Future Precipitation Changes Research Articles

Intensification scenarios in projected precipitation using stochastic weather generators: a case study of central Oklahoma

Previous studies have investigated the character and distribution of intense precipitation events across the United States. Increasing trends in intense, daily precipitation events at heavy (90–< 95th percentile), very heavy (95–< 99th percentile), and extreme (≥ 99th percentile) thresholds have all been reported. However, no previous studies have investigated the potential application of stochastic weather generators in determining future, site-specific distributions of such intense precipitation occurrences. In this study, two scenarios of future changes in intense precipitation for Weatherford, Oklahoma were examined through the use of a specific weather generator, SYNTOR, and by examination of heavy, very heavy, and extreme precipitation categories. All precipitation events across the three categories were increased multiple times by eight different percentages ranging from 5% to 75%, while precipitation events within the three categories were simultaneously increased by 14%, 20%, and 30%, respectively. Projected changes in the occurrence and categorical thresholds of intense precipitation events, as well as total monthly and annual precipitation and wet-dry transition probabilities, were assessed. The findings of this study show that projected increases in intense precipitation ranging from 5% to 40% are plausible and within the margin of error, based on the application of the two intensification scenarios to the synthetically generated weather data. Overall, the precipitation intensification scenarios markedly impacted estimates of intense precipitation, as well as average annual and monthly precipitation totals, but did not markedly impact the temporal distribution of precipitation annually or across seasons, nor the transition probabilities of projected precipitation between wet and dry days. Precipitation intensification scenarios can ultimately benefit in simulating erosion, runoff, and crop productivity responses to future precipitation distributions in agricultural watersheds of the Southern Great Plains as well as other locations.

Evaluation of CMIP5 models and ensemble climate projections using a Bayesian approach: a case study of the Upper Indus Basin, Pakistan

The availability of a variety of Global Climate Models (GCMs) has increased the importance of the selection of suitable GCMs for impact assessment studies. In this study, we have used Bayesian Model Averaging (BMA) for GCM(s) selection and ensemble climate projection from the output of thirteen CMIP5 GCMs for the Upper Indus Basin (UIB), Pakistan. The results show that the ranking of the top best models among thirteen GCMs is not uniform regarding maximum, minimum temperature, and precipitation. However, some models showed the best performance for all three variables. The selected GCMs were used to produce ensemble projections via BMA for maximum, minimum temperature and precipitation under RCP4.5 and RCP8.5 scenarios for the duration of 2011–2040. The ensemble projections show a higher correlation with observed data than individual GCM’s output, and the BMA’s prediction well captured the trend of observed data. Furthermore, the 90% prediction intervals of BMA’s output closely captured the extreme values of observed data. The projected results of both RCPs were compared with the climatology of baseline duration (1981–2010) and it was noted that RCP8.5 show more changes in future temperature and precipitation compared to RCP4.5. For maximum temperature, there is more variation in monthly climatology for the duration of 2011–2040 in the first half of the year; however, under the RCP8.5, higher variation was noted during the winter season. A decrease in precipitation is projected during the months of January and August under the RCP4.5 while under RCP8.5, decrease in precipitation was noted during the months of March, May, July, August, September, and October; however, the changes (decrease/increase) are higher than under the RCP4.5.

Evaluating watershed hydrological responses to climate changes at Hangar Watershed, Ethiopia

AbstractThe aim of this study is to model the responses of Hangar Watershed hydrology to future climate changes under two representative concentration pathway (RCP) scenarios. Future changes in precipitation and temperature were produced using the output of dynamically downscaled data of a regional climate model (RCM) 0.44° resolution under RCP 4.5 and 8.5 scenarios for 2025–2055 and 2056–2086. The future projection of the RCM model of precipitation and temperatures showed an increasing trend relative to the base period (1987–2017). At 2025–2055 average annual precipitation increments of +15.7 and +19.8% were expected for RCP 4.5 and RCP 8.5, respectively. For 2056–2086 of RCP 4.5 and 8.5, a similar trend was also shown as average annual precipitation may increase by +20.1 and +23.4%, respectively. The changes of climate parameters were used as input into the SWAT hydrological model to simulate the future runoff at Hangar Watershed. The increment in precipitation projection resulted in a positive magnitude impact on average runoff flow. The average annual change in runoff at 2025–2055 of both RCP 4.5 and 8.5 may increase by +24.5 and +23.6%, respectively. In 2056–2086, a change in average annual runoff of +73.2 and +73.2% for RCP 4.5 and 8.5 may be expected, respectively.

