HadISDH: an updateable land surface specific humidity product for climate monitoring

Abstract

HadISDH is a near-global land surface specific humidity monitoring product providing monthly means from 1973 onwards over large-scale grids. Presented herein to 2012, annual updates are anticipated. HadISDH is an update to the land component of HadCRUH, utilising the global high-resolution land surface station product HadISD as a basis. HadISD, in turn, uses an updated version of NOAA's Integrated Surface Database. Intensive automated quality control has been undertaken at the individual observation level, as part of HadISD processing. The data have been subsequently run through the pairwise homogenisation algorithm developed for NCDC's US Historical Climatology Network monthly temperature product. For the first time, uncertainty estimates are provided at the grid-box spatial scale and monthly timescale. <br><br> HadISDH is in good agreement with existing land surface humidity products in periods of overlap, and with both land air and sea surface temperature estimates. Widespread moistening is shown over the 1973–2012 period. The largest moistening signals are over the tropics with drying over the subtropics, supporting other evidence of an intensified hydrological cycle over recent years. Moistening is detectable with high (95%) confidence over large-scale averages for the globe, Northern Hemisphere and tropics, with trends of 0.089 (0.080 to 0.098) g kg⁻¹ per decade, 0.086 (0.075 to 0.097) g kg⁻¹ per decade and 0.133 (0.119 to 0.148) g kg⁻¹ per decade, respectively. These changes are outside the uncertainty range for the large-scale average which is dominated by the spatial coverage component; station and grid-box sampling uncertainty is essentially negligible on large scales. A very small moistening (0.013 (−0.005 to 0.031) g kg⁻¹ per decade) is found in the Southern Hemisphere, but it is not significantly different from zero and uncertainty is large. When globally averaged, 1998 is the moistest year since monitoring began in 1973, closely followed by 2010, two strong El Niño years. The period in between is relatively flat, concurring with previous findings of decreasing relative humidity over land

Comparison of land surface humidity between observations and CMIP5 models

“…Since the 1970s, when most humidity monitoring records begin, until the turn of the century, specific humidity has increased over most of the well-observed parts of the globe (Dai, 2006;Berry and Kent, 2011;Willett et al, 2013). This has been largely driven by rising surface temperatures, which have, in turn, increased the water holding capacity of the atmosphere.…”

Pairwise homogeneity assessment of HadISD

“…PHA has been used on NCDC's US Historical Climatology Network (USHCN) monthly surface temperature record, and subsequently applied to the Global Historical Climatology Network (GHCN) (Lawrimore et al, 2011) and more recently to surface humidity measurements (Willett et al, 2013(Willett et al, , 2014. PHA has been designed to run on large networks of stations in an automated fashion, and hence suits the requirements of homogenising HadISD.…”

“…HadISD is updated on an annual basis, with each new release being given a unique version number to allow full traceability, with the current version (v1.0.2.2013f) running to the end of 2013. HadISD is an updated, quality-controlled data set, but it has not as yet been homogenised, although it the basis of the monthly homogeneous specific humidity product (Willett et al, 2013). Initial steps in releasing a homogenised HadISD are detailed in this manuscript.…”

Propagation of biases in humidity in the estimation of global irrigation water

“…In fact, Willett et al (2013) reported that the maximum uncertainties in humidity measurements with dry-and wet-bulb thermometers amounted to 2.75 and 5 % RH at temperatures of 0 and −10 • C, respectively. Emeis (2010) summarized the errors for various measurement equipment: for example, advanced equipment based on the capacitive method has an accuracy of 2 % RH (for a humidity of 10-80 % RH) to 3 % RH (for a humidity of 80-ca.…”

“…Haddeland et al (2012) intensively examined the compound effects of the bias correction of radiation, wind and humidity, and showed that bias correction has an impact on absolute values of evapotranspiration but less impact on relative changes. Moreover, global humidity observation data sets contain uncertainties originating from the accuracy of measurements, grid sampling (Willett et al, 2013) and the spatial variability within land cells. Knowing the sensitivity of irrigation water to humidity conditions at different locations would help clarify the Table 1.…”