1. Introduction
The Indian summer monsoon (ISM) develops in response to the large thermal gradient between the warm Asian continent and cooler Indian Ocean. The strong southwesterly flow in the lower troposphere brings large amount of moisture into the Indian region, which is released as precipitation. The prosperity of agriculture in India largely depends on the arrival and subsequent distribution of monsoon rains. In most of the years, the monsoon strikes the southern tip of the west coast of India in early June, advances northward, and is established over most of the country by the end of June. The summer monsoon also known as southwest monsoon accounts for 70% of the annual rainfall of India. Numerous studies have been made to identify the onset of the monsoon based on the changes in various atmospheric parameters.
Precipitation patterns in the Indian subcontinent are characterized by dry conditions in the early summer and relatively moist conditions in late summer. The conditions during dry and moist regimes have been studied in the past using the data from radiosonde with a relatively coarse time and height resolutions. In general, the onset of ISM is usually noted by a change of wind direction and conventionally identified in terms of rainfall occurrence. Using rain gauge data, Ananthakrishnan and Soman (1988) defined the onset of ISM based on Kerala, India, rainfall during which the rainfall amounts increase to over 15 mm day−1. Fasullo and Webster (2003) defined the ISM onset and withdrawal by vertically integrated moisture transport over the Arabian Sea. Using satellite observations, Ramesh Kumar (2004) studied the onset of the southwest monsoon over the Kerala coast by identifying the premonsoon rainfall peak. Prasad and Hayashi (2005) studied onset in terms of zonal asymmetric temperature anomaly between 850 and 200 hPa with the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis data. Taniguchi and Koike (2006) defined onset based on wind speed exceeding 8 m s−1 at 850 hPa using NCEP–NCAR reanalysis data. Joseph et al. (2006) developed a three step method objectively for defining monsoon onset over Kerala (MOK) using NCEP–NCAR winds, outgoing longwave radiation (OLR), and integrated water vapor with a criterion of area mean wind reaching 6 m s−1 at 600 hPa. Jagannadha Rao et al. (2007) presented a study on the onset/arrival of monsoon at single location Gadanki, India, using UHF radar winds especially vertical winds and signal-to-noise ratio (SNR) without the need of rainfall separately.
It is well known that monsoon affects not only rainfall but also tropospheric wind, humidity, and temperature fields. Rao et al. (1998) identified the onset phase of southwest monsoon using scatterometer winds over the Indian Ocean and observed that increase in wind speed coincides with the onset of the monsoon. Simon et al. (2006) identified an increase in the water vapor content over the west Arabian Sea using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) data, which have provided a lead time of two and a half weeks for the onset of monsoon. Recently, Ramesh Kumar et al. (2009) examined the columnar water vapor content, sea surface temperature, and evaporation to study the monsoon onset over Kerala using recently released high-resolution Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS). Using a network of weather stations across Thailand, Cook and Buckley (2009) revealed that both onset and withdrawal are associated with expected wind and geopotential height anomalies in the lower atmosphere using daily precipitation data. Note that all the above-mentioned studies utilized mostly radiosonde data, reanalysis data, VHF/UHF wind profiler, and only few studies have used satellite observations.
By using rainfall and large-scale features, the India Meteorological Department (IMD) adopted new criteria for MOK operationally (Pai and Rajeevan, 2009). According to this criteria, “if 2.5 mm or more rainfall is reported in the available 14 stations over southern tip of India, then MOK may be declared on the second day provided the depth of westerlies should maintain up to 600 hPa in the grid box 0°–10°N and 55°–80°E, zonal wind speed in the grid box 5°–10°N and 70°–80°E should be of the order of 15–20 kt at 925 hPa and OLR values should be below 200 W m−2 in the grid box 5°–10°N and 70°–75°E.”
