Calibration Changes to Terra MODIS Collection-5 Radiances for CERES Edition 4 Cloud Retrievals.

Previous research has revealed inconsistencies between the Collection 5 (C5) calibrations of certain channels common to the Terra and Aqua MODerate-resolution Imaging Spectroradiometers (MODIS). To achieve consistency between the Terra and Aqua MODIS radiances used in the Clouds and the Earth's Radiant Energy System (CERES) Edition 4 (Ed4) cloud property retrieval system, adjustments were developed and applied to the Terra C5 calibrations for channels 1-5, 7, 20, and 26. These calibration corrections were developed independently of those used for MODIS Collection 6 (C6) data, which became available after the CERES Ed4 processing had commenced. The comparisons demonstrate that the corrections applied to the Terra C5 data for CERES Edition 4 generally resulted in Terra-Aqua radiance consistency that is as good as or better than that of the C6 datasets. The C5 adjustments resulted in more consistent Aqua and Terra cloud property retrievals than seen in the previous CERES edition. Other calibration artifacts were found in one of the corrected channels and in some of the uncorrected thermal channels after Ed4 began. Where corrections were neither developed nor applied, some artifacts are likely to have been introduced into the Ed4 cloud property record. For example, the degradation in the Aqua MODIS 0.65-µm channel in both the C5 and C6 datasets affects trends in cloud optical depth retrievals. Thus, despite the much-improved consistency achieved for the Terra and Aqua datasets in Ed4, the CERES Ed4 cloud property datasets should be used cautiously for cloud trend studies because of those remaining calibration artifacts.

Object-based verification of a prototype Warn-on-Forecast system.

An object-based verification methodology for the NSSL Experimental Warn-on-Forecast System for ensembles (NEWS-e) has been developed and applied to 32 cases between December 2015 and June 2017. NEWS-e forecast objects of composite reflectivity and 30-minute rotation tracks of updraft helicity are matched to corresponding objects in Multi-Radar Multi-Sensor data on space and time scales typical of a National Weather Service warning. Object matching allows contingency table-based verification statistics to be used to establish baseline performance metrics for NEWS-e thunderstorm and mesocyclone forecasts. NEWS-e critical Success Index (CSI) scores of reflectivity (updraft helicity) forecasts decrease from approximately 0.7 (0.4) to 0.4 (0.2) over 3 hours of forecast time. CSI scores decrease through the forecast period, indicating that errors have not saturated and skill is retained at 3 hours of forecast time. Lower verification scores for rotation track forecasts are primarily a result of a high frequency bias. Comparison of different system configurations used in 2016 and 2017 show an increase in skill for 2017 reflectivity forecasts, attributable mainly to improvements in the forecast initial condition. A small decrease in skill in 2017 rotation track forecasts is likely a result of sample differences between 2016 and 2017. Although large case-to-case variation is present, evidence is found that NEWS-e forecast skill improves with increasing object size and intensity, as well as in mesoscale environments in which an enhanced or higher risk of severe thunderstorms was forecast.

Improving aerosol distributions below clouds by assimilating satellite-retrieved cloud droplet number.

Limitations in current capabilities to constrain aerosols adversely impact atmospheric simulations. Typically, aerosol burdens within models are constrained employing satellite aerosol optical properties, which are not available under cloudy conditions. Here we set the first steps to overcome the long-standing limitation that aerosols cannot be constrained using satellite remote sensing under cloudy conditions. We introduce a unique data assimilation method that uses cloud droplet number (N(d)) retrievals to improve predicted below-cloud aerosol mass and number concentrations. The assimilation, which uses an adjoint aerosol activation parameterization, improves agreement with independent N(d) observations and with in situ aerosol measurements below shallow cumulus clouds. The impacts of a single assimilation on aerosol and cloud forecasts extend beyond 24 h. Unlike previous methods, this technique can directly improve predictions of near-surface fine mode aerosols responsible for human health impacts and low-cloud radiative forcing. Better constrained aerosol distributions will help improve health effects studies, atmospheric emissions estimates, and air-quality, weather, and climate predictions.

Cloud System Evolution in the Trades-CSET: Following the Evolution of Boundary Layer Cloud Systems with the NSF/NCAR GV.

