Pseudo Global Warming Simulation Research Articles

The Response of Tropopause-Overshooting Convection over North America to Climate Change

Abstract Recent field campaigns, observational studies, and modeling work have demonstrated that extratropical tropopause-overshooting convection has a substantial, and previously underestimated impact on stratospheric water vapor concentrations. This necessitates improved understanding of how tropopause-overshooting convection will respond to a warming climate. A growing body of research indicates that environments conducive to severe thunderstorms will occur more often and be increasingly unstable in the future, but no study has examined how this may be related to increased overshooting. To rectify this, this study leverages an existing pseudo-global warming (PGW) experiment to evaluate potential future changes in tropopause-overshooting convection over North America. We examine two 10-year simulations consisting of (1) a retrospective period (2003 – 2012) forced by ERA-interim initial and boundary conditions (the control simulation), and (2) the same retrospective period with CMIP5 ensemble-mean high-end emission scenario climate changes added to the initial and boundary conditions (the PGW simulation). Tropopause-overshooting convection in the control simulation is validated against observed overshoots from both ground-based radar observations in the United States and GOES satellite observations over North America. The model is shown to effectively simulate the observed regional distribution, annual cycle, and diurnal cycle of tropopause-overshooting convection. The projected response of tropopause-overshooting convection in the PGW simulation is found to increase more than 250% across the model domain, and the projected seasonal period of frequent tropopause-overshooting convection is shown to extend into late-summer. Additionally, tropopause-overshooting convection with extreme tropopause-relative heights (> 4 km) are more frequent in a warmed climate scenario.

Sensitivity of the pseudo-global warming method under flood conditions: a case study from the northeastern US

Abstract. Intensified extreme precipitation and corresponding floods are the most relevant consequences of climate change over the northeastern US (NEUS). To evaluate the impacts of climate change or certain climate perturbations on future extreme weather events which are dynamically similar to historic analogs, the pseudo-global warming (PGW) method has been frequently employed; however, this method lacks precise definition and guidelines, thus limiting its application. More specifically, three key questions related to the application of the PGW method remain unanswered: at what spatial scale should climate perturbations be applied? Among the different meteorological variables available, which ones should be perturbed? And will PGW projections vary significantly when different perturbations are applied? To address these questions, we examine the sensitivity and robustness of conclusions drawn from the PGW method over the NEUS by conducting multiple PGW experiments with varied perturbation spatial scales and choice of perturbed meteorological variables. The results show that the projections of precipitation and other essential variables at the regional mean scale are consistent across the PGW simulations, with a relative difference of much less than 10 %; however, different perturbation modifications can cause significant displacements of the storm events being simulated. Several previously assumed advantages of modifying only the temperature at regional mean scale, such as the preservation of geostrophic balance, do not appear to hold. Also, for these experiments, we find the regional mean perturbation produces a positive precipitation bias because it ignores the land–ocean warming contrast, which is a robust regional response to global warming. Overall, PGW experiments with perturbations from temperature or the combination of temperature and wind at the grid point scale are both recommended, depending on the research questions. The first approach can isolate the spatially dependent thermodynamic impact, and the latter incorporates both the thermodynamic and dynamic impacts.

The pseudo-global-warming (PGW) approach: methodology, software package PGW4ERA5 v1.1, validation, and sensitivity analyses

Abstract. The term “pseudo-global warming” (PGW) refers to a simulation strategy in regional climate modeling. The strategy consists of directly imposing large-scale changes in the climate system on a control regional climate simulation (usually representing current conditions) by modifying the boundary conditions. This differs from the traditional dynamic downscaling technique where output from a global climate model (GCM) is used to drive regional climate models (RCMs). The PGW climate changes are usually derived from a transient global climate model (GCM) simulation. The PGW approach offers several benefits, such as lowering computational requirements, flexibility in the simulation design, and avoiding biases from global climate models. However, implementing a PGW simulation is non-trivial, and care must be taken not to deteriorate the physics of the regional climate model when modifying the boundary conditions. To simplify the preparation of PGW simulations, we present a detailed description of the methodology and provide the companion software PGW4ERA5 facilitating the preparation of PGW simulations. In describing the methodology, particular attention is devoted to the adjustment of the pressure and geopotential fields. Such an adjustment is required when ensuring consistency between thermodynamical (temperature and humidity) changes on the one hand and dynamical changes on the other hand. It is demonstrated that this adjustment is important in the extratropics and highly essential in tropical and subtropical regions. We show that climate projections of PGW simulations prepared using the presented methodology are closely comparable to traditional dynamic downscaling for most climatological variables.