GPS radio occultation (RO) observations of Earth’s atmosphere are one of the sources of meteorological data (refractivity, temperature, and water vapor, etc.) with good altitude resolution and global coverage in recent time (Ware et al. 1996; Kursinski et al. 1997; Rocken et al. 1997; Healy 2001; Hajj et al. 2002). The technique depends on accurate measurements of the global positioning system (GPS) dual-frequency phase delays obtained from a receiver in low-Earth orbit (LEO), which tracks a GPS satellite by setting or rising behind Earth’s atmosphere. The extra phase delays due to atmospheric refractivity changes at different heights are converted to atmospheric bending angles. Assuming spherical symmetry in the locality of occulting atmosphere, the profiles of refractivity can be estimated and subsequently the pressure and temperature. Water vapor can be extracted using independent information of temperature. A detailed description of the inversion of RO measurements can be found in Kursinski et al. (1997). Although numerous studies have focused on the evolution of various parameters during the onset of ISM, for the first time the present study takes the advantage of the calibration-free GPS RO refractivity for monitoring arrival and progression of monsoon over the Arabian Sea. Note that Huang et al. (2010) showed a reasonably good impact on regional weather predictions by using GPS RO data assimilation.
Pearce and Mohanty (1984) observed moisture buildup followed by rapid intensification of winds and substantial increase in latent heat release over the Arabian Sea during the evolution of the monsoon. Soman and Kumar (1993) observed that the buildup of moisture occurs a few days before the onset. Sharma and Prasad (1993) have reported that the changes in radio refractive index in the lower troposphere over Bombay (Mumbai), India, matched well with the onset of the monsoon whereas the index over Trivandrum, India, does not show such significant changes. Since the single refractivity parameter obtained from GPS RO contains both temperature and water vapor information, it can be utilized to monitor the monsoon arrival without looking for temperature and humidity separately. In this study we examine whether refractivity derived from GPS RO can properly represent the arrival and progression of ISM by looking into the time series of tropospheric refractivity over the east Arabian Sea (5°–15°N, 65°–75°E) and its activity during active and break spells of ISM over the land region (10°–15°N, 79°–81°E) covering Gadanki (13.5°N, 79.2°E), where several collocated instruments are available. Note that the former grid box is selected to take care of the area used by IMD (Pai and Rajeevan 2009) as mentioned above.
2. Data and methodology
Level 3 GPS RO data from the Challenging Minisatellite Payload (CHAMP) German mission (Wickert et al. 2001) collected from GeoForschungs-Zentrum (GFZ), Potsdam, Germany, using their standard method for the radio occultation processing during 2001–06 and the Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC, which is a joint U.S.–Taiwanese mission; Rocken et al. 2000) data processed by COSMIC Data Analysis and Archive Centre (DAAC) for the period of 2006–10 are used for the present study. The daily refractivity and temperature over the Arabian Sea (5°–15°N, 65°–75°E) region during the period April–September are taken as it is considered to be the transition, evolution period, and establishment of ISM. The collected data have global coverage with more than 200 refractivity and temperature profiles per day through CHAMP GPS RO and increased to almost 5 times by COSMIC GPS RO. As the study region is in the tropics, the number of occultations is relatively lower in density than in the high latitudes due to high inclination of CHAMP and COSMIC LEOs giving rise to data gaps on some days, particularly in CHAMP GPS RO. However, since the study region covers a larger area, probability of at least three occultations per day over the grid is high. In the case of COSMIC GPS RO, the number of occultations per day in the grid box amount to 5 on an average.
To study the variations of wind and water vapor over the study region, NCEP–NCAR reanalysis data (Kalnay et al. 1996) are used. The OLR data from the National Oceanic and Atmospheric Administration (http://www.cdc.noaa.gov) are utilized to examine the convective activity over the study region.
In addition to the satellite and reanalysis datasets, the daily accumulated rainfall over the Gadanki region has been considered during May–August from 1998–2010 to observe the variation of refractivity during rainfall conditions and also to differentiate the active and break spells of monsoon over Gadanki.
