Regional Climate Model Research Articles

Did recent sea surface temperature warming reinforce the extreme East Asian summer monsoon precipitation in 2020?

We analyzed the possible effects of recent sea surface temperature (SST) warming on the extraordinary East Asian summer monsoon (EASM) precipitation in 2020 summer. The dynamic and thermodynamic impacts of SST are examined by conducting regional climate model experiments with observed SST and cold SST where the 22-year SST trend is removed. In the presence of warm SST, precipitation increases in low latitudes but decreases in the EASM region. This dipolar precipitation change pattern opposes the precipitation anomalies in 2020 summer, indicating that the extraordinary 2020 EASM precipitation is not likely driven by recent SST warming. The warm SST suppresses the western North Pacific subtropical high expansion and weakens the southwesterly from the South China Sea toward the EASM region. In terms of large-scale atmospheric circulations, SST-induced wind changes strengthen the local Walker circulation in the South China Sea and the Philippines and the local Hadley circulation across the EASM region. These support the reduced EASM rainfall in the control experiment compared to the cold SST experiment and imply that the precipitation reduction by dynamical effects could exceed the precipitation increase by thermodynamic effects in the EASM region under warm SST.

Extreme precipitation and temperature indices under future climate change in central Asia based on CORDEX-CORE

The present study analyzes the projected changes of extreme climate indices over Central Asia using regional climate model (RCM) simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX) - Coordinated Output for Regional Evaluations (CORE). The extreme indices are based on precipitation and temperature and are inspected for present (1981–2005) and future periods - near- (2031–2055) and far-future (2071–2095) - to assess the long-term climate change under the representative concentration pathway RCP8.5. Projected changes are analyzed for three different model ensembles. These ensembles are based on CORDEX-Central Asia (ENS_CAS, four ensemble members) and CORDEX-East Asia (ENS_EAS, six ensemble members), and a combination of both (ENS, ten ensemble members) for our study area centered over high mountain Asia, called Central East Asia (CEAS). For precipitation indices, an increase of consecutive dry days (CDD) in ENS_EAS and a slight to moderate decrease in northern parts in ENS_CAS during near-future is observed. Consecutive wet days (CWD), very heavy precipitation events (R20mm), maximum one-day precipitation (RX1day), and very wet days (R95p) are projected to increase in most areas. All indices show a further intensification towards the end of the century over large parts of the domain, e.g., + 7.8% / +5.6 days for CDD, + 96.6% / +0.26 days for R20mm, and + 19.7% for RX1day as median of ENS over CEAS. For temperature indices, the ensembles project a strong increase over the high mountain regions and southern parts for consecutive summer days (CSU, + 108.5% / +38.3 days), heat wave duration index (HWDI, + 1379.1% / +91.37 days), and the percentage of very hot days (TX90p, + 391.1% / +34.54 days). Accordingly, the number of consecutive frost days (CFD, -43.7% / -25.2 days) and the percentage of very cold days (TX10p, -83.4% / -8.13 days) are projected to decrease. The first-time usage of CORDEX-CORE and the larger ensemble size by considering simulations from overlapping domains increase the robustness of the findings from earlier studies. However, some discrepancies in the projected changes prevail among the different RCMs being part of the two CORDEX-domains and in specific landscapes like complex mountainous or lake areas. These uncertainties may be tackled by further model development with improved land-surface processes and potentially higher spatial resolution.

Evaluation of precipitation extremes in ERA5 reanalysis driven regional climate simulations over the CORDEX-Australasia domain

Reanalysis-driven regional climate simulations using the Weather Research and Forecasting (WRF) model in New South Wales (NSW) and Australian Regional Climate Modelling (NARCliM) Version 2.0 are assessed for capturing precipitation extreme indices. Seven configurations of the WRF model driven by ECMWF (European Centre for Medium-Range Weather Forecasts) Reanalysis v5 (ERA5) for Australia from 1979 to 2020 at 20 km resolution are evaluated. We assess the spatiotemporal patterns of six selected Expert Team on Sector-Specific Climate Indices (ET-SCI) precipitation extremes by comparing regional climate model (RCM) simulations against gridded observations. The RCMs evaluated have varying levels of accuracy in simulating precipitation extremes. While they capture climatology and coefficient of variation of precipitation extremes relatively well, temporal correlation and trend reproduction present challenges. Some RCMs perform more effectively for specific extreme indices, while others encounter challenges in accurately replicating them. No single RCM excels in all aspects, highlighting the need to consider specific strengths when selecting RCMs for global climate model (GCM) driven simulations.

