| CLIMATOLOGY |
WEATHER FORECASTING |
To intensify research on aerobic
meteorology, hydrometeorology, micrometeorology, crop production meteorology
(crop-weather studies), soil climatology, microbial meteorology, herbicide
meteorology, forest meteorology, horticultural meteorology, animal
meteorology, seed meteorology and other related subjects.
To provide center of activities for the
different agromet observatories of TNAU.
To strengthen the agricultural meteorology
education for the State of Tamil Nadu through
Certificate course for B.Sc (Ag) graduates
on agricultural meteorology.
Specialized degree course for
Short course for farmers of Tamil Nadu.
To improve weather forecast in
collaboration with NCMRWF, New Delhi.
To develop resource personnel on
drought climatology, agromet-spectral modeling for yield forecast, Weather
modifications and allied techniques.
To develop simulation crop
modeling and as well as crop pests - weather interaction modeling.
To undertake climate change
yield of both kuruvai and Thaladi seasons over 30 years (1961-1990) were
correlated with respective weather data to find out the crop weather
relationship of concerned season. The study indicated that reproductive
stage of rice was very critical for both kuruvai and Thaladi seasons for
weather parameter. In addition maturity stage of kuruvai season and
vegetative stage of Thaladi season were also critical to weather. During
Thaladi season, correlation study indicated that positive correlation was
observed for maximum temperature at vegetative and reproductive stages.
The experimental result revealed that pre monsoon
sowing with recommended plant population (60 x 20 cm) recorded higher grain
yield (2970 kg/ha) compared to other treatments studied. Among N fertilizer
application, 50 per cent basal +50 per cent flexible as per the rainfall
receipt recorded maximum yield (2510 kg/ha) and it was 42 per cent higher
than the full basal application.
In the crop weather relationship study in cotton,
sowing cotton in the first week of August second fortnight recorded maximum
yield of 1357 kg/ha. When the sowing was delayed up to September first
fortnight, the yield reduction was 89 per cent. If the sowing was further
delayed up to September second fortnight, the yield reduction was 143
percent. If the sowing was done in earlier July, the yield was declined, but
it was not significantly different from August second fortnight sowing.
CATEGORIZATION OF COIMBATORE RAINFALL
BASED ON EL-NINO EPISODE
Coimbatore lies on the rain shadow region of
western ghat in India. Coimbatore gets most of its rainfall from northeast
monsoons (October – December). The strong Asian summer monsoon is generally
associated with positive sea surface anomaly in the western Pacific
(El-Nino). In the present study an attempt was made to categorise the
rainfall data of Coimbatore based on El-Nino episodes. The results revealed
that El-Nino favoured both annual as well as northeast monsoon rainfall
while the La-Nina had influenced the South west monsoon rainfall. The study
also indicated that in Coimbatore during El – Nino years crop production is
with less risky during northeast monsoon season and the farmers can choose
even crops with comparatively high water requirement, whereas in La-Nina
years higher yields could be reaped from the southwest monsoon season in
certain taluks of Coimbatore district, India.
LENGTH OF GROWING PERIOD (LGP) IN RELATION TO WARM (EL-NINO) AND COLD
(LA-NINA) PHASES OF EQUATORIAL PACIFIC OCEAN
using historical rainfall data an integrated study was attempted between the
Length of Growing Period (LGP) and Global weather phenomenon factors like
El-Nino and La-Nina. Successful crop production and choice of crops based
on the length of growing period is highly influenced by the El-Nino and
La-Nina conditions. The method suggested by Jeevananda Reddy (1983) was
used to find out the LGP. El-Nino, La-Nina and Normal years were
disintegrated from the total years of study by collecting the information
from the web site of Bureau of Meteorology. Eventhough not much difference
could be observed from the length of growing period between various
conditions studied, the occurrence of intermittent wet spell and dry spell
varied and that decides the yield of the crop. During El-Nino years crop
production is less risky with the occurrence of continuous wet spell as
compared to the La-Nina years. Based on the forecast of the El-Nino or
La-Nina situations, agronomical practices such as land configuration,
selection of crops and varieties and other management practices can be
manipulated to suit the expected weather challenge.
STUDIES– INSIGHT REVIEW ON MELNOKKU NAL AND KEELNOKKU NAL
Indigenous knowledge and beliefs of the farmers many times become true as
far as weather forecasting is concerned. Almanac is one such source that
provides valuable forecast information and many people believe on that.
