Convection-permitting Climate Simulations Research Articles

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

AbstractWe 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.

Past, present and future rainfall erosivity in central Europe based on convection-permitting climate simulations

Abstract. Heavy rainfall is the main driver of soil erosion by water, which is a threat to soil and water resources across the globe. As a consequence of climate change, precipitation – especially extreme precipitation – is increasing in a warmer world, leading to an increase in rainfall erosivity. However, conventional global climate models struggle to represent extreme rain events and cannot provide precipitation data at the high spatiotemporal resolution that is needed for an accurate estimation of future rainfall erosivity. Convection-permitting simulations (CPSs), on the other hand, provide high-resolution precipitation data and a better representation of extreme rain events, but they are mostly limited to relatively small spatial extents and short time periods. Here, we present, for the first time, rainfall erosivity in a large modeling domain such as central Europe based on high-resolution CPS climate data generated with the regional climate model COSMO-CLM using the Representative Concentration Pathway 8.5 (RCP8.5) emission scenario. We calculated rainfall erosivity for the past (1971–2000), present (2001–2019), near future (2031–2060) and far future (2071–2100). Our results showed that future increases in rainfall erosivity in central Europe can be up to 84 % in the region's river basins. These increases are much higher than previously estimated based on regression with mean annual precipitation. We conclude that despite remaining limitations, CPSs have an enormous and currently unexploited potential for climate impact studies on soil erosion. Thus, the soil erosion modeling community should closely follow the recent and future advances in climate modeling to take advantage of new CPSs for climate impact studies.

Intercomparing the quality of recent reanalyses for offshore wind farm planning in Germany's exclusive economic zone of the North Sea

Abstract. In order to facilitate offshore wind farm tenders, Deutscher Wetterdienst (DWD, Germany's national meteorological service) provides reanalysis data and quality assessments to Bundesamt für Seeschifffahrt und Hydrographie (BSH, Federal Maritime and Hydrographic Agency). The regional reanalysis COSMO-REA6 is used besides the global reanalysis ERA5. New reanalyses and derived products getting available are (i) the regional reanalysis CERRA (C3S), (ii) COSMO-R6G2, a successor of COSMO-REA6 which is currently produced by DWD and (iii) HoKliSim-De, a convection-permitting climate simulation for Germany with COSMO-CLM as a regional downscaling of ERA5. In the present study, the quality of the different data sets for offshore wind energy application is compared using in-situ measurements of the wind speed and wind direction from the top anemometer and vane of the FINO1 research platform and satellite-based data of the near-surface wind speed from the Copernicus Marine Environment Monitoring Service (CMEMS) and the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF). Evaluation at FINO1 focuses on the time period prior to the installation of nearby wind farms to avoid wake effects. COSMO-REA6, CERRA and HoKliSim-De show only small biases and resemble the observed distribution of the wind speed at FINO1 whereas ERA5 shows slightly lower values of the wind speed at 100 m. All model-based products tend to slightly underestimate the occurrence of south-westerly wind directions and overestimate wind directions from West to Northwest. Smallest directional biases are analysed for COSMO-REA6. Analysis of the windstorm CHRISTIAN suggests that ensemble information is required for the representation of individual extreme events. Evaluation of the near-surface wind speed using satellite-based data is performed for an area around the German Exclusive Economic Zone (EEZ) of the North Sea. The median bias of ERA5 and COSMO-REA6 is close to zero. CERRA shows a systematic overestimation of the near-surface wind speed compared to the satellite-based reference datasets. By contrast, a slight underestimation is analysed for HoKliSim-De. The bias distribution analysed for a first simulation stream of COSMO-R6G2 is similar to COSMO-REA6 which provides initial indication for the applicability of the new product.