Mid-century climate change impacts on tornado-producing tropical cyclones

Tornadoes are a co-occurring extreme that can be produced by landfalling tropical cyclones (TCs). These tornadoes can exacerbate the loss of life and property damage caused by the TC from which they were spawned. It is uncertain how the severe weather environments of landfalling TCs may change in a future climate and how this could impact tornado activity from TCs. In this study, we investigated four TCs that made landfall in the U.S. and produced large tornado outbreaks. We performed four-member ensembles of convective-allowing (4-km resolution) regional climate model simulations representing each TC in the historical climate and a mid-twenty-first century future climate. To identify potentially tornadic storms, or TC-tornado (TCT) surrogates, we used thresholds for three-hourly maximum updraft helicity and radar reflectivity, as tornadoes are not resolved in the model. We found that the ensemble-mean number of TCT-surrogates increased substantially (56–299%) in the future, supported by increases in most-unstable convective available potential energy, surface-to-700-hPa bulk wind shear, and 0–1-km storm-relative helicity in the tornado-producing region of the TCs. On the other hand, future changes in most-unstable convective inhibition had minimal influence on future TCT-surrogates. This provides robust evidence that tornado activity from TCs may increase in the future. Furthermore, TCT-surrogate frequency between 00Z and 09Z increased for three of the four cases, suggesting enhanced tornado activity at night, when people are asleep and more likely to miss warnings. All of these factors indicate that TC-tornadoes may become more frequent and a greater hazard in the future, compounding impacts from future increases in TC winds and precipitation.

Characteristics of extreme meteorological droughts over the Brazilian Pantanal throughout the 21st century

The Brazilian Pantanal is a remarkable ecosystem, encompassing vital aspects such as fish, fruit, and grain production, greenhouse gas emission regulation, temperature and precipitation modulation, and groundwater recharge. However, 2019 and 2020 experienced prolonged and severe drought that profoundly impacted the Pantanal region. Although these impacts are still under review, their effects on wildlife, vegetation, and the local population are undeniable. To enhance our understanding of the magnitude and consequences of the 2019/2020 drought, the present study conducted a comprehensive evaluation of drought occurrences in the Pantanal biome. Utilizing two well-established drought indices, the standard precipitation index (SPI) and the standard precipitation evapotranspiration index (SPEI), we analyzed the available observational data provided by the Climate Research Unit (CRU). Additionally, we endeavored to project droughts throughout the 21st century, thereby facilitating the visualization of potential reoccurrences of hazardous events in the Pantanal area. Two regional climate model (RCM) ensembles, the Eta ensemble (E1) and CORDEX ensemble (E2), along with representative concentration pathways (RCP4.5 and RCP8.5 scenarios) were used to project the severity of droughts in the Brazilian Pantanal until 2098/2099. The findings indicate that the hydrological year of 2019/2020 was the driest on record in the Pantanal over the past 80 years. The E1 ensemble did not project such an extreme event, whereas the E2 ensemble forecasted extreme droughts before the 2040s under the RCP4.5 and RCP8.5 scenarios. Using the SPEI, both ensembles showed similar results, with extreme droughts projected toward the end of the 21st century. Notably, the SPI demonstrated effectiveness in detecting short-term droughts, while the SPEI was more efficient for long-term assessments, projecting extreme drought events for the last two decades. The SPEI, employed with the Eta and CORDEX ensembles, can provide valuable insights into drought projections. Moreover, the potential recurrence of extreme droughts, characterized by significant below-average precipitation spanning vast areas throughout the hydrological year, poses a severe threat to the Pantanal biome in this century.

