Resolving Surface Rain from GMI High-Frequency Channels: Limits Imposed by the Three-Dimensional Structure of Precipitation.
ABSTRACT: The scattering of microwaves at frequencies between 50 and 200 GHz by ice particles in the atmosphere is an essential element in the retrieval of instantaneous surface precipitation from spaceborne passive radiometers. This paper explores how the variable distribution of solid and liquid hydrometeors in the atmospheric column over land surfaces affects the brightness temperature (TB) measured by GMI at 89 GHz through the analysis of Dual-Frequency Precipitation Radar (DPR) reflectivity profiles along the 89-GHz beam. The objective is to refine the statistical relations between observed TBs and surface precipitation over land and to define their limits. As GMI is scanning with a 53° Earth incident angle, the observed atmospheric volume is actually not a vertical column, which may lead to very heterogeneous and seemingly inconsistent distributions of the hydrometeors inside the beam. It is found that the 89-GHz TB is mostly sensitive to the presence of ice hydrometeors several kilometers above the 0°C isotherm, up to 10 km above the 0°C isotherm for the deepest convective systems, but is a modest predictor of the surface precipitation rate. To perform a precise mapping of atmospheric ice, the altitude of the individual ice clusters must be known. indeed, if variations in the altitude of ice are not accounted for, then the high incident angle of GMI causes a horizontal shift (parallax shift) between the estimated position of the ice clusters and their actual position. We show here that the altitude of ice clusters can be derived from the 89-GHz TB itself, allowing for correction of the parallax shift.
Project description:The diurnal variation of tropical ice clouds has been well observed and examined in terms of the occurring frequency and total mass but rarely from the viewpoint of ice microphysical parameters. It accounts for a large portion of uncertainties in evaluating ice clouds' role on global radiation and hydrological budgets. Owing to the advantage of precession orbit design and paired polarized observations at a high-frequency microwave band that is particularly sensitive to ice particle microphysical properties, three years of polarimetric difference (PD) measurements using the 166 GHz channel of Global Precipitation Measurement Microwave Imager (GPM-GMI) are compiled to reveal a strong diurnal cycle over tropical land (30°S-30°N) with peak amplitude varying up to 38%. Since the PD signal is dominantly determined by ice crystal size, shape, and orientation, the diurnal cycle observed by GMI can be used to infer changes in ice crystal properties. Moreover, PD change is found to lead the diurnal changes of ice cloud occurring frequency and total ice mass by about 2 hours, which strongly implies that understanding ice microphysics is critical to predict, infer, and model ice cloud evolution and precipitation processes.
Project description:Tropical anvil clouds have a profound impact on Earth's weather and climate. Their role in Earth's energy balance and hydrologic cycle is heavily modulated by the vertical structure of the microphysical properties for various hydrometeors in these clouds and their dependence on the ambient environmental conditions. Accurate representations of the variability and covariability of such vertical structures are key to both the satellite remote sensing of cloud and precipitation and numerical modeling of weather and climate, which remain a challenge. This study presents a new method to combine vertically resolved observations from CloudSat radar reflectivity and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation cloud masks with probability distributions of cloud microphysical properties and the ambient atmospheric conditions from detailed in situ measurements on tropical anvils sampled during the National Aeronautics and Space Administration TC4 (Tropical Composition, Cloud and Climate Coupling) mission. We focus on the microphysical properties of the vertical distribution of ice water content, particle size distributions, and effective sizes for different hydrometeors, including ice particles and supercooled liquid droplets. Results from this method are compared with those from in situ data alone and various CloudSat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation cloud retrievals. The sampling limitation of the field experiment and algorithm limitations in the current retrievals is highlighted, especially for the liquid cloud particles, while a generally good agreement with ice cloud microphysical properties is seen from different methods. While the method presented in this study is applied to tropical anvil clouds observed during TC4, it can be readily employed to study a broad range of ice clouds sampled by various field campaigns.
Project description:The cycling of atmospheric aerosols through clouds can change their chemical and physical properties and thus modify how aerosols affect cloud microphysics and, subsequently, precipitation and climate. Current knowledge about aerosol processing by clouds is rather limited to chemical reactions within water droplets in warm low-altitude clouds. However, in cold high-altitude cirrus clouds and anvils of high convective clouds in the tropics and midlatitudes, humidified aerosols freeze to form ice, which upon exposure to subsaturation conditions with respect to ice can sublimate, leaving behind residual modified aerosols. This freeze-drying process can occur in various types of clouds. Here we simulate an atmospheric freeze-drying cycle of aerosols in laboratory experiments using proxies for atmospheric aerosols. We find that aerosols that contain organic material that undergo such a process can form highly porous aerosol particles with a larger diameter and a lower density than the initial homogeneous aerosol. We attribute this morphology change to phase separation upon freezing followed by a glass transition of the organic material that can preserve a porous structure after ice sublimation. A porous structure may explain the previously observed enhancement in ice nucleation efficiency of glassy organic particles. We find that highly porous aerosol particles scatter solar light less efficiently than nonporous aerosol particles. Using a combination of satellite and radiosonde data, we show that highly porous aerosol formation can readily occur in highly convective clouds, which are widespread in the tropics and midlatitudes. These observations may have implications for subsequent cloud formation cycles and aerosol albedo near cloud edges.
