Added value of convection-permitting simulations for understanding future urban humidity extremes: case studies for Berlin and its surroundings

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Added value of convection-permitting simulations for understanding future urban humidity extremes: case studies for Berlin and its surroundings. / Langendijk, Gaby S.; Rechid, Diana; Sieck, Kevin et al.
In: Weather and Climate Extremes, Vol. 33, 100367, 01.09.2021.

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@article{3f69b60fb3004e42b487cf5302a6b89e,
title = "Added value of convection-permitting simulations for understanding future urban humidity extremes: case studies for Berlin and its surroundings",
abstract = "Climate extremes affected cities and their populations during the last decades. Future climate projections indicate climate extremes will increasingly impact urban areas during the 21st century. Humidity related fluctuations and extremes directly underpin convective processes, as well as can influence human health conditions. Regional climate models are a powerful tool to understand regional-to-local climate change processes for cities and their surroundings. Convection-permitting regional climate models, operating on very high resolutions, indicate improved simulation of convective extremes, particularly on sub-daily timescales and in regions with complex terrain such as cities. This research aims to understand how crossing spatial resolutions from ~12.5 km to ~3 km grid size affect humidity extremes and related variables under future climate change for urban areas and its surroundings. Taking Berlin and its surroundings as the case study area, the research identifies two categories of unprecedented future extreme atmospheric humidity conditions happening under 1.5 °C and 2.0 °C mean warming based on statistical distributions, respectively near surface specific humidity >0.02 kg/kg and near surface relative humidity <30%. Two example cases for each future extreme condition are dynamically downscaled for a two months period from the 0.44° horizontal resolution following a double-nesting approach: first to the 0.11° (~12.5 km) horizontal resolution with the regional climate model REMO and thereafter to the 0.0275° (~3 km) horizontal resolution with the non-hydrostatic version of REMO. The findings show that crossing spatial resolutions from ~12.5 km to ~3 km grid size affects humidity extremes and related variables under climate change. Generally, a stronger decrease in moisture (up to 0.0007–0.005 kg/kg SH and 10–20% RH) and an increase in temperature (1–2 °C) is found on the 0.0275° compared to the 0.11° horizontal resolution, which is more profound in Berlin than in the surroundings. The convection-permitting scale mitigates the specific humidity moist extreme and intensifies the relative humidity dry extreme in Berlin, posing challenges with respect to health for urban dwellers.",
keywords = "Convection permitting, Future climate extremes, Humidity, Regional climate modelling, Urban-rural contrasts, Sustainability Science, Environmental planning",
author = "Langendijk, {Gaby S.} and Diana Rechid and Kevin Sieck and Daniela Jacob",
note = "We thank the “Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI)” project ( https://www.happimip.org/ ) for making the data available which enabled this research. We would like to express great gratitude to the GERICS staff members working on REMO development for their support while conducting the REMO simulations, and particularly thank them for their help to fix technical model errors; Lars Buntemeyer, Thomas Frisius, Joni-Pekka Pietik{\"a}inen, and Thomas Remke. We are grateful for the helpful suggestions by our colleague Joni-Pekka Pietik{\"a}inen to improve the first draft of the manuscript. We would like to thank the staff members at the German Climate Computing Center (DKRZ) for their technical expertise and support. The research was kindly funded by the Climate Service Center Germany (GERICS), Helmholtz-Zentrum Hereon, Germany. ",
year = "2021",
month = sep,
day = "1",
doi = "10.1016/j.wace.2021.100367",
language = "English",
volume = "33",
journal = "Weather and Climate Extremes",
issn = "2212-0947",
publisher = "Elsevier B.V.",

}

RIS

TY - JOUR

T1 - Added value of convection-permitting simulations for understanding future urban humidity extremes

T2 - case studies for Berlin and its surroundings

AU - Langendijk, Gaby S.

AU - Rechid, Diana

AU - Sieck, Kevin

AU - Jacob, Daniela

N1 - We thank the “Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI)” project ( https://www.happimip.org/ ) for making the data available which enabled this research. We would like to express great gratitude to the GERICS staff members working on REMO development for their support while conducting the REMO simulations, and particularly thank them for their help to fix technical model errors; Lars Buntemeyer, Thomas Frisius, Joni-Pekka Pietikäinen, and Thomas Remke. We are grateful for the helpful suggestions by our colleague Joni-Pekka Pietikäinen to improve the first draft of the manuscript. We would like to thank the staff members at the German Climate Computing Center (DKRZ) for their technical expertise and support. The research was kindly funded by the Climate Service Center Germany (GERICS), Helmholtz-Zentrum Hereon, Germany.