Melnokku nal or keelnokku nal was mainly based on the position of sun from
equator either to tropic of cancer or to tropic of Capricorn and also due to
position of moon around the earth. A study was undertaken to find out the
scientific rationale behind the melnokku nal and keelnokku nal information
given in the Almanac. The study indicated that in respect of rainfall in
all the keelnokku nal of different months there was rainfall irrespective of
the quantity received while in melnokku nal of different months rainfall was
absent in February and March months. Relatively higher rainfall was recorded
in keelnokku nal during April, May, June and October months and reverse
trend for melnokku nal in the remaining months of the calendar year.
INFLUENCE OF WEATHER ON POPULATION DYNAMICS OF
Spodoptera - A POLYPHAGOUS PEST
Spodoptera is a polyphagous pest and
its activity is highly influenced by the prevailing weather conditions. A
study was conducted at TNAU for two years (1999/ 2000) to find out the
influence of weather conditions that lead to sudden eruption of this pest by
collecting the moths trapped in pheramone trap. Frequency analysis of
Spodoptera moth population revealed that maximum temperature of 26°C,
minimum temperature of 18°C favoured moth activity. Increasing relative
humidity and cloudiness increased the moth population. Emergence of more
than 50 moths per week could be observed when the morning relative humidity
increased from 85.6 to 89.4 per cent. At rainfall of 20 to 40 mm/week the
moth population was higher. Different seasons also had influenced the moth
population and South West Monsoon season had more influence in erupting the
population than other season. The derived information could be well
utilised for forecasting the pest incidence, monitoring its occurrence and
control of this polyphagous pest.
INFLUENCE OF THITHIES (LUNAR DAY) ON RAINFALL
Based on the interaction between earth and moon in relation to Sun, there
are two phases of the moon viz., full moon and new moon. The shadow effect
of earth triggers new moon (Ammavasai) while the opposite one is full moon.
Each month is governed by both new moon and full moon and in between these
two there are fourteen thithies covering the 14 days interval and those are
Prathamai (1), Thuthiai (2), Thiruthiai (3), Charthurthi (4), Panchami (5),
Sasti (6), Sabthami (7), Astami (8), Navami (9), Dhasami (10), Yegadhasi
(11), Thuvadhasi (12), Thiriodhasi (13) and Sathurthasi (14). A
study was undertaken to find out the relationship between the rainfall and
the different thithies occur in between the two
phases of the moon viz., full moon and new moon and the results revealed
that the first eight thithies succeeding new moon (ammavasai), and
eight thithies preceding to new moon did influence annual rainfall events.
Further it is observed that with reference to higher intensity rainfall, it
occurred normally the eight thithies preceding to new moon as compared to
thithies succeeding to new moon. Almost similar results could be noticed
for both South west monsoon season and for North east monsoon season. Over
year analysis indicated that towards full moon phase (Valar Pirai), the
thithi Sasti had a tendency to offer high rainfall while such effect was
offered by Yegadasi thithi towards new moon. Neverthless, all the thithies
both during new moon phase and full moon phase did have rainfall events
though not as high. The results further indicated that high intensity events
occurred frequently during new moon phase as compared to full moon phase.
TO SEASONAL CLIMATE FORECASTS IN SOUTHERN INDIA’S DRYLAND CROPPING SYSTEMS
The Southern Indian Peninsular receives monsoon rain in summer
(June-September) and winter (October-December) that is highly variable. The
ability to predict seasonal rainfall and associated crop yield distributions
in advance could have a major impact on the management of dryland cropping
systems in this region. A comprehensive systems approach and a climate
forecasting system were used to quantify the cropping system management
responses to seasonal climate forecasts. In this part of India, the SOI is
positively related to summer monsoon rainfall, but exhibits an inverse
relationship for the winter monsoon. The probability of exceeding the median
summer monsoon rainfall following a warm ENSO phase in April/May is 31%,
while it was 60% in cold phase years. Conversely, warm phase during
June/July showed 82% chance of exceeding median rainfall during winter
monsoon, while a cold phase showed only a 28% chance. This finding is
consistent with general scientific understanding of the ENSO (El Niņo
Southern Oscillation) life-cycle.
