First Satellite-detected Perturbations of Outgoing Longwave Radiation Associated with Blowing Snow Events over Antarctica

NASA Technical Reports Server (NTRS)

Yang, Yuekui; Palm, Stephen P.; Marshak, Alexander; Wu, Dong L.; Yu, Hongbin; Fu, Qiang

2014-01-01

We present the first satellite-detected perturbations of the outgoing longwave radiation (OLR) associated with blowing snow events over the Antarctic ice sheet using data from Cloud-Aerosol Lidar with Orthogonal Polarization and Clouds and the Earth's Radiant Energy System. Significant cloud-free OLR differences are observed between the clear and blowing snow sky, with the sign andmagnitude depending on season and time of the day. During nighttime, OLRs are usually larger when blowing snow is present; the average difference in OLRs between without and with blowing snow over the East Antarctic Ice Sheet is about 5.2 W/m2 for the winter months of 2009. During daytime, in contrast, the OLR perturbation is usually smaller or even has the opposite sign. The observed seasonal variations and day-night differences in the OLR perturbation are consistent with theoretical calculations of the influence of blowing snow on OLR. Detailed atmospheric profiles are needed to quantify the radiative effect of blowing snow from the satellite observations.

A Supplementary Clear-Sky Snow and Ice Recognition Technique for CERES Level 2 Products

NASA Technical Reports Server (NTRS)

Radkevich, Alexander; Khlopenkov, Konstantin; Rutan, David; Kato, Seiji

2013-01-01

Identification of clear-sky snow and ice is an important step in the production of cryosphere radiation budget products, which are used in the derivation of long-term data series for climate research. In this paper, a new method of clear-sky snow/ice identification for Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. The algorithm's goal is to enhance the identification of snow and ice within the Clouds and the Earth's Radiant Energy System (CERES) data after application of the standard CERES scene identification scheme. The input of the algorithm uses spectral radiances from five MODIS bands and surface skin temperature available in the CERES Single Scanner Footprint (SSF) product. The algorithm produces a cryosphere rating from an aggregated test: a higher rating corresponds to a more certain identification of the clear-sky snow/ice-covered scene. Empirical analysis of regions of interest representing distinctive targets such as snow, ice, ice and water clouds, open waters, and snow-free land selected from a number of MODIS images shows that the cryosphere rating of snow/ice targets falls into 95% confidence intervals lying above the same confidence intervals of all other targets. This enables recognition of clear-sky cryosphere by using a single threshold applied to the rating, which makes this technique different from traditional branching techniques based on multiple thresholds. Limited tests show that the established threshold clearly separates the cryosphere rating values computed for the cryosphere from those computed for noncryosphere scenes, whereas individual tests applied consequently cannot reliably identify the cryosphere for complex scenes.

Virtual Sensors: Using Data Mining to Efficiently Estimate Spectra

NASA Technical Reports Server (NTRS)

Srivastava, Ashok; Oza, Nikunj; Stroeve, Julienne

2004-01-01

Detecting clouds within a satellite image is essential for retrieving surface geophysical parameters, such as albedo and temperature, from optical and thermal imagery because the retrieval methods tend to be valid for clear skies only. Thus, routine satellite data processing requires reliable automated cloud detection algorithms that are applicable to many surface types. Unfortunately, cloud detection over snow and ice is difficult due to the lack of spectral contrast between clouds and snow. Snow and clouds are both highly reflective in the visible wavelen,ats and often show little contrast in the thermal Infrared. However, at 1.6 microns, the spectral signatures of snow and clouds differ enough to allow improved snow/ice/cloud discrimination. The recent Terra and Aqua Moderate Resolution Imaging Spectro-Radiometer (MODIS) sensors have a channel (channel 6) at 1.6 microns. Presently the most comprehensive, long-term information on surface albedo and temperature over snow- and ice-covered surfaces comes from the Advanced Very High Resolution Radiometer ( AVHRR) sensor that has been providing imagery since July 1981. The earlier AVHRR sensors (e.g. AVHRR/2) did not however have a channel designed for discriminating clouds from snow, such as the 1.6 micron channel available on the more recent AVHRR/3 or the MODIS sensors. In the absence of the 1.6 micron channel, the AVHRR Polar Pathfinder (APP) product performs cloud detection using a combination of time-series analysis and multispectral threshold tests based on the satellite's measuring channels to produce a cloud mask. The method has been found to work reasonably well over sea ice, but not so well over the ice sheets. Thus, improving the cloud mask in the APP dataset would be extremely helpful toward increasing the accuracy of the albedo and temperature retrievals, as well as extending the time-series of albedo and temperature retrievals from the more recent sensors to the historical ones. In this work, we use data mining methods to construct a model of MODIS channel 6 as a function of other channels that are common to both MODIS and AVHRR. The idea is to use the model to generate the equivalent of MODIS channel 6 for AVHRR as a function of the AVHRR equivalents to MODIS channels. We call this a Virtual Sensor because it predicts unmeasured spectra. The goal is to use this virtual channel 6. to yield a cloud mask superior to what is currently used in APP . Our results show that several data mining methods such as multilayer perceptrons (MLPs), ensemble methods (e.g., bagging), and kernel methods (e.g., support vector machines) generate channel 6 for unseen MODIS images with high accuracy. Because the true channel 6 is not available for AVHRR images, we qualitatively assess the virtual channel 6 for several AVHRR images.

In situ observations of snow particle size distributions over a cold frontal rainband within an extratropical cyclone

NASA Astrophysics Data System (ADS)

Yang, Jiefan; Lei, Hengchi

2016-02-01

Cloud microphysical properties of a mixed phase cloud generated by a typical extratropical cyclone in the Tongliao area, Inner Mongolia on 3 May 2014, are analyzed primarily using in situ flight observation data. This study is mainly focused on ice crystal concentration, supercooled cloud water content, and vertical distributions of fit parameters of snow particle size distributions (PSDs). The results showed several discrepancies of microphysical properties obtained during two penetrations. During penetration within precipitating cloud, the maximum ice particle concentration, liquid water content, and ice water content were increased by a factor of 2-3 compared with their counterpart obtained during penetration of a nonprecipitating cloud. The heavy rimed and irregular ice crystals obtained by 2D imagery probe as well as vertical distributions of fitting parameters within precipitating cloud show that the ice particles grow during falling via riming and aggregation process, whereas the lightly rimed and pristine ice particles as well as fitting parameters within non-precipitating cloud indicate the domination of sublimation process. During the two cloud penetrations, the PSDs were generally better represented by gamma distributions than the exponential form in terms of the determining coefficient ( R 2). The correlations between parameters of exponential /gamma form within two penetrations showed no obvious differences compared with previous studies.

Microphysical Properties and Water Budget for Summer Convective Clouds over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Guo, X.; Tang, J.; Chang, Y.

2017-12-01

During the Third Tibetan Plateau Atmospheric Scientific Experiment (TIPEX-III), the clouds and precipitation processes over the Tibetan Plateau have been intensively investigated. On basis of field campaign, the cloud microphysical structure, water transformation and budget properties for typical convective precipitation processes in the summer season of 2014 over the plateau are studied using mesoscale numerical prediction model (WRF) combined with observational data collected during the experiment. The results indicate that WRF model could reproduce the general characteristics of diurnal variation of clouds and precipitation process over the plateau, however, the temporal and spatial distribution and intensity of cloud bands and precipitation simulated by WRF model still had large differences with those observed. Ice process played a critical role in the development of summer convective clouds and precipitation over the plateau. The surface precipitation was primarily formed by the melting process of graupel particles. Although the warm cloud microphysical process had small direct contribution on the surface precipitation, it had an important contribution in the formation of graupel embryos. High amount of supercooled cloud water content and graupel particles could be found in the clouds. The formation and growth of snow particles relied on the conversion of ice crystal and the aggregation with ice crystal over 12 km (-40°), but the formation of snow particles below 12 km (-40°)was dependent on the conversion of Bergeron process of ice crystals and its growth resulted from riming process with supercooled cloud water. The accretion process of supercooled raindrops by ice crystal and snow particles contributed to the production of graupel embryos and their growth mainly relied on the riming process with supercooled cloud water and aggregation process with snow particles. The mean daily conversion rate from vapor to precipitation was as high as 27.27%, which is close to Yangtze River downstream, and is higher than the regions of northern and northwestern China. The contribution of daily mean surface evaporation to precipitation was 10.92%, indicating that the 90% rainfall was from the conversion of water vapor outside the plateau.

Strategies for cloud-top phase determination: differentiation between thin cirrus clouds and snow in manual (ground truth) analyses

NASA Astrophysics Data System (ADS)

Hutchison, Keith D.; Etherton, Brian J.; Topping, Phillip C.

1996-12-01

Quantitative assessments on the performance of automated cloud analysis algorithms require the creation of highly accurate, manual cloud, no cloud (CNC) images from multispectral meteorological satellite data. In general, the methodology to create ground truth analyses for the evaluation of cloud detection algorithms is relatively straightforward. However, when focus shifts toward quantifying the performance of automated cloud classification algorithms, the task of creating ground truth images becomes much more complicated since these CNC analyses must differentiate between water and ice cloud tops while ensuring that inaccuracies in automated cloud detection are not propagated into the results of the cloud classification algorithm. The process of creating these ground truth CNC analyses may become particularly difficult when little or no spectral signature is evident between a cloud and its background, as appears to be the case when thin cirrus is present over snow-covered surfaces. In this paper, procedures are described that enhance the researcher's ability to manually interpret and differentiate between thin cirrus clouds and snow-covered surfaces in daytime AVHRR imagery. The methodology uses data in up to six AVHRR spectral bands, including an additional band derived from the daytime 3.7 micron channel, which has proven invaluable for the manual discrimination between thin cirrus clouds and snow. It is concluded that while the 1.6 micron channel remains essential to differentiate between thin ice clouds and snow. However, this capability that may be lost if the 3.7 micron data switches to a nighttime-only transmission with the launch of future NOAA satellites.

A Robust Multi-Scale Modeling System for the Study of Cloud and Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2012-01-01

During the past decade, numerical weather and global non-hydrostatic models have started using more complex microphysical schemes originally developed for high resolution cloud resolving models (CRMs) with 1-2 km or less horizontal resolutions. These microphysical schemes affect the dynamic through the release of latent heat (buoyancy loading and pressure gradient) the radiation through the cloud coverage (vertical distribution of cloud species), and surface processes through rainfall (both amount and intensity). Recently, several major improvements of ice microphysical processes (or schemes) have been developed for cloud-resolving model (Goddard Cumulus Ensemble, GCE, model) and regional scale (Weather Research and Forecast, WRF) model. These improvements include an improved 3-ICE (cloud ice, snow and graupel) scheme (Lang et al. 2010); a 4-ICE (cloud ice, snow, graupel and hail) scheme and a spectral bin microphysics scheme and two different two-moment microphysics schemes. The performance of these schemes has been evaluated by using observational data from TRMM and other major field campaigns. In this talk, we will present the high-resolution (1 km) GeE and WRF model simulations and compared the simulated model results with observation from recent field campaigns [i.e., midlatitude continental spring season (MC3E; 2010), high latitude cold-season (C3VP, 2007; GCPEx, 2012), and tropical oceanic (TWP-ICE, 2006)].

Laser Pulse Bidirectional Reflectance from CALIPSO Mission

NASA Technical Reports Server (NTRS)

Lu, Xiaomei; Hu, Yongxiang; Yang, Yuekui; Liu, Zhaoyan; Vaughan, Mark; Lucker, Patricia; Trepte, Charles

2017-01-01

In this Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) study, we present a simple way of determining laser pulse bidirectional reflectance over snow/ice surface using the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) 532 nanometer polarization channels' measurements. The saturated laser pulse returns from snow and ice surfaces are recovered based on surface tail information. The method overview and initial assessment of the method performance will be presented. The retrieved snow surface bidirectional reflectance is compared with reflectance from both CALIOP cloud cover regions and Moderate Resolution Imaging Spectroradiometer (Earth Observing System (EOS)) (MODIS) Bi-directional Reflectance Distribution Function (BRDF) / Albedo model parameters. The comparisons show that the snow surface bidirectional reflectance over Antarctica for saturation region are generally reliable with a mean value of about 0.90 plus or minus 0.10, while the mean surface reflectance from cloud cover region is about 0.84 plus or minus 0.13 and the calculated MODIS reflectance at 555 nanometers from the BRDF / Albedo model with near nadir illumination and viewing angles is about 0.96 plus or minus 0.04. The comparisons here demonstrate that the snow surface reflectance underneath the cloud with cloud optical depth of about 1 is significantly lower than that for a clear sky condition.

Improved simulation of Antarctic sea ice due to the radiative effects of falling snow

NASA Astrophysics Data System (ADS)

Li, J.-L. F.; Richardson, Mark; Hong, Yulan; Lee, Wei-Liang; Wang, Yi-Hui; Yu, Jia-Yuh; Fetzer, Eric; Stephens, Graeme; Liu, Yinghui

2017-08-01

Southern Ocean sea-ice cover exerts critical control on local albedo and Antarctic precipitation, but simulated Antarctic sea-ice concentration commonly disagrees with observations. Here we show that the radiative effects of precipitating ice (falling snow) contribute substantially to this discrepancy. Many models exclude these radiative effects, so they underestimate both shortwave albedo and downward longwave radiation. Using two simulations with the climate model CESM1, we show that including falling-snow radiative effects improves the simulations relative to cloud properties from CloudSat-CALIPSO, radiation from CERES-EBAF and sea-ice concentration from passive microwave sensors. From 50-70°S, the simulated sea-ice-area bias is reduced by 2.12 × 106 km2 (55%) in winter and by 1.17 × 106 km2 (39%) in summer, mainly because increased wintertime longwave heating restricts sea-ice growth and so reduces summer albedo. Improved Antarctic sea-ice simulations will increase confidence in projected Antarctic sea level contributions and changes in global warming driven by long-term changes in Southern Ocean feedbacks.

A Solar Reflectance Method for Retrieving Cloud Optical Thickness and Droplet Size Over Snow and Ice Surfaces

NASA Technical Reports Server (NTRS)

Platnick, S.; Li, J. Y.; King, M. D.; Gerber, H.; Hobbs, P. V.

1999-01-01

Cloud optical thickness and effective radius retrievals from solar reflectance measurements are traditionally implemented using a combination of spectral channels that are absorbing and non-absorbing for water particles. Reflectances in non-absorbing channels (e.g., 0.67, 0.86, 1.2 micron spectral window bands) are largely dependent on cloud optical thickness, while longer wavelength absorbing channels (1.6, 2. 1, and 3.7 micron window bands) provide cloud particle size information. Cloud retrievals over ice and snow surfaces present serious difficulties. At the shorter wavelengths, ice is bright and highly variable, both characteristics acting to significantly increase cloud retrieval uncertainty. In contrast, reflectances at the longer wavelengths are relatively small and may be comparable to that of dark open water. A modification to the traditional cloud retrieval technique is devised. The new algorithm uses only a combination of absorbing spectral channels for which the snow/ice albedo is relatively small. Using this approach, retrievals have been made with the MODIS Airborne Simulator (MAS) imager flown aboard the NASA ER-2 from May - June 1998 during the Arctic FIRE-ACE field deployment. Data from several coordinated ER-2 and University of Washington CV-580 in situ aircraft observations of liquid water stratus clouds are examined. MAS retrievals of optical thickness, droplet effective radius, and liquid water path are shown to be in good agreement with the in situ measurements. The initial success of the technique has implications for future operational satellite cloud retrieval algorithms in polar and wintertime regions.

Optical Thickness and Effective Radius Retrievals of Liquid Water Clouds over Ice and Snow Surface

NASA Technical Reports Server (NTRS)

Platnick, S.; King, M. D.; Tsay, S.-C.; Arnold, G. T.; Gerber, H.; Hobbs, P. V.; Rangno, A.

1999-01-01

Cloud optical thickness and effective radius retrievals from solar reflectance measurements traditionally depend on a combination of spectral channels that are absorbing and non-absorbing for liquid water droplets. Reflectances in non-absorbing channels (e.g., 0.67, 0.86 micrometer bands) are largely dependent on cloud optical thickness, while longer wavelength absorbing channels (1.6, 2.1, and 3.7 micrometer window bands) provide cloud particle size information. Retrievals are complicated by the presence of an underlying ice/snow surface. At the shorter wavelengths, sea ice is both bright and highly variable, significantly increasing cloud retrieval uncertainty. However, reflectances at the longer wavelengths are relatively small and may be comparable to that of dark open water. Sea ice spectral albedos derived from Cloud Absorption Radiometer (CAR) measurements during April 1992 and June 1995 Arctic field deployments are used to illustrate these statements. A modification to the traditional retrieval technique is devised. The new algorithm uses a combination of absorbing spectral channels for which the snow/ice albedo is relatively small. Using this approach, preliminary retrievals have been made with the MODIS Airborne Simulator (MAS) imager flown aboard the NASA ER-2 during FIRE-ACE. Data from coordinated ER-2 and University of Washington CV-580 aircraft observations of liquid water stratus clouds on June 3 and June 6, 1998 have been examined. Size retrievals are compared with in situ cloud profile measurements of effective radius made with the CV-580 PMS FSSP probe, and optical thickness retrievals are compared with extinction profiles derived from the Gerber Scientific "g-meter" probe. MAS retrievals are shown to be in good agreement with the in situ measurements.

Influence of projected snow and sea-ice changes on future climate in heavy snowfall region

NASA Astrophysics Data System (ADS)

Matsumura, S.; Sato, T.

2011-12-01

Snow/ice albedo and cloud feedbacks are critical for climate change projection in cryosphere regions. However, future snow and sea-ice distributions are significantly different in each GCM. Thus, surface albedo in cryosphere regions is one of the causes of the uncertainty for climate change projection. Northern Japan is one of the heaviest snowfall regions in the world. In particular, Hokkaido is bounded on the north by the Okhotsk Sea, where is the southernmost ocean in the Northern Hemisphere that is covered with sea ice during winter. Wintertime climate around Hokkaido is highly sensitive to fluctuations in snow and sea-ice. The purpose of this study is to evaluate the influence of global warming on future climate around Hokkaido, using the Pseudo-Global-Warming method (PGW) by a regional climate model. The boundary conditions of the PGW run were obtained by adding the difference between the future (2090s) and past (1990s) climates simulated by coupled general circulation model (MIROC3.2 medres), which is from the CMIP3 multi-model dataset, into the 6-hourly NCEP reanalysis (R-2) and daily OISST data in the past climate (CTL) run. The PGW experiments show that snow depth significantly decreases over mountainous areas and snow cover mainly decreases over plain areas, contributing to higher surface warming due to the decreased snow albedo. Despite the snow reductions, precipitation mainly increases over the mountainous areas because of enhanced water vapor content. However, precipitation decreases over the Japan Sea and the coastal areas, indicating the weakening of a convergent cloud band, which is formed by convergence between cold northwesteries from the Eurasian continent and anticyclonic circulation over the Okhotsk Sea. These results suggest that Okhotsk sea-ice decline may change the atmospheric circulation and the resulting effect on cloud formation, resulting in changes in winter snow or precipitation. We will also examine another CMIP3 model (MRI-CGCM2.3.2), which sensitivity of surface albedo to surface air temperature is the lowest in the CMIP3 models.

Evaluation of and Suggested Improvements to the WSM6 Microphysics in WRF- ARW Using Synthetic and Observed GOES-13 Imagery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grasso, Lewis; Lindsey, Daniel T.; Lim, Kyo-Sun

Synthetic satellite imagery can be employed to evaluate simulated cloud fields. Past studies have revealed that the Weather Research and Forecasting (WRF) WRF Single-Moment 6-class (WSM6) microphysics in WRF-ARW produces less upper level ice clouds within synthetic images compared to observations. Synthetic Geostationary Operational Environmental Satellite (GOES)-13 imagery at 10.7 μm of simulated cloud fields from the 4 km National Severe Storms Laboratory (NSSL) WRF-ARW is compared to observed GOES-13 imagery. Histograms suggest that too few points contain upper level simulated ice clouds. In particular, side-by-side examples are shown of synthetic and observed convective anvils. Such images illustrate the lackmore » of anvil cloud associated with convection produced by the NSSL WRF-ARW. A vertical profile of simulated hydrometeors suggests that too much cloud water mass may be converted into graupel mass, effectively reducing the main source of ice mass in a simulated anvil. Further, excessive accretion of ice by snow removes ice from an anvil by precipitation settling. Idealized sensitivity tests reveal that a 50% reduction of the conversion of cloud water mass to graupel and a 50% reduction of the accretion rate of ice by snow results in a significant increase in anvil ice of a simulated storm. Such results provide guidance as to which conversions could be reformulated, in a more physical manner, to increase simulated ice mass in the upper troposphere.« less

Effects of latent heat in various cloud microphysics processes on autumn rainstorms with different intensities on Hainan Island, China

NASA Astrophysics Data System (ADS)

Li, Jiangnan; Wu, Kailu; Li, Fangzhou; Chen, Youlong; Huang, Yanbin; Feng, YeRong

2017-06-01

In this study, we used the Weather Research and Forecasting (WRF) and WRF-3DVAR models to perform a series of simulations of two autumn rainstorms on Hainan Island. The results of neighborhood fractions and Hanssen skill scoring (FSS, HSS) methods show that the control experiments reproduced well two heavy rainfall episodes. Effects of latent heat in various cloud microphysical processes are different at distinct intensities or stages of precipitation. In the absence of any heating effect of deposition, precipitation weakened. The greater was the precipitation, the more significant was the weakening effect. Ascending movement at upper troposphere could be weakened or descending movement at lower troposphere enhanced. With decreases in the strength of precipitation, cloud ice, snow, graupel, and rainwater, increases in latent heat lessened. With weak precipitation, at upper troposphere the rainwater content increased and snow and ice content decreased, whereas at middle troposphere, the ice, snow, and graupel contents increased. Latent heating increased at middle and lower troposphere and decreased at upper troposphere. The absence of any heating effect of freezing had little effect on precipitation. By removing the evaporative cooling of cloud water, the interactions between vertical movement and cloud microphysical processes resulted in a weakening of strong precipitation and an intensification of weak precipitation. However, in the preliminary stages of these two precipitation events, snow, graupel, cloud ice, and rainwater all increased, and precipitation was enhanced in both. In the later stages, strong precipitation systems weakened and weak precipitation systems strengthened. Latent heating first increased and then dropped in strong precipitation systems, whereas they continuously increased in weak precipitation systems.

The impact of boundary layer turbulence on snow growth and precipitation: Idealized Large Eddy Simulations

NASA Astrophysics Data System (ADS)

Chu, Xia; Xue, Lulin; Geerts, Bart; Kosović, Branko

2018-05-01

Ice particles and supercooled droplets often co-exist in planetary boundary-layer (PBL) clouds. The question examined in this numerical study is how large turbulent PBL eddies affect snow growth and surface precipitation from mixed-phase PBL clouds. In order to simplify this question, this study assumes an idealized BL with well-developed turbulence but no surface heat fluxes or radiative heat exchanges. Large Eddy Simulations with and without resolved PBL turbulence are compared. This comparison demonstrates that the impact on snow growth in mixed-phase clouds is controlled by two opposing mechanisms, a microphysical and a dynamical one. The cloud microphysical impact of large turbulent eddies is based on the difference in saturation vapor pressure over water and over ice. The net outcome of alternating turbulent up- and downdrafts is snow growth by diffusion and/or accretion (riming). On the other hand, turbulence-induced entrainment and detrainment may suppress snow growth. In the case presented herein, the net effect of these microphysical and dynamical processes is positive, but in general the net effect depends on ambient conditions, in particular the profiles of temperature, humidity, and wind.

Enhanced Solar Energy Absorption by Internally-mixed Black Carbon in Snow Grains

DOE Office of Scientific and Technical Information (OSTI.GOV)

Flanner, M. G.; Liu, Xiaohong; Zhou, Cheng

2012-05-30

Here we explore light absorption by snowpack containing black carbon (BC) particles residing within ice grains. Basic considerations of particle volumes and BC/snow mass concentrations show that there are generally 0:05-109 BC particles for each ice grain. This suggests that internal BC is likely distributed as multiple inclusions within ice grains, and thus the dynamic effective medium approximation (DEMA) (Chylek and Srivastava, 1983) is a more appropriate optical representation for BC/ice composites than coated-sphere or standard mixing approximations. DEMA calculations show that the 460 nm absorption cross-section of BC/ice composites, normalized to the mass of BC, is typically enhanced bymore » factors of 1.8-2.1 relative to interstitial BC. BC effective radius is the dominant cause of variation in this enhancement, compared with ice grain size and BC volume fraction. We apply two atmospheric aerosol models that simulate interstitial and within-hydrometeor BC lifecycles. Although only {approx}2% of the atmospheric BC burden is cloud-borne, 71-83% of the BC deposited to global snow and sea-ice surfaces occurs within hydrometeors. Key processes responsible for within-snow BC deposition are development of hydrophilic coatings on BC, activation of liquid droplets, and subsequent snow formation through riming or ice nucleation by other species and aggregation/accretion of ice particles. Applying deposition fields from these aerosol models in offline snow and sea-ice simulations, we calculate that 32-73% of BC in global surface snow resides within ice grains. This fraction is smaller than the within-hydrometeor deposition fraction because meltwater flux preferentially removes internal BC, while sublimation and freezing within snowpack expose internal BC. Incorporating the DEMA into a global climate model, we simulate increases in BC/snow radiative forcing of 43-86%, relative to scenarios that apply external optical properties to all BC. We show that snow metamorphism driven by diffusive vapor transfer likely proceeds too slowly to alter the mass of internal BC while it is radiatively active, but neglected processes like wind pumping and convection may play much larger roles. These results suggest that a large portion of BC in surface snowpack may reside within ice grains and increase BC/snow radiative forcing, although measurements to evaluate this are lacking. Finally, previous studies of BC/snow forcing that neglected this absorption enhancement are not necessarily biased low, because of application of absorption-enhancing sulfate coatings to hydrophilic BC, neglect of coincident absorption by dust in snow, and implicit treatment of cloud-borne BC resulting in longer-range transport.« less

The 20-22 January 2007 Snow Events over Canada: Microphysical Properties

NASA Technical Reports Server (NTRS)

Tao. W.K.; Shi, J.J.; Matsui, T.; Hao, A.; Lang, S.; Peters-Lidard, C.; Skofronick-Jackson, G.; Petersen, W.; Cifelli, R.; Rutledge, S.

2009-01-01

One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve precipitation measurements in mid- and high-latitudes during cold seasons through the use of high-frequency passive microwave radiometry. Toward this end, the Weather Research and Forecasting (WRF) model with the Goddard microphysics scheme is coupled with a Satellite Data Simulation Unit (WRF-SDSU) that has been developed to facilitate over-land snowfall retrieval algorithms by providing a virtual cloud library and microwave brightness temperature (Tb) measurements consistent with the GPM Microwave Imager (GMI). This study tested the Goddard cloud microphysics scheme in WRF for snowstorm events (January 20-22, 2007) that took place over the Canadian CloudSAT/CALIPSO Validation Project (C3VP) ground site (Centre for Atmospheric Research Experiments - CARE) in Ontario, Canada. In this paper, the performance of the Goddard cloud microphysics scheme both with 2ice (ice and snow) and 3ice (ice, snow and graupel) as well as other WRF microphysics schemes will be presented. The results are compared with data from the Environment Canada (EC) King Radar, an operational C-band radar located near the CARE site. In addition, the WRF model output is used to drive the Goddard SDSU to calculate radiances and backscattering signals consistent with direct satellite observations for evaluating the model results.

Microphysical processing of aerosol particles in orographic clouds

NASA Astrophysics Data System (ADS)

Pousse-Nottelmann, S.; Zubler, E. M.; Lohmann, U.

2015-01-01

An explicit and detailed treatment of cloud-borne particles allowing for the consideration of aerosol cycling in clouds has been implemented in the regional weather forecast and climate model COSMO. The effects of aerosol scavenging, cloud microphysical processing and regeneration upon cloud evaporation on the aerosol population and on subsequent cloud formation are investigated. For this, two-dimensional idealized simulations of moist flow over two bell-shaped mountains were carried out varying the treatment of aerosol scavenging and regeneration processes for a warm-phase and a mixed-phase orographic cloud. The results allowed to identify different aerosol cycling mechanisms. In the simulated non-precipitating warm-phase cloud, aerosol mass is incorporated into cloud droplets by activation scavenging and released back to the atmosphere upon cloud droplet evaporation. In the mixed-phase cloud, a first cycle comprises cloud droplet activation and evaporation via the Wegener-Bergeron-Findeisen process. A second cycle includes below-cloud scavenging by precipitating snow particles and snow sublimation and is connected to the first cycle via the riming process which transfers aerosol mass from cloud droplets to snow flakes. In the simulated mixed-phase cloud, only a negligible part of the total aerosol mass is incorporated into ice crystals. Sedimenting snow flakes reaching the surface remove aerosol mass from the atmosphere. The results show that aerosol processing and regeneration lead to a vertical redistribution of aerosol mass and number. However, the processes not only impact the total aerosol number and mass, but also the shape of the aerosol size distributions by enhancing the internally mixed/soluble accumulation mode and generating coarse mode particles. Concerning subsequent cloud formation at the second mountain, accounting for aerosol processing and regeneration increases the cloud droplet number concentration with possible implications for the ice crystal number concentration.

Cloud Properties Simulated by a Single-Column Model. Part II: Evaluation of Cumulus Detrainment and Ice-phase Microphysics Using a Cloud Resolving Model

NASA Technical Reports Server (NTRS)

Luo, Yali; Krueger, Steven K.; Xu, Kuan-Man

2005-01-01

This paper is the second in a series in which kilometer-scale-resolving observations from the Atmospheric Radiation Measurement program and a cloud-resolving model (CRM) are used to evaluate the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model. Part I demonstrated that kilometer-scale cirrus properties simulated by the SCM significantly differ from the cloud radar observations while the CRM simulation reproduced most of the cirrus properties as revealed by the observations. The present study describes an evaluation, through a comparison with the CRM, of the SCM's representation of detrainment from deep cumulus and ice-phase microphysics in an effort to better understand the findings of Part I. It is found that detrainment occurs too infrequently at a single level at a time in the SCM, although the detrainment rate averaged over the entire simulation period is somewhat comparable to that of the CRM simulation. Relatively too much detrained ice is sublimated when first detrained. Snow falls over too deep of a layer due to the assumption that snow source and sink terms exactly balance within one time step in the SCM. These characteristics in the SCM parameterizations may explain many of the differences in the cirrus properties between the SCM and the observations (or between the SCM and the CRM). A possible improvement for the SCM consists of the inclusion of multiple cumulus cloud types as in the original Arakawa-Schubert scheme, prognostically determining the stratiform cloud fraction and snow mixing ratio. This would allow better representation of the detrainment from deep convection, better coupling of the volume of detrained air with cloud fraction, and better representation of snow field.

Glaciological studies in the central Andes using AIRSAR/TOPSAR

NASA Technical Reports Server (NTRS)

Forster, Richard R.; Klein, Andrew G.; Blodgett, Troy A.; Isacks, Bryan L.

1993-01-01

The interaction of climate and topography in mountainous regions is dramatically expressed in the spatial distribution of glaciers and snowcover. Monitoring existing alpine glaciers and snow extent provides insight into the present mountain climate system and how it is changing, while mapping the positions of former glaciers as recorded in landforms such as cirques and moraines provide a record of the large past climate change associated with the last glacial maximum. The Andes are an ideal mountain range in which to study the response of snow and ice to past and present climate change. Their expansive latitudinal extent offers the opportunity to study glaciers in diverse climate settings from the tropical glaciers of Peru and Bolivia to the ice caps and tide-water glaciers of sub-polar Patagonia. SAR has advantages over traditional passive remote sensing instruments for monitoring present snow and ice and differentiating moraine relative ages. The cloud penetrating ability of SAR is indispensable for perennially cloud covered mountains. Snow and ice facies can be distinguished from SAR's response to surface roughness, liquid water content and grain size distribution. The combination of SAR with a coregestered high-resolution DEM (TOPSAR) provides a promising tool for measuring glacier change in three dimensions, thus allowing ice volume change to be measured directly. The change in moraine surface roughness over time enables SAR to differentiate older from younger moraines. Polarimetric SAR data have been used to distinguish snow and ice facies and relatively date moraines. However, both algorithms are still experimental and require ground truth verification. We plan to extend the SAR classification of snow and ice facies and moraine age beyond the ground truth sites to throughout the Cordillera Real to provide a regional view of past and present snow and ice. The high resolution DEM will enhance the SAR moraine dating technique by discriminating relative ages based on moraine slope degradation.

Waves on White: Ice or Clouds?

NASA Technical Reports Server (NTRS)

2005-01-01

As it passed over Antarctica on December 16, 2004, the Multi-angle Imaging SpectroRadiometer (MISR) on NASA's Terra satellite captured this image showing a wavy pattern in a field of white. At most other latitudes, such wavy patterns would likely indicate stratus or stratocumulus clouds. MISR, however, saw something different. By using information from several of its multiple cameras (each of which views the Earth's surface from a different angle), MISR was able to tell that what looked like a wavy cloud pattern was actually a wavy pattern on the ice surface. One of MISR's cloud classification products, the Angular Signature Cloud Mask (ASCM), correctly identified the rippled area as being at the surface.

In this image pair, the view from MISR's most oblique backward-viewing camera is on the left, and the color-coded image on the right shows the results of the ASCM. The colors represent the level of certainty in the classification. Areas that were classed as cloudy with high confidence are white, and areas where the confidence was lower are yellow; dark blue shows confidently clear areas, while light blue indicates clear with lower confidence. The ASCM works particularly well at detecting clouds over snow and ice, but also works well over ocean and land. The rippled area on the surface which could have been mistaken for clouds are actually sastrugi -- long wavelike ridges of snow formed by the wind and found on the polar plains. Usually sastrugi are only several centimeters high and several meters apart, but large portions of East Antarctica are covered by mega-sastrugi ice fields, with dune-like features as high as four meters separated by two to five kilometers. The mega-sastrugi fields are a result of unusual snow accumulation and redistribution processes influenced by the prevailing winds and climate conditions. MISR imagery indicates that these mega sastrugi were stationary features between 2002 and 2004.

Being able to distinguish clouds from snow or ice-covered surfaces is important in order to adequately characterize the radiation balance of the polar regions. However, detecting clouds using spaceborne detectors over snow and ice surfaces is notoriously difficult, because the surface may often be as bright and as cold as the overlying clouds, and because polar atmospheric temperature inversions sometimes mean that clouds are warmer than the underlying snow or ice surface. The Angular Signature Cloud Mask (ASCM) was developed based on the Band-Differenced Angular Signature (BDAS) approach, introduced by Di Girolamo and Davies (1994) and updated for MISR application by Di Girolamo and Wilson (2003). BDAS uses both spectral and angular changes in reflectivity to distinguish clouds from the background, and the ASCM calculates the difference between the 446 and 866 nanometer reflectances at MISR's two most oblique cameras that view forward-scattered light. New land thresholds for the ASCM are planned for delivery later this year.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire globe between 82o north and 82o south latitude. This image area covers about 277 kilometers by 421 kilometers in the interior of the East Antarctic ice sheet. These data products were generated from a portion of the imagery acquired during Terra orbit 26584 and utilize data from within blocks 159 to 161 within World Reference System-2 path 63.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Fungal spores as potential ice nuclei in fog/cloud water and snow

NASA Astrophysics Data System (ADS)

Bauer, Heidi; Goncalves, Fabio L. T.; Schueller, Elisabeth; Puxbaum, Hans

2010-05-01

INTRODUCTION: In discussions about climate change and precipitation frequency biological ice nucleation has become an issue. While bacterial ice nucleation (IN) is already well characterized and even utilized in industrial processes such as the production of artificial snow or to improve freezing processes in food industry, less is known about the IN potential of fungal spores which are also ubiquitous in the atmosphere. A recent study performed at a mountain top in the Rocky Mountains suggests that fungal spores and/or pollen might play a role in increased IN abundance during periods of cloud cover (Bowers et al. 2009). In the present work concentrations of fungal spores in fog/cloud water and snow were determined. EXPERIMENTAL: Fog samples were taken with an active fog sampler in 2008 in a traffic dominated area and in a national park in São Paulo, Brazil. The number concentrations of fungal spores were determined by microscopic by direct enumeration by epifluorescence microscopy after staining with SYBR Gold nucleic acid gel stain (Bauer et al. 2008). RESULTS: In the fog water collected in the polluted area at a junction of two highly frequented highways around 22,000 fungal spores mL-1 were counted. Fog in the national park contained 35,000 spores mL-1. These results were compared with cloud water and snow samples from Mt. Rax, situated at the eastern rim of the Austrian Alps. Clouds contained on average 5,900 fungal spores mL-1 cloud water (1,300 - 11,000) or 2,200 spores m-3 (304 - 5,000). In freshly fallen snow spore concentrations were lower than in cloud water, around 1,000 fungal spores mL-1 were counted (Bauer et al. 2002). In both sets of samples representatives of the ice nucleating genus Fusarium could be observed. REFERENCES: Bauer, H., Kasper-Giebl, A., Löflund, M., Giebl, H., Hitzenberger, R., Zibuschka, F., Puxbaum, H. (2002). The contribution of bacteria and fungal spores to the organic carbon content of cloud water, precipitation and aerosols. Atmos. Res. 64, 109-119. Bauer, H., Schueller, E., Weinke, G. Berger, A., Hitzenberger, R., Marr, I.L., Puxbaum, H. (2008). Significant contributions of fungal spores to the organic carbon and to the aerosol mass balance of the urban atmospheric aerosol. Atmos. Environ. 42, 5542-5549. Bowers, R.M., Lauber, C.L., Wiedinmyer, C., Hamady, M., Hallar, A.G., Fall, R., Knight, R., Fierer, N. (2009). Characterization of airborne microbial communities at a high-elevation site and their potential to act as atmospheric ice nuclei. Appl. Environ. Microbiol: 75, 5121-5130.

Investigating ice nucleation in cirrus clouds with an aerosol-enabled Multiscale Modeling Framework

DOE PAGES

Zhang, Chengzhu; Wang, Minghuai; Morrison, H.; ...

2014-11-06

In this study, an aerosol-dependent ice nucleation scheme [Liu and Penner, 2005] has been implemented in an aerosol-enabled multi-scale modeling framework (PNNL MMF) to study ice formation in upper troposphere cirrus clouds through both homogeneous and heterogeneous nucleation. The MMF model represents cloud scale processes by embedding a cloud-resolving model (CRM) within each vertical column of a GCM grid. By explicitly linking ice nucleation to aerosol number concentration, CRM-scale temperature, relative humidity and vertical velocity, the new MMF model simulates the persistent high ice supersaturation and low ice number concentration (10 to 100/L) at cirrus temperatures. The low ice numbermore » is attributed to the dominance of heterogeneous nucleation in ice formation. The new model simulates the observed shift of the ice supersaturation PDF towards higher values at low temperatures following homogeneous nucleation threshold. The MMF models predict a higher frequency of midlatitude supersaturation in the Southern hemisphere and winter hemisphere, which is consistent with previous satellite and in-situ observations. It is shown that compared to a conventional GCM, the MMF is a more powerful model to emulate parameters that evolve over short time scales such as supersaturation. Sensitivity tests suggest that the simulated global distribution of ice clouds is sensitive to the ice nucleation schemes and the distribution of sulfate and dust aerosols. Simulations are also performed to test empirical parameters related to auto-conversion of ice crystals to snow. Results show that with a value of 250 μm for the critical diameter, Dcs, that distinguishes ice crystals from snow, the model can produce good agreement to the satellite retrieved products in terms of cloud ice water path and ice water content, while the total ice water is not sensitive to the specification of Dcs value.« less

Vertical Structure of Ice Cloud Layers From CloudSat and CALIPSO Measurements and Comparison to NICAM Simulations

NASA Technical Reports Server (NTRS)

Ham, Seung-Hee; Sohn, Byung-Ju; Kato, Seiji; Satoh, Masaki

2013-01-01

The shape of the vertical profile of ice cloud layers is examined using 4 months of CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) global measurements taken on January, April, July, and October 2007. Ice clouds are selected using temperature profiles when the cloud base is located above the 253K temperature level. The obtained ice water content (IWC), effective radius, or extinction coefficient profiles are normalized by their layer mean values and are expressed in the normalized vertical coordinate, which is defined as 0 and 1 at the cloud base and top heights, respectively. Both CloudSat and CALIPSO observations show that the maximum in the IWC and extinction profiles shifts toward the cloud bottom, as the cloud depth increases. In addition, clouds with a base reaching the surface in a high-latitude region show that the maximum peak of the IWC and extinction profiles occurs near the surface, which is presumably due to snow precipitation. CloudSat measurements show that the seasonal difference in normalized cloud vertical profiles is not significant, whereas the normalized cloud vertical profile significantly varies depending on the cloud type and the presence of precipitation. It is further examined if the 7 day Nonhydrostatic Icosahedral Atmospheric Model (NICAM) simulation results from 25 December 2006 to 1 January 2007 generate similar cloud profile shapes. NICAM IWC profiles also show maximum peaks near the cloud bottom for thick cloud layers and maximum peaks at the cloud bottom for low-level clouds near the surface. It is inferred that oversized snow particles in the NICAM cloud scheme produce a more vertically inhomogeneous IWC profile than observations due to quick sedimentation.

Validation of Cloud Optical Parameters from Passive Remote Sensing in the Arctic by using the Aircraft Measurements

NASA Astrophysics Data System (ADS)

Chen, H.; Schmidt, S.; Coddington, O.; Wind, G.; Bucholtz, A.; Segal-Rosenhaimer, M.; LeBlanc, S. E.

2017-12-01

Cloud Optical Parameters (COPs: e.g., cloud optical thickness and cloud effective radius) and surface albedo are the most important inputs for determining the Cloud Radiative Effect (CRE) at the surface. In the Arctic, the COPs derived from passive remote sensing such as from the Moderate Resolution Imaging Spectroradiometer (MODIS) are difficult to obtain with adequate accuracy owing mainly to insufficient knowledge about the snow/ice surface, but also because of the low solar zenith angle. This study aims to validate COPs derived from passive remote sensing in the Arctic by using aircraft measurements collected during two field campaigns based in Fairbanks, Alaska. During both experiments, ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) and ARISE (Arctic Radiation-IceBridge Sea and Ice Experiment), the Solar Spectral Flux Radiometer (SSFR) measured upwelling and downwelling shortwave spectral irradiances, which can be used to derive surface and cloud albedo, as well as the irradiance transmitted by clouds. We assess the variability of the Arctic sea ice/snow surfaces albedo through these aircraft measurements and incorporate this variability into cloud retrievals for SSFR. We then compare COPs as derived from SSFR and MODIS for all suitable aircraft underpasses of the satellites. Finally, the sensitivities of the COPs to surface albedo and solar zenith angle are investigated.

Ice nucleation active particles are efficiently removed by precipitating clouds.

PubMed

Stopelli, Emiliano; Conen, Franz; Morris, Cindy E; Herrmann, Erik; Bukowiecki, Nicolas; Alewell, Christine

2015-11-10

Ice nucleation in cold clouds is a decisive step in the formation of rain and snow. Observations and modelling suggest that variations in the concentrations of ice nucleating particles (INPs) affect timing, location and amount of precipitation. A quantitative description of the abundance and variability of INPs is crucial to assess and predict their influence on precipitation. Here we used the hydrological indicator δ(18)O to derive the fraction of water vapour lost from precipitating clouds and correlated it with the abundance of INPs in freshly fallen snow. Results show that the number of INPs active at temperatures ≥ -10 °C (INPs-10) halves for every 10% of vapour lost through precipitation. Particles of similar size (>0.5 μm) halve in number for only every 20% of vapour lost, suggesting effective microphysical processing of INPs during precipitation. We show that INPs active at moderate supercooling are rapidly depleted by precipitating clouds, limiting their impact on subsequent rainfall development in time and space.

Clouds enhance Greenland ice sheet meltwater runoff.

PubMed

Van Tricht, K; Lhermitte, S; Lenaerts, J T M; Gorodetskaya, I V; L'Ecuyer, T S; Noël, B; van den Broeke, M R; Turner, D D; van Lipzig, N P M

2016-01-12

The Greenland ice sheet has become one of the main contributors to global sea level rise, predominantly through increased meltwater runoff. The main drivers of Greenland ice sheet runoff, however, remain poorly understood. Here we show that clouds enhance meltwater runoff by about one-third relative to clear skies, using a unique combination of active satellite observations, climate model data and snow model simulations. This impact results from a cloud radiative effect of 29.5 (±5.2) W m(-2). Contrary to conventional wisdom, however, the Greenland ice sheet responds to this energy through a new pathway by which clouds reduce meltwater refreezing as opposed to increasing surface melt directly, thereby accelerating bare-ice exposure and enhancing meltwater runoff. The high sensitivity of the Greenland ice sheet to both ice-only and liquid-bearing clouds highlights the need for accurate cloud representations in climate models, to better predict future contributions of the Greenland ice sheet to global sea level rise.

Clouds enhance Greenland ice sheet meltwater runoff

PubMed Central

Van Tricht, K.; Lhermitte, S.; Lenaerts, J. T. M.; Gorodetskaya, I. V.; L'Ecuyer, T. S.; Noël, B.; van den Broeke, M. R.; Turner, D. D.; van Lipzig, N. P. M.

2016-01-01

The Greenland ice sheet has become one of the main contributors to global sea level rise, predominantly through increased meltwater runoff. The main drivers of Greenland ice sheet runoff, however, remain poorly understood. Here we show that clouds enhance meltwater runoff by about one-third relative to clear skies, using a unique combination of active satellite observations, climate model data and snow model simulations. This impact results from a cloud radiative effect of 29.5 (±5.2) W m−2. Contrary to conventional wisdom, however, the Greenland ice sheet responds to this energy through a new pathway by which clouds reduce meltwater refreezing as opposed to increasing surface melt directly, thereby accelerating bare-ice exposure and enhancing meltwater runoff. The high sensitivity of the Greenland ice sheet to both ice-only and liquid-bearing clouds highlights the need for accurate cloud representations in climate models, to better predict future contributions of the Greenland ice sheet to global sea level rise. PMID:26756470

Predicting Clear-Sky Reflectance Over Snow/Ice in Polar Regions

NASA Technical Reports Server (NTRS)

Chen, Yan; Sun-Mack, Sunny; Arduini, Robert F.; Hong, Gang; Minnis, Patrick

2015-01-01

Satellite remote sensing of clouds requires an accurate estimate of the clear-sky radiances for a given scene to detect clouds and aerosols and to retrieve their microphysical properties. Knowing the spatial and angular variability of clear-sky albedo is essential for predicting clear-sky radiance at solar wavelengths. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the nearinfrared (NIR; 1.24, 1.6 or 2.13 micrometers), visible (VIS; 0.63 micrometers) and vegetation (VEG; 0.86 micrometers) channels available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) to help identify clouds and retrieve their properties in both snow-free and snow-covered conditions. Thus, it is critical to have reliable distributions of clear-sky albedo for all of these channels. In CERES Edition 4 (Ed4), the 1.24-micrometer channel is used to retrieve cloud optical depth over snow/ice-covered surfaces. Thus, it is especially critical to accurately predict the 1.24-micrometer clear-sky albedo alpha and reflectance rho for a given location and time. Snow albedo and reflectance patterns are very complex due to surface texture, particle shapes and sizes, melt water, and vegetation protrusions from the snow surface. To minimize those effects, this study focuses on the permanent snow cover of Antarctica where vegetation is absent and melt water is minimal. Clear-sky albedos are determined as a function of solar zenith angle (SZA) from observations over all scenes determined to be cloud-free to produce a normalized directional albedo model (DRM). The DRM is used to develop alpha(SZA=0 degrees) on 10 foot grid for each season. These values provide the basis for predicting r at any location and set of viewing & illumination conditions. This paper examines the accuracy of this approach for two theoretical snow surface reflectance models.

