Prediction of summer monsoon rainfall over India using the NCEP climate forecast system

The performance of a dynamical seasonal forecast system is evaluated for the prediction of summer monsoon rainfall over the Indian region during June to September (JJAS). The evaluation is based on the National Centre for Environmental Prediction’s (NCEP) climate forecast system (CFS) initialized during March, April and May and integrated for a period of 9 months with a 15 ensemble members for 25 years period from 1981 to 2005. The CFS’s hindcast climatology during JJAS of March (lag-3), April (lag-2) and May (lag-1) initial conditions show mostly an identical pattern of rainfall similar to that of verification climatology with the rainfall maxima (one over the west-coast of India and the other over the head Bay of Bengal region) well simulated. The pattern correlation between verification and forecast climatology over the global tropics and Indian monsoon region (IMR) bounded by 50°E–110°E and 10°S–35°N shows significant correlation coefficient (CCs). The skill of simulation of broad scale monsoon circulation index (Webster and Yang; WY index) is quite good in the CFS with highly significant CC between the observed and predicted by the CFS from the March, April and May forecasts. High skill in forecasting El Nino event is also noted for the CFS March, April and May initial conditions, whereas, the skill of the simulation of Indian Ocean Dipole is poor and is basically due to the poor skill of prediction of sea surface temperature (SST) anomalies over the eastern equatorial Indian Ocean. Over the IMR the skill of monsoon rainfall forecast during JJAS as measured by the spatial Anomaly CC between forecast rainfall anomaly and the observed rainfall anomaly during 1991, 1994, 1997 and 1998 is high (almost of the order of 0.6), whereas, during the year 1982, 1984, 1985, 1987 and 1989 the ACC is only around 0.3. By using lower and upper tropospheric forecast winds during JJAS over the regions of significant CCs as predictors for the All India Summer Monsoon Rainfall (AISMR; only the land stations of India during JJAS), the predicted mean AISMR with March, April and May initial conditions is found to be well correlated with actual AISMR and is found to provide skillful prediction. Thus, the calibrated CFS forecast could be used as a better tool for the real time prediction of AISMR.     

Characteristics of ambient ammonia over Delhi,India

In the present paper, we have characterized the ambient ammonia over Delhi along with other trace gases (NH₃, NO, NO₂, SO₂ and CO) and particulates (PM_2.5 and PM₁₀) measured during December 2011 to June 2012. The average mixing ratios of ambient NH₃, NO, NO₂, SO₂ and CO were recorded as 21.2 ± 5.4, 19.5 ± 4.9, 17.4 ± 1.4, 1.7 ± 0.5 ppb and 1.6 ± 0.7 ppm, respectively, during winter, whereas the average mixing ratios of ambient NH₃, NO, NO₂, SO₂ and CO were recorded as 20.8 ± 4.7, 21.7 ± 6.3, 16.8 ± 3.1, 2.2 ± 0.8 ppb and 1.8 ± 0.9 ppm, respectively, during summer. In the present case, non-significant seasonal and diurnal variations of NH₃, NO, NO₂, SO₂ and CO were observed during both the seasons. The average monthly NH₃/NH₄ ⁺ ratios varied from 0.28 to 2.56 with an average value of 1.46 in winter. The higher NH₃/NH₄ ⁺ ratio (3.5) observed in summer indicates the abundance of NH₃ in the atmosphere during summer. The higher fraction of particulate NH₄ ⁺ observed in winter than summer attributes to the conversion of gaseous NH₃ into NH₄ ⁺. The results emphasized that the traffic could be one of the significant sources of ambient NH₃ at the urban site of Delhi as illustrated by positive correlations of NH₃ with traffic-related pollutants (NO, NO₂ and CO). Surface wind analysis and wind directions also support the roadside traffic and agricultural activities at the nearby area indicating possible major sources of ambient NH₃ at the study site.     

Temporal variability in the withdrawal phase of southwest monsoon over India and related consequences in northeast monsoon: a climatological perspective

Theoretical and Applied Climatology - The variability in duration of withdrawal phase of southwest monsoon over India is often witnessed to influence the northeast monsoon rainfall of India as...     

