ALBERT

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Description: According to CDC, a sharp increase in reported Valley fever cases (Coccidioidomycosis) has been found between 2009 and 2012. Environmental conditions play an important role for Valley fever outbreaks. For example, dust storms can significantly increase the amount of the fungus Coccidioides in the air and associated strong winds can transport the fungus to other areas. In last years AGU session, we reported a preliminary study to investigate hydrometeorological conditions and their connection with dust storm activities in southwestern United States. We found wind is a major contributing factor for the seasonal variation of dust storm activities. Interannual variation of the regional hydrometeorological conditions are closely linked to the large-scale environment such as the Pacific Decadal Oscillation (PDO). Strong winds are linked with a number of weather events such cold front passages, thunderstorms that produce downbursts and strong winds, the Santa Ana winds, etc. In this presentation, we will report the results of our latest investigation on meteorological conditions associated with Valley fever outbreaks in southwestern United States, using NLDAS (North American Land Data Assimilation System), GPM (Global Precipitation Measurement), and MERRA-2 (Modern Era Retrospective-analysis for Research and Applications, Version 2) hourly datasets, from the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC).

Description: Atmospheric rivers (ARs) are responsible for some of the hydroclimatic extremes around the world. Their mechanisms and contribution to flooding in the Middle East are relatively poorly understood. This study shows that the record floods during March 2019 across the Middle East were caused by a powerful AR, originated from the North Atlantic Ocean. Iran, in particular, was substantially affected by the floods. The nearly 9000 km long AR propagated across North Africa and the Middle-East, and was fed by additional moisture from several other sources on its pathway. Simultaneous presence of a mid-latitude system and a subtropical jet facilitated the moisture supply. The AR, as passing over the Zagros Mountains, produced record rainfall induced by the orographic forcing.

Description: Atmospheric Rivers (ARs) are responsible for much of the precipitation along the west coast of the United States. In order to accurately predict AR events in numerical weather prediction, subseasonal and seasonal timescales, it is important to understand the large-scale meteorological influence on extreme AR events.Here, characteristics of ARs that result in an extreme precipitation event are compared to typical ARs on the coast of WashingtonState. In addition to more intense water vapor transport, notable differences in the synoptic forcing are present during extreme precipitation events that are not present during typical AR events.In particular, a negatively tilted low pressure system is positioned to the west in the Gulf of Alaska, alongside an upper level jet streak. Subseasonal and seasonal teleconnection patterns are known to influence the weather in the Pacific Northwest. The Madden JulianOscillation (MJO) is shown to be particularly important in determining the strength of precipitation associated with in AR ont he Washington coast.

Description: Project Loon has an overall goal of providing worldwide internet coverage using a network of long-duration super-pressure balloons. Beginning in 2013, Loon has launched over 1600 balloons from multiple tropical and middle latitude locations. These GPS tracked balloon trajectories provide lower stratospheric wind information over the oceans and remote land areas where traditional radiosonde soundings are sparse, thus providing unique coverage of lower stratospheric winds. To fully investigate these Loon winds we: 1) compare the Loon winds to winds produced by a global data assimilation system (DAS: NASA GEOS) and 2) assimilate the Loon winds into the same comprehensive DAS. During May through December 2016 Loon balloons were often able to remain near the equator by selectively adjusting the Loon altitude. Our results based on global wind analyses show that the expected mean poleward motion from the Brewer-Dobson circulation can be circumvented by vertically adjusting the Loon altitudes with the phasing with the meridional wind of equatorial Rossby waves, allowing the Loon balloons to remain in the tropics.

Description: Terrestrial gross primary production (GPP) is the basis of vegetation growth and food production globally and plays a critical role in regulating atmospheric CO2 through its impact on ecosystem carbon balance. Even though higher CO2 concentrations in future decades can increase GPP, low soil water availability, heat stress and disturbances associated with droughts could reduce the benefits of such CO2 fertilization. Here we analysed outputs of 13 Earth system models to show an increasingly stronger impact on GPP by extreme droughts than by mild and moderate droughts over the twenty-first century. Due to a dramatic increase in the frequency of extreme droughts, the magnitude of globally averaged reductions in GPP associated with extreme droughts was projected to be nearly tripled by the last quarter of this century (2075-2099) relative to that of the historical period (1850-1999) under both high and intermediate GHG emission scenarios. By contrast, the magnitude of GPP reductions associated with mild and moderate droughts was not projected to increase substantially. Our analysis indicates a high risk of extreme droughts to the global carbon cycle with atmospheric warming; however, this risk can be potentially mitigated by positive anomalies of GPP associated with favourable environmental conditions.

