humidity relationships are comparable except for the extratropical Southern Hemisphere where observations exhibit no trend but models exhibit moistening. This may arise from: long-term biases remaining in the observations; the relative paucity of observational coverage; or common model errors. The overall degree of consistency of anthropogenically forced models with the observations is further evidence for anthropogenic influence on the climate of the late 20th century.

Toward an integrated set of surface meteorological observations for climate science and applications

AbstractObservations are the foundation for understanding the climate system. Yet, currently available land meteorological data are highly fractured into various global, regional, and national holdings for different variables and time scales, from a variety of sources, and in a mixture of formats. Added to this, many data are still inaccessible for analysis and usage. To meet modern scientific and societal demands as well as emerging needs such as the provision of climate services, it is essential that we improve the management and curation of available land-based meteorological holdings. We need a comprehensive global set of data holdings, of known provenance, that is truly integrated both across essential climate variables (ECVs) and across time scales to meet the broad range of stakeholder needs. These holdings must be easily discoverable, made available in accessible formats, and backed up by multitiered user support. The present paper provides a high-level overview, based upon broad community input, ...

Benchmarking homogenization algorithms for monthly data

The COST (European Cooperation in Science and Technology) Action ES0601: advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies and because they represent two important types of statistics (additive and multiplicative). The algorithms were validated against a realistic benchmark dataset. The benchmark contains real inhomogeneous data as well as simulated data with inserted inhomogeneities. Random independent break-type inhomogeneities with nor- mally distributed breakpoint sizes were added to the simu- lated datasets. To approximate real world conditions, breaks were introduced that occur simultaneously in multiple station series within a simulated network of station data. The sim- ulated time series also contained outliers, missing data peri- ods and local station trends. Further, a stochastic nonlinear global (network-wide) trend was added.

The international surface temperature initiative

The aim of International Surface Temperature Initiative is to create an end-to-end process for analysis of air temperature data taken over the land surface of the Earth. The foundation of any analysis is the source data. Land surface air temperature records have traditionally been stored in local, organizational, national and international holdings, some of which have been available digitally but many of which are available solely on paper or as imaged files. Further, economic and geopolitical realities have often precluded open sharing of these data. The necessary first step therefore is to collate readily available holdings and augment these over time either through gaining access to previously unavailable digital data or through data rescue and digitization activities. Next, it must be recognized that these historical measurements were made primarily in support of real-time weather applications where timeliness and coverage are key. At almost every long-term station it is virtually certain that changes...