The Canadian Prairies are a major grain production region, producing most of the wheat for export in Canada. Global warming and the associated changes in extreme precipitation and temperature events pose significant risks to agriculture on the Canadian Prairies. Compound hazards can cause higher crop failure than isolated events, especially in the main grain production regions in western Canada. To achieve informed climate risk management, it is critical to characterize the threats posed by compound hazards in current and future climates in western Canada. In this study, return periods of events were computed to assess the potential changes in the hotspots for agriculturally relevant compound events in western Canada using two convection-permitting climate simulations: current (CTL) climate and future climate under the RCP8.5 scenario based on a pseudo-global-warming (PGW) approach. Specifically, our study analyzed agricultural drought, low precipitation, heatwaves, and cool waves related to cool-season crops. The results showed the overall good performance of the CTL simulation in capturing spatial patterns of these compound events in western Canada. In the current climate, droughts and heatwaves co-occur mostly in southeastern parts of the prairies. Under the RCP8.5 scenario, they are likely to increase in frequency and expand to cover the major croplands of western Canada. This study provides information that policymakers in the fields of climate change adaptation and agricultural disaster management will find useful.

The Canadian Prairies are a major grain production region, producing most of the wheat for export in Canada. Global warming and the associated changes in extreme precipitation and temperature events pose significant risks to agriculture on the Canadian Prairies. Compound hazards can cause higher crop failure than isolated events, especially in the main grain production regions in western Canada. To achieve informed climate risk management, it is critical to characterize the threats posed by compound hazards in current and future climates in western Canada. In this study, return periods of events were computed to assess the potential changes in the hotspots for agriculturally relevant compound events in western Canada using two convection-permitting climate simulations: current (CTL) climate and future climate under the RCP8.5 scenario based on a pseudo-global-warming (PGW) approach. Specifically, our study analyzed agricultural drought, low precipitation, heatwaves, and cool waves related to cool-season crops. The results showed the overall good performance of the CTL simulation in capturing spatial patterns of these compound events in western Canada. In the current climate, droughts and heatwaves co-occur mostly in southeastern parts of the prairies. Under the RCP8.5 scenario, they are likely to increase in frequency and expand to cover the major croplands of western Canada. This study provides information that policymakers in the fields of climate change adaptation and agricultural disaster management will find useful.

Abstract. The US Northern Great Plains and the Canadian Prairies are known as the world’s breadbaskets for its large spring wheat production and exports to the world. It is essential to accurately represent spring wheat growing dynamics and final yield and improve our ability to predict food production under climate change. This study attempts to incorporate spring wheat growth dynamics into the Noah-MP crop model, for a long time period (13-year) and fine spatial scale (4-km). The study focuses on three aspects: (1) developing and calibrating the spring wheat model at point-scale, (2) applying a dynamic planting/harvest date to facilitate large-scale simulations, and (3) applying a temperature stress function to assess crop responses to heat stress amid extreme heat. Model results are evaluated using field observations, satellite leaf area index (LAI), and census data from Statistics Canada and the US Department of Agriculture (USDA). Results suggest that incorporating a dynamic planting/harvest threshold can better constrain the growing season, especially the peak timing and magnitude of wheat LAI, as well as obtain realistic yield compared to prescribing a static province/state-level map. Results also demonstrate an evident control of heat stress upon wheat yield in three Canadian Prairies Provinces, which are reasonably captured in the new temperature stress function. This study has important implications for estimating crop production, simulating the land-atmosphere interactions in croplands, and crop growth’s responses to the raising temperatures amid climate change.

Abstract. The US Northern Great Plains and the Canadian Prairies are known as the world’s breadbaskets for its large spring wheat production and exports to the world. It is essential to accurately represent spring wheat growing dynamics and final yield and improve our ability to predict food production under climate change. This study attempts to incorporate spring wheat growth dynamics into the Noah-MP crop model, for a long time period (13-year) and fine spatial scale (4-km). The study focuses on three aspects: (1) developing and calibrating the spring wheat model at point-scale, (2) applying a dynamic planting/harvest date to facilitate large-scale simulations, and (3) applying a temperature stress function to assess crop responses to heat stress amid extreme heat. Model results are evaluated using field observations, satellite leaf area index (LAI), and census data from Statistics Canada and the US Department of Agriculture (USDA). Results suggest that incorporating a dynamic planting/harvest threshold can better constrain the growing season, especially the peak timing and magnitude of wheat LAI, as well as obtain realistic yield compared to prescribing a static province/state-level map. Results also demonstrate an evident control of heat stress upon wheat yield in three Canadian Prairies Provinces, which are reasonably captured in the new temperature stress function. This study has important implications for estimating crop production, simulating the land-atmosphere interactions in croplands, and crop growth’s responses to the raising temperatures amid climate change.

Abstract. The US Northern Great Plains and the Canadian Prairies are known as the world's breadbaskets for their large spring wheat production and exports to the world. It is essential to accurately represent spring wheat growing dynamics and final yield and improve our ability to predict food production under climate change. This study attempts to incorporate spring wheat growth dynamics into the Noah-MP crop model for a long time period (13 years) and fine spatial scale (4 km). The study focuses on three aspects: (1) developing and calibrating the spring wheat model at a point scale, (2) applying a dynamic planting and harvest date to facilitate large-scale simulations, and (3) applying a temperature stress function to assess crop responses to heat stress amid extreme heat. Model results are evaluated using field observations, satellite leaf area index (LAI), and census data from Statistics Canada and the United States Department of Agriculture (USDA). Results suggest that incorporating a dynamic planting and harvest threshold can better constrain the growing season, especially the peak timing and magnitude of wheat LAI, as well as obtain realistic yield compared to prescribing a static province/state-level map. Results also demonstrate an evident control of heat stress upon wheat yield in three Canadian Prairies Provinces, which are reasonably captured in the new temperature stress function. This study has important implications in terms of estimating crop yields, modeling the land–atmosphere interactions in agricultural areas, and predicting crop growth responses to increasing temperatures amidst climate change.

Abstract. The US Northern Great Plains and the Canadian Prairies are known as the world's breadbaskets for their large spring wheat production and exports to the world. It is essential to accurately represent spring wheat growing dynamics and final yield and improve our ability to predict food production under climate change. This study attempts to incorporate spring wheat growth dynamics into the Noah-MP crop model for a long time period (13 years) and fine spatial scale (4 km). The study focuses on three aspects: (1) developing and calibrating the spring wheat model at a point scale, (2) applying a dynamic planting and harvest date to facilitate large-scale simulations, and (3) applying a temperature stress function to assess crop responses to heat stress amid extreme heat. Model results are evaluated using field observations, satellite leaf area index (LAI), and census data from Statistics Canada and the United States Department of Agriculture (USDA). Results suggest that incorporating a dynamic planting and harvest threshold can better constrain the growing season, especially the peak timing and magnitude of wheat LAI, as well as obtain realistic yield compared to prescribing a static province/state-level map. Results also demonstrate an evident control of heat stress upon wheat yield in three Canadian Prairies Provinces, which are reasonably captured in the new temperature stress function. This study has important implications in terms of estimating crop yields, modeling the land–atmosphere interactions in agricultural areas, and predicting crop growth responses to increasing temperatures amidst climate change.