Description: We revisit the bias correction problem in current climate models, taking advantage of state-of-the-art atmospheric reanalysis data and new data assimilation tools that simplify the estimation of short-term (6 hourly) atmospheric tendency errors. The focus is on the extent to which correcting biases in atmospheric tendencies improves the models climatology, variability, and ultimately forecast skill at subseasonal and seasonal time scales. Results are presented for the NASA GMAO GEOS model in both uncoupled (atmosphere only) and coupled (atmosphereocean) modes. For the uncoupled model, the focus is on correcting a stunted North Pacific jet and a dry bias over the central United States during boreal summerlong-standing errors that are indeed common to many current AGCMs. The results show that the tendency bias correction (TBC) eliminates the jet bias and substantially increases the precipitation over the Great Plains. These changes are accompanied by much improved (increased) storm-track activity throughout the northern midlatitudes. For the coupled model, the atmospheric TBCs produce substantial improvements in the simulated mean climate and its variability, including a much reduced SST warm bias, more realistic ENSO-related SST variability and teleconnections, and much improved subtropical jets and related submonthly transient wave activity. Despite these improvements, the improvement in subseasonal and seasonal forecast skill over North America is only modest at best. The reasons for this, which are presumably relevant to any forecast system, involve the competing influences of predictability loss with time and the time it takes for climate drift to first have a significant impact on forecast skill.

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Description: This study evaluates some available schemes designed to solve the stochastic collection equation (SCE) for collision-coalescence of hydrometeors using a size-resolved (bin) microphysics approach, and documents their numerical properties within the framework of a box model. Comparing three widely used SCE schemes, we find that all converge to almost identical solutions at sufficiently fine mass grids. However, one scheme converges far slower than the other two and shows pronounced numerical diffusion at the large-drop tail of the size distribution. One of the remaining two schemes is recommended on the basis that it is well-converged on a relatively coarse mass grid, stable for large time steps, strictly mass-conservative, and computationally efficient. To examine the effects of SCE scheme choice on simulating clouds and precipitation, two of the three schemes are compared in large-eddy simulations of a drizzling stratocumulus field. A forward simulator that produces Doppler spectra from the large-eddy simulation results is used to compare the model output directly with radar observations. The scheme with pronounced numerical diffusion predicts excessively large mean Doppler velocities and overly broad and negatively skewed spectra compared with observations, consistent with numerical diffusion demonstrated in the box model. Statistics obtained using the recommended scheme are closer to observations, but notable differences remain, indicating that factors other than SCE scheme accuracy are limiting simulation fidelity.

Description: If an industrial civilization had existed on Earth many millions of years prior to ourown era, what traces would it have left and would they be detectable today? We summarize the likely geological fingerprint of the Anthropocene, and demonstrate that while clear, it will not differ greatly in many respects from other known events in the geological record. We then propose tests that could plausibly distinguish an industrial cause from an otherwise naturally occurring climate event.

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Description: Falling snow is a key component for the global atmospheric, hydrological and energy cycles, and its retrieval from space-based observations represents the best current capability to evaluate it globally. The Global Precipitation Measurement (GPM) Mission Core Observatory, launched in 2014, together with its constellation sensors, can provide quasi-global precipitation estimates every 30 minutes (for level 3 products). Evaluation and validation efforts for such products are crucial, and for global evaluations, one of the most suitable instruments is the Cloud Profiling Radar (CPR) on board CloudSat, which is sensitive to light rain and falling snow. However, due to a battery anomaly in 2011, during its period of overlapping observations with GPM the CPR has operated in a Daylight Only Operations mode (DO-Op) in which it makes measurements primarily during only the daylit portion of its orbit. The goal of this work is to estimate biases inherent in global snowfall amounts derived from CPR measurements due to this shift to DO-Op mode. We use CloudSat's snowfall measurements during its Full Operations (Full-Op) period from 2006 to 2010 to evaluate the impact DO-Op mode would have had during this period. Results indicate that omitting the nocturnal component of the diurnal cycle of snowfall has nonnegligible impact on snowfall amounts in some regions. The lack of nighttime data during DO-Op biases the latitudinally averaged mean snowfall rates as well as some regional values. Hemispheric differences in bias may be due to more pronounced diurnal variability in the northern hemisphere owing to more prevalent land surface versus the southern hemisphere. The results highlight the need to sample consistently with the CloudSat observations or to adjust snowfall estimates derived from CloudSat when using DO-Op data to evaluate other precipitation products.

Description: The Ground Validation (GV) component of the Global Precipitation Measurement (GPM) mission involved several field campaigns, involving aircraft, ground radars, and other instrument networks designed to measure various aspects of precipitation. In many cases, these instruments are still in operation at ongoing data collection sites at Wallops Flight Facility, VA and Marquette, MI. The data collected has been used for algorithm formulation and validation, but in many cases has been under-utilized. This presentation describes aspects of GPM algorithms that could benefit from GV data that has been collected and announces a workshop to be held for that purpose in March 2020.

