Local versus regional impact changes for storms like Boris (2024): insights from high-resolution pseudo global warming simulations

Accurately assessing cyclone intensity changes due to global warming is crucial for predicting and mitigating sequential hazards. This study develops a high-resolution, fully coupled air–sea model to investigate the impact of global warming on Supertyphoon Mangkhut (2018). A numerical sensitivity analysis is conducted using the pseudo–global warming (PGW) technique based on multiple global climate models (GCMs) from phase 6 of Coupled Model Intercomparison Project (CMIP6). Under ocean warming scenarios, the increasing average sea surface temperature (SST) by 2.26°, 2.44°, 3.45°, and 4.53°C results in reductions in the minimum sea level pressure by 9.2, 10.6, 15.7, and 19.4 hPa, respectively, compared to the original state of Typhoon Mangkhut. Rising SST increases the turbulent heat flux; to be specific, an average SST increase of 2.26°–4.53°C changes the turbulent heat flux into 177%–272% of the original value. Besides, stronger winds enhance SST cooling, including upwelling and entrainment, leading to an increase in the mixed layer depth (MLD). Tropical cyclone heat potential (TCHP) tends to be enhanced under the combined influences as the SST rises. An average increase in the SST of 2.26°, 2.44°, 3.45°, and 4.53°C leads to an increase in the TCHP of 9.94%, 9.85%, 14.67%, and 15.30%, respectively. However, future changes in atmospheric temperature and humidity will moderate typhoon intensification induced by ocean warming. Considering atmospheric conditions, the maximum wind speed decreases by approximately 10% compared to only considering ocean warming. Nevertheless, typhoon intensity is projected to strengthen under future climate change. Significance Statement This study examines the role of global warming in typhoon intensity and the response of typhoon events to changes in the oceanic thermal structure. Sensitivity experiments considering future warming climates are conducted using a fully coupled air–sea numerical model. An average increase in sea surface temperature (SST) by 4.53°C can lead to a reduction in the minimum sea level pressure by 19.4 hPa. Ocean warming enhances oceanic mixing, potentially increasing the availability of heat energy for typhoon’s development (i.e., an average increase in SST by 4.53°C leads to a 15.30% increase in heat energy). However, future changes in atmospheric temperature and humidity will moderate the intensification of typhoons induced by ocean warming. These results are expected to provide information for assessing the future changes in typhoon intensity under a warming climate, which is important for predicting and reducing sequential risks.

<p>In general terms, climate adaptation in cities is highly complicated by the very high required spatial and temporal resolution. The high resolution is needed to capture both the full variability of small-scale high-impact weather phenomena and the associated response from the mosaic of land uses and buildings in urban environments. Most commonly available climate model simulations and projections are too spatially coarse (≥10 km) for a proper assessment of many important urban climate impacts. </p><p>In terms of water-related impacts, a key issue concerns the reproduction of local short-duration rainfall extremes (cloudbursts) that may cause pluvial flooding. An accurate reproduction of the convective generation of such extremes requires a spatial resolution of at least 5 km, preferably even higher, in convection-permitting regional climate models (CPRCM). Conceivably, estimates of future changes in cloudburst characteristics and associated statistics based on CPRCM simulations will be more reliable than today’s estimates based on non-CP RCMs. Because of the extreme computational demand, however, the number of CPRCM simulations made is still rather low and generally limited to small domains and/or short time slices.</p><p>But many efforts are currently being made in this direction and the main focus of this presentation will be a case study evaluation of hourly rainfall extremes from 3×3 km² convection-permitting simulations with the HARMONIE-climate model over the Nordic region. The case study will focus on the region around the Öresund strait, that connects southern Sweden and eastern Denmark. This region contains the cities Malmö and Copenhagen that were both hit by heavy cloudburst in the last decade, that caused severe flooding and substantial damage to infrastructure.</p><p>The presentation will include different aspects of the simulations and their applicability:</p><ul><li><em>Historical performance.</em> Evaluation of reference period simulations, with both ERA-Interim and GCM boundaries, against high-resolution observations, focusing at the reproduction of short-duration (sub-daily) extremes but also e.g. diurnal cycle and spatial variability.</li> <li><em>Future changes.</em> Assessment in terms of climate factors for different durations, return periods and future time horizons. A comparison is made with climate factors estimated from lower-resolution, non-convection permitting downscalings based on the same GCM projections.</li> <li><em>End-user practices.</em> A discussion of what resolution that is needed in order to meet different stakeholders’ needs in the light of climate adaptation. The key question is how the output from CPRCM simulations can be processed and interpreted to provide an added value. </li> </ul><p>Besides the above analyses, two additional related investigations will be presented:</p><ul><li>Lessons learnt from experiments of tailored “urban downscaling” of climate projections down to 1×1 km² and 15 min over selected European urban regions (Stockholm, Bologna, Amsterdam) performed in the Urban SIS project.</li> <li>An evaluation of hourly rainfall extremes over selected European countries in a 11×11 km² EURO-CORDEX ensemble, including spatial patterns and temperature scaling of the estimated future changes.</li> </ul>