Object-oriented analysis as a foundation for building climate storylines of compounding short-term drought and crop heat stress

IntroductionCrops are vulnerable to precipitation and heat extremes during late spring through summer.MethodsWe analyzed for a north-central U.S. region short-term drought and agricultural heat stress during April-May-June-July. We used the 4-km Parameter Elevation Regression on Independent Slopes Model (PRISM) for observations, aggregated to a 25-km grid, and two 25-km Regional Climate Model version 4 (RegCM4) simulns used either GFDL- or MPI-GCM boundary conditions. We chose 1981-2000 as our contemporary time period, and 2041-2060 as our scenario time period, which used the Representative Concentration Pathway 8.5 emissions scenario. We used object-oriented analysis to identify events of interest in observations and simulations by identifying objects in a space-time domain that meet specified criteria, such as exceeding a heat-stress temperature threshold. The event diagnosis allowed analysis of compound events, occurring when temperature and drought objects overlap.ResultsIdentified objects yielded events that can undermine agricultural productivity and which are thus relevant to decision makers, making them building blocks for possible climate storylines. The observations and simulations showed similar spatial distributions of event frequencies across the analysis region. However, the simulations attained this distribution by having fewer events that tend to cover larger areas compared to observed events, suggesting that the effective resolution of the simulations was coarser than their 25-km grids. Short-term drought frequency increased and heat-stress frequency decreased in transitioning to the scenario climate. When compounding occurred heat-stress events generally preceded the short-term drought events. The overlapping, compound events tended to be more extreme compared to non-overlapping events of either type.DiscussionThe information yielded projected changes in these agriculturally motivated events. One prominent conditional behavior emerging from the work was that a heat-stress event should be a warning to watch for potential drought, as both could compound each other to more intense levels.

Numerical investigation of different cooling technologies during heatwaves in Catalan Mediterranean buildings

The Mediterranean area is particularly affected by heatwaves, which are extremely critical for health and productivity of people inside the dwellings as well as for energy consumptions related to cooling demand. This study numerically investigated the resilience of different cooling technologies in the most common construction in Catalan building stock during present and future climatic conditions, heatwaves. The studied technologies include green roof, blinds, advanced windows, air conditioning and their combinations. Meteorological data of heatwaves for Barcelona city have been created for three time periods, Present, Mid Future and Long Future. They have been modelled using dynamical downscaled Regional Climate Models, climate projections based on IPCC scenarios. Resilience was assessed using indicators that consider the linear correlation between the grade of overheating inside a dwelling and the severity of outdoor conditions. Thermal comfort and survivability have been also investigated, evaluating sensations of building’s occupants related to indoor air temperature and relative humidity. The original building presented acceptable levels of resilience with a resilience index α below 1, while thermal comfort conditions resulted poor, especially during heatwaves, being for more than 60% of the time in Extreme Caution conditions or worst. The application of the different cooling technologies significantly helped in the improvement of resilience and survivability inside the dwelling. However, their performances reduced in the future scenarios, reaching more than 90% of the time under Extreme Caution conditions or worst. Air conditioning resulted the best solution for avoiding overheating, especially in heatwaves constraining it to a maximum of 1.8°C. Combinations of several passive measures resulted necessary for maintaining suitable conditions.

On the Sensitivity of the Potential Evapotranspiration of Egypt to Different Initial Conditions of the Soil Moisture Using a High-resolution Regional Climate Model

The present study investigated the sensitivity of the Potential Evapotranspiration (PET) of Egypt to different initial conditions of soil moisture using a high-resolution Regional Climate Model (RegCM4). To address this issue, two 32-year simulations were conducted from 1979 to 2010. The first two years were considered as spin-up. In the first simulation, the RegCM4 was initialized with the satellite product ESACCI (ESA) and the RegCM4 was initialized with version 3 of the Century Reanalysis Product (CEN) in the second simulation. The PET was computed using a calibrated version of the Hargreaves–Samani (HS) equation. In the two simulations, the RegCM4 was configured with the Community Land Model version 4.5 (CLM45). Era-Interim Reanalysis of 1.5 degrees (EIN15) was used to downscale the RegCM4 with 25 km grid spacing. The ERA5-based product (ERA5) was used as the observational dataset. The results showed that switching between ESA and CEN didn’t induce a notable influence on the daily maximum air temperature. Regarding the daily minimum air temperature, the CEN outperforms the ESA concerning the Climate Research Unit (CRU). In comparison with the ERA5 product, the CEN was able to reduce the PET negative bias (0.8 to 1.8 mm day-1) better than the one noted in the ESA (0.8 to 3 mm day-1). On a point scale, the performance of the ESA/CEN varies with the location and month. Such a point was confirmed using different statistical metrics such as mean bias, Pearson correlation coefficient and standard deviation ratio. In conclusion, the CEN can be recommended to initialize the RegCM4 to ensure a reliable estimation of the PET of Egypt either in the present climate or under different future scenarios.