Impact of climate change under the RCP8.5 emission scenario on multivariable agroclimatic indices in Western Canada from convection-permitting climate simulation

Climate change will impact crop production in Western Canada by modifying growing season conditions. Precipitation pattern changes and warmer temperatures will pose significant risks to crops. Studies have shown that multivariable agroclimatic indices can enhance climatic impact assessment on crop production. This study uses multivariable agroclimatic indices to assess how climate change may impact crop production in western Canada by the end of the 21st century. We use convection-permitting regional climate simulations for the current (CTL) and future climate under the Representative Concentration Pathway 8.5 scenario (RCP8.5) scenario based on the pseudo-global warming (PGW) approach to assess the impact of the climate on growing season indices. CTL and PGW are bias-corrected to the Global Environmental Multiscale (GEM) Canadian Precipitation Analysis (CaPA) (GEM-CaPA) dataset using the multivariate quantile mapping method. Our study analyses Effective Precipitation (Pe), Temperature Humidity Index (THI), and Precipitation Intensity Index (PII) at seasonal and sub-seasonal scales as they apply to cool-season crops. The CTL simulation shows a good performance in reproducing the spatial patterns and the temporal variability of the selected indices in western Canada. Results show that precipitation (Effective Precipitation) will decrease by over 60 mm (40 mm), rainy days will decrease by up to 10 days, and precipitation intensities will increase across western Canada. Warming will lead to THI unit increases of about 3.5 (>5) in the prairies (northeastern parts of western Canada in June). This study’s findings can be useful in generating appropriate information to inform policy on adaptation for sustainable crop production by the end of the 21st century.

The ratio of mesoscale convective system precipitation to total precipitation increases in future climate change scenarios

Mesoscale convective systems (MCSs) are a substantial source of precipitation in the eastern U.S. and may be sensitive to regional climatic change. We use a suite of convection-permitting climate simulations to examine possible changes in MCS precipitation. Specifically, annual and regional totals of MCS and non-MCS precipitation generated during a retrospective simulation are compared to end-of-21st-century simulations based on intermediate and extreme climate change scenarios. Both scenarios produce more MCS precipitation and less non-MCS precipitation, thus significantly increasing the proportion of precipitation associated with MCSs across the U.S.

Changes in design precipitation over the Nordic-Baltic region as given by convection-permitting climate simulations

The increased risk of flooding due to global warming and subsequent heavy rainfall events in the Nordic-Baltic region, call for recommendations directed at long-term planning. One example of such recommendations are climate change allowances. These are often based on expected changes in design precipitation as given by climate model simulations, and are used as a buffer on top of current design values to avoid a future increased damage potential as a consequence of climate change. We here compute expected changes in precipitation design values, so-called climate factors (CFs), for the Nordic-Baltic region, based on 3 km convection permitting simulations from the Nordic Convection Permitting Climate Projections project. These have the advantage of explicitly resolving convection, which has been shown to be the main contributor to increased rainfall. We assess the dependence of the CFs on rainfall duration, return period, and geographical location, focusing on the summer (convective) season, short durations and the high emission scenario RCP8.5. We also compare these CFs to those computed from a non-convection permitting regional climate model ensemble.We found higher CFs for the longer return period, with only few exceptions, and distinctly higher CFs going from daily to sub-daily durations. However, the different simulations give conflicting results for very short-duration rainfall (<3 h). The huge difference in the climate sensitivity of driving GCMs dominates the magnitude of estimated return levels. Our analysis is shaped by the high computational costs of running convection permitting models, resulting in a very limited ensemble (3 members) representing a single emission scenario (RCP8.5). Therefore, we believe that combining results from convection permitting simulations with a larger ensemble (21 members) of non-convection permitting simulations adds value to the assessment of robust climate change allowances for heavy precipitation in the Nordic-Baltic region.

