Orographic Enhancement Research Articles

Orographic Controls on Extreme Precipitation Associated with a Mei-Yu Front

Abstract Taiwan regularly receives extreme rainfall due to seasonal mei-yu fronts that are modified by Taiwan’s complex topography. One such case occurred between 1 and 3 June 2017 when a mei-yu front contributed to flooding and landslides from over 600 mm of rainfall in 12 h near the Taipei basin, and over 1500 mm of rainfall in 2 days near the Central Mountain Range (CMR). This mei-yu event is simulated using the Weather Research and Forecasting (WRF) Model with halved terrain as a sensitivity test to investigate the orographic mechanisms that modify the intensity, duration, and location of extreme rainfall. The reduction in WRF terrain height produced a decrease in rainfall duration and accumulation in northern Taiwan and a decrease in rainfall duration, intensity, and accumulation over the CMR. The reductions in northern Taiwan are linked to a weaker orographic barrier jet resulting from a lowered terrain height. The reductions in rainfall intensity and duration over the CMR are partially explained by a lack of orographic enhancements to mei-yu frontal convergence near the terrain. A prominent feature missing with the reduced terrain is a redirection of postfrontal westerly winds attributed to orographic deformation, i.e., the redirection of flow due to upstream topography. Orographically deforming winds converge with prefrontal flow to maintain the mei-yu front. In both regions, the decrease in mei-yu front propagation speed is linked to increased rainfall duration. These orographic features will be further explored using observations captured during the 2022 Prediction of Rainfall Extremes Campaign in the Pacific (PRECIP) field campaign. Significance Statement This study examines the impact of terrain on rainfall intensity, duration, and location. A mei-yu front, an East Asian weather front known for producing heavy, long-lasting rainfall, was simulated for an extreme rain event in Taiwan with mountain heights halved as a sensitivity test. Reducing terrain decreased rainfall duration in northern and central Taiwan. Decreases in rainfall duration for both regions is attributed to increased mei-yu front propagation speed. This increase in northern Taiwan is attributed to a weakened barrier jet, a low-level jet induced by flow blocked by the steep mountains of Taiwan. A unique finding of this work is a change in winds north of the front controlling movement of the front near the mountains in central Taiwan.

Dual-Polarimetric Radar Applications for Investigating Severe Thunderstorms in Northern Thailand during the Pre-Monsoon Season

Understanding the physical characteristics of severe pre-monsoon thunderstorms is crucial for mitigating the adverse impacts of natural disasters on people in tropical regions. On April 23, 2020, a severe storm affected the Chiang Khong District of the Chiang Rai Province in Northern Thailand, causing devastation to more than 500 houses with hail and strong winds. This study investigated the storm's physical characteristics using dual-polarimetric radar data from the Thai Meteo-rological Department (TMD). Using a combination of polarimetric radar variables, such as reflectivity (ZH), specific differential phase (KDP), differential reflectivity (ZDR), and copolar correlation coefficient (ρhv), fuzzy logic was utilized to classify the hydrometeor types. During the severe storm that affected the Chiang Khong District, hail and large raindrops were mixed in with the rain, according to the analysis. Two severe storms were observed in the unorganized mesoscale convective systems that were analyzed, with the second storm producing more intense effects due to the radar reflectivity shape of a bow echo that generated strong wind gusts. The Doppler radar data retrieved the wind field, indicating the convergence of intense local winds during the storm, which was consistent with the analysis results of synoptic-scale weather systems from ECMWF Reanalysis v5 (ERA5). In addition, a Hovmöller diagram revealed orographic enhancement of the convective cloud as the storm passed through mountainous regions prior to approaching the Chiang Khong District. The findings of this study can provide valuable information for TMD's near-real-time warning operation in order to minimize loss of life and property from future severe storms.

