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Distinct atmosphere-ocean coupling processes on the onset phase of Indian summer monsoon during 2017 and 2018 as revealed through SCATSAT-1 and its comparison with CFSv2
International Journal of Remote Sensing
Abstract
Distinct atmosphere-ocean coupled processes determine the inter-annual variability in the onset processes of Indian Summer Monsoon. In this work, we have analysed the distinct characteristics of onset process during 2017 (MOK17) and 2018 (MOK18) using SCATSAT-1 observations. Two years of dedicated SCATSAT-1 analysed winds and other flux datasets are used to understand distinct-coupled processes and further compared with coupled model forecasts from National Centres for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). Air-sea coupled mechanism during 2017 and 2018 suggests that there is a delayed response (about one pentad) of atmosphere-ocean coupling over North Indian Ocean on the monsoon onset and its propagation during 2018. It is found that the influence of cyclone Mekunu formed over Western Arabian Sea disturbed the onset vortex formed over Eastern Arabian Sea during MOK18. The presence of cyclone Mekunu results in a sudden spike of East-west Sea Surface Temperature gradient, Latent Heat Flux and wind stress over Arabian Sea during one pentad before monsoon onset over Kerala. This created an onset like situation in the next pentad, and later the conditions are not favoured for the further progress of the monsoon. It leads to a weak onset followed by a sluggish and halted northward progression of monsoon during 2018. In the absence of a cyclonic system during the onset phase of MOK17, conventional onset and its further progress took place during 2017. Further comparison of SCATSAT-1 and other analysed data sets with the CFSv2 model show that the CFSv2 model is able to capture the atmosphere-ocean coupled processes during the onset phase up to four pentads in advance during MOK17. However, due to the presence of Mekunu cyclone before the monsoon onset limited the forecast skill of CFSv2 only up to two pentads in advance during MOK18. We found that the presence of strong convective instability due to strong synoptic-scale system can influence the skill of coupled model forecast in the extended range. The new SCATSAT-1 observations provide high-quality observations that can be used to quantify the errors and identify common biases in the coupled models.
... However, this method has various downsides such as not defining the progress of the monsoon, and tropical cyclones can also replicate these criteria. In recent years, cyclone formation during the onset evolution has created false alarms in determining onset dates (Athira et al., 2020;Baburaj et al., 2020). Arabian sea cyclones are increased by 52% in recent 20 years (Deshpande et al., 2021) which might have influence on ISM onset dynamics also. ...
... The delayed establishment of easterly wind shear, coupled with weaker wind shear throughout ISM onset in pst20 period, may have contributed to the development of ArS cyclones during the onset period reported in previous studies. This can disrupt the onset process and result in a weak onset during pst20 epoch (Athira et al., 2020). ...
... Offshore Ekman transport indicated that in 2017, the upwelling event was initiated in June and ended before September; whereas, in 2018, it started in July and peaked in early September . This was related to the delay in monsoon propagation in 2018 (Athira et al., 2020). The upwelling was intensified in 2017 as the alongshore wind component was stronger (Jayaram et al., 2010) compared to 2018, when wind speed was higher. ...
The western Indian continental shelf is characterized by contrasting biogeochemical features from south to north mostly governed by monsoon wind forcing. Here we present the first detailed study on the phytoplankton community (analyzed by marker pigments and microscopy) during the summer monsoon addressing the interannual variability (Aug 2017 and 2018) along the Western Indian Continental Shelf waters (8°N-21°N at 200 m isobaths). A distinct interannual variability in monsoon impacted the hydrography and nutrient stoichiometry that was further cascaded to the phytoplankton community structure. The timing of the monsoon onset, wind speeds, and the strength of the alongshore wind component were the major factors that governed the interannual variability in the development and progression of the upwelling as well as phytoplankton bloom. The upwelling-dominated southwestern shelf was characterized by cold, nutrient-rich waters dominated by the marker pigment of diatoms, fucoxanthin, and microscopy also revealed the presence of large, chain-forming diatoms (Chaetoceros sp.; Dactyliosolen fragilissimus). In contrast, the low nutrient warm waters in the northern shelf housed nanophytoplankton and picophytoplankton along with small diatoms (Thalassiosira sp.) and dinoflagellates (Gymnodinium sp.). Interestingly, in a few stations in the southern shelf, the surface waters were low saline that was intensified in 2018 compared to 2017 inhibiting upwelled water from reaching the surface. Consequently, due to low nutrient levels caused by reduced upwelling and low salinity, picoplanktonic cyanobacteria dominated replacing the larger diatoms that were found plenty in 2017. Likely, such a niche shift adversely impacted the planktivorous fish stock (Oil Sardine) that was seen to be less in 2018 relative to 2017. Any further changes in monsoon variability and freshwater flow to this region may have direct consequences on the phytoplankton community as well as fisheries.
... The negative Ekman transport values observed at~8 0 N earlier in 2017 indicated a notable contribution of alongshore winds to the interannual differences of upwelling propagation (Figs. 3 and 4). Likewise, Athira et al. (2020) reported a delayed monsoon propagation and oceanatmospheric coupling in 2018 due to the formation of cyclone Mekunu which was primarily responsible for the observed interannual differences in alongshore winds. ...
Particulate organic carbon and nitrogen (POC, PN, collectively particulate organic matter, POM) and the stable isotopic signature of POC (δ13CPOC) are important to delineate its sources and recycling in shelf water. The present study provides insights into the factors responsible for spatial and interannual variability in POM and δ13CPOC values along the western Indian shelf waters (8 –21 degree N) during the southwest (SW) monsoon (August) 2017 and 2018. The dominance of phytoplankton-derived POM with a negligible terrestrial influence was evident from the positive correlation between POC and TChla contents, ratios of C: N, and δ13CPOC signatures. Prominent upwelling signatures [cold nutrient-rich water, higher POM, total Chlorophylla (TChla), and δ13CPOC values] were noted in the south (8–12 degree N), whereas low nutrient warm waters (lower values of POM, TChla, and δ13CPOC) were prevalent in the north (13–21 degree N). Phytoplankton biomass was significantly higher and matured in 2017 due to an early and stronger upwelling in the south. In 2018, delayed and weak upwelling (evident from Ekman offshore transport and pumping velocity) resulted in the late development of phytoplankton bloom and lower POM. Furthermore, considerably lower nutrient supply within the mixed layers in 2018 compared to 2017 was partially attributed to the enhanced spatial expansion of low salinity waters closer to the surface. In the north, in 2018, higher wind speeds enhanced vertical mixing resulting in increased nutrient supply and TChla compared to 2017. We conclude that monsoon wind speed in the northern shelf and strength as well as the timing of the upwelling, including freshwater flux in the south, can be the key factors in modulating the interannual variability in POM distribution and δ13CPOC signature in the western Indian Shelf waters.
... It allows more than 90% global coverage and offers high-quality wind vector products at 6.25-km enhanced resolution, which allows weather forecasting, tropical cyclone prediction, and tracking services [10], [79]- [81]. With the availability of enhanced-resolution data products (generated via the SIR algorithm), SCATSAT-1 has also been utilized in many other scientific domains, such as the cryosphere (sea ice, snow cover, and SWE) [22], [23], [25], [28], agriculture (crop phenology, soil moisture estimation [16], [82]- [84], and leaf area index [LAI]), land hydrology (river water level) [31], and atmosphere-ocean coupling [85]. ...
A scatterometer, as an active microwave radar sensor, measures the return of radar waves in the form of a backscatter coefficient after reflection or scattering from Earth’s surface. The primary objective of the scatterometer is to record the surface-wind vector observations over the ocean for the study of the climate, monitoring, the forecasting of cyclones/hurricanes, and air–sea interactions. Since its first launch in 1978, many technical improvements have been made to the scatterometer due to its potential for all-weather global-level monitoring. The scatterometer has found many
emerging applications in different scientific domains, such
as cryosphere, hydrology, agriculture, and climate studies,
with the continuous development of methods and models.