3. Results
Figure 1 shows the infrared channel picture taken from the Kalpana-1 satellite on 28 May 2007, the day onset of ISM, which was declared over Kerala by the IMD. The study region of interest is shown with the box. Large amount of clouds over the study region are noticed. Before analyzing the refractivity variations with respect to the onset of monsoon, it is necessary to understand the temporal variations of some of the important meteorological parameters and their abrupt transitions at the time of onset of monsoon over the study region. The summer monsoon normally sets in over the Arabian Sea around 1 June with a standard deviation of 8 days (Soman and Kumar 1993). Table 1 provides the dates of onset of ISM declared by IMD during 2001–10. Figure 2a shows the time series of daily wind speed at 850 hPa averaged over the southeast Arabian Sea (5°–15°N, 65°–75°E) during April–July 2007 using the NCEP–NCAR reanalysis data. The zonal wind speed is around 2 m s−1 up to 2 May and then shows rapid strengthening of the low-level wind exceeding 8 m s−1 (Taniguchi and Koike 2006) around 1 June, which persisted for the next few weeks except for a small dip during 4–9 June. The precipitable water averaged over the same region using NCEP–NCAR data shows similar increase of moisture by 10 kg m−2 in a few days (Fig. 2a) signaling the monsoon arrival. The arrival of the monsoon can be understood using OLR, which can be used as proxy for tropical deep convection. Figure 2b shows the time series of OLR averaged over the east Arabian Sea. OLR value less than 220 W m−2 is considered as regions of convective activity (Soman and Kumar 1993). The OLR shows a decreasing trend from early May and reaches the value of 220 W m−2 around 26 May indicating the development of convective activity and reaches a minimum value of ~170 W m−2 on the same day. This deep convection continued for few more days showing the progression of the monsoon except during the dip observed in the wind speed. Thus, the wind speed picking up to optimum levels with establishment of the westerly jet and an increase in precipitable water and deep convective activity reveal the arrival of the monsoon over the southern Arabian Sea around 28 May 2007, which happens to be the onset of ISM over the Arabian Sea (IMD weather analysis). Note that the criteria of 8 m s−1 to detect the onset of ISM obtained by Taniguchi and Koike (2006) is for the grid 7.5°–20°N, 62.5°–75°E. This criterion, when applied for the data obtained during 2002–10 for the same grid, finds that this value (8 m s−1) holds well with an average difference of 3.5 ± 1.26 days with the onset dates declared by IMD. The same exercise has been done for the Arabian Sea grid and found that there exists the difference of 2.8 ± 0.74 days revealing that there will be an error of ~3–4 days when the wind speed criteria is applied and holds good for the year 2007 case also shown in Fig. 2a. The year-wise dates of crossing of the wind speed 8 m s−1 for both the grids are also provided in Table 1. This strong wind during the evolution of the monsoon transports moist air onto the Indian region (Pearce and Mohanty 1984) giving rise to rainfall.
Infrared channel picture taken from the Kalpana-1 satellite on 28 May 2007. The box represents the study region.
Citation: Monthly Weather Review 141, 6; 10.1175/MWR-D-12-00180.1
Year-wise onset days declared by IMD, days before enhancement in N is seen, the date on which wind speed (WS) crossing 8 m s−1 is seen in the Arabian Sea grid (present study), and the date on which WS crossing 8 m s−1 seen in the grid defined by Taniguchi and Koike (2006).
Time series of daily (a) wind speed (m s−1) at 850 hPa (left axis) and precipitable water (mm) (right axis), and (b) mean OLR (W m−2) averaged over the southeast Arabian Sea (5°–15°N, 65°–75°E) during April–July 2007 using NCEP–NCAR reanalysis data. The arrow on the x axis shows the onset day over the Arabian Sea (IMD weather analysis).
Citation: Monthly Weather Review 141, 6; 10.1175/MWR-D-12-00180.1
To examine whether refractivity observed from GPS RO represent the monsoon evolution over the Arabian Sea, the temporal variation of refractivity is analyzed. Figure 3 shows the time series of refractivity averaged for three heights centering at 4.8 km (~600 hPa) and 16 km (~100 hPa) for consistency and their difference along with mean upper-tropospheric temperature between 13 km and the tropopause using COSMIC GPS RO during the period 1 April–19 July 2007. Note that standard deviations are also shown for the days having more than three profiles within the grid box. We note that smaller standard deviations shown in the figure reveals high consistency and accuracy in the measurements on a given day within the selected grid box. It is clear that the refractivity around 600 hPa (Fig. 3a) is around 170 N-units in the premonsoon month of April and starts increasing gradually during the early May and increase sharply by 5–10 N-units a few days before the arrival of monsoon. It continues for the next few days and also during the active period of monsoon. Contrasting to the lower levels, the refractivity changes slightly in the upper troposphere around 100 hPa (~16 km) during the monsoon period (Fig. 3b). The variation in refractivity is around 0.5–1 N-units. Though the change is very small compared to lower level, it is considerable at higher levels. Noticeable changes are seen especially before and after the onset at both the levels. Thus, the vertical refractivity difference between 600 and 100 hPa has a strong seasonal variation and can be used as a good indicator for the arrival of monsoon over the Arabian Sea.
