Changes In Precipitation Characteristics Research Articles

Changes in Precipitation Characteristics over Russia in the 20th and 21st Centuries According to CMIP6 Model Ensemble Data

Changes in Precipitation Characteristics over Russia in the 20th and 21st Centuries According to CMIP6 Model Ensemble Data

Seasonal Differences of Precipitation and Microphysical Characteristics over the Asian Monsoon Region Using Spaceborne Dual-Frequency Precipitation Radar

Abstract This study aimed to reveal the seasonal climatic variations in the microphysical properties of precipitation over the Asian monsoon region. We used the Dual-Frequency Precipitation Radar satellite product aboard the Global Precipitation Measurement Mission Core Observatory for 8 years from 2014 to 2021 to statistically analyze the mass-weighted mean diameter (Dm) and frequency of heavy ice precipitation (graupel and hail). The results showed statistically significant seasonal changes. The microphysical characteristics of large Dm and frequent heavy ice precipitation were observed over the Indian subcontinent and Indochina Peninsula in the premonsoon season and over the western Himalayan region in the mature-monsoon season, which can be related to the intense and deeply developed precipitation systems. The relationship between precipitation rate and Dm was also examined. The results indicated that changes in Dm were not caused only by changes in precipitation rate but were probably induced by changes in precipitation characteristics. In terms of the relationship between the microphysical properties, heavy ice precipitation particles in the upper atmosphere above the melting layer were observed more frequently as Dm near the surface increased. We also studied lower-atmospheric instability by investigating the vertical gradients of the dry and moist static energies. The results indicated that instability properties were different; dry and wet instabilities were dominant in the premonsoon and monsoon seasons, respectively, consistent with the results of the precipitation characteristics. Significance Statement The purpose of this study was to reveal seasonal variations in precipitation microphysical characteristics, such as precipitation particle size and the existence of graupel and hail in the upper atmosphere, by climatological analysis over the Asian monsoon region. In previous studies, microphysical characteristics have mainly been addressed using ground-based observations. However, more sampling is needed to expand our understanding of climatological perspectives; therefore, we used recently available satellite observations. As a result, we found that precipitation particles at the surface were larger, and more graupel and hail existed in clouds in the premonsoon season when less precipitation was observed, compared to the mature-monsoon season when precipitation amount and frequency were abundant.

Precipitation-based climate change hotspots across India through a Multi-model assessment from CMIP6

This study presents an analysis to identify precipitation-based climate change hotspots and key-vulnerable cities using multi-model, multi-scenario, high-resolution (0.25°×0.25°), bias-corrected precipitation dataset across India from 14 state-of-the-art General Circulation Models (GCMs), participating in Coupled Model Intercomparison Project version 6 (CMIP6). Preliminary analysis indicates an overall wetter future across India with 290 ± 150 mm to 530 ± 260 mm increase in mean annual precipitation towards end of this century under various climate change scenarios. Apart from the mean precipitation, the extremes are also found to be increasing by alarmingly higher rates. However, the spatio-temporal variations of such increments are notably diverse over different seasons in a year and across different Homogeneous Precipitation Zones (HPZs) in the country. Therefore, a new and more inclusive index, named as Precipitation-based Hotspot Index (PHI), is developed to identify the ‘precipitation-based hotspots’, i.e. the places with most pronounced changes in precipitation characteristics. The PHI considers the changes in various aspects of precipitation, such as mean, variability, and characteristics of extremes (magnitude, frequency and intensity). Based on the PHI values in the far-future period (2061–2100) and for the worst climate change scenario, the hotspot regions are identified mostly in the northwest, west-central, west coast, and northeast parts of India. Further, considering two important socio-economic vulnerability factors (population density and human development index) along with PHI, the key-vulnerable tier-I cities are identified across India. The analysis reveals four out of ten tier-I cities will be highly vulnerable towards end of this century. The findings of this analysis (hotspot maps) and the data products (high-resolution, bias-corrected precipitation dataset) are expected to be highly beneficial for impact assessments, hydrologic modelling, and formulating suitable adaptation and mitigation strategies for India over future.

