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All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Potential of GPM IMERG Precipitation Estimates to Monitor Natural Disaster Triggers in Urban Areas: the Case of Rio deJaneiro, Brazil

Extreme rainfall can be a catastrophic trigger for natural disaster events at urban scales. However, there remains large uncertainties as to how satellite precipitation can identify these triggers at a city scale. The objective of this study is to evaluate the potential of satellite-based rainfall estimates to monitor natural disaster triggers in urban areas. Rainfall estimates from the Global Precipitation Measurement (GPM) mission are evaluated over the city of Rio de Janeiro, Brazil, where urban floods and landslides occur periodically as a result of extreme rainfall events. Two rainfall products derived from the Integrated Multi-satellite Retrievals for GPM (IMERG), the IMERG Early and IMERG Final products, are integrated into the Noah Multi-Parameterization (Noah-MP) land surface model in order to simulate the spatial and temporal dynamics of two key hydrometeorological disaster triggers across the city over the wet seasons during 2001-2019. Here, total runoff (TR) and rootzone soil moisture (RZSM) are considered as flood and landslide triggers, respectively. Ground-based observations at 33 pluviometric stations are interpolated, and the resulting rainfall fields are used in an in-situ precipitation-based simulation, considered as the reference for evaluating the IMERG-driven simulations. The evaluation is performed during the wet seasons (November-April), when average rainfall over the city is 4.4mm/day. Results show that IMERG products show low spatial variability at the city scale, generally overestimate rainfall rates by 12-35%, and impacts on TR and RZSM vary spatially mostly as a function of land cover and soil types. Results based on statistical and categorical metrics show that IMERG skill in detecting extreme events is moderate, with IMERG Final performing slightly better for most metrics. By analyzing two recent storms, we observe that IMERG detects mostly hourly extreme events, but underestimates rainfall rates, resulting in underestimated TR and RZSM. An evaluation of normalized time series using percentiles shows that both satellite products have significantly improved skill in detecting extreme events when compared to the evaluation using absolute values, indicating that IMERG precipitation could be potentially used as a predictor for natural disasters in urban areas.

IMERG↗
DOE OSTI2019

The dynamic and thermodynamic structure of the monsoon over southern India: New observations from the INCOMPASS IOP

Some of the highest summer monsoon rainfall in South Asia falls on the windward slopes of the Western Ghats mountains on India's west coast and offshore over the eastern Arabian Sea. Understanding of the processes determining the spatial distribution and temporal variability of this region remains incomplete. In this paper, new Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) aircraft and ground‐based measurements of the summer monsoon over the Western Ghats and upstream of them are presented and placed within the context of remote‐sensing observations and reanalysis. The transition from widespread rainfall over the eastern Arabian Sea to rainfall over the Western Ghats is documented in high spatial and temporal resolution. Heavy rainfall offshore during the campaign was associated primarily with mid‐tropospheric humidity, secondarily with sea surface temperature, and only weakly with orographic blocking. A mid‐tropospheric dry intrusion suppressed deep convection offshore in the latter half of the campaign, allowing the build‐up of low‐level humidity in the onshore flow and enhancing rainfall over the mountains. Rainfall on the lee side of the Western Ghats occurred during the latter half of the campaign in association with enhanced mesoscale easterly upslope flow. Diurnal cycles in rainfall offshore (maximum in the morning) and on the mountains (maximum in the afternoon) were observed. Considerable zonal and temporal variability was seen in the offshore boundary layer, suggesting the presence of convective downdraughts and cold pools. Persistent drying of the subcloud mixed layer several hundred kilometres off the coast was observed, suggesting strong mixing between the boundary layer and the free troposphere. These observations provide quantitative targets to test models and suggest hypotheses on the physical mechanisms determining the distribution and variability in rainfall in the Western Ghats region.

