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Aerosols have significant and complex impacts on regional climate in East Asia. Cloud‐aerosol‐precipitation interactions (CAPI) remain most challenging in climate studies. The quantitative understanding of CAPI requires good knowledge of aerosols, ranging from their formation, composition, transport, and their radiative, hygroscopic, and microphysical properties. A comprehensive review is presented here centered on the CAPI based chiefly, but not limited to, publications in the special section named EAST‐AIRcpc concerning (1) observations of aerosol loading and properties, (2) relationships between aerosols and meteorological variables affecting CAPI, (3) mechanisms behind CAPI, and (4) quantification of CAPI and their impact on climate. Heavy aerosol loading in East Asia has significant radiative effects by reducing surface radiation, increasing the air temperature, and lowering the boundary layer height. A key factor is aerosol absorption, which is particularly strong in central China. This absorption can have a wide range of impacts such as creating an imbalance of aerosol radiative forcing at the top and bottom of the atmosphere, leading to inconsistent retrievals of cloud variables from space‐borne and ground‐based instruments. Aerosol radiative forcing can delay or suppress the initiation and development of convective clouds whose microphysics can be further altered by the microphysical effect of aerosols. For the same cloud thickness, the likelihood of precipitation is influenced by aerosols: suppressing light rain and enhancing heavy rain, delaying but intensifying thunderstorms, and reducing the onset of isolated showers in most parts of China. Rainfall has become more inhomogeneous and more extreme in the heavily polluted urban regions.

Climate Model Development and Validation (CMDV) program - Office of Biological and Environmental Research in the US Department of Energy Office of Science [DE-SC0017015]; NASA CERES project [NNX17AC52G]

U.S. Department of Energy (DOE) Atmospheric System Research (ASR) Program; U.S. Department of Energy (DOE) Climate Model Development and Validation (CMDV) program; DOE [DE-AC06-76RLO1830]; Office of Science of the U.S. DOE [DE-AC02-05CH1123]; National Basic Research Program of China [2013CB430105]; National Natural Science Foundation of China [41575130, 41775132]; U.S. DOE ASR grant [DE-SC0008678, DE-SC0008648, DE-SC0016476]; DOE CMDV project at University of Arizona [DE-SC0017015]; U.S. DOE [DE-AC02-98CH10886]; Israel Science Foundation [2027/17]; U.S. National Science Foundation; [DE-SC008811]

Author(s): Qiu, S; Xi, B; Dong, X | Abstract: Seven years of autumnal ground-based observations (September–November 2002–2008) at the U.S. Department of Energy Atmospheric Radiation Measurement North Slope of Alaska site have been analyzed for addressing the occurrence frequency and macrophysical and microphysical properties of Arctic mixed-phase clouds (AMC), as well as the relationship between environmental parameters and AMC properties. In September and October, AMC occurrence frequency is 20–30% lower during a southerly wind when compared to the other wind directions; in November, the variation of AMC occurrence frequency with wind direction is small. The mean liquid water path in November is about half of that in October and September. When the surface is snow free, temperature (T) and specific humidity (q) profiles during a northerly wind are warmer and moister than those for the southerly wind. Northerly wind profiles have a higher relative humidity to ice (RHi) and lower atmosphere stability. Furthermore, the AMC occurrence frequency has a positive relationship with RHi and a negative relationship with stability. These two points may explain the lower AMC occurrence frequency during a southerly wind. During a northerly wind, AMCs have larger radar reflectivity, wider spectrum width, and larger Doppler velocity signatures. The stronger precipitation for AMC during a northerly wind is possibly due to the cleaner air masses from the ocean (north). With the same amount of q, the radar spectrum width has a higher frequency in the larger bins during a northerly wind. Both T, q, and radar reflectivity, radar spectrum width profiles show evidence of deposition in the sub-cloud layer in September and October.

NOAA MAPP under grant at the University of North Dakota [NA13OAR4310105]; NASA CERES project under grant at the University of Arizona [NNX17AC52G]

From April 2009 to December 2010, the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program carried out an observational field campaign on Graciosa Island, targeting the marine boundary layer (MBL) clouds over the Azores region. In this paper, we present an inter-comparison of the MBL cloud properties, namely, cloud liquid water path (LWP), cloud optical thickness (COT) and cloud-droplet effective radius (CER), among retrievals from the ARM mobile facility (AMF) and two Moderate Resolution Spectroradiometer (MODIS) cloud products (GSFC-MODIS and CERES-MODIS). A total of 63 daytime single-layer MBL cloud cases are selected for inter-comparison. Comparison of collocated retrievals indicates that the two MODIS cloud products agree well on both COT and CER retrievals, with the correlation coefficient R>0.95. despite their significant difference in spatial sampling. In both MODIS products, the CER retrievals based on the 2.1 µm band (CER(2.1)) is significantly smaller than that based on the 3.7 µm band (CER(3.7)). The GSFC-MODIS cloud product is collocated and compared with ground-based ARM observations at several temporal-spatial scales. In general, the correlation increases with more precise collocation. For the 63 selected MBL cloud cases, the GSFC-MODIS LWP and COT retrievals agree reasonably well with the ground-based observations with no apparent bias and correlation coefficient R around 0.85 and 0.70, respectively. However, GSFC-MODIS CER(3.7) and CER(2.1) retrievals have a lower correlation (R~0.5) with the ground-based retrievals. For the 63 selected cases, they are on average larger than ground observations by about 1.5 µm and 3.0 µm, respectively. Taking into account that the MODIS CER retrievals are only sensitive to cloud top reduces the bias only by 0.5 µm.