The yield and gross margin of peanut (summer monsoon crop),
sorghum (winter monsoon crop) and cotton (overlapping in to two seasons)
based cropping systems, showed significant response to seasonal climate
forecasts. The peanut yield potential cold phase is increased by 374 kg/ha
(58%) compared to warm phase season type. The higher yield potential during
the cold phase years are caused by more opportunity of planting rains and
greater in-season rainfall. The yield of winter monsoon sorghum after summer
peanut can be substantially increased during warm ENSO phase years by 36%
and 68%, respectively over climatologically average yield. Our analysis
indicated that forecast responsive sorghum crop management strategies were
superior to traditional management (p<0.01). The chance of producing sorghum
fodder for animal is lower in cold phase years than warm phases. The farm
management decision on choice of cropping system (peanut-sorghum and cotton)
before start of the season also showed significant response to seasonal
climate forecasts. Cropping system simulation showed that during cold phase
during April/May, peanut-sorghum systems were superior to cotton systems,
while following warm phases, cotton often benefited from greater winter
monsoon rainfall coinciding with critical crop growth period. The results
demonstrated a significant response of dryland cropping system management
decisions to climate-forecasting system. The simulated crop yield and gross
margin probability distributions conditioned by climate forecasts can
support the small-holder farmers to manage the climate risk in cropping
systems through enhanced decision-making capacity of farmers.
IMPROVING FOOD SECURITY
AND RESOURCE USE OF IRRIGATED CROP PRODUCTION SYSTEM THROUGH CLIMATE
FORECASTS IN SOUTHERN INDIA
Agricultural systems in semi-arid
tropics are strongly affected by climate variability. Timing and frequency
of rainfall events conditioned by the inter-annual large-scale
ocean-atmosphere circulation features strongly influences the dryland
cropping systems. Very low level of rainfall use efficiency has been
observed in these systems due to inappropriate crop management decisions.
However, the current emerging capacity to forecast the likelihood of future
climatic distributions can enhance the rainfall use efficiency of
smallholder cropping systems exposed to climatic risk.
Global climate models (GCMs) have done
a reasonable job in simulating many aspects of the climate variability on
inter-annual time scales. Climate simulations through global circulation
model, downscaled for selected locations of the southern peninsular
India-showed reasonable prediction. Briefly, a statistical transformation of
seasonal rainfall output fields from each of several GCMs were used to
identify optimal predictors. Model Output Statistics (MOS) and strong
multivariate techniques have been used to generate dominant large-scale
modes of patterns in the simulated GCM fields. The monthly rainfall
hindcasts of GCMs were disaggregated into daily values (five realizations)
using a stochastic weather generator. Both predictor selection and
regression were fully cross-validated to avoid false skill in rainfall
prediction. The observed and hindcast rainfall showed significant
The simulated rainfall was combined
with the systems simulation approaches to find out the optimal management
practices for improving rainfall use efficiency of dryland cropping systems.
The groundnut yields simulated with observed weather and
stochastically-disaggregated monthly hindcasts also showed reasonable
closeness (r = 0.554). Emphasis was given to assess the impact of El-Nino
Southern Oscillation (ENSO) related inter-annual climate variability on
ground water resources. Additional analyses examined crop evapotranspiration
and irrigation requirement for maize crops in the study region. Results
indicate that effective rainfall was 18% less in warm ENSO years that also
exhibited 14% greater crop evapotranspiration, necessitating supplemental
irrigation. Such information on the type of water requirement conditioned by
ENSO phases would assist farmers in making water management decisions.
Development of weather based Pest and disease forecasting in cotton
Weather pest relationship studies
taken up in cotton crop showed that there is a positive relationship existed
between aphid incidence and relative humidity (morning, evening and mean),
temperature (maximum and minimum) and rainfall. In contrast, a negative
relationship existed with solar radiation bright sunshine hours and wind
speed in both early sown and late sown cotton crops. Adult moth catches in
pheromone trap indicated that there is positive relationship between maximum
temperature, minimum temperature, afternoon relative humidity and
Helicoverba moth emergence. Negative relationship could be observed for
rainfall, solar radiation, bright sunshine hours and wind speed.
weather based forewarning system for groundnut pest and disease
The observation on rust and late
leaf spot was studies at TNAU, Coimbatore at three days interval in all the
three dates of sowing viz., normal date of sowing, 15 days after normal
sowing and 30 days after normal sowing. In all the three sowings there was
pest control, disease control, pest and disease control and total
unprotected control. In the first sowing the rust incidence was upto 65.33
per cent as against 37.33 per cent in disease control plot. In second sowing
the rust incidence was upto 71.78 per cent as against 42.67 per cent in
disease control plot. In third sowing the rust was 64.44 per cent against
43.78 per cent as against 46 per cent in disease control. In second sowing
the incidence was upto 68.44 per cent as against 42.67 per cent in disease
control. In the third sowing the disease incidence was 60.44 per cent as
against 42.0 per cent in disease control plot. The result indicated that the
rust incidence was severe in second date of sowing (4.12.2001) as compared
to first sowing (22.06.2001) and third sowing (25.07.2001). Such trend was
not observed for late leaf sport disease.
