Understanding the Asian water tower requires a redesigned precipitation observation strategy.

The Asian water tower (AWT) serves as the source of 10 major Asian river systems and supports the lives of ~2 billion people. Obtaining reliable precipitation data over the AWT is a prerequisite for understanding the water cycle within this pivotal region. Here, we quantitatively reveal that the "observed" precipitation over the AWT is considerably underestimated in view of observational evidence from three water cycle components, namely, evapotranspiration, runoff, and accumulated snow. We found that three paradoxes appear if the so-called observed precipitation is corrected, namely, actual evapotranspiration exceeding precipitation, unrealistically high runoff coefficients, and accumulated snow water equivalent exceeding contemporaneous precipitation. We then explain the cause of precipitation underestimation from instrumental error caused by wind-induced gauge undercatch and the representativeness error caused by sparse-uneven gauge density and the complexity of local surface conditions. These findings require us to rethink previous results concerning the water cycle, prompting the study to discuss potential solutions.

A global meta-analysis on the drivers of salt marsh planting success and implications for ecosystem services.

Planting has been widely adopted to battle the loss of salt marshes and to establish living shorelines. However, the drivers of success in salt marsh planting and their ecological effects are poorly understood at the global scale. Here, we assemble a global database, encompassing 22,074 observations reported in 210 studies, to examine the drivers and impacts of salt marsh planting. We show that, on average, 53% of plantings survived globally, and plant survival and growth can be enhanced by careful design of sites, species selection, and novel planted technologies. Planting enhances shoreline protection, primary productivity, soil carbon storage, biodiversity conservation and fishery production (effect sizes = 0.61, 1.55, 0.21, 0.10 and 1.01, respectively), compared with degraded wetlands. However, the ecosystem services of planted marshes, except for shoreline protection, have not yet fully recovered compared with natural wetlands (effect size = -0.25, 95% CI -0.29, -0.22). Fortunately, the levels of most ecological functions related to climate change mitigation and biodiversity increase with plantation age when compared with natural wetlands, and achieve equivalence to natural wetlands after 5-25 years. Overall, our results suggest that salt marsh planting could be used as a strategy to enhance shoreline protection, biodiversity conservation and carbon sequestration.

Global rainfall erosivity database (GloREDa) and monthly R-factor data at 1 km spatial resolution.

Here, we present and release the Global Rainfall Erosivity Database (GloREDa), a multi-source platform containing rainfall erosivity values for almost 4000 stations globally. The database was compiled through a global collaboration between a network of researchers, meteorological services and environmental organisations from 65 countries. GloREDa is the first open access database of rainfall erosivity (R-factor) based on hourly and sub-hourly rainfall records at a global scale. This database is now stored and accessible for download in the long-term European Soil Data Centre (ESDAC) repository of the European Commission's Joint Research Centre. This will ensure the further development of the database with insertions of new records, maintenance of the data and provision of a helpdesk. In addition to the annual erosivity data, this release also includes the mean monthly erosivity data for 94% of the GloREDa stations. Based on these mean monthly R-factor values, we predict the global monthly erosivity datasets at 1 km resolution using the ensemble machine learning approach (ML) as implemented in the mlr package for R. The produced monthly raster data (GeoTIFF format) may be useful for soil erosion prediction modelling, sediment distribution analysis, climate change predictions, flood, and natural disaster assessments and can be valuable inputs for Land and Earth Systems modelling.

Sediment reduction in the middle Yellow River basin over the past six decades: Attribution, sustainability, and implications.

Understanding the underlying driving forces causing changes in sediment yield is crucial for decision-making and major strategy development for the management of the middle Yellow River basin (MYRB). In this work, we quantified the causes of sediment yield reduction in the MYRB and investigated the sustainability of sediment reduction strategies. The sediment yield in the middle Yellow River during 1957-2017 exhibits a significant downward trend. The average sediment yield in 1970-2017 decreased by 798.84 × 106 t compared with that during the 1950s to 1960s, with 27.40 % ascribed to decreased precipitation and 72.60 % attributed to human activities. The sediment yield modulus of all sub-basins within the MYRB has been reduced to <5000 t/km2, demonstrating the dominant influence of water and soil conservation measures. Check dams have limited on-site effectiveness in reducing sediment yield but exhibit a dominant effect in trapping the already yielded sediment and preventing it from being delivered into the lower Yellow River. The strong dependence on the storage capacity of check dams makes the system unsustainable in the long run, since it necessitates ongoing investment in check dam construction to maintain the sediment trapping effect. Promoting biological measures such as planting trees and grass to increase vegetation coverage is a more sustainable way to fix the sediment on-site and keep it from being eroded. These efforts should be intensified, with appropriate consideration for local conditions.

