Convection-permitting Regional Climate Model Research Articles

Correction to: Evaluation of Alpine-Mediterranean precipitation events in convection-permitting regional climate models using a set of tracking algorithms

Correction to: Evaluation of Alpine-Mediterranean precipitation events in convection-permitting regional climate models using a set of tracking algorithms

Enhanced Role of Convection in Future Hourly Rainfall Extremes Over South Korea

AbstractA convection‐permitting regional climate model (CPRCM) with 2.5 km resolution has been simulated over South Korea for current and future conditions, and the role of convection in the scaling of hourly extreme precipitation (EP) with temperature is examined. It is found that the CPRCM can reproduce the observed super Clausius‐Clapeyron (C‐C) scaling for hourly EP. Precipitation type estimated based on the convective available potential energy reveals the important role of convection in the super C‐C scaling. Fraction of convective rainfall events increases rapidly with temperature, and the contribution of convection becomes dominant in future simulations under high‐emission scenarios. In the late 21st century, as temperature ranges shift to warmer conditions, unprecedented hourly extreme rainfall events are projected to occur particularly during the late summer season. Future changes in hourly extreme events are found to be affected much by boundary conditions from different global climate models.

Evaluation of Alpine-Mediterranean precipitation events in convection-permitting regional climate models using a set of tracking algorithms

We here inter-compare four different tracking algorithms by applying them onto the precipitation fields of an ensemble of convection-permitting regional climate models (cpRCMs) and on high-resolution observational datasets of precipitation. The domain covers the Alps and the northern Mediterranean and thus we here analyse heavy precipitation events, that are renowned for causing hydrological hazards. In this way, this study is both, an inter-comparison of tracking algorithms as well as an evaluation study of cpRCMs in the Lagrangian frame of reference. The tracker inter-comparison is performed by comparison of two case studies as well as of climatologies of cpRCMs and observations. We find that that all of the trackers produce qualitatively equal results concerning characteristic track properties. This means that, despite of quantitative differences, equivalent scientific conclusions would be drawn. This result suggests that all trackers investigated are reliable analysis tools of atmospheric research. With respect to the model ensemble evaluation, we find an encouraging performance of cpRCMs in comparison to radar-based observations. In particular prominent hotspots of heavy precipitation events are well-reproduced by the models. In general most characteristic properties of precipitation events have positive biases. Assuming the under-catchment of precipitation in observations in a domain of such complex orography, this result is to be expected. Only the mean area of tracks is underestimated, while their duration is overestimated. Mean precipitation rate is estimated well, while maximum precipitation rate is overestimated. Furthermore, geometrical and rain volume are overestimated. We find that models overestimate the occurrence of precipitation events over all mountain chains, whereas over plain terrain in summer precipitation events are seen underestimated. This suggests that, despite the convection-permitting resolution, thermally driven thunderstorms are either not triggered or their dynamics still under-resolved. Eventually we find that biases in the spatio-temporal properties of precipitation events appear reduced when evaluating cpRCMs against Doppler radar-based and rain gauge-adjusted observational datasets of comparable spatial resolution, strengthening their role in evaluation studies.

Dynamic and Thermodynamic Factors Involved in Future Changes in Extreme Summertime Precipitation in Japan Projected by Convection-Permitting Regional Climate Model Simulations

Abstract Dynamic and thermodynamic factors involved in future changes in local-scale short-term extreme summertime precipitation on the mesoscale and hourly time scale in Japan were examined using convection-permitting regional climate model simulations under the representative concentration pathway 8.5 scenario. The change in the dynamic component primarily contributes to the total change in vertically integrated moisture flux convergence over the analysis domain that is located off Okinawa Island, whereas the thermodynamic component is dominant over the analysis domain that is located off Kyushu Island. Differences in the amount of the dynamic and thermodynamic components are noticeable in these two domains. These results are explained by the difference in the vertical profiles of the convergence term, and hence the convergence itself between the two specific domains. A mesoscale low pressure system on the seasonal rain front—termed the baiu front—is a key factor underlying the difference in the magnitudes and vertical profiles of convergence between the two specific domains. In the vicinity of the domain off Okinawa Island, a mesoscale low pressure system on the baiu front enhances low-level convergence in the future climate when compared with the present climate. This atmospheric state is attributable to the location of the baiu front itself, which is located relatively southward in the future climate and is affected by the domain off Okinawa Island. In the domain where the dynamic component is dominant such as the domain off Okinawa Island, the total moisture flux convergence follows a super–Clausius–Clapeyron scaling.

