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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Tropical Cyclones Feed More Heavy Rain in a Warmer Climate

The possible linkage of tropical cyclones (TC) to global warming is a hotly debated scientific topic, with immense societal impacts. Most of the debate has been focused on the issue of uncertainty in the use of non-research quality data for long-term trend analyses, especially with regard to TC intensity provided by TC forecasting centers. On the other hand, it is well known that TCs are associated with heavy rain during the processes of genesis and intensification, and that there are growing evidences that rainfall characteristics (not total rainfall) are most likely to be affected by global warming. Yet, satellite rainfall data have not been exploited in any recent studies of linkage between tropical cyclones (TC) and global warming. This is mostly due to the large uncertainties associated with detection of long-term trend in satellite rainfall estimates over the ocean. This problem, as we demonstrate in this paper, can be alleviated by examining rainfall distribution, rather than rainfall total. This paper is the first to use research-quality, satellite-derived rainfall from TRMM and GPCP over the tropical oceans to estimate shift in rainfall distribution during the TC season, and its relationships with TCs, and sea surface temperature (SST) in the two major ocean basins, the northern Atlantic and the northern Pacific for 1979-2005. From the rainfall distribution, we derive the TC contributions to rainfall in various extreme rainfall categories as a function to time. Our results show a definitive trend indicating that TCs are contributing increasingly to heavier rain events, i.e., intense TC's are more frequent in the last 27 years. The TC contribution to top 5% heavy rain has nearly doubled in the last two decades in the North Atlantic, and has increased by about 10% in the North Pacific. The different rate of increase in TC contribution to heavy rain may be related to the different rates of different rate of expansion of the warm pool (SST >2S0 C) area in the two oceans.

Lau, K.-M.↗
NASA NTRS2011

Spatial Correlation of Rain Drop Size Distribution from Polarimetric Radar and 2D-Video Disdrometers

Spatial correlations of two of the main rain drop-size distribution (DSD) parameters - namely the median-volume diameter (Do) and the normalized intercept parameter (Nw) - as well as rainfall rate (R) are determined from polarimetric radar measurements, with added information from 2D video disdrometer (2DVD) data. Two cases have been considered, (i) a widespread, long-duration rain event in Huntsville, Alabama, and (ii) an event with localized intense rain-cells within a convection line which occurred during the MC3E campaign. For the first case, data from a C-band polarimetric radar (ARMOR) were utilized, with two 2DVDs acting as ground-truth , both being located at the same site 15 km from the radar. The radar was operated in a special near-dwelling mode over the 2DVDs. In the second case, data from an S-band polarimetric radar (NPOL) data were utilized, with at least five 2DVDs located between 20 and 30 km from the radar. In both rain event cases, comparisons of Do, log10(Nw) and R were made between radar derived estimates and 2DVD-based measurements, and were found to be in good agreement, and in both cases, the radar data were subsequently used to determine the spatial correlations For the first case, the spatial decorrelation distance was found to be smallest for R (4.5 km), and largest fo Do (8.2 km). For log10(Nw) it was 7.2 km (Fig. 1). For the second case, the corresponding decorrelation distances were somewhat smaller but had a directional dependence. In Fig. 2, we show an example of Do comparisons between NPOL based estimates and 1-minute DSD based estimates from one of the five 2DVDs.

Thurai, Merhala↗
NASA NTRS2017

High Sensitivity of Gross Primary Production in the Rocky Mountains to Summer Rain

n the catchments of the Rocky Mountains, peak snowpack is declining in response to warmer spring temperatures. To understand how this will influence terrestrial gross primary production (GPP), we compared precipitation data across the intermountain west with satellite retrievals of solar-induced fluorescence (SIF), a proxy for GPP. Annual precipitation patterns explained most of the spatial and temporal variability of SIF, but the slope of the response was dependent on site to site differences in the proportion of snowpack to summer rain. We separated the response of SIF to different seasonal precipitation amounts and found that SIF was approximately twice as sensitive to variations in summer rain than snowpack. The response of peak GPP to a secular decline in snowpack will likely be subtle, whereas a change in summer rain amount will have precipitous effects on GPP. The study suggests that the rain use efficiency of Rocky Mountain ecosystems is strongly dependent on precipitation form and timing.

solar-induced 15 Fuorescence (SIF)↗
NASA NTRS2006

SeaWinds Scatterometer Wind Vector Retrievals Within Hurricanes Using AMSR and NEXRAD to Perform Corrections for Precipitation Effects: Comparison of AMSR and NEXRAD Retrievals of Rain

