- Heavier precipitation and longer/more intense droughts are effects of climate change.
- Satellite measurements of greenhouse gases like CO2, CH4, N2O can provide global coverage but require complex retrieval algorithms to account for atmospheric conditions.
- Newer retrieval techniques like using merged fitting windows have improved accuracy for scenes with thin cirrus clouds compared to earlier techniques.
Statistical Model
ii Phonological Model
iii Mechanistic Model
iv Deterministic Model
v Stochastic Model
Dynamic Model
vii Static Model
viii Crop Simulation Models
ix Descriptive Model
x Explanatory Model
contact: dhota3@gmail.com
Statistical Model
ii Phonological Model
iii Mechanistic Model
iv Deterministic Model
v Stochastic Model
Dynamic Model
vii Static Model
viii Crop Simulation Models
ix Descriptive Model
x Explanatory Model
contact: dhota3@gmail.com
It focuses on the breeding objectives in blackgram (Vigna mungo) to enhance its genetic potential for improved yield and quality. The presentation covers key objectives such as increasing yield through traits like pod number and length, developing resistance against diseases and abiotic stresses, enhancing nutritional quality, and improving agronomic traits. By incorporating advanced breeding techniques and genetic markers, breeders aim to develop high-yielding blackgram varieties that are resilient, disease-resistant, and nutritionally rich, thereby contributing to sustainable agriculture and improved food security.
The portion of a plant left in the field after harvest of the crop that is (straw, stalks, stems, leaves, roots) not used domestically or sold commercially”. The non – economical plant parts that are left in the field after harvest and remains that are generated from packing sheds or that are discarded during crop processing. Organic recycling has to play a key role in achieving sustainability in agricultural production. Multipurpose uses of crop residue include, but are not limited to, animal feeding, soil mulching, bio-manure, thatching of rural homes and fuel for domestic and industrial use. Thus, crop residues are of tremendous value to the farmers. Crop residue benefit the soil physically, chemically as well as biologically.
The greenhouse effect is a process by which thermal radiation from a planetary surface is absorbed by atmospheric greenhouse gases, and is re-radiated in all directions
IMPACTS OF CLIMATE CHANGE ON AGRICULTURE AND ALLIED.pptxSGowriShankar5
The Earth's climate has varied vastly in the history. Climate change is the change that can be attributed directly or laterally to mortal exertion that alters the composition of the global atmosphere and which is in addition to natural climate variability observed over similar time ages. The climate sensitivity of agriculture is uncertain, as there is regional variation in rainfall, temperature, crops and cropping systems, soils and management practices. Increase in water and air pollution causing migration of birds and animals as well as decrease in drinking water availability. So, Changes occurred in flowering and fruiting time of crops causing scarcity of fodder in area was affected most impact on Climate Change. The crop losses may increase if the predicted climate change increases the climate variability. Climate change will have its impact on the particulars like Vulnerability to Extreme Events, Impacts on Coastal Areas, Impacts on Biodiversity, Impacts on Pest, Impact of Climate Change on Disease and Crop Loss. The intermittent famines hang seriously the livelihood of billions of people who depend on land for utmost of their requirements. Among the greenhouse effects, CO2 is the predominant gas leading to global warming as it traps long surge radiation and emits it back to the earth surface. The global warming is nothing but heating of surface atmosphere due to emission of greenhouse gases, thereby increasing global atmospheric temperature over a long period of time. There is strong evidence of increase in average global air and ocean temperatures, widespread melting of snow and ice, and rising of average global sea levels. The policies and the mission should ensure the Sustainability of the agricultural development. The need of the hour is strengthening the agricultural policies and programme to address the issues related to impact of climate change.
Keyword: Climate change, Global warming, Impact in Agriculture.
Carbon Farming, A Solution to Climate Change.pptxNaveen Prasath
Global warming and climate change refer to an increase in average global temperatures over a very long period of time. Natural events and human activities are believed to be contributing to an increase in average global temperatures, This is caused primarily by increases in “greenhouse” gases such as Carbon Dioxide (CO2).
