Satellite estimated water vapour in relation to Asian monsoon Circulation

Water vapour plays a crucial role in various exchange and transport processes in the atmosphere and its knowledge in the tropics is extremely important for input to various global circulation models. The vast oceans of earth's surface provide a large source of moisture and continuously modify the thermodynamics of the atmosphere through latent heat flux and condensational heating. In the tropics, especially in the Indian ocean the water vapour is highly heterogeneousin nature, and is one of the parameters which is responsible for cloud formation, associated with tropical systems like monsoon flows, depression, cyclones etc. The present paper reviews the various information’s available from deferent geostationary and polar orbiting satellites about water vapour affecting the southwest monsoon region around the Indian Ocean and Indian subcontinent. The temperature and moisture data from TIROS operational vertical sounder (TOVS) and INSAT-2E water vapour channel are examined to study water vapour distribution. Their usefulness in characterizing the Asian south-west (SW) monsoon circulation is focused. The Western Indian ocean showed an increase in mid-tropospheric moisture (700-500hPa) over about 8 to 10 days prior to the onset over Kerala coast. NOAA/TOVS layer tmperature and humidity is used to extrapolate the humidity profile at standard pressure levels. It is also used to compute latent and sensible heat flux. Total integrated water vapour from SSM/I is also used for estimating latent heat fluxes and for the diagnostics of NWP models. Recently, INSAT-2E water vapour channel was used to monitor the monsoon circiulation features. The new WV channel brought out clearly the feeding of various air masses, especially water vapour associated with monsoon onset and monsoon lows.

Deterministic methods for prediction of tropical cyclone tracks

ABSTRACT. The paper presents a state-of-art review of different objective techniques available for tropical cyclone track prediction. A brief description of current theories of tropical cyclone motion is given. Deterministic models with statistical and dynamical methods have been discussed. Recent advances in the understanding of cyclone structure and motion aspects have led to improved prediction of tropical cyclones. There has been considerable progress in the field of prediction by dynamical methods. High resolution Limited Area Models (LAM) as well as Global Circulation Models (GCM) are now being used extensively by most of the leading operational numerical weather prediction (NWP) centres in the world The major achievements towards improvement of such models have come from improved horizontal resolution of the models, inclusion of physical processes, use of synthetic and other non-conventional data in the data assimilation schemes and nudging method for initial matching of analysed cyclone centres with corresponding observations. A brief description of further improvement in deterministic approach for prediction of tropical cyclone tracks is outlined.

­Comparison of Statistical Downscaling of Summer Daily Precipitation Through a Certain Perfect Prognosis and Bias Corrections - A Case Study Across China

Fewer perfect prognosis (PP) based statistical downscaling were applied to future projections produced by global circulation models (GCM), when compared with the method of model output statistics (MOS). This study is a trial to use a multiple variable based PP downscaling for summer daily precipitation at many sites in China and to compare with the MOS. For the PP method (denoted as ‘OGB-PP’), predictors for each site are screened from surface-level variables in ERA-Interim reanalysis by an optimal grid-box method, then the biases in predictors are corrected and fitted to generalized linear models to downscale daily precipitation. The historical and the future simulations under the medium emission scenario (often represented as ‘RCP4.5’), produced by three GCMs (CanESM2, HadGEM2-ES and GFDL-ESM2G) in the coupled model intercomparison project phase five (CMIP5) were used as the downscaling bases. The bias correction based MOS downscaling (denoted as ‘BC-MOS’) were used to compare with the OGB-PP. The OGB-PP generally produced the climatological mean of summer precipitation across China, based on both ERAI and CMIP5 historical simulations. The downscaled spatial patterns of long-term changes are diverse, depending on the different GCMs, different predictor-bias corrections, and the choices on selecting PP and MOS. The annual variations downscaled by OGB-PP have small differences among the choices of different predictor-bias corrections, but have large difference to that downscaled by BC-MOS. The future changes downscaled from each GCM are sensitive to the bias corrections on predictors. The overall change patterns in some OGB-PP results on future projections produced similar trends as those projected by other multiple-model downscaling in CMIP5, while the result of the BC-MOS on the same GCMs did not, implying that PP methods may be promising. OGB-PP produced more significant increasing/decreasing trends and larger spatial variability of trends than the BC-MOS methods did. The reason maybe that in OGB-PP the independent precipitation modeling mechanism and the freely selected grid-box predictors can give rise to more diverse outputs over different sites than that from BC-MOS, which can contribute additional local variability.