Precipitation response to climate change and urban development over the continental United States

Appropriately characterizing future changes in regional-scale precipitation requires assessment of the interactive effect owing to greenhouse gas-induced climate change and the physical growth of the built environment. Here we use a suite of medium resolution (20 km grid spacing) decadal scale simulations conducted with the Weather Research and Forecasting model coupled to an urban canopy parameterization to examine the interplay between end-of-century long-lived greenhouse gas (LLGHG) forcing and urban expansion on continental US (CONUS) precipitation. Our results show that projected changes in extreme precipitation are at least one order of magnitude greater than projected changes in mean precipitation; this finding is geographically consistent over the seven CONUS National Climate Assessment (NCA) regions and between the pair of dynamically downscaled global climate model (GCM) forcings. We show that dynamical downscaling of the Geophysical Fluid Dynamics Laboratory GCM leads to projected end-of-century changes in extreme precipitation that are consistently greater compared to dynamical downscaling of the Community Earth System Model GCM for all regions except the Southeast NCA region. Our results demonstrate that the physical growth of the built environment can either enhance or suppress extreme precipitation across CONUS metropolitan regions. Incorporation of LLGHGs indicates compensating effects between urban environments and greenhouse gases, shifting the probability spectrum toward broad enhancement of extreme precipitation across future CONUS metropolitan areas. Our results emphasize the need for development of management policies that address flooding challenges exacerbated by the twin forcing agents of urban- and greenhouse gas-induced climate change.

Sensitivity of modeled Indian monsoon to Chinese and Indian aerosol emissions

Abstract. The South Asian summer monsoon supplies over 80 % of India's precipitation. Industrialization over the past few decades has resulted in severe aerosol pollution in India. Understanding monsoonal sensitivity to aerosol emissions in general circulation models (GCMs) could improve predictability of observed future precipitation changes. The aims here are (1) to assess the role of aerosols in India's monsoon precipitation and (2) to determine the roles of local and regional emissions. For (1), we study the Precipitation Driver Response Model Intercomparison Project experiments. We find that the precipitation response to changes in black carbon is highly uncertain with a large intermodel spread due in part to model differences in simulating changes in cloud vertical profiles. Effects from sulfate are clearer; increased sulfate reduces Indian precipitation, a consistency through all of the models studied here. For (2), we study bespoke simulations, with reduced Chinese and/or Indian emissions in three GCMs. A significant increase in precipitation (up to ∼20 %) is found only when both countries' sulfur emissions are regulated, which has been driven in large part by dynamic shifts in the location of convective regions in India. These changes have the potential to restore a portion of the precipitation losses induced by sulfate forcing over the last few decades.

Mean sea surface temperature changes influence ENSO-related precipitation changes in the mid-latitudes

El Niño profoundly impacts precipitation in high-population regions. This demands an advanced understanding of the changes in El Niño-induced precipitation under the future global warming scenario. However, thus far, consensus is lacking regarding future changes in mid-latitude precipitation influenced by El Niño. Here, by analyzing the Coupled Model Intercomparison Project simulations, we show that future precipitation changes are tightly linked to the response of each type of El Niño to the tropical Pacific mean sea surface temperature (SST) change. A La Niña-like mean SST change intensifies basin-wide El Niño events causing approximately 20% more precipitation over East Asia and North America via enhancing moisture transport. Meanwhile, an El Niño-like mean SST change generates more frequent eastern Pacific El Niño events, enhancing precipitation in North American. Our findings highlight the importance of the mean SST projection in selectively influencing the types of El Niño and their remote impact on precipitation.