Fletcher, Jennifer K.↗
DOE OSTI2018

Role of Troposphere-Convection-Land Coupling in the Southwestern Amazon Precipitation Bias of the Community Earth System Model version 1 (CESM1)

The Amazon forest plays an important role in the tropical circulation and global water and biogeochemical cycles. However, the common Amazon precipitation biases in global climate models undermine our ability to understand future changes in the Amazon and their global consequences. The Community Earth System Model exhibits a persistent wet season dry bias over the southwestern Amazon. The bias is also characterized by inaccurate diurnal timing and intensity of rainfall events. Analysis of a diverse set of simulations suggests that the bias originates from local processes. A known land model bias in the partitioning of surface energy fluxes is found not to contribute significantly to the rainfall bias. Key model processes are identified to be the low-level divergent circulation controlling horizontal moisture flow and the sensitivity of the modeled deep convection to the lower tropospheric moisture. The lower tropospheric moisture divergence dictates the spatiotemporal distributions of convective precipitation through parameterized entrainment mixing, which generally improves the rainfall diurnal cycle. However, it also limits convective precipitation over the areas with frequent and large-scale divergence in the lower troposphere. The southwestern Amazon is such an area, particularly in the late afternoon, although uncertainty exists in the low-level flow in the simulation and reanalyses. One way to sustain rainfall in the presence of low-level divergence is a convective trigger based on both the moisture and temperature changes by large-scale processes, which is shown to help in reducing the dry bias.

Sakaguchi, Koichi↗
DOE OSTI2025

Ubiquity and Causes of Soil Water Preferential Flow Across 17 Ecoregions

Abstract Preferential flow (PF) in soil causes the rapid transport of water, nutrients, and contaminants into the subsurface, influencing groundwater recharge and streamflow. Data scarcity has hindered the quantification of PF occurrence and the identification of its drivers across diverse ecoregions. We address this gap by analyzing high‐frequency, multi‐depth soil moisture data across 17 ecoregions in the USA, using ∼1,500 sensors at 40 sites. We discovered that PF is widespread, with sites experiencing PF in up to 60% of rainfall events ≥2 mm. Multiple approaches consistently show that PF is more likely to occur with increased peak rainfall intensity, finer textured material, low soil moisture variability, humid climate, and higher net primary productivity. This suggests that PF patterns could shift with projected climate changes, increasing uncertainty in predictions of groundwater recharge, water quality, and streamflow generation. Plain Language Summary Water can bypass part of the soil's matrix through a process called preferential flow (PF). This quick transport of water through the soil brings with it nutrients and contaminants and eventually makes it to groundwater and streams. To ensure ample amounts of good quality groundwater and surface water we need to understand when and where PF occurs. We inferred when PF occurred at 40 different sites across 17 ecoregions in the USA using soil moisture and rainfall data. We found that PF happened at all sites and in up to 60% of rainfall events ≥2 mm. Preferential flow was most likely at sites with high rainfall intensities, high clay content in soils, low variability in soil moisture, and high vegetation productivity. As rainfall intensities are predicted to increase due to climate change and vegetation becomes more productive, PF occurrence becomes more important for predicting groundwater recharge, water quality, and streamflow generation. Key Points Preferential flow (PF) is ubiquitous across the USA and occurs in up to 60% of all rainfall events ≥2 mm Rainfall intensity, soil texture, and antecedent soil moisture emerge as critical in generating PF across diverse ecoregions Two different PF detection approaches show similar relationships between key drivers and occurrence of PF

Li, Bonan↗
DOE OSTI2014

Parameter Tuning and Calibration of RegCM3 with MIT-Emanuel Cumulus Parameterization Scheme over CORDEX East Asian Domain

