Spatially Heterogeneous Changes in the Frequency and Intensity of Precipitation in Iran

Changes in classified precipitation in Iran and its relationship with global mean surface temperature (GMST) have not been comprehensively investigated. Therefore, this study analyzed changes in precipitation of different intensities over Iran for the 1987–2017 period. Results show that the total annual precipitation (PRCPTOT) and the number of wet days (RR) have significantly decreased over Iran. Also, the mean precipitation intensity (SDII) has increased somewhat. There is a non-uniform change for three intensity categories of precipitation. The amounts (frequency) of light, moderate, and heavy precipitation have significantly decreased at 47% (57.9%), 18.7% (15.8%), and 3.94% (7.9%) of stations respectively. Therefore, the decrease in the amount and frequency of light and moderate precipitation is more severe than heavy precipitation and the proportion of heavy precipitation to the total annual precipitation has increased somewhat during 1987-2017. Overall, the result shows that the intensity of decreasing trends of amount and frequency of precipitation has increased from the south (east) to the north (west) of Iran. Also, SDII has increased from the south (east) to the north (west) of Iran. The sensitivity value was obtained by calculating the ratio of linear trends of precipitation indices and GMST. The regional median sensitivity and percentage change in PRCPTOT, RR, and SDII per 1-kelvin increase in GMST are -6.1%, -11.2%, and 12.9% respectively. Considering that Iran is located in the arid subtropical region, a significant decrease in the amount and frequency of precipitation may have destructive effects on water resources.

In this paper, we examined the spatial and temporal variations in precipitation amount, frequency, and intensity in China based on daily precipitation data from 2050 weather stations from 1973 to 2016. We used two Markov chain parameters to quantify the wet persistence and dry persistence that characterizes the temporal pattern of wet and dry days, respectively. We found that China’s annual precipitation changed little from 1973 to 2016, but varied dramatically from 524 to 688 mm yr−1, with an average of 592 mm yr−1, during this period. China’s precipitation frequency, the number of days with effective precipitation (>0.1 mm day−1) in a year, significantly decreased at a rate of 0.9 days decade−1 from 1973 to 2016, but precipitation intensity significantly increased at a rate of 0.12 mm day−1 decade−1 during the same period. Of the changes in China’s total precipitation amount, precipitation intensity played a dominant role, contributing 70.8%, while precipitation frequency contributed the remaining 29.2%. Little change was found in the wet persistence in China over the period of 1973–2016, but the dry persistence significantly increased with an average increasing trend of 1.62 × 10−3 probability per decade during the same period, and no significant correlations were found between these two variables. China’s precipitation also changed nonuniformly in space, with increasing trends in precipitation amount, frequency, intensity, and wet persistence in western and northeastern China but decreasing trends in the Sichuan basin, northeast of Inner Mongolia, and the Beijing–Tianjin–Hebei region.

The analysis of precipitation intensity and frequency should be conducted on data with high temporal resolution, such as hourly precipitation data. This study focuses on the spatial distribution and temporal variation of precipitation intensity and frequency in the Yarlung Zangbo River basin during 2008–2017, based on a merged hourly precipitation dataset with 0.1° of latitude/longitude spatial resolution. The hourly precipitation intensity is represented as the mean accumulated amount in each observation hour and the precipitation frequency is the proportion of precipitation hours in this study. The multi-year mean values and temporal changes of precipitation intensity and frequency are compared at annual time scale, during the warm season (from May to October) and cold season (from November to the next April), as well as among the upper, middle and lower basins. For the whole stream region, the mean hourly precipitation intensity is 0.92 mm/h during the warm season, larger than 0.69 mm/h during the cold season. The mean precipitation frequency is about 7.79% during the warm season, larger than 4.40% during the cold season. For the sub-region, the mean hourly precipitation intensity and frequency are largest for the lower basin during the warm season (1.10 mm/h and 10.62%), whereas largest for the upper basin during the cold season (0.86 mm/h and 4.26%). The hourly precipitation intensity increases during the warm season but decreases during the cold season. The precipitation frequency continuously decreases with larger tendency during the warm season than that during the cold season.