Radar observations of winds, waves and tides in the mesosphere and lower thermosphere over South Georgia island (54°S, 36°W) and comparison to WACCM simulations

The mesosphere and lower thermosphere (MLT) is a dynamic layer of the earth’s atmosphere. This region marks the interface at which neutral atmosphere dynamics begin to influence the ionosphere and space weather. However, our understanding of this region and our ability to accurately simulate it in global circulation models (GCMs) is limited by a lack of observations, especially in remote locations. To this end, a meteor radar was deployed on the remote mountainous island of South Georgia (54° S, 36° W) in the Southern Ocean from 2016 to 2020. The goal of this study is to use these new measurements to characterise the fundamental dynamics of the MLT above South Georgia including large-scale winds, solar tides, planetary waves (PWs) and mesoscale gravity waves (GWs). We first present an improved method for time-height localisation of radar wind measurements and characterise the large-scale MLT winds. We then explore the amplitudes and phases of the diurnal (24 h), semidiurnal (12 h) and terdiurnal (8 h) solar tides at this latitude. We also explore PW activity and find very large amplitudes up to 30 ms−1 for the quasi-2 day wave in summer and show that the dominant modes of the quasi-5, 10 and 16 day waves are westward W1 and W2. We investigate wind variance due to GWs in the MLT and use a new method to show an east-west tendency of GW variance of up to 20 % during summer and a weaker north-south tendency of 0–5 % during winter. This is contrary to the expected tendency of GW directions in the winter stratosphere below, which is a strong suggestion of secondary GW (2GW) observations in the MLT. Lastly, comparison of radar winds to a climatological Whole Atmosphere Community Climate Model (WACCM) simulation reveals a simulated summertime mesopause and zonal wind shear that occur at altitudes around 10 km lower than observed, and southward winds during winter above 90 km altitude in the model that are not seen in observations. Further, wintertime zonal winds above 85 km altitude are eastward in radar observations but in WACCM they are found to weaken and reverse to westward. Recent studies have linked this discrepancy to the impact of 2GWs on the residual circulation which are not included in WACCM. These measurements therefore provide vital constraints that can guide the development of GCMs as they extend upwards into this important region of the atmosphere.

Advance forecasting of cyclone track over north Indian Ocean using a global circulation model

