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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

An A-Train Climatology of Extratropical Cyclone Clouds

Extratropical cyclones (ETCs) are the main purveyors of precipitation in the mid-latitudes, especially in winter, and have a significant radiative impact through the clouds they generate. However, general circulation models (GCMs) have trouble representing precipitation and clouds in ETCs, and this might partly explain why current GCMs disagree on to the evolution of these systems in a warming climate. Collectively, the A-train observations of MODIS, CloudSat, CALIPSO, AIRS and AMSR-E have given us a unique perspective on ETCs: over the past 10 years these observations have allowed us to construct a climatology of clouds and precipitation associated with these storms. This has proved very useful for model evaluation as well in studies aimed at improving understanding of moist processes in these dynamically active conditions. Using the A-train observational suite and an objective cyclone and front identification algorithm we have constructed cyclone centric datasets that consist of an observation-based characterization of clouds and precipitation in ETCs and their sensitivity to large scale environments. In this presentation, we will summarize the advances in our knowledge of the climatological properties of cloud and precipitation in ETCs acquired with this unique dataset. In particular, we will present what we have learned about southern ocean ETCs, for which the A-train observations have filled a gap in this data sparse region. In addition, CloudSat and CALIPSO have for the first time provided information on the vertical distribution of clouds in ETCs and across warm and cold fronts. We will also discuss how these observations have helped identify key areas for improvement in moist processes in recent GCMs. Recently, we have begun to explore the interaction between aerosol and cloud cover in ETCs using MODIS, CloudSat and CALIPSO. We will show how aerosols are climatologically distributed within northern hemisphere ETCs, and how this relates to cloud cover.

clouds↗
NASA NTRS2008

Tennessee Valley Total and Cloud-to-Ground Lightning Climatology Comparison

The North Alabama Lightning Mapping Array (NALMA) has been in operation since 2001 and consists often VHF receivers deployed across northern Alabama. The NALMA locates sources of impulsive VHF radio signals from total lightning by accurately measuring the time that the signals arrive at the different receiving stations. The sources detected are then clustered into flashes by applying spatially and temporally constraints. This study examines the total lightning climatology of the region derived from NALMA and compares it to the cloud-to-ground (CG) climatology derived from the National Lightning Detection Network (NLDN) The presentation compares the total and CG lightning trends for monthly, daily, and hourly periods.

Buechler, Dennis↗
NASA NTRS1990

An eight-month climatology of marine stratocumulus cloud fraction, albedo, and integrated liquid water

As part of the FIRE/Extended Time Observations (ETO) program, extended time observations were made at San Nicolas Island (SNI) from March to October, 1987. Hourly averages of air temperature, relative humidity, wind speed and direction, solar irradiance, and downward longwave irradiance were recorded. The radiation sensors were standard Eppley pyranometers (shortwave) and pyrgeometers (longwave). The SNI data were processed in several ways to deduce properties of the stratocumulus covered marine boundary layer (MBL). For example, from the temperature and humidity the lifting condensation level, which is an estimate of the height of the cloud bottom, can be computed. A combination of longwave irradiance statistics can be used to estimate fractional cloud cover. An analysis technique used to estimate the integrated cloud liquid water content (W) and the cloud albedo from the measured solar irradiance is also described. In this approach, the cloud transmittance is computed by dividing the irradiance measured at some time by a clear sky value obtained at the same hour on a cloudless day. From the transmittance and the zenith angle, values of cloud albedo and W are computed using the radiative transfer parameterizations of Stephens (1978). These analysis algorithms were evaluated with 17 days of simultaneous and colocated mm-wave (20.6 and 31.65 GHz) radiometer measurements of W and lidar ceilometer measurements of cloud fraction and cloudbase height made during the FIRE IFO. The algorithms are then applied to the entire data set to produce a climatology of these cloud properties for the eight month period.