Abstract Agriculture is directly related to food security as it determines the global food supply. Research in agriculture to predict crop productivity and losses helps avoid high food demand with little supply and price spikes. Here, we review ten crop models and one intercomparison project used for simulating crop growth and productivity under various impacts from soil–crop–atmosphere interactions. The review outlines food security and production assessments using numerical models for maize, wheat, and rice production. A summary of reviewed studies shows the following: (1) model ensembles provide smaller modeling errors compared to single models, (2) single models show better results when coupled with other types of models, (3) the ten reviewed crop models had improvements over the years and can accurately predict crop growth and yield for most of the locations, management conditions, and genotypes tested, (4) APSIM and DSSAT are fast and reliable in assessing broader output variables, (5) AquaCrop is indicated to investigate water footprint, quality and use efficiency in rainfed and irrigated systems, (6) all models assess nitrogen dynamics and use efficiency efficiently, excluding AquaCrop and WOFOST, (7) JULES specifies in evaluating food security vulnerability, (8) ORYZA is the main crop model used to evaluate paddy rice production, (9) grain filling is usually assessed with APSIM, DAISY, and DSSAT, and (10) the ten crop models can be used as tools to evaluate food production, availability, and security.

Abstract Motivated by the limited understanding of future changes in mesoscale convective systems (MCSs), we investigated characteristics of warm‐season (June–August) MCSs in the central United States based on high‐resolution convection‐permitting Weather Research and Forecasting simulations. We examined two 15‐year simulations, which include current simulations (2004–2018) forced by European Centre for Medium‐Range Weather Forecasts Reanalysis version 5 (ERA5) and future simulations (2086–2100) forced by perturbed ERA5 (i.e., ERA5 plus climate change signal derived from 28 Coupled Intercomparison Projected Phase 6 models under the Shared Socioeconomic Pathway–Representative Concentration Pathway 8.5 emission scenario). The initiations and longevities of MCSs were determined using the object‐tracking algorithm MODE‐Time Domain (MTD) from observation, current simulations (ERA), and future simulations (pseudo‐global warming, PGW). Objects identified by MODE‐Time Domain were divided into short‐/long‐lived (based on 75th percentiles of longevity) and daytime (initiated during 0000–1100 UTC)/nighttime (initiated during 1200–2300 UTC). We found that ERA and observation have comparable occurrences of MCSs. MCSs in PGW are associated with intensified rain rates in New Mexico, Colorado, and Kansas and lower rain rates in Texas, Louisiana, and Arkansas than in ERA. Moreover, the statistical analysis based on 15 parameters before MCSs initiation indicates that short‐lived MCSs in PGW are characterized by prominent changes in precipitable water (PW) and the most unstable convective available potential energy. We also found that long‐lived MCSs in PGW are associated with prominent changes in PW, unstable convective available potential energy, and isentropic potential vorticity at 345 K. According to the statistical results, PW is the most important variable in determining the longevity of MCSs and in understanding future changes.

Abstract. The energy and water vapor exchange between the land surface and atmospheric boundary layer plays a critical role in regional climate simulations. This paper implemented a hybrid data assimilation and machine learning framework (DA-ML method) into the Weather Research and Forecasting (WRF) model to optimize surface soil and vegetation conditions. The hybrid method can integrate remotely sensed leaf area index (LAI), multi-source soil moisture (SM) observations, and land surface models (LSMs) to accurately describe regional climate and land–atmosphere interactions. The performance of the hybrid method on the regional climate was evaluated in the Heihe River basin (HRB), the second-largest endorheic river basin in Northwest China. The results show that the estimated sensible (H) and latent heat (LE) fluxes from the WRF (DA-ML) model agree well with the large aperture scintillometer (LAS) observations. Compared to the WRF (open loop – OL), the WRF (DA-ML) model improved the estimation of evapotranspiration (ET) and generated a spatial distribution consistent with the ML-based watershed ET (ETMap). The proposed WRF (DA-ML) method effectively reduces air warming and drying biases in simulations, particularly in the oasis region. The estimated air temperature and specific humidity from WRF (DA-ML) agree well with the observations. In addition, this method can simulate more realistic oasis–desert boundaries, including wetting and cooling effects and wind shield effects within the oasis. The oasis–desert interactions can transfer water vapor to the surrounding desert in the lower atmosphere. In contrast, the dry and hot air over the desert is transferred to the oasis from the upper atmosphere. The results show that the integration of LAI and SM will induce water vapor intensification and promote precipitation in the upstream of the HRB, particularly on windward slopes. In general, the proposed WRF (DA-ML) model can improve climate modeling by implementing detailed land characterization information in basins with complex underlying surfaces.

Wetlands are important ecosystems—they provide vital hydrological and ecological services such as regulating floods, storing carbon, and providing wildlife habitat. The ability to simulate their spatial extents and hydrological processes is important for valuing wetlands' function. The purpose of this study is to dynamically represent the spatial extents and hydrological processes of wetlands and investigate their feedback to regional climate in the Prairie Pothole Region (PPR) of North America, where a large number of wetlands exist. In this study, we incorporated a wetland scheme into the Noah-MP land surface model with two major modifications: (a) modifying the subgrid saturation fraction for spatial wetland extent and (b) incorporating a dynamic wetland storage to simulate hydrological processes. This scheme was evaluated at a fen site in central Saskatchewan, Canada and applied regionally in the PPR with 13-year climate forcing produced by a high-resolution convection-permitting model. The differences between wetland and no-wetland simulations are significant, with increasing latent heat and evapotranspiration while suppressing sensible heat and runoff in the wetland scheme. Finally, the dynamic wetland scheme was applied in the Weather Research and Forecasting (WRF) model. The wetlands scheme not only modifies the surface energy balance but also interacts with the lower atmosphere, shallowing the planetary boundary layer height and promoting cloud formation. A cooling effect of 1–3°C in summer temperature is evident where wetlands are abundant. In particular, the wetland simulation shows reduction in the number of hot days for >10 days over the summer of 2006, when a long-lasting heatwave occurred. This research has great implications for land surface/regional climate modeling and wetland conservation, especially in mitigating extreme heatwaves under climate change.

This paper describes the occurrences and conditions before Mesoscale Convective Systems (MCSs) are initiated over the Canadian Prairies, using 10 years of observations and convection-permitting climate model simulations. The features of MCSs occurring in summer were analyzed using the Regional Deterministic Reforecast System (RDRS, hourly and 10-km grid spacing) and ECMWF Reanalysis v5 (ERA5)-forced Weather Research and Forecasting (WRF) model simulations (FSCT, 4-km grid spacing). MCSs were defined and tracked using the Method for Object-Based Diagnostic Evaluation-Time Domain (MTD). MTD-identified MCSs were divided into short−/long-lived and daytime/nighttime, considering the longevities and initiation times. FCST showed the skills to simulate MCSs but overestimated MCS features compared to RDRS. Fifteen meteorological parameters were calculated using sounding data from FCST to determine pre-conventional conditions of MCSs (at init. -9, −6, −3, and − 1 h). The distributions of parameters were tested to determine the significance of differences between short- and long-lived MCSs. The key findings are as follows: 1) long-lived daytime MCSs (LLM12) showed favorable thermodynamic processes and 2) long-lived nighttime MCSs (LLM00) were initiated based on dynamic processes. We also found that the most appropriate parameters (i.e., those that were statistically different in short- and long-lived MCSs) to determine the longevities of MCSs were 1) most unstable convective available potential energy and 2) vertical wind shear of 0–3 km.