& m".kdfVca/kh; pØokr lewps fo’o esa vf/kdka’k rVorhZ {ks=ksa esa xaHkhj vkSj fodjky Mj mRiUu djrs jgrs gSaA blfy, m".kdfVca/kh; pØokrksa ds laca/k esa vf/kd lVhd vkSj yEch vof/k ds iwokZuqeku dh ek¡x c<+rh tk jgh gSA ;|fi dkQh le; ls lhfer {ks= fun’kZ ¼,y- ,- ,e-½ m".kdfVca/kh; pØokrksa ds xfrdh; iwokZuqeku ds fy, ijEijkxr lk/ku jgs gSa fQj Hkh bl ckr ls Hkh badkj ugh fd;k tk ldrk gS fd pØokrksa dh xfrdh; izÑfr ds izLrqrhdj.k esa HkweaMyh; ifjlapj.k fun’kkZsa ¼th- lh- ,e-½ ds mi;ksx ds Qy Lo:Ik dkQh lq/kkj vk;k gSA mnkgj.k ds fy, caxky dh [kkM+h ds dqN pØokr rks caxky dh [kkM+h esa gh fodflr gksrs gSa fdarq cgqr ls pØokr [kkM+h ds iwoZ dh rjQ cus fuEu nkc {ks= ds l?ku gksus vkSj [kkM+h dh vksj c<+us ds dkj.k curs gSa ftlls ;g Li"V gS fd pØokr ds iwokZuqeku ds fy, pØokr ds mRiUu gksus ds foLr`r {ks= dks 'kkfey djus dh vko’;drk gSA bl 'kks/k&i= esa geus crk;k gS fd ,y- ,- ,e- vkSj th- lh- ,e- dh la;qDr fo’ks"krk rqyukRed :Ik ls uohu Js.kh ds HkweaMyh; ekWMyksa ¼th- lh- ,e-½ ls pØokr ds ekxZ vkSj mldh rhozrk tSls dqN vR;ar egRoiw.kZ y{k.kksa ds laca/k eas yEch vof/k ds vkSj vf/kd lVhd rjg ds iwokZuqeku nksuksa miyC/k djk ldrs gSaA lkr pØokrksa ls lacaf/kr fofHkUu LFkkuksa] _rqvksa] o"kZ vkSj mudh rhozrk] izfr:fir ekxksZa vkSj pØokrksa ds ySaMQky ds LFkyksa ds ik¡p fnuksa ls Hkh vf/kd le; igys dh mudh vkjafHkd voLFkkvksa vkSj muds laca/k esa leqnz lrg rkieku ¼,l- ,l- Vh-½ ds ekfld tyok;q foKku ds 48 ?kaVs igys tkjh fd, x, gSaA buesa rkRdkfyd izpkyukRed iwokZuqeku ds leku gh =qfV;k¡ ikbZ xbZ gSaA Tropical cyclones pose a serious and growing threat to many coastal areas world over; there is increasing demand for better accuracy as well as longer range for tropical cyclone forecasts. While the traditional tool for dynamical forecasting of tropical cyclones has been Limited Area Models (LAM), there are reasons to believe that use of Global Circulation Models (GCM) may result in improved representation of cyclone dynamics. Over Bay of Bengal, for example, while some cyclones develop in situ, many result from intensification of low pressure system that travel from the east, implying need for consideration of a large domain. We show here that a relatively new class of Global Circulation Models (GCM), combining the advantages of LAMs and GCMs, can provide both longer range and better accuracy for such critical parameters like track and intensity. For seven cyclones representing different locations, seasons, years and strength, simulated tracks and land-fall locations show, with initial condition more than 5 days ahead and only monthly climatology of sea surface temperature (SST), errors comparable to those from current operational forecast 48 hours in advance.

Major advances in understanding and prediction of tropical cyclones over north Indian Ocean : A Perspective

