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At least 811 records · Page 45

Effects of Uncertainty in TRMM Precipitation Radar Path Integrated Attenuation on Interannual Variations of Tropical Oceanic Rainfall

Considerable uncertainty surrounds the issue of whether precipitation over the tropical oceans (30 deg N/S) systematically changes with interannual sea-surface temperature (SST) anomalies that accompany El Nino (warm) and La Nina (cold) events. Time series of rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM Precipitation Radar (PR) over the tropical oceans show marked differences with estimates from two TRMM Microwave Imager (TMI) passive microwave algorithms. We show that path-integrated attenuation derived from the effects of precipitation on the radar return from the ocean surface exhibits interannual variability that agrees closely with the TMI time series. Further analysis of the frequency distribution of PR (2A25 product) rain rates suggests that the algorithm incorporates the attenuation measurement in a very conservative fashion so as to optimize the instantaneous rain rates. Such an optimization appears to come at the expense of monitoring interannual climate variability.

Robertson, Franklin R.↗

A-Train Based Observational Metrics for Model Evaluation in Extratropical Cyclones

Extratropical cyclones contribute most of the precipitation in the midlatitudes, i.e. up to 70 during winter in the northern hemisphere, and can generate flooding, extreme winds, blizzards and have large socio-economic impacts. As such, it is important that general circulation models (GCMs) accurately represent these systems so their evolution in a warming climate can be understood. However, there are still uncertainties on whether warming will increase their frequency of occurrence, their intensity and how much rain or snow they bring. Part of the issue is that models have trouble representing their strength, but models also have biases in the amount of clouds and precipitation they produce. This is caused by potential issues in various aspects of the models: convection, boundary layer, and cloud scheme to only mention a few. In order to pinpoint which aspects of the models need improvement for a better representation of extratropical cyclone precipitation and cloudiness, we will present A-train based observational metrics: cyclone-centered, warm and cold frontal composites of cloud amount and type, precipitation rate and frequency of occurrence. Using the same method to extract similar fields from the model, we will present an evaluation of the GISS-ModelE2 and the IPSL-LMDZ-5B models, based on their AR5 and more recent versions. The AR5 version of the GISS model underestimates cloud cover in extratropical cyclones while the IPSL AR5 version overestimates it. In addition, we will show how the observed CloudSat-CALIPSO cloud vertical distribution across cold fronts changes with moisture amount and cyclone strength, and test if the two models successfully represent these changes. We will also show how CloudSat-CALIPSO derived cloud type (i.e. convective vs. stratiform) evolves across warm fronts as cyclones age, and again how this is represented in the models. Our third process-based analysis concerns cumulus clouds in the post-cold frontal region and how their amount relates to the stability of the boundary layer. This test uses Aqua cloud and vertical atmospheric profiles and when applied to the model output can help assess the accuracy of the convection, boundary layer and cloud scheme.

Convection clouds↗

Can ERA5 Be Used to Study Mesoscale Convective System Climatological Characteristics?

Mesoscale convective systems (MCSs) produce more than half of tropical rainfall and are central to the global hydrologic cycle. As the climate warms, environments favorable for MCSs may become more common; however, limited observational records hamper understanding of how MCSs respond to variations and changes in their environments. Here, we evaluate how well MCSs are represented in ERA5, a widely used global high‐resolution reanalysis product. Using PyFLEXTRKR, which jointly tracks top‐of‐atmosphere infrared brightness temperature and surface precipitation, we identified MCSs in ERA5 and compared them with those identified in satellite observations using the same detection algorithm. This comparison analysis spans 2007–2020 using hourly data at 0.25° horizontal resolution focusing over the tropics. ERA5 reproduces observed brightness‐temperature statistics and captures the geographic distribution and seasonal and diurnal cycles of MCS cold cloud shields. However, ERA5 precipitation exhibits an intensity bias—too much light rain and too little heavy rain—which shifts the rain‐rate distribution and reduces the frequency of MCSs relative to observations. Within MCSs, ERA5 precipitation exhibits the same pattern of bias, yielding a systematic underestimation of MCS precipitation intensity. Consistent with these biases, ERA5 underestimates the contribution of MCS to tropical rainfall by 25%–34% in key regions. Overall, ERA5 is suitable for studying MCS cold cloud‐shield climatology and evolution, but precipitation‐based MCS characteristics (including event‐level precipitation features and the geospatial distribution of MCS precipitation) should be interpreted with caution. These findings clarify which aspects of MCS behavior are robustly represented in ERA5 for climatological applications.