NASA CERES project at the University of Arizona [NNX17AC52G]; NOAA R2O project at the University of North Dakota [NA15NWS468004]; University of Arizona; NASA CERES Project; DOE ARM program [DE-SC0013896]; DOE ASR program [DE-SC0013896]; DOE ARM [DE-SC0013896]

In this study, the characteristics of the Arctic mixed-phase cloud (AMC) have been investigated using data collected at the Atmospheric Radiation Measurement North Slope Alaska site from October 2006 to September 2009. AMC has an annual occurrence frequency of 42.3%, which includes 18.7% of single-layered AMCs and 23.6% for multiple layers. Two cloud base heights (CBHs) are defined from ceilometer and micropulse lidar (MPL) measurements. For single-layered AMC, the ceilometer-derived CBH represents the base of the liquid-dominant layer near the cloud top, while MPL-derived CBH represents base of the lower ice-dominant layer. The annual mean CBHs from ceilometer and MPL measurements are 1.0 km and 0.6 km, respectively, with the largest difference (~1.0 km) occurring from December to March and the smallest difference in September. The humidity inversion occurrence decreases with increasing humidity inversion intensity (stronger in summer than in winter). During the winter months, AMC occurrences increase from 15% to 35% when the inversion intensity increases from 0.1 to 0.9 g/kg. On the contrary, despite a higher frequency of strong humidity inversion in summer, AMC occurrences are nearly invariant for different inversion intensities. On average, humidity and temperature inversion frequencies of occurrence above an AMC are 5 and 8 times, respectively, as high as those below an AMC. The strong inversion occurrences for both humidity and temperature above an AMC provide the moisture sources from above for the formation and maintenance of AMCs. This result helps to reconcile the persistency of AMCs even when the Arctic surface is covered by snow and ice.

Six coupled and decoupled marine boundary layer (MBL) clouds were chosen from the 19 month Atmospheric Radiation Measurement Mobile Facility data set over the Azores. Thresholds of liquid water potential temperature difference ΔθL 0.5 K) and total water mixing ratio difference Δqt 0.5 g/kg) below the cloud base were used for selecting the coupled (decoupled) cases. A schematic diagram was given to demonstrate the coupled and decoupled MBL vertical structures and how they associate with nondrizzle, virga, and rain drizzle events. Out of a total of 2676 5 min samples, 34.5% were classified as coupled and 65.5% as decoupled, 36.2% as nondrizzle and 63.8% as drizzle (47.7% as virga and 16.1% as rain), and 33.4% as daytime and 66.6% as nighttime. The decoupled cloud layer is deeper (0.406 km) than coupled cloud layer (0.304 km), and its liquid water path and cloud droplet effective radius (re) values (122.1 gm−2 and 13.0 µm) are higher than coupled ones (83.7 gm−2 and 10.4 µm). Conversely, decoupled stratocumuli have lower cloud droplet number concentration (Nd) and surface cloud condensation nucleus (CCN) concentration (NCCN) (74.5 cm−3 and 150.9 cm−3) than coupled stratocumuli (111.7 cm−3 and 216.4 cm−3). The linear regressions between re and Nd with NCCN have demonstrated that coupled re and Nd strongly depend on NCCN and have higher correlations (−0.56 and 0.59) with NCCN than decoupled results (−0.14 and 0.25). The MBL cloud properties under nondrizzle and virga drizzle conditions are similar to each other but significantly different to those of rain drizzle.

Six deep convective systems (DCSs) with a total of 5589 five-second samples and a range of temperatures from −41°C to 0°C during the Midlatitude Continental Convective Clouds Experiment (MC3E) were selected to investigate the ice cloud microphysical properties of DCSs over the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. The ice cloud measurements of the DCS cases were made by the University of North Dakota Citation II research aircraft, and the ice cloud properties were derived through the following processes. First, the instances of supercooled liquid water in the ice-dominated cloud layers of DCSs have been eliminated using multisensor detection, including the Rosemount Icing Detector, King and Cloud Droplet Probes, as well as 2DC and Cloud Imaging Probe images. Then the Nevzorov-measured ice water contents (IWCs) at maximum diameter Dmax

The ultimate goal of this study is to improve the representation of convective transport by cumulus parameterization for mesoscale and climate models. As Part 1 of the study, we perform extensive evaluations of cloud-resolving simulations of a squall line and mesoscale convective complexes in midlatitude continent and tropical regions using the Weather Research and Forecasting model with spectral bin microphysics (SBM) and with two double-moment bulk microphysics schemes: a modified Morrison (MOR) and Milbrandt and Yau (MY2). Compared to observations, in general, SBM gives better simulations of precipitation and vertical velocity of convective cores than MOR and MY2 and therefore will be used for analysis of scale dependence of eddy transport in Part 2. The common features of the simulations for all convective systems are (1) the model tends to overestimate convection intensity in the middle and upper troposphere, but SBM can alleviate much of the overestimation and reproduce the observed convection intensity well; (2) the model greatly overestimates Ze in convective cores, especially for the weak updraft velocity; and (3) the model performs better for midlatitude convective systems than the tropical system. The modeled mass fluxes of the midlatitude systems are not sensitive to microphysics schemes but are very sensitive for the tropical case indicating strong microphysics modification to convection. Cloud microphysical measurements of rain, snow, and graupel in convective cores will be critically important to further elucidate issues within cloud microphysics schemes.

