Monsoon - Science topic

Ákos Bede-Fazekas Thank you for your guideline Sir.

Dear @Sam Nicholson, I'm afraid climate models do not calibrate any parameter. These models are developed considering different physical processes in terms of their equations. The number of physical processes considered, the way in which they are analytically described and also numerically implemented, depends on different factors, including the spatio-temporal discretization of the climate model (i.e. grid dimension, time step length) and the total temporal horizon to be simulated. The evolution of the state variables of climate models depends on different model forcings such as the income radiative flux affecting the modeled system through the physical processes considered by the model (e.g. vapor condensation, evaporation, moisture recycling, etc. ). Therefore, to simulate the expected paleoclimate trends, which are often revealed by different proxies, you should include the corresponding climate forcings in the model, which are supposed to generate such paleoclimate trends.

Dear Sam, I'm afraid climate models do not calibrate any parameter. These models are developed considering different physical processes in terms of their equations. The number of physical processes considered, the way in which they are analytically described and numerically implemented depends on different factors, including the spatio-temporal discretization of the climate model (i.e. grid dimension, time step length) ensuring the numerical convergence of the solution at every time step, and the total temporal horizon to be simulated. The evolution of the state variables of climate models depends on the different model forcings such as the income radiative flux affecting the modeled system through the physical processes considered by the model (e.g. vapor condensation, evaporation, moisture recycling, etc. ). Therefore, to simulate the expected paleoclimate trends, which are often revealed by different proxies, you should include the corresponding climate forcings in the model, which are supposed to generate such paleoclimate trends.

Management of flow and aquifer capacity can reduce the adverse effect

Hello Guillermo,

Thankyou so much for helping me out. It helped me a lot and i compiled the sst regions corresponding to south america monsoon.

these articles can be useful:

I think yes.

There is no exact rule to define the grid spacing on the horizontal, but since your study is on mountainous terrain, I recommend that you run the model with at least one nesting (two domains total). You could simulate with 12 and 4 km or with 9 and 3 km of resolution for the parent domain and the nested domain respectively.

Whether this resolution will affect large-scale systems will depend on the boundaries of the study area. Therefore, it is important that you identify the processes that interact with the study area and delimit correctly.

You should review articles about success stories with the WRF model in your study area or in areas with similar characteristics. In addition, it is always recommended to carry out a sensitivity study of the WRF model with different physical parameters so that you can identify the one that best suits your study area.

Finally, the available computing capacity is also important to consider when defining the resolution to implement with the WRF model.

Thank you so much @Areezo.

Will surely go through your suggestions.

Sher Bahadur Gurung there was a scientific paper i came across and I guess this answers your question please refer to the link shared here with

which shows the details about " Determining bioclimatic space of Himalayan alder for agroforestry systems in Nepal "

A couple of my earliest Researchgate entries and citations may be informative, even though different conditions. Many water quality parameters have influence from flow rate (discharge), and in part often due to rainfall dilution effect, runoff and movement of sediment and other non-point pollutants and nutrients during storms. You may find a hysteresis effect with markedly higher values during rising limb of hydrograph, and lower rates as hydrograph recedes. Geology and groundwater and its chemistry influences contribute to varying degrees as some streams loose water to groundwater, while others gain water inputs from groundwater for substantial periods of time. There are many books and papers on the subject, as well as professional or informational courses. It is not unusual to find these trends. Stream temperature in many locations increases in the summer growing season as more solar radiation, higher temperatures with lower streamflow often combine to elevate temperatures. Streams heavily augmented by groundwater or springflow as well as dense forest cover have substantially less effect than conditions without these benefits. In one of my studies, mountain streams without dense forest cover actually had lower winter temperatures, so forested stream buffers may have a moderating effect on temperature extremes in both summer and winter. It is highly useful to have recording water levels to estimate flow rates with time. A relative moderate expense tool for this is transducer (vented or barometric adjusted unvented). Streams with excessive sediment may contribute to transducer fouling, but properly installed, they can collect high quality data for weeks or months without service. The USGS collects flow data every 15 minutes, and appropriate for your study area. For small catchments, more frequent readings may be needed. A variety of tools or techniques are available to collect samples during storms or more routinely, if ample research funding exists.