High-quality reconstruction of China's natural streamflow.

Reconstruction of natural streamflow is fundamental to the sustainable management of water resources. In China, previous reconstructions from sparse and poor-quality gauge measurements have led to large biases in simulation of the interannual and seasonal variability of natural flows. Here we use a well-trained and tested land surface model coupled to a routing model with flow direction correction to reconstruct the first high-quality gauge-based natural streamflow dataset for China, covering all its 330 catchments during the period from 1961 to 2018. A stronger positive linear relationship holds between upstream routing cells and drainage areas, after flow direction correction to 330 catchments. We also introduce a parameter-uncertainty analysis framework including sensitivity analysis, optimization, and regionalization, which further minimizes biases between modeled and inferred natural streamflow from natural or near-natural gauges. The resulting behavior of the natural hydrological system is represented properly by the model which achieves high skill metric values of the monthly streamflow, with about 83% of the 330 catchments having Nash-Sutcliffe efficiency coefficient (NSE) > 0.7, and about 56% of the 330 catchments having Kling-Gupta efficiency coefficient (KGE) > 0.7. The proposed construction scheme has important implications for similar simulation studies in other regions, and the developed low bias long-term national datasets by statistical postprocessing should be useful in supporting river management activities in China.

Full-stream erosion in the lower Yellow River: Feasibility, sustainability and opportunity.

The issue of how to achieve removal of recently accumulated sediment is one of the largest unresolved puzzles in China's lower Yellow River. In this work, the feasibility and sustainability of achieving full-stream erosion in the lower Yellow River based on a water-sediment regulation scheme (WSRS) have been comprehensively investigated. The results indicate that the erosion-deposition state of the lower Yellow River is controlled by the incoming flow discharge level and the corresponding sediment concentration. The year 1987 is identified as an abrupt change point for streamflow in Xiaolangdi station. The relationships between channel erosion or deposition and the sediment concentration of the incoming discharge are constructed for the periods 1960-1987 and 1988-2017. Based on a constrained optimization approach, a sediment concentration lower than 19.96 kg/m3 in the discharge from Xiaolangdi Reservoir is determined to be the critical controlling condition for achieving full-stream erosion in the lower Yellow River under the average discharge level observed during 1960-1987; however, it is challenging to achieve full-stream erosion under the average discharge level of 1988-2017. Although this erosion status could potentially be achieved through continued implementation of the WSRS, its sustainability is restricted by the declining storage capacity of Xiaolangdi Reservoir, decreasing water discharge levels and riverbed coarsening in the Yellow River. It is necessary to design cross-basin collaboration measures for the upper, middle and lower Yellow River to achieve sustainable sediment reduction and healthy development of the Yellow River basin as a whole.

Long-term trends in Songhua River Basin streamflow and its multivariate relationships with meteorological factors.

Long-term streamflow trends are closely related to meteorological factors; understanding the relationships between them helps to improve water resources management in advance. In this study, we examined long-term annual and seasonal streamflow trends over 1961-2010 in 28 stations in the Songhua River Basin (SRB), China, using four kinds of trend detection methods and then determined the optimal meteorological predictors for SRB streamflow based on the multiple wavelet coherence. We found significant downward trends in annual streamflow in a large part of the study stations (varies from 10 to 18 for different methods), and fewer decreasing stations were detected when we consider the full autocorrelation and the long-term persistence in streamflow. In contrast to annual streamflow, fewer stations showed significant downward trends in summer and winter streamflow. Streamflow generally followed the pattern of precipitation (PRE); the largest streamflow changes occurred in summer and August monthly streamflow variation contributed the most to the annual streamflow variation. We found PRE and potential evapotranspiration (PET) combined was the optimal predictor for streamflow above Jiangqiao and on the Jiangqiao-Dalai section of the Songhua River; as for the Dalai-Harbin section and the Harbin-Jiamusi section, the optimal predictor combinations are PRE and number of rainy days (WET), and PRE and average monthly temperature (TMP) respectively.