Abstract In this work, we characterized the occurrences and conditions before the initiations of mesoscale convective systems (MCSs) in the central United States, using 15 years of observations and convection-permitting climate model simulations. The variabilities of MCSs in summer were obtained using high-resolution (4 km) observation data [Stage-IV (stIV)] and ECMWF Re-Analysis v5 (ERA5)-forced Weather Research and Forecasting (WRF) Model simulations (E5RUN). MCSs were identified using the object tracking algorithm MODE-time domain (MTD). MTD-determined MCSs were divided into daytime short-lived MCSs (SLM12), daytime long-lived MCSs (LLM12), nighttime short-lived MCSs (SLM00), and nighttime long-lived MCSs (LLM00). E5RUN showed skill to simulate MCSs by obtaining similar statistics in occurrences, areal coverages, and propagation speeds compared to those of stIV. We calculated the 15 parameters using sounding data from E5RUN before an MCS was initiated (−1, −3, −6, and −9 h) at each location of an MCS. The parameters were tested to figure out the significance of predicting the longevities of MCSs. The key findings are 1) LLM12 showed favorable thermodynamic variables compared to that of SLM12 and 2) LLM00 showed significant conditions of vertically rotating winds and sheared environments that affect the longevity of MCSs. Moreover, storm-relative helicity of 0–3 km, precipitable water, and vertical wind shear of 0–6 km are the most significant parameters to determine the longevities of MCSs (both daytime and nighttime MCSs). Significance Statement The purpose of this study is to understand the features of mesoscale convective systems (MCSs) in observational data and convection-permitting climate model simulations. We tested long-term simulations using new forcing data (ERA5) to see the benefits and limitations. We designed a novel approach to obtain the distributions of meteorological parameters (instead of obtaining one value for one event of MCS) before initiations of MCSs to understand preconvective conditions (times from −9 to −1 h from initiation). We also divided MCSs into daytime/nighttime and short-/long-lived MCSs to help predict MCSs longevity considering the initiation times. Our results provide hints for the forecasters to predict MCS longevity based on preconvective conditions from parameters discussed in this work.

To 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.

To 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.

Abstract In this study, two sets of precipitation estimates based on the regional Weather Research and Forecasting model (WRF) –the high Asia refined analysis (HAR) and outputs with a 9 km resolution from WRF (WRF-9km) are evaluated at both basin and point scales, and their potential hydrological utilities are investigated by driving the Variable Infiltration Capacity (VIC) large-scale land surface hydrological model in seven Third Pole (TP) basins. The regional climate model (RCM) tends to overestimate the gauge-based estimates by 20–95% in annual means among the selected basins. Relative to the gauge observations, the RCM precipitation estimates can accurately detect daily precipitation events of varying intensities (with absolute bias < 3 mm). The WRF-9km exhibits a high potential for hydrological application in the monsoon-dominated basins in the southeastern TP (with NSE of 0.7–0.9 and bias of -11% to 3%), while the HAR performs well in the upper Indus (UI) and upper Brahmaputra (UB) basins (with NSE of 0.6 and bias of -15% to -9%). Both the RCM precipitation estimates can accurately capture the magnitudes of low and moderate daily streamflow, but show limited capabilities in flood prediction in most of the TP basins. This study provides a comprehensive evaluation of the strength and limitation of RCMs precipitation in hydrological modeling in the TP with complex terrains and sparse gauge observations.

Abstract In this study, two sets of precipitation estimates based on the regional Weather Research and Forecasting model (WRF) –the high Asia refined analysis (HAR) and outputs with a 9 km resolution from WRF (WRF-9km) are evaluated at both basin and point scales, and their potential hydrological utilities are investigated by driving the Variable Infiltration Capacity (VIC) large-scale land surface hydrological model in seven Third Pole (TP) basins. The regional climate model (RCM) tends to overestimate the gauge-based estimates by 20–95% in annual means among the selected basins. Relative to the gauge observations, the RCM precipitation estimates can accurately detect daily precipitation events of varying intensities (with absolute bias < 3 mm). The WRF-9km exhibits a high potential for hydrological application in the monsoon-dominated basins in the southeastern TP (with NSE of 0.7–0.9 and bias of -11% to 3%), while the HAR performs well in the upper Indus (UI) and upper Brahmaputra (UB) basins (with NSE of 0.6 and bias of -15% to -9%). Both the RCM precipitation estimates can accurately capture the magnitudes of low and moderate daily streamflow, but show limited capabilities in flood prediction in most of the TP basins. This study provides a comprehensive evaluation of the strength and limitation of RCMs precipitation in hydrological modeling in the TP with complex terrains and sparse gauge observations.

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

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

Numerous wetlands in the prairies of Canada provide important ecosystem services, yet are threatened by climate and land-use changes. Understanding the impacts of climate change on prairie wetlands is critical to effective conservation planning. In this study, we construct a wetland model with surface water balance and ecoregions to project future distribution of wetlands. The climatic conditions downscaled from the Weather Research and Forecasting model were used to drive the Noah-MP land surface model to obtain surface water balance. The climate change perturbation is derived from an ensemble of general circulation models using the pseudo global warming method, under the RCP8.5 emission scenario by the end of 21st century. The results show that climate change impacts on wetland extent are spatiotemporally heterogenous. Future wetter climate in the western Prairies will favor increased wetland abundance in both spring and summer. In the eastern Prairies, particularly in the mixed grassland and mid-boreal upland, wetland areas will increase in spring but experience enhanced declines in summer due to strong evapotranspiration. When these effects of climate change are considered in light of historical drainage, they suggest a need for diverse conservation and restoration strategies. For the mixed grassland in the western Canadian Prairies, wetland restoration will be favorable, while the highly drained eastern Prairies will be challenged by the intensified hydrological cycle. The outcomes of this study will be useful to conservation agencies to ensure that current investments will continue to provide good conservation returns in the future.

Numerous wetlands in the prairies of Canada provide important ecosystem services, yet are threatened by climate and land-use changes. Understanding the impacts of climate change on prairie wetlands is critical to effective conservation planning. In this study, we construct a wetland model with surface water balance and ecoregions to project future distribution of wetlands. The climatic conditions downscaled from the Weather Research and Forecasting model were used to drive the Noah-MP land surface model to obtain surface water balance. The climate change perturbation is derived from an ensemble of general circulation models using the pseudo global warming method, under the RCP8.5 emission scenario by the end of 21st century. The results show that climate change impacts on wetland extent are spatiotemporally heterogenous. Future wetter climate in the western Prairies will favor increased wetland abundance in both spring and summer. In the eastern Prairies, particularly in the mixed grassland and mid-boreal upland, wetland areas will increase in spring but experience enhanced declines in summer due to strong evapotranspiration. When these effects of climate change are considered in light of historical drainage, they suggest a need for diverse conservation and restoration strategies. For the mixed grassland in the western Canadian Prairies, wetland restoration will be favorable, while the highly drained eastern Prairies will be challenged by the intensified hydrological cycle. The outcomes of this study will be useful to conservation agencies to ensure that current investments will continue to provide good conservation returns in the future.

