Long-term trends in stratospheric ozone, temperature, and water vapor over the Indian region

Abstract

Abstract. We have investigated the long-term trends in and variabilities of stratospheric ozone, water vapor and temperature over the Indian monsoon region using the long-term data constructed from multi-satellite (Upper Atmosphere Research Satellite (UARS MLS and HALOE, 1993-2005), Aura Microwave Limb Sounder (MLS, 2004(MLS, -2015, Sounding of the Atmosphere using Broadband Emission Radiometry (SABER, 2002(SABER, -2015 on board TIMED (Thermosphere Ionosphere Mesosphere Energetics Dynamics)) observations covering the period 1993-2015. We have selected two locations, namely, Trivandrum (8.4 • N, 76.9 • E) and New Delhi (28 • N, 77 • E), covering northern and southern parts of the Indian region. We also used observations from another station, Gadanki (13.5 • N, 79.2 • E), for comparison. A decreasing trend in ozone associated with NO x chemistry in the tropical middle stratosphere is found, and the trend turned to positive in the upper stratosphere. Temperature shows a cooling trend in the stratosphere, with a maximum around 37 km over Trivandrum (−1.71 ± 0.49 K decade −1 ) and New Delhi (−1.15 ± 0.55 K decade −1 ). The observed cooling trend in the stratosphere over Trivandrum and New Delhi is consistent with Gadanki lidar observations during 1998-2011. The water vapor shows a decreasing trend in the lower stratosphere and an increasing trend in the middle and upper stratosphere. A good correlation between N 2 O and O 3 is found in the middle stratosphere (∼ 10 hPa) and poor correlation in the lower stratosphere. There is not much regional difference in the water vapor and temperature trends. However, upper stratospheric ozone trends over Trivandrum and New Delhi are different. The trend analysis carried out by varying the initial year has shown significant changes in the estimated trend.

Long-term trends of instability and associated parameters over the Indian region obtained using a radiosonde network

“…Since a minimum wind speed of 31 km h −1 or 8.61 m s −1 is required for identification as an ordinary thunderstorm, this 1 m s −1 error is not expected to perturb the thunderstorm severity climatology presented in this study. In the same way, IMD has provided daily rainfall accumulations in 0.25 • spatial resolution over the Indian region since the year 1900 (Rajeevan et al, 2006(Rajeevan et al, , 2008Pai et al, 2014). These daily precipitation data at the closest grid point are used to define the frequency of severe and weak rainfall days, hereafter referred to as WRF and SRF, respectively.…”

“…We have estimated all parameters from daily radiosonde data, averaged over seasons and annually to obtain a trend at a 95 % confidence interval using robust regression analysis (Shepard, 1968). Further, the parameters from radiosonde were averaged region-wise, and then the robust fit algorithm is employed on the normalized time series to get the longterm trends (Andersen, 2008;Raj et al, 2018). These yearly trend values are multiplied by 37 to get the total climatological trend in one parameter over the complete data span of 1980-2016.…”

Long‐Term Observations of Stratosphere‐Troposphere Exchange Using MST Radar and Aura MLS Measurements Over a Tropical Station Gadanki

“…Table 2 shows the number of radiosonde and ozonesonde launched per month, and their burst height is listed in Table 3. Details of uncertainty, precision, and accuracy of radiosonde/ozonesonde can be found in Akhil Raj et al (2018) and Das et al (2019). The cold-point and convective tropopause (COT) are derived from the radiosonde-measured temperature profile as described in Mehta et al (2008) and Suneeth et al (2017).…”

Long‐Term Trends in the Low‐Latitude Middle Atmosphere Temperature and Winds: Observations and WACCM‐X Model Simulations

“…As shown in Figure A1, temperature sensor has been changed several times which has hampered the long-term trend estimations. The merging is carried out by calculating the offset following Froidevaux et al (2015) and Akhil Raj et al (2018). Nevertheless, it includes 25 years of observations (1993-2017) from both these satellites.…”

“…Trends in the temperature are being reported using the long-term measurements from network of radiosondes (Philipona et al, 2018, and references therein), Rayleigh lidars (Kishore et al, 2014), and satellite observations (Akhil Raj et al, 2018;Huang et al, 2014;Randel et al, 2017, and references therein). Trends in the temperature are being reported using the long-term measurements from network of radiosondes (Philipona et al, 2018, and references therein), Rayleigh lidars (Kishore et al, 2014), and satellite observations (Akhil Raj et al, 2018;Huang et al, 2014;Randel et al, 2017, and references therein).…”