We present here the first climatology of extreme sub-daily rainfall for a large part of western Europe, developed using a newly developed set of sub-daily rainfall indices, derived from a recently created global sub-daily rainfall (GSDR) dataset. The indices describe sub-daily (3-hourly) rainfall extremes in terms of their intensity, frequency and timing. Analysis of the frequency index (number of 3hr periods with >20 mm rain (R3hr20mm)) and a suite of intensity indices including the annual maxima (Rx3hr) and values of the 99.9th percentile at each gauge (R99.9p3hr) indicate a peak in the frequency and intensity of short-duration rainfall extremes in summer across most of western Europe, while areas around the north-west Mediterranean experience the highest intensities and frequencies of 3-hr rainfall in autumn. The index of contribution from 3-h annual maxima to the daily total (Rx3hrP) indicates that these events are often produced by very short-duration or very peaked storms, with a tendency towards a late afternoon or evening peak in the time of occurrence. There are also clear differences in the spatiotemporal occurrence of the sub-daily extremes when compared to extreme daily rainfall indices, which could have repercussions for flood management. Additional analysis of the sub-daily rainfall indices within the context of Köppen-Geiger climate zones indicates Mediterranean-type climate zones experience more intense and more frequent sub-daily extremes, while the intensity of rainfall within cooler climate zones is lower and the most intense events are restricted to summer. The climate zones are found to be a relatively good indicator of the extreme rainfall characteristics that can be expected in a region. Being able to compare sub-daily rainfall characteristics across a wide region in this manner greatly enhances our ability to investigate future variability and change in sub-daily extremes and will aid in high-resolution climate model validation.

Mesoscale convective systems (MCSs) and isolated deep convection (IDC) significantly influence local weather conditions and the hydrological cycle across the United States. Their future changes under warming is critical to the society. However, the exact impacts of thermodynamic environmental changes on them are difficult to resolve using climate model simulations which integrate both dynamic and thermodynamic factors. This study explores a theoretical modeling approach to isolate environmental thermodynamic effects on their future changes through a case study. For a 50‐day period during the 2020 summer, a pair of convection‐permitting model simulations indicate contrasting changes in MCSs and IDC between inland and coastal regions under pseudo global warming. Driven by the thermodynamic environments of these simulations, a single‐column parcel model indicates a decrease in the frequency of IDC occurrences, along with increases in duration and precipitation amount under warming, attributable to rising most unstable convective available potential energy (MUCAPE), convective inhibition (MUCIN), and precipitable water (PW). A multi‐column parcel model reveals contrasting changes in the frequency and mean area of MCSs between inland and coastal regions, underscoring the increase in mean MUCIN over inland regions and increases in mean MUCAPE and PW over coastal regions. The increase in mean MCS area over inland regions is linked to the interplay between accelerated gust fronts and enhanced subsidence strength, which is further traced to the unchanged mean MUCIN but increased mean MUCAPE in large‐scale environments. These case study results suggest a major role of thermodynamic environmental changes in controlling characteristics of MCSs and IDC under warming.