Abrupt drought termination in the British–Irish Isles driven by high atmospheric vapour transport

During protracted dry spells, there is considerable interest from water managers, media and the public in when and how drought termination (DT) will occur. Robust answers to these questions require better understanding of the hydroclimatic drivers of DT than currently available. Integrated vapour transport (IVT) has been found to drive DT in Western North America, but evidence elsewhere is lacking. To evaluate this association for the British–Irish Isles, event coincidence analysis is applied to 354 catchments in the UK and Ireland over the period 1900–2010 using ERA-20C reanalysis IVT data and 7589 DT events extracted from reconstructed river flow series. Linkages are identified for 53% of all DT events across all catchments. Associations are particularly strong for catchments in western and southern regions and in autumn and winter. In Western Scotland, 80% of autumn DTs are preceded by high IVT, whilst in Southern England more than two thirds of winter DTs follow high IVT episodes. High IVT and DT are most strongly associated in less permeable, wetter upland catchments of Western Britain, reflecting their maritime setting and orographic enhancement of prevailing south-westerly high IVT episodes. Although high IVT remains an important drought-terminating mechanism further east, it less frequently results in DT. Furthermore, the highest rates of DT occur with increasing IVT intensity, and the vast majority of the most abrupt DTs only occur following top decile IVT and under strongly positive North Atlantic Oscillation (NAO) conditions. Since IVT and NAO forecasts may be more skilful than those for rainfall which underpin current forecasting systems, incorporating these findings into such systems has potential to underpin enhanced forecasting of DTs. This could help to mitigate impacts of abrupt recoveries from drought including water quality issues and managing compound drought–flood hazards concurrently.

Scale Dependence of Errors in Snow Water Equivalent Simulations Using ERA5 Reanalysis over Alpine Basins

This study aims to evaluate the potential of ERA5 precipitation and temperature reanalysis for snow water equivalent (SWE) simulation by considering the role of catchment spatial scale in controlling the errors obtained by comparison with corresponding SWE simulations from ground stations. This is obtained by exploiting a semi-distributed snowpack model (TOPMELT) implemented over the upper Adige River basin in the Eastern Italian Alps, where 16 sub-catchments of varying sizes are considered. The comparison is carried out from 1992 to 2019. The findings show that ERA5 precipitation overestimated low-intensity rainfall (drizzle problem) and underestimated high-intensity rainfall, while ERA5 temperature underestimated observations. The overestimation of low-intensity rainfall created fictitious low-intensity snowfall events, which, when combined with colder ERA5 temperature, resulted in delayed snowmelt and increased fictitious snow-cover days over the study area. The quantile mapping (QM) technique was used to remove errors in ERA5 variables. It was shown that ERA5 could struggle to resolve the orographic enhancement in precipitation, which may be particularly important during high-SWE years. This reduces the positive precipitation bias during those years, thus reducing comparatively the ability of the quantile mapping technique to correct for bias homogeneously during all years. This study highlighted the importance of temperature correction over precipitation correction in SWE simulation, particularly for smaller basins.

Does the Sierra Madre Mountain Range in Luzon Act as a Barrier to Typhoons?

Tropical cyclones (TCs) making landfall in Luzon weaken due to the surface friction of Luzon’s mountainous terrain and the reduced ocean heat, momentum, and moisture fluxes over the landmass. Landmass also influences TC rain distribution by orographic enhancement or blocking of a TC’s moisture-laden circulation. In this study, we investigated the influence of the effects of the Sierra Madre and the Cordillera Mountains Ranges (SMMR and CMR) on TC-associated wind and rainfall hazards to answer the question of whether the SMMR or the CMR mitigates TC hazards. We used the Weather Research and Forecasting (WRF) model with modified SMMR and CMR terrains to disentangle the effects of the orography with flat land. Results show that Luzon-passing TCs maintain their intensities at landfall regardless of the frictional effects of the mountain ranges but the CMR inhibits the re-intensification of westward-moving TCs emerging from landmass after traversing Luzon. The SMMR reduces wind exposure and basin-wide rainfall of the Cagayan Valley. Hence, the SMMR can be considered a barrier for that region. In addition, the weakening effect of the SMMR reduces the wind exposure of the island of Catanduanes and eastern Bicol the most. However, for the rest of Luzon, the SMMR enhances rainfall which will likely compensate for the slight decrease in wind exposure – especially considering that most TC-related damages are water/rainfall related. The CMR, overall, has a larger hazard-mitigating effect than the SMMR. In any case, we believe that shifting the discourse to these mountains’ biodiversity conservation and restoration – rather than their purported TC mitigating effects – will be more strategically constructive.