The opportunity provided by satellite scatterometers to measure ocean surface winds in strong storms and hurricanes is diminished by the errors in the received backscatter (SIGMA-0) caused by the attenuation, scattering and surface roughening produced by heavy rain. Providing a good rain correction is a very challenging problem, particularly at Ku band (13.4 GHz) where rain effects are strong. Corrections to the scatterometer measurements of ocean surface winds can be pursued with either of two different methods: empirical or physical modeling. The latter method is employed in this study because of the availability of near simultaneous and collocated measurements provided by the MIDORI-II suite of instruments. The AMSR was designed to measure atmospheric water-related parameters on a spatial scale comparable to the SeaWinds scatterometer. These quantities can be converted into volumetric attenuation and scattering at the Ku-band frequency of SeaWinds. Optimal estimates of the volume backscatter and attenuation require a knowledge of the three dimensional distribution of reflectivity on a scale comparable to that of the precipitation. Studies selected near the US coastline enable the much higher resolution NEXRAD reflectivity measurements evaluate the AMSR estimates. We are also conducting research into the effects of different beam geometries and nonuniform beamfilling of precipitation within the field-of-view of the AMSR and the scatterometer. Furthermore, both AMSR and NEXRAD estimates of atmospheric correction can be used to produce corrected SIGMA-0s, which are then input to the JPL wind retrieval algorithm.

SeaWinds↗
NASA NTRS2015

High Ice Water Content at Low Radar Reflectivity near Deep Convection: Consistency of In Situ and Remote-Sensing Observations with Stratiform Rain Column Simulations - Part I

Occurrences of jet engine power loss and damage have been associated with flight through fully glaciated deep convection at -10 to -50 degrees Centigrade. Power loss events commonly occur during flight through radar reflectivity (Zeta (sub e)) less than 20-30 decibels relative to Zeta (dBZ - radar returns) and no more than moderate turbulence, often overlying moderate to heavy rain near the surface. During 2010-2012, Airbus carried out flight tests seeking to characterize the highest ice water content (IWC) in such low-radar-reflectivity regions of large, cold-topped storm systems in the vicinity of Cayenne, Darwin, and Santiago. Within the highest IWC regions encountered, at typical sampling elevations (circa 11 kilometers), the measured ice size distributions exhibit a notably narrow concentration of mass over area-equivalent diameters of 100-500 micrometers. Given substantial and poorly quantified measurement uncertainties, here we evaluate the consistency of the Airbus in situ measurements with ground-based profiling radar observations obtained under quasi-steady, heavy stratiform rain conditions in one of the Airbus-sampled locations. We find that profiler-observed radar reflectivities and mean Doppler velocities at Airbus sampling temperatures are generally consistent with those calculated from in situ size-distribution measurements. We also find that column simulations using the in situ size distributions as an upper boundary condition are generally consistent with observed profiles of radar reflectivity (Ze), mean Doppler velocity (MDV), and retrieved rain rate. The results of these consistency checks motivate an examination of the microphysical pathways that could be responsible for the observed size-distribution features in Ackerman et al. (2015).

Rain↗
NASA NTRS2017

Meteorological Inventory of Rain-On-Snow Events in the Canadian Arctic Archipelago and Satellite Detection Assessment Using Passive Microwave Data

The spatial and temporal distributions of rain-on-snow (ROS) events across the Canadian Arctic Archipelago (CAA) remain poorly understood owing to their sporadic nature in time and space. This situation motivated the development of remote sensing detection algorithms. This paper uses a large meteorological dataset across the CAA to adapt an existing ROS-detection algorithm developed in a previous study by our group. Results highlight the spatial distribution and evolution of ROS occurrences reported since 1985 at 14 weather stations across the CAA. Results show that >600 ROS events were inventoried since 1985, for which >70% were classified as pure rain (liquid form) and 30% as mixed precipitation (solid/liquid). Of the pure rain events, 75% occurred during spring, 14% during fall, 8% during summer and <1% during winter. Such events can have significant impacts on ungulate grazing conditions through the creation of ice layers, causing serious problems for caribou calf survival, especially during the migration period. This paper introduces an adaptation for larger scale Arctic application of a detection algorithm (sensitivity analysis on the detection threshold) with an error of ~5%. The validation, however, remains limited due to a short study period and limited number of sites.