Projected changes in precipitation characteristics over the Drakensberg Mountain Range

AbstractThis study examines the potential impacts of climate change on the characteristics of precipitation over the Drakensberg Mountain Range (DMR) at different global warming levels (GWLs: 1.5, 2.0, 2.5 and 3.0°C) under the Representative Concentration Pathway 8.5 (RCP8.5) scenario, using dynamical and statistical downscaled datasets. The dynamical datasets consist of 19 multi‐model simulations datasets from the Coordinated Regional Climate Downscaling Experiment (CORDEX), whereas the statistical downscaled datasets comprise 19 multi‐model simulations from the National Aeronautics and Space Administration (NASA) Earth Exchange (NEX) Global Daily Downscaled Projections (NEX‐GDDP, hereafter NEX). The capacity of the CORDEX and NEX datasets to represent past characteristics of extreme precipitation over the DMR was evaluated against eight observation datasets. The precipitation characteristics were represented by eight precipitation indices. Both CORDEX and NEX realistically capture the characteristics of extreme precipitation over the Drakensberg and, in most cases, their biases lie within the observation uncertainty. However, NEX performs better than CORDEX in reproducing most of the precipitation characteristics, except in simulating the threshold of extreme rainfall. The ensemble means of CORDEX and NEX agree on a future increase in the intensity of normal precipitation, in the frequency and intensity of extreme precipitation, as well as an increase in widespread extreme events, with a decrease in the number of precipitation days and continuous wet days. However, they disagree on the projected changes of annual precipitation, for which CORDEX projects an increase over most parts of the DMR, whereas NEX indicates a decrease. The self‐organizing‐map analysis, which reveals diversity in the projection patterns hidden in the ensemble means, shows the most probable combinations of projected changes in the annual precipitation and extreme precipitation events (in terms of intensity and frequency): (a) increase in both annual precipitation and extreme precipitation events; (b) decrease in both annual precipitation and extreme precipitation events; (c) decrease in annual precipitation but increase in extreme precipitation events. The results of this study can thus provide a basis for developing climate change adaptation and mitigating strategies over the DMR.

Assessing Soil Vulnerability Index classification with respect to rainfall characteristics

The Soil Vulnerability Index (SVI) uses widely available inputs from the SSURGO database to classify cropland into four levels of vulnerability to sediment and nutrient losses: Low, Moderate, Moderately High, and High. Previous work has identified inconsistencies in SVI assessments across the United States, possibly because neither precipitation amount nor intensity were included in the development of SVI. This study aimed to determine if rainfall characteristics influence the SVI classification and which ones are most critical. The objectives were to (1) evaluate the impact of precipitation characteristics on land vulnerability to sediment loss, and (2) evaluate if rainfall characteristics alter the degree of agreement between the simulated sediment yield and SVI classification. The study focused on four Conservation Effects Assessment Project (CEAP) watersheds in Ohio, Missouri, Mississippi, and Pennsylvania for which sediment yields were simulated using previously calibrated models. The models were run with input precipitation data from these four watersheds. In addition, in order to examine a wider range of precipitation characteristics, model runs were made for the same four watersheds utilizing precipitation data from two CEAP areas in Georgia and Maryland. Sediment yields for all the cropland units in four of the watersheds were simulated using the Soil and Water Assessment Tool or the Annualized Agricultural Nonpoint Source Pollution Model using 1985 to 2014 precipitation data from all six areas as inputs. Similarities and differences between precipitation characteristics such as precipitation amount, intensity, and rainfall erosivity R-factors were compared with the similarities and differences in simulated sediment loss. Results confirmed that SVI is a useful tool for relative ranking of cropland at risk of erosion within a region, as SVI and the model-based vulnerability classifications agreed for 55% to 100% of the watersheds’ subunits. However, model-based classification of field vulnerability could shift due to changes in precipitation characteristics. Thus, the range of soil loss for each vulnerability class can shift from one region to another. The results suggest that precipitation intensity or annual R-factor may help improve the correspondence between vulnerability and the range of expected soil loss.