Variations in Flash Flood–Producing Storm Characteristics Associated with Changes in Vertical Velocity in a Future Climate in the Mississippi River Basin

AbstractThe Mississippi River basin (MRB) is a flash flood hotspot receiving the most frequent flash floods and highest average rainfall accumulation of any region in the United States. Given the destruction flash floods cause in the current climate in the MRB, it is critical to understand how they will change in a future, warmer climate in order to prepare for these impacts. Recent work utilizing convection-permitting climate simulations to analyze future precipitation changes in flash flood–producing storms in the United States shows that the MRB experiences the greatest future increase in flash flood rainfall. This result motivates the goal of the present study to better understand the changes to precipitation characteristics and vertical velocity in flash flood–producing storms in the MRB. Specifically, the variations in flash flood–producing storm characteristics related to changes in vertical velocity in the MRB are examined by identifying 484 historical flash flood–producing storms from 2002 and 2013 and studying how they change in a future climate using 4-km convection-permitting simulations under a pseudo–global warming framework. In a future climate, precipitation and runoff increase by 17% and 32%, respectively, in flash flood–producing storms in the MRB. While rainfall increases in all flash flood–producing storms due to similar increases in moisture, it increases the most in storms with the strongest vertical velocity, suggesting that storm dynamics might modulate future changes in rainfall. These results are necessary to predict and prepare for the multifaceted impacts of climate change on flash flood–producing storms in order to create more resilient communities.

Shifting community composition determines the biodiversity–productivity relationship under increasing precipitation and N deposition

AbstractQuestionsThe relationships between biodiversity and ecosystem functioning (BEF) vary largely across natural ecosystems, with a unimodal, monotonous linear or no relationship. However, it remains unclear how BEF relationships vary under global change. Given future predicted changes in precipitation and nitrogen (N) deposition, it is crucial to determine how precipitation change and N deposition affect grassland biodiversity and productivity, and regulate their relationships.LocationA Dry Mixed‐Grass Prairie of western Canada.MethodsWe established a manipulative field experiment of increased precipitation (water addition with approximately 15% and 30% more monthly precipitation) and N addition (10 g/m2) using a randomized complete block design, including six treatments, each replicated five times (30 plots). We conducted vegetation sampling with a 1 m × 1 m quadrat in each plot from 2016 to 2017, to examine the individual and interactive effects of water and N addition on plant diversity, functional group composition, above‐ and below‐ground productivity, and the diversity–productivity relationships.ResultsWe found a positive linear diversity–above‐ground biomass (AGB) relationship under increased precipitation, which was attributed to the water‐induced increase in the abundance of forbs in the plant community, further promoting the positive effect of plant diversity on AGB. However, N addition caused a negative linear diversity–AGB relationship by increasing AGB and reducing plant diversity. The effects of N on diversity and productivity can be further strengthened under increased precipitation, which was due to the increase of C3rhizomatous grasses with high above‐ and below‐ground biomass and the decrease of forbs with high richness.ConclusionsOur results suggest that changes in functional group composition determine the plant species’ diversity, productivity, and their relationships under increasing precipitation and N deposition, which has significant implications for understanding and modelling ecosystem productivity in the context of global change.

How Much Arctic Fresh Water Participates in the Subpolar Overturning Circulation?

AbstractFresh Arctic waters flowing into the Atlantic are thought to have two primary fates. They may be mixed into the deep ocean as part of the overturning circulation, or flow alongside regions of deep water formation without impacting overturning. Climate models suggest that as increasing amounts of freshwater enter the Atlantic, the overturning circulation will be disrupted, yet we lack an understanding of how much freshwater is mixed into the overturning circulation’s deep limb in the present day. To constrain these freshwater pathways, we build steady-state volume, salt, and heat budgets east of Greenland that are initialized with observations and closed using inverse methods. Freshwater sources are split into oceanic Polar Waters from the Arctic and surface freshwater fluxes, which include net precipitation, runoff, and ice melt, to examine how they imprint the circulation differently. We find that 65 mSv (1 Sv ≡ 106 m3 s−1) of the total 110 mSv of surface freshwater fluxes that enter our domain participate in the overturning circulation, as do 0.6 Sv of the total 1.2 Sv of Polar Waters that flow through Fram Strait. Based on these results, we hypothesize that the overturning circulation is more sensitive to future changes in Arctic freshwater outflow and precipitation, while Greenland runoff and iceberg melt are more likely to stay along the coast of Greenland.

Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6

Abstract. The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081–2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5 ∘C) reached at the upper end of the 5 %–95 % envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5 ∘C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2 ∘C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5 ∘C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s.

Projection of future extreme precipitation in Iran based on CMIP6 multi-model ensemble

Extreme precipitation is the leading cause of the flood, soil erosion, and drought with significant socioeconomic impacts on human resources. Therefore, projecting future precipitation changes, especially the intensity of extreme precipitation (IEP) in the future, is very important. This study’s main objective is IEP projection in Iran based on CMIP6 bias-correction (BC) multi-model ensemble (MME). The daily precipitation data of five CMIP6 BC models with 0.5 horizontal resolution was used under three shared socioeconomic pathways; SSP1-2.6, SSP3-7.0, and SSP5-8.5 scenarios. Simple Daily Intensity (SDII) and maximum consecutive 1-day precipitation (RX1day) were used to measure IEP changes. Two Kling Gupta efficiency (KGE) and percent bias (PBIAS) methods evaluate the performance of the models, and the independence weighted mean (IWM) method was applied for ensemble averaging. Among the studied CMIP6 bias-correction models, the IPSL-CM6A-LR model has more underestimation than other models with a KGE score of 0.751 has the lowest performance and the MPI-ESM1-2-HR model (0.768) showed the highest performance. In general, the study results showed the uncertainties in CMIP6 models for precipitation, according to which no single model is reliable even in the BC method. The PBIAS in the region affected by Asian summer monsoon (ASM) in Iran is about 10%, based on which the bias of the mentioned models for monsoon precipitation is high. SDII and RX1day anomalies in all climatic zones of Iran except for the RX1day index in Cfa climatic zones in other zones and scenarios during the two periods 2021-2060 and 2061-2100 are positive. Also, the trend and slope of the IEP are increasing in all zones except for BWh, BWk, and Cfa zones for SSP1-2.6 and SSP3-7.0 scenarios. Investigation of trend IEP changes showed that the maximum of these changes will occur in the BWh climate zone, and the minimum would occur in the cold and mountainous climate zone of Iran (Dsc).

Temperature and precipitation projections for the Antarctic Peninsula over the next two decades: contrasting global and regional climate model simulations

This study presents near future (2020–2044) temperature and precipitation changes over the Antarctic Peninsula under the high-emission scenario (RCP8.5). We make use of historical and projected simulations from 19 global climate models (GCMs) participating in Coupled Model Intercomparison Project phase 5 (CMIP5). We compare and contrast GCMs projections with two groups of regional climate model simulations (RCMs): (1) high resolution (15-km) simulations performed with Polar-WRF model forced with bias-corrected NCAR-CESM1 (NC-CORR) over the Antarctic Peninsula, (2) medium resolution (50-km) simulations of KNMI-RACMO21P forced with EC-EARTH (EC) obtained from the CORDEX-Antarctica. A further comparison of historical simulations (1981–2005) with respect to ERA5 reanalysis is also included for circulation patterns and near-surface temperature climatology. In general, both RCM boundary conditions represent well the main circulation patterns of the historical period. Nonetheless, there are important differences in projections such as a notable deepening and weakening of the Amundsen Sea Low in EC and NC-CORR, respectively. Mean annual near-surface temperatures are projected to increase by about 0.5–1.5 $$^{\circ }$$ C across the entire peninsula. Temperature increase is more substantial in autumn and winter ( $$\sim $$ 2 $$^{\circ }$$ C). Following opposite circulation pattern changes, both EC and NC-CORR exhibit different warming rates, indicating a possible continuation of natural decadal variability. Although generally showing similar temperature changes, RCM projections show less warming and a smaller increase in melt days in the Larsen Ice Shelf compared to their respective driving fields. Regarding precipitation, there is a broad agreement among the simulations, indicating an increase in mean annual precipitation ( $$\sim $$ 5 to 10%). However, RCMs show some notable differences over the Larsen Ice Shelf where total precipitation decreases (for RACMO) and shows a small increase in rain frequency. We conclude that it seems still difficult to get consistent projections from GCMs for the Antarctic Peninsula as depicted in both RCM boundary conditions. In addition, dominant and common changes from the boundary conditions are largely evident in the RCM simulations. We argue that added value of RCM projections is driven by processes shaped by finer local details and different physics schemes that are introduced by RCMs, particularly over the Larsen Ice Shelf.

