An Observation-Based Dataset of Global Sub-Daily Precipitation Indices (GSDR-I)

Precipitation indices based on daily gauge observations are well established, openly available and widely used to detect and understand climate change. However, in many areas of climate science and risk management, it has become increasingly important to understand precipitation characteristics, variability and extremes at shorter (sub-daily) durations. Yet, no unified dataset of sub-daily indices has previously been available, due in large part to the lesser availability of suitable observations. Following extensive efforts in data collection and quality control, this study presents a new global dataset of sub-daily precipitation indices calculated from a unique database of 18,591 gauge time series. Developed together with prospective users, the indices describe sub-daily precipitation variability and extremes in terms of intensity, duration and frequency properties. The indices are published for each gauge where possible, alongside a gridded data product based on all gauges. The dataset will be useful in many fields concerned with variability and extremes in the climate system, as well as in climate model evaluation and management of floods and other risks.

Climatology and changes in hourly precipitation extremes over China during 1970-2018

Sub-daily precipitation extremes could intensify with temperature at a higher rate than the scaling for daily precipitation extremes, posing increasing risks to natural ecosystem and human society in the era of global warming. A systematic investigation of the climatology and spatiotemporal changes in sub-daily precipitation extremes is of paramount importance to inform future precipitation projection as well as to guide climate adaptation. Here, leveraging a newly proposed set of sub-daily extreme precipitation indices, we examine the climatology and changes in hourly precipitation extremes in mainland China across the major river basins during the warm period of 1970-2018. Our results show that the southern and eastern parts of China tend to experience more frequent hourly precipitation extremes with larger intensity, and the Pearl river basin has the most frequent and intense extreme precipitation at hourly timescale. The Southeast and Yangtze river basins and the mainland China as a whole have field significantly increasing trends in average and extreme precipitation intensities as well as in extreme precipitation frequencies. The intensification signals in hourly precipitation extremes of mainland China seem to emerge from internal climate variability around 2010, whereas average precipitation intensity since 1970 could become field significant earlier than 1999. Besides, we note a marked shift in the probability distributions of the extreme indices, with a wetting tendency toward more frequent and more intense precipitation extremes from the 1970-1999 period to the recent two decades in the 21st century. Our findings provide an alternative line of evidence for changes in precipitation extremes at hourly timescale over China and could contribute to societal decision-making for climate adaptation.

Towards Quantifying the Uncertainty in Estimating Observed Scaling Rates

Short-duration precipitation extremes (PE) increase at a rate of around 7%/K explained by the Clausius-Clapeyron relationship. Previous studies show uncertainty in the extreme precipitation-temperature relationship (scaling) due to various thermodynamic/dynamic factors. Here, we show that uncertainty may arise from the choice of data and methods. Using hourly precipitation (PPT) and daily dewpoint temperature (DPT) across 2,905 locations over the United States, we found higher scaling for quality-controlled data, all locations showing positive (median 6.2%/K) scaling, as compared to raw data showing positive (median 5.3%/K) scaling over 97.5% of locations. We found higher scaling for higher measurement precision of PPT (0.25 mm: median 7.8%/K; 2.54 mm: median 6.6%/K). The method that removes seasonality in PPT and DPT gives higher (with seasonality: median 6.2%/K; without seasonality: median 7.2%/K) scaling. Our results demonstrate the importance of quality-controlled, high-precision observations and robust methods in estimating accurate scaling for a better understanding of PE change with warming.

Effects of climate and environmental variance on the performance of a novel peatland-based integrated multi-trophic aquaculture (IMTA) system: Implications and opportunities for advancing research and disruptive innovation post COVID-19 era