Future changes in East Asian summer monsoon precipitation climatology, frequency, and intensity are analyzed using historical climate simulations and future climate simulations under the RCP4.5 scenario using the World Climate Research Programme’s (WCRP) Coupled Model Intercomparison Project 5 (CMIP5) multi-model dataset. The model reproducibility is evaluated, and well performance in the present-day climate simulation can be obtained by most of the studied models. However, underestimation is obvious over the East Asian region for precipitation climatology and precipitation intensity, and overestimation is observed for precipitation frequency. The overestimation of precipitation frequency is mainly due to the large positive bias of the light precipitation (precipitation 10 mm/day) intensity. For the future climate simulations, simple multi-model ensemble (MME) averages using all of the models show increases in precipitation and its intensity over almost all of East Asia, while the precipitation frequency is projected to decrease over eastern China and around Japan and increase in other regions. When the weighted MME is considered, no large difference can be observed compared with the simple MME. For the MME using the six best models that have good performance in simulating the present-day climate, the future climate changes over East Asia are very similar to those predicted using all of the models. Further analysis shows that the frequency and intensity of intense precipitation events are also projected to significantly increase over East Asia. Increases in precipitation frequency and intensity are the main contributors to increases in precipitation, and the contribution of frequency increases (contributed by 40.8 % in the near future and by 58.9 % by the end of the twenty-first century) is much larger than that of intensity increases (contributed by 29.9 % in the near future and by 30.1 % by the end of the twenty-first century). This finding also implies an increased risk of intense precipitation events over the East Asian region under global warming scenario. These results regarding future climate simulations show much greater reliability than those using CMIP3 simulations.

Trends of precipitation intensity and frequency in hydrological regions of China from 1956 to 2005

Atmospheric circulation and precipitation in Southwest Asia: The role of the Arabian Anticyclone in precipitation of Iran

Intra-Annual Variability of Diurnal Cycle Precipitation over China from 1960-2000

Intra-Annual Variability of Diurnal Cycle Precipitation over China from 1960–2000

Conventional low‐resolution (LR) climate models, including the Energy Exascale Earth System Model (E3SMv1), have well‐known biases in simulating the frequency, intensity, and timing of precipitation. Approaches to next‐generation E3SM, whether the high‐resolution (HR) or multiscale modeling framework (MMF) configuration, improve the simulation of the intensity and frequency of precipitation, but regional and seasonal deficiencies still exist. Here we apply a methodology to assess the contribution of tropical cyclones (TCs), extratropical cyclones (ETCs), and mesoscale convective systems (MCSs) to simulated precipitation in E3SMv1‐HR and E3SMv1‐MMF relative to E3SMv1‐LR. Across the United States, E3SMv1‐MMF provides the best simulation in terms of precipitation accumulation, frequency and intensity from MCSs and TCs compared to E3SMv1‐LR and E3SMv1‐HR. All E3SMv1 configurations overestimate precipitation amounts from and the frequency of ETCs over CONUS, with conventional E3SMv1‐LR providing the best simulation compared to observations despite limitations in precipitation intensity within these events.