PY - 2021/9/1

Y1 - 2021/9/1

N2 - Climate extremes affected cities and their populations during the last decades. Future climate projections indicate climate extremes will increasingly impact urban areas during the 21st century. Humidity related fluctuations and extremes directly underpin convective processes, as well as can influence human health conditions. Regional climate models are a powerful tool to understand regional-to-local climate change processes for cities and their surroundings. Convection-permitting regional climate models, operating on very high resolutions, indicate improved simulation of convective extremes, particularly on sub-daily timescales and in regions with complex terrain such as cities. This research aims to understand how crossing spatial resolutions from ~12.5 km to ~3 km grid size affect humidity extremes and related variables under future climate change for urban areas and its surroundings. Taking Berlin and its surroundings as the case study area, the research identifies two categories of unprecedented future extreme atmospheric humidity conditions happening under 1.5 °C and 2.0 °C mean warming based on statistical distributions, respectively near surface specific humidity >0.02 kg/kg and near surface relative humidity <30%. Two example cases for each future extreme condition are dynamically downscaled for a two months period from the 0.44° horizontal resolution following a double-nesting approach: first to the 0.11° (~12.5 km) horizontal resolution with the regional climate model REMO and thereafter to the 0.0275° (~3 km) horizontal resolution with the non-hydrostatic version of REMO. The findings show that crossing spatial resolutions from ~12.5 km to ~3 km grid size affects humidity extremes and related variables under climate change. Generally, a stronger decrease in moisture (up to 0.0007–0.005 kg/kg SH and 10–20% RH) and an increase in temperature (1–2 °C) is found on the 0.0275° compared to the 0.11° horizontal resolution, which is more profound in Berlin than in the surroundings. The convection-permitting scale mitigates the specific humidity moist extreme and intensifies the relative humidity dry extreme in Berlin, posing challenges with respect to health for urban dwellers.

AB - Climate extremes affected cities and their populations during the last decades. Future climate projections indicate climate extremes will increasingly impact urban areas during the 21st century. Humidity related fluctuations and extremes directly underpin convective processes, as well as can influence human health conditions. Regional climate models are a powerful tool to understand regional-to-local climate change processes for cities and their surroundings. Convection-permitting regional climate models, operating on very high resolutions, indicate improved simulation of convective extremes, particularly on sub-daily timescales and in regions with complex terrain such as cities. This research aims to understand how crossing spatial resolutions from ~12.5 km to ~3 km grid size affect humidity extremes and related variables under future climate change for urban areas and its surroundings. Taking Berlin and its surroundings as the case study area, the research identifies two categories of unprecedented future extreme atmospheric humidity conditions happening under 1.5 °C and 2.0 °C mean warming based on statistical distributions, respectively near surface specific humidity >0.02 kg/kg and near surface relative humidity <30%. Two example cases for each future extreme condition are dynamically downscaled for a two months period from the 0.44° horizontal resolution following a double-nesting approach: first to the 0.11° (~12.5 km) horizontal resolution with the regional climate model REMO and thereafter to the 0.0275° (~3 km) horizontal resolution with the non-hydrostatic version of REMO. The findings show that crossing spatial resolutions from ~12.5 km to ~3 km grid size affects humidity extremes and related variables under climate change. Generally, a stronger decrease in moisture (up to 0.0007–0.005 kg/kg SH and 10–20% RH) and an increase in temperature (1–2 °C) is found on the 0.0275° compared to the 0.11° horizontal resolution, which is more profound in Berlin than in the surroundings. The convection-permitting scale mitigates the specific humidity moist extreme and intensifies the relative humidity dry extreme in Berlin, posing challenges with respect to health for urban dwellers.

KW - Convection permitting

KW - Future climate extremes

KW - Humidity

KW - Regional climate modelling

KW - Urban-rural contrasts

KW - Sustainability Science

KW - Environmental planning

UR - http://www.scopus.com/inward/record.url?scp=85112294021&partnerID=8YFLogxK

U2 - 10.1016/j.wace.2021.100367

DO - 10.1016/j.wace.2021.100367

M3 - Journal articles

AN - SCOPUS:85112294021

VL - 33

JO - Weather and Climate Extremes

JF - Weather and Climate Extremes

SN - 2212-0947

M1 - 100367

ER -

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