Using global station‐based observations of precipitation, near‐surface air temperature (SAT), and dew point temperature (DPT), we show that the negative scaling relationship found between extreme ...daily precipitation and SAT over the tropics is associated with the low seasonality in temperature. When using a binning technique or quantile regression, not accounting for seasonality in temperature produces a negative scaling for the majority of stations in the tropics, with higher temperatures associated with smaller precipitation extremes. After removing temperature seasonality, we find that most locations show a positive (median 5.2%/K) scaling with SAT and 96% of global locations exhibit positive (median 6.1%/K) scaling with DPT. Moreover, about 33% (22%) of the locations show super C‐C scaling (higher than 7%/K) with DPT (SAT). Our results show that the impact of warming on extreme precipitation (especially over the tropics) may be higher than previously thought.
Plain Language Summary
Extreme precipitation events have increased during the recent decades and are likely to increase under the warming climate. Understanding the role of changes in air temperature on extreme precipitation events is important for the risk assessment and planning of infrastructure. Using station‐based observations of precipitation, air temperature, and dew point temperature, we show that precipitation extremes increase with the rise of local temperature in the majority of regions. However, precipitation extremes are negatively correlated with surface air temperature over the tropics mainly due to the effect of seasonality and relative humidity. We show that the dew point temperature is a more robust indicator of changes in precipitation extremes in comparison to surface air temperature.
Key Points
We establish the relationship between SAT and DPT with precipitation extremes
The negative scaling between precipitation extremes and temperature over the tropics is associated with low seasonality
Conditional quantile methods (binning and quantile regression) should be applied after considering seasonality for the scaling estimates
A flood forecasting system commonly consists of at least two essential components, that is, a numerical weather prediction (NWP) model to provide rainfall forecasts and a hydrological/hydraulic model ...to predict the hydrological response. While being widely used for flood forecasting, hydrological models only provide a simplified representation of the physical processes of flooding due to negligence of strict momentum conservation. They cannot reliably predict the highly transient flooding process from intense rainfall, in which case a fully 2‐D hydrodynamic model is required. Due to high computational demand, hydrodynamic models have not been exploited to support real‐time flood forecasting across a large catchment at sufficiently high resolution. To fill the current research and practical gaps, this work develops a new forecasting system by coupling a graphics processing unit (GPU) accelerated hydrodynamic model with NWP products to provide high‐resolution, catchment‐scale forecasting of rainfall‐runoff and flooding processes induced by intense rainfall. The performance of this new forecasting system is tested and confirmed by applying it to “forecast” an extreme flood event across a 2,500‐km2 catchment at 10‐m resolution. Quantitative comparisons are made between the numerical predictions and field measurements in terms of water level and flood extent. To produce simulation results comparing well with the observations, the new flood forecasting system provides 34 hr of lead time when the weather forecasts are available 36 hr beforehand. Numerical experiments further confirm that uncertainties from the rainfall inputs are not amplified by the hydrodynamic model toward the final flood forecasting outputs in this case.
Key Points
A high‐resolution, real‐time flood forecasting system is developed based on a hydrodynamic model and numerical weather forecasts
Catchment‐scale flood simulation is achieved using a fully 2‐D hydrodynamic model accelerated by multiple GPUs
The forecasting system is successfully applied to “forecast” an extreme event in a 2,500‐km2 domain with a lead time of 34 hr
Globally, thermodynamics explains an increase in atmospheric water vapor with warming of around 7%/°C near to the surface. In contrast, global precipitation and evaporation are constrained by the ...Earth's energy balance to increase at ∼2–3%/°C. However, this rate of increase is suppressed by rapid atmospheric adjustments in response to greenhouse gases and absorbing aerosols that directly alter the atmospheric energy budget. Rapid adjustments to forcings, cooling effects from scattering aerosol, and observational uncertainty can explain why observed global precipitation responses are currently difficult to detect but are expected to emerge and accelerate as warming increases and aerosol forcing diminishes. Precipitation increases with warming are expected to be smaller over land than ocean due to limitations on moisture convergence, exacerbated by feedbacks and affected by rapid adjustments. Thermodynamic increases in atmospheric moisture fluxes amplify wet and dry events, driving an intensification of precipitation extremes. The rate of intensification can deviate from a simple thermodynamic response due to in‐storm and larger‐scale feedback processes, while changes in large‐scale dynamics and catchment characteristics further modulate the frequency of flooding in response to precipitation increases. Changes in atmospheric circulation in response to radiative forcing and evolving surface temperature patterns are capable of dominating water cycle changes in some regions. Moreover, the direct impact of human activities on the water cycle through water ion, irrigation, and land use change is already a significant component of regional water cycle change and is expected to further increase in importance as water demand grows with global population.
Societies experience impacts through localized changes in water availability that are controlled by large‐scale atmospheric circulation as well as smaller‐scale physical processes. At regional to local scales, water cycle changes therefore result from the interplay between multiple drivers (CO2, aerosols, land use change and human water use). A primary focus here is on reviewing recent advances in understanding how these complex interactions are expected to determine responses in the global water cycle.