Stable carbon and nitrogen isotopic characteristics of PM2.5 and PM10 in Delhi,India

This study presents the chemical composition (carbonaceous and nitrogenous components) of aerosols (PM_2.5 and PM₁₀) along with stable isotopic composition (δ¹³C and δ¹⁵N) collected during winter and the summer months of 2015–16 to explore the possible sources of aerosols in megacity Delhi, India. The mean concentrations (mean?±?standard deviation at 1σ) of PM_2.5 and PM₁₀ were 223?±?69 µg m^?3 and 328?±?65 µg m^?3, respectively during winter season whereas the mean concentrations of PM_2.5 and PM₁₀ were 147?±?22 µg m^?3 and 236?±?61 µg m^?3, respectively during summer season. The mean value of δ¹³C (range: ??26.4 to ??23.4‰) and δ¹⁵N (range: 3.3 to 14.4‰) of PM_2.5 were ??25.3?±?0.5‰ and 8.9?±?2.1‰, respectively during winter season whereas the mean value of δ¹³C (range: ??26.7 to ??25.3‰) and δ¹⁵N (range: 2.8 to 11.5‰) of PM_2.5 were ??26.1?±?0.4‰ and 6.4?±?2.5‰, respectively during the summer season. Comparison of stable C and N isotopic fingerprints of major identical sources suggested that major portion of PM_2.5 and PM₁₀ at Delhi were mainly from fossil fuel combustion (FFC), biomass burning (BB) (C-3 and C-4 type vegitation), secondary aerosols (SAs) and road dust (SD). The correlation analysis of δ¹³C with other C (OC, TC, OC/EC and OC/WSOC) components and δ¹⁵N with other N components (TN, NH₄⁺ and NO₃^?) are also support the source identification of isotopic signatures.

     

Climate change,the monsoon,and rice yield in India

Recent research indicates that monsoon rainfall became less frequent but more intense in India during the latter half of the Twentieth Century, thus increasing the risk of drought and flood damage to the country’s wet-season (kharif) rice crop. Our statistical analysis of state-level Indian data confirms that drought and extreme rainfall negatively affected rice yield (harvest per hectare) in predominantly rainfed areas during 1966–2002, with drought having a much greater impact than extreme rainfall. Using Monte Carlo simulation, we find that yield would have been 1.7% higher on average if monsoon characteristics, especially drought frequency, had not changed since 1960. Yield would have received an additional boost of nearly 4% if two other meteorological changes (warmer nights and lower rainfall at the end of the growing season) had not occurred. In combination, these changes would have increased cumulative harvest during 1966–2002 by an amount equivalent to about a fifth of the increase caused by improvements in farming technology. Climate change has evidently already negatively affected India’s hundreds of millions of rice producers and consumers.     

Trace elements in the atmospheric aerosols at Delhi,North India

The total suspended particulate (TSP) levels at Delhi (north India) were measured on 116 days between February and October 1980. The observations were stratified according to season and the values of cross-correlation of the TSP and its components were evaluated. High TSP (209 g m^-3) levels were found during the summer period associated with hot and dry weather in the region and low TSP (109 g m^-3) were found during the monsoon period. Most of the TSP mass was associated with natural soil elements, such as Fe, Al, Mn, Ca, and K. Only a fraction of the mass of the TSP was comprised of elements from anthropogenic sources, e.g., Pb, Ni, Cd, Sb, Cu, and Zn. The aerosols at Delhi were potentially basic in nature, unlike those in European countries which are acidic in nature and cause acid rainfall.     

New statistical models for long-range forecasting of southwest monsoon rainfall over India

The India Meteorological Department (IMD) has been issuing long-range forecasts (LRF) based on statistical methods for the southwest monsoon rainfall over India (ISMR) for more than 100 years. Many statistical and dynamical models including the operational models of IMD failed to predict the recent deficient monsoon years of 2002 and 2004. In this paper, we report the improved results of new experimental statistical models developed for LRF of southwest monsoon seasonal (June–September) rainfall. These models were developed to facilitate the IMD’s present two-stage operational forecast strategy. Models based on the ensemble multiple linear regression (EMR) and projection pursuit regression (PPR) techniques were developed to forecast the ISMR. These models used new methods of predictor selection and model development. After carrying out a detailed analysis of various global climate data sets; two predictor sets, each consisting of six predictors were selected. Our model performance was evaluated for the period from 1981 to 2004 by sliding the model training period with a window length of 23 years. The new models showed better performance in their hindcast, compared to the model based on climatology. The Heidke scores for the three category forecasts during the verification period by the first stage models based on EMR and PPR methods were 0.5 and 0.44, respectively, and those of June models were 0.63 and 0.38, respectively. Root mean square error of these models during the verification period (1981–2004) varied between 4.56 and 6.75% from long period average (LPA) as against 10.0% from the LPA of the model based on climatology alone. These models were able to provide correct forecasts of the recent two deficient monsoon rainfall events (2002 and 2004). The experimental forecasts for the 2005 southwest monsoon season based on these models were also found to be accurate.     