Aerosol indirect effects on orographic clouds and precipitation

The sensitivity of warm orographic cloud development to aerosol indirect effects was investigated through aerosol-aware Weather Research and Forecast model simulations contrasting aerosol-cloud-precipitation interactions using the default (generic) aerosol and regional aerosol measurements from the Integrated Precipitation and Hydrology Experiment in the Southern Appalachian Mountains for three rainfall events: 1) enhanced local convection; 2) a frontal system, and 3) a tropical system. Using the regional aerosol activation spectrum yields higher number of drops than using the default, smaller cloud droplets and delayed rainfall onset under weak synoptic forcing conditions. Evaluation against aircraft measurements in isolated convective clouds reveals that while the model microphysics falls short of reproducing the vertical structure of nonprecipitating clouds, the liquid water content, and the concentration of cloud droplets near cloud base are in keeping with observations. The simulated cloud vertical structure shows the regional signature of orographic enhancement over the mountains vis-a-vis the adjacent plains. In the inner region, valley-ridge circulations organize the spatial patterns of cloudiness under weak synoptic forcing. The formation of early afternoon low-level clouds over the ridges in the summertime reflects the aerosol indirect effect. By contrast, for large-scale systems with strong and sustained moisture convergence at low levels (frontal and tropical systems), mechanically forced rainfall efficiency is enhanced, there is no delay in the onset of precipitation, and the aerosol indirect effect is negligible. This study shows that the impact of aerosol-cloud-precipitation interactions on the spatial variability of orographic rainfall is conditional on weather regime.

Application of Machine Learning Techniques to Improve Multi-Radar Multi-Sensor (MRMS) Precipitation Estimates in the Western United States

Abstract The Multi-Radar Multi-Sensor (MRMS) system produces a suite of hydrometeorological products that are widely used for applications such as flash flood warning operations, water resource management, and climatological studies. The MRMS radar-based quantitative precipitation estimation (QPE) products have greater challenges in the western United States compared to the eastern two-thirds of the CONUS due to terrain-related blockages and gaps in radar coverage. Further, orographic enhancement of precipitation often occurs, which is highly variable in space and time and difficult to accurately capture with physically based approaches. A deep learning approach was applied in this study to understand the correlations between several interacting variables and to obtain a more accurate precipitation estimation in these scenarios. The model presented here is a convolutional neural network (CNN), which uses spatial information from small grids of several radar variables to predict an estimated precipitation value at the central grid point. Several case analyses are presented along with a yearlong statistical evaluation. The CNN model 24-h QPE shows higher accuracy than the MRMS radar QPE for several cool season atmospheric river events. Areas of consistent improvement from the CNN model are highlighted in the discussion along with areas where the model can be further improved. The initial findings from this work help set the foundation for further exploration of machine learning techniques and products for precipitation estimation as part of the MRMS operational system. Significance Statement This study explores the development and use of a deep learning model to generate precipitation fields in the complex terrain of the western United States. Generally, the model is able to improve on the statistical performance of existing radar-based precipitation estimation methods for several case studies and over a long-term period in 2021. We explore the patterns associated with certain areas of strong performance and suggest potential means of improving areas with weaker performance. These initial results indicate the potential of deep learning to supplement radar-based approaches in areas with observational limitations.