Convection-permitting climate simulations for South America with the Met Office Unified Model

AbstractWe present the first convection-permitting regional climate model (CPRCM) simulations at 4.5 km horizontal resolution for South America at near-continental scale, including full details of the experimental setup and results from the reanalysis-driven hindcast and climate model-driven present-day simulations. We use a range of satellite and ground-based observations to evaluate the CPRCM simulations covering the period 1998–2007 comparing the CPRCM output with lower resolution regional and global climate model configurations for key regions of Brazil. We find that using the convection-permitting model at high resolution leads to large improvements in the representation of precipitation, specifically in simulating its diurnal cycle, frequency, and sub-daily intensity distribution (i.e. the proportion of heavy and light precipitation). We tentatively conclude that there are also improvements in the spatial structure of precipitation. We see higher precipitation intensity and extremes over Amazonia in the CPRCMs compared with observations, though more sub-daily observational data from meteorological stations are required to conclusively determine whether the CPRCMs add value in this regard. For annual mean precipitation and mean, maximum and minimum near surface temperatures, it is not clear that the CPRCMs add value compared with coarser-resolution models with parameterised convection. We also find large changes in the contribution to evapotranspiration from canopy evaporation compared to soil evaporation and transpiration compared with the RCM. This is likely to be related to the shift in precipitation intensity distribution of the CPRCMs compared to the RCM and its impact on the hydrological requires further investigation.

Convection-permitting climate simulations with COSMO-CLM for Germany: Analysis of present and future daily and sub-daily extreme precipitation

Convection-permitting climate simulations with COSMO-CLM for Germany: Analysis of present and future daily and sub-daily extreme precipitation

Modelling urban stormwater management changes using SWMM and convection-permitting climate simulations in cold areas

Urbanization coupled with climate change is expected to put pressure on the urban stormwater network. To predict and mitigate the effects of these trends, accurate modeling of urban stormwater changes is required at scales and resolutions meaningful to stormwater management. Although numerous studies have analyzed the effect of climate change on urban flooding risk using the event-based approach, none have incorporated the continuous modelling approach to investigate the whole spectrum of changes in an urban catchment. This study analyzes seasonal changes in future urban hydrological behavior using a mini-ensemble of six state-of-the-art climate model projections and a calibrated hydrological-hydraulic Storm Water Management Model (SWMM). The modelling results show future changes in seasonal and monthly hydrological behavior. The notable winter warming is the major driver in the future snow processes, resulting in considerably less snow days and an increase in the flow events frequency during the winter months. The modelling results also suggest an increase in the annual maximum hourly flow in all seasons, with the clearest trend modelled in winter. Monthly average runoff during the cold period is modelled to increase, while no clear trends are detected for the rest of the year. There is a clear added benefit in using convection-permitting regional climate models throughout the year. Overall, the climate change mitigation and adaption strategies in urban catchments should focus more on the whole spectrum of changes rather than only on urban pluvial flooding risk. These findings call for a transition from traditional to a more advanced stormwater management.

Mesoscale convective systems in the third pole region: Characteristics, mechanisms and impact on precipitation

The climate system of the Third Pole region, including the (TP) and its surroundings, is highly sensitive to global warming. Mesoscale convective systems (MCSs) are understood to be a vital component of this climate system. Driven by the monsoon circulation, surface heating, and large-scale and local moisture supply, they frequently occur during summer and mostly over the central and eastern TP as well as in the downstream regions. Further, MCSs have been highlighted as important contributors to total precipitation as they are efficient rain producers affecting water availability (seasonal precipitation) and potential flood risk (extreme precipitation) in the densely populated downstream regions. The availability of multi-decadal satellite observations and high-resolution climate model datasets has made it possible to study the role of MCSs in the under-observed TP water balance. However, the usage of different methods for MCS identification and the different focuses on specific subregions currently hamper a systematic and consistent assessment of the role played by MCSs and their impact on precipitation over the TP headwaters and its downstream regions. Here, we review observational and model studies of MCSs in the TP region within a common framework to elucidate their main characteristics, underlying mechanisms, and impact on seasonal and extreme precipitation. We also identify major knowledge gaps and provide suggestions on how these can be addressed using recently published high-resolution model datasets. Three important identified knowledge gaps are 1) the feedback of MCSs to other components of the TP climate system, 2) the impact of the changing climate on future MCS characteristics, and 3) the basin-scale assessment of flood and drought risks associated with changes in MCS frequency and intensity. A particularly promising tool to address these knowledge gaps are convection-permitting climate simulations. Therefore, the systematic evaluation of existing historical convection-permitting climate simulations over the TP is an urgent requirement for reliable future climate change assessments.