lkj & mRrjh fgUn egklkxj esa m".kdfVca/kh pØokrksa ij fd, x, vuqla/kku xr 150 o"kksZa esa fofHkUu pj.kksa ls xqtjs gSa vkSj vf/kd rFkk csgrj izs{k.kksa dks fodflr djus ds fy, izkS|ksfxdh ds :Ik es bldk fodkl fd;k x;k gSA 20oha 'krkCnh ds e/; rd leqnz esa bl vkinkdkjh ifj?kVuk ds cuus vkSj blds rhoz gksus dh tkudkjh iksrksa esa gh dqN gn rd fojyrk ls izkIr gksus okys izs{k.kksa ds ek/;e ls feyrh Fkh vkSj blfy, 1960 ds n’kd rd Hkkjr esa fd, x, vf/kdka’k vuqla/kku v/;;uksa esa pØokrksa ds tyok;q foKku] mudh /kjkryh; lajpuk] mudh xfr vkSj leqnz esa tgktksa dks ig¡qpkusa okyh {kfr dks vuns[kk djus okys fu;eksa ij vf/kd cy fn;k x;k FkkA ekSle jsMkj] mifjru ok;q ifjKkiuksa] vuqla/kku ok;q;ku losZ{k.k ekSle mixzgksa vkSj daI;wVjksa ds ek/;e ls izkIr dh xbZ ubZ ok;qeaMyh; izks|ksfxdh ds izLrqrhdj.k ls 1950 ds n’kd ls ysdj 1980 ds n’kd ds nkSjku fofHkUu ns’kksa ds m".kdfVca/kh pØokr vuqla/kku esa vk’p;Ztud :Ik ls ifjorZu vk;k gSA bl vof/k esa m".kdfVca/kh pØokrksa ds laiw.kZ mRifRr pØ dk izfr:i.k djus ds fy, lS)kafrd v/;;uksa vkSj daI;wVj fun’kksaZ ds fodkl esa lq/kkj ns[kk x;k gSA bl vof/k esa m".kdfVca/kh pØokr ds ekxZ dk iwokZuqeku yxkuk Hkh vuqla/kku dk ,d {ks= cu x;k gS vkSj 1950 ds n’kd ls ysdj 1980 ds n’kd ds nkSjku tyok;q foKku] flukfIVd lkaf[;dh; vkSj xfrdh; i)fr;ksa ij vk/kkfjr rduhdksa ds izdkjksa esa fujarj fodkl gqvk gS rFkk bUgsa ekU;rk feyh gSA xr 10 o"kksZa dh vof/k ds nkSjku fodflr ns’kksa esa HkweaMyh; ifjpkyu fun’kksZa esa fufgr ifj"Ñr mPp foHksnu ds fun’kksZa dk fodkl fd;k x;k gS vkSj ikjLifjd fØ;kvksa dh izfØ;k ds :Ik esa bl Ik)fr dk fodkl djus vkSj bldh xfr dk iwokZuqeku yxkus ds fy, budh tk¡p dh xbZ gSA ;s iw.kZ :i ls lgh ikbZ xbZ gSaA Hkkjr esa Hkh bl izdkj ds fodklksa dks viuk;k x;k gSA bl 'kks/k&i= esa m".kdfVca/kh pØokr ds fodkl vkSj bldh xfr esa lfUufgr izR;{k izfØ;kvksa ds laca/k esa fd, x, izeq[k fodklksa dh lwph miyC/k djkus dk iz;kl fd;k x;k gSA lkekU; :Ik ls HkweaMyh; vuqla/kku ds {ks= esa fd, x, iz;kl fgan egklkxj csflu esa fd, tk jgs v/;;uksa ij dsafnzr jgs gSaA mRrjh fgan egklkxj esa m".kdfVca/kh pØokrksa ds vUr% nl o"khZ; fHkUurkvksa dh tk¡p dh xbZ gS vkSj 1980 ds n’kd ls budh xfr;ksa esa vDlj vR;kf/kd deh ns[kh xbZ gSA fgan egklkxj csflu esa m".k@'khr bulksa dh ?kVukvksa ds e/; dksbZ laca/k ugha ik;k x;k gSA izpaM m".kdfVca/kh pØokrksa ds fodkl vkSj xfr ds fy, vko’;d o`gr eku fLFkfr;ksa dh izÑfr ls lacaf/kr izs{k.kkRed vkSj lS}kafrd ekWMfyax i)fr;ksa esa daI;wVj izfr:i.kksa lfgr izs{k.kkRed vkSj lS)kafrd i)fr;ksa ls fHkUu fHkUu fopkjksa dk irk pyk gSA mRrjh fgan egklkxj csflu esa fd, x, vkSj vf/kd vuqla/kku dh vksj fo’ks"k /;ku nsus dh fn’kk esa dqN lq>ko fn, x, gSaA Research on tropical cyclones in the north Indian Ocean has passed through different phases in the last 150 years and progress was made as the technology for more and better observations evolved. Till the middle of the 20th century, the only way of knowing about the formation and intensification of this disastrous phenomenon, while out at sea, was through rather sparse ship observations and hence the climatology of the cyclones, their surface structure, movement and the rules to avoid the damage to shipping at sea were emphasized in most of the research studies in India till 1960s. Introduction of new atmospheric technologies through weather radars, upper air soundings, weather satellites and computers have brought a phenomenal change in tropical cyclone research in different countries during 1950s to 1980s. The period also witnessed break-through in theoretical studies and the development of computer models to simulate the complete genesis cycle of tropical cyclones. Predicting the track of tropical cyclone also became an area of active research in this period and a variety of techniques were increasingly developed. During the last 10 years sophisticated high resolution models embedded within global circulation models have been developed in advanced countries and tested for predicting the development and movement of the system as an interactive process. In India, too such developments have been adopted. Within the scope of global research effort in general, the focus of the article is on the studies in north Indian Ocean basin. Inter-decadal variation of tropical cyclones in the north Indian Ocean has been examined and the frequency of their formations have shown drastic decrease since 1980s. No connection is found between the warm/cold ENSO events in the Indian Ocean basin and tropical cyclone frequency in the basin. Observational and theoretical approaches with computer simulations have brought a convergence of views concerning the nature of large-scale conditions needed for development and movement of severe tropical cyclones. Some suggestions are provided for directing special attention toward further research in this area in the north Indian Ocean basin.