An intercomparison study of a midlatitude mesoscale squall line is performed using the Weather Research and Forecasting (WRF) model at 1 km horizontal grid spacing with eight different cloud microphysics schemes to investigate processes that contribute to the large variability in simulated cloud and precipitation properties. All simulations tend to produce a wider area of high radar reflectivity (Z_e > 45 dBZ) than observed but a much narrower stratiform area. The magnitude of the virtual potential temperature drop associated with the gust front passage is similar in simulations and observations, while the pressure rise and peak wind speed are smaller than observed, possibly suggesting that simulated cold pools are shallower than observed. Most of the microphysics schemes overestimate vertical velocity and Ze in convective updrafts as compared with observational retrievals. Simulated precipitation rates and updraft velocities have significant variability across the eight schemes, even in this strongly dynamically driven system. Differences in simulated updraft velocity correlate well with differences in simulated buoyancy and low-level vertical perturbation pressure gradient, which appears related to cold pool intensity that is controlled by the evaporation rate. Simulations with stronger updrafts have a more optimal convective state, with stronger cold pools, ambient low-level vertical wind shear, and rear-inflow jets. Updraft velocity variability between schemes is mainly controlled by differences in simulated ice-related processes, which impact the overall latent heating rate, whereas surface rainfall variability increases in no-ice simulations mainly because of scheme differences in collision-coalescence parameterizations.

In this study, an atmospheric river (AR) detection algorithm is developed to investigate the downstream modulation of the eastern North Pacific ARs by another weather extreme, known as the East Asian cold surge (EACS), in both reanalysis data and high-resolution global model simulations. It is shown that following the peak of an EACS, atmospheric disturbances of intermediate frequency (IF; 10–30 day period) are excited downstream. This leads to the formation of a persistent cyclonic circulation anomaly over the eastern North Pacific that dramatically enhances the AR occurrence probability and the surface precipitation over the western U.S. between 30°N and 50°N. A diagnosis of the local geopotential height tendency further confirms the essential role of IF disturbances in establishing the observed persistent anomaly. This downstream modulation effect is then examined in the two simulations of the National Center for Atmospheric Research Community Climate System Model version 4 with different horizontal resolutions (T85 and T341) for the same period (1979–2005). The connection between EACS and AR is much better captured by the T341 version of the model, mainly due to a better representation of the scale interaction and the characteristics of IF atmospheric disturbances in the higher-resolution model. The findings here suggest that faithful representations of scale interaction in a global model are critical for modeling and predicting the occurrences of hydrological extremes in the western U.S. and for understanding their potential future changes.

This study presents newly developed algorithms for retrieving ice cloud microphysical properties (ice water content (IWC) and median mass diameter (Dm)) for the stratiform rain and thick anvil regions of Deep Convective Systems (DCSs) using Next-Generation Radar (NEXRAD) reflectivity and empirical relationships from aircraft in situ measurements. A typical DCS case (20 May 2011) during the Midlatitude Continental Convective Clouds Experiment (MC3E) is selected as an example to demonstrate the 4-D retrievals. The vertical distributions of retrieved IWC are compared with previous studies and cloud-resolving model simulations. The statistics from six selected cases during MC3E show that the aircraft in situ derived IWC and Dm are 0.47 ± 0.29 g m-3 and 2.02 ± 1.3 mm, while the mean values of retrievals have a positive bias of 0.19 g m-3 (40%) and negative bias of 0.41 mm (20%), respectively. To evaluate the new retrieval algorithms, IWC and Dm are retrieved for other DCSs observed during the Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX) using NEXRAD reflectivity and compared with aircraft in situ measurements. During BAMEX, a total of 63 1-min collocated aircraft and radar samples are available for comparisons, and the averages of radar retrieved and aircraft in situ measured IWC values are 1.52 g m-3 and 1.25 g m-3 with a correlation of 0.55, and their averaged Dm values are 2.08 and 1.77 mm. In general, the new retrieval algorithms are suitable for continental DCSs during BAMEX, especially within stratiform rain and thick anvil regions.