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.

Future intensification of precipitation and wind gust associated thunderstorms over Lake Victoria

Severe thunderstorms affect more than 30 million people living along the shores of Lake Victoria (East Africa). Thousands of fishers lose their lives on the lake every year. While deadly waves are assumed to be initiated by severe wind gusts, knowledge about thunderstorms is restricted to precipitation or environmental proxies. Here we use a regional climate model run at convection-permitting resolution to simulate both precipitation and wind gusts over Lake Victoria for a historical 10-year period. In addition, a pseudo global warming simulation provides insight into the region’s future climate. In this simulation, ERA5’s initial and boundary conditions are perturbed with atmospheric changes between 1995–2025 and 2070–2100, projected by CMIP6’s ensemble mean. It was found that future decreases in both mean precipitation and wind gusts over Lake Victoria can be attributed to a weaker mean mesoscale circulation that reduces the trigger for over-lake nighttime convection and decreases the mean wind shear. However, an intensification of extremes is projected for both over-lake precipitation and wind gusts. The observed ∼7 %K−1 Clausius–Clapeyron extreme precipitation scaling is ascribed to increased water vapor content and a compensation of weaker mesoscale circulations and stronger thunderstorm dynamics. More frequent wind gust extremes result from higher wind shear conditions and more compound thunderstorms with both intense rainfall and severe wind gusts. Overall, our study emphasizes Lake Victoria’s modulating role in determining regional current and future extremes, in addition to changes expected from the Clausius–Clapeyron relation.

Modelled changes in selected agroclimatic indices over the croplands of western Canada under the RCP8.5 scenario

AbstractTo assess the potential change in agroclimatic indices in western Canada, this study used a convection‐permitting Weather Research Forecasting (WRF) model to conduct simulations for the current climate (CTL, 2000–2015) and future climate under the RCP8.5 scenario based on a pseudo‐global‐warming (PGW) approach. Both CTL and PGW simulations were bias‐corrected to the GEM‐CaPA dataset using a multivariate quantile mapping method. An evaluation of the CTL simulation of daily maximum and minimum temperatures and precipitation during the growing season against the gridded observations has been performed, indicating good agreements in the spatial patterns of air temperature and precipitation in western Canada. The PGW − CTL differences in several selected agroclimatic indices were then examined. Due to rising temperatures, substantial increases in growing degree‐days (GDD) by 800–1,200° days and reductions in frost days by 10 to 20 days, favouring regional crop production, are found in southern Alberta and Saskatchewan. However, global warming also poses great risks to Canadian agriculture by modifying heat accumulations and water availability during the growing season. Plant heat stress will substantially increase by ∼50° days in southern Alberta and Saskatchewan, offsetting the positive effects caused by the reduction in frost days and increase in GDD. The southern Canadian Prairies will experience statistically significant increases in the number of dry days and precipitation deficit, suggesting an exacerbation of water stress on the Canadian Prairies by global warming.