Patrice Poyet Thank you so much for your exhaustive reply. my best regards. Franco

Hi Ankur,

there are several methods to find the relation between two variables, the most known is to use regressions of type: linear, power, logarithmic, ...etc, otherwise you find also the new techniques of artificial intelligence to link the two variables, Artificial Neural Networks ANN, ...etc

good luck

Dear Anirudh,

You will find a lot of papers based on the past 2000 yrs of climate history in India. Few of them

1. Yadava and Ramesh 2005: Monsoon reconstruction from radiocarbon-dated tropical Indian speleothems

2. Sinha et al., 2011: The leading mode of Indian Summer Monsoon precipitation variability during the last millennium

3. Sinha et al., 2015: Trends and oscillations in the Indian summer monsoon rainfall over the last two millennia....................................

Important review papers...................

Misra et al., 2019: Holocene climate records from lake sediments in India: Assessment of coherence across climate zones

Dixit and Tandon 2016: Hydroclimatic variability on the Indian subcontinent in the past millennium: Review and assessment

Please also go through the papers from the Himalayan region based on pollens and treen rings. You will get a lot of information.

Take average value of rainfall from nearly located gauging sites

Hi there !

It's very difficult to find a short answer to such a question. But maybe I don't need to.

I would recommend you to look into the latest IPCC reports. While the new version of the main assessment report is only due in April 2021 (AR6 WGI: https://www.ipcc.ch/report/sixth-assessment-report-working-group-i/ ), there is already available plenty of available resources from the fifth assessment report https://www.ipcc.ch/report/ar5/wg1/ and also from the special report on ocean and cryosphere (especially for the high mountain regions) and on the special report on 1.5° of warming ( https://www.ipcc.ch/sr15/ ).

What I find personally very interesting is how the monsoon systems will react to the impact of climate change. While during the holocene, both the Indian and African monsoon systems have decreased in intensity due to the impact of precession, it is not clear yet how they will evolved in a warmer climate.

I hope this helps, it is a lot to read, but the summary for policy makers can maybe already offer you the answer you're looking for. The complete reports are still very useful though !

Cheers,

Mathieu

Hi,

The attached file is printed out by NCL. It is very easy to generate beautiful figures if you add "load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/popRemap.ncl"".

Here is the instruction website "http://www.ncl.ucar.edu/Applications/paleo.shtml ". I hope the NCL can help you.

Zhibo

Rajashekhar Mandla

(PDF) Export of Rice from India: Performance and Determinants

www.researchgate.net › publication › 304710097_Export...

might help ?

Open the *.grd data using ENVI following these steps:

Step 1: Open the file and give parameters e.g. Samples = <no of columns>, Lines = <no. o frows>, Bands = 365, File type ENVI standard, Data type= Floating, Interleave = BSQ.

Step 2: Rotate the image by Angle = 270 and Transpose = Yes

Step 3: Change the Map Info.... Image X: 1, Image Y:1, Proj: Geographic Lat/Lon, Daturm: WGS84, E = 66.5, N = 37.5, X Pixel Size = 0.25 Deg, Y pixel size = 0.25 Deg

Step 4: Change geographic corner coordinates: Point 1: 1 (image X), 1 (Image Y), 37.5 (Lat), 66.5(Lon), Point 2: <no of column>, 1, 37.5, 100.5; Point 3: 1, <no. of rows>, 6.5, 66.5; Point 4: <no. of columns>, <no. of rows>, 6.5, 100.5.

thats it.. enjoy !!

Step 5: copy the *.hdr file and rename it as template.hdr and make a batch file (e.g. rename.bat) with command copy template.hdr <name of the other files> so that all four steps are not to be repeated next time.

In this case basal does is totally wastage specially n case of rice cultivation how will it effect if we planted little earlier so that it will grow well during time of heavy monsoon as we all now that nutrient is blood of land but early it is wasting and farmer are buying fertilizer at high cost.🙄🙄

Please refer to the links below

Best wishes,

Saeed

Well,

Tritium environmental isotopes can be applied with the chloride mixing mechanism.

Regards

You should read the book (Today's Meteorology: An Introduction to Weather, Climate and Environment), Fronts Section

Try to identify the species through one of the sources of diversity of aquatic plants

this will be based on the river stage (darcy law) and the uranium will be moved to and from the river based the hydraulic gradient

hydrus 3d software can model this situation

Kindly go through the attached file. Here you get your expected answer, here methodology is fulfill your demand.