Fairall, C. W.↗
NASA NTRS2004

Improving Total Column Ozone Retrievals by Using Cloud Pressures Derived from Raman Scattering in the UV

The higher spectral resolution, coverage, and sampling of the Aura satellite ozone monitoring instrument (OMI), as compared with the total ozone mapping spectrometer (TOMS) should allow for improved ozone retrievals, including estimates of tropospheric ozone. By default, the TOMS-like OMI total column ozone algorithm uses climatological cloud-top pressures based on infrared (IR) measurements to estimate the column ozone below the clouds. Alternatively, cloud pressure can be retrieved using atmospheric rotational Raman scattering with OMI. The retrieved cloud pressures should be more consistent with assumptions made in the total ozone algorithm. Here, we use data from the global ozone monitoring experiment (GOME) to estimate total ozone using both the IR-climatological and retrieved cloud pressures. The exceed approximately 15 DU. Use of the UV cloud pressure retrievals leads to a smoother distribution of ozone along a satellite track by reducing small spatial irregularities presumably caused by errors in the climatological cloud pressures.

Vasilkov, A.↗
NASA NTRS2009

A Method for Retrieving Ground Flash Fraction from Satellite Lightning Imager Data

A general theory for retrieving the fraction of ground flashes in N lightning observed by a satellite-based lightning imager is provided. An "exponential model" is applied as a physically reasonable constraint to describe the measured optical parameter distributions, and population statistics (i.e., mean, variance) are invoked to add additional constraints to the retrieval process. The retrieval itself is expressed in terms of a Bayesian inference, and the Maximum A Posteriori (MAP) solution is obtained. The approach is tested by performing simulated retrievals, and retrieval error statistics are provided. The ability to retrieve ground flash fraction has important benefits to the atmospheric chemistry community. For example, using the method to partition the existing satellite global lightning climatology into separate ground and cloud flash climatologies will improve estimates of lightning nitrogen oxides (NOx) production; this in turn will improve both regional air quality and global chemistry/climate model predictions.

Koshak, William J.↗
NASA NTRS2011

A New SBUV Ozone Profile Time Series

Under NASA's MEaSUREs program for creating long term multi-instrument data sets, our group at Goddard has re-processed ozone profile data from a series of SBUV instruments. We have processed data from the Nimbus 7 SBUV instrument (1979-1990) and data from SBUV/2 instruments on NOAA-9 (1985-1998), NOAA-11 (1989-1995), NOAA-16 (2001-2010), NOAA-17 (2002-2010), and NOAA-18 (2005-2010). This reprocessing uses the version 8 ozone profile algorithm but now uses the Brion, Daumont, and Malicet (BMD) ozone cross sections instead of the Bass and Paur cross sections. The new cross sections have much better resolution, and extended wavelength range, and a more consistent temperature dependence. The re-processing also uses an improved cloud height climatology based on the Raman cloud retrievals of OMI. Finally, the instrument-to-instrument calibration is set using matched scenes so that ozone diurnal variation in the upper stratosphere does not alias into the ozone trands. Where there is no instrument overlap, SAGE and MLS are used to estimate calibration offsets. Preliminary analysis shows a more coherent time series as a function of altitude. The net effect on profile total column ozone is on average an absolute reduction of about one percent. Comparisons with ground-based systems are significantly better at high latitudes.

McPeters, Richard↗
NASA NTRS1990

Interannual variation of seasonal means and subseasonal variability of cloud streets off the east coast of North America 1984-1987

Convection waves are a strong function of the original forcing by convection in the boundary layer. This convection can take the form of random or 2-D spatial structure. When clouds are formed as a result of 2-D boundary layer forcing, they are called cloud streets. Convective waves may be important in the global momentum balance. Global circulation models presently overestimate wind speeds in the middle and upper troposphere, and do not account for convective waves. If the hypothesis that convective waves significantly contribute to momentum transport in the troposphere is correct, then climatology of cloud streets will help understand convective waves' role in the global momentum balance. If the hypothesis is incorrect, then cloud street climatology is still useful because cloud streets show areas where large amounts of sensible and latent heat are transferred from the ocean to the atmosphere. Interannual variation of seasonal means and subseasonal variability of cloud street occurrence off the east coast of North America is examined and compared. The months of Dec., Jan., and Feb. during 1984-85, 1985-86, and 1986-87 are examined along with each season.