West Nile virus is predicted to be more geographically widespread in New York State and Connecticut under future climate change

The effects of climate change on infectious diseases are a topic of considerable interest and discussion. We studied West Nile virus (WNV) in New York (NY) and Connecticut (CT) using a Weather Research and Forecasting (WRF) model climate change scenario, which allows us to examine the effects of climate change and variability on WNV risk at county level. We chose WNV because it is well studied, has caused over 50,000 reported human cases, and over 2200 deaths in the United States. The ecological impacts have been substantial (e.g., millions of avian deaths), and economic impacts include livestock deaths, morbidity, and healthcare-related expenses. We trained two Random Forest models with observational climate data and human cases to predict future levels of WNV based on future weather conditions. The Regional Model used present-day data from NY and CT, whereas the Analog Model was fit for states most closely matching the predicted future conditions in the region. Separately, we predicted changes to mosquito-based WNV risk using a trait-based thermal biology approach (Mosquito Model). The WRF model produced control simulations (present day) and pseudo-global warming simulations (future). The Regional and Analog Models predicted an overall increase in human cases of WNV under future warming. However, the Analog Model did not predict as strong of an increase in the number of human cases as the Regional Model, and predicted a decrease in cases in some counties that currently experience high numbers of WNV cases. The Mosquito Model also predicted a decrease in risk in current high-risk areas, with an overall reduction in the population-weighted relative risk (but an increase in area-weighted risk). The Mosquito Model supports the Analog Model as making more realistic predictions than the Regional Model. All three models predicted a geographic increase in WNV cases across NY and CT.

Assessing past and future hazardous freezing rain and wet snow events in Manitoba, Canada using a pseudo-global warming approach

Freezing precipitation, in the form of freezing rain, freezing drizzle, and/or wet snow, can damage transportation networks, infrastructure, and vegetation. Ten events with freezing precipitation (including freezing rain and wet snow) over the province of Manitoba, Canada were examined using surface observational datasets, reanalysis products and 4-km resolution Weather Research and Forecasting (WRF) products that were both a retrospective control (CTRL) simulation as well as a pseudo-global warming (PGW) simulation. All events tracked to the south and/or east of Manitoba and most (8 of 10) events were associated with a consistent large scale pattern of extratropical cyclone with 500 hPa trough, low surface pressure center nearby, and an atmospheric river. Local factors, such as the 400 m elevated terrain of Riding Mountain, influenced 2 events mainly by altering surface temperature to be favorable for freezing precipitation. These events in the PGW simulation occurred 40–120 km farther north on average, with freezing rain generally being enhanced and wet snow generally being reduced, although wet snow was introduced into events which originally only had freezing rain. This study further showed that power lines aligned west to east, perpendicular to the strongest winds, are most susceptible to the consequences of icing and accretion within the current climate as well as the thermodynamically forced future one.

Estimation of Potential Economic Losses Due to Flooding Considering Variations of Spatial Distribution of Houses and Firms in a City

In Japan, flood disasters caused by record-breaking heavy rainfall frequently cause significant damages. It is also great concern that heavy rainfall may increase and occur more frequently due to global warming. In July 2013, a heavy rainfall event caused record-flooding of the Kakehashi River in Ishikawa Prefecture. In this study, pseudo global warming (PGW) experiments were implemented for the heavy rainfall in 1998 and 2013 around the Kakehashi River basin. Based on the results of PGW simulations, rainfall with different return periods were generated. Runoff analyses and inundation simulations were carried out by forcings with multiple return periods, and the results were used to estimate the economic losses due to flood inundation. Expected values of the economic losses were calculated using two methods for multiple return periods. Differences between the two expected values indicates the importance of the weighting method for the result of each return period. In addition, variations of spatial distribution of houses and firms in a city (i.e., urban structure) were simulated using a computable urban economics (CUE) model for the area of middle-lower reach of the Kakehashi River basin to examine its impact on economic loss due to flooding. In the simulation using the CUE model, a more severe flood inundation risk and an additional insurance burden for general households were added, and possible variations of urban structure were estimated around the lower part of the Kakehashi River basin. Under the more severe risk condition, relocation proceeded from higher risk areas to safer areas, and possible economic losses decreased in the target area. This result indicates that proper recognition of risk can reduce flood damages. On the other hand, there were small variations in economic losses under the condition with the additional flood insurance burden.