Regards

There are more than 100 drought indices being used/studied worldwide for drought monitoring. You may consider many other indices for more than one parameters like SPEI, TVDI, NDVI, VCI, VHI ETC. Some are ground based and some are satellite based parameters and indices.

The seasonal migration of the intertropical convergence zone (ITCZ) over the latitude of maximum insolation regulates the monsoon circulation. During summer (June to September) ITCZ shifts towards the low pressure area (~23°N) and surface winds bringing large amount of precipitation from SW ocean (Arabian sea) to central India.

In lacustrine sequence, Ti can be used as proxy (tool) to understand the surface runoff from the catchment. Higher Ti concentration means higher surface runoff. High atmospheric rainfall leads to increase in the surface runoff and thus high Ti concentration in sediments.

There are lot of paper, deals with the relation between Ti and monsoon intensity.

1. Haug et al., 2001: southward migration of the intertropical convergence zone through the Holocene.

2. Doberschutz et al., Monsoonal forcing of Holocene paleoenvironmental change on the central Tibetan Plateau inferred using a sediment record from Lake Nam Co (Xizang, China)

3. Mishra et al., 2015, Reconstructed late Quaternary hydrological changes from Lake Tso Moriri, NW Himalaya

Thanks for your recommendations.

Good hydrology models account for soil water content when considering soil runoff. The two models I am familiar with are the curve number model, which using antecedent water content as one of the inputs, and there is usually a table giving suggestions for how to do this. I personally like the Water Erosion Prediction Project (WEPP) model hydrology that does a continuous run, but does a water balance each day. That means that sometimes a less severe storm on a wet soil will generate more runoff than a more severe storm on a dry soil. As the model is run for maybe 50 years, there are many combinations of storm severity and soil water content in that time fram to consider a number of possible conditions that may occur,

Ari Jokimäki Thank you both!

I think, Pre-monsoon because that time land and soil moisture in a moderate condition

You could, for instance, use it to find out which variables are mostly independent of the season which might be interesting in itself. Do you have the access to the meteorological data? Perhaps there are continuous variables associated with the monsoon (wind direction, speed, temperature, humidity, precipitation, etc.) which you could use instead? You could also consider dividing your data into two sub-sets (monsoon and not-monsoon) and running the analysis separately.

If the upper-air circulation patterns as well as the steering winds are studied carefully, it is not so difficult to forecast cyclones in the peninsular India. It may become complex if a 'Col' develops at 300/200 hPa level over the cyclone area. Of course the Coriolis force near the low latitude may have some effect on the intensity and direction of the movement of cyclone. @

Thank you sir.

The following papers may help you.

1. Tariq Masood Ali Khan, Arif Mahmood, Nadeem Faisal, M. M. Rabbani. (2006). “Influence of ENSO on the Southwest Monsoon Rainfall over Pakistan”, in the proceedings of International Roundtable “Understanding and Forecasting of Monsoons (Editor: PNVinayachandran)”, organized by Center for Science Technology of the Non-Aligned and other Developing Countries (NAM S&T) during 21-24 November 2005 held in Indonesia, Published by Daya Publishing House, Delhi. 119-126.

2. Arif Mahmood, Tariq Masood Ali Khan and Nadeem Faisal(2006), Relationship Between El Nino and Summer Monsoon Rainfall over Pakistan, Pakistan Journal of Marine Sciences, 15, 2, 161-178.

3. Arif Mahmood, Tariq Masood Ali Khan, Nadeem Faisal (2004) “Correlation between Multivariate ENSO Index (MEI) and Pakistan’s Summer Rainfall. Pakistan J. of Meteorology, Vol. 1, 2, 53-64.

4. O. P. Singh, Tariq Masood Ali Khan, Md. Sazedur Rahman and Salahuddin (2000) "Summer Monsoon Rainfall over Bangladesh in relation to Multivariate ENSO Index", Mausam, 51, 3, 255-260.

Overall, there is a clear negative correlation between ENSO and the Indian monsoon rainfall in both observations and models and the average correlation is about -0.4. The monsoon therefore weakens on average during El Nino. This is the main driver of seasonal forecasts for the Indian monsoon as ENSO is predictable with quite good skill a few months ahead.