Impacts of anthropogenic aerosols in China on autumn precipitation over Southwest China were investigated using version 5.1 of the Community Atmosphere Model. Simulations with and without anthropogenic aerosol emissions were compared to examine the effects of anthropogenic aerosols on surface air temperature and precipitation in East Asia. Our results show that the aerosol increase induces strong cooling over East Asia by aerosols' direct effect on radiation and indirect effect on clouds. Substantial reductions in precipitation are found across eastern China, but the largest decrease is in Southwest China. Anthropogenic aerosols cause a considerable increase in the cloud condensation nuclei number concentration and a decline in the cloud droplet effective radius in East Asia. The reduced cloud droplet sizes suppress the formation of precipitation and increase cloud depth and liquid water path. Consequently, aerosols' direct radiative effect as well as indirect effect on cloud depth and albedo significantly reduce the shortwave radiation for all sky between 20°and 40°N in China. More absorbing aerosols in the lower troposphere increase shortwave radiative heating, which possibly burns off low-level convective clouds and could cause significant reductions in condensational heating in the lower troposphere. The patterns of the shortwave heating increase and condensational heating reduction are generally consistent with significant reductions in the convective precipitation over China. We further investigated other factors governing precipitation and found moderate stability enhancement and moisture transport reductions in most of China, both of which partially contribute to a decrease in the convective precipitation in Southwest China. Aerosols' direct and indirect effects reduce the amount of solar radiation reaching the surface and cool the surface and lower troposphere between 20° and 40°N, causing anomalous subsidence and reductions in the large-scale precipitation over central and eastern China. Both convective and large-scale precipitation are suppressed over Southwest China, leading to a significant decrease in total precipitation over this area. • Aerosols induce strong cooling by their direct and indirect effects. • The largest decrease in autumn precipitation is found over Southwest China. • Absorbing aerosols increase shortwave heating, reducing low-level convective clouds. • Aerosols' cooling causes subsidence and large-scale precipitation reductions.

Impacts of anthropogenic aerosols in China on autumn precipitation over Southwest China were investigated using version 5.1 of the Community Atmosphere Model. Simulations with and without anthropogenic aerosol emissions were compared to examine the effects of anthropogenic aerosols on surface air temperature and precipitation in East Asia. Our results show that the aerosol increase induces strong cooling over East Asia by aerosols' direct effect on radiation and indirect effect on clouds. Substantial reductions in precipitation are found across eastern China, but the largest decrease is in Southwest China. Anthropogenic aerosols cause a considerable increase in the cloud condensation nuclei number concentration and a decline in the cloud droplet effective radius in East Asia. The reduced cloud droplet sizes suppress the formation of precipitation and increase cloud depth and liquid water path. Consequently, aerosols' direct radiative effect as well as indirect effect on cloud depth and albedo significantly reduce the shortwave radiation for all sky between 20°and 40°N in China. More absorbing aerosols in the lower troposphere increase shortwave radiative heating, which possibly burns off low-level convective clouds and could cause significant reductions in condensational heating in the lower troposphere. The patterns of the shortwave heating increase and condensational heating reduction are generally consistent with significant reductions in the convective precipitation over China. We further investigated other factors governing precipitation and found moderate stability enhancement and moisture transport reductions in most of China, both of which partially contribute to a decrease in the convective precipitation in Southwest China. Aerosols' direct and indirect effects reduce the amount of solar radiation reaching the surface and cool the surface and lower troposphere between 20° and 40°N, causing anomalous subsidence and reductions in the large-scale precipitation over central and eastern China. Both convective and large-scale precipitation are suppressed over Southwest China, leading to a significant decrease in total precipitation over this area. • Aerosols induce strong cooling by their direct and indirect effects. • The largest decrease in autumn precipitation is found over Southwest China. • Absorbing aerosols increase shortwave heating, reducing low-level convective clouds. • Aerosols' cooling causes subsidence and large-scale precipitation reductions.

Abstract. The interior of western Canada, like many similar cold mid- to high-latitude regions worldwide, is undergoing extensive and rapid climate and environmental change, which may accelerate in the coming decades. Understanding and predicting changes in coupled climate–land–hydrological systems are crucial to society yet limited by lack of understanding of changes in cold-region process responses and interactions, along with their representation in most current-generation land-surface and hydrological models. It is essential to consider the underlying processes and base predictive models on the proper physics, especially under conditions of non-stationarity where the past is no longer a reliable guide to the future and system trajectories can be unexpected. These challenges were forefront in the recently completed Changing Cold Regions Network (CCRN), which assembled and focused a wide range of multi-disciplinary expertise to improve the understanding, diagnosis, and prediction of change over the cold interior of western Canada. CCRN advanced knowledge of fundamental cold-region ecological and hydrological processes through observation and experimentation across a network of highly instrumented research basins and other sites. Significant efforts were made to improve the functionality and process representation, based on this improved understanding, within the fine-scale Cold Regions Hydrological Modelling (CRHM) platform and the large-scale Modélisation Environmentale Communautaire (MEC) – Surface and Hydrology (MESH) model. These models were, and continue to be, applied under past and projected future climates and under current and expected future land and vegetation cover configurations to diagnose historical change and predict possible future hydrological responses. This second of two articles synthesizes the nature and understanding of cold-region processes and Earth system responses to future climate, as advanced by CCRN. These include changing precipitation and moisture feedbacks to the atmosphere; altered snow regimes, changing balance of snowfall and rainfall, and glacier loss; vegetation responses to climate and the loss of ecosystem resilience to wildfire and disturbance; thawing permafrost and its influence on landscapes and hydrology; groundwater storage and cycling and its connections to surface water; and stream and river discharge as influenced by the various drivers of hydrological change. Collective insights, expert elicitation, and model application are used to provide a synthesis of this change over the CCRN region for the late 21st century.

Abstract. The interior of western Canada, like many similar cold mid- to high-latitude regions worldwide, is undergoing extensive and rapid climate and environmental change, which may accelerate in the coming decades. Understanding and predicting changes in coupled climate–land–hydrological systems are crucial to society yet limited by lack of understanding of changes in cold-region process responses and interactions, along with their representation in most current-generation land-surface and hydrological models. It is essential to consider the underlying processes and base predictive models on the proper physics, especially under conditions of non-stationarity where the past is no longer a reliable guide to the future and system trajectories can be unexpected. These challenges were forefront in the recently completed Changing Cold Regions Network (CCRN), which assembled and focused a wide range of multi-disciplinary expertise to improve the understanding, diagnosis, and prediction of change over the cold interior of western Canada. CCRN advanced knowledge of fundamental cold-region ecological and hydrological processes through observation and experimentation across a network of highly instrumented research basins and other sites. Significant efforts were made to improve the functionality and process representation, based on this improved understanding, within the fine-scale Cold Regions Hydrological Modelling (CRHM) platform and the large-scale Modélisation Environmentale Communautaire (MEC) – Surface and Hydrology (MESH) model. These models were, and continue to be, applied under past and projected future climates and under current and expected future land and vegetation cover configurations to diagnose historical change and predict possible future hydrological responses. This second of two articles synthesizes the nature and understanding of cold-region processes and Earth system responses to future climate, as advanced by CCRN. These include changing precipitation and moisture feedbacks to the atmosphere; altered snow regimes, changing balance of snowfall and rainfall, and glacier loss; vegetation responses to climate and the loss of ecosystem resilience to wildfire and disturbance; thawing permafrost and its influence on landscapes and hydrology; groundwater storage and cycling and its connections to surface water; and stream and river discharge as influenced by the various drivers of hydrological change. Collective insights, expert elicitation, and model application are used to provide a synthesis of this change over the CCRN region for the late 21st century.

