SEARCH · Engineering Papers

Results for “Rainfall”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,351 records · Page 75

All sources NASA NTRS DOE OSTI

DOE OSTI2016

Strontium isotope investigation of ungulate movement patterns on the Pleistocene Paleo-Agulhas Plain of the Greater Cape Floristic Region, South Africa

Middle Stone Age sites located within the Greater Cape Floristic Region on the South African southern coast have material culture with early evidence for key modern human behaviors such as projectile weaponry, large animal hunting, and symbolic behavior. In order to interpret how and why these changes evolved, it is necessary to understand their ecological context as it has direct relevance to foraging behavior. During periods of lowered sea level, a largely flat and vast expanse of land existed south of the modern coastline, but it is now submerged by higher sea levels. This exposed area, the Paleo-Agulhas Plain, likely created an ecological context unlike anything in the region today, as evidenced by fossil assemblages dominated by migratory ungulates. One hypothesis is that the Paleo-Agulhas Plain supported a migration ecosystem of large grazers driven by summer rainfall, producing palatable forage during summer in the east, and winter rainfall, producing palatable forage during winter in the west. Furthermore, ungulates may have been moving from the coastal plain in the south to the interior north of the Cape Fold Mountains, as observed for elephants in historic times.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

An isotopic test of the seasonal migration hypothesis for large grazing ungulates inhabiting the Palaeo-Agulhas Plain

The Greater Cape Floristic Region of South Africa was critical to the evolution of early modern humans ( Homo sapiens ) during the Pleistocene. The now submerged continental shelf formed its own ecosystem, the Palaeo-Agulhas Plain (PAP), where early humans lived and foraged. Grazing animals living on the plain might have migrated east and west tracking seasonally varying rains—a hypothesis tested here by examining δ 13 C and δ 18 O of serially-drilled teeth from seven ungulate genera: Alcelaphus , Connochaetes , Antidorcus , Redunca , Damaliscus , and Hippotragus . Modern observations and paleoecological reconstructions indicate that summer rainfall areas to the east have more C 4 grasses while the winter rainfall areas to the west have more C 3 grasses, and that summer and winter rains differ in δ 18 O. Thus, we analyze δ 13 C and δ 18 O preserved in herbivore teeth from the site of PP30 (a hyena den dating to ~151 ka) to infer diet and water source throughout tooth formation. On a generic level, we report none of the samples exhibit δ 13 C or δ 18 O values that differ significantly from a taxon that likely foraged locally through the year (Southern reedbuck, Redunca arundium ). Overall, results indicate that the PAP could support herbivore populations year-round without substantial migration, providing an ecosystem ideal for human inhabitants.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Field-scale dynamics of planting dates in the US Corn Belt from 2000 to 2020

Crop planting dates are a dynamic feature of agricultural systems that respond to short- and long-term climate signals, crop and cultivar selection, and technology changes. Planting date records are essential for yield gap analyses, accurate crop modeling, and tracking farmer adaptations to weather and climate change. Although planting dates have high variation at local scales due to heterogeneity in farm resources and decision-making, available long-term data on planting dates is largely restricted to aggregated regional statistics or, at best, satellite-derived datasets with limited spatiotemporal extent and at resolutions unable to distinguish individual fields (> 250 m). Here, we generated retrospective annual field-scale (30 m) planting date maps for both maize and soybeans spanning 2000-2020 across a 12 state region in the United States Corn Belt based on Landsat satellite data and a large ground sample of over 28,000 maize and soybean fields. Using training data from 2015-2020 for model selection, we found that planting date predictions improved with harmonic regression of Landsat data and additional annual weather covariates. The preferred random forests model approximately doubled performance compared to a null model based on state median planting dates, capturing 47% of field-level variation for maize (mean absolute error, MAE = 7.4 days) and 44% for soybeans (MAE = 7.5 days) against held-out ground truth test data for 2008-2014. We also evaluated the full 2000-2020 dataset with state agricultural statistics, finding strong agreement with median planting dates for maize (R 2 = 0.76, MAE = 4.4 days) and slightly lower agreement for soybeans (R 2 = 0.65, MAE = 5.4 days) when aggregated to the state level. We then used this new dataset to analyze environmental determinants of planting dates at a finer-scale than previously possible, controlling for unobserved variation at the sub-state district level. We found that during 2000-2020, each standard deviation increase in rainfall delayed planting by ~ 2.5 days, and fields with higher soil productivity ratings tended to be planted earlier. We did not find meaningful trends over the last two decades in planting dates for maize or soybeans, in contrast to trends towards earlier planting dates late last century and predicted for this period in climate adaptation studies. We hypothesize increases in early season rainfall may have inhibited these shifts towards earlier planting. Remotely sensed planting dates will be a useful tool for yield gap analyses, crop simulation modeling, and ongoing assessment of climate adaptation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Susceptibility of new soil organic carbon to mineralization during dry-wet cycling in soils from contrasting ends of a precipitation gradient

