Contrasting lightning projection using the lightning potential index adapted in a convection-permitting regional climate model

AbstractLightning climate change projections show large uncertainties caused by limited empirical knowledge and strong assumptions inherent to coarse-grid climate modeling. This study addresses the latter issue by implementing and applying the lightning potential index parameterization (LPI) into a fine-grid convection-permitting regional climate model (CPM). This setup takes advantage of the explicit representation of deep convection in CPMs and allows for process-oriented LPI inputs such as vertical velocity within convective cells and coexistence of microphysical hydrometeor types, which are known to contribute to charge separation mechanisms. The LPI output is compared to output from a simpler flash rate parameterization, namely the CAPE $$\times$$ × PREC parameterization, applied in a non-CPM on a coarser grid. The LPI’s implementation into the regional climate model COSMO-CLM successfully reproduces the observed lightning climatology, including its latitudinal gradient, its daily and hourly probability distributions, and its diurnal and annual cycles. Besides, the simulated temperature dependence of lightning reflects the observed dependency. The LPI outperforms the CAPE $$\times$$ × PREC parameterization in all applied diagnostics. Based on this satisfactory evaluation, we used the LPI to a climate change projection under the RCP8.5 scenario. For the domain under investigation centered over Germany, the LPI projects a decrease of $$4.8\%$$ 4.8 % in flash rate by the end of the century, in opposition to a projected increase of $$17.4\%$$ 17.4 % as projected using the CAPE $$\times$$ × PREC parameterization. The future decrease of LPI occurs mostly during the summer afternoons and is related to (i) a change in convection occurrence and (ii) changes in the microphysical mixing. The two parameterizations differ because of different convection occurrences in the CPM and non-CPM and because of changes in the microphysical mixing, which is only represented in the LPI lightning parameterization.

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Contrasting lightning projection using the lightning potential index adapted in a convection-permitting regional climate model

10.21203/rs.3.rs-339754/v1 ◽

2021 ◽

Author(s):

Erwan Brisson ◽

Ulrich Blahak ◽

Philippe Lucas-Picher ◽

Christopher Purr ◽

Bodo Ahrens

Keyword(s):

Climate Change ◽

Regional Climate Model ◽

Climate Model ◽

Climate Modeling ◽

Probability Distributions ◽

Deep Convection ◽

Regional Climate ◽

Fine Grid ◽

Flash Rate ◽

Potential Index

Abstract Lightning climate change projections show large uncertainties caused by limited empirical knowledge and strong assumptions inherent to coarse-grid climate modeling. This study addresses the latter issue by implementing and applying the lightning potential index parameterization (LPI) into a fine-grid convection-permitting regional climate model (CPM). This setup takes advantage of the explicit representation of deep convection in CPMs and allows for process-oriented LPI inputs such as vertical velocity within convective cells and coexistence of microphysical hydrometeor types, which are known to contribute to charge separation mechanisms. The LPI output is compared to output from a simpler flash rate parameterization, namely the CAPE x PREC parameterization, applied in a non-CPM on a coarser grid. The LPI's implementation into the regional climate model COSMO-CLM successfully reproduces the observed lightning climatology, including its latitudinal gradient, its daily and hourly probability distributions, and its diurnal and annual cycles. Besides, the simulated temperature dependence of lightning reflects the observed dependency. The LPI outperforms the CAPE x PREC parameterization in all applied diagnostics. Based on this satisfactory evaluation, we used the LPI to a climate change projection under the RCP8.5 scenario. For the domain under investigation centered over Germany, the LPI projects a decrease of 4.8% in flash rate by the end of the century, in opposition to a projected increase of 17.4% as projected using the CAPE x PREC parameterization. The future decrease of LPI occurs mostly during the summer afternoons and is related to (i) a change in convection occurrence and (ii) changes in the microphysical mixing. The two parameterizations differ because of different convection occurrences in the CPM and non-CPM and because of changes in the microphysical mixing, which is only represented in the LPI lightning parameterization.

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Development of probability distributions for regional climate change from uncertain global mean warming and an uncertain scaling relationship

Hydrology and Earth System Sciences ◽

10.5194/hess-11-1097-2007 ◽

2007 ◽

Vol 11 (3) ◽

pp. 1097-1114 ◽

Cited By ~ 25

Author(s):

B. Hingray ◽

A. Mezghani ◽

T. A. Buishand

Keyword(s):

Climate Change ◽

Regional Climate Model ◽

Climate Model ◽

Probability Distributions ◽

Regional Climate ◽

Natural Variability ◽

Model Simulations ◽

Temperature And Precipitation ◽

Climate Model Simulations ◽

Global Mean

Abstract. To produce probability distributions for regional climate change in surface temperature and precipitation, a probability distribution for global mean temperature increase has been combined with the probability distributions for the appropriate scaling variables, i.e. the changes in regional temperature/precipitation per degree global mean warming. Each scaling variable is assumed to be normally distributed. The uncertainty of the scaling relationship arises from systematic differences between the regional changes from global and regional climate model simulations and from natural variability. The contributions of these sources of uncertainty to the total variance of the scaling variable are estimated from simulated temperature and precipitation data in a suite of regional climate model experiments conducted within the framework of the EU-funded project PRUDENCE, using an Analysis Of Variance (ANOVA). For the area covered in the 2001–2004 EU-funded project SWURVE, five case study regions (CSRs) are considered: NW England, the Rhine basin, Iberia, Jura lakes (Switzerland) and Mauvoisin dam (Switzerland). The resulting regional climate changes for 2070–2099 vary quite significantly between CSRs, between seasons and between meteorological variables. For all CSRs, the expected warming in summer is higher than that expected for the other seasons. This summer warming is accompanied by a large decrease in precipitation. The uncertainty of the scaling ratios for temperature and precipitation is relatively large in summer because of the differences between regional climate models. Differences between the spatial climate-change patterns of global climate model simulations make significant contributions to the uncertainty of the scaling ratio for temperature. However, no meaningful contribution could be found for the scaling ratio for precipitation due to the small number of global climate models in the PRUDENCE project and natural variability, which is often the largest source of uncertainty. In contrast, for temperature, the contribution of natural variability to the total variance of the scaling ratio is small, in particular for the annual mean values. Simulation from the probability distributions of global mean warming and the scaling ratio results in a wider range of regional temperature change than that in the regional climate model experiments. For the regional change in precipitation, however, a large proportion of the simulations (about 90%) is within the range of the regional climate model simulations.