Trend analysis for rainfall in Delhi and Mumbai, India

Urbanisation has burdened cities with many problems associated with growth and the physical environment. Some of the urban locations in India are becoming increasingly vulnerable to natural hazards related to precipitation and flooding. Thus it becomes increasingly important to study the characteristics of these events and their physical explanation. This work studies rainfall trends in Delhi and Mumbai, the two biggest Metropolitan cities of Republic of India, during the period from 1951 to 2004. Precipitation data was studied on basis of months, seasons and years, and the total period divided in the two different time periods of 1951–1980 and 1981–2004 for detailed analysis. Long-term trends in rainfall were determined by Man-Kendall rank statistics and linear regression. Further this study seeks for an explanation for precipitation trends during monsoon period by different global climate phenomena. Principal component analysis and Singular value decomposition were used to find relation between southwest monsoon precipitation and global climatic phenomena using climatic indices. Most of the rainfall at both the stations was found out to be taking place in Southwest monsoon season. The analysis revealed great degree of variability in precipitation at both stations. There is insignificant decrease in long term southwest monsoon rainfall over Delhi and slight significant decreasing trends for long term southwest monsoon rainfall in Mumbai. Decrease in average maximum rainfall in a day was also indicated by statistical analysis for both stations. Southwest monsoon precipitation in Delhi was found directly related to Scandinavian Pattern and East Atlantic/West Russia and inversely related to Pacific Decadal Oscillation, whereas precipitation in Mumbai was found inversely related to Indian ocean dipole, El Ni?o- Southern Oscillation and East Atlantic Pattern.     

Uncertainties in the regional climate models simulations of South-Asian summer monsoon and climate change

The uncertainties in the regional climate models (RCMs) are evaluated by analyzing the driving global data of ERA40 reanalysis and ECHAM5 general circulation models, and the downscaled data of two RCMs (RegCM4 and PRECIS) over South-Asia for the present day simulation (1971–2000) of South-Asian summer monsoon. The differences between the observational datasets over South-Asia are also analyzed. The spatial and the quantitative analysis over the selected climatic regions of South-Asia for the mean climate and the inter-annual variability of temperature, precipitation and circulation show that the RCMs have systematic biases which are independent from different driving datasets and seems to come from the physics parameterization of the RCMs. The spatial gradients and topographically-induced structure of climate are generally captured and simulated values are within a few degrees of the observed values. The biases in the RCMs are not consistent with the biases in the driving fields and the models show similar spatial patterns after downscaling different global datasets. The annual cycle of temperature and rainfall is well simulated by the RCMs, however the RCMs are not able to capture the inter-annual variability. ECHAM5 is also downscaled for the future (2071–2100) climate under A1B emission scenario. The climate change signal is consistent between ECHAM5 and RCMs. There is warming over all the regions of South-Asia associated with increasing greenhouse gas concentrations and the increase in summer mean surface air temperature by the end of the century ranges from 2.5 to 5 °C, with maximum warming over north western parts of the domain and 30 % increase in rainfall over north eastern India, Bangladesh and Myanmar.     

Turbulence characteristics in the atmospheric surface layer during summer monsoon of 1997 over a semi-arid location in India

A land surface processes experiment (LASPEX) was conducted in the semi-arid region of Northwest India during January 1997–February 1998. Analysis of turbulent components of wind and air temperature collected in the surface layer (SL) at Anand (22°35′N, 72°55′E) during the Indian summer monsoon season from June to September 1997 is presented. Turbulent fluctuation of wind components and air temperature observed at Anand varied as a function of terrain features and stability of the surface layer. Under neutral conditions, the standard deviation of vertical velocity (σ _w ) and temperature (σ _T ) were normalized using respective surface layer scaling parameter u _* and T _* which fitted the expressions σ _w /u _* = 1.25 and σ _T /T _* ≈ 4. Micrometeorological spectrum of wind and temperature at 5 m above ground level (AGL) at Anand showed peaks at time scale of 1–3 min at the low-frequency end. The inertial sub-range characteristics (?2/3 slope) of the spectrum are exhibited mostly. However, in some occasions, slope of ?1 denoting brown noise was depicted by the wind and temperature spectrum, which indicated anisotropy in turbulence.     

The Convective Boundary Layer over the Deccan Plateau,India during the summer monsoon

The thermodynamic structure of the Convective Boundary Layer (CBL) over the Deccan Plateau, India has been investigated using aerological data during the summer monsoon seasons of 1980 and 1981. Conserved-variable analysis and the saturation-point approach, which were used in this study, suggest that the top of the CBL varied between 700–600 mb during the monsoon. The air above the top of the CBL during a weak monsoon was estimated to have subsided for 4 days with a subsidence rate of 30 mb day^-1.     