Global Observations and CMIP6 Simulations of Compound Extremes of Monthly Temperature and Precipitation.

Compound climate extremes, such as events with concurrent temperature and precipitation extremes, have significant impacts on the health of humans and ecosystems. This paper aims to analyze temporal and spatial characteristics of compound extremes of monthly temperature and precipitation, evaluate the performance of the sixth phase of the Coupled Model Intercomparison Project (CMIP6) models in simulating compound extremes, and investigate their future changes under Shared Socioeconomic Pathways (SSPs). The results show a significant increase in the frequency of compound warm extremes (warm/dry and warm/wet) but a decrease in compound cold extremes (cold/dry and cold/wet) during 1985-2014 relative to 1955-1984. The observed upward trends of compound warm extremes over China are much higher than those worldwide during the period of interest. A multi-model ensemble (MME) of CMIP6 models performs well in simulating temporal changes of warm/wet extremes, and temporal correlation coefficients between MME and observations are above 0.86. Under future scenarios, CMIP6 simulations show substantial rises in compound warm extremes and declines in compound cold extremes. Globally, the average frequency of warm/wet extremes over a 30-yr period is projected to increase for 2070-2099 relative to 1985-2014 by 18.53, 34.15, 48.79, and 59.60 under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. Inter-model uncertainties for the frequencies of compound warm extremes are considerably higher than those of compound cold extremes. The projected uncertainties in the global occurrences of warm/wet extremes are 3.82 times those of warm/dry extremes during 2070-2099 and especially high for the Amazon and the Tibetan Plateau.

Soil erosion modelling: A bibliometric analysis.

Soil erosion can present a major threat to agriculture due to loss of soil, nutrients, and organic carbon. Therefore, soil erosion modelling is one of the steps used to plan suitable soil protection measures and detect erosion hotspots. A bibliometric analysis of this topic can reveal research patterns and soil erosion modelling characteristics that can help identify steps needed to enhance the research conducted in this field. Therefore, a detailed bibliometric analysis, including investigation of collaboration networks and citation patterns, should be conducted. The updated version of the Global Applications of Soil Erosion Modelling Tracker (GASEMT) database contains information about citation characteristics and publication type. Here, we investigated the impact of the number of authors, the publication type and the selected journal on the number of citations. Generalized boosted regression tree (BRT) modelling was used to evaluate the most relevant variables related to soil erosion modelling. Additionally, bibliometric networks were analysed and visualized. This study revealed that the selection of the soil erosion model has the largest impact on the number of publication citations, followed by the modelling scale and the publication's CiteScore. Some of the other GASEMT database attributes such as model calibration and validation have negligible influence on the number of citations according to the BRT model. Although it is true that studies that conduct calibration, on average, received around 30% more citations, than studies where calibration was not performed. Moreover, the bibliographic coupling and citation networks show a clear continental pattern, although the co-authorship network does not show the same characteristics. Therefore, soil erosion modellers should conduct even more comprehensive review of past studies and focus not just on the research conducted in the same country or continent. Moreover, when evaluating soil erosion models, an additional focus should be given to field measurements, model calibration, performance assessment and uncertainty of modelling results. The results of this study indicate that these GASEMT database attributes had smaller impact on the number of citations, according to the BRT model, than anticipated, which could suggest that these attributes should be given additional attention by the soil erosion modelling community. This study provides a kind of bibliographic benchmark for soil erosion modelling research papers as modellers can estimate the influence of their paper.

Soil erosion modelling: A global review and statistical analysis.

To gain a better understanding of the global application of soil erosion prediction models, we comprehensively reviewed relevant peer-reviewed research literature on soil-erosion modelling published between 1994 and 2017. We aimed to identify (i) the processes and models most frequently addressed in the literature, (ii) the regions within which models are primarily applied, (iii) the regions which remain unaddressed and why, and (iv) how frequently studies are conducted to validate/evaluate model outcomes relative to measured data. To perform this task, we combined the collective knowledge of 67 soil-erosion scientists from 25 countries. The resulting database, named 'Global Applications of Soil Erosion Modelling Tracker (GASEMT)', includes 3030 individual modelling records from 126 countries, encompassing all continents (except Antarctica). Out of the 8471 articles identified as potentially relevant, we reviewed 1697 appropriate articles and systematically evaluated and transferred 42 relevant attributes into the database. This GASEMT database provides comprehensive insights into the state-of-the-art of soil- erosion models and model applications worldwide. This database intends to support the upcoming country-based United Nations global soil-erosion assessment in addition to helping to inform soil erosion research priorities by building a foundation for future targeted, in-depth analyses. GASEMT is an open-source database available to the entire user-community to develop research, rectify errors, and make future expansions.