ABSTRACTAn intensive observational hourly precipitation data set from the China Meteorological Administration was utilized to investigate the changes in precipitation amount, frequency, intensity and duration over central eastern China during the warm season from 1982 to 2012. Ten intensity categories were used to reveal the contributions of precipitation frequency and intensity to the variation of rainfall amount. Moreover, the trends of frequency were also evaluated by comparing the respective contributions of the number and the duration of precipitation events. The main results are as follows: (1) The precipitation amount and intensity both decreased from southeast to northwest China, with two areas of high precipitation frequency located in southwestern and southeastern China. A region of high precipitation duration was found in central China and two lower duration regions were found in southern and northern China. (2) Generally, the extreme heavy rainfall showed a significant increasing trend while the light rainfall showed a significant decreasing trend over central eastern China. Nevertheless, the spatial unevenness was detected and in south and southeast China, significant increasing trends were found, whereas in northeast China and the Sichuan Basin, precipitation amounts showed a declining trend in each precipitation intensity category. (3) The trends of precipitation amount were mainly caused by the variations of precipitation frequency, which had a contribution rate of greater than 95%; however, for the heavy rainfall category, intensity changes were also very important. (4) Increased precipitation frequency was largely caused by the prolonged duration of rainfall events, whereas the decreased frequency was mainly due to the reduction in the number of rainfall events.

Precipitation sensitivity to soil moisture and its seasonal and diurnal changes are investigated in Bangladesh and surrounding regions using a regional climate model with a 5-km grid spacing. In the control experiment, soil moisture is calculated by a land surface scheme, and simulated accuracy of seasonal and diurnal variations in precipitation intensity and frequency is capable of assessing the soil moisture impact on precipitation. In sensitivity experiments with wetter land surfaces, daytime precipitation intensity decreases over the southern plains for both the premonsoon and mature monsoon seasons because of the weakening of surface heating and vertical mixing in the planetary boundary layer (PBL). Weakened vertical turbulent flux of moisture reduces condensation heating and upward motion in the mid- and upper troposphere, which suppresses development of convective precipitation. The simulated precipitation intensity response to soil moisture suggests that land surface wetness contributes to the seasonal contrast in observed precipitation intensity (i.e., stronger in the premonsoon than the mature monsoon seasons). Meanwhile, the precipitation frequency response to soil moisture varies with season and by region. Over the southern plains in the wet land surface experiments, daytime precipitation frequency decreases (increases) during the premonsoon (mature monsoon) season compared with the dry land surface experiments, as influenced by seasonal differences in relative humidity and the condensation process in the lower troposphere. Around the northern mountainous area, higher soil moisture increases precipitation frequency regardless of season because of additional water vapor supply from the ground and frequent orographic precipitation forced by the mountainous topography.

Human transformation of landscapes is pervasive and accelerating across the Earth. However, existing studies have not provided a comprehensive picture of how precipitation frequency and intensity respond to vegetation cover change. Therefore, this study took the Loess Plateau as a typical example, and used satellite-based Normalized Difference Vegetation Index (NDVI) data and daily gridded climatic variables to assess the responses of precipitation dynamics to human-induced vegetation cover change. Results showed that the total precipitation amount exhibited little change at the regional scale, showing an upward but statistically insignificant (p > 0.05) trend of 7.6 mm/decade in the period 1982–2015. However, the frequency of precipitation with different intensities showed large variations over most of the Loess Plateau. The number of rainy days (light, moderate, heavy, very heavy and severe precipitation) increased in response to increased vegetation cover, especially in the central-eastern Loess Plateau. Anthropogenic land cover change is largely responsible for precipitation intensity changes. Additionally, this study also observed high spatially explicit heterogeneity in different precipitation intensities in response to vegetation cover change across the Loess Plateau. These findings provide some reference information for our understanding of precipitation frequency and intensity changes in response to regional vegetation cover change in the Loess Plateau.