mesoscale convection↗

Estimating Sampling Biases and Measurement Uncertainties of AIRS-AMSU-A Temperature and Water Vapor Observations Using MERRA Reanalysis

We use MERRA (Modern Era Retrospective-Analysis for Research Applications) temperature and water vapor data to estimate the sampling biases of climatologies derived from the AIRS/AMSU-A (Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A) suite of instruments. We separate the total sampling bias into temporal and instrumental components. The temporal component is caused by the AIRS/AMSU-A orbit and swath that are not able to sample all of time and space. The instrumental component is caused by scenes that prevent successful retrievals. The temporal sampling biases are generally smaller than the instrumental sampling biases except in regions with large diurnal variations, such as the boundary layer, where the temporal sampling biases of temperature can be +/- 2 K and water vapor can be 10% wet. The instrumental sampling biases are the main contributor to the total sampling biases and are mainly caused by clouds. They are up to 2 K cold and greater than 30% dry over mid-latitude storm tracks and tropical deep convective cloudy regions and up to 20% wet over stratus regions. However, other factors such as surface emissivity and temperature can also influence the instrumental sampling bias over deserts where the biases can be up to 1 K cold and 10% wet. Some instrumental sampling biases can vary seasonally and/or diurnally. We also estimate the combined measurement uncertainties of temperature and water vapor from AIRS/AMSU-A and MERRA by comparing similarly sampled climatologies from both data sets. The measurement differences are often larger than the sampling biases and have longitudinal variations.

MERRA↗

Projected changes in extreme rainfall and temperature events and possible implications for Cameroon's socio-economic sectors

Extreme events like flooding, droughts and heatwave are among the factors causing huge socio-economic losses to Cameroonians. Investigating the potential response of rainfall and temperature extremes to global warming is therefore critically needed for tailoring and adjusting the country's policies. Recent datasets have been developed for this purpose within the Coordinated Output for Regional Evaluations (CORDEX-CORE) initiative, at ~25 km grid spacing. These regional climate models were used to dynamically downscaled four global climate models participating in the Coupled Model Intercomparison Project phase 5 (CMIP5), under the optimistic and pessimistic representative concentration pathways (RCPs) 2.6 and 8.5, respectively. These models were employed in this study for characterizing the response of Cameroon's extreme precipitation and temperature events to global warming, using seven indices defined by the Expert Team on Cli mate Change Detection and Indices. Under global warming, the maximum number of consecutive dry (wet) days' is expected to increase (decrease). However, the annual total rainfall amount is expected to increase, mainly due to the intensification of very wet days and daily rainfall intensity. Furthermore, the temperature-based indices reveal an increase (decrease) in the total annual hot (cold) days, and overall, changes intensify with increased radiative forcing. The high-mitigated low-emission pathway RCP2.6 features attenuated changes, and even sometimes adapts to reverse the sign of changes. Designing reliable policies to limit the risks associated with the above changes is required, as their socio-economic consequences are likely to include food insecurity, heat-related illness, population impoverishment, price rises and market instability.

54 ENVIRONMENTAL SCIENCES↗

North American Tropical Cyclone Landfall and SST: A Statistical Model Study

A statistical-stochastic model of the complete life cycle of North Atlantic (NA) tropical cyclones (TCs) is used to examine the relationship between climate and landfall rates along the North American Atlantic and Gulf Coasts. The model draws on archived data of TCs throughout the North Atlantic to estimate landfall rates at high geographic resolution as a function of the ENSO state and one of two different measures of sea surface temperature (SST): 1) SST averaged over the NA subtropics and the hurricane season and 2) this SST relative to the seasonal global subtropical mean SST (termed relSST). Here, the authors focus on SST by holding ENSO to a neutral state. Jackknife uncertainty tests are employed to test the significance of SST and relSST landfall relationships. There are more TC and major hurricane landfalls overall in warm years than cold, using either SST or relSST, primarily due to a basinwide increase in the number of storms. The signal along the coast, however, is complex. Some regions have large and significant sensitivity (e.g., an approximate doubling of annual major hurricane landfall probability on Texas from -2 to +2 standard deviations in relSST), while other regions have no significant sensitivity (e.g., the U.S. mid-Atlantic and Northeast coasts). This geographic structure is due to both shifts in the regions of primary TC genesis and shifts in TC propagation.