Effects of cloud condensation nuclei and ice nucleating particles on precipitation processes and supercooled liquid in mixed-phase orographic clouds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fan, Jiwen; Leung, L. Ruby; Rosenfeld, Daniel

How orographic mixed-phase clouds respond to the change in cloud condensation nuclei (CCN) and ice nucleating particles (INPs) are highly uncertain. The main snow production mechanism in warm and cold mixed-phase orographic clouds (referred to as WMOCs and CMOCs, respectively, distinguished here as those having cloud tops warmer and colder than -20°C) could be very different. We quantify the CCN and INP impacts on supercooled water content, cloud phases, and precipitation for a WMOC case and a CMOC case, with sensitivity tests using the same CCN and INP concentrations between the WMOC and CMOC cases. It was found that depositionmore » plays a more important role than riming for forming snow in the CMOC case, while the role of riming is dominant in the WMOC case. As expected, adding CCN suppresses precipitation, especially in WMOCs and low INPs. However, this reverses strongly for CCN of 1000 cm -3 and larger. We found a new mechanism through which CCN can invigorate mixed-phase clouds over the Sierra Nevada and drastically intensify snow precipitation when CCN concentrations are high (1000 cm -3 or higher). In this situation, more widespread shallow clouds with a greater amount of cloud water form in the Central Valley and foothills west of the mountain range. The increased latent heat release associated with the formation of these clouds strengthens the local transport of moisture to the windward slope, invigorating mixed-phase clouds over the mountains, and thereby producing higher amounts of snow precipitation. Under all CCN conditions, increasing the INPs leads to decreased riming and mixed-phase fraction in the CMOC as a result of liquid-limited conditions, but has the opposite effects in the WMOC as a result of ice-limited conditions. However, precipitation in both cases is increased by increasing INPs due to an increase in deposition for the CMOC but enhanced riming and deposition in the WMOC. Increasing the INPs dramatically reduces supercooled water content and increases the cloud glaciation temperature, while increasing CCN has the opposite effect with much smaller significance.« less

Effects of cloud condensation nuclei and ice nucleating particles on precipitation processes and supercooled liquid in mixed-phase orographic clouds

DOE PAGES

Fan, Jiwen; Leung, L. Ruby; Rosenfeld, Daniel; ...

2017-01-23

How orographic mixed-phase clouds respond to the change in cloud condensation nuclei (CCN) and ice nucleating particles (INPs) are highly uncertain. The main snow production mechanism in warm and cold mixed-phase orographic clouds (referred to as WMOCs and CMOCs, respectively, distinguished here as those having cloud tops warmer and colder than -20°C) could be very different. We quantify the CCN and INP impacts on supercooled water content, cloud phases, and precipitation for a WMOC case and a CMOC case, with sensitivity tests using the same CCN and INP concentrations between the WMOC and CMOC cases. It was found that depositionmore » plays a more important role than riming for forming snow in the CMOC case, while the role of riming is dominant in the WMOC case. As expected, adding CCN suppresses precipitation, especially in WMOCs and low INPs. However, this reverses strongly for CCN of 1000 cm -3 and larger. We found a new mechanism through which CCN can invigorate mixed-phase clouds over the Sierra Nevada and drastically intensify snow precipitation when CCN concentrations are high (1000 cm -3 or higher). In this situation, more widespread shallow clouds with a greater amount of cloud water form in the Central Valley and foothills west of the mountain range. The increased latent heat release associated with the formation of these clouds strengthens the local transport of moisture to the windward slope, invigorating mixed-phase clouds over the mountains, and thereby producing higher amounts of snow precipitation. Under all CCN conditions, increasing the INPs leads to decreased riming and mixed-phase fraction in the CMOC as a result of liquid-limited conditions, but has the opposite effects in the WMOC as a result of ice-limited conditions. However, precipitation in both cases is increased by increasing INPs due to an increase in deposition for the CMOC but enhanced riming and deposition in the WMOC. Increasing the INPs dramatically reduces supercooled water content and increases the cloud glaciation temperature, while increasing CCN has the opposite effect with much smaller significance.« less

Tropical Convective Responses to Microphysical and Radiative Processes: A Sensitivity Study With a 2D Cloud Resolving Model

NASA Technical Reports Server (NTRS)

Li, Xiao-Fan; Sui, C.-H.; Lau, K.-M.; Tao, W.-K.

2004-01-01

Prognostic cloud schemes are increasingly used in weather and climate models in order to better treat cloud-radiation processes. Simplifications are often made in such schemes for computational efficiency, like the scheme being used in the National Centers for Environment Prediction models that excludes some microphysical processes and precipitation-radiation interaction. In this study, sensitivity tests with a 2D cloud resolving model are carried out to examine effects of the excluded microphysical processes and precipitation-radiation interaction on tropical thermodynamics and cloud properties. The model is integrated for 10 days with the imposed vertical velocity derived from the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment. The experiment excluding the depositional growth of snow from cloud ice shows anomalous growth of cloud ice and more than 20% increase of fractional cloud cover, indicating that the lack of the depositional snow growth causes unrealistically large mixing ratio of cloud ice. The experiment excluding the precipitation-radiation interaction displays a significant cooling and drying bias. The analysis of heat and moisture budgets shows that the simulation without the interaction produces more stable upper troposphere and more unstable mid and lower troposphere than does the simulation with the interaction. Thus, the suppressed growth of ice clouds in upper troposphere and stronger radiative cooling in mid and lower troposphere are responsible for the cooling bias, and less evaporation of rain associated with the large-scale subsidence induces the drying in mid and lower troposphere.

Improving the Representation of Snow Crystal Properties Within a Single-Moment Microphysics Scheme

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Dembek, S. R.

2010-01-01

As computational resources continue their expansion, weather forecast models are transitioning to the use of parameterizations that predict the evolution of hydrometeors and their microphysical processes, rather than estimating the bulk effects of clouds and precipitation that occur on a sub-grid scale. These parameterizations are referred to as single-moment, bulk water microphysics schemes, as they predict the total water mass among hydrometeors in a limited number of classes. Although the development of single moment microphysics schemes have often been driven by the need to predict the structure of convective storms, they may also provide value in predicting accumulations of snowfall. Predicting the accumulation of snowfall presents unique challenges to forecasters and microphysics schemes. In cases where surface temperatures are near freezing, accumulated depth often depends upon the snowfall rate and the ability to overcome an initial warm layer. Precipitation efficiency relates to the dominant ice crystal habit, as dendrites and plates have relatively large surface areas for the accretion of cloud water and ice, but are only favored within a narrow range of ice supersaturation and temperature. Forecast models and their parameterizations must accurately represent the characteristics of snow crystal populations, such as their size distribution, bulk density and fall speed. These properties relate to the vertical distribution of ice within simulated clouds, the temperature profile through latent heat release, and the eventual precipitation rate measured at the surface. The NASA Goddard, single-moment microphysics scheme is available to the operational forecast community as an option within the Weather Research and Forecasting (WRF) model. The NASA Goddard scheme predicts the occurrence of up to six classes of water mass: vapor, cloud ice, cloud water, rain, snow and either graupel or hail.

Cloud Microphysics Budget in the Tropical Deep Convective Regime

NASA Technical Reports Server (NTRS)

Li, Xiao-Fan; Sui, C.-H.; Lau, K.-M.; Einaudi, Franco (Technical Monitor)

2001-01-01

Cloud microphysics budgets in the tropical deep convective regime are analyzed based on a 2-D cloud resolving simulation. The model is forced by the large-scale vertical velocity and zonal wind and large-scale horizontal advections derived from TOGA COARE for a 20-day period. The role of cloud microphysics is first examined by analyzing mass-weighted mean heat budget and column-integrated moisture budget. Hourly budgets show that local changes of mass-weighted mean temperature and column-integrated moisture are mainly determined by the residuals between vertical thermal advection and latent heat of condensation and between vertical moisture advection and condensation respectively. Thus, atmospheric thermodynamics depends on how cloud microphysical processes are parameterized. Cloud microphysics budgets are then analyzed for raining conditions. For cloud-vapor exchange between cloud system and its embedded environment, rainfall and evaporation of raindrop are compensated by the condensation and deposition of supersaturated vapor. Inside the cloud system, the condensation of supersaturated vapor balances conversion from cloud water to raindrop, snow, and graupel through collection and accretion processes. The deposition of supersaturated vapor balances conversion from cloud ice to snow through conversion and riming processes. The conversion and riming of cloud ice and the accretion of cloud water balance conversion from snow to graupel through accretion process. Finally, the collection of cloud water and the melting of graupel increase raindrop to compensate the loss of raindrop due to rainfall and the evaporation of raindrop.

Siberian Islands

Atmospheric Science Data Center

2013-04-16

... Distinguishing Clouds from Ice over the East Siberian Sea, Russia     View Larger Image ... snow and ice. The central portion of Russia's East Siberian Sea, including one of the New Siberian Islands, Novaya Sibir, are portrayed in ...

Explicit prediction of ice clouds in general circulation models

NASA Astrophysics Data System (ADS)

Kohler, Martin

1999-11-01

Although clouds play extremely important roles in the radiation budget and hydrological cycle of the Earth, there are large quantitative uncertainties in our understanding of their generation, maintenance and decay mechanisms, representing major obstacles in the development of reliable prognostic cloud water schemes for General Circulation Models (GCMs). Recognizing their relative neglect in the past, both observationally and theoretically, this work places special focus on ice clouds. A recent version of the UCLA - University of Utah Cloud Resolving Model (CRM) that includes interactive radiation is used to perform idealized experiments to study ice cloud maintenance and decay mechanisms under various conditions in term of: (1) background static stability, (2) background relative humidity, (3) rate of cloud ice addition over a fixed initial time-period and (4) radiation: daytime, nighttime and no-radiation. Radiation is found to have major effects on the life-time of layer-clouds. Optically thick ice clouds decay significantly slower than expected from pure microphysical crystal fall-out (taucld = 0.9--1.4 h as opposed to no-motion taumicro = 0.5--0.7 h). This is explained by the upward turbulent fluxes of water induced by IR destabilization, which partially balance the downward transport of water by snowfall. Solar radiation further slows the ice-water decay by destruction of the inversion above cloud-top and the resulting upward transport of water. Optically thin ice clouds, on the other hand, may exhibit even longer life-times (>1 day) in the presence of radiational cooling. The resulting saturation mixing ratio reduction provides for a constant cloud ice source. These CRM results are used to develop a prognostic cloud water scheme for the UCLA-GCM. The framework is based on the bulk water phase model of Ose (1993). The model predicts cloud liquid water and cloud ice separately, and which is extended to split the ice phase into suspended cloud ice (predicted) and falling snow (diagnosed) components. An empirical parameterization of the effect of upward turbulent water fluxes in cloud layers is obtained from the CRM simulations by (1) identifying the time-scale of conversion of cloud ice to snow as the key parameter, and (2) regressing it onto cloud differential IR heating and environmental static stability. The updated UCLA-GCM achieves close agreement with observations in global mean top of atmosphere fluxes (within 1--4 W/m2). Artificially suppressing the impact of cloud turbulent fluxes reduces the global mean ice water path by a factor of 3 and produces errors in each of solar and IR fluxes at the top of atmosphere of about 5--6 W/m2.

Using Field and Satellite Measurements to Improve Snow and Riming Processes in Cloud Resolving Models

NASA Technical Reports Server (NTRS)

Colle, Brian A.; Molthan, Andrew L.

2013-01-01

The representation of clouds in climate and weather models is a driver in forecast uncertainty. Cloud microphysics parameterizations are challenged by having to represent a diverse range of ice species. Key characteristics of predicted ice species include habit and fall speed, and complex interactions that result from mixed-phased processes like riming. Our proposed activity leverages Global Precipitation Measurement (GPM) Mission ground validation studies to improve parameterizations

Carbon Dioxide Snow Storms During the Polar Night on Mars

NASA Technical Reports Server (NTRS)

Toon, Owen B.; Colaprete, Anthony

2001-01-01

The Mars Orbiter Laser Altimeter (MOLA) detected clouds associated with topographic features during the polar night on Mars. While uplift generated from flow over mountains initiates clouds on both Earth and Mars, we suggest that the Martian clouds differ greatly from terrestrial mountain wave clouds. Terrestrial wave clouds are generally compact features with sharp edges due to the relatively small particles in them. However, we find that the large mass of condensible carbon dioxide on Mars leads to clouds with snow tails that may extend many kilometers down wind from the mountain and even reach the surface. Both the observations and the simulations suggest substantial carbon dioxide snow precipitation in association with the underlying topography. This precipitation deposits CO2, dust and water ice to the polar caps, and may lead to propagating geologic features in the Martian polar regions.

An Investigation of the Radiative Effects and Climate Feedbacks of Sea Ice Sources of Sea Salt Aerosol

NASA Astrophysics Data System (ADS)

Horowitz, H. M.; Alexander, B.; Bitz, C. M.; Jaegle, L.; Burrows, S. M.

2017-12-01

In polar regions, sea ice is a major source of sea salt aerosol through lofting of saline frost flowers or blowing saline snow from the sea ice surface. Under continued climate warming, an ice-free Arctic in summer with only first-year, more saline sea ice in winter is likely. Previous work has focused on climate impacts in summer from increasing open ocean sea salt aerosol emissions following complete sea ice loss in the Arctic, with conflicting results suggesting no net radiative effect or a negative climate feedback resulting from a strong first aerosol indirect effect. However, the radiative forcing from changes to the sea ice sources of sea salt aerosol in a future, warmer climate has not previously been explored. Understanding how sea ice loss affects the Arctic climate system requires investigating both open-ocean and sea ice sources of sea-salt aerosol and their potential interactions. Here, we implement a blowing snow source of sea salt aerosol into the Community Earth System Model (CESM) dynamically coupled to the latest version of the Los Alamos sea ice model (CICE5). Snow salinity is a key parameter affecting blowing snow sea salt emissions and previous work has assumed constant regional snow salinity over sea ice. We develop a parameterization for dynamic snow salinity in the sea ice model and examine how its spatial and temporal variability impacts the production of sea salt from blowing snow. We evaluate and constrain the snow salinity parameterization using available observations. Present-day coupled CESM-CICE5 simulations of sea salt aerosol concentrations including sea ice sources are evaluated against in situ and satellite (CALIOP) observations in polar regions. We then quantify the present-day radiative forcing from the addition of blowing snow sea salt aerosol with respect to aerosol-radiation and aerosol-cloud interactions. The relative contributions of sea ice vs. open ocean sources of sea salt aerosol to radiative forcing in polar regions is discussed.

Radiative transfer model of snow for bare ice regions

NASA Astrophysics Data System (ADS)

Tanikawa, T.; Aoki, T.; Niwano, M.; Hosaka, M.; Shimada, R.; Hori, M.; Yamaguchi, S.

2016-12-01

Modeling a radiative transfer (RT) for coupled atmosphere-snow-bare ice systems is of fundamental importance for remote sensing applications to monitor snow and bare ice regions in the Greenland ice sheet and for accurate climate change predictions by regional and global climate models. Recently, the RT model for atmosphere-snow system was implemented for our regional and global climate models. However, the bare ice region where recently it has been expanded on the Greenland ice sheet due to the global warming, has not been implemented for these models, implying that this region leads miscalculations in these climate models. Thus, the RT model of snow for bare ice regions is needed for accurate climate change predictions. We developed the RT model for coupled atmosphere-snow-bare ice systems, and conducted a sensitivity analysis of the RT model to know the effect of snow, bare ice and geometry parameters on the spectral radiant quantities. The RT model considers snow and bare-ice inherent optical properties (IOPs), including snow grain size, air bubble size and its concentration and bare ice thickness. The conventional light scattering theory, Mie theory, was used for IOP calculations. Monte Carlo method was used for the multiple scattering. The sensitivity analyses showed that spectral albedo for the bare ice increased with increasing the concentration of the air bubble in the bare ice for visible wavelengths because the air bubble is scatterer with no absorption. For near infrared wavelengths, spectral albedo has no dependence on the air bubble due to the strong light absorption by ice. When increasing solar zenith angle, the spectral albedo were increased for all wavelengths. This is the similar trend with spectral snow albedo. Cloud cover influenced the bare ice spectral albedo by covering direct radiation into diffuse radiation. The purely diffuse radiation has an effective solar zenith angle near 50°. Converting direct into diffuse radiation reduces the effective solar zenith angle, resulting in reducing the spectral albedo. This is also the similar trend with spectral snow albedo. Further work should focus on the validation of the RT model using in situ measurement data through field and laboratory experiments.

Freeboard, Snow Depth and Sea-Ice Roughness in East Antarctica from In Situ and Multiple Satellite Data

NASA Technical Reports Server (NTRS)

Markus, Thorsten; Masson, Robert; Worby, Anthony; Lytle, Victoria; Kurtz, Nathan; Maksym, Ted

2011-01-01

In October 2003 a campaign on board the Australian icebreaker Aurora Australis had the objective to validate standard Aqua Advanced Microwave Scanning Radiometer (AMSR-E) sea-ice products. Additionally, the satellite laser altimeter on the Ice, Cloud and land Elevation Satellite (ICESat) was in operation. To capture the large-scale information on the sea-ice conditions necessary for satellite validation, the measurement strategy was to obtain large-scale sea-ice statistics using extensive sea-ice measurements in a Lagrangian approach. A drifting buoy array, spanning initially 50 km 100 km, was surveyed during the campaign. In situ measurements consisted of 12 transects, 50 500 m, with detailed snow and ice measurements as well as random snow depth sampling of floes within the buoy array using helicopters. In order to increase the amount of coincident in situ and satellite data an approach has been developed to extrapolate measurements in time and in space. Assuming no change in snow depth and freeboard occurred during the period of the campaign on the floes surveyed, we use buoy ice-drift information as well as daily estimates of thin-ice fraction and rough-ice vs smooth-ice fractions from AMSR-E and QuikSCAT, respectively, to estimate kilometer-scale snow depth and freeboard for other days. The results show that ICESat freeboard estimates have a mean difference of 1.8 cm when compared with the in situ data and a correlation coefficient of 0.6. Furthermore, incorporating ICESat roughness information into the AMSR-E snow depth algorithm significantly improves snow depth retrievals. Snow depth retrievals using a combination of AMSR-E and ICESat data agree with in situ data with a mean difference of 2.3 cm and a correlation coefficient of 0.84 with a negligible bias.

Sensitivity of simulated snow cloud properties to mass-diameter parameterizations.

NASA Astrophysics Data System (ADS)

Duffy, G.; Nesbitt, S. W.; McFarquhar, G. M.

2015-12-01

Mass to diameter (m-D) relationships are used in model parameterization schemes to represent ice cloud microphysics and in retrievals of bulk cloud properties from remote sensing instruments. One of the most common relationships, used in the current Global Precipitation Measurement retrieval algorithm for example, assigns the density of snow as a constant tenth of the density of ice (0.1g/m^3). This assumption stands in contrast to the results of derived m-D relationships of snow particles, which imply decreasing particle densities at larger sizes and result in particle masses orders of magnitude below the constant density relationship. In this study, forward simulations of bulk cloud properties (e.g., total water content, radar reflectivity and precipitation rate) derived from measured size distributions using several historical m-D relationships are presented. This expands upon previous studies that mainly focused on smaller ice particles because of the examination of precipitation-sized particles here. In situ and remote sensing data from the GPM Cold season Experiment (GCPEx) and Canadian CloudSAT/Calypso Validation Program (C3VP), both synoptic snowstorm field experiments in southern Ontario, Canada, are used to evaluate the forward simulations against total water content measured by the Nevzorov and Cloud Spectrometer and Impactor (CSI) probe, radar reflectivity measured by a C band ground based radar and a nadir pointing Ku/Ka dual frequency airborne radar, and precipitation rate measured by a 2D video disdrometer. There are differences between the bulk cloud properties derived using varying m-D relations, with constant density assumptions producing results differing substantially from the bulk measured quantities. The variability in bulk cloud properties derived using different m-D relations is compared against the natural variability in those parameters seen in the GCPEx and C3VP field experiments.

Double-moment Cloud Microphysics Scheme for the Deep Convection Parameterization in the GFDL AM3

NASA Astrophysics Data System (ADS)

Belochitski, A.; Donner, L.

2013-12-01

A double-moment cloud microphysical scheme originally developed by Morrision and Gettelman (2008) for the stratiform clouds and later adopted for the deep convection by Song and Zhang (2011) is being implemented in to the deep convection parameterization of Geophysical Fluid Dynamics Laboratory's atmospheric general circulation model AM3. The scheme treats cloud drop, cloud ice, rain, and snow number concentrations and mixing ratios as diagnostic variables and incorporates processes of autoconversion, self-collection, collection between hydrometeor species, sedimentation, ice nucleation, drop activation, homogeneous and heterogeneous freezing, and the Bergeron-Findeisen process. Detailed representation of microphysical processes makes the scheme suitable for studying the interactions between aerosols and convection, as well as aerosols' indirect effects on clouds and the roles of these effects in climate change. The scheme is implemented into the single column version of the GFDL AM3 and evaluated using large scale forcing data obtained at the U.S. Department of Energy Atmospheric Radiation Measurment project's Southern Great Planes and Tropical West Pacific sites. Sensitivity of the scheme to formulations for autoconversion of cloud water and its accretion by rain, self-collection of rain and self-collection of snow, as well as the formulation for heterogenous ice nucleation is investigated. In the future, tests with the full atmospheric GCM will be conducted.

Sea ice-atmospheric interaction: Application of multispectral satellite data in polar surface energy flux estimates

NASA Technical Reports Server (NTRS)

Steffen, Konrad; Key, J.; Maslanik, J.; Schweiger, A.

1993-01-01

This is the third annual report on: Sea Ice-Atmosphere Interaction - Application of Multispectral Satellite Data in Polar Surface Energy Flux Estimates. The main emphasis during the past year was on: radiative flux estimates from satellite data; intercomparison of satellite and ground-based cloud amounts; radiative cloud forcing; calibration of the Advanced Very High Resolution Radiometer (AVHRR) visible channels and comparison of two satellite derived albedo data sets; and on flux modeling for leads. Major topics covered are arctic clouds and radiation; snow and ice albedo, and leads and modeling.

Evaluating the Performance of the Goddard Multi-Scale Modeling Framework against GPM, TRMM and CloudSat/CALIPSO Products

NASA Astrophysics Data System (ADS)

Chern, J. D.; Tao, W. K.; Lang, S. E.; Matsui, T.; Mohr, K. I.

2014-12-01

Four six-month (March-August 2014) experiments with the Goddard Multi-scale Modeling Framework (MMF) were performed to study the impacts of different Goddard one-moment bulk microphysical schemes and large-scale forcings on the performance of the MMF. Recently a new Goddard one-moment bulk microphysics with four-ice classes (cloud ice, snow, graupel, and frozen drops/hail) has been developed based on cloud-resolving model simulations with large-scale forcings from field campaign observations. The new scheme has been successfully implemented to the MMF and two MMF experiments were carried out with this new scheme and the old three-ice classes (cloud ice, snow graupel) scheme. The MMF has global coverage and can rigorously evaluate microphysics performance for different cloud regimes. The results show MMF with the new scheme outperformed the old one. The MMF simulations are also strongly affected by the interaction between large-scale and cloud-scale processes. Two MMF sensitivity experiments with and without nudging large-scale forcings to those of ERA-Interim reanalysis were carried out to study the impacts of large-scale forcings. The model simulated mean and variability of surface precipitation, cloud types, cloud properties such as cloud amount, hydrometeors vertical profiles, and cloud water contents, etc. in different geographic locations and climate regimes are evaluated against GPM, TRMM, CloudSat/CALIPSO satellite observations. The Goddard MMF has also been coupled with the Goddard Satellite Data Simulation Unit (G-SDSU), a system with multi-satellite, multi-sensor, and multi-spectrum satellite simulators. The statistics of MMF simulated radiances and backscattering can be directly compared with satellite observations to assess the strengths and/or deficiencies of MMF simulations and provide guidance on how to improve the MMF and microphysics.

An automated approach for mapping persistent ice and snow cover over high latitude regions

USGS Publications Warehouse

Selkowitz, David J.; Forster, Richard R.

2016-01-01

We developed an automated approach for mapping persistent ice and snow cover (glaciers and perennial snowfields) from Landsat TM and ETM+ data across a variety of topography, glacier types, and climatic conditions at high latitudes (above ~65°N). Our approach exploits all available Landsat scenes acquired during the late summer (1 August–15 September) over a multi-year period and employs an automated cloud masking algorithm optimized for snow and ice covered mountainous environments. Pixels from individual Landsat scenes were classified as snow/ice covered or snow/ice free based on the Normalized Difference Snow Index (NDSI), and pixels consistently identified as snow/ice covered over a five-year period were classified as persistent ice and snow cover. The same NDSI and ratio of snow/ice-covered days to total days thresholds applied consistently across eight study regions resulted in persistent ice and snow cover maps that agreed closely in most areas with glacier area mapped for the Randolph Glacier Inventory (RGI), with a mean accuracy (agreement with the RGI) of 0.96, a mean precision (user’s accuracy of the snow/ice cover class) of 0.92, a mean recall (producer’s accuracy of the snow/ice cover class) of 0.86, and a mean F-score (a measure that considers both precision and recall) of 0.88. We also compared results from our approach to glacier area mapped from high spatial resolution imagery at four study regions and found similar results. Accuracy was lowest in regions with substantial areas of debris-covered glacier ice, suggesting that manual editing would still be required in these regions to achieve reasonable results. The similarity of our results to those from the RGI as well as glacier area mapped from high spatial resolution imagery suggests it should be possible to apply this approach across large regions to produce updated 30-m resolution maps of persistent ice and snow cover. In the short term, automated PISC maps can be used to rapidly identify areas where substantial changes in glacier area have occurred since the most recent conventional glacier inventories, highlighting areas where updated inventories are most urgently needed. From a longer term perspective, the automated production of PISC maps represents an important step toward fully automated glacier extent monitoring using Landsat or similar sensors.

Windblown Snow

NASA Image and Video Library

2011-04-11

On April 11, 2011, IceBridge finally got the clear weather necessary to fly over glaciers in southeast Greenland, but with clear skies came winds of up to 70 knots. What looks like clouds is actually wind-blown snow. The data could help scientists to evaluate the impact of wind-blown snow on satellite-based laser altimetry measurements. Operation IceBridge, now in its third year, makes annual campaigns in the Arctic and Antarctic where science flights monitor glaciers, ice sheets and sea ice. Credit: NASA/GSFC/Michael Studinger To learn more about Ice Bridge go to: www.nasa.gov/mission_pages/icebridge/news/spr11/index.html NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Join us on Facebook

ERTS-1 views the Great Lakes

NASA Technical Reports Server (NTRS)

Lyons, W. A.; Pease, S. R.

1973-01-01

The meteorological content of ERTS images, particularly mesoscale effects of the Great Lakes and air pollution dispersion is summarized. Summertime lake breeze frontal clouds and various winter lake-effect convection patterns and snow squalls are revealed in great detail. A clear-cut spiral vortex over southern Lake Michigan is related to a record early snow storm in the Chicago area. Marked cloud changes induced by orographic and frictional effects on Lake Michigan's lee shore snow squalls are seen. The most important finding, however, is a clear-cut example of alterations in cumulus convection by anthropogenic condensation and/or ice nuclei from northern Indiana steel mills during a snow squall situation. Jet aircraft condensation trails are also found with surprising frequency.

The hydrometeor partitioning and microphysical processes over the Pacific Warm Pool in numerical modeling

NASA Astrophysics Data System (ADS)

Huang, Yi-Chih; Wang, Pao K.

2017-01-01

Numerical modeling is conducted to study the hydrometeor partitioning and microphysical source and sink processes during a quasi-steady state of thunderstorms over the Pacific Warm Pool by utilizing the microphysical model WISCDYMM to simulate selected storm cases. The results show that liquid-phase hydrometeors dominate thunderstorm evolution over the Pacific Warm Pool. The ratio of ice-phase mass to liquid-phase mass is about 41%: 59%, indicating that ice-phase water is not as significant over the Pacific Warm Pool as the liquid water compared to the larger than 50% in the subtropics and 80% in the US High Plains in a previous study. Sensitivity tests support the dominance of liquid-phase hydrometeors over the Pacific Warm Pool. The major rain sources are the key hail sinks: melting of hail and shedding from hail; whereas the crucial rain sinks are evaporation and accretion by hail. The major snow sources are Bergeron-Findeisen process, transfer of cloud ice to snow and accretion of cloud water; whereas the foremost sink of snow is accretion by hail. The essential hail sources are accretions of rain, cloud water, and snow; whereas the critical hail sinks are melting of hail and shedding from hail. The contribution and ranking of sources and sinks of these precipitates are compared with the previous study. Hydrometeors have their own special microphysical processes in the development and depletion over the Pacific Warm Pool. Microphysical budgets depend on atmospheric dynamical and thermodynamical conditions which determine the partitioning of hydrometeors. This knowledge would benefit the microphysics parameterization in cloud models and cumulus parameterization in global circulation models.

Direct Comparisons of Ice Cloud Macro- and Microphysical Properties Simulated by the Community Atmosphere Model CAM5 with HIPPO Aircraft Observations

NASA Astrophysics Data System (ADS)

Wu, C.; Liu, X.; Diao, M.; Zhang, K.; Gettelman, A.

2015-12-01

A dominant source of uncertainty within climate system modeling lies in the representation of cloud processes. This is not only because of the great complexity in cloud microphysics, but also because of the large variations of cloud amount and macroscopic properties in time and space. In this study, the cloud properties simulated by the Community Atmosphere Model version 5.4 (CAM5.4) are evaluated using the HIAPER Pole-to-Pole Observations (HIPPO, 2009-2011). CAM5.4 is driven by the meteorology (U, V, and T) from GEOS5 analysis, while water vapor, hydrometeors and aerosols are calculated by the model itself. For direct comparison of CAM5.4 and HIPPO observations, model output is collocated with HIPPO flights. Generally, the model has an ability to capture specific cloud systems of meso- to large-scales. In total, the model can reproduce 80% of observed cloud occurrences inside model grid boxes, and even higher (93%) for ice clouds (T≤-40°C). However, the model produces plenty of clouds that are not presented in the observation. The model also simulates significantly larger cloud fraction including for ice clouds compared to the observation. Further analysis shows that the overestimation is a result of bias in relative humidity (RH) in the model. The bias of RH can be mostly attributed to the discrepancies of water vapor, and to a lesser extent to those of temperature. Down to the micro-scale level of ice clouds, the model can simulate reasonably well the magnitude of ice and snow number concentration (Ni, with diameter larger than 75 μm). However, the model simulates fewer occurrences of Ni>50 L-1. This can be partially ascribed to the low bias of aerosol number concentration (Naer, with diameter between 0.1-1 μm) simulated by the model. Moreover, the model significantly underestimates both the number mean diameter (Di,n) and the volume mean diameter (Di,v) of ice/snow. The result shows that the underestimation may be related to a weaker positive relationship between Di,n and Naer and/or the underestimation of Naer. Finally, it is suggested that better representation of sub-grid variability of meteorology (e.g., water vapor) is needed to improve the formation and evolution of ice clouds in the model.

Snow Clouds and the Carbon Dioxide Cycle on Mars

NASA Astrophysics Data System (ADS)

Hayne, P. O.; Paige, D. A.

2009-12-01

The present climate of Mars is strongly influenced by the energy balance at the planet’s poles, with ~30% of the atmospheric mass exchanged seasonally with the polar ice caps. While the spring and summer sublimation process is observable in sunlight, the deposition process occurs in the darkness of polar night. We present direct radiometric observations of carbon dioxide snow clouds from the Mars Climate Sounder (MCS) and estimate the rate of deposition due to snowfall. We also present radiative transfer models capable of reproducing the observations and providing constraints on the radiative and thermal properties of the cap-atmosphere system. Snow clouds display a multi-layered structure with greatest opacity near the surface and extending to typical altitudes of about 20 km, with equivalent normal visible optical depths of ~0.1. Our modeling suggests the observed carbon dioxide snow grains are ~10 μm in radius, implying modest deposition rates, and suggesting the majority of the seasonal cap is deposited in a vertical region within one MCS field of view (or ~1 km) of the surface. Models reproducing the MCS limb observations only reproduce the nadir observations if the surface (or near-surface) is an optically thick layer of small (< 100 μm radius) carbon dioxide grains, which are therefore the primary cause of radiometrically cold areas (“cold spots”) observed since the Viking era. For the extreme polar regions, a persistent, ~500 km diameter snow cloud is strongly coupled to the most active cold spots, and smaller clouds (< 50 km diameter) in the latitude range 60-80°, though unobserved, cannot be ruled out by the MCS data. Based on this correlation, and observations of cold spots recurring near topographic slopes, we conclude that deposition is indeed linked to cloud formation, with the majority of material condensing below ~1 km altitude. Optically thin water ice layers are necessary to accurately model the MCS spectrum, particularly at altitudes above 20 km. This suggests water ice functions as the required condensation nucleus, consistent with earlier laboratory and theoretical studies. Important hemispherical differences are observed in the deposition process: 1) northern clouds are optically thicker at middle altitudes, ~5-15 km; 2) southern clouds are more often “detached”, showing a local maximum opacity near 20-25 km altitude; 3) mode particle radii are larger (~100 μm versus ~10 μm) in the north. Total normal optical depths are typically higher by a factor of ~2 in the north, and water ice content is relatively higher. Energy balance constraints can be placed on the system by MCS observations of outgoing infrared flux, which we map through time as an effective emissivity by taking account of the topography from MOLA and the expected frost point temperature.

Impact of Precipitating Ice Hydrometeors on Longwave Radiative Effect Estimated by a Global Cloud-System Resolving Model

NASA Astrophysics Data System (ADS)

Chen, Ying-Wen; Seiki, Tatsuya; Kodama, Chihiro; Satoh, Masaki; Noda, Akira T.

2018-02-01

Satellite observation and general circulation model (GCM) studies suggest that precipitating ice makes nonnegligible contributions to the radiation balance of the Earth. However, in most GCMs, precipitating ice is diagnosed and its radiative effects are not taken into account. Here we examine the longwave radiative impact of precipitating ice using a global nonhydrostatic atmospheric model with a double-moment cloud microphysics scheme. An off-line radiation model is employed to determine cloud radiative effects according to the amount and altitude of each type of ice hydrometeor. Results show that the snow radiative effect reaches 2 W m-2 in the tropics, which is about half the value estimated by previous studies. This effect is strongly dependent on the vertical separation of ice categories and is partially generated by differences in terminal velocities, which are not represented in GCMs with diagnostic precipitating ice. Results from sensitivity experiments that artificially change the categories and altitudes of precipitating ice show that the simulated longwave heating profile and longwave radiation field are sensitive to the treatment of precipitating ice in models. This study emphasizes the importance of incorporating appropriate treatments for the radiative effects of precipitating ice in cloud and radiation schemes in GCMs in order to capture the cloud radiative effects of upper level clouds.

Optical properties of CO2 ice and CO2 snow from ultraviolet to infrared: Application to frost deposits and clouds on Mars

NASA Technical Reports Server (NTRS)

Hansen, Gary B.; Warren, Stephen G.; Leovy, Conway B.

1991-01-01

Researchers found that it is possible to grow large clear samples of CO2 ice at Mars-like temperatures of 150-170K if a temperature controlled refrigerator is connected to an isolated two-phase pure CO2 system. They designed a chamber for transmission measurements whose optical path between the 13mm diameter window is adjustable from 1.6mm to 107mm. This will allow measurements of linear absorption down to less than 0.01 cm (exp -1). A preliminary transmission spectrum of a thick sample of CO2 ice in the near infrared was obtained. Once revised optical constants have been determined as a function of wavelength and temperature, they can be applied to spectral reflectance/emissivity models for CO2 snow surfaces, both pure and contaminated with dust and water ice, using previously established approaches. It will be useful, also, to develop an infrared scattering-emission cloud radiance model (especially as viewed from near the limb) in order to develop a strategy for the identification of CO2 cloud layers by the atmospheric infrared radiometer instrument on the Mars Observer.

Monitoring Snow Using Geostationary Satellite Retrievals During the SAAWSO Project

NASA Astrophysics Data System (ADS)

Rabin, Robert M.; Gultepe, Ismail; Kuligowski, Robert J.; Heidinger, Andrew K.

2016-09-01

The SAAWSO (Satellite Applications for Arctic Weather and SAR (Search And Rescue) Operations) field programs were conducted by Environment Canada near St. Johns, NL and Goose Bay, NL in the winters of 2012-13 and 2013-14, respectively. The goals of these programs were to validate satellite-based nowcasting products, including snow amount, wind intensity, and cloud physical parameters (e.g., cloud cover), over northern latitudes with potential applications to Search And Rescue (SAR) operations. Ground-based in situ sensors and remote sensing platforms were used to measure microphysical properties of precipitation, clouds and fog, radiation, temperature, moisture and wind profiles. Multi-spectral infrared observations obtained from Geostationary Operational Environmental Satellite (GOES)-13 provided estimates of cloud top temperature and height, phase (water, ice), hydrometer size, extinction, optical depth, and horizontal wind patterns at 15 min intervals. In this work, a technique developed for identifying clouds capable of producing high snowfall rates and incorporating wind information from the satellite observations is described. The cloud top physical properties retrieved from operational satellite observations are validated using measurements obtained from the ground-based in situ and remote sensing platforms collected during two precipitation events: a blizzard heavy snow storm case and a moderate snow event. The retrieved snow precipitation rates are found to be comparable to those of ground-based platform measurements in the heavy snow event.

The effect of ice nuclei on a deep convective cloud in South China

NASA Astrophysics Data System (ADS)

Deng, Xin; Xue, Huiwen; Meng, Zhiyong

2018-07-01

This study uses the Weather Research and Forecasting Model to simulate a deep convective cloud under a relatively polluted condition in South China. Ice nuclei (IN) aerosols near the surface are effectively transported upwards to above the 0 °C level by the strong updrafts in the convective cloud. Four cases with initial surface IN aerosol concentrations of 1, 10, 100, and 1000 L-1 are simulated. All simulations can well reproduce the major characteristics of the deep convective cloud in terms of the evolution, spatial distribution, and its track. IN aerosols have little effect on these macrophysical characteristics but can significantly affect ice formation. When IN concentration is increased, all heterogeneous nucleation modes are significantly enhanced, whereas the homogeneous freezing of cloud droplets is unchanged or weakened depending on the IN concentration and the development stages of the deep convective cloud. The homogeneous freezing of haze particles is generally not affected by increased IN but is slightly weakened in the extremely high IN case. As IN concentration is increased by 10 and 100 times, the enhanced heterogeneous nucleation is still not strong enough to compete with homogeneous freezing. Ice formation is hence still dominated by the homogenous freezing of cloud droplets and haze particles in the layer of 9-14 km, where most of the ice crystals are produced. The microphysical properties are generally unaffected in all the stages of cloud evolution. As IN concentration is increased by 1000 times and heterogeneous nucleation is further enhanced, the homogeneous freezing of cloud droplets and haze particles dominates only in the mature and dissipating stages, leading to unaffected ice number mixing ratio in the anvil region (approximately above 9 km) for these two stages. However, in the developing stage, when the supply of cloud droplets is limited, the homogeneous freezing of cloud droplets is weakened or even suppressed due to the very strong competition for liquid water with heterogeneous nucleation, leading to significantly lower ice number mixing ratio in the anvil regions. In addition, the microphysical properties in the convective core regions below the cloud anvil (approximately below 9 km) are also affected in the case of 1000 L-1. The enhanced heterogeneous nucleation produces more ice crystals below 9 km, leading to a stronger conversion from ice crystals to snow particles, and hence higher number and mass mixing ratios of snow. The IN effect on the spatial distributions and temporal evolutions of the surface precipitation and updraft velocity is generally insignificant.

A path towards uncertainty assignment in an operational cloud-phase algorithm from ARM vertically pointing active sensors

DOE PAGES

Riihimaki, Laura D.; Comstock, Jennifer M.; Anderson, Kevin K.; ...

2016-06-10

Knowledge of cloud phase (liquid, ice, mixed, etc.) is necessary to describe the radiative impact of clouds and their lifetimes, but is a property that is difficult to simulate correctly in climate models. One step towards improving those simulations is to make observations of cloud phase with sufficient accuracy to help constrain model representations of cloud processes. In this study, we outline a methodology using a basic Bayesian classifier to estimate the probabilities of cloud-phase class from Atmospheric Radiation Measurement (ARM) vertically pointing active remote sensors. The advantage of this method over previous ones is that it provides uncertainty informationmore » on the phase classification. We also test the value of including higher moments of the cloud radar Doppler spectrum than are traditionally used operationally. Using training data of known phase from the Mixed-Phase Arctic Cloud Experiment (M-PACE) field campaign, we demonstrate a proof of concept for how the method can be used to train an algorithm that identifies ice, liquid, mixed phase, and snow. Over 95 % of data are identified correctly for pure ice and liquid cases used in this study. Mixed-phase and snow cases are more problematic to identify correctly. When lidar data are not available, including additional information from the Doppler spectrum provides substantial improvement to the algorithm. As a result, this is a first step towards an operational algorithm and can be expanded to include additional categories such as drizzle with additional training data.« less

A path towards uncertainty assignment in an operational cloud-phase algorithm from ARM vertically pointing active sensors

NASA Astrophysics Data System (ADS)

Riihimaki, Laura D.; Comstock, Jennifer M.; Anderson, Kevin K.; Holmes, Aimee; Luke, Edward

2016-06-01

Knowledge of cloud phase (liquid, ice, mixed, etc.) is necessary to describe the radiative impact of clouds and their lifetimes, but is a property that is difficult to simulate correctly in climate models. One step towards improving those simulations is to make observations of cloud phase with sufficient accuracy to help constrain model representations of cloud processes. In this study, we outline a methodology using a basic Bayesian classifier to estimate the probabilities of cloud-phase class from Atmospheric Radiation Measurement (ARM) vertically pointing active remote sensors. The advantage of this method over previous ones is that it provides uncertainty information on the phase classification. We also test the value of including higher moments of the cloud radar Doppler spectrum than are traditionally used operationally. Using training data of known phase from the Mixed-Phase Arctic Cloud Experiment (M-PACE) field campaign, we demonstrate a proof of concept for how the method can be used to train an algorithm that identifies ice, liquid, mixed phase, and snow. Over 95 % of data are identified correctly for pure ice and liquid cases used in this study. Mixed-phase and snow cases are more problematic to identify correctly. When lidar data are not available, including additional information from the Doppler spectrum provides substantial improvement to the algorithm. This is a first step towards an operational algorithm and can be expanded to include additional categories such as drizzle with additional training data.

Investigating the Sensitivity of Nucleation Parameterization on Ice Growth

NASA Astrophysics Data System (ADS)

Gaudet, L.; Sulia, K. J.

2017-12-01

The accurate prediction of precipitation from lake-effect snow events associated with the Great Lakes region depends on the parameterization of thermodynamic and microphysical processes, including the formation and subsequent growth of frozen hydrometeors. More specifically, the formation of ice hydrometeors has been represented through varying forms of ice nucleation parameterizations considering the different nucleation modes (e.g., deposition, condensation-freezing, homogeneous). These parameterizations have been developed from in-situ measurements and laboratory observations. A suite of nucleation parameterizations consisting of those published in Meyers et al. (1992) and DeMott et al. (2010) as well as varying ice nuclei data sources are coupled with the Adaptive Habit Model (AHM, Harrington et al. 2013), a microphysics module where ice crystal aspect ratio and density are predicted and evolve in time. Simulations are run with the AHM which is implemented in the Weather Research and Forecasting (WRF) model to investigate the effect of ice nucleation parameterization on the non-spherical growth and evolution of ice crystals and the subsequent effects on liquid-ice cloud-phase partitioning. Specific lake-effect storms that were observed during the Ontario Winter Lake-Effect Systems (OWLeS) field campaign (Kristovich et al. 2017) are examined to elucidate this potential microphysical effect. Analysis of these modeled events is aided by dual-polarization radar data from the WSR-88D in Montague, New York (KTYX). This enables a comparison of the modeled and observed polarmetric and microphysical profiles of the lake-effect clouds, which involves investigating signatures of reflectivity, specific differential phase, correlation coefficient, and differential reflectivity. Microphysical features of lake-effect bands, such as ice, snow, and liquid mixing ratios, ice crystal aspect ratio, and ice density are analyzed to understand signatures in the aforementioned modeled dual-polarization radar variables. Hence, this research helps to determine an ice nucleation scheme that will best model observations of lake-effect clouds producing snow off of Lake Ontario and Lake Erie, and analyses will highlight the sensitivity of the evolution of the cases to a given nucleation scheme.

Bio-organic materials in the atmosphere and snow: measurement and characterization.

PubMed

Ariya, P A; Kos, G; Mortazavi, R; Hudson, E D; Kanthasamy, V; Eltouny, N; Sun, J; Wilde, C

2014-01-01

Bio-organic chemicals are ubiquitous in the Earth's atmosphere and at air-snow interfaces, as well as in aerosols and in clouds. It has been known for centuries that airborne biological matter plays various roles in the transmission of disease in humans and in ecosystems. The implication of chemical compounds of biological origins in cloud condensation and in ice nucleation processes has also been studied during the last few decades, and implications have been suggested in the reduction of visibility, in the influence on oxidative potential of the atmosphere and transformation of compounds in the atmosphere, in the formation of haze, change of snow-ice albedo, in agricultural processes, and bio-hazards and bio-terrorism. In this review we critically examine existing observation data on bio-organic compounds in the atmosphere and in snow. We also review both conventional and cutting-edge analytical techniques and methods for measurement and characterisation of bio-organic compounds and specifically for microbial communities, in the atmosphere and snow. We also explore the link between biological compounds and nucleation processes. Due to increased interest in decreasing emissions of carbon-containing compounds, we also briefly review (in an Appendix) methods and techniques that are currently deployed for bio-organic remediation.

Spatio Temporal Variability of the Global Transmittance During the Arctic POLARSTERN Expedition 106/1 Ice Floe Station

NASA Astrophysics Data System (ADS)

Barrientos Velasco, C.; Macke, A.; Griesche, H.; Engelmann, R.; Deneke, H.; Seifert, P.

2017-12-01

The Arctic is warming at a higher rate than the rest of the planet. This has been leading to a dramatically decrease of snow coverage and sea ice thickness in recent years and several studies have suggested that a similar trend is expected in the upcoming years. Large uncertainties in predicting the Arctic climate arise from our lack of understanding the role clouds play in sea ice / atmosphere interaction. During summer the shortwave radiation dominates and clouds have a net cooling effect at the surface. The strength of this cooling critically depends on cloud phase, composition and height. Clouds interactions with aerosols, and its sensitivity to surface properties further complicates their role in the Arctic system. Scattering between the surface and cloud layers amplifies the cloud shortwave contribution, especially over a highly reflective surface such as snow or ice. Therefore, to comprehend how the Arctic's surface is significantly modulated by solar radiation is necessary to more clearly understand the cloud-induced spatio-temporal variability at process relevant scales. Irradiance variability may also have an effect on the biological productivity of various plankton species below the ice. The present study provides an overview of spatio-temporal variability at spatial scales ranging from several decameters to 1 kilometer of the global transmittance derived from 15 pyranometer stations installed at an ice floe station (June 4-16 2017) during the POLARSTERN expedition PS106/1. Specific irradiance statistics under clear sky, broken clouds and overcast conditions will be described considering the combination of a Cloud Radar Mira 35 and a Polly Raman polarization Lidar. Ultimately, radiative closure studies will be performed to quantify our abilities to reproduce realistic cloud solar radiative forcing under Arctic conditions. Acknowledgements. This research is funded by Deutsche Forschunsgemeinschaft (DFG) and involves the active participation of Leibniz Institut für Troposphärenforschung (TROPOS), Universität Leipzig Institut für Meteorologie (LIM), Universitäat Bremen, Universität zu Köln and Alfred-Wegener-Institut, Helmholtz Zentrum für Polar - und Meeresforschung (AWI).

Ice crystal number concentration measured at mountain-top research stations - What do we measure?

NASA Astrophysics Data System (ADS)

Beck, A.; Henneberger, J.; Fugal, J. P.; David, R.; Larcher, L.; Lohmann, U.

2017-12-01

To assess the impact of surface processes (e.g. blowing snow and hoar frost) on the ice crystal number concentrations (ICNCs) measured at mountain-top research stations, vertical profiles of ICNCs were observed up to a height of 10 m at the Sonnblick Observatory (SBO) in the Hohen Tauern Region, Austria. Independent of the presence of a cloud, the observed ICNCs decrease with height. This suggests a strong impact of surface processes on ICNCs measured at mountain-top research stations. Consequently, the measured ICNCs are not representative of the cloud, which limits the relevance of ground-based measurements for atmospheric studies. When the SBO was cloud free, the observed ICNCs reached several hundreds per liter near the surface and gradually decreased by more than two orders of magnitudes within the observed height interval of 10 m. The observed ice crystals had predominantly irregular habits, which is expected from surface processes. During in-cloud conditions, the ICNCs decreased between a factor of five and ten, if the ICNC at the surface was larger than 100 l-1. For one case study, the ICNC for regular and irregular ice crystals showed a similar relative decrease with height, which is not expected from surface processes. Therefore, we propose two near-surface processes that potentially enrich ICNCs near the surface and explain these findings: Either sedimenting ice crystals are captured in a turbulent layer above the surface or the ICNC is enhanced in a convergence zone, as the cloud is forced over a mountain. These two processes would also have an impact on ICNCs measured at mountain-top stations if the surrounding surface is not snow covered. Thus, ground-based measured ICNCs are uncharacteristic of the cloud properties aloft.