Modelling a tropical-like cyclone in the Mediterranean Sea under present and warmer climate

Abstract. This study focuses on a single Mediterranean hurricane (hereafter medicane), to investigate its response to global warming during the middle of the 21st century and assesses the effects of a warmer ocean and a warmer atmosphere on its development. Our investigation uses the state-of-the-art regional climate model WRF to produce the six-member, multi-physics ensembles. Results show that our model setup simulates a realistic cyclone track and the transition from an initial disturbance to a tropical-like cyclone with a deep warm core. However, the simulated transition occurs earlier than for the observed medicane. The response of the medicane to future climate change is investigated with a pseudo global warming (PGW) approach. This is the first application of the PGW framework to medicanes. The PGW approach adds a climate change delta (defined as difference between future and present climate) to WRF's boundary conditions which is obtained for all prognostic variables using the mean change in an ensemble of CMIP5 simulations. A PGW simulation where the climate change delta is added to all prognostic variables (PGWALL) shows that most of the medicane characteristics moderately intensify, e.g. surface wind speed, uptake of water vapour, and precipitation. However, the minimum sea level pressure (SLP) is almost identical to that under present climate conditions. Two additional PGW simulations were undertaken; One simulation adds the projected change in sea surface and skin temperature only (PGWSST) while the second simulation adds the PGW changes to only atmospheric variables (PGWATMS); i.e. we use present-day sea surface temperatures. These simulations show opposing responses of the medicane. In PGWSST, the medicane is more intense than PGWALL as indicated by lower SLP values, the stronger surface wind, and the more intense evaporation and precipitation. In contrast, the medicane in PGWATMS still transitions into a tropical-like cyclone with a deep warm core, but the PGWATMS medicane weakens considerably (SLP, surface wind, and rainfall decrease). This difference can be explained by an increase in water vapour driven by the warmer ocean surface (favourable for cumulus convection). The warmer and drier atmosphere in PGWATMS tends to inhibit condensation (unfavourable for cumulus convection). The warmer ocean and warmer atmosphere have counteracting effects which leads to only a modest enhancement of the medicane by global warming. The novel approach in this study provides new insights into the different roles of warming of the ocean and atmosphere in medicane development.

Reduced frequency and size of late-twenty-first-century snowstorms over North America

Understanding how snowstorms may change in the future is critical for estimating impacts on water resources and the Earth and socioeconomic systems that depend on them. Here we use snowstorms as a marker to assess the mesoscale fingerprint of climate change, providing a description of potential changes in winter weather event occurrence, character and variability in central and eastern North America under a high anthropogenic emissions pathway. Snowstorms are segmented and tracked using high-resolution, snow water equivalent output from dynamically downscaled simulations which, unlike global climate models, can resolve important mesoscale features such as banded snow. Significant decreases are found in the frequency and size of snowstorms in a pseudo-global warming simulation, including those events that produce the most extreme snowfall accumulations. Early and late boreal winter months show particularly robust proportional decreases in snowstorms and snow water equivalent accumulations. Predicting the impact of climate change on snowstorms is key for future water resource estimates. North American snowstorms are tracked in high-resolution warming simulations and exhibit robust decreases in storm count, snow water equivalent and areal footprint, particularly in shoulder seasons.

Variations in extreme wave events near a South Pacific Island under global warming: case study of Tropical Cyclone Tomas

The intensification of tropical cyclones (TCs) and wind-induced ocean waves is expected to be amplified under global warming conditions. In 2010, strong TC Tomas approached the Fiji Islands and caused severe damage. Here, an ensemble simulation technique is combined with a pseudo-global warming (PGW) method to investigate future variations in TCs and wind-induced ocean waves. Ensemble PGW simulations were implemented using the weather research and forecasting (WRF) model with five different future projections. Hindcast and PGW simulations showed similar tracks of Tomas. In four PGW simulations, the central pressures of the simulated TCs decreased. Enhanced near-surface wind was recognized in three PGW simulations around the Fiji main island (Viti Levu). In the other two future simulations, the surface wind speed was weaker than the one in the present climate because of the slight eastward shift in the track and delayed development of the TC. WaveWatchIII (WW3) was applied for offshore wave simulations forced by the wind field obtained by WRF simulation results. In three future simulations, a clear increase in the maximum significant wave height (Hs) was found on the southeastern coast of Viti Levu. One future simulation yielded almost the same offshore wave characteristics as those under the present climate. In another future simulation, the ensemble mean Hs was as high as that in the present climate, but extremely large Hs values were found in several ensemble members. Future simulations using multiple global climate model (GCM) projections showed possible variations in TCs and wind-induced ocean waves which is useful for the risk assessment of various hazards.