Indicators
Global Green House Gas emission
Atmospheric concentration of green house gases
Change in Temperature pattern
Change in precipitation pattern
Heat related deaths
Melting of Ice
Rise in sea level
Affecting crop production
Green house gases released by power plant, automobiles, deforestation etc
According to IPCC WG AR-5 the Earth’s average temperature has increased by one degree Fahrenheit to its highest level in the past four decade – believed to be the fastest rise in a thousand years.
Research found that if emissions of heat-trapping carbon emissions aren’t reduced, average surface temperatures could increase by 3 to 10 degrees Fahrenheit by the end of the century.
It focuses on the breeding objectives in blackgram (Vigna mungo) to enhance its genetic potential for improved yield and quality. The presentation covers key objectives such as increasing yield through traits like pod number and length, developing resistance against diseases and abiotic stresses, enhancing nutritional quality, and improving agronomic traits. By incorporating advanced breeding techniques and genetic markers, breeders aim to develop high-yielding blackgram varieties that are resilient, disease-resistant, and nutritionally rich, thereby contributing to sustainable agriculture and improved food security.
The portion of a plant left in the field after harvest of the crop that is (straw, stalks, stems, leaves, roots) not used domestically or sold commercially”. The non – economical plant parts that are left in the field after harvest and remains that are generated from packing sheds or that are discarded during crop processing. Organic recycling has to play a key role in achieving sustainability in agricultural production. Multipurpose uses of crop residue include, but are not limited to, animal feeding, soil mulching, bio-manure, thatching of rural homes and fuel for domestic and industrial use. Thus, crop residues are of tremendous value to the farmers. Crop residue benefit the soil physically, chemically as well as biologically.
The greenhouse effect is a process by which thermal radiation from a planetary surface is absorbed by atmospheric greenhouse gases, and is re-radiated in all directions
IMPACTS OF CLIMATE CHANGE ON AGRICULTURE AND ALLIED.pptxSGowriShankar5
The Earth's climate has varied vastly in the history. Climate change is the change that can be attributed directly or laterally to mortal exertion that alters the composition of the global atmosphere and which is in addition to natural climate variability observed over similar time ages. The climate sensitivity of agriculture is uncertain, as there is regional variation in rainfall, temperature, crops and cropping systems, soils and management practices. Increase in water and air pollution causing migration of birds and animals as well as decrease in drinking water availability. So, Changes occurred in flowering and fruiting time of crops causing scarcity of fodder in area was affected most impact on Climate Change. The crop losses may increase if the predicted climate change increases the climate variability. Climate change will have its impact on the particulars like Vulnerability to Extreme Events, Impacts on Coastal Areas, Impacts on Biodiversity, Impacts on Pest, Impact of Climate Change on Disease and Crop Loss. The intermittent famines hang seriously the livelihood of billions of people who depend on land for utmost of their requirements. Among the greenhouse effects, CO2 is the predominant gas leading to global warming as it traps long surge radiation and emits it back to the earth surface. The global warming is nothing but heating of surface atmosphere due to emission of greenhouse gases, thereby increasing global atmospheric temperature over a long period of time. There is strong evidence of increase in average global air and ocean temperatures, widespread melting of snow and ice, and rising of average global sea levels. The policies and the mission should ensure the Sustainability of the agricultural development. The need of the hour is strengthening the agricultural policies and programme to address the issues related to impact of climate change.
Keyword: Climate change, Global warming, Impact in Agriculture.
Carbon Farming, A Solution to Climate Change.pptxNaveen Prasath
Global warming and climate change refer to an increase in average global temperatures over a very long period of time. Natural events and human activities are believed to be contributing to an increase in average global temperatures, This is caused primarily by increases in “greenhouse” gases such as Carbon Dioxide (CO2).
Indicators
Global Green House Gas emission
Atmospheric concentration of green house gases
Change in Temperature pattern
Change in precipitation pattern
Heat related deaths
Melting of Ice
Rise in sea level
Affecting crop production
Green house gases released by power plant, automobiles, deforestation etc
According to IPCC WG AR-5 the Earth’s average temperature has increased by one degree Fahrenheit to its highest level in the past four decade – believed to be the fastest rise in a thousand years.