Glacial Inception in north-east Canada: The Role of Topography and Clouds

NASA Astrophysics Data System (ADS)

Birch, Leah; Tziperman, Eli; Cronin, Timothy

2016-04-01

Over the past 0.8 million years, ice ages have dominated Earth's climate on a 100 thousand year cycle. Interglacials were brief, sometimes lasting only a few thousand years, leading to the next inception. Currently, state-of-the-art global climate models (GCMs) are incapable of simulating the transition of Earth's climate from interglacial to glaciated. We hypothesize that this failure may be related to their coarse spatial resolution, which does not allow resolving the topography of inception areas, and their parameterized representation of clouds and atmospheric convection. To better understand the small scale topographic and cloud processes mis-represented by GCMs, we run the Weather Research and Forecasting model (WRF), which is a regional, cloud-resolving atmospheric model capable of a realistic simulation of the regional mountain climate and therefore of surface ice and snow mass balance. We focus our study on the mountain glaciers of Canada's Baffin Island, where geologic evidence indicates the last inception occurred at 115kya. We examine the sensitivity of mountain glaciers to Milankovitch Forcing, topography, and meteorology, while observing impacts of a cloud resolving model. We first verify WRF's ability to simulate present day climate in the region surrounding the Penny Ice Cap, and then investigate how a GCM-like biased representation of topography affects sensitivity of this mountain glacier to Milankovitch forcing. Our results show the possibility of ice cap growth on an initially snow-free landscape with realistic topography and insolation values from the last glacial inception. Whereas, smoothed topography as seen in GCMs has a negative surface mass balance, even with the relevant orbital parameter configuration. We also explore the surface mass balance feedbacks from an initially ice-covered Baffin Island and discuss the role of clouds and convection.

Snow cover detection algorithm using dynamic time warping method and reflectances of MODIS solar spectrum channels

NASA Astrophysics Data System (ADS)

Lee, Kyeong-sang; Choi, Sungwon; Seo, Minji; Lee, Chang suk; Seong, Noh-hun; Han, Kyung-Soo

2016-10-01

Snow cover is biggest single component of cryosphere. The Snow is covering the ground in the Northern Hemisphere approximately 50% in winter season and is one of climate factors that affects Earth's energy budget because it has higher reflectance than other land types. Also, snow cover has an important role about hydrological modeling and water resource management. For this reason, accurate detection of snow cover acts as an essential element for regional water resource management. Snow cover detection using satellite-based data have some advantages such as obtaining wide spatial range data and time-series observations periodically. In the case of snow cover detection using satellite data, the discrimination of snow and cloud is very important. Typically, Misclassified cloud and snow pixel can lead directly to error factor for retrieval of satellite-based surface products. However, classification of snow and cloud is difficult because cloud and snow have similar optical characteristics and are composed of water or ice. But cloud and snow has different reflectance in 1.5 1.7 μm wavelength because cloud has lower grain size and moisture content than snow. So, cloud and snow shows difference reflectance patterns change according to wavelength. Therefore, in this study, we perform algorithm for classifying snow cover and cloud with satellite-based data using Dynamic Time Warping (DTW) method which is one of commonly used pattern analysis such as speech and fingerprint recognitions and reflectance spectral library of snow and cloud. Reflectance spectral library is constructed in advance using MOD21km (MODIS Level1 swath 1km) data that their reflectance is six channels including 3 (0.466μm), 4 (0.554μm), 1 (0.647μm), 2 (0.857μm), 26 (1.382μm) and 6 (1.629μm). We validate our result using MODIS RGB image and MOD10 L2 swath (MODIS swath snow cover product). And we use PA (Producer's Accuracy), UA (User's Accuracy) and CI (Comparison Index) as validation criteria. The result of our study detect as snow cover in the several regions which are did not detected as snow in MOD10 L2 and detected as snow cover in MODIS RGB image. The result of our study can improve accuracy of other surface product such as land surface reflectance and land surface emissivity. Also it can use input data of hydrological modeling.

Benefits of a 4th Ice Class in the Simulated Radar Reflectivities of Convective Systems Using a Bulk Microphysics Scheme

NASA Technical Reports Server (NTRS)

Lang, Stephen E.; Tao, Wei-Kuo; Chern, Jiun-Dar; Wu, Di; Li, Xiaowen

2015-01-01

Numerous cloud microphysical schemes designed for cloud and mesoscale models are currently in use, ranging from simple bulk to multi-moment, multi-class to explicit bin schemes. This study details the benefits of adding a 4th ice class (hail) to an already improved 3-class ice bulk microphysics scheme developed for the Goddard Cumulus Ensemble model based on Rutledge and Hobbs (1983,1984). Besides the addition and modification of several hail processes from Lin et al. (1983), further modifications were made to the 3-ice processes, including allowing greater ice super saturation and mitigating spurious evaporationsublimation in the saturation adjustment scheme, allowing graupelhail to become snow via vapor growth and hail to become graupel via riming, and the inclusion of a rain evaporation correction and vapor diffusivity factor. The improved 3-ice snowgraupel size-mapping schemes were adjusted to be more stable at higher mixing rations and to increase the aggregation effect for snow. A snow density mapping was also added. The new scheme was applied to an intense continental squall line and a weaker, loosely-organized continental case using three different hail intercepts. Peak simulated reflectivities agree well with radar for both the intense and weaker case and were better than earlier 3-ice versions when using a moderate and large intercept for hail, respectively. Simulated reflectivity distributions versus height were also improved versus radar in both cases compared to earlier 3-ice versions. The bin-based rain evaporation correction affected the squall line case more but did not change the overall agreement in reflectivity distributions.

The application of satellite data in the determination of ocean temperatures and cloud characteristics and statistics

NASA Technical Reports Server (NTRS)

Curran, R. J.; Salomonson, V. V.; Shenk, W. (Principal Investigator)

1975-01-01

The author has identified the following significant results. The major shortcoming of the data was the loss of the infrared radiances from the S191 spectrometer. The cloud thermodynamic phase determination procedure was derived and tested with the data collected by the S192 multispectral scanner. Results of the test indicate a large fraction of the data could be classified thermodynamically. An added bonus was the inclusion of snow in the classification approach. The conclusion to be drawn from this portion of the effort is that in most cases considered ice clouds, liquid water droplet clouds, and snow fields can be spectroscopically separated to a high degree of accuracy.

10-Year Observations of Cloud and Surface Longwave Radiation at Ny-Ålesund, Svalbard

NASA Astrophysics Data System (ADS)

Yeo, H.; Kim, S. W.; Kim, B. M.; Kim, J. H.; Shiobara, M.; Choi, T. J.; Son, S. W.; Kim, M. H.; Jeong, J. H.; Kim, S. J.

2015-12-01

Arctic clouds play a key role in surface radiation budget and may influence sea ice and snow melting. In this study, 10-year (2004-2013) observations of cloud from Micro-Pulse Lidar (MPL) and surface longwave (LW) radiation at Ny-Ålesund, Svalbard are analyzed to investigate cloud radiative effect. The cloud fraction (CF) derived from MPL shows distinct monthly variation, having higher CF (0.90) in summer and lower CF (0.79) in winter. Downward longwave radiation (DLW) during wintertime (Nov., Dec., Jan., and Feb.) decreases as cloud base height (CBH) increases. The DLW for CBH < 1km (264.7±35.4 W m-2) is approximately 1.46 times larger than that for cloud-free (181.8±25.8 W m-2) conditions. The temperature difference (ΔT) and DLW difference (ΔDLW), which are calculated as the difference of monthly mean temperature and DLW between all-sky and cloud-free conditions, are positively correlated (R2 = 0.83). This implies that an increase of DLW may influence surface warming, which can result in snow and sea ice melting. However, dramatic changes in surface temperature, cloud and DLW are observed with a time scale of a few days. The averaged surface temperature on the presence of low-level clouds (CBH < 2km) and under cloud-free conditions are estimated to be -6.9±6.1°C and -14.5±5.7°C, respectively. The duration of low-level clouds, showing relatively high DLW and high surface temperature, is about 2.5 days. This suggests that DLW induced by low-level clouds may not have a critical effect on surface temperature rising and sea ice melting.

Long-range-transported bioaerosols captured in snow cover on Mount Tateyama, Japan: impacts of Asian-dust events on airborne bacterial dynamics relating to ice-nucleation activities

NASA Astrophysics Data System (ADS)

Maki, Teruya; Furumoto, Shogo; Asahi, Yuya; Lee, Kevin C.; Watanabe, Koichi; Aoki, Kazuma; Murakami, Masataka; Tajiri, Takuya; Hasegawa, Hiroshi; Mashio, Asami; Iwasaka, Yasunobu

2018-06-01

The westerly wind travelling at high altitudes over eastern Asia transports aerosols from the Asian deserts and urban areas to downwind areas such as Japan. These long-range-transported aerosols include not only mineral particles but also microbial particles (bioaerosols), that impact the ice-cloud formation processes as ice nuclei. However, the detailed relations of airborne bacterial dynamics to ice nucleation in high-elevation aerosols have not been investigated. Here, we used the aerosol particles captured in the snow cover at altitudes of 2450 m on Mt Tateyama to investigate sequential changes in the ice-nucleation activities and bacterial communities in aerosols and elucidate the relationships between the two processes. After stratification of the snow layers formed on the walls of a snow pit on Mt Tateyama, snow samples, including aerosol particles, were collected from 70 layers at the lower (winter accumulation) and upper (spring accumulation) parts of the snow wall. The aerosols recorded in the lower parts mainly came from Siberia (Russia), northern Asia and the Sea of Japan, whereas those in the upper parts showed an increase in Asian dust particles originating from the desert regions and industrial coasts of Asia. The snow samples exhibited high levels of ice nucleation corresponding to the increase in Asian dust particles. Amplicon sequencing analysis using 16S rRNA genes revealed that the bacterial communities in the snow samples predominately included plant associated and marine bacteria (phyla Proteobacteria) during winter, whereas during spring, when dust events arrived frequently, the majority were terrestrial bacteria of phyla Actinobacteria and Firmicutes. The relative abundances of Firmicutes (Bacilli) showed a significant positive relationship with the ice nucleation in snow samples. Presumably, Asian dust events change the airborne bacterial communities over Mt Tateyama and carry terrestrial bacterial populations, which possibly induce ice-nucleation activities, thereby indirectly impacting climate change.

Mapping Snow Grain Size over Greenland from MODIS

NASA Technical Reports Server (NTRS)

Lyapustin, Alexei; Tedesco, Marco; Wang, Yujie; Kokhanovsky, Alexander

2008-01-01

This paper presents a new automatic algorithm to derive optical snow grain size (SGS) at 1 km resolution using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. Differently from previous approaches, snow grains are not assumed to be spherical but a fractal approach is used to account for their irregular shape. The retrieval is conceptually based on an analytical asymptotic radiative transfer model which predicts spectral bidirectional snow reflectance as a function of the grain size and ice absorption. The analytical form of solution leads to an explicit and fast retrieval algorithm. The time series analysis of derived SGS shows a good sensitivity to snow metamorphism, including melting and snow precipitation events. Preprocessing is performed by a Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, which includes gridding MODIS data to 1 km resolution, water vapor retrieval, cloud masking and an atmospheric correction. MAIAC cloud mask (CM) is a new algorithm based on a time series of gridded MODIS measurements and an image-based rather than pixel-based processing. Extensive processing of MODIS TERRA data over Greenland shows a robust performance of CM algorithm in discrimination of clouds over bright snow and ice. As part of the validation analysis, SGS derived from MODIS over selected sites in 2004 was compared to the microwave brightness temperature measurements of SSM\\I radiometer, which is sensitive to the amount of liquid water in the snowpack. The comparison showed a good qualitative agreement, with both datasets detecting two main periods of snowmelt. Additionally, MODIS SGS was compared with predictions of the snow model CROCUS driven by measurements of the automatic whether stations of the Greenland Climate Network. We found that CROCUS grain size is on average a factor of two larger than MODIS-derived SGS. Overall, the agreement between CROCUS and MODIS results was satisfactory, in particular before and during the first melting period in mid-June. Following detailed time series analysis of SGS for four permanent sites, the paper presents SGS maps over the Greenland ice sheet for the March-September period of 2004.

Modis Collection 6 Shortwave-Derived Cloud Phase Classification Algorithm and Comparisons with CALIOP

NASA Technical Reports Server (NTRS)

Marchant, Benjamin; Platnick, Steven; Meyer, Kerry; Arnold, George Thomas; Riedi, Jerome

2016-01-01

Cloud thermodynamic phase (e.g., ice, liquid) classification is an important first step for cloud retrievals from passive sensors such as MODIS (Moderate-Resolution Imaging Spectroradiometer). Because ice and liquid phase clouds have very different scattering and absorbing properties, an incorrect cloud phase decision can lead to substantial errors in the cloud optical and microphysical property products such as cloud optical thickness or effective particle radius. Furthermore, it is well established that ice and liquid clouds have different impacts on the Earth's energy budget and hydrological cycle, thus accurately monitoring the spatial and temporal distribution of these clouds is of continued importance. For MODIS Collection 6 (C6), the shortwave-derived cloud thermodynamic phase algorithm used by the optical and microphysical property retrievals has been completely rewritten to improve the phase discrimination skill for a variety of cloudy scenes (e.g., thin/thick clouds, over ocean/land/desert/snow/ice surface, etc). To evaluate the performance of the C6 cloud phase algorithm, extensive granule-level and global comparisons have been conducted against the heritage C5 algorithm and CALIOP. A wholesale improvement is seen for C6 compared to C5.

Ten Years of Cloud Optical and Microphysical Retrievals from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, Michael D.; Wind, Galina; Hubanks, Paul; Arnold, G. Thomas; Amarasinghe, Nandana

2010-01-01

The MODIS cloud optical properties algorithm (MOD06/MYD06 for Terra and Aqua MODIS, respectively) has undergone extensive improvements and enhancements since the launch of Terra. These changes have included: improvements in the cloud thermodynamic phase algorithm; substantial changes in the ice cloud light scattering look up tables (LUTs); a clear-sky restoral algorithm for flagging heavy aerosol and sunglint; greatly improved spectral surface albedo maps, including the spectral albedo of snow by ecosystem; inclusion of pixel-level uncertainty estimates for cloud optical thickness, effective radius, and water path derived for three error sources that includes the sensitivity of the retrievals to solar and viewing geometries. To improve overall retrieval quality, we have also implemented cloud edge removal and partly cloudy detection (using MOD35 cloud mask 250m tests), added a supplementary cloud optical thickness and effective radius algorithm over snow and sea ice surfaces and over the ocean, which enables comparison with the "standard" 2.1 11m effective radius retrieval, and added a multi-layer cloud detection algorithm. We will discuss the status of the MOD06 algorithm and show examples of pixellevel (Level-2) cloud retrievals for selected data granules, as well as gridded (Level-3) statistics, notably monthly means and histograms (lD and 2D, with the latter giving correlations between cloud optical thickness and effective radius, and other cloud product pairs).

Process-model Simulations of Cloud Albedo Enhancement by Aerosols in the Arctic

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kravitz, Benjamin S.; Wang, Hailong; Rasch, Philip J.

2014-11-17

A cloud-resolving model is used to simulate the effectiveness of Arctic marine cloud brightening via injection of cloud condensation nuclei (CCN). An updated cloud microphysical scheme is employed, with prognostic CCN and cloud particle numbers in both liquid and mixed-phase marine low clouds. Injection of CCN into the marine boundary layer can delay the collapse of the boundary layer and increase low-cloud albedo. Because nearly all of the albedo effects are in the liquid phase due to the removal of ice water by snowfall when ice processes are involved, albedo increases are stronger for pure liquid clouds than mixed-phase clouds.more » Liquid precipitation can be suppressed by CCN injection, whereas ice precipitation (snow) is affected less; thus the effectiveness of brightening mixed-phase clouds is lower than for liquid-only clouds. CCN injection into a clean regime results in a greater albedo increase than injection into a polluted regime, consistent with current knowledge about aerosol-cloud interactions. Unlike previous studies investigating warm clouds, dynamical changes in circulation due to precipitation changes are small.« less

The Rossby Centre Regional Atmospheric Climate Model part II: application to the Arctic climate.

PubMed

Jones, Colin G; Wyser, Klaus; Ullerstig, Anders; Willén, Ulrika

2004-06-01

The Rossby Centre regional climate model (RCA2) has been integrated over the Arctic Ocean as part of the international ARCMIP project. Results have been compared to observations derived from the SHEBA data set. The standard RCA2 model overpredicts cloud cover and downwelling longwave radiation, during the Arctic winter. This error was improved by introducing a new cloud parameterization, which significantly improves the annual cycle of cloud cover. Compensating biases between clear sky downwelling longwave radiation and longwave radiation emitted from cloud base were identified. Modifications have been introduced to the model radiation scheme that more accurately treat solar radiation interaction with ice crystals. This leads to a more realistic representation of cloud-solar radiation interaction. The clear sky portion of the model radiation code transmits too much solar radiation through the atmosphere, producing a positive bias at the top of the frequent boundary layer clouds. A realistic treatment of the temporally evolving albedo, of both sea-ice and snow, appears crucial for an accurate simulation of the net surface energy budget. Likewise, inclusion of a prognostic snow-surface temperature seems necessary, to accurately simulate near-surface thermodynamic processes in the Arctic.

Improvements in AVHRR Daytime Cloud Detection Over the ARM NSA Site

NASA Technical Reports Server (NTRS)

Chakrapani, V.; Spangenberg, D. A.; Doelling, D. R.; Minnis, P.; Trepte, Q. Z.; Arduini, R. F.

2001-01-01

Clouds play an important role in the radiation budget over Arctic and Antarctic. Because of limited surface observing capabilities, it is necessary to detect clouds over large areas using satellite imagery. At low and mid-latitudes, satellite-observed visible (VIS; 0.65 micrometers) and infrared (IR; 11 micrometers) radiance data are used to derive cloud fraction, temperature, and optical depth. However, the extreme variability in the VIS surface albedo makes the detection of clouds from satellite a difficult process in polar regions. The IR data often show that the surface is nearly the same temperature or even colder than clouds, further complicating cloud detection. Also, the boundary layer can have large areas of haze, thin fog, or diamond dust that are not seen in standard satellite imagery. Other spectral radiances measured by satellite imagers provide additional information that can be used to more accurately discriminate clouds from snow and ice. Most techniques currently use a fixed reflectance or temperature threshold to decide between clouds and clear snow. Using a subjective approach, Minnis et al. (2001) found that the clear snow radiance signatures vary as a function of viewing and illumination conditions as well as snow condition. To routinely process satellite imagery over polar regions with an automated algorithm, it is necessary to account for this angular variability and the change in the background reflectance as snow melts, vegetation grows over land, and melt ponds form on pack ice. This paper documents the initial satellite-based cloud product over the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) site at Barrow for use by the modeling community. Cloud amount and height are determined subjectively using an adaptation of the methodology of Minnis et al. (2001) and the radiation fields arc determined following the methods of Doelling et al. (2001) as applied to data taken during the Surface Heat and Energy Budget of the Arctic (SHEBA). The procedures and data produced in this empirically based analysis will also facilitate the development of the automated algorithm for future processing of satellite data over the ARM NSA domain. Results are presented for May, June, and July 1998. ARM surface data are use to partially validate the results taken directly over the ARM site.

Time-variability of Polar Winter Snow Clouds on Mars

NASA Astrophysics Data System (ADS)

Hayne, P. O.; Kass, D. M.; Kleinboehl, A.; Schofield, J. T.; McCleese, D. J.

2015-12-01

Carbon dioxide snow clouds are known to occur in the polar regions on Mars during the long polar night. Earlier studies have shown that a substantial fraction (up to ~20%) of the seasonal ice caps of Mars can be deposited as CO2 snowfall. The presence of optically thick clouds can also strongly influence the polar energy balance, by scattering thermal radiation emitted by the surface and lower atmosphere. Furthermore, snow deposition is likely to affect the surface morphology and subsequent evolution of the seasonal caps. Therefore, both the spatial distribution and time variability of polar snow clouds are important for understanding their influence on the Martian CO2cycle and climate. However, previous investigations have suffered from relatively coarse time resolution (typically days), coarse or incomplete spatial coverage, or both. Here we report results of a dedicated campaign by the Mars Climate Sounder (MCS) onboard the Mars Reconnaissance Orbiter, to observe polar CO2 clouds with an unprecedented time-resolution within the same spatial region. By scanning the MCS field of view, we acquired observations directly over the north pole for every ~2hr orbit over the course of several days. This was repeated during two separate periods in northern winter. The 2 hr sampling frequency enables the detailed study of cloud evolution. These observations were also compared to a cloud-free, control region just off the pole, which was sampled in the same way. Results from this experiment show that the north polar CO2 clouds are dynamic, and appear to follow a consistent pattern: Beginning with a relatively clear atmosphere, the cloud rapidly grows to ~25 - 30 km altitude in < 2 hr. Then, the altitude of the cloud tops diminishes slowly, reaching near the surface after ~6 - 10 hr. We interpret this slow decay as the precipitation of snow particles, which constrains their size to be ~10 - 100 μm. Also pervasive in this season are water ice clouds, which may provide condensation nuclei for the CO2. The interplay between these two atmospheric aerosol species on short timescales is a potentially fruitful area of future research, enabled by these unique observations. Part of this work was performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

Cloud Statistics and Discrimination in the Polar Regions

NASA Astrophysics Data System (ADS)

Chan, M.; Comiso, J. C.

2012-12-01

Despite their important role in the climate system, cloud cover and their statistics are poorly known, especially in the polar regions, where clouds are difficult to discriminate from snow covered surfaces. The advent of the A-train, which included Aqua/MODIS, CALIPSO/CALIOP and CloudSat/CPR sensors has provided an opportunity to improve our ability to accurately characterize the cloud cover. MODIS provides global coverage at a relatively good temporal and spatial resolution while CALIOP and CPR provide limited nadir sampling but accurate characterization of the vertical structure and phase of the cloud cover. Over the polar regions, cloud detection from a passive sensors like MODIS is challenging because of the presence of cold and highly reflective surfaces such as snow, sea-ice, glaciers, and ice-sheet, which have surface signatures similar to those of clouds. On the other hand, active sensors such as CALIOP and CPR are not only very sensitive to the presence of clouds but can also provide information about its microphysical characteristics. However, these nadir-looking sensors have sparse spatial coverage and their global data can have data spatial gaps of up to 100 km. We developed a polar cloud detection system for MODIS that is trained using collocated data from CALIOP and CPR. In particular, we employ a machine learning system that reads the radiative profile observed by MODIS and determine whether the field of view is cloudy or clear. Results have shown that the improved cloud detection scheme performs better than typical cloud mask algorithms using a validation data set not used for training. A one-year data set was generated and results indicate that daytime cloud detection accuracies improved from 80.1% to 92.6% (over sea-ice) and 71.2% to 87.4% (over ice-sheet) with CALIOP data used as the baseline. Significant improvements are also observed during nighttime, where cloud detection accuracies increase by 19.8% (over sea-ice) and 11.6% (over ice-sheet). The immediate impact of the new algorithm is that it can minimize large biases of MODIS-derived cloud amount over the Polar Regions and thus a more realistic and high quality global cloud statistics. In particular, our results show that cloud fraction in the Arctic is typically 81.2 % during daytime and 84.0% during nighttime. This is significantly higher than the 71.8% and 58.5%, respectively, derived from standard MODIS cloud product.

Measured Black Carbon Deposition on the Sierra Nevada Snow Pack and Implication for Snow Pack Retreat

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hadley, O.L.; Corrigan, C.E.; Kirchstetter, T.W.

2010-01-12

Modeling studies show that the darkening of snow and ice by black carbon deposition is a major factor for the rapid disappearance of arctic sea ice, mountain glaciers and snow packs. This study provides one of the first direct measurements for the efficient removal of black carbon from the atmosphere by snow and its subsequent deposition to the snow packs of California. The early melting of the snow packs in the Sierras is one of the contributing factors to the severe water problems in California. BC concentrations in falling snow were measured at two mountain locations and in rain atmore » a coastal site. All three stations reveal large BC concentrations in precipitation, ranging from 1.7 ng/g to 12.9 ng/g. The BC concentrations in the air after the snow fall were negligible suggesting an extremely efficient removal of BC by snow. The data suggest that below cloud scavenging, rather than ice nuclei, was the dominant source of BC in the snow. A five-year comparison of BC, dust, and total fine aerosol mass concentrations at multiple sites reveals that the measurements made at the sampling sites were representative of large scale deposition in the Sierra Nevada. The relative concentration of iron and calcium in the mountain aerosol indicates that one-quarter to one-third of the BC may have been transported from Asia.« less

A statistical retrieval of cloud parameters for the millimeter wave Ice Cloud Imager on board MetOp-SG

NASA Astrophysics Data System (ADS)

Prigent, Catherine; Wang, Die; Aires, Filipe; Jimenez, Carlos

2017-04-01

The meteorological observations from satellites in the microwave domain are currently limited to below 190 GHz. However, the next generation of European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Polar System-Second Generation-EPS-SG will carry an instrument, the Ice Cloud Imager (ICI), with frequencies up to 664 GHz, to improve the characterization of the cloud frozen phase. In this paper, a statistical retrieval of cloud parameters for ICI is developed, trained on a synthetic database derived from the coupling of a mesoscale cloud model and radiative transfer calculations. The hydrometeor profiles simulated with the Weather Research and Forecasting model (WRF) for twelve diverse European mid-latitude situations are used to simulate the brightness temperatures with the Atmospheric Radiative Transfer Simulator (ARTS) to prepare the retrieval database. The WRF+ARTS simulations have been compared to the Special Sensor Microwave Imager/Sounder (SSMIS) observations up to 190 GHz: this successful evaluation gives us confidence in the simulations at the ICI channels from 183 to 664 GHz. Statistical analyses have been performed on this simulated retrieval database, showing that it is not only physically realistic but also statistically satisfactory for retrieval purposes. A first Neural Network (NN) classifier is used to detect the cloud presence. A second NN is developed to retrieve the liquid and ice integrated cloud quantities over sea and land separately. The detection and retrieval of the hydrometeor quantities (i.e., ice, snow, graupel, rain, and liquid cloud) are performed with ICI-only, and with ICI combined with observations from the MicroWave Imager (MWI, with frequencies from 19 to 190 GHz, also on board MetOp-SG). The ICI channels have been optimized for the detection and quantification of the cloud frozen phases: adding the MWI channels improves the performance of the vertically integrated hydrometeor contents, especially for the cloud liquid phases. The relative error for the retrieved integrated frozen water content (FWP, i.e., ice+snow+graupel) is below 40% for 0.1kg/m2 < FWP < 0.5kg/m2 and below 20% for FWP > 0.5 kg/m2.

Study and simulation results for video landmark acquisition and tracking technology (Vilat-2)

NASA Technical Reports Server (NTRS)

Lowrie, J. W.; Tietz, J. C.; Thomas, H. M.; Gremban, K. D.; Hughes, C.; Chang, C. Y.

1983-01-01

The results of several investigations and hardware developments which supported new technology for Earth feature recognition and classification are described. Data analysis techniques and procedures were developed for processing the Feature Identification and Location Experiment (FILE) data. This experiment was flown in November 1981, on the second Shuttle flight and a second instrument, designed for aircraft flights, was flown over the United States in 1981. Ground tests were performed to provide the basis for designing a more advanced version (four spectral bands) of the FILE which would be capable of classifying clouds and snow (and possibly ice) as distinct features, in addition to the features classified in the Shuttle experiment (two spectral bands). The Shuttle instrument classifies water, bare land, vegetation, and clouds/snow/ice (grouped).

Arctic Sea Salt Aerosol from Blowing Snow and Sea Ice Surfaces - a Missing Natural Source in Winter

NASA Astrophysics Data System (ADS)

Frey, M. M.; Norris, S. J.; Brooks, I. M.; Nishimura, K.; Jones, A. E.

2015-12-01

Atmospheric particles in the polar regions consist mostly of sea salt aerosol (SSA). SSA plays an important role in regional climate change through influencing the surface energy balance either directly or indirectly via cloud formation. SSA irradiated by sunlight also releases very reactive halogen radicals, which control concentrations of ozone, a pollutant and greenhouse gas. However, models under-predict SSA concentrations in the Arctic during winter pointing to a missing source. It has been recently suggested that salty blowing snow above sea ice, which is evaporating, to be that source as it may produce more SSA than equivalent areas of open ocean. Participation in the 'Norwegian Young Sea Ice Cruise (N-ICE 2015)' on board the research vessel `Lance' allowed to test this hypothesis in the Arctic sea ice zone during winter. Measurements were carried out from the ship frozen into the pack ice North of 80º N during February to March 2015. Observations at ground level (0.1-2 m) and from the ship's crows nest (30 m) included number concentrations and size spectra of SSA (diameter range 0.3-10 μm) as well as snow particles (diameter range 50-500 μm). During and after blowing snow events significant SSA production was observed. In the aerosol and snow phase sulfate is fractionated with respect to sea water, which confirms sea ice surfaces and salty snow, and not the open ocean, to be the dominant source of airborne SSA. Aerosol shows depletion in bromide with respect to sea water, especially after sunrise, indicating photochemically driven release of bromine. We discuss the SSA source strength from blowing snow in light of environmental conditions (wind speed, atmospheric turbulence, temperature and snow salinity) and recommend improved model parameterisations to estimate regional aerosol production. N-ICE 2015 results are then compared to a similar study carried out previously in the Weddell Sea during the Antarctic winter.

Continuity of MODIS and VIIRS Snow-Cover Maps during Snowmelt in the Catskill Mountains in New York

NASA Astrophysics Data System (ADS)

Hall, D. K.; Riggs, G. A., Jr.; Roman, M. O.; DiGirolamo, N. E.

2015-12-01

We investigate the local and regional differences and possible biases between the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible-Infrared Imager Radiometer Suite (VIIRS) snow-cover maps in the winter of 2012 during snowmelt conditions in the Catskill Mountains in New York using a time series of cloud-gap filled daily snow-cover maps. The MODIS Terra instrument has been providing daily global snow-cover maps since February 2000 (Riggs and Hall, 2015). Using the VIIRS instrument, launched in 2011, NASA snow products are being developed based on the heritage MODIS snow-mapping algorithms, and will soon be available to the science community. Continuity of the standard NASA MODIS and VIIRS snow-cover maps is essential to enable environmental-data records (EDR) to be developed for analysis of snow-cover trends using a consistent data record. For this work, we compare daily MODIS and VIIRS snow-cover maps of the Catskill Mountains from 29 February through 14 March 2012. The entire region was snow covered on 29 February and by 14 March the snow had melted; we therefore have a daily time series available to compare normalized difference snow index (NDSI), as an indicator of snow-cover fraction. The MODIS and VIIRS snow-cover maps have different spatial resolutions (500 m for MODIS and 375 m for VIIRS) and different nominal overpass times (10:30 AM for MODIS Terra and 2:30 PM for VIIRS) as well as different cloud masks. The results of this work will provide a quantitative assessment of the continuity of the snow-cover data records for use in development of an EDR of snow cover.http://modis-snow-ice.gsfc.nasa.gov/Riggs, G.A. and D.K. Hall, 2015: MODIS Snow Products User Guide to Collection 6, http://modis-snow-ice.gsfc.nasa.gov/?c=userguides

Modelling the climate and surface mass balance of polar ice sheets using RACMO2 - Part 1: Greenland (1958-2016)

NASA Astrophysics Data System (ADS)

Noël, Brice; van de Berg, Willem Jan; Melchior van Wessem, J.; van Meijgaard, Erik; van As, Dirk; Lenaerts, Jan T. M.; Lhermitte, Stef; Kuipers Munneke, Peter; Smeets, C. J. P. Paul; van Ulft, Lambertus H.; van de Wal, Roderik S. W.; van den Broeke, Michiel R.

2018-03-01

We evaluate modelled Greenland ice sheet (GrIS) near-surface climate, surface energy balance (SEB) and surface mass balance (SMB) from the updated regional climate model RACMO2 (1958-2016). The new model version, referred to as RACMO2.3p2, incorporates updated glacier outlines, topography and ice albedo fields. Parameters in the cloud scheme governing the conversion of cloud condensate into precipitation have been tuned to correct inland snowfall underestimation: snow properties are modified to reduce drifting snow and melt production in the ice sheet percolation zone. The ice albedo prescribed in the updated model is lower at the ice sheet margins, increasing ice melt locally. RACMO2.3p2 shows good agreement compared to in situ meteorological data and point SEB/SMB measurements, and better resolves the spatial patterns and temporal variability of SMB compared with the previous model version, notably in the north-east, south-east and along the K-transect in south-western Greenland. This new model version provides updated, high-resolution gridded fields of the GrIS present-day climate and SMB, and will be used for projections of the GrIS climate and SMB in response to a future climate scenario in a forthcoming study.

A Bulk Microphysics Parameterization with Multiple Ice Precipitation Categories.

NASA Astrophysics Data System (ADS)

Straka, Jerry M.; Mansell, Edward R.

2005-04-01

A single-moment bulk microphysics scheme with multiple ice precipitation categories is described. It has 2 liquid hydrometeor categories (cloud droplets and rain) and 10 ice categories that are characterized by habit, size, and density—two ice crystal habits (column and plate), rimed cloud ice, snow (ice crystal aggregates), three categories of graupel with different densities and intercepts, frozen drops, small hail, and large hail. The concept of riming history is implemented for conversions among the graupel and frozen drops categories. The multiple precipitation ice categories allow a range of particle densities and fall velocities for simulating a variety of convective storms with minimal parameter tuning. The scheme is applied to two cases—an idealized continental multicell storm that demonstrates the ice precipitation process, and a small Florida maritime storm in which the warm rain process is important.

Satellite Estimation of Spectral Surface UV Irradiance. 2; Effect of Horizontally Homogeneous Clouds

NASA Technical Reports Server (NTRS)

Krothov, N.; Herman, J. R.; Bhartia, P. K.; Ahmad, Z.a; Fioletov, V.

1998-01-01

The local variability of UV irradiance at the Earth's surface is mostly caused by clouds in addition to the seasonal variability. Parametric representations of radiative transfer RT calculations are presented for the convenient solution of the transmission T of ultraviolet radiation through plane parallel clouds over a surface with reflectivity R(sub s). The calculations are intended for use with the Total Ozone Mapping Spectrometer (TOMS) measured radiances to obtain the calculated Lambert equivalent scene reflectivity R for scenes with and without clouds. The purpose is to extend the theoretical analysis of the estimation of UV irradiance from satellite data for a cloudy atmosphere. Results are presented for a range of cloud optical depths and solar zenith angles for the cases of clouds over a low reflectivity surface R(sub s) less than 0.1, over a snow or ice surface R(sub s) greater than 0.3, and for transmission through a non-conservative scattering cloud with single scattering albedo omega(sub 0) = 0.999. The key finding for conservative scattering is that the cloud-transmission function C(sub T), the ratio of cloudy-to clear-sky transmission, is roughly C(sub T) = 1 - R(sub c) with an error of less than 20% for nearly overhead sun and snow-free surfaces. For TOMS estimates of UV irradiance in the presence of both snow and clouds, independent information about snow albedo is needed for conservative cloud scattering. For non-conservative scattering with R(sub s) greater than 0.5 (snow) the satellite measured scene reflectance cannot be used to estimate surface irradiance. The cloud transmission function has been applied to the calculation of UV irradiance at the Earth's surface and compared with ground-based measurements.

Direct comparisons of ice cloud macro- and microphysical properties simulated by the Community Atmosphere Model version 5 with HIPPO aircraft observations

NASA Astrophysics Data System (ADS)

Wu, Chenglai; Liu, Xiaohong; Diao, Minghui; Zhang, Kai; Gettelman, Andrew; Lu, Zheng; Penner, Joyce E.; Lin, Zhaohui

2017-04-01

In this study we evaluate cloud properties simulated by the Community Atmosphere Model version 5 (CAM5) using in situ measurements from the HIAPER Pole-to-Pole Observations (HIPPO) campaign for the period of 2009 to 2011. The modeled wind and temperature are nudged towards reanalysis. Model results collocated with HIPPO flight tracks are directly compared with the observations, and model sensitivities to the representations of ice nucleation and growth are also examined. Generally, CAM5 is able to capture specific cloud systems in terms of vertical configuration and horizontal extension. In total, the model reproduces 79.8 % of observed cloud occurrences inside model grid boxes and even higher (94.3 %) for ice clouds (T ≤ -40 °C). The missing cloud occurrences in the model are primarily ascribed to the fact that the model cannot account for the high spatial variability of observed relative humidity (RH). Furthermore, model RH biases are mostly attributed to the discrepancies in water vapor, rather than temperature. At the micro-scale of ice clouds, the model captures the observed increase of ice crystal mean sizes with temperature, albeit with smaller sizes than the observations. The model underestimates the observed ice number concentration (Ni) and ice water content (IWC) for ice crystals larger than 75 µm in diameter. Modeled IWC and Ni are more sensitive to the threshold diameter for autoconversion of cloud ice to snow (Dcs), while simulated ice crystal mean size is more sensitive to ice nucleation parameterizations than to Dcs. Our results highlight the need for further improvements to the sub-grid RH variability and ice nucleation and growth in the model.

UV 380 nm reflectivity of the Earth's surface, clouds and aerosols

NASA Astrophysics Data System (ADS)

Herman, J. R.; Celarier, E.; Larko, D.

2001-03-01

The 380 nm radiance measurements of the Total Ozone Mapping Spectrometer (TOMS) have been converted into a global data set of daily (1979-1992) Lambert equivalent reflectivities R of the Earth's surface and boundary layer (clouds, aerosols, surface haze, and snow/ice) and then corrected to RPC for the presence of partly clouded scenes. Since UV surface reflectivity is between 2 and 8% for both land and water during all seasons of the year (except for ice and snow cover), reflectivities larger than the surface value indicate the presence of clouds, haze, or aerosols in the satellite field of view. A statistical analysis of 14 years of daily reflectivity data shows that most snow-/ice-free scenes observed by TOMS have a reflectivity less than 10% for the majority of days during a year. The 380 nm reflectivity data show that the true surface reflectivity is 2-3% lower than the most frequently occurring reflectivity value for each TOMS scene as seen from space. Most likely the cause is a combination of frequently occurring boundary layer water and/or aerosol haze. For most regions the observation of extremely clear conditions needed to estimate the surface reflectivity from space is a comparatively rare occurrence. Certain areas (e.g., Australia, southern Africa, portions of northern Africa) are cloud-free more than 80% of the year, which exposes these regions to larger amounts of UV radiation than at comparable latitudes in the Northern Hemisphere. Regions over rain forests, jungle areas, Europe and Russia, the bands surrounding the Arctic and Antarctic regions, and many ocean areas have significant cloud cover (R>15%) more than half of each year. In the low to middle latitudes the areas with the heaviest cloud cover (highest reflectivity for most of the year) are the forest areas of northern South America, southern Central America, the jungle areas of equatorial Africa, and high mountain regions such as the Himalayas or the Andes. The TOMS reflectivity data show both the presence of large nearly clear ocean areas and the effects of the major ocean currents on cloud production.

Atmospheric icing of structures: Observations and simulations

NASA Astrophysics Data System (ADS)

Ágústsson, H.; Elíasson, Á. J.; Thorsteins, E.; Rögnvaldsson, Ó.; Ólafsson, H.

2012-04-01

This study compares observed icing in a test span in complex orography at Hallormsstaðaháls (575 m) in East-Iceland with parameterized icing based on an icing model and dynamically downscaled weather at high horizontal resolution. Four icing events have been selected from an extensive dataset of observed atmospheric icing in Iceland. A total of 86 test-spans have been erected since 1972 at 56 locations in complex terrain with more than 1000 icing events documented. The events used here have peak observed ice load between 4 and 36 kg/m. Most of the ice accretion is in-cloud icing but it may partly be mixed with freezing drizzle and wet snow icing. The calculation of atmospheric icing is made in two steps. First the atmospheric data is created by dynamically downscaling the ECMWF-analysis to high resolution using the non-hydrostatic mesoscale Advanced Research WRF-model. The horizontal resolution of 9, 3, 1 and 0.33 km is necessary to allow the atmospheric model to reproduce correctly local weather in the complex terrain of Iceland. Secondly, the Makkonen-model is used to calculate the ice accretion rate on the conductors based on the simulated temperature, wind, cloud and precipitation variables from the atmospheric data. In general, the atmospheric model correctly simulates the atmospheric variables and icing calculations based on the atmospheric variables correctly identify the observed icing events, but underestimate the load due to too slow ice accretion. This is most obvious when the temperature is slightly below 0°C and the observed icing is most intense. The model results improve significantly when additional observations of weather from an upstream weather station are used to nudge the atmospheric model. However, the large variability in the simulated atmospheric variables results in high temporal and spatial variability in the calculated ice accretion. Furthermore, there is high sensitivity of the icing model to the droplet size and the possibility that some of the icing may be due to freezing drizzle or wet snow instead of in-cloud icing of super-cooled droplets. In addition, the icing model (Makkonen) may not be accurate for the highest icing loads observed.

Machine learning based cloud mask algorithm driven by radiative transfer modeling

NASA Astrophysics Data System (ADS)

Chen, N.; Li, W.; Tanikawa, T.; Hori, M.; Shimada, R.; Stamnes, K. H.

2017-12-01

Cloud detection is a critically important first step required to derive many satellite data products. Traditional threshold based cloud mask algorithms require a complicated design process and fine tuning for each sensor, and have difficulty over snow/ice covered areas. With the advance of computational power and machine learning techniques, we have developed a new algorithm based on a neural network classifier driven by extensive radiative transfer modeling. Statistical validation results obtained by using collocated CALIOP and MODIS data show that its performance is consistent over different ecosystems and significantly better than the MODIS Cloud Mask (MOD35 C6) during the winter seasons over mid-latitude snow covered areas. Simulations using a reduced number of satellite channels also show satisfactory results, indicating its flexibility to be configured for different sensors.

Clouds enhance Greenland ice sheet mass loss

NASA Astrophysics Data System (ADS)

Van Tricht, Kristof; Gorodetskaya, Irina V.; L'Ecuyer, Tristan; Lenaerts, Jan T. M.; Lhermitte, Stef; Noel, Brice; Turner, David D.; van den Broeke, Michiel R.; van Lipzig, Nicole P. M.

2015-04-01

Clouds have a profound influence on both the Arctic and global climate, while they still represent one of the key uncertainties in climate models, limiting the fidelity of future climate projections. The potentially important role of thin liquid-containing clouds over Greenland in enhancing ice sheet melt has recently gained interest, yet current research is spatially and temporally limited, focusing on particular events, and their large scale impact on the surface mass balance remains unknown. We used a combination of satellite remote sensing (CloudSat - CALIPSO), ground-based observations and climate model (RACMO) data to show that liquid-containing clouds warm the Greenland ice sheet 94% of the time. High surface reflectivity (albedo) for shortwave radiation reduces the cloud shortwave cooling effect on the absorbed fluxes, while not influencing the absorption of longwave radiation. Cloud warming over the ice sheet therefore dominates year-round. Only when albedo values drop below ~0.6 in the coastal areas during summer, the cooling effect starts to overcome the warming effect. The year-round excess of energy due to the presence of liquid-containing clouds has an extensive influence on the mass balance of the ice sheet. Simulations using the SNOWPACK snow model showed not only a strong influence of these liquid-containing clouds on melt increase, but also on the increased sublimation mass loss. Simulations with the Community Earth System Climate Model for the end of the 21st century (2080-2099) show that Greenland clouds contain more liquid water path and less ice water path. This implies that cloud radiative forcing will be further enhanced in the future. Our results therefore urge the need for improving cloud microphysics in climate models, to improve future projections of ice sheet mass balance and global sea level rise.

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.

2005-01-01

Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds, Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.

Snow and Ice Applications of AVHRR in Polar Regions: Report of a Workshop

NASA Technical Reports Server (NTRS)

Steffen, K.; Bindschadler, R.; Casassa, G.; Comiso, J.; Eppler, D.; Fetterer, F.; Hawkins, J.; Key, J.; Rothrock, D.; Thomas, R.;

DOE Office of Scientific and Technical Information (OSTI.GOV)

None, None

This 3-year project has studied how aerosol pollution influences glaciated clouds. The tool applied has been an 'aerosol-cloud model'. It is a type of Cloud-System Resolving Model (CSRM) modified to include 2-moment bulk microphysics and 7 aerosol species, as described by Phillips et al. (2009, 2013). The study has been done by, first, improving the model and then performing sensitivity studies with validated simulations of a couple of observed cases from ARM. These are namely the Tropical Warm Pool International Cloud Experiment (TWP-ICE) over the tropical west Pacific and the Cloud and Land Surface Interaction Campaign (CLASIC) over Oklahoma. Duringmore » the project, sensitivity tests with the model showed that in continental clouds, extra liquid aerosols (soluble aerosol material) from pollution inhibited warm rain processes for precipitation production. This promoted homogeneous freezing of cloud droplets and aerosols. Mass and number concentrations of cloud-ice particles were boosted. The mean sizes of cloud-ice particles were reduced by the pollution. Hence, the lifetime of glaciated clouds, especially ice-only clouds, was augmented due to inhibition of sedimentation and ice-ice aggregation. Latent heat released from extra homogeneous freezing invigorated convective updrafts, and raised their maximum cloud-tops, when aerosol pollution was included. In the particular cases simulated in the project, the aerosol indirect effect of glaciated clouds was twice than of (warm) water clouds. This was because glaciated clouds are higher in the troposphere than water clouds and have the first interaction with incoming solar radiation. Ice-only clouds caused solar cooling by becoming more extensive as a result of aerosol pollution. This 'lifetime indirect effect' of ice-only clouds was due to higher numbers of homogeneously nucleated ice crystals causing a reduction in their mean size, slowing the ice-crystal process of snow production and slowing sedimentation. In addition to the known indirect effects (glaciation, riming and thermodynamic), new indirect effects were discovered and quantified due to responses of sedimentation, aggregation and coalescence in glaciated clouds to changing aerosol conditions. In summary, the change in horizontal extent of the glaciated clouds ('lifetime indirect effects'), especially of ice-only clouds, was seen to be of higher importance in regulating aerosol indirect effects than changes in cloud properties ('cloud albedo indirect effects').« less

Trends in annual minimum exposed snow and ice cover in High Mountain Asia from MODIS

NASA Astrophysics Data System (ADS)

Rittger, Karl; Brodzik, Mary J.; Painter, Thomas H.; Racoviteanu, Adina; Armstrong, Richard; Dozier, Jeff

2016-04-01

Though a relatively short record on climatological scales, data from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2000-2014 can be used to evaluate changes in the cryosphere and provide a robust baseline for future observations from space. We use the MODIS Snow Covered Area and Grain size (MODSCAG) algorithm, based on spectral mixture analysis, to estimate daily fractional snow and ice cover and the MODICE Persistent Ice (MODICE) algorithm to estimate the annual minimum snow and ice fraction (fSCA) for each year from 2000 to 2014 in High Mountain Asia. We have found that MODSCAG performs better than other algorithms, such as the Normalized Difference Index (NDSI), at detecting snow. We use MODICE because it minimizes false positives (compared to maximum extents), for example, when bright soils or clouds are incorrectly classified as snow, a common problem with optical satellite snow mapping. We analyze changes in area using the annual MODICE maps of minimum snow and ice cover for over 15,000 individual glaciers as defined by the Randolph Glacier Inventory (RGI) Version 5, focusing on the Amu Darya, Syr Darya, Upper Indus, Ganges, and Brahmaputra River basins. For each glacier with an area of at least 1 km2 as defined by RGI, we sum the total minimum snow and ice covered area for each year from 2000 to 2014 and estimate the trends in area loss or gain. We find the largest loss in annual minimum snow and ice extent for 2000-2014 in the Brahmaputra and Ganges with 57% and 40%, respectively, of analyzed glaciers with significant losses (p-value<0.05). In the Upper Indus River basin, we see both gains and losses in minimum snow and ice extent, but more glaciers with losses than gains. Our analysis shows that a smaller proportion of glaciers in the Amu Darya and Syr Darya are experiencing significant changes in minimum snow and ice extent (3.5% and 12.2%), possibly because more of the glaciers in this region are smaller than 1 km2 than in the Indus, Ganges, and Brahmaputra making analysis from MODIS (pixel area ~0.25 km2) difficult. Overall, we see 23% of the glaciers in the 5 river basins with significant trends (in either direction). We relate these changes in area to topography and climate to understand the driving processes related to these changes. In addition to annual minimum snow and ice cover, the MODICE algorithm also provides the date of minimum fSCA for each pixel. To determine whether the surface was snow or ice we use the date of minimum fSCA from MODICE to index daily maps of snow on ice (SOI), or exposed glacier ice (EGI) and systematically derive an equilibrium line altitude (ELA) for each year from 2000-2014. We test this new algorithm in the Upper Indus basin and produce annual estimates of ELA. For the Upper Indus basin we are deriving annual ELAs that range from 5350 m to 5450 m which is slightly higher than published values of 5200 m for this region.