Description: Cloud and precipitation systems over the tropics and subtropics are simulated with a multi-scale modeling framework (MMF) and compared against the TRMM radar precipitation features (RPFs) product. A methodology, in close analogy to the TRMM RPFs, is developed to analyze simulated cloud precipitating structures from the embedded two-dimensional cloud-resolving models (CRMs) within an MMF. Despite the two-dimensionality of the CRMs, the simulated RPFs population distribution, and horizontal and vertical structure are in good agreement with TRMM observations. However, some deficits are also found in the model simulations. The model tends to overestimate mean convective precipitation rates for RPFs with a size less than 100 km, contributing to the excessive precipitation biases in the warm pool and western Pacific, western and northern India Ocean, and eastern Pacific commonly found in most MMFs. For large features with a size greater than 150 km, both convective and stratiform rain rates are underestimated. The distribution of maximum radar echo top heights as a function of RPF size is well simulated except the model tends to underestimate the occurrence frequency of maximum heights greater than 15 km. The maximum echo top heights for convective cells embedded within large RPFs with a size greater than 150 km are also underestimated. The cyclic lateral boundary with a limited model domain generates artificial occurrences for RPFs with a size close to the model domain size, producing a significant contribution to the total rainfall due to their sizes. This cyclic lateral boundary effect can be easily identified and quantified in both probability and cumulative distribution functions of RPFs. The geophysical distribution of the population of the largest RPFs in the control experiment shows they are mainly located in the Subtropics but also partially contribute to the common MMF biases of excessive precipitation in the Tropics. Sensitivity experiments using CRMs with different domain sizes and different grid spacings show larger domains (higher resolution) tend to shift the RPFs distribution to large (small) sizes. The cyclic lateral boundary biases increase as CRM domain size decreases. The impacts of model horizontal and vertical resolution on simulated convective systems are also investigated.

Description: Explosive volcanic eruptions are one of the largest natural climate perturbations, but few observational constraints exist on either the climate responses to eruptions or the properties (size, hemispheric aerosol distribution, etc.) of the eruptions themselves. Paleoclimate records are thus important sources of information on past eruptions, often through the measurement of oxygen isotopic ratios (18O) in natural archives. However, since many processes affect 18O, the dynamical interpretation of these records can be quite complex. Here we present results from new, isotope-enabled members of the Community Earth System Model Last Millennium Ensemble, documenting eruption-induced 18O variations throughout the climate system. Eruptions create significant perturbations in the 18O of precipitation and soil moisture in central/eastern North America, via excitation of the Atlantic Multidecadal Oscillation. Monsoon Asia and Australia also exhibit strong precipitation and soil 18O anomalies; in these cases, 18O may reflect changes to El Nio-Southern Oscillation phase following eruptions. Salinity and seawater 18O patterns demonstrate the importance of both local hydrologic shifts and the phasing of the El Nio-Southern Oscillation response, both along the equator and in the subtropics. In all cases, the responses are highly sensitive to eruption latitude, which points to the utility of isotopic records in constraining aerosol distribution patterns associated with past eruptions. This is most effective using precipitation 18O; all Southern eruptions and the majority (66%) of Northern eruptions can be correctly identified. This work thus serves as a starting point for new, quantitative uses of isotopic records for understanding volcanic impacts on climate.

Description: Global warming due to greenhouse gases and atmospheric aerosols alter precipitation rates, but the influence on extreme precipitation by aerosols relative to greenhouse gases is still not well known. Here we use the simulations from the Precipitation Driver and Response Model Intercomparison Project that enable us to compare changes in mean and extreme precipitation due to greenhouse gases with those due to black carbon and sulfate aerosols, using indicators for dry extremes as well as for moderate and very extreme precipitation. Generally, we find that the more extreme a precipitation event is, the more pronounced is its response relative to global mean surface temperature change, both for aerosol and greenhouse gas changes. Black carbon (BC) stands out with distinct behavior and large differences between individual models. Dry days become more frequent with BC-induced warming compared to greenhouse gases, but so does the intensity and frequency of extreme precipitation. An increase in sulfate aerosols cools the surface and thereby the atmosphere, and thus induces a reduction in precipitation with a stronger effect on extreme than on mean precipitation. A better understanding and representation of these processes in models will provide knowledge for developing strategies for both climate change and air pollution mitigation.