The uneven impact of climate change on drought with elevation in the Canary Islands

Climate models project an increase in drought and aridity in many regions in response to greenhouse gas concentrations in the atmosphere. In areas with complex topography, such as the Canary Islands, elevation gradients may play an important role in future changes. Convection-permitting climate simulations driven by data from three global climate models included in the Coupled Model Intercomparison Project (CMIP5) have been performed for the Canary Islands. A significant increase in the duration and severity of drought is projected by the end of the twenty-first century (2070–2099), relative to the recent past (1980–2009), under intermediate and high emissions scenarios. In addition, the percentage of land affected by droughts, on average, would increase considerably, covering up to 96% in the higher elevations, in the business-as-usual scenario. These changes and the increase in aridity are more pronounced at higher altitudes due to a clear dependence of temperature rise as a function of elevation and a substantial decrease in precipitation.

Large-scale dynamics moderate impact-relevant changes to organised convective storms

Larger organised convective storms (mesoscale-convective systems) can lead to major flood events in Europe. Here we assess end-of-century changes to their characteristics in two convection-permitting climate simulations from the UK Met Office and ETH-Zürich that both use the high Representative Concentration Pathway 8.5 scenario but different approaches to represent atmospheric changes with global warming and different models. The UK Met Office projections indicate more frequent, smaller, and slower-moving storms, while ETH-Zürich projections show fewer, larger, and faster-moving storms. However, both simulations show increases to peak precipitation intensity, total precipitation volume, and temporal clustering, suggesting increasing risks from mesoscale-convective systems in the future. Importantly, the largest storms that pose increased flood risks are projected to increase in frequency and intensity. These results highlight that understanding large-scale dynamical drivers as well as the thermodynamical response of storms is essential for accurate projections of changes to storm hazards, needed for future climate adaptation.

The Future of Supercells in the United States

Abstract A supercell is a distinct type of intense, long-lived thunderstorm that is defined by its quasi-steady, rotating updraft. Supercells are responsible for most damaging hail and deadly tornadoes, causing billions of dollars in losses and hundreds of casualties annually. This research uses high-resolution, convection-permitting climate simulations across 15-yr epochs that span the twenty-first century to assess how supercells may change across the United States. Specifically, the study explores how late-twentieth-century supercell populations compare with their late-twenty-first-century counterparts for two—intermediate and pessimistic—anthropogenic climate change trajectories. An algorithm identifies, segments, and tracks supercells in the simulation output using updraft helicity, which measures the magnitude of corkscrew flow through a storm’s updraft and is a common proxy for supercells. Results reveal that supercells will be more frequent and intense in future climates, with robust spatiotemporal shifts in their populations. Supercells are projected to become more numerous in regions of the eastern United States, while decreasing in frequency in portions of the Great Plains. Supercell risk is expected to escalate outside of the traditional severe storm season, with supercells and their perils likely to increase in late winter and early spring months under both emissions scenarios. Conversely, the latter part of the severe storm season may be curtailed, with supercells expected to decrease midsummer through early fall. These results suggest the potential for more significant tornadoes, hail, and extreme rainfall that, when combined with an increasingly vulnerable society, may produce disastrous consequences.