The persistence of soil organic carbon (SOC) is influenced by soil physicochemical properties, organic matter quality, and climatic conditions that govern its vulnerability to microbial activity. We compared the susceptibility of newly formed SOC to mineralization in two soils (Andosols) that developed under contrasting precipitation regimes. Soil from the high rainfall region (‘high rain ’) had higher SOC and lower iron concentrations than soils exposed to less rainfall (‘low rain ’). We amended soils with 13 C-labeled carbohydrates and measured the amount of substrate-derived SO 13 C mineralized when exposed to dry-wet cycling following months-long incubations. We hypothesized that susceptibility would differ due to iron content and mineralogy, initial SOC, substrate solubility (cellulose versus glucose amendment), and microbial substrate use efficiency (SUE). We found that SO 13 C was less susceptible to dry-wet cycling when more 13 C was assimilated into microbial biomass and co-localized with mineral surfaces than when co-localized with existing organo-mineral surfaces, according to microscale NanoSIMS imaging. Considerably less SO 13 C was susceptible to mineralization in the ferrihydrite-rich (low SOC) low rain soil than the leached (high SOC) high rain soil when C was added as either glucose (7.3-fold less C mineralized) or cellulose (15.2-fold less). Additionally, the SUE of glucose was comparable to cellulose in low rain soil where SO 13 C was less water soluble and coprecipitated with ferrihydrite, and used half as efficiently as cellulose in high rain soil. Our results show that the susceptibility of newly formed SOC to mineralization is modified by the effects of bioavailability on microbial metabolism and the availability of mineral surfaces for forming new organo-mineral complexes.

21 NanoSIMS↗

DOE OSTI2022

Active populations and growth of soil microorganisms are framed by mean annual precipitation in three California annual grasslands

Climate influences soil microbial composition and function, but the relative importance of a site's historic climate versus its more immediate environmental conditions is unclear. Using quantitative stable isotope probing (qSIP), we characterized actively growing soil microbial communities and soil properties in three California annual grasslands that span a rainfall gradient and have developed on similar parent material. The soils were assayed in the wet winter season, when environmental conditions are most similar across sites. Since growing populations might be expected to be most responsive to contemporary environmental conditions, we hypothesized that the structure of growing microbial communities would be more similar across the gradient than that of total communities (i.e., including non-growing populations). In addition, we hypothesized that population growth rates would be slowest in the driest site, reflecting a legacy effect of low soil moisture on microbial growth. Soils along the rainfall gradient differed in pH, texture, and cation exchange capacity, but not in total C, C:N or dominant minerals. The radiocarbon (14C) age of soil C (reflecting turnover time) increased with mean annual precipitation but soil respiration was uniformly modern, reflecting microbial reliance on recent C inputs across the sites. The structure of both total and growing microbial communities differed across sites. Across major microbial phyla, including the Actinobacteria, Acidobacteria, Bacteroidetes, Gemmatimonadetes and Proteobacteria, bacterial growth rates were consistently lower in the site with the lowest mean annual precipitation. Taxa that were growing at the dry site alone grew more slowly than taxa that grew at multiple sites. These results reflect the influence of climate history and point to the role of environmental filtering at the driest site in shaping its slower growing microbial community, possibly reflecting adaptation to repeated exposure to water stress. Lastly, across taxa, the growth rate of a taxon at one site was correlated with its growth rate in the other sites. Furthermore, this growth rate coherence is likely a consequence of genetically determined physiological traits and is consistent with the idea that evolutionary history constrains growth rate.