Some of the confusion arises because the strength of the monsoon-ENSO correlation fluctuates from one multi-decadal period to the next. Some studies therefore claim the relationship is 'non-stationary' in time. However, it's important to note that atmospheric chaos will inevitably lead to some of these fluctuations and so the underlying relationship is more constant than observations alone would suggest. This last point is made in the recent paper by Shukla and colleagues:

Hope this helps

Adam

For calculating various hydraulic properties of aquifer systems, viz., transmissivity (T), hydraulic conductivity (K), storage coefficient (S) etc from pumping (aquifer) test which is the standard technique for that. Kindly see here

"Hydrogeological Parameters Calculation "Springer

Also, a graphical method is widely used for that, Please see here

G. Venkata Rao, P. Kalpana, R. Srinivasa Rao "Estimation of Aquifer Properties Using Pumping Tests: Case Study of Pydibhimavaram Industrial Area, Srikakulam, India " World Academy of Science, Engineering and Technology International Journal of Environmental and Ecological Engineering, Vol:9, No:9, 2015 (https://waset.org/publications/10002811/estimation-of-aquifer-properties-using-pumping-tests-case-study-of-pydibhimavaram-industrial-area-srikakulam-india)

Have to verified LHF with surface wind and SST ?

To add up on the answer provided by Ita, the nature of water during wet season can contribute to the variation in pH. For instance if the rainfall is acidic. The nature of flood water entering the system is dependent on the nature of soil and the vegetation cover. Dilution due to increased amount of water in wet season and concentration due to evaporation in drier season can also contribute the variation.

SW monsoon 2017 was weak during August and Sept in North India

Will you please tell for which area are you speaking about? Location of your reservoirs, soil type, average rainfall, rainfall pattern in last 10 years also give idea.

I have no experience with cotton. Have you measured soil nitrogen? Is there perhaps a lack of potassium and/or phosphorous? Can you find a better cultivar that does not grow as tall?

Dear Khunsa, such extreme periods are always advisable to be avoided. It depends upon the repeatibility of spatial variability validated by coefficient of variation over temporal domain...It will also depend upon whether or not , it is crop land. If it is crop land , you can take samples after the harvesting of the crop, but how will you decide the optimum grid size ( means sampling distance in the given field) in order to measure the spatial variability in soil fertility. ..

Dear Sarthak,

I am puzzled by your question because, in the meteorological literature, the acronym 'OLR' stands for 'Outgoing Long-wave Radiation', i.e., the radiation emerging from the planet and lost to space, in the thermal domain. See

This spectral range is largely separate from the 'Solar' domain: the boundaries are somewhat arbitrary, but the effective overlap between these two domains is tiny from an energy point of view.

The monsoon is a large (sub-planetary) scale seasonal dynamic process that involves very many factors, including the differential heating rates over the continents and oceans. Radiation (both solar and thermal) thus plays an important role, but so does thermodynamics and in particular the evaporation from the oceans and the condensation of water vapor in clouds. I don't think that any single process or variable can be held responsible for the onset of the monsoon. For an initial introduction to this topic, see

and for specific information on the Indian monsoon, consult

Michel.

Dibakar Pal Sir, Thank you for your Answer. 

Sir, So many papers are ther to explain the Influence of ENSO. But am specifically concerned about Multivariate ENSO and Methodolgy to interpret the relationship. How to consider the lead-lag duration of ENSO and rainfall for Annual and seasonal. 

Your question is hardly clear, please clarify. Although I agree there is a role of tectonic activity and precipitation variability ( and other factors as well, wind, material, etc)  in the slop dynamics anywhere. 

Thank you Kenneth, yes, my research is based on newspapers and other historical sources (church records), and on fieldwork as well. But I was looking for some information on other places (outside the Iberian Peninsula or the USA), where the snow could have caused damage, just to contextualize my results ... I also think that the effects on the East Coast of the United States hid what happened in other places, thank you very much for your kind answer!

Dear Dr Ray

Please find attached paper.  I hope you will find it useful. 

Plz, see here too..

Thank you Beckline Mukete...

You could also look for data from Satellites such as TRMM (https://trmm.gsfc.nasa.gov) and use time series analysis to develop an statistical distribution and then compare your data with it.

Also more info..

Hi Krishan,

using one or two different indices to make sure that the answers are the same will be a good idea.  Nino3.4 is standard and you might try Nino3 too. Also try looking at the difference between Central Pacific and East Pacific El Nino's as they may well have different effects in your region.

A key thing to note is that during El Nino, Sri Lanka is close to the boundary between the dry West Pacific/East Indian Ocean signal and the wet West Indian Ocean/E African signal. 