Snow depth in high-resolution regional climate model simulations over southern Germany – suitable for extremes and impact-related research?

Abstract. Snow dynamics play a critical role in the climate system, as they affect the water cycle, ecosystems, and society. In climate modelling, the representation of the amount and extent of snow on the land surface is crucial for simulating the mass and energy balance of the climate system. Here, we evaluate simulations of daily snow depths against 83 station observations in southern Germany in an elevation range of 150 to 1000 m over the time period 1987–2018. Two simulations stem from high-resolution regional climate models – the Weather Research & Forecasting (WRF) model at 1.5 km resolution and the COnsortium for Small scale MOdelling model in CLimate Mode (COSMO-CLM; abbreviated to CCLM hereafter) at 3 km resolution. Additionally, the hydrometeorological snow model Alpine MUltiscale Numerical Distributed Simulation ENgine (AMUNDSEN) is run at point scale at the locations of the climate stations, based on the atmospheric output of CCLM. To complement the comparison, the ERA5-Land dataset (9 km), a state-of-the-art reanalysis land-surface product, is also compared. All four simulations are driven by the atmospheric boundary conditions of ERA5. Due to an overestimation of the snow albedo, the WRF simulation features a cold bias of 1.2 °C, leading to the slight overestimation of the snow depth in low-lying areas, whereas the snow depth is underestimated at snow-rich stations. The number of snow days (days with a snow depth above 1 cm) is reproduced well. The WRF simulation can recreate extreme snow depths, i.e. annual maxima of the snow depth, their timings, and inter-station differences, and thereby shows the best performance of all models. The CCLM reproduces the climatic conditions with very low bias and error metrics. However, all snow-related assessments show a strong systematic underestimation, which we relate to deficiencies in the snow module of the land-surface model. When driving AMUNDSEN with the atmospheric output of the CCLM, the results show a slight tendency to overestimate snow depth and number of snow days, especially in the northern parts of the study area. Snow depth extremes are reproduced well. For ERA5-Land (ERA5L), the coarser spatial resolution leads to larger differences between the model elevation and the station elevation, which contributes to a significant correlation of climatic biases with the elevation bias. In addition, the mean snow depth and number of snow days are strongly overestimated, with conditions that are too snowy in the late winter. Extreme snow depth conditions are reproduced well in the low-lying areas, whereas strong deviations occur with more complex topography. In sum, due to the high spatial resolution of convection-permitting climate models, they show the potential to reproduce the winter climate (temperature and precipitation) in southern Germany. However, different sources of uncertainties, i.e. the spatial resolution, the snow albedo parametrisation, and other parametrisations within the snow model, prevent their further use in a straightforward manner for impact research. Hence, careful evaluation is needed before any impact-related interpretation of the simulations, such as in the context of climate change research.

Evaluation of COSMO-CLM Model Parameter Sensitivity in the Study of Extreme Events across the Eastern Region of India

