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ICAR AICE-JRF/SRF Climate Models, Scenarios & Downscaling: practice questions

ICAR AICE-JRF/SRF (PhD) — Environmental Sciences (subject 71) and Agricultural Meteorology (subject 60) · India · National Testing Agency for ICAR

Original practice questions written to the published syllabus · not past papers
10worked here, free
36written to this exam in this subject
10syllabus units

What this subject covers

How future climate is projected and how to use projections responsibly: model hierarchy, CMIP ensembles, RCP and SSP scenarios, downscaling and bias correction, and uncertainty. Needed for impact studies, climate-risk disclosure and adaptation planning.

In the exams: GARP SCR 'Climate Models and Scenario Analysis'; PG and PhD research in agrometeorology and climate change; ICAR AICE subject 60 (climate variability)

What ICAR AICE-JRF/SRF asks from it

ICAR AICE-JRF/SRF (PhD) — Agricultural Meteorology (60) and Environmental Sciences (71)

Climate variability and change, ENSO and monsoon forecasting, long-range forecasts and LPA categories, GCMs and RCMs, downscaling and bias correction for crop impact studies, and climate indices.

Where the 36 questions fall

How our questions for ICAR AICE-JRF/SRF spread across the units of Climate Models, Scenarios & Downscaling. Difficulty: 9 easy, 19 medium, 8 hard.

Bias correction methods6
Seasonal and sub-seasonal forecasting6
Climate indices and extreme-event indices6
Using climate data portals and open datasets6
Statistical and dynamical downscaling5
Model hierarchy: energy-balance, GCM, ESM and regional models3
CMIP ensembles and model evaluation1
Representative Concentration Pathways and Shared Socioeconomic Pathways1
Integrated assessment models and mitigation pathways1
Sources of uncertainty: scenario, model and internal variability1

10 practice questions, worked

Choose an answer, then open the working. Each explanation says why the right answer is right and why the others are not.

1 · Model hierarchy: energy-balance, GCM, ESM and regional models · medium

Why do climate models need parameterisations?

  1. They replace observations, so models never need to be compared with real data
  2. Sub-grid processes such as convective clouds cannot be resolved explicitly
  3. The large-scale circulation cannot be computed from physical laws in any model
  4. Parameterisations are legal requirements imposed on modelling centres by the IPCC
Answer and working

B. Sub-grid processes such as convective clouds cannot be resolved explicitly

Sub-grid processes such as convection, cloud microphysics and turbulence are represented by parameterisations in terms of resolved variables. They are not legal requirements, the large-scale flow is resolved from physical laws, and models are still evaluated against observations.

Further reading: See the manual sources: IPCC AR6 WGI/WGIII, CMIP6 design papers, ETCCDI and the documents named in the explanation

2 · Representative Concentration Pathways and Shared Socioeconomic Pathways · easy

What is AR6's best estimate of global warming in 2081–2100, relative to 1850–1900, under SSP2-4.5?

  1. 2.7 °C
  2. 1.8 °C
  3. 3.6 °C
  4. 4.4 °C
Answer and working

A. 2.7 °C

AR6 best estimates: SSP1-1.9 1.4 °C, SSP1-2.6 1.8 °C, SSP2-4.5 2.7 °C, SSP3-7.0 3.6 °C, SSP5-8.5 4.4 °C.

Further reading: See the manual sources: IPCC AR6 WGI/WGIII, CMIP6 design papers, ETCCDI and the documents named in the explanation

3 · Bias correction methods · hard

Using linear scaling, a model's reference-period mean July maximum temperature is 28.5 °C and the observed mean is 27.0 °C. The model projects 29.4 °C for a future July. What is the corrected value?

  1. 29.4 °C
  2. 27.9 °C
  3. 27.0 °C
  4. 30.9 °C
Answer and working

B. 27.9 °C

Additive correction: 29.4 + (27.0 − 28.5) = 27.9 °C. 30.9 applies the bias with the wrong sign; 27.0 is the observed mean, which ignores the projected change; 29.4 is uncorrected.

Further reading: See the manual sources: IPCC AR6 WGI/WGIII, CMIP6 design papers, ETCCDI and the documents named in the explanation

4 · Bias correction methods · hard

For rainfall, the reference-period observed mean is 4.2 mm day⁻¹ and the model's is 3.0 mm day⁻¹. Using multiplicative linear scaling, what is the corrected value of a future model day with 3.6 mm?

  1. 5.04 mm
  2. 2.57 mm
  3. 3.60 mm
  4. 4.80 mm
Answer and working

A. 5.04 mm

Corrected = 3.6 × (4.2/3.0) = 5.04 mm. Adding the difference gives 4.80 (additive scaling, which can produce negative rain on dry days); inverting the ratio gives 2.57; 3.60 is uncorrected.