Extreme precipitation records in Antarctica

AbstractMonitoring extreme precipitation records (EPRs), that is, the most extreme precipitation events, is a challenge in Antarctica due to the reduced number of stations available in the continent and the limitations of the instrumentation for measuring solid precipitation. Still, extreme precipitation events may contribute substantially to the variability of ice sheet snow accumulation and even may cause important ecological impacts. This article presents the Antarctic EPRs at different temporal scales, studying the relationship between precipitation amount and temporal duration through a power scaling law, ranging from 1 day to 2 years. This is achieved using precipitation datasets from the ERA5 reanalysis and the RACMO2 regional climate model. Moreover, we present a selection of EPRs case studies examining the synoptic mechanisms that produce such events in Antarctica. Despite ERA5 EPRs are usually lower than those found in RACMO2, they present similar scaling exponents. EPRs are found in Loubet and south Graham Coasts, in the central section of the Antarctic Peninsula, and in the north of Alexander Island, where orographic enhancement increases precipitation amounts. As expected, Antarctic EPRs are much lower than world‐wide EPRs, ranging from 6 to 10% at short temporal scales (from 1 to 10 days) and from 10 to 20% at long temporal scales (from 90 days to 2 years) in ERA5. Regional variability of extreme precipitation scaling exponents show similar spatial patterns than previously calculated precipitation concentration. On the other hand, the lack of summer events in Antarctic EPRs evidences that stronger fluxes in winter play a key role on extreme precipitation during EPR events, which are mainly produced by long‐range transport of moisture by atmospheric rivers impinging on Antarctic mountains.

Performance of New Near-Real-Time PERSIANN Product (PDIR-Now) for Atmospheric River Events over the Russian River Basin, California

Abstract Most heavy precipitation events and extreme flooding over the U.S. Pacific coast can be linked to prevalent atmospheric river (AR) conditions. Thus, reliable quantitative precipitation estimation with a rich spatiotemporal resolution is vital for water management and early warning systems of flooding and landslides over these regions. At the same time, high-quality near-real-time measurements of AR precipitation remain challenging due to the complex topographic features of land surface and meteorological conditions of the region: specifically, orographic features occlude radar measurements while infrared-based algorithms face challenges, differentiating between both cold brightband (BB) precipitation and the warmer nonbrightband (NBB) precipitation. It should be noted that the latter precipitation is characterized by greater orographic enhancement. In this study, we evaluate the performance of a recently developed near-real-time satellite precipitation algorithm: Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) Dynamic Infrared–Rain Rate-Now (PDIR-Now). This model is primarily dependent on infrared information from geostationary satellites as input; consequently, PDIR-Now has the advantage of short data latency, 15–60-min delay between observation to precipitation product delivery. The performance of PDIR-Now is analyzed with a focus on AR-related events for cases dominated by NBB and BB precipitation over the Russian River basin. In our investigations, we utilize S-band (3-GHz) precipitation profilers with Joss/Parsivel disdrometer measurements at the Middletown and Santa Rosa stations to classify BB and NBB precipitation events. In general, our analysis shows that PDIR-Now is more skillful in retrieving precipitation rates over both BB and NBB events across the topologically complex study area as compared to PERSIANN-Cloud Classification System (CCS). Also, we discuss the performance of well-known operational near-real-time precipitation products from 2017 to 2019. Conventional categorical and volumetric categorical indices, as well as continuous statistical metrics, are used to show the differences between various high-resolution precipitation products such as Multi-Radar Multi-Sensor (MRMS).

Orographic Effects on Landfalling Lake-Effect Systems

Abstract Landfalling lake- and sea-effect (hereafter lake-effect) systems often interact with orography, altering the distribution and intensity of precipitation, which frequently falls as snow. In this study, we examine the influence of orography on two modes of lake-effect systems: long-lake-axis-parallel (LLAP) bands and broad-coverage, open-cell convection. Specifically, we generate idealized large-eddy simulations of a LLAP band produced by an oval lake and broad-coverage, open-cell convection produced by an open lake (i.e., without flanking shorelines) with a downstream coastal plain, 500-m peak, and 2000-m ridge. Without terrain, the LLAP band intersects a coastal baroclinic zone over which ascent and hydrometeor mass growth are maximized, with transport and fallout producing an inland precipitation maximum. The 500-m peak does not significantly alter this structure, but slightly enhances precipitation due to orographic ascent, increased hydrometeor mass growth, and reduced subcloud sublimation. In contrast, a 2000-m ridge disrupts the band by blocking the continental flow that flanks the coastlines. This, combined with differential surface heating between the lake and land, leads to low-level flow reversal, shifting the coastal baroclinic zone and precipitation maximum offshore. In contrast, the flow moves over the terrain in open lake, open-cell simulations. Over the 500-m peak, this yields an increase in the frequency of weaker (<1 m s−1) updrafts and weak precipitation enhancement, although stronger updrafts decline. Over the 2000-m ridge, however, buoyancy and convective vigor increase dramatically, contributing to an eightfold increase in precipitation. Overall, these results highlight differences in the influence of orography on two common lake-effect modes. Significance Statement Landfalling lake- and sea-effect snowstorms frequently interact with hills, mountains, and upland regions, altering the distribution and intensity of snowfall. Using high-resolution numerical modeling with simplified lake shapes and terrain features, we illustrate how terrain features affect two common types of lake-effect storms and why long-lake-axis-parallel (LLAP) bands can feature high precipitation rates but weaker orographic enhancement than broad-coverage, open-cell convection.