A Legacy for IPY: The Global Snowflake Network (GSN) Together With Art and Ice, and Music and Ice; Unique new Features for Science Education.

NASA Astrophysics Data System (ADS)

Wasilewski, P. J.

2007-12-01

The Global Snowflake Network (GSN) is a program that is simultaneously a science program and an education program. When the validation of the procedures (collection and identification of the type of snowflakes and the associated satellite image archive, as a serial record of a storm), is achieved, then the program becomes a scientific resource. This latter is the ultimate goal. That's why NASA has launched the Global Snowflake Network, a massive project that aims to involve the general public to "collect and classify" falling snowflakes. The data will be compiled into a massive database, along with satellite images, that will help climatologists and others who study climate-related phenomena gain a better understanding of wintry meteorology as they track various snowstorms around the globe. A great deal of information about the atmosphere dynamics and cloud microphysics can be derived from the serial collection and identification of the types of snow crystals and the degree of riming of the snow crystals during the progress of a snow storm. Forecasting winter weather depends in part on cloud physics, which deals with precipitation type, and if it happens to be snow- the crystal type, size, and density of the snowflake population. The History of Winter website will host the evolving snow and ice features for the IPY. Type "Global Snowflake Network" into the search engine (such as GOOGLE) and you will receive a demonstration of the operation of the preliminary GSN by the Indigenous community. The expeditions FINNMARK2007 and the POLAR Husky GoNorth 2007 expedition took the complement of Thermochrons with multimedia instructions for the Global Snowflake Network. This approach demonstrates the continuous Thermochron monitoring of expedition temperature and provides otherwise inaccessible snowflake information to NASA and others interested in the Polar region snow. In addition, reindeer herder and Ph.D. student, Inger Marie G. Eira, will incorporate the HOW, GSN thermochrons, snow pit observations, and snowflake identification protocols into her Ph.D. dissertation on snow changes, and reindeer pastures in Northern Norway. SCIENTISTS DISCOVER - ARTISTS INTERPRET - TOGETHER WE CAN OPEN THE EYES OF THE WORLD. This theme of the "Polar Artists "can be reached from the web search. Water ice is one of the most widespread, intriguing, and familiar compounds on the planet, in the solar system, and beyond. On the planet, it falls as snow, forms lacy deposits on winter windows, creates skating surfaces on lakes, gracefully drapes rock cliffs, packs thickly on the polar oceans, and lays even thicker on the ice caps blanketing Greenland and Antarctica. Of the 11 forms of water ice so far identified, only the form found on Earth can provide a "Frizion". Communicating this is part of Polar Artists outreach. We are working with Terje Isungset, from Norway, who creates musical instruments from ice. We will demonstrate how ART and Ice and Music and Ice are presented. In addition to video presentations appearing on YOUTUBE, we are preparing additional live performances of this work.

The GLAS Standard Data Products Specification-Data Dictionary, Version 1.0. Volume 15

NASA Technical Reports Server (NTRS)

Lee, Jeffrey E.

2013-01-01

The Geoscience Laser Altimeter System (GLAS) is the primary instrument for the ICESat (Ice, Cloud and Land Elevation Satellite) laser altimetry mission. ICESat was the benchmark Earth Observing System (EOS) mission for measuring ice sheet mass balance, cloud and aerosol heights, as well as land topography and vegetation characteristics. From 2003 to 2009, the ICESat mission provided multi-year elevation data needed to determine ice sheet mass balance as well as cloud property information, especially for stratospheric clouds common over polar areas. It also provided topography and vegetation data around the globe, in addition to the polar-specific coverage over the Greenland and Antarctic ice sheets.This document contains the data dictionary for the GLAS standard data products. It details the parameters present on GLAS standard data products. Each parameter is defined with a short name, a long name, units on product, type of variable, a long description and products that contain it. The term standard data products refers to those EOS instrument data that are routinely generated for public distribution. These products are distributed by the National Snow and Ice Data Center (NSDIC).

Influence of Ice Cloud Microphysics on Imager-Based Estimates of Earth's Radiation Budget

NASA Astrophysics Data System (ADS)

Loeb, N. G.; Kato, S.; Minnis, P.; Yang, P.; Sun-Mack, S.; Rose, F. G.; Hong, G.; Ham, S. H.

2016-12-01

A central objective of the Clouds and the Earth's Radiant Energy System (CERES) is to produce a long-term global climate data record of Earth's radiation budget from the TOA down to the surface along with the associated atmospheric and surface properties that influence it. CERES relies on a number of data sources, including broadband radiometers measuring incoming and reflected solar radiation and OLR, high-resolution spectral imagers, meteorological, aerosol and ozone assimilation data, and snow/sea-ice maps based on microwave radiometer data. While the TOA radiation budget is largely determined directly from accurate broadband radiometer measurements, the surface radiation budget is derived indirectly through radiative transfer model calculations initialized using imager-based cloud and aerosol retrievals and meteorological assimilation data. Because ice cloud particles exhibit a wide range of shapes, sizes and habits that cannot be independently retrieved a priori from passive visible/infrared imager measurements, assumptions about the scattering properties of ice clouds are necessary in order to retrieve ice cloud optical properties (e.g., optical depth) from imager radiances and to compute broadband radiative fluxes. This presentation will examine how the choice of an ice cloud particle model impacts computed shortwave (SW) radiative fluxes at the top-of-atmosphere (TOA) and surface. The ice cloud particle models considered correspond to those from prior, current and future CERES data product versions. During the CERES Edition2 (and Edition3) processing, ice cloud particles were assumed to be smooth hexagonal columns. In the Edition4, roughened hexagonal columns are assumed. The CERES team is now working on implementing in a future version an ice cloud particle model comprised of a two-habit ice cloud model consisting of roughened hexagonal columns and aggregates of roughened columnar elements. In each case, we use the same ice particle model in both the imager-based cloud retrievals (inverse problem) and the computed radiative fluxes (forward calculation). In addition to comparing radiative fluxes using the different ice cloud particle models, we also compare instantaneous TOA flux calculations with those observed by the CERES instrument.

TOMS UV Algorithm: Problems and Enhancements. 2

NASA Technical Reports Server (NTRS)

Krotkov, Nickolay; Herman, Jay; Bhartia, P. K.; Seftor, Colin; Arola, Antti; Kaurola, Jussi; Kroskinen, Lasse; Kalliskota, S.; Taalas, Petteri; Geogdzhaev, I.

2002-01-01

Satellite instruments provide global maps of surface ultraviolet (UV) irradiance by combining backscattered radiance measurements with radiative transfer models. The models are limited by uncertainties in input parameters of the atmosphere and the surface. We evaluate the effects of possible enhancements of the current Total Ozone Mapping Spectrometer (TOMS) surface UV irradiance algorithm focusing on effects of diurnal variation of cloudiness and improved treatment of snow/ice. The emphasis is on comparison between the results of the current (version 1) TOMS UV algorithm and each of the changes proposed. We evaluate different approaches for improved treatment of pixel average cloud attenuation, with and without snow/ice on the ground. In addition to treating clouds based only on the measurements at the local time of the TOMS observations, the results from other satellites and weather assimilation models can be used to estimate attenuation of the incident UV irradiance throughout the day. A new method is proposed to obtain a more realistic treatment of snow covered terrain. The method is based on a statistical relation between UV reflectivity and snow depth. The new method reduced the bias between the TOMS UV estimations and ground-based UV measurements for snow periods. The improved (version 2) algorithm will be applied to re-process the existing TOMS UV data record (since 1978) and to the future satellite sensors (e.g., Quik/TOMS, GOME, OMI on EOS/Aura and Triana/EPIC).

From the clouds to the ground - snow precipitation patterns vs. snow accumulation patterns

NASA Astrophysics Data System (ADS)

Gerber, Franziska; Besic, Nikola; Mott, Rebecca; Gabella, Marco; Germann, Urs; Bühler, Yves; Marty, Mauro; Berne, Alexis; Lehning, Michael

2017-04-01

Knowledge about snow distribution and snow accumulation patterns is important and valuable for different applications such as the prediction of seasonal water resources or avalanche forecasting. Furthermore, accumulated snow on the ground is an important ground truth for validating meteorological and climatological model predictions of precipitation in high mountains and polar regions. Snow accumulation patterns are determined by many different processes from ice crystal nucleation in clouds to snow redistribution by wind and avalanches. In between, snow precipitation undergoes different dynamical and microphysical processes, such as ice crystal growth, aggregation and riming, which determine the growth of individual particles and thereby influence the intensity and structure of the snowfall event. In alpine terrain the interaction of different processes and the topography (e.g. lifting condensation and low level cloud formation, which may result in a seeder-feeder effect) may lead to orographic enhancement of precipitation. Furthermore, the redistribution of snow particles in the air by wind results in preferential deposition of precipitation. Even though orographic enhancement is addressed in numerous studies, the relative importance of micro-physical and dynamically induced mechanisms on local snowfall amounts and especially snow accumulation patterns is hardly known. To better understand the relative importance of different processes on snow precipitation and accumulation we analyze snowfall and snow accumulation between January and March 2016 in Davos (Switzerland). We compare MeteoSwiss operational weather radar measurements on Weissfluhgipfel to a spatially continuous snow accumulation map derived from airborne digital sensing (ADS) snow height for the area of Dischma valley in the vicinity of the weather radar. Additionally, we include snow height measurements from automatic snow stations close to the weather radar. Large-scale radar snow accumulation patterns show a snowfall gradient consistent with the prevailing wind direction. Deriving snow accumulation based on radar data is challenging as the close-ground precipitation patters cannot be resolved by the radar due to shielding and ground clutter in highly complex terrain. Nonetheless, radar measurements show distinct patterns of snowfall and accumulation, which may be the result of orographic enhancement. Station-based snow accumulation measurements are in reasonable agreement with the estimated large-scale radar snow accumulation. The ADS-based snow accumulation maps feature much smaller scale snow accumulation patterns likely due to close-ground wind effects and snow redistribution on top of an altitudinal gradient. To evaluate microphysical processes and patterns influenced by the topography we run a hydrometeor classification on the radar data. The relative importance of topographically induced effects on snow accumulation patterns is investigated based on vertical cross sections of hydrometeor data and corresponding snow accumulation.

The Landsat Image Mosaic of Antarctica

USGS Publications Warehouse

Bindschadler, Robert; Vornberger, P.; Fleming, A.; Fox, A.; Mullins, J.; Binnie, D.; Paulsen, S.J.; Granneman, Brian J.; Gorodetzky, D.

2008-01-01

The Landsat Image Mosaic of Antarctica (LIMA) is the first true-color, high-spatial-resolution image of the seventh continent. It is constructed from nearly 1100 individually selected Landsat-7 ETM+ scenes. Each image was orthorectified and adjusted for geometric, sensor and illumination variations to a standardized, almost seamless surface reflectance product. Mosaicing to avoid clouds produced a high quality, nearly cloud-free benchmark data set of Antarctica for the International Polar Year from images collected primarily during 1999-2003. Multiple color composites and enhancements were generated to illustrate additional characteristics of the multispectral data including: the true appearance of the surface; discrimination between snow and bare ice; reflectance variations within bright snow; recovered reflectance values in regions of sensor saturation; and subtle topographic variations associated with ice flow. LIMA is viewable and individual scenes or user defined portions of the mosaic are downloadable at http://lima.usgs.gov. Educational materials associated with LIMA are available at http://lima.nasa.gov.

LANDSAT-D investigations in snow hydrology

NASA Technical Reports Server (NTRS)

Dozier, J. (Principal Investigator)

1982-01-01

Snow reflectance in all 6 TM reflective bands, i.e., 1, 2, 3, 4, 5, and 7 was simulated using a delta-Eddington model. Snow reflectance in bands 4, 5, and 7 appear sensitive to grain size. It appears that the TM filters resemble a ""square-wave'' closely enough that a square-wave can be assumed in calculations. Integrated band reflectance over the actual response functions was calculated using sensor data supplied by Santa Barbara Research Center. Differences between integrating over the actual response functions and the equivalent square wave were negligible. Tables are given which show (1) sensor saturation radiance as a percentage of the solar constant, integrated through the band response function; (2) comparisons of integrations through the sensor response function with integrations over the equivalent square wave; and (3) calculations of integrated reflectance for snow over all reflective TM bands, and water and ice clouds with thickness of 1 mm water equivalent over TM bands 5 and 7. These calculations look encouraging for snow/cloud discrimination with TM bands 5 and 7.

Three-dimensional nonhydrostatic simulations of summer thunderstorms in the humid subtropics versus High Plains

NASA Astrophysics Data System (ADS)

Lin, Hsin-mu; Wang, Pao K.; Schlesinger, Robert E.

2005-11-01

This article presents a detailed comparison of cloud microphysical evolution among six warm-season thunderstorm simulations using a time-dependent three-dimensional model WISCDYMM. The six thunderstorms chosen for this study consist of three apiece from two contrasting climate zones, the US High Plains (one supercell and two multicells) and the humid subtropics (two in Florida, US and one in Taipei, Taiwan, all multicells). The primary goal of this study is to investigate the differences among thunderstorms in different climate regimes in terms of their microphysical structures and how differently these structures evolve in time. A subtropical case is used as an example to illustrate the general contents of a simulated storm, and two examples of the simulated storms, one humid subtropical and one northern High Plains case, are used to describe in detail the microphysical histories. The simulation results are compared with the available observational data, and the agreement between the two is shown to be at least fairly close overall. The analysis, synthesis and implications of the simulation results are then presented. The microphysical histories of the six simulated storms in terms of the domain-integrated masses of all five hydrometeor classes (cloud water, cloud ice, rain, snow, graupel/hail), along with the individual sources (and sinks) of the three precipitating hydrometeor classes (rain, snow, graupel/hail) are analyzed in detail. These analyses encompass both the absolute magnitudes and their percentage contributions to the totals, for the condensate mass and their precipitation production (and depletion) rates, respectively. Comparisons between the hydrometeor mass partitionings for the High Plains versus subtropical thunderstorms show that, in a time-averaged sense, ice hydrometeors (cloud ice, snow, graupel/hail) account for ˜ 70-80% of the total hydrometeor mass for the High Plains storms but only ˜ 50% for the subtropical storms, after the systems have reached quasi-steady mature states. This demonstrates that ice processes are highly important even in thunderstorms occurring in warm climatic regimes. The dominant rain sources are two of the graupel/hail sinks, shedding and melting, in both High Plains and subtropical storms, while the main rain sinks are accretion by hail and evaporation. The dominant graupel/hail sources are accretion of rain, snow and cloud water, while its main sinks are shedding and melting. The dominant snow sources are the Bergeron-Findeisen process and accretion of cloud water, while the main sinks are accretion by graupel/hail and sublimation. However, the rankings of the leading production and depletion mechanisms differ somewhat in different storm cases, especially for graupel/hail. The model results indicate that the same hydrometeor types in the different climates have their favored microphysical sources and sinks. These findings not only prove that thunderstorm structure depends on local dynamic and thermodynamic atmospheric conditions that are generally climate-dependent, but also provide information about the partitioning of hydrometeors in the storms. Such information is potentially useful for convective parameterization in large-scale models.

Implementing a warm cloud microphysics parameterization for convective clouds in NCAR CESM

NASA Astrophysics Data System (ADS)

Shiu, C.; Chen, Y.; Chen, W.; Li, J. F.; Tsai, I.; Chen, J.; Hsu, H.

2013-12-01

Most of cumulus convection schemes use simple empirical approaches to convert cloud liquid mass to rain water or cloud ice to snow e.g. using a constant autoconversion rate and dividing cloud liquid mass into cloud water and ice as function of air temperature (e.g. Zhang and McFarlane scheme in NCAR CAM model). There are few studies trying to use cloud microphysical schemes to better simulate such precipitation processes in the convective schemes of global models (e.g. Lohmann [2008] and Song, Zhang, and Li [2012]). A two-moment warm cloud parameterization (i.e. Chen and Liu [2004]) is implemented into the deep convection scheme of CAM5.2 of CESM model for treatment of conversion of cloud liquid water to rain water. Short-term AMIP type global simulations are conducted to evaluate the possible impacts from the modification of this physical parameterization. Simulated results are further compared to observational results from AMWG diagnostic package and CloudSAT data sets. Several sensitivity tests regarding to changes in cloud top droplet concentration (here as a rough testing for aerosol indirect effects) and changes in detrained cloud size of convective cloud ice are also carried out to understand their possible impacts on the cloud and precipitation simulations.

In situ measurements of cloud microphysics and aerosol over coastal Antarctica during the MAC campaign

NASA Astrophysics Data System (ADS)

O'Shea, Sebastian J.; Choularton, Thomas W.; Flynn, Michael; Bower, Keith N.; Gallagher, Martin; Crosier, Jonathan; Williams, Paul; Crawford, Ian; Fleming, Zoë L.; Listowski, Constantino; Kirchgaessner, Amélie; Ladkin, Russell S.; Lachlan-Cope, Thomas

2017-11-01

During austral summer 2015, the Microphysics of Antarctic Clouds (MAC) field campaign collected unique and detailed airborne and ground-based in situ measurements of cloud and aerosol properties over coastal Antarctica and the Weddell Sea. This paper presents the first results from the experiment and discusses the key processes important in this region, which is critical to predicting future climate change. The sampling was predominantly of stratus clouds, at temperatures between -20 and 0 °C. These clouds were dominated by supercooled liquid water droplets, which had a median concentration of 113 cm-3 and an interquartile range of 86 cm-3. Both cloud liquid water content and effective radius increased closer to cloud top. The cloud droplet effective radius increased from 4 ± 2 µm near cloud base to 8 ± 3 µm near cloud top. Cloud ice particle concentrations were highly variable with the ice tending to occur in small, isolated patches. Below approximately 1000 m, glaciated cloud regions were more common at higher temperatures; however, the clouds were still predominantly liquid throughout. When ice was present at temperatures higher than -10 °C, secondary ice production most likely through the Hallett-Mossop mechanism led to ice concentrations 1 to 3 orders of magnitude higher than the number predicted by commonly used primary ice nucleation parameterisations. The drivers of the ice crystal variability are investigated. No clear dependence on the droplet size distribution was found. The source of first ice in the clouds remains uncertain but may include contributions from biogenic particles, blowing snow or other surface ice production mechanisms. The concentration of large aerosols (diameters 0.5 to 1.6 µm) decreased with altitude and were depleted in air masses that originated over the Antarctic continent compared to those more heavily influenced by the Southern Ocean and sea ice regions. The dominant aerosol in the region was hygroscopic in nature, with the hygroscopicity parameter κ having a median value for the campaign of 0.66 (interquartile range of 0.38). This is consistent with other remote marine locations that are dominated by sea salt/sulfate.

Sea Ice, Clouds, Sunlight, and Albedo: The Umbrella Versus the Blanket

NASA Astrophysics Data System (ADS)

Perovich, D. K.

2017-12-01

The Arctic sea ice cover has undergone a major decline in recent years, with reductions in ice extent, ice thickness, and ice age. Understanding the feedbacks and forcing driving these changes is critical in improving predictions. The surface radiation budget plays a central role in summer ice melt and is governed by clouds and surface albedo. Clouds act as an umbrella reducing the downwelling shortwave, but also serve as a blanket increasing the downwelling longwave, with the surface albedo also determining the net balance. Using field observations from the SHEBA program, pairs of clear and cloudy days were selected for each month from May through September and the net radiation flux was calculated for different surface conditions and albedos. To explore the impact of albedo we calculated a break even albedo, where the net radiation for cloudy skies is the same as clear skies. For albedos larger than the break-even value the net radiation flux is smaller under clear skies compared to cloudy skies. Break-even albedos ranged from 0.30 in September to 0.58 in July. For snow covered or bare ice, clear skies always resulted in less radiative heat input. In contrast, leads always had, and ponds usually had, more radiative heat input under clear skies than cloudy skies. Snow covered ice had a net radiation flux that was negative or near zero under clear skies resulting in radiative cooling. We combined the albedo of individual ice types with the area of those ice types to calculate albedos averaged over a 50 km x 50 km area. The July case had the smallest areally averaged albedo of 0.50. This was less than the breakeven albedo, so cloudy skies had a smaller net radiation flux than clear skies. For the cases from the other four months, the areally averaged albedo was greater than the break-even albedo. The areally averaged net radiation flux was negative under clear skies for the May and September cases.

Distinguishing Clouds from Ice over the East Siberian Sea, Russia

NASA Technical Reports Server (NTRS)

2002-01-01

As a consequence of its capability to retrieve cloud-top elevations, stereoscopic observations from the Multi-angle Imaging SpectroRadiometer (MISR) can discriminate clouds from snow and ice. The central portion of Russia's East Siberian Sea, including one of the New Siberian Islands, Novaya Sibir, are portrayed in these views from data acquired on May 28, 2002.

The left-hand image is a natural color view from MISR's nadir camera. On the right is a height field retrieved using automated computer processing of data from multiple MISR cameras. Although both clouds and ice appear white in the natural color view, the stereoscopic retrievals are able to identify elevated clouds based on the geometric parallax which results when they are observed from different angles. Owing to their elevation above sea level, clouds are mapped as green and yellow areas, whereas land, sea ice, and very low clouds appear blue and purple. Purple, in particular, denotes elevations very close to sea level. The island of Novaya Sibir is located in the lower left of the images. It can be identified in the natural color view as the dark area surrounded by an expanse of fast ice. In the stereo map the island appears as a blue region indicating its elevation of less than 100 meters above sea level. Areas where the automated stereo processing failed due to lack of sufficient spatial contrast are shown in dark gray. The northern edge of the Siberian mainland can be found at the very bottom of the panels, and is located a little over 250 kilometers south of Novaya Sibir. Pack ice containing numerous fragmented ice floes surrounds the fast ice, and narrow areas of open ocean are visible.

The East Siberian Sea is part of the Arctic Ocean and is ice-covered most of the year. The New Siberian Islands are almost always covered by snow and ice, and tundra vegetation is very scant. Despite continuous sunlight from the end of April until the middle of August, the ice between the island and the mainland typically remains until August or September.

The Multi-angle Imaging SpectroRadiometer views almost the entire Earth every 9 days. These images were acquired during Terra orbit 12986 and cover an area of about 380 kilometers x 1117 kilometers. They utilize data from blocks 24 to 32 within World Reference System-2 path 117.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Pine Island Glacier, Antarctica, MISR Multi-angle Composite

Atmospheric Science Data Center

2013-12-17

...     View Larger Image (JPEG) A large iceberg has finally separated from the calving front ... next due to stereo parallax. This parallax is used in MISR processing to retrieve cloud heights over snow and ice. Additionally, a plume ...

Evolution of Snow-Size Spectra in Cyclonic Storms. Part I: Snow Growth by Vapor Deposition and Aggregation.

NASA Astrophysics Data System (ADS)

Mitchell, David L.

1988-11-01

Based on the stochastic collection equation, height- and time-dependent snow growth models were developed for unrimed stratiform snowfall. Moment conservation equations were parameterized and solved by constraining the size distribution to be of the form N(D)dD = N0 exp(D)dD, yielding expressions for the slope parameter, , and the y-intercept parameters, NO, as functions of height or time. The processes of vapor deposition and aggregation were treated analytically without neglecting changes in ice crystal habits, while the ice particle breakup process was dealt with empirically.The models were compared against vertical profiles of snow-size spectra, obtained from aircraft measurements, for three case studies. The predicted spectra are in good agreement with the observed evolution of snow-size spectra in all three cases, indicating the proposed scheme for ice particle aggregation was successful. The temperature dependence of aggregation was assumed to result from differences in ice crystal habit. Using data from an earlier study, the aggregation efficiency between two levels in a cloud was calculated. Finally, other height-dependent, steady-state snowfall models in the literature were compared against spectra from one of the above case studies. The agreement between the predicted and observed spectra regarding these models was less favorable than was obtained from the models presented here.

Arctic Mixed-phase Clouds Simulated by a Cloud-Resolving Model: Comparison with ARM Observations and Sensitivity to Microphysics Parameterizations

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man; Luo, Yali; Morrison, Hugh; Mcfarquhar, G.M.

2008-01-01

Single-layer mixed-phase stratiform (MPS) Arctic clouds, which formed under conditions of large surface heat flux combined with general subsidence during a subperiod of the Atmospheric Radiation Measurement (ARM) Program Mixed-Phase Arctic Cloud Experiment (M-PACE), are simulated with a cloud resolving model (CRM). The CRM is implemented with either an advanced two-moment (M05) or a commonly used one-moment (L83) bulk microphysics scheme and a state-of-the-art radiative transfer scheme. The CONTROL simulation, that uses the M05 scheme and observed aerosol size distribution and ice nulei (IN) number concentration, reproduces the magnitudes and vertical structures of cloud liquid water content (LWC), total ice water content (IWC), number concentration and effective radius of cloud droplets as suggested by the M-PACE observations. It underestimates ice crystal number concentrations by an order of magnitude and overestimates effective radius of ice crystals by a factor of 2-3. The OneM experiment, that uses the L83 scheme, produces values of liquid water path (LWP) and ice plus snow water path (ISWP) that were about 30% and 4 times, respectively, of those produced by the CONTROL. Its vertical profile of IWC exhibits a bimodal distribution in contrast to the constant distribution of IWC produced in the CONTROL and observations.

Developing Cloud Chambers with High School Students

NASA Astrophysics Data System (ADS)

Ishizuka, Ryo; Tan, Nobuaki; Sato, Shoma; Zeze, Syoji

The result and outcome of the cloud chamber project, which aims to develop a cloud chamber useful for science education is reported in detail. A project includes both three high school students and a teacher as a part of Super Science High School (SSH) program in our school. We develop a dry-ice-free cloud chamber using salt and ice (or snow). Technical details of the chamber are described. We also argue how the project have affected student's cognition, motivation, academic skills and behavior. The research project has taken steps of professional researchers, i.e., in planning research, applying fund, writing a paper and giving a talk in conferences. From interviews with students, we have learnt that such style of scientific activity is very effective in promoting student's motivation for learning science.

Detection Thresholds of Falling Snow From Satellite-Borne Active and Passive Sensors

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail M.; Johnson, Benjamin T.; Munchak, S. Joseph

2013-01-01

There is an increased interest in detecting and estimating the amount of falling snow reaching the Earths surface in order to fully capture the global atmospheric water cycle. An initial step toward global spaceborne falling snow algorithms for current and future missions includes determining the thresholds of detection for various active and passive sensor channel configurations and falling snow events over land surfaces and lakes. In this paper, cloud resolving model simulations of lake effect and synoptic snow events were used to determine the minimum amount of snow (threshold) that could be detected by the following instruments: the W-band radar of CloudSat, Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR)Ku- and Ka-bands, and the GPM Microwave Imager. Eleven different nonspherical snowflake shapes were used in the analysis. Notable results include the following: 1) The W-band radar has detection thresholds more than an order of magnitude lower than the future GPM radars; 2) the cloud structure macrophysics influences the thresholds of detection for passive channels (e.g., snow events with larger ice water paths and thicker clouds are easier to detect); 3) the snowflake microphysics (mainly shape and density)plays a large role in the detection threshold for active and passive instruments; 4) with reasonable assumptions, the passive 166-GHz channel has detection threshold values comparable to those of the GPM DPR Ku- and Ka-band radars with approximately 0.05 g *m(exp -3) detected at the surface, or an approximately 0.5-1.0-mm * h(exp -1) melted snow rate. This paper provides information on the light snowfall events missed by the sensors and not captured in global estimates.

UV 380 nm Reflectivity of the Earth's Surface

NASA Technical Reports Server (NTRS)

Herman, J. R.; Celarier, E.; Larko, D.

2000-01-01

The 380 nm radiance measurements of TOMS (Total Ozone Mapping Spectrometer) have been converted into a global data set of daily (1979 to 1992) Lambert equivalent reflectivities R of the Earth's surface and boundary layer (clouds, aerosols, surface haze, and snow/ice). Since UV surface reflectivity is between 2 and 8% for both land and water during all seasons of the year (except for ice and snow cover), reflectivities larger than the surface value indicates the presence of clouds, haze, or aerosols in the satellite field of view. Statistical analysis of 14 years of daily data show that most snow/ice-free regions of the Earth have their largest fraction of days each year when the reflectivity is low (R less than 10%). The 380 nm reflectivity data shows that the true surface reflectivity is 2 to 3% lower than the most frequently occurring reflectivity value for each TOMS scene. The most likely cause of this could be a combination of frequently occurring boundary-layer water or aerosol haze. For most regions, the observation of extremely clear conditions needed to estimate the surface reflectivity from space is a comparatively rare occurrence. Certain areas (e.g., Australia, southern Africa, portions of northern Africa) are cloud-free more than 80% of the year, which exposes these regions to larger amounts of UV radiation than at comparable latitudes in the Northern Hemisphere. Regions over rain-forests, jungle areas, Europe and Russia, the bands surrounding the Arctic and Antarctic regions, and many ocean areas have significant cloud cover (R greater than 15%) more than half of each year. In the low to middle latitudes, the areas with the heaviest cloud cover (highest reflectivity for most of the year) are the forest areas of northern South America, southern Central America, the jungle areas of equatorial Africa, and high mountain regions such as the Himalayas or the Andes. The TOMS reflectivity data show the presence of large nearly clear ocean areas and the effects of the major ocean currents on cloud production.

West Antarctic Ice Sheet cloud cover and surface radiation budget from NASA A-Train satellites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scott, Ryan C.; Lubin, Dan; Vogelmann, Andrew M.

Clouds are an essential parameter of the surface energy budget influencing the West Antarctic Ice Sheet (WAIS) response to atmospheric warming and net contribution to global sea-level rise. A four-year record of NASA A-Train cloud observations is combined with surface radiation measurements to quantify the WAIS radiation budget and constrain the three-dimensional occurrence frequency, thermodynamic phase partitioning, and surface radiative effect of clouds over West Antarctica (WA). The skill of satellite-modeled radiative fluxes is confirmed through evaluation against measurements at four Antarctic sites (WAIS Divide Ice Camp, Neumayer, Syowa, and Concordia Stations). And due to perennial high-albedo snow and icemore » cover, cloud infrared emission dominates over cloud solar reflection/absorption leading to a positive net all-wave cloud radiative effect (CRE) at the surface, with all monthly means and 99.15% of instantaneous CRE values exceeding zero. The annual-mean CRE at theWAIS surface is 34 W m -2, representing a significant cloud-induced warming of the ice sheet. Low-level liquid-containing clouds, including thin liquid water clouds implicated in radiative contributions to surface melting, are widespread and most frequent in WA during the austral summer. Clouds warm the WAIS by 26 W m -2, in summer, on average, despite maximum offsetting shortwave CRE. Glaciated cloud systems are strongly linked to orographic forcing, with maximum incidence on the WAIS continuing downstream along the Transantarctic Mountains.« less

West Antarctic Ice Sheet cloud cover and surface radiation budget from NASA A-Train satellites

DOE PAGES

Scott, Ryan C.; Lubin, Dan; Vogelmann, Andrew M.; ...

2017-04-26

Clouds are an essential parameter of the surface energy budget influencing the West Antarctic Ice Sheet (WAIS) response to atmospheric warming and net contribution to global sea-level rise. A four-year record of NASA A-Train cloud observations is combined with surface radiation measurements to quantify the WAIS radiation budget and constrain the three-dimensional occurrence frequency, thermodynamic phase partitioning, and surface radiative effect of clouds over West Antarctica (WA). The skill of satellite-modeled radiative fluxes is confirmed through evaluation against measurements at four Antarctic sites (WAIS Divide Ice Camp, Neumayer, Syowa, and Concordia Stations). And due to perennial high-albedo snow and icemore » cover, cloud infrared emission dominates over cloud solar reflection/absorption leading to a positive net all-wave cloud radiative effect (CRE) at the surface, with all monthly means and 99.15% of instantaneous CRE values exceeding zero. The annual-mean CRE at theWAIS surface is 34 W m -2, representing a significant cloud-induced warming of the ice sheet. Low-level liquid-containing clouds, including thin liquid water clouds implicated in radiative contributions to surface melting, are widespread and most frequent in WA during the austral summer. Clouds warm the WAIS by 26 W m -2, in summer, on average, despite maximum offsetting shortwave CRE. Glaciated cloud systems are strongly linked to orographic forcing, with maximum incidence on the WAIS continuing downstream along the Transantarctic Mountains.« less

Cloud Streets over the Bering Sea

NASA Image and Video Library

2017-12-08

NASA image captured January 4, 2012 Most of us prefer our winter roads free of ice, but one kind of road depends on it: a cloud street. Such streets formed over the Bering Sea in early January 2012, thanks to snow and ice blanketing the nearby land, and sea ice clinging to the shore. The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite captured this natural-color image of the cloud streets on January 4, 2012. Air blowing over frigid ice then warmer ocean water can lead to the development of parallel cylinders of spinning air. Above the upward cycle of these cylinders (rising air), small clouds form. Along the downward cycle (descending air), skies are clear. The resulting cloud formations resemble streets. This image shows that some of the cloud streets begin over the sea ice, but most of the clouds hover over the open ocean water. These streets are not perfectly straight, but curve to the east and west after passing over the sea ice. By lining up along the prevailing wind direction, the tiny clouds comprising the streets indicate the wind patterns around the time of their formation. NASA images courtesy LANCE/EOSDIS MODIS Rapid Response Team at NASA GSFC. Caption by Michon Scott. Instrument: Terra - MODIS Credit: NASA Earth Observatory NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Snow Cover Mapping and Ice Avalanche Monitoring from the Satellite Data of the Sentinels

NASA Astrophysics Data System (ADS)

Wang, S.; Yang, B.; Zhou, Y.; Wang, F.; Zhang, R.; Zhao, Q.

2018-04-01

In order to monitor ice avalanches efficiently under disaster emergency conditions, a snow cover mapping method based on the satellite data of the Sentinels is proposed, in which the coherence and backscattering coefficient image of Synthetic Aperture Radar (SAR) data (Sentinel-1) is combined with the atmospheric correction result of multispectral data (Sentinel-2). The coherence image of the Sentinel-1 data could be segmented by a certain threshold to map snow cover, with the water bodies extracted from the backscattering coefficient image and removed from the coherence segment result. A snow confidence map from Sentinel-2 was used to map the snow cover, in which the confidence values of the snow cover were relatively high. The method can make full use of the acquired SAR image and multispectral image under emergency conditions, and the application potential of Sentinel data in the field of snow cover mapping is exploited. The monitoring frequency can be ensured because the areas obscured by thick clouds are remedied in the monitoring results. The Kappa coefficient of the monitoring results is 0.946, and the data processing time is less than 2 h, which meet the requirements of disaster emergency monitoring.

Relating C-band Microwave and Optical Satellite Observations as A Function of Snow Thickness on First-Year Sea Ice during the Winter to Summer Transition

NASA Astrophysics Data System (ADS)

Zheng, J.; Yackel, J.

2015-12-01

The Arctic sea ice and its snow cover have a direct impact on both the Arctic and global climate system through their ability to moderate heat exchange across the ocean-sea ice-atmosphere (OSA) interface. Snow cover plays a key role in the OSA interface radiation and energy exchange, as it controls the growth and decay of first-year sea ice (FYI). However, meteoric accumulation and redistribution of snow on FYI is highly stochastic over space and time, which makes it poorly understood. Previous studies have estimated local-scale snow thickness distributions using in-situ technique and modelling but it is spatially limited and challenging due to logistic difficulties. Moreover, snow albedo is also critical for determining the surface energy balance of the OSA during the critical summer ablation season. Even then, due to persistent and widespread cloud cover in the Arctic at various spatio-temporal scales, it is difficult and unreliable to remotely measure albedo of snow cover on FYI in the optical spectrum. Previous studies demonstrate that only large-scale sea ice albedo was successfully estimated using optical-satellite sensors. However, space-borne microwave sensors, with their capability of all-weather and 24-hour imaging, can provide enhanced information about snow cover on FYI. Daily spaceborne C-band scatterometer data (ASCAT) and MODIS data are used to investigate the the seasonal co-evolution of the microwave backscatter coefficient and optical albedo as a function of snow thickness on smooth FYI. The research focuses on snow-covered FYI near Cambridge Bay, Nunavut (Fig.1) during the winter to advanced-melt period (April-June, 2014). The ACSAT time series (Fig.2) show distinct increase in scattering at melt onset indicating the first occurrence of melt water in the snow cover. The corresponding albedo exhibits no decrease at this stage. We show how the standard deviation of ASCAT backscatter on FYI during winter can be used as a proxy for surface roughness and subsequent snow thickness (ie. Rougher surfaces acquire thicker snow covers) and then how this surface manifests into statistically distinguishable surface melt pond fractions which largely governs the optical derived albedo. Such relationships are useful for modelling the subsequent summer melt pond fraction and albedo from winter snow cover.

The GLAS Science Algorithm Software (GSAS) Detailed Design Document Version 6. Volume 16

NASA Technical Reports Server (NTRS)

Lee, Jeffrey E.

2013-01-01

The Geoscience Laser Altimeter System (GLAS) is the primary instrument for the ICESat (Ice, Cloud and Land Elevation Satellite) laser altimetry mission. ICESat was the benchmark Earth Observing System (EOS) mission for measuring ice sheet mass balance, cloud and aerosol heights, as well as land topography and vegetation characteristics. From 2003 to 2009, the ICESat mission provided multi-year elevation data needed to determine ice sheet mass balance as well as cloud property information, especially for stratospheric clouds common over polar areas. It also provided topography and vegetation data around the globe, in addition to the polar-specific coverage over the Greenland and Antarctic ice sheets.This document describes the detailed design of GLAS Science Algorithm Software (GSAS). The GSAS is used to create the ICESat GLAS standard data products. The National Snow and Ice Data Center (NSDIC) distribute these products. The document contains descriptions, flow charts, data flow diagrams, and structure charts for each major component of the GSAS. The purpose of this document is to present the detailed design of the GSAS. It is intended as a reference source to assist the maintenance programmer in making changes that fix or enhance the documented software.

Effects of bubbles, cracks, and volcanic tephra on the spectral albedo of bare ice near the Transantarctic Mountains: Implications for sea glaciers on Snowball Earth

NASA Astrophysics Data System (ADS)

Dadic, Ruzica; Mullen, Peter C.; Schneebeli, Martin; Brandt, Richard E.; Warren, Stephen G.

2013-09-01

Spectral albedo was measured along a 6 km transect near the Allan Hills in East Antarctica. The transect traversed the sequence from new snow through old snow, firn, and white ice, to blue ice, showing a systematic progression of decreasing albedo at all wavelengths, as well as decreasing specific surface area (SSA) and increasing density. Broadband albedos under clear-sky range from 0.80 for snow to 0.57 for blue ice, and from 0.87 to 0.65 under cloud. Both air bubbles and cracks scatter sunlight; their contributions to SSA were determined by microcomputed tomography on core samples of the ice. Although albedo is governed primarily by the SSA (and secondarily by the shape) of bubbles or snow grains, albedo also correlates highly with porosity, which, as a proxy variable, would be easier for ice sheet models to predict than bubble sizes. Albedo parameterizations are therefore developed as a function of density for three broad wavelength bands commonly used in general circulation models: visible, near-infrared, and total solar. Relevance to Snowball Earth events derives from the likelihood that sublimation of equatorward-flowing sea glaciers during those events progressively exposed the same sequence of surface materials that we measured at Allan Hills, with our short 6 km transect representing a transect across many degrees of latitude on the Snowball ocean. At the equator of Snowball Earth, climate models predict thick ice, or thin ice, or open water, depending largely on their albedo parameterizations; our measured albedos appear to be within the range that favors ice hundreds of meters thick.

Cloud Masking and Surface Temperature Distribution in the Polar Regions Using AVHRR and other Satellite Data

NASA Technical Reports Server (NTRS)

Comiso, Joey C.

1995-01-01

Surface temperature is one of the key variables associated with weather and climate. Accurate measurements of surface air temperatures are routinely made in meteorological stations around the world. Also, satellite data have been used to produce synoptic global temperature distributions. However, not much attention has been paid on temperature distributions in the polar regions. In the polar regions, the number of stations is very sparse. Because of adverse weather conditions and general inaccessibility, surface field measurements are also limited. Furthermore, accurate retrievals from satellite data in the region have been difficult to make because of persistent cloudiness and ambiguities in the discrimination of clouds from snow or ice. Surface temperature observations are required in the polar regions for air-sea-ice interaction studies, especially in the calculation of heat, salinity, and humidity fluxes. They are also useful in identifying areas of melt or meltponding within the sea ice pack and the ice sheets and in the calculation of emissivities of these surfaces. Moreover, the polar regions are unique in that they are the sites of temperature extremes, the location of which is difficult to identify without a global monitoring system. Furthermore, the regions may provide an early signal to a potential climate change because such signal is expected to be amplified in the region due to feedback effects. In cloud free areas, the thermal channels from infrared systems provide surface temperatures at relatively good accuracies. Previous capabilities include the use of the Temperature Humidity Infrared Radiometer (THIR) onboard the Nimbus-7 satellite which was launched in 1978. Current capabilities include the use of the Advance Very High Resolution Radiometer (AVHRR) aboard NOAA satellites. Together, these two systems cover a span of 16 years of thermal infrared data. Techniques for retrieving surface temperatures with these sensors in the polar regions have been developed. Errors have been estimated to range from 1K to 5K mainly due to cloud masking problems. With many additional channels available, it is expected that the EOS-Moderate Resolution Imaging Spectroradiometer (MODIS) will provide an improved characterization of clouds and a good discrimination of clouds from snow or ice surfaces.

Light-absorbing Particles in Snow and Ice: Measurement and Modeling of Climatic and Hydrological Impact

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qian, Yun; Yasunari, Teppei J.; Doherty, Sarah J.

2015-01-01

Light absorbing particles (LAP, e.g., black carbon, brown carbon, and dust) influence water and energy budgets of the atmosphere and snowpack in multiple ways. In addition to their effects associated with atmospheric heating by absorption of solar radiation and interactions with clouds, LAP in snow on land and ice can reduce the surface reflectance (a.k.a., surface darkening), which is likely to accelerate the snow aging process and further reduces snow albedo and increases the speed of snowpack melt. LAP in snow and ice (LAPSI) has been identified as one of major forcings affecting climate change, e.g. in the fourth andmore » fifth assessment reports of IPCC. However, the uncertainty level in quantifying this effect remains very high. In this review paper, we document various technical methods of measuring LAPSI and review the progress made in measuring the LAPSI in Arctic, Tibetan Plateau and other mid-latitude regions. We also report the progress in modeling the mass concentrations, albedo reduction, radiative forcing, andclimatic and hydrological impact of LAPSI at global and regional scales. Finally we identify some research needs for reducing the uncertainties in the impact of LAPSI on global and regional climate and the hydrological cycle.« less

The impact of snow and glaciers on meteorological variables in the Khumbu Valley, Nepalese Himalaya.

NASA Astrophysics Data System (ADS)

Potter, E.; Orr, A.; Willis, I.

2017-12-01

Previous observational studies have suggested that snow and glaciers have a big impact on local meteorological variables in the Himalayas, in particular affecting near surface temperature and the localised wind system. Understanding the impact of changing surface conditions on these systems and is crucial in improving future predictions of glacier melt and precipitation in the Himalayas. However, the mechanisms that control the local meteorology remain poorly understood due to the lack of in-situ data and detailed modelling studies. To investigate these mechanisms, we run the Weather Research and Forecasting (WRF) model at kilometre scale resolution for one month during the monsoon over the Khumbu Valley, Nepalese Himalaya. The model is run with and without snow and glacier coverage at the surface. The impact of adding debris cover into the model is also investigated. In the control run with snow and ice, thermally-driven near-surface winds are found to travel up valley during the day except over the glacier slopes. When the snow and ice is removed from the model, the up valley winds extend over the entire slope. Removal of the snow and ice also results in changes to cloud cover and hydrometeors. A momentum budget approach is used to fully understand the mechanisms that maintain the localised wind system, e.g. to determine the contributions from local forcing or synoptic forcing.

Earth Observing System (EOS) Snow and Ice Products for Observation and Modeling

NASA Technical Reports Server (NTRS)

Hall, D.; Kaminski, M.; Cavalieri, D.; Dickinson, R.; Marquis, M.; Riggs, G.; Robinson, D.; VanWoert, M.; Wolfe, R.

2005-01-01

Snow and ice are the key components of the Earth's cryosphere, and their influence on the Earth's energy balance is very significant due at least in part to the large areal extent and high albedo characterizing these features. Large changes in the cryosphere have been measured over the last century and especially over the past decade, and remote sensing plays a pivotal role in documenting these changes. Many of NASA's Earth Observing System (EOS) products derived from instruments on the Terra, Aqua, and Ice, Cloud and land Elevation Satellite (ICESat) satellites are useful for measuring changes in features that are associated with climate change. The utility of the products is continually enhanced as the length of the time series increases. To gain a more coherent view of the cryosphere and its historical and recent changes, the EOS products may be employed together, in conjunction with other sources of data, and in models. To further this goal, the first EOS Snow and Ice Products Workshop was convened. The specific goals of the workshop were to provide current and prospective users of EOS snow and ice products up-to-date information on the products, their validation status and future enhancements, to help users utilize the data products through hands-on demonstrations, and to facilitate the integration of EOS products into models. Oral and poster sessions representing a wide variety of snow and ice topics were held; three panels were also convened to discuss workshop themes. Panel discussions focused on data fusion and assimilation of the products into models. Approximately 110 people attended, representing a wide array of interests and organizations in the cryospheric community.

Impacts of Subgrid Heterogeneous Mixing between Cloud Liquid and Ice on the Wegner-Bergeron-Findeisen Process and Mixed-phase Clouds in NCAR CAM5

NASA Astrophysics Data System (ADS)

Liu, X.; Zhang, M.; Zhang, D.; Wang, Z.; Wang, Y.

2017-12-01

Mixed-phase clouds are persistently observed over the Arctic and the phase partitioning between cloud liquid and ice hydrometeors in mixed-phase clouds has important impacts on the surface energy budget and Arctic climate. In this study, we test the NCAR Community Atmosphere Model Version 5 (CAM5) with the single-column and weather forecast configurations and evaluate the model performance against observation data from the DOE Atmospheric Radiation Measurement (ARM) Program's M-PACE field campaign in October 2004 and long-term ground-based multi-sensor remote sensing measurements. Like most global climate models, we find that CAM5 also poorly simulates the phase partitioning in mixed-phase clouds by significantly underestimating the cloud liquid water content. Assuming pocket structures in the distribution of cloud liquid and ice in mixed-phase clouds as suggested by in situ observations provides a plausible solution to improve the model performance by reducing the Wegner-Bergeron-Findeisen (WBF) process rate. In this study, the modification of the WBF process in the CAM5 model has been achieved with applying a stochastic perturbation to the time scale of the WBF process relevant to both ice and snow to account for the heterogeneous mixture of cloud liquid and ice. Our results show that this modification of WBF process improves the modeled phase partitioning in the mixed-phase clouds. The seasonal variation of mixed-phase cloud properties is also better reproduced in the model in comparison with the long-term ground-based remote sensing observations. Furthermore, the phase partitioning is insensitive to the reassignment time step of perturbations.

Testing ice microphysics parameterizations in the NCAR Community Atmospheric Model Version 3 using Tropical Warm Pool-International Cloud Experiment data

DOE PAGES

Wang, Weiguo; Liu, Xiaohong; Xie, Shaocheng; ...