Description: The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides archive and distribution services for several data products in the Planetary Boundary Layer (PBL) category. As a new variable added to the Atmospheric Infrared Sounder (AIRS) Version 6 support product, the PBL height from AIRS is derived based on the gradients of the retrieved relative humidity profile, and provides the atmospheric pressure at the top of the PBL over the ocean. The GES DISC also hosts the Modern-Era Retrospective analysis for Research and Applications-2 (MERRA-2) product generated by the Goddard Earth Observing System Model Version 5 (GEOS-5) data assimilation system. The PBL height from MERRA-2 is based on the total eddy diffusion coefficient of heat. The monthly PBL height has been made available in the Giovanni system (Giovanni is a Web-based application developed by the GES DISC providing a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data). Recently, the GES DISC began serving the global PBL height climatology product derived from the COSMIC/FORMOSAT-3 and TerraSAR-X Global Positioning System (GPS) radio occultation (RO) measurements from June 2006 to December 2015. In a previous study, we presented the monthly PBL height data from AIRS and MERRA-2 and demonstrated the GES DISC services which support data intercomparison, such as access, plotting, sub-setting, regridding, and generation of a multi-year monthly mean. We also provided intercomparison results, and found that different PBL height definitions contributed to significant differences of PBL height values between AIRS and MERRA-2. In this work, we present the 10-year seasonal climatologies from the AIRS, MERRA-2 and GPS-RO. We also used the cross section and vertical profile services in Giovanni to display and analyze the vertical atmosphere structure over regions where the PBL height derived from the AIRS and MERRA-2 are quite different. The examination of the AIRS and MERRA-2 three-dimensional data found that the relative humidity profiles had larger differences than the temperature profiles. The MERRA-2 gives more details than the AIRS for the vertical distribution of the humidity.

Description: Low clouds continue to contribute greatly to the uncertainty in cloud feedback estimates. Depending on whether a region is dominated by cumulus (Cu) or stratocumulus (Sc) clouds, the interannual low-cloud feedback is somewhat different in both spaceborne and large-eddy simulation studies. Therefore, simulating the correct amount and variation of the Cu and Sc cloud distributions could be crucial to predict future cloud feedbacks. Here we document spatial distributions and profiles of Sc and Cu clouds derived from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat measurements. For this purpose, we create a new dataset called the Cumulus And Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD), which identifies Sc, broken Sc, Cu under Sc, Cu with stratiform outflow and Cu. To separate the Cu from Sc, we design an original method based on the cloud height, horizontal extent, vertical variability and horizontal continuity, which is separately applied to both CALIPSO and combined CloudSatCALIPSO observations. First, the choice of parameters used in the discrimination algorithm is investigated and validated in selected Cu, Sc and ScCu transition case studies. Then, the global statistics are compared against those from existing passive- and active-sensor satellite observations. Our results indicate that the cloud optical thickness as used in passive-sensor observations is not a sufficient parameter to discriminate Cu from Sc clouds, in agreement with previous literature. Using clustering-derived datasets shows better results although one cannot completely separate cloud types with such an approach. On the contrary, classifying Cu and Sc clouds and the transition between them based on their geometrical shape and spatial heterogeneity leads to spatial distributions consistent with prior knowledge of these clouds, from ground-based, ship-based and field campaigns. Furthermore, we show that our method improves existing ScCu classifications by using additional information on cloud height and vertical cloud fraction variation. Finally, the CASCCAD datasets provide a basis to evaluate shallow convection and stratocumulus clouds on a global scale in climate models and potentially improve our understanding of low-level cloud feedbacks. The CASCCAD dataset (Cesana, 2019, https://doi.org/10.5281/zenodo.2667637) is available on the Goddard Institute for Space Studies (GISS) website at https://data.giss.nasa.gov/clouds/casccad/ (last access: 5 November 2019) and on the zenodo website at https://zenodo.org/record/2667637 (last access: 5 November 2019).

Description: Ground validation (GV) for the Global Precipitation Measurement (GPM) mission encompasses in-situ (e.g., gauge, disdrometer) measurements, ground radar products, and comprehensive datasets from dedicated airborne field campaigns. These datasets are used for direct validation of the precipitation products from GPM as well as to inform assumptions used by the algorithms that produce these products. This presentation will focus on current and potential such uses of GV data in the GPM combined radar-radiometer algorithm.The GPM combined algorithm, by virtue of using data from the Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI), is the most well-constrained instantaneous precipitation product from GPM. It also plays an important in role the passive microwave algorithms as a basis for the construction of brightness temperature-precipitation profile databases and is a calibrator for the multi- satellite gridded product IMERG. Since both radar and radiometer data are used as observational inputs, and even with these data the retrievals are underconstrained, microphysical properties of the hydrometeor profile that are relevant over the range of GMI and DPR wavelengths and incidence angles need to be assumed by the algorithm forward models. Such properties include the normalized intercept parameter (N w ) and shape parameter () of the particle size distribution, ice size-density relationship, and particle size-aspect ratio relationships. The sub-beam variability must also be prescribed in order to accurately simulate the observed radar reflectivity profiles without introducing significant biases. The sensitivity of the algorithm to these parameters, along with their mean values and variability, will be discussed. Examples of future directions include refinement with new data (particularly the assumptions related to ice), and seeking relationships between assumptions and observable or environmental data.