Converting tropical forests to agriculture increases fire risk by fourfold

Deforestation exacerbates climate change through greenhouse gas emissions, but other climatic alterations linked to the local biophysical changes from deforestation remain poorly understood. Here, we assess the impact of tropical deforestation on fire weather risk—defined as the climate conditions conducive to wildfires—using high-resolution convection-permitting climate simulations. We consider two land cover scenarios for the island of Borneo: land cover in 1980 (forest scenario) and land cover in 2050 (deforestation scenario) to force a convection-permitting climate model, using boundary conditions from ERA-Interim reanalysis for the 2002–2016 period. Our findings revealed significant alterations in post-deforestation fire precursors such as increased temperature, wind speed and potential evapotranspiration and decreased humidity, cloud cover and precipitation. As a result, fire weather events that would occur once a year in the forested scenario, are likely to occur four times a year following deforestation. Likewise, for extreme conditions, such as those occurring on longer time-horizons than 20 years, the magnitude of extreme fire weather is likely to double following deforestation. These increases in extreme fire weather conditions demonstrate the key role of tropical forests in regulating regional climate processes, including reduced fire weather risk.

Changes in freezing rain occurrence over eastern Canada using convection-permitting climate simulations

Freezing precipitation has major consequences for ground and air transportation, the health of citizens, and power networks. Previous studies using coarse resolution climate models have shown a northward migration of freezing rain in the future. Increased model resolution can better define local topography leading to improved representation of conditions that are favorable for freezing rain. The goal of this study is to examine the climatology and characteristics of future freezing rain events using very-high resolution climate simulations. Historical and pseudo-global warming simulations with a 4-km horizontal grid length were used and compared with available observations. Simulations revealed a northerly shift of freezing rain occurrence, and an increase in the winter. Freezing rain was still shown to occur in the Saint-Lawrence River Valley in a warmer climate, primarily due to stronger wind channeling. Up to 50% of the future freezing rain events also occurred in present day climate within 12 h of each other. In northern Maine, they are typically shorter than 6 h in current climate and longer than 6 h in warmer conditions due to the onset of precipitation during low-pressure systems occurrences. The occurrence of freezing rain also locally increases slightly north of Québec City in a warmer climate because of freezing rain that is produced by warm rain processes. Overall, the study shows that high-resolution regional climate simulations are needed to study freezing rain events in warmer climate conditions, because high horizontal resolutions better define small-scale topographic features and local physical mechanisms that have an influence on these events.

A Sensitivity Assessment of COSMO-CLM to Different Land Cover Schemes in Convection-Permitting Climate Simulations over Europe

The question of how sensitive the regional and local climates are to different land cover maps and fractions is important, as land cover affects the atmospheric circulation via its influence on heat, moisture, and momentum transfer, as well as the chemical composition of the atmosphere. In this study, we used three independent land cover data sets, GlobCover 2009, GLC2000 and ESACCI-LC, as the lower boundary of the regional climate model COSMO-CLM (Consortium for Small Scale Modeling in Climate Mode, v5.0-clm15) to perform convection-permitting regional climate simulations over the large part of Europe covering the years 1999 and 2000 at a 0.0275° horizontal resolution. We studied how the sensitivity of the impacts on regional and local climates is represented by different land cover maps and fractions, especially between warm (summer) and cold (winter) seasons. We show that the simulated regional climate is sensitive to different land cover maps and fractions. The simulated temperature and observational data are generally in good agreement, though with differences between the seasons. In comparison to winter, the summer simulations are more heterogeneous across the study region. The largest deviation is found for the alpine area (−3 to +3 °C), which might be among different reasons due to different classification systems in land cover maps and orographical aspects in the COSMO-CLM model. The leaf area index and plant cover also showed different responses based on various land cover types, especially over the area with high vegetation coverage. While relating the differences of land cover fractions and the COSMO-CLM simulation results (the leaf area index, and plant coverage) respectively, the differences in land cover fractions did not necessarily lead to corresponding bias in the simulation results. We finally provide a comparative analysis of how sensitive the simulation outputs (temperature, leaf area index, plant cover) are related to different land cover maps and fractions. The different regional representations of COSMO-CLM indicate that the soil moisture, atmospheric circulation, evaporative demand, elevation, and snow cover schemes need to be considered in the regional climate simulation with a high horizontal resolution.