2009-07-23

Here, cloud properties have been simulated with a new double-moment microphysics scheme under the framework of the single-column version of NCAR Community Atmospheric Model version 3 (CAM3). For comparison, the same simulation was made with the standard single-moment microphysics scheme of CAM3. Results from both simulations compared favorably with observations during the Tropical Warm Pool–International Cloud Experiment by the U.S. Department of Energy Atmospheric Radiation Measurement Program in terms of the temporal variation and vertical distribution of cloud fraction and cloud condensate. Major differences between the two simulations are in the magnitude and distribution of ice water content within themore » mixed-phase cloud during the monsoon period, though the total frozen water (snow plus ice) contents are similar. The ice mass content in the mixed-phase cloud from the new scheme is larger than that from the standard scheme, and ice water content extends 2 km further downward, which is in better agreement with observations. The dependence of the frozen water mass fraction on temperature from the new scheme is also in better agreement with available observations. Outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) from the simulation with the new scheme is, in general, larger than that with the standard scheme, while the surface downward longwave radiation is similar. Sensitivity tests suggest that different treatments of the ice crystal effective radius contribute significantly to the difference in the calculations of TOA OLR, in addition to cloud water path. Numerical experiments show that cloud properties in the new scheme can respond reasonably to changes in the concentration of aerosols and emphasize the importance of correctly simulating aerosol effects in climate models for aerosol-cloud interactions. Further evaluation, especially for ice cloud properties based on in-situ data, is needed.« less

Evaluation of Cloud-resolving and Limited Area Model Intercomparison Simulations using TWP-ICE Observations. Part 1: Deep Convective Updraft Properties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Varble, A. C.; Zipser, Edward J.; Fridlind, Ann

2014-12-27

Ten 3D cloud-resolving model (CRM) simulations and four 3D limited area model (LAM) simulations of an intense mesoscale convective system observed on January 23-24, 2006 during the Tropical Warm Pool – International Cloud Experiment (TWP-ICE) are compared with each other and with observed radar reflectivity fields and dual-Doppler retrievals of vertical wind speeds in an attempt to explain published results showing a high bias in simulated convective radar reflectivity aloft. This high bias results from ice water content being large, which is a product of large, strong convective updrafts, although hydrometeor size distribution assumptions modulate the size of this bias.more » Snow reflectivity can exceed 40 dBZ in a two-moment scheme when a constant bulk density of 100 kg m-3 is used. Making snow mass more realistically proportional to area rather than volume should somewhat alleviate this problem. Graupel, unlike snow, produces high biased reflectivity in all simulations. This is associated with large amounts of liquid water above the freezing level in updraft cores. Peak vertical velocities in deep convective updrafts are greater than dual-Doppler retrieved values, especially in the upper troposphere. Freezing of large rainwater contents lofted above the freezing level in simulated updraft cores greatly contributes to these excessive upper tropospheric vertical velocities. Strong simulated updraft cores are nearly undiluted, with some showing supercell characteristics. Decreasing horizontal grid spacing from 900 meters to 100 meters weakens strong updrafts, but not enough to match observational retrievals. Therefore, overly intense simulated updrafts may partly be a product of interactions between convective dynamics, parameterized microphysics, and large-scale environmental biases that promote different convective modes and strengths than observed.« less

The defective nature of ice Ic and its implications for atmospheric science

NASA Astrophysics Data System (ADS)

Kuhs, W. F.; Hansen, T. C.

2009-04-01

The possible atmospheric implication of ice Ic (cubic ice) has already been suggested some time ago in the context of snow crystal formation [1]. New findings from air-borne measurements in cirrus clouds and contrails have put ice Ic into the focus of interest to understand the so-called "supersaturation puzzle" [2,3,4,5]. Our recent microstructural work on ice Ic [6,7] appears to be highly relevant in this context. We have found that ice Ic is characterized by a complex stacking fault pattern, which changes as a function of temperature as well as time. Indeed, from our own [8] and other group's work [9] one knows that (in contrast to earlier believe) ice Ic can form up to temperatures at least as high as 240K - thus in the relevant range for cirrus clouds. We have good preliminary evidence that the "cubicity" (which can be related to stacking fault probabilities) as well as the particle size of ice Ic are the relevant parameters for this correlation. The "cubicity" of stacking faulty ice Ic (established by diffraction) correlates nicely with the increased supersaturation at decreasing temperatures observed in cirrus clouds and contrails, a fact, which may be considered as further evidence for the presence of ice Ic. Moreover, the stacking faults lead to kinks in the outer shapes of the minute ice Ic crystals as seen by cryo scanning electron microscopy (cryo-SEM); these defective sites are likely to play some role in heterogeneous reactions in the atmosphere. The cryo-SEM work suggests that stacking-faulty ice Ic has many more active centres for such reactions than the usually considered thermodynamically stable form, ice Ih. [1] T Kobayashi & T Kuroda (1987) Snow Crystals. In: Morphology of Crystals (ed. I Sunagawa), Terra Scientific Publishing, Tokyo, pp.649-743. [2] DM Murphy (2003) Dehydration in cold clouds is enhanced by a transition from from cubic to hexagonal ice. Geophys.Res.Lett.,30, 2230, doi:10.1029/2003GL018566. [3] RS Gao & 19 other authors (2004) Evidence that nitric acid increases relative humidity in low-temperature cirrus clouds. Science 303, 516-520. [4] T Peter, C Marcolli, P Spaichinger, T Corti, MC Baker & T Koop (2006) When dry air is too humid. Science 314, 1399-1402. [5] JE Shilling, MA Tolbert, OB Toon, EJ Jensen, BJ Murray & AK Bertram (2006) Measurements of the vapor pressure of cubic ice and their implications for atmospheric ice clouds. Geophys.Res.Lett. 33, 026671. [6] TC Hansen, MM Koza & WF Kuhs (2008) Formation and annealing of cubic ice: I Modelling of stacking faults. J.Phys.Cond.Matt. 20, 285104. [7] TC Hansen, MM Koza, P Lindner & WF Kuhs (2008) Formation and annealing of cubic ice: II. Kinetic study. J.Phys.Cond.Matt. 20, 285105. [8] WF Kuhs, G Genov, DK Staykova & AN Salamatin (2004) Ice perfection and the onset of anomalous preservation of gas hydrates. Phys.Chem.Chem.Phys. 6, 4917-4920. [9] BJ Murray, DA Knopf & AK Bertram (2005) The formation of cubic ice under conditions relevant to Earth's atmosphere. Nature 434, 292-205.

Evaluation of cloud-resolving and limited area model intercomparison simulations using TWP-ICE observations: 1. Deep convective updraft properties: Eval. of TWP-ICE CRMs and LAMs Pt. 1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Varble, Adam; Zipser, Edward J.; Fridlind, Ann M.

2014-12-18

Ten 3D cloud-resolving model (CRM) simulations and four 3D limited area model (LAM) simulations of an intense mesoscale convective system observed on 23-24 January 2006 during the Tropical Warm Pool – International Cloud Experiment (TWP-ICE) are compared with each other and with observed radar reflectivity fields and dual-Doppler retrievals of vertical wind speeds in an attempt to explain published results showing a high bias in simulated convective radar reflectivity aloft. This high bias results from ice water content being large, which is a product of large, strong convective updrafts, although hydrometeor size distribution assumptions modulate the size of this bias.more » Making snow mass more realistically proportional to D2 rather than D3 eliminates unrealistically large snow reflectivities over 40 dBZ in some simulations. Graupel, unlike snow, produces high biased reflectivity in all simulations, which is partly a result of parameterized microphysics, but also partly a result of overly intense simulated updrafts. Peak vertical velocities in deep convective updrafts are greater than dual-Doppler retrieved values, especially in the upper troposphere. Freezing of liquid condensate, often rain, lofted above the freezing level in simulated updraft cores greatly contributes to these excessive upper tropospheric vertical velocities. The strongest simulated updraft cores are nearly undiluted, with some of the strongest showing supercell characteristics during the multicellular (pre-squall) stage of the event. Decreasing horizontal grid spacing from 900 to 100 meters slightly weakens deep updraft vertical velocity and moderately decreases the amount of condensate aloft, but not enough to match observational retrievals. Therefore, overly intense simulated updrafts may additionally be a product of unrealistic interactions between convective dynamics, parameterized microphysics, and the large-scale model forcing that promote different convective strengths than observed.« less

Snow-borne nanosized particles: Abundance, distribution, composition, and significance in ice nucleation processes

NASA Astrophysics Data System (ADS)

Rangel-Alvarado, Rodrigo Benjamin; Nazarenko, Yevgen; Ariya, Parisa A.

2015-11-01

Physicochemical processes of nucleation constitute a major uncertainty in understanding aerosol-cloud interactions. To improve the knowledge of the ice nucleation process, we characterized physical, chemical, and biological properties of fresh snow using a suite of state-of-the-art techniques based on mass spectrometry, electron microscopy, chromatography, and optical particle sizing. Samples were collected at two North American Arctic sites, as part of international campaigns (2006 and 2009), and in the city of Montreal, Canada, over the last decade. Particle size distribution analyses, in the range of 3 nm to 10 µm, showed that nanosized particles are the most numerous (38-71%) in fresh snow, with a significant portion (11 to 19%) less than 100 nm in size. Particles with diameters less than 200 nm consistently exhibited relatively high ice-nucleating properties (on average ranged from -19.6 ± 2.4 to -8.1 ± 2.6°C). Chemical analysis of the nanosized fraction suggests that they contain bioorganic materials, such as amino acids, as well as inorganic compounds with similar characteristics to mineral dust. The implication of nanoparticle ubiquity and abundance in diverse snow ecosystems are discussed in the context of their importance in understanding atmospheric nucleation processes.

Percentage Contributions from Atmospheric and Surface Features to Computed Brightness Temperatures

NASA Technical Reports Server (NTRS)

Jackson, Gail Skofronick

2006-01-01

Over the past few years, there has become an increasing interest in the use of millimeter-wave (mm-wave) and sub-millimeter-wave (submm-wave) radiometer observations to investigate the properties of ice particles in clouds. Passive radiometric channels respond to both the integrated particle mass throughout the volume and field of view, and to the amount, location, and size distribution of the frozen (and liquid) particles with the sensitivity varying for different frequencies and hydrometeor types. One methodology used since the 1960's to discern the relationship between the physical state observed and the brightness temperature (TB) is through the temperature weighting function profile. In this research, the temperature weighting function concept is exploited to analyze the sensitivity of various characteristics of the cloud profile, such as relative humidity, ice water path, liquid water path, and surface emissivity. In our numerical analysis, we compute the contribution (in Kelvin) from each of these cloud and surface characteristics, so that the sum of these various parts equals the computed TB. Furthermore, the percentage contribution from each of these characteristics is assessed. There is some intermingling/contamination of the contributions from various components due to the integrated nature of passive observations and the absorption and scattering between the vertical layers, but all in all the knowledge gained is useful. This investigation probes the sensitivity over several cloud classifications, such as cirrus, blizzards, light snow, anvil clouds, and heavy rain. The focus is on mm-wave and submm-wave frequencies, however discussions of the effects of cloud variations to frequencies as low as 10 GHz and up to 874 GHz will also be presented. The results show that nearly 60% of the TB value at 89 GHz comes from the earth's surface for even the heaviest blizzard snow rates. On the other hand, a significant percentage of the TB value comes from the snow in the cloud for 166, and 183 plus or minus 7 GHz for the heavy and medium snow rates. For submm-wave channels, there is no contribution from the surface because these channels cannot probe through clouds, nor normal water vapor amounts in clear air regions. This work is extremely valuable in physically-based retrieval algorithm development research.

Towards a new parameterization of ice particles growth

NASA Astrophysics Data System (ADS)

Krakovska, Svitlana; Khotyayintsev, Volodymyr; Bardakov, Roman; Shpyg, Vitaliy

2017-04-01

Ice particles are the main component of polar clouds, unlike in warmer regions. That is why correct representation of ice particle formation and growth in NWP and other numerical atmospheric models is crucial for understanding of the whole chain of water transformation, including precipitation formation and its further deposition as snow in polar glaciers. Currently, parameterization of ice in atmospheric models is among the most difficult challenges. In the presented research, we present a renewed theoretical analysis of the evolution of mixed cloud or cold fog from the moment of ice nuclei activation until complete crystallization. The simplified model is proposed that includes both supercooled cloud droplets and initially uniform particles of ice, as well as water vapor. We obtain independent dimensionless input parameters of a cloud, and find main scenarios and stages of evolution of the microphysical state of the cloud. The characteristic times and particle sizes have been found, as well as the peculiarities of microphysical processes at each stage of evolution. In the future, the proposed original and physically grounded approximations may serve as a basis for a new scientifically substantiated and numerically efficient parameterizations of microphysical processes in mixed clouds for modern atmospheric models. The relevance of theoretical analysis is confirmed by numerical modeling for a wide range of combinations of possible conditions in the atmosphere, including cold polar regions. The main conclusion of the research is that until complete disappearance of cloud droplets, the growth of ice particles occurs at a practically constant humidity corresponding to the saturated humidity over water, regardless to all other parameters of a cloud. This process can be described by the one differential equation of the first order. Moreover, a dimensionless parameter has been proposed as a quantitative criterion of a transition from dominant depositional to intense collectional growth of ice particles; it could be used in models with bulk parameterization of cloud and precipitation formation processes.

The time-dependence of the defective nature of ice Ic (cubic ice) and its implications for atmospheric science

NASA Astrophysics Data System (ADS)

Sippel, Christian; Koza, Michael M.; Hansen, Thomas C.; Kuhs, Werner F.

2010-05-01

The possible atmospheric implication of ice Ic (cubic ice) has already been suggested some time ago in the context of snow crystal formation [1]. New findings from air-borne measurements in cirrus clouds and contrails have put ice Ic into the focus of interest to understand the so-called "supersaturation puzzle" [2,3,4]. Our recent microstructural work on ice Ic [5,6] appears to be highly relevant in this context. We have found that ice Ic is characterized by a complex stacking fault pattern, which changes as a function of temperature as well as time. Indeed, from our own [7] and other group's work [8] one knows that (in contrast to earlier believe) ice Ic can form up to temperatures at least as high as 240K - thus in the relevant range for cirrus clouds. We have good preliminary evidence that the "cubicity" (which can be related to stacking fault probabilities) as well as the particle size of ice Ic are the relevant parameters for this correlation. The "cubicity" of stacking faulty ice Ic (established by diffraction) correlates nicely with the increased supersaturation at decreasing temperatures observed in cirrus clouds and contrails, a fact, which may be considered as further evidence for the presence of ice Ic. Recently, we have studied the time-dependency of the changes in both "cubicity" and particle size at various temperatures of relevance for cirrus clouds and contrails by in-situ neutron powder diffraction. The timescales over which changes occur (several to many hours) are similar to the life-time of cirrus clouds and contrails and suggest that the supersaturation situation may change within this time span in the natural environment too. Some accompanying results obtained by cryo-SEM (scanning electron microscopy) work will also be presented and suggest that stacking-faulty ice Ic has kinky surfaces providing many more active centres for heterogeneous reactions on the surface than in the usually assumed stable hexagonal form of ice Ih with its rather flat low-indexed crystal faces. [1] T Kobayashi & T Kuroda (1987) Snow Crystals. In: Morphology of Crystals (ed. I Sunagawa), Terra Scientific Publishing, Tokyo, pp.649-743. [2] RS Gao & 19 other authors (2004) Evidence that nitric acid increases relative humidity in low-temperature cirrus clouds. Science 303, 516-520. [3] T Peter, C Marcolli, P Spichtinger, T Corti, MC Baker & T Koop (2006) When dry air is too humid. Science 314, 1399-1402. [4] JE Shilling, MA Tolbert, OB Toon, EJ Jensen, BJ Murray & AK Bertram (2006) Measurements of the vapor pressure of cubic ice and their implications for atmospheric ice clouds. Geophys.Res.Lett. 33, 026671. [5] TC Hansen, MM Koza & WF Kuhs (2008) Formation and annealing of cubic ice: I Modelling of stacking faults. J.Phys.Cond.Matt. 20, 285104. [6] TC Hansen, MM Koza, P Lindner & WF Kuhs (2008) Formation and annealing of cubic ice: II. Kinetic study. J.Phys.Cond.Matt. 20, 285105. [7] WF Kuhs, G Genov, DK Staykova & AN Salamatin, T Hansen (2004) Ice perfection and the onset of anomalous preservation of gas hydrates. Phys.Chem.Chem.Phys. 6, 4917-4920. [8] BJ Murray, DA Knopf & AK Bertram (2005) The formation of cubic ice under conditions relevant to Earth's atmosphere. Nature 434, 292-205.

Evaluation of the SMAP model calculated snow albedo at the SIGMA-A site, northwest Greenland, during the 2012 record surface melt event

NASA Astrophysics Data System (ADS)

Niwano, M.; Aoki, T.; Matoba, S.; Yamaguchi, S.; Tanikawa, T.; Kuchiki, K.; Motoyama, H.

2015-12-01

The snow and ice on the Greenland ice sheet (GrIS) experienced the extreme surface melt around 12 July, 2012. In order to understand the snow-atmosphere interaction during the period, we applied a physical snowpack model SMAP to the GrIS snowpack. In the SMAP model, the snow albedo is calculated by the PBSAM component explicitly considering effects of snow grain size and light-absorbing snow impurities such as black carbon and dust. Temporal evolution of snow grain size is calculated internally in the SMAP model, whereas mass concentrations of snow impurities are externally given from observations. In the PBSAM, the (shortwave) snow albedo is calculated from a weighted summation of visible albedo (primarily affected by snow impurities) and near-infrared albedo (mainly controlled by snow grain size). The weights for these albedos are the visible and near-infrared fractions of the downward shortwave radiant flux. The SMAP model forced by meteorological data obtained from an automated weather station at SIGMA-A site, northwest GrIS during 30 June to 14 July, 2012　(IOP) was evaluated in terms of surface (optically equivalent) snow grain size and snow albedo. Snow grain size simulated by the model was compared against that retrieved from in-situ spectral albedo measurements. Although the RMSE and ME were reasonable (0.21 mm and 0.17 mm, respectively), the small snow grain size associated with the surface hoar could not be simulated by the SMAP model. As for snow albedo, simulation results agreed well with observations throughout the IOP (RMSE was 0.022 and ME was 0.008). Under cloudy-sky conditions, the SMAP model reproduced observed rapid increase in the snow albedo. When cloud cover is present the near-infrared fraction of the downward shortwave radiant flux is decreased, while it is increased under clear-sky conditions. Therefore, the above mentioned performance of the SMAP model can be attributed to the PBSAM component driven by the observed near-infrared and visible fractions of the downward shortwave radiant flux. This result suggests that it is necessary for snowpack models to consider changes in the visible and near-infrared fractions of the downward shortwave radiant flux caused by the presence of cloud cover to reproduce realistic temporal changes in the snow albedo and consequently the surface energy balance.

Estimation of ice activation parameters within a particle tracking Lagrangian cloud model using the ensemble Kalman filter to match ISCDAC golden case observations

NASA Astrophysics Data System (ADS)

Reisner, J. M.; Dubey, M. K.

2010-12-01

To both quantify and reduce uncertainty in ice activation parameterizations for stratus clouds occurring in the temperature range between -5 to -10 C ensemble simulations of an ISDAC golden case have been conducted. To formulate the ensemble, three parameters found within an ice activation model have been sampled using a Latin hypercube technique over a parameter range that induces large variability in both number and mass of ice. The ice activation model is contained within a Lagrangian cloud model that simulates particle number as a function of radius for cloud ice, snow, graupel, cloud, and rain particles. A unique aspect of this model is that it produces very low levels of numerical diffusion that enable the model to accurately resolve the sharp cloud edges associated with the ISDAC stratus deck. Another important aspect of the model is that near the cloud edges the number of particles can be significantly increased to reduce sampling errors and accurately resolve physical processes such as collision-coalescence that occur in this region. Thus, given these relatively low numerical errors, as compared to traditional bin models, the sensitivity of a stratus deck to changes in parameters found within the activation model can be examined without fear of numerical contamination. Likewise, once the ensemble has been completed, ISDAC observations can be incorporated into a Kalman filter to optimally estimate the ice activation parameters and reduce overall model uncertainty. Hence, this work will highlight the ability of an ensemble Kalman filter system coupled to a highly accurate numerical model to estimate important parameters found within microphysical parameterizations containing high uncertainty.

The Modification of Orographic Snow Growth Processes by Cloud Nucleating Aerosols

NASA Astrophysics Data System (ADS)

Cotton, W. R.; Saleeby, S.

2011-12-01

Cloud nucleating aerosols have been found to modify the amount and spatial distribution of snowfall in mountainous areas where riming growth of snow crystals is known to contribute substantially to the total snow water equivalent precipitation. In the Park Range of Colorado, a 2km deep supercooled liquid water orographic cloud frequently enshrouds the mountaintop during snowfall events. This leads to a seeder-feeder growth regime in which snow falls through the orographic cloud and collects cloud water prior to surface deposition. The addition of higher concentrations of cloud condensation nuclei (CCN) modifies the cloud droplet spectrum toward smaller size droplets and suppresses riming growth. Without rime growth, the density of snow crystals remains low and horizontal trajectories carry them further downwind due to slower vertical fall speeds. This leads to a downwind shift in snowfall accumulation at high CCN concentrations. Cloud resolving model simulations were performed (at 600m horizontal grid spacing) for six snowfall events over the Park Range. The chosen events were well simulated and occurred during intensive observations periods as part of two winter field campaigns in 2007 and 2010 based at Storm Peak Laboratory in Steamboat Springs, CO. For each event, sensitivity simulations were run with various initial CCN concentration vertical profiles that represent clean to polluted aerosol environments. Microphysical budget analyses were performed for these simulations in order to determine the relative importance of the various cloud properties and growth processes that contribute to precipitation production. Observations and modeling results indicate that initial vapor depositional growth of snow tends to be maximized within about 1km of mountaintop above the windward slope while the majority of riming growth occurs within 500m of mountaintop. This suggests that precipitation production is predominantly driven by locally enhanced orography. The large scale synoptic flow simply provides the background dynamics and moisture that impinge upon the steep terrain. The addition of cloud nucleating aerosols to this scenario tends to reduce the amount of riming and leads to greater snow vapor growth. Increased vapor growth leads to larger snow crystals but does not necessarily increase their density or fall speed. There is frequently a zone on the periphery of the orographic cloud where water saturation is low and ice saturation remains high. Here the Bergeron process allows for snow to continue growing at the expense of the cloud water. Furthermore, since less cloud water is removed by riming, and droplets are smaller in polluted conditions, there is an increase in cloud water evaporation along the lee slope. This enhanced droplet evaporation in polluted conditions allows for more saturated air to persist to the lee of the ridge. Higher saturation reduces the amount of snow crystal sublimation prior to surface deposition. In very moist winter events, the lee slope evaporation relative to the primary mountain barrier can saturate the air relative to a downstream ridge and aid in further orographic cloud development. The combination of reduced riming, the Bergeron process, and reduced lee-side sublimation leads to the snowfall spillover effect under polluted conditions.

Nonspherical and Spherical Characterization of Ice in Hurricane Erin for Wideband Passive Microwave Comparisons

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail; Holthaus, Eric; Albers, Cerese; Kim, Min-Jeong

2007-01-01

In order to better understand the characteristics of frozen cloud particles in hurricane systems, computed brightness temperatures were compared with radiometric observations of Hurricane Erin (2001) from the NASA ER-2 aircraft. The focus was oil the frozen particle microphysics and the high frequencies (2 85 GHz) that are particularly sensitive to frozen particles. Frozen particles in hurricanes are an indicator of increasing hurricane intensity. In fact "hot towers" associated with increasing hurricane intensity are composed of frozen ice cloud particles. (They are called hot towers because their column of air is warmer than the surrounding air temperature, but above about 5-7 km to the tops of the towers at 15-19 km, the cloud particles are frozen.) This work showed that indeed, one can model information about cloud ice particle characteristics and indicated that nonspherical ice shapes, instead of spherical particles, provided the best match to the observations. Overall, this work shows that while non-spherical particles show promise, selecting and modeling a proper ice particle parameterization can be difficult and additional in situ measurements are needed to define and validate appropriate parameterizations. This work is important for developing Global Precipitation Measurement (GPM) mission satellite algorithms for the retrieval of ice characteristics both above the melting layer, as in Hurricane Erin, and for ice particles that reach the surface as falling snow.

Study of Tropospheric Ozone and UV Reflectivity Using TOMS Data

NASA Technical Reports Server (NTRS)

Yung, Yuk L.

2002-01-01

Perhaps the single most important result from the study of Chuang and Yung is that the interannual variability of the Earth's albedo (especially in Spring) on land is dominated by snow/ice, and not by clouds. This interannual variability could be the major driver of changes in the atmosphere and the biosphere. It is plausible that the interannual variability of snow/ice, through interactions with the atmosphere and biosphere, is responsible for the interannual variability of atmospheric CO2. By carefully studying the albedo variations off the Peru coast, we found evidence for indirect aerosol effect on clouds. Based on a detailed analysis of the cloud data obtained by the International Satellite Cloud Climatology Project (SCCP) in the years 1983-1991, we show that besides the reported 3 % variation in global cloudiness, the global mean cloud optical thickness (MCOT) also has significant variation which is out of phase with that of the global cloudiness. The combined effect of the two opposing variations may be a null effect on the cloud reflectivity. These results are consistent with the Total Ozone Mapping Spectrometer (TOMS) reflectively measurements. The MCOT variation is further shown to be correlated with both the solar cycle and the ENSO (El Nino Southern Oscillation) cycle. Our present analysis cannot distinguish which of the above two provides better correlation, although independent data from the High resolution Infrared Radiation Sounder (HIRS) from 1990 to 1996 favor the solar cycle. Future data are needed to identify the true cause of these changes.

Microphysical processing of aerosol particles in orographic clouds

NASA Astrophysics Data System (ADS)

Pousse-Nottelmann, S.; Zubler, E. M.; Lohmann, U.

2015-08-01

An explicit and detailed treatment of cloud-borne particles allowing for the consideration of aerosol cycling in clouds has been implemented into COSMO-Model, the regional weather forecast and climate model of the Consortium for Small-scale Modeling (COSMO). The effects of aerosol scavenging, cloud microphysical processing and regeneration upon cloud evaporation on the aerosol population and on subsequent cloud formation are investigated. For this, two-dimensional idealized simulations of moist flow over two bell-shaped mountains were carried out varying the treatment of aerosol scavenging and regeneration processes for a warm-phase and a mixed-phase orographic cloud. The results allowed us to identify different aerosol cycling mechanisms. In the simulated non-precipitating warm-phase cloud, aerosol mass is incorporated into cloud droplets by activation scavenging and released back to the atmosphere upon cloud droplet evaporation. In the mixed-phase cloud, a first cycle comprises cloud droplet activation and evaporation via the Wegener-Bergeron-Findeisen (WBF) process. A second cycle includes below-cloud scavenging by precipitating snow particles and snow sublimation and is connected to the first cycle via the riming process which transfers aerosol mass from cloud droplets to snowflakes. In the simulated mixed-phase cloud, only a negligible part of the total aerosol mass is incorporated into ice crystals. Sedimenting snowflakes reaching the surface remove aerosol mass from the atmosphere. The results show that aerosol processing and regeneration lead to a vertical redistribution of aerosol mass and number. Thereby, the processes impact the total aerosol number and mass and additionally alter the shape of the aerosol size distributions by enhancing the internally mixed/soluble Aitken and accumulation mode and generating coarse-mode particles. Concerning subsequent cloud formation at the second mountain, accounting for aerosol processing and regeneration increases the cloud droplet number concentration with possible implications for the ice crystal number concentration.

Advances in Understanding the Role of Frozen Precipitation in High Latitude Hydrology

NASA Astrophysics Data System (ADS)

L'Ecuyer, T. S.; Wood, N.; Smalley, M.; McIlhattan, E.; Kulie, M.

2017-12-01

Satellite-based millimeter wavelength radar observations provide a unique perspective on the global character of frozen precipitation that has been difficult to detect using conventional spaceborne precipitation sensors. This presentation will describe the methodology underpinning the ten-year CloudSat global snowfall product and discuss the results of a number of complementary approaches that have been adopted to quantify its uncertainties. These datasets are shedding new light on the distribution, character, and impacts of frozen precipitation on high latitude hydrology. Inferred regional snowfall accumulations, for example, provide valuable constraints on projected changes in precipitation and mass balance on the Antarctic ice sheet in climate models. When placed in the broader context of complementary observations from other A-Train sensors, instantaneous snowfall estimates also hint at the large-scale processes that influence snow formation including air-sea interactions associated with cold-air outbreaks, lake-effect snows, and orographic enhancement. Simultaneous CloudSat and CALIPSO observations further emphasize the important role snowfall plays in the lifetime of super-cooled liquid containing clouds in the Arctic and highlight a model deficiency with important implications for surface energy and mass balance on the Greenland ice sheet.

Uncertainty, Sensitivity Analysis, and Causal Identification in the Arctic using a Perturbed Parameter Ensemble of the HiLAT Climate Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hunke, Elizabeth Clare; Urrego Blanco, Jorge Rolando; Urban, Nathan Mark

Coupled climate models have a large number of input parameters that can affect output uncertainty. We conducted a sensitivity analysis of sea ice proper:es and Arc:c related climate variables to 5 parameters in the HiLAT climate model: air-ocean turbulent exchange parameter (C), conversion of water vapor to clouds (cldfrc_rhminl) and of ice crystals to snow (micro_mg_dcs), snow thermal conduc:vity (ksno), and maximum snow grain size (rsnw_mlt). We used an elementary effect (EE) approach to rank their importance for output uncertainty. EE is an extension of one-at-a-time sensitivity analyses, but it is more efficient in sampling multi-dimensional parameter spaces. We lookedmore » for emerging relationships among climate variables across the model ensemble, and used causal discovery algorithms to establish potential pathways for those relationships.« less

The effects of cloud inhomogeneities upon radiative fluxes, and the supply of a cloud truth validation dataset

NASA Technical Reports Server (NTRS)

1994-01-01

With the growing awareness and debate over the potential changes associated with global climate change, the polar regions are receiving increased attention. Global cloud distributions can be expected to be altered by increased greenhouse forcing. Owing to the similarity of cloud and snow-ice spectral signatures in both the visible and infrared wavelengths, it is difficult to distinguish clouds from surface features in the polar regions. This work is directed towards the development of algorithms for the ASTER and HIRIS science/instrument teams. Special emphasis is placed on a wide variety of cloud optical property retrievals, and especially retrievals of cloud and surface properties in the polar regions.

Investigations into the climate of the South Pole

NASA Astrophysics Data System (ADS)

Town, Michael S.

Four investigations into the climate of the South Pole are presented. The general subjects of polar cloud cover, the surface energy balance in a stable boundary layer, subsurface energy transfer in snow, and modification of water stable isotopes in snow after deposition are investigated based on the historical data set from the South Pole. Clouds over the South Pole. A new, accurate cloud fraction time series is developed based on downwelling infrared radiation measurements taken at the South Pole. The results are compared to cloud fraction estimates from visual observations and satellite retrievals of cloud fraction. Visual observers are found to underestimate monthly mean cloud fraction by as much as 20% during the winter, and satellite retrievals of cloud fraction are not accurate for operational or climatic purposes. We find associations of monthly mean cloud fraction with other meteorological variables at the South Pole for use in testing models of polar weather and climate. Surface energy balance. A re-examination of the surface energy balance at the South Pole is motivated by large discrepancies in the literature. We are not able to find closure in the new surface energy balance, likely due to weaknesses in the turbulent heat flux parameterizations in extremely stable boundary layers. These results will be useful for constraining our understanding and parameterization of stable boundary layers. Subsurface energy transfer. A finite-volume model of the snow is used to simulate nine years of near-surface snow temperatures, heating rates, and vapor pressures at the South Pole. We generate statistics characterizing heat and vapor transfer in the snow on submonthly to interannual time scales. The variability of near-surface snow temperatures on submonthly time scales is large, and has potential implications for revising the interpretation of paleoclimate records of water stable isotopes in polar snow. Modification of water stable isotopes after deposition. The evolution of water stable isotopes in near-surface polar snow is simulated using a Rayleigh fractionation model including the processes of pore-space diffusion, forced ventilation, and intra-ice-grain diffusion. We find isotopic enrichment of winter snow during subsequent summers as enriched water vapor is forced into the snow and deposits as frost. This process depends on snow and atmospheric temperatures, surface wind speed, accumulation rate, and surface morphology. We further find that differential enrichment between the present day and the Last Glacial Maximum (LGM) may exaggerate the greenlandic glacial-interglacial temperature difference derived from water stable isotopes. In Antarctica, present-day post-depositional modification is likely equal to that of the LGM due to the compensating factors of lower temperatures and lower accumulation rate during the LGM.

The GLAS Standard Data Products Specification--Level 2, Version 9. Volume 14

NASA Technical Reports Server (NTRS)

Lee, Jeffrey E.

2013-01-01

The Geoscience Laser Altimeter System (GLAS) is the primary instrument for the ICESat (Ice, Cloud and Land Elevation Satellite) laser altimetry mission. ICESat was the benchmark Earth Observing System (EOS) mission for measuring ice sheet mass balance, cloud and aerosol heights, as well as land topography and vegetation characteristics. From 2003 to 2009, the ICESat mission provided multi-year elevation data needed to determine ice sheet mass balance as well as cloud property information, especially for stratospheric clouds common over polar areas. It also provided topography and vegetation data around the globe, in addition to the polar-specific coverage over the Greenland and Antarctic ice sheets.This document defines the Level-2 GLAS standard data products. This document addresses the data flow, interfaces, record and data formats associated with the GLAS Level 2 standard data products. The term standard data products refers to those EOS instrument data that are routinely generated for public distribution. The National Snow and Ice Data Center (NSDIC) distribute these products. Each data product has a unique Product Identification code assigned by the Senior Project Scientist. The Level 2 Standard Data Products specifically include those derived geophysical data values (i.e., ice sheet elevation, cloud height, vegetation height, etc.). Additionally, the appropriate correction elements used to transform the Level 1A and Level 1B Data Products into Level 2 Data Products are included. The data are packaged with time tags, precision orbit location coordinates, and data quality and usage flags.

Drivers and environmental responses to the changing annual snow cycle of northern Alaska

USGS Publications Warehouse

Cox, Christopher J.; Stone, Robert S.; Douglas, David C.; Stanitski, Diane; Divoky, George J.; Dutton, Geoff S.; Sweeney, Colm; George, J. Craig; Longenecker, David U.

2017-01-01

On the North Slope of Alaska, earlier spring snowmelt and later onset of autumn snow accumulation are tied to atmospheric dynamics and sea ice conditions, and result in environmental responses.Linkages between atmospheric, ecological and biogeochemical variables in the changing Arctic are analyzed using long-term measurements near Utqiaġvik (formerly Barrow), Alaska. Two key variables are the date when snow disappears in spring, as determined primarily by atmospheric dynamics, precipitation, air temperature, winter snow accumulation and cloud cover, as well as the date of onset of snowpack in autumn that is additionally influenced by ocean temperature and sea ice extent. In 2015 and 2016 the snow melted early at Utqiaġvik due mainly to anomalous warmth during May of both years attributed to atmospheric circulation patterns, with 2016 having the record earliest snowmelt. These years are discussed in the context of a 115-year snowmelt record at Utqiaġvik with a trend toward earlier melting since the mid- 1970s (-2.86 days/decade, 1975-2016). At nearby Cooper Island, where a colony of seabirds, Black Guillemots, have been monitored since 1975, timing of egg laying is correlated with Utqiaġvik snowmelt with 2015 and 2016 being the earliest years in the 42-year record. Ice-out at a nearby freshwater lagoon is also correlated with Utqiaġvik snowmelt. The date when snow begins to accumulate in autumn at Utqiaġvik shows a trend towards later dates (+4.6 days/decade, 1975-2016), with 2016 the latest on record. The relationships between the lengthening snow-free season and regional phenology, soil temperatures, fluxes of gases from the tundra, and to regional sea ice conditions are discussed. Better understanding of these interactions is needed to predict the annual snow cycles in the region at seasonal to decadal scales, and to anticipate coupled environmental responses.

Ice sheet climate modeling: past achievements, ongoing challenges, and future endeavors

NASA Astrophysics Data System (ADS)

Lenaerts, J.

2017-12-01

Fluctuations in surface mass balance (SMB) mask out a substantial portion of contemporary Greenland and Antarctic ice sheet mass loss. That implies that we need accurate, consistent, and long-term SMB time series to isolate the mass loss signal. This in turn requires understanding of the processes driving SMB, and how they interplay. The primary controls on present-day ice sheet SMB are snowfall, which is regulated by large-scale atmospheric variability, and surface meltwater production at the ice sheet's edges, which is a complex result of atmosphere-surface interactions. Additionally, wind-driven snow redistribution and sublimation are large SMB contributors on the downslope areas of the ice sheets. Climate models provide an integrated framework to simulate all these individual ice sheet components. Recent developments in RACMO2, a regional climate model bound by atmospheric reanalyses, have focused on enhancing horizontal resolution, including blowing snow, snow albedo, and meltwater processes. Including these physics not only enhanced our understanding of the ice sheet climate system, but also enabled to obtain increasingly accurate estimates of ice sheet SMB. However, regional models are not suitable to capture the mutual interactions between ice sheet and the remainder of the global climate system in transient climates. To take that next step, global climate models are essential. In this talk, I will highlight our present work on improving ice sheet climate in the Community Earth System Model (CESM). In particular, we focus on an improved representation of polar firn, ice sheet clouds, and precipitation. For this exercise, we extensively use field observations, remote sensing data, as well as RACMO2. Next, I will highlight how CESM is used to enhance our understanding of ice sheet SMB, its drivers, and past and present changes.

A Comparison between Airborne and Mountaintop Cloud Microphysics

NASA Astrophysics Data System (ADS)

David, R.; Lowenthal, D. H.; Hallar, A. G.; McCubbin, I.; Avallone, L. M.; Mace, G. G.; Wang, Z.

2014-12-01

Complex terrain has a large impact on cloud dynamics and microphysics. Several studies have examined the microphysical details of orographically-enhanced clouds from either an aircraft or from a mountain top location. However, further research is needed to characterize the relationships between mountain top and airborne microphysical properties. During the winter of 2011, an airborne study, the Colorado Airborne Mixed-Phase Cloud Study (CAMPS), and a ground-based field campaign, the Storm Peak Lab (SPL) Cloud Property Validation Experiment (StormVEx) were conducted in the Park Range of the Colorado Rockies. The CAMPS study utilized the University of Wyoming King Air (UWKA) to provide airborne cloud microphysical and meteorological data on 29 flights totaling 98 flight hours over the Park Range from December 15, 2010 to February 28, 2011. The UWKA was equipped with instruments that measured both cloud droplet and ice crystal size distributions, liquid water content, total water content (vapor, liquid, and ice), and 3-dimensional wind speed and direction. The Wyoming Cloud Radar and Lidar were also deployed during the campaign. These measurements are used to characterize cloud structure upwind and above the Park Range. StormVEx measured cloud droplet, ice crystal, and aerosol size distributions at SPL, located on the west summit of Mt. Werner at 3220m MSL. The observations from SPL are used to determine mountain top cloud microphysical properties at elevations lower than the UWKA was able to sample in-situ. Comparisons showed that cloud microphysics aloft and at the surface were consistent with respect to snow growth processes while small crystal concentrations were routinely higher at the surface, suggesting ice nucleation near cloud base. The effects of aerosol concentrations and upwind stability on mountain top and downwind microphysics are considered.

Comparing modelled and measured ice crystal concentrations in orographic clouds during the INUPIAQ campaign

NASA Astrophysics Data System (ADS)

Farrington, Robert; Connolly, Paul J.; Lloyd, Gary; Bower, Keith N.; Flynn, Michael J.; Gallagher, Martin W.; Field, Paul R.; Dearden, Chris; Choularton, Thomas W.; Hoyle, Chris

2016-04-01

At temperatures between -35°C and 0°C, the presence of insoluble aerosols acting as ice nuclei (IN) is the only way in which ice can nucleate under atmospheric conditions. Previous field and laboratory campaigns have suggested that mineral dust present in the atmosphere act as IN at temperatures warmer than -35°C (e.g. Sassen et al. 2003); however, the cause of ice nucleation at temperatures greater than -10°C is less certain. In-situ measurements of aerosol properties and cloud micro-physical processes are required to drive the improvement of aerosol-cloud processes in numerical models. As part of the Ice NUcleation Process Investigation and Quantification (INUPIAQ) project, two field campaigns were conducted in the winters of 2013 and 2014 (Lloyd et al. 2014). Both campaigns included measurements of cloud micro-physical properties at the summit of Jungfraujoch in Switzerland (3580m asl), using cloud probes, including the Two-Dimensional Stereo Hydrometeor Spectrometer (2D-S), the Cloud Particle Imager 3V (CPI-3V) and the Cloud Aerosol Spectrometer with Depolarization (CAS-DPOL). The first two of these probes measured significantly higher ice number concentrations than those observed in clouds at similar altitudes from aircraft. In this contribution, we assess the source of the high ice number concentrations observed by comparing in-situ measurements at Jungfraujoch with WRF simulations applied to the region around Jungfraujoch. During the 2014 field campaign the model simulations regularly simulated ice particle concentrations that were 3 orders of magnitude per litre less than the observed ice number concentration, even taking into account the aerosol properties measured upwind. WRF was used to investigate a number of potential sources of the high ice crystal concentrations, including: an increased ice nucleating particle (INP) concentration, secondary ice multiplication and the advection of surface ice or snow crystals into the clouds. It was found that the influence of these processes on the ice particle concentrations could not explain the observations. We also assessed whether the inclusion of a surface flux of hoar crystals into the WRF model could account for the increased ice concentrations in the orographic clouds found at Jungfraujoch. By including a simple parameterisation based on the surface wind speed, the inclusion of the surface crystal flux provided good agreement with the measurements at Jungfraujoch. A summary of these results will be presented at the meeting. References Lloyd, G., et al., 2015. The origins of ice crystals measured in mixed-phase clouds at the high-alpine site Jungfraujoch. Atmos. Chem. Phys., 15, 12953-12969. Sassen, K., et al., 2003. Saharan dust storms and indirect aerosol effects on clouds: Crystal-face results. Geophys. Res. Lett., 30, 1633-1636.

Antarctic Sea Ice Thickness and Snow-to-Ice Conversion from Atmospheric Reanalysis and Passive Microwave Snow Depth

NASA Technical Reports Server (NTRS)

Markus, Thorsten; Maksym, Ted

2007-01-01

Passive microwave snow depth, ice concentration, and ice motion estimates are combined with snowfall from the European Centre for Medium Range Weather Forecasting (ECMWF) reanalysis (ERA-40) from 1979-200 1 to estimate the prevalence of snow-to-ice conversion (snow-ice formation) on level sea ice in the Antarctic for April-October. Snow ice is ubiquitous in all regions throughout the growth season. Calculated snow- ice thicknesses fall within the range of estimates from ice core analysis for most regions. However, uncertainties in both this analysis and in situ data limit the usefulness of snow depth and snow-ice production to evaluate the accuracy of ERA-40 snowfall. The East Antarctic is an exception, where calculated snow-ice production exceeds observed ice thickness over wide areas, suggesting that ERA-40 precipitation is too high there. Snow-ice thickness variability is strongly controlled not just by snow accumulation rates, but also by ice divergence. Surprisingly, snow-ice production is largely independent of snow depth, indicating that the latter may be a poor indicator of total snow accumulation. Using the presence of snow-ice formation as a proxy indicator for near-zero freeboard, we examine the possibility of estimating level ice thickness from satellite snow depths. A best estimate for the mean level ice thickness in September is 53 cm, comparing well with 51 cm from ship-based observations. The error is estimated to be 10-20 cm, which is similar to the observed interannual and regional variability. Nevertheless, this is comparable to expected errors for ice thickness determined by satellite altimeters. Improvement in satellite snow depth retrievals would benefit both of these methods.

MODIS Snow-Cover Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.; DiGirolamo, Nicole E.; Bayr, Klaus J.; Houser, Paul R. (Technical Monitor)

2002-01-01

On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS). Many geophysical products are derived from MODIS data including global snow-cover products. MODIS snow and ice products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. MODIS snow-cover products represent potential improvement to or enhancement of the currently-available operational products mainly because the MODIS products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set may be generated for long-term climate studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the products. The MODIS snow product suite begins with a 500-m resolution, 2330-km swath snow-cover map which is then gridded to an integerized sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to a climate-modeling grid (CMG) product at about 5.6-km spatial resolution, with both daily and 8-day composite products. Each pixel of the CMG contains fraction of snow cover from 40 - 100%. Measured errors of commission in the CMG are low, for example, on the continent of Australia in the spring, they vary from 0.02 - 0.10%. Near-term enhancements include daily snow albedo and fractional snow cover. A case study from March 6, 2000, involving MODIS data and field and aircraft measurements, is presented to show some early validation work.

The microphysical properties of convective precipitation over the Tibetan Plateau by a high-resolution cloud-resolving simulation

NASA Astrophysics Data System (ADS)

Gao, W.; Liu, L.; Hu, Z.

2017-12-01

The microphysical properties of precipitating convective systems over the Tibetan Plateau (TP) are unique because of the extremely high topography and special atmospheric conditions. In this study, the ground-based millimeter cloud radar and optical disdrometer observations during the Third Tibetan Plateau Atmospheric Scientific Experiment (TIPEX-III), and the high-resolution (600-m horizontal grid size) simulations with the Chinese Academy of Meteorological Sciences microphysics (CAMS) are used to investigate the microphysics and precipitation mechanism of a convection event on 24 July 2014. The model reasonably reproduces the spatial distribution of 24-h accumulated rainfall yet the temporal evolution of rainfall rate has a two hours delay. The simulated raindrop size distribution (RSD) is in general agreement with the disdrometer measurement, and the number concentration for small raindrop is a certain degree overestimated. The RSD over the TP is wider than that over plain at the same latitude, implying that the precipitation may be more easily produced in the former. Results demonstrate that the leading ice crystal microphysical processes are the depositional growth of ice crystal and autoconversion of ice crystal to snow. The dominant source term of snow/graupel in convection is the accretion of cloud water by snow/graupel (riming) due to the plentiful supercooled cloud water over there. Note that the accretion of snow by rain to form graupel has a great contribution to graupel number concentration as the existence of large liquid particles in cold region over the TP. In addition, the microphysics-produced graupel fall out completely through the sedimentation process and accumulate near the melting layer with the rate of 0.09 g kg-1s-1. They then melt immediately to form rain water in warm region and half of them can finally reach the ground to form precipitation (the rest evaporated). Furthermore, the water vapor budgets analyses reveal that the surface evaporation is the principal source of water vapor at the beginning of convection. While during the development of convection, the total vapor flux convergence (horizontal and vertical) supplies about 90% of the net condensation (condensation and deposition) and has the similar phase with the area-averaged rainfall rate, indicating its important role in TP convective precipitation.

Estimating the rates of mass change, ice volume change and snow volume change in Greenland from ICESat and GRACE data

NASA Astrophysics Data System (ADS)

Slobbe, D. C.; Ditmar, P.; Lindenbergh, R. C.

2009-01-01

The focus of this paper is on the quantification of ongoing mass and volume changes over the Greenland ice sheet. For that purpose, we used elevation changes derived from the Ice, Cloud, and land Elevation Satellite (ICESat) laser altimetry mission and monthly variations of the Earth's gravity field as observed by the Gravity Recovery and Climate Experiment (GRACE) mission. Based on a stand alone processing scheme of ICESat data, the most probable estimate of the mass change rate from 2003 February to 2007 April equals -139 +/- 68 Gtonyr-1. Here, we used a density of 600+/-300 kgm-3 to convert the estimated elevation change rate in the region above 2000m into a mass change rate. For the region below 2000m, we used a density of 900+/-300 kgm-3. Based on GRACE gravity models from half 2002 to half 2007 as processed by CNES, CSR, DEOS and GFZ, the estimated mass change rate for the whole of Greenland ranges between -128 and -218Gtonyr-1. Most GRACE solutions show much stronger mass losses as obtained with ICESat, which might be related to a local undersampling of the mass loss by ICESat and uncertainties in the used snow/ice densities. To solve the problem of uncertainties in the snow and ice densities, two independent joint inversion concepts are proposed to profit from both GRACE and ICESat observations simultaneously. The first concept, developed to reduce the uncertainty of the mass change rate, estimates this rate in combination with an effective snow/ice density. However, it turns out that the uncertainties are not reduced, which is probably caused by the unrealistic assumption that the effective density is constant in space and time. The second concept is designed to convert GRACE and ICESat data into two totally new products: variations of ice volume and variations of snow volume separately. Such an approach is expected to lead to new insights in ongoing mass change processes over the Greenland ice sheet. Our results show for different GRACE solutions a snow volume change of -11 to 155km3yr-1 and an ice loss with a rate of -136 to -292km3yr-1.

Modeling Jupiter's Great Red Spot with an Active Hydrological Cycle

NASA Astrophysics Data System (ADS)

Palotai, C. J.; Dowling, T. E.; Morales-Juberías, R.