The projection of canadian wind energy potential in future scenarios using a convection-permitting regional climate model

The distribution of wind resources in the future will be altered by climate change. The high-resolution regional climate model is a powerful tool for predicting wind power changes. We use a pair of 4-km convection-permitting Weather Research Forecasting (WRF) simulations over southern Canada to study wind energy. The high-resolution model better represents orography and the underlying surface that strongly affect near-surface winds. The simulations include a historical simulation (CTRL) of 13 years (2001–2013) and a future projection for the end of the 21st century (RCP 8.5 scenario), using the Pseudo Global Warming (PGW) approach. The wind power density (WPD) and extractable wind power (EWP) obtained from the winds from the two simulations are analyzed and compared. In the future, the wind energy potential over most areas of Canada will decrease, while the changes over current wind farms, located in optimal locations, would be less significant in terms of EWP. In fact, there will be a slight increase of EWP distributed along the coastal area of Eastern Quebec and the Great Lakes regions in southern Ontario. The changes also show seasonal and diurnal variations: In winter when wind energy growth is more significant, a larger magnitude of changes occurs at noon

Future changes in extreme precipitation over the San Francisco Bay Area: Dependence on atmospheric river and extratropical cyclone events

Extreme precipitation poses a major challenge for local governments, including the City and County of San Francisco, California, as flooding can damage and destroy infrastructure and property. As the climate continues to warm, reliable future precipitation projections are needed to provide the best possible information to decision makers. However, future changes in the magnitude of extreme precipitation are uncertain, as current state-of-the-art global climate models are typically run at relatively coarse horizontal resolutions that require the use of convective parameterization and have difficulty simulating observed extreme rainfall rates. Here, we performed ensembles of convection-permitting regional climate model simulations to investigate how five historically impactful extreme precipitation events over the San Francisco Bay Area could change if similar events occurred in future climates. We found that changes in storm-total precipitation depend strongly on storm type. Precipitation associated with an atmospheric river (AR) accompanied by an extratropical cyclone (ETC) is projected to increase at a rate exceeding (by up to 1.5 times) the theoretical Clausius Clapeyron scaling of 6–7% per °C warming. On the other hand, future precipitation changes are weak or negative for events characterized by an AR only, despite increases in precipitable water and integrated vapor transport that are similar to those of the co-occurring AR and ETC events. The differences in the sign of future precipitation change between AR-only events and co-occurring AR and ETC events is instead linked with changes in mid-tropospheric vertical velocity. Given that the majority of observed ARs are associated with an ETC, this research has important implications for future precipitation impacts over the Bay Area, as it indicates that storm-total precipitation associated with the most common type of storm event may increase by up to 26–37% in 2100 relative to historical.

Dynamics of Probable Maximum Precipitation Within Coastal Urban Areas in a Convection-Permitting Regional Climate Model

The west coast of Canada is strongly affected by the extreme precipitation events triggered by frequent atmospheric river (AR) activities over the eastern North Pacific. Across the region, assessing the probable maximum precipitation (PMP), can provide valuable information for resilience building of the coastal communities that are vulnerable to hydrological risks. In this study, a 3-km convection-permitting regional climate model is used to physically estimate the PMP in Vancouver. This technique maximizes the effect of AR-related water vapor transport by spatially adjusting the lateral boundary conditions (LBCs) of the model simulations for the selected AR-related extreme precipitation events. The PMP in Vancouver is identified among the simulations driven by the spatially adjusted LBCs that are corresponding with the AR-induced “worst-case scenario,” i.e., landfalling ARs hit Vancouver with optimal landfalling location and transport direction. Results suggest that the PMP in Vancouver, in terms of the maxima of the regionally averaged 72-h total precipitation for the historical extreme precipitation events, is up to 790 mm, which is 130% greater than the historical peak precipitation for the period 1980∼2017. On average, all the PMP simulations shows an overall increase by 81% in precipitation by relative to historical simulations. In addition, the PMP simulations suggested an overall decrease in snowfall by 12% due to the warmer near-surface air temperature; however, a pronounced increase in freezing rain is seen. The precipitation increase for the estimated PMP relative to the historical extreme precipitation is closely associated with the increased atmospheric moisture transport and the changes in the atmospheric dynamic factors when the AR effects are maximized. These include the enhanced low-tropospheric ascent and moisture transport convergence, which can induce stronger depletion of atmospheric moistures as indicated by the increased precipitation efficiency.