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Description: Arctic clouds play an important role in modifying the surface energy balance. In the Arctic, clouds are thought to influence the underlying sea ice cover through changing downwelling longwave radiative fluxes to the surface and through the selective reflection of the shortwave flux in summer. Atmospheric reanalyses are generally thought to have a poor representation of cloud processes at high latitudes, although the representation of trends over the perennial Arctic sea ice pack is less well known. Here, atmospheric energy fluxes are examined at the top of the atmosphere from contemporary reanalyses in comparison to satellite measurements from the CERES-EBAF version 4.1 product. The principal reanalyses examined are the NASA MERRA-2, the ECMWF ERA5 and ERA-Interim, the JRA-55, and the regional Arctic System Reanalysis version 2. In agreement with previous observation-based studies, changes with time in the shortwave cloud radiative forcing in reanalyses are found to be negligible despite strong trends in the absorbed shortwave. Over the full satellite period, there is large disagreement in the seasonality of longwave cloud forcing trends. These trends are reduced during the CERES-EBAF observing period (2003-present). An examination of these trends with respect to sea ice cover changes in each of the reanalyses is conducted.

Description: The TTL lies between the neutral buoyancy level (NBL) at ~350 K and the tropopause. Within the the TTL radiative heating drives ascent and air parcel supersaturation. Ticosonde measurements since 2005 show that the incidence ofsupersaturation in the TTL over Costa Rica is ~60%. This is due to diabatic ascent. The frequency is highest (68%) in summer, when convection is frequent. The TSL was defined by Selkirk et al. (2010) as the upper edge of the TTL. It isIn this layer that the final saturation of air parcels rising into the stratosphere occurs and thus the water vapor minima which define the so-called "writehead" of the Atmospheric Tape Recorder.

Description: Observing and better understanding clouds and aerosols are priorities in the NASA Earth Science Decadal Survey, US National Climate Assessment, and Intergovernmental Panel on Climate Change Report. The Global Learning & Observations to Benefit the Environment (GLOBE) Program is NASA's largest and longest running citizen science program in the Earth Sciences that collects cloud observations. Since January 2017, NASA GLOBE students and citizen scientists have submitted over 800,000 cloud observations worldwide using both paper-based and smartphone app platforms. In this presentation, we compare satellite, model, and volunteer-reported total cloud cover. The comparison reveals a systematic misreporting of obscured skies (sky not visible due to smoke, dust, haze, etc.) versus overcast skies (100% total cloud cover) by GLOBE participants. We discuss implications for improving procedures for volunteer reporting under overcast and obscured sky conditions, and relevance for reporting extreme air pollution events in areas with little or no formal institutional monitoring networks.

Description: To overcome a deficiency in the standard Ku- and Ka-band dual-wavelength radar technique, a modified version of the method is introduced. The deficiency arises from ambiguities in the estimate of the massweighted diameter Dm of the raindrop size distribution (DSD) derived from the differential frequency ratio (DFR), defined as the difference between the radar reflectivity factors (dB) at Ku and Ka band Z(sub Ku) - Z(sub Ka). In particular, for DFR values less than zero, there are two possible solutions of Dm, leading to ambiguities in the retrieved DSD parameters. It is shown that the double solutions to Dm are effectively eliminated if the DFR is modified from Z(sub Ku) - Z(sub Ka) to Z(sub Ku) - gZ(sub Ka). (dB), where g is a constant with a value less than 0.8. An optimal radar algorithm that uses the modified DFR for the retrieval of rain and Dm profiles is described. The validity and accuracy of the algorithm are tested by applying it to radar profiles that are generated from measured DSD data. Comparisons of the rain rates and Dm estimated from the modified DFR algorithm to the same hydrometeor quantities computed directly from the DSD spectra (or the truth) indicate that the modified DFR-based profiling retrievals perform fairly well and are superior in accuracy and robustness to retrievals using the standard DFR.

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Description: The GLOBE (Global Learning and Observations to Benefit the Environment) Program is NASA's largest and longest-operating citizen science program contributing Earth observations. Over 800,000 cloud observations have been reported worldwide since YEAR that include reports of short-lived, persistent, and persistent-spreading contrails. While contrails can be challenging to observe with space-borne platforms, humans are adept at spotting contrails from the ground. The NASA GLOBE Clouds team at NASA Langley Research Center in Hampton, Virginia matches cloud observations to multiple satellite platforms for comparison, including: NASA's CERES (Clouds and Earth's Radiant Energy System) instrument onboard Terra and Aqua, CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation), and geostationary satellites. A pilot project was started with select students in the United States to track airplanes above 25,000 ft and report airplane type, altitude, and report if a contrail was being or was not being produced. The objective of the pilot project was to establish if this is a scalable approach for building an international observational dataset documenting what types of airplanes are creating what types of contrails (short-lived, persistent, spreading) under what atmospheric conditions. Preliminary results of this pilot project will be presented.

