Increase In Precipitation Intensity Research Articles

Linking hydroclimate indices to projected warming temperature and increased precipitation under CMIP6 for a sub-arctic basin

Study regionOulujoki River basin- Inland sub-Arctic. Study focusUnderstanding the impact of projected accelerated warming and increasing precipitation in the Arctic and sub-Arctic is crucial. This study examines how these changes will reshape the hydroclimatic dynamics of the inland sub-Arctic river basin, using cold climate and precipitation indices derived from statistically downscaled General Circulation Models. New hydrological insights for the regionThe results show an increase in precipitation indices, with mid-century primarily dominated by scenarios SSP1–2.6 and SSP3–7.0. Under SSP5–8.5, precipitation magnitude and intensity steadily rise throughout the century. The projected increase in precipitation magnitudes, intensity, and extreme events are highly correlated with the increasing spring and summer precipitation, linking intensified and heavy precipitation events during these seasons under all future scenarios. Cold climate indices are projected to decrease with a shortened frost season by 3.3 months, advance in spring freshet by 1.5 months under SSP5–8.5, and a drastic decline in cold spell duration index in all scenarios, indicating a lack of supercooling events. These decreasing indices are strongly correlated with warming temperatures with a Pearson correlation coefficient reaching 0.84 under SSP5–8.5. The findings also highlight the limitations of the CMIP6 ensemble in capturing extreme values, as extreme climate indices were not statistically significant. This study thus contributes to the broader understanding of climate dynamics and their potential impacts on cold regions.

Assessment of nutrient differences in detached soil particles between cropland and revegetated abandoned land

AbstractCropland (CRL) abandonment is a worldwide phenomenon of land use change with significant impacts on agro‐ecosystems. This research attempts to deepen the analysis of the positive and negative effects arising by focusing on the changes in soil properties and the amount and composition of soil particles detached after several periods of rainfall and the resulting exported sediment that occurs in abandoned areas with natural revegetation compared to CRL. The study was carried out in an agroforestry catchment with a temperate climate, on which CRL and abandoned land with natural vegetation were compared. The soil was sampled along two representative hillslopes integrating elements of the landscape and land use/land covers. Sediments were collected after seven periods in which flood events were recorded during the period July 2016 to December 2017, using artificial‐lawn mats. Soil and sediment composition (texture, soil organic carbon [SOC] and nutrients [total nitrogen and total phosphorous]) under both land uses were assessed and compared and related to rainfall characteristics using principal component analysis. Nutrient enrichment factors in the sediments compared to soils were also evaluated. The results highlight that after abandonment, SOC increased significantly, reaching contents almost three times higher than in CRL. Consequently, soil erodibility decreased, resulting in substantially lower sediment generation after erosive rainfall events. On average, sediment generation was three times lower in abandoned areas than in CRL, despite their steeper slopes. Soil total nitrogen also increased on abandoned lands, reaching values about twice as high as those in CRL. However, total phosphorous content was almost twice as high in CRL than in abandoned land posing a potential risk for water due to higher erosion rates recorded in CRL. The results confirmed the association of phosphorous with smaller particles and also demonstrated the total phosphorous‐SOC link in abandoned land. Furthermore, the effect of rainfall intensity on phosphorous mobilisation was confirmed, whilst nitrogen losses were mainly related to the total amount of rainfall recorded. In a scenario of increasing extreme precipitation, both total amount and increased precipitation intensity may exacerbate water pollution problems following nutrient loss in cultivated areas. This research contributes to identifying the impacts on agroforestry systems within the current context of converting natural areas into cultivated land, whilst in other regions revegetated natural areas are developed from abandoned agricultural land.

Spatiotemporal variation and teleconnections of extreme precipitation in the Upper Indus Basin: insights for natural hazard assessment

ABSTRACT The study investigates trends and teleconnections of extreme precipitation events in the Upper Indus Basin (UIB) within the Indian region, part of the crucial geo-ecological Hindu Kush Himalayan Mountain system. Utilizing high-resolution (10km) HAR data from 2002 to 2013, we analyzed 11 indices established by the Expert Team on Climate Change Detection and Indices (ETCCDI) to observe variations in extreme precipitation at the monthly, seasonal, and annual scales. Results show an increase in dry and wet extreme precipitation frequency and intensity, increased monsoon precipitation, and a shift of winter precipitation, increasing continuous dry days. Using APHRODITE daily (0.25°) data from 1952 to 2014, continuous wavelet transform and wavelet coherence analysis indicate significant periodicities and correlations with large-scale climate anomalies such as El Niño-Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO). Wavelet coherence analysis reveals that monthly extreme precipitation events significantly correlate with ENSO at 3-5 years periodicity, while annual extremes show significant coherence with NAO at 8-10 years and over 16 years periodicities. The study highlights the impact of global climate change on regional precipitation and the need for adaptive water management policies to mitigate flood risks during the rainy season and address water scarcity in the dry season.