Further reading: See the manual sources: IPCC AR6 WGI/WGIII, CMIP6 design papers, ETCCDI and the documents named in the explanation

5 · Bias correction methods · easy

Why is precipitation usually bias-corrected multiplicatively rather than additively?

  1. Multiplying keeps rain non-negative; adding a negative bias gives negative rain
  2. Precipitation is measured in kelvin, which can only be corrected by multiplying
  3. Multiplying always removes all bias in variance and extremes as well as the mean
  4. Additive correction is forbidden by international meteorological agreements
Answer and working

A. Multiplying keeps rain non-negative; adding a negative bias gives negative rain

A ratio correction keeps zero as zero and avoids negative values; additive correction can push dry days below zero. Rainfall is not measured in kelvin, there is no ban, and ratio scaling corrects only the mean.

Further reading: See the manual sources: IPCC AR6 WGI/WGIII, CMIP6 design papers, ETCCDI and the documents named in the explanation

6 · Seasonal and sub-seasonal forecasting · easy

Roughly how long does deterministic predictability of day-to-day weather last before chaos destroys skill?

  1. About two weeks
  2. About two years
  3. About two decades
  4. About two hours
Answer and working

A. About two weeks

Lorenz's work on chaos implies deterministic skill is lost after roughly two weeks; beyond that, skill comes from slowly varying boundary conditions and is probabilistic.

Further reading: See the manual sources: IPCC AR6 WGI/WGIII, CMIP6 design papers, ETCCDI and the documents named in the explanation

7 · Seasonal and sub-seasonal forecasting · hard

Four forecasts give probabilities of 0.8, 0.6, 0.3 and 0.1 for heavy rain; the event occurred on the first and third occasions only. What is the Brier score?

  1. 0.400
  2. 0.100
  3. 0.900
  4. 0.225
Answer and working

D. 0.225

BS = [(0.8−1)² + (0.6−0)² + (0.3−1)² + (0.1−0)²]/4 = (0.04 + 0.36 + 0.49 + 0.01)/4 = 0.225. 0.400 uses absolute errors; 0.900 forgets to divide by 4; 0.100 is the Brier skill score against a 0.5 climatology.

Further reading: See the manual sources: IPCC AR6 WGI/WGIII, CMIP6 design papers, ETCCDI and the documents named in the explanation

8 · Climate indices and extreme-event indices · medium

How is the Dipole Mode Index for the Indian Ocean Dipole defined?

  1. Pressure difference between the Azores high and the Icelandic low
  2. West minus south-east tropical Indian Ocean SST anomaly
  3. Sea surface temperature anomaly in the Niño 3.4 region of the Pacific
  4. Sea-level pressure at Tahiti minus sea-level pressure at Darwin
Answer and working

B. West minus south-east tropical Indian Ocean SST anomaly

The DMI is the SST anomaly difference between the western and south-eastern equatorial Indian Ocean. Tahiti–Darwin is the Southern Oscillation Index, Niño 3.4 is ENSO, and Azores–Iceland is the NAO.

Further reading: See the manual sources: IPCC AR6 WGI/WGIII, CMIP6 design papers, ETCCDI and the documents named in the explanation

9 · Using climate data portals and open datasets · easy

ERA5, from ECMWF and the Copernicus Climate Change Service, provides

  1. monthly station climatologies for 1961–1990 only
  2. hourly global reanalysis at 31 km from 1940 onwards
  3. downscaled CMIP6 projections at 1 km for Europe only
  4. daily satellite rainfall at 0.05° from 1981 for 50°S–50°N
Answer and working

B. hourly global reanalysis at 31 km from 1940 onwards

ERA5 is an hourly reanalysis at ~0.25° (31 km) from 1940. CHIRPS is the 0.05° rainfall product; the other descriptions do not fit ERA5.

Further reading: See the manual sources: IPCC AR6 WGI/WGIII, CMIP6 design papers, ETCCDI and the documents named in the explanation

10 · Using climate data portals and open datasets · medium

Where is raw CMIP6 model output primarily distributed?

  1. The Earth System Grid Federation and the Copernicus Data Store
  2. Each country's national statistics office, under its census law
  3. The World Bank's procurement database for climate projects
  4. The UNFCCC national inventory submission portal for each party
Answer and working

A. The Earth System Grid Federation and the Copernicus Data Store

CMIP data are served through ESGF nodes, and many variables via the Copernicus CDS. UNFCCC portals hold inventories, and statistics offices do not distribute CMIP output.

Further reading: See the manual sources: IPCC AR6 WGI/WGIII, CMIP6 design papers, ETCCDI and the documents named in the explanation

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Read the subject

Climate Models, Scenarios & DownscalingThe full study manual, free ICAR AICE-JRF/SRFFormat, sections and how it has changed

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