The present study aims to identify the parameters from the Consortium for Small-scale Modelling in CLimate Mode (COSMO-CLM) regional climate model that strongly controls the prediction of extreme events over West Bengal and the adjoining areas observed between 2013 to 2018. Metrics, namely Performance Score (PS) screen out the most persuasive parameter on model output. Additionally, the Performance Index (PI) measure the reliability of the model and Skill Score (SS) establishes the model performance against the reference simulation leading to the optimization of the model for a given variable. In this study, parameter screening for four output variables such as 2m-temperature, surface latent heat flux, precipitation and cloud cover of COSMO-CLM is accomplished. For heat wave simulations, 2m-temperature and surface latent heat flux are explored whereas cloud cover and precipitation are examined for extreme rainfall events. A total of 25 adjustable parameters representing the following parameterization schemes: turbulence, land surface process, microphysics, convection, radiation and soil. Out of the six parameterization schemes, the scaling factor of the laminar boundary layer for heat (rlam_heat) and the ratio of laminar scaling factors for heat over sea and land (rat_sea) from the land surface process is sensitive to SLH, TP. The exponent to get the effective surface area (e_surf) from the land surface has a large impact on 2m-temperature. A few parameters from microphysics (cloud ice threshold for auto conversion), convection (mean entrainment rate for shallow convection) and radiation (parameter for computing the amount of cloud cover in saturated conditions) play a significant role in producing TP, and TCC fields. It is evident from the results that the parameter sensitivities on model performance depend on the choice of the meteorological field. Furthermore, in almost all input model parameters, the model performance reveals the opposite character in different domains for a given meteorological field.

Improving land surface feedbacks to the atmosphere in convection-permitting climate simulations for Europe

We investigated positive temperature (warm) and negative precipitation (dry) biases in convection-permitting model (CPM) simulations for Europe (2.2 km grid spacing) that were considerably larger than in equivalent regional climate model (RCM) simulations (12 km grid spacing). We found that improvements in dry biases could be made by (1) using a more complex runoff scheme which takes into account topography and groundwater, (2) delaying the onset of water stress in vegetation to enhance transpiration, (3) changing the microphysics scheme to CASIM (Cloud AeroSol Interacting Microphysics) which also decreases heavy rainfall and increases light rainfall. Increasing soil moisture to the critical point can remove dry precipitation biases in southern Europe but not in northern areas, indicating that soil moisture limitation is a key contributor to precipitation biases in the south only. Instead, in the north, changing the cloud scheme of the model has more impact on precipitation biases. We found that the more intense and intermittent nature of rainfall in the CPM, which is more realistic leads to different canopy interception compared to the RCM. This can impact canopy evaporation, evapotranspiration and feed back on precipitation. Increasing rainfall storage in the canopy only leads to small improvements in warm biases, since it still fills rapidly with intense CPM rainfall, suggesting the need for an additional moisture store via improved groundwater modelling or surface pooling. Overall, this work highlights the challenge of correctly capturing land surface feedbacks in CPMs, which play an important role in future climate projections in some regions.

Diurnal emission variation of ozone precursors: Impacts on ozone formation during Sep. 2019

With the issue of ozone (O3) pollution having increasingly gained visibility and prominence in China, the Chinese government explored various policies to mitigate O3 pollution. In some provinces and cities, diurnal regulations of O3 precursor were implemented, such as shifting O3 precursor emission processes to nighttime and offering preferential refueling at night. However, the effectiveness of these policies remains unverified, and their impact on the O3 generation process requires further elucidation. In this study, we utilized a regional climate and air quality model (WRF-Chem, v4.5) to test three scenarios aimed at exploring the impact of diurnal industry emission variation of O3 precursors on O3 formation. Significant O3 variations were observed mainly in urban areas. Shifting volatile organic compounds (VOCs) to nighttime have slight decreased daytime O3 levels while moving nitrogen oxides (NOx) to nighttime elevates O3 levels. Simultaneously moving both to nighttime showed combined effects. Process analysis indicates that the diurnal variation in O3 was mainly attributed to chemical process and vertical mixing in urban areas, while advection becomes more important in non-urban areas, contributing to the changes in O3 and O3 precursors levels through regional transportation. Further photochemical analysis reveals that the O3 photochemical production in urban areas was affected by reduced daytime O3 precursors emissions. Specifically, decreasing VOCs lowered the daytime O3 production by reducing the ROx radicals (ROx = HO + HO˙2 + RO˙2), whereas decreasing NOx promoted the daytime O3 production by weakening ROx radical loss. Our results demonstrate that diurnal regulation of O3 precursors will disrupt the ROx radical and O3 formation in local areas, resulting in a change in O3 concentration and atmospheric oxidation capacity, which should be considered in formulating new relevant policies.