Temporal variation of refractivity (N-units) at (a) 4.8 km (~600 hPa), (b) 16 km (~100 hPa), (c) refractivity difference between 4.8 and 16 km, and (d) mean upper-tropospheric temperature derived from GPS RO measurements during April–July 2007. The vertical bar represents the standard deviation obtained while averaging the number of occultations in the grid box each day. The arrow on the x axis shows the onset day over the Arabian Sea (IMD weather analysis).
Citation: Monthly Weather Review 141, 6; 10.1175/MWR-D-12-00180.1
Figure 3c shows the difference of refractivity between 600 and 100 hPa. Making use of the onset day (28 May 2007) as referenced from the IMD weather analysis (http://www.imd.gov.in/) (small vertical arrow on x axis) it is found that a sharp increase of nearly 10 N-units in refractivity took place few days before the onset of monsoon. On the day of onset and during the next few days, a sudden dip in the refractivity is seen. These two features can give us an insight of the arrival of the monsoon. It is also to be noted that the mean upper-tropospheric temperature (13-km tropopause) increases by 1.5–2 K, 3–4 days before the onset (Fig. 3d).
We have performed a similar analysis for the year 2002 using the CHAMP GPS RO data available over the Arabian Sea where there was “bogus onset” (29 May 2002) and “real onset” (13 June 2002) (Flatau et al. 2003). According to the Flatau et al. (2003), monsoonlike perturbations that appeared in mid-May disappeared by the end of the month and were followed by a heat wave in India, caused the bogus onset and it is associated with delaying onset of the monsoon. The features mentioned above for the year 2007 are also found matching well (figure not shown) for the year 2002 [i.e., enhancement of N eight days before the bogus onset day (29 May 2002)]. However, continuous data are not available from CHAMP GPS RO after 9 June 2002 to investigate in detail the real onset that happened on 13 June 2002. Instead we have taken radiosonde data available over Trivandrum and analyzed the variability of N [by putting radiosonde temperature and water vapor in Eq. (1)].
Figure 4 shows the time series of N averaged for three heights centering at 4.8 km (~600 hPa) and 16 km (~100 hPa) and their difference along with mean upper-tropospheric temperature from 13 km and tropopause using Trivandrum radiosonde during the period from 1 April to 31 July 2002. As only two observations per day are available, we have not provided standard deviations. Since these observations are over a land region where moisture and temperature variability will be different, the features are expected to be different than those observed in Fig. 3 over the Arabian Sea. Note that on average the higher N (by 10 N-units) is found around 600 hPa though there is not much difference around 100 hPa. Figure 4c shows the difference of N between 600 and 100 hPa. In the year 2002, enhancement in the N started from 8 May 2002 onward until the bogus onset date (i.e., 29 May 2002), though there are some dips a few days before this day, which represents the variability of the small region over Trivandrum. However, the dip of 5 N-units on the date on bogus onset is again noticed in this year also. After this day, the variability in N is highly random. Interestingly from 5 June 2002, the enhancement in N again started and continued till the real onset day (13 June 2002). On the day of real onset and the next day, a sudden dip of 16 N-units in the refractivity is seen. These two features can give us an insight of the true arrival of the monsoon. However, no significant variability in the mean upper-tropospheric temperature is seen in this case (Fig. 4d). Note that Flatau et al. (2003) attributed the bogus onset to a convectively coupled Kelvin wave rather than a Madden–Julian oscillation (MJO)-like disturbance that has been typically associated with the “real monsoon onset” in the past. From this analysis we are not in position to support or against Flatau et al. (2003), as prior to the both the onset days we see similar features. In addition, most of the radiosonde observations are not reaching 16 km on many days, which restricted our study. Perhaps more cases are needed to address this issue.
As in Fig. 3, but observed using Trivandrum radiosonde data for the year 2002. The dotted, thick vertical line is drawn at the dates of bogus and real onset dates. The thick horizontal line is drawn at the climatological (1972–2010) mean obtained from Trivandrum radiosonde data.
Citation: Monthly Weather Review 141, 6; 10.1175/MWR-D-12-00180.1
Centered on the onset date over the Arabian Sea based on IMD, the pentad refractivity has been composite from 45 days before to 45 days after the date of onset. Figure 5 shows the composite of pentad refractivity difference between 600 and 100 hPa for the study region (with the onset pentad marked as 0) taken during 2001–06. The pentad refractivity is calculated with pentad 0 representing from day 0 to +4 and pentad −1 indicating −1 to −5. A gradual increase in refractivity difference is found 4–6 pentads before with sharp enhancement during 1–2 pentads before the onset exceeding 128 N-units. At the time of monsoon arrival a dip of ~5 N-units in the refractivity attaining minimum is seen and persisted for few more days. An arbitrary value of 128 N-units represents a clear transition of atmospheric conditions. Coupled with this, the fall in the refractivity might be an indicator for the arrival of onset. We further verified the observed features at lower levels using COSMIC GPS RO by taking advantage of occultations reaching up to the near surface. Figure 5b shows the composite pentad refractivity difference between 850 and 600 hPa observed using COSMIC GPS RO during 2006–10. Similar features observed in the higher levels again reproduced well even at lower levels suggesting that refractivity is a good measure to detect the onset of ISM.
(a) Composite pentad refractivity difference between 600 and 100 hPa from 45 days before to 45 days after the date of onset (with onset pentad marked as 0) for the study region taken during 2001–06 from CHAMP GPS RO. The horizontal line at 128 N-units represents a clear transition of atmospheric conditions. (b) As in (a), but with the composite pentad refractivity difference between 850 and 600 hPa observed using COSMIC GPS RO during 2006–10. The vertical bar represents the standard deviation.
Citation: Monthly Weather Review 141, 6; 10.1175/MWR-D-12-00180.1
The year-wise details on the how many days before enhancement in N (difference between 4.8 and 16 km) are seen is provided in Table 1. By using regression analysis, we further tested how good this arbitrary number (128 N-units) works for the prediction of onset of ISM though the present data length is not sufficient (only 10 years). For this we have constructed a regression equation by using the onset dates declared by IMD as a reference and the date at which the enhancement in the refractivity above 128 N-units is observed during the period 2002–08. The regressed values (with slope = 0.58 and intercept = 1.26) are tested for the years 2009 and 2010 and it is found that there is a difference of 3–4 days between the IMD declared onset dates and the enhancements observed in the refractivity (enhancement in the refractivity always leads). More rigorous analysis procedures like the f test, t test, and jackknife validation are applied to the dataset. The f-test and t-test values are found to be 3.15 and 4.32, respectively. The jackknife bias is found to be 1.23. Though the difference of 3–4 days is expected with any criteria (as also seen with wind speed criteria), since the data length is not sufficient to apply such regression analysis it is tested qualitatively and more quantitative analysis will be done once the data of sufficient length are obtained.
We also investigated the activity of ISM by using refractivity profiles over land regions (10°–15°N, 77°–81°E) where other meteorological information also exists. Figure 6a shows the time series of zonal and meridional wind speed at 850 hPa taken from the NCEP–NCAR reanalysis during May–September 2010. It is clear that the zonal wind during the first half of May is easterly in direction and slowly turned southwesterly (zonal wind westerly with meridional wind southerly) with the wind speed exceeding 8 m s−1 and persisting up to the end of the season. The onset date over Kerala was 31 May 2010. Figure 6b shows the refractivity at 1.5 km (850 hPa), daily rainfall during the period of May–August 2010, and climatological mean (1998–2010) rainfall over the above-mentioned region. Mean refractivity has been computed during the period of ISM from 2006–10 and is given as 325 N-units. A direct relation between the refractivity and rainfall is clearly seen; as the refractivity exceeds 325 N-units, the rainfall is noticed (very clear in the first half of the season). Enhancement in the refractivity indicates increase in the moisture level in the atmosphere carried by the monsoon winds (Jagannadha Rao et al. 2007). Note that Gadanki is a unique region where equal amount of rainfall occurs in both seasons, as evident from wind and rainfall information, monsoon is active over Gadanki for several days in the year 2010. Similar features are also depicted in refractivity, which shows refractivity above 325 N-units as active spell and the rest as break spell. Thus, from the above results it is obvious that the changes in refractivity can effectively represent the onset and activity of the monsoon at any place.
Time series of (a) zonal and meridional wind velocity at 1.5 km, (b) refractivity at 1.5 km over the land region (10°–15°N, 79°–81°E), daily rainfall during the period of May–August 2010, and climatological mean (1998–2010) rainfall over Gadanki. The line is drawn at 325 N-units, which is the average value obtained for a given season.
Citation: Monthly Weather Review 141, 6; 10.1175/MWR-D-12-00180.1
4. Discussion
The differential heating between the Indian subcontinent and the ocean south of it produces a circulation in the lower troposphere resulting in a cross-equatorial flow blowing into the Arabian Sea and developing into low-level southwesterlies. This strong cross-equatorial flow known as the low-level jet blows into the Arabian Sea and intensifies at the time of onset over the southwest coast of India bringing more moisture. This causes deepening of the humid layer. This moisture transport is more evident in the lower and midtroposphere. Appreciable moisture is present in the upper levels especially in the monsoon period during which deep convection is predominant. This upper-level moisture presence cannot be visualized with the conventional radiosondes. As the refractivity is proportional to the water vapor [Eq. (1)], it is common to observe an enhancement in the refractivity more at the 600-hPa level relative to 100 hPa. The sharp enhancement in the refractivity a few days before can be attributed to moisture buildup before onset probably due to evaporation (Soman and Kumar 1993; Pearce and Mohanty 1984). With the advancement of the monsoon, the convective activity over the Arabian Sea increases and is maximum at the time of onset, which is evident from the time evolution of the OLR presented in Fig. 2b. This development of convective activity causes the release of latent heat thereby increasing tropospheric temperature (Fig. 3d). Further, this deep convection may transport moisture vertically resulting in small enhancement in refractivity at the upper levels. The combined effect of these two processes results in the decrease of refractivity at the time of monsoon arrival as refractivity is inversely related to temperature. This dip can also be attributed to a decrease in moisture content at the time of the monsoon onset (Rao et al. 2005). During the active phase of ISM, large moisture content can be noticed before it precipitates and vice versa during the break phase. Thus, enhancement (reduction) in the refractivity around 850 hPa is clearly noticed during the active (break) phase of ISM.
5. Summary
Using GPS RO it is possible to retrieve profiles of refractivity and temperature with good altitude resolution and global coverage. In this study, it is examined whether refractivity variations can represent the evolution of the Indian monsoon and its arrival. A noteworthy feature is the appreciable enhancement in the refractivity difference between 600 and 100 hPa a few days (9.23 ± 3.6 days) before the arrival of the monsoon coupled with a dip at the time of onset. This is also true at low levels confirmed using COSMIC GPS RO observations. A clear correlation between the activity of the monsoon and the variations in the refractivity is also noticed. Whenever there is an above-normal enhancement in the refractivity, enhancement of rainfall is noticed and vice versa. Thus, it is proposed that variations in the refractivity can be used to monitor the onset of ISM and its activity. However, there are certain limitations with the currently available dataset. The present study is preliminary and is the first of its kind with the existing data. The limitations of the retrieval of refractivity in the lower heights below 2 km are due to multipath effects (Gorbunov and Gurvich 1998) and the high inclination of LEOs. The density of occultations is low resulting in data gaps over the study area. However, an arbitrary value of 128 (or 60) N-units difference between 600 hPa (850 hPa) and 100 hPa (600 hPa) coupled with a fall in refractivity at the time of arrival might give an indication of the clear transition of atmospheric conditions. To substantiate this choice of criterion, a large number of occultations are needed. Though some of the existing satellite measurements [e.g., the Atmospheric Infrared Sounder (AIRS)] also provide information on temperature and water vapor, however, their vertical resolution and accuracies in the lower troposphere are not on par with GPS RO measurements. With the commissioning of more missions especially low-inclination satellites like Megha Tropiques (launched in October 2011), an Indo–French mission, dense occultations are expected that will allow us to study monsoon dynamics in more detail.