Advancing wet peatland 'paludiculture' innovation present enormous potential to sustain carbon-cycles, reduce greenhouse-gas (GHG) gas emissions and to transition communities to low-carbon economies; however, there is limited scientific-evidence to support and enable direct commercial viability of eco-friendly products and services. This timely study reports on a novel, paludiculture-based, integrated-multi-trophic-aquaculture (IMTA) system for sustainable food production in the Irish midlands. This freshwater IMTA process relies on a naturally occurring ecosystem of microalgae, bacteria and duckweed in ponds for managing waste and water quality that is powered by wind turbines; however, as it is recirculating, it does not rely upon end-of-pipe solutions and does not discharge effluent to receiving waters. This constitutes the first report on the effects of extreme weather events on the performance of this IMTA system that produces European perch (Perca fluviatilis), rainbow trout (Oncorhynchus mykiis) during Spring 2020. Sampling coincided with lockdown periods of worker mobility restriction due to COVID-19 pandemic. Observations revealed that the frequency and intensity of storms generated high levels of rainfall that disrupted the algal and bacterial ecosystem in the IMTA leading to the emergence and predominance of toxic cyanobacteria that caused fish mortality. There is a pressing need for international agreement on standardized set of environmental indicators to advance paludiculture innovation that addresses climate-change and sustainability. This study describes important technical parameters for advancing freshwater aquaculture (IMTA), which can be future refined using real-time monitoring-tools at farm level to inform management decision-making based on evaluating environmental indicators and weather data. The relevance of these findings to informing global sustaining and disruptive research and innovation in paludiculture is presented, along with alignment with UN Sustainable Development goals. This study also addresses global challenges and opportunities highlighting a commensurate need for international agreement on resilient indicators encompassing linked ecological, societal, cultural, economic and cultural domains.

The role of cyclonic activity in tropical temperature-rainfall scaling

The attribution of changing intensity of rainfall extremes to global warming is a key challenge of climate research. From a thermodynamic perspective, via the Clausius-Clapeyron relationship, rainfall events are expected to become stronger due to the increased water-holding capacity of a warmer atmosphere. Here, we employ global, 1-hourly temperature and 3-hourly rainfall data to investigate the scaling between temperature and extreme rainfall. Although the Clausius-Clapeyron scaling of +7% rainfall intensity increase per degree warming roughly holds on a global average, we find very heterogeneous spatial patterns. Over tropical oceans, we reveal areas with consistently strong negative scaling (below -40%∘C-1). We show that the negative scaling is due to a robust linear correlation between pre-rainfall cooling of near-surface air temperature and extreme rainfall intensity. We explain this correlation by atmospheric and oceanic dynamics associated with cyclonic activity. Our results emphasize that thermodynamic arguments alone are not enough to attribute changing rainfall extremes to global warming. Circulation dynamics must also be thoroughly considered.

Towards advancing scientific knowledge of climate change impacts on short-duration rainfall extremes

A large number of recent studies have aimed at understanding short-duration rainfall extremes, due to their impacts on flash floods, landslides and debris flows and potential for these to worsen with global warming. This has been led in a concerted international effort by the INTENSE Crosscutting Project of the GEWEX (Global Energy and Water Exchanges) Hydroclimatology Panel. Here, we summarize the main findings so far and suggest future directions for research, including: the benefits of convection-permitting climate modelling; towards understanding mechanisms of change; the usefulness of temperature-scaling relations; towards detecting and attributing extreme rainfall change; and the need for international coordination and collaboration. Evidence suggests that the intensity of long-duration (1 day+) heavy precipitation increases with climate warming close to the Clausius-Clapeyron (CC) rate (6-7% K^-1), although large-scale circulation changes affect this response regionally. However, rare events can scale at higher rates, and localized heavy short-duration (hourly and sub-hourly) intensities can respond more strongly (e.g. 2 × CC instead of CC). Day-to-day scaling of short-duration intensities supports a higher scaling, with mechanisms proposed for this related to local-scale dynamics of convective storms, but its relevance to climate change is not clear. Uncertainty in changes to precipitation extremes remains and is influenced by many factors, including large-scale circulation, convective storm dynamics andstratification. Despite this, recent research has increased confidence in both the detectability and understanding of changes in various aspects of intense short-duration rainfall. To make further progress, the international coordination of datasets, model experiments and evaluations will be required, with consistent and standardized comparison methods and metrics, and recommendations are made for these frameworks. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'.