El Nino↗

Faster recovery of North Atlantic tropical cyclone-induced cold wakes in recent decades

Intense winds associated with tropical cyclones (TCs) generate surface ocean cooling in their wakes, which can persist for several weeks in their aftermath. While multi-decadal observations of the sea surface have shown a substantial warming of the ocean, long-term changes in cold wake recovery time remain largely unknown. Here we find a trend toward faster recovery of TC cold wakes in the Atlantic main development region (MDR) since 2001. This is due primarily to a decrease in the strength of the North Atlantic trade winds, which reduces evaporative cooling of the ocean. The faster damping of TC cold wakes has led to a significant increase in the intensification of subsequent TCs that encounter lingering wakes from prior TCs, with a magnitude that is about 9% of that from long-term warming of the ocean. Finally, earth system model simulations indicate that the observed decrease in the cold wake recovery time will likely continue into the future.

54 ENVIRONMENTAL SCIENCES↗

Important ice processes are missed by the Community Earth System Model (CESM) in Southern Ocean mixed–phase clouds: Bridging SOCRATES observations to model developments

Global climate models (GCMs) are challenged by difficulties in simulating cloud phase and cloud radiative effect over the Southern Ocean (SO). Some of the new generation GCMs predict too much liquid and too little ice in mixed-phase clouds. This misrepresentation of cloud phase in GCMs results in weaker negative cloud feedback over the SO and a higher climate sensitivity. Based on a model comparison with observational data obtained during the Southern Ocean Cloud Radiation and Aerosol Transport Experimental Study (SOCRATES), this study addresses a key uncertainty in the Community Earth System Model version 2 (CESM2) related to cloud phase, namely ice formation in pristine remote SO clouds. It is found that sea spray organic aerosols (SSOA) are the most important type of ice nucleating particles (INPs) over the SO with concentrations one order of magnitude higher than those of dust INPs based on measurements and CESM2 simulations. Secondary ice production (SIP) which includes riming splintering, rain droplet shattering, and ice-ice collisional fragmentation as implemented in CESM2 is the dominant ice production process in moderately cold clouds with cloud temperatures greater than –20°C. SIP enhances the in-cloud ice number concentrations (Ni) by 1-3 orders of magnitude and predicts more mixed-phase (with percentage occurrence increased from 15% to 21%), in better agreement with the observations. Finally, this study highlights the importance of accurately representing cloud phase over the pristine remote SO by considering the ice nucleation of SSOA and SIP processes, which are currently missing in most GCM cloud microphysics parameterizations.

54 ENVIRONMENTAL SCIENCES↗

Source apportionment of VOCs, IVOCs and SVOCs by positive matrix factorization in suburban Livermore, California

Abstract. Gas- and particle-phase molecular markers provide highly specific information about the sources and atmospheric processes that contribute to air pollution. In urban areas, major sources of pollution are changing as regulation selectively mitigates some pollution sources and climate change impacts the surrounding environment. In this study, a comprehensive thermal desorption aerosol gas chromatograph (cTAG) was used to measure volatile, intermediate-volatility and semivolatile molecular markers every other hour over a 10 d period from 11 to 21 April 2018 in suburban Livermore, California. Source apportionment via positive matrix factorization (PMF) was performed to identify major sources of pollution. The PMF analysis identified 13 components, including emissions from gasoline, consumer products, biomass burning, secondary oxidation, aged regional transport and several factors associated with single compounds or specific events with unique compositions. The gasoline factor had a distinct morning peak in concentration but lacked a corresponding evening peak, suggesting commute-related traffic emissions are dominated by cold starts in residential areas. More monoterpene and monoterpenoid mass was assigned to consumer product emissions than biogenic sources, underscoring the increasing importance of volatile chemical products to urban emissions. Daytime isoprene concentrations were controlled by biogenic sunlight- and temperature-dependent processes, mediated by strong midday mixing, but gasoline was found to be the dominant and likely only source of isoprene at night. Biomass burning markers indicated residential wood burning activity remained an important pollution source even in the springtime. This study demonstrates that specific high-time-resolution molecular marker measurements across a wide range of volatility enable more comprehensive pollution source profiles than a narrower volatility range would allow.