Canadian Arctic Archipelago (CAA)↗
DOE OSTI2022

Rain-Induced Stratification of the Equatorial Indian Ocean and Its Potential Feedback to the Atmosphere

Surface freshening through precipitation can act to stably stratify the upper ocean, forming a rain layer (RL). RLs inhibit subsurface vertical mixing, isolating deeper ocean layers from the atmosphere. This process has been studied using observations and idealized simulations. The present ocean modeling study builds upon this body of work by incorporating spatially resolved and realistic atmospheric forcing. Fine-scale observations of the upper ocean collected during the Dynamics of the Madden-Julian Oscillation field campaign are used to verify the General Ocean Turbulence Model (GOTM). Spatiotemporal characteristics of equatorial Indian Ocean RLs are then investigated by forcing a 2D array of GOTM columns with realistic and well-resolved output from an existing regional atmospheric simulation. RL influence on the ocean-atmosphere system is evaluated through analysis of RL-induced modification to surface fluxes and sea surface temperature (SST). This analysis demonstrates that RLs cool the ocean surface on time scales longer than the associated precipitation event. A second simulation with identical atmospheric forcing to that in the first, but with rainfall set to zero, is performed to investigate the role of rain temperature and salinity stratification in maintaining cold SST anomalies within RLs. Approximately one third, or 0.1°C, of the SST reduction within RLs can be attributed to rain effects, while the remainder is attributed to changes in atmospheric temperature and humidity. The prolonged RL-induced SST anomalies enhance SST gradients that have been shown to favor the initiation of atmospheric convection. These findings encourage continued research of RL feedbacks to the atmosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Synchronization of the Recent Decline of East African Long Rains and Northwestern Eurasian Warming

Abstract The East African March–April–May (MAM, “long rains”) precipitation decline in recent decades remains a puzzle marked by various proposed large‐scale drivers. Here, the interannual variability of the long rains and their recent drying trend are examined using global model simulations and observations. Comparison of a control simulation and re‐initialized simulations in which land‐surface feedback is suppressed shows that much of the long rains deficit experienced between 1980 and 2014 is synchronized with the warming of the Northwestern Eurasian landmass. In agreement with the modeling results, multiple observational data sets reveal a strong negative correlation between MAM mean East African rainfall amount and the surface temperature over Northwestern Eurasia. Idealized simulations further indicate that warming in Northwestern Eurasia weakens the regional Hadley Cell and diverts the monsoonal transport of moisture away from Eastern Africa toward Europe and southern Africa, highlighting the role of remote land surface warming on the observed precipitation decline.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The microphysics of the warm-rain and ice crystal processes of precipitation in simulated continental convective storms

Precipitation in clouds can form by either warm-rain or ice crystal processes, referred to as warm and cold formation pathways, respectively. Here, we investigate the warm and cold pathway contributions to surface precipitation in simulated continental convective storms. We analyze three contrasting convective storms that are cold-based, slightly warm-based and very warm-based. We apply tracer-tagging techniques in our aerosol-cloud model to determine simulated microphysical pathways that lead to precipitation. We find cold components of graupel and rain mass were higher than warm components in cold- and slightly warm-based clouds. By contrast, in very warm-based clouds nearly 80% of surface precipitation was formed via warm-rain processes. Lowering of cloud base altitude to levels about 10–20 K warmer switched surface precipitation to being mostly warm, due to enhanced moisture content in the planetary boundary layer and larger cloud droplets aloft intensifying raindrop freezing. Our simulations indicate that warm and cold processes co-exist in any storm and the balance between them is determined by cloud base temperature and solute aerosol conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The Diurnal and Microphysical Characteristics of MJO Rain Events during DYNAMO

The Madden–Julian oscillation (MJO) dominates the intraseasonal variability of cloud populations of the tropical Indian and Paci?c Oceans. Suppressed MJO periods consist primarily of shallow and isolated deep convection. During the transition to an active MJO, the shallow and isolated deep clouds grow upscale into the overnight hours. During active MJO periods, mesoscale convective systems occur mostly during 2–4-day bursts of rainfall activity with a statistically signi?cant early morning peak. Yet when these rain events are separated into individual active periods, some periods do not follow the mean pattern, with the November events in particular exhibiting an afternoon peak. The radar-observed microphysical processes producing the precipitation during the major rain events of active MJO periods evolve in connection with synoptic-scale wave passages with varying in?uences of diurnal forcing. MJO studies that do not account for the in-termittency of rainfall during active MJO phases through averaging over multiple events can lead to the misimpression that the primary rain-producing clouds of the MJO are modulated solely by the diurnal cycle.