Research found that if emissions of heat-trapping carbon emissions aren’t reduced, average surface temperatures could increase by 3 to 10 degrees Fahrenheit by the end of the century.
Climate Change:
Definitions: USA EPA!
Climate change refers to any significant change in the measures of climate lasting for an extended period of time. In other words, climate change includes major changes in temperature, precipitation, or wind patterns, among other effects, that occur over several decades or longer.
History:
20 hottest years in the last and present century occurred after 1980.
KYOTO PROTOCOL
On February 2005 KYOTO PROTOCOL came into force in most of the 169 countries of the world.
It was decided that by 2010 GHG emissions would be reduced by 5.2% below 1990 level.
Causes:
Constantly emitting GHGs are the prime cause of it.
1.Water vapor (H. 2O)
2.Carbon dioxide (CO2)
3.Methane (CH4)
4.Nitrous oxide (N2O)
5.Ozone (O3)
6.Chloro-fluorocarbons (CFCs)
Effects:
Ill health of mother earth.
Future:
A darker future awaits for us if we don't take rationale steps right now.
This presentation examines global public opinion about climate change. Using the Pew Research Center’s spring 2015 Global Attitudes survey, issues such as concern about climate change and support for action on climate change are addressed. It is based on 45,435 face-to-face and telephone interviews in 40 countries with adults 18 and older conducted from March 25 to May 27, 2015.
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BASIC UNDERSTANDING OF FIGURE..
FOLLOW THE REFERENCE BOOK FOR MORE DETAIL.
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The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
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5. GLOBAL AVERAGES OF THE CONCENTRATIONS OF CARBON DIOXIDE,
METHANE, NITROUS OXIDE, CFC-12 AND CFC-11
These gases account for about 97% of the direct warming effect of the long-lived
greenhouse gases since 1750. The remaining 3% is contributed by an assortment
of 10 minor halogen gases. ( Source NOAA, Annual Greenhouse Gas Index )
CO2
N2O
CH4 CFCs
6. Retrieval & Monitoring of AtmosphericRetrieval & Monitoring of Atmospheric
Green House Gases (GHGs) throughGreen House Gases (GHGs) through
remote sensingremote sensing
Debasish Chakraborty
Roll No. – 4843
Division of Agricultural Physics
7. RETRIEVAL: To find or extract stored information.
MONITORING: To watch & check over a period of time in order
to see how any phenomena develops/changes so that one can take
necessary action.
So, monitoring of Green House Gases(GHGs) over the
globe is a spatiotemporal property.
GHGs Measurement
Conventional
Remote sensing
8. Standard type of technique to measure GHGs
VIALS
GC analysis
ECD, FID
detectors
Gas storage
Gas accumulation over time
Closed chamber – Gas Chromatographic analysis,
IRGA
9. Advantage:
Technique is simple
Can be handled with short training
Very accurate
Limitation:
Limited spatial distribution
Sampling error
Closed chamber – Gas Chromatographic analysis,
IRGA
10. SATELLITE MEASUREMENTS
DVANTAGE:
Provide Global coverage
High temporal resolution
Data with sufficient precision is becoming available
- Multi-purpose missions-SCIAMACHY,AIRS
-Missions dedicated to GHGs-GOSAT/JAXA ; launched on jan,200
LIMITATION:
Absolute measurement of physical parameters
Several disturbances (sensor cal/val, clouds, aerosol etc)
Retrieval needs complex algorithms
Asks for expertise
11. Ground Based Project :
FLUXNET
LIMITATION
DISCONTINUITY OF
MEASUREMENTS
COORDINATION BETWEEN
STATIONS
UPSCALING METHODS
LIMITED AREA COVERAGE
SATELLITE MONITORING COMBINED WITH THIS
GROUND BASED PROJECTS CAN BE A BETTER
OPTION
13. CURRENTLY WORKING
SATELLITES
MID & THERMAL INFRARED REGION(TIR & MIR)
HIRS(2002) - NOAA
AIRS(2002) - NASA
IASI(2006) - EUMETSAT
DETECTION
Thermal radiation emitted from surface & atmosphere
(3.6 to 15µm)
ADVANTAGE:
Day & night measurement is possible
DISADVANTAGE:
Lack of sensitivity in lower troposphere
14. CURRENTLY WORKING SATELLITES
UV/VIS/NIR/SWIR REGION
SCIAMACHY(2002) - ESA
TANSO(2009) - JAXA
OCO(2009) - NASA
DETECTION
Reflected, backscattered, transmitted & emitted from
surface & atmosphere (240 to 2400 nm)
DISADVANTAGE:
Restricted to day only
ADVANTAGE:
Sensitivity constant with height
& maximum near the surface
16. POSSIBLE ERROR SOURCES
EVALUATED IN ADVANCE:
Spectroscopic parameters
Solar spectra
CORRECTED BY ADDITIONAL
INFORMATION
Cloud covered scene
Aerosol covered scene
Surface elevation
Surface spectra
Water vapor
Temperature
Cirrus effect can be cancelled by 760 nm(O2
band) and 2000nm (H2O saturated spectral
region).