Runoff uncertainty associated with global climate model chosen in regional climate modeling

Runoff uncertainty associated with global climate model chosen in regional climate modeling

Uncertainty in simulated streamflow using runoff driven by the outputs of a high-resolution regional climate model

Uncertainty in simulated streamflow using runoff driven by the outputs of a high-resolution regional climate model

Using of hydrological model and geospatial tool to assess climate change impact on the hydropower potential of the White Bandama watershed in Côte d'Ivoire (West Africa)

Abstract. This study was carried out in the White Bandama watershed (WBW) in Côte d'Ivoire (West Africa). The objective is to assess the impacts of future climate change (CC) on the hydropower potential (HPP) of the WBW. The methodology is based on coupling the SWAT (Soil and Water Assessment Tool) hydrological model with the Geographic Information System (GIS) QGIS to assess HPP on streams and evaluate the impacts of future CC on HPP of the watershed. Historical and climate projection data (precipitation, minimum and maximum temperature) for a set of three Regional Climate Models (RCM) from CORDEX-AFRICA (CCCma-CanRCM4, CCLM4-8-17 and REMO 2009) under RCP 4.5 were used. The biases of the ensemble mean were corrected by the Delta-change method. The relative change of streamflow discharge and HPP was assessed as the relative difference between the projection periods (2041–2070 and 2071–2100) and the reference period (1976–2005). The results showed a total of 22 future hydropower potential sites in the watershed. These sites were identified, geolocated and classified according to their potential capacity of generation in 82 % as small (1–25 MW potential capacity), 9 % as medium (25–100 MW potential capacity) and 9 % as large (more than 100 MW potential capacity) hydropower. The climate models' ensemble projected an upward trend for both the annual mean discharge of rivers and HPP of the WBW according to RCP 4.5 for the periods 2041–2070 and 2071–2100. On the annual cycle, the months of August and September will record the highest monthly mean flows between 150 and 200 m3 s−1 while the months from November to April will record low monthly mean flows in the WBW.

The expected wind power dynamics in the Mediterranean Sea considering different climate change scenarios

An accelerated transition to renewable energy sources is foreseen in the very near future in Europe, including a 25-time enhancement in terms of offshore wind power capacity which is planned until 2050 in relationship with 2021. The potential of the Mediterranean Sea, although not so significant as that of the North or of the Baltic Seas, cannot be neglected and many wind projects will become operational in the next years in this nearshore. In this context, the objective of the present work is to give a perspective of the past and future expected wind power dynamics in the Mediterranean Sea until the end of the twenty-first century. Data from two different Regional Climate Models were processed considering the scenario RCP4.5. An analysis of the historical wind data provided by these two climate wind models for the past 30-year period 1976–2005 is also performed and compared with the ERA5 data. The average and extreme wind power conditions are analysed. Further on, two different future time intervals are considered. These are near future, the 30-year interval 2041–2070, and distant future, the interval 2071–2100. The results indicate that the wind power is expected to remain significant in the Mediterranean Sea.

Contributions of atmospheric forcing and ocean preconditioning in the 2016 Antarctic sea ice extent drop

The 2016 Antarctic sea ice extent (SIE) drop was a rapid decrease that led to persistent low sea ice conditions. The event was triggered by atmospheric anomalies, but the potential preconditioning role of the ocean is unsettled. Here, we use sensitivity experiments with a fully-coupled regional climate model to elucidate the impact of the ocean conditions on the drop and on the persistence of the negative SIE anomalies during 2017. In particular, we re-initialize the model in January 2016 using different ocean and sea ice conditions, keeping lateral boundary forcings in the atmosphere and ocean unchanged. We find that the state of the Southern Ocean in early 2016 does not determine whether the drop occurs or not, but indeed has an impact on its amplitude and regional characteristics. Our results also indicate that the ocean initialization affects the sea ice recovery after the drop in the short term (one year), especially in the Weddell sector. The ocean’s influence appears not to be linked to the ocean surface and sea-ice initialization, but rather to the sub-surface conditions (between 50 m and 150 m) and heat exchange fluctuations at the regional scale, while the atmospheric forcing triggering the drop is driven by the large-scale circulation.