2003-05-01

We are studying the interaction of Jupiter's hydrological cycle with the formation and maintenance of its long-lived vortices and jet streams using numerical simulations. We are particularly interested in establishing the importance of the large convective storm system to the northwest of Jupiter's Great Red Spot (GRS). We have adapted into the EPIC model the cloud microphysics scheme used at Colorado State University (Fowler et al. 1996, J. Cli. 9, 489), which contains prognostic equations for vapor, liquid cloud, ice cloud, rain and snow. We are focussing on the role of water, but the EPIC model can also handle multiple species (water, ammonia, etc.). Processes that are currently working in the microphysics model include large-scale condensation/deposition, cloud evaporation, melting/freezing, and Bergeron-Findeisen diffusional growth of ice from supercooled liquid. The form of precipitation on gas giants is a major unknown. We are currently using a simple scheme for precipitation, but are studying the effect that processes known to be important in terrestrial models have on our results, including formation and accretion of rain and snow, preciptation evaporation, detrainment and cloud-top entrainment. We will present comparisons of ``dry'' and ``wet'' runs of a channel Jupiter EPIC simulation covering -40S to the equator that includes various initial water-vapor profiles and a GRS model. The effects of latent heating on the energy budget and vertical transport will be discussed. This research is funded by NASA's Planetary Atmospheres and EPSCoR Programs.

Analysis of reactive bromine production and ozone depletion in the Arctic boundary layer using 3-D simulations with GEM-AQ: inference from synoptic-scale patterns

NASA Astrophysics Data System (ADS)

Toyota, K.; McConnell, J. C.; Lupu, A.; Neary, L.; McLinden, C. A.; Richter, A.; Kwok, R.; Semeniuk, K.; Kaminski, J. W.; Gong, S.-L.; Jarosz, J.; Chipperfield, M. P.; Sioris, C. E.

2011-04-01

Episodes of high bromine levels and surface ozone depletion in the springtime Arctic are simulated by an online air-quality model, GEM-AQ, with gas-phase and heterogeneous reactions of inorganic bromine species and a simple scheme of air-snowpack chemical interactions implemented for this study. Snowpack on sea ice is assumed to be the only source of bromine to the atmosphere and to be capable of converting relatively stable bromine species to photolabile Br2 via air-snowpack interactions. A set of sensitivity model runs are performed for April 2001 at a horizontal resolution of approximately 100 km×100 km in the Arctic, to provide insights into the effects of temperature and the age (first-year, FY, versus multi-year, MY) of sea ice on the release of reactive bromine to the atmosphere. The model simulations capture much of the temporal variations in surface ozone mixing ratios as observed at stations in the high Arctic and the synoptic-scale evolution of areas with enhanced BrO column amount ("BrO clouds") as estimated from satellite observations. The simulated "BrO clouds" are in modestly better agreement with the satellite measurements when the FY sea ice is assumed to be more efficient at releasing reactive bromine to the atmosphere than on the MY sea ice. Surface ozone data from coastal stations used in this study are not sufficient to evaluate unambiguously the difference between the FY sea ice and the MY sea ice as a source of bromine. The results strongly suggest that reactive bromine is released ubiquitously from the snow on the sea ice during the Arctic spring while the timing and location of the bromine release are largely controlled by meteorological factors. It appears that a rapid advection and an enhanced turbulent diffusion associated with strong boundary-layer winds drive transport and dispersion of ozone to the near-surface air over the sea ice, increasing the oxidation rate of bromide (Br-) in the surface snow. Also, if indeed the surface snowpack does supply most of the reactive bromine in the Arctic boundary layer, it appears to be capable of releasing reactive bromine at temperatures as high as -10 °C, particularly on the sea ice in the central and eastern Arctic Ocean. Dynamically-induced BrO column variability in the lowermost stratosphere appears to interfere with the use of satellite BrO column measurements for interpreting BrO variability in the lower troposphere but probably not to the extent of totally obscuring "BrO clouds" that originate from the surface snow/ice source of bromine in the high Arctic. A budget analysis of the simulated air-surface exchange of bromine compounds suggests that a "bromine explosion" occurs in the interstitial air of the snowpack and/or is accelerated by heterogeneous reactions on the surface of wind-blown snow in ambient air, both of which are not represented explicitly in our simple model but could have been approximated by a parameter adjustment for the yield of Br2 from the trigger.

Balloon-borne match measurements of midlatitude cirrus clouds

NASA Astrophysics Data System (ADS)

Cirisan, A.; Luo, B. P.; Engel, I.; Wienhold, F. G.; Sprenger, M.; Krieger, U. K.; Weers, U.; Romanens, G.; Levrat, G.; Jeannet, P.; Ruffieux, D.; Philipona, R.; Calpini, B.; Spichtinger, P.; Peter, T.

2014-07-01

Observations of high supersaturations with respect to ice inside cirrus clouds with high ice water content (> 0.01 g kg-1) and high crystal number densities (> 1 cm-3) are challenging our understanding of cloud microphysics and of climate feedback processes in the upper troposphere. However, single measurements of a cloudy air mass provide only a snapshot from which the persistence of ice supersaturation cannot be judged. We introduce here the "cirrus match technique" to obtain information about the evolution of clouds and their saturation ratio. The aim of these coordinated balloon soundings is to analyze the same air mass twice. To this end the standard radiosonde equipment is complemented by a frost point hygrometer, "SnowWhite", and a particle backscatter detector, "COBALD" (Compact Optical Backscatter AerosoL Detector). Extensive trajectory calculations based on regional weather model COSMO (Consortium for Small-Scale Modeling) forecasts are performed for flight planning, and COSMO analyses are used as a basis for comprehensive microphysical box modeling (with grid scale of 2 and 7 km, respectively). Here we present the results of matching a cirrus cloud to within 2-15 km, realized on 8 June 2010 over Payerne, Switzerland, and a location 120 km downstream close to Zurich. A thick cirrus cloud was detected over both measurement sites. We show that in order to quantitatively reproduce the measured particle backscatter ratios, the small-scale temperature fluctuations not resolved by COSMO must be superimposed on the trajectories. The stochastic nature of the fluctuations is captured by ensemble calculations. Possibilities for further improvements in the agreement with the measured backscatter data are investigated by assuming a very slow mass accommodation of water on ice, the presence of heterogeneous ice nuclei, or a wide span of (spheroidal) particle shapes. However, the resulting improvements from these microphysical refinements are moderate and comparable in magnitude with changes caused by assuming different regimes of temperature fluctuations for clear-sky or cloudy-sky conditions, highlighting the importance of proper treatment of subscale fluctuations. The model yields good agreement with the measured backscatter over both sites and reproduces the measured saturation ratios with respect to ice over Payerne. Conversely, the 30% in-cloud supersaturation measured in a massive 4 km thick cloud layer over Zurich cannot be reproduced, irrespective of the choice of meteorological or microphysical model parameters. The measured supersaturation can only be explained by either resorting to an unknown physical process, which prevents the ice particles from consuming the excess humidity, or - much more likely - by a measurement error, such as a contamination of the sensor housing of the SnowWhite hygrometer by a precipitation drop from a mixed-phase cloud just below the cirrus layer or from some very slight rain in the boundary layer. This uncertainty calls for in-flight checks or calibrations of hygrometers under the special humidity conditions in the upper troposphere.

Cloud-Resolving Model Simulations of Aerosol-Cloud Interactions Triggered by Strong Aerosol Emissions in the Arctic

NASA Astrophysics Data System (ADS)

Wang, H.; Kravitz, B.; Rasch, P. J.; Morrison, H.; Solomon, A.

2014-12-01

Previous process-oriented modeling studies have highlighted the dependence of effectiveness of cloud brightening by aerosols on cloud regimes in warm marine boundary layer. Cloud microphysical processes in clouds that contain ice, and hence the mechanisms that drive aerosol-cloud interactions, are more complicated than in warm clouds. Interactions between ice particles and liquid drops add additional levels of complexity to aerosol effects. A cloud-resolving model is used to study aerosol-cloud interactions in the Arctic triggered by strong aerosol emissions, through either geoengineering injection or concentrated sources such as shipping and fires. An updated cloud microphysical scheme with prognostic aerosol and cloud particle numbers is employed. Model simulations are performed in pure super-cooled liquid and mixed-phase clouds, separately, with or without an injection of aerosols into either a clean or a more polluted Arctic boundary layer. Vertical mixing and cloud scavenging of particles injected from the surface is still quite efficient in the less turbulent cold environment. Overall, the injection of aerosols into the Arctic boundary layer can delay the collapse of the boundary layer and increase low-cloud albedo. The pure liquid clouds are more susceptible to the increase in aerosol number concentration than the mixed-phase clouds. Rain production processes are more effectively suppressed by aerosol injection, whereas ice precipitation (snow) is affected less; thus the effectiveness of brightening mixed-phase clouds is lower than for liquid-only clouds. Aerosol injection into a clean boundary layer results in a greater cloud albedo increase than injection into a polluted one, consistent with current knowledge about aerosol-cloud interactions. Unlike previous studies investigating warm clouds, the impact of dynamical feedback due to precipitation changes is small. According to these results, which are dependent upon the representation of ice nucleation processes in the employed microphysical scheme, Arctic geoengineering/shipping could have substantial local radiative effects, but is unlikely to be effective as the sole means of counterbalancing warming due to climate change.

High-Resolution NU-WRF Simulations of a Deep Convective-Precipitation System During MC3E: Part I: Comparisons Between Goddard Microphysics Schemes and Observations

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Wu, Di; Lang, Stephen; Chern, Jiun-Dar; Peters-Lidard, Christa; Fridlind, Ann; Matsui, Toshihisa

2016-01-01

The Goddard microphysics was recently improved by adding a fourth ice class (frozen dropshail). This new 4ICE scheme was developed and tested in the Goddard Cumulus Ensemble (GCE) model for an intense continental squall line and a moderate, less organized continental case. Simulated peak radar reflectivity profiles were improved in intensity and shape for both cases, as were the overall reflectivity probability distributions versus observations. In this study, the new Goddard 4ICE scheme is implemented into the regional-scale NASA Unified-Weather Research and Forecasting (NU-WRF) model, modified and evaluated for the same intense squall line, which occurred during the Midlatitude Continental Convective Clouds Experiment (MC3E). NU-WRF simulated radar reflectivities, total rainfall, propagation, and convective system structures using the 4ICE scheme modified herein agree as well as or significantly better with observations than the original 4ICE and two previous 3ICE (graupel or hail) versions of the Goddard microphysics. With the modified 4ICE, the bin microphysics-based rain evaporation correction improves propagation and in conjunction with eliminating the unrealistic dry collection of icesnow by hail can replicate the erect, narrow, and intense convective cores. Revisions to the ice supersaturation, ice number concentration formula, and snow size mapping, including a new snow breakup effect, allow the modified 4ICE to produce a stronger, better organized system, more snow, and mimic the strong aggregation signature in the radar distributions. NU-WRF original 4ICE simulated radar reflectivity distributions are consistent with and generally superior to those using the GCE due to the less restrictive domain and lateral boundaries.

Advances in understanding and parameterization of small-scale physical processes in the marine Arctic climate system: a review

NASA Astrophysics Data System (ADS)

Vihma, T.; Pirazzini, R.; Fer, I.; Renfrew, I. A.; Sedlar, J.; Tjernström, M.; Lüpkes, C.; Nygård, T.; Notz, D.; Weiss, J.; Marsan, D.; Cheng, B.; Birnbaum, G.; Gerland, S.; Chechin, D.; Gascard, J. C.

2014-09-01

The Arctic climate system includes numerous highly interactive small-scale physical processes in the atmosphere, sea ice, and ocean. During and since the International Polar Year 2007-2009, significant advances have been made in understanding these processes. Here, these recent advances are reviewed, synthesized, and discussed. In atmospheric physics, the primary advances have been in cloud physics, radiative transfer, mesoscale cyclones, coastal, and fjordic processes as well as in boundary layer processes and surface fluxes. In sea ice and its snow cover, advances have been made in understanding of the surface albedo and its relationships with snow properties, the internal structure of sea ice, the heat and salt transfer in ice, the formation of superimposed ice and snow ice, and the small-scale dynamics of sea ice. For the ocean, significant advances have been related to exchange processes at the ice-ocean interface, diapycnal mixing, double-diffusive convection, tidal currents and diurnal resonance. Despite this recent progress, some of these small-scale physical processes are still not sufficiently understood: these include wave-turbulence interactions in the atmosphere and ocean, the exchange of heat and salt at the ice-ocean interface, and the mechanical weakening of sea ice. Many other processes are reasonably well understood as stand-alone processes but the challenge is to understand their interactions with and impacts and feedbacks on other processes. Uncertainty in the parameterization of small-scale processes continues to be among the greatest challenges facing climate modelling, particularly in high latitudes. Further improvements in parameterization require new year-round field campaigns on the Arctic sea ice, closely combined with satellite remote sensing studies and numerical model experiments.

Advances in understanding and parameterization of small-scale physical processes in the marine Arctic climate system: a review

NASA Astrophysics Data System (ADS)

Vihma, T.; Pirazzini, R.; Renfrew, I. A.; Sedlar, J.; Tjernström, M.; Nygård, T.; Fer, I.; Lüpkes, C.; Notz, D.; Weiss, J.; Marsan, D.; Cheng, B.; Birnbaum, G.; Gerland, S.; Chechin, D.; Gascard, J. C.

2013-12-01

The Arctic climate system includes numerous highly interactive small-scale physical processes in the atmosphere, sea ice, and ocean. During and since the International Polar Year 2007-2008, significant advances have been made in understanding these processes. Here these advances are reviewed, synthesized and discussed. In atmospheric physics, the primary advances have been in cloud physics, radiative transfer, mesoscale cyclones, coastal and fjordic processes, as well as in boundary-layer processes and surface fluxes. In sea ice and its snow cover, advances have been made in understanding of the surface albedo and its relationships with snow properties, the internal structure of sea ice, the heat and salt transfer in ice, the formation of super-imposed ice and snow ice, and the small-scale dynamics of sea ice. In the ocean, significant advances have been related to exchange processes at the ice-ocean interface, diapycnal mixing, tidal currents and diurnal resonance. Despite this recent progress, some of these small-scale physical processes are still not sufficiently understood: these include wave-turbulence interactions in the atmosphere and ocean, the exchange of heat and salt at the ice-ocean interface, and the mechanical weakening of sea ice. Many other processes are reasonably well understood as stand-alone processes but challenge is to understand their interactions with, and impacts and feedbacks on, other processes. Uncertainty in the parameterization of small-scale processes continues to be among the largest challenges facing climate modeling, and nowhere is this more true than in the Arctic. Further improvements in parameterization require new year-round field campaigns on the Arctic sea ice, closely combined with satellite remote sensing studies and numerical model experiments.

ASPECTS OF ARCTIC SEA ICE OBSERVABLE BY SEQUENTIAL PASSIVE MICROWAVE OBSERVATIONS FROM THE NIMBUS-5 SATELLITE.

USGS Publications Warehouse

Campbell, William J.; Gloersen, Per; Zwally, H. Jay; ,

1984-01-01

Observations made from 1972 to 1976 with the Electrically Scanning Microwave Radiometer on board the Nimbus-5 satellite provide sequential synoptic information of the Arctic sea ice cover. This four-year data set was used to construct a fairly continuous series of three-day average 19-GHz passive microwave images which has become a valuable source of polar information, yielding many anticipated and unanticipated discoveries of the sea ice canopy observed in its entirety through the clouds and during the polar night. Short-term, seasonal, and annual variations of key sea ice parameters, such as ice edge position, ice types, mixtures of ice types, ice concentrations, and snow melt on the ice, are presented for various parts of the Arctic.

Ice Sheet Temperature Records - Satellite and In Situ Data from Antarctica and Greenland

NASA Astrophysics Data System (ADS)

Shuman, C. A.; Comiso, J. C.

2001-12-01

Recently completed decadal-length surface temperature records from Antarctica and Greenland are providing insights into the challenge of detecting climate change. Ice and snow cover at high latitudes influence the global climate system by reflecting much of the incoming solar energy back to space. An expected consequence of global warming is a decrease in area covered by snow and ice and an increase in Earth's absorption of solar radiation. Models have predicted that the effects of climate warming may be amplified at high latitudes; thinning of the Greenland ice sheet margins and the breakup of Antarctic Peninsula ice shelves suggest this process may have begun. Satellite data provide an excellent means of observing climate parameters across both long temporal and remote spatial domains but calibration and validation of their data remains a challenge. Infrared sensors can provide excellent temperature information but cloud cover and calibration remain as problems. Passive-microwave sensors can obtain data during the long polar night and through clouds but have calibration issues and a much lower spatial resolution. Automatic weather stations are generally spatially- and temporally-restricted and may have long gaps due to equipment failure. Stable isotopes of oxygen and hydrogen from ice sheet locations provide another means of determining temperature variations with time but are challenging to calibrate to observed temperatures and also represent restricted areas. This presentation will discuss these issues and elaborate on the development and limitations of composite satellite, automatic weather station, and proxy temperature data from selected sites in Antarctica and Greenland.

Machine Learning Algorithms for Automated Satellite Snow and Sea Ice Detection

NASA Astrophysics Data System (ADS)

Bonev, George

The continuous mapping of snow and ice cover, particularly in the arctic and poles, are critical to understanding the earth and atmospheric science. Much of the world's sea ice and snow covers the most inhospitable places, making measurements from satellite-based remote sensors essential. Despite the wealth of data from these instruments many challenges remain. For instance, remote sensing instruments reside on-board different satellites and observe the earth at different portions of the electromagnetic spectrum with different spatial footprints. Integrating and fusing this information to make estimates of the surface is a subject of active research. In response to these challenges, this dissertation will present two algorithms that utilize methods from statistics and machine learning, with the goal of improving on the quality and accuracy of current snow and sea ice detection products. The first algorithm aims at implementing snow detection using optical/infrared instrument data. The novelty in this approach is that the classifier is trained using ground station measurements of snow depth that are collocated with the reflectance observed at the satellite. Several classification methods are compared using this training data to identify the one yielding the highest accuracy and optimal space/time complexity. The algorithm is then evaluated against the current operational NASA snow product and it is found that it produces comparable and in some cases superior accuracy results. The second algorithm presents a fully automated approach to sea ice detection that integrates data obtained from passive microwave and optical/infrared satellite instruments. For a particular region of interest the algorithm generates sea ice maps of each individual satellite overpass and then aggregates them to a daily composite level, maximizing the amount of high resolution information available. The algorithm is evaluated at both, the individual satellite overpass level, and at the daily composite level. Results show that at the single overpass level for clear-sky regions, the developed multi-sensor algorithm performs with accuracy similar to that of the optical/infrared products, with the advantage of being able to also classify partially cloud-obscured regions with the help of passive microwave data. At the daily composite level, results show that the algorithm's performance with respect to total ice extent is in line with other daily products, with the novelty of being fully automated and having higher resolution.

From enzymes and viruses to clouds, snow, sea-glaciers, and green icebergs: How a protein crystallographer got into glaciology and atmospheric radiation

NASA Astrophysics Data System (ADS)

Warren, S. G.

2016-12-01

Through a series of lucky breaks beginning five years after my Ph.D., I was able to change careers from molecular biology to earth science, via a postdoc at NCAR in 1978, leading to a job at the University of Washington (UW) in 1982. Steve Schneider, Warren Wiscombe, Julius London, Gary Thomas, and Ed LaChapelle helped me make the transition. At UW, a collaboration with Tom Grenfell got me started in Antarctic fieldwork. Long-term dedicated coworkers Carole Hahn (cloud climatology) and Rich Brandt (radiative and thermal properties of snow and sea ice) kept our funded projects going. Conversations with UW colleagues Bob Charlson on dimethyl sulfide (DMS) and Qiang Fu on the microwave sounding unit (MSU) enticed me into unfunded projects (biological influence on cloud albedo; satellite-derived tropospheric temperatures). Several other key collaborators I first met when they were students at UW: Tony Clarke and Sarah Doherty (black carbon in snow), Bonnie Light (laboratory experiments for Snowball Earth), and Von Walden (longwave radiation spectra). Ian Allison of the Australian Antarctic Division sponsored my first sabbatical, to learn about sea ice. Most of our work, of course, is on projects that are proposed, then funded, then completed (or not completed). But at least as much fun are projects that were completed but not proposed. Some of these were inspired by listening to seminars (particularly by Charlson), or were developed from student term-papers in my snow-and-ice class (Jon Rhodes's report on suncups, and Steve Hudson's on Antarctic bacteria). There is not much cross-cultural connection between my former life and my current life, but there is some, now institutionalized in UW's Astrobiology Program. My enthusiasm for the CLAW project was partly motivated by my background in biology and the knowledge that DMS originates from the amino acid methionine. I was happy to accept oceanic biota as the explanation for the color of green icebergs. And my motivation for Snowball Earth research is its role in biological evolution: If the ocean froze all the way to the equator, where did surface life survive?

Vertical structure of recent Arctic warming.

PubMed

Graversen, Rune G; Mauritsen, Thorsten; Tjernström, Michael; Källén, Erland; Svensson, Gunilla

2008-01-03

Near-surface warming in the Arctic has been almost twice as large as the global average over recent decades-a phenomenon that is known as the 'Arctic amplification'. The underlying causes of this temperature amplification remain uncertain. The reduction in snow and ice cover that has occurred over recent decades may have played a role. Climate model experiments indicate that when global temperature rises, Arctic snow and ice cover retreats, causing excessive polar warming. Reduction of the snow and ice cover causes albedo changes, and increased refreezing of sea ice during the cold season and decreases in sea-ice thickness both increase heat flux from the ocean to the atmosphere. Changes in oceanic and atmospheric circulation, as well as cloud cover, have also been proposed to cause Arctic temperature amplification. Here we examine the vertical structure of temperature change in the Arctic during the late twentieth century using reanalysis data. We find evidence for temperature amplification well above the surface. Snow and ice feedbacks cannot be the main cause of the warming aloft during the greater part of the year, because these feedbacks are expected to primarily affect temperatures in the lowermost part of the atmosphere, resulting in a pattern of warming that we only observe in spring. A significant proportion of the observed temperature amplification must therefore be explained by mechanisms that induce warming above the lowermost part of the atmosphere. We regress the Arctic temperature field on the atmospheric energy transport into the Arctic and find that, in the summer half-year, a significant proportion of the vertical structure of warming can be explained by changes in this variable. We conclude that changes in atmospheric heat transport may be an important cause of the recent Arctic temperature amplification.

Balloon-borne match measurements of mid-latitude cirrus clouds

NASA Astrophysics Data System (ADS)

Cirisan, A.; Luo, B. P.; Engel, I.; Wienhold, F. G.; Krieger, U. K.; Weers, U.; Romanens, G.; Levrat, G.; Jeannet, P.; Ruffieux, D.; Philipona, R.; Calpini, B.; Spichtinger, P.; Peter, T.

2013-10-01

Observations of persistent high supersaturations with respect to ice inside cirrus clouds are challenging our understanding of cloud microphysics and of climate feedback processes in the upper troposphere. Single measurements of a cloudy air mass provide only a snapshot from which the persistence of ice supersaturation cannot be judged. We introduce here the "cirrus match technique" to obtain information of the evolution of clouds and their saturation ratio. The aim of these coordinated balloon soundings is to analyze the same air mass twice. To this end the standard radiosonde equipment is complemented by a frost point hygrometer "SnowWhite" and a particle backscatter detector "COBALD" (Compact Optical Backscatter Aerosol Detector). Extensive trajectory calculations based on regional weather model COSMO forecasts are performed for flight planning and COSMO analyses are used as basis for comprehensive microphysical box modeling (with grid scale 2 km and 7 km, respectively). Here we present the results of matching a cirrus cloud to within 2-15 km, realized on 8 June 2010 over Payerne, Switzerland, and a location 120 km downstream close to Zurich. A thick cirrus was detected over both measurement sites. We show that in order to quantitatively reproduce the measured particle backscatter ratios, the small-scale temperature fluctuations not resolved by COSMO must be superimposed on the trajectories. The stochastic nature of the fluctuations is captured by ensemble calculations. Possibilities for further improvements in the agreement with the measured backscatter data are investigated by assuming a very slow mass accommodation of water on ice, the presence of heterogeneous ice nuclei, or a wide span of (spheroidal) particle shapes. However, the resulting improvements from microphysical refinements are moderate and comparable in magnitude with changes caused by assuming different regimes of temperature fluctuations for clear sky or cloudy sky conditions, highlighting the importance of a proper treatment of subscale fluctuations. The model yields good agreement with the measured backscatter over both sites and reproduces the measured saturation ratios with respect to ice over Payerne. Conversely, the 30% in-cloud supersaturation measured in a massive, 4-km thick cloud layer over Zurich cannot be reproduced, irrespective of the choice of meteorological or microphysical model parameters. The measured supersaturation can only be explained by either resorting to an unknown physical process, which prevents the ice particles from consuming the excess humidity, or - much more likely - by a measurement error, such as a contamination of the sensor housing of the SnowWhite hygrometer by a precipitation drop from a mixed phase cloud just below the cirrus layer or from some very slight rain in the boundary layer. This uncertainty calls for in-flight checks or calibrations of hygrometers under the extreme humidity conditions in the upper troposphere.

Precipitation formation from orographic cloud seeding.

PubMed

French, Jeffrey R; Friedrich, Katja; Tessendorf, Sarah A; Rauber, Robert M; Geerts, Bart; Rasmussen, Roy M; Xue, Lulin; Kunkel, Melvin L; Blestrud, Derek R

2018-02-06

Throughout the western United States and other semiarid mountainous regions across the globe, water supplies are fed primarily through the melting of snowpack. Growing populations place higher demands on water, while warmer winters and earlier springs reduce its supply. Water managers are tantalized by the prospect of cloud seeding as a way to increase winter snowfall, thereby shifting the balance between water supply and demand. Little direct scientific evidence exists that confirms even the basic physical hypothesis upon which cloud seeding relies. The intent of glaciogenic seeding of orographic clouds is to introduce aerosol into a cloud to alter the natural development of cloud particles and enhance wintertime precipitation in a targeted region. The hypothesized chain of events begins with the introduction of silver iodide aerosol into cloud regions containing supercooled liquid water, leading to the nucleation of ice crystals, followed by ice particle growth to sizes sufficiently large such that snow falls to the ground. Despite numerous experiments spanning several decades, no direct observations of this process exist. Here, measurements from radars and aircraft-mounted cloud physics probes are presented that together show the initiation, growth, and fallout to the mountain surface of ice crystals resulting from glaciogenic seeding. These data, by themselves, do not address the question of cloud seeding efficacy, but rather form a critical set of observations necessary for such investigations. These observations are unambiguous and provide details of the physical chain of events following the introduction of glaciogenic cloud seeding aerosol into supercooled liquid orographic clouds.

Process-model simulations of cloud albedo enhancement by aerosols in the Arctic.

PubMed

Kravitz, Ben; Wang, Hailong; Rasch, Philip J; Morrison, Hugh; Solomon, Amy B

2014-12-28

A cloud-resolving model is used to simulate the effectiveness of Arctic marine cloud brightening via injection of cloud condensation nuclei (CCN), either through geoengineering or other increased sources of Arctic aerosols. An updated cloud microphysical scheme is employed, with prognostic CCN and cloud particle numbers in both liquid and mixed-phase marine low clouds. Injection of CCN into the marine boundary layer can delay the collapse of the boundary layer and increase low-cloud albedo. Albedo increases are stronger for pure liquid clouds than mixed-phase clouds. Liquid precipitation can be suppressed by CCN injection, whereas ice precipitation (snow) is affected less; thus, the effectiveness of brightening mixed-phase clouds is lower than for liquid-only clouds. CCN injection into a clean regime results in a greater albedo increase than injection into a polluted regime, consistent with current knowledge about aerosol-cloud interactions. Unlike previous studies investigating warm clouds, dynamical changes in circulation owing to precipitation changes are small. According to these results, which are dependent upon the representation of ice nucleation processes in the employed microphysical scheme, Arctic geoengineering is unlikely to be effective as the sole means of altering the global radiation budget but could have substantial local radiative effects. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Process-model simulations of cloud albedo enhancement by aerosols in the Arctic

PubMed Central

Kravitz, Ben; Wang, Hailong; Rasch, Philip J.; Morrison, Hugh; Solomon, Amy B.

2014-01-01

A cloud-resolving model is used to simulate the effectiveness of Arctic marine cloud brightening via injection of cloud condensation nuclei (CCN), either through geoengineering or other increased sources of Arctic aerosols. An updated cloud microphysical scheme is employed, with prognostic CCN and cloud particle numbers in both liquid and mixed-phase marine low clouds. Injection of CCN into the marine boundary layer can delay the collapse of the boundary layer and increase low-cloud albedo. Albedo increases are stronger for pure liquid clouds than mixed-phase clouds. Liquid precipitation can be suppressed by CCN injection, whereas ice precipitation (snow) is affected less; thus, the effectiveness of brightening mixed-phase clouds is lower than for liquid-only clouds. CCN injection into a clean regime results in a greater albedo increase than injection into a polluted regime, consistent with current knowledge about aerosol–cloud interactions. Unlike previous studies investigating warm clouds, dynamical changes in circulation owing to precipitation changes are small. According to these results, which are dependent upon the representation of ice nucleation processes in the employed microphysical scheme, Arctic geoengineering is unlikely to be effective as the sole means of altering the global radiation budget but could have substantial local radiative effects. PMID:25404677

Spaceborne SAR and sea ice

NASA Technical Reports Server (NTRS)

Weeks, W. F.

1983-01-01

A number of remote sensing systems deployed in satellites to view the Earth which are successful in gathering data on the behavior of the world's snow and ice covers are described. Considering sea ice which covers over 10% of the world ocean, systems that have proven capable to collect useful data include those operating in the visible, near-infrared, infrared, and microwave frequency ranges. The microwave systems have the essential advantage in observing the ice under all weather and lighting conditions. Without this capability data are lost during the long polar night and during times of storm passage, periods when ice activity can be intense. The margins of the ice pack, a region of particular interest, is shrouded in cloud between 80 and 90% of the time.

Quantifying spatial variability of AgI cloud seeding benefits and Ag enrichments in snow

NASA Astrophysics Data System (ADS)

Fisher, J.; Benner, S. G.; Lytle, M. L.; Kunkel, M. L.; Blestrud, D.; Holbrook, V. P.; Parkinson, S.; Edwards, R.

2016-12-01

Glaciogenic cloud seeding is an important scientific technology for enhancing water resources across in the Western United States. Cloud seeding enriches super cooled liquid water layers with plumes of silver iodide (AgI), an artificial ice nuclei. Recent studies using target-control regression analysis and modeling estimate glaciogenic cloud seeding increases snow precipitation between 3-15% annually. However, the efficacy of cloud seeding programs is difficult to assess using weather models and statistics alone. This study will supplement precipitation enhancement statistics and Weather Research and Forecasting (WRF) model outputs with ultra-trace chemistry. Combining precipitation enhancement estimates with trace chemistry data (to estimate AgI plume targeting accuracy) may provide a more robust analysis. Precipitation enhancement from the 2016 water year will be modeled two ways. First, by using double-mass curve. Annual SNOTEL data of the cumulative SWE in unseeded areas and cumulative SWE in seeded areas will be compared before, and after, the cloud seeding program's initiation in 2003. Any change in the double-mass curve's slope after 2003 may be attributed to cloud seeding. Second, WRF model estimates of precipitation will be compared to the observed precipitation at SNOTEL sites. The difference between observed and modeled precipitation in AgI seeded regions may also be attributed to cloud seeding (assuming modeled and observed data are comparable at unseeded SNOTEL stations). Ultra-trace snow chemistry data from the 2016 winter season will be used to validate whether estimated precipitation increases are positively correlated with the mass of silver in the snowpack.

A Near Perfect Spin Balance (Measurement in Chaos)

NASA Technical Reports Server (NTRS)

Luntz, R. A.

1997-01-01

The stringent spin balance requirements arise from the predecessor of SSMIS, the SSMI. The SSMI sensor spinning portion weighed only 85 pounds and contained 7 channels of radiometric data. The Aerospace Corporation recommended to pass on the same requirements from the smaller SSMI to our larger SSMIS (with slight change for increased weight). The SSMIS spinning portion will weigh about 155 pounds and contain 24 channels of radiometeric data. The SSMIS, on orbit, spins a CCW direction at 31.6 RPM its own drive motor. The packaging of this SSMIS is unique, as it combines three sensor into one unit. This combination allows for concurrently reading data in one beam. The unit will have a polar orbit about 500 miles above the earths surface. One of the primary influences for our receipt of the follow-on contract for the next generation sensor, was the ability to package 24 channels of radiometeric data into about the some volume as its predecessor. The data from SSMIS will be used to measure the following: (1) Ocean surface wind speed, (2) Rain over land an ocean, (3) Cloud water over Ocean, (4) Soil moisture, (5) Ice Concentration, (6) Ice age, (7) Ice Edge and snow edge, (8) Water vapor over Ocean, (9) Surface type, (10) Snow water content, (11) Land surface Temperature, (12) Cloud amount over ocean.

A Comparison of Satellite-Derived Snow Maps with a Focus on Ephemeral Snow in North Carolina

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Fuhrmann, Christopher M.; Perry, L. Baker; Riggs, George A.; Robinson, David A.; Foster, James L.

2010-01-01

In this paper, we focus on the attributes and limitations of four commonly-used daily snowcover products with respect to their ability to map ephemeral snow in central and eastern North Carolina. We show that the Moderate-Resolution Imaging Spectroradiometer (MODIS) fractional snow-cover maps can delineate the snow-covered area very well through the use of a fully-automated algorithm, but suffer from the limitation that cloud cover precludes mapping some ephemeral snow. The semi-automated Interactive Multi-sensor Snow and ice mapping system (IMS) and Rutgers Global Snow Lab (GSL) snow maps are often able to capture ephemeral snow cover because ground-station data are employed to develop the snow maps, The Rutgers GSL maps are based on the IMS maps. Finally, the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) provides some good detail of snow-water equivalent especially in deeper snow, but may miss ephemeral snow cover because it is often very thin or wet; the AMSR-E maps also suffer from coarse spatial resolution. We conclude that the southeastern United States represents a good test region for validating the ability of satellite snow-cover maps to capture ephemeral snow cover,

Flooding of the Taz, Pur, and Yenisey Rivers, Russia

NASA Technical Reports Server (NTRS)

2002-01-01

Each spring and summer, rivers across Siberia experience flooding as the waters in the south begin to melt and run before the ice has retreated from the northern limits. The ice causes jams which are sometimes loosened up using explosives. This pair of MODIS images from June 18, 2002, shows flooding on the Pur (left), Taz (center), and Yenisey (right) Rivers in central Siberia. In the false-color image, ice and snow are red, clouds are white, water is black, and vegetation is green. Bare soil is brown. Credit: Jacques Descloitres, MODIS Land Rapid Response Team, NASA/GSFC

The Effects of Snow Depth Forcing on Southern Ocean Sea Ice Simulations

NASA Technical Reports Server (NTRS)

Powel, Dylan C.; Markus, Thorsten; Stoessel, Achim

2003-01-01

The spatial and temporal distribution of snow on sea ice is an important factor for sea ice and climate models. First, it acts as an efficient insulator between the ocean and the atmosphere, and second, snow is a source of fresh water for altering the already weak Southern Ocean stratification. For the Antarctic, where the ice thickness is relatively thin, snow can impact the ice thickness in two ways: a) As mentioned above snow on sea ice reduces the ocean-atmosphere heat flux and thus reduces freezing at the base of the ice flows; b) a heavy snow load can suppress the ice below sea level which causes flooding and, with subsequent freezing, a thickening of the sea ice (snow-to-ice conversion). In this paper, we compare different snow fall paramterizations (incl. the incorporation of satellite-derived snow depth) and study the effect on the sea ice using a sea ice model.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wong, May Wai San; Ovchinnikov, Mikhail; Wang, Minghuai

Potential ways of parameterizing vertical turbulent fluxes of hydrometeors are examined using a high-resolution cloud-resolving model. The cloud-resolving model uses the Morrison microphysics scheme, which contains prognostic variables for rain, graupel, ice, and snow. A benchmark simulation with a horizontal grid spacing of 250 m of a deep convection case carried out to evaluate three different ways of parameterizing the turbulent vertical fluxes of hydrometeors: an eddy-diffusion approximation, a quadrant-based decomposition, and a scaling method that accounts for within-quadrant (subplume) correlations. Results show that the down-gradient nature of the eddy-diffusion approximation tends to transport mass away from concentrated regions, whereasmore » the benchmark simulation indicates that the vertical transport tends to transport mass from below the level of maximum to aloft. Unlike the eddy-diffusion approach, the quadri-modal decomposition is able to capture the signs of the flux gradient but underestimates the magnitudes. The scaling approach is shown to perform the best by accounting for within-quadrant correlations, and improves the results for all hydrometeors except for snow. A sensitivity study is performed to examine how vertical transport may affect the microphysics of the hydrometeors. The vertical transport of each hydrometeor type is artificially suppressed in each test. Results from the sensitivity tests show that cloud-droplet-related processes are most sensitive to suppressed rain or graupel transport. In particular, suppressing rain or graupel transport has a strong impact on the production of snow and ice aloft. Lastly, a viable subgrid-scale hydrometeor transport scheme in an assumed probability density function parameterization is discussed.« less

Development of Spaceborne Radar Simulator by NICT and JAXA using JMA Cloud-resolving Model

NASA Astrophysics Data System (ADS)

Kubota, T.; Eito, H.; Aonashi, K.; Hashimoto, A.; Iguchi, T.; Hanado, H.; Shimizu, S.; Yoshida, N.; Oki, R.

2009-12-01

We are developing synthetic spaceborne radar data toward a simulation of the Dual-frequency Precipitation Radar (DPR) aboard the Global Precipitation Measurement (GPM) core-satellite. Our purposes are a production of test-bed data for higher level DPR algorithm developers, in addition to a diagnosis of a cloud resolving model (CRM). To make the synthetic data, we utilize the CRM by the Japan Meteorological Agency (JMA-NHM) (Ikawa and Saito 1991, Saito et al. 2006, 2007), and the spaceborne radar simulation algorithm by the National Institute of Information and Communications Technology (NICT) and the Japan Aerospace Exploration Agency (JAXA) named as the Integrated Satellite Observation Simulator for Radar (ISOSIM-Radar). The ISOSIM-Radar simulates received power data in a field of view of the spaceborne radar with consideration to a scan angle of the radar (Oouchi et al. 2002, Kubota et al. 2009). The received power data are computed with gaseous and hydrometeor attenuations taken into account. The backscattering and extinction coefficients are calculated assuming the Mie approximation for all species. The dielectric constants for solid particles are computed by the Maxwell-Garnett model (Bohren and Battan 1982). Drop size distributions are treated in accordance with those of the JMA-NHM. We assume a spherical sea surface, a Gaussian antenna pattern, and 49 antenna beam directions for scan angles from -17 to 17 deg. in the PR. In this study, we report the diagnosis of the JMA-NHM with reference to the TRMM Precipitation Radar (PR) and CloudSat Cloud Profiling Radar (CPR) using the ISOSIM-Radar from the view of comparisons in cloud microphysics schemes of the JMA-NHM. We tested three kinds of explicit bulk microphysics schemes based on Lin et al. (1983), that is, three-ice 1-moment scheme, three-ice 2-moment scheme (Eito and Aonashi 2009), and newly developed four-ice full 2-moment scheme (Hashimoto 2008). The hydrometeor species considered here are rain, graupel, snow, cloud water, cloud ice and hail (4-ice scheme only). We examined a case of an intersection with the TRMM PR and the CloudSat CPR on 6th April 2008 over sea surface in the south of Kyushu Island of Japan. In this work, observed rainfall systems are simulated with one-way double nested domains having horizontal grid sizes of 5 km (outer) and 2 km (inner). Data used here are from the inner domain only. Results of the PR indicated better performances of 2-moment bulk schemes. It suggests that prognostic number concentrations of frozen hydrometeors are more effective in high altitudes and constant number concentrations can lead to the overestimation of the snow there. For three-ice schemes, simulated received power data overestimated above freezing levels with reference to the observed data. In contrast, the overestimation of frozen particles was heavily reduced for the four-ice scheme.

Characterization of ice nucleating particles during continuous springtime measurements in Prudhoe Bay: an Arctic oilfield location

NASA Astrophysics Data System (ADS)

Creamean, J.; Spada, N. J.; Kirpes, R.; Pratt, K.

2017-12-01

Aerosols that serve as ice nucleating particles (INPs) have the potential to modulate cloud microphysical properties. INPs can thus subsequently impact cloud radiative forcing in addition to modification of precipitation formation processes. In regions such as the Arctic, aerosol-cloud interactions are severely understudied yet have significant implications for surface radiation reaching the sea ice and snow surfaces. Further, uncertainties in model representations of heterogeneous ice nucleation are a significant hindrance to simulating Arctic mixed-phase cloud processes. Characterizing a combination of aerosol chemical, physical, and ice nucleating properties is pertinent to evaluating of the role of aerosols in altering Arctic cloud microphysics. We present preliminary results from an aerosol sampling campaign called INPOP (Ice Nucleating Particles at Oliktok Point), which took place at a U.S. Department of Energy's Atmospheric Radiation Measurement (DOE ARM) facility on the North Slope of Alaska. Three time- and size-resolved aerosol samplers were deployed from 1 Mar to 31 May 2017 and were co-located with routine measurements of aerosol number, size, chemical, and radiative property measurements conducted by DOE ARM at their Aerosol Observing System (AOS). Offline analysis of samples collected at a daily time resolution included composition and morphology via single-particle analysis and drop freezing measurements for INP concentrations, while analysis of 12-hourly samples included mass, optical, and elemental composition. We deliberate the possible influences on the aerosol and INP population from the Prudhoe Bay oilfield resource extraction and daily operations in addition to what may be local background or long-range transported aerosol. To our knowledge our results represent some of the first INP characterization measurements in an Arctic oilfield location and can be used as a benchmark for future INP characterization studies in Arctic locations impacted by local resource extraction pollution. Ultimately, these results can be used to evaluate the impacts of oil exploration activities on Arctic cloud aerosol composition and possible linkages to Arctic cloud ice formation.

The GLAS Standard Data Products Specification-Level 1, Version 9

NASA Technical Reports Server (NTRS)

Lee, Jeffrey E.

2013-01-01

The Geoscience Laser Altimeter System (GLAS) is the primary instrument for the ICESat (Ice, Cloud and Land Elevation Satellite) laser altimetry mission. ICESat was the benchmark Earth Observing System (EOS) mission for measuring ice sheet mass balance, cloud and aerosol heights, as well as land topography and vegetation characteristics. From 2003 to 2009, the ICESat mission provided multi-year elevation data needed to determine ice sheet mass balance as well as cloud property information, especially for stratospheric clouds common over polar areas. It also provided topography and vegetation data around the globe, in addition to the polar-specific coverage over the Greenland and Antarctic ice sheets.This document defines the Level-1 GLAS standard data products. This document addresses the data flow, interfaces, record and data formats associated with the GLAS Level 1 standard data products. GLAS Level 1 standard data products are composed of Level 1A and Level 1B data products. The term standard data products refers to those EOS instrument data that are routinely generated for public distribution. The National Snow and Ice Data Center (NSDIC) distribute these products. Each data product has a unique Product Identification code assigned by the Senior Project Scientist. GLAS Level 1A and Level 1B Data Products are composed from those Level 0 data that have been reformatted or transformed to corrected and calibrated data in physical units at the full instrument rate and resolution.

Impact of aerosol intrusions on sea-ice melting rates and the structure Arctic boundary layer clouds

NASA Astrophysics Data System (ADS)

Cotton, W.; Carrio, G.; Jiang, H.

2003-04-01

The Los Alamos National Laboratory sea-ice model (LANL CICE) was implemented into the real-time and research versions of the Colorado State University-Regional Atmospheric Modeling System (RAMS@CSU). The original version of CICE was modified in its structure to allow module communication in an interactive multigrid framework. In addition, some improvements have been made in the routines involved in the coupling, among them, the inclusion of iterative methods that consider variable roughness lengths for snow-covered ice thickness categories. This version of the model also includes more complex microphysics that considers the nucleation of cloud droplets, allowing the prediction of mixing ratios and number concentrations for all condensed water species. The real-time version of RAMS@CSU automatically processes the NASA Team SSMI F13 25km sea-ice coverage data; the data are objectively analyzed and mapped to the model grid configuration. We performed two types of cloud resolving simulations to assess the impact of the entrainment of aerosols from above the inversion on Arctic boundary layer clouds. The first series of numerical experiments corresponds to a case observed on May 4 1998 during the FIRE-ACE/SHEBA field experiment. Results indicate a significant impact on the microstructure of the simulated clouds. When assuming polluted initial profiles above the inversion, the liquid water fraction of the cloud monotonically decreases, the total condensate paths increases and downward IR tends to increase due to a significant increase in the ice water path. The second set of cloud resolving simulations focused on the evaluation of the potential effect of aerosol concentration above the inversion on melting rates during spring-summer period. For these multi-month simulations, the IFN and CCN profiles were also initialized assuming the 4 May profiles as benchmarks. Results suggest that increasing the aerosol concentrations above the boundary layer increases sea-ice melting rates when mixed phase clouds are present.

In search of the best match: probing a multi-dimensional cloud microphysical parameter space to better understand what controls cloud thermodynamic phase

NASA Astrophysics Data System (ADS)

Tan, Ivy; Storelvmo, Trude

2015-04-01

Substantial improvements have been made to the cloud microphysical schemes used in the latest generation of global climate models (GCMs), however, an outstanding weakness of these schemes lies in the arbitrariness of their tuning parameters, which are also notoriously fraught with uncertainties. Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has neglected to focus on improving the ability of GCMs to accurately simulate the present-day global distribution of thermodynamic phase partitioning in mixed-phase clouds. Liquid droplets and ice crystals not only influence the Earth's radiative budget and hence climate sensitivity via their contrasting optical properties, but also through the effects of their lifetimes in the atmosphere. The current study employs NCAR's CAM5.1, and uses observations of cloud phase obtained by NASA's CALIOP lidar over a 79-month period (November 2007 to June 2014) guide the accurate simulation of the global distribution of mixed-phase clouds in 20∘ latitudinal bands at the -10∘ C, -20∘C and -30∘C isotherms, by adjusting six relevant cloud microphysical tuning parameters in the CAM5.1 via Quasi-Monte Carlo sampling. Among the parameters include those that control the Wegener-Bergeron-Findeisen (WBF) timescale for the conversion of supercooled liquid droplets to ice and snow in mixed-phase clouds, the fraction of ice nuclei that nucleate ice in the atmosphere, ice crystal sedimentation speed, and wet scavenging in stratiform and convective clouds. Using a Generalized Linear Model as a variance-based sensitivity analysis, the relative contributions of each of the six parameters are quantified to gain a better understanding of the importance of their individual and two-way interaction effects on the liquid to ice proportion in mixed-phase clouds. Thus, the methodology implemented in the current study aims to search for the combination of cloud microphysical parameters in a GCM that produce the most accurate reproduction of observations of cloud thermodynamic phase, while simultaneously assessing the weaknesses of the parameterizations in the model. We find that the simulated proportion of liquid to ice in mixed-phase clouds is dominated by the fraction of active ice nuclei in the atmosphere and the WBF timescale. In a follow-up to this study, we apply these results to a fully-coupled GCM, CESM, and find that cloud thermodynamic phase has profound ramifications for the uncertainty associated with climate sensitivity estimates.

CO2 flux over young and snow-covered Arctic pack ice in winter and spring

NASA Astrophysics Data System (ADS)

Nomura, Daiki; Granskog, Mats A.; Fransson, Agneta; Chierici, Melissa; Silyakova, Anna; Ohshima, Kay I.; Cohen, Lana; Delille, Bruno; Hudson, Stephen R.; Dieckmann, Gerhard S.

2018-06-01

Rare CO2 flux measurements from Arctic pack ice show that two types of ice contribute to the release of CO2 from the ice to the atmosphere during winter and spring: young, thin ice with a thin layer of snow and older (several weeks), thicker ice with thick snow cover. Young, thin sea ice is characterized by high salinity and high porosity, and snow-covered thick ice remains relatively warm ( > -7.5 °C) due to the insulating snow cover despite air temperatures as low as -40 °C. Therefore, brine volume fractions of these two ice types are high enough to provide favorable conditions for gas exchange between sea ice and the atmosphere even in mid-winter. Although the potential CO2 flux from sea ice decreased due to the presence of the snow, the snow surface is still a CO2 source to the atmosphere for low snow density and thin snow conditions. We found that young sea ice that is formed in leads without snow cover produces CO2 fluxes an order of magnitude higher than those in snow-covered older ice (+1.0 ± 0.6 mmol C m-2 day-1 for young ice and +0.2 ± 0.2 mmol C m-2 day-1 for older ice).

Next-Generation Angular Distribution Models for Top-of-Atmosphere Radiative Flux Calculation from CERES Instruments: Validation

NASA Technical Reports Server (NTRS)

Su, W.; Corbett, J.; Eitzen, Z.; Liang, L.

2015-01-01

Radiative fluxes at the top of the atmosphere (TOA) from the Clouds and the Earth's Radiant Energy System (CERES) instrument are fundamental variables for understanding the Earth's energy balance and how it changes with time. TOA radiative fluxes are derived from the CERES radiance measurements using empirical angular distribution models (ADMs). This paper evaluates the accuracy of CERES TOA fluxes using direct integration and flux consistency tests. Direct integration tests show that the overall bias in regional monthly mean TOA shortwave (SW) flux is less than 0.2Wm(exp -2) and the RMSE is less than 1.1Wm(exp -2). The bias and RMSE are very similar between Terra and Aqua. The bias in regional monthly mean TOA LW fluxes is less than 0.5Wm(exp -2) and the RMSE is less than 0.8Wm(exp -)2 for both Terra and Aqua. The accuracy of the TOA instantaneous flux is assessed by performing tests using fluxes inverted from nadir- and oblique-viewing angles using CERES along-track observations and temporally and spatially matched MODIS observations, and using fluxes inverted from multi-angle MISR observations. The averaged TOA instantaneous SW flux uncertainties from these two tests are about 2.3% (1.9Wm(exp -2) over clear ocean, 1.6% (4.5Wm(exp -2) over clear land, and 2.0% (6.0Wm(exp -) over clear snow/ice; and are about 3.3% (9.0Wm(exp -2), 2.7% (8.4Wm(exp -2), and 3.7% (9.9Wm(exp -2) over ocean, land, and snow/ice under all-sky conditions. The TOA SW flux uncertainties are generally larger for thin broken clouds than for moderate and thick overcast clouds. The TOA instantaneous daytime LW flux uncertainties derived from the CERESMODIS test are 0.5% (1.5Wm(exp -2), 0.8% (2.4Wm(exp -2), and 0.7% (1.3Wm(exp -2) over clear ocean, land, and snow/ice; and are about 1.5% (3.5Wm(exp -2), 1.0% (2.9Wm(exp -2), and 1.1% (2.1Wm(exp -2) over ocean, land, and snow/ice under all-sky conditions. The TOA instantaneous nighttime LW flux uncertainties are about 0.5-1% (<2.0Wm(exp -2) for all surface types. Flux uncertainties caused by errors in scene identification are also assessed by using the collocated CALIPSO, CloudSat, CERES and MODIS data product. Errors in scene identification tend to underestimate TOA SW flux by about 0.6Wm(exp -2) and overestimate TOA daytime (nighttime) LW flux by 0.4 (0.2)Wm(exp -2) when all CERES viewing angles are considered.

Snow depth evolution on sea ice from Snow Buoy measurement

NASA Astrophysics Data System (ADS)

Nicolaus, M.; Arndt, S.; Hendricks, S.; Hoppmann, M.; Katlein, C.; König-Langlo, G.; Nicolaus, A.; Rossmann, H. L.; Schiller, M.; Schwegmann, S.; Langevin, D.

2016-12-01

Snow cover is an Essential Climate Variable. On sea ice, snow dominates the energy and momentum exchanges across the atmosphere-ice-ocean interfaces, and actively contributes to sea ice mass balance. Yet, snow depth on sea ice is one of the least known and most difficult to observe parameters of the Arctic and Antarctic; mainly due to its exceptionally high spatial and temporal variability. In this study; we present a unique time series dataset of snow depth and air temperature evolution on Arctic and Antarctic sea ice recorded by autonomous instruments. Snow Buoys record snow depth with four independent ultrasonic sensors, increasing the reliability of the measurements and allowing for additional analyses. Auxiliary measurements include surface and air temperature, barometric pressure and GPS position. 39 deployments of such Snow Buoys were achieved over the last three years either on drifting pack ice, on landfast sea ice or on an ice shelf. Here we highlight results from two pairs of Snow Buoys installed on drifting pack ice in the Weddell Sea. The data reveals large regional differences in the annual cycle of snow depth. Almost no reduction in snow depth (snow melt) was observed in the inner and southern part of the Weddell Sea, allowing a net snow accumulation of 0.2 to 0.9 m per year. In contrast, summer snow melt close to the ice edge resulted in a decrease of about 0.5 m during the summer 2015/16. Another array of eight Snow Buoys was installed on central Arctic sea ice in September 2015. Their air temperature record revealed exceptionally high air temperatures in the subsequent winter, even exceeding the melting point but with almost no impact on snow depth at that time. Future applications of Snow Buoys on Arctic and Antarctic sea ice will allow additional inter-annual studies of snow depth and snow processes, e.g. to support the development of snow depth data products from airborne and satellite data or though assimilation in numerical models.

NASA IceBridge: Scientific Insights from Airborne Surveys of the Polar Sea Ice Covers

NASA Astrophysics Data System (ADS)

Richter-Menge, J.; Farrell, S. L.

2015-12-01

The NASA Operation IceBridge (OIB) airborne sea ice surveys are designed to continue a valuable series of sea ice thickness measurements by bridging the gap between NASA's Ice, Cloud and Land Elevation Satellite (ICESat), which operated from 2003 to 2009, and ICESat-2, which is scheduled for launch in 2017. Initiated in 2009, OIB has conducted campaigns over the western Arctic Ocean (March/April) and Southern Oceans (October/November) on an annual basis when the thickness of sea ice cover is nearing its maximum. More recently, a series of Arctic surveys have also collected observations in the late summer, at the end of the melt season. The Airborne Topographic Mapper (ATM) laser altimeter is one of OIB's primary sensors, in combination with the Digital Mapping System digital camera, a Ku-band radar altimeter, a frequency-modulated continuous-wave (FMCW) snow radar, and a KT-19 infrared radiation pyrometer. Data from the campaigns are available to the research community at: http://nsidc.org/data/icebridge/. This presentation will summarize the spatial and temporal extent of the OIB campaigns and their complementary role in linking in situ and satellite measurements, advancing observations of sea ice processes across all length scales. Key scientific insights gained on the state of the sea ice cover will be highlighted, including snow depth, ice thickness, surface roughness and morphology, and melt pond evolution.

Factors Controlling Black Carbon Deposition in Snow in the Arctic

NASA Astrophysics Data System (ADS)

Qi, L.; Li, Q.; He, C.; Li, Y.

2015-12-01

This study evaluates the sensitivity of black carbon (BC) concentration in snow in the Arctic to BC emissions, dry deposition and wet scavenging efficiency using a 3D global chemical transport model GEOS-Chem driven by meteorological field GEOS-5. With all improvements, simulated median BC concentration in snow agrees with observation (19.2 ng g-1) within 10%, down from -40% in the default GEOS-Chem. When the previously missed gas flaring emissions (mainly located in Russia) are included, the total BC emission in the Arctic increases by 70%. The simulated BC in snow increases by 1-7 ng g-1, with the largest improvement in Russia. The discrepancy of median BC in snow in the whole Arctic reduces from -40% to -20%. In addition, recent measurements of BC dry deposition velocity suggest that the constant deposition velocity of 0.03 cm s-1 over snow and ice used in the GEOS-Chem is too low. So we apply resistance-in-series method to calculate the dry deposition velocity over snow and ice and the resulted dry deposition velocity ranges from 0.03 to 0.24 cm s-1. However, the simulated total BC deposition flux in the Arctic and BC in snow does not change, because the increased dry deposition flux has been compensated by decreased wet deposition flux. However, the fraction of dry deposition to total deposition increases from 16% to 25%. This may affect the mixing of BC and snow particles and further affect the radative forcing of BC deposited in snow. Finally, we reduced the scavenging efficiency of BC in mixed-phase clouds to account for the effect of Wegener-Bergeron-Findeisen (WBF) process based on recent observations. The simulated BC concentration in snow increases by 10-100%, with the largest increase in Greenland (100%), Tromsø (50%), Alaska (40%), and Canadian Arctic (30%). Annual BC loading in the Arctic increases from 0.25 to 0.43 mg m-2 and the lifetime of BC increases from 9.2 to 16.3 days. This indicates that BC simulation in the Arctic is really sensitive to the representation of BC scavenging efficiency. More measurements are needed to better understand the BC-cloud interaction and to constrain the model.

IOCCG Report Number 16, 2015 Ocean Colour Remote Sensing in Polar Seas . Chapter 2; The Polar Environment: Sun, Clouds, and Ice

NASA Technical Reports Server (NTRS)

Comiso, Josefino C.; Perovich, Don; Stamnes, Knut; Stuart, Venetia (Editor)

2015-01-01

The polar regions are places of extremes. There are months when the regions are enveloped in unending darkness, and months when they are in continuous daylight. During the daylight months the sun is low on the horizon and often obscured by clouds. In the dark winter months temperatures are brutally cold, and high winds and blowing snow are common. Even in summer, temperatures seldom rise above 0degC. The cold winter temperatures cause the ocean to freeze, forming sea ice. This sea ice cover acts as a barrier limiting the transfer of heat, moisture, and momentum between the atmosphere and the ocean. It also greatly complicates the optical signature of the surface. Taken together, these factors make the polar regions a highly challenging environment for optical remote sensing of the ocean.

Changes in cloud and aerosol cover (1980-2006) from reflectivity time series using SeaWiFS, N7-TOMS, EP-TOMS, SBUV-2, and OMI radiance data

NASA Astrophysics Data System (ADS)

Herman, J. R.; Labow, G.; Hsu, N. C.; Larko, D.

2009-01-01

The amount of solar radiation reflected back to space or reaching the Earth's surface is primarily governed by the amount of cloud cover and, to a much lesser extent, by Rayleigh scattering, aerosols, and various absorbing gases (e.g., O3, NO2, H2O). A useful measure of the effect of cloud plus aerosol cover is given by the amount that the 331 nm Lambert Equivalent Reflectivity (LER) of a scene exceeds the surface reflectivity for snow/ice-free scenes after Rayleigh scattering has been removed. Twenty-eight years of reflectivity data are available by overlapping data from several satellites: N7 (Nimbus 7, TOMS; 331 nm) from 1979 to 1992, SBUV-2 series (Solar Backscatter Ultraviolet, NOAA; 331 nm) 1985 to 2007, EP (Earth-Probe, TOMS; 331 nm) 1997 to 2006, SW (SeaWiFS; 412 nm) 1998 to 2006, and OMI (Ozone Measuring Instrument; 331 nm) 2004-2007. Only N7 and SW have a sufficiently long data record, Sun-synchronous orbits, and are adequately calibrated for long-term reflectivity trend estimation. Reflectivity data derived from these instruments and the SBUV-2 series are compared during the overlapping years. Key issues in determining long-term reflectivity changes that have occurred during the N7 and SW operating periods are discussed. The largest reflectivity changes in the 412 nm SW LER and 331 nm EP LER are found to occur near the equator and are associated with a large El Nino-Southern Oscillation event. Most other changes that have occurred are regional, such as the apparent cloud decrease over northern Europe since 1998. The fractional occurrence (fraction of days) of high reflectivity values over Hudson Bay, Canada (snow/ice and clouds) appears to have decreased when comparing reflectivity data from 1980 to 1992 to 1997-2006, suggesting shorter duration of ice in Hudson Bay since 1980.

Changes in Cloud and Aerosol Cover (1980-2006) from Reflectivity Time Series Using SeaWiFS, N7-TOMS, EP-TOMS, SBUV-2, and OMI Radiance Data

NASA Technical Reports Server (NTRS)

Herman, J. R.; Labow, G.; Hsu, N. C.; Larko, D.

2009-01-01

The amount of solar radiation reflected back to space or reaching the Earth's surface is primarily governed by the amount of cloud cover and, to a much lesser extent, by Rayleigh scatteri ng, aerosols, and various absorbing gases (e.g., O3, NO2, H2O). A useful measure of the effect of cloud plus aerosol cover is given by the amount that the 331 run Lambert Equivalent Reflectivity (LER) ofa scene exceeds the surfuce reflectivity for snow/ice-free scenes after Rayleigh scattering has been removed. Twenty-eight years of reflectivity data are available by overlapping data from several satellites: N7 (Nimbus 7, TOMS; 331 nm) from 1979 to 1992, SBUV-2 series (Solar Backscatter Ultraviolet, NOAA; 331 nm) 1985 to 2007, EP (Earth-Probe, TOMS; 331 nm) 1997 to 2006, SW (SeaWiFS; 412 nm) 1998 to 2006, and OMI (Ozone Measuring Instrument; 331 nm) 2004-2007. Only N7 and SW have a sufficiently long data record, Sun-synchronous orbits, and are adequately calibrated for long-term reflectivity trend estimation. Reflectivity data derived from these instruments and the SBUV-2 series are compared during the overlapping years. Key issues in determining long-term reflecti vity changes that have occurred during the N7 and SW operating periods are discussed. The largest reflectivity changes in the 412 nm SW LER and 331 nm EP LER are found to occur near the equator and are associated with a large EI Nino-Southern Oscillation event. Most other changes that have occurred are regional, such as the apparent cloud decrease over northern Europe since 1998. The fractional occurrence (fraction of days) of high reflectivity values over Hudson Bay, Canada (snow/ice and clouds) appears to have decreased when comparing reflectivity data from 1980 to 1992 to 1997-2006, suggesting shorter duration of ice in Hudson Bay since 1980.

On the extraordinary snow on the sea ice off East Antarctica in late winter, 2012

NASA Astrophysics Data System (ADS)

Toyota, Takenobu; Massom, Robert; Lecomte, Olivier; Nomura, Daiki; Heil, Petra; Tamura, Takeshi; Fraser, Alexander D.

2016-09-01

In late winter-early spring 2012, the second Sea Ice Physics and Ecosystems Experiment (SIPEX II) was conducted off Wilkes Land, East Antarctica, onboard R/V Aurora Australis. The sea-ice conditions were characterized by significantly thick first-year ice and snow, trapping the ship for about 10 days in the near coastal region. The deep snow cover was particularly remarkable, in that its average value of 0.45 m was almost three times that observed between 1992 and 2007 in the region. To reveal factors responsible, we used in situ observations and ERA-Interim reanalysis (1990-2012) to examine the relative contribution of the different components of the local-regional snow mass balance equation i.e., snow accumulation on sea ice, precipitation minus evaporation (P-E), and loss by (i) snow-ice formation and (ii) entering into leads due to drifting snow. Results show no evidence for significantly high P-E in the winter of 2012. Ice core analysis has shown that although the snow-ice layer was relatively thin, indicating less transformation from snow to snow-ice in 2012 as compared to measurements from 2007, the difference was not enough to explain the extraordinarily deep snow. Based on these results, we deduce that lower loss of snow into leads was probably responsible for the extraordinary snow in 2012. Statistical analysis and satellite images suggest that the reduction in loss of snow into leads is attributed to rough ice surface associated with active deformation processes and larger floe size due to sea-ice expansion. This highlights the importance of snow-sea ice interaction in determining the mean snow depth on Antarctic sea ice.

Environmental Technology Verification Program Advanced Monitoring Systems Center Quality Assurance Project Plan for Verification of Black Carbon Monitors

EPA Science Inventory

Black carbon is a term that is commonly used to describe strongly light absorbing carbon (LAC), which is thought to play a significant role in global climate change through direct absorption of light, interaction with clouds, and by reducing the reflectivity of snow and ice. BC ...

Winter snow conditions on Arctic sea ice north of Svalbard during the Norwegian young sea ICE (N-ICE2015) expedition

NASA Astrophysics Data System (ADS)

Merkouriadi, Ioanna; Gallet, Jean-Charles; Graham, Robert M.; Liston, Glen E.; Polashenski, Chris; Rösel, Anja; Gerland, Sebastian

2017-10-01

Snow is a crucial component of the Arctic sea ice system. Its thickness and thermal properties control heat conduction and radiative fluxes across the ocean, ice, and atmosphere interfaces. Hence, observations of the evolution of snow depth, density, thermal conductivity, and stratigraphy are crucial for the development of detailed snow numerical models predicting energy transfer through the snow pack. Snow depth is also a major uncertainty in predicting ice thickness using remote sensing algorithms. Here we examine the winter spatial and temporal evolution of snow physical properties on first-year (FYI) and second-year ice (SYI) in the Atlantic sector of the Arctic Ocean, during the Norwegian young sea ICE (N-ICE2015) expedition (January to March 2015). During N-ICE2015, the snow pack consisted of faceted grains (47%), depth hoar (28%), and wind slab (13%), indicating very different snow stratigraphy compared to what was observed in the Pacific sector of the Arctic Ocean during the SHEBA campaign (1997-1998). Average snow bulk density was 345 kg m-3 and it varied with ice type. Snow depth was 41 ± 19 cm in January and 56 ± 17 cm in February, which is significantly greater than earlier suggestions for this region. The snow water equivalent was 14.5 ± 5.3 cm over first-year ice and 19 ± 5.4 cm over second-year ice.

Remote Sensing of Energy Distribution Characteristics over the Tibet

NASA Astrophysics Data System (ADS)

Shi, J.; Husi, L.; Wang, T.

2017-12-01

The overall objective of our study is to quantify the spatiotemporal characteristics and changes of typical factors dominating water and energy cycles in the Tibet region. Especially, we focus on variables of clouds optical & microphysical parameters, surface shortwave and longwave radiation. Clouds play a key role in the Tibetan region's water and energy cycles. They seriously impact the precipitation, temperature and surface energy distribution. Considering that proper cloud products with relatively higher spatial and temporal sampling and with satisfactory accuracy are serious lacking in the Tibet region, except cloud optical thickness, cloud effective radius and liquid/ice water content, the cloud coverage dynamics at hourly scales also analyzed jointly based on measurements of Himawari-8, and MODIS. Surface radiation, as an important energy source in perturbating the Tibet's evapotranspiration, snow and glacier melting, is a controlling factor in energy balance in the Tibet region. All currently available radiation products in this area are not suitable for regional scale study of water and energy exchange and snow/glacier melting due to their coarse resolution and low accuracies because of cloud and topography. A strategy for deriving land surface upward and downward radiation by fusing optical and microwave remote sensing data is proposed. At the same time, the big topographic effect on the surface radiation are also modelled and analyzed over the Tibet region.

Global shortwave energy budget at the earth's surface from ERBE observations

NASA Technical Reports Server (NTRS)

Breon, Francois-Marie; Frouin, Robert

1994-01-01

A method is proposed to compute the net solar (shortwave) irradiance at the earth's surface from Earth Radiation Budget Experiment (ERBE) data in the S4 format. The S4 data are monthly averaged broadband planetary albedo collected at selected times during the day. Net surface shortwave irradiance is obtained from the shortwave irradiance incident at the top of the atmosphere (known) by subtracting both the shortwave energy flux reflected by the earth-atmosphere system (measured) and the energy flux absorbed by the atmosphere (modeled). Precalculated atmospheric- and surface-dependent functions that characterize scattering and absorption in the atmosphere are used, which makes the method easily applicable and computationally efficient. Four surface types are distinguished, namely, ocean, vegetation, desert, and snow/ice. Over the tropical Pacific Ocean, the estimates based on ERBE data compare well with those obtained from International Satellite Cloud Climatology Project (ISCCP) B3 data. For the 9 months analyzed the linear correlation coefficient and the standard difference between the two datasets are 0.95 and 14 W/sq m (about 6% of the average shortwave irradiance), respectively, and the bias is 15 W/sq m (higher ERBE values). The bias, a strong function of ISCCP satellite viewing zenith angle, is mostly in the ISCCP-based estimates. Over snow/ice, vegetation, and desert no comparison is made with other satellite-based estimates, but theoretical calculations using the discrete ordinate method suggest that over highly reflective surfaces (snow/ice, desert) the model, which accounts crudely for multiple reflection between the surface and clouds, may substantially overestimate the absorbed solar energy flux at the surface, especially when clouds are optically thick. The monthly surface shortwave irradiance fields produced for 1986 exhibit the main features characteristic of the earth's climate. As found in other studies, our values are generally higher than Esbensen and Kushnir's by as much as 80 W/sq m in the tropical oceans. A cloud parameter, defined as the difference between clear-sky and actual irradiances normalized to top-of-atmosphere clear-sky irradiance, is also examined. This parameter, minimally affected by sun zenith angle, is higher in the midlatitude regions of storm tracks than in the intertropical convergence zone (ITCZ), suggesting that, on average, the higher cloud coverage in midlatitudes is more effective at reducing surface shortwave irradiance than opaque, convective, yet sparser clouds in the ITCZ. Surface albedo estimates are realistic, generally not exceeding 0.06 in the ocean, as high as 0.9 in polar regions, and reaching 0.5 in the Sahara and Arabian deserts.

Fingerprints of a riming event on cloud radar Doppler spectra: observations and modeling

DOE PAGES

Kalesse, Heike; Szyrmer, Wanda; Kneifel, Stefan; ...

2016-03-09

In this paper, Radar Doppler spectra measurements are exploited to study a riming event when precipitating ice from a seeder cloud sediment through a supercooled liquid water (SLW) layer. The focus is on the "golden sample" case study for this type of analysis based on observations collected during the deployment of the Atmospheric Radiation Measurement Program's (ARM) mobile facility AMF2 at Hyytiälä, Finland, during the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) field campaign. The presented analysis of the height evolution of the radar Doppler spectra is a state-of-the-art retrieval with profiling cloud radars in SLW layers beyondmore » the traditional use of spectral moments. Dynamical effects are considered by following the particle population evolution along slanted tracks that are caused by horizontal advection of the cloud under wind shear conditions. In the SLW layer, the identified liquid peak is used as an air motion tracer to correct the Doppler spectra for vertical air motion and the ice peak is used to study the radar profiles of rimed particles. A 1-D steady-state bin microphysical model is constrained using the SLW and air motion profiles and cloud top radar observations. The observed radar moment profiles of the rimed snow can be simulated reasonably well by the model, but not without making several assumptions about the ice particle concentration and the relative role of deposition and aggregation. In conclusion, this suggests that in situ observations of key ice properties are needed to complement the profiling radar observations before process-oriented studies can effectively evaluate ice microphysical parameterizations.« less

Evaluation of Cloud-Resolving Model Intercomparison Simulations Using TWP-ICE Observations: Precipitation and Cloud Structure

NASA Technical Reports Server (NTRS)

Varble, Adam; Fridlind, Ann M.; Zipser, Edward J.; Ackerman, Andrew S.; Chaboureau, Jean-Pierre; Fan, Jiwen; Hill, Adrian; McFarlane, Sally A.; Pinty, Jean-Pierre; Shipway, Ben

2011-01-01

The Tropical Warm Pool.International Cloud Experiment (TWP ]ICE) provided extensive observational data sets designed to initialize, force, and constrain atmospheric model simulations. In this first of a two ]part study, precipitation and cloud structures within nine cloud ]resolving model simulations are compared with scanning radar reflectivity and satellite infrared brightness temperature observations during an active monsoon period from 19 to 25 January 2006. Seven of nine simulations overestimate convective area by 20% or more leading to general overestimation of convective rainfall. This is balanced by underestimation of stratiform rainfall by 5% to 50% despite overestimation of stratiform area by up to 65% because of a preponderance of very low stratiform rain rates in all simulations. All simulations fail to reproduce observed radar reflectivity distributions above the melting level in convective regions and throughout the troposphere in stratiform regions. Observed precipitation ]sized ice reaches higher altitudes than simulated precipitation ]sized ice despite some simulations that predict lower than observed top ]of ]atmosphere infrared brightness temperatures. For the simulations that overestimate radar reflectivity aloft, graupel is the cause with one ]moment microphysics schemes whereas snow is the cause with two ]moment microphysics schemes. Differences in simulated radar reflectivity are more highly correlated with differences in mass mean melted diameter (Dm) than differences in ice water content. Dm is largely dependent on the mass ]dimension relationship and gamma size distribution parameters such as size intercept (N0) and shape parameter (m). Having variable density, variable N0, or m greater than zero produces radar reflectivities closest to those observed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kalesse, Heike; Szyrmer, Wanda; Kneifel, Stefan

In this paper, Radar Doppler spectra measurements are exploited to study a riming event when precipitating ice from a seeder cloud sediment through a supercooled liquid water (SLW) layer. The focus is on the "golden sample" case study for this type of analysis based on observations collected during the deployment of the Atmospheric Radiation Measurement Program's (ARM) mobile facility AMF2 at Hyytiälä, Finland, during the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) field campaign. The presented analysis of the height evolution of the radar Doppler spectra is a state-of-the-art retrieval with profiling cloud radars in SLW layers beyondmore » the traditional use of spectral moments. Dynamical effects are considered by following the particle population evolution along slanted tracks that are caused by horizontal advection of the cloud under wind shear conditions. In the SLW layer, the identified liquid peak is used as an air motion tracer to correct the Doppler spectra for vertical air motion and the ice peak is used to study the radar profiles of rimed particles. A 1-D steady-state bin microphysical model is constrained using the SLW and air motion profiles and cloud top radar observations. The observed radar moment profiles of the rimed snow can be simulated reasonably well by the model, but not without making several assumptions about the ice particle concentration and the relative role of deposition and aggregation. In conclusion, this suggests that in situ observations of key ice properties are needed to complement the profiling radar observations before process-oriented studies can effectively evaluate ice microphysical parameterizations.« less

Observations of Recent Arctic Sea Ice Volume Loss and Its Impact on Ocean-Atmosphere Energy Exchange and Ice Production

NASA Technical Reports Server (NTRS)

Kurtz, N. T.; Markus, T.; Farrell, S. L.; Worthen, D. L.; Boisvert, L. N.

2011-01-01

Using recently developed techniques we estimate snow and sea ice thickness distributions for the Arctic basin through the combination of freeboard data from the Ice, Cloud, and land Elevation Satellite (ICESat) and a snow depth model. These data are used with meteorological data and a thermodynamic sea ice model to calculate ocean-atmosphere heat exchange and ice volume production during the 2003-2008 fall and winter seasons. The calculated heat fluxes and ice growth rates are in agreement with previous observations over multiyear ice. In this study, we calculate heat fluxes and ice growth rates for the full distribution of ice thicknesses covering the Arctic basin and determine the impact of ice thickness change on the calculated values. Thinning of the sea ice is observed which greatly increases the 2005-2007 fall period ocean-atmosphere heat fluxes compared to those observed in 2003. Although there was also a decline in sea ice thickness for the winter periods, the winter time heat flux was found to be less impacted by the observed changes in ice thickness. A large increase in the net Arctic ocean-atmosphere heat output is also observed in the fall periods due to changes in the areal coverage of sea ice. The anomalously low sea ice coverage in 2007 led to a net ocean-atmosphere heat output approximately 3 times greater than was observed in previous years and suggests that sea ice losses are now playing a role in increasing surface air temperatures in the Arctic.

Airborne radar surveys of snow depth over Antarctic sea ice during Operation IceBridge

NASA Astrophysics Data System (ADS)

Panzer, B.; Gomez-Garcia, D.; Leuschen, C.; Paden, J. D.; Gogineni, P. S.

2012-12-01

Over the last decade, multiple satellite-based laser and radar altimeters, optimized for polar observations, have been launched with one of the major objectives being the determination of global sea ice thickness and distribution [5, 6]. Estimation of sea-ice thickness from these altimeters relies on freeboard measurements and the presence of snow cover on sea ice affects this estimate. Current means of estimating the snow depth rely on daily precipitation products and/or data from passive microwave sensors [2, 7]. Even a small uncertainty in the snow depth leads to a large uncertainty in the sea-ice thickness estimate. To improve the accuracy of the sea-ice thickness estimates and provide validation for measurements from satellite-based sensors, the Center for Remote Sensing of Ice Sheets deploys the Snow Radar as a part of NASA Operation IceBridge. The Snow Radar is an ultra-wideband, frequency-modulated, continuous-wave radar capable of resolving snow depth on sea ice from 5 cm to more than 2 meters from long-range, airborne platforms [4]. This paper will discuss the algorithm used to directly extract snow depth estimates exclusively using the Snow Radar data set by tracking both the air-snow and snow-ice interfaces. Prior work in this regard used data from a laser altimeter for tracking the air-snow interface or worked under the assumption that the return from the snow-ice interface was greater than that from the air-snow interface due to a larger dielectric contrast, which is not true for thick or higher loss snow cover [1, 3]. This paper will also present snow depth estimates from Snow Radar data during the NASA Operation IceBridge 2010-2011 Antarctic campaigns. In 2010, three sea ice flights were flown, two in the Weddell Sea and one in the Amundsen and Bellingshausen Seas. All three flight lines were repeated in 2011, allowing an annual comparison of snow depth. In 2011, a repeat pass of an earlier flight in the Weddell Sea was flown, allowing for a comparison of snow depths with two weeks elapsed between passes. [1] Farrell, S.L., et al., "A First Assessment of IceBridge Snow and Ice Thickness Data Over Arctic Sea Ice," IEEE Tran. Geoscience and Remote Sensing, Vol. 50, No. 6, pp. 2098-2111, June 2012. [2] Kwok, R., and G. F. Cunningham, "ICESat over Arctic sea ice: Estimation of snow depth and ice thickness," J. Geophys. Res., 113, C08010, 2008. [3] Kwok, R., et al., "Airborne surveys of snow depth over Arctic sea ice," J. Geophys. Res., 116, C11018, 2011. [4] Panzer, B., et al., "An ultra-wideband, microwave radar for measuring snow thickness on sea ice and mapping near-surface internal layers in polar firn," Submitted to J. Glaciology, July 23, 2012. [5] Wingham, D.J., et al., "CryoSat: A Mission to Determine the Fluctuations in Earth's Land and Marine Ice Fields," Advances in Space Research, Vol. 37, No. 4, pp. 841-871, 2006. [6] Zwally, H. J., et al., "ICESat's laser measurements of polar ice, atmosphere, ocean, and land," J. Geodynamics, Vol. 34, No. 3-4, pp. 405-445, Oct-Nov 2002. [7] Zwally, H. J., et al., "ICESat measurements of sea ice freeboard and estimates of sea ice thickness in the Weddell Sea," J. Geophys. Res., 113, C02S15, 2008.

MODIS Snow-Cover Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vinvent V.; DiGirolamo, Nicolo; Bayr, Klaus J.; Houser, Paul (Technical Monitor)

2001-01-01

On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS). Many geophysical products are derived from MODIS data including global snow-cover products. These products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. MODIS snow-cover products represent potential improvement to the currently available operation products mainly because the MODIS products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set is generated for long-term climates studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the product. The snow product suite starts with a 500-m resolution swath snow-cover map which is gridded to the Integerized Sinusoidal Grid to produce daily and eight-day composite tile products. The sequence then proceeds to a climate-modeling grid product at 5-km spatial resolution, with both daily and eight-day composite products. A case study from March 6, 2000, involving MODIS data and field and aircraft measurements, is presented. Near-term enhancements include daily snow albedo and fractional snow cover.

Surface and Atmospheric Contributions to Passive Microwave Brightness Temperatures for Falling Snow Events

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail; Johnson, Benjamin T.

2011-01-01

Physically based passive microwave precipitation retrieval algorithms require a set of relationships between satellite -observed brightness temperatures (TBs) and the physical state of the underlying atmosphere and surface. These relationships are nonlinear, such that inversions are ill ]posed especially over variable land surfaces. In order to elucidate these relationships, this work presents a theoretical analysis using TB weighting functions to quantify the percentage influence of the TB resulting from absorption, emission, and/or reflection from the surface, as well as from frozen hydrometeors in clouds, from atmospheric water vapor, and from other contributors. The percentage analysis was also compared to Jacobians. The results are presented for frequencies from 10 to 874 GHz, for individual snow profiles, and for averages over three cloud-resolving model simulations of falling snow. The bulk structure (e.g., ice water path and cloud depth) of the underlying cloud scene was found to affect the resultant TB and percentages, producing different values for blizzard, lake effect, and synoptic snow events. The slant path at a 53 viewing angle increases the hydrometeor contributions relative to nadir viewing channels. Jacobians provide the magnitude and direction of change in the TB values due to a change in the underlying scene; however, the percentage analysis provides detailed information on how that change affected contributions to the TB from the surface, hydrometeors, and water vapor. The TB percentage information presented in this paper provides information about the relative contributions to the TB and supplies key pieces of information required to develop and improve precipitation retrievals over land surfaces.

MODIS Snow and Sea Ice Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.

2004-01-01

In this chapter, we describe the suite of Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua snow and sea ice products. Global, daily products, developed at Goddard Space Flight Center, are archived and distributed through the National Snow and Ice Data Center at various resolutions and on different grids useful for different communities Snow products include binary snow cover, snow albedo, and in the near future, fraction of snow in a 5OO-m pixel. Sea ice products include ice extent determined with two different algorithms, and sea ice surface temperature. The algorithms used to develop these products are described. Both the snow and sea ice products, available since February 24,2000, are useful for modelers. Validation of the products is also discussed.

The Microphysical Properties of Convective Precipitation Over the Tibetan Plateau by a Subkilometer Resolution Cloud-Resolving Simulation

NASA Astrophysics Data System (ADS)

Gao, Wenhua; Liu, Liping; Li, Jian; Lu, Chunsong

2018-03-01

The microphysical properties of convective precipitation over the Tibetan Plateau are unique because of the extremely high topography and special atmospheric conditions. In this study, the ground-based cloud radar and disdrometer observations as well as high-resolution Weather Research and Forecasting simulations with the Chinese Academy of Meteorological Sciences microphysics and four other microphysical schemes are used to investigate the microphysics and precipitation mechanisms of a convection event on 24 July 2014. The Weather Research and Forecasting-Chinese Academy of Meteorological Sciences simulation reasonably reproduces the spatial distribution of 24-hr accumulated rainfall, yet the temporal evolution of rain rate has a delay of 1-3 hr. The model reflectivity shares the common features with the cloud radar observations. The simulated raindrop size distributions demonstrate more of small- and large-size raindrops produced with the increase of rain rate, suggesting that changeable shape parameter should be used in size distribution. Results show that abundant supercooled water exists through condensation of water vapor above the freezing layer. The prevailing ice crystal microphysical processes are depositional growth and autoconversion of ice crystal to snow. The dominant source term of snow/graupel is riming of supercooled water. Sedimentation of graupel can play a vital role in the formation of precipitation, but melting of snow is rather small and quite different from that in other regions. Furthermore, water vapor budgets suggest that surface moisture flux be the principal source of water vapor and self-circulation of moisture happen at the beginning of convection, while total moisture flux convergence determine condensation and precipitation during the convective process over the Tibetan Plateau.

On The Importance of Connecting Laboratory Measurements of Ice Crystal Growth with Model Parameterizations: Predicting Ice Particle Properties

NASA Astrophysics Data System (ADS)

Harrington, J. Y.

2017-12-01

Parameterizing the growth of ice particles in numerical models is at an interesting cross-roads. Most parameterizations developed in the past, including some that I have developed, parse model ice into numerous categories based primarily on the growth mode of the particle. Models routinely possess smaller ice, snow crystals, aggregates, graupel, and hail. The snow and ice categories in some models are further split into subcategories to account for the various shapes of ice. There has been a relatively recent shift towards a new class of microphysical models that predict the properties of ice particles instead of using multiple categories and subcategories. Particle property models predict the physical characteristics of ice, such as aspect ratio, maximum dimension, effective density, rime density, effective area, and so forth. These models are attractive in the sense that particle characteristics evolve naturally in time and space without the need for numerous (and somewhat artificial) transitions among pre-defined classes. However, particle property models often require fundamental parameters that are typically derived from laboratory measurements. For instance, the evolution of particle shape during vapor depositional growth requires knowledge of the growth efficiencies for the various axis of the crystals, which in turn depends on surface parameters that can only be determined in the laboratory. The evolution of particle shapes and density during riming, aggregation, and melting require data on the redistribution of mass across a crystals axis as that crystal collects water drops, ice crystals, or melts. Predicting the evolution of particle properties based on laboratory-determined parameters has a substantial influence on the evolution of some cloud systems. Radiatively-driven cirrus clouds show a broader range of competition between heterogeneous nucleation and homogeneous freezing when ice crystal properties are predicted. Even strongly convective squall lines show a substantial influence to predicted particle properties: The more natural evolution of ice crystals during riming produces graupel-like particles with size and fall-speeds required for the formation of a classic transition zone and extended stratiform precipitation region.

14 CFR 139.313 - Snow and ice control.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 3 2014-01-01 2014-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each... carry out a snow and ice control plan in a manner authorized by the Administrator. (b) The snow and ice...

14 CFR 139.313 - Snow and ice control.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each... carry out a snow and ice control plan in a manner authorized by the Administrator. (b) The snow and ice...

14 CFR 139.313 - Snow and ice control.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 3 2011-01-01 2011-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each... carry out a snow and ice control plan in a manner authorized by the Administrator. (b) The snow and ice...

14 CFR 139.313 - Snow and ice control.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 3 2013-01-01 2013-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each... carry out a snow and ice control plan in a manner authorized by the Administrator. (b) The snow and ice...

14 CFR 139.313 - Snow and ice control.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 3 2012-01-01 2012-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each... carry out a snow and ice control plan in a manner authorized by the Administrator. (b) The snow and ice...

Response of Alpine Grassland Vegetation Phenology to Snow Accumulation and Melt in Namco Basin

NASA Astrophysics Data System (ADS)

Chen, S.; Cui, X.; Liang, T.

2018-04-01

Snow/ice accumulation and melt, as a vital part of hydrological processes, is close related with vegetation activities. Taking Namco basin for example, based on multisource remote sensing data and the ground observation data of temperature and precipitation, phenological information was extracted by S-G filtering and dynamic threshold method. Daily snow cover fraction was calculated with daily cloud-free snow cover maps. Evolution characteristics of grassland vegetation greening, growth length and daily snow cover fraction and their relationship were analyzed from 2001 to 2013. The results showed that most of grassland vegetation had advanced greening and prolong growth length trend in Namco basin. There were negative correlations between snow cover fraction and vegetation greening or growth length. The response of vegetation phenology to snow cover fraction is more sensitive than that to temperature in spring. Meanwhile, vegetation growth condition turned worse with advanced greening and prolong growth length. To a certain extent, our research reveals the relationship between grassland vegetation growth cycle and snow in alpine ecosystem. It has provided reference to research the response mechanism of alpine grassland ecosystem to climate changes.

Active and Passive 3D Vector Radiative Transfer with Preferentially-Aligned Ice Particles

NASA Technical Reports Server (NTRS)

Adams, Ian S.; Munchak, Stephen J.; Pelissier, Craig S.; Kuo, Kwo-Sen; Heymsfield, Gerald M.

2017-01-01

For the purposes of interpreting active (radar) and passive (radiometer) microwave and millimeter wave remote sensing data, we have constructed a consistent radiative transfer modeling framework to simulate the responses for arbitrary sensors with differing sensing geometries and hardware configurations. As part of this work, we have implemented a recent method for calculating the electromagnetic properties of individual ice crystals and snow flakes. These calculations will allow us to exploit polarized remote sensing observations to discriminate different particles types and elucidate dynamics of cloud and precipitating systems.

Aerosol Impacts on California Winter Clouds and Precipitation during CalWater 2011: Local Pollution versus Long-Range Transported Dust

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fan, Jiwen; Leung, Lai-Yung R.; DeMott, Paul J.

2014-01-03

Mineral dust aerosols often observed over California in winter and spring, associated with long-range transport from Asia and Sahara, have been linked to enhanced precipitation based on observations. Local anthropogenic pollution, on the other hand, was shown in previous observational and modeling studies to reduce precipitation. Here we incorporate recent developments in ice nucleation parameterizations to link aerosols with ice crystal formation in a spectral-bin cloud microphysical model coupled with the Weather Research and Forecasting (WRF) model, to examine the relative and combined impacts of dust and local pollution particles on cloud properties and precipitation type and intensity. Simulations aremore » carried out for two cloud cases with contrasting meteorology and cloud dynamics that occurred on February 16 (FEB16) and March 02 (MAR02) from the CalWater 2011 field campaign. In both cases, observations show the presence of dust and biological particles in a relative pristine environment. The simulated cloud microphysical properties and precipitation show reasonable agreement with aircraft and surface measurements. Model sensitivity experiments indicate that in the pristine environment, the dust and biological aerosol layers increase the accumulated precipitation by 10-20% from the Central Valley to the Sierra Nevada Mountains for both FEB16 and MAR02 due to a ~40% increase in snow formation, validating the observational hypothesis. Model results show that local pollution increases precipitation over the windward slope of the mountains by few percent due to increased snow formation when dust is present but reduces precipitation by 5-8% if dust is removed on FEB16. The effects of local pollution on cloud microphysics and precipitation strongly depend on meteorology including the strength of the Sierra Barrier Jet, and cloud dynamics. This study further underscores the importance of the interactions between local pollution, dust, and environmental conditions for assessing aerosol effects on cold season precipitation in California.« less

Snow depth on Arctic and Antarctic sea ice derived from autonomous (Snow Buoy) measurements

NASA Astrophysics Data System (ADS)

Nicolaus, Marcel; Arndt, Stefanie; Hendricks, Stefan; Heygster, Georg; Huntemann, Marcus; Katlein, Christian; Langevin, Danielle; Rossmann, Leonard; Schwegmann, Sandra

2016-04-01

The snow cover on sea ice received more and more attention in recent sea ice studies and model simulations, because its physical properties dominate many sea ice and upper ocean processes. In particular; the temporal and spatial distribution of snow depth is of crucial importance for the energy and mass budgets of sea ice, as well as for the interaction with the atmosphere and the oceanic freshwater budget. Snow depth is also a crucial parameter for sea ice thickness retrieval algorithms from satellite altimetry data. Recent time series of Arctic sea ice volume only use monthly snow depth climatology, which cannot take into account annual changes of the snow depth and its properties. For Antarctic sea ice, no such climatology is available. With a few exceptions, snow depth on sea ice is determined from manual in-situ measurements with very limited coverage of space and time. Hence the need for more consistent observational data sets of snow depth on sea ice is frequently highlighted. Here, we present time series measurements of snow depths on Antarctic and Arctic sea ice, recorded by an innovative and affordable platform. This Snow Buoy is optimized to autonomously monitor the evolution of snow depth on sea ice and will allow new insights into its seasonality. In addition, the instruments report air temperature and atmospheric pressure directly into different international networks, e.g. the Global Telecommunication System (GTS) and the International Arctic Buoy Programme (IABP). We introduce the Snow Buoy concept together with technical specifications and results on data quality, reliability, and performance of the units. We highlight the findings from four buoys, which simultaneously drifted through the Weddell Sea for more than 1.5 years, revealing unique information on characteristic regional and seasonal differences. Finally, results from seven snow buoys co-deployed on Arctic sea ice throughout the winter season 2015/16 suggest the great importance of local effects, weather events, and potential influences of dynamic sea ice processes on snow accumulation.

The "Physical feedbacks of Arctic PBL, Sea ice, Cloud and AerosoL (PASCAL)" campaign during the Arctic POLARSTERN expedition PS106 in spring 2017.

NASA Astrophysics Data System (ADS)

Macke, A.

2017-12-01

The Polar regions are important components in the global climate system. The widespread surface snow and ice cover strongly impacts the surface energy budget, which is tightly coupled to global atmospheric and oceanic circulations. The coupling of sea ice, clouds and aerosol in the transition zone between Open Ocean and sea ice is the focus of the PASCAL investigations to improve our understanding of the recent dramatic reduction in Arctic sea-ice. A large variety of active/passive remote sensing, in-situ-aerosol observation, and spectral irradiance measurements have been obtained during the German research icebreaker POLARSTERN expedition PS106, and provided detailed information on the atmospheric spatiotemporal structure, aerosol and cloud chemical and microphysical properties as well as the resulting surface radiation budget. Nearly identical measurements at the AWIPEV Base (German - French Research Base) in Ny-Ålesund close to the Open Ocean and collocated airborne activities of the POLAR 5 and POLAR 6 AWI aircraft in the framework of the ACLOUD project have been carried out in parallel. The airborne observations have been supplemented by observations of the boundary layer structure (mean and turbulent quantities) from a tethered balloon reaching up to 1500 m, which was operated at an ice floe station nearby POLARSTERN for two weeks. All observational activities together with intense modelling at various scales are part of the German Collaborative Research Cluster TR 172 "Arctic Amplification" that aims to provide an unprecedented picture of the complex Arctic weather and climate system. The presentation provides an overview of the measurements on-board POLARSTERN and on the ice floe station during PASCAL from May 24 to July 21 2017. We conclude how these and future similar measurements during the one-year ice drift of POLARSTERN in the framework of MOSAiC help to reduce uncertainties in Arctic aerosol-cloud interaction, cloud radiative forcing, and surface/atmosphere feedback mechanisms.

Is snow-ice now a major contributor to sea ice mass balance in the western Transpolar Drift region?

NASA Astrophysics Data System (ADS)

Graham, R. M.; Merkouriadi, I.; Cheng, B.; Rösel, A.; Granskog, M. A.

2017-12-01

During the Norwegian young sea ICE (N-ICE2015) campaign, which took place in the first half of 2015 north of Svalbard, a deep winter snow pack (50 cm) on sea ice was observed, that was 50% thicker than earlier climatological studies suggested for this region. Moreover, a significant fraction of snow contributed to the total ice mass in second-year ice (SYI) (9% on average). Interestingly, very little snow (3% snow by mass) was present in first-year ice (FYI). The combination of sea ice thinning and increased precipitation north of Svalbard is expected to promote the formation of snow-ice. Here we use the 1-D snow/ice thermodynamic model HIGHTSI forced with reanalysis data, to show that for the case study of N-ICE2015, snow-ice would even form over SYI with an initial thickness of 2 m. In current conditions north of Svalbard, snow-ice is ubiquitous and contributes to the thickness growth up to 30%. This contribution is important, especially in the absence of any bottom thermodynamic growth due to the thick insulating snow cover. Growth of FYI north of Svalbard is mainly controlled by the timing of growth onset relative to snow precipitation events and cold spells. These usually short-lived conditions are largely determined by the frequency of storms entering the Arctic from the Atlantic Ocean. In our case, a later freeze onset was favorable for FYI growth due to less snow accumulation in early autumn. This limited snow-ice formation but promoted bottom thermodynamic growth. We surmise these findings are related to a regional phenomenon in the Atlantic sector of the Arctic, with frequent storm events which bring increasing amounts of precipitation in autumn and winter, and also affect the duration of cold temperatures required for ice growth in winter. We discuss the implications for the importance of snow-ice in the future Arctic, formerly believed to be non-existent in the central Arctic due to thick perennial ice.

An Ultra-Wideband, Microwave Radar for Measuring Snow Thickness on Sea Ice and Mapping Near-Surface Internal Layers in Polar Firn

NASA Technical Reports Server (NTRS)

Panzer, Ben; Gomez-Garcia, Daniel; Leuschen, Carl; Paden, John; Rodriguez-Morales, Fernando; Patel, Azsa; Markus, Thorsten; Holt, Benjamin; Gogineni, Prasad

2013-01-01

Sea ice is generally covered with snow, which can vary in thickness from a few centimeters to >1 m. Snow cover acts as a thermal insulator modulating the heat exchange between the ocean and the atmosphere, and it impacts sea-ice growth rates and overall thickness, a key indicator of climate change in polar regions. Snow depth is required to estimate sea-ice thickness using freeboard measurements made with satellite altimeters. The snow cover also acts as a mechanical load that depresses ice freeboard (snow and ice above sea level). Freeboard depression can result in flooding of the snow/ice interface and the formation of a thick slush layer, particularly in the Antarctic sea-ice cover. The Center for Remote Sensing of Ice Sheets (CReSIS) has developed an ultra-wideband, microwave radar capable of operation on long-endurance aircraft to characterize the thickness of snow over sea ice. The low-power, 100mW signal is swept from 2 to 8GHz allowing the air/snow and snow/ ice interfaces to be mapped with 5 c range resolution in snow; this is an improvement over the original system that worked from 2 to 6.5 GHz. From 2009 to 2012, CReSIS successfully operated the radar on the NASA P-3B and DC-8 aircraft to collect data on snow-covered sea ice in the Arctic and Antarctic for NASA Operation IceBridge. The radar was found capable of snow depth retrievals ranging from 10cm to >1 m. We also demonstrated that this radar can be used to map near-surface internal layers in polar firn with fine range resolution. Here we describe the instrument design, characteristics and performance of the radar.

Snow Climatology of Arctic Sea Ice: Comparison of Reanalysis and Climate Model Data with In Situ Measurements

NASA Astrophysics Data System (ADS)

Chevooruvalappil Chandran, B.; Pittana, M.; Haas, C.

2015-12-01

Snow on sea ice is a critical and complex factor influencing sea ice processes. Deep snow with a high albedo and low thermal conductivity inhibits ice growth in winter and minimizes ice loss in summer. Very shallow or absent snow promotes ice growth in winter and ice loss in summer. The timing of snow ablation critically impacts summer sea ice mass balance. Here we assess the accuracy of various snow on sea ice data products from reanalysis and modeling comparing them with in situ measurements. The latter are based on the Warren et al. (1999) monthly climatology derived from snow ruler measurements between 1954-1991, and on daily snow depth retrievals from few drifting ice mass balance buoys (IMB) with sufficiently long observations spanning the summer season. These were compared with snow depth data from the National Center for Environmental Prediction Department of Energy Reanalysis 2 (NCEP), the Community Climate System Model 4 (CCSM4), and the Canadian Earth System Model 2 (CanESM2). Results are quite variable in different years and regions. However, there is often good agreement between CanESM2 and IMB snow depth during the winter accumulation and spring melt periods. Regional analyses show that over the western Arctic covered primarily with multiyear ice NCEP snow depths are in good agreement with the Warren climatology while CCSM4 overestimates snow depth. However, in the Eastern Arctic which is dominated by first-year ice the opposite behavior is observed. Compared to the Warren climatology CanESM2 underestimates snow depth in all regions. Differences between different snow depth products are as large as 10 to 20 cm, with large consequences for the sea ice mass balance. However, it is also very difficult to evaluate the accuracy of reanalysis and model snow depths due to a lack of extensive, continuous in situ measurements.

No evidence of widespread decline of snow cover on the Tibetan Plateau over 2000-2015.

PubMed

Wang, Xiaoyue; Wu, Chaoyang; Wang, Huanjiong; Gonsamo, Alemu; Liu, Zhengjia

2017-11-07

Understanding the changes in snow cover is essential for biological and hydrological processes in the Tibetan Plateau (TP) and its surrounding areas. However, the changes in snow cover phenology over the TP have not been well documented. Using Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow products and the Interactive Multi-sensor Snow and Ice Mapping System (IMS) data, we reported daily cloud-free snow cover product over the Tibetan Plateau (TP) for 2000-2015. Snow cover start (SCS), melt (SCM) and duration (SCD) dates were calculated for each hydrological year, and their spatial and temporal variations were analyzed with elevation variations. Our results show no widespread decline in snow cover over the past fifteen years and the trends of snow cover phenology over the TP has high spatial heterogeneity. Later SCS, earlier SCM, and thus decreased SCD mainly occurred in the areas with elevation below 3500 m a.s.l., while regions in central and southwestern edges of the TP showed advanced SCS, delayed SCM and consequently longer SCD. The roles of temperature and precipitation on snow cover penology varied in different elevation zones, and the impact of both temperature and precipitation strengthened as elevation increases.

Evaluation of Cloud Microphysics in JMA-NHM Simulations Using Bin or Bulk Microphysical Schemes through Comparison with Cloud Radar Observations

NASA Technical Reports Server (NTRS)

Iguchi, Takamichi; Nakajima, Teruyuki; Khain, Alexander P.; Saito, Kazuo; Takemura, Toshihiko; Okamoto, Hajime; Nishizawa, Tomoaki; Tao, Wei-Kuo

2012-01-01

Numerical weather prediction (NWP) simulations using the Japan Meteorological Agency NonhydrostaticModel (JMA-NHM) are conducted for three precipitation events observed by shipborne or spaceborneW-band cloud radars. Spectral bin and single-moment bulk cloud microphysics schemes are employed separatelyfor an intercomparative study. A radar product simulator that is compatible with both microphysicsschemes is developed to enable a direct comparison between simulation and observation with respect to theequivalent radar reflectivity factor Ze, Doppler velocity (DV), and path-integrated attenuation (PIA). Ingeneral, the bin model simulation shows better agreement with the observed data than the bulk modelsimulation. The correction of the terminal fall velocities of snowflakes using those of hail further improves theresult of the bin model simulation. The results indicate that there are substantial uncertainties in the masssizeand sizeterminal fall velocity relations of snowflakes or in the calculation of terminal fall velocity of snowaloft. For the bulk microphysics, the overestimation of Ze is observed as a result of a significant predominanceof snow over cloud ice due to substantial deposition growth directly to snow. The DV comparison shows thata correction for the fall velocity of hydrometeors considering a change of particle size should be introducedeven in single-moment bulk cloud microphysics.

First Moderate Resolution Imaging Spectroradiometer (MODIS) Snow and Ice Workshop

NASA Technical Reports Server (NTRS)

Hall, Dorothy K. (Editor)

1995-01-01

This document is a compilation of summaries of talks presented at a 2-day workshop on Moderate Resolution maging Spectroradiometer (MODIS) snow and ice products. The objectives of the workshop were to: inform the snow and ce community of potential MODIS products, seek advice from the participants regarding the utility of the products, and letermine the needs for future post-launch MODIS snow and ice products. Four working groups were formed to discuss at-launch snow products, at-launch ice products, post-launch snow and ice products and utility of MODIS snow and ice products, respectively. Each working group presented recommendations at the conclusion of the workshop.

CloudSat First Image of a Warm Front Storm Over the Norwegian Sea

NASA Technical Reports Server (NTRS)

2006-01-01

[figure removed for brevity, see original site] Figure 1

CloudSat's first image, of a warm front storm over the Norwegian Sea, was obtained on May 20, 2006. In this horizontal cross-section of clouds, warm air is seen rising over colder air as the satellite travels from right to left. The red colors are indicative of highly reflective particles such as water droplets (or rain) or larger ice crystals (or snow), while the blue indicates thinner clouds (such as cirrus). The flat green/blue lines across the bottom represent the ground signal. The vertical scale on the CloudSat Cloud Profiling Radar image is approximately 30 kilometers (19 miles). The blue line below the Cloud Profiling Radar image indicates that the data were taken over water. The inset image shows the CloudSat track relative to a Moderate Resolution Imaging Spectroradiometer (MODIS) infrared image taken at nearly the same time.

Snow accumulation on Arctic sea ice: is it a matter of how much or when?

NASA Astrophysics Data System (ADS)

Webster, M.; Petty, A.; Boisvert, L.; Markus, T.

2017-12-01

Snow on sea ice plays an important, yet sometimes opposing role in sea ice mass balance depending on the season. In autumn and winter, snow reduces the heat exchange from the ocean to the atmosphere, reducing sea ice growth. In spring and summer, snow shields sea ice from solar radiation, delaying sea ice surface melt. Changes in snow depth and distribution in any season therefore directly affect the mass balance of Arctic sea ice. In the western Arctic, a decreasing trend in spring snow depth distribution has been observed and attributed to the combined effect of peak snowfall rates in autumn and the coincident delay in sea ice freeze-up. Here, we build on this work and present an in-depth analysis on the relationship between snow accumulation and the timing of sea ice freeze-up across all Arctic regions. A newly developed two-layer snow model is forced with eight reanalysis precipitation products to: (1) identify the seasonal distribution of snowfall accumulation for different regions, (2) highlight which regions are most sensitive to the timing of sea ice freeze-up with regard to snow accumulation, and (3) show, if precipitation were to increase, which regions would be most susceptible to thicker snow covers. We also utilize a comprehensive sensitivity study to better understand the factors most important in controlling winter/spring snow depths, and to explore what could happen to snow depth on sea ice in a warming Arctic climate.

The effects of cloud inhomogeneities upon radiative fluxes, and the supply of a cloud truth validation dataset

NASA Technical Reports Server (NTRS)

Welch, Ronald M.

1996-01-01

The ASTER polar cloud mask algorithm is currently under development. Several classification techniques have been developed and implemented. The merits and accuracy of each are being examined. The classification techniques under investigation include fuzzy logic, hierarchical neural network, and a pairwise histogram comparison scheme based on sample histograms called the Paired Histogram Method. Scene adaptive methods also are being investigated as a means to improve classifier performance. The feature, arctan of Band 4 and Band 5, and the Band 2 vs. Band 4 feature space are key to separating frozen water (e.g., ice/snow, slush/wet ice, etc.) from cloud over frozen water, and land from cloud over land, respectively. A total of 82 Landsat TM circumpolar scenes are being used as a basis for algorithm development and testing. Numerous spectral features are being tested and include the 7 basic Landsat TM bands, in addition to ratios, differences, arctans, and normalized differences of each combination of bands. A technique for deriving cloud base and top height is developed. It uses 2-D cross correlation between a cloud edge and its corresponding shadow to determine the displacement of the cloud from its shadow. The height is then determined from this displacement, the solar zenith angle, and the sensor viewing angle.

Improved ocean-color remote sensing in the Arctic using the POLYMER algorithm

NASA Astrophysics Data System (ADS)

Frouin, Robert; Deschamps, Pierre-Yves; Ramon, Didier; Steinmetz, François

2012-10-01

Atmospheric correction of ocean-color imagery in the Arctic brings some specific challenges that the standard atmospheric correction algorithm does not address, namely low solar elevation, high cloud frequency, multi-layered polar clouds, presence of ice in the field-of-view, and adjacency effects from highly reflecting surfaces covered by snow and ice and from clouds. The challenges may be addressed using a flexible atmospheric correction algorithm, referred to as POLYMER (Steinmetz and al., 2011). This algorithm does not use a specific aerosol model, but fits the atmospheric reflectance by a polynomial with a non spectral term that accounts for any non spectral scattering (clouds, coarse aerosol mode) or reflection (glitter, whitecaps, small ice surfaces within the instrument field of view), a spectral term with a law in wavelength to the power -1 (fine aerosol mode), and a spectral term with a law in wavelength to the power -4 (molecular scattering, adjacency effects from clouds and white surfaces). Tests are performed on selected MERIS imagery acquired over Arctic Seas. The derived ocean properties, i.e., marine reflectance and chlorophyll concentration, are compared with those obtained with the standard MEGS algorithm. The POLYMER estimates are more realistic in regions affected by the ice environment, e.g., chlorophyll concentration is higher near the ice edge, and spatial coverage is substantially increased. Good retrievals are obtained in the presence of thin clouds, with ocean-color features exhibiting spatial continuity from clear to cloudy regions. The POLYMER estimates of marine reflectance agree better with in situ measurements than the MEGS estimates. Biases are 0.001 or less in magnitude, except at 412 and 443 nm, where they reach 0.005 and 0.002, respectively, and root-mean-squared difference decreases from 0.006 at 412 nm to less than 0.001 at 620 and 665 nm. A first application to MODIS imagery is presented, revealing that the POLYMER algorithm is robust when pixels are contaminated by sea ice.

Antarctic cloud and surface properties: Satellite observations and climate implications

NASA Astrophysics Data System (ADS)

Berque, Joannes

2004-12-01

The radiative effect of clouds in the Antarctic, although small at the top of the atmosphere, is very large within the surface-atmosphere system, and influences a variety of climate processes on a global scale. Because field observations are difficult in the Antarctic interior, satellite observations may be especially valuable in this region; but the remote sensing of clouds and surface properties over the high ice sheets is problematic due to the lack of radiometric contrast between clouds and the snow. A radiative transfer model of the Antarctic snow-atmosphere system is developed, and a new method is proposed for the examination of the problem of cloud properties retrieval from multi-spectral measurements. Key limitations are identified, and a method is developed to overcome them. Using data from the Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Agency (NOAA) polar orbiters, snow grain size is retrieved over the course of a summer. Significant variability is observed, and it appears related to major precipitation events. A radiative transfer model and a single-column model are used to evaluate the impact of this variability on the Antarctic plateau. The range of observed grain size induces changes of up to 30 Wm-2 on the absorption of shortwave radiation in both models. Cloud properties are then retrieved in summertime imagery of the South Pole. Comparison of model to observations over a wide range of cloud optical depths suggests that this method allows the meaningful interpretation of AVHRR radiances in terms of cloud properties over the Antarctic plateau. The radiative effect of clouds at the top of the atmosphere is evaluated over the South Pole with ground-based lidar observations and data from Clouds and the Earth Radiant Energy System (CERES) onboard NASA's Terra satellite. In accord with previous work, results indicate that the shortwave and net effect are one of cooling throughout the year, while the longwave effect is one of cooling in winter and slight warming in summer.

MODIS Snow and Ice Products from the NSIDC DAAC

NASA Technical Reports Server (NTRS)

Scharfen, Greg R.; Hall, Dorothy K.; Riggs, George A.

1997-01-01

The National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) provides data and information on snow and ice processes, especially pertaining to interactions among snow, ice, atmosphere and ocean, in support of research on global change detection and model validation, and provides general data and information services to cryospheric and polar processes research community. The NSIDC DAAC is an integral part of the multi-agency-funded support for snow and ice data management services at NSIDC. The Moderate Resolution Imaging Spectroradiometer (MODIS) will be flown on the first Earth Observation System (EOS) platform (AM-1) in 1998. The MODIS Instrument Science Team is developing geophysical products from data collected by the MODIS instrument, including snow and ice products which will be archived and distributed by NSIDC DAAC. The MODIS snow and ice mapping algorithms will generate global snow, lake ice, and sea ice cover products on a daily basis. These products will augment the existing record of satellite-derived snow cover and sea ice products that began about 30 years ago. The characteristics of these products, their utility, and comparisons to other data set are discussed. Current developments and issues are summarized.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pandey, Ravindra; Usui, Kota; Livingstone, Ruth A.

Ice-nucleating organisms play important roles in the environment. With their ability to induce ice formation at temperatures just below the ice melting point, bacteria such as Pseudomonas syringae attack plants through frost damage using specialized ice-nucleating proteins. Besides the impact on agriculture and microbial ecology, airborne P. syringae can affect atmospheric glaciation processes, with consequences for cloud evolution, precipitation, and climate. Biogenic ice nucleation is also relevant for artificial snow production and for biomimetic materials for controlled interfacial freezing. We use interface-specific sum frequency generation (SFG) spectroscopy to show that hydrogen bonding at the water-bacteria contact imposes structural ordering onmore » the adjacent water network. Experimental SFG data and molecular dynamics simulations demonstrate that ice active sites within P. syringae feature unique hydrophilic-hydrophobic patterns to enhance ice nucleation. Finally, the freezing transition is further facilitated by the highly effective removal of latent heat from the nucleation site, as apparent from time-resolved SFG spectroscopy.« less

Discrimination Between Clouds and Snow in Landsat 8 Imagery: an Assessment of Current Methods and a New Approach

NASA Astrophysics Data System (ADS)

Stillinger, T.; Dozier, J.; Phares, N.; Rittger, K.

2015-12-01

Discrimination between snow and clouds poses a serious but tractable challenge to the consistent delivery of high-quality information on mountain snow from remote sensing. Clouds obstruct the surface from the sensor's view, and the similar optical properties of clouds and snow make accurate discrimination difficult. We assess the performance of the current Landsat 8 operational snow and cloud mask products (LDCM CCA and CFmask), along with a new method, using over one million manually identified snow and clouds pixels in Landsat 8 scenes. The new method uses physically based scattering models to generate spectra in each Landsat 8 band, at that scene's solar illumination, for snow and cloud particle sizes that cover the plausible range for each. The modeled spectra are compared to pixels' spectra via several independent ways to identify snow and clouds. The results are synthesized to create a final snow/cloud mask, and the method can be applied to any multispectral imager with bands covering the visible, near-infrared, and shortwave-infrared regions. Each algorithm we tested misidentifies snow and clouds in both directions to varying degrees. We assess performance with measures of Precision, Recall, and the F statistic, which are based on counts of true and false positives and negatives. Tests for significance in differences between spectra in the measured and modeled values among incorrectly identified pixels help ascertain reasons for misidentification. A cloud mask specifically designed to separate snow from clouds is a valuable tool for those interested in remotely sensing snow cover. Given freely available remote sensing datasets and computational tools to feasibly process entire mission histories for an area of interest, enabling researchers to reliably identify and separate snow and clouds increases the usability of the data for hydrological and climatological studies.

Rapid melting dynamics of the Morteratsch glacier (Swiss Alps) from UAV photogrammetry and field spectroscopy data

NASA Astrophysics Data System (ADS)

Di Mauro, Biagio; Garzonio, Roberto; Rossini, Micol; Baccolo, Giovanni; Julitta, Tommaso; Cavallini, Giuseppe; Mattavelli, Matteo; Colombo, Roberto

2017-04-01

The impact of atmospheric impurities on the optical properties of snow and ice has been largely acknowledged in the scientific literature. Beyond this, the evaluation of the effect of specific organic and inorganic particles on melting dynamics remains a major challenge. In this contribution, we examine the annual melting dynamics of a large valley glacier of the Swiss Alps using UAV photogrammetry. We then compare the melting patterns to the presence of surface impurities on the glacier surface. Two surveys (in July and September 2016) with a lightweight Unmanned Aerial Vehicle (UAV) were organized on the ablation zone of the Morteratsch glacier (Swiss Alps). The UAV (DJI, Phantom 4) was equipped with a high resolution digital camera, and flew at a constant altitude of 150 from the glacier surface. 30 ground control points were placed on the glacier, and their coordinates were determined with a differential GPS (dGPS) for georeferencing UAV images. Contemporary to the UAV surveys, field spectroscopy data were collected on the glacier surface with an Analytical Spectral Device (ASD Field spec.) spectrometer covering the visible and near infrared spectral ranges, and ice samples were collected to determine the abundance of microorganism and algae. From the UAV RGB data, two point clouds were created using Structure from Motion (SfM) algorithms. The point clouds (each consisting of about 15M points) were then converted in Digital Surface Models (DSM) and orthomosaics by interpolation. The difference between the two DSM was calculated and converted in Snow Water Equivalent (SWE), in order to assess the ice lost by the glacier during the ablation season. The point clouds were compared and the displacement vectors were estimated using different algorithms. The elevation changes estimated from UAV data were compared with the abundance of microorganisms and algae. The reflectance spectra of ice with microorganisms and algae show a chlorophyll absorption feature at 680 nm. The depth of this absorption was extracted from reflectance spectra using a continuum-removal procedure and correlated to the abundance of microorganisms and algae in the snow sample. This result opens interesting perspectives for mapping the spatial distribution of organic material on the glacier surface using remote sensing data, enabling a better understanding of the effect of specific organic particles on melting dynamics.

Antarctica Cloud Cover for October 2003 from GLAS Satellite Lidar Profiling

NASA Technical Reports Server (NTRS)

Spinhirne, J. D.; Palm, S. P.; Hart, W. D.

2005-01-01

Seeing clouds in polar regions has been a problem for the imagers used on satellites. Both clouds and snow and ice are white, which makes clouds over snow hard to see. And for thermal infrared imaging both the surface and the clouds cold. The Geoscience Laser Altimeter System (GLAS) launched in 2003 gives an entirely new way to see clouds from space. Pulses of laser light scatter from clouds giving a signal that is separated in time from the signal from the surface. The scattering from clouds is thus a sensitive and direct measure of the presence and height of clouds. The GLAS instrument orbits over Antarctica 16 times a day. All of the cloud observations for October 2003 were summarized and compared to the results from the MODIS imager for the same month. There are two basic cloud types that are observed, low stratus with tops below 3 km and high cirrus form clouds with cloud top altitude and thickness tending at 12 km and 1.3 km respectively. The average cloud cover varies from over 93 % for ocean and coastal regions to an average of 40% over the East Antarctic plateau and 60-90% over West Antarctica. When the GLAS monthly average cloud fractions are compared to the MODIS cloud fraction data product, differences in the amount of cloud cover are as much as 40% over the continent. The results will be used to improve the way clouds are detected from the imager observations. These measurements give a much improved understanding of distribution of clouds over Antarctica and may show how they are changing as a result of global warming.

The role of ice particles in the microphysics and dynamics of deep convective storms in various latitudes

NASA Astrophysics Data System (ADS)

Huang, Y. C.; Wang, P. K.

2017-12-01

The role of ice particles in the microphysics and dynamics of deep convective storms in various latitudes Yi-Chih Huang and Pao K. Wang Ice particles contribute to the microphysics and dynamics of severe storms in various regions of the world to a degree that is not commonly recognized. This study is motivated by the need to understand the role of ice particles plays in the development of severe storms so that their impact on various aspects of the storm behavior can be properly assessed. In this study, we perform numerical simulations of thunderstorms using a cloud resolving model WISCDYMM that includes parameterized microphysical processes to understand the role played by ice processes. We simulate thunderstorms occurred over various regions of the world including tropics, substropics and midlatitudes. We then perform statistical analysis of the simulated results to show the formation of various categories of hydrometeors to reveal the importance of ice processes. We will show that ice hydrometeors (cloud ice, snow, graupel/hail) account for 80% of the total hydrometeor mass for the High Plains storms but 50% for the subtropical storms. In addition, the melting of large ice particles (graupel and hail) is the major production process of rain in tropical storms although the ratio of ice-phase mass is responsible for only 40% of the total hydrometeor mass. Furthermore, hydrometeors have their own special microphysical processes in development and depletion over various latitudes. Microphysical structures depend on atmospheric dynamical and thermodynamical conditions which determine the partitioning of hydrometeors. This knowledge would benefit the microphysics parameterization in cloud models and cumulus parameterization in global circulation models.

Blowing Snow Sublimation and Transport over Antarctica from 11 Years of CALIPSO Observations

NASA Technical Reports Server (NTRS)

Palm, Stephen P.; Kayetha, Vinay; Yang, Yuekui; Pauly, Rebecca

2017-01-01

Blowing snow processes commonly occur over the earth's ice sheets when the 10 mile wind speed exceeds a threshold value. These processes play a key role in the sublimation and redistribution of snow thereby influencing the surface mass balance. Prior field studies and modeling results have shown the importance of blowing snow sublimation and transport on the surface mass budget and hydrological cycle of high-latitude regions. For the first time, we present continent-wide estimates of blowing snow sublimation and transport over Antarctica for the period 2006-2016 based on direct observation of blowing snow events. We use an improved version of the blowing snow detection algorithm developed for previous work that uses atmospheric backscatter measurements obtained from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar aboard the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellite. The blowing snow events identified by CALIPSO and meteorological fields from MERRA-2 are used to compute the blowing snow sublimation and transport rates. Our results show that maximum sublimation occurs along and slightly inland of the coastline. This is contrary to the observed maximum blowing snow frequency which occurs over the interior. The associated temperature and moisture reanalysis fields likely contribute to the spatial distribution of the maximum sublimation values. However, the spatial pattern of the sublimation rate over Antarctica is consistent with modeling studies and precipitation estimates. Overall, our results show that the 2006-2016 Antarctica average integrated blowing snow sublimation is about 393 +/- 196 Gt yr(exp -1), which is considerably larger than previous model-derived estimates. We find maximum blowing snow transport amount of 5 Mt km-1 yr(exp -1) over parts of East Antarctica and estimate that the average snow transport from continent to ocean is about 3.7 Gt yr(exp -1). These continent-wide estimates are the first of their kind and can be used to help model and constrain the surface mass budget over Antarctica.

Evaluating the effect of soil dust particles from semi-arid areas on clouds and climate

NASA Astrophysics Data System (ADS)

Kristjansson, J. E.; Hummel, M.; Lewinschal, A.; Grini, A.

2016-12-01

Primary ice production in mixed-phase clouds predominantly takes place by heterogeneous freezing of mineral dust particles. Therefore, mineral dust has a large impact on cloud properties. Organic matter attached to mineral dust particles can expand their already good freezing ability further to warmer subzero temperatures. These dust particles are called "soil dust". Dusts emitted from deserts contribute most to the total dust concentration in the atmosphere and they can be transported over long distances. Soil dust is emitted from semi-arid regions, e.g. agricultural areas. Besides wind erosion, human activities like tillage or harvest might be a large source for soil dust release into the atmosphere. In this study, we analyze the influence of soil dust particles on clouds with the Norwegian Earth System Model (NorESM; Bentsen et al., 2013: GMD). The parameterization of immersion freezing on soil dust is based on findings from the AIDA cloud chamber (Steinke et al., in prep.). Contact angle and activation energy for soil dust are estimated in order to be used in the dust immersion freezing scheme of the model, which is based on classical nucleation theory. Our first results highlight the importance of soil dust for ice nucleation on a global scale. Its influence is expected to be highest in the northern hemisphere due to its higher area for soil dust emission. The immersion freezing rates due to additional soil dust can on average increase by a factor of 1.2 compared to a mineral dust-only simulation. Using a budget tool for NorESM, influences of soil dust ice nuclei on single tendencies of the cloud microphysics can be identified. For example, accretion to snow is sensitive to adding soil dust ice nuclei. This can result in changes e.g. in the ice water path and cloud radiative properties.

Snow cover data records from satellite and conventional measurements

NASA Astrophysics Data System (ADS)

Derksen, C.; Brown, R.; Wang, L.

2008-12-01

A major goal of snow-related research in the Climate Research Division of Environment Canada is the development of consistent snow cover information from satellite and in situ data sources for climate monitoring and model evaluation. This work involves new satellite algorithm development for reliable mapping of snow water equivalent (SWE), snow cover extent (SCE) and snow cover onset and melt dates, evaluation of existing snow cover products such as the NOAA weekly data set with in situ and satellite data, and the reconstruction and reanalysis of snow cover information from the application of physical snow models, geostatistics and data assimilation methods. In the context of the International Polar Year, a major effort is being made to develop and evaluate snow cover information over the Arctic region with a particular focus on the dynamic spring melt period where positive feedbacks to the climate system are more pronounced. Assessment of the NOAA daily and weekly SCE products with MODIS and QuikSCAT derived datasets identified a systematic late bias of 2-3 weeks in snow-off dates over northern Canada. This bias was not observed over northern Eurasia which suggests that regional differences in variables such as lake fraction and cloud cover are systematically influencing the accuracy of the NOAA product over northern Canada. Considerable progress has been made in deriving passive microwave derived SWE information over sub- Arctic regions of North America where pre-existing algorithms were unable to account for the influence of forest cover and lake ice. Previous uncertainties in retrieving SWE across the boreal forest have been resolved with the combination of 18.7 and 10.7 GHz measurements from the Advanced Microwave Scanning Radiometer (AMSR-E; 2002-present). Full time series development (1978-onwards) remains problematic, however, because 10.7 GHz measurements are not available from the Special Sensor Microwave/Imager (1987-present). Satellite measurements coupled with lake ice model simulations have illustrated frequency dependent, seasonally evolving relationships between brightness temperature and lake fraction across tundra regions. A potential solution based on the temporal evolution of 37 GHz AMSR-E measurements shows some promise as this was found to be significantly correlated with field measurements of tundra SWE, and to be relatively insensitive to lake fraction. New pan-Arctic (N 60°N) snowmelt onset and end date records (2000-2006) were produced from enhanced resolution (4.45 km) QuikSCAT (QSCAT) Ku-band backscatter measurements. The goal is to merge this with melt onset information from other components of the cryosphere (e.g. glaciers, ice caps, ice sheets, lake ice, sea ice) to provide an integrated circumpolar melt onset and duration dataset for climate monitoring and research on cryosphere-climate links and feedbacks. A major challenge is expanding the relatively short time period of Ku-band satellite measurements with historical C-band data (i.e. from ERS-1). Geostatistical methods and snow cover modeling were used to develop a 10-km gridded SWE dataset over Quebec from 1970-2005 for climate studies and evaluation of the performance of the Canadian Regional Climate Model.

Estimation of Sea Ice Thickness Distributions through the Combination of Snow Depth and Satellite Laser Altimetry Data

NASA Technical Reports Server (NTRS)

Kurtz, Nathan T.; Markus, Thorsten; Cavalieri, Donald J.; Sparling, Lynn C.; Krabill, William B.; Gasiewski, Albin J.; Sonntag, John G.

2009-01-01

Combinations of sea ice freeboard and snow depth measurements from satellite data have the potential to provide a means to derive global sea ice thickness values. However, large differences in spatial coverage and resolution between the measurements lead to uncertainties when combining the data. High resolution airborne laser altimeter retrievals of snow-ice freeboard and passive microwave retrievals of snow depth taken in March 2006 provide insight into the spatial variability of these quantities as well as optimal methods for combining high resolution satellite altimeter measurements with low resolution snow depth data. The aircraft measurements show a relationship between freeboard and snow depth for thin ice allowing the development of a method for estimating sea ice thickness from satellite laser altimetry data at their full spatial resolution. This method is used to estimate snow and ice thicknesses for the Arctic basin through the combination of freeboard data from ICESat, snow depth data over first-year ice from AMSR-E, and snow depth over multiyear ice from climatological data. Due to the non-linear dependence of heat flux on ice thickness, the impact on heat flux calculations when maintaining the full resolution of the ICESat data for ice thickness estimates is explored for typical winter conditions. Calculations of the basin-wide mean heat flux and ice growth rate using snow and ice thickness values at the 70 m spatial resolution of ICESat are found to be approximately one-third higher than those calculated from 25 km mean ice thickness values.

MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

NASA Technical Reports Server (NTRS)

Riggs, George A.; Hall, Dorothy K.

2010-01-01

Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

Application of a Snow Growth Model to Radar Remote Sensing

NASA Astrophysics Data System (ADS)

Erfani, E.; Mitchell, D. L.

2014-12-01

Microphysical growth processes of diffusion, aggregation and riming are incorporated analytically in a steady-state snow growth model (SGM) to solve the zeroth- and second- moment conservation equations with respect to mass. The SGM is initiated by radar reflectivity (Zw), supersaturation, temperature, and a vertical profile of the liquid water content (LWC), and it uses a gamma size distribution (SD) to predict the vertical evolution of size spectra. Aggregation seems to play an important role in the evolution of snowfall rates and the snowfall rates produced by aggregation, diffusion and riming are considerably greater than those produced by diffusion and riming alone, demonstrating the strong interaction between aggregation and riming. The impact of ice particle shape on particle growth rates and fall speeds is represented in the SGM in terms of ice particle mass-dimension (m-D) power laws (m = αDβ). These growth rates are qualitatively consistent with empirical growth rates, with slower (faster) growth rates predicted for higher (lower) β values. In most models, β is treated constant for a given ice particle habit, but it is well known that β is larger for the smaller crystals. Our recent work quantitatively calculates β and α for cirrus clouds as a function of D where the m-D expression is a second-order polynomial in log-log space. By adapting this method to the SGM, the ice particle growth rates and fall speeds are predicted more accurately. Moreover, the size spectra predicted by the SGM are in good agreement with those from aircraft measurements during Lagrangian spiral descents through frontal clouds, indicating the successful modeling of microphysical processes. Since the lowest Zw over complex topography is often significantly above cloud base, the precipitation is often underestimated by radar quantitative precipitation estimates (QPE). Our SGM is capable of being initialized with Zw at the lowest reliable radar echo and consequently improves QPE at ground level.

Spatial scales of light transmission through Antarctic pack ice: Surface flooding vs. floe-size distribution

NASA Astrophysics Data System (ADS)

Arndt, S.; Meiners, K.; Krumpen, T.; Ricker, R.; Nicolaus, M.

2016-12-01

Snow on sea ice plays a crucial role for interactions between the ocean and atmosphere within the climate system of polar regions. Antarctic sea ice is covered with snow during most of the year. The snow contributes substantially to the sea-ice mass budget as the heavy snow loads can depress the ice below water level causing flooding. Refreezing of the snow and seawater mixture results in snow-ice formation on the ice surface. The snow cover determines also the amount of light being reflected, absorbed, and transmitted into the upper ocean, determining the surface energy budget of ice-covered oceans. The amount of light penetrating through sea ice into the upper ocean is of critical importance for the timing and amount of bottom sea-ice melt, biogeochemical processes and under-ice ecosystems. Here, we present results of several recent observations in the Weddell Sea measuring solar radiation under Antarctic sea ice with instrumented Remotely Operated Vehicles (ROV). The combination of under-ice optical measurements with simultaneous characterization of surface properties, such as sea-ice thickness and snow depth, allows the identification of key processes controlling the spatial distribution of the under-ice light. Thus, our results show how the distinction between flooded and non-flooded sea-ice regimes dominates the spatial scales of under-ice light variability for areas smaller than 100-by-100m. In contrast, the variability on larger scales seems to be controlled by the floe-size distribution and the associated lateral incidence of light. These results are related to recent studies on the spatial variability of Arctic under-ice light fields focusing on the distinctly differing dominant surface properties between the northern (e.g. summer melt ponds) and southern (e.g. year-round snow cover, surface flooding) hemisphere sea-ice cover.

Empirical Retrieval of Surface Melt Magnitude from Coupled MODIS Optical and Thermal Measurements over the Greenland Ice Sheet during the 2001 Ablation Season

PubMed Central

Lampkin, Derrick; Peng, Rui

2008-01-01

Accelerated ice flow near the equilibrium line of west-central Greenland Ice Sheet (GIS) has been attributed to an increase in infiltrated surface melt water as a response to climate warming. The assessment of surface melting events must be more than the detection of melt onset or extent. Retrieval of surface melt magnitude is necessary to improve understanding of ice sheet flow and surface melt coupling. In this paper, we report on a new technique to quantify the magnitude of surface melt. Cloud-free dates of June 10, July 5, 7, 9, and 11, 2001 Moderate Resolution Imaging Spectroradiometer (MODIS) daily reflectance Band 5 (1.230-1.250μm) and surface temperature images rescaled to 1km over western Greenland were used in the retrieval algorithm. An optical-thermal feature space partitioned as a function of melt magnitude was derived using a one-dimensional thermal snowmelt model (SNTHERM89). SNTHERM89 was forced by hourly meteorological data from the Greenland Climate Network (GC-Net) at reference sites spanning dry snow, percolation, and wet snow zones in the Jakobshavn drainage basin in western GIS. Melt magnitude or effective melt (E-melt) was derived for satellite composite periods covering May, June, and July displaying low fractions (0-1%) at elevations greater than 2500m and fractions at or greater than 15% at elevations lower than 1000m assessed for only the upper 5 cm of the snow surface. Validation of E-melt involved comparison of intensity to dry and wet zones determined from QSCAT backscatter. Higher intensities (> 8%) were distributed in wet snow zones, while lower intensities were grouped in dry zones at a first order accuracy of ∼ ±2%. PMID:27873793

Empirical Retrieval of Surface Melt Magnitude from Coupled MODIS Optical and Thermal Measurements over the Greenland Ice Sheet during the 2001 Ablation Season.

PubMed

Lampkin, Derrick; Peng, Rui

2008-08-22

Accelerated ice flow near the equilibrium line of west-central Greenland Ice Sheet (GIS) has been attributed to an increase in infiltrated surface melt water as a response to climate warming. The assessment of surface melting events must be more than the detection of melt onset or extent. Retrieval of surface melt magnitude is necessary to improve understanding of ice sheet flow and surface melt coupling. In this paper, we report on a new technique to quantify the magnitude of surface melt. Cloud-free dates of June 10, July 5, 7, 9, and 11, 2001 Moderate Resolution Imaging Spectroradiometer (MODIS) daily reflectance Band 5 (1.230-1.250μm) and surface temperature images rescaled to 1km over western Greenland were used in the retrieval algorithm. An optical-thermal feature space partitioned as a function of melt magnitude was derived using a one-dimensional thermal snowmelt model (SNTHERM89). SNTHERM89 was forced by hourly meteorological data from the Greenland Climate Network (GC-Net) at reference sites spanning dry snow, percolation, and wet snow zones in the Jakobshavn drainage basin in western GIS. Melt magnitude or effective melt (E-melt) was derived for satellite composite periods covering May, June, and July displaying low fractions (0-1%) at elevations greater than 2500m and fractions at or greater than 15% at elevations lower than 1000m assessed for only the upper 5 cm of the snow surface. Validation of E-melt involved comparison of intensity to dry and wet zones determined from QSCAT backscatter. Higher intensities (> 8%) were distributed in wet snow zones, while lower intensities were grouped in dry zones at a first order accuracy of ~ ±2%.

Rocky Mountain Snow

NASA Image and Video Library

2017-12-08

NASA image acquired December 19, 2012 In time for the 2012 winter solstice, a storm dropped snow over most of the Rocky Mountains in the United States. On December 20, the National Weather Service reported snow depths exceeding 100 centimeters (39 inches) in some places—the result of the recent snowfall plus accumulation from earlier storms. The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua satellite captured this natural-color image on December 19, 2012. Clouds had mostly cleared from the region, though some cloud cover lingered over parts of the Pacific Northwest and Colorado. Showing more distinct contours than the clouds, the snow cover stretched across the Rocky Mountains and the surrounding region, from Idaho to Arizona and from California to Colorado. Snowfall did not stop in Colorado, as the storm continued moving eastward across the Midwest. By December 20, 2012, a combination of heavy snow and strong winds had closed schools, iced roads, and delayed flights, complicating plans for holiday travelers. Though troublesome for travel, the snow brought much-needed moisture; multiple cities had set new records for consecutive days without measurable snow, CBS news reported. As of December 18, the U.S. Drought Monitor stated that a substantial portion of the continental United States continued to suffer from drought, and “exceptional” drought conditions extended from South Dakota to southern Texas. NASA image courtesy Jeff Schmaltz, LANCE MODIS Rapid Response. Caption by Michon Scott. Instrument: Aqua - MODIS To read more go to: earthobservatory.nasa.gov/IOTD/view.php?id=80035 Credit: NASA Earth Observatory NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Modulation of Sea Ice Melt Onset and Retreat in the Laptev Sea by the Timing of Snow Retreat in the West Siberian Plain

NASA Astrophysics Data System (ADS)

Crawford, A. D.; Stroeve, J.; Serreze, M. C.; Rajagopalan, B.; Horvath, S.

2017-12-01

As much of the Arctic Ocean transitions to ice-free conditions in summer, efforts have increased to improve seasonal forecasts of not only sea ice extent, but also the timing of melt onset and retreat. This research investigates the potential of regional terrestrial snow retreat in spring as a predictor for subsequent sea ice melt onset and retreat in Arctic seas. One pathway involves earlier snow retreat enhancing atmospheric moisture content, which increases downwelling longwave radiation over sea ice cover downstream. Another pathway involves manipulation of jet stream behavior, which may affect the sea ice pack via both dynamic and thermodynamic processes. Although several possible connections between snow and sea ice regions are identified using a mutual information criterion, the physical mechanisms linking snow retreat and sea ice phenology are most clearly exemplified by variability of snow retreat in the West Siberian Plain impacting melt onset and sea ice retreat in the Laptev Sea. The detrended time series of snow retreat in the West Siberian Plain explains 26% of the detrended variance in Laptev Sea melt onset (29% for sea ice retreat). With modest predictive skill and an average time lag of 53 (88) days between snow retreat and sea ice melt onset (retreat), West Siberian Plains snow retreat is useful for refining seasonal sea ice predictions in the Laptev Sea.

Double-moment cloud microphysics scheme for the deep convection parameterization in the GFDL AM3

NASA Astrophysics Data System (ADS)

Belochitski, A.; Donner, L.

2014-12-01

A double-moment cloud microphysical scheme originally developed by Morrision and Gettelman (2008) for the stratiform clouds and later adopted for the deep convection by Song and Zhang (2011) has been implemented in to the Geophysical Fluid Dynamics Laboratory's atmospheric general circulation model AM3. The scheme treats cloud drop, cloud ice, rain, and snow number concentrations and mixing ratios as diagnostic variables and incorporates processes of autoconversion, self-collection, collection between hydrometeor species, sedimentation, ice nucleation, drop activation, homogeneous and heterogeneous freezing, and the Bergeron-Findeisen process. Such detailed representation of microphysical processes makes the scheme suitable for studying the interactions between aerosols and convection, as well as aerosols' indirect effects on clouds and their roles in climate change. The scheme is first tested in the single column version of the GFDL AM3 using forcing data obtained at the U.S. Department of Energy Atmospheric Radiation Measurment project's Southern Great Planes site. Scheme's impact on SCM simulations is discussed. As the next step, runs of the full atmospheric GCM incorporating the new parameterization are compared to the unmodified version of GFDL AM3. Global climatological fields and their variability are contrasted with those of the original version of the GCM. Impact on cloud radiative forcing and climate sensitivity is investigated.

NAVO MSRC Navigator. Fall 2001

DTIC Science & Technology

2001-01-01

of the CAVE. A view from the VR Juggler simulator . The particles indicate snow (white) & ice (blue). Rainfall is shown on the terrain, and clouds as...the Cover: Virtual environment built by the NAVO MSRC Visualization Center for the Concurrent Computing Laboratory for Materials Simulation at...Louisiana State University. This application allows the researchers to visualize a million atom simulation of an indentor puncturing a block of gallium

Light-absorbing impurities enhance glacier albedo reduction in the southeastern Tibetan plateau

NASA Astrophysics Data System (ADS)

Zhang, Yulan; Kang, Shichang; Cong, Zhiyuan; Schmale, Julia; Sprenger, Michael; Li, Chaoliu; Yang, Wei; Gao, Tanguang; Sillanpää, Mika; Li, Xiaofei; Liu, Yajun; Chen, Pengfei; Zhang, Xuelei

2017-07-01

Light-absorbing impurities (LAIs) in snow of the southeastern Tibetan Plateau (TP) and their climatic impacts are of interest not only because this region borders areas affected by the South Asian atmospheric brown clouds but also because the seasonal snow and glacier melt from this region form important headwaters of large rivers. In this study, we collected surface snow and snowpit samples from four glaciers in the southeastern TP in June 2015 to investigate the comprehensive observational data set of LAIs. Results showed that the LAI concentrations were much higher in the aged snow and granular ice than in the fresh snow and snowpits due to postdepositional processes. Impurity concentrations fluctuated across snowpits, with maximum LAI concentrations frequently occurring toward the bottom of snowpits. Based on the SNow ICe Aerosol Radiative model, the albedo simulation indicated that black carbon and dust account for approximately 20% of the albedo reduction relative to clean snow. The radiative forcing caused by black carbon and dust deposition on the glaciers were between 1.0-141 W m-2 and 1.5-120 W m-2, respectively. Black carbon (BC) played a larger role in albedo reduction and radiative forcing than dust in the study area, enhancing approximately 15% of glacier melt. Analysis based on the Fire INventory from NCAR indicated that nonbiomass-burning sources of BC played an important role in the total BC deposition, especially during the monsoon season. This study suggests that eliminating anthropogenic BC could mitigate glacier melt in the future of the southeastern TP.

Evaluating precipitation in a regional climate model using ground-based radar measurements in Dronning Maud Land, East Antarctica

NASA Astrophysics Data System (ADS)

Gorodetskaya, Irina; Maahn, Maximilan; Gallée, Hubert; Souverijns, Niels; Gossart, Alexandra; Kneifel, Stefan; Crewell, Susanne; Van Lipzig, Nicole

2017-04-01

Occasional very intense snowfall events over Dronning Maud Land (DML) region in East Antarctica, contributed significantly to the entire Antarctic ice sheet surface mass balance (SMB) during the last years. The meteorological-cloud-precipitation observatory running at the Princess Elisabeth station (PE) in the DML escarpment zone since 2009 (HYDRANT/AEROCLOUD projects), provides unique opportunity to estimate contribution of precipitation to the local snow accumulation and new data for evaluating precipitation in climate models. Our previous work using PE measurements showed that occasional intense precipitation events determine the total local yearly SMB and account for its large interannual variability. Here we use radar measurements to evaluate precipitation in a regional climate model with a special focus on intense precipitation events together with the large-scale atmospheric dynamics responsible for these events. The coupled snow-atmosphere regional climate model MAR (Modèle Atmosphérique Régional) is used to simulate climate and SMB in DML at 5-km horizontal resolution during 2012 using initial and boundary conditions from the European Centre for Medium-range Weather Forecasts (ECMWF) Interim re-analysis atmospheric and oceanic fields. Two evaluation approaches are used: observations-to-model and model-to-observations. In the first approach, snowfall rate (S) is derived from the MRR (vertically profiling 24-GHz precipitation radar) effective reflectivity factor (Ze) at 400 m agl using various Ze-S relationships for dry snow. The uncertainty in Ze-S relationships is constrained using snow particle size distribution from Snow Video Imager - Precipitation Imaging Package (SVI/PIP) and information about particle shapes. For the second approach we apply the Passive and Active Microwave radiative TRAnsfer model (PAMTRA), which allows direct comparison of the radar-measured and climate model-based vertical profiles of the radar Ze and Doppler velocity. In MAR, the mass and terminal velocity of snow particles are defined as for the graupel-like snowflakes of hexagonal type, determining single scattering properties for snow hydrometeors used as input (along with cloud particle properties and atmospheric parameters) into PAMTRA. MAR simulates well the timing of major synoptic-scale precipitation events, while overestimating snowfall rate during the intense precipitation events beyond the Ze-S relationship uncertainty. This bias is also evident in significantly longer tail of the frequency distribution towards high values for MAR synthetic Ze near the surface compared to PE radar. This bias can be related to the differences both in the amount and type of snowflakes reaching the surface. The most intense precipitation event contributing almost 50% to the local yearly SMB occurred on 6 November 2012 and was associated with an atmospheric river. MAR model produced more than twice as much precipitation compared to PE radar measurements on this event. Reasons for this high bias are investigated by looking at the moisture transports, cloud properties (ice/liquid occurrence and cloud vertical structure), and precipitation formation efficiency especially related to the mixed-phase clouds (the Bergeron-Findeisen process).

Retrieval of Atmospheric Water Vapor Profiles from the Special Sensor Microwave TEMPERATURE-2

NASA Astrophysics Data System (ADS)

Al-Khalaf, Abdulrahman Khal

1995-01-01

Radiometric measurements from the Special Sensor Microwave/Temperature-2 (SSM/T-2) instrument are used to retrieve atmospheric water vapor profiles over ocean, land, coast, and ice/snow backgrounds. These measurements are used to retrieve vertical distribution of integrated water vapor (IWV) and total integrated water vapor (TIWV) using a physical algorithm. The algorithm infers the presence of cloud at a given height from super-saturation of the retrieved humidity at that height then the algorithm estimate the cloud liquid water content. Retrievals of IWV over five different layers are validated against available ground truth such as global radiosondes and ECMWF analyses. Over ocean, the retrieved total integrated water vapor (TIWV) and IWV close to the surface compare quite well, with those from radiosonde observations and the European Center for Medium Range Weather Forecasts (ECMWF) analyses. However, comparisons to radiosonde results are better than (ECMWF) analyses. TIWV root mean square (RMS) difference was 5.95 mm and TWV RMS difference for the lowest layer (SFC-850 mb) was 2.8 mm for radiosonde comparisons. Water vapor retrieval over land is less accurate than over ocean due to the low contrast between the surface and the atmosphere near the surface; therefore, land retrievals are more reliable at layers above 700 mb. However, TIWV and IWV at all layers compare appropriately with ground truth. Over coastal areas the agreement between retrieved water vapor profiles and ground truth is quite good for both TIWV and IWV for the five layers. The natural variability and large variations in the surface emissivity over ice and snow fields leads toward poor results. Clouds degrade retrievals over land and coast, improve the retrievals a little over ocean, and improve dramatically over snow/ice. Examples of retrieved relative humidity profiles were shown to illustrate the algorithm performance for the actual profile retrieval. The overall features of the retrieved profiles compared well with those from radiosonde data and ECMWF analyses. However, due to the limited number of channels, the retrieved profiles generally do not reproduce the fine details when a rapid change in relative humidity versus height was observed.

Snow contribution to first-year and second-year Arctic sea ice mass balance north of Svalbard

NASA Astrophysics Data System (ADS)

Granskog, Mats A.; Rösel, Anja; Dodd, Paul A.; Divine, Dmitry; Gerland, Sebastian; Martma, Tõnu; Leng, Melanie J.

2017-03-01

The salinity and water oxygen isotope composition (δ18O) of 29 first-year (FYI) and second-year (SYI) Arctic sea ice cores (total length 32.0 m) from the drifting ice pack north of Svalbard were examined to quantify the contribution of snow to sea ice mass. Five cores (total length 6.4 m) were analyzed for their structural composition, showing variable contribution of 10-30% by granular ice. In these cores, snow had been entrained in 6-28% of the total ice thickness. We found evidence of snow contribution in about three quarters of the sea ice cores, when surface granular layers had very low δ18O values. Snow contributed 7.5-9.7% to sea ice mass balance on average (including also cores with no snow) based on δ18O mass balance calculations. In SYI cores, snow fraction by mass (12.7-16.3%) was much higher than in FYI cores (3.3-4.4%), while the bulk salinity of FYI (4.9) was distinctively higher than for SYI (2.7). We conclude that oxygen isotopes and salinity profiles can give information on the age of the ice and enables distinction between FYI and SYI (or older) ice in the area north of Svalbard.