Project description:Due to the large natural variability of its microphysical properties, the characterization of solid precipitation is a longstanding problem. Since in situ observations are unavailable in severe convective systems, innovative remote sensing retrievals are needed to extend our understanding of such systems. This study presents a novel technique able to retrieve the density, mass, and effective diameter of graupel and hail in severe convection through the combination of airborne microwave remote sensing instruments. The retrieval is applied to measure solid precipitation properties within two convective cells observed on 23-24 May 2014 over North Carolina during the IPHEx campaign by the NASA ER-2 instrument suite. Between 30 and 40 degrees of freedom of signal are associated with the measurements, which is insufficient to provide full microphysics profiling. The measurements have the largest impact on the retrieval of ice particle sizes, followed by ice water contents. Ice densities are mainly driven by a priori assumptions, though low relative errors in ice densities suggest that in extensive regions of the convective system, only particles with densities larger than 0.4 g/cm3 are compatible with the observations. This is in agreement with reports of large hail on the ground and with hydrometeor classification derived from ground-based polarimetric radars observations. This work confirms that multiple scattering generated by large ice hydrometeors in deep convection is relevant for airborne radar systems already at Ku band. A fortiori, multiple scattering will play a pivotal role in such conditions also for Ku band spaceborne radars (e.g., the GPM Dual Precipitation Radar).
Project description:We developed a method for classifying hydrometeor particle types, including cloud and precipitation phase and ice crystal habit, by a synergistic use of CloudSat/Cloud Profiling Radar (CPR) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)/Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP). We investigated how the cloud phase and ice crystal habit characterized by CALIOP globally relate with radar reflectivity and temperature. The global relationship thus identified was employed to develop an algorithm for hydrometeor type classification with CPR alone. The CPR-based type classification was then combined with CALIPSO-based type characterization to give CPR-CALIOP synergy classification. A unique aspect of this algorithm is to exploit and combine the lidar's sensitivity to thin ice clouds and the radar's ability to penetrate light precipitation to offer more complete picture of vertically resolved hydrometeor type classification than has been provided by previous studies. Given the complementary nature of radar and lidar detections of hydrometeors, our algorithm delivers thirteen hydrometeor types: warm water, supercooled water, randomly-oriented ice crystal (3D-ice), horizontally-oriented plate (2D-plate), 3D-ice+2D-plate, liquid drizzle, mixed-phase drizzle, rain, snow, mixed-phase cloud, water+liquid drizzle, water+rain and unknown. The global statistics of three-dimensional occurrence frequency of each hydrometeor type revealed that 3D-ice contributes the most to the total cloud occurrence frequency (53.8%), followed by supercooled water (14.3%), 2D-plate (9.2%), rain (5.9%), warm water (5.7%), snow (4.8%), mixed-phase drizzle (2.3%), and the remaining types (4.0%). This hydrometeor type classification provides useful observation-based information for climate model diagnostics in representation of cloud phase and their microphysical characteristics.
Project description:Understanding how dynamical and aerosol inputs affect the temporal variability of hydrometeor formation in climate models will help to explain sources of model diversity in cloud forcing, to provide robust comparisons with data, and, ultimately, to reduce the uncertainty in estimates of the aerosol indirect effect. This variability attribution can be done at various spatial and temporal resolutions with metrics derived from online adjoint sensitivities of droplet and crystal number to relevant inputs. Such metrics are defined and calculated from simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1 (CAM5.1). Input updraft velocity fluctuations can explain as much as 48% of temporal variability in output ice crystal number and 61% in droplet number in GEOS-5 and up to 89% of temporal variability in output ice crystal number in CAM5.1. In both models, this vertical velocity attribution depends strongly on altitude. Despite its importance for hydrometeor formation, simulated vertical velocity distributions are rarely evaluated against observations due to the sparsity of relevant data. Coordinated effort by the atmospheric community to develop more consistent, observationally based updraft treatments will help to close this knowledge gap.