The Cloud System Evolution in the Trades (CSET) study was designed to describe and explain the evolution of the boundary layer aerosol, cloud, and thermodynamic structures along trajectories within the north-Pacific trade-winds. The study centered on 7 round-trips of the NSF NCAR Gulfstream V (GV) between Sacramento, CA and Kona, Hawaii between 1 July and 15 August 2015. The CSET observing strategy was to sample aerosol, cloud, and boundary layer properties upwind from the transition zone over the North Pacific and to resample these areas two days later. GFS forecast trajectories were used to plan the outbound flight to Hawaii with updated forecast trajectories setting the return flight plan two days later. Two key elements of the CSET observing system were the newly developed HIAPER Cloud Radar (HCR) and the High Spectral Resolution Lidar (HSRL). Together they provided unprecedented characterizations of aerosol, cloud and precipitation structures that were combined with in situ measurements of aerosol, cloud, precipitation, and turbulence properties. The cloud systems sampled included solid stratocumulus infused with smoke from Canadian wildfires, mesoscale cloud-precipitation complexes, and patches of shallow cumuli in very clean environments. Ultra-clean layers observed frequently near the top of the boundary layer were often associated with shallow, optically thin, layered veil clouds. The extensive aerosol, cloud, drizzle and boundary layer sampling made over open areas of the Northeast Pacific along 2-day trajectories during CSET is unprecedented and will enable modeling studies of boundary layer cloud system evolution and the role of different processes in that evolution.

Depolarization ratio and attenuated backscatter for nine cloud types: analyses based on collocated CALIPSO lidar and MODIS measurements.

This paper reports on the relationship between lidar backscatter and the corresponding depolarization ratio for nine types of cloud systems. The data used in this study are the lidar returns measured by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite and the collocated cloud products derived from the observations made by the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua satellite. Specifically, the operational MODIS cloud optical thickness and cloud-top pressure products are used to classify cloud types on the basis of the International Satellite Cloud Climatology Project (ISCCP) cloud classification scheme. While the CALIPSO observations provide information for up to 10 cloud layers, in the present study only the uppermost clouds are considered. The layer-averaged attenuated backscatter (gamma') and layer-averaged depolarization ratio (delta) from the CALIPSO measurements show both water- and ice-phase features for global cirrus, cirrostratus, and deep convective cloud classes. Furthermore, we screen both the MODIS and CALIPSO data to eliminate cases in which CALIPSO detected two- or multi-layered clouds. It is shown that low gamma' values corresponding to uppermost thin clouds are largely eliminated in the CALIPSO delta-gamma' relationship for single-layered clouds. For mid-latitude and polar regions corresponding, respectively, to latitude belts 30 degrees -60 degrees and 60 degrees -90 degrees in both the hemispheres, a mixture of water and ice is also observed in the case of the altostratus class. MODIS cloud phase flags are also used to screen ice clouds. The resultant water clouds flagged by the MODIS algorithm show only water phase feature in the delta-gamma' relation observed by CALIOP; however, in the case of the ice clouds flagged by the MODIS algorithm, the co-existence of ice- and water-phase clouds is still observed in the CALIPSO delta-gamma' relationship.

The lifecycle of anvil clouds and the top-of-atmosphere radiation balance over the tropical west Pacific.

Observations from a geostationary satellite are used to describe the lifecycle of mesoscale convective systems (MCS), their associated anvil clouds, and their effects on the radiation balance over the warm pool of the tropical west Pacific Ocean. In their developing stages, MCS primarily consist of clouds that are optically thick and have a negative net cloud radiative effect (CRE). As MCS age, ice crystals in the anvil become larger, the cloud top lowers somewhat, and clouds with neutral and positive net CRE become more common. Shading from anvils causes cool anomalies in the underlying sea surface temperature (SST) of up to -0.6 °C. MCS often occur in clusters that are embedded within large westward-propagating disturbances, so shading from anvils can cool SSTs over regions spanning hundreds of kilometers. Triggering of convection is more likely to follow a warm SST anomaly than a cold SST anomaly on timescales of several days. This information is used to test hypotheses on why, over the warm pool, the average shortwave and longwave CRE are individually large but nearly cancel. The results are consistent with the hypothesis that the cancelation in CRE is caused by feedbacks between cloud albedo, large-scale circulation, and SST.

A Prototype Method for Diagnosing High Ice Water Content Probability Using Satellite Imager Data.

