quality assurance checklist (quack) - reporting...the bisalpur dam project plays an important role...

Version: 2.0

Copernicus Climate Change Service – Global Impacts

Quality Assurance Checklist (QUACK) - reporting

What is QUACK:

This tool is developed for the showcases of in C3S_422_Lot1_SMHI to promote high quality in each showcase

For a set of quality indicators it offers you structured questions in combination with guidance material

How to apply QUACK*:

For each quality indicator you will find assessment questions. Please state if they apply for your showcase.

For each assessment question; you will find supporting material under: http://climateservice-global.eu/quality-assurance/

Give a short description about how you treated the quality indicators

Wherever possible – provide any documents, links, scripts, etc. that support your performance

Note: Please save the file name as: Organization_Country_QUACK_reporting (e.g SMHI_Sweden_QUACK_reporting.docx)

*in case you have any questions contact: [email protected]

http://climateservice-global.eu/quality-assurance/

Copernicus Climate Change Service - C3S_422_Lot1_SMHI

Version: 2.0

reporting Version: 2.0

Showcase name: Impact Assessment of Climate Change on the Water Resources and Agriculture in Banas basin in Western

India using Climate Change Indicators (CII’s)

Short description of a showcase: Rajasthan is the largest state of India with 10.4% of the country’s area and 5.5% of

its population, but only about 1% of the country’s water resources producing 5.49% of the nation’s total food grains and 21.31% of

its oil seeds. The Bisalpur dam project plays an important role in the economy of the western Rajasthan region of the Banas river

basin providing water for drinking to various cities and irrigation in the Tonk district. However, the present water resources of this

region are not enough to cater to the needs of the increasing population, including agriculture and non- agriculture demands and

climate change will act as an additional stressor. Thus, it is vital to assess the effects of climate change in order to have optimal

reservoir operation and adapt to best crop management practices.

Organization: NIH, India

Reporter name & email: Archana Sarkar ([email protected]); Surjeet Singh ([email protected])

Last update and Place: 28/01/2019, Roorkee (India)

Copernicus Climate Change Service - C3S_422_Lot1_SMH

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Dimension: Input data

Criterion: Scientific & methodological quality

Quality indicator

Applied

Short description

Supporting documents

Comments

Yes

No

Transparency

Are all data sources referenced? Please provide which category (observation, simulation, etc) of data you used and the source.

Example: Forcing data: Precipitation , Station data, 1 h, 24 stations, national weather service

Simulation: GCM data, 50 km resolution; ensemble of five models; RCP 4.5 and 8.5, provided by

x Daily observed rainfall (precipitation)

data was downloaded from the Water Resources Department, Rajasthan, India website. Daily air temperature (min, max, mean) gridded data (re-analysis) at 1 degree grid developed by India Meteorological Department (IMD), Pune, India was purchased Simulation: Downloaded CII (Global), 2.0° x 2.0° resolution; bias adjusted monthly

http://water.rajasthan.gov.in/content/water/en/waterresourcesdepartment/WaterManagement/IWRM.html http://www.imd.gov.in/advertisements/20170320_advt_34.pdf Simulation: produced within C3S_422_Lot1_SMHI

http://water.rajasthan.gov.in/content/water/en/waterresourcesdepartment/WaterManagement/IWRM.html




http://www.imd.gov.in/advertisements/20170320_advt_34.pdf




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C3S_422_Lot1_SMHI data of 19 model ensemble (max, mean & min); for the current situation (historical simulation) and for the RCP 4.5 & RCP8.5 experiment for all the four time periods Monthly time series of the Climate Impact Indicators (CII): - Mean precipitation (Monsoon

months) - Maximum temperature

(monthly) produced within C3S_422_Lot1_SMHI contract, and available in the climate data store catalogue

contract, and available in the climate data store catalogue

Do the metadata follow international standards?

x Metadata follows international/national/regional standards

Appropriateness

Are the used data appropriate for the case study in terms of spatial and temporal scale?

x The Global (2 deg) CII data used presently is at a coarser spatial scale but due to various limitations, the finer scale data (0.5 deg) that would have been appropriate could not be used. In terms of temporal scale, the CII’s at monthly scale and monsoon period


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(mean of JJAS) have been prepared as CII data available is at monthly scale. However, the CII of maximum temperature at a daily/weekly scale would be more appropriate for information to farmers.