Rowe, Angela K.↗
DOE OSTI2020

A Bayesian Approach for Statistical–Physical Bulk Parameterization of Rain Microphysics. Part I: Scheme Description

A novel framework is proposed for the bulk parameterization of rain microphysics: the Bayesian Observationally Constrained Statistical–Physical Scheme (BOSS). It is designed to facilitate direct constraint by observations using Bayesian inference. BOSS combines existing process-level microphysical knowledge with flexible process rate formulations and parameters constrained by observations within a Bayesian framework. Furthermore, using a raindrop size distribution (DSD) normalization method that relates DSD moments to one another via generalized power series, generalized multivariate power expressions are derived for the microphysical process rates as functions of a set of prognostic DSD moments. The scheme is flexible and can utilize any number and combination of prognostic moments and any number of terms in the process rate formulations. This means that both uncertainty in parameter values and structural uncertainty associated with the process rate formulations can be investigated systematically, which is not possible using traditional schemes. In this paper, BOSS is compared to two- and three-moment versions of a traditional bulk rain microphysics scheme (denoted as MORR). It is demonstrated that some process formulations in MORR are analytically equivalent to the generalized power expressions in BOSS using one or two terms, while others are not. BOSS is able to replicate the behavior of MORR in idealized one-dimensional rainshaft tests, but with a much more flexible and systematic design. Part II of this study describes the application of BOSS to derive rain microphysical process rates and posterior parameter distributions in Bayesian experiments using Markov chain Monte Carlo sampling constrained by synthetic observations.

58 GEOSCIENCES↗
DOE OSTI2024

A Comprehensive Analysis of Uncertainties in Warm-Rain Parameterizations in Climate Models Based on In Situ Measurements

Abstract Because of the coarse grid size of Earth system models (ESMs), representing warm-rain processes in ESMs is a challenging task involving multiple sources of uncertainty. Previous studies evaluated warm-rain parameterizations mainly according to their performance in emulating collision–coalescence rates for local droplet populations over a short period of a few seconds. The representativeness of these local process rates comes into question when applied in ESMs for grid sizes on the order of 100 km and time steps on the order of 20–30 min. We evaluate several widely used warm-rain parameterizations in ESM application scenarios. In the comparison of local and instantaneous autoconversion rates, the two parameterization schemes based on numerical fitting to stochastic collection equation (SCE) results perform best. However, because of Jessen’s inequality, their performance deteriorates when grid-mean, instead of locally resolved, cloud properties are used in their simulations. In contrast, the effect of Jessen’s inequality partly cancels the overestimation problem of two semianalytical schemes, leading to an improvement in the ESM-like comparison. In the assessment of uncertainty due to the large time step of ESMs, it is found that the rainwater tendency simulated by the SCE is roughly linear for time steps smaller than 10 min, but the nonlinearity effect becomes significant for larger time steps, leading to errors up to a factor of 4 for a time step of 20 min. After considering all uncertainties, the grid-mean and time-averaged rainwater tendency based on the parameterization schemes is mostly within a factor of 4 of the local benchmark results simulated by SCE.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

Evaluation of WSR-88D Level III and MRMS Rainfall Estimates Against Rain Gauge Observations at the Savannah River Site

Rainfall data for the Savannah River Site (SRS) has been historically measured by rain gauges. These instruments serve as ground truth for most climatological and weather applications; however, gauge measurements are prone to errors or biases under certain weather conditions. Rainfall estimates from radar reflectivity values have been developed and improved over the years and serve as an alternative or supplement for gauge measurements. This study compares measurements from tipping bucket rain gauges with rainfall estimates from the NOAA NWS WSR-88D Level III hourly rainfall product and the Multi-Radar Multi-Sensor (MRMS) gauge-corrected precipitation estimate. Results show good agreement between radar derived amounts and ground measurements, with MRMS values showing correlation coefficients of 0.60-0.95 and RMSE values of less than 1.0 cm (0.4 in). The WSR-88D Level III estimates result in correlation coefficients of 0.46-0.86 and RMSE values of less than 1.3 cm (0.5 in). Few outliers are observed for each data pair and are evaluated against precipitation classification products (WSR-88D Hybrid Hydrometeor Classification product and MRMS Precipitation Flag product). The rain gauges used in this study are not part of the Hydrometeorological Automated Data System (HADS) network used to correct the MRMS estimates and therefore, results of this work provide an independent validation of the MRMS gauge correction scheme.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

CROCUS Tipping Bucket Rain Gauge Data from Argonne Deployable Mast Deployed at Argonne National Laboratory During Urban Flooding Campaign