The Mesoscale Heavy Rainfall Observing System (MHROS), supported by the Institute of Heavy Rain (IHR), Chinese Meteorology Administration, is one of the major systems to observe mesoscale convective systems (MCSs) over the middle region of the Yangtze River in China. The IHR MHROS consists of mobile C-POL and X-POL precipitation radars, millimeter wavelength cloud radar (MMCR), fixed S-band precipitation radars, GPS network, microwave radiometers, radio soundings, wind profiler radars and disdrometers. The atmospheric variables observed or retrieved by these instruments include the profiles of atmospheric temperature, moisture, wind speed and direction, vertical structures of MCS clouds and precipitation, atmospheric water vapor, and cloud liquid water. These quality controlled observations and retrievals have been used in mesoscale numerical weather prediction to improve the accuracy of weather forecasting and MCS research since 2007. These long-term observations have provided the most comprehensive datasets for researchers to investigate the formation-dissipation processes of MCSs and for modelers to improve their simulations of MCSs. As the first paper of a series, we briefly introduce the IHR MHROS and describe the specifications of its major instruments. Then, we provide an integrative analysis of the IHR MHROS observations for a heavy rain case on 3–5 July 2014 as well as the application of IHR MHROS observations in improving the model simulations. In a series of papers, we will tentatively answer several key scientific questions related to the MCS and Meiyu frontal systems over the middle region of the Yangtze River using the IHR MHROS observations.

Atmospheric profiles of temperature (T), vapor density (ρv), and relative humidity (RH) retrieved from ground-based microwave radiometer (MWR) measurements are compared with radiosonde soundings at Wuhan, China. The MWR retrievals were averaged in the ±30 min period centered at sounding times of 00 and 12 UTC. A total of 403 and 760 profiles under clear and cloudy skies were selected. Based on the comparisons, temperature profiles have better consistency than the ρv and RH profiles, lower levels are better than upper levels, and the cloudy are better than the clear-sky profiles. Three cloud types (low, middle, and high) were identified by matching the infrared radiation thermometer-detected cloud base temperature to the MWR-retrieved temperature-height profiles. Temperature profile under high cloud has the highest correlation coefficient (R) and the lowest bias and RMS, but under low cloud is in the opposite direction. The ρv profile under middle cloud has the highest R and the lowest bias but under high cloud has the lowest R, the largest bias, and RMS. Based on the radiosonde soundings, both clear and cloudy wind speeds and drifting distances increase with height but increase much faster under clear than cloudy above 4 km. The increased wind speeds and drifting distances with height have resulted in decreased correlation coefficient and increased temperature biases and RMSs with height for both clear and cloudy skies. The differences in R, bias, and RMS between clear and cloudy skies are primarily resulted from their wind speeds and drifting distances.

NASA Earth and Space Science Fellowship program; NASA CERES project [NNX14AP84G]; NOAA MAPP grant at the University of North Dakota [NA13OAR4310105]; Jet Propulsion Laboratory, California Institute of Technology; NASA

Author(s): Dong, X; Xi, B; Qiu, S; Minnis, P; Sun-Mack, S; Rose, F | Abstract: Retrievals of cloud microphysical properties based on passive satellite imagery are especially difficult over snow-covered surfaces because of the bright and cold surface. To help quantify their uncertainties, single-layered overcast liquid-phase Arctic stratus cloud microphysical properties retrieved by using the Clouds and the Earth’s Radiant Energy System Edition 2 and Edition 4 (CERES Ed2 and Ed4) algorithms are compared with ground-based retrievals at the Atmospheric Radiation Measurement North Slope of Alaska (ARM NSA) site at Barrow, AK, during the period from March 2000 to December 2006. A total of 206 and 140 snow-free cases (Rsfc ≤ 0.3), and 108 and 106 snow cases (Rsfcg0.3), respectively, were selected from Terra and Aqua satellite passes over the ARM NSA site. The CERES Ed4 and Ed2 optical depth (t) and liquid water path (LWP) retrievals from both Terra and Aqua are almost identical and have excellent agreement with ARM retrievals under snow-free and snow conditions. In order to reach a radiation closure study for both the surface and top of atmosphere (TOA) radiation budgets, the ARM precision spectral pyranometer-measured surface albedos were adjusted (63.6% and 80% of the ARM surface albedos for snow-free and snow cases, respectively) to account for the water and land components of the domain of 30 km × 30 km. Most of the radiative transfer model calculated SW↓sfc and SW↑TOA fluxes by using ARM and CERES cloud retrievals and the domain mean albedos as input agree with the ARM and CERES flux observations within 10Wm-2 for both snow-free and snow conditions. Sensitivity studies show that the ARM LWP and re retrievals are less dependent on solar zenith angle (SZA), but all retrieved optical depths increase with SZA.

A new method to retrieve cloud liquid water path using 23.8 and 31.4 GHz microwave radiometer brightness temperature measurements is developed. This method does not depend on climatological estimates of either the mean radiating temperature of the atmosphere Tmr or the mean cloud liquid water temperature Tcloud. Rather, Tmr is estimated from surface temperature and relative humidity measurements, while Tcloud is estimated using millimeter-wave cloud radar data, together with atmospheric temperature profiles obtained from either radiosonde or rapid update cycle (RUC) model output. Simulations demonstrate that the new retrieval method significantly reduces the biases in the liquid water path estimates that are apparent in a site-specific retrieval based on monthly stratified, local climatology. An analysis of the liquid water path estimates produced by the two retrievals over four case study days illustrates trends and retrieval performances consistent with the model simulations.