Time lag of vegetation growth on the Loess Plateau in response to climate factors: Estimation, distribution, and influence.

Vegetation growth is importantly affected by seasonal weather patterns. The time lag between changes in these patterns and the vegetative response is an important factor in vegetation-climate interactions and can vary considerably with the spatial heterogeneity of an ecosystem. In this study of the Loess Plateau, China, highly accurate time lags were determined at the daily scale using linear regression based on a multiyear normalized difference vegetation index (NDVI) dataset (1982-2015) and the corresponding reconstructed monthly climate series. We found that lag length varied among catchments, vegetation zones, and land-cover types. The mean time lag between precipitation and the NDVI response varied from 7.9 days to 17.7 days across the catchments; for temperature and NDVI, the lag in response ranged from 6.2 days to 25.3 days. Across the six vegetation zones that range from the southeast to the northwest of the Loess Plateau, both the precipitation-NDVI and temperature-NDVI lag lengths were largest in the central zones and lower in the zones closer to the edges of the plateau. Among the different land-cover types, grassland had the largest lags between precipitation or temperature change and the NDVI response, followed by shrubland, arable land, and then forests. The possible impact of vegetative time lags on sediment yield was also investigated for the first time, and this information has great relevance for soil conservation on the Loess Plateau and sediment reduction in the lower Yellow River.

Human activities aggravate nitrogen-deposition pollution to inland water over China.

In the past three decades, China has built more than 87 000 dams with a storage capacity of ≈6560 km3 and the total surface area of inland water has increased by 6672 km2. Leaching of N from fertilized soils to rivers is the main source of N pollution in China, but the exposure of a growing inland water area to direct atmospheric N deposition and N leaching caused by N deposition on the terrestrial ecosystem, together with increased N deposition and decreased N flow, also tends to raise N concentrations in most inland waters. The contribution of this previously ignored source of N deposition to freshwaters is estimated in this study, as well as mitigation strategies. The results show that the annual amounts of N depositions ranged from 4.9 to 16.6 kg · ha-1 · yr-1 in the 1990s to exceeding 20 kg · ha-1 · yr-1 in the 2010s over most of regions in China, so the total mass of ΔN (the net contribution of N deposition to the increase in N concentration) for lakes, rivers and reservoirs change from 122.26 Gg N · yr-1 in the 1990s to 237.75 Gg N · yr-1 in the 2010s. It is suggested that reducing the N deposition from various sources, shortening the water-retention time in dams and decreasing the degree of regulation for rivers are three main measures for preventing a continuous increase in the N-deposition pollution to inland water in China.

Homogenization and polarization of the seasonal water discharge of global rivers in response to climatic and anthropogenic effects.

We investigate global trends in seasonal water discharge using data from 5668 hydrological stations in catchments whose total drainage area accounts for 2/3 of the Earth's total land area. Homogenization of water discharge, which occurs when the gap in water discharge between dry and flood seasons shrinks significantly, affects catchments occupying 2/5 of the total land area, and is mainly concentrated in Eurasia and North America. By contrast, polarization of water discharge, associated with widening of the gap in water discharge between dry and flood seasons, occurs in catchments covering 1/6 of the land area, most notably in the Amazon Basin and river basins in West Africa. Considering the major climatic and anthropogenic controlling factors, i.e. precipitation (P), evaporation (E), glacial runoff (G), and dam operations (D), the world's river basins are classified as P, DEP, GEP, and EP types. Contributions from each controlling factor to either the homogenization or polarization of the seasonal water discharge for each type of river have been analyzed. We found that homogenization of discharge is dominated by dam operations in GDEP and DEP river basins (contributing 48% and 64%) and by homogenized precipitation in GEP and EP river basins. Evaporation and precipitation are primary factors behind the polarization of discharge, contributing 56% and 41%. This study provides a basis for a possible decision tool for controlling drought/flood disasters and for assessing and preventing ecological damage in endangered regions.