Extreme windstorms and sting jets in convection-permitting climate simulations over Europe

Extra-tropical windstorms are one of the costliest natural hazards affecting Europe, and windstorms that develop a sting jet are extremely damaging. A sting jet is a mesoscale core of very high wind speeds that occurs in Shapiro–Keyser type cyclones, and high-resolution models are required to adequately model sting jets. Here, we develop a low-cost methodology to automatically detect sting jets, using the characteristic warm seclusion of Shapiro–Keyser cyclones and the slantwise descent of high wind speeds, within pan-European 2.2 km convection-permitting climate model (CPM) simulations. The representation of wind gusts is improved with respect to ERA-Interim reanalysis data compared to observations; this is linked to better representation of cold conveyor belts and sting jets in the CPM. Our analysis indicates that Shapiro–Keyser cyclones, and those that develop sting jets, are the most damaging windstorms in present and future climates. The frequency of extreme windstorms is projected to increase by 2100 and a large contribution comes from sting jet storms. Furthermore, extreme wind speeds and their future changes are underestimated in the global climate model (GCM) compared to the CPM. We conclude that the CPM adds value in the representation of extreme winds and surface wind gusts and can provide improved input for impact models compared to coarser resolution models.

Added value of convection permitting climate modelling in urban overheating assessments

As a consequence of global warming and rapid urbanization around the globe, the magnitudes and frequencies of extreme heat events (EHEs) are increasing and this trend is expected to continue into the future. In this study, the added benefit of modelling climate at convection-permitting spatial resolutions (grid spacing <4 km) is considered for a set of exterior climate and interior building simulations during EHEs in the urban areas of Ottawa and Montreal, Canada over the summer of 2018. The climate is modelled at two spatial resolutions: i) 25 km – typically considered for regional-scale climate modelling; and ii) 1 km. The results derived from modelling at each of these resolutions is compared in respect to their adequacy in predicting different measures of overheating outdoors as well as those within a typical single-detached home. The results clearly demonstrate that simulations undertaken at a 1 km resolution permit more accurately calculate the magnitude of overheating, whereas simulations completed at a 25 km resolution lead to an underestimation of overheating in about 95% of the urban grids within either of these two cities. These results suggest the necessity of using convection-permitting climate simulations for overheating assessments over the urban scale.

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.

Snowfall and snowpack in the Western U.S. as captured by convection permitting climate simulations: current climate and pseudo global warming future climate

This study examines current and future western U.S. snowfall and snowpack through current and future climate simulations with a 4-km horizontal grid spacing cloud permitting regional climate model over the entire CONtinental U.S. for a 13-year period between 2001 and 2013. At this horizontal resolution, the spatiotemporal distribution of the orographic snowfall and snowpack is well captured partly due to the ability of the model to realistically simulate mesoscale and microphysical features such as orographically induced updrafts driving clouds and precipitation. The historical simulation well captures the observed snowfall and snowpack amounts and pattern in the western U.S. The future climate simulation uses the Pseudo-Global Warming approach, taking the climate change signal from CMIP5 multi-model ensemble-mean difference between 2070–2099 and 1976–2005. The results show that the thermodynamic impacts of climate change in the western U.S. can be characterized considering mountain ranges in two distinct geographic regions: the mountain ranges close to the Pacific Ocean (coastal ranges) and those in the inter-mountain west. Climate change out to 2100 significantly impacts all aspects of the water cycle, with pronounced climate change response in the coastal ranges. A notable result is that the snowpack in the Pacific Northwest is predicted to decrease by ~ 70% by 2100. Trends of this magnitude have already been observed in the historical data and in previous studies. The current Pseudo Global Warming future climate simulation and previous global climate simulations all suggest that these trends will continue to the point that most snowpack will be gone by 2100 in the Pacific Northwest for the most aggressive RCP8.5 climate scenario, even if annual precipitation increases by 10%. Future work will focus on extending the current convective permitting results to a full climate change simulation allowing for dynamical changes in the flow.