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Climate change impacts on hydrological processes in Norway based on two methods for transferring regional climate model results to meteorological station sites

Tellus A Dynamic Meteorology and Oceanography ◽

10.3402/tellusa.v60i3.15307 ◽

2008 ◽

Author(s):

Stein Beldring ◽

Torill Engen-Skaugen ◽

Eirik J. FÃ¸rland ◽

Lars A. Roald

Keyword(s):

Climate Change ◽

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Climate Change Impacts ◽

Meteorological Station ◽

Hydrological Processes

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UNCERTAINTY OF REGIONAL CLIMATE MODEL AND IMPACT ASSESSMENT MODEL TOWARD CLIMATE CHANGE IMPACT ASSESSMENT

Journal of Japan Society of Civil Engineers Ser B1 (Hydraulic Engineering) ◽

10.2208/jscejhe.74.5_i_109 ◽

2018 ◽

Vol 74 (5) ◽

pp. I_109-I_114

Author(s):

Yasuyuki MARUYA ◽

Morihiro HARADA ◽

Rui ITO ◽

Hiroaki KAWASE ◽

Koji DAIRAKU ◽

...

Keyword(s):

Climate Change ◽

Impact Assessment ◽

Regional Climate Model ◽

Climate Change Impact ◽

Climate Model ◽

Regional Climate ◽

Assessment Model ◽

Climate Change Impact Assessment ◽

Change Impact

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Assessing the impacts of climate change on the water resources in the Nile Basin using a regional climate model ensemble

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1307/6/29/292017 ◽

2009 ◽

Vol 6 (29) ◽

pp. 292017 ◽

Cited By ~ 1

Author(s):

Carlo Buontempo ◽

J K Lørup ◽

M A Antar ◽

M Sanderson ◽

M B Butts ◽

...

Keyword(s):

Climate Change ◽

Water Resources ◽

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Model Ensemble ◽

Nile Basin ◽

Impacts Of Climate Change

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On the added value of the regional climate model REMO in the assessment of climate change signal over Central Africa

Climate Dynamics ◽

10.1007/s00382-017-3547-7 ◽

2017 ◽

Vol 49 (11-12) ◽

pp. 3813-3838 ◽

Cited By ~ 24

Author(s):

Thierry C. Fotso-Nguemo ◽

Derbetini A. Vondou ◽

Wilfried M. Pokam ◽

Zéphirin Yepdo Djomou ◽

Ismaïla Diallo ◽

...

Keyword(s):

Climate Change ◽

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Central Africa ◽

Added Value ◽

Climate Change Signal

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Regionalization of Climate Change Simulations over the Eastern Mediterranean

Journal of Climate ◽

10.1175/2008jcli1807.1 ◽

2009 ◽

Vol 22 (8) ◽

pp. 1944-1961 ◽

Cited By ~ 75

Author(s):

Bariş Önol ◽

Fredrick H. M. Semazzi

Keyword(s):

Climate Change ◽

Regional Climate Model ◽

Temperature Increase ◽

Climate Model ◽

Eastern Mediterranean ◽

Regional Climate ◽

Future Climate ◽

Climate Change Projections ◽

Model Simulations ◽

The Future

Abstract In this study, the potential role of global warming in modulating the future climate over the eastern Mediterranean (EM) region has been investigated. The primary vehicle of this investigation is the Abdus Salam International Centre for Theoretical Physics Regional Climate Model version 3 (ICTP-RegCM3), which was used to downscale the present and future climate scenario simulations generated by the NASA’s finite-volume GCM (fvGCM). The present-day (1961–90; RF) simulations and the future climate change projections (2071–2100; A2) are based on the Intergovernmental Panel on Climate Change (IPCC) greenhouse gas (GHG) emissions. During the Northern Hemispheric winter season, the general increase in precipitation over the northern sector of the EM region is present both in the fvGCM and RegCM3 model simulations. The regional model simulations reveal a significant increase (10%–50%) in winter precipitation over the Carpathian Mountains and along the east coast of the Black Sea, over the Kackar Mountains, and over the Caucasus Mountains. The large decrease in precipitation over the southeastern Turkey region that recharges the Euphrates and Tigris River basins could become a major source of concern for the countries downstream of this region. The model results also indicate that the autumn rains, which are primarily confined over Turkey for the current climate, will expand into Syria and Iraq in the future, which is consistent with the corresponding changes in the circulation pattern. The climate change over EM tends to manifest itself in terms of the modulation of North Atlantic Oscillation. During summer, temperature increase is as large as 7°C over the Balkan countries while changes for the rest of the region are in the range of 3°–4°C. Overall the temperature increase in summer is much greater than the corresponding changes during winter. Presentation of the climate change projections in terms of individual country averages is highly advantageous for the practical interpretation of the results. The consistence of the country averages for the RF RegCM3 projections with the corresponding averaged station data is compelling evidence of the added value of regional climate model downscaling.

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