Assessment of the Paris urban heat island in ERA5 and offline SURFEX-TEB (v8.1) simulations using the METEOSAT land surface temperature product

Nogueira, Miguel; Hurduc, Alexandra; Ermida, Sofia; Lima, Daniela C. A.; Soares, Pedro M. M.; Johannsen, Frederico; Dutra, Emanuel

doi:https://doi.org/10.5194/gmd-15-5949-2022

Articles | Volume 15, issue 14

https://doi.org/10.5194/gmd-15-5949-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-15-5949-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 14

Model evaluation paper

|

29 Jul 2022

Model evaluation paper |

| 29 Jul 2022

Assessment of the Paris urban heat island in ERA5 and offline SURFEX-TEB (v8.1) simulations using the METEOSAT land surface temperature product

Miguel Nogueira, Alexandra Hurduc, Sofia Ermida, Daniela C. A. Lima, Pedro M. M. Soares, Frederico Johannsen, and Emanuel Dutra

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Final revised paper (published on 29 Jul 2022)
Preprint (discussion started on 28 Jan 2022)

Interactive discussion

Status: closed

RC1: 'Comment on gmd-2021-431', Anonymous Referee #1, 11 Feb 2022

Review of Nogueira et al.: Assessment of the Paris urban heat island in ERA5 and offline SURFEX-TEB (v8.1) simulations using METEOSAT land surface temperature product

The present article evaluates the Paris Surface Urban Heat Island (SUHI) and Urban Heat Island (UHI) in the ERA5 re-analysis data and Offline

simulations with the land surface model SURFEX using a "rock-type" urban parametrisation or the urban canopy model TEB to simulate

the urban surface energy balance.

Observed SUHI is derived from LSA-SAF (SEVIRI) satellite observations, UHI from station data.

Results show that ERA5 does not capture the SUHI or UHI, which is no surprise given that the underlying IFS model has not been using an

urban parametrisation and no urban stations have been assimilated.

A major improvement of the results for SUHI and UHI is found when using SURFEX-TEB. This shows that even with an Offline application of SURFEX-TEB, re-analysis products like ERA5 could be strongly improved and spatially refined in urbanised areas, which is a very useful finding.

The present paper is interesting, very well structured and written, the results are clear, so I have only very minor comments:

There is a recent study on the Paris urban climate including

the SUHI: Benjamin Le Roy, Aude Lemonsu, Raphaëlle Kounkoud-Arnaud, Denis Brion,

Valéry Masson: Long time series spatialized data for urban

climatological studies: a case study of Paris, France.

International Journal of Climatology, Wiley, 2019, ï¿¿10.1002/joc.6414ï¿¿.

The results from the present study should be compared with this study.

The absolute value of the bias (|Bias|) is used throughout the paper.

I dont understand why this is done, since the information on the sign

of the bias is lost. I propose to use the Bias as is, and change the

related figures and text.

L114: I am wondering how to simulate the UHI with a single-column

approach. In fact, the advection of cool air from the rural areas

around the city towards the city cannot be taken into account.

Do these simulations parametrise the advection via a forcing term?

L121: I guess all observations are for the same 2004-2018 period?

It seems not to be stated explicitly for the station observations.

L177: Schoetter et al. (2020) has only dealt with simulations on Hong Kong,

so did not formally show that the single-layer TEB is adequate for mid-rise cities.

So I think this statement has to be changed.

Figure 2: The comparison is a bit unfair since the ERA5 resolution is so coarse. You could add a third column with the other datasets interpolated to the ERA5 grid.

Figures 3, 5 and 6: More space should be added between the different lines of figures.

Figures 6 and 9: In the legend you should use points instead of lines for ERA5, SFX-ROCK, SFX-TEB.

Figure 8ace: There are some weird features (rectangle-shaped). What is their origin?

L403: high-resolution simulation.

Citation: https://doi.org/10.5194/gmd-2021-431-RC1
RC2: 'Comment on gmd-2021-431', Anonymous Referee #2, 28 Apr 2022

Please see attached PDF.

Citation: https://doi.org/10.5194/gmd-2021-431-RC2
AC1: 'Comment on gmd-2021-431', Frederico Johannsen, 08 Jun 2022

Our response to the reviewers' comments are in the attatched PDF file.

Citation: https://doi.org/10.5194/gmd-2021-431-AC1

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Frederico Johannsen on behalf of the Authors (08 Jun 2022) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (09 Jun 2022) by Jinkyu Hong

RR by Anonymous Referee #1 (13 Jun 2022)

ED: Publish subject to minor revisions (review by editor) (19 Jun 2022) by Jinkyu Hong

Please check if the comments below are relevant to provide more synthetic information to improve your manuscript readability.

1. L38-43:
- Could you replace Oke (1982) or add to more updated reference, Oke et al. (2017, Urban Climates, T. R. Oke, H. Mills, A. Christen, Cambridge Univ. Press)
- There are studies to relate long-term UHI to economic conditions and add them to this paragraph (e.g., Hong et al., 2019; Li et al., 2020; He et al., 2022).

Hong et al. (2019) Temporal dynamics of urban heat island correlated with the socio-economic development over the past half-century in Seoul, Korea, Environmental Pollution.

Li et al. (2020) Socioeconomic drivers of urban heat island effect: Empirical evidence from major Chinese cities, Sustainable Cities and Society

He et al. (2022) Localized synergies between heat waves and urban heat islands: Implications to human thermal comfort and urban heat management, Environmental Research

2. L88-90: I expect that UCM considers vertical exchanges of energy and mass only, which may emphasize the importance of your study.

3. L 139: Could you also mention uncertainty of LST by building material emissivity?

4. L174-176: I am quite sure if this sentence is in the relevant position when I consider the sentences before this one.

5. Section 2.3: For comparison of other studies, I recommend that you provide RMSE in the manuscript.

6. Figure 3:
- Can you reduce negative bias in the SFX-ROCK experiment by modifying thermal properties of rock covers in the experiment? This may provide some hints for the simple diagnostic values for UHI simulations.

- Also, I wonder if you can discuss why SFX-TEB shows substantial positive bias of daytime LSTmax in JJA. I wonder how to assign anthropogenic heat emission in summer and winter.

- I expect that UHI is dominant in nighttime temperature because of thermal properties of buildings but Fig 3 and 5 show that SFX-TEB does not give substantial improvement in nighttime. Could you provide any idea and implications on this?

7. Figure 7: It is interesting that the SFX-TEB improves the UHI near sunrise and sunset substantially. Could you discuss this finding?

8. Figure 2 and 8: Can you add urban boundary described in Figure into these two figures?

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AR by Frederico Johannsen on behalf of the Authors (30 Jun 2022) Author's response Author's tracked changes Manuscript

ED: Publish subject to technical corrections (03 Jul 2022) by Jinkyu Hong

Short summary

We evaluated the quality of the ERA5 reanalysis representation of the urban heat island (UHI) over the city of Paris and performed a set of offline runs using the SURFEX land surface model. They were compared with observations (satellite and in situ). The SURFEX-TEB runs showed the best performance in representing the UHI, reducing its bias significantly. We demonstrate the ability of the SURFEX-TEB framework to simulate urban climate, which is crucial for studying climate change in cities.