54 ENVIRONMENTAL SCIENCES↗

Tropical Tropopause Structure and Processes as Observed with GPS Radio Occultation

The vertical temperature structure of the tropical atmosphere has been explained as controlled by the combined effect of three green house gases: water vapor, carbon dioxide, and ozone. Absorption by water vapor of the light reflected off the Earth's surface would determine the temperature lapse rate in the lower troposphere up to the bottom of the Tropical Transition Layer (TTL); radiative absorption by carbon dioxide would dominate the temperature lapse rate between the bottom of the TTL and the coldest point in the upper-troposphere, the cold point tropopause (CPT), and; absorption of incoming solar radiation by ozone would control the temperature above the CPT. The TTL region can thus be very sensitive to changes in the relative abundances of these greenhouse gases. In this contribution we describe the seasonal evolution of temperature profiles in the TTL and their longitudinal structure using GPS radio occultation.

global positioning system (GPS)↗

Measurement of SST and SSS Using Frequencies in the Range 0.3–2.0 GHz

Wide bandwidth radiometer systems that make measurements at multiple frequencies in the range from 300 MHz to 2 GHz have been proposed to address parameters important for understanding issues in the cryosphere associated with climate change such as ice sheet thickness and temperature. It is also possible with such a system to retrieve sea surface salinity (SSS), which is important for understanding the impact of climate change on ocean circulation at high latitude. In contemporary sensors for retrieving SSS, such as on Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP), sea surface temperature (SST), another parameter important for understanding ocean circulation and necessary in the retrieval of salinity, is treated as an ancillary parameter obtained from an independent source. However, both SSS and SST have peaks in sensitivity below 1 GHz; and it has been shown that measurements at multiple frequencies in this portion of the spectrum can take advantage of this peak in sensitivity to improve the accuracy of the retrieval of SSS. In this manuscript, it will be shown that there is also the potential to retrieve SST and, in cold water, the possibility for improved accuracy over existing retrievals.

Microwave remote sensing↗

Landslides in West Coast Metropolitan Areas: The Role of Extreme Weather Events

Rainfall-induced landslides represent a pervasive issue in areas where extreme rainfall intersects complex terrain. A farsighted management of landslide risk requires assessing how landslide hazard will change in coming decades and thus requires, inter alia, that we understand what rainfall events are most likely to trigger landslides and how global warming will affect the frequency of such weather events. We take advantage of 9 years of landslide occurrence data compiled by collating Google news reports and of a high-resolution satellite-based daily rainfall data to investigate what weather triggers landslide along the West Coast US. We show that, while this landslide compilation cannot provide consistent and widespread monitoring everywhere, it captures enough of the events in the major urban areas that it can be used to identify the relevant relationships between landslides and rainfall events in Puget Sound, the Bay Area, and greater Los Angeles. In all these regions, days that recorded landslides have rainfall distributions that are skewed away from dry and low-rainfall accumulations and towards heavy intensities. However, large daily accumulation is the main driver of enhanced hazard of landslides only in Puget Sound. There, landslide are often clustered in space and time and major events are primarily driven by synoptic scale variability, namely "atmospheric rivers" of high humidity air hitting anywhere along the West Coast, and the interaction of frontal system with the coastal orography. The relationship between landslide occurrences and daily rainfall is less robust in California, where antecedent precipitation (in the case of the Bay area) and the peak intensity of localized downpours at sub-daily time scales (in the case of Los Angeles) are key factors not captured by the same-day accumulations. Accordingly, we suggest that the assessment of future changes in landslide hazard for the entire the West Coast requires consideration of future changes in the occurrence and intensity of atmospheric rivers, in their duration and clustering, and in the occurrence of short-duration (sub-daily) extreme rainfall as well. Major regional landslide events, in which multiple occurrences are recorded in the catalog for the same day, are too rare to allow a statistical characterization of their triggering events, but a case study analysis indicates that a variety of synoptic-scale events can be involved, including not only atmospheric rivers but also broader cold- and warm-front precipitation. That a news-based catalog of landslides is accurate enough to allow the identification of different landslide/ rainfall relationships in the major urban areas along the US West Coast suggests that this technology can potentially be used for other English-language cities and could become an even more powerful tool if expanded to other languages and non-traditional news sources, such as social media.