Linking Future Precipitation Changes to Weather Features in CESM2‐LE

AbstractWeather features, such as extratropical cyclones, atmospheric rivers (ARs), and fronts, contribute to substantial amounts of precipitation globally and are associated with different precipitation characteristics. However, future changes in these characteristics, as well as their representation in climate models, remain uncertain. We attribute 6‐hourly accumulated precipitation to cyclones, moisture transport axes (AR‐like features), fronts, and cold air outbreaks, and the combinations thereof in 10 ensemble members of the CESM2‐LE between 1960 and 2100 under the SSP3‐7.0 scenario. We find that, despite some biases in both precipitation and weather features, CESM2‐LE adeptly represents the precipitation characteristics associated with the different combinations of weather features. The combinations of weather features that contribute most to precipitation in the present climate also contribute the most to future changes, both due to changes in intensity as well as frequency. While the increase in precipitation intensity dominates the overall response for total precipitation in the storm track regions, the precipitation intensity for the individual weather features does not necessarily change significantly. Instead, approximately half of the increase in precipitation intensity in the storm track regions can be attributed to a higher occurrence of the more intensely precipitating combinations of weather features, such as the co‐occurrence of extratropical cyclones, fronts, and moisture transport axes.

MeV Electron Precipitation During Radiation Belt Dropouts

AbstractTo gain deeper insights into radiation belt loss into the atmosphere, a statistical study of MeV electron precipitation during radiation belt dropout events is undertaken. During these events, electron intensities often drop by an order of magnitude or more within just a few hours. For this study, dropouts are defined as a decrease by at least a factor of five in less than 8 hours. Van Allen probe measurements are employed to identify dropouts across various parameters, complemented by precipitation data from the CALorimetric Electron Telescope instrument on the International Space Station. A temporal analysis unveils a notable increase in precipitation occurrence and intensity during dropout onset, correlating with the decline of SYM‐H, the north‐south component of the interplanetary magnetic field, and the peak of the solar wind dynamic pressure. Moreover, dropout occurrences show correlations with the solar cycle, exhibiting maxima at the spring and autumn equinoxes. This increase during equinoxes reflects the correlation between equinoxes and the SYM‐H index, which itself exhibits a correlation with precipitation during dropouts. Spatial analysis reveals that dropouts with precipitation penetrate into lower L‐star regions, mostly reaching L‐star <4, while most dropouts without precipitation don't penetrate deeper than L‐star 5. This is consistent with the larger average dimensions of dropouts associated with precipitation. During dropouts, precipitation is predominantly observed in the dusk‐midnight sector, coinciding with the most intense precipitation events. The results of this study provide insight into the contribution of precipitation to radiation belt dropouts by deciphering when and where precipitation occurred.

Quantifying the influence of atmospheric rivers on rainfall over the Jianghuai River Basin during the 2022 Mei‐yu season

AbstractAtmospheric rivers (ARs) are narrow, elongated belts of intense water vapor transport that often occur in mid‐latitude areas and are the primary drivers of heavy precipitation in these regions. This study investigates the impact of ARs on precipitation patterns in the Jianghuai River Basin during the Mei‐yu period. Focusing on a specific rainstorm event on June 27, 2022, we analyze atmospheric circulation, water vapor attributes, and transport trajectories. Three distinct classes of grids (Class A, significantly influenced by ARs; Class B, moderately affected; and Class C, untouched by ARs) are identified based on their response to ARs. Class A grids, located centrally, experience substantial precipitation, with a higher probability of rainstorm events. Class B grids, situated at a distance from ARs, exhibit moderate precipitation and a longer duration of rainy days. Class C grids, minimally affected by ARs, experience minimal precipitation with almost no chance of rainstorm events. The results from grid‐based analysis emphasize the localized influence of ARs, indicating a 8–30 times increase in precipitation intensity of Class A compared to Class C. The 23‐day Mei‐yu period is further categorized into AR days and non‐AR days, revealing that ARs amplify precipitation intensity by 2–5 times on average. Grid‐based and day‐based analyses provide complementary insights, with the former offering a broader spatial perspective and the latter emphasizing temporal distinctions. These findings underscore the nuanced influence of ARs on precipitation, emphasizing their role in extreme events and highlighting the importance of considering both spatial and temporal factors in understanding precipitation variability.