High-resolution regional climate modeling and projection over western Canada using a weather research forecasting model with a pseudo-global warming approach

Abstract. Climate change poses great risks to western Canada's ecosystem and socioeconomical development. To assess these hydroclimatic risks under high-end emission scenario RCP8.5, this study used the Weather Research Forecasting (WRF) model at a convection-permitting (CP) 4 km resolution to dynamically downscale the mean projection of a 19-member CMIP5 ensemble by the end of the 21st century. The CP simulations include a retrospective simulation (CTL, 2000–2015) for verification forced by ERA-Interim and a pseudo-global warming (PGW) for climate change projection forced with climate change forcing (2071–2100 to 1976–2005) from CMIP5 ensemble added on ERA-Interim. The retrospective WRF-CTL's surface air temperature simulation was evaluated against Canadian daily analysis ANUSPLIN, showing good agreements in the geographical distribution with cold biases east of the Canadian Rockies, especially in spring. WRF-CTL captures the main pattern of observed precipitation distribution from CaPA and ANUSPLIN but shows a wet bias near the British Columbia coast in winter and over the immediate region on the lee side of the Canadian Rockies. The WRF-PGW simulation shows significant warming relative to CTL, especially over the polar region in the northeast during the cold season, and in daily minimum temperature. Precipitation changes in PGW over CTL vary with the seasons: in spring and late autumn precipitation increases in most areas, whereas in summer in the Saskatchewan River basin and southern Canadian Prairies, the precipitation change is negligible or decreased slightly. With almost no increase in precipitation and much more evapotranspiration in the future, the water availability during the growing season will be challenging for the Canadian Prairies. The WRF-PGW projected warming is less than that by the CMIP5 ensemble in all seasons. The CMIP5 ensemble projects a 10 %–20 % decrease in summer precipitation over the Canadian Prairies and generally agrees with WRF-PGW except for regions with significant terrain. This difference may be due to the much higher resolution of WRF being able to more faithfully represent small-scale summer convection and orographic lifting due to steep terrain. WRF-PGW shows an increase in high-intensity precipitation events and shifts the distribution of precipitation events toward more extremely intensive events in all seasons. Due to this shift in precipitation intensity to the higher end in the PGW simulation, the seemingly moderate increase in the total amount of precipitation in summer east of the Canadian Rockies may underestimate the increase in flooding risk and water shortage for agriculture. The change in the probability distribution of precipitation intensity also calls for innovative bias-correction methods to be developed for the application of the dataset when bias correction is required. High-quality meteorological observation over the region is needed for both forcing high-resolution climate simulation and conducting verification. The high-resolution downscaled climate simulations provide abundant opportunities both for investigating local-scale atmospheric dynamics and for studying climate impacts on hydrology, agriculture, and ecosystems.