Global heat stress on health, wildfires, and agricultural crops under different levels of climate warming.

The effects of heat stress are spatially heterogeneous owing to local variations in climate response, population density, and social conditions. Using global climate and impact models from the Inter-Sectoral Impact Model Intercomparison Project, our analysis shows that the frequency and intensity of heat events increase, especially in tropical regions (geographic perspective) and developing countries (national perspective), even with global warming held to the 1.5 °C target. An additional 0.5 °C increase to the 2 °C warming target leads to >15% of global land area becoming exposed to levels of heat stress that affect human health; almost all countries in Europe will be subject to increased fire danger, with the duration of the fire season lasting 3.3 days longer; 106 countries are projected to experience an increase in the wheat production-damage index. Globally, about 38%, 50%, 46%, 36%, and 48% of the increases in exposure to health threats, wildfire, crop heat stress for soybeans, wheat, and maize could be avoided by constraining global warming to 1.5 °C rather than 2 °C. With high emissions, these impacts will continue to intensify over time, extending to almost all countries by the end of the 21st century: >95% of countries will face exposure to health-related heat stress, with India and Brazil ranked highest for integrated heat-stress exposure. The magnitude of the changes in fire season length and wildfire frequency are projected to increase substantially over 74% global land, with particularly strong effects in the United States, Canada, Brazil, China, Australia, and Russia. Our study should help facilitate climate policies that account for international variations in the heat-related threats posed by climate change.

Temporal and spatial variations in water discharge and sediment load on the Loess Plateau, China: A high-density study.

Over the past 50 years, a series of soil and water conservation measures have been implemented on the Loess Plateau, including biological, engineering, and agricultural measures. As a result, water discharge and sediment load on the plateau have undergone significant changes. In this study, we compared the water discharge and sediment load at >100 hydrological stations across the Loess Plateau during the period 2008-2016 (P2) with the water discharge and sediment load during the period 1971-1987 (P1), and detected the main sources of sediment in each of the two periods. We then performed an attribution analysis to quantify the influence of different factors on the changes in sediment load. We found the following results: (1) Water discharge was reduced by 22% in P2 compared with P1, whereas the sediment load was reduced by 74%. (2) Sediment resources are mainly concentrated between Toudaoguai and Tongguan stations: this region contributed >88% of the total sediment load at the terminal station (Huayuankou station) in both P1 and P2. (3) When considering only the changes in sediment concentration on the Loess Plateau, we conclude that the contribution of human activities was >72%. This study provides a detailed description of the temporal and spatial variations in water and sediment across the Loess Plateau, providing a reliable reference for the future development of ecological soil and water conservation measures on the Loess Plateau.

Spatiotemporal variations in vegetation cover on the Loess Plateau, China, between 1982 and 2013: possible causes and potential impacts.

Vegetation is a key component of the ecosystem and plays an important role in water retention and resistance to soil erosion. In this study, we used a multiyear normalized difference vegetation index (NDVI) dataset (1982-2013) and corresponding datasets for observed climatic variables to analyze changes in the NDVI at both temporal and spatial scales. The relationships between NDVI, climate change, and human activities were also investigated. The annual average NDVI showed an upward trend over the 32-year study period, especially in the center of the Loess Plateau. NDVI variations lagged behind monthly temperature changes by approximately 1 month. The contribution of human activities to variations in NDVI has become increasingly significant in recent years, with human activities responsible for 30.4% of the change in NDVI during the period 2001-2013. The increased vegetation coverage has reduced soil erosion on the Loess Plateau in recent years. It is suggested that natural restoration of vegetation is the most effective measure for control of erosion; engineering measures that promote this should feature in the future governance of the Loess Plateau.

Global rainfall erosivity assessment based on high-temporal resolution rainfall records.