The impacts of global warming/climate change on extreme rainfall events during the Baiu period in Japan and their dependency on weather patterns (WPs) were examined using the self-organizing map (SOM) method. To investigate the differences in climate change impacts on daily rainfall among the WPs, a SOM was applied to surface atmospheric circulation data from the Database for Policy Decision Making for Future Climate Change (d4PDF) to determine the dominant heavy rainfall WPs. The obtained SOM shows that different WPs are associated with regional variations in extreme rainfall events. Projected future changes in the occurrence of heavy rainfall displayed a non-uniform spatial distribution. To understand the spatial heterogeneous rainfall changes, the sensitivity of heavy rainfall WPs to climate forcing was evaluated. Results of the SOM analysis suggest that this regional variation in the future changes in extreme rainfall events could be attributed to sensitivity differences between WPs to the climate changes. These sensitivity differences can be attributed to the non-uniform spatial changes in the large-scale climatological background state in East Asia via modulations in the moist air intrusion into Japan.

Over the Quaternary, the geographic distributions of many species have experienced shifts in response to climatic changes. We examined the range-shift patterns of six oak (Quercus) species occupying different climatic zones of the western Palearctic under both past and future climate conditions. Using ecological niche models, we reconstructed distributions during the Last Glacial Maximum (LGM, ~22,000 years before present), compared them to the Present, and projected future changes under two scenarios for 2081-2100 (SSP1-2.6 and SSP5-8.5). Quantitative metrics of latitudinal centroid movement, range limits, and area change revealed consistent contrasts among climatic groups. During the LGM, temperate (Q. robur and Q. petraea) and transition-zone (Q. cerris and Q. pubescens) species contracted strongly, persisting in southern refugia across Anatolia, the Balkans, and the western Mediterranean, whereas Mediterranean oaks (Q. coccifera and Q. suber) retained more stable ranges. Future projections suggest that temperate and transition-zone species will undergo substantial range loss and poleward shifts, particularly under the pessimistic scenario, whereas Mediterranean oaks will experience limited latitudinal shifts but pronounced expansion in to northern latitudes and temperate regions. These findings indicate Mediterranean oaks are ecologically distinct from temperate and transition-zone species, which show similar climate sensitivities. Our results emphasize the need for climate-zone-specific conservation strategies, including enhancing connectivity and genetic diversity for temperate and transition-zone species, and prioritizing drought-resilient populations and adaptive management for Mediterranean species, to support the long-term resilience of European oak forests under ongoing and future climate change.

A regional atmospheric climate model with multi-layer snow module (RACMO2) is forced at the lateral boundaries by global climate model (GCM) data to assess the future climate and surface mass balance (SMB) of the Antarctic ice sheet (AIS). Two different GCMs (ECHAM5 until 2100 and HadCM3 until 2200) and two different emission scenarios (A1B and E1) are used as forcing to capture a realistic range in future climate states. Simulated ice sheet averaged 2 m air temperature (T2m) increases (1.8–3.0 K in 2100 and 2.4–5.3 K in 2200), simultaneously and with the same magnitude as GCM simulated T2m. The SMB and its components increase in magnitude, as they are directly influenced by the temperature increase. Changes in atmospheric circulation around Antarctica play a minor role in future SMB changes. During the next two centuries, the projected increase in liquid water flux from rainfall and snowmelt, together 60–200 Gt year−1, will mostly refreeze in the snow pack, so runoff remains small (10–40 Gt year−1). Sublimation increases by 25–50 %, but remains an order of magnitude smaller than snowfall. The increase in snowfall mainly determines future changes in SMB on the AIS: 6–16 % in 2100 and 8–25 % in 2200. Without any ice dynamical response, this would result in an eustatic sea level drop of 20–43 mm in 2100 and 73–163 mm in 2200, compared to the twentieth century. Averaged over the AIS, a strong relation between \(\Updelta\)SMB and \(\Updelta\hbox{T}_{2{\rm m}}\) of 98 ± 5 Gt w.e. year−1 K−1 is found.