A 25-month database of the macrophysical, microphysical, and radiative properties of isolated and overcast low-level stratus clouds has been generated using a newly developed parameterization and surface measurements from the Atmospheric Radiation Measurement central facility in Oklahoma. The database (5-min resolution) includes two parts: measurements and retrievals. The former consist of cloud base and top heights, layer-mean temperature, cloud liquid water path, and solar transmission ratio measured by a ground-based lidar/ceilometer and radar pair, radiosondes, a microwave radiometer, and a standard Eppley precision spectral pyranometer, respectively. The retrievals include the cloud-droplet effective radius and number concentration and broadband shortwave optical depth and cloud and top-of-atmosphere albedos. Stratus without any overlying mid or high-level clouds occurred most frequently during winter and least often during summer. Mean cloud-layer altitudes and geometric thicknesses were higher and greater, respectively, in summer than in winter. Both quantities are positively correlated with the cloud-layer mean temperature. Mean cloud-droplet effective radii range from 8.1 μm in winter to 9.7 μm during summer, while cloud-droplet number concentrations during winter are nearly twice those in summer. Since cloud liquid water paths are almost the same in both seasons, cloud optical depth is higher during the winter, leading to greater cloud albedos and lower cloud transmittances.

In earlier work a δ2-stream radiative transfer model was used in conjunction with ground-based measurements to retrieve the rnicrophysical and shortwave radiative properties of boundary layer stratus. The effective radii output by the retrieval scheme for optically thick clouds have now been parameterized as a function of the cloud liquid water path, the transmission ratio, and the cosine of the solar zenith angle. The parameterization enables estimation of stratus cloud microphysical properties using ground-based measurements that are readily available at a number of locations. To validate the retrieved and parameterized cloud microphysics, ∼5 hours of data were analyzed and compared to collocated in situ measurements made by a Forward Scattering Spectrometer Probe. On average, the retrieved values of the cloud droplet effective radius and the cloud droplet number concentration differed from the corresponding aircraft measurements by 7% and 27%, respectively, while the parameterized values differed from the aircraft measurements by 15% and 32%, respectively. Averaging all of the data to 30-min resolution significantly reduced the differences between the aircraft data and the retrieved and parameterized results, suggesting that both the aircraft and the ground-based data are capable of characterizing the cloud microphysics over this temporal scale. The parameterizations of the stratus shortwave radiative properties were generally within 5% of Slingo's four-band, model-derived parameterization when absorption above cloud top was incorporated into the Slingo parameterization.

Two methods for retrieving the microphysical and radiative properties of marine and continental boundary layer stratiform clouds from ground-based measurements are implemented. The first method uses measurements of the cloud liquid water path and the cloud nadir radiance at 1 μm to infer the cloud optical depth, cloud droplet effective radius, and cloud droplet concentration. In the second method a

Deep Convective Systems (DCSs) consist of intense convective cores (CC), large stratiform rain (SR) regions, and extensive non-precipitating anvil clouds (AC). This study focuses on the evolution of these three components and the factors that affect convective AC production. An automated satellite tracking method is used in conjunction with a recently developed multi-sensor hybrid classification to analyze the evolution of DCS structure in a Lagrangian framework over the central United States. Composite analysis from 4221 tracked DCSs during two warm seasons (May-August, 2010-2011) shows that maximum system size correlates with lifetime, and longer-lived DCSs have more extensive SR and AC. Maximum SR and AC area lag behind peak convective intensity and the lag increases linearly from approximately 1-hour for short-lived systems to more than 3-hours for long-lived ones. The increased lag, which depends on the convective environment, suggests that changes in the overall diabatic heating structure associated with the transition from CC to SR and AC could prolong the system lifetime by sustaining stratiform cloud development. Longer-lasting systems are associated with up to 60% higher mid-tropospheric relative humidity and up to 40% stronger middle to upper tropospheric wind shear. Regression analysis shows that the areal coverage of thick AC is strongly correlated with the size of CC, updraft strength, and SR area. Ambient upper tropospheric wind speed and wind shear also play an important role for convective AC production where for systems with large AC (radius greater than 120-km) they are 24% and 20% higher, respectively, than those with small AC (radius=20 km).

[1] A new hybrid classification algorithm to objectively identify Deep Convective Systems (DCSs) in radar and satellite observations has been developed. This algorithm can classify the convective cores (CC), stratiform rain (SR) area and nonprecipitating anvil cloud (AC) from the identified DCSs through an integrative analysis of ground-based scanning radar and geostationary satellite data over the Southern Great Plains. In developing the algorithm, AC is delineated into transitional, thick, and thin components. While there are distinct physical/dynamical differences among these subcategories, their top-of-atmosphere (TOA) radiative fluxes are not significantly different. Therefore, these anvil subcategories are grouped as total anvil, and the radiative impact of each DCS component on the TOA radiation budget is quantitatively estimated. We found that more DCSs occurred during late afternoon, producing peak AC fraction right after sunset. AC covers 3 times the area of SR and almost an order of magnitude larger than CC. The average outgoing longwave (LW) irradiances are almost identical for CC and SR, while slightly higher for AC. Compared to the clear-sky average, the reflected shortwave (SW) fluxes for the three DCS components are greater by a factor of 2–3 and create a strong cooling effect at TOA. The calculated SW and LW cloud radiative forcing (CRF) of AC contribute up to 31% of total NET CRF, while CC and SR contribute only 4 and 11%, respectively. The hybrid classification further lays the groundwork for studying the life cycle of DCS and improvements in geostationary satellite IR-based precipitation retrievals.