In this study, we calibrated the performance of regional climate model RegCM3 with Massachusetts Institute of Technology (MIT)-Emanuel cumulus parameterization scheme over CORDEX East Asia domain by tuning the selected seven parameters through multiple very fast simulated annealing (MVFSA) sampling method. The seven parameters were selected based on previous studies, which customized the RegCM3 with MIT-Emanuel scheme through three different ways by using the sensitivity experiments. The responses of model results to the seven parameters were investigated. Since the monthly total rainfall is constrained, the simulated spatial pattern of rainfall and the probability density function (PDF) distribution of daily rainfall rates are significantly improved in the optimal simulation. Sensitivity analysis suggest that the parameter “relative humidity criteria” (RH), which has not been considered in the default simulation, has the largest effect on the model results. The responses of total rainfall over different regions to RH were examined. Positive responses of total rainfall to RH are found over northern equatorial western Pacific, which are contributed by the positive responses of explicit rainfall. Followed by an increase of RH, the increases of the low-level convergence and the associated increases in cloud water favor the increase of the explicit rainfall. The identified optimal parameters constrained by the total rainfall have positive effects on the low-level circulation and the surface air temperature. Furthermore, the optimized parameters based on the extreme case are suitable for a normal case and the model’s new version with mixed convection scheme.

emanual cumulus parameterization↗
NASA NTRS1999

Vertical Profiles of Latent Heat Release and Their Retrieval for TOGA COARE Convective Systems Using a Cloud Resolving Model, SSM/I, and Ship-borne Radar Data

Latent heating profiles associated with three (TOGA COARE) Tropical Ocean and Global Atmosphere Coupled Ocean Atmosphere Response Experiment active convective episodes (December 10-17 1992; December 19-27 1992; and February 9-13 1993) are examined using the Goddard Cumulus Ensemble (GCE) Model and retrieved by using the Goddard Convective and Stratiform Heating (CSH) algorithm . The following sources of rainfall information are input into the CSH algorithm: Special Sensor Microwave Imager (SSM/1), Radar and the GCE model. Diagnostically determined latent heating profiles calculated using 6 hourly soundings are used for validation. The GCE model simulated rainfall and latent heating profiles are in excellent agreement with those estimated by soundings. In addition, the typical convective and stratiform heating structures (or shapes) are well captured by the GCE model. Radar measured rainfall is smaller than that both estimated by the GCE model and SSM/I in all three different COARE IFA periods. SSM/I derived rainfall is more than the GCE model simulated for the December 19-27 and February 9-13 periods, but is in excellent agreement with the GCE model for the December 10-17 period. The GCE model estimated stratiform amount is about 50% for December 19-27, 42% for December 11-17 and 56% for the February 9-13 case. These results are consistent with large-scale analyses. The accurate estimates of stratiform amount is needed for good latent heating retrieval. A higher (lower) percentage of stratiform rain can imply a maximum heating rate at a higher (lower) altitude. The GCE model always simulates more stratiform rain (10 to 20%) than the radar for all three convective episodes. SSM/I derived stratiform amount is about 37% for December 19-27, 48% for December 11-17 and 41% for the February 9-13 case. Temporal variability of CSH algorithm retrieved latent heating profiles using either GCE model simulated or radar estimated rainfall and stratiform amount is in good agreement with that diagnostically determined for all three periods. However, less rainfall and a smaller stratiform percentage estimated by radar resulted in a weaker (underestimated) latent heating profile and a lower maximum latent heating level compared to those determined diagnostically. Rainfall information from SSM/I can not retrieve individual convective events due to poor temporal sampling. Nevertheless, this study suggests that a good 4r, rainfall retrieval from SSM/I for a convective event always leads to a good latent heating retrieval. Sensitivity testing has been performed and the results indicate that the SSM/I derived time averaged stratiform amount may be underestimated for December 19-27. Time averaged heating profiles derived from SSM/I, however, are not in bad agreement with those derived by soundings for the December 10-17 convective period. The heating retrievals may be more accurate for longer time scales provided there is no bias in the sampling.