The data revealed that
irrespective of two sowings (I sowing 22.6.2201, II sowing 4.7.2001) the pod
yield was similar for control, but however it varied for other treatments
between two sowings. In respect of first sowing highest pod yield was
obtained under pest and disease control as compared to pest control, disease
control separately, such difference was not noticed in respect of second
sowing. The relation between weather elements and pest and disease incidence
was established through correlation and regression.
Forecasting NEM rainfall (SCF) and assessing its validity with real
From the rainfall records of
different stations of Tamil Nadu. The El-Nino years rainfall data alone were
separated and analysed.
South west monsoon:
Analyses of long term average of South west
monsoon rainfall during El-Nino years revealed that during El-Nino years, in
general the amount of rainfall decreases when com-pared to the South west
monsoon normal rainfall of all years. Only North eastern parts of Tamil Nadu
received more than 400 mm of rainfall in SWM season during El-Nino years.
North east monsoon:
Analyses of long-term average of North east
monsoon rainfall during El-Nino years revealed that in many places, the
quantum of rainfall increased during the El-Nino all the places in Tamil
Nadu received more than 300 mm of rainfall during NEM. Coimbatore, Erode and
Salem districts received 300 – 400 mm of rainfall. Southern districts
received 400-500 mm rainfall and the places along the coastal line received
more than 600 mm rainfall. By employing Australian Rainman software seasonal
climate forecast was developed for Southwest monsoon and Northeast monsoon
2001 for different centers and communicated. Informations are given with
Validity of medium
range weather forecasting under farm situations
highest accuracy in rainfall prediction was observed in the month of March,
2001 (96.3%) followed by February, 2001 (95.7) and January, 2001 (84.2%).
Lower RMSE values indicate better predictability. Lower RMSE values were
observed for January, February and March, 2001 indicating better prediction.
Higher ratio score indicate good prediction. Ratio score was >0.8 for the
months December, 2000 and from January to March 2001. Seasonal analysis of
rainfall data indicate that the prediction was better in Cold Weather
Period, 2001 followed by Hot Weather Period, 2001. North East Monsoon, 2000
and South West Monsoon, 2000.
of maximum temperature indicate that in all the months the prediction was
correct and usable for > 70% of the occasions except June and July, 2000.
All the months showed lesser RMSE values indicating the effectiveness of the
predicted data. Correlation between the predicted and observed data
indicated that the correlation values were more than 0.4 for all the months
except June, July, December, 2000 and for March, May and June, 2001.
minimum temperature indicated that in all the month the prediction was
correct and usable for > 80% of the occasions except September, 2000
January, 2001. All the months showed lesser RMSE values indicating the
effectiveness of the predicted data. Correlation between the predicted and
observed data indicated that the correlation values were comparatively lower
in June-September, 2000 and in January and May, 2001.
Maximum wind speed was
predicted and observed during the month of July 1999, predicted wind speed
was cent per cent correct and usable during February and March, 2000. Except
in May and June, 2000, prediction of wind speed was comparatively
satisfactory. Seasonal analysis of wind speed indicated the forecast
accuracy was higher during CWP, followed by NEM, HWP and then SWM. In
general prediction of wind speed was correct and usable for > 80% in all the
seasons except SWM.
Month-wise analysis of
wind direction indicated that the prediction of wind direction was not good
during the months between February and May, 2000 as well as during October,
1999. Correlation analysis indicated that during November and December,
1999, the correlation value between the predicted and observed wind speed
was >0.9. Seasonal analysis of wind direction indicated that during NEM and
SWM, the prediction was satisfactory as compared to the other two seasons.