The exposure of the Earth's surface to the energetic input of rainfall is one of the key factors controlling water erosion. While water erosion is identified as the most serious cause of soil degradation globally, global patterns of rainfall erosivity remain poorly quantified and estimates have large uncertainties. This hampers the implementation of effective soil degradation mitigation and restoration strategies. Quantifying rainfall erosivity is challenging as it requires high temporal resolution(<30 min) and high fidelity rainfall recordings. We present the results of an extensive global data collection effort whereby we estimated rainfall erosivity for 3,625 stations covering 63 countries. This first ever Global Rainfall Erosivity Database was used to develop a global erosivity map at 30 arc-seconds(~1 km) based on a Gaussian Process Regression(GPR). Globally, the mean rainfall erosivity was estimated to be 2,190 MJ mm ha-1 h-1 yr-1, with the highest values in South America and the Caribbean countries, Central east Africa and South east Asia. The lowest values are mainly found in Canada, the Russian Federation, Northern Europe, Northern Africa and the Middle East. The tropical climate zone has the highest mean rainfall erosivity followed by the temperate whereas the lowest mean was estimated in the cold climate zone.

Detecting the quantitative hydrological response to changes in climate and human activities.

Understanding the relative contributions of climate change and human activities to changes in runoff is important for sustainable management of regional water resources. In this study, we systematically review ten commonly used quantitative methods drawn from three main categories-empirical statistics, elasticity-based methods, and hydrological modeling. We explain the calculation processes for the different methods and summarize their applications and characteristics. Then, using the Yanhe River basin as a case study, we employ all ten methods to separate out the effects of climate change and human activities on changes in runoff. The results show that climate change played a dominant role in the decline in runoff in the Yanhe River basin. Climate change was estimated to account for 46.1%-60.8% (mean 54.1%) of the total decrease in runoff, whereas human activities accounted for 39.1%-53.9% (mean 45.9%). Elasticity-based methods and hydrological modeling produced similar estimates, but the estimates made using empirical statistics were different. Empirical statistics were not a suitable method for the Yanhe River basin. We also discuss the factors that influence the different methods and the applicable conditions for each methodological category.

Environmental impact assessments of the Xiaolangdi Reservoir on the most hyperconcentrated laden river, Yellow River, China.

The Yellow River is the most hyperconcentrated sediment-laden river in the world. Throughout recorded history, the Lower Yellow River (LYR) experienced many catastrophic flood and drought events. To regulate the LYR, a reservoir was constructed at Xiaolangdi that became operational in the early 2000s. An annual water-sediment regulation scheme (WSRS) was then implemented, aimed at flood control, sediment reduction, regulated water supply, and power generation. This study examines the eco-environmental and socioenvironmental impacts of Xiaolangdi Reservoir. In retrospect, it is found that the reservoir construction phase incurred huge financial cost and required large-scale human resettlement. Subsequent reservoir operations affected the local geological environment, downstream riverbed erosion, evolution of the Yellow River delta, water quality, and aquatic biodiversity. Lessons from the impact assessment of the Xiaolangdi Reservoir are summarized as follows: (1) The construction of large reservoirs is not merely an engineering challenge but must also be viewed in terms of resource exploitation, environmental protection, and social development; (2) long-term systems for monitoring large reservoirs should be established, and decision makers involved at national policy and planning levels must be prepared to react quickly to the changing impact of large reservoirs; and (3) the key to solving sedimentation in the LYR is not Xiaolangdi Reservoir but instead soil conservation in the middle reaches of the Yellow River basin. Proper assessment of the impacts of large reservoirs will help promote development strategies that enhance the long-term sustainability of dam projects.

Linkage Between Hourly Precipitation Events and Atmospheric Temperature Changes over China during the Warm Season.

We investigated changes in the temporospatial features of hourly precipitation during the warm season over mainland China. The frequency and amount of hourly precipitation displayed latitudinal zonation, especially for light and moderate precipitation, which showed successive downward change over time in northeastern and southern China. Changes in the precipitation amount resulted mainly from changes in frequency rather than changes in intensity. We also evaluated the linkage between hourly precipitation and temperature variations and found that hourly precipitation extreme was more sensitive to temperature than other categories of precipitation. A strong dependency of hourly precipitation on temperature occurred at temperatures colder than the median daily temperature; in such cases, regression slopes were greater than the Clausius-Clapeyron (C-C) relation of 7% per degree Celsius. Regression slopes for 31.6%, 59.8%, 96.9%, and 99.1% of all stations were greater than 7% per degree Celsius for the 75th, 90th, 99th, and 99.9th percentiles for precipitation, respectively. The mean regression slopes within the 99.9th percentile of precipitation were three times the C-C rate. Hourly precipitation showed a strong negative relationship with daily maximum temperature and the diurnal temperature range at most stations, whereas the equivalent correlation for daily minimum temperature was weak.