Hydrological years 2006 (HY06, 10/2005-09/2006) and 2007 (HY07, 10/2006-09/2007) provide a unique opportunity to examine hydrological extremes in the central US because there are no other examples of two such highly contrasting precipitation extremes occurring in consecutive years at the Southern Great Plains (SGP) in recorded history. The HY06 annual precipitation in the state of Oklahoma, as observed by the Oklahoma Mesonet, is around 61% of the normal (92.84 cm, based on the 1921-2008 climatology), which results in HY06 the second-driest year in the record. In particular, the total precipitation during the winter of 2005-06 is only 27% of the normal, and this winter ranks as the driest season. On the other hand, the HY07 annual precipitation amount is 121% of the normal and HY07 ranks as the seventh-wettest year for the entire state and the wettest year for the central region of the state. Summer 2007 is the second-wettest season for the state. Large-scale dynamics play a key role in these extreme events. During the extreme dry period (10/2005-02/2006), a dipole pattern in the 500-hPa GH anomaly existed where an anomalous high was over the southwestern U.S. region and an anomalous low was over the Great Lakes. This pattern is associated with inhibited moisture transport from the Gulf of Mexico and strong sinking motion over the SGP, both contributing to the extreme dryness. The precipitation deficit over the SGP during the extreme dry period is clearly linked to significantly suppressed cyclonic activity over the southwestern U.S., which shows robust relationship with the Western Pacific (WP) teleconnection pattern. The precipitation events during the extreme wet period (May-July 2007) were initially generated by active synoptic weather patterns, linked with moisture transport from the Gulf of Mexico by the northward low level jet, and enhanced by the mesoscale convective systems. Although the drought and pluvial conditions are dominated by large-scale dynamic patterns, we have demonstrated that the two positive feedback processes during the extreme dry and wet periods found in this study play a key role to maintain and reinforce the length and severity of existing drought and flood events. For example, during the extreme dry period, with less clouds, LWP, PWV, precipitation, and thinner Cu cloud thickness, more net radiation was absorbed and used to evaporate water from the ground. The evaporated moisture, however, was removed by low-level divergence. Thus, with less precipitation and removed atmospheric moisture, more absorbed incoming solar radiation was used to increase surface temperature and to make the ground drier.

[1] Asian dust events occur frequently during the boreal spring season. Their optical properties have been analyzed by using a combination of source region (ground-based and satellite) and remote Pacific Ocean (aircraft) measurements during the Intercontinental Chemical Transport Experiment-Phase B (INTEX-B) field campaign which lasted from 7 April to 15 May 2006. A strong dust event originating from the Gobi Desert and passing over the Xianghe surface site on 17 April 2006 has been extensively analyzed. The surface averaged aerosol optical depth (AOD) values increased from 0.17 (clear sky) to 4.0 (strong dust), and the Angstrom exponent (α) dropped from 1.26 (clear sky) to below 0.1. Its total downwelling SW flux over the Xianghe site (thousands of kilometers away from the dust source region) is only 46% of the clear-sky value with almost no direct transmission and nearly double the diffuse SW clear-sky value. This event was also captured 6 days later by satellite observations as well as the UND/NASA DC-8 aircraft over the eastern Pacific Ocean. The DC-8 measurements in the remote Pacific region further classified the plumes into dust dominant, pollution dominant, and a mixture of dust and pollution events. HYSPLIT backward trajectories not only verified the origins of each case we selected but also showed (1) two possible origins for the dust: the Gobi and Taklimakan deserts; and (2) pollution: urban areas in eastern China, Japan, and other industrialized cities east of the two deserts. Based on the averaged satellite retrieved AOD data (0.5° × 0.5° grid box), declining AOD values with respect to longitude demonstrated the evolution of the transpacific transport pathway of Asian dust and pollution over the period of the field campaign.

[1] A 10 year record of Arctic cloud fraction and radiative forcing has been generated using data collected at the Atmospheric Radiation Measurement (ARM) North Slope of Alaska site and the nearby NOAA Barrow Observatory (BRW) from June 1998 to May 2008. The cloud fractions (CFs) derived from ARM radar-lidar and ceilometer measurements increase significantly from March to May (0.57→0.84), remain relatively high (∼0.80–0.9) from May to October, and then decrease from November to the following March (0.8→0.57), having an annual average of 0.76. These CFs are comparable to those derived from ground-based radar-lidar observations during the Surface Heat Budget of the Arctic Ocean experiment and from satellite observations over the western Arctic regions. The monthly means of estimated clear-sky and measured all-sky shortwave (SW)-down and longwave (LW)-down fluxes at the two facilities are almost identical with the annual mean differences less than 1.6 Wm−2. Values of LW cloud radiative forcing (CRF) are minimum (6 Wm−2) in March, then increase monotonically to reach maximum (63 Wm−2) in August, then decrease continuously to the following March. The cycle of SW CRF mirrors its LW counterpart with the greatest negative impact occurring during the snow-free months of July and August. On annual average, the negative SW CRFs and positive LW CRFs nearly cancel, resulting in annual average NET CRF of about 3.5 Wm−2 on the basis of the combined ARM and BRW analysis. Compared with other studies, we find that LW CRF does not change over the Arctic regions significantly, but NET CRFs change from negative to positive from Alaska to the Beaufort Sea, indicating that Barrow is at a critical latitude for neutral NET CRF. The sensitivity study has shown that LW CRFs increase with increasing cloud fraction, liquid water path, and radiating temperature with high positive correlations (0.8–0.9). Negative correlations are found for SW CRFs, but a strong positive correlation between SW CRF and surface albedo exists.