Rademacher, Kurt R.↗
NASA NTRS2005

Using Cloud-to-Ground Lightning Climatologies to Initialize Gridded Lightning Threat Forecasts for East Central Florida

Each morning, the forecasters at the National Weather Service in Melbourn, FL (NWS MLB) produce an experimental cloud-to-ground (CG) lightning threat index map for their county warning area (CWA) that is posted to their web site (http://www.srh.weather.gov/mlb/ghwo/lightning.shtml) . Given the hazardous nature of lightning in central Florida, especially during the warm season months of May-September, these maps help users factor the threat of lightning, relative to their location, into their daily plans. The maps are color-coded in five levels from Very Low to Extreme, with threat level definitions based on the probability of lightning occurrence and the expected amount of CG activity. On a day in which thunderstorms are expected, there are typically two or more threat levels depicted spatially across the CWA. The locations of relative lightning threat maxima and minima often depend on the position and orientation of the low-level ridge axis, forecast propagation and interaction of sea/lake/outflow boundaries, expected evolution of moisture and stability fields, and other factors that can influence the spatial distribution of thunderstorms over the CWA. The lightning threat index maps are issued for the 24-hour period beginning at 1200 UTC (0700 AM EST) each day with a grid resolution of 5 km x 5 km. Product preparation is performed on the AWIPS Graphical Forecast Editor (GFE), which is the standard NWS platform for graphical editing. Currently, the forecasters create each map manually, starting with a blank map. To improve efficiency of the forecast process, NWS MLB requested that the Applied Meteorology Unit (AMU) create gridded warm season lightning climatologies that could be used as first-guess inputs to initialize lightning threat index maps. The gridded values requested included CG strike densities and frequency of occurrence stratified by synoptic-scale flow regime. The intent is to increase consistency between forecasters while enabling them to focus on the mesoscale detail of the forecast, ultimately benefiting the end-users of the product. Several studies took place at the Florida State University (FSU) and NWS Tallahassee (TAE) for which they created daily flow regimes using Florida 1200 UTC synoptic soundings and CG strike densities from National Lightning Detection Network (NLDN) data. The densities were created on a 2.5 km x 2.5 km grid for every hour of every day during the warm seasons in the years 1989-2004. The grids encompass an area that includes the entire state of Florida and adjacent Atlantic and Gulf of Mexico waters. Personnel at the two organizations provided this data and supporting software for the work performed by the AMU. The densities were first stratified by flow regime, then by time in 1-, 3-, 6-, 12-, and 24-hour increments while maintaining the 2.5 km x 2.5 km grid resolution. A CG frequency of occurrence was calculated for each stratification and grid box by counting the number of days with lightning and dividing by the total number of days in the data set. New CG strike densities were calculated for each stratification and grid box by summing the strike number values over all warm seasons, then normalized by dividing the summed values by the number of lightning days. This makes the densities conditional on whether lightning occurred. The frequency climatology values will be used by forecasters as proxy inputs for lightning prObability, while the density climatology values will be used for CG amount. In addition to the benefits outlined above, these climatologies will provide improved temporal and spatial resolution, expansion of the lightning threat area to include adjacent coastal waters, and potential to extend the forecast to include the day-2 period. This presentation will describe the lightning threat index map, discuss the work done to create the maps initialized with climatological guidance, and show examples of the climatological CG lightning densities and frequencies of occurren based on flow regime.

Lambert, Winnie↗
NASA NTRS2004

Cloud Inhomogeneity from MODIS

Two full months (July 2003 and January 2004) of MODIS Atmosphere Level-3 data from the Terra and Aqua satellites are analyzed in order to characterize the horizontal variability of cloud optical thickness and water path at global scales. Various options to derive cloud variability parameters are discussed. The climatology of cloud inhomogeneity is built by first calculating daily parameter values at spatial scales of l degree x 1 degree, and then at zonal and global scales, followed by averaging over monthly time scales. Geographical, diurnal, and seasonal changes of inhomogeneity parameters are examined separately for the two cloud phases, and separately over land and ocean. We find that cloud inhomogeneity is weaker in summer than in winter, weaker over land than ocean for liquid clouds, weaker for local morning than local afternoon, about the same for liquid and ice clouds on a global scale, but with wider probability distribution functions (PDFs) and larger latitudinal variations for ice, and relatively insensitive to whether water path or optical thickness products are used. Typical mean values at hemispheric and global scales of the inhomogeneity parameter nu (roughly the mean over the standard deviation of water path or optical thickness), range from approximately 2.5 to 3, while for the inhomogeneity parameter chi (the ratio of the logarithmic to linear mean) from approximately 0.7 to 0.8. Values of chi for zonal averages can occasionally fall below 0.6 and for individual gridpoints below 0.5. Our results demonstrate that MODIS is capable of revealing significant fluctuations in cloud horizontal inhomogenity and stress the need to model their global radiative effect in future studies.

Oreopoulos, Lazaros↗
NASA NTRSDate not supplied

Imbalanced Multi-layer Cloud Classification with Advanced Baseline Imager (ABI) and CloudSat/CALIPSO Data

Clouds at different altitudes play different roles in Earth’s climate. Comprehensive understanding of overlapping clouds is important for climate and weather prediction. The East Pacific region is where El Ni˜no and La Ni˜na originate and where multi-layer clouds frequently occur. The overlap of clouds at different altitudes in this region increases the classification complexity for cloud-based climatological studies. Unlike prior work in cloud layer classification that assumes single layer or two-layer of clouds, in this work, we consider multi-layer cloud classification with 8 cloud-level classes (clear-sky, high, middle, low, high+middle, high+low, middle+low, high+middle+low). We develop and analyze machine learning models on features extracted from satellite images from the East Pacific regions collected by GOES Advanced Baseline Imager (ABI). These are used to classify CloudSat/CALIPSO observed multi-layer clouds. Due to the imbalanced nature of the data, we investigate the adoption of conventional resampling methods, as well as deep learning methods with data augmentation. In our experiments, we utilize the random forest classifier and Multilayer perceptron classifier with data augmentation methods to reduce the class imbalance during training. With these approaches, we achieve a classification accuracy of 83.6% without exploiting any ancillary information.

machine learning↗
NASA NTRS2006

Satellite Sounder-Based OLR-, Cloud- and Atmospheric Temperature Climatologies for Climate Analyses

Global energy balance of the Earth-atmosphere system may change due to natural and man-made climate variations. For example, changes in the outgoing longwave radiation (OLR) can be regarded as a crucial indicator of climate variations. Clouds play an important role -still insufficiently assessed in the global energy balance on all spatial and temporal scales, and satellites provide an ideal platform to measure cloud and large-scale atmospheric variables simultaneously. The TOVS series of satellites were the first to provide this type of information since 1979. OLR [Mehta and Susskind], cloud cover and cloud top pressure [Susskind et al] are among the key climatic parameters computed by the TOVS Pathfinder Path-A algorithm using mainly the retrieved temperature and moisture profiles. AIRS, regarded as the new and improved TOVS , has a much higher spectral resolution and greater S/N ratio, retrieving climatic parameters with higher accuracy. First we present encouraging agreements between MODIS and AIRS cloud top pressure (C(sub tp) and effective (A(sub eff), a product of infrared emissivity at 11 microns and physical cloud cover or A(sub c)) cloud fraction seasonal and interannual variabilities for selected months. Next we present validation efforts and preliminary trend analyses of TOVS-retrieved C(sub tp) and A(sub eff). For example, decadal global trends of the TOVS Path-A and ISCCP-D2 P(sub c), and A(sub eff)/A(sub c), values are similar. Furthermore, the TOVS Path-A and ISCCP-AVHRR [available since 19831 cloud fractions correlate even more strongly, including regional trends. We also present TOVS and AIRS OLR validation effort results and (for the longer-term TOVS Pathfinder Path-A dataset) trend analyses. OLR interannual spatial variabilities from the available state-of-the-art CERES measurements and both from the AIRS [Susskind et al] and TOVS OLR computations are in remarkably good agreement. Global monthly mean CERES and TOVS OLR time series show very good agreement in absolute values also. Finally, we will assess correlations among long-term trends of selected parameters, derived simultaneously from the TOVS Pathfinder Path-A datase

Molnar, Gyula I.↗
NASA NTRS1994

Global surface-based cloud observation for ISCCP

Visual observations of cloud cover are hindered at night due to inadequate illumination of the clouds. This usually leads to an underestimation of the average cloud cover at night, especially for the amounts of middle and high clouds, in climatologies on surface observations. The diurnal cycles of cloud amounts, if based on all the surface observations, are therefore in error, but they can be obtained more accurately if the nighttime observations are screened to select those made under sufficient moonlight. Ten years of nighttime weather observations from the northern hemisphere in December were classified according to the illuminance of moonlight or twilight on the cloud tops, and a threshold level of illuminance was determined, above which the clouds are apparently detected adequately. This threshold corresponds to light from a full moon at an elevation angle of 6 degrees or from a partial moon at higher elevation, or twilight from the sun less than 9 degrees below the horizon. It permits the use of about 38% of the observations made with the sun below the horizon. The computed diurnal cycles of total cloud cover are altered considerably when this moonlight criterion is imposed. Maximum cloud cover over much of the ocean is now found to be at night or in the morning, whereas computations obtained without benefit of the moonlight criterion, as in our published atlases, showed the time of maximum to be noon or early afternoon in many regions. Cloud cover is greater at night than during the day over the open oceans far from the continents, particularly in summer. However, near noon maxima are still evident in the coastal regions, so that the global annual average oceanic cloud cover is still slightly greater during the day than at night, by 0.3%. Over land, where daytime maxima are still obtained but with reduced amplitude, average cloud cover is 3.3% greater during the daytime. The diurnal cycles of total cloud cover we obtain are compared with those of ISCCP for a few regions; they are generally in better agreement if the moonlight criterion is imposed on the surface observations. Using the moonlight criterion, we have analyzed ten years (1982-1991) of surface weather observations over land and ocean, worldwide, for total cloud cover and for the frequency of occurrence of clear sky, fog and precipitation The global average cloud cover (average of day and night) is about 2% higher if we impose the moonlight criterion than if we use all observations. The difference is greater in winter than in summer, because of the fewer hours of darkness in the summer. The amplitude of the annual cycle of total cloud cover over the Arctic Ocean and at the South Pole is diminished by a few percent when the moonlight criterion is imposed. The average cloud cover for 1982-1991 is found to be 55% for northern hemisphere land, 53% for southern hemisphere land, 66% for northern hemisphere ocean, and 70% for southern hemisphere ocean, giving a global average of 64%. The global average for daytime is 64.6% for nighttime 63.3%.

Source record↗
NASA NTRS2006

A Climatology of Midlatitude Continental Clouds from the ARM SGP Central Facility: Cloud Fraction and Radiative Forcing - Part II

Data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) central facility are analyzed for determining the variability of cloud fraction and radiative forcing at several temporal scales between January 1997 and December 2002. Cloud fractions are estimated for total cloud cover and for single-layer low (0-3 km), middle (3-6 km), and high clouds (greater than 6 km) using ARM SGP ground-based paired lidar-radar measurements. Shortwave (SW), longwave (LW), and net cloud radiative forcings (CRF) are derived from up- and down-looking standard precision spectral pyranometers and precision infrared radiometer measurements. The annual averages of total, and single-layer, nonoverlapped low, middle and high cloud fractions are 0.49, 0.11, 0.03, and 0.17, respectively. Total and low cloud amounts were greatest from December through March and least during July and August. The monthly variation of high cloud amount is relatively small with a broad maximum from May to August. During winter, total cloud cover varies diurnally with a small amplitude, mid-morning maximum and early evening minimum, and during summer it changes by more than 0.14 over the daily cycle with a pronounced early evening minimum. The diurnal variations of mean single-layer cloud cover change with season and cloud height. Annual averages of all-sky, total, and single-layer high, middle, and low LW CRFs are 21.4, 40.2, 16.7, 27.2, and 55.0 Wm(sup -2), respectively; and their SW CRFs are -41.5, -77.2, -37.0, -47.0, and -90.5 Wm(sup -2). Their net CRFs range from -20 to -37 Wm(sup -2). For all-sky, total, and low clouds, the maximum negative net CRFs of -40.1, -70, and -69.5 Wm(sup -2), occur during April; while the respective minimum values of -3.9, -5.7, and -4.6 Wm(sup -2), are found during December. July is the month having maximum negative net CRF of -46.2 Wm(sup -2) for middle clouds, and May has the maximum value of -45.9 Wm(sup -2) for high clouds. An uncertainty analysis demonstrates that the calculated CRFs are not significantly affected by the difference between clear-sky and cloudy conditions. A more comprehensive cloud fraction study from both surface and satellite observations will follow.

Dong, Xiquan↗
NASA NTRS2005

A Climatology of Midlatitude Continental Clouds from the ARM SGP Site: Low-Level Cloud Macrophysical, Microphysical, and Radiative Properties - Part I

A record of single-layer and overcast low cloud (stratus) properties has been generated using approximately 4000 hours of data collected from January 1997 to December 2002 at the Atmospheric Radiation Measurement (ARM) Southern Great Plains Central Facility (SCF). The cloud properties include liquid-phase and liquid-dominant, mixed-phase, low cloud macrophysical, microphysical, and radiative properties including cloud-base and -top heights and temperatures, and cloud physical thickness derived from a ground-based radar and lidar pair, and rawinsonde sounding; cloud liquid water path (LWP) and content (LWC), and cloud-droplet effective radius (r(sub e)) and number concentration (N) derived from the macrophysical properties and radiometer data; and cloud optical depth (tau), effective solar transmission (gamma), and cloud/top-of-atmosphere albedos (R(sub cldy)/R(sub TOA)) derived from Eppley precision spectral pyranometer measurements. The cloud properties were analyzed in terms of their seasonal, monthly, and hourly variations. In general, more stratus clouds occur during winter and spring than in summer. Cloud-layer altitudes and physical thicknesses were higher and greater in summer than in winter with averaged physical thicknesses of 0.85 km and 0.73 km for day and night, respectively. The seasonal variations of LWP, LWC, N. tau, R(sub cldy), and R(sub TOA) basically follow the same pattern with maxima and minima during winter and summer, respectively. There is no significant variation in mean r(sub e), however, despite a summertime peak in aerosol loading, Although a considerable degree of variability exists, the 6-yr average values of LWP, LWC, r(sub e), N, tau, gamma, R(sub cldy) and R(sub TOA) are 150 gm(exp -2) (138), 0.245 gm(exp -3) (0.268), 8.7 micrometers (8.5), 213 cm(exp -3) (238), 26.8 (24.8), 0.331, 0.672, 0.563 for daytime (nighttime). A new conceptual model of midlatitude continental low clouds at the ARM SGP site has been developed from this study. The low stratus cloud amount monotonically increases from midnight to early morning (0930 LT), and remains large until around local noon, then declines until 1930 LT when it levels off for the remainder of the night. In the morning, the stratus cloud layer is low, warm, and thick with less LWC, while in the afternoon it is high, cold, and thin with more LWC. Future parts of this series will consider other cloud types and cloud radiative forcing at the ARM SCF.

Dong, Xiquan↗
NASA NTRS2006

A Climatology of Midlatitude Continental Clouds from the ARM SGP Site: Cloud Fraction and Surface Radiative Forcing - Part II

Data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility (SCF) are analyzed to determine the monthly and hourly variations of cloud fraction and radiative forcing between January 1997 and December 2002. Cloud fractions are estimated for total cloud cover and for single-layered low (0-3 km), middle (3-6 km), and high clouds (more than 6 km) using ARM SCG ground-based paired lidar-radar measurements. Shortwave (SW) and longwave (LW) fluxes are derived from up- and down-looking standard precision spectral pyranometers and precision infrared radiometer measurements with uncertainties of approximately 10 Wm(exp -2). The annual averages of total, and single-layered low, middle and high cloud fractions are 0.49, 0.11, 0.03, and 0.17, respectively. Both total and low cloud amounts peak during January and February and reach a minimum during July and August, high clouds occur more frequently than other types of clouds with a peak in summer. The average annual downwelling surface SW fluxes for total and low clouds (151 and 138 Wm(exp-2), respectively) are less than those under middle and high clouds (188 and 201 Wm(exp -2), respectively), but the downwelling LW fluxes (349 and 356 Wm(exp -2)) underneath total and low clouds are greater than those from middle and high clouds (337 and 333 Wm(exp -2)). Low clouds produce the largest LW warming (55 Wm(exp -2) and SW cooling (-91 Wm(exp -2)) effects with maximum and minimum absolute values in spring and summer, respectively. High clouds have the smallest LW warming (17 Wm(exp -2)) and SW cooling (-37 Wm(exp -2)) effects at the surface. All-sky SW CRF decreases and LW CRF increases with increasing cloud fraction with mean slopes of -0.984 and 0.616 Wm(exp -2)%(exp -1), respectively. Over the entire diurnal cycle, clouds deplete the amount of surface insolation more than they add to the downwelling LW flux. The calculated CRFs do not appear to be significantly affected by uncertainties in data sampling and clear-sky screening. Traditionally, cloud radiative forcing includes, not only the radiative impact of the hydrometeors, but also the changes in the environment. Taken together over the ARM SCF, changes in humidity and surface albedo between clear and cloudy conditions offset approximately 20% of the NET radiative forcing caused by the cloud hydrometeors alone. Variations in water vapor, on average, account for 10% and 83% of the SW and LW CRFs, respectively, in total cloud cover conditions. The error analysis further reveals that the cloud hydrometeors dominate the SW CRF, while water vapor changes are most important for LW flux changes in cloudy skies. Similar studies over other locales are encouraged where water and surface albedo changes from clear to cloudy conditions may be much different than observed over the ARM SCF.

Xi, B.↗
DOE OSTI2021

Climatology of Melting Layer Heights Estimated From Cloud Radar Observations at Various Locations

A melting layer (ML) detection algorithm for cloud radar with polarimetric capability was developed and applied to the cloud radar data collected from five different sites around the world for several years. The retrieved melting layer top height (MLH) showed a very good correspondence with the ECMWF Reanalysis 5 zero degree level data for all five sites. The ML characteristics were distinctively different for different sites, revealing climatological characteristics of ML forming clouds in different regions. Generally, ML tended to occur more frequently in summer than in winter except for a maritime site, where low stratiform clouds formed frequently in summer, the top of which might be lower than the freezing level. In contrast, at two Arctic sites, ML occurred almost exclusively in summer because it was too cold to have an ML in the other seasons. The MLH also varied significantly from site to site but generally was higher during warmer seasons. Based on MLH, two new indices, bulk temperature lapse rate (BLR) and relative depth (RD) of liquid cloud below MLH (RD) were developed, which were useful to explain the environmental characteristics of the five sites. BLR generally increased with the surface temperature at all sites except at the marine site that showed an opposite trend, where a unique synoptic pattern in winter generated high BLR in this cold season. Finally, these findings confirm that studies on thermodynamic structures using cloud radars can be broadened, taking advantage of BLR and RD information, as these indices can represent environmental thermodynamic characteristics of the clouds that have ML.

54 ENVIRONMENTAL SCIENCES↗