Multiscale Interactions Contributing to Enhanced Orographic Precipitation in Landfalling Frontal Systems over the Olympic Peninsula

Abstract Orographic precipitation results from complex interactions between terrain, large-scale flow, turbulent motions, and microphysical processes. This study appeals to polarimetric radar data in conjunction with surface-based disdrometer observations, airborne particle probes, and reanalysis data to study these processes and their interactions as observed during the Olympic Mountain Experiment (OLYMPEX). Radar and disdrometer observations from OLYMPEX, which was conducted over the Olympic Peninsula in the winter of 2015, revealed 3 times as much rain fell over elevated sites compared to those along the ocean and coast. Several events were marked by significant water vapor transport and strong onshore flow. Detailed analysis of four cases demonstrated that the warm sector, which previous authors noted to be a period of strong orographic enhancement over the terrain, is associated not only with deeper warm cloud regions, but also deeper cold cloud regions, with the latter supporting the growth of dendritic ice crystals between 4 and 6 km. This dendritic growth promotes enhanced aggregation just above the melting layer, which then seeds the warm cloud layer below, allowing additional drop growth via coalescence. Periods of subsynoptic variability associated with mesoscale boundaries and low-level jets are shown to locally modify both the ice microphysics as well as surface drop-size distributions. This study explores the spatial and temporal variability of precipitation, cloud microphysics, and their relationship over the complex terrain of the Olympic Peninsula. Significance Statement This study appeals to polarimetric radar, aircraft particle probes, disdrometer data, and reanalysis to investigate the complex interactions between large frontal systems, terrain, and microphysical processes contributing to precipitation characteristics at the surface over the Olympic Peninsula. The study finds that the precipitation is a complex function of the synoptic regime, distance inland, and terrain height. Ice microphysical processes aloft act to modulate the surface rain drop size distributions, and are more important in contributing to higher rain accumulations inland during the later phases of the warm sector, particularly over the middle terrain heights (100–500 m).

Quality Control Impacts on Total Precipitation Gauge Records for Montane Valley and Ridge Sites in SW Alberta, Canada

This paper presents adjustment routines for Geonor totalizing precipitation gauge data collected from the headwaters of the Oldman River, within the southwestern Alberta Canadian Rockies. The gauges are situated at mountain valley and alpine ridge locations with varying degrees of canopy cover. These data are prone to sensor noise and environment-induced measurement errors requiring an ordered set of quality control (QC) corrections using nearby weather station data. Sensor noise at valley sites with single-vibrating wire gauges accounted for the removal of 5% to 8% (49–76 mm) of annual precipitation. This was compensated for by an increase of 6% to 8% (50–76 mm) from under-catch. A three-wire ridge gauge did not experience significant sensor noise; however, the under-catch of snow resulted in 42% to 52% (784–1342 mm) increased precipitation. When all QC corrections were applied, the annual cumulative precipitation at the ridge demonstrated increases of 39% to 49% (731–1269 mm), while the valley gauge adjustments were −4% to 1% (−39 mm to 13 mm). Public sector totalizing precipitation gauge records often undergo minimal QC. Care must be exercised to check the corrections applied to such records when used to estimate watershed water balance or precipitation orographic enhancement. Systematic errors at open high-elevation sites may exceed nearby valley or forest sites.