Tao, Wei-Kuo↗
NASA NTRS2000

Effect of Combined Spaceborne Microwave and Continuous Lightning Measurements on Precipitation Forecasts of the 1998 Ground-Hog Day Storm

We evaluated the impact of several newly available sources of meteorological data on mesoscale model forecasts of precipitation produced by the extra-tropical cyclone that struck Florida on February 2, 1998. Precipitation distributions of convective rainfall events were derived from Special Sensor Microwave Imager (SSM/I) and Multi-Channel Passive Microwave Sensor (TMI) microwave radiometric data by means of the Goddard PROFiling (GPROF) algorithm. Continuous lightning distributions were obtained from sferics measurements obtained from a network of VLF radio receivers. Histograms of coincident sferics frequency distributions were matched to those of precipitation to derive bogus convective rainfall rates from the continuously available sferics measurements. SSM/I and TMI microwave data were used to derive Integrated Precipitable Water (IPW) distributions. The TMI also provided sea surface temperatures (SSTS) of the Loop Current and Gulf Stream with improved structural detail. A series of experiments assimilated IPW and latent heating from the bogus convective rainfall for six-hours in the MM5 mesoscale forecast model to produce nine-hour forecasts of all rainfall as well as other weather parameters. Although continuously assimilating latent heating only slightly improved the surface pressure distribution forecast, it significantly improved the precipitation forecasts. Correctly locating convective rainfall was found critical for assimilating latent heating in the forecast model, but measurement of the rainfall intensity proved to be less important. The improved SSTs also had a positive impact on rainfall forecasts for this case. Assimilating bogus rainfall in the model produced nine-hour forecasts of radar reflectivity distributions that agreed well with coincident observations from the TRMM spaceborne precipitation radar, ground based radar and spaceborne microwave measurements.

Weinman, James A.↗
NASA NTRS2003

Seasonal Evolution and Variability Associated with the West African Monsoon System

In this study, we investigate the seasonal variations in surface rainfall and associated large-scale processes in the tropical eastern Atlantic and West African region. The 5-yr (1998-2002) high-quality TRMM rainfall, sea surface temperature (SST), water vapor and cloud liquid water observations are applied along with the NCEP/NCAR reanalysis wind components and a 3-yr (2000-2002) Quickscat satellite-observed surface wind product. Major mean rainfall over West Africa tends to be concentrated in two regions and is observed in two different seasons, manifesting an abrupt shift of the mean rainfall zone during June-July. (i) Near the Gulf of Guinea (about 5 degN), intense convection and rainfall are seen during April-June and roughly follow the seasonality of SST in the tropical eastern Atlantic. (ii) Along the latitudes of about 10 deg. N over the interior West African continent, a second intense rain belt begins to develop from July and remains there during the later summer season. This belt co-exists with a northwardmoved African Easterly Jet (AEJ) and its accompanying horizonal and vertical shear zones, the appearance and intensification of an upper tropospheric Tropical Easterly Jet (TEJ), and a strong low-level westerly flow. Westward-propagating wave signals [ i e . , African easterly waves (AEWs)] dominate the synoptic-scale variability during July-September, in contrast to the evident eastward-propagating wave signals during May- June. The abrupt shift of mean rainfall zone thus turns out to be a combination of two different physical processes: (i) Evident seasonal cycles in the tropical eastern Atlantic ocean which modulate convection and rainfall in the Gulf of Guinea by means of SST thermal forcing and SST-related meridional gradient; (ii) The interaction among the AEJ, TEJ, low-level westerly flow, moist convection and AEWs during July-September which modulates rainfall variability in the interior West Africa, primarily within the ITCZ rain band. Evident seasonality in synoptic-scale wave signals is shown to be a good evidence for this seasonal evolution.

Gu, Guojun↗
NASA NTRS2003

High-Resolution Simulation of Hurricane Bonnie (1998): The Organization of Vertical Motion - Part 1

Hurricanes are well known for their strong winds and heavy rainfall, particularly in the intense rainband (eyewall) surrounding the calmer eye of the storm. In some hurricanes, the rainfall is distributed evenly around the eye so that it has a donut shape on radar images. In other cases, the rainfall is concentrated on one side of the eyewall and nearly absent on the other side and is said to be asymmetric. This study examines how the vertical air motions that produce the rainfall are distributed within the eyewall of an asymmetric hurricane and the factors that cause this pattern of rainfall. We use a sophisticated numerical forecast model to simulate Hurricane Bonnie, which occurred in late August of 1998 during a special NASA field experiment designed to study hurricanes. The simulation results suggest that vertical wind shear (a rapid change in wind speed or direction with height) caused the asymmetric rainfall and vertical air motion patterns by tilting the hurricane vortex and favoring upward air motions in the direction of tilt. Although the rainfall in the hurricane eyewall may surround more than half of the eye, the updrafts that produce the rainfall are concentrated in very small-scale, intense updraft cores that occupy only about 10% of the eyewall area. The model simulation suggests that the timing and location of individual updraft cores are controlled by intense, small-scale vortices (regions of rapidly swirling flow) in the eyewall and that the updrafts form when the vortices encounter low-level air moving into the eyewall.

