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1. Introduction To calculate relative humidity in percent (hereinafter denoted as RH%) from dry-bulb temperature T and wet-bulb temperature T w , one can use a well-known set of “forward” analytical psychrometric equations ( Bohren and Albrecht 1998 ; Stull 2011 ). For any pressure, such as standard sea level pressure of 101.325 kPa, the resulting calculated values of RH% can be listed in psychrometric tables or plotted in graphs such as Fig. 1 . There is, however, no easy analytical
1. Introduction To calculate relative humidity in percent (hereinafter denoted as RH%) from dry-bulb temperature T and wet-bulb temperature T w , one can use a well-known set of “forward” analytical psychrometric equations ( Bohren and Albrecht 1998 ; Stull 2011 ). For any pressure, such as standard sea level pressure of 101.325 kPa, the resulting calculated values of RH% can be listed in psychrometric tables or plotted in graphs such as Fig. 1 . There is, however, no easy analytical
from northern New England that is unique due to its elevation (1914 m), mean annual barometric pressure (802 hPa), and exposure to predominantly free troposphere conditions; 50% of days experience advective free troposphere influence and 20% (37%) of winter (summer) days experience convective boundary layer influence ( Grant et al. 2005 ). This paper presents the dewpoint, relative humidity, and water vapor mixing ratio records for the period 1935 through 2004. 2. Data and methods a. Location The
from northern New England that is unique due to its elevation (1914 m), mean annual barometric pressure (802 hPa), and exposure to predominantly free troposphere conditions; 50% of days experience advective free troposphere influence and 20% (37%) of winter (summer) days experience convective boundary layer influence ( Grant et al. 2005 ). This paper presents the dewpoint, relative humidity, and water vapor mixing ratio records for the period 1935 through 2004. 2. Data and methods a. Location The
1. Introduction An important feedback for the warming predicted by climate models due to an increase in greenhouse gas concentration is an increase in atmospheric water vapor ( Philipona et al. 2005 ). As temperatures rise, the atmosphere’s capacity to hold water increases. Knowledge about changes in water vapor in the upper troposphere and lower stratosphere is important because it can result in strong alterations in radiative forcing. Changes in the surface air temperature and humidity are
1. Introduction An important feedback for the warming predicted by climate models due to an increase in greenhouse gas concentration is an increase in atmospheric water vapor ( Philipona et al. 2005 ). As temperatures rise, the atmosphere’s capacity to hold water increases. Knowledge about changes in water vapor in the upper troposphere and lower stratosphere is important because it can result in strong alterations in radiative forcing. Changes in the surface air temperature and humidity are
vertical distribution of water vapor in the tropics. The top panel of Fig. 1 shows the annual mean relative humidity at 500 hPa over the tropics, as diagnosed from the Interim European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-Interim) for the year 2013. The regions of high relative humidity (RH) coincide with regions with significant amounts of deep convection (i.e., the Indo-Pacific warm pool, the ITCZ, and equatorial Africa and South America). The region with the largest RH at 500
vertical distribution of water vapor in the tropics. The top panel of Fig. 1 shows the annual mean relative humidity at 500 hPa over the tropics, as diagnosed from the Interim European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-Interim) for the year 2013. The regions of high relative humidity (RH) coincide with regions with significant amounts of deep convection (i.e., the Indo-Pacific warm pool, the ITCZ, and equatorial Africa and South America). The region with the largest RH at 500
1. Introduction Vaisala is the largest manufacturer of radiosondes, and with their recent RS92 model a new generation of radiosondes is introduced. This model replaces the older RS80 radiosonde and, to a smaller extent, the RS90 model. The two relative humidity (RH) sensors (A and H Humicaps), which had been available with the RS80, were well characterized and have been compared with reference instruments in simultaneous soundings. The RS80-A had a calibration-based dry bias (e.g., Miloshevich
1. Introduction Vaisala is the largest manufacturer of radiosondes, and with their recent RS92 model a new generation of radiosondes is introduced. This model replaces the older RS80 radiosonde and, to a smaller extent, the RS90 model. The two relative humidity (RH) sensors (A and H Humicaps), which had been available with the RS80, were well characterized and have been compared with reference instruments in simultaneous soundings. The RS80-A had a calibration-based dry bias (e.g., Miloshevich