High impact weather events such as extreme temperatures or rainfall can cause significant disruption across the UK affecting sectors such as health, transport, agriculture and energy. In this study we draw on the latest set of UK climate projections, UKCP, to examine metrics relating to high-impact weather over the UK and how these change with different levels of future global warming from 1.5 °C to 4 °C above pre-industrial. The changes to these hazards show increases in the frequency of extremely hot days and nights, with a UK average increase in hot days of between 5 and 39 days per year between 1.5 °C and 4 °C of global warming. Projections indicate an increase in cooling degree days of 134–627% and an increase in growing degree days of 19–60% between 1.5 °C and 4 °C of global warming. Extremely hot nights, which are currently rare, are emerging as more common occurrences. The frequency of high daily temperatures and rainfall increase systematically, while the frequency of very cold conditions (based on days where temperatures fall below 0 °C) is shown to decrease by 10 to 49 days per year. A reduction in heating degree days, of 11–32% between 1.5 °C and 4 °C of warming, is projected. Levels of daily rainfall, which currently relate to increased risk of river flooding, are shown to increase across the country, with increases of days with high impact levels of rainfall occurring by 1 to 8 days per year between 1.5 °C and 4 °C of warming. Average drought severity is projected to increase for 3-, 6-, 12- and 36-month-long droughts. The largest changes in the severity of the 12-month drought are between −3 and +19% between 1.5 °C and 4 °C of warming and for 36-month drought between −2 and +54% between 1.5 °C and 4 °C of warming. The projected future changes in high impact weather from this study will enable the characterization of climate risks and ultimately be able to better inform adaptation planning in different sectors to support the increase in resilience of the UK to future climate variability and change.

Chapter 11 - Analysis of extreme rainfall events under the climatic change

Tropical cyclones (TCs) can produce large rainfall totals which lead to devastating flooding, loss of life, and significant damage to infrastructure. Many studies have examined future changes in TC precipitation; however, few have considered changes owing to differences in the synoptic environment during landfall. Here, we focus on three North Atlantic TCs that impacted the southeastern United States: Hurricanes Floyd (1999), Matthew (2016), and Florence (2018). While these storms were impactful when they occurred, how might the impacts of similar systems change in a future climate? We address these questions using a pseudo–global warming (PGW) approach and ensembles of convection-allowing numerical model simulations. With this method, we compare future changes in precipitation characteristics such as accumulated rainfall and rain-rate frequency and distribution to assess how these changes differ as a function of synoptic environment. Hurricanes Matthew and Floyd, which have more synoptic-scale forcing for ascent while over our study region than Hurricane Florence, exhibit higher average rain rates in the present and future, but Hurricane Florence exhibits the largest increases in rain rates with warming (34% ± 12% vs 23% ± 9% and 21% ± 6% for Hurricanes Matthew and Floyd, respectively). When we consider accumulated precipitation, Hurricanes Matthew and Floyd have larger areal increases in precipitation totals greater than 250 mm than Hurricane Florence (17 600 ± 800 km2 and 22 400 ± 400 km2 vs 9800 ± 500 km2, respectively). These results point to the potential for future TCs in synoptically forced environments to have larger spatial footprints of heavy precipitation but smaller increases in rain rate than storms with less synoptic forcing, especially when considering overland precipitation. Significance Statement Many previous studies demonstrate that tropical cyclone (TC) precipitation will increase in a warmer climate, but few studies consider how TC precipitation responds to climate change as a function of the accompanying weather pattern. Here, we examine future changes in precipitation for TCs in three distinct weather patterns. By analyzing the response of TC rainfall to warming for a diverse set of patterns, we can increase readiness for a variety of future scenarios, with the ultimate goal of maximizing the resilience of future transportation infrastructure.

<strong class="journal-contentHeaderColor">Abstract.</strong> Projections of changes in extreme droughts under future climate conditions are associated with large uncertainties, owing to the complex genesis of droughts and large model uncertainty in the atmospheric dynamics. In this study we investigate the impact of global warming on soil moisture drought severity in west-central Europe by employing pseudo-global warming (PGW) experiments, which project the 1980&ndash;2020 period in a globally warmer world. The future analogues of present-day drought episodes allow investigation of changes in drought severity conditional on the historic day-to-day evolution of the atmospheric circulation. The 2018 west-central European drought is the most severe drought in the 1980&ndash;2020 reference period in this region. Under 1.5 &deg;C, 2 &deg;C and 3 &deg;C global warming, this drought episode experiences strongly enhanced summer temperatures, but a fairly modest soil moisture drying response compared to the change in climatology. This is primarily because evaporation is already strongly moisture-constrained during present-day conditions, limiting the increase in evaporation and thus the modulation of the temperature response under PGW. Increasing precipitation in winter, spring and autumn limit or prevent an earlier drought onset and duration. Nevertheless, the drought severity, defined as the cumulative soil moisture deficit volume, increases considerably, with 20 % to 39 % under 2 &deg;C warming. The extreme drought frequency in the 1980&ndash;2020 period strongly increases under 2 &deg;C warming. Several years without noticeable droughts under present-day conditions show very strong drying and warming. This results in an increase in 2003-like drought occurrences, compounding with local summer temperature increases considerably above 2 &deg;C. Even without taking into account a (potentially large) dynamical response to climate change, drought risk in west-central Europe is strongly enhanced under global warming. Owing to increases in drought frequency, severity and compounding heat, a reduction in recovery times between drought episodes is expected to occur. Our physical climate storyline provides evidence complementing conventional large-ensemble approaches, and is intended to contribute to the formulation of effective adaptation strategies.

