Data and Methodology

Humidity is a general term used to indicate moisture in the atmosphere. The specific humidity (g kg-1) is the mass of water vapour contained within a unit mass of moist air which means that the higher the amount of water vapour, the higher the specific humidity. The commonly used term relative humidity is defined as the ratio (%) of the actual vapour pressure of the air to the saturation vapour pressure at the same pressure and temperature. In other words, it is a measure of the actual amount of water vapour in the air compared to the total amount of vapour that can exist in the air at its current temperature.

In this study, we have analysed data from 244 surface meteorological stations for surface humidity and 27 agro-meteorological stations for surface moisture. The geographical locations of these stations in the network of IMD are shown in Fig. 1, where six homogeneous regions of India, viz., north-west (NW), east (E), north-east (NE), central (C), west (W) and south (S), are also marked. These data records are processed and quality checked before archival at the National Data Centre of India Meteorological Department. Daily observations recorded at 0300 and 1200 UTC are used for calculating mean monthly specific humidity and relative humidity. Since daily surface data are available from 1969 onwards, the period of study is restricted to 1969-2012. Daily specific humidity values in g kg-1 are calculated by

Geographical locations of 244 stations measuring surface humidity and 27 stations measuring soil moisture distributed over six regions of India

Fig. 1 Geographical locations of 244 stations measuring surface humidity and 27 stations measuring soil moisture distributed over six regions of India

using the following relation originally given by Tetens (1930) and simplified by Murray (1967).

Here ew is the vapour pressure in hPa and dpt is the dew point temperature in °K. The specific humidity sph in g kg-1 is calculated by the following relation:

where slp is the station-level pressure in hPa at the time of observation.

From daily values, monthly means of specific humidity and relative humidity were obtained which are then used to prepare time series for annual (January- December), winter (December-February), summer (March-May), monsoon (June- September) and post-monsoon (October-November). Based upon 244 stations considered in this study, averaged all India and regional (six regions) time series of

Temporal vacations in a annual, b winter, c summer, d monsoon and e post-monsoon surface specific humidity during 1969-2012

Fig. 2 Temporal vacations in a annual, b winter, c summer, d monsoon and e post-monsoon surface specific humidity during 1969-2012. Data series are specific humidity (in g kg-1) averaged over India based upon 244 stations under study. Specific humidity trends (in g kg-1 per decade) are statistically significant at 95 % level for the annual and the four seasons

Temporal variations in a annual, b winter, c summer, d monsoon and e post-monsoon surface relative humidity during the period of 1969-2012

Fig. 3 Temporal variations in a annual, b winter, c summer, d monsoon and e post-monsoon surface relative humidity during the period of 1969-2012. Data series are relative humidity (in %) averaged over India based upon 244 stations under study. Relative humidity trends (in % per decade) are statistically significant at the 95 % significance level for all seasons except the monsoon season

Fig. 4 Annual and seasonal rate of change in specific humidity in g kg-1 per decade in six regions of India during 1969-2012

Annual and seasonal rate of change in relative humidity in % per decade in six regions of India during 1969-2012

Fig. 5 Annual and seasonal rate of change in relative humidity in % per decade in six regions of India during 1969-2012

SPH and RH is prepared for 1969-2012. Temporal variations in all India averaged annual and seasonal mean SPH and RH are shown in Figs. 2 and 3, respectively. From regional time series, we have calculated rate of change in SPH and RH for annual and four seasons as shown in Figs. 4 and 5, respectively. Statistical significance of linear trends is tested at the 95 % confidence level using t test.

Soil moisture observations are taken once per week at several depths by gravimetric method. In this method, smaller soil samples are taken using coring devices at required depths and locations from each segment. The sample is weighed, oven-dried and weighed again. The difference in mass gives the total soil moisture in the sample, which is converted to volumetric units using the density of the soil. We have taken surface soil moisture data from 27 stations for the period of 1991 onwards. Location of these stations is given in Table 3. Spatial variations in annual mean surface soil moisture and linear trends are shown in Fig. 6, where trends statistically significant at 95 % level are marked by an outer circle. In evaluating the atmospheric moisture content, the specific humidity and relative humidity from ERA Interim (Dee et al. 2011), MERRA (Rienecker et al. 2011) reanalyses and from IMD stations observations have been analysed to evaluate the atmospheric moisture content over the Indian region (Singh et al. 2014). Further, to assess the variability of atmospheric water content, the precipitable water has been used. To link the atmospheric water content with the lower level, low-level atmospheric moisture content has been analysed.

Spatial distribution of annual surface soil moisture means and trends during the period of 1991-2013. Trends significant at the 95 % confidence level are circled

Fig. 6 Spatial distribution of annual surface soil moisture means and trends during the period of 1991-2013. Trends significant at the 95 % confidence level are circled

 
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