Representing climate-crop interactions is critical to earth system modeling. Despite recent progress in modeling dynamic crop growth and irrigation in land surface models (LSMs), transitioning thes...

The oil sands industry in Canada uses soil–vegetation–atmosphere-transfer (SVAT) water balance models, calibrated against short-term (<ã10 years) field monitoring data, to evaluate long-term (ã60 years) reclamation cover design performance. These evaluations use long-term historical climate data; however, the effects of climate change should also be incorporated in these analyses. Although statistical downscaling of global climate change projections is commonly used to obtain local, site-specific climate, high resolution dynamical downscaling can also be used. The value of this latter approach to obtain local site-specific projections for mine reclamation covers has not been evaluated previously. This study explored the differences in key water balance components of three reclamation covers and three natural sites in northern Alberta, Canada, under future, site-specific, statistical, and dynamical climate change projections. Historical meteorological records were used to establish baseline periods. Temperature datasets were used to calculate potential evapotranspiration (PET) using the Hargreaves–Samani method. Statistical downscaling uses the Long Ashton Research Station Weather Generator (LARS-WG) and global circulation model (GCM) projections of temperature and precipitation. Dynamical climate change projections were generated on a 4 km grid using the weather research and forecasting (WRF) model. These climate projections were applied to a physically-based water balance model (i.e. Hydrus-1D) to simulate actual evapotranspiration (AET) and net percolation (NP) for the baseline and future periods. The key findings were: (a) LARS-WG outperformed WRF in simulating baseline temperatures and precipitation; (b) both downscaling methods showed similar directional shifts in the future temperatures and precipitation; (c) this, in turn, created similar directional shifts in future growing season median AET and NP, although the increase in future NP for LARS-WG was higher than that for WRF. The relative increases in future NP were much higher than the relative increases in future AET, particularly for the reclamation covers.

Abstract. Water resources in cold regions in western Canada face severe risks posed by anthropogenic global warming as evapotranspiration increases and precipitation regimes shift. Although understanding the water cycle is key for addressing climate change issues, it is difficult to obtain high spatial- and temporal-resolution observations of hydroclimatic processes, especially in remote regions. Climate models are useful tools for dissecting and diagnosing these processes, especially the convection-permitting (CP) high-resolution regional climate simulation, which provides advantages over lower-resolution models by explicitly representing convection. In addition to better representing convective systems, higher spatial resolution also better represents topography, mountain meteorology, and highly heterogeneous geophysical features. However, there is little work with convection-permitting regional climate models conducted over western Canada. Focusing on the Mackenzie River and Saskatchewan River basins, this study investigated the surface water budget and atmospheric moisture balance in historical and representative concentration pathway (RCP8.5) projections using 4 km CP Weather Research and Forecasting (WRF). We compared the high-resolution 4 km CP WRF and three common reanalysis datasets, namely the North American Regional Reanalysis (NARR), the Japanese 55-year Reanalysis (JRA-55), and European Centre for Medium-Range Weather Forecasts reanalysis interim dataset (ERA-Interim). High-resolution WRF outperforms the reanalyses in balancing the surface water budget in both river basins with much lower residual terms. For the pseudo-global-warming scenario at the end of the 21st century with representative concentration pathway (RCP8.5) radiative forcing, both the Mackenzie River and Saskatchewan River basins show increases in the amplitude for precipitation and evapotranspiration and a decrease in runoff. The Saskatchewan River basin (SRB) shows a moderate increase in precipitation in the west and a small decrease in the east. Combined with a significant increase in evapotranspiration in a warmer climate, the Saskatchewan River basin would have a larger deficit of water resources than in the current climate based on the pseudo-global-warming (PGW) simulation. The high-resolution simulation also shows that the difference of atmospheric water vapour balance in the two river basins is due to flow orientation and topography differences at the western boundaries of the two basins. The sensitivity of water vapour balance to fine-scale topography and atmospheric processes shown in this study demonstrates that high-resolution dynamical downscaling is important for large-scale water balance and hydrological cycles.

Abstract. Shallow groundwater in the Prairie Pothole Region (PPR) is predominantly recharged by snowmelt in the spring and supplies water for evapotranspiration through the summer and fall. This two-way exchange is underrepresented in current land surface models. Furthermore, the impacts of climate change on the groundwater recharge rates are uncertain. In this paper, we use a coupled land–groundwater model to investigate the hydrological cycle of shallow groundwater in the PPR and study its response to climate change at the end of the 21st century. The results show that the model does a reasonably good job of simulating the timing of recharge. The mean water table depth (WTD) is well simulated, except for the fact that the model predicts a deep WTD in northwestern Alberta. The most significant change under future climate conditions occurs in the winter, when warmer temperatures change the rain/snow partitioning, delaying the time for snow accumulation/soil freezing while advancing early melting/thawing. Such changes lead to an earlier start to a longer recharge season but with lower recharge rates. Different signals are shown in the eastern and western PPR in the future summer, with reduced precipitation and drier soils in the east but little change in the west. The annual recharge increased by 25 % and 50 % in the eastern and western PPR, respectively. Additionally, we found that the mean and seasonal variation of the simulated WTD are sensitive to soil properties; thus, fine-scale soil information is needed to improve groundwater simulation on the regional scale.

The growing concerns over urbanization and climate change have resulted in an exponential growth in publications on urban climatology in recent decades. However, an advanced synthesis that characterizes the existing studies is lacking. In this review, we used citation network analysis and a text mining approach to identify research trends and extract common research topics and the emerging domains in urban climatology. Based on the clustered networks, we found that aerosols and ozone, and urban heat island are the most popular topics. Together with other clusters, four emerging topical fields were identified: secondary organic aerosols, urban precipitation, flood risk and adaptation, and greenhouse gas emissions. The city case studies' geographical information was analyzed to explore the spatial–temporal patterns, especially in the emerging topical fields. Interdisciplinary research grew in recent years as the field of urban climatology expanded to interact with urban hydrology, health, energy issues, and social sciences. A few knowledge gaps were proposed: the lack of long‐term high‐temporal‐resolution observational data of organic aerosols for model validation and improvements, the need for predictions of urban effects on precipitation and extreme flooding events under climate change, and the lack of a framework for cooperation between physical sciences and social sciences under urban settings. To fill these gaps, we call for more observational data with high spatial and temporal resolution, using high‐resolution models that adequately represent urban processes to conduct scenario analyses for urban planning, and the development of intellectual frameworks for better integration of urban climatology and social‐economical systems in cities. This article is categorized under: Climate, History, Society, Culture > Disciplinary Perspectives

Object-based algorithm provides additional spatiotemporal information of precipitation, besides traditional aspects such as amount and intensity. Using the Method for Object-based Diagnostic Evaluation with Time Dimension (MODE-TD, or MTD), precipitation features in western Canada have been analyzed comprehensively based on the Canadian Precipitation Analysis, North American Regional Reanalysis, Multi-Source Weighted-Ensemble Precipitation, and a convection-permitting climate model. We found light precipitation occurs frequently in the interior valleys of western Canada while moderate to heavy precipitation is rare there. The size of maritime precipitation system near the coast is similar to the continental precipitation system on the Prairies for moderate to heavy precipitation while light precipitation on the Prairies is larger in size than that occurs near the coast. For temporal features, moderate to heavy precipitation lasts longer than light precipitation over the Pacific coast, and precipitation systems on the Prairies generally move faster than the coastal precipitation. For annual cycle, the west coast has more precipitation events in cold seasons while more precipitation events are identified in warm seasons on the Prairies due to vigorous convection activities. Using two control experiments, the way how the spatiotemporal resolution of source data influences the MTD results has been examined. Overall, the spatial resolution of source data has little influence on MTD results. However, MTD driven by dataset with coarse temporal resolution tend to identify precipitation systems with relatively large size and slow propagation speed. This kind of precipitation systems normally have short track length and relatively long lifetime. For a typical precipitation system (0.7 ∼ 2 × 104 km2 in size) in western Canada, the maximum propagation speed that can be identified by 6-h data is approximately 25 km h−1, 33 km h−1 for 3-h, and 100 km h−1 for hourly dataset. Since the propagation speed of precipitation systems in North America is basically between 0 and 80 km h−1, we argue that precipitation features can be identified properly by MTD only when dataset with hourly or higher temporal resolution is used.

Abstract. To assess the hydroclimatic risks posed by climate change in western Canada, this study conducted a retrospective simulation (CTL) and a pseudo-global warming (PGW) dynamical downscaling of future warming projection under RCP8.5 from an ensemble of CMIP5 climate model projections using a convection-permitting 4-km Weather Research Forecasting (WRF) model. The convection-permitting resolution of the model avoids the error-prone convection parameterization by explicitly resolving cumulus plumes. The evaluation of surface air temperature by the retrospective simulation WRF-CTL against a gridded observation ANUSPLIN shows that WRF simulation of daily mean temperature agrees well with ANUSPLIN temperature in terms of the geographical distribution of cold biases east of the Canadian Rockies, especially in spring. Compared with the observed precipitation from ANUSPLIN and CaPA, the WRF-CTL simulation captures the main pattern of distribution, but with a wet bias seen in higher precipitation near the British Columbia coast in winter and over the immediate region on the lee side of the Canadian Rockies. The PGW simulation shows more warming than 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 fall for both basins, precipitation is shown to increase, whereas in summer in the Saskatchewan River Basin, it either shows no increase or decreases, with less summer precipitation shown in PGW than in CTL for some parts of the Prairies. This seasonal difference in precipitation change suggests that in summer the Canadian Prairies and the southern Boreal Forest biomes will likely see a slight decline in precipitation minus evapotranspiration, which might impact soil moisture for farming and forest fires. With almost no increase in summer precipitation and much more evapotranspiration in PGW than in CTL, the water availability during the growing season will be challenging for the Canadian Prairies. WRF-PGW shows an increase of high-intensity precipitation events and shifts the distribution of precipitation events toward more extremely intensive events in all seasons, as current moderate events become extreme events with more vapor loading, especially in summer. 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 for both the Mackenzie and Saskatchewan river basins may not reflect the real change in flooding risk and water availability for agriculture. The high-resolution downscaled climate simulations provide abundant opportunities both for investigating local-scale atmospheric dynamics and for studying climate impacts in hydrology, agriculture, and ecosystems. 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.

Abstract. The Interior of Western Canada, up to and including the Arctic, has experienced rapid change in its climate, hydrology, cryosphere and ecosystems and this is expected to continue. Although there is general consensus that warming will occur in the future, many critical issues remain. In this first of two articles, attention is placed on atmospheric-related issues that range from large scales down to individual precipitation events. Each of these is considered in terms of expected change organized by season and utilizing climate scenario information as well as thermodynamically-driven future climatic forcing simulations. Large scale atmospheric circulations affecting this region are generally projected to become stronger in each season and, coupled with warming temperatures, lead to enhancements of numerous water-related and temperature-related extremes. These include winter snowstorms, freezing rain, drought as well as atmospheric forcing of spring floods although not necessarily summer convection. Collective insights of these atmospheric findings are summarized in a consistent, connected physical framework.

Abstract. Water resources in cold regions in western Canada face severe risks posed by anthropogenic global warming as evapotranspiration increases and precipitation regimes shift. Although understanding the water cycle is key in addressing climate change issues, it is difficult to obtain high spatial and temporal resolution observations of hydroclimatic processes, especially in remote regions. Climate models are useful tools for dissecting and diagnosing these processes, especially, convection-permitting (CP) high-resolution regional climate simulation provides advantages over lower-resolution models by explicitly representing convection. In addition to better representing convective systems, higher spatial resolution also better represents topography and mountain meteorology, and highly heterogeneous geophysical features. However, there is little work with convection-permitting regional climate models conducted over western Canada. Focusing on the Mackenzie and Saskatchewan river basins, this study investigated the surface water budget and atmospheric moisture balance in historical and RCP8.5 projections using 4-km CP Weather Research and Forecast (WRF). We compared the high-resolution 4-km CP WRF and three common reanalysis datasets: NARR, JRA-55, and ERA-Interim. High-resolution WRF out-performs the reanalyses in balancing the surface water budget in both river basins with much lower residual terms. For the pseudo-global warming scenario at the end of the 21st century with RCP8.5 radiative forcing, both the Mackenzie and Saskatchewan river basins show increases in the amplitude for precipitation and evapotranspiration and a decrease in runoff. The Saskatchewan river basin shows a moderate increase of precipitation in the west and a small decrease in the east. Combined with a significant increase of evapotranspiration in a warmer climate, the Saskatchewan river basin would have a larger deficit of water resources than in the current climate based on the PGW simulation. The high-resolution simulation also shows the difference of atmospheric water vapour balance in the two river basins is due to flow orientation and topography differences at the western boundaries of the two basins. The sensitivity of water vapour balance to fine-scale topography and atmospheric processes shown in this study demonstrates that high-resolution dynamical downscaling is important for large-scale water balance and hydrological cycles.

Uncertainties in representing land–atmosphere interactions can substantially influence regional climate simulations. Among these uncertainties, the surface exchange coefficient Ch is a critical parameter, controlling the total energy transported from the land surface to the atmosphere. Although it directly impacts the coupling strength between the surface and atmosphere, it has not been properly evaluated for regional climate models. This study assesses the representation of surface coupling strength in a stand-alone Noah-MP land surface model and in coupled 4-km Weather Research and Forecasting (WRF) model simulations. The data collected at eight FLUXNET sites of the Canadian Carbon Program and seven AMRIFLUX sites are used to evaluate the offline Noah-MP simulations. Nine of these FLUXNET sites are used for the evaluation of the coupled WRF simulations. These sites are categorized into three land use types: grassland, cropland, and forest. The surface exchange coefficients derived using three formulations in Noah-MP simulations are compared to those calculated from observations. Then, the default Czil  = 0 and new canopy-height dependent Czil are used in coupled WRF simulations over the spring and summer in 2006 to compare their effects on surface heat flux, temperature, and precipitation. When the new canopy-height dependent Czil scheme is used, the simulated Ch exchange coefficient agrees better with observation and improves the daily maximum air temperature and heat flux simulation over grassland and cropland in the US Great Plains. Over grassland, the modeled Ch shows a different diurnal cycle than that for observed Ch, which makes WRF lag behind the observed diurnal cycle of sensible heat flux and temperature. The difference in precipitation between the two schemes is not as clear as the temperature difference because the impact of changing Ch is not local.

The United Nations (UN) has identified 17 Sustainable Development Goals (SDGs) to tackle major barriers to sustainable development by 2030. Achieving these goals will rely on the contribution of all nations and require balancing trade-offs among different sectors. Water and food insecurity have long been the two major challenges facing China. To address these challenges and achieve the SDGs, China needs to safeguard its agricultural irrigation and water conservancy projects. Although China is making efforts to transition its agricultural development to a sustainable trajectory by promoting water-saving irrigation, a number of issues are emerging, both with policy reforms and technological innovations. Through synthesizing the historical development of agriculture and its relationship with policy and political regimes, this paper identifies four major issues that are challenging the sustainability transformation of China’s agricultural irrigation system and water conservancy projects: (1) problems with financial policy coordination between central and local governments; (2) the lack of incentives for farmers to construct and maintain irrigation infrastructure; (3) conflicts between decentralized operation of land and benefits from shared irrigation infrastructure; and (4) deterioration of small-scale irrigation infrastructure calls for action. In addressing these challenges, policy changes are required: government financial accountability at all levels needs to be clarified; subsidies need to be raised for the construction and management of small-scale irrigation and water conservancy projects; local non-profit organizations need to be established to enhance co-management between farmers and government.

Climate change and food security are complex global issues that require multidisciplinary approaches to resolve. A nexus exists between both issues, especially in developing countries, but little prior research has successfully bridged the divide. Existing resolutions to climate change and food security are expensive and resource demanding. Climate modelling is at the forefront of climate change literature and development planning, whereas agronomy research is leading food security plans. The Benin Republic and Nigeria have grown and developed in recent years but may not have all the tools required to implement and sustain long-term food security in the face of climate change. The objective of this paper is to describe the development and outputs of a new model that bridges climate change and food security. Data from the Intergovernmental Panel on Climate Change’s 5th Regional Assessment (IPCC AR5) were combined with a biodiversity database to develop the model to derive these outputs. The model was used to demonstrate what potential impacts climate change will have on the regional food security by incorporating agronomic data from four local underutilized indigenous vegetables (Amaranthus cruentus L., Solanum macrocarpon L., Telfairia occidentalis Hook f., and Ocimum gratissimum L.). The model shows that, by 2099, there is significant uncertainty within the optimal recommendations that originated from the MicroVeg project. This suggests that MicroVeg will not have long-term success for food security unless additional options (e.g., new field trials, shifts in vegetable grown) are considered, creating the need for need for more dissemination tools.

Convection-permitting models (CPM) with at least 4 km horizontal grid spacing enable the cumulus parameterization to be switched off and thus simulate convective processes more realistically than coarse resolution models. This study investigates if a North American scale CPM can reproduce the observed warm season precipitation diurnal cycle on a climate scale. Potential changes in the precipitation diurnal cycle characteristics at the end of the twenty first century are also investigated using the pseudo global warming approach under a high-end anthropogenic emission scenario (RCP8.5). Simulations are performed with the Advanced Research Weather Research and Forecasting (ARW-WRF) model with 4-km horizontal grid spacing. Results from the WRF historical run (2001–2013) are evaluated against hourly precipitation from 2903 weather stations and a gridded hourly precipitation product in the U.S. The magnitude and timing of the diurnal cycle peak are realistically simulated in most of the U.S. and southern Canada. The model also captures the transition from afternoon precipitation peaks eastward of the Rocky Mountains to night peaks in the central U.S., which is related to propagating mesoscale convective systems. However, the historical climate simulation does not capture the observed early morning peaks in the central U.S. and overestimates the magnitude of the diurnal precipitation peak in the southeast region. In the simulation of the future climate, both the precipitation amount of the diurnal cycle and precipitation intensity increase throughout the domain, along with an increase in precipitation frequency in the northern region of the domain in May. These increases indicate a clear intensification of the hydrologic cycle during the warm season with potential impacts on future water resources, agriculture, and flooding.

Abstract. The interior of western Canada, up to and including the Arctic, has experienced rapid change in its climate, hydrology, cryosphere, and ecosystems, and this is expected to continue. Although there is general consensus that warming will occur in the future, many critical issues remain. In this first of two articles, attention is placed on atmospheric-related issues that range from large scales down to individual precipitation events. Each of these is considered in terms of expected change organized by season and utilizing mainly “business-as-usual” climate scenario information. Large-scale atmospheric circulations affecting this region are projected to shift differently in each season, with conditions that are conducive to the development of hydroclimate extremes in the domain becoming substantially more intense and frequent after the mid-century. When coupled with warming temperatures, changes in the large-scale atmospheric drivers lead to enhancements of numerous water-related and temperature-related extremes. These include winter snowstorms, freezing rain, drought, forest fires, as well as atmospheric forcing of spring floods, although not necessarily summer convection. Collective insights of these atmospheric findings are summarized in a consistent, connected physical framework.

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.

Abstract. Warm-season precipitation over the Canadian Prairies plays a crucial role in activities in environment and society and has particular importance to agricultural production over the region. This research investigates how a warm season precipitation deficit over the Canadian Prairies is related to tropical Pacific forcing in the early summer 2015 drought. The significant deficit of precipitation in May and June of 2015 were coincident with a warm phase of El Nino–Southern Oscillation (ENSO) and a negative phase of Madden–Julian Oscillation (MJO)-4 index as they both favor a positive geopotential height anomaly in western Canada. Further investigation during the instrumental record period (1979–2015) shows that the warm-season precipitation in the Canadian Prairies and the corresponding atmospheric circulation anomalies over western Canada teleconnected with the lower boundary conditions in the tropical western Pacific. MJO may play a crucial role in determining the summer precipitation anomaly in the western Canadian Prairie when equatorial central Pacific is warmer than normal (NINO4 > 0) and MJO is more active. The mechanism of this teleconnection may be due to the propagation of stationary Rossby wave that is generated in the MJO-4 index region. When the tropical convection around MJO-4 index regions (western tropical Pacific, centered over 140 E) is more active than normal when NINO4 > 0, a Rossby wave train originates from western Pacific and propagates into the midlatitude North America causing an anomalous ridge in the upper level over western Canada.