17. MEASURED DATA FILTERING FOR NOISE REMOVAL
FILTERING
ITEMS
Solar Zenith
Angle
Cloud
Estimation
Aerosol at high
Altitudes
Filtered
spectra
Aerosol Transport
Model
(ex.SPRINTARS)
Cloud
Input
Spectra
18. ATMOSPHERE
R T MODEL
INITIAL CONSTITUENTS
TEMPERATURE
PRESSURE
ALBEDO
DATA PROCESSING
SYNTHESIZED
SPECTRA
FILTERED SPECTRA
Yokota et. al
20. CASE STUDY-I
STUDY AREA: Boreal forests (Novosibirsk region) & the region
of Surgut
SENSOR USED: AIRS
AMSU-A
RADIATIVE TRANSFER MODEL: SARTA
RUSSIAN METEOROLOGY AND HYDROLOGY Vol. 34 No. 4 2009
21. 1. SELECTION OF C02 SENSITIVE CHANNELS
CO2-sensitive channels at low sensitivity to
interfering factors
Nine LW-channels in the spectral range of 699–
705 cm–1
Six SW-channels in the spectral range of 1939–
2017 cm–1
THE STUDY HAS TWO PARTS:
∆TB(i) = δTB(i) +δqH2O TB(i) + δqO3TB(i) + δqTB(i) + . . . . + ξi
22. 2. AIRS DATA INVERSION
Analysis of satellite data to sample cloud free measurement or
measurements reduced to cloud cleared conditions
(http://disc.gsfc.nasa/AIRS/data)
Inverse problem in respect to Xco2 is solved numerically using the
Gauss-Newton iteration algorithm, two independent estimates of
Xco2 (LW) & Xco2 (SW) are estimated by AIRS data
Sampling of estimates Xco2(LW) & Xco2(SW) derived for time interval
and the sounding area are subject to spatiotemporal filtering
The results of aircraft CO2measurements (spatially coincident and
quasi- synchronous with satellite )at different altitudes are used for
comparison
The systematic biases is calculated by -
δ(ᾳ) = [TB
obs
(ᾳ) - TB
calc
(ᾳ)], ᾳ= 1, . . . ., n,
23. The standard deviations (SD) of Xco2(sat) from the aircraft observations
at altitudes 7 and 3 km were calculated to estimate the errors of the
results of the satellite sounding. The SD are 1.5 and 1.2 ppm compared
to the aircraft CO2 observations at altitudes 7 and 3 km, respectively.
Fig: comparison of satellite(2) and aircraft data of 7000 m (1) & 3000 m (3)
RESULT COMPARISON
Novosibirsk
Surgut
24. CASE STUDY-II
STUDIED GAS: Methane(CH4)
SENSOR USED: SCIAMACHY (Channel 8 – 2260 to 2385 nm )
RADIATIVE TRANSFER MODEL: SCIATRAN
RADIATIVE TRANSFER ALGORITHM: WFM-DOAS
Atmos. Chem. Phys. Discussion., 4,2004
25. THE WFM-DOAS RETRIEVAL ALGORITHM
Based on fitting a linearised radiative transfer model Ii
mod
plus a low order polynomial Pi to the algorithm of the ratio
of a measured nadir radiance & solar irradiance spectrum,i.e.
observed sun-normalised radiance Ii
obs
.
The WFM-DOAS equation can be written as-
|In Ii
obs
(Vt
) – [ In Ii
mod
(V) + ∑δ Ii
mod
/ δvj /( vj – vj ) + Pi (am )]|2
= |RESi|2
→min
The fit parameters are the desired “trace gas vertical column Vj”
and the polynomial coefficient am”.
Fit parameters are determined by LEAST SQUARE method
PRINCIPLE: Differential detection of radiance in gaseous
absorption channels with respect to neighbouring
atmospheric transparent spectral channels (not influenced
by gas) ,to detect the conce. Of desired gas.
26. Parameters:
Cloud condition- UV PMD(Polarization Measurement Device)
SCIAMACHY
Standard atmospheric condition-CH4, CO2 current concentration
Tropospheric and stratospheric condition- aerosol
Surface albedo and solar zenith angle
Surface elevation
Water vapour column and temperature profile shift
The reference spectra was generated by-
Radiative transfer model- SCIATRAN
27. WFM-DOAS CH4 VERTICAL COLUMN RETRIEVAL ERROR(A) USING
SIMULATED MEASUERMENTS
ERROR B-TEMPERATURE PROFILE SHIFT is included
RESULT DISCUSSION
28. Tab; Comparison of SCIAMACHY WFM-DOAS v 0.5 with
ground based FTS measurement.
N= no. of SCIAMACHY measurements compared with FTS.
Result And Discussion
29. Fig. Methane column averaged mixing ratios as retrieved from
SCIAMACHY WFM-DOAS V 0.5.
RESULT DISCUSSION
30. APPLICATION
STUDY AREA: Low and mid latitudes of Northern Hemisphere
SENSOR USED: SCIAMACHY (1558 to 1594 nm)
ALGORITHM USED: WFM-DOAS version 1.0
Atmos. Chem. Phys. Discuss.,7,2007
31. ALGORITHM: WFM-DOAS version 1.0
An improved version (Schneising et al., 2007).
The main problems of the previous version WFMDv0.4 (Buchwitz et
al.,) was solved using spectra with improved calibration
Better consideration of surface spectral reflectivity variability
It is no longer required to apply a quite large empirical scaling factor
as was necessary for WFMDv0.4.
QUALITY FILTERING OF SCIAMACHY:
For cloud detection the measured oxygen column(755 to 775 nm) and
PMDs is used.
Ground altitude(pressure) used in simulation by WFM-DOAS increased
above
4.1 km.
To reject ground scenes with strong aerosol contamination, additional
filtration of the SCIAMACHY XCO2 measurements using NASA’s
Absorbing Aerosol Index (AAI) data product from TOMS/ Earthprobe
was done.
Concentration of CO2 can only be retrieved over land , not over sea.
32. Fig. Atmospheric CO2 over the northern hemisphere
during 2003–2005 as retrieved from SCIAMACHY
satellite measurements.
FIRST DIRECT OBSERVATION OF ATMOSPHERIC CO2 IN
YEAR TO YEAR FROM SPACE
33. Fig; Satellite retrieved XCO2 and NOAA ESRL Carbon Tracker global
assimilation system data
Increase in the amplitude of the CO2 seasonal cycle with the increase in
latitude
In the retrieved XCO2 seasonal cycle an error of 2ppm is seen.