Ambient Factors Controlling the Wintertime Precipitation Distribution across Mountain Ranges in the Interior Western United States. Part II: Changes in Orographic Precipitation Distribution in a Pseudo–Global Warming Simulation

AbstractTwo high-resolution (4 km) regional climate simulations over a 10-yr period are conducted to study the changes in wintertime precipitation distribution across mountain ranges in the interior western United States (IWUS) in a warming climate. One simulation represents the current climate, and another represents an ~2050 climate using a pseudo–global warming approach. The climate perturbations are derived from the ensemble mean of 15 global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). These simulations provide an estimate of average changes in wintertime orographic precipitation enhancement and finescale distribution across mountain ranges. The variability in these changes among CMIP5 models is quantified using statistical downscaling relations between orographic precipitation distribution and upstream conditions, developed in Part I. The CMIP5 guidance indicates a robust warming signal (~2 K) over the IWUS by ~2050 but minor changes in relative humidity and cloud-base height. The IWUS simulations reveal a widespread increase in precipitation on account of higher precipitation rates during winter storms in this warmer climate. This precipitation increase is most significant over the mountains rather than on the surrounding plains. The increase in precipitation rate is largely due to an increase in low-level cross-mountain moisture transport. The application of the statistical relations indicates that individual CMIP5 models disagree about the magnitude and distribution of orographic precipitation change in the IWUS, although most agree with the ensemble-mean-predicted orographic precipitation increase.

Future Projections of Typhoon Intensity Change by Pseudo-global Warming Simulations

Future Projections of Typhoon Intensity Change by Pseudo-global Warming Simulations

Characterization of the Simulated Regional Snow Albedo Feedback Using a Regional Climate Model over Complex Terrain

Abstract Midlatitude mountain regions are particularly sensitive to climate change because of an active snow albedo feedback (SAF). Here, the SAF is characterized and quantified over the complex terrain of the Colorado Headwaters region using high-resolution regional climate model simulations. A pair of 7-yr control and pseudo-global warming simulations is used to study the regional climate response to a large-scale thermodynamic climate perturbation. Warming is strongly enhanced in regions of snow loss by as much as 5°C. Linear feedback analysis is used to quantify the strength of the SAF within the Headwaters region. The strength of the SAF reaches a maximum value of 4 W m−2 K−1 during April when snow loss coincides with strong incoming solar radiation. Simulations using 4- and 12-km horizontal grid spacing show good agreement in the strength and timing of the SAF, whereas a 36-km simulation shows discrepancies that are tied to differences in snow accumulation and ablation caused by smoother terrain. Energy budget analysis shows that transport by atmospheric circulations acts as a negative feedback to regional warming, damping the effects of the SAF. On the mesoscale, the SAF nonlocally enhances warming in locations with no snow, and enhances snowmelt in locations that do not experience snow cover change. The methods presented here can be used generally to quantify the role of the SAF in simulated regional climate change, illuminating the causes of differences in climate warming between models and regions.

High-Resolution Coupled Climate Runoff Simulations of Seasonal Snowfall over Colorado: A Process Study of Current and Warmer Climate

Abstract Climate change is expected to accelerate the hydrologic cycle, increase the fraction of precipitation that is rain, and enhance snowpack melting. The enhanced hydrological cycle is also expected to increase snowfall amounts due to increased moisture availability. These processes are examined in this paper in the Colorado Headwaters region through the use of a coupled high-resolution climate–runoff model. Four high-resolution simulations of annual snowfall over Colorado are conducted. The simulations are verified using Snowpack Telemetry (SNOTEL) data. Results are then presented regarding the grid spacing needed for appropriate simulation of snowfall. Finally, climate sensitivity is explored using a pseudo–global warming approach. The results show that the proper spatial and temporal depiction of snowfall adequate for water resource and climate change purposes can be achieved with the appropriate choice of model grid spacing and parameterizations. The pseudo–global warming simulations indicate enhanced snowfall on the order of 10%–25% over the Colorado Headwaters region, with the enhancement being less in the core headwaters region due to the topographic reduction of precipitation upstream of the region (rain-shadow effect). The main climate change impacts are in the enhanced melting at the lower-elevation bound of the snowpack and the increased snowfall at higher elevations. The changes in peak snow mass are generally near zero due to these two compensating effects, and simulated wintertime total runoff is above current levels. The 1 April snow water equivalent (SWE) is reduced by 25% in the warmer climate, and the date of maximum SWE occurs 2–17 days prior to current climate results, consistent with previous studies.