The present work is focused on reviewing historical, current, and future scatterometer missions and the progress of scatterometers in various emerging and scientific applications. Here, both C-band and Ku-band-based scatterometers are considered and explored. Subsequently, a metaanalysis has also been conducted to analyze the research status of scatterometer studies. The scope of this article allows an extensive exploration of emerging applications of
scatterometers and discusses their strengths, limitations, and current progress in the real world.
... The development of offshore phytoplankton bloom (Fig. 9) can lag behind the coastal upwelling by up to a month (Brock and McClain, 1992). Hence, the delayed monsoon onset during 2018 (Athira et al., 2020) presumably delayed the open-ocean phytoplankton biomass development. Higher nutrient, along with lower POC concentrations particularly, at the stations influenced by the Findlater Jet axis and south of it during SWM-18, indicate early uptake stage. ...
... SCATSAT-1 is an ISRO satellite having scatterometer sensor which is capable of measuring ocean surface wind parameters. The SCATSAT data-sets well captures the air-sea coupling processes over Arabian Sea during ISM (Athira et al., 2020). The data products used here are the daily Analyzed wind products of Ocean surface wind at 10 m, Wind stress and Latent Heat Flux (LHF) during the 2018 JJA. ...
Southwestern Indian state, Kerala experienced extreme devastating statewide flood event of the century during 2018 monsoon season. In this study, an attempt has been made to bring out the salient dynamical factors contributed to the Kerala flood. There were 3 active spells over Kerala during 2018 Monsoon season. All the three spells were accustomed with the intrinsic factors of low frequency components of the active spells such as strength of monsoon Low Level Jet (LLJ), Monsoon depressions in the Bay of Bengal, favorable Madden-Julian oscillation (MJO) phases and Western Pacific systems. Though all the common ingredients remain same, the third spell is distinct with the less evaporation flux over Western and Central Arabian Sea and unusual moisture transport from maritime continent through South Equatorial Indian ocean (SEIO) towards the Kerala coast across Equator. Strong meridional pressure gradient force created by the combined effect of high pressure anomaly oriented Northwest-Southeast direction across tropical Indian ocean and anomalous low pressure along monsoon trough might have contributed to this unusual moisture transport across SEIO originating from west of Australia. The anomalous high pressure in South Indian ocean was greatly influenced by the position of the Mascarene high. Subtropical Indian ocean dipole (SIOD) also exhibits an influential role by altering tropical Southern Indian ocean dynamics in favor of the unusual moisture transport. The position of the monsoon depression and presence of typhoons in Western Pacific might have aided to this moisture transport. However, the normal moisture transport from Central Arabian sea towards Kerala coast by virtue of the strong LLJ along with additional moisture transport directly from South of maritime continent through SEIO across the Equator towards Kerala coast might have played a dominant role in the historical flood event over entire Kerala state.
... The development of offshore phytoplankton bloom (Fig. 9) can lag behind the coastal upwelling by up to a month (Brock and McClain, 1992). Hence, the delayed monsoon onset during 2018 (Athira et al., 2020) presumably delayed the open-ocean phytoplankton biomass development. Higher nutrient, along with lower POC concentrations particularly, at the stations influenced by the Findlater Jet axis and south of it during SWM-18, indicate early uptake stage. ...
Monsoonal changes in particulate organic matter (POM) and its isotopic signatures (δ13CPOC and δ15NPN) were studied (Aug 2017 and 2018) in the central Arabian Sea (21-11°N 64°E) . A low-level atmospheric jet (Findlater Jet) forms during the south-west (SW) monsoon and results in “open ocean upwelling” to the north of the jet’s axis. Higher wind speed and jet-induced wind stress curl coupled with low sea surface temperature (SST) and higher nutrients were noticed in 2018 than in 2017. The region to the north of the jet was characterized by substantially shallower Mixed Layers Depths (MLDs) and higher POM contents relative to the jet’s axis and southern stations. The molar ratio between particulate organic carbon (POC) and nitrogen (PN) (6.2±1.9in 2017; 6.4±0.9 in 2018) was very close to the canonical Redfield ratio (6.63). The δ13CPOC values (-26.3±1.4 ‰ in 2017; 25.5±1.4 ‰ in 2018) exhibited typical marine signature reported from this area and revealed a noticeable inter-annual difference. Relatively higher δ15NPN values noticed in the north (7.68±2.6 ‰ in 2017; 9.24±3 ‰ in 2018) indicated regenerated dissolved inorganic nitrogen coming from the oxygen minimum zone (OMZ) into the well-lit zone. The lower δ15NPN values along the jet axis and south of it were attributed to lateral advection of nitrogen from the Somali upwelling. Despite the higher nutrient availability, POC contents in 2018 did not exceed the values in 2017. Considering the total consumption of nitrogen (according to C:N: P=106:16:1), the potential POC development in 2018 could be double the value in 2017. The interannual differences in SW monsoon onset and wind speed seem to directly control the nutrient supply, affecting plankton community structure and POM variability. Thus, any future change in the physical forcing may directly influence the POC pool and consequent export flux to the mesopelagic.
The Indian monsoon is a complex phenomenon that greatly impacts agriculture and the economy of the region. Understanding the dynamics of the monsoon onset and its accurate predictions with a longer lead time is essential for effective planning and management decisions. Double monsoon onset is characterized by an early monsoon-like condition leading to a “bogus” (or false) onset followed by a delayed real onset. The present study provides an in-depth analysis of the 2023 monsoon onset, which was delayed 7 days than the normal monsoon onset, with a particular focus on understanding the predictive signature of such double monsoon onset. The study focuses on the total precipitable water vapour (TPW) to discern the monsoon onset over Kerala (MOK). Further investigation into the nature of the 2023 monsoon onset reveals the formation of Madden–Julian Oscillations (MJO) and twin perturbations, influencing convective activity and sea surface temperatures (SSTs). Notably, a distinct bi-peak evolution of surface winds is observed during the 2023 monsoon onset, suggesting a double monsoon onset pattern. Detailed analysis of 54 years of historical data spanning from 1950 to 2003 also suggests significant changes in wind speed over the Western Arabian Sea (WAS) for the cases of double monsoon onset. Accordingly, an index, namely the Double Monsoon Identification Index (DMII), is proposed to identify the potential cases of double monsoon onset. The DMII successfully predicted historical double monsoon onset cases (between 1950–2003) with an accuracy (ACC) of 0.96, a probability of detection (POD) of 0.9, and a false alarm rate (FAR) of 0.1 and identified two new cases between 2004–2023. The study highlights the predictive potential of surface winds in anticipating the double monsoon onset with considerable lead time from the climatological onset date, aiding proactive measures and planning in response to monsoon variability.
Graphical abstract
The Arabian Sea, a land-locked low latitude high productive oceanic province, is characterized by strong seasonality due to the reversal of monsoon winds. “Open ocean upwelling” occurs during the southwest monsoon (SWM) in the northern part of the Findlater Jet, (a low-level atmospheric jet that forms in the Arabian Sea), and consequently, the southern part experiences downwelling. Moreover, the hydrography of this region can be further modulated by coupled ocean-atmospheric events such as ENSO and IOD which eventually lead to changes in biological production. After two decades of joint global ocean flux studies (JGOFS), this is the first report on the phytoplankton community from the central Arabian Sea during the SWM. We tried to interlink the north-south gradient in hydrography as well as the physicochemical features with the phytoplankton community structure (within 60 m) along 64E (11-21N) during two consecutive SWM cruises (August 2017 and 2018). The variability in surface wind forcing directly influenced the nutrient stoichiometry and phytoplankton dynamics, through the changes in open ocean upwelling and mixing. Significant spatial and inter-annual variability in phytoplankton abundance, diversity, ratios of diatom: dinoflagellate and centric: pennate diatoms were noticed and were closely coupled with the nutrient availability (bottom-up control). Relatively low phytoplankton cell density in 2017 was coupled with high zooplankton biomass (top-down control). During 2018, higher dissolved silicate (DSi) supply due to stronger open-ocean upwelling along with the advection of upwelled water from the Somali coast likely promoted larger diatoms capable of escaping grazing and have led to higher export production. The large centric diatoms occupied the upwelled regions (21-20N) (e. g. Rhizosolenia imbricata, R. hebetata and Coscinodiscus radiatus) whereas, small pennate diatoms (Pseudo-nitzschia spp., Navicula spp. Nitzschia spp.) and dinoflagellates (Gymnodinium spp.) were pronounced in the south (11-15N). And while comparing the trends with the JGOFS reports, no considerable community shift was noticed. However, in the context of ongoing climate change, the rapid warming of the Arabian Sea may potentially influence the hydrography and biogeochemistry of this region and thus may impact phytoplankton community structure, trophic transfer, and organic carbon export flux.
An optimal interpolation (OI)-based technique is utilized to generate global daily gridded wind products from Scatsat-1 data. The first guess (i.e., background) for the OI is used from the analyses of National Centre for Medium Range Weather Forecasting (NCMRWF) global operational model. The generated gridded products are subsequently validated using observations from global moored buoys and surface winds analyses from European Centre for Medium-Range Weather Forecasts (ECMWF), and that shows a root mean square error of ~1.3 m/s in wind speed and ~19° in wind direction. Along with the gridded winds, several wind-dependent products (e.g., wind stress, wind divergence, wind stress curl, sensible and latent heat flux, etc.) are also generated. The gridded products from Scatsat-1 are available freely from Meteorological and Oceanographic Satellite Data Archival Center (
http://www.mosdac.gov.in
) since October 03, 2016.
Somali upwelling system during northern summer is believed to be the largest upwelling region in the Indian Ocean and has motivated some of the early studies on the Indian Ocean. Here we present results from observations and ocean model to show that the upwelling along the Somali coast is limited to the early phase of the summer monsoon and later primarily limited to the eddy dominated flows in the northern and some extent in the southern part of the coast. Major part of the Somali coast (~60% of the entire coastal length) shows prominent downwelling features driven by offshore negative windstress curl and subsurface entrainment mixing. Further, we show that the surface cooling of coastal waters are dominantly driven by subsurface entrainment and surface heat fluxes. These findings not only augment the existing knowledge of the Somali upwelling system, but also have serious implications on the regional climate. Most importantly, our analysis underscores the use of alongshore winds only to project future (climate driven) changes in the upwelling intensity along this coast.
The performance of revised climate forecast system version 2 (CFSv2) are evaluated on the simulation of the underlying cloud and convective processes associated with the strong and weak boreal summer intraseasonal oscillations (BSISOs) events. The revised version of the CFSv2 consists of a six-class Weather Research Forecasting single moment (WSM6) cloud microphysics scheme and the default version has Zhao and Carr (ZC) cloud microphysics scheme. Both the version uses revised simplified Arakawa-Schubert (RSAS) convection scheme. The study reveals that the revised version of CFSv2 (RSAS-WSM) is able to better simulate the northward propagation of BSISOs and associated dynamical and thermodynamical mechanism put forward by earlier observation-based studies. It is found that the large-scale organized northwest-southeast tilted structure of rain band is better captured in RSAS-WSM simulation as compared to the default version of CFSv2 (RSAS-ZC) during strong BSISO events. Further, the reasonable large-scale or stratiform rainfall associated with the northward propagating strong BSISO events is seen in RSAS-WSM while it is completely missing in RSAS-ZC simulation. The pressure-latitude profiles of cloud liquid water (CLW) and cloud ice (CLI) show more realistic steady northward propagation in RSAS-WSM simulation. Consistent with the CLW and CLI distribution and their influence on the large-scale heating structure, the large-scale condensation heating shows quasi-periodic northward propagation in RSAS-WSM whereas such type of distribution is not captured in RSAS-ZC simulation. The realistic representation of cloud processes in WSM leads to simulate reasonable dynamical and thermodynamical processes associated with the strong BSISO events which follows the observation-based hypothesis proposed by earlier studies.
Large socioeconomic impact of the Indian summer monsoon (ISM) extremes motivated numerous attempts at its long range prediction over the past century. However, a rather low potential predictability (PP) of the seasonal ISM, contributed significantly by “internal,” interannual variability was considered insurmountable. Here we show that the internal variability contributed by the ISM subseasonal (synoptic + intraseasonal) fluctuations, so far considered chaotic, is partly predictable as found to be tied to slowly varying forcing (e.g., El Niño and Southern Oscillation). This provides a scientific basis for predictability of the ISM rainfall beyond the conventional estimates of PP. We establish a much higher actual limit of PP (r∼0.82) through an extensive reforecast experiment (1,920 years of simulation) by improving two major physics in a global coupled climate model, which raises a hope for a very reliable dynamical seasonal ISM forecasting in the near future.
An attempt has been made in this study to evaluate the performance of a multi-model ensemble prediction system (MMEPS) in the extended range prediction of genesis and track of cyclonic storms (CS) over North Indian Ocean (NIO) during the onset phase of Indian summer monsoon. The MMEPS comprises of National Centres for Environmental Prediction Climate Forecast System version 2 and its atmospheric component, Global Forecast System version 2, at two different resolutions. In this study, we analyse the performance of this MMEPS in the prediction of six CS cases formed around the onset phase of the Indian summer monsoon over NIO. Along with this, we evaluate the usefulness of the genesis potential parameter used by India Meteorological Department (IMD) for the real-time cyclogenesis prediction. ERA-Interim re-analysis data sets are used to compare MME predictions from two initial conditions (IC) close to the genesis date of each storm. Results show that genesis forecasts from nearest available IC is capturing the vorticity and associated features of the storm better than far-IC. A modified version of vortex tracking scheme developed by Geophysical Fluid Dynamics Laboratory is used to obtain the mean track positions from MME outputs and compare with IMD-best tracks. Track verification is done by calculating average direct position error, cross-track error and along-track error against corresponding IMD-best tracks. It is found that track predictions from both near and far ICs have lower average errors initially with near-IC having lesser errors as compared to far-IC. Along-track error for pre-genesis track prediction from far-IC implies that the predicted tracks remarkably lag behind observed tracks for most of the cases. These errors could be contributed from the inability of the models in realistically capturing the region of evolution and intensification of both thermodynamic and dynamic parameters with increasing lead time.
Global climate models including the Climate Forecast System version 2 (CFSv2), the operational model used for prediction of Indian Summer Monsoon Rainfall (ISMR) by the India Meteorological Department, has dry precipitation bias, mostly over densely populated Ganga basin. This restricts the use of model output in hydrological simulations/ forecasts. We use regional atmospheric Weather Research and Forecasting (WRF) model coupled with land surface models, driven by the boundary conditions from CFSv2. We find significant reduction in the dry bias of ISMR with regional land-atmosphere model and this attributes to (a) improved moisture transport from Western and Upper Indian Ocean to Ganga Basin and (b) improved precipitation recycling over the Ganga basin. We find that the smoothened topography in the global model allows advection of cold dry sub-tropical air into the Indian monsoon region, contributing to the cold temperature and dry precipitation bias. These results have important implications for monsoon simulations in developing operational hydro-climatic prediction system in India.
Indian summer monsoon of 2015 was deficient with prominence of short-lived (long-lived) active (break) spells. The real-time extended range forecasts disseminated by Indian Institute of Tropical Meteorology using an indigenous ensemble prediction system (EPS) based on National Center for Environmental Predictions’s climate forecast system could broadly predict these intraseasonal fluctuations at shorter time leads (i.e. up to 10 days), but failed to predict at longer leads (15–20 days). Considering the multi-scale nature of Indian Summer Monsoon system, this particular study aims to examine the inability of the EPS in predicting the active/break episodes at longer leads from the perspective of non-linear scale interaction between the synoptic, intraseasonal and seasonal scale. It is found that the 2015 monsoon season was dominated by synoptic scale disturbances that can hinder the prediction on extended range. Further, the interaction between synoptic scale disturbances and low frequency mode was prominent during the season, which might have contributed to the reduced prediction skill at longer leads.
This paper analyzes the role of ocean–atmosphere processes associated with break days and their impact on dry-land biases of Indian summer monsoon in Climate Forecast System version 2 (CFSv2)’s sub daily and monthly hindcasts, which are produced by initializing the forecast system every 5 days in each month from January 1982 to December 2007. Each initialized forecast produces 24 ensemble members and they are characterized by a systematic dry-land bias over central India and have been interlinked with higher break days in majority of the ensemble members. Analyses on 15–45 day band-passed summer precipitation anomalies indicate that the monsoon intraseasonal oscillations are very weak in Mar- and Apr-initialized forecasts while they get stronger in May- and Jun-initialized forecasts. The persistent low-level anticyclonic activity in the Findlater jet in the longer lead months (Mar- and Apr-initialized forecasts) is systematically diminished in the summer forecasts that are produced by initializing the forecast system closer to the June–September (JJAS) season (e.g., May- and Jun-initialized forecasts). This low-level negative vorticity bias extends across central India and diminishes with the systematic oceanic mixed layer shoaling in the northern Bay of Bengal (BoB) and Indian Ocean (IO). The deeper ocean mixed layer in BoB and northern IO in conjunction with persistent negative vorticity biases suppresses intraseasonal variability of Indian summer monsoon rainfall and induces a large number of break days, which lead to the dry-land biases in July and August in the core monsoon zone. CFSv2-produced Pacific sea surface temperatures exert a strong influence on mixed layer depths (MLDs) across the basins in Arabian Sea (AS), BOB and IO unlike in observations. The forecasted extended break spells are systematically and highly correlated with the model produced Niño3 index while no such strong correlation is found between total monsoonal break days and ENSO in the observations. The May- and Jun-initialized CFSv2 forecasts reproduce the Indian summer monsoon rainfall in July–August reliably by reasonably alleviating the ocean–atmosphere coupled biases relative to earlier initializations.
Monsoon onset is an inherent transient phenomenon of Indian Summer Monsoon and it was never envisaged that this transience can be predicted at long lead times. Though onset is precipitous, its variability exhibits strong teleconnections with large scale forcing such as ENSO and IOD and hence may be predictable. Despite of the tremendous skill achieved by the state-of-the-art models in predicting such large scale processes, the prediction of monsoon onset variability by the models is still limited to just 2–3 weeks in advance. Using an objective definition of onset in a global coupled ocean-atmosphere model, it is shown that the skillful prediction of onset variability is feasible under seasonal prediction framework. The better representations/simulations of not only the large scale processes but also the synoptic and intraseasonal features during the evolution of monsoon onset are the comprehensions behind skillful simulation of monsoon onset variability. The changes observed in convection, tropospheric circulation and moisture availability prior to and after the onset are evidenced in model simulations, which resulted in high hit rate of early/delay in monsoon onset in the high resolution model.
The National Centre for Environmental Prediction (NCEP) Climate Forecast System (CFS) is being used for operational monsoon prediction over the Indian region. Recent studies indicate that the moist convective process in CFS is one of the major sources of uncertainty in monsoon predictions. In this study, the existing simple cloud microphysics of CFS is replaced by the six-class Weather Research Forecasting (WRF) single moment (WSM6) microphysical scheme. Additionally, a revised convective parameterization is employed to improve the performance of the model in simulating the boreal summer mean climate and intraseasonal variability over the Indian summer monsoon (ISM) region. The revised version of the model (CFSCR) exhibits a potential to improve shortcomings in the seasonal mean precipitation distribution relative to the standard CFS (CTRL), especially over the ISM region. Consistently, notable improvements are also evident in other observed ISM characteristics. These improvements are found to be associated with a better simulation of spatial and vertical distributions of cloud hydrometeors in CFSCR. A reasonable representation of the sub-grid scale convective parameterization along with cloud hydrometeors helps to improve the convective and large-scale precipitation distribution in the model. As a consequence, the simulated low frequency boreal summer intraseasonal oscillation (BSISO) exhibits realistic propagation and the observed northwest-southeast rainband is well reproduced in CFSCR. Additionally, both the high and low frequency BSISOs are better captured in CFSCR. The improvement of low and high frequency BSISOs in CFSCR is shown to be related to a realistic phase relationship of clouds. This article is protected by copyright. All rights reserved.
This paper analyzes the role of the Indian Ocean (IO) and the atmosphere biases in generating and sustaining large-scale precipitation biases over Central India (CI) during the Indian summer monsoon (ISM) in the climate forecast system version 2 (CFSv2) hindcasts that are produced by initializing the system each month from January 1982 to March 2011. The CFSv2 hindcasts are characterized by a systematic dry monsoon bias over CI that deteriorate with forecast lead-times and coexist with a wet bias in the tropical IO suggesting a large-scale interplay between coupled ocean–atmosphere and land biases. The biases evolving from spring-initialized forecasts are analyzed in detail to understand the evolution of summer biases. The northward migration of the Inter Tropical Convergence Zone (ITCZ) that typically crosses the equator in the IO sector during April in nature is delayed in the hindcasts when the forecast system is initialized in early spring. Our analyses show that the delay in the ITCZ coexists with wind and SST biases and the associated processes project onto the seasonal evolution of the coupled ocean–atmosphere features. This delay in conjunction with the SST and the wind biases during late spring and early summer contributes to excessive precipitation over the ocean and leading to a deficit in rainfall over CI throughout the summer. Attribution of bias to a specific component in a coupled forecast system is particularly challenging as seemingly independent biases from one component affect the other components or are affected by their feedbacks. In the spring-initialized forecasts, the buildup of deeper thermocline in association with warmer SSTs due to the enhanced Ekman pumping in the southwest IO inhibits the otherwise typical northward propagation of ITCZ in the month of April. Beyond this deficiency in the forecasts, two key ocean–atmosphere coupled mechanisms are identified; one in the Arabian Sea, where a positive windstress curl bias in conjunction with warmer SSTs lead to a weakening of Findlater jet and the other in the east equatorial IO where a remote forcing by the predominantly westerly bias in the western-central equatorial IO in the summer strengthen the seasonal downwelling Kelvin wave that in turn deepens the thermocline in the eastern IO. The equatorial Kelvin wave continues as a coastal Kelvin wave and disperses as Rossby waves off Sumatra and induces positive SST and precipitation biases in the eastern and southern Bay of Bengal. This study shows that the biases that first appear in winds lead to a cascade of coupled processes that exacerbate the subsequent biases by modulating the evolution of seasonal processes such as the annual Kelvin and Rossby waves and the cross-equatorial vertically integrated moisture transport. While this analysis does not offer any particular insights into improving the ISM forecasts, it is a foundational first step towards this goal.