Equilibrium climate response of the East Asian summer monsoon to forcing of anthropogenic aerosol species

We used an online aerosol–climate model to study the equilibrium climate response of the East Asian summer monsoon (EASM) to increases in anthropogenic emissions of sulfate, organic carbon, and black carbon aerosols from 1850 to 2000. Our results show that each of these aerosol species has a different effect on the EASM as a result of changes in the local sea–land thermal contrast and atmospheric circulation. The increased emission of sulfate aerosol leads to a decrease in the thermal contrast between the land and ocean, a southward shift of the East Asian subtropical jet, and significant northerly wind anomalies at 850 hPa over eastern China and the ambient oceans, markedly dampening the EASM. An increase in organic carbon aerosol results in pronounced surface cooling and the formation of an anomalous anticyclone over the oceans north of 30°N. These effects cause a slight increase in the sea–land thermal contrast and southerly flow anomalies to the west of the anticyclonic center, strengthening the northern EASM. An increase in organic carbon emission decreases the sea–land thermal contrast over southern China, which weakens the southern EASM. The response of the summer 850-hPa winds and rainfall over the East Asian monsoon region to an increase in black carbon emission is generally consistent with the response to an increase in organic carbon. The increase in black carbon emission leads to a strengthening of the northern EASM north of 35°N and a slight weakening of the southern EASM south of 35°N. The simulated response of the EASM to the increase in black carbon emission is unchanged when the emission of black carbon is scaled up by five times its year 2000 levels, although the intensities of the response is enhanced. The increase in sulfate emission primarily weakens the EASM, whereas the increases in black carbon and organic carbon emissions mitigate weakening of the northern EASM.     

Long-term hydroclimatic variability in monsoon shadow zone of western Himalaya, India

Tree-ring-width data of Himalayan cedar [Cedrus deodara (Roxb.) G. Don] from 11 homogeneous moisture stressed sites in the monsoon shadow zone of the western Himalaya were used to develop a mean chronology extending back to ad 1353. The chronology developed using Regional Curve Standardization method is the first from the Himalayan region of India showing centennial-scale variations. The calibration of ring-width chronology with instrumental precipitation data available from stations close to the tree ring sampling sites showed strong, direct relationship with March?CApril?CMay?CJune (MAMJ) precipitation. This strong relationship was used to supplement the instrumental precipitation data back to ad 1410. The precipitation reconstruction showed extended period of drought in fifteenth and sixteenth centuries. Increasingly pluvial conditions were recorded since eighteenth century, with the highest precipitation in the early part of the nineteenth century. The decreasing trend in reconstructed precipitation in the last decade of the twentieth century, consistent with the instrumental records, is associated with the decreasing trend in frequency of western disturbances. MAMJ precipitation over the monsoon shadow zone in the western Himalaya is directly associated with the North Atlantic Oscillation (NAO) and NINO3-SST index of El Nino-Southern Oscillation (ENSO), the leading modes of climate variability influencing climate over large parts of the Northern Hemisphere. However, the relationship between ENSO and MAMJ precipitation collapsed completely during 1930?C1960. The breakdown in this relationship is associated with the warm phase of Atlantic Multidecadal Oscillation (AMO). A spectral analysis of reconstructed MAMJ precipitation indicates frequencies in the range of the variability associated with modes of NAO, ENSO and AMO.     

Surface and upper air temperatures over India in relation to monsoon rainfall

Summary The relationship between the all-India summer monsoon rainfall and surface/upper air (850, 700, 500 and 200 mb levels) temperatures over the Indian region and its spatial and temporal characteristics have been examined to obtain a useful predictor for the monsoon rainfall. The data series of all-India and subdivisional summer monsoon rainfall and various seasonal air temperatures at 73 surface observatories and 9 radiosonde stations (1951–1980) have been used in the analysis. The Correlation Coefficients (CCs) between all-India monsoon rainfall and seasonal surface air temperatures with different lags relative to the monsoon season indicate a systematic relationship.The CCs between the monsoon rainfall and surface-air temperature of the preceding MAM (pre-monsoon spring) season are positive over many parts of India and highly significant over central and northwestern regions. The average surface air temperature of six stations i.e., Jodhpur, Ahmedabad, Bombay, Indore, Sagar and Akola in this region (Western Central India, WCI) showed a highly significant CC of 0.60 during the period 1951–1980. This relationship is also found to be consistently significant for the period from 1950 to present, though decreasing in magnitude after 1975. WCI MAM surface air temperature has shown significant CCs with the monsoon rainfall over eleven sub-divisions mainly in northwestern India, i.e., north of 15 °N and west of 80 °E.Upper air temperatures of the MAM season at almost all the stations and all levels considered show positive CCs with the subsequent monsoon rainfall. These correlations are significant at some central and north Indian stations for the lower and middle tropospheric temperatures.The simple regression equation developed for the period 1951–1980 isy = – 183.20 + 8.83x, wherey is the all-India monsoon rainfall in cm andx is the WCI average surface air temperature of MAM season in °C. This equation is significant at 0.1% level. The suitability of this parameter for inclusion in a predictive regression model along with five other global and regional parameters has been discussed. Multiple regression analysis for the long-range prediction of monsoon rainfall, using several combinations of these parameters indicates that the improvement of predictive skill considerably depends upon the selection of the predictors.With 9 Figures