Analysis of the atmospheric parameters during recent floods in
Jammu and Kashmir using satellite data: A case study
Abhisek Das and Charu Singh
Marine and Atmospheric Sciences Department,IIRS, Dehradun. India
Email id: iabhisekdas@gmail.com
KEY WORDS: INSAT 3D, IMR, merged Satellite-gauge data, floods,OLR,KALPANA-1
ABSTRACT:
Using INSAT-3D 3 hourly IMR product (0.25 ° spatial resolution)and daily merged satellite-gauge (NCMRWF) (Mitra et
al,2009,2013) rainfall product, potentiality of capturing accurate rainfall has been analysed by image generation for an event of
torrential rainfall throughout the first week of September,2014 over Jammu and Kashmir region. The Local weather stations have
recorded approximately 156.7 mm amount of rain fall in a day during the flood week in some parts of the flood-affected region
whereas on that day INSAT-3D satellite product IMR has not produced any rainfall value above than 60 mm and the other daily
merged satellite-gauge rainfall data gridded at 0.5 x 0.5 degree has underperformed in capturing the accurate amount of rainfall
over that region during first week of September. For validation purpose rainfall images have been generated for 2 nd September,
data of 3 hourly IMR product have been added to get the daily accumulated rainfall and the total rainfall value comes up about
133.44 mm whereas daily merged gridded (NCMWRF) product has received maximum rainfall of about 115.14 mm on that day.
Both the rainfall products have failed to capture the accurate rainfall over Jammu and Kashmir region during the first week of
September where local weather stations have recorded high rainfall which was eight times higher than the normal rainfall as
compared to the last few years but atmospheric parameter OLR,UTH have evidenced formation of convective system over that
region. Technique using multispectral infrared channel to estimate actual rainfall has shown the inability to capture accurate
rainfall and daily rainfall gridded merged product work accurately for large scale atmospheric phenomena. Incorporation of raingauge data to IMR data will enhance the satellite rainfall information and it can be used as input to monitor the development of
heavy rainfall event and would provide a pathway for now-casting of such extremes of weather.
INTRODUCTION:
Flood forecasting is very crucial in mountainous region
because short heavy rainfall causes a fast, voluminous stream
in the river which causes flood over land. Heavy rainfall in
the first week of September is the major reason of disastrous
flood. As the rainfall is one of the primary reasons of flood,
Satellite data is the only source of information on rainfall
estimation with large ground coverage and higher temporal
coverage in comparison to rain-gauge coverage. Indian
geostationary satellite INSAT-3D captures information on
precipitation using visible, infrared and water vapor channel
using IMSRA(IMR) technique. IMSRA(IMR) is a technique
technique of combining microwave and IR measurement.
Microwave measurement is more accurate in terms of
measuring rain rate direct from rain drops where IR technique
measure cloud top brightness temperature to give rainfall
estimation. Microwave technique gives accurate estimation of
rainfall over ocean as compared to estimate over land owing
to different emissivity of land surfaces. Precipitation
algorithms based on single satellite infrared (IR) channel data
are indirectly inferred from cloud top temperatures and have
limited application in the mid-latitudes, due to the difficulty
of delineating rain and no rain clouds(Apostolos Giannakos et
al). Rainfall estimation models tend to overestimate
precipitation because they are affected by the problem of
rain/no rain clouds discrimination.INSAT-3D satellite
produces IMR product at .25 degree spatial resolution with 3
hourly temporal resolution using visible and infrared channel.
IMSRA uses a cloud classification technique(Roca et al 2002)
followed by TRMM-PR and Kalpana-1 IR, this technique
gives better performance than GPI and MGPI(Mishra et
al2009).Deep convective clouds absorb outgoing long-wave
radiation coming from the earth, so where cloud
forms satellite captures less value of OLR and higher value
where cloud does not absorb OLR. Global map of OLR gives
information on temperature, humidity and cloudiness of the
atmosphere and possibility of rainfall over those regions.