Cloud Characteristics in South China Using Ka-Band Millimeter Cloud Radar Datasets

In this study, we investigate the seasonal and diurnal variations in cloud occurrence frequency, as well as cloud vertical structure (CVS) characteristics under different seasons and precipitation intensities over the Guangzhou region in South China, based on the analysis of millimeter-wave cloud radar (MMCR) and ground automatic weather station rainfall observations from May 2019 to August 2021. The results showed that the occurrence frequency of clouds exhibits a bimodal distribution throughout the year, with peaks in March to June and October, reaching its highest occurrence in May at approximately 80% and its lowest from December to February at around 40%. Additionally, there are distinct diurnal variations in occurrence frequency, with the lowest rates occurring around 0005 LST, rapidly increasing after 0006 LST, and peaking during the afternoon to evening hours. Cloud top height (CTH) shows bimodal distributions during the pre-flood and post-flood seasons. The most frequently occurring range of CTH during the pre-flood season is below 3 km, accounting for approximately 43%, while during the post-flood season, it ranges from 11 to 14 km, constituting about 37%. For precipitation clouds, CTH can extend beyond 12 km, with the radar reflectivity decreasing gradually with increasing height. The highest frequencies of radar echoes are observed below 2 km and between 4 and 7 km, exhibiting clear diurnal variations, with echoes mainly below 2 km and between 4 to 6 km during the early morning, intensifying and shifting to higher altitudes during the day and reaching their maximum below 4 km during the afternoon to nighttime hours, while both the frequency and intensity increase in the height range of 4 to 12 km. Vertical profiles of radar reflectivity and cloud ice/liquid water content (IWC/LWC) exhibit similar trends under different precipitation intensities. The main differences are observed below 4 km, where both radar reflectivity and IWC/LWC generally increase with increasing precipitation intensity. These findings contribute to a better understanding of cloud characteristics in the South China region, enhance the accuracy of model simulations, and provide a scientific basis for accurate forecasting and warning of meteorological disasters.

Research on Frequency Matching Correction Techniques for South China Precipitation Ensemble Forecast Based on the GRAPES Model

This study focuses on the real-time precipitation forecast products of the GRAPES_MESO regional ensemble forecast model, which is developed by the Numerical Weather Prediction Center of the China Meteorological Administration and is initialized 1–3 days in advance at 12:00 UTC. Using a national-level homogenized precipitation grid dataset from surface meteorological stations as observational data, a frequency matching method (FMM) is employed to correct precipitation forecasts for different precipitation intensity levels, including light rain, moderate rain, heavy rain, and torrential rain. Case studies and statistical tests (TS scores) are conducted to compare the forecast performance before and after correction. The results indicate that the model’s Cumulative Distribution Function (CDF) curves deviate from observations, and the longer the lead time, the more significant the error. The correction coefficients (CCs) show an increasing trend with the growth of precipitation intensity, indicating that for larger precipitation amounts and longer lead times, larger CCs are needed, highlighting the necessity of correction. Analyzing two precipitation events in South China in July 2019, the FMM results in an increase in precipitation intensity and a widening of the range of heavy precipitation. The corrected precipitation magnitudes are closer to the observations. The statistical tests using TS scores reveal that the FMM has a certain correction effect on the overall precipitation forecast in the South China region, especially for longer lead times and higher precipitation intensities, where the correction effect is more significant. The necessity of frequency matching correction becomes more apparent for heavier precipitation, and the correction effect becomes more significant with longer lead times.