Environmental filtering↗

DOE OSTI2014

Sources and transport of nitrogen in arid urban watersheds

Urban watersheds are often sources of nitrogen (N) to downstream systems, contributing to poor water quality. However, it is unknown which components (e.g., land cover and stormwater infrastructure type) of urban watersheds contribute to N export and which may be sites of retention. In this study we investigated which watershed characteristics control N sourcing, biogeochemical processing of nitrate (NO3–) during storms, and the amount of rainfall N that is retained within urban watersheds. We used triple isotopes of NO3– (δ15N, δ18O, and Δ17O) to identify sources and transformations of NO3– during storms from 10 nested arid urban watersheds that varied in stormwater infrastructure type and drainage area. Stormwater infrastructure and land cover—retention basins, pipes, and grass cover—dictated the sourcing of NO3– in runoff. Urban watersheds can be strong sinks or sources of N to stormwater depending on the proportion of rainfall that leaves the watershed as runoff, but we found no evidence that denitrification occurred during storms. Our results suggest that watershed characteristics control the sources and transport of inorganic N in urban stormwater but that retention of inorganic N at the timescale of individual runoff events is controlled by hydrologic, rather than biogeochemical, mechanisms.

arid-urban watersheds↗

DOE OSTI2018

Short-Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks

Short-term Quantitative Precipitation Forecasting is important for flood forecasting, early flood warning, and natural hazard management. This study proposes a precipitation forecast model by extrapolating Cloud-Top Brightness Temperature (CTBT) using advanced Deep Neural Networks, and applying the forecasted CTBT into an effective rainfall retrieval algorithm to obtain the Short-term Quantitative Precipitation Forecasting (0–6 hr). To achieve such tasks, we propose a Long Short-Term Memory (LSTM) and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), respectively. The precipitation forecasts obtained from our proposed framework, (i.e., LSTM combined with PERSIANN) are compared with a Recurrent Neural Network (RNN), Persistency method, and Farneback optical flow each combined with PERSIANN algorithm and the numerical model results from the first version of Rapid Refresh (RAPv1.0) over three regions in the United States, including the states of Oregon, Oklahoma, and Florida. We report our experiments indicate better statistics, such as correlation coefficient and root-mean-square error, for the CTBT forecasts from the proposed LSTM compared to the RNN, Persistency, and the Farneback method. The precipitation forecasts from the proposed LSTM and PERSIANN framework has demonstrated better statistics compared to the RAPv1.0 numerical forecasts and PERSIANN estimations from RNN, Persistency, and Farneback projections in terms of Probability of Detection, False Alarm Ratio, Critical Success Index, correlation coefficient, and root-mean-square error, especially in predicting the convective rainfalls. The proposed method shows superior capabilities in short-term forecasting over compared methods, and has the potential to be implemented globally as an alternative short-term forecast product.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Impacts of Local Convective Processes on Rain on the Caribbean Island of Puerto Rico

Abstract This study aims to determine the impacts of tropical island processes on local convective storms. An analysis of rain events on the island of Puerto Rico between 1 June 2015 and 31 July 2016 showed that local island‐enhanced western storms accounted for 89 of 322 storms. This period is of particular importance for the Caribbean as 2015 was one of the driest years on record. While large‐scale influences such as the El Niño–Southern Oscillation, the North Atlantic Oscillation, African easterly waves, and Saharan dust transport modulate moisture conditions in the region, correlations between precipitation and El Niño–Southern Oscillation (−0.14), North Atlantic Oscillation (−0.42), and Saharan dust (0.1) for 1980–2016 ranged from weak to moderate. Local data for the island of Puerto Rico from weather stations, the Convection, Aerosol, and Synoptic‐Effects in the Tropics field campaign, and the North American Mesoscale model support the initiation or enhancement of convective rain events due to local island processes. In particular, analysis of surface wind speed/direction, convective available potential energy, lifted index, and the bulk Richardson number substantiate local instability due to surface heating, orographic uplift, and sea breeze trade‐wind convergence. These convective forcings along with available precipitable water in excess of 50 mm ultimately led to intense storms despite severe rainfall‐mitigating dust episodes for which aerosol optical thickness exceeded 0.4. These results may have major implications for considering the impacts of local air‐sea‐land interactions on rainfall over other tropical islands.