Approaches to Understanding Decadal and Long-Term Shifts in Observed Precipitation Distributions in Victoria, Australia

Abstract Over the past century, precipitation totals in Australia’s southeastern state of Victoria have shown multidecadal variability without clear trends. This has impacted agriculture, water security, ecosystem services, and flood hazards. Hydrological and meteorological evidence suggests that Victorian precipitation regimes have changed since the beginning of the Millennium Drought in 1997. Until now, Victorian precipitation intensity distributions have not been assessed in detail. We assess the time-varying aspect of observed precipitation intensity distributions by identifying temporal shifts in Victorian precipitation and using those different epochs to assess multidecadal changes in precipitation characteristics. We used 788 manual rain gauges and 49 automatic weather stations to analyze subdaily-to-multiday precipitation distributions from 1900 to 2020 for three Victorian regions and four seasons. Distributions are significantly different for the three epochs (1900–45, 1946–96, and 1997–2020). We summarized precipitation distributions by categorizing precipitation intensities, calculating histograms, and fitting gamma distributions. This study provides evidence that Victorian precipitation distributions have shifted over decades and that distributions depend on regional and seasonal differences. Recent precipitation declines are mostly due to decreasing light and moderate precipitation, despite increasing heavy precipitation. Heavy precipitation has shown a tendency to increase in frequency since 1997. Increases were greatest for 6-h springtime and summertime precipitation in northern Victoria and wintertime precipitation in southern and eastern Victoria. Observed precipitation distributions show changes that are consistent with climate projections. To better understand processes driving observed and projected changes to precipitation distributions globally, interdecadal shifts, seasonal variations, and regional climates need to be considered. Significance Statement Our research investigated how different rainfall intensities have contributed to changing rainfall totals over the last century in Victoria, Australia. This is important because different rainfall intensities have various impacts on farms, rivers, catchments, and infrastructure. In Victoria, we found three multidecade periods with different average rainfall intensity distributions. Early-twentieth-century rainfall is close to the observed average, 1946–96 was very wet, and 1997–2020 was drier. Recent years were drier because of fewer light and moderate rainfall events. Changes in heavy rainfall depend on the season and subregional factors. This may indicate that weather processes have changed. Decreasing light-to-moderate rainfall intensities will affect stakeholders by decreasing soil moisture, runoff, and streamflow.

Effects of elevated temperature and abnormal precipitation on soil carbon and nitrogen dynamics in a Pinus densiflora forest

Forests have the largest terrestrial nutrient pools. The loss of soil carbon and nitrogen in forests under ongoing climate warming is subject to severe environmental degradation. To mitigate the negative effects of global warming on soil carbon and nitrogen in forest, it is important to obtain a better understanding of how elevated temperature and altered precipitation variability impact soil nutrient dynamics. To explore such interactions, we coupled an eco-hydrological model (Multi-Layer Canopy model, MLCan) with a biogeochemical model and applied the combined model to Pinus densiflora forest in Gwangneung Experimental Forest, South Korea, from 2004 to 2020. Our results showed that there was a time lag of 4 years to trigger soil organic carbon losses under the elevated temperature of +1.11°C during 2014–2020 compared to 2010–2013. A temperature rise over a prolonged period increased microbial biomass and activity, stimulating soil organic carbon decomposition. The combination of soil nitrate accumulation and exceptional but expected delay in heavy precipitation seasons of 2 months led to nitrate leaching four times higher than the average at 1 m depth in 2010. Reduced evapotranspiration and heavy precipitation during early fall caused intense subsurface water flux, resulting in a great increase in the risk of nitrate leaching. Our results highlight that the impacts of global warming on soil carbon decompositions has a time lag of 4 years and changes in precipitation characteristics will lead to excessive nitrate loss in P. densiflora forests under climate change.