– A viable predictor of Tamil Nadu Seasonal rainfall
The impact of climate variability on
agriculture is large, particularly in those countries impacted by the El
Nino / Southern Oscillation (ENSO) phenomenon such as Australia, India, Indonesia and Africa. An attempt was made to document the relationship
between the ENSO and rainfall of different locations of Tamil Nadu and using
this relationship monsoon rainfall was forecasted and verified. The results
are summarized below:
The spatial coherence of the
correlations with the Southern Oscillation is encouraging. During SWM, there
is a consistent positive correlation existed in most of the study locations,
in the sense that monsoon rainfall is higher (lower) during a La Niņa (El
Niņo), while there is a consistent negative relationship existed with NEM
rainfall. The sign actually changes from positive to negative between
September and October, so that the individual monthly rainfall for October
is correlated in less magnitude with the SOI. This presents problems for
crop management in Tamil Nadu in the month of October, which is the critical
time for sowing of North east monsoon crop.
NEM Rainfall of most of the
places in Tamil Nadu deviated in positive side during El-Nino years
and on negative side during La-Nina years.
South west monsoon onset was
delayed by 34.7 per cent during El-Nino years, while it was only 13.3 per
cent during La-Nina years. During 80 per cent of the La-Nina years, the
monsoon onset was on normal date.
In 87.1 per cent of the El-Nino
years and in 90.2 per cent of the normal years, the North east monsoon onset
was either early or normal. During El-Nino year, farmers of Tamil Nadu can
take up pre-monsoon sowing during NEM period to utilize the full benefit of
Both El-Nino and La-Nina had
good influence over withdrawal of NE monsoon favourably. More than 95 % of
the El-Nino and La-Nina years had either normal or late withdrawal which was
favourable for agriculture and the crops with escape from the terminal
Under El-Nino situation, the
mean length of growing period was 21 weeks. Hence, if the expected
situation is an El-Nino year, farmers can go in for more water requiring
long duration crops. During La-Nina years, although the length of growing
period was more, the crop would suffer due to intermittent dry spell, as
there were only four wet spell weeks and nine dry spell weeks with in the
growing period. In normal years, the growing period registered was 16 weeks
and a medium duration crop may be grown with out any risk under normal years
by providing necessary drainage facilities.
The seasonal rainfall forecast
accuracy ranged from 47.8 to 85.7 % over different seasons.
ASSESSMENT OF CLIMATE
CHANGE IMPACTS ON IRRIGATED AND RAINFED CROP PRODUCTION SYSTEMS
A study on assessment of climate
change impacts on cropping systems in southern India has been undertaken.
Climate change scenarios were developed by following two methods (i) fixed
climate change scenario and (ii) daily outputs of a Regional Climate Models
(HadRM2). Validated crop models were parameterized for current management
simulated climate by HadRM2 under control (CTL) was compared with observed
climate (base line) for past three decades to understand the likely pattern
of current climate in future (2041-2060) with 1990 GHG emission scenario.
The temperature predictions are very close to current observations. The
simulated annual rainfall under CTL was consistently lower by 16.8% compared
to current observed rainfall. The difference in rainfall might be
unimportant for irrigated rice crop performance, but will have major effect
on rainfed crops. The future climate change scenario (GHG) of HadRM2 showed
increase in solar radiation, maximum temperature, and minimum temperature by
0.35 MJ/m2, 3.4° C and 3.6° C, respectively and decline in
rainfall by 9.5% over control (CTL), corresponding to the period 2041-2060.
The temperature scenario projected by the model is higher by 1.5° C greater
than the pessimistic scenario of earlier reports for south Asia. This
uncertainty in temperature could produce a larger difference in impact
assessment and needs careful interpretation.
based systems of southern India exhibited greater probability of yield
reduction under future climate change scenario with temperature and CO2
increments and HadRM2 model projections under GHG scenario. The average
decline in rice yield is –8.4% and -7.6% for the first (Jun-Sep) and second
season rice (Oct-Jan/Feb) of double crop systems, while the average
reduction for single crop rice (Sep-Dec/Jan) system is lowest with -3.7%.
Impact of climate change simulated by HadRM2 has revealed that the rice
yield reduction under GHG scenario ranges from 370 kg to 783 kg/ha with
current level of management. Delay in planting of first season rice by a
month (July planting) reduced the rate of yield decline. However, delayed
planting of first rice by a month will have greater overlap with the
subsequent seasons, making the options very difficult. The economic
inequality gap widens among the farmers due to varied level of management
under future climate change. Farmers have already exploited the production
potential by shifting the time of planting, leaving very little scope for
change in practice. Researching for high temperature tolerant and
drought resistant rice verities might be the better adaptation option.