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Description: Blowing snow is a frequent and ubiquitous phenomenon over most over Antarctica. The transport and sublimation of blowing snow are important for the mass balance of the Antarctic ice sheet and the latter is a major contributor to the hydrological cycle in high latitude regions. While much is known about blowing snow from surface observations, our knowledge of the thermodynamic structure of deep blowing snow layers is lacking. Here dropsonde measurements are used to investigate the temperature, moisture and wind structure of deep blowing snow layers over Antarctica. The temperature lapse rate within the blowing snow layer is found to be at times close to dry adiabatic and on average between dry and moist adiabatic. Initiation of blowing snow causes the surface temperature to increase to a degree proportional to the depth of the blowing snow layer. The relative humidity is generally largest near the surface (but less than 100%) and decreases with height reaching a minimum near the top of the layer. These findings are at odds with accepted theory which assumes blowing snow sublimation will cool and eventually saturate the layer. The observations support the conclusion that high levels of wind shear induced turbulence causes mixing and entrainment of warmer and drier air from above the blowing snow layer which suppresses humidity and produces the observed well-mixed temperature structure within the layer. The results may have important consequences for Antarctic ice sheet mass balance and the moisture budget of the atmosphere in high latitudes.

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Description: Lightning produces NO because the extreme temperatures (〉20000 K) in lightning channels dissociate molecular O2 and molecular N2, which then combine to form NOx which quickly reacts with O3 to form NO2. Lightning is responsible for 10-15% of NOx emissions globally. This is 2 8 Tg N a-1 [Schumann and Huntrieser, 2007] or 100 to 400 mol per flash. Much of the uncertainty stems from limited knowledge of lightning NOx production per flash (LNOx PE) or per unit flash length. Most LNOx is injected into mid- and upper-troposphere where away from deep convection its lifetime is longer relative to lower troposphere NOx. NOx in this region enhances the concentrations of upper tropospheric NOy, OH, and O3 and contributes to positive radiative forcing by O3 and negative forcing by CH4. We have previously used OMI NO2 to obtain estimates of LNOx production per flash over the Gulf of Mexico (Pickering et al., 2016, JGR), in convective events during NASAs TC4 field program (Bucsela et al., 2010, JGR), and over broad regions of the tropics (Allen et al., 2019, JGR) and midlatitudes (Bucsela et al., 2019, JGR). In the latter studies, we obtained PE values of 170 100 mol flash and 180 100 mol flash, respectively.

Description: As the number of Earth pointing satellites has increased over the last several decades, the data volume retrieved from instruments onboard these satellites has also increased. It is expected that this trend will continue as more data intensive missions and small satellite constellations are launched. Currently, feature detection - namely atmospheric phenomena - in these datasets is performed manually and is thus not scalable with the growing data archives. Recent advancements in computational efficiency allow for the Earth science community to leverage machine learning to identify interesting atmospheric phenomena. Given the wide range of distinctive features in various atmospheric phenomena, a specialized machine learning model is required for accurate detection of these phenomena independently. The Phenomena Portal, developed at NASA IMPACT, is designed to provide visualization for the output from these machine learning models. In addition, detected events for each atmospheric phenomena are stored in a database that can be used to more easily use/subset larger spatiotemporal datasets. The user interface also incorporates additional features to enhance the user experience including spatiotemporal analysis, multiple base layer images, and a slider to filter events with lower probabilities of positive detection. Each detection supports user feedback on whether the detection is true or false that can then be stored and used to improve the machine learning model performance.

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Description: Heterogeneous ice nucleation initiated by particles immersed within droplets is likely the main pathway of ice formation in the atmosphere. Theoretical models commonly used to describe this process assume that it mimics ice formation from the vapor, neglecting interactions unique to the liquid phase. This work introduces a new approach that accounts for such interactions by linking the ability of particles to promote ice formation to the modification of the properties of water near the particle-liquid interface. It is shown that the same mechanism that lowers the thermodynamic barrier for ice nucleation also tends to decrease the mobility of water molecules, hence the ice-liquid interfacial flux. Heterogeneous ice nucleation in the liquid phase is thus determined by the competition between thermodynamic and kinetic constraints to the formation and propagation of ice. At the limit, ice nucleation may be mediated by kinetic factors instead of the nucleation work. This new ice nucleation regime is termed spinodal ice nucleation. Comparison of predicted nucleation rates against published data suggests that some materials of atmospheric relevance may nucleate ice in this regime.

Description: The radiative flux data and other meteorological data in the BSRN archive start from 1992, but the RadFlux data, the clearsky radiative fluxes at the BSRN sites derived through regression analyses of actually observed clearsky fluxes, did not come into existence until the early 2000s, and at first, they were limited to the 7 NOAA SURFRAD and 4 DOE ARM sites, a subset of the BSRN sites. Recently, the RadFlux algorithm was applied more extensively to the BSRN sites for the production of clearsky groundbased fluxes. At the time of this writing, there are 7119 site-months of clearsky fluxes at 42 BSRN sites spanning the time from 1992 to late 2017. These data provide an unprecedented opportunity to validate the satellite based clearsky fluxes. In this paper, the GEWEX SRB GSW(V3.0) shortwave downward fluxes spanning 24.5 years from 198307 to 200712, the CERES SYN1deg(Ed4A) and EBAF(Ed4.0) shortwave fluxes spanning 200003 to mid2017 are compared with their RadFlux counterparts on the hourly, 3hourly, daily and monthly time scales. All the three datasets show reasonable agreement with their groundbased counterparts. Comparison of the satellitebased surface shortwave clearsky radiative fluxes to the BSRN RadFlux analysis shows negative biases. Further analysis shows that the satellitebased atmosphere contains greater aerosol optical paths as well as more precipitable water than RadFlux analysis estimates.