Climate change information over Fenno-Scandinavia produced with a convection-permitting climate model

This paper presents results from high-resolution climate change simulations that permit convection and resolve mesoscale orography at 3-km grid spacing over Fenno-Scandinavia using the HARMONIE-Climate (HCLIM) model. Two global climate models (GCMs) have been dynamically down-scaled for the RCP4.5 and RCP8.5 emission scenarios and for both near and far future periods in the 21st century. The warmer and moister climate conditions simulated in the GCMs lead to changes in precipitation characteristics. Higher precipitation amounts are simulated in fall, winter and spring, while in summer, precipitation increases in northern Fenno-Scandinavia and decreases in the southern parts of the domain. Both daily and sub-daily intense precipitation over Fenno-Scandinavia become more frequent at the expense of low-intensity events, with most pronounced shifts in summer. In the Scandinavian mountains, pronounced changes occur in the snow climate with a shift in precipitation falling as snow to rain, reduced snow cover and less days with a significant snow depth. HCLIM at 3-km grid spacing exhibits systematically different change responses in several aspects, e.g. a smaller shift from snow to rain in the western part of the Scandinavian mountains and a more consistent decrease in the urban heat island effect by the end of the 21st century. Most importantly, the high-resolution HCLIM shows a significantly stronger increase in summer hourly precipitation extremes compared to HCLIM at the intermediate 12-km grid spacing. In addition, an analysis of the statistical significance of precipitation changes indicates that simulated time periods of at least a couple of decades is recommended to achieve statistically robust results, a matter of important concern when running such high-resolution climate model experiments. The results presented here emphasizes the importance of using “convection-permitting” models to produce reliable climate change information over the Fenno-Scandinavian region.

Spatiotemporal Changes in Air Temperature and Precipitation Extremes over Iran

In this study, a comprehensive trend analysis was employed to study the spatiotemporal changes in precipitation characteristics with air temperature increasing over time. The nonparametric Mann–Kendall test and the quantile regression methods were applied to detect the plausible temporal trends in 11 extreme rainfall indices and three air temperature indices employed in this study. The results showed there was little evidence to suggest that increases in the maximum of 3-h and 24-h precipitation at higher temperatures resulted in similar increases in the annual precipitation, with most stations throughout Iran showing drying features with higher temperatures. Generally, most regions over Iran scaled negatively, implying a reduction in the annual precipitation ranging from −2.64 to −0.44 mm/°C at higher temperatures. The linear tendencies of the maximum 24-h precipitation ranged from −0.4 to 0.23 mm/°C. The annual precipitation of the stations located at Urmia Lake, Caspian Sea, and the Eastern Border Basins showed a decreasing trend (−3.70 to 1.11 mm/year), while the number of rainy days increased (−2.78 to 4.72), which showed the occurrence of lighter rainfall in these regions. The increasing trend in the maximum 24-h precipitation over Western and Central Iran implied a higher probability of extreme precipitation with a higher intensity. This study revealed that the shift in precipitation extremes shifted from fall to winter by increasing the elevation, but these effects have no statistical significance in Iran.

Temporal Variation of Suspended Sediment and Solute Fluxes in a Permafrost-Underlain Headwater Catchment on the Tibetan Plateau

Under global warming, the permafrost-underlain headwater catchments of the Tibetan Plateau have undergone extensive permafrost degradation and changes in precipitation characteristics, which may substantially alter the riverine suspended sediment and riverine solute fluxes. However, these fluxes and their influencing factors in such catchments are poorly understood. We studied the suspended sediment and solute fluxes in a permafrost-underlain headwater catchment on the northeastern Tibetan Plateau, based on comprehensive measurements of various water types in spring and summer in 2017. The daily flux of suspended sediment in spring was close to that in summer, but heavy rainfall events following a relatively long dry period made the largest contribution to the suspended sediment fluxes in summer. The riverine solute flux (in tons) was 12.6% and 27.8% of the suspended sediment flux (in tons) in spring and summer, indicating the dominating role of physical weathering in total material exportation. The snowmelt mobilized more suspended sediment fluxes and fewer solutes fluxes than summer rain, which may be due to the meltwater erosion and freeze–thaw processes in spring and the thicker thawed soil layer and better vegetation coverage in summer, and the longer contact time between the soil pore water and the soil and rock minerals after the thawing of frozen soil. The input of snowmelt driven by higher air temperatures in spring and the direct input of rainfall in summer would both act to dilute the stream water; however, the supra-permafrost water, with high solute contents, recharged the adjacent streamflow as frozen soil seeps and thus moderated the decrease in the riverine solute content during heavy snowmelt or rainfall events. With the permafrost degradation under future global warming, the solute fluxes in permafrost-underlain headwater catchments may increase, but the suspended sediment flux in spring may decrease due to the expansion of discontinuous permafrost areas and active layer thickness.

Discrepancies in changes in precipitation characteristics over the contiguous United States based on six daily gridded precipitation datasets

Variability and spatiotemporal changes in precipitation characteristics can have profound socioenvironmental impacts. Several studies have shown that the frequency and/or magnitude of precipitation events have changed over the contiguous United States (CONUS) in the past decades. Most previous studies used only one precipitation dataset and only investigated mean or extreme precipitation. Here, using 6 gridded daily precipitation datasets, we show that there are substantial discrepancies in the changes in characteristics of both extreme and non-extreme precipitation events from 1983 to 2017. Our results highlight that using a single record to study precipitation changes can potentially lead to biased results. Using different datasets enables examining the overall agreements and discrepancies in precipitation characteristics. For example, we show that almost all datasets agree that some areas show statistically significant changes in the annual precipitation maxima; however, the locations and signs of changes are not consistent across datasets. There is a relative agreement between datasets on changes in the total annual precipitation. When examining other percentiles of the precipitation distribution, including non-extreme values, however, we find widespread discrepancies among different precipitation products (e.g., what part of the precipitation distribution is changing). In fact, depending on the source of data, there exist opposing trends and patterns of change in precipitation characteristics. This highlights the need to further investigate non-extreme precipitation events to unravel potential non-extreme but “unexpected” or “unusual” patterns. Finally, we argue that protocols for data selection are needed to address the issue of inter-data variability and to ensure reliability of statistical analysis.

Present and future changes in precipitation characteristics during Indian summer monsoon in CORDEX‐CORE simulations

AbstractThis work examines the changes in precipitation characteristics over the Indian region using the latest high‐resolution CORDEX‐CORE model simulations. Individual RCM (COSMO, RegCM4.7, and REMO) experiments, their ensembles, and all RCM ensembles are examined to evaluate their performance using various statistical metrics. It aims to provide a holistic idea for choosing better models for specific analysis (variability, climatology, temporal evolution, indices, etc.) of precipitation distribution over India. The COSMO model experiments show lesser mean bias and have a high correlation coefficient (>0.8) compared to REMO and RegCM4. Each RCM ensemble performs better than its members in representing the spatial patterns of precipitation. Interestingly, the RCM experiments downscaling the forcings from MPI_ESM GCMs and ERA‐Interim outperforms other RCM experiments in the present day period. The probability distribution function reflects that the mean frequency and the intensity of precipitation are best represented in the RegCM4 ensemble. Further, most RCMs agree to a robust increase in low‐intensity rainfall (>0.1–4 mm⋅day‑1) in the future under the RCP8.5 scenario. The intraseasonal variability in terms of active and break spells are best represented in the RegCM4 ensemble. There exists uncertainty in terms of projection of active phases, while all model experiments agree to the decrease in the break phases in the near future compared to the present day. The projected consecutive dry (wet) days and their spells will decrease (increase) over India. The heavy precipitation events are expected to increase (by 18–32 days) along with its contribution (by 14–48%) towards the total precipitation over entire India indicating a possible increase in flooding events in the future. The present‐day ISM characteristics is well captured in the model ensemble compared to individual experiments. The model ensemble indicates towards a robust increase in low‐intensity rainfall in the future. The very heavy precipitation events and its contribution towards total precipitation are increasing in the future.

Projected Changes of Precipitation Characteristics Depend on Downscaling Method and Training Data: MACA versus LOCA Using the U.S. Northeast as an Example

AbstractThis study compares projected changes of precipitation characteristics in the U.S. Northeast in two analog-based climate downscaling products, Multivariate Adaptive Constructed Analogs (MACA) and Localized Constructed Analogs (LOCA). The level of similarity or differences between the two products varies with the type of precipitation metrics. For the total precipitation amount, the two products project significant annual increases that are similar in magnitude, spatial pattern, and seasonal distribution, with the largest increases in winter and spring. For the overall precipitation intensity or temporal aggregation of heavy precipitation (e.g., number of days with more than one inch of precipitation, the simple intensity index, and the fraction of annual precipitation accounted for by heavy events), both products project significant increases across the region with strong model consensus; the magnitude of absolute increases are similar between the two products, but the relative increases are larger in LOCA due to an underestimation of heavy precipitation in LOCA’s training data. For precipitation extremes such as the annual maximum 1-day precipitation, both products project significant increases in the long-term mean, but the magnitude of both the absolute and relative changes are much smaller in LOCA than in MACA, indicating that the extreme precipitation differences in the training data are amplified in future projections as a result of the analog-based downscaling algorithms. The two products differ the most in the intensity and frequency of rare extremes (e.g., 1-in-20-years events) for which MACA projects significant increases while the LOCA-projected changes are inconclusive over much of the study area.

A tale of two futures: contrasting scenarios of future precipitation for West Africa from an ensemble of regional climate models

The results of a large ensemble of regional climate models lead to two contrasting but plausible scenarios for the precipitation change over West Africa, one where mean precipitation is projected to decrease significantly over the Gulf of Guinea in spring and the Sahel in summer, and the other where summer precipitation over both regions is projected to increase.Dry and wet models show similar patterns of the dynamic and thermodynamic terms of the moisture budget, although their magnitudes are larger in the dry models. The largest discrepancies are found in the strength of the land-atmosphere coupling, with dry models showing a marked decrease in soil moisture and evapotranspiration.Some changes in precipitation characteristics are consistent for both sets of models. In particular, precipitation frequency is projected to decrease in spring over the Gulf of Guinea and in summer over the Sahel, but precipitation is projected to become more intense.

Evaluation of Modeled Precipitation in Oceanic Extratropical Cyclones Using IMERG

ABSTRACTUsing a high-spatial- and high-temporal-resolution precipitation dataset, Integrated Multi-satellite Retrievals for GPM (IMERG), extratropical cyclone precipitation is evaluated in two reanalyses and two climate models. Based on cyclone-centered composites, all four models overestimate precipitation in the western subsiding and dry side of the cyclones, and underestimate the precipitation in the eastern ascending and moist side. By decomposing the composites into frequency of occurrence and intensity (mean precipitation rate when precipitating), the analysis reveals a tendency for all four models to overestimate frequency and underestimate intensity, with the former issue dominating in the western half and the latter in the eastern half of the cyclones. Differences in frequency are strongly dependent on cyclone environmental moisture, while the differences in intensity are strongly impacted by the strength of ascent within the cyclone. There are some uncertainties associated with the observations: IMERG might underreport frozen precipitation and possibly exaggerate rates in vigorously ascending regions. Nevertheless, the analysis suggests that all models produce extratropical cyclone precipitation too often and too lightly. These biases have consequences when evaluating the changes in precipitation characteristics with changes in cyclone properties: the models disagree on the magnitude of the change in precipitation intensity with a change in environmental moisture and in precipitation frequency with a change in cyclone strength. This complicates accurate predictions of precipitation changes in a changing climate.

Intensified hydroclimatic regime in Korean basins under 1.5 and 2°C global warming

AbstractThis study assesses the potential changes in regional hydroclimates over South Korea in response to 1.5 and 2.0°C of global warming above preindustrial levels based on multimodel ensemble projections forced by a representative concentration pathway (RCP4.5) scenario. The meteorological inputs, which are derived from five global climate models after removing systematic bias using quantile mapping, are fed into a distributed hydrological model, the variable infiltration capacity model, to estimate the hydrologic responses to different levels of greenhouse gas concentrations in future periods. The changes in seasonal mean precipitation differ between monsoon and intermonsoon seasons. An increase in summer precipitation and a decrease in winter precipitation commonly occur under 1.5 and 2.0°C of global warming, resulting in intensified precipitation seasonality. However, changes in spring and fall precipitation show opposite change signals or relatively little robustness (as measured by model agreement) in response to different degrees of warming. Spatial and seasonal changes in precipitation are directly transferred to runoff patterns, increasing the disparity between wet and dry seasons. Global warming also leads to changes in the distributions of daily precipitation and streamflow, and the projected changes systematically involve an increase in high‐intensity precipitation and a decrease in relatively low‐intensity precipitation. This behaviour tends to be amplified under 2.0°C in comparison to 1.5°C of global warming, with potential implications for increased water stress under a much warmer climate. More importantly, under 2.0°C of global warming, the magnitude of extremes such as the annual maximum day flow in Korean basins is likely to be enhanced. This study demonstrates that changes in precipitation characteristics can explicitly modulate runoff and subsequently streamflow patterns, suggesting positive benefits of half a degree less warming in terms of the frequency and intensity of extreme streamflow.

Precipitation Variations under a Changing Climate from 1961–2015 in the Source Region of the Indus River

The source region of the Indus River (SRIR), which is located in the Hindukush, Karakoram and Himalayan (HKH) mountainous range and on the Third Pole (TP), is very sensitive to climate change, especially precipitation changes, because of its multifarious orography and fragile ecosystem. Climate changes in the SRIR also have important impacts on social and economic development, as well as on the ecosystems of the downstream irrigation areas in Pakistan. This paper investigates the changes in precipitation characteristics by dividing the daily precipitation rate into different classes, such as light (0–10 mm), moderate (10.1–25 mm) and heavy precipitation (>25 mm). Daily precipitation data from gauging and non-gauging stations from 1961–2015 are used. The results of the analysis of the annual precipitation and rainy day trends show significant (p < 0.05) increases and decreases, respectively, while light and heavy precipitation show significant decreasing and increasing trends, respectively. The analysis of the precipitation characteristics shows that light precipitation has the highest number of rainy days compared to moderate or heavy precipitation. The analysis of the seasonal precipitation trends shows that only 18 stations have significant increasing trends in winter precipitation, while 27 stations have significant increasing trends in summer precipitation. Both short and long droughts exhibit increasing trends, which indicates that the Indus Basin will suffer from water shortages for agriculture. The results of this study could help policymakers cope with floods and droughts and sustain eco-environmental resources in the study area.