atmospheric water vapor content using various types of observations. Since the middle of the twentieth century, many countries have made routine observations of atmospheric humidity using balloon-borne radiosondes. These radiosonde humidity observations provide the only record that has high vertical resolution and is long enough for quantifying multidecadal changes in atmospheric water vapor, although other observations, such as surface humidity data ( Dai 2006 ; Willett et al. 2008 ) and recent
atmospheric water vapor content using various types of observations. Since the middle of the twentieth century, many countries have made routine observations of atmospheric humidity using balloon-borne radiosondes. These radiosonde humidity observations provide the only record that has high vertical resolution and is long enough for quantifying multidecadal changes in atmospheric water vapor, although other observations, such as surface humidity data ( Dai 2006 ; Willett et al. 2008 ) and recent
1. Introduction Water vapor is the earth’s strongest greenhouse gas. Researchers have long expected actual water vapor amounts to change in proportion to those at equilibrium over liquid or ice (in effect conserving relative humidity), which is born out in modern numerical climate models and, at least roughly, in observations ( Colman 2004 ; Hall and Manabe 1999 ; Held and Soden 2000 ; Ingram 2002 ; Rind et al. 1991 ; Soden and Held 2006 ; Soden et al. 2002 , 2005 ). This behavior
1. Introduction Water vapor is the earth’s strongest greenhouse gas. Researchers have long expected actual water vapor amounts to change in proportion to those at equilibrium over liquid or ice (in effect conserving relative humidity), which is born out in modern numerical climate models and, at least roughly, in observations ( Colman 2004 ; Hall and Manabe 1999 ; Held and Soden 2000 ; Ingram 2002 ; Rind et al. 1991 ; Soden and Held 2006 ; Soden et al. 2002 , 2005 ). This behavior
planet. Stratiform anvil clouds characterized by negative net radiative forcing, and thin cirrus clouds characterized by positive net radiative forcing ( Hartmann et al. 2001 ), spread outward from deep cumulonimbus clouds and are the most prominent clouds in the convective regions of the tropics. Moist boundary layer air is transported by deep convection to the dry mid- and upper troposphere, where even slight humidity increases can strongly reduce the radiation emitted to space ( Shine and Sinha
planet. Stratiform anvil clouds characterized by negative net radiative forcing, and thin cirrus clouds characterized by positive net radiative forcing ( Hartmann et al. 2001 ), spread outward from deep cumulonimbus clouds and are the most prominent clouds in the convective regions of the tropics. Moist boundary layer air is transported by deep convection to the dry mid- and upper troposphere, where even slight humidity increases can strongly reduce the radiation emitted to space ( Shine and Sinha
1. Introduction The High-Resolution Infrared Radiation Sounder (HIRS) has been on board the National Oceanic and Atmospheric Administration (NOAA) polar-orbiting satellite series for more than 30 yr. There are 20 channels in the HIRS instrument, providing measurement in a spatial resolution of approximately 20 km at nadir. Among these channels, channels 7, 8, 10, and 11 are designed to measure the surface and lower-atmosphere temperature and humidity. Central wavenumbers for these channels are
1. Introduction The High-Resolution Infrared Radiation Sounder (HIRS) has been on board the National Oceanic and Atmospheric Administration (NOAA) polar-orbiting satellite series for more than 30 yr. There are 20 channels in the HIRS instrument, providing measurement in a spatial resolution of approximately 20 km at nadir. Among these channels, channels 7, 8, 10, and 11 are designed to measure the surface and lower-atmosphere temperature and humidity. Central wavenumbers for these channels are
observations in both space and time, but also because the large suite of instrument platforms typically deployed allows for cross-calibration that can greatly enhance the accuracy of the data. With the goal to create high-quality field program datasets, several efforts have been undertaken in recent years to correct humidity biases identified in upper-air sounding datasets. For example, dry biases identified in Vaisala RS80 sondes and moist biases in VIZ sondes were corrected in the Tropical Ocean Global
observations in both space and time, but also because the large suite of instrument platforms typically deployed allows for cross-calibration that can greatly enhance the accuracy of the data. With the goal to create high-quality field program datasets, several efforts have been undertaken in recent years to correct humidity biases identified in upper-air sounding datasets. For example, dry biases identified in Vaisala RS80 sondes and moist biases in VIZ sondes were corrected in the Tropical Ocean Global