Description: 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.

Description: Previous multi-model intercomparisons have shown that chemistryclimate models exhibit significant biases in tropospheric ozone compared with observations. We investigate annual-mean tropospheric column ozone in 15 models participating in the SPARCIGAC (Stratospheretroposphere Processes And their Role in ClimateInternational Global Atmospheric Chemistry) Chemistry-Climate Model Initiative (CCMI). These models exhibit a positive bias, on average, of up to 40 %50 % in the Northern Hemisphere compared with observations derived from the Ozone Monitoring Instrument and Microwave Limb Sounder (OMI/MLS), and a negative bias of up to 30 % in the Southern Hemisphere. SOCOLv3.0 (version 3 of the Solar-Climate Ozone Links CCM), which participated in CCMI, simulates global-mean tropospheric ozone columns of 40.2 DU approximately 33 % larger than the CCMI multi-model mean. Here we introduce an updated version of SOCOLv3.0, SOCOLv3.1, which includes an improved treatment of ozone sink processes, and results in a reduction in the tropospheric column ozone bias of up to 8 DU, mostly due to the inclusion of N2O5 hydrolysis on tropospheric aerosols. As a result of these developments, tropospheric column ozone amounts simulated by SOCOLv3.1 are comparable with several other CCMI models. We apply Gaussian process emulation and sensitivity analysis to understand the remaining ozone bias in SOCOLv3.1. This shows that ozone precursors (nitrogen oxides (NO(sub x)), carbon monoxide, methane and other volatile organic compounds, VOCs) are responsible for more than 90 % of the variance in tropospheric ozone. However, it may not be the emissions inventories themselves that result in the bias, but how the emissions are handled in SOCOLv3.1, and we discuss this in the wider context of the other CCMI models. Given that the emissions data set to be used for phase 6 of the Coupled Model Intercomparison Project includes approximately 20 % more NO(sub x) than the data set used for CCMI, further work is urgently needed to address the challenges of simulating sub-grid processes of importance to tropospheric ozone in the current generation of chemistryclimate models.

Description: Efforts to limit global warming to below 2C in relation to the preindustrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming 〉2C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5 and 2.0C warming above the preindustrial period) on global wheat production and local yield variability. A multicrop and multiclimate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by 2.3% to 7.0% under the 1.5C scenario and 2.4% to 10.5% under the 2.0C scenario, compared to a baseline of 19802010, when considering changes in local temperature, rainfall, and global atmospheric CO2 concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield interannual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producerIndia, which supplies more than 14% of global wheat. The projected global impact of warming 〈2C on wheat production is therefore not evenly distributed and will affect regional food security across the globe as well as food prices and trade.

Description: The purpose of this study was to evaluate snow and snowmelt simulated by version 4 of the Community Land Model (CLM4). We performed uncoupled CLM4 simulations, forced by ModernEra Retrospective Analysis for Research and Applications Landonly meteorological fields. GlobSnow snow cover fraction, snow water equivalent (SWE), and satellitebased passive microwave snowmeltoff day of year (MoD) data were used to evaluate snow cover fraction, SWE, and snowmelt simulations. Simulated runoff was then fed into a river routing scheme and evaluation was performed at 408 snowdominated catchments using gauge observations. CLM4 and GlobSnow snow cover extent showed a strong agreement, especially during the peak snow cover months. Overall there was a good correlation between simulated and observed SWE (correlation coefficient, R = 0.6). Simulated and observed SWE were similar over areas with relatively flat terrain and moderate forest density. The simulated MoD agreed (MoD differences [CLM4passive microwave] = 7 days) with observations over 39.4% of the study domain. Snowmeltoff occurred earlier in the model compared to the observations over 39.5% of the domain and later over 21.1% of the domain. Large differences of MoD were seen in the areas with complex terrain and dense forest cover. We also found that, although streamflow seasonal phase was accurately modeled (R = 0.9), the peaks controlled by snowmelt were underestimated. Routed CLM4 streamflow tended to occur early (by 10 days on average).