Future changes in precipitation characteristics in China

This study examines potential future changes of precipitation in China based on Coupled Model Intercomparison Project Phase 5 (CMIP5) climate model projections for the medium (RCP4.5) and high (RCP8.5) emission scenarios. We first evaluate the biases of climate model output and correct the biases through quantile mapping. After bias correction, we examine the changes in mean precipitation as well as shifts in its frequency distribution. We also evaluate the changes in extreme precipitation based on frequency analysis techniques. Our results show that by the end of the century, mean precipitation is going to increase by 8% (12%) under RCP4.5 (RCP8.5) scenarios, resulted from a combination of an increase in precipitation intensity and a slight decrease in precipitation frequency. Spatially, precipitation is projected to increase more in northern China than southern China, and the increase is the least in the southeast. Seasonally, precipitation is projected to increase more in fall and winter, and less in spring and summer. The precipitation intensity distribution is likely to shift towards more heavy events, with a decrease in the contribution from light events and a significant increase in contribution from heavy events. Extreme precipitation is going to increase at much higher rates than mean precipitation, and the increase is more spatially uniform. Changes in annual and seasonal precipitation are closely linked with temperature change. Total precipitation increases at 2.6% (1.9%) per degree warming under RCP4.5 (RCP8.5), but extreme precipitation has much higher sensitivities ranging 4.5–6.5% per degree warming for events of various return intervals. The percentage increase per degree is generally smaller for RCP8.5 than RCP4.5 scenarios, suggesting a reduced sensitivity at higher temperature. In addition, the precipitation increase seems to be linked with changes in the atmospheric circulations that transport moisture in different regions in China. These changes have significant implications for the management of water resources and water‐related hazards.

Evaluating the Reliability of the U.S. Cooperative Observer Program Precipitation Observations for Extreme Events Analysis Using the LTAR Network

AbstractThe detection and attribution of changes in precipitation characteristics relies on dense networks of rain gauges. In the United States, the COOP network is widely used for such studies even though there are reported inconsistencies due to changes in instruments and location, inadequate maintenance, dissimilar observation time, and the fact that measurements are made by a group of dedicated volunteers. Alternately, the Long-Term Agroecosystem Research (LTAR) network has been consistently and professionally measuring precipitation since the early 1930s. The purpose of this study is to compare changes in extreme daily precipitation characteristics during the warm season using paired rain gauges from the LTAR and COOP networks. The comparison, done at 12 LTAR sites located across the United States, shows underestimation and overestimation of daily precipitation totals at the COOP sites compared to the reference LTAR observations. However, the magnitude and direction of the differences are not linked to the underlying precipitation climatology of the sites. Precipitation indices that focus on extreme precipitation characteristics match closely between the two networks at most of the sites. Our results show consistency between the COOP and LTAR networks with precipitation extremes. It also indicates that despite the discrepancies at the daily time steps, the extreme precipitation observed by COOP rain gauges can be reliably used to characterize changes in the hydrologic cycle due to natural and human causes.

Effects of global warming and solar geoengineering on precipitation seasonality

The effects of global warming and geoengineering on annual precipitation and its seasonality over different parts of the world are examined using the piControl, 4xCO2 and G1 simulations from eight global climate models participating in the Geoengineering Model Intercomparison Project. Specifically, we have used relative entropy, seasonality index, duration of the peak rainy season and timing of the peak rainy season to investigate changes in precipitation characteristics under 4xCO2 and G1 scenarios with reference to the piControl. In a 4xCO2 world, precipitation is projected to increase over many parts of the globe, along with an increase in both the relative entropy and seasonality index. Further, in a 4xCO2 world the increase in peak precipitation duration is found to be highest over the subpolar climatic region. However, over the tropical rain belt, the duration of the peak precipitation period is projected to decrease. Furthermore, there is a significant shift in the timing of the peak precipitation period by 15 days–2 months (forward) over many parts of the Northern Hemisphere except for over a few regions, such as North America and parts of Mediterranean countries, where a shift in the precipitation peak by 1–3 months (backward) is observed. However, solar geoengineering is found to significantly compensate many of the changes projected in a 4xCO2 scenario. Solar geoengineering nullifies the precipitation increase to a large extent. Relative entropy and the seasonality index are almost restored back to that in the control simulations, although with small positive and negative deviations over different parts of the globe, thus, significantly nullifying the impact of 4xCO2. However, over some regions, such as northern parts of South America, the Arabian Sea and Southern Africa, geoengineering does not significantly nullify changes in the seasonality index seen in 4xCO2. Finally, solar geoengineering significantly compensates the changes in timing of the peak and duration of the peak precipitation seen in 4xCO2.