It has been established through a numerical model that the onset vortex (OV) was formed dramatically in the shear line on the northern flank of a low level jet (LLJ) at 850 hPa over the mini warm pool (MWP) in the East Central Arabian Sea with the aid of sea surface temperature (SST) anomalies using MONEX-79 data. This study has led to serious investigation of MWP over the ECAS, but little attention has been given to its counterpart, i.e. the atmospheric pattern at 850 hPa, the level at which OV generally forms and extends on either side during the course of development. The present study examines the SST distribution over the Arabian Sea and circulation at 850 hPa to identify the MWP and the LLJ positions for five consecutive days with onset day as its centre and for six consecutive years 2000-05. The study has revealed that OV had formed only in 2001 under the influence of MWP on the northern flank of LLJ. During other years it seldom formed due to (i) absence of MWP, (ii) lack of sufficient strength of LLJ, and (iii) absence of the location of shear line (over the northern flank of LLJ) over MWP. The air-sea flux transfer processes for the OV year 2001 and a non-OV year 2002 are studied and compared for better understanding of the above process in relation to the OV and non-OV weather conditions over the study area.
An ensemble prediction system (EPS) is devised for the extended range prediction (ERP) of monsoon
intraseasonal oscillations (MISO) of Indian summer monsoon (ISM) using National Centers for Environmental
Prediction Climate Forecast System model version 2 at T126 horizontal resolution. The EPS is formulated by
generating 11 member ensembles through the perturbation of atmospheric initial conditions. The hindcast experiments were conducted at every 5-day interval for 45 days lead time starting from 16th May to 28th September during 2001–2012. The general simulation of ISM characteristics and the ERP skill of the proposed EPS at pentad mean scale are evaluated in the present study. Though the EPS underestimates both the mean and variability of ISM rainfall, it simulates the northward propagation of MISO
reasonably well. It is found that the signal-to-noise ratio of the forecasted rainfall becomes unity by about 18 days. The potential predictability error of the forecasted rainfall saturates by about 25 days. Though useful deterministic forecasts could be generated up to 2nd pentad lead significant correlations are found even up to 4th pentad lead. The skill in predicting large-scale MISO, which is assessed by comparing the predicted and observed MISO indices, is found to be *17 days. It is noted that the prediction skill of actual rainfall is closely related to the prediction of large-scale MISO amplitude as well as the initial conditions related to the different phases of MISO. An analysis of categorical prediction skills reveals that break is more skillfully predicted, followed by active and then normal. The categorical probability skill scores suggest that useful probabilistic forecasts could be generated even up to 4th pentad lead.
The NCEP Climate Forecast System version 2 (CFSv2) provides important
source of information about the seasonal prediction of climate over the
Indo-Pacific oceans. In this study, the authors provide a comprehensive
assessment of the prediction of sea surface temperature (SST) in the
tropical Indian Ocean (IO). They also investigate the impact of tropical
IO SST on the summer anomalous anticyclonic circulation over the western
North Pacific (WNPAC), focusing on the relative contributions of local
SST and remote forcing of tropical IO SST to WNPAC variations. The CFSv2
captures the two most dominant modes of summer tropical IO SST: the IO
basin warming (IOBW) mode and the IO dipole (IOD) mode, as well as their
relationship with El Niño-Southern Oscillation (ENSO). However,
it produces a cold SST bias in IO, which may be attributed to
deeper-than-observed mixed layer and smaller-than-observed total
downward heat flux in the tropical IO. It also overestimates the
correlations of ENSO with IOBW and IOD, but underestimates the magnitude
of IOD and summer IOBW. The CFSv2 captures the climate anomalies related
to IOBW but not those related to IOD. It depicts the impact of summer
IOBW on WNPAC via the equatorial Kelvin wave, which contributes to the
maintenance of WNPAC in July and August. The WNPAC in June is mostly
forced by local cold SST, which is better predicted by the CFSv2
compared to July and August. The mechanism for WNPAC maintenance may
vary with lead time in the CFSv2.
Impact of bias correction of sea surface temperature (SST) forecast on extended range (ER, ∼3–4 weeks) prediction skill is studied using the bias-corrected forecasted SST from Climate Forecast System version 2 (CFSv2) as the boundary condition for running the Global Forecast System version 2 (GFSv2) model. Potential predictability limit is comparable (∼16 days) for both bias-corrected GFSv2 (GFSv2bc) and CFSv2. Prediction skills of active and break spells and of low-frequency monsoon intraseasonal oscillations is higher for GFSv2bc at all lead pentads. Although initially same, predictability error after 14 days grows slightly faster for GFSv2bc compared to CFSv2. Bias correction in SST has minimal impact in short-to-medium range, while substantial influence is felt in ER between 12–18 days.
The response of sea surface temperature (SST) to tropical cyclones is studied using gridded SST data and global cyclone tracks from the period 1981–2008. A compositing approach is used whereby temperature time series before and after cyclone occurrence at individual cyclone track positions are averaged together.
Results reveal a variability of several days in the time of maximum cooling with respect to cyclone passage, with the most common occurrence 1 day after cyclone passage. When compositing is carried out relative to the day of maximum cooling, the global average response to cyclone passage is a local minimum SST anomaly of −0.9°C. The recovery of the ocean to cyclone passage is generally quite rapid with 44% of the data points recovering to climatological SST within 5 days, and 88% of the data points recovering within 30 days. Although differences exist between the mean results from the separate tropical cyclone basins, they are in broad agreement with the global mean results. Storm intensity and translation speed affect both the size of the SST response and the recovery time.
Cyclones occurring in the first half of the cyclone season disrupt the seasonal warming trend, which is not resumed until 20–30 days after cyclone passage. Conversely, cyclone occurrences in the later half of the season bring about a 0.5°C temperature drop from which the ocean does not recover due to the seasonal cooling cycle.
Inter-annual variability in the formation of the mini warm pool [sea-surface temperature (SST)>30°C] over the south eastern Arabian Sea (SEAS) and its role in the formation of the monsoon onset vortex (MOV) has been examined using two independent SST data sets. The role of SST, convection, integrated columnar water vapour and the low-level jet in the setting up of the monsoon onset over Kerala (MOK) is examined. It is found that the MOV which forms over the SEAS region upsets the delicate balance between convection, buildup of moisture and strengthening and deepening of the westerlies over the SEAS that is needed for the setting up of the MOK. Thus, the formation over the SEAS of an MOV is not necessarily conducive for MOK. Furthermore, it is shown that a mini warm pool over the southeastern Arabian Sea is not a sufficient condition for the formation of an MOV because such a warm pool is present over this region during most of the years, but an MOV does not necessarily form over there.
Atmospheric dynamical mechanisms have been prevalently used to explain the characteristics of the summer monsoon intraseasonal oscillation (MISO), which dictates the wet and dry spells of the monsoon rainfall. Recent studies show that ocean–atmosphere coupling has a vital role in simulating the observed amplitude and relationship between precipitation and sea surface temperature (SST) at the intraseasonal scale. However it is not clear whether this role is simply ‘passive’ response to the atmospheric forcing alone, or ‘active’ in modulating the northward propagation of MISO, and also whether the extent to which it modulates is considerably noteworthy. Using coupled NCEP–Climate Forecast System (CFSv2) model and its atmospheric component the Global Forecast System (GFS), we investigate the relative role of the atmospheric dynamics and the ocean–atmosphere coupling in the initiation, maintenance, and northward propagation of MISO. Three numerical simulations are performed including (1) CFSv2 coupled with high frequency interactive SST, the GFS forced with both (2) observed monthly SST (interpolated to daily) and (3) daily SST obtained from the CFSv2 simulations. Both CFSv2 and GFS simulate MISO of slightly higher period (~60 days) than observations (~45 days) and have reasonable seasonal rainfall over India. While MISO simulated by CFSv2 has realistic northward propagation, both the GFS model experiments show standing mode of MISO over India with no northward propagation of convection from the equator. The improvement in northward propagation in CFSv2, therefore, may not be due to improvement of the model physics in the atmospheric component alone. Our analysis indicates that even with the presence of conducive vertical wind shear, the absence of meridional humidity gradient and moistening of the atmosphere column north of convection hinders the northward movement of convection in GFS. This moistening mechanism works only in the presence of an ‘active’ ocean. In CFSv2, the lead-lag relationship between the atmospheric fluxes, SST and convection are maintained, while such lead-lag is unrealistic in the uncoupled simulations. This leads to the conclusion that high frequent and interactive ocean–atmosphere coupling is a necessary and crucial condition for reproducing the realistic northward propagation of MISO in this particular model.
The summer monsoon onset over Kerala (MOK) marks the beginning of the rainy season for the country. Associated with the MOK,
significant transitions of large scale atmospheric and oceanic circulation patterns are observed over the Asia-Pacific region.
In this study, a new method for the objective identification of MOK, based on large scale circulation features and rainfall
over Kerala, is discussed. Further, a set of empirical models based on the principal component regression (PCR) technique
was developed for the prediction of the date of MOK by keeping in mind the IMD’s operational forecasting service requirements.
Predictors for the models were derived using correlation analysis from the thermal, convective and circulation patterns. Only
five predictors pertaining to the second half of April were used in the first model (Model-1) so that the prediction of MOK
can be prepared by the end of April itself. The second model (Model-2) used four additional predictors pertaining up to the
first half of May along with two predictors used in the Model-1 for update prediction at the end of the first half of May.
To develop each of the PCR models, Principal Components Analysis (PCA) of the respective predictor data was carried out followed
by regression analysis of first two principal components (PCs) with the date of MOK. Both these models showed good skill in
predicting the date of MOK during the independent test period of 1997–2007. The root mean square error (RMSE) of the predictions
from both the models during the independent test period was about four days which was nearly half the RMSE of the predictions
based on climatology.
During the pre-onset regime of MONEX-79, the short period (1–2 weeks) time series measurements of surface meteorological elements, vertical profiles of temperature (BT) and salinity (Nansen casts) made from 5 former USSR and 2 Indian research vessels were utilised to investigate the observed near-surface heating rates at a few selected locations in the Arabian Sea. The influence of local surface heat fluxes on the upper ocean heat content variability is explored. The associated synoptic scale variability in the thermohaline structure of the upper layers is presented. The efficacy of a simple Kraus-Turner type one dimensional numerical model in simulating the observed variability of mixed layer heating rates is evaluated.
Progress in the scientific application of space-based scatterometer data over the past two decades is reviewed. There has
been continuous improvement in coverage, resolution, and accuracy. Besides the traditional applications in weather and ocean-atmosphere
interaction, which are based on ocean surface wind vectors, emerging applications over land and ice are also described. Future
missions and new technology are introduced.
The interannual variability in the formation of mini warm pool (MWP, SST≥30.5°C) and its impact on the formation of onset
vortex (OV) over the east-central Arabian Sea (ECAS) are addressed by analyzing the NCEP OIV 2-weekly SST data and NCEP–NCAR
reanalysis 850hPa wind fields from May to June (prior to the onset of monsoon) over the north Indian Ocean for a period of
12years from 1992 to 2003. Strong interannual variability in the formation and intensification of MWP was observed. Further,
the 850hPa wind fields showed that OV developed into an intense system only during 1994, 1998 and 2001. It formed in the
region north of the MWP and on the northern flank of the low-level jet axis, which approached the southern tip of India just
prior to the onset of monsoon, similar to the vortex of MONEX-79. The area-averaged zonal kinetic energy (ZKE) over the ECAS
(8–15°N, 65–75°E) as well as over the western Arabian Sea (WAS, 5°S–20°N, 50–70°E) showed a minimum value of 5–15m2s−2 prior to monsoon onset over Kerala (MOK), whereas a maximum value of 280m2s−2 (40–70m2s−2) was observed over the ECAS (WAS) during and after MOK. The study further examined the plausible reasons for the occurrence
of MWP and OV.
On average 1-2 tropical cyclones form over the Arabian Sea each year, and few of these storms are intense enough to be classified as very severe or super cyclonic storms. As such, few studies have explicitly identified the seasonal to interannual changes in environmental conditions that are associated with Arabian Sea tropical cyclogenesis. However, over the last 30 yr several intense Arabian storms did form and make landfall, with large impacts, which motivates this new study of the basin. The conclusions of earlier studies are visited by utilizing modern observational and reanalysis data to identify the large-scale features associated with Arabian tropical cyclone variability on seasonal time scales. Then year-to-year changes in environmental conditions that are related to interannual variability in Arabian storms during the pre- and postmonsoon periods are elucidated. The analysis of the relationship between large-scale environmental variables and seasonal storm frequency supports conclusions from work completed more than 40 yr prior. Investigation of the year-to-year changes in premonsoon storm frequency suggests that May (June) storms are associated with an early (late) onset of the southwest monsoon. The findings also demonstrate that November cyclones (the month when the majority of postmonsoon cyclogenesis occurs) primarily form during periods when the Bay of Bengal experiences a broad region of high sea level pressure, implying that November storms form in either the Arabian Sea or the Bay of Bengal but not in both during the same year. Finally, the analysis of changes in a genesis potential index suggests that long-term variability in the potential for a storm to form is dictated by changes in midlevel moisture.
In this paper we examine the epochal changes in the frequency of cyclones over the North Indian Ocean during the pre-onset and onset phases of the monsoon. We consider three epochs; namely, the early (1955–74), middle (1975–94) and recent (1995–2014) epochs. It is found that the number of cyclones in the Bay of Bengal (BOB) decreases throughout the three epochs. Over the Arabian Sea (ARB), however, there is a decrease in the early epoch, before then reaching a minimum in the middle epoch followed by an increase in the recent epoch, thus exhibiting epochal variability. Dynamic and thermodynamic parameters along with Genesis Potential Index (GPI) are examined to understand the frequency variation in cyclogenesis over the ARB and BOB. Over the ARB, thermodynamic factors such as mid-level moisture, surface latent heat flux and sensible heat flux, and dynamic parameters such as lower-level convergence and upper-level divergence, are favorable during the early and recent epochs but unfavorable during the middle epoch, and these results are found to be consistent with the observed epochal variability in the frequency of cyclogenesis. However, all these influential parameters are found to have decreased over the BOB during the entire 60-year period.
SCATSAT-1 carries a Ku-band scatterometer with a
scanning pencil beam configuration. It deploys two
beams, a vertically polarized outer beam and a horizontally polarized inner beam, to cover a swath of
1800 km. The mission mainly caters to oceanographic
applications and weather forecasting, with the data
being extensively used for cyclogenesis predictions
across the globe and specifically, the tropical region.
Since the launch of SCATSAT-1 in September 2016,
the satellite and payload performances as well as mission and ground segment operations have been found
to be nominal and satisfactory. This article highlights
various levels of operational data products as well as
algorithms used for deriving radar backscatter and
retrieving wind vector data from scatterometer measurements.
Two sets of CFSv2 retrospective forecast experiments are performed to check the
model’s fidelity for operational forecast usage for the prediction of Indian summer
monsoon rainfall (ISMR). The first experiment (Exp1) is identical to the present
operational mode of the model. The second experiment (Exp2) includes major
changes in terms of the different cumulus parameterization scheme, modified
cloud microphysics scheme and the variable critical relative humidity. These
changes have already shown enhancement in the seasonal viability of the model in
the free-run mode. This study has carried out exclusive hindcast experiments by
combining the above mentioned major changes. There is a marked improvement
in the spatial distribution of the precipitation and the amplitude of the annual cycle
of ISMR. The underestimation of the peak of the annual cycle of ISMR in Exp1 is
enhanced by 23% in Exp2. Because of better simulations of clouds and tropospheric
temperature gradient, the point of maximum precipitation has migrated
northwards from equator (Exp1) to 20N (Exp2). These improvements also
impress upon all the other aspect of the ocean–atmosphere coupled interaction,
namely planetary-scale Hadley circulation, air–sea interactions and most of the
facets of monsoon teleconnections. The skill of extended Indian monsoon rainfall
region (65–95E, 5–35 N) has increased from 0.50 in Exp1 to 0.67 in Exp2 and
the same holds true for other regions as well. The skill of Niño3.4 index enhances
from 0.58 in Exp1 to 0.67 in Exp2. The dynamical wind shear based monsoon
performance indices also show the surge in the skill score. The significant
improvement of seasonal skill scores across all the variables clearly shows the
dynamical consistency and at the same time establishes the superiority of the
Exp2 for seasonal forecast. This work will add new dimension to develop a new
genre of monsoon forecasting model.
An examination of the variations of surface meteorological fields and derived surface heat fluxes associated with onset of summer monsoon seasons over India based on 50 years data from 1957 to 2006 is carried out over the domain 30°S–30°N and 30°–150°E. Significant changes in the surface meteorological parameters are observed over Arabian Sea off Somali coast, Bay of Bengal and move eastwards to northwards as onset approaches. The changes and shift in the south Indian Ocean are not prominent. Some precursors such as changes in almost all parameters used in this study over northern Australia and its adjoining, and East China Sea during pre- to post-onset phase indicate the approach of onset situation.
Examines the evolution of the low-level flow over the Arabian Sea during the onset of the summer monsoon. A detailed examination of the onset vortex that forms over the Arabian Sea just prior to the commencement of heavy rains over central India is carried out. Of major interest is a finding that the kinetic energy of the zonal flow over the central Arabian Sea increases by an order, of magnitude 1 week prior to the commencement of monsoon rain over central India. -from Authors Department of Meteorology, Florida State University, Tallahassee 32306, USA.
This study describes an attempt to overcome the underdispersive nature of single-model ensembles (SMEs). As an Indo-U.S. collaboration designed to improve the prediction capabilities of models over the Indian monsoon region, the Climate Forecast System (CFS) model framework, developed at the National Centers for Environmental Prediction (NCEP-CFSv2), is selected. This article describes a multimodel ensemble prediction system, using a suite of different variants of the CFSv2 model to increase the spread without relying on very different codes or potentially inferior models. The SMEs are generated not only by perturbing the initial condition, but also by using different resolutions, parameters, and coupling configurations of the same model (CFS and its atmosphere component, the Global Forecast System). Each of these configurations was created to address the role of different physical mechanisms known to influence error growth on the 10-20-day time scale. Last, the multimodel consensus forecast is developed, which includes ensemble-based uncertainty estimates. Statistical skill of this CFS-based Grand Ensemble Prediction System (CGEPS) is better than the best participating SME configuration, because increased ensemble spread reduces overconfidence errors.
Role of the cloud parameterization scheme and critical relative humidity (RHcrit) for large-scale precipitation is examined for simulating Indian summer monsoon (ISM) by theNational Centers for Environmental Prediction (NCEP) climate forecast system version 2 (CFSv2). The major biases of the model simulations namely dry bias over the major continents, cold tropospheric temperature (TT) bias and cold sea surface temperature (SST) bias are related to biases in distribution of clouds. This study evaluates the role of variable RHcrit to get better simulation of high level clouds and reduce TT bias and cloud microphysical parameterization to improve the meridional gradient of TT towards achieving better simulation of south Asian
monsoon precipitation. Sensitivity experiments of CFSv2 with themodified RHcrit and cloud microphysical scheme compared to the control simulation show that while the RHcrit leads to some development of the cloud distribution and contributes to some progress of the dry bias over India, the cloud microphysics changes lead to a significant improvement of the cloud simulations. Particularly, revised cloud microphysics scheme coupled with modified RHcrit results in a much improved global distribution of cloud fraction with zonal mean cloud fraction being close to observation. This leads to significant improvement in the meridional gradient of TT leading to rainfall over south Asian monsoon region. The dry bias is not only reduced over the
Indian subcontinent but also over other regions of global tropics such as the central Africa and the northern South America. The annual cycle of all India rainfall is in good agreement with observation not only in amount but also in the onset and withdrawal phases. Thus, modifications in the cloud microphysical parameterization scheme in CFSv2 have played a vital role in simulation of the ISM in particular. The sensitivity experiments demonstrate the betterment of the mean monsoon and may lead to help improve monsoon forecasts.
Cloud fraction, which varies greatly among general
circulation models, plays a crucial role in simulation of Indian
summer monsoon rainfall (ISMR). The NCEP Climate
Forecast System version 2 (CFSv2) model is evaluated in
terms of its simulation of cloud fraction, cloud condensate,
outgoing longwave radiation (OLR), and tropospheric temperature
(TT). Biases in these simulated quantities are computed
using observations from CALIPSO and reanalysis data from
MERRA. It is shown that CFSv2 underestimates
(overestimates) high- (mid-) level clouds. The cloud condensate
is also examined to see its impact on different types of
clouds. The upper-level cloud condensate is underestimated,
particularly during the summer monsoon period, which leads
to a cold TT and a dry precipitation bias. The unrealistically
weak TT gradient between ocean and land is responsible for
the underestimation of ISMR. The model-simulated OLR is
overestimated which depicts the weaker convective activity. A
large underestimate of precipitable water is also seen along the
cross-equatorial flow and particularly over the Indian land
region collocated with a dry precipitation bias. The linkages
among cloud microphysical, thermodynamical, and dynamical
processes are identified here. Thus, this study highlights
the importance of cloud properties, a major cause of uncertainty
in CFSv2, and also proposes a pathway for improvements
in its simulation of the Indian summer monsoon.
Several aspects of real‐time forecast of Indian summer monsoon ( ISM ) in 3–4 pentad lead time (extended range) are discussed in this study to explore the operational capability of the Climate Forecast System model version 2 ( CFSv2 ) developed by National Centre for Environmental Prediction ( NCEP ). 2013 summer monsoon was a near excess monsoon year in terms of seasonal mean and was a result of rich diversity of phenomena including strong intraseasonal variations and intense northward propagations over the Indian region. Eleven‐member forecasts were made at every 5‐day interval during the June–September monsoon season which included monsoon onset and withdrawal phases. The ensemble members were created by perturbing the initial conditions at each start time. In addition to the CFSv2 forecasts, we also carried out forecasts using the atmospheric‐only component ( GFSv2 ) forced with CFSv2 ‐derived sea surface temperature (SST) subjected to a bias correction based on historical observations ( GFSbc runs).
Both the CFSv2 and GFSbc runs were able to predict the progression of ISM over the Indian region and the subsequent intraseasonal oscillations (active and break phases). The analysis for an extreme event (Uttarakhand flood) and monsoon revival (MR) towards the end of the season was also performed. Comparison between the two runs shows that active and break spells were predicted with good fidelity over the Indian region, though GFSbc outperforms CFSv2 on several occasions. Thus, improvement of the operational monsoon forecast over Indian region using NCEP CFSv2 requires better representation of air–sea interaction and mean states of ocean.
The onset is found to consist of two main phases: a moisture buildup over the Arabian Sea during which synoptic- and mesoscale transient disturbances develop; the relationship of this buildup with planetary wave activity is discussed. This is followed by a rapid intensification of the Arabian Sea winds and a substantial increase in latent heat release, essentially a large-scale feedback process. Similar analyses are carried out for 1980, 1981 and 1982, using ECMWF operational analyzed fields although moisture fields are analyzed only for 1981. Although these show characteristics generally similar to those of 1979, there are some differences. Comparisons are made of the four years, and related to the commencement of rains over India.-from Authors
The onset process of the tropical eastern Indian Ocean (TEIO) summer monsoon (TEIOSM) and its relationship with the cross-equatorial
flows are investigated via climatological analysis. Climatologically, results indicate that the earliest onset process of
the Asian summer monsoon occurs over the TEIO at pentad 22 (April 15–20). Unlike the abrupt onset of the South China Sea (SCS)
summer monsoon, the TEIOSM onset process displays a stepwise advance. Moreover, a close relationship between the TEIOSM development
and the northward push of the cross-equatorial flows over 80–90E is revealed. A difference vorticity center, together with
the counterpart over the southern Indian Ocean, constitutes a pair of difference cyclonic vortices, which strengthens the
southwesterly wind over the TEIO and the northerly wind to the west of the Indian Peninsula from the end of March to late
May. Therefore, the occurrence of the southwesterly wind over the TEIO is earlier than its counterpart over the tropical western
Indian Ocean, and the cross-equatorial flows emerge firstly over the TEIO rather than over the Somali area. The former increases
in intensity during its northward propagation, which provides a precondition for the TEIOSM onset and its northward advance.
Sea surface temperatures (SSTs) in the equatorial Indian Ocean have warmed by about 0.6-0.8 K since the 1950s, accompanied by very little warming or even a slight cooling trend over the northern Indian Ocean (NIO). It is reported that this differential trend has resulted in a substantial weakening of the meridional SST gradient from the equatorial region to the South Asian coast during summer, to the extent that the gradient has nearly vanished recently. Based on simulations with the Community Climate Model Version 3 (CCM3), it is shown that the summertime weakening in the SST gradient weakens the monsoon circu- lation, resulting in less monsoon rainfall over India and excess rainfall in sub-Saharan Africa. The observed trend in SST is decomposed into a hypothetical uniform warming and a reduction in the meridional gradient. The uniform warming of the tropical Indian Ocean in the authors' simulations increases the Indian summer monsoon rainfall by 1-2 mm day1, which is opposed by a larger drying tendency due to the weakening of the SST gradient. The net effect is to decrease the Indian monsoon rainfall, while preventing the sub-Saharan region from becoming too dry. Published coupled ocean-atmosphere model simulations are used to describe the competing effects of the anthropogenic radiative forcing due to greenhouse gases and the anthropogenic South Asian aerosols on the observed SST gradient and the monsoon rainfall.
This study examines the phase dependant temporal and spatial error evolution and prediction of active break spells of Indian summer monsoon rainfall in an ensemble prediction system (EPS) on a pentad time scale using climate forecast system (CFS). The EPS system shows systematic wet bias (overestimation)
over west coast over the Arabian Sea and Myanmar coast and dry bias (underestimation) over Indian land mass even at pentad 1 lead and these biases consistently increase up to 4 pentad lead and saturate thereafter. Irrespective of the phases of the monsoon, the lower bound of predictability is 2 pentads, while upper bound of predictability for initial conditions starting from active phase saturates at 3 pentads and for break and transition phases predictability error saturates at a later stage at about 5 pentad. Initial conditions started from transition phase shows higher potential predictability followed by break phase and then active phase.
Eight pentads before the monsoon onset over Kerala (MOK), a spatially large area of deep convection formed near the equator south of the Bay of Bengal, which moved to Southeast Asia marking the onset of the South China Sea monsoon (SCSM) for many years. Three pentads before MOK, a similar area of convection formed near the equator south of the Arabian Sea. This heat source and the associated cross-equatorial low-level jet stream (LLJ) grew steadily in strength while moving north and at MOK the convective heat source passed through Kerala latitudes and the core of a well developed LLJ was located just south of Kerala.
Eight pentads before MOK a warm pool was located over central Bay of Bengal and the area of active convection formed to its south near the equator in the region of large sea surface temperature (SST) gradient. Three pentads before MOK when the Bay of Bengal SST had cooled, a warm pool formed over central Arabian Sea and an active convection area was located south of it, also in the region of large SST gradient.
A three-step method for objectively defining MOK has been developed in this paper. In step 1 of this operationally usable method, the date on which the zonal wind of 850 hPa, averaged over a box bounded by latitudes 5°N and 10°N and longitudes 70°E and 85°E, reached 6 m/s at 600 hPa is taken as the tentative date of MOK. Steps 2 and 3 checked whether the date thus chosen was a bogus monsoon onset or not and whether on that date there was widespread convection (low OLR) around Kerala, which moved north from the equatorial region. Copyright
The air-sea interface properties during the early stages of formation of a depression over East Central Arabian Sea during summer MONEX are examined by analyzing the ship data for air and sea temperatures, sea level pressures, sea state numbers and wind fields. Analysis of the data revealed a pronounced increase in sea-air temperature difference (2–4 C) and this increase in the value is considered, obviously, to be due to a drop in the air temperature. The variations in the sea-air temperature difference and surface pressure are in opposite phase to each other. Some of the plausible mechanisms for the incipient development and movement of the depression are also discussed.Es werden die Verhltnisse im Luft-Meer-Grenzbereich im frhen Entwicklungsstand einer Depression ber der stlichen zentralen Arabischen See whrend der Monsun MONEX-79 durch Analyse der Schiffsbeobachtungsdaten ber Luft- und Meerestemperaturen, Luftdruck an der Oberflche, Seegang und Wind untersucht. Diese Analyse zeigte eine ausgesprochene Zunahme der Temperaturdifferenz zwischen Meer und Luft (2–4 C) und diese Zunahme erweist sich klar als durch eine Abnahme der Lufttemperatur verursacht. Die nderungen in der Temperaturdifferenz zwischen Meer und Luft und des Luftdrucks verlaufen in zueinander entgegengesetzter Phase. Einige einleuchtende Mechanismen fr die beginnende Entwicklung und die Bewegung der Depression werden auch besprochen.
The Somali Current typically develops in different phases in response to the onset of the summer monsoon. Each of these phases exists quasistationary for some time ranging from weeks to months. These periods of rather constant circulation patterns are separated by periods of rapid transition.In the early phase of the monsoon response, during May, with weak southerly winds off Somalia, a cross equatorial inertial current develops which turns offshore a few degrees north of the equator with a coastal upwelling wedge just north of the offshore flow. North of that region, an Ekman upwelling regime exists all the way up the coast. At the onset of strong winds in June, a northern anticyclonic gyre develops north of 5°N and a second cold wedge forms north of 8°–9°N, where that current turns offshore. The most drastic change of upwelling pattern occurs in the late phase of the summer monsoon, August/September, when the southern cold wedge propagates northward, indicating a break-down of the two-gyre pattern and development of a continuous boundary current from south of the equator to about 10°N. The wedge propagation during 1976–1978 is discussed, based on satellite observations (EVANS and BROWN, 1981), moored station data during 1978, 1979 and shipboard hydrographic data during 1979. A simple relation between the decrease of local monsoon winds offshore and wedge propagation cannot be determined.The southward coastal undercurrent, which is part of the Ekman upwelling regime north of 5° during the early summer monsoon, seems to turn offshore between 3° and 5°, probably due to a zonal excursion of depth contours in that area. With the spin-up of the deep-reaching northern gyre the undercurrent is extinguished during July to August but seems to get reestablished after the coalescence of the two gyres.
This paper utilizes panel data from rural India to examine how the composition of asset holdings varies across farme rs with different levels of total wealth and across farmers facing different degrees of weather risk. In particular, the riskiness of farmers' asset portfolios are measured in terms of their sensitivity to weather variation and a test is developed and implemented of risk aversion based on the association between the average returns to individual production assets and their sensitivity to weather variability. How the responsiveness of portfolio riskiness and farm profitability to the influence of exogenous weather risk varies with wealth is also estimated. Copyright 1993 by Royal Economic Society.
Southwest Monsoon.” Met. Monography, Synoptic Meteorology. India Meteorology Department
- Y Rao