Analysis of a decade of ARM radar-lidar and GOES observations at the SGP site reveal that 0.5 and 4-hr averages of the surface cloud fraction correspond closely to 0.5deg and 2.5deg averages of GOES cloudiness, respectively. The long-term averaged surface and GOES cloud fractions agree to within 0.5%. Cloud frequency increases and cloud amount decreases as the temporal and spatial averaging scales increase. Clouds occurred most often during winter and spring. Single-layered clouds account for 61.5% of the total cloud frequency. There are distinct bimodal vertical distributions of clouds with a lower peak around 1 km and an upper one that varies from 7.5 to 10.8 km between winter and summer, respectively. The frequency of occurrence for nighttime GOES high-cloud tops agree well with the surface observations, but are underestimated during the day.

Atmospheric column absorption of solar radiation A(sub col) is a fundamental part of the Earth's energy cycle but is an extremely difficult quantity to measure directly. To investigate A(sub col), we have collocated satellite-surface observations for the optically thick Deep Convective Systems (DCS) at the Department of Energy Atmosphere Radiation Measurement (ARM) Tropical Western Pacific (TWP) and Southern Great Plains (SGP) sites during the period of March 2000 December 2004. The surface data were averaged over a 2-h interval centered at the time of the satellite overpass, and the satellite data were averaged within a 1 deg X 1 deg area centered on the ARM sites. In the DCS, cloud particle size is important for top-of-atmosphere (TOA) albedo and A(sub col) although the surface absorption is independent of cloud particle size. In this study, we find that the A(sub col) in the tropics is approximately 0.011 more than that in the middle latitudes. This difference, however, disappears, i.e., the A(sub col) values at both regions converge to the same value (approximately 0.27 of the total incoming solar radiation) in the optically thick limit (tau greater than 80). Comparing the observations with the NASA Langley modified Fu_Liou 2-stream radiative transfer model for optically thick cases, the difference between observed and model-calculated surface absorption, on average, is less than 0.01, but the model-calculated TOA albedo and A(sub col) differ by 0.01 to 0.04, depending primarily on the cloud particle size observation used. The model versus observation discrepancies found are smaller than many previous studies and are just within the estimated error bounds. We did not find evidence for a large cloud absorption anomaly for the optically thick limit of extensive ice cloud layers. A more modest cloud absorption difference of 0.01 to 0.04 cannot yet be ruled out. The remaining uncertainty could be reduced with additional cases, and by reducing the current uncertainty in cloud particle size.

Overcast stratus cloud properties derived for the Clouds and the Earth's Radiant Energy system (CERES) Project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site from March 2000 through December 2004. Retrievals from ARM surface-based data were averaged over a 1-hour interval centered at the time of each satellite overpass, and the CERES-MODIS cloud properties were averaged within a 30-km x 30 km box centered on the ARM SGP site. Two datasets were analyzed: all of the data (ALL) which include multilayered, single-layered, and slightly broken stratus decks and a subset, single-layered unbroken decks (SL). The CERES-MODIS effective cloud heights were determined from effective cloud temperature using a lapse rate method with the surface temperature specified as the 24-h mean surface air temperature. For SL stratus, they are, on average, within the ARM radar-lidar estimated cloud boundaries and are 0.534 +/- 0.542 km and 0.108 +/- 0.480 km lower than the cloud physical tops and centers, respectively, and are comparable for day and night observations. The mean differences and standard deviations are slightly larger for ALL data, but not statistically different to those of SL data. The MODIS-derived effective cloud temperatures are 2.7 +/- 2.4 K less than the surface-observed SL cloud center temperatures with very high correlations (0.86-0.97). Variations in the height differences are mainly caused by uncertainties in the surface air temperatures, lapse rates, and cloud-top height variability. The biases are mainly the result of the differences between effective and physical cloud top, which are governed by cloud liquid water content and viewing zenith angle, and the selected lapse rate, -7.1 K km(exp -1). Based on a total of 43 samples, the means and standard deviations of the differences between the daytime Terra and surface retrievals of effective radius r(sub e), optical depth, and liquid water path for SL stratu are 0.1 +/- 1.9 micrometers (1.2 +/- 23.5%), -1.3 +/- 9.5 (-3.6 +/-26.2%), and 0.6 +/- 49.9 gm (exp -2) (0.3 +/- 27%), respectively, while the corresponding correlation coefficients are 0.44, 0.87, and 0.89. For Aqua, they are 0.2 +/- 1.9 micrometers (2.5 +/- 23.4%), 2.5 +/- 7.8 (7.8 +/- 24.3%), and 28.1 +/- 52.7 gm (exp -2) (17.2 +/- 32.2%), as well as 0.35, 0.96, and 0.93 from a total of 21 cases. The results for ALL cases are comparable. Although a bias in R(sub e) was expected because the satellite retrieval of effective radius only represents the top of the cloud, the surface-based radar retrievals revealed that the vertical profile of r(sub e) is highly variable with smaller droplets occurring at cloud top in some cases. The larger bias in optical depth and liquid water path for Aqua is due, at least partially, to differences in the Terra and Aqua MODIS visible channel calibrations. methods for improving the cloud-top height and microphysical property retrievals are suggested.