It looks to me like observations suggest that Sri Lanka is dry during El Nino. See for example MacLachlan et al 2015, Quart J Roy Met Soc. It's available here:

or from my ResearchGate page.

Best

Adam

The BoM maintains a good record of IOD-positive/negative years (http://www.bom.gov.au/climate/iod/) which is good for an overview; though I prefer the more detailed analysis from JAMSTEC (http://www.jamstec.go.jp/frcgc/research/d1/iod/HTML/Dipole%20Mode%20Index.html).

Again for ENSO, the BoM has a good overview (http://www.bom.gov.au/climate/enso/enlist/index.shtml, with links for La Nina therein), as does NOAA (https://www.esrl.noaa.gov/psd/enso/mei/); if you want something more detailed in terms of numbers, I would recommend the CPC (http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ensoyears.shtml).

Hope these help. 

yes, weekly rainfall is more relevant

Dear Tina,

                You may not be so casual in this global warming effects and aspects. The entire world has awakened  since last 2 decades on the subject matter and you are finding nothing. Your contribution/rating for survival of this planet will be nil.Please be informed on latest developments on the subject matter. Earth is too large as compared to your place of living.

Anthropogenic global warming, large-scale land use and cover change, and aerosols emissions from Asian industrial areas have been regarded as the major driving agents affecting summer monsoon changes. A lot of papers, especially the modeling works by using climate models, have been published in these fields, but most of the scientific questions still remain to be tackled.

 Respected Svetoslav,

Thanks a lot for your valuable suggestion.

Regards with respect

Dear Aswin Kokkat,

You can refer "A Look at the Relationship between the ENSO and the Indian Ocean Dipole " by Ashok et al. (2003), "Impact of the Indian Ocean dipole on the relationship between the Indian monsoon rainfall and ENSO" by Ashok et al.(2001). 

Prof. Ashok Karumuri (University of Hyderabad), Roxy Mathew Koll (Indian Institute of Tropical Meteorology) and Prof. Raghu Murtugudde (University of Maryland) have several contributions in this regard. You can read their papers for a better insight.

The very recent paper is "Teleconnections of ENSO and IOD to summer monsoon and rice production potential of India" by Jha et al.(2016).

Some recent papers are quite critical in this regard like, "Evolution of Indian Ocean dipole and its forcing mechanisms in the absence of ENSO" by  Wang et al. (2016); "Indian Ocean and Indian summer monsoon: relationships without ENSO in ocean–atmosphere coupled simulations" by Crétat et al. (2016); "Statistical Evidence for Asymmetry in ENSO–IOD Interactions" by Lestari and Koh (2016); "The weakening of the ENSO–Indian Ocean Dipole (IOD) coupling strength in recent decades" by Ham et al. (2016).

I am providing links of some other relevant papers.

I hope this helps.

All the best!

Dear Kilian Mathan,

If you need only precipitation data (observed), you can get it from India meteorological department (IMD) or Water Resources Department of TamilNadu or from Central Water Commission, India... Basically, these 3 organisations are providing station-wise data for Chennai.. Out of which, IMD is considered to be more reliable...

I hope it helps.

All the best!

Dear Suman,

The spin up time is the time the model takes for the input/ouput values of an annual to reach a steady state. However, if you are doing a seasonal model then it will not reach a steady state because it is part of an annual cycle which is continually changing throughout the seasonal cycle.

You will have to incorporate your model within an annual model and run the annul model for several years until it reaches a steady state. Running a seasonal model, March through June, will always give the same results for every run since input values for March will always be the same. The output values form June are not suitable as input values for March. For March you need the output values for February which you do not have.

HTH,

Cheers, Alastair.

For precipitation:

TRMM 3B42V7 and Bookhagen and Burbank (no snow! and high error with snow)

High Asia Reanalysis (HAR) 2001 to 2014 (TU Berlin Climate group) (with snow)

For temperature:

High Asia Reanalysis (HAR) 2001 to 2014 (TU Berlin Climate group)

proxy through MODIS MOD11 land surface temperatures (calibration with in situ needed and little or no vegetation cover)

Downscaling using climate model data such as ECMWF Era-Interim (apply lapse rates and a DEM)

Snow cover:

MODIS 

good luck

You may contact to Dr. Borgaonkar at IITM Pune or Prof. Ramesh from PRL ahmedabad.

Dear Malte LuKowski,

The rise and uplifting of the mountain was not enough as main splitter for the monsoonal season became catastrophic as well as peculiar monsoon (episodic likely) without conceivable of main geological provenance such as i.e, the buoyant of crust and mantle fluctuation as beam piling up by mountain constructions. This might be others reason how the atmospheric breakdown began as asthenosphere was unstable and began uplifting too.

regard's

Zolhizir bin Daud

Dear Arun,

Global Precipitation Measurement or GPM is a program of several space agencies led by the US space agency NASA whose objective is to make periodic measurements of precipitation close to the level of the entire planet. This program is a continuation of the mission Tropical Rainfall Measuring Mission with broader objectives. Several satellites must collect data whose consistency will be ensured by the GPM Core Observatory satellite developed by NASA with an important participation of the Japanese space agency JAXA. The data collected by the GPM satellite fleet should improve the daily weather forecasts, better prevention of natural disasters related to flooding or droughts, and for the long term, help improve modeling of change climate. GPM Core Observatory is a satellite of 3.2 tonnes which carries two instruments developed especially: a dual frequency radar and a radiometer.

GPM extends the scope of observations in low-intensity rainfall (up to 0.5 mm per hour) and the snow, which predominate at mid and high latitudes. This capability required the premise developing appropriate instruments.

The Global Precipitation Measurement program aims to measure precipitation globally and is implementing several satellites. It is based on the implementation of a central satellite (GPM Core Observatory) carrying a radiometer and radar to measure rainfall from space and serve as a reference to unify the measurements made by the other spacecraft attached in the program.

With my best regards

Prof. Bachir ACHOUR

The Phosphorus in the filtrate would be soluble inorganic P as ortho phosphate. The suspended particulate would be exported P which would either be organic Phosphate or Phosphate bound to clay or humic materials. When you talk about the export from compost and raw manure you may find much more loss from raw manure than cured aged compost. Intact soil core lysimeters would give good data on this if you have the time and investment to follow this over several years.

Yes, I agree with  Waqas Qazi that SAR (Synt,hetic Aperture Radar) will be very effective for monitoring floods. SAR (Synthetic Aperture Radar) is an all weather imaging radar which can operate without sunlight. Here, the "all weather" means that it can operate through clouds and also at night. In the past, we have used RADARSAT images, successfully monitoring floods of Red River and they were very effective. RADARSAT is a C-band SAR system but TerraSAR-X  (X-band SAR, DLR) and ALOS (L-band SAR, JAXA) should be effective for monitoring floods.       

No one study can be comprehensively concluding that a particular CMIP5 model or a set of these models are realistic in simulating Indian summer monsoon. Because ISM is not a single entity and it has so many associated features so it depends on what you are looking at-  from the recent CMIP5 studies it can be concluded that a set of models can be good in representing mean state and hence interannual changes but if you go further into the values, the same set is not that good in representing the daily values and hence the intraseasonal variability. similarly for annual cycle or monsoon-enso teleconnection. try to understand one of the reasons behind this. a model simulation is in essence,  merely one combination out of of a large number of possible combinations of existing physical parameterisation schemes and this combination of schemes play together for simulation to happen. one scheme's success (for a particular process like convection and hence real mean state) lies in compensating other scheme's failure (for say cloud formation and hence daily value) for one combination/simulation/model. it's philosophical and mathematical more than physics. so by science it is never possible for design a perfect model or simulation or combination to exist. what is only possible is to (through use of high computational facility) to find a perfect combination of output or ensemble. try reading this. very good article/report in nature's scientific report journal on CMIP5

see figure 3a

some suggestions:

[Daily Monsoon Indices-2015]

Improved rainfall estimation over the Indian monsoon region by synergistic use of Kalpana-1 and rain gauge data

Japan Aerospace Exploration Agency

3-hr Realtime Rainfall Analyses

TRMM Online Visualization and Analysis System (TOVAS)

Gairola, R. M., Prakash, S., & Pal, P. K. (2015). Improved rainfall estimation over the Indian monsoon region by synergistic use of Kalpana-1 and rain gauge data. Atmósfera, 28(1), 51-61.

Saludos

You might want to study the effects of cloud cover and rainfall in your location. Collecting daily/ monthly data will enable you compare the cloudy or rainy days effect on your output. You might want to consider temperature as well since dust might not be a major problem during monsoon.