ERROR & IT’S CORRECTION:
34. The correction equation is –
DIF=a + b*AMF
Where, DIF=difference between SCIAMACHY &
Carbon Tracker
AMF=1/cos(SZA) + 1/cos(LOS)
where,
AMF=Air mass factor
SZA=Solar zenith angle
LOS=Line of sight scan angle
35. APPLICATION:
STUDY AREA: 50
N to 67.50
S , 54.50
E to 1470
E
SENSOR USED:
SCIAMACHY (Channel 8 – 2259 to 2361 nm) with WFM-DOAS V 0.4
SPOT-VEGETATION
ISPRS Archives XXXVIII-8/W3 Workshop Proceedings: Impact of climate
change on agriculture,2009
36. METHODOLOGY
Global weekly ENVISAT-SCIAMACHY
CH4 conce. (ppbv) data of 2004 &
2005
Global 10 days composite of
SPOT-NDVI products of 2004 &
2005
Computed mean monthly CH4 (ppbv)
Study area was extracted by overlying the region’s boundary
and gridded to 0.50
x 0.50
latitude/longitude grid
Validation using NOAA-
CMDL Global view data
Spatial and temporal
variability over study area
CH4 data covering Kharif
season (May-Oct) for
2004 & 2005
NDVI data covering Kharif
season(May-Oct) for 2004 &
2005
Correlation between CH4 conce. & NDVI during
Kharif season over study area
Computed mean monthly NDVI
37. Fig 1. Temporal and Spatial
Variation of Atmospheric CH4
Concentration Over India
During 2004 – 05
RESULTS:
Fig2. Temporal Variation of
Vegetation Over India
During 2004–05
38. ig 3. Two year kharif season averaged CH4 conce.
Fig 4. Two year kharif season averaged NDVI.
Fig 5. Correlation between CH4 Conc. and
Vegetation During Kharif Season in 2004-05
39. PROBLEM OF THESE STUDIES:
Scattering at aerosol and/or cloud particles remains a major
source of uncertainty for SCIAMACHY XCO2 retrievals
The XCO2 retrieval error may amount to 10% in the
presence of mineral dust aerosols.
Houweling et al. (2005)
The thin scattering layer with an optical thickness of 0.03
in the upper troposphere can introduce XCO2 uncertainties
of up to several percent. Schneising
et al. (2008)
Unfortunately, thin clouds with optical thicknesses below 0.1
cannot easily be detected within nadir measurements in the
visible and near infrared spectral region.
Reuter et al., 2009; Rodriguez et al.
(2007).
41. Algorithm: Merged fit windows approach.
Radiative transfer model: SCIATRAN 3.0
Atmos. Meas. Tech., 3, 209–232, 2010
42. The measurement vector y consists of SCIAMACHY
sun-normalized radiances of two merged fit windows
concatenating the measurements in the CO2 and O2 fit
window.
= ( , ) +y F x b ԑ
X = state vector
b = parameter vector
&, =ԑ error
The information about these parameters comes mainly from the
O2 measurements and is made available in the CO2 band by the merged
fit windows approach..
43. The accuracy for scenes with optically thin cirrus clouds was
drastically enhanced compared to a WFM-DOAS like retrieval.
At solar zenith angles of 400
, the presence of ice clouds with
optical thicknesses in the range of 0.01 to 1.00 contributed with
less than 0.5 ppm to the systematic absolute XCO2 error if a
perfect forward model is assumed.
RESULTS:
44. Conclusions:
Green House Gases (GHGs) can be measured with good
accuracy from satellite data if proper algorithms are
applied
Through inverse modeling of measured GHGs we can
know in detail about their sources and sinks
Further development in understanding about different
factors, their interactions influencing the GHG retrieval
and improvement in mathematical methods will surely be
able to predict GHGs with better accuracy
Monitoring of GHGs emitted from agricultural practices
and activities, wetlands over a region can be done with
good accuracy
More intense and longer droughts have been observed over wider areas since the 1970s, particularly in the tropics and subtropics. {3.3} The frequency of heavy precipitation events has increased over most land areas. WG1 {3.8, 3.9} (SPM p.8) It is very likely that hot extremes, heat waves and heavy precipitation events will continue to become more frequent {10.3} and that future tropical cyclones (typhoons and hurricanes) will become more intense. WG1 {9.5, 10.3, 3.8} (SPM p.15)