Hosannah, N.↗

DOE OSTI2019

Laboratory Experiments of Volcanic Ash Resuspension by Wind

Abstract Fresh volcanic eruption deposits tend to be loose, bare, and readily resuspended by wind. Major resuspension events in Patagonia, Iceland, and Alaska have lofted ash clouds with potential to impact aircraft, infrastructure, and downwind communities. However, poor constraints on this resuspension process limit our ability to model this phenomenon. Here, we present laboratory experiments measuring threshold shear velocities and emission rates of resuspended ash under different environmental conditions, including relative humidity of 25–75% and simulated rainfall with subsequent drying. Eruption deposits were replicated using ash collected from two major eruptions: the 18 May 1980 eruption of Mount St. Helens and the 1912 eruption of Novarupta, in Alaska's Valley of Ten Thousand Smokes. Samples were conditioned in a laboratory chamber and prepared with bulk deposit densities of 1,300–1,500 kg/m 3 . A control sample of dune sand was included for comparison. The deposits were subjected to different wind speeds using a modified PI‐SWERL® instrument. Under a constant relative humidity of 50% and shear velocities 0.4–0.8 m/s, PM 10 emission by resuspension ranged from 10 to >100 mg·m −2 ·s −1 . Addition of liquid water equivalent to 5 mm of rainfall had little lasting effect on Mount St. Helens wind erosion potential, while the Valley of Ten Thousand Smokes deposits exhibited lower emissions for at least 12 days. The results indicate that particle resuspension due to wind erosion from ash deposits potentially exceeds that of most desert surfaces and approaches some of the highest emissions ever measured.

Etyemezian, V.↗

DOE OSTI2018

Structure and Evolution of Mesoscale Convective Systems: Sensitivity to Cloud Microphysics in Convection‐Permitting Simulations Over the United States

Abstract Regional climate simulations over the continental United States were conducted for the 2011 warm season using the Weather Research and Forecasting model at convection‐permitting resolution (4 km) with two commonly used microphysics parameterizations (Thompson and Morrison). Sensitivities of the simulated mesoscale convective system (MCS) properties and feedbacks to large‐scale environments are systematically examined against high‐resolution geostationary satellite and 3‐D mosaic radar observations. MCS precipitation including precipitation amount, diurnal cycle, and distribution of hourly precipitation intensity are reasonably captured by the two simulations despite significant differences in their simulated MCS properties. In general, the Thompson simulation produces better agreement with observations for MCS upper level cloud shield and precipitation area, convective feature horizontal and vertical extents, and partitioning between convective and stratiform precipitation. More importantly, Thompson simulates more stratiform rainfall, which agrees better with observations and results in top‐heavier heating profiles from robust MCSs compared to Morrison. A stronger dynamical feedback to the large‐scale environment is therefore seen in Thompson, wherein an enhanced mesoscale vortex behind the MCS strengthens the synoptic‐scale trough and promotes advection of cool and dry air into the rear of the MCS region. The latter prolongs the MCS lifetimes in the Thompson relative to the Morrison simulations. Hence, different treatment of cloud microphysics not only alters MCS convective‐scale dynamics but also has significant impacts on their macrophysical properties such as lifetime and precipitation. As long‐lived MCSs produced 2–3 times the amount of rainfall compared to short‐lived ones, cloud microphysics parameterizations have profound impact in simulating extreme precipitation and the hydrologic cycle.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Seasonal and Interannual Patterns and Controls of Hydrological Fluxes in an Amazon Floodplain Lake With a Surface-Subsurface Process Model

Floodplain lakes represent important aquatic ecosystems, and field-based estimates of their water budgets are difficult to obtain, especially over multiple years. We examine the hydrological fluxes for an Amazon floodplain lake connected to the Solimões River using a process-based hydrologic model. Water exchanges between the river and lake agree well with field estimates, including the timing of different hydrological phases. However, beyond available field data, modeling results show that the seven simulated years all differed from each other. These interannual differences were caused by the interplay between phases when water levels were rising with river-water flowing into the lake (RWRI), versus rising with lake-water flowing out to the river (RWLO). This exchange determines the river-water content in the lake ( C L ). Maximum C L occurred before river levels peaked because local catchment contributions can be sufficient to push lake-water out to the river, even as river levels rise. Numerical experiments show that the seasonal distribution of local rainfall, local catchment size, and interannual variability in both climate and river stage can contribute to differing dynamics of C L in a floodplain lake. Their impacts vary among phases: river-rise dominates the RWRI, whereas local hydrological processes dominate the RWLO and receding-water phases. Intermediate-to-long-term rainfall accumulation controls C L during the RWLO phase, whereas annual precipitation accumulation is important for C L during low water. Finally, our model generalizes beyond limited available field studies and offers potential to better understand floodplain lakes in other areas and how regional versus local changes in climate may affect their hydrological dynamics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Intensification of the Pre-Meiyu Rainband in the Late 21st Century