Acknowledgments
We wish to thank GFZ, Potsdam, Germany; TACC, Taiwan; and NOAA–CIRES for providing the GPS RO datasets of CHAMP, COSMIC, and reanalysis data, respectively. Jagannadha Rao is thankful to the Commissioner of the Department of Technical Education, government of Andhra Pradesh, India, for giving permission to carry out this work. We thank all three anonymous reviewers for their constructive comments/suggestions, which helped to improve the manuscript significantly.
REFERENCES
Ananthakrishnan, R., and M. K. Soman, 1988: The onset of the southwest monsoon over Kerala: 1901–1980. J. Climatol., 8, 283–296.
Basha, G., and M. V. Ratnam, 2009: Identification of atmospheric boundary layer height over a tropical station using high-resolution radiosonde refractivity profiles: Comparison with GPS radio occultation measurements. J. Geophys. Res., 114, D16101, doi:10.1029/2008JD011692.
Cook, B. I., and B. M. Buckley, 2009: Objective determination of monsoon season onset, withdrawal, and length. J. Geophys. Res., 114, D23109, doi:10.1029/2009JD012795.
Fasullo, J., and P. J. Webster, 2003: A hydrological definition of Indian monsoon onset and withdrawal. J. Climate, 16, 3200–3211.
Flatau, M. K., P. J. Flatau, J. Schmidt, and G. N. Kiladis, 2003: Delayed onset of the 2002 Indian monsoon. Geophys. Res. Lett., 30, 1768, doi:10.1029/2003GL017434.
Gorbunov, M. E., and A. S. Gurvich, 1998: Microlab-1 experiment: Multipath effects in the lower troposphere. J. Geophys. Res., 103 (D12), 13 819–13 826.
Hajj, G. A., E. R. Kursinski, L. J. Romans, W. I. Bertiger, and S. S. Leroy, 2002: A technical description of atmospheric sounding by GPS occultation. J. Atmos. Sol. Terr. Phys., 64, 451–469.
Healy, S. B., 2001: Smoothing radio occultation bending angles above 40 km. Ann. Geophys., 19, 459–468.
Huang, C.-Y., and Coauthors, 2010: Impact of GPS radio occultation data assimilation on regional weather predictions. GPS Solutions, 14, 35–49, doi:10.1007/s10291-009-0144-1.
Jagannadha Rao, V. V. M., M. Roja Raman, M. Venkat Ratnam, D. Narayana Rao, and S. V. Bhaskara Rao, 2007: Onset of Indian summer monsoon over Gadanki (13.5°N, 79.2°E): Study using lower atmospheric wind profiler. Geophys. Res. Lett., 34, L22803, doi:10.1029/2007GL031592.
Joseph, P. V., K. P. Sooraj, and C. K. Rajan, 2006: The Summer Monsoon onset process over South Asia and an objective method for the date of monsoon onset over Kerala. Int. J. Climatol., 26, 1871–1893.
Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437–472.
Kursinski, E. R., G. A. Hajj, J. T. Schofield, R. P. Linfield, and K. R. Hardy, 1997: Observing Earth’s atmosphere with radio occultation measurements using the Global Positioning System. J. Geophys. Res., 102 (D19), 23 429–23 465.
Narayana Rao, D., and Coauthors, 2009: Validation of the COSMIC radio occultation data over Gadanki (13.48°N, 79.2°E): A tropical region. Terr. Atmos. Oceanic Sci., 20, 59–70, doi:10.3319/TAO.2008.01.23.01(F3C).