landslides↗

PHyTIR - A Prototype Thermal Infrared Radiometer

This paper describes the PHyTIR (Prototype HyspIRI Thermal Infrared Radiometer) instrument, which is the engineering model for the proposed HyspIRI (Hyperspectral Infrared Imager) earth observing instrument. The HyspIRI mission would be comprised of the HyspIRI TIR (Thermal Infrared Imager), and a VSWIR (Visible Short-Wave Infra-Red Imaging Spectrometer). Both instruments would be used to address key science questions related to the earth's carbon cycle, ecosystems, climate, and solid earth properties. Data gathering of volcanic activities, earthquakes, wildfires, water use and availability, urbanization, and land surface compositions and changes, would aid the predictions and evaluations of such events and the impact they create. Even though the proposed technology for the HyspIRI imager is mature, the PHyTIR prototype is needed to advance the technology levels for several of the instrument's key components, and to reduce risks, in particular to validate 1) the higher sensitivity, spatial resolution, and higher throughput required for this focal plane array, 2) the pointing accuracy, 2) the characteristics of several spectral channels, and 4) the use of ambient temperature optics. The PHyTIR telescope consists of the focal plane assembly that is housed within a cold housing located inside a vacuum enclosure; all mounted to a bulkhead, and an optical train that consists of 3 powered mirrors; extending to both sides of the bulkhead. A yoke connects the telescope to a scan mirror. The rotating mirror enables to scan- a large track on the ground. This structure is supported by kinematic mounts, linking the telescope assembly to a base plate that would also become the spacecraft interface for HyspIRI. The focal plane's cooling units are also mounted to the base plate, as is an overall enclosure that has two viewing ports with large exterior baffles, shielding the focal plane from incoming stray light. PHyTIR's electronics is distributed inside and near the vacuum enclosure, and in a nearby rack. The data acquisition technique would be to take measurements over a 51deg wide swath in the cross spacecraft velocity direction, which is brought into view through the rotating scan mirror. A landscape mosaic thus can be assembled by overlaying rows of measurements. The paper briefly outlines the proposed HyspIRI mission and its data acquisition technique; it then describes the prototype PHyTIR instrument.

Space Instrument↗

An earth outgoing longwave radiation climate model. I - Clear sky radiation

An earth outgoing longwave radiation (OLWR) climate model is presented. The model uses the upward radiative transfer parameterization of Thompson and Warren (1982) for radiation calculations, and a climatologic dataset from Crutcher and Meserve (1970) and Taljaard et al. (1969) to provide data on temperature, dewpoint, and geopotential height for various altitudes. Using the model for a monthly average radiation budget study, clear sky cases of OLWR were calculated for the global average, zonal averages, and global distributions. The regional results on North and South America were compared with GOES data and were found to agree well. The clear sky case shows that the OLWR field is highly modulated by water vapor, especially in the tropics, where the strongest longitudinal variations in OLWR occur. In the high latitudes, where cold air contains less water vapor, OLWR is basically modulated by the surface temperature.

Yang, Shi-Keng↗

The Global Precipitation Climatology Project: First Algorithm Intercomparison Project

The Global Precipitation Climatology Project (GPCP) was established by the World Climate Research Program to produce global analyses of the area- and time-averaged precipitation for use in climate research. To achieve the required spatial coverage, the GPCP uses simple rainfall estimates derived from IR and microwave satellite observations. In this paper, we describe the GPCP and its first Algorithm Intercomparison Project (AIP/1), which compared a variety of rainfall estimates derived from Geostationary Meteorological Satellite visible and IR observations and Special Sensor Microwave/Imager (SSM/I) microwave observations with rainfall derived from a combination of radar and raingage data over the Japanese islands and the adjacent ocean regions during the June and mid-July through mid-August periods of 1989. To investigate potential improvements in the use of satellite IR data for the estimation of large-scale rainfall for the GPCP, the relationship between rainfall and the fractional coverage of cold clouds in the AIP/1 dataset is examined. Linear regressions between fractional coverage and rainfall are analyzed for a number of latitude-longitude areas and for a range of averaging times. The results show distinct differences in the character of the relationship for different portions of the area. These results suggest that the simple IR-based estimation technique currently used in the GPCP can be used to estimate rainfall for global tropical and subtropical areas, provided that a method for adjusting the proportional coefficient for varying areas and seasons can be determined.