The increase in water holding capacity of the atmosphere with temperature, given by the Clausius‐Clapeyron (CC) relationship, describes the changes in extreme rainfall intensities at warmer atmospheric states. We study the characteristics of extreme rainfall events (EREs) during the Indian summer monsoon season with respect to thermodynamic changes and precipitation‐scaling over the Indian subcontinent and its homogeneous rainfall zones. We utilize outputs from a present‐day climate simulation and a time‐slice future climate change projection experiments of a high‐resolution global climate model. Large changes are seen for very EREs (vEREs) which suggests their sensitivity to warmer temperatures. In future, the altered radiative forcing will heat up the upper atmosphere, stabilize it and offset the effect of increasing humidity on precipitation intensity. Our analysis also suggests that more convective clouds and the interplay of increased moisture content and circulation will result in future changes in EREs.

The understanding of climate change impacts and the associated climate extreme events at regional and local scales is of critical importance for planning and development of feasible adaptation strategies. In this paper, we present an analysis of climate change and extreme climate events in the Lake Victoria region of Tanzania, focusing on the Kagera and Geita regions. We use daily simulated climate variables (rainfall and minimum and maximum temperatures) from the Coordinated Regional Climate Downscaling Experiment Program Regional Climate Models (CORDEX_RCMs) for the analysis. Extreme climate event, rainfall, and minimum and maximum temperatures time series during historical (1971–2000) climate condition are compared to future climate projection (2011–2100) under two Representative Concentration Pathway (RCP): RCP 4.5 and RCP 8.5 emission scenarios. The existence, magnitude, and statistical significance of potential trends in climate data time series are estimated using the Mann–Kendall (MK) non-parametric test and Theil-SEN slope estimator methods. Results show that during historical (1971–2000) climate, the Lake Victoria region of Tanzania experienced a statistically significant increasing trend in temperature. The annual minimum and maximum temperatures in the Kagera and Geita regions have increased by 0.54–0.69°C, and 0.51–0.69°C, respectively. The numbers of warm days (TX90p) and warm nights (TN90p) during the historical climate have increased, while the numbers of cold days (TX10p) and cold nights (TN10p) have decreased significantly. However, in future climate condition (2011–2100) under both RCP 4.5 and RCP 8.5 emission scenarios, the Lake Victoria region is likely to experience increased temperatures and rainfall. The frequency of cold events (cold days and cold nights) is likely to decrease, while the frequency of warm events (warm days and warm nights) is likely to increase significantly. The number of consecutive wet days, the intensity of very wet days, and the number of extreme wet days are likely to increase. These results indicate that in future climate condition, socioeconomic livelihoods of people in the Kagera and Geita regions are likely to experience significant challenges from climate-related stresses. It is, therefore, recommended that appropriate planning and effective adaptation policies are in place for disaster risk prevention.