Project description:This study characterizes the spatial and temporal patterns of aerosol and precipitation composition at six sites across the United States Southwest between 1995 and 2010. Precipitation accumulation occurs mostly during the wintertime (December-February) and during the monsoon season (July-September). Rain and snow pH levels are usually between 5-6, with crustal-derived species playing a major role in acid neutralization. These species (Ca2+, Mg2+, K+, Na+) exhibit their highest concentrations between March and June in both PM2.5 and precipitation due mostly to dust. Crustal-derived species concentrations in precipitation exhibit positive relationships with [Formula: see text], [Formula: see text], and Cl-, suggesting that acidic gases likely react with and partition to either crustal particles or hydrometeors enriched with crustal constituents. Concentrations of particulate [Formula: see text] show a statistically significant correlation with rain [Formula: see text] unlike snow [Formula: see text], which may be related to some combination of the vertical distribution of [Formula: see text] (and precursors) and the varying degree to which [Formula: see text]-enriched particles act as cloud condensation nuclei versus ice nuclei in the region. The coarse : fine aerosol mass ratio was correlated with crustal species concentrations in snow unlike rain, suggestive of a preferential role of coarse particles (mainly dust) as ice nuclei in the region. Precipitation [Formula: see text] : [Formula: see text] ratios exhibit the following features with potential explanations discussed: (i) they are higher in precipitation as compared to PM2.5; (ii) they exhibit the opposite annual cycle compared to particulate [Formula: see text] : [Formula: see text] ratios; and (iii) they are higher in snow relative to rain during the wintertime. Long-term trend analysis for the monsoon season shows that the [Formula: see text] : [Formula: see text] ratio in rain increased at the majority of sites due mostly to air pollution regulations of [Formula: see text] precursors.
Project description:The Multi-Sensor Advanced Climatology of Liquid Water Path (MAC-LWP), an updated and enhanced version of the University of Wisconsin (UWisc) cloud liquid water path (CLWP) climatology, currently provides 29 years (1988 - 2016) of monthly gridded (1°) oceanic CLWP information constructed using Remote Sensing Systems (RSS) inter-calibrated 0.25°-resolution retrievals. Satellite sources include SSM/I, TMI, AMSR-E, WindSat, SSMIS, AMSR-2 and GMI. To mitigate spurious CLWP trends, the climatology is corrected for drifting satellite overpass times by simultaneously solving for the monthly average CLWP and monthly-mean diurnal cycle. In addition to a longer record and six additional satellite products, major enhancements relative to the UWisc climatology include updating the input to version 7 RSS retrievals, a correction for a CLWP bias (based on matchups to clear-sky MODIS scenes), and the construction of a total (cloud+rain) liquid water path (TLWP) record for use in analyses of columnar liquid water in raining clouds. Because the microwave emission signal from cloud water is similar to that of precipitation-sized hydrometeors, greater uncertainty in the CLWP record is expected in regions of substantial precipitation. Therefore, the TLWP field can also be used as a quality-control screen, where uncertainty increases as the ratio of CLWP to TLWP decreases. For regions where confidence in CLWP is highest (i.e. CLWP:TLWP > 0.8), systematic differences in MAC CLWP relative to UWisc CLWP range from -15% (e.g. global oceanic stratocumulus decks) to +5-10% (e.g. portions of the higher-latitudes, storm tracks, and shallower convection regions straddling the ITCZ). The dataset is currently hosted at the Goddard Earth Science Data and Information Services Center (http://disc.sci.gsfc.nasa.gov).
Project description:From 2012 to 2016, California experienced one of the worst droughts since the start of observational records. As in previous dry periods, precipitation-inducing winter storms were steered away from California by a persistent atmospheric ridging system in the North Pacific. Here we identify a new link between Arctic sea-ice loss and the North Pacific geopotential ridge development. In a two-step teleconnection, sea-ice changes lead to reorganization of tropical convection that in turn triggers an anticyclonic response over the North Pacific, resulting in significant drying over California. These findings suggest that the ability of climate models to accurately estimate future precipitation changes over California is also linked to the fidelity with which future sea-ice changes are simulated. We conclude that sea-ice loss of the magnitude expected in the next decades could substantially impact California's precipitation, thus highlighting another mechanism by which human-caused climate change could exacerbate future California droughts.
Project description:Ice nucleation and the resulting cloud glaciation are significant atmospheric processes that affect the evolution of clouds and their properties including radiative forcing and precipitation, yet the sources and properties of atmospheric ice nucleants are poorly constrained. Heterogeneous ice nucleation caused by ice-nucleating particles (INPs) enables cloud glaciation at temperatures above the homogeneous freezing regime that starts near -35 °C. Biomass burning is a significant global source of atmospheric particles and a highly variable and poorly understood source of INPs. The nature of these INPs and how they relate to the fuel composition and its combustion are critical gaps in our understanding of the effects of biomass burning on the environment and climate. Here we show that the combustion process transforms inorganic elements naturally present in the biomass (not soil or dust) to form potentially ice-active minerals in both the bottom ash and emitted aerosol particles. These particles possess ice-nucleation activities high enough to be relevant to mixed-phase clouds and are active over a wide temperature range, nucleating ice at up to -13 °C. Certain inorganic elements can thus serve as indicators to predict the production of ice nucleants from the fuel. Combustion-derived minerals are an important but understudied source of INPs in natural biomass-burning aerosol emissions in addition to lofted primary soil and dust particles. These discoveries and insights should advance the realistic incorporation of biomass-burning INPs into atmospheric cloud and climate models. These mineral components produced in biomass-burning aerosol should also be studied in relation to other atmospheric chemistry processes, such as facilitating multiphase chemical reactions and nutrient availability.