Challenges and outlook for convection-permitting climate modelling

Climate projections at very high resolution (kilometre-scale grid spacing) are becoming affordable. These 'convection-permitting' models (CPMs), commonly used for weather forecasting, better represent land-surface characteristics and small-scale processes in the atmosphere such as convection. They provide a step change in our understanding of future changes at local scales and for extreme weather events. For short-duration precipitation extremes, this includes capturing local storm feedbacks, which may modify future increases. Despite the major advance CPMs offer, there are still key challenges and outstanding science issues. Heavy rainfall tends to be too intense; there are challenges in representing land-surface processes; sub-kilometre scale processes still need to be parametrized, with existing parametrization schemes often requiring development for use in CPMs; CPMs rely on the quality of lateral boundary forcing and typically do not include ocean-coupling; large CPM ensembles that comprehensively sample future uncertainties are costly. Significant progress is expected over the next few years: scale-aware schemes may improve the representation of unresolved convective updrafts; work is underway to improve the modelling of complex land-surface fluxes; CPM ensemble experiments are underway and methods to synthesize this information with larger coarser-resolution model ensembles will lead to local-scale predictions with more comprehensive uncertainty context for user application. Large-domain (continental or tropics-wide) CPM climate simulations, potentially with additional earth-system processes such as ocean and wave coupling and terrestrial hydrology, are an exciting prospect, allowing not just improved representation of local processes but also of remote teleconnections. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'.

Fingerprint of climate change in precipitation aggressiveness across the central Mediterranean (Italian) area

Rainfall erosivity and its derivative, erosivity density (ED, i.e., the erosivity per unit of rain), is a main driver of considerable environmental damages and economic losses worldwide. This study is the first to investigate the interannual variability, and return periods, of both rainfall erosivity and ED over the Mediterranean for the period 1680–2019. By capturing the relationship between seasonal rainfall, its variability, and recorded hydrological extremes in documentary data consistent with a sample (1981–2015) of detailed Revised Universal Soil Loss Erosion-based data, we show a noticeable decreasing trend of rainfall erosivity since about 1838. However, the 30-year return period of ED values indicates a positive long-term trend, in tandem with the resurgence of very wet days (> 95th percentile) and the erosive activity of rains during the past two decades. A possible fingerprint of recent warming is the occurrence of prolonged wet spells in apparently more erratic and unexpected ways.

PPDIST, global 0.1° daily and 3-hourly precipitation probability distribution climatologies for 1979-2018

We introduce the Precipitation Probability DISTribution (PPDIST) dataset, a collection of global high-resolution (0.1°) observation-based climatologies (1979-2018) of the occurrence and peak intensity of precipitation (P) at daily and 3-hourly time-scales. The climatologies were produced using neural networks trained with daily P observations from 93,138 gauges and hourly P observations (resampled to 3-hourly) from 11,881 gauges worldwide. Mean validation coefficient of determination (R2) values ranged from 0.76 to 0.80 for the daily P occurrence indices, and from 0.44 to 0.84 for the daily peak P intensity indices. The neural networks performed significantly better than current state-of-the-art reanalysis (ERA5) and satellite (IMERG) products for all P indices. Using a 0.1 mm 3 h-1 threshold, P was estimated to occur 12.2%, 7.4%, and 14.3% of the time, on average, over the global, land, and ocean domains, respectively. The highest P intensities were found over parts of Central America, India, and Southeast Asia, along the western equatorial coast of Africa, and in the intertropical convergence zone. The PPDIST dataset is available via www.gloh2o.org/ppdist .

Overview of Observed Clausius-Clapeyron Scaling of Extreme Precipitation in Midlatitudes

This paper presents an overview of recent observational studies on the Clausius-Clapeyron precipitation-temperature (P-T) scaling in midlatitudes. As the capacity of air to hold moisture increases in connection with increasing temperature, extreme precipitation events may become more abundant and intense. The capacity of air to hold moisture is governed by the Clausius-Clapeyron (CC) relation, approximately 7% per °C. Departures from this, so called super-CC scaling and sub-CC scaling, are consequences of different factors (moisture availability, type of precipitation, annual cycle, the percentile of precipitation intensity and regional weather patterns). Since the moisture availability and enhanced convection were considered as the most important drivers governing the P-T scaling, dew point temperature as a scaling variable is discussed in detail and methods of disaggregation of precipitation events into convective and non-convective are also reviewed.