The Tipping Bucket Rain Gauge (TBRG) dataset contains data from a non-heated Met One 12-inch tipping bucket rain gauge that was mounted on the Argonne Deployable Mast (ADM). The ADM is a rapid deployable meteorological trailer that can be outfitted with instrumentation to measure urban heat island effects, urban flooding or urban flux measurements. During the urban flooding field campaign, the ADM was outfitted with multiple precipitation measurement systems, including the TBRG. This dataset contains one minute measurements for precipitation accumulation during the ADM's deployment at the Argonne Testbed for Multiscale Observational Science (ATMOS) site. These data are helpful for identifying periods of precipitation, leading to potential flooding. TBRGs can be used to validate optical rain gauge data and disdrometer data collected during the CROCUS urban flooding campaign. Data were collected at ATMOS, a 20-acre prairie site at Argonne National Laboratory in Lemont, Illinois. The data is presented as daily NetCDF (.nc) files, each containing approximately 24 hours of observations. Files follow the naming convention of: the project (CROCUS), location (ADM-atmos), instrument name (tbrg), data level (raw, a1), and date (year, month, day). The NetCDF format can be accessed using common scientific software such as Python using xarray, netCDF4 or act-doe.

1-min Precipitation Accumulation↗
DOE OSTI2026

CROCUS Tipping Bucket Rain Gauge Data from Argonne Deployable Mast Deployed at NEIU Carruthers Center for Inner City Studies (CCICS)

The Tipping Bucket Rain Gauge (TBRG) dataset contains data from a non-heated Met One 12-inch tipping bucket rain gauge that was mounted on the Argonne Deployable Mast (ADM). The ADM is a rapid deployable meteorological trailer that can be outfitted with instrumentation to measure urban heat island effects, urban flooding or urban flux measurements. During the urban flooding field campaign, the ADM was outfitted with multiple precipitation measurement systems, including the TBRG. This dataset contains one minute measurements for precipitation accumulation during the ADM's deployment at the Northeastern Illinois University (NEIU) Carruthers Center for Inner City Studies (CCICS) campus. These data are helpful for identifying periods of precipitation, leading to potential flooding. TBRGs can be used to validate optical rain gauge data and disdrometer data collected during the CROCUS urban flooding campaign. Data were collected at the CCICS building parking lot, located in the south side of Chicago, IL. The data is presented as daily NetCDF (.nc) files, each containing approximately 24 hours of observations. Files follow the naming convention of: the project (CROCUS), location (ADM-ccics), instrument name (tbrg), data level (raw, a1), and date (year, month, day). The NetCDF format can be accessed using common scientific software such as Python using xarray, netCDF4 or act-doe.

1-minute Precipitation Accumulation↗
DOE OSTI2016

Rain Gauges Handbook

To improve the quantitative description of precipitation processes in climate models, the Atmospheric Radiation Measurement (ARM) Climate Research Facility deployed rain gauges located near disdrometers (DISD and VDIS data streams). This handbook deals specifically with the rain gauges that make the observations for the RAIN data stream. Other precipitation observations are made by the surface meteorology instrument suite (i.e., MET data stream).

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Optical Rain Gauge Instrument Handbook

To improve the quantitative description of precipitation processes in climate models, the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility deploys several types of rain gauges (MET, RAIN, and optical rain gauge [ORG] datastreams) as well as disdrometers (DISD and VDIS datastreams) at the Southern Great Plains (SGP) Site. This handbook deals specifically with the independent analog ORG (i.e., the ORG datastream).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Quasar Rain: The Broad Emission Line Region as Condensations in the Warm Accretion Disk Wind

The origin of the broad emission line region (BELR) in quasars and active galactic nuclei is still unclear. I propose that condensations form in the warm, radiation-pressure-driven, accretion disk wind of quasars creating the BEL clouds and uniting them with the other two manifestations of cool (∼10{sup 4} K) gas in quasars, the low ionization phase of the warm absorbers (WAs) and the clouds causing X-ray eclipses. The cool clouds will condense quickly (days to years), before the WA outflows reach escape velocity (which takes months to centuries). Cool clouds form in equilibrium with the warm phase of the wind because the rapidly varying X-ray quasar continuum changes the force multiplier, causing pressure waves to move gas into stable locations in pressure–temperature space. The narrow range of two-phase equilibrium densities may explain the (luminosity){sup 1/2} scaling of the BELR size, while the scaling of cloud formation timescales could produce the Baldwin effect. These dense clouds have force multipliers of order unity and so cannot be accelerated to escape velocity. They fall back on a dynamical timescale (months to centuries), producing an inflow that rains down toward the central black hole. As they soon move at Mach ∼10–100 with respect to the WA outflow, these “raindrops” will be rapidly destroyed within months. This rain of clouds may produce the elliptical BELR orbits implied by velocity-resolved reverberation mapping in some objects and can explain the opening angle and destruction timescale of the narrow “cometary” tails of the clouds seen in X-ray eclipse observations. Some consequences and challenges of this “quasar rain” model are presented, along with several avenues for theoretical investigation.

79 ASTRONOMY AND ASTROPHYSICS↗