A characterization of clouds over the Great Barrier Reef and the role of local forcing

AbstractA characterization of cloud properties associated with precipitation in the region around the Great Barrier Reef (GBR) is constructed using decade‐long (2007–2017) satellite observations from Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) combined with CloudSat. The spatial and vertical distributions of low‐level cloud properties over the region are also investigated and discussed. In general, different cloud types are observed over different regions and vary by season: high clouds are dominant over the low latitudes in summer, altocumulus are mainly observed over northeast Queensland and low‐level clouds are dominant over the ocean and coast during the winter months at higher latitudes under a trade wind regime. A strong latitudinal dependence of total precipitation across the Greater GBR region is identified with a significant orographic enhancement near Cairns in the wet tropics. MODIS and CloudSat‐CALIPSO cloud observations show good agreement on significant differences in low‐level cloud microphysical properties between the land and the ocean. The largest land–ocean differences in warm cloud microphysical properties are found over the mid‐latitudes near 18°S, which is strongly associated with orographic forcing, with these enhancements extending further east to the coral reef area. However, the frequency of warm cloud is not enhanced upwind of the mountains in the wet tropics. In addition, no significant differences in warm cloud properties between the actual GBR and the open ocean are identified. These results suggest that low‐level clouds over the GBR do not show any significant response to the reef‐related microphysical perturbations.

Precipitation Estimates and Orographic Gradients Using Snow, Temperature, and Humidity Measurements From a Wireless‐Sensor Network

AbstractThis study reports on a blending approach using snowpack measurements from a wireless‐sensor network, gauge precipitation, and atmospheric‐moisture data to estimate mountain precipitation amount and phase. We applied the approach in California's American River basin, using dense measurements from a network consisting of over 130 sensor nodes distributed across the upper, more snow‐dominated part of the basin (≥1,500 m elevation). Analysis of 60 precipitation events in water years 2014–2017 showed that the approach provides estimates of precipitation and orographic enhancement that reduce uncertainty from apparent snow undercatch by limited gauges. This approach also infers total precipitation based on snow measurements during rain‐on‐snow events. The sensor network and blending approach yielded median upper‐basin orographic precipitation gradients (OPGs) of 0.57 km−1, smaller than the also‐positive lower‐basin (<1,500 m) medians OPGs from precipitation gauges and a gauge‐based gridded data set of 1.23 and 1.00 km−1, respectively. However, during 73% of the events, both gauges and the gridded product showed negative OPGs in the upper basin, inconsistent with typically positive values from the distributed sensor network. Upper‐basin OPGs from gauges and the gridded product were more negative (p‐values < 0.03) during heavy events related to atmospheric rivers and Sierra barrier jets than during milder events, revealing the challenges for gauges to reliably measure precipitation from large moisture transport by strong winds. In snow‐dominated headwater areas, precipitation from the blending approach is recommended as being more accurate for decision support, providing critical rain‐versus‐snow amounts and complementing precipitation‐gauge data.

Extreme Precipitation Produced by Relatively Weak Convective Systems in the Tropics and Subtropics

AbstractThis study investigates warm‐season extreme precipitation events (EPEs) with the focus on the less‐attended weak convection (WeEPEs) using spaceborne radar observations. WeEPEs are compared to EPEs with intense convection (InEPEs), including their frequency/location, convective structures, and storm environments. WeEPEs and InEPEs both account for about 30% of the EPEs, highlighting the importance of WeEPEs. Overland WeEPEs mainly occur over key monsoon regions and maximize over windward sides of coastal mountains likely due to orographic enhancement. WeEPEs develop under conditions with deep moist profiles and strengthened low‐level onshore flows. Radar, microwave, and lightning proxies all suggest a weak updraft and limited ice contents in WeEPEs. However, vertical radar profiles of WeEPEs exceptionally increase (∼15 dBZ) downward below the melting level, indicating substantial raindrop growth and/or concentration increase through very active warm‐rain processes. This study provides useful guidelines for evaluating high‐resolution model simulations and satellite rainfall retrievals on extreme precipitation.