Increased atmospheric moisture content and changing land-ocean thermal contrasts are usually implicated in the East Asian summer rainfall response to global warming. We highlight an additional influence whereby increased meridional stationary eddy circulation downstream of the Tibetan Plateau drives a stronger moisture flux convergence over southeastern China, intensifying the early summer rainband. This effect occurs robustly across the Community Earth System Model large ensemble Representative Control Pathway 8.5 simulations, and only for its pre-Meiyu stage (mid-May through late June). The westerly jet impinging on the Plateau is also enhanced, suggesting an orographic influence on the westerlies as the root cause. The increased westerlies result from warmer tropical tropospheric temperatures that enhance the meridional temperature gradient at the latitudes of the Plateau. Finally, our results highlight the potential role of the westerlies in altering the East Asian early summer monsoon rainfall in the late 21st century.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

The Relationship of Cloud Number and Size With Their Large-Scale Environment in Deep Tropical Convection

Accurately representing the properties and impact of tropical convection in climate models requires an understanding of the relationships between the state of a convective cloud ensemble and the environment it is embedded in. We investigate this relationship using 13 years of radar observations in the tropics. Specifically, we focus on convective cell number and size and quantify their relationship to atmospheric stability, midtropospheric vertical motion and humidity. We find several key convective states embedded in their own unique environments. The most area-averaged rainfall occurs with a moderate number of moderate size convective cell in an environment of high humidity, strong vertical ascent, and moderate convective available potential energy (CAPE) and convective inhibition (CIN). The strongest rainfall intensities are found with few large cells. Those exist in a dry and subsiding environment with both high CAPE and CIN. Finally, large numbers of convective cells are associated with small CAPE and CIN, weak ascent, and a moist midtroposphere.

58 GEOSCIENCES↗

DOE OSTI2019

Surface‐Atmosphere Coupling Scale, the Fate of Water, and Ecophysiological Function in a Brazilian Forest

Abstract Tropical South America plays a central role in global climate. Bowen ratio teleconnects to circulation and precipitation processes far afield, and the global CO 2 growth rate is strongly influenced by carbon cycle processes in South America. However, quantification of basin‐wide seasonality of flux partitioning between latent and sensible heat, the response to anomalies around climatic norms, and understanding of the processes and mechanisms that control the carbon cycle remains elusive. Here, we investigate simulated surface‐atmosphere interaction at a single site in Brazil, using models with different representations of precipitation and cloud processes, as well as differences in scale of coupling between the surface and atmosphere. We find that the model with parameterized clouds/precipitation has a tendency toward unrealistic perpetual light precipitation, while models with explicit treatment of clouds produce more intense and less frequent rain. Models that couple the surface to the atmosphere on the scale of kilometers, as opposed to tens or hundreds of kilometers, produce even more realistic distributions of rainfall. Rainfall intensity has direct consequences for the “fate of water,” or the pathway that a hydrometeor follows once it interacts with the surface. We find that the model with explicit treatment of cloud processes, coupled to the surface at small scales, is the most realistic when compared to observations. These results have implications for simulations of global climate, as the use of models with explicit (as opposed to parameterized) cloud representations becomes more widespread.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Spatiotemporal Characteristics and Propagation of Summer Extreme Precipitation Events over United States: A Complex Network Analysis

Complex Network (CN) is a graph-theory based depiction of relation shared by various elements of a complex-dynamical system such as the atmosphere. Here we applied the concept of CN to understand the directionality and topological structure of summer extreme precipitation events (SEPEs) over the conterminous United States (CONUS). The SEPEs are calculated based on the 95th percentile daily rainfall at 0.5ox0.5o spatial resolution for CONUS to investigate the multi-dimensional characteristics of precipitation extremes. The derived CN coefficients (e.g., betweenness centrality, clustering coefficient, orientation, and network divergence) reveal important structural and dynamical information about the topology of the SEPEs and improve understanding of the dominant meteorological patterns. The initiation and propagation of SEPEs from the source-zones to the sink-zones are identified. The SEPEs are influenced by topography, dominant wind patterns, and moisture sources in terms of their topological structure and spatial dynamics.