Gridded daily Indian rainfall dataset at 1°x1°
latitude/longitude resolution has been used to find any
agreement with INSAT-3D IMR data set. The merged satellite
data combines TRMM TMPA rainfall estimates with IMD
gridded data of gauge information which is better for
delineating the aspect of large spatial-temporal scale
phenomena. In this study two products of rainfall and two
other atmospheric parameter have been plotted during very
high rainfall occurrence throughout the first week of the flood
event.
between
40°N-40°S
and
40°E-120°E.(
http://www.imdpune.gov.in/ne_monsoon/ne_index.html)
UTH(Upper Tropospheric Humidity)
Upper Tropospheric Humidity (UTH) calculated from
INSAT-3D IMAGER is an estimate of the mean relative
umidity of the atmosphere between approximately 600 hPa
and 300 hPa. UTH is basically a measure of weighted mean of
relative humidity according to the weighting function of the
water vapor channel. The UTH data at .5°x.5° spatial
resolution is available on MOSDAC website. This parameter
gives information on formation of any cloud in the geographic
domain if saturation
level
reaches
100%.(http://www.mosdac.gov).
DATA USED
METHODOLOGY
INSAT-3D IMR Data
INSAT-3D satellite uses visible,IR and water vapor channel
and carries multi-spectral Imager(optical radiometer) capable
of generating the images of the earth in six wavelength bands
significant for meteorological observations.IMR data is
produced using multispectral rainfall algorithm daily, weekly
and
monthly
and
generated
in,
HDF
format(http://www.mosdac.gov.in/login.jsp)
OLR Data
Outgoing Long wave Radiations is estimated by utilizing
infrared and water vapor radiances of very high resolution
radiometer(VHRR) instrument onboard Kalpana-1 satellite
stationed at 74° .OLR data are available at three hour
intervals(i.e. 00,03,..,21 UTC) starting from May 2004 over
the Indian region( 40° S-40°N,25°E-125°E) in regular
latitude-longitude grid of resolution 0.25X0.25 degrees.(
http://www.mosdac.gov.in/login.jsp).
Daily Gridded Merged Rainfall Data
This data set merges TRMM(Tropical rain measurement
mission ) TMPA with IMD gauge data of 0.50x0.50 grid at
real-time. The data set is available at 1°x1° spatial resolution
from 1998 to 2012..An algorithm is used to merge TRMM
TMPA with rain gauge –captured precipitation value to
estimate rainfall in monsoon season. This data set is mainly
useful for analyzing the behaviors of monsoon system of large
spatial scale. Inclusion of rain-gauge data corrects the satellite
data and it also enhances satellite rainfall estimation
data(Mitra et. al).The geographic domain of the data set is
.
All the data sets are plotted and are visualized for whole
Indian region. The data set are subset for 60°-100° E and 0°40° N geographic region.As the rainfall occurred for first four
days at the beginning September. IMR product, daily gridded
daily rainfall and OLR data are plotted for those days(1st Sep4th Sep).IMR L3 data is converted into gridded data from
tabular data. As for a particular day data is available at three
hourly interval, total rainfall is calculated by adding all the
precipitation estimates for every location to find comparable
result between INSAT-3D IMR and daily gridded
rainfall(NCMRWF).Images of OLR emission have been
compared with IMR-estimated rainfall to better understand the
relationship between low radiance value indicating formation
of deep convective cloud and retrieval of precipitation
information.
RESULTS AND DISCUSSION
Three hourly rainfall images generated using INSAT-3d
satellite’s IMR product has not captured any information on
heavy precipitation over the study region during flood(Figure1). The IMD rates precipitation between 64.4 mm and 124.4
mm as heavy rainfall, while precipitation between 124.5 mm
and 244.4 mm is rated as very heavy rainfall. More than 244.4
mm is recorded as extremely heavy rainfall. Jammu and
Kashmir has received 558 mm of rain in the June-September
period, as against the normal 477.4 mm.Three hourly images
produced using IMR data for 4th September has recorded
highest rainfall of 32 mm and at 1515 GMT some part of
J&K region has received 26.2 mm rainfall according to the
satellite estimate. This amount is considerably less than the
actual amount of rainfall recorded by rain gauges
Figure: 1 Three hourly rainfall estimate by INSAT-3D IMR product on 4th of September The color bar indicates rainfall (mm)
In figure-2 daily total rainfall estimated using daily gridded
merged rainfall over the specified geographic region has been
represented. This product estimated very low amount of
rainfall(21 mm) on 2nd of September, on this day J&k region
received heavy rainfall above 60 mm.There is no record of
rainfall estimate greater than 50 mm during heavy-rainfall
over that region.INSAT-3D IMR and daily rainfall gridded
product have produced almost produced congruent images in
terms of high amount of rainfall(mm) of about 120 mm over
Bay of Bengal region but NCMRWF gridded data has not
recorded rainfall occurrence over region off Maharastra,
Gujrat coast.
Figure-2 : Total rainfall (mm) images generated using daily merged gridded satellite-rain gauge data(NCMRWF) from 1st to 4th
September. J&K witnessed heavy rainfall for these four days. The color bar indicates rain intensity in mm per day.
Figure-3: Total rainfall over South Asian region. Images generated using daily-gridded data of NCMWRF and INSAT-3D
IMR for 2nd September,2014 .The colorbar indicates rainfall in mm.
Figure -4 : Total rainfall captured by Insat-3d satellite and Outgoing longwave radiation measured by KALPANA-1 satellite on
3rd and 4th september. Satellite recorded radiation around 160 w/m² over flooded region of Kashmir and total rainfall estimation is
around 40 mm.The colorbar of the OLR image indicates radiance(W/m^2) and 2 nd colorbar indicates rainfall(mm).
INSAT-3D IMR product and OLR parameter have shown very
good aggrement in providing the information of formation of
precipitable cloud over J&K region on 4th of September.IMR
product has estimated rainfall of the amount of about 40 mm
for the region which has concurred with the record of low
radinace value of 160 watt/m^2.Over that region thick
precipitable cloud formed which absorbed outgoing longwave
radiation and hence has produced low value compared to
radiance value coming from the sea surface.
UTH(upper tropospheric humidity)also concords with OLR
result.White pixel in the figure 5 indicates UTH to have
reached 100% humidty and clouds are visible over Jammu and
Kashmir region on 4th of September.During the first week of
heavy precipitation over Jammu and Kashmir,Satellite has
retrived rainfall information on 4th of September and daily
gridded ranfall merged product has underperformed in
estimating rainfall over heavily rainfall-occurred region.
CONCLUSION
Figure-5. This images shows the UTH(upper tropospheric
humidity) between 300-700 hpa on 4th September
According to the information on rainfall recorded by
traditional rain-gauges of IMD,rainfall more than 64 mm is
considered heavy rainfall. In this study satellite-estimated
precipitation estimate pales in comparison to the rainfall
recorded by rain-gauges. Both the satellite data and daily
gridded merged rain gauge data have underperformed in
capturing actual rainfall on the ground. Daily gridded rainfall
data is more accurate in analyzing the spatial distribution of
large spatial-temporal scale phenomena but in case of detection
of convective cells over short spatial scale this data product has
considerably underperformed and sometimes satellite does not
retrieve correct radiance value owing to warm cloud formation.
Other atmospheric parameter like UTH,OLR are important
precursor to the event of potential rainfall over a particular
region. Hourly rainfall product estimated using passive and
active remote sensing in combination would be a better option
to detect rainfall over land.
Sandeep & Frode Stordal et.al.Use of daily outgoing longwave
radiation (OLR) data in detecting precipitation extremes in the
tropics. IEEE Geoscience and Remote Sensing Letters.
The present work is a part of EOAM and authors thankfully
ISSN 1545-598X. 4(6), s 570- 578
acknowledge the support & encouragement provided by Head
MASD, Group director ER & SS group, Director IIRS. We
Satya prakash,Mahesh C,2009.combined use of
thank the MOSDAC data portal for providing the
Indian
microwave and IR data for the study of Indian monsoon
Meteorological Satellite Data and NCMWRF for daily merge
rainfall-2009.ISPRS archives,xxxviii-8\w\3
satellite-gauge gridded data for research purpose.
ACKNOWLEDGEMENT
WEB RESOURCES
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