As climate change research becomes increasingly applied, the need for actionable information is growing rapidly. A key aspect of this requirement is the representation of uncertainties. The ...conventional approach to representing uncertainty in physical aspects of climate change is probabilistic, based on ensembles of climate model simulations. In the face of deep uncertainties, the known limitations of this approach are becoming increasingly apparent. An alternative is thus emerging which may be called a ‘storyline’ approach. We define a storyline as a physically self-consistent unfolding of past events, or of plausible future events or pathways. No a priori probability of the storyline is assessed; emphasis is placed instead on understanding the driving factors involved, and the plausibility of those factors. We introduce a typology of four reasons for using storylines to represent uncertainty in physical aspects of climate change: (i) improving risk awareness by framing risk in an event-oriented rather than a probabilistic manner, which corresponds more directly to how people perceive and respond to risk; (ii) strengthening decision-making by allowing one to work backward from a particular vulnerability or decision point, combining climate change information with other relevant factors to address compound risk and develop appropriate stress tests; (iii) providing a physical basis for partitioning uncertainty, thereby allowing the use of more credible regional models in a conditioned manner and (iv) exploring the boundaries of plausibility, thereby guarding against false precision and surprise. Storylines also offer a powerful way of linking physical with human aspects of climate change.
ABSTRACT
Sub‐daily rainfall extremes may be associated with flash flooding, particularly in urban areas but, compared with extremes on daily timescales, have been relatively little studied in many ...regions. This paper describes a new, hourly rainfall dataset for the UK based on ∼1600 rain gauges from three different data sources. This includes tipping bucket rain gauge data from the UK Environment Agency (EA), which has been collected for operational purposes, principally flood forecasting. Significant problems in the use of such data for the analysis of extreme events include the recording of accumulated totals, high frequency bucket tips, rain gauge recording errors and the non‐operation of gauges. Given the prospect of an intensification of short‐duration rainfall in a warming climate, the identification of such errors is essential if sub‐daily datasets are to be used to better understand extreme events. We therefore first describe a series of procedures developed to quality control this new dataset. We then analyse ∼380 gauges with near‐complete hourly records for 1992–2011 and map the seasonal climatology of intense rainfall based on UK hourly extremes using annual maxima, n‐largest events and fixed threshold approaches. We find that the highest frequencies and intensities of hourly extreme rainfall occur during summer when the usual orographically defined pattern of extreme rainfall is replaced by a weaker, north–south pattern. A strong diurnal cycle in hourly extremes, peaking in late afternoon to early evening, is also identified in summer and, for some areas, in spring. This likely reflects the different mechanisms that generate sub‐daily rainfall, with convection dominating during summer. The resulting quality‐controlled hourly rainfall dataset will provide considerable value in several contexts, including the development of standard, globally applicable quality‐control procedures for sub‐daily data, the validation of the new generation of very high‐resolution climate models and improved understanding of the drivers of extreme rainfall.
The question of when the influence of climate change on U.K. rainfall extremes may be detected is important from a planning perspective, providing a time scale for necessary climate change adaptation ...measures. Short-duration intense rainfall is responsible for flash flooding, and several studies have suggested an amplified response to warming for rainfall extremes on hourly and subhourly time scales. However, there are very few studies examining the detection of changes in subdaily rainfall. This is due to the high cost of very high-resolution (kilometer scale) climate models needed to capture hourly rainfall extremes and to a lack of sufficiently long, high-quality, subdaily observational records. Results using output from a 1.5-km climate model over the southern United Kingdom indicate that changes in 10-min and hourly precipitation emerge before changes in daily precipitation. In particular, model results suggest detection times for short-duration rainfall intensity in the 2040s in winter and the 2080s in summer, which are, respectively, 5–10 years and decades earlier than for daily extremes. Results from a new quality-controlled observational dataset of hourly rainfall over the United Kingdom do not show a similar difference between daily and hourly trends. Natural variability appears to dominate current observed trends (including an increase in the intensity of heavy summer rainfall over the last 30 years), with some suggestion of larger daily than hourly trends for recent decades. The expectation of the reverse, namely, larger trends for short-duration rainfall, as the signature of underlying climate change has potentially important implications for detection and attribution studies.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Although observations and modeling studies show that heavy rainfall is increasing in many regions, how changes will manifest themselves on sub‐daily timescales remains highly uncertain. Here, for the ...first time, we combine observational analysis and high‐resolution modeling results to examine changes to extreme rainfall intensities in urbanized Kuala Lumpur, Malaysia. We find that hourly intensities of extreme rainfall have increased by ~35% over the last three decades, nearly 3 times more than in surrounding rural areas, with daily intensities showing much weaker increases. Our modeling results confirm that the urban heat island effect creates a more unstable atmosphere, increased vertical uplift and moisture convergence. This, combined with weak surface winds in the Tropics, causes intensification of rainfall extremes over the city, with reduced rainfall in the surrounding region.
Plain Language Summary
Major floods and rainfall‐related impacts are often caused by short‐duration heavy rainfall events. Although there is evidence of cities modifying rainfall in many urban areas, uncertainties still exist around their role in intense rainfall episodes. We investigate the impact of the growth of Kuala Lumpur (Malaysia) on intense rainfall using observations and modeling experiments. We find that over the last three decades hourly rainfall events have become more intense over the city than surrounding rural areas. Our modeling experiments support this finding and help us understand mechanisms behind the intensification. The relative warmth of the city with respect to its surroundings contributes to the increase. The city creates a low‐level anomaly of warm and dry air that then rises. To compensate for this, the moist surrounding air is brought into the urban area and lifted upward. This feeds the air above the city with moisture and sustains a local circulation initiated by the relative warmth of the urban area. We find that the city's influence on extreme rainfall is located over the urban area itself, as opposed to other studies that have detected a footprint downwind. This is likely due to the typical calm background wind conditions in the tropics.
Key Points
Observed hourly rainfall extremes have intensified more in urban Kuala Lumpur than the surrounding rural areas over the last three decades
Convection‐modeling experiments provide further support that this intensification comes from urbanization, providing physical mechanisms
Urbanization increases the potential future risk of urban flash flooding in tropical regions
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