Impact of Climate Change on Extreme Rainfall Events and Pluvial Flooding Risk in the Vojvodina Region (North Serbia)

Extreme precipitation events, which are common natural hazards, are expected to increase in frequency due to global warming, leading to various types of floods, including pluvial floods. In this study, we investigated the probabilities of maximum 3-day precipitation amount (Rx3day) occurrences during spring in the Vojvodina region, covering both past (1971–2019) and future (2020–2100) periods. We utilized an ensemble of eight downscaled, bias-corrected regional climate models from the EURO-CORDEX project database, selecting the RCP8.5 scenario to examine future Rx3day amounts. The probabilities of occurrences of Rx3day were modeled using the GEV distribution, while the number of events where Rx3day in spring exceeds specific thresholds was modeled using the Poisson distribution. The results indicate that Rx3day with a ten-year return period during the spring months is expected to increase by 19% to 33%. Additionally, the probabilities of having more than one event where Rx3day exceeds thresholds are projected to rise by 105.6% to 200.0% in the future compared to the historical period. The analysis comparing the design values of Rx3day with future projections for the period 2020–2100 revealed that 51 drainage systems are likely to function without difficulties under future climate conditions. However, for the remaining 235 drainage systems, an increased risk of pluvial flooding was identified, as their design precipitation amounts are lower than the future projections. This study reveals that analyzing extreme rainfall events in the context of climate change yields crucial information that facilitates effective planning and policy making in water management, particularly flood protection.

Comparison and Evaluation of Five Global Land Cover Products on the Tibetan Plateau

The Tibetan Plateau (TP) region contains maximal alpine grassland ecology at the mid-latitudes. This region is also recognized as an ecologically fragile and sensitive area under the effects of global warming. Regional climate modeling and ecosystem research depend on accurate land cover (LC) information. In order to obtain accurate LC information over the TP, the reliability and precision of five moderate/high-resolution LC products (MCD12Q1, C3S-LC, GlobeLand30, GLC_FCS30, and ESA2020 in 2020) were analyzed and evaluated in this study. The different LC products were compared with each other in terms of areal/spatial consistency and assessed with four reference sample datasets (Geo-Wiki, GLCVSS, GOFC-GOLD, and USGS) using the confusion matrix method for accuracy evaluation over the TP. Based on the paired comparison of these five LC datasets, all five LC products show that grass is the major land cover type on the TP, but the range of grass coverage identified by the different products varies noticeably, from 43.35% to 65.49%. The fully consistent spatial regions account for 43.72% of the entire region of the TP, while, in the transition area between grass and bare soil, there is still a large area of medium-to-low consistency. In addition, a comparison of LC datasets using integrated reference datasets shows that the overall accuracies of MCD12Q1, C3S-LC, GlobeLand30, GLC_FCS30, and ESA2020 are 54.29%, 49.32%, 53.03%, 53.73%, and 60.11%, respectively. The producer accuracy of the five products is highest for grass, while glaciers have the most reliable and accurate characteristics among all LC products for users. These findings provide valuable insights for the selection of rational and appropriate LC datasets for studying land-atmosphere interactions and promoting ecological preservation in the TP.

Possible changes and occurrences of future wave power in an enclosed sea using a high-resolution regional climate model

The present study evaluates future wave power resources and detects a possible impact of climate change on wave power in an enclosed sea (Black Sea) for the 21st century. The wave data are obtained from a third-generation spectral wave model using a validated RCM (Regional Climate Model). The wave power projection and projected occurrences are analyzed for near and middle future (NF, MF) periods based on two RCP (Representative Concentration Pathway) scenarios (4.5 and 8.5). Possible changes in wave power for the NF 2021–2060 and MF 2061−2100 periods are evaluated by comparing the historical (1970–2005) period. According to two RCP scenarios, the wave power potential for the NF is expected to increase markedly over the entire basin, while, for the MF, the changes are projected by decreases, especially in the northeastern and western parts of the basin. Furthermore, projected occurrences are examined using Energy Level Occurrences known as available, moderate, and rich level occurrences. The 15 reference points over the basin are chosen to detect the most suitable location(s) for future wave power developments. All spatial and local analyses indicate that the western basin, especially the southwest, will continue having high wave power potential and occurrences in future periods.