Arkin, Phillip A.↗

Global Precipitation Patterns Associated with ENSO and Tropical Circulations

Tropical precipitation and the accompanying latent heat release is the engine that drives the global circulation. An increase or decrease in rainfall in the tropics not only leads to the local effects of flooding or drought, but contributes to changes in the large scale circulation and global climate system. Rainfall in the tropics is highly variable, both seasonally (monsoons) and interannually (ENSO). Two experimental observational data sets, developed under the auspices of the Global Precipitation Climatology Project (GPCP), are used in this study to examine the relationships between global precipitation and ENSO and extreme monsoon events over the past 20 years. The V2x79 monthly product is a globally complete, 2.5 deg x 2.5 deg, satellite-gauge merged data set that covers the period 1979 to the present. Indices based on patterns of satellite-derived rainfall anomalies in the Pacific are used to analyze the teleconnections between ENSO and global precipitation, with emphasis on the monsoon systems. It has been well documented that dry (wet) Asian monsoons accompany warm (cold) ENSO events. However, during the summer seasons of the 1997/98 ENSO the precipitation anomalies were mostly positive over India and the Bay of Bengal, which may be related to an epoch-scale variability in the Asian monsoon circulation. The North American monsoon may be less well linked to ENSO, but a positive precipitation anomaly was observed over Mexico around the September following the 1997/98 event. For the twenty-year record, precipitation and SST patterns in the tropics are analyzed during wet and dry monsoons. For the Asian summer monsoon, positive rainfall anomalies accompany two distinct patterns of tropical precipitation and a warm Indian Ocean. Negative anomalies coincide with a wet Maritime Continent.

Curtis, Scott↗

Mars Surveyor Program '01 Mars Environmental Compatibility Assessment wet chemistry lab: a sensor array for chemical analysis of the Martian soil

The Mars Environmental Compatibility Assessment (MECA) instrument was designed, built, and flight qualified for the now canceled MSP (Mars Surveyor Program) '01 Lander. The MECA package consisted of a microscope, electrometer, material patch plates, and a wet chemistry laboratory (WCL). The primary goal of MECA was to analyze the Martian soil (regolith) for possible hazards to future astronauts and to provide a better understanding of Martian regolith geochemistry. The purpose of the WCL was to analyze for a range of soluble ionic chemical species and electrochemical parameters. The heart of the WCL was a sensor array of electrochemically based ion-selective electrodes (ISE). After 20 months storage at -23 degrees C and subsequent extended freeze/thawing cycles, WCL sensors were evaluated to determine both their physical durability and analytical responses. A fractional factorial calibration of the sensors was used to obtain slope, intercept, and all necessary selectivity coefficients simultaneously for selected ISEs. This calibration was used to model five cation and three anion sensors. These data were subsequently used to determine concentrations of several ions in two soil leachate simulants (based on terrestrial seawater and hypothesized Mars brine) and four actual soil samples. The WCL results were compared to simulant and soil samples using ion chromatography and inductively coupled plasma optical emission spectroscopy. The results showed that flight qualification and prolonged low-temperature storage conditions had minimal effects on the sensors. In addition, the analytical optimization method provided quantitative and qualitative data that could be used to accurately identify the chemical composition of the simulants and soils. The WCL has the ability to provide data that can be used to "read" the chemical, geological, and climatic history of Mars, as well as the potential habitability of its regolith.

Non-NASA Center↗

Relationships between the Raindrop Size Distribution and Properties of the Environment and Clouds Inferred from TRMM

Variability in the raindrop sized distribution (DSD) has long been recognized as a source of uncertainty in relationships between radar reflectivity Z and rain rate R. In this study, we analyze DSD retrievals from two years of data gathered by the Tropical Rainfall Measuring Mission (TRMM) satellite and processed with a combined radar-radiometer retrieval algorithm over the global oceans equatorward of 35◦. Numerous variables describing properties of each reflectivity profile, large-scale organization, and the background environment are examined for relationships to the reflectivity-normalized median drop diameter, epsilonDSD. In general, we find that higher freezing levels and relative humidities are associated with smaller epsilonDSD. Within a given environment, the mesoscale organization of precipitation and the vertical profile of reflectivity are associated with DSD characteristics. In the tropics, the smallest epsilonDSD values are found in large but shallow convective systems, where warm rain formation processes are thought to be predominant, whereas larger sizes are found in the stratiform regions of organized deep convection. In the extratropics, the largest epsilonDSD values are found in the scattered convection that occurs when cold, dry continental air moves over the much warmer ocean after the passage of a cold front. The geographical distribution of the retrieved DSDs is consistent with many of the observed regional Z−R relationships found in the literature as well as discrepancies between the TRMM radar-only and radiometer-only precipitation products. In particular, mid-latitude and tropical regions near land tend to have larger drops for a given reflectivity, whereas the smallest drops are found in the eastern Pacific Intertropical Convergence Zone.

raindrop size distribution↗