Improved summer daily and sub-daily precipitation over Eastern China in convection-permitting simulations

Based on the long-term (1998–2007) regional climate simulations using the Weather Research and Forecasting (WRF) model with three different horizontal resolutions (36 km, 12 km and 4 km), this work examines the improvement of convection-permitting regional climate model (CP RCM) in simulating the daily and sub-daily precipitation over eastern China. CP RCM produces more reliable mean precipitation and more realistic wet day frequency as well as better low-level wind and moisture than those in the convection-parameterized counterpart. Due to the more realistic surface heterogeneities, CP RCM distinctly improves the representation of hourly precipitation by increasing the occurrence of high-intensity precipitation compared to the 36-km and 12-km simulations, especially over areas with complex topography. Moreover, the improvement of diurnal variation of low-level wind direction and moisture convergence also coincides with the more reasonable diurnal amplitude and nocturnal precipitation in CP RCM as compared to the 12-km and 36-km simulations. Because of the better depiction of convection and its interaction with large-scale motions, CP RCM has a clear advantage in reproducing low-level wind and moisture, which lead to the better reproduced sub-daily precipitation. This study provides greater confidence in the projection of future climate change using CP RCM.

Correction to: Modelling Mediterranean heavy precipitation events at climate scale: an object-oriented evaluation of the CNRM-AROME convection-permitting regional climate model

Correction to: Modelling Mediterranean heavy precipitation events at climate scale: an object-oriented evaluation of the CNRM-AROME convection-permitting regional climate model

Convection‐permitting modeling with regional climate models: Latest developments and next steps

AbstractApproximately 10 years ago, convection‐permitting regional climate models (CPRCMs) emerged as a promising computationally affordable tool to produce fine resolution (1–4 km) decadal‐long climate simulations with explicitly resolved deep convection. This explicit representation is expected to reduce climate projection uncertainty related to deep convection parameterizations found in most climate models. A recent surge in CPRCM decadal simulations over larger domains, sometimes covering continents, has led to important insights into CPRCM advantages and limitations. Furthermore, new observational gridded datasets with fine spatial and temporal (~1 km; ~1 h) resolutions have leveraged additional knowledge through evaluations of the added value of CPRCMs. With an improved coordination in the frame of ongoing international initiatives, the production of ensembles of CPRCM simulations is expected to provide more robust climate projections and a better identification of their associated uncertainties. This review paper presents an overview of the methodology to produce CPRCM simulations and the latest research on the related added value in current and future climates. Impact studies that are already taking advantage of these new CPRCM simulations are highlighted. This review paper ends by proposing next steps that could be accomplished to continue exploiting the full potential of CPRCMs.This article is categorized under: Climate Models and Modeling > Earth System Models

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

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.

An Analysis of (Sub-)Hourly Rainfall in Convection-Permitting Climate Simulations Over Southern Sweden From a User’s Perspective

To date, the assessment of hydrological climate change impacts, not least on pluvial flooding, has been severely limited by i) the insufficient spatial resolution of regional climate models (RCMs) as well as ii) the simplified description of key processes, e.g., convective rainfall generation. Therefore, expectations have been high on the recent generation of high-resolution convection-permitting regional climate models (CPRCMs), to reproduce the small-scale features of observed (extreme) rainfall that are driving small-scale hydrological hazards. Are they living up to these expectations? In this study, we zoom in on southern Sweden and investigate to which extent two climate models, a 3-km resolution CPRCM (HCLIM3) and a 12-km non-convection permitting RCM (HCLIM12), are able to reproduce the rainfall climate with focus on short-duration extremes. We use three types of evaluation–intensity-based, time-based and event-based–which have been designed to provide an added value to users of high-intensity rainfall information, as compared with the ways climate models are generally evaluated. In particular, in the event-based evaluation we explore the prospect of bringing climate model evaluation closer to the user by investigating whether the models are able to reproduce a well-known historical high-intensity rainfall event in the city of Malmö 2014. The results very clearly point at a substantially reduced bias in HCLIM3 as compared with HCLIM12, especially for short-duration extremes, as well as an overall better reproduction of the diurnal cycles. Furthermore, the HCLIM3 model proved able to generate events similar to the one in Malmö 2014. The results imply that CPRCMs offer a clear potential for increased confidence in future projections of small-scale hydrological climate change impacts, which is crucial for climate-proofing, e.g., our cities, as well as climate modeling in general.

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

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 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% in flash rate by the end of the century, in opposition to a projected increase of 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.

Dryline characteristics in North America’s historical and future climates

Drylines are atmospheric boundaries separating dry from moist air that can initiate convection. Potential changes in the location, frequency, and characteristics of drylines in future climates are unknown. This study applies a multi-parametric algorithm to objectively identify and characterize the dryline in North America using convection-permitting regional climate model simulations with 4-km horizontal grid spacing for 13-years under a historical and a pseudo-global warming climate projection by the end of the century. The dryline identification is successfully achieved with a set of standardized algorithm parameters across the lee side of the Rocky Mountains from the Canadian Rockies to the Sierra Madres in Mexico. The dryline is present 27% of the days at 00 UTC between April and September in the current climate, with a mean humidity gradient magnitude of 0.16 g−1 kg−1 km−1. The seasonal cycle of drylines peak around April and May in the southern Plains, and in June and July in the northern Plains. In the future climate, the magnitude and frequency of drylines increase 5% and 13%, correspondingly, with a stronger intensification southward. Future drylines strengthen during their peak intensity in the afternoon in the Southern U.S. and Northeast Mexico. Drylines also show increasing intensities in the morning with future magnitudes that are comparable to peak intensities found in the afternoon in the historical climate. Furthermore, an extension of the seasonality of intense drylines could produce end-of-summer drylines that are as strong as mid-summer drylines in the current climate. This might affect the seasonality and the diurnal cycle of convective activity in future climates, challenging weather forecasting and agricultural planning.

Synoptic forcing associated with extreme precipitation events over Southeastern South America as depicted by a CORDEX FPS set of convection-permitting RCMs

Southeastern South America (SESA) stands out as a remarkable region of occurrence of deep convection. This is mainly due to the proximity of the Andes, which eventually determine their magnitude and intensity. In this work, we used a set of convection-permitting (4 km horizontal resolution) regional climate models to explore their ability to reproduce the synoptic forcings that trigger deep convection over La Plata basin. The study considered simulating three extreme convective precipitation events in two different timescales. On one hand, a short-term simulation initiated a few hours before the onset of each event, spanning 3–4 days. On the other hand, as regional climate modelling, a 6-month simulation that includes the three selected events. In contrast to parameterized convection, the convection-permitting resolutions not only intensified the events, but also modified the location of the maximum precipitation by modulating the low-level atmospheric circulation. Vertically integrated moisture flux convergence emerged as a noticeable footprint of deep moist convection, regardless of the model and timescale. The performance of the models in reproducing the observed precipitation was also quantitatively analyzed. The skill depends on the spatial scale. The results were case-dependent in the short-term simulations. However, an analysis over multiple events in the long-term simulations revealed that, in general, convection-permitting resolutions better capture the spatial distribution of the extreme precipitation in SESA. The study comprises the first multi-model ensemble of convection-permitting simulations over the region, a seed for a further analysis with a more complete ensemble to better understand the results presented here.

Modelling Mediterranean heavy precipitation events at climate scale: an object-oriented evaluation of the CNRM-AROME convection-permitting regional climate model

Modelling the rare but high-impact Mediterranean Heavy Precipitation Events (HPEs) at climate scale remains a largely open scientific challenge. The issue is adressed here by running a 38-year-long continuous simulation of the CNRM-AROME Convection-Permitting Regional Climate Model (CP-RCM) at a 2.5 km horizontal resolution and over a large pan-Alpine domain. First, the simulation is evaluated through a basic Eulerian statistical approach via a comparison with selected high spatial and temporal resolution observational datasets. Northwestern Mediterranean fall extreme precipitation is correctly represented by CNRM-AROME at a daily scale and even better at an hourly scale, in terms of location, intensity, frequency and interannual variability, despite an underestimation of daily and hourly highest intensities above 200 mm/day and 40 mm/h, respectively. A comparison of the CP-RCM with its forcing convection-parameterised 12.5 km Regional Climate Model (RCM) demonstrates a clear added value for the CP-RCM, confirming previous studies. Secondly, an object-oriented Lagrangian approach is proposed with the implementation of a precipitating system detection and tracking algorithm, applied to the model and the reference COMEPHORE precipitation dataset for twenty fall seasons. Using French Mediterranean HPEs as objects, CNRM-AROME’s ability to represent the main characteristics of fall convective systems and tracks is highlighted in terms of number, intensity, area, duration, velocity and severity. Further, the model is able to simulate long-lasting and severe extreme fall events similar to observations. However, it fails to reproduce the precipitating systems and tracks with the highest intensities (maximum intensities above 40 mm/h) well, and the model’s tendency to overestimate the cell size increases with intensity.

The Projection of Canadian Wind Energy Potential in Future Scenarios Using a Convection-Permitting Regional Climate Model

The Projection of Canadian Wind Energy Potential in Future Scenarios Using a Convection-Permitting Regional Climate Model

A Hybrid Downscaling Approach for Future Temperature and Precipitation Change

AbstractWe used empirical–statistical downscaling in a pseudoreality context, in which both large-scale predictors and small-scale predictands were based on climate model results. The large-scale conditions were taken from a global climate model, and the small-scale conditions were taken from dynamical downscaling of the same global model with a convection-permitting regional climate model covering southern Norway. This hybrid downscaling approach, a “perfect model”–type experiment, provided 120 years of data under the CMIP5 high-emission scenario. Ample calibration samples made rigorous testing possible, enabling us to evaluate the effect of empirical–statistical model configurations and predictor choices and to assess the stationarity of the statistical models by investigating their sensitivity to different calibration intervals. The skill of the statistical models was evaluated in terms of their ability to reproduce the interannual correlation and long-term trends in seasonal 2-m temperature T2m, wet-day frequency fw, and wet-day mean precipitation μ. We found that different 30-yr calibration intervals often resulted in differing statistical models, depending on the specific choice of years. The hybrid downscaling approach allowed us to emulate seasonal mean regional climate model output with a high spatial resolution (0.05° latitude and 0.1° longitude grid) for up to 100 GCM runs while circumventing the issue of short calibration time, and it provides a robust set of empirically downscaled GCM runs.

Future Changes in the Hydrologic Cycle Associated with Flood-Producing Storms in California

AbstractCalifornia receives much of its precipitation from cool-season atmospheric rivers, which contribute to water resources and flooding. In winter 2017, a large number of atmospheric rivers caused anomalous winter precipitation, near-saturated soils, and a partial melting of snowpack, which led to excessive runoff that damaged the emergency spillway of the Oroville Dam. Given the positive and negative impacts ARs have in California, it is necessary to understand how they will change in a future climate. While prior studies have examined future changes in the frequency of atmospheric rivers impacting the West Coast of the United States, these studies primarily use coarse global climate models that are unable to resolve the complex terrain of this region. Such a limitation is overcome by using a high-resolution convection-permitting regional climate model, which resolves complex topography and orographic rainfall processes that are the main drivers of heavy precipitation in landfalling atmospheric rivers. This high-resolution model is used to examine changes to precipitation and runoff in California’s cool season from 2002 to 2013, particularly in flood-producing storms associated with atmospheric rivers, in a future, warmer climate using a pseudo–global warming approach. In 45 flood-producing storms, precipitation and runoff increase by 21%–26% and 15%–34%, respectively, while SWE decreases by 32%–90%, with the greatest changes at mid-elevations. These trends are consistent with future precipitation changes during the entire cool season. Results suggest more intense floods and less snowpack available for water resources in the future, which should be carefully considered in California’s future water management plans.

Mid-Century Changes in the Mean and Extreme Climate in the Kingdom of Saudi Arabia and Implications for Water Harvesting and Climate Adaptation

The Kingdom of Saudi Arabia (KSA) is a water-scarce region with a dry, desert climate, yet flood-producing precipitation events and heat extremes lead to loss of life and damages to local infrastructure, property and economy. Due to its distinctive natural and man-made spatial features (e.g., coastal features, wadis, agricultural areas) studying changes in the mean climate and extreme events requires higher-resolution climate projections than those available from the current generation of Earth System Models. Here, a high-resolution convection-permitting regional climate model is used to downscale the middle of the 21st century (2041–2050) climate projections of the Community Earth System Model (CESM) under representative concentration pathway (RCP) 8.5 and for a historical time period (2008–2017) focusing on two months (August and November) within KSA’s dry-hot and wet seasons, where extreme events have historically been observed more frequently. Downscaling of climate reanalysis is also performed for the historical time period (2008–2017) to evaluate the downscaling methodology. An increase in the intensity and frequency of precipitation events is found in August by mid-century, particularly along the mountainous western coast of KSA, suggesting potential for water harvesting. Conversely, the northern flank of the Empty Quarter experiences a noticeable reduction in mean and extreme precipitation rates during the wet season. Increasing August heat index is found to particularly make regional habitability difficult in Jeddah by mid-century.