Mondal, Somnath↗

DOE OSTI2020

Assessing Historical Variability of South Asian Monsoon Lows and Depressions With an Optimized Tracking Algorithm

Abstract Cyclonic low‐pressure systems (LPS) produce abundant rainfall in South Asia, where they are traditionally categorized as monsoon lows, monsoon depressions, and more intense cyclonic storms. The India Meteorological Department (IMD) has tracked monsoon depressions for over a century, finding a large decline in their number in recent decades, but their methods have changed over time and do not include monsoon lows. This study presents a fast, objective algorithm for identifying monsoon LPS and uses it to assess interannual variability and trends in reanalyses. Variables and thresholds used in the algorithm are selected to best match a subjectively analyzed LPS data set while minimizing disagreement between four reanalyses in a training period. The stream function of 850 hPa horizontal wind is found to be optimal in this sense; it is less noisy than vorticity and represents the complete nondivergent wind, even when flow is not geostrophic. Using this algorithm, LPS statistics are computed for five reanalyses, and none show a detectable trend in monsoon depression counts since 1979. Both the Japanese 55‐year Reanalysis (JRA‐55) and the IMD data set show a step‐like reduction in depression counts when they began using geostationary satellite data, in 1979 and 1982, respectively; the 1958–2018 linear trend in JRA‐55, however, is smaller than in the IMD data set, and its error bar includes 0. There are more LPS in seasons with above‐average monsoon rainfall and in La Niña years, but few other large‐scale modes of interannual variability are found to modulate LPS counts, lifetimes, or track length consistently across reanalyses.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

A Global High‐Resolution Mesoscale Convective System Database Using Satellite‐Derived Cloud Tops, Surface Precipitation, and Tracking

Abstract A new methodology is developed to construct a global (60°S–60°N) long‐term (2000–2019) high‐resolution (∼10‐km h) mesoscale convective system (MCS) database by tracking MCS jointly using geostationary satellite infrared brightness temperature ( T b ) and precipitation feature (PF) characteristics from the Integrated Multi‐satellitE Retrievals for GPM precipitation data sets. Independent validation shows that the satellite‐based MCS data set is able to reproduce important MCS statistics derived from ground‐based radar network observations in the United States and China. We show that by carefully considering key PF characteristics in addition to T b signatures, the new method significantly improves upon previous T b ‐only methods in detecting MCSs in the midlatitudes for all seasons. Results show that MCSs account for over 50% of annual total rainfall across most of the tropical belt and in selected regions of the midlatitudes, with a strong seasonality over many regions of the globe. The tracking database allows Lagrangian aspects such as MCS lifetime and translational speed and direction to be analyzed. The longest‐lived MCSs preferentially occur over the subtropical oceans. The land MCSs have higher cloud‐tops associated with more intense convection, and oceanic MCSs have much higher rainfall production. While MCSs are observed in many regions of the globe, there are fundamental differences in their dynamic and thermodynamic structures that warrant a better understanding of processes that control their evolution. This global database provides significant opportunities for observational and modeling studies of MCSs, their characteristics, and roles in regional and global water and energy cycles, as well as their hydrologic and other impacts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Distortions of the Rain Distribution With Warming, With and Without Self-Aggregation

We investigate how mesoscale circulations associated with convective aggregation can modulate the sensitivity of the hydrologic cycle to warming. We quantify changes in the full distribution of rain across radiative-convective equilibrium states in a cloud-resolving model. For a given Sea Surface Temperature (SST), the shift in mean rainfall between disorganized and organized states is associated with a shift in atmospheric radiative cooling, and is roughly analogous to the effect of a 4K SST increase. With rising temperatures, the increase in mean rain rate is insensitive to the presence of organization, while extremes can intensify faster in the aggregated state, leading to a faster amplification in the sporadic nature of rain. When convection aggregates, heavy rain is enhanced by 20%–30% and nonlinear behaviors are observed as a function of SST and strength of aggregation feedbacks. First, radiative- and surface-flux aggregation feedbacks have multiplicative effects on extremes, illustrating a non-trivial sensitivity to the degree of organization. Second, alternating Clausius-Clapeyron and super-Clausius-Clapeyron regimes in extreme rainfall are found as a function of SST, corresponding to varying thermodynamic and dynamic contributions, and a large sensitivity to precipitation efficiency variations in some SST ranges. The potential for mesoscale circulations in amplifying the hydrologic cycle is established. However, these nonlinear distortions question the quantitative relevance of idealized self-aggregation. This calls for a deeper investigation of relationships which capture the coupling between global energetics, aggregation feedbacks and local convection, and for systematic tests of their sensitivity to domain configurations, surface boundary conditions, microphysics, and turbulence schemes.

54 ENVIRONMENTAL SCIENCES↗