Braun, Scott A.↗
NASA NTRS2004

Studying the Diurnal Cycle of Convection Using a TRMM-Calibrated Infrared Rain Algorithm

The development of a satellite infrared (IR) technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall on a global scale is presented. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the global tropics. The technique makes use of the IR data from the TRMM Visible/Infrared Scanner (VIRS) before application to global geosynchronous satellite data. The calibrated CST technique has the advantages of high spatial resolution (4 km), filtering of non-raining cirrus clouds, and the stratification of the rainfall into its convective and stratiform components, the last being important for the calculation of vertical profiles of latent heating. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall will be presented. The technique is validated using available data sets and compared to other global rainfall products such as Global Precipitation Climatology Project (GPCP) IR product, calibrated with TRMM Microwave Imager (TMI) data. Results from five years of PR data will show the global-tropical partitioning of convective and stratiform rainfall.

Negri, Andrew J.↗
NASA NTRS2005

Studying the Diurnal Cycle of Convection Using a TRMM-Calibrated Infrared Rain Algorithm

The development of a satellite infrared (IR) technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall on a global scale is presented. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the global tropics. The technique makes use of the IR data from the TRMM Visible/Infrared Scanner (VIRS) before application to global geosynchronous satellite data. The calibrated CST technique has the advantages of high spatial resolution (4 km), filtering of nonraining cirrus clouds, and the stratification of the rainfall into its convective and stratiform components, the last being important for the calculation of vertical profiles of latent heating. The diurnal cycle of rainfall, as well as the division between convective and Stratiform rainfall will be presented. The technique is validated using available data sets and compared to other global rainfall products such as Global Precipitation Climatology Project (GPCP) IR product, calibrated with TRMM Microwave Imager (TMI) data. Results from five years of PR data will show the global-tropical partitioning of convective and stratiform rainfall.

Negri, Andrew J.↗
NASA NTRS2011

Toward a Framework for Systematic Error Modeling of NASA Spaceborne Radar with NOAA/NSSL Ground Radar-Based National Mosaic QPE

Characterization of the error associated to satellite rainfall estimates is a necessary component of deterministic and probabilistic frameworks involving space-born passive and active microwave measurement") for applications ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. We focus here on the error structure of NASA's Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) quantitative precipitation estimation (QPE) at ground. The problem is addressed by comparison of PR QPEs with reference values derived from ground-based measurements using NOAA/NSSL ground radar-based National Mosaic and QPE system (NMQ/Q2). A preliminary investigation of this subject has been carried out at the PR estimation scale (instantaneous and 5 km) using a three-month data sample in the southern part of US. The primary contribution of this study is the presentation of the detailed steps required to derive trustworthy reference rainfall dataset from Q2 at the PR pixel resolution. It relics on a bias correction and a radar quality index, both of which provide a basis to filter out the less trustworthy Q2 values. Several aspects of PR errors arc revealed and quantified including sensitivity to the processing steps with the reference rainfall, comparisons of rainfall detectability and rainfall rate distributions, spatial representativeness of error, and separation of systematic biases and random errors. The methodology and framework developed herein applies more generally to rainfall rate estimates from other sensors onboard low-earth orbiting satellites such as microwave imagers and dual-wavelength radars such as with the Global Precipitation Measurement (GPM) mission.