The IMERG V06 hourly rainfall product at daily and hourly scales was evaluated during the warm season (May to September) from 2015 to 2020 using 651 high-quality rain-gauge stations over the Tibetan Plateau (TP). Based on hourly observed rain-gauge precipitation, four categories were classified: light rainfall (0–12 mm·d−1), moderate rainfall (12–20.1 mm·d−1), torrential rainfall (20.1–32.2 mm·d−1), and extreme torrential rainfall (>32.2 mm·d−1). Precipitation frequency and intensity were calculated to further validate the accuracy and suitability of the IMERG estimated-precipitation product. At the daily scale, IMERG underestimated the number of days with less than moderate rainfall, but overestimated the frequency of torrential and extreme torrential rainfall. IMERG estimated the main characteristics of precipitation frequency at different daily precipitation amount levels better than the precipitation intensity, but its best estimate was at the moderate rainfall level, with the highest correlation coefficient (0.69) and the lowest root mean square error (0.17). At the hourly scale, IMERG underestimated the hourly precipitation amount mainly between the early morning and midday (the average deviation was 0.019 mm·h−1) and overestimated it between the afternoon and late night (the average deviation was 0.047 mm·h−1). IMERG overestimated precipitation frequency and underestimated precipitation intensity between the afternoon and the evening, which means that this analysis shows that IMERG estimated more precipitation hours than the observation and underestimated precipitation intensity. These results further our understanding of the suitability of the IMERG precipitation products over the TP and further improve the IMERG retrieval algorithm to better apply the corresponding precipitation product to light and extreme rainfall over regions with complicated topography.

Precipitation is expected to increase under global warming. However, large discrepancies in precipitation sensitivities to global warming among observations and models have been reported, partly owing to the large natural variability of precipitation, which accounts for over 90% of its total variance in China. Here, the authors first elucidated precipitation sensitivities to the long-term warming trend and interannual–decadal variations of surface air temperature Ta over China based on daily data from approximately 2000 stations from 1961 to 2014. The results show that the number of dry, trace, and light precipitation days has stronger sensitivities to the warming trend than to the Ta interannual–decadal variation, with 14.1%, −35.7%, and −14.6% K−1 versus 2.7%, −7.9%, and −3.1% K−1, respectively. Total precipitation frequency has significant sensitivities to the warming trend (−18.5% K−1) and the Ta interannual–decadal variation (−3.6% K−1) over China. However, very heavy precipitation frequencies exhibit larger sensitivities to the Ta interannual–decadal variation than to the long-term trend over Northwest and Northeast China and the Tibetan Plateau. A warming trend boosts precipitation intensity, especially for light precipitation (9.8% K−1). Total precipitation intensity increases significantly by 13.1% K−1 in response to the warming trend and by 3.3% K−1 in response to the Ta interannual–decadal variation. Very heavy precipitation intensity also shows significant sensitivity to the interannual–decadal variation of Ta (3.7% K−1), particularly in the cold season (8.0% K−1). Combining precipitation frequency and intensity, total precipitation amount has a negligible sensitivity to the warming trend, and the consequent trend in China is limited. Moderate and heavy precipitation amounts are dominated by their frequencies.

The Tropical Rainfall Measurement Mission (TRMM) satellite is the first to be designed to measure precipitation, and its precipitation products have been assessed in a variety of ways. Data for its post-real-time level 2 product (3B42) performed well in terms of the precipitation amount at the monthly scale because they were corrected by a precipitation dataset that was gauged every month. However, the performance of this dataset in terms of precipitation frequency and intensity is still not ideal. To this end, TRMM 3B42 products were evaluated using precipitation data from 747 meteorological stations over mainland China in this study. The Pearson’s correlation coefficient (CC), relative bias (RB), and relative error (RE) were used to assess the capability of TRMM products in terms of estimating the frequency, intensity, and amount of precipitation for different categories of precipitation during nighttime and daytime in a multiscale analysis (including interannual variation, seasonal cycles, and spatial distribution). Our results showed the following: (1) The 3B42 products reproduced interannual trends of the frequency and amount of precipitation (except for trace precipitation) with an average correlation coefficient of 0.84. (2) 3B42 performed well at calculating the annual and monthly precipitation amount, but performed poorly for frequency and even worse for intensity. The biases in these two properties canceled out, however, which led to a better estimate of the amount. (3) 3B42 represented the distribution of the subdaily amount of precipitation over a majority of the regions in the east, but did not perform well on the Tibetan Plateau or in northwest China. The performance of 3B42, as detailed in this study, can serve as valuable guidance to data users and algorithm developers.