Europe-wide precipitation projections at convection permitting scale with the Unified Model

For the first time, we analyze 2.2 km UK Met Office Unified Model convection-permitting model (CPM) projections for a pan-European domain. These new simulations represent a major increase in domain size, allowing us to examine the benefits of CPMs across a range of European climates. We find a change to the seasonality of extreme precipitation with warming. In particular, there is a relatively muted response for summer, which contrasts with much larger increases in autumn and winter. This flattens the hourly extreme precipitation seasonal cycle across Northern Europe which has a summer peak in the present climate. Over the Western Mediterranean, where autumn is the main extreme precipitation season, there is a regional increase in hourly extreme precipitation frequency, but local changes for lower precipitation thresholds are often insignificant. For mean precipitation, decreases are projected across Europe in summer, smaller decreases in autumn, and increases in winter; comparable changes are seen in the driving general circulation model (GCM) simulations. The winter mean increase is accompanied by a large decrease of winter mean snowfall. Comparing the driving GCM projections with the CPM ones, the CPMs show a robust enhanced intensification of precipitation extremes at the convection-permitting scale compared to coarser resolution climate model projections across various European regions for summer and autumn.

UKGrsHP: a UK high-resolution gauge-radar-satellite merged hourly precipitation analysis dataset

There is an urgent need for high-quality and high-spatial-resolution hourly precipitation products around the globe, including the UK. Although hourly precipitation products exist for the UK, these either contain large errors, or are insufficient in spatial resolution. An efficient way to solve this is to develop a merged precipitation product that combines the information and benefits from multiple data sources, improving both the spatial resolution and accuracy of hourly precipitation estimates over the UK. In this study, we develop a UK high-resolution gauge-radar-satellite merged hourly precipitation analysis: the UKGrsHP. It covers the UK from 12.5° W to  3.5° E, 49° N-60° N, with a spatial resolution of 0.01° × 0.01° in latitude/longitude (equivalent to 1 km resolution in the mid-latitudes). An optimal interpolation (OI)-based multi-source merging scheme with compound strategy is developed and tested for producing the UKGrsHP. Three input data sources are used: gauge analysis data interpolated from 1903 quality-controlled hourly observations, the UK Nimrod radar precipitation analysis and the GSMaP global satellite precipitation analysis. Using independent tests against ~ 220 independent gauge observations on 1 year's experimental UKGrsHP, covering the period from January to December 2014, we find that the final merged data performs better than three individual precipitation analyses used as inputs. A full version of the UKGrsHP starting in April 2004 is now under production, which will have wide applications in climate services and scientific research across multiple disciplines.

Synoptic-Scale Precursors of Extreme U.K. Summer 3-Hourly Rainfall

The synoptic-scale meteorological conditions leading up to the 30 most extreme subdaily summer rain events for two regions of the United Kingdom (northwest and southeast) were examined for the period 1979-2013. Using a recently available, quality controlled, national hourly rain gauge data set, we were able to identify extreme 3-hr rainfall accumulations that may be indicative of flash flooding. Composites of the state of the atmosphere leading up to these dates were produced to investigate synoptic-scale processes, thus potentially allowing for them to be identified in coarse resolution reanalyses and in climate models. The results show that the two regions have different dominant synoptic-scale conditions leading to extreme 3-hr rainfall, which is thought to be related to the type of rainfall typically experienced in each region. In particular, positive anomalies in mean sea level pressure and the geopotential height at 200 hPa over the United Kingdom are associated with extreme rainfall in the northwest, where the position of the westerly jet is also important. For the southeast, no clear anomalous synoptic-scale conditions could be identified; however, localized moisture sources and unstable air masses were observed in association with extremes. These results indicate the importance of better understanding of both synoptic-scale and thermodynamic drivers of short-duration extreme rainfall, with potential implications in forecasting and flood warning, as well as for understanding the representation of key processes by regional climate models.