Kirstettier, Pierre-Emmanual↗
DOE OSTI2015

Stochastic generation of hourly rainstorm events in Johor

Engineers and researchers in water-related studies are often faced with the problem of having insufficient and long rainfall record. Practical and effective methods must be developed to generate unavailable data from limited available data. Therefore, this paper presents a Monte-Carlo based stochastic hourly rainfall generation model to complement the unavailable data. The Monte Carlo simulation used in this study is based on the best fit of storm characteristics. Hence, by using the Maximum Likelihood Estimation (MLE) and Anderson Darling goodness-of-fit test, lognormal appeared to be the best rainfall distribution. Therefore, the Monte Carlo simulation based on lognormal distribution was used in the study. The proposed model was verified by comparing the statistical moments of rainstorm characteristics from the combination of the observed rainstorm events under 10 years and simulated rainstorm events under 30 years of rainfall records with those under the entire 40 years of observed rainfall data based on the hourly rainfall data at the station J1 in Johor over the period of 1972–2011. The absolute percentage error of the duration-depth, duration-inter-event time and depth-inter-event time will be used as the accuracy test. The results showed the first four product-moments of the observed rainstorm characteristics were close with the simulated rainstorm characteristics. The proposed model can be used as a basis to derive rainfall intensity-duration frequency in Johor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Pan-YANG/RA-ABM

Crowd-sourcing incorporates common citizens as rich sources of data and is promising for environmental monitoring. In this paper, we propose and test the idea of incorporating incentives to crowd-sourcing management for rainfall monitoring. Specifically, we modeled the allocation of incentives (quantitatively measurable and limited rewards) among crowd-sourcing participants for a theoretical rainfall monitoring case. For this purpose, we developed an integrated model comprising a reward allocation component to represent the decision‐making process of a central manager, an agent‐based model to simulate the interactions between the manager and participants, and a rainfall simulation model to evaluate the effectiveness of various reward allocation policies. We simulated six reward allocation policies of varying levels of administrative cost, and consideration of participant and rainfall spatial heterogeneities. The results suggest the performance of each policy to improve with the reward budget and their spatial uniformity. Among the six policies tested, we found that the participant density weighted maximum participation policy yields the most accurate estimation of rainfall intensity due to its more explicit consideration of the spatial distribution of participants; however, this policy associates with a high administrative cost. This highlights the trade‐off between performance and cost in designing effective reward allocation policies. This paper provides a physical and behavior simulation modeling tool to study the feasibility and complexity of reward‐based participant management for crowd-sourcing rainfall monitoring. The proposed crowd-sourcing method is beneficial for a wide range of applications that require rainfall data with fine resolution, such as stormwater management and water availability and biomass assessment for food and energy crops.

Yang, Pan↗
DOE OSTI2014

Persistence of systematic errors in the Asian-Australian monsoon precipitation basic states in climate models: a way forward

The annual cycle of the Asian-Australian monsoon (AAM) system can be regarded as the seasonal displacement of the large-scale Intertropical Convergence Zone (ITCZ), which is anchored by the north-south migration of the Indo-Pacific warm pool. In the respective hemispheres, intense solar heating over land during spring and early summer provide the necessary thermodynamic conditions for the occurrence of deep convection off the equator. The rainfall and diabatic heating associated with the AAM is perhaps the most vigorous of all the regional monsoon components in the globe. Yet, skill in monsoon prediction (days to seasons) by dynamical models remains low, partly due to our lack of understanding of the entirety of the monsoon system and our inability to model the interactive processes that govern it. Simulating the monsoon precipitation climatology remains a grand challenge. The multi-model mean (MMM) errors for summertime precipitation relative to GPCP observations have shown little improvement in CMIP5 as compared to CMIP3. For the Asian Summer Monsoon, the MMM monsoon rainfall is weaker over South Asia, the western equatorial Indian Ocean and tropical West Pacific. For the Australian summer monsoon, it is excessive over most of the Maritime Continent, and deficient over northern Australia. Throughout the year, excessive rainfall is simulated over South China Sea – Maritime Continent regions, and CMIP5 models do not capture the annual cycle of the AAM. One implication is that uncertainties in future projections (e.g., IPCC 2013) of AAM mean rainfall may not have reduced from CMIP3 to CMIP5. Solutions from an intermediate model show that diabatic heating (Q) associated with the AAM influences the global circulation. Compared to the reanalysis, many models tend to have maxima at the mid-troposphere but their simulated amplitude is overestimated in the lower troposphere (900-700 hPa) and underestimated from 600-300 hPa, a feature readily apparent in the MMM composite (dashed black line). The lower troposphere peak may be attributed to misrepresentations in shallow convection. Some outliers, such as CSIROMk3- 6-0 and ACCESS1-3, do not show any appreciable vertical structure, and the simulated monsoon over South Asia is virtually absent in these models. TRMM observations indicate that over the monsoon region the contribution from stratiform rainfall is about 40% to the Q intensity. In contrast, most of the CMIP3 models produce too much convective rainfall (95% of the total) and too little stratiform precipitation. Given the persistence of errors, we speculate that errors in the partitioning of total rainfall into convective-stratiform still persist in CMIP5, and may be one of the reasons for underestimation (overestimation) of Q in the layer 600-300 (900-700) hPa. In summary, the rather slow progress in modeling in the last decade or so led us to wonder: Has the scientific community reached a “plateau” in modeling mean monsoon precipitation?