Recent studies have found that flight through deep convective storms and ingestion of high mass concentrations of ice crystals, also known as high ice water content (HIWC), into aircraft engines can adversely impact aircraft engine performance. These aircraft engine icing events caused by HIWC have been documented during flight in weak reflectivity regions near convective updraft regions that do not appear threatening in onboard weather radar data. Three airborne field campaigns were conducted in 2014 and 2015 to better understand how HIWC is distributed in deep convection, both as a function of altitude and proximity to convective updraft regions, and to facilitate development of new methods for detecting HIWC conditions, in addition to many other research and regulatory goals. This paper describes a prototype method for detecting HIWC conditions using geostationary (GEO) satellite imager data coupled with in-situ total water content (TWC) observations collected during the flight campaigns. Three satellite-derived parameters were determined to be most useful for determining HIWC probability: 1) the horizontal proximity of the aircraft to the nearest overshooting convective updraft or textured anvil cloud, 2) tropopause-relative infrared brightness temperature, and 3) daytime-only cloud optical depth. Statistical fits between collocated TWC and GEO satellite parameters were used to determine the membership functions for the fuzzy logic derivation of HIWC probability. The products were demonstrated using data from several campaign flights and validated using a subset of the satellite-aircraft collocation database. The daytime HIWC probability was found to agree quite well with TWC time trends and identified extreme TWC events with high probability. Discrimination of HIWC was more challenging at night with IR-only information. The products show the greatest capability for discriminating TWC ≥ 0.5 g m-3. Product validation remains challenging due to vertical TWC uncertainties and the typically coarse spatio-temporal resolution of the GEO data.

Quantifying the Dependence of Satellite Cloud Retrievals on Changes in Instrument Calibration.

How clouds will respond to Earth's warming climate is the greatest contributor to intermodel spread of Equilibrium Climate Sensitivity (ECS). Although global climate models (GCMs) generally agree that the total cloud feedback is positive, GCMs disagree on the magnitude of cloud feedback. Satellite instruments with sufficient accuracy to detect climate change-scale trends in cloud properties will provide improved confidence in our understanding of the relationship between observed climate change and cloud property trends, thus providing essential information to the effort to better constrain ECS. However, a robust framework is needed to determine what constitutes sufficient or necessary accuracy for such an achievement. Our study presents and applies such an accuracy framework to quantify the impact of absolute calibration accuracy requirements on climate change-scale trend detection times for cloud amount, height, optical thickness, and effective radius. The accuracy framework used here was previously applied to SW cloud radiative effect and global mean surface temperature in a study that demonstrated the importance of high instrument accuracy to constrain trend detection times for essential climate variables (ECVs). This paper expands upon these previous studies by investigating cloud properties, demonstrating the versatility of applying this framework to other ECVs and the implications of the results within climate science studies.

Inter-comparisons of marine boundary layer cloud properties from the ARM CAP-MBL campaign and two MODIS cloud products.

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 (CER2.1) is significantly smaller than that based on the 3.7 µm band (CER3.7). 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 CER3.7 and CER2.1 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.

Dust and biological aerosols from the Sahara and Asia influence precipitation in the western U.S.

Winter storms in California's Sierra Nevada increase seasonal snowpack and provide critical water resources and hydropower for the state. Thus, the mechanisms influencing precipitation in this region have been the subject of research for decades. Previous studies suggest Asian dust enhances cloud ice and precipitation, whereas few studies consider biological aerosols as an important global source of ice nuclei (IN). Here, we show that dust and biological aerosols transported from as far as the Sahara were present in glaciated high-altitude clouds coincident with elevated IN concentrations and ice-induced precipitation. This study presents the first direct cloud and precipitation measurements showing that Saharan and Asian dust and biological aerosols probably serve as IN and play an important role in orographic precipitation processes over the western United States.

Formation and spread of aircraft-induced holes in clouds.

Hole-punch and canal clouds have been observed for more than 50 years, but the mechanisms of formation, development, duration, and thus the extent of their effect have largely been ignored. The holes have been associated with inadvertent seeding of clouds with ice particles generated by aircraft, produced through spontaneous freezing of cloud droplets in air cooled as it flows around aircraft propeller tips or over jet aircraft wings. Model simulations indicate that the growth of the ice particles can induce vertical motions with a duration of 1 hour or more, a process that expands the holes and canals in clouds. Global effects are minimal, but regionally near major airports, additional precipitation can be induced.

Changes in Earth's albedo measured by satellite.

NASA global satellite data provide observations of Earth's albedo, i.e., the fraction of incident solar radiation that is reflected back to space. The satellite data show that the last four years are within natural variability and fail to confirm the 6% relative increase in albedo inferred from observations of earthshine from the moon. Longer global satellite records will be required to discern climate trends in Earth's albedo.