Orographic enhancement of rainfall over the Congo Basin

AbstractThe Congo rainforest located in central equatorial Africa is an important, yet understudied part of the globe surrounded by complex orographic features. A primitive understanding of precipitation processes such as mesoscale convective dynamics magnifies uncertainties in the future climate projections of the hydrological cycle over the Congo. Furthermore, the effects of orography, which is an important forcing for convection and precipitation, are poorly resolved by climate models, and ill‐conceptualized over the Congo. To address this knowledge gap, perturbed orographic forcing experiments are conducted using the Weather Research and Forecasting (WRF) mesoscale numerical model in a high‐resolution convection‐permitting model setup. The model simulated selected dates in November 2014. The thunderstorms and rainfall simulated in the control run for the case study analyzed in this article compared reasonably well to satellite‐derived brightness temperature and rainfall data. The results from this case study show that the dynamical impact of increasing the height of the East African Highlands is the blocking of the lower‐tropospheric tropical easterlies. This weakening of the lower‐tropospheric zonal winds increases the windshear over the Congo Basin resulting in slower propagating, more intense mesoscale convective systems with enhanced rainfall.

Cloud and fog deposition: Monitoring in high elevation and coastal ecosystems. The past, present, and future

Deposition of pollutants by cloud water exceeds deposition by precipitation and dry deposition in many high elevation settings. This larger loading of pollutants in these environments is due to a combination of factors such as high frequency of cloud immersion, high wind speeds, orographic enhancement of precipitation, and large leaf area of tree species typical in these environments. Fog-impacted coastal ecosystems also experience increased pollutant deposition similar to cloud-impacted high elevation sites. Therefore, development of meaningful critical load values and total nitrogen budgets for high-elevation and fog-impacted sites requires reliable cloud and fog water deposition estimates. The cost and labor intensity of cloud/fog water sample collection have made it difficult to conduct long-term studies that would provide the data needed to develop accurate estimates. Current understanding of fog formation, transport, and the role of fog and cloud deposition in hydrogeological and biogeochemical cycles is incomplete due, in part, to lack of a concerted interdisciplinary approach to the problem. Historically, these obstacles have limited interest in and collection of cloud and fog water samples. In addition to measurements of cloud/fog chemical composition, documenting fog/cloud deposition fluxes of pollutant and nutrient species requires knowledge of cloud/fog physical properties, frequency and duration of fog/cloud interception with landscapes, properties of vegetation on those landscapes, and properties of the wind that drive droplet/vegetation interactions. Because drop deposition efficiency is dependent on drop size, it is also important to consider variations in fog/cloud drop composition with drop size as species enriched in larger/smaller drops will experience enhanced/reduced deposition rates.This paper presents summary results from a small U.S. cloud water monitoring network that operated from the mid-nineties through 2011, as well as a brief qualitative review of other cloud and fog water studies conducted in the United States (including Puerto Rico), Europe, South America/Pacific, and Asia. Current collection methods are also reviewed. Recent scientific efforts by the National Atmospheric Deposition Program's (NADP) Total Deposition Science Committee and NADP's Critical Loads of Atmospheric Deposition Science Committee have identified occult (cloud/fog) deposition as a “need” in developing critical loads for ecosystems that experience significant cloud and fog impaction. To this end, remaining knowledge gaps and suggestions for future research to investigate these gaps are explored.

Assessment of Satellite Precipitation Products in Relation With Orographic Enhancement Over the Western United States

AbstractTwo years (2018–2019) of different precipitation products are assessed for their skill in capturing orographic precipitation over the western United States (30°–50°N & 105°–135°W) using two popular methods. The first method defines orographic indices using orographic enhancement and moisture content that represents the amount of moisture advected over sloping terrain. In contrast, the second method classifies precipitation events into orographic and non‐orographic events. NCEP Stage‐IV product is used as a reference. All of the evaluated products (radar, microwave imager/sounder, and infrared) show more significant errors for the orographic than the non‐orographic events. The Global Precipitation Mission (GPM) products; Dual‐frequency Precipitation Radar (DPR), combined radar and radiometer (COMBINE), and GPM Microwave Imager (GMI), and Microwave Humidity Sounder (MHS), severely underestimate the precipitation rates, especially for heavy precipitation (>4 mm/day), whereas infrared precipitation (used in the Integrated Multi‐satellite Retrievals for GPM; IMERG‐IR) and a reanalysis product (ERA5) show relatively better estimation. It was found that the amount of precipitation over the reference (rate BIAS) varies with seasons, so in cold seasons satellite precipitation products tend to underestimate while in warm‐season they (except DPR) tend to overestimate precipitation amount. Most of the satellite products severely underestimate precipitation volume at relatively colder surfaces (<10°C) and lower TPW (<15 mm), but ERA5 shows little rate BIAS in such cases. The underestimation tends to be larger for orographic than non‐orographic events. In contrast, ERA5 shows relatively large underestimation at warmer temperatures (>20°C), where satellite products tend to overestimate precipitation amounts.

Tropical Cyclone Flooding in the Carolinas

Abstract The climatology of tropical cyclone flooding in the Carolinas is analyzed through annual flood peak observations from 411 U.S. Geological Survey (USGS) stream gauging stations. Tropical cyclones (TCs) account for 28% of the top 10 annual flood peaks, 55% of record floods, and 91% of floods with peak magnitudes at least 5 times greater than the 10-yr floods, highlighting the prominent role of TCs for flood extremes in the Carolinas. Of all TC-related flood events, the top 10 storms account for nearly 1/3 of annual flood peaks and more than 2/3 of record floods, reflecting the dominant role of a small number of storms in determining the upper tail of flood peak distributions. Analyses of the 10 storms highlight both common elements and diversity in storm properties that are responsible for flood peaks. Extratropical transition and orographic enhancement are important elements of extreme TC flooding in the Carolinas. Analyses of the Great Flood of 1916 highlight the flood peak of 3115 m3 s−1 in French Broad River at Asheville, 2.6 times greater than the second-largest peak from a record of 124 years. We also examine the hydroclimatology, hydrometeorology, and hydrology of flooding from Hurricanes Matthew (2016) and Florence (2018). Results point to contrasting storm properties for the two events, including tracks as well as rainfall distribution and associated physical mechanisms. Climatological analyses of vertically integrated water vapor transport (IVT) highlight the critical role of anomalous moisture transport from the Atlantic Ocean in producing extreme rainfall and flooding over the Carolinas.

Differential orographic impact on sub-hourly, hourly, and daily extreme precipitation

Extreme precipitation of multiple durations is responsible for major natural hazards in mountainous regions, such as flash floods and debris flows. Understanding the orographic impact on the statistics of precipitation extremes is therefore crucial for improving hydrological design and risk management strategies. Here, we use a novel statistical approach for the analysis of extremes based on ordinary events to improve our understanding of the orographic impact on extreme precipitation of durations ranging between 5 min and 24 h. We focus on Trentino, a rough orographic region in the eastern Italia Alps, and use data from 78 quality-controlled rain gauges with 5-minute resolution. We show that our framework well reproduces the statistical properties of the observed annual maxima (Nash-Sutcliffe 0.82–0.95, Bias from -4% to 7%) as well as their relation with orography. We then exploit the reduced uncertainty of this approach to quantify the orographic impact on precipitation right-tail statistics and on extreme return levels using a regression analysis. We identify two main modes of orographic relationship: a reverse orographic effect for hourly and sub-hourly durations (10–20% decrease per 1000 m elevation) and an orographic enhancement for durations of ∼8 h or longer (7.5–10% increase per 1000 m elevation). We observe that these two modes result from three main precipitation regimes, which show different proportion between extreme and very-extreme events and which emerge at very short durations (∼20 min or shorter), mid durations (∼30 min-1 hour) and long durations (∼2 h or longer). These findings are of interest for risk management applications and climate change impact studies.