[1] It has been hypothesized that continuous ground-based remote sensing measurements from collocated active and passive remote sensors combined with regular soundings of the atmospheric thermodynamic structure can be combined to describe the effects of clouds on the clear sky radiation fluxes. We critically test that hypothesis in this paper and a companion paper (part 2). Using data collected at the Southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) site sponsored by the U.S. Department of Energy, we explore an analysis methodology that results in the characterization of the physical state of the atmospheric profile at time resolutions of 5 min and vertical resolutions of 90 m. The description includes thermodynamics and water vapor profile information derived by merging radiosonde soundings with ground-based data and continues through specification of the cloud layer occurrence and microphysical and radiative properties derived from retrieval algorithms and parameterizations. The description of the atmospheric physical state includes a calculation of the clear and cloudy sky solar and infrared flux profiles. Validation of the methodology is provided by comparing the calculated fluxes with top of atmosphere (TOA) and surface flux measurements and by comparing the total column optical depths to independently derived estimates. We find over a 1-year period of comparison in overcast uniform skies that the calculations are strongly correlated to measurements with biases in the flux quantities at the surface and TOA of less than 6% and median fractional errors ranging from 12% to as low as 2%. In the optical depth comparison for uniform overcast skies during the year 2000 where the optical depth varies over more than 3 orders of magnitude we find a mean positive bias of less than 1% and a 0.6 correlation coefficient. In addition to a case study where we examine the cloud radiative effects at the TOA, surface and atmosphere by a middle latitude cyclone, we examine the cloud top pressure and optical depth retrievals of ISCCP and LBTM over a period of 1 year. Using overcast periods from the year 2000, we find that the satellite algorithms tend to compare well with data overall but there is a tendency to bias cloud tops into the middle troposphere and underestimate optical depth in high optical depth events.

This study investigates the impact of snow, graupel, and hail processes on the simulated squall lines over the Southern Great Plains in the United States. Weather Research and Forecasting (WRF) model is used to simulate two squall line events in May 2007, and the results are validated against radar and surface observations in Oklahoma. Several microphysics schemes are tested in this study, including WRF 5-Class Microphysics Scheme (WSM5), WRF 6-Class Microphysics Scheme (WSM6), Goddard Three Ice scheme (Goddard 3-ice) with graupel, Goddard Two Ice scheme (Goddard 2-ice), and Goddard 3-ice hail scheme. The simulated surface precipitation is sensitive to the microphysics scheme, and especially to whether graupel or hail category is included. All of the three ice (3-ice) schemes overestimated the total precipitation, within which WSM6 has the highest overestimation. Two ice (2-ice) schemes, missing a graupel/hail category, produced less total precipitation than 3-ice schemes. By applying a radar-based convective/stratiform partitioning algorithm, we find that by including the graupel/hail processes, there is an increase in areal coverage, precipitation intensity, updraft and downdraft intensity in convective region and a reduction of areal coverage and its precipitation intensity in stratiform region. For vertical structures, all the bulk schemes, especially 2-ice schemes, havemore » the highest reflectivity located at upper levels (~8 km), which is unrealistic compared to observations. In addition, this study shows the radar-based convective/stratiform partitioning algorithm can reasonably identify WRF simulated precipitation, wind and microphysics fields in both convective and stratiform regions.« less

To study Arctic stratus cloud properties and their effect on the surface radiation balance during the spring transition season, analyses are performed using data taken during three cloudy and two clear days in May 1998 as part of the First ISCCP Regional Experiment (FIRE) Arctic Cloud Experiment (ACE). Radiative transfer models are used in conjunction with surface- and satellite-based measurements to retrieve the layer-averaged microphysical and shortwave radiative properties. The surface-retrieved cloud properties in Cases 1 and 2 agree well with the in situ and satellite retrievals. Discrepancies in Case 3 are due to spatial mismatches between the aircraft and the surface measurements in a highly variable cloud field. Also, the vertical structure in the cloud layer is not fully characterized by the aircraft measurements. Satellite data are critical for understanding some of the observed discrepancies. The satellite-derived particle sizes agree well with the coincident surface retrievals and with the aircraft data when they were collocated. Optical depths derived from visible-channel data over snow backgrounds were overestimated in all three cases, suggesting that methods currently used in satellite cloud climatologies derive optical depths that are too large. Use of a near-infrared channel with a solar infrared channel to simultaneously derive optical depth and particle size appears to alleviate this overestimation problem. Further study of the optical depth retrieval is needed. The surface-based radiometer data reveal that the Arctic stratus clouds produce a net warming of 20 W m(exp -2) in the surface layer during the transition season suggesting that these clouds may accelerate the spring time melting of the ice pack. This surface warming contrasts with the net cooling at the top of the atmosphere (TOA) during the same period. All analysis of the complete FIRE ACE data sets will be valuable for understanding the role of clouds during the entire melting and refreezing process that occurs annually in the Arctic.