The Effect of Convective/Advective Precipitation Partitions on the Precipitation Isotopes in the Monsoon Regions of China: A Case Study of Changsha

Abstract Convective/advective precipitation partitions refer to the divisions of precipitation that are either convective or advective in nature, relative to the total precipitation amount. These distinct partitions can have a significant influence on the stable isotope composition of precipitation. This study analyzed and compared the effect of precipitation partitions on δ18O in precipitation (δ18Op) by using daily precipitation stable isotope data from Changsha station and monthly precipitation stable isotope data from the Global Network of Isotopes in Precipitation (GNIP), under different time scales, time intervals (i.e., annual, warm season, and cold season), and precipitation intensities. The results showed that the correlation between the convective precipitation fraction (CPF) and total precipitation amount was influenced by the intensity of convection in different time intervals. On both the daily and monthly scales, the CPF decreased as the precipitation amount increased in the warm season, while it increased with increasing precipitation amount in the cold season. Regardless of the season, daily δ18Op at Changsha station consistently increased with an increase in daily CPF. On a daily scale, the effect of convective activity on δ18Op was stronger than that of the “precipitation amount effect” in the cold season, as compared to the situation in the warm season. As a result, the regression line slope between δ18Op and CPF increased with increasing precipitation intensity in the warm season, meaning that as the CPF increased, the δ18Op increased at a faster rate under higher precipitation intensity. Similarly, the slope increased with increasing precipitation intensity in the cold season. This suggests that precipitation intensity and convection intensity can affect the relationship between δ18Op and CPF. Our findings shed light on how different precipitation partitions affect stable isotope composition of precipitation, thus enhancing our understanding of the variability of precipitation stable isotopes in the monsoon regions of China. Significance Statement This study aims to better elucidate the influence of different precipitation partitions on precipitation stable isotopes. In the eastern monsoon region of China, stable isotopes in precipitation showed a robust positive relationship with convective precipitation faction. On a daily scale, the convective activity enhanced the influences of the “precipitation amount effect” on precipitation stable isotopes in the warm season and reduced such influences in the cold season. These results improve our understanding of stable isotopic variability of precipitation in the eastern monsoon region, China.

Upper limits for post-wildfire floods and distinction from debris flows.

Upper magnitude limits and scaling with basin size for post-wildfire floods are unknown. An envelope curve was estimated defining post-wildfire flood upper limits as a function of basin area. We show the importance of separating peak flows by floods versus debris flows. Post-wildfire flood maxima are a constant 43 m3 s-1 km-2 for basins from 0.01 to 23 to 34 km2 and then declining with added basin area according to a power law relation. Intense rainfall spatial scaling may cause the envelope curve threshold at 23 to 34 km2. Post-wildfire flood maxima are smaller than unburned flood maxima for similar basin area. Rainstorm comparisons indicate that post-wildfire floods are triggered by smaller precipitation depths than unburned floods. Post-wildfire exceptional floods are driven by extreme rainfall rates, in contrast to post-wildfire debris flows. Runoff rates for post-wildfire envelope floods are consistent with infiltration-excess runoff. Future increases in precipitation intensity or wildfire frequency and extent could increase post-wildfire flood upper limits.

Climate Extremes and Sustainability Issues: A Case of Proposed Hydropower Projects in Lahaul Valley, Himachal Pradesh

Water and energy are the key to development; however, a great deal of contestation is at the very core of hydropower and sustainability debate in the context climate change and risk of disasters. A vast potential for renewable energy in the Himalayas has led to planning for hydropower projects since 1990s. However, social, economic and environmental issues linked to such development has also led to a fear among local communities in light of climate change. This study analysed the relation between climate extremes, disaster risk and hydropower development in Lahaul Valley of Himachal Pradesh. The study examined long-term climate data for precipitation and temperature trends while daily rainfall gridded data was used for the analysis of climate extremes. The results show statistically significant increase in precipitation intensity and rise of winter and post winter temperature. Also, heavy and very heavy rainfall days, daily rainfall intensity shows increasing trends that may have serious repercussions on local economy, livelihood and hydropower development. The field observations reveal discontentment of local population to proposed development. It is important that this debate must be reviewed logically to ensure safe future of the area with sound understanding of disasters and climate change risk.

Resilient Stormwater Management of a Coastal Catchment

Designing stormwater drainage systems considering deep uncertainty is a task that has no correct solution, rather, it can only be addressed by managing the system in a smart, robust way. Over recent decades, robust decision-making has been promoted as a solution to planning systems that are vulnerable to deep uncertainty. In this paper, we adopt a robust decision-making methodology to propose a stormwater drainage system in a coastal catchment in an arid region which is vulnerable to sea-level rise and increased precipitation intensity. We used bias-corrected precipitation and sea-level rise projections from a regional climate model, in addition to analyzing observed data. The decision-making methodology adopted is the Dynamic Adaptive Policy Pathways (DAPP). It involves building a decision tree with probable actions to consider when the stormwater system is expected to fail. The success of DAPP relies on continuous and extensive monitoring of the system and all components/factors that form risk or add to the vulnerability of the system, in addition to extensive simulations of the pre-identified actions that enable quick implementation of the solutions preceding failure of the system. This gives an early warning and aids the proactive execution of actions, hence making the system resilient to deep uncertainty. The DAPP for the study site is presented, and the advantages of relying on robust decision-making for arid regions are discussed.

Modelling and forecasting of urban flood under changing climate and land use land cover

Abstract Chennai is a rapidly urbanizing Indian mega-city and experiences flooding frequently. Literature state that climate change and land use change have a significant impact on the runoff generated every year, making it essential to study the historical trend and forecast changes in land use land cover (LULC) and climate to model runoff. This study considered Adyar watershed for LULC change detection, climate change analysis, and flood forecasting for 2030 and 2050 based on LULC and runoff from 2005 and 2015. A coupled hydrologic–hydraulic model (HEC-HMS and HEC-RAS) was developed to assess flooding for future LULC and climate scenarios. LULC analysis shows an increase in built-up cover by 6%. Climate analysis shows 74% probability of increase in precipitation intensity between 2015 and 2050 compared to 2015. It was observed that depth of flooding increased by 19.4% in 2030 and 60.4% in 2050 compared to 2015. This study makes a structural proposition for flood mitigation through flood carrier canals on the downstream reach of the river which flows through Chennai. The canals were found to significantly reduce overbanking, providing protection against flooding. This is the best measure for providing the highest flood reduction for the study area.

Evaluation of precipitation measurements using a standard rain gauge in relation to data from a precision lysimeter

Abstract The construction of modern lysimeters with a precise weighing system made it possible to achieve an unprecedented accuracy of precipitation measurement. This study compares two methods of measuring precipitation in the conditions of the humid continental climate of the Eastern Slovakian Lowland (Slovakia): measurement using a standard tipping-bucket rain gauge vs. precision weighable lysimeter. Data from the lysimeter were used as a reference measurement. The comparison period lasted four years (2019–2022). Only liquid rainfall was compared. The rain gauge was found to underestimate precipitation compared to the lysimeter. Cumulative precipitation for the entire monitored period captured by the rain gauge was 2.8% lower compared to lysimeter measurements. When comparing hourly and daily totals of precipitation and precipitation events, a very high degree of agreement was detected (r 2 > 0.99; RMSE from 0.22 to 0.51 mm h–1). A comparison based on precipitation intensity showed a decreasing trend in measurement accuracy with increasing precipitation intensity. This tendency has an exponential course. With increasing intensity of precipitation, increasing intensity of wind was also recorded. In order to correct measurement errors, simple correction method was proposed, which helped to partially eliminate the inaccuracies of the rain gauge measurement.

Assessment of Climate Change’s Impact on Flow Quantity of the Mountainous Watershed of the Jajrood River in Iran Using Hydroclimatic Models

Rivers are the main source of fresh water in mountainous and downstream areas. It is crucial to investigate the possible threats of climate change and understand their impact on river watersheds. In this research, climate change’s impact on the mountainous watershed of the Jajrood River, upstream of Latyan Dam in Iran, was assessed by using a multivariate recursive quantile-matching nesting bias correction (MRQNBC) and the soil and water assessment tool (SWAT). Also, this study considered ten global circulation models (GCMs) from the coupled model intercomparison project phase VI (CMIP6). With a higher correlation coefficient, the MIROC6 model was selected among other models. For the future period of 2031–2060, the large-scale outputs of the MIROC6 model, corresponding to the observational data were extracted under four common socioeconomic path scenarios (SSPs 1–2.6, 2–4.5, 3–7.0, 5–8.5). The bias was corrected and downscaled by the MRQNBC method. The downscale outputs were given to the hydrological model to predict future flow. The results show that, in the period 2031–2060, the flow will be increased significantly compared to the base period (2005–2019). This increase can be seen in all scenarios. In general, changes in future flow are caused by an increase in precipitation intensity, as a result of an increase in temperature. The findings indicate that, although the results show an increase in the risk of flooding, considering the combined effects of three components, i.e., increased precipitation concentration, temperature, and reduced precipitation, climate change is intensifying the problem of water scarcity.

Climatological trends of mean and extreme daily precipitation in Arizona (USA)

Precipitation in Arizona, USA, represents a fundamental resource for the needs of agriculture, people, and the environment. However, due to the risk associated with flash flooding, extreme precipitation also constitutes a natural hazard. Available research on precipitation in Arizona has been limited in scope and focus and there currently exists no comprehensive assessment of statewide, historical, mean, and extreme precipitation. We use daily precipitation records from 43 Global Historical Climate Network daily (GHCNd) weather stations to examine trends in mean and extreme precipitation across Arizona from 1950 to 2020. We use a suite of standardized precipitation indices and explore the statistical significance of historical changes at the annual, monthly, and seasonal scales. Our analysis returns a motley collection of results displaying a great degree of spatial variability and sensitivity to the temporal scale of analysis. Mean total precipitation at the statewide scale underwent a small decreasing trend of 0.15 mm year−1, with considerable interannual variability being a dominant feature. The majority of stations experienced no statistically significant change in extreme precipitation at the annual scale. Monsoon season mean precipitation followed a similar pattern to annual means, with an overall reduction of 0.14 mm year−1 across the state. One fourth of stations, all located at elevations lower than 650 m, recorded decreases in monsoon precipitation intensity. Winter season analysis presents a different picture, displaying a positive statewide trend of 0.11 mm year−1 in mean precipitation. One tenth of stations recorded increases in extreme precipitation intensity and decreases in the number of consecutive dry days. Results of our observational analysis indicate a lack of a clear consensus on the climatological trends of mean/extreme precipitation in Arizona during the study period. Our findings are in contrast to those from other similarly arid areas across the world and highlight the role of regional differences in modulating the potential hydrometeorological impacts associated with climate change. However, while we do not find widespread, significant, modification in the spectrum of precipitation changes examined, the hydrologic system of the state has been – and will continue to be - impacted by the ongoing temperature increase associated with the buildup of greenhouse gases and continued population growth.

Effects of extreme precipitation intensity and duration on the runoff and nutrient yields

Extreme precipitation and its subsequent natural disasters, including soil erosion and flood, have been confirmed to have major impacts on watershed hydrology and water quality. However, the contributions of the intensity and duration of extreme precipitation to the changes in runoff and nutrient yields have not been fully understood. In this study, we quantified the contributions of extreme precipitation intensity and duration to the changes in watershed runoff and nutrient yields through constructing a quantitative simulation protocol in a distributed hydrological model. The results showed that the historical extreme precipitation, runoff, and nutrient yields have similar inter-annual variation trends. Between 2010 and 2020, extreme precipitation events induced more than 90% of annual runoff and total phosphorus (TP) yields. Runoff and TP yields increased with the increase in extreme precipitation intensity, while total nitrogen (TN) yields did not always decrease linearly with reduced intensity. The impacts of the duration in extreme precipitation on runoff and nutrient yields were less than intensity. Nutrient yields from farmland were stably influenced by extreme precipitation intensity, while that from forestland and grassland have higher inter-annual variability. The contributions of duration to TP yields were higher in farmland and forestland than in grassland and urban and rural areas. Changes in the intensity and duration of extreme precipitation transformed watershed nutrient composition pattern. With the increase of intensity, the contribution ratio of farmland increased while that of urban and rural areas decreased. Moreover, the increase in intensity decreased the spatial autocorrelation degree of TN yields between sub-watersheds, increasing the spatial heterogeneity in TN yields. This study improved the understanding for the responses of runoff and nutrient yields to the variations in extreme precipitation characteristics, which is helpful for more targeted water quality management to cope with increasing climate extremes.

Untangling the effects of seasonality and stream channel erosion on the runoff composition in a previously burned mountain catchment

AbstractStream channel incision and deposition are common after wildfire, and after these geomorphic changes occur, they may impact runoff mechanisms and the composition of pre‐event and event water in runoff. To investigate this, we monitored discharge and electrical conductivity at six nested sites within a 15.5 km2 watershed in the northern Colorado Front Range that had burned several years prior, and then experienced large flooding and well‐documented and significant channel erosion and deposition in the following years. Over the study period, which occurs 3 years after the fire, and 2 years after the beginning of significant geomorphic changes, the watershed experienced seven precipitation events. For each hydrograph, we separate baseflow from runoff using a new method to characterize and account for the strong diurnal signal in the baseflow. Electrical conductivity is used as a tracer in a two‐component end‐member mixing analysis to separate the event hydrographs into event and pre‐event water. Correlation coefficients were computed between key variables of the hydrologic response (such as runoff ratio, volumes of event and pre‐event water) to storm and basin characteristics (including stream channel erosion/deposition, fraction of high/moderate burn severity, precipitation intensity and antecedent precipitation). The strength and significance of correlations was found to vary seasonally. In the early season, event and pre‐event volumes did not vary significantly with basin or storm characteristics. In the late season, antecedent precipitation correlated with a decrease in event runoff (R2 = 0.34) and total runoff (R2 = 0.40), increased precipitation intensity correlated with an increase in event runoff (R2 = 0.48) and local erosion correlated with an increase in pre‐event runoff (R2 = 0.60) and total runoff (R2 = 0.53). We hypothesize that the difference in correlations between early season and late season is due seasonal variations in the groundwater table gradient. These findings indicate that seasonality and postfire stream channel erosion influence the makeup of runoff response.

The Dichotomy of Wet and Dry Trends Over India by Aerosol Indirect Effects in CMIP5 Models

AbstractAerosol‐cloud interactions, also known as aerosol indirect effect (AIE), substantially impact rainfall frequency and intensity. Here, we analyze NEX‐GDDP, a multimodel ensemble of high‐resolution (0.25°) historical simulations and future projections statistically downscaled from 21 CMIP5 models, to quantify the importance of AIE on extreme climate indices, specifically consecutive dry days (CDD), consecutive wet days (CWD), and simple daily intensity index (SDII). The 21 NEX‐GDDP CMIP5 models are classified into models with reliable (REM) and unreliable (UREM) monsoon climate simulated over India based on their simulations of the climate indices. The REM group is further decomposed based on whether the models represent only the direct (REMADE) or the direct and indirect (REMALL) aerosol effects. Compared to REMADE, including all aerosol effects significantly improves the model skills in simulating the observed historical trends of all three climate indices over India. Specifically, AIE enhances dry days and reduces wet days in India in the historical period, consistent with the observed changes. However, by the middle and end of the 21st century, there is a relative decrease in dry days and an increase in wet days and precipitation intensity. Moreover, the REMALL simulated future CWD and CDD changes are mostly opposite to those in REMADE, indicating the substantial role of AIE in the future projection of dry and wet climates. These findings underscore the crucial role of AIE in future projections of the Indian hydroclimate and motivate efforts to accurately represent AIE in climate models.

Projected changes in annual maximum discharge for Iowa communities

Understanding the projected changes in annual maximum peak discharge is important to improve resiliency in water resource planning and design at the community level. Currently, much of the literature on climate change impacts focuses on analyses at the regional scale. In this study we use a hydrologic model to evaluate the projected changes in annual maximum peak discharge at the community-level across Iowa under two emission scenarios, Representative Concentration Pathway 4.5 and 8.5 (RCP4.5 and RCP8.5). We utilize climate forcings from global climate models part of the Coupled Model Intercomparison Projected Phase 5 (CMIP5) from 1950 to 2100. Our simulations show a detectable increase in annual maximum discharge for 27% of Iowa’s communities under RCP8.5. However, under RCP4.5 none of the communities are projected to face an increase in annual maximum discharge by the end of the 21st century; furthermore, precipitation intensity under this scenario is not projected to increase in the latter half of the 21st century. Our results point to a larger increase in precipitation intensity and annual maximum discharge under RCP8.5 compared to RCP4.5, especially in the second half of this century. The projected flood peak distributions tend to become statistically different from the historical ones later in the 21st century under RCP8.5 than under RCP4.5. This study provides a basis for analyzing climate change impacts at a local decision-making scale.