Pai, D. S., and M. N. Rajeevan, 2009: Summer monsoon onset over Kerala: New definition and prediction. J. Earth Syst. Sci., 118, 123–135.
Pearce, R. P., and U. C. Mohanty, 1984: Onset of the Asian summer monsoon 1979–1982. J. Atmos. Sci., 41, 1620–1639.
Prasad, V. S., and T. Hayashi, 2005: Onset and withdrawal of Indian summer monsoon. Geophys. Res. Lett., 32, L20715, doi:10.1029/2005GL023269.
Ramesh Kumar, M. R., 2004: Forecasting of onset of southwest monsoon over Kerala coast using satellite data. Geosci. Remote Sens. Lett. IEEE, 1 (4), 265–267, doi:10.1109/LGRS.2004.832226.
Ramesh Kumar, M. R., S. Sankar, and C. Reason, 2009: An investigation into the conditions leading to monsoon onset over Kerala. Theor. Appl. Climatol., 95 (1–2), 69–82, doi:10.1007/s00704-008-0376-y.
Rao, P. L. S., U. C. Mohanty, and K. J. Ramesh, 2005: The evolution and retreat features of the summer monsoon over India. Meteor. Appl., 12, 241–255, doi:10.1017/S1350482705001775.
Rao, U. R., P. S. Desai, P. C. Joshi, and P. C. Pandey, 1998: Early prediction of onset of South west monsoon from ERS-1 Scatterometer winds. Proc. Indian. Acad. Sci. (Earth Planet. Sci.), 107, 33–43.
Rocken, C., and Coauthors, 1997: Analysis and validation of GPS/MET data in the neutral atmosphere. J. Geophys. Res., 102 (D25), 29 849–29 866.
Rocken, C., Y. H. Kuo, W. Schreiner, D. Hunt, S. Sokolovskiy, and C. McCormick, 2000: COSMIC system description. Terr. Atmos. Oceanic Sci., 11, 21–52.
Scherllin-Pirscher, B., G. Kirchengast, A. K. Steiner, Y.-H. Kuo, and U. Foelsche, 2011: Quantifying uncertainty in climatological fields from GPS radio occultation: An empirical-analytical error model. Atmos. Meas. Technol., 4, 2019–2034, doi:10.5194/amt-4-2019-2011.
Sharma, R. V., and T. Prasad, 1993: A study of wind index in association with onset of south-west monsoon. Advances in Tropical Meteorology: Meteorology and National Development, R. K. Datta, Ed., Indian Meteorological Society, 217–221.
Simon, B., S. H. Rahaman, and P. C. Joshi, 2006: Conditions leading to the onset of the Indiana monsoon: A satellite perspective. Meteor. Atmos. Phys., 93, 201–210, doi:10.1007/s00703-005-0155-6.
Sokolovskiy, S., 2001: Tracking tropospheric radio occultation signals from low Earth orbit. Radio Sci., 36, 483–498, doi:10.1029/1999RS002305.
Sokolovskiy, S., C. Rocken, W. Schreiner, and D. Hunt, 2010: On the uncertainty of radio occultation inversions in the lower troposphere. J. Geophys. Res., 115, D22111, doi:10.1029/2010JD014058.
Soman, M. K., and K. K. Kumar, 1993: Space–time evolution of meteorological features associated with the onset of Indian summer monsoon. Mon. Wea. Rev., 121, 1177–1194.
Taniguchi, K., and T. Koike, 2006: Comparison of definitions of Indian summer monsoon onset: Better representation of rapid transitions of atmospheric conditions. Geophys. Res. Lett., 33, L02709, doi:10.1029/2005GL024526.
Ware, R., and Coauthors, 1996: GPS sounding of the atmosphere from low Earth orbit: Preliminary results. Bull. Amer. Meteor. Soc., 77, 19–40.
Wickert, J., and Coauthors, 2001: Atmosphere sounding by GPS radiooccultation: First results from CHAMP. Geophys. Res. Lett., 28, 3263–3266.