Soil moisture plays an important role in modulating regional climate from sub-seasonal to seasonal timescales. Particularly important, soil moisture deficits can amplify summer heatwaves (HWs) through soil moisture-temperature feedback which has critical impacts on society, economy and human health. In this study, we evaluate decade-long convection-permitting Weather Research and Forecast (WRF) model simulations over the contiguous US on simulating heatwaves and their relationship with antecedent soil moisture using a dense observational network. We showed that the WRF model is capable of capturing the spatial patten of temperature threshold to define HWs, though the simulation shows a warm bias in the Midwest and cold bias in western mountainous regions. Two HW indices, based on frequency (HWF) and magnitude (HWM), are evaluated. Significant anti-correlations between antecedent soil moisture and both HW indices have been found in most parts of the domain except the South Pacific Coast. A detailed study has been conducted for the Midwest and South Great Plains regions, where two heatwaves had occurred in the last decade. In both regions, the high quantile of the HWF distribution shows a strong dependence on antecedent soil moisture: drier soil leads to much larger increase on the upper quantile of HWF than it does on the lower quantile. Soil moisture effects on the higher end of HWM are not as strong as on the lower end: wetter antecedent soil corresponds to a larger decrease on the lower quantile of HWM. WRF captures the heterogeneous responses to dry soil on HWF distribution in both regions, but overestimates these HWM responses in the Midwest and underestimates them in the South Great Plains. Our results show confidence in WRF’s ability to simulate HW characteristics and the impacts of antecedent soil moisture on HWs. These are also important implications for using high-resolution convection-permitting mode to study the coupling between land and atmosphere.

Abstract. Warm-season precipitation on the Canadian Prairies plays a crucial role in agricultural production. This research investigates how the early summer 2015 drought across the Canadian Prairies is related to the tropical Pacific forcing. The significant deficit of precipitation in May and June 2015 coincided with a warm phase of the El Niño–Southern Oscillation (ENSO) and a negative phase of Madden–Julian Oscillation (MJO)-4 index, which favour a positive geopotential height (GPH) anomaly in western Canada. Our further investigation during the instrumental record (1979–2016) shows that warm-season precipitation in the Canadian Prairies and the corresponding atmospheric circulation anomalies over western Canada teleconnected with the lower boundary conditions in the tropical western Pacific. Our results indicate that MJO can play a crucial role in determining the summer precipitation anomaly in the western Canadian Prairies when the equatorial central Pacific is warmer than normal (NINO4 > 0) and MJO is more active. This teleconnection is due to the propagation of a stationary Rossby wave that is generated in the MJO-4 index region. When the tropical convection around MJO-4 index region (western tropical Pacific, centred over 140∘ E) is more active than normal (NINO4 > 0), Rossby wave trains originate from the western Pacific with wavenumbers determined by the background mean wind and meridional absolute vorticity gradient. Under warm NINO4 conditions waves are generated with smaller wavenumbers compared to cold NINO4 conditions. These waves under warm NINO4 can propagate into the mid-latitudes over North America, causing a persistent anomalous ridge in the upper level over western Canada, which favours dry conditions over the region.

Abstract A devastating, flood-producing rainstorm occurred over southern Alberta, Canada, from 19 to 22 June 2013. The long-lived, heavy rainfall event was a result of complex interplays between topographic, synoptic, and convective processes that rendered an accurate simulation of this event a challenging task. In this study, the Weather Research and Forecasting (WRF) Model was used to simulate this event and was validated against several observation datasets. Both the timing and location of the model precipitation agree closely with the observations, indicating that the WRF Model is capable of reproducing this type of severe event. Sensitivity tests with different microphysics schemes were conducted and evaluated using equitable threat and bias frequency scores. The WRF double-moment 6-class microphysics scheme (WDM6) generally performed better when compared with other schemes. The application of a conventional convective/stratiform separation algorithm shows that convective activity was dominant during the early stages, then evolved into predominantly stratiform precipitation later in the event. The HYSPLIT back-trajectory analysis and regional water budget assessments using WRF simulation output suggest that the moisture for the precipitation was mainly from recycling antecedent soil moisture through evaporation and evapotranspiration over the Canadian Prairies and the U.S. Great Plains. This analysis also shows that a small fraction of the moisture can be traced back to the northeastern Pacific, and direct uptake from the Gulf of Mexico was not a significant source in this event.

The circulation patterns of persistent cold weather spells with durations longer than 10 days in central–eastern North America (United States and Canada; 32°–52°N, 95°–65°W) are investigated by using NCEP reanalysis data from 1948 to 2014. The criteria for the persistent cold spells are: (1) three-day averaged temperature anomalies for the regional average over the central–eastern United States and Canada must be below the 10th percentile, and (2) such extreme cold spells must last at least 10 days. The circulation patterns associated with these cold spells are examined to find the common signals of these events. The circulation anomaly patterns of these cold spells are categorized based on the El Nino–Southern Oscillation, Arctic Oscillation (AO), and other climate indices. The atmospheric circulation patterns that favor the cold spells are identified through composites of geopotential height maps for the cold spells. Negative AO phases favor persistent cold spells. Phases of sea surface temperature (SST) modes that are associated with warm SSTs in the eastern extratropical Pacific also favor persistent cold events in the study region. Stratospheric polar vortex breakdown alone is not a good predictor for the regional extreme cold spells in central–eastern North America. The meridional dispersions of quasi-stationary Rossby waves in the Pacific–North America sector in terms of cut-off zonal wavenumber modulated by background flow are analyzed to provide insight into the difference in evolution of the cold spells under different mean AO phases. The waveguide for AO > 1 is in a narrow latitudinal band centered on 40°N, whereas the waveguide for AO <–1 is in a broader latitudinal band from 40° to 65°N. The circulation patterns and lower boundary conditions favorable for persistent cold spells identified by this study can be a stepping-stone for improving winter subseasonal forecasting in North America.

In June 2013, excessive rainfall associated with an intense weather system triggered severe flooding in southern Alberta, which became the costliest natural disaster in Canadian history. This article provides an overview of the climatological aspects and large-scale hydrometeorological features associated with the flooding event based upon information from a variety of sources, including satellite data, upper air soundings, surface observations and operational model analyses. The results show that multiple factors combined to create this unusually severe event. The event was characterized by a slow-moving upper level low pressure system west of Alberta, blocked by an upper level ridge, while an associated well-organized surface low pressure system kept southern Alberta, especially the eastern slopes of the Rocky Mountains, in continuous precipitation for up to two days. Results from air parcel trajectory analysis show that a significant amount of the moisture originated from the central Great Plains, transported into Alberta by a southeasterly low level jet. The event was first dominated by significant thunderstorm activity, and then evolved into continuous precipitation supported by the synoptic-scale low pressure system. Both the thunderstorm activity and upslope winds associated with the low pressure system produced large rainfall amounts. A comparison with previous similar events occurring in the same region suggests that the synoptic-scale features associated with the 2013 rainfall event were not particularly intense; however, its storm environment was the most convectively unstable. The system also exhibited a relatively high freezing level, which resulted in rain, rather than snow, mainly falling over the still snow-covered mountainous areas. Melting associated with this rain-on-snow scenario likely contributed to downstream flooding. Furthermore, above-normal snowfall in the preceding spring helped to maintain snow in the high-elevation areas, which facilitated the rain-on-snow event.