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1978

The rain parameter diagram - Methods and applications

A rain parameter diagram is presented which displays the relationships between all rainfall parameters defined in terms of an exponential drop size distribution. Special emphasis is given to remotely measurable quantities such as radar reflectivity, microwave attenuation, and optical extinction. Although an exponential distribution is used to construct the diagram, it is shown to have general application for arbitrary size distributions and for a wide variety of rainfall-related problems. Some of the problems are: analysis of the sources of error which result from the use of empirical rainfall relations; depiction of the physical differences between different types of rainfall and of the similarity between all empirical relations which apply to the same type of rainfall; and determination of the accuracy with which remote measurements must be made to obtain accurate rain parameters. A set of overlays is shown for four common radar wavelengths and four temperatures which display the relationships between microwave attenuation and the other rainfall parameters. These diagrams can be used to determine rainfall parameters remotely in dual-measurement techniques.

Ulbrich, C. W.↗
NASA NTRS1991

Estimation of the diurnal cycle of oceanic precipitation from SSM/I data

A study of differences between the morning and evening monthly rainfall for 5 x 5 deg cells over the oceans from the SSM/I data has been conducted. The monthly rainfalls are estimated from the technique given by Wilheit et al. The difference between the morning and evening monthly rainfall arises due to the various random errors involved in the retrieval process, the sampling error in the observations, and the diurnal component of oceanic rainfall. The diurnal component is weak but clearly visible when averaged over large areas and for long time periods. The analysis shows that morning rainfall is consistently greater than evening rainfall. The Northern Hemisphere seem to have a larger diurnal variation than does the Southern Hemisphere. The maximum ratio between the morning and evening monthly rainfall is 1.7 while 1.2 is the more typical value.

Sharma, Awdhesh K.↗
NASA NTRS1993

International Conference on Mesoscale Precipitation: Hydrologic and Meteorological Aspects, 3rd, College Station, TX, Feb. 27-Mar. 1, 1991, Proceedings

Papers presented in this volume discuss a mechanism causing mesoscale organizations of precipitation in midlatitude cyclones, the spatial variability of summer Florida precipitation and its impact on microwave radiometer rainfall-measurement systems, the relation between the mean areal rainfall and the fractional area where it rains above a given threshold, and a possible explanation for low correlation dimension estimates for the atmosphere. Attention is also given to a physically based simulation of radar rainfall data using a space-time rainfall model, the predictability of mesoscale rainfall in the tropics, and an intercomparison of tree satellite infrared rainfall techniques over Japan and surrounding waters. Other papers are on an evaluation of sampling errors of precipitation from spaceborne and ground sensors, an approach to the estimation of the areal rain-rate distribution from spaceborne radar by the use of multiple thresholds, and a comparison of two satellite-based rainfall algorithms using Pacific atoll raingage data.

Valdes, Juan B.↗