Completeness

Is the technical consistency checked (no outliers, no gaps in time series, etc.)?

x Technical consistency (outliers) already checked by WRD & IMD. We have checked the gaps in time series and discarded some time series with huge data gaps

There were no data gaps in the CII data produced within C3S_422_Lot1_SMHI contract

Do you have all available data sets considered?

x We have all the observed datasets available with us We intended to use the ECV data sets of all 19 GCMs (available in C3S_422_Lot1_SMHI) after downscaling and bias correction. But we do not have the ECVs data of 0.5 deg resolution in the Excel format. Instead, we have the Global 2 deg CII data.

produced within C3S_422_Lot1_SMHI contract, and available in the climate data store catalogue


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Dimension: Processing


Quality indicator

Applied

Short description


Comments

Yes

No

Transparency

Are the processing steps (i.e. scripts) well documented and reproducible?

x Scripts not written

Are the applied methods well documented and follow scientific standards (i.e. peer reviewed)?

Appropriateness

Are the used methods, for instance bias-adjustment, appropriate for the case study?

x Bias adjusted data has been used for production of Global 2 deg CIIs.

https://climate.copernicus.eu/global-users-copernicus-climate-change-service


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Accuracy/Robustness

Are the uncertainties assessed systematically in a standard manner?

x The downloaded CII data, we have used, have been bias adjusted and the details are given in the FAQ’s in https://climate.copernicus.eu/global-users-copernicus-climate-change-service

Is the case study based on different global or regional climate model simulations? In case that not all simulations of an ensemble are used, is the selection well explained and justified?

x The case study is based on Global CIIs. All 19 ensemble members have been used in the case study

Is the showcase using climate emission scenarios i.e. a low, medium and high scenario? (Please specify the name of scenarios used in the showcase).

RCP 4.5 (moderate) and RCP 8.5 (high) scenarios have been used in the present case study

Validation

Is validation possible for the showcase? Is there a

x Validation is not possible in the present state of the case study


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procedure in place for a validation against independent data?

Reflectivity

Is the scientific consistency among multiple data sets and their findings well documented? (i.e. comparing your results to the existing peer reviewed studies in the region)

x

Criterion: Practical Relevance

Suitability for target group

Is the relevance for the client assured?

x The CII’s being at coarser spatial and temporal scale, the results are relevant to the client but in a broad sense, i.e., in qualitative terms

To some extent


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Dimension: Output


Quality indicator

Applied

Short description


Comments

Yes

No

Transparency

Are the produced results provided with metadata?

x Following 19 GCMs: GFDL-CM3 GFDL-ESM2G NorESM1-M MPI-ESM-LR MPI-ESM-MR HadGEM2-CC HadGEM2-ES IPSL-CM5A-LR IPSL-CM5A-MR IPSL-CM5B-LR INM-CM4 EC-EARTH GFDL-ESM2M ACCESS1-0 ACCESS1-3 CNRM-CM5


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BNU-ESM BCC-CSM1.1 BCC-CSM1.1(m)

Are the limits of provided information disclosed?

x The Global CIIs used in the case study have a spatial scale of 2 deg and temporal scale as monthly. The spatial and temporal scales are described in the maps. The maps produced show the mean of ensemble as well as max & min which gives an idea of uncertainty.

Consistency

About the visualization of your output: Do the graphics and tables of the presentation match the captions and explanations?

x Only maps have been prepared

Reliability

Is the confidence of the data presented (e.g. the spread of the whole ensemble)?

x The maps produced show the mean of ensemble as well as max & min which gives an idea of uncertainty.


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Criterion: Practical Relevance

Lucidity/Clarity

Is the presentation of your output clear and does It follow visualization standards?

x

The maps produced are clear & self-explanatory and have been shared with SMHI

Do the pictures, and maps used match the explanation i.e. story?

x To some extent

Rights of Use

Are the rights of dissemination clarified (i.e. open access)?

x Copernicus License (https://cds.climate.copernicus.eu/api/v2/terms/static/20180314_Copernicus_License_V1.1.pdf)

Usability

Is the output intuitively presented and freely accessible?


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Criterion: Review Process Review by third party

Are the results of the showcases reviewed externally or internally? To what level the review process was taken.

X

Results reviewed internally and also shared with SMHI


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Dimension: Outcome

Criterion: Satisfaction

Quality indicator

Applied

Short description


Comments

Yes

No

Usefulness

Does the product help for problem solving of your client?

x

Due to the coarser spatial resolution of the CII developed in the present case study, it is useful on a coarser scale, i.e., basin scale and not on small block/agricultural farms scale.

To some extent

quality assurance checklist (quack) - reporting...the bisalpur dam project plays an important role...

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