Extreme weather events have been increasing as global temperatures rise. Semi-enclosed basins such as the Black Sea and the Mediterranean are particularly susceptible to extreme weather due to their unique topographic features and land-sea distribution. Extreme precipitation events on the north-facing slopes of the mountains in the Black Sea Region occur due to relatively cold air interacting with the warm sea and being orographically lifted over the mountains. On August 10-12 2021, a deadly flash flood occurred on the coast of the Black Sea in Northern T&amp;#252;rkiye which resulted in excessive precipitation (200-450 mm) causing loss of lives of 97 people and leaving 228 injured. We investigated extreme weather event which occurred near the Black Sea along with future climate conditions using the Pseudo-Global Warming method. In order to analyze the event, we used a numerical weather prediction model (WRF) in convection-permitting 3 km horizontal resolution with a domain covering the Black Sea and surrounding area. The model simulations are driven by ECMWF Reanalysis 5th Generation (ERA5) data for initial and boundary conditions. To derive climate change signals, we used 25 CMIP6 Earth System Models and eliminating the rest of the models that have no ocean model component over the Black Sea. The signals are computed for three different future periods (2025&amp;#8211;2049, 2050&amp;#8211;2074, and 2075&amp;#8211;2099) relative to the 1990&amp;#8211;2014 historical period. Each climate change signal which represents different periods were added to ERA5 6-hourly data as ensemble means. In the first future period (2025-2049), sea surface temperature (SST) in August is projected to increase by 1.7 &amp;#176;C, and by the end of the period (2075-2099), SST is expected to rise by 5 &amp;#176;C over the Black Sea. Additionally, while near-surface air temperatures in August are projected to increase by 1.5 &amp;#176;C to 2.5 &amp;#176;C initially, they are expected to rise by approximately 5.5 &amp;#176;C to 8.5 &amp;#176;C in the final period over the simulation domain. Moreover, near-surface relative humidity over land in August is simulated to decrease by nearly 10% in the last quarter of the century. The findings of this study will contribute to our understanding of how extreme precipitation events develop under future climate conditions and provide insights of the physical and dynamic processes that could drive these events in a warmer world.

Arhopalus rusticus is a significant forestry pest known for its destructive impact on various host plants. This species, commonly found in coniferous forests across the Northern Hemisphere, has successfully spread to regions like New Zealand, Australia, and South America. This research is based on the known distribution sites of A. rusticus. Projections are made for the potential global distribution of A. rusticus under historical climatic conditions (1970–2000) and future climatic conditions (2081–2100) for the four forcing scenarios of the Coupled Model International Comparison Program 6 (CMIP6). The aim was to analyze the effects of climate change on the distribution range of this pest and its invasion trend in the southern hemisphere, and to support relevant departments in enhancing the effectiveness of forestry pest control strategies. The study utilized the Biomod2 software package in R to compare six models: generalized linear models (GLMs), generalized additive models (GAMs), multivariate adaptive regression splines (MARSs), artificial neural networks (ANNs), classification and regression trees (CTAs), and random forests (RFs) for modeling species distributions. The optimal model was selected based on evaluation indexes such as AUC and TSS. Projections of A. rusticus distribution under historical and future climate scenarios were created. The prediction results were visualized using ArcGIS software (version 10.2) to classify fitness levels and calculate distribution areas. Based on evaluation metrics, random forests (RFs) demonstrated the highest average assessment index scores, indicating high prediction accuracy (AUC = 0.99, TSS = 0.91, Kappa = 0.93). Model predictions revealed that, under historical climatic conditions, A. rusticus was predominantly found in northern Europe, eastern Asia, eastern and southwestern coastal regions of North America, and there were also highly suitable regions in parts of the southern hemisphere, including central and southwestern Argentina, southern Australia, New Zealand, and South Africa. Among these models, each of the CMIP6’s different climate prediction scenarios had a significant impact on the predicted distribution of A. rusticus. The SSP126 scenario depicted the broadest range of suitability, while the SSP585 scenario presented the narrowest and, overall, the extent of highly suitable regions was contracting. Multi-model predictions suggested that the potential distribution area of A. rusticus during the period of 2081–2100 would likely expand compared to that of 1970–2000, ranging from an increase of 1.13% (SSP126) up to 6.61% (SSP585), positively correlating with the level of radiative forcing. Notably, the most substantial growth was observed in potentially low-suitability region, escalating from 1.17% (SSP126) to 5.55% (SSP585). The distribution of A. rusticus shows decreasing trends from coastal areas to inland areas and from high to low level suitability of regions, and further expansion into the southern hemisphere under future climate conditions. Therefore, quarantine efforts at ports of entry should be strengthened in areas that are not currently infested but are at risk of invasion, and precise preventive measures should be strengthened in areas that are at risk of further expansion under future climatic conditions to prevent its spread to inland areas.