Influence of the Madden–Julian Oscillation on the Arctic Oscillation Prediction in S2S Operational Models

The connections between the Madden–Julian Oscillation (MJO) and the Arctic Oscillation (AO) are examined in both observations and model forecasts. In the observations, the time-lag composites are carried out for AO indices and anomalies of 1,000-hPa geopotential height after an active or inactive initial MJO. The results show that when the AO is in its positive (negative) phase at the initial time, the AO activity is generally enhanced (weakened) after an active MJO. Reforecast data of the 11 operational global circulation models from the Sub-seasonal to Seasonal (S2S) Prediction Project are further used to examine the relationship between MJO activity and AO prediction. When the AO is in its positive phase on the initial day of the S2S prediction, an initial active MJO can generally improve the AO prediction skill in most of the models. This is consistent with results found in the observations that a leading MJO can enhance the AO activity. However, when the AO is in its negative phase, the relationship between the MJO and AO prediction is not consistent among the 11 models. Only a few S2S models provide results that agree with the observations. Furthermore, the S2S prediction skill of the AO is examined in different MJO phases. There is a significantly positive relationship between the MJO-related AO activity and the AO prediction skill. When the AO activity is strong (weak) in an MJO phase, including the inactive MJO, the models tend to have a high (low) AO prediction skill. For example, no matter what phase the initial AO is in, the AO prediction skill is generally high in MJO phase 7, in which the AO activity is generally strong. Thus, the MJO is an important predictability source for the AO forecast in the S2S models.

A review of methods to account for impacts of non-stationary climate data on extreme rainfalls for design rainfall estimation in South Africa

Frequency analysis of extreme rainfall and flood events are used to determine design rainfalls and design floods which are needed to design hydraulic structures such as dams, spillways and culverts. Standard methods for frequency analysis of extreme events are based on the assumption of a stationary climate. However, this assumption in rainfall and flood frequency analysis is being challenged with growing evidence of climate change. As a consequence of a changing climate, the frequency and magnitude of extreme rainfall events are reported to have increased in parts of South Africa, and these and other changes in extreme rainfall occurrences are expected to continue into the future. The possible non-stationarity in climate resulting in changes in rainfall may impact on the accuracy of the estimation of extreme rainfall quantities and design rainfall estimations. This may have significant consequences for the design of new hydraulic infrastructure, as well as for the rehabilitation of existing infrastructure. Hence, methods that account for non-stationary data, such as caused by climate change, need to be developed. This may be achieved by using data from downscaled global circulation models in order to identify non-stationary climate variables which affect rainfall, and which can then be incorporated into extreme value analysis of a non-stationary data series.

Investigation of impact of climate change on small catchments using different climate models and statistical approaches

The use of a statistical downscaling technique is needed to investigate the hydrological consequences of climate change on the local hydropower capacity. Global Circulation Models (GCMs) are crucial tools used in various simulations for potential climate change effects, including precipitation and temperature. Statistical downscaling methods comprise the improvement of relations between the large-scale climatic parameters and the local variables. This study presents the trend analysis of the observed variables compared to the statistically downscaled emission scenarios that are adopted from the Canadian Second Generation Earth Systems Model (CanESM2) in the basin of Göksu River which is located in Turkey. The key purpose of the research is to evaluate both the predicted monthly precipitation and the projections of GCMs within the three simulated scenarios of RCP2.6, RCP4.5, and RCP8.5 by Gene Expression Programming (GEP). In addition, the findings of statistical downscaling of monthly mean precipitation will be compared to the Linear Regression model (LR). The R-value is 0.827 and 0.755 for precipitation of the GEP model for the periods of calibrating and validation. In comparison with the LR model for the validation and calibration periods (1971–2005), the results of the GEP model prove its applicability in projecting the data of the monthly mean rainfall. Generally, in the simulated periods of 2021–2100, the mentioned scenarios forecast a decline in the monthly mean precipitation in the basin. Moreover, the scenario of RCP8.5 projects more suitably for the case study than expected under the scenarios of the RCP4.5 and RCP2.6. The mean statistically downscaled CanESM2 model was compared with the trend analysis of the areal mean precipitation (PM) over the case study area, and the trend was shown decreasing. However, the RCP 8.5 scenario has the more quasi-asymptotic for trend.