Description: In the early Pleistocene, global temperature cycles predominantly varied with ~41kyr (obliquityscale) periodicity. Atmospheric greenhouse gas concentrations likely played a role in these climate cycles; marine sediments provide an indirect geochemical means to estimate early Pleistocene CO2. Here we present a boron isotopebased record of continuous highresolution surface ocean pH and inferred atmospheric CO2 changes. Our results show that, within a window of time in the early Pleistocene (1.381.54 Ma), pCO2 varied with obliquity, confirming that, analogous to late Pleistocene conditions, the carbon cycle and climate covaried at ~1.5 Ma. Pairing the reconstructed early Pleistocene pCO2 amplitude (92 13 atm) with a comparably smaller global surface temperature glacial/interglacial amplitude (3.0 0.5 K) yields a surface temperature change to CO2 radiative forcing ratio of S[CO2]~0.75 (0.5) C(sup -1)W(sup -1)m(sup -2), as compared to the late Pleistocene S[CO2] value of ~1.75 (0.6) C(sup -1)W(sup -1)m(sup -2). This direct comparison of pCO2 and temperature implicitly incorporates the large ice sheet forcing as an internal feedback and is not directly applicable to future warming. We evaluate this result with a simple climate model and show that the presumably thinner, though extensive, northern hemisphere ice sheets would increase surface temperature sensitivity to radiative forcing. Thus, the mechanism to dampen actual temperature variability in the early Pleistocene more likely lies with Southern Ocean circulation dynamics or antiphase hemispheric forcing. We also compile this new carbon dioxide record with published PlioPleistocene (sup 11)B records using consistent boundary conditions and explore potential reasons for the discrepancy between Pliocene pCO2 based on different planktic foraminifera.

Description: The Clouds and the Earths Radiant Energy System (CERES)partial radiative perturbation [PRP (CERES-PRP)] methodology applies partial-radiative-perturbation-like calculations to observational datasets to directly isolate the individual cloud, atmospheric, and surface property contributions to the variability of the radiation budget. The results of these calculations can further be used to construct radiative kernels. A suite of monthly mean observation-based inputs are used for the radiative transfer, including cloud properties from either the diurnally resolved passive-sensor-based CERES synoptic (SYN) data or the combination of the CloudSat cloud radar and CloudAerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar. The CloudSat/CALIPSO cloud profiles are incorporated via a clustering method that obtains monthly mean cloud properties suitable for accurate radiative transfer calculations. The computed fluxes are validated using the TOA fluxes observed by CERES. Applications of the CERES-PRP methodology are demonstrated by computing the individual contributions to the variability of the radiation budget over multiple years and by deriving water vapor radiative kernels. The calculations for the former are used to show that an approximately linear decomposition of the total flux anomalies is achieved. The observation-based water vapor kernels were used to investigate the accuracy of the GCM-based NCAR CAM3.0 water vapor kernel. Differences between our observation-based kernel and the NCAR one are marginally larger than those inferred by previous comparisons among different GCM kernels.

Description: This study cross-validates the radar reflectivity Z, the rainfall drop size distribution parameter (median volume diameter, D(sub o)) and the rainfall rate R estimated from the Tropical Rainfall Measuring Mission (TRMM) satellite Precipitation Radar (PR), a combined PR and TRMM Microwave Imager (TMI) algorithm (COM) and a C-band dual-polarised ground-radar (GR) for TRMM overpasses during the passage of tropical cyclone (TC) and non-TC events over Darwin, Australia. Two overpass events during the passage of TC Carlos and eleven non-TC overpass events are used in this study and the GR is taken as the reference. It is shown that the correspondence is dependent on the precipitation type whereby events with more (less) stratiform rainfall usually have a positive (negative) bias in the reflectivity and the rainfall rate whereas in the D(sub o) the bias is generally positive but small (large). The COM reflectivity estimates are similar to the PR but it has a smaller bias in the D(sub o) for most of the greater stratiform events. This suggests that combining the TMI with the PR adjusts the D(sub o) towards the "correct" direction if the GR is taken as the reference. Moreover, the association between the TRMM estimates and the GR for the two TC events, which are highly stratiform in nature, is similar to that observed for the highly stratiform non-TC events (there is no significant difference) but it differs largely from that observed for the majority of the highly convective non-TC events.

Description: Recent analyses of global climate models suggest that uncertainty in the coupling between mid-latitude clouds and the atmospheric circulation contributes to uncertainty in climate sensitivity. However, the reasons behind model differences in the cloud-circulation coupling have remained unclear. Here, we use a global climate model in idealized aquaplanet setup to show that the Southern Hemisphere climatological circulation, which in many models is biased equatorward, contributes to the model differences in the cloud-circulation coupling. For the same poleward shift of the Hadley circulation (HC) edge, models with narrower climatological HCs exhibit stronger mid-latitude cloud-induced shortwave warming than models with wider climatological HCs. This cloud-induced radiative warming results predominantly from a subsidence warming that decreases cloud fraction and is stronger for narrower HCs because of a larger meridional gradient in the vertical velocity. A comparison of our aquaplanet results with comprehensive climate models suggