Dear Gargi Akhoury,

Composite analysis is often a useful technique to determine some of the basic structural characteristics of a meteorological or climatological phenomenon that are difficult to observe in totality (such as a hurricane, a squall line thunderstorm, or a cold front), or phenomenon which occur over time (e.g., the weather/climate over a given geographic area). In studying climate, composites can be quite useful for exploring the large scale impacts of teleconnections from modes of atmospheric variability such as El Nino. 

Composite analysis involves collecting large numbers of cases of a given meteorological phenomenon. It may be necessary to standardize the cases in some fashion (for example, to construct a composite of the wind in a hurricane, it may be necessary to adjust the radial flight level observations into a frame normalized by the radius of maximum wind). Then these cases are composited together as a collection, perhaps with different types of stratification using one or more covariates that are suspected to have an influence on the phenomenon. For a composite of hurricane structure, one might stratify by the intensity of the hurricane, or vertical wind shear, or some other factor. For a climate composite, one might composite the weather over a large area over a period of many years by an ENSO index to study how precipitation or temperature vary due to ENSO. 

The composite analysis then generally involves computing the composite mean and perhaps computing some other statistical measures, such as the standard deviation and statistical significance. If done properly, the resulting structures which emerge can tell a powerful story about how that meteorological phenomenon is affected by the factors used in the composite stratification. 

Best regards,

Jonathan

Dear Gargi Akhoury,

Composite analysis is often a useful technique to determine some of the basic structural characteristics of a meteorological or climatological phenomenon that are difficult to observe in totality (such as a hurricane, a squall line thunderstorm, or a cold front), or phenomenon which occur over time (e.g., the weather/climate over a given geographic area). In studying climate, composites can be quite useful for exploring the large scale impacts of teleconnections from modes of atmospheric variability such as El Nino. 

Composite analysis involves collecting large numbers of cases of a given meteorological phenomenon. It may be necessary to standardize the cases in some fashion (for example, to construct a composite of the wind in a hurricane, it may be necessary to adjust the radial flight level observations into a frame normalized by the radius of maximum wind). Then these cases are composited together as a collection, perhaps with different types of stratification using one or more covariates that are suspected to have an influence on the phenomenon. For a composite of hurricane structure, one might stratify by the intensity of the hurricane, or vertical wind shear, or some other factor. For a climate composite, one might composite the weather over a large area over a period of many years by an ENSO index to study how precipitation or temperature vary due to ENSO. 

The composite analysis then generally involves computing the composite mean and perhaps computing some other statistical measures, such as the standard deviation and statistical significance. If done properly, the resulting structures which emerge can tell a powerful story about how that meteorological phenomenon is affected by the factors used in the composite stratification. 

Best regards,

Jonathan

 Dear Henk Smid,

             No problem .....but Thanku that I got some new facts about composite analysis.

Regards

Gargi

Dear Jonathan Leslie Vigh,

     Thanks a lot for the detailed answer. Is there any limitation of period like 2 years , 3 years etc...??

Regards

Gargi

No, as long as the class of events being considered are all relevant to the phenomenon being studied. Generally, it's good to have as many cases as possible in order to get good statistical samples. So for instance, for a composite of hurricane wind structure, collaborators and I have recently used 13 years worth of data. In another study, I used 25 years worth of data. 

I should add that for a climate composite study, one might need to consider whether the climate is stationary. If the climate is changing, then this may need to be carefully accounted for. If the goal is not to examine the effect of climate change on the phenomenon, then the data could be detrended, or some other technique used. 

Dear Jonathan Vigh

Thank you so much for the guidance

Regards

You're most welcome. 

Best,

   Jonathan

Response from Jonathan was useful as I had the same question.

Thank Jonathan

Best,

Jully

Thanks Jonathan...I was searching an answer for the same question..

Wonderful explanation Jonathan Leslie Vigh

Dear Gargi,

Composite analysis is often a useful technique to determine some of the basic structural characteristics of a meteorological or climatological phenomenon that are difficult to observe in totality (such as a hurricane, a squall line thunderstorm, or a cold front). This is a sampling technique based on the conditional probability of a certain event occurring. Oceanic Niño Index (ONI) is quite popular finding of composite analysis.

Why we use?

This is utmost helpful for Forecast Verification. In order to improve seasonal forecasts of rainfall, hurricane, line thunderstorm etc., verification provides information about the quality, reliability, and confidence of the product analysis. CPC Nino 3.4 forecasts, CPC El Niño/La Niña forecasts are available from 1982 to the present. Than data relevance of this type of analysis for decision making in the most recent events and of most impact on the economy of Colombia, whether forecast on Australia and more or less for all countries.

Example of Australia,

A composite analysis has performed to show the large-scale and regional SST conditions observed during summer heat waves (HWs) in Perth, southwest Australia Heat waves (HWs) and sea surface temperatures (SSTs). Composite results initially point to the importance of the subtropical South Indian Ocean, where physically coherent SST dipole anomalies appear to form a necessary condition for HWs to develop across southwest Australia.

Requirement for composite data analysis (how to arrange composite analysis)

1. Climatological Data Download the data set from xmACIS and Select area of interest. Select routine, Select the climate variable and period of interest and submit the request, data display (they will show the start and end year).

2. Moving the Data to the Station Spreadsheet- Use by setup Excel spreadsheet, copying the data into the spreadsheet. Formatting the data. Save your work, Setup the composite analysis spreadsheet, open template Open the template, Composite_XXX_MMMYYYY_cccc_template.xls. Save this spreadsheet as Composite_XXX_MMMYYYY_cccc.xls, where XXX is a three letter identifier for the station you are investigating, MMM is the 3 letters of the month the forecast is issued, YYYY is the year, and cccc is the four letter climate variable abbreviation assigned by NCDC (alternatively, a four letter identifier you create).

3. Copying station data to composite analysis spreadsheet. Calculate a 3-month weighted average of the climate variable. Add Oceanic Nino Index (ONI) data.

4. Compute Historical Composite Analysis

5. Trend Adjustment

6. Risk Analysis (Statistical Significance)- Risk analysis assesses whether the composite forecast is statistically significant.

7. click on Composite analysis forecast

8. Create Graphical Products

Ashish