Future changes in the Dominant Source Layer of riparian lateral water fluxes in a subhumid Mediterranean catchment

The ‘Dominant Source Layer’ (DSL) is defined as the riparian zone (RZ) depth stratum that contributes the most to water and solute fluxes to streams. The concept can be used to explain timing and amount of matter transferred from RZs to streams in forest headwaters. Here, we investigated the potential impact of future climate changes on the long-term position of the DSL in a subhumid Mediterranean headwater catchment. We used the rainfall-runoff model PERSiST to simulate reference (1981–2000) and future (2081–2100) stream runoff. The latter were simulated using synthetic temperature, precipitation, and inter-event length scenarios in order to simulate possible effects of changes in temperature, rainfall amount, and rainfall event frequency and intensity. Simulated stream runoff was then used to estimate RZ groundwater tables and the proportion of lateral water flux at every depth in the riparian profile; and hence the DSL. Our simulations indicated that future changes in temperature and precipitation will have a similar impact on the long-term DSL position. Nearly all scenarios projected that, together with reductions in stream runoff and water exports, the DSL will move down in the future, by as much as ca. 30 cm. Shallow organic-rich layers in the RZ will only be hydrologically activated during sporadic, large rainfall episodes predicted for the most extreme inter-event length scenarios. Consequently, terrestrial organic matter inputs to streams will decrease, likely reducing catchment organic matter exports and stream dissolved organic carbon concentrations. This study highlights the importance of identifying vertical, hydrologically active layers in the RZ for a better understanding of the potential impact of future climate on lateral water transfer and their relationship with surface water quality and carbon cycling.

Cool season precipitation projections for California and the Western United States in NA-CORDEX models

Understanding future precipitation changes is critical for water supply and flood risk applications in the western United States. The North American COordinated Regional Downscaling EXperiment (NA-CORDEX) matrix of global and regional climate models at multiple resolutions (~ 50-km and 25-km grid spacings) is used to evaluate mean monthly precipitation, extreme daily precipitation, and snow water equivalent (SWE) over the western United States, with a sub-regional focus on California. Results indicate significant model spread in mean monthly precipitation in several key water-sensitive areas in both historical and future projections, but suggest model agreement on increasing daily extreme precipitation magnitudes, decreasing seasonal snowpack, and a shortening of the wet season in California in particular. While the beginning and end of the California cool season are projected to dry according to most models, the core of the cool season (December, January, February) shows an overall wetter projected change pattern. Daily cool-season precipitation extremes generally increase for most models, particularly in California in the mid-winter months. Finally, a marked projected decrease in future seasonal SWE is found across all models, accompanied by earlier dates of maximum seasonal SWE, and thus a shortening of the period of snow cover as well. Results are discussed in the context of how the diverse model membership and variable resolutions offered by the NA-CORDEX ensemble can be best leveraged by stakeholders faced with future water planning challenges.

Atmospheric dynamic constraints on Tibetan Plateau freshwater under Paris climate targets

Rivers originating in the Tibetan Plateau provide freshwater to downstream populations, yet runoff projections from warming are unclear due to precipitation uncertainties. Here, we use a historical atmospheric circulation–precipitation relationship to constrain future modelled wet-season precipitation over the Tibetan Plateau. Our constraint reduces precipitation increases to half of those from the unconstrained ensemble and reduces spread by around a factor of three. This constrained precipitation is used with estimated glacier melt contributions to constrain future runoff for seven rivers. We estimate runoff increases of 1.0–7.2% at the end of the twenty-first century for global mean warming of 1.5–4 °C above pre-industrial levels. Because population projections diverge across basins, this runoff increase will reduce the population fraction living under water scarcity conditions in the Yangtze and Yellow basins but not in the Indus and Ganges basins, necessitating improved water security through climate change adaptation policies in these regions at higher risk. Tibetan Plateau runoff projections are uncertain due to precipitation change uncertainty in climate models. Historical precipitation–circulation relationships constrain future wet-season precipitation and runoff change, suggesting worsening water scarcity for the Indus and Ganges river basins.

Present-day climate and projected future temperature and precipitation changes in Ecuador

Ecuador is likely to experience significant impacts associated with future changes in climate, but future projections for this region are challenging due to the complex topography and a wide range of climatic conditions. Here we use the Weather Research and Forecasting (WRF) model run at 10 km horizontal resolution over a domain encompassing all of Ecuador to investigate future changes in temperature and precipitation for the middle of the twenty-first century (2041–2070) under a low (RCP4.5) and a high (RCP8.5) emission scenario. The model was validated by running 30-year control runs for the present climate, driven both by the Climate Forecast System Reanalysis (CFSR) and the CCSM4 General Circulation Model. Bias and different correlation coefficient metrics were employed to compare the present-day model results with gridded (CRU TS v 4.03 and CHIRPS v 2.0) and in situ meteorological observations. Detailed hydrometeorological analyses over the Andes in both space and time domains show that WRF accurately simulates temperature variability. The precipitation seasonal cycle and interannual variability are also adequately simulated, but the model shows a general dry bias over the lowlands and a significant wet bias along the eastern Andean slopes. Results from future projections show that Ecuador could warm by an additional 1–2 K by the middle of the century compared with the end of the twentieth century. This warming is highly elevation-dependent, subjecting the highest peaks of the Andes to the strongest future warming. Bias-corrected future precipitation changes document a drying trend along coastal areas in RCP4.5 and increased future precipitation along the eastern Andean slopes in both scenarios.

Climate change, precipitation shifts and early summer drought: An irrigation tipping point for Finnish farmers?

In Finland early summer droughts are common. They cause yield losses (YLoss) of spring cereals, barley, oats and wheat, that cannot be compensated for later in the growing season. To support farmers in deciding whether to switch or not from rainfed to irrigated production, more data and understanding are needed on precipitation, its regional and interannual variation, caused YLoss and the cost-effectiveness of irrigation investments. This study aims to assess the spatiotemporal variation in early summer droughts and YLoss for spring cereals in the drought-prone Southwest Finland using past weather data (1971–2020). Furthermore, probability of early summer droughts was estimated based on two climate models, MPI-ESM and HadGEM2 and two greenhouse gas concentration scenarios, RCP4.5 and RCP8.5 for 2041–2070. Past data and future estimates of droughts were provided as 10 × 10 km2 gridded data. A cost-benefit analysis was used retrospectively to estimate the feasibility of irrigation in 1991–2020. Two irrigation systems were found to be economically feasible for larger farm units and in the case of high farm yield levels. However, projected changes in future precipitation were not substantial for the critical yield determination phase of cereals. Hence, the change in precipitation per se does not necessarily encourage farmers to invest in irrigation in the future but further expanding farm size and higher future cereal yields might act as additional incentives. To conclude, this novel data on precipitation patterns, caused YLoss, and economic feasibility may promote irrigation as a key measure to reduce production uncertainties and yield variability in high-latitude conditions, although early summer droughts are not necessarily increasing.

An Efficient Statistical Approach to Develop Intensity-Duration-Frequency Curves for Precipitation and Runoff under Future Climate.

Ongoing and potential future changes in precipitation will affect water management infrastructure. Urban drainage systems are particularly vulnerable. Design standards for many stormwater practices rely on precipitation intensity-duration-frequency (IDF) curves based on extreme value analysis. General Circulation Models (GCMs) project increases in future average temperature but are less clear on changes in precipitation. In many areas, climate projections suggest relatively small changes in total precipitation volume, but also suggest increased magnitude of extreme events. Model skill in predicting extreme precipitation events, however, is limited. We develop an approach for estimating future IDF curves that is efficient, uses widely available statistically downscaled GCM output, and is consistent with published IDF curves for the United States that are often incorporated into local stormwater regulations and design guides (and are GCM model agnostic). The method provides a relatively simple way to develop scenarios in a format directly useful to assessing risk to stormwater management infrastructure. Model biases are addressed through equidistant quantile mapping, in which the modeled change in the cumulative distribution of storm events from historical to future conditions is used to adjust the extreme value fit used for IDF curve development. The approach is efficient because it requires only annual maxima and is readily automated, allowing rapid examination of results across projections. We estimate future IDF curves at locations throughout the United States and link IDF-derived design storms to a rainfall-runoff model to evaluate the potential change in storage volume requirements for capture-based stormwater management practices by 2065.

Vine Copula Ensemble Downscaling for Precipitation Projection Over the Loess Plateau Based on High‐Resolution Multi‐RCM Outputs

AbstractA vine copula‐based ensemble downscaling (VCED) framework is proposed to jointly downscale the projected precipitation from multiple regional climate models (RCMs). This approach can effectively reduce the biases inherent to precipitation projections from different RCMs and thus provide more reliable ensemble projections. The proposed approach was applied to RCM projections over the Loess Plateau of China, which features complex topography and various climatic zones. Precipitation projections from 7 RCMs were used, and 21 sets of downscaling results were obtained. The performance of the VCED in reproducing historical precipitation across the Loess Plateau was evaluated using mean absolute error (MAE), the Taylor diagram, and the rank histogram (RH). The proposed VCED approach was found to be more effective than quantile mapping and bivariate copula methods in achieving robust precipitation projections. Overall flat RH diagrams indicate that the ensemble prediction and observations have strong consistency in distribution. Future precipitation changes of two 30‐year periods (i.e., the 2050s and 2080s) under two Representative Concentration Pathway (RCP) scenarios (RCP 4.5 and RCP 8.5) over the Loess Plateau were then analyzed after postdownscaling processes. The results show that the average annual precipitation over the Loess Plateau may increase by 8.4%–11.4% under the RCP 4.5 scenario and by 9.3%–17.5% under RCP 8.5. The projected precipitation in the south‐central parts of the Loess Plateau would be significantly reduced whereas those of the other parts be significantly increased.

Intraseasonal Precipitation Variability over West Africa under 1.5 °C and 2.0 °C Global Warming Scenarios: Results from CORDEX RCMs

This study assessed the performance of 24 simulations, from five regional climate models (RCMs) participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX), in representing spatiotemporal characteristics of precipitation over West Africa, compared to observations. The top five performing RCM simulations were used to assess future precipitation changes over West Africa, under 1.5 °C and 2.0 °C global warming levels (GWLs), following the representative concentration pathway (RCP) 8.5. The performance evaluation and future change assessment were done using a set of seven ‘descriptors’ of West African precipitation namely the simple precipitation intensity index (SDII), the consecutive wet days (CWD), the number of wet days index (R1MM), the number of wet days with moderate and heavy intensity precipitation (R10MM and R30MM, respectively), and annual and June to September daily mean precipitation (ANN and JJAS, respectively). The performance assessment and future change outlook were done for the CORDEX–Africa subdomains of north West Africa (WA-N), south West Africa (WA-S), and a combination of the two subdomains. While the performance of RCM runs was descriptor- and subregion- specific, five model runs emerged as top performers in representing precipitation characteristics over both WA-N and WA-S. The five model runs are CCLM4 forced by ICHEC-EC-EARTH (r12i1p1), RCA4 forced by CCCma-CanESM2 (r1i1p1), RACMO22T forced by MOHC-HadGEM2-ES (r1i1p1), and the ensemble means of simulations made by CCLM4 and RACMO22T. All precipitation descriptors recorded a reduction under the two warming levels, except the SDII which recorded an increase. Unlike the WA-N that showed less frequency and more intense precipitation, the WA-S showed increased frequency and intensity. Given the potential impact that these projected changes may have on West Africa’s socioeconomic activities, adjustments in investment may be required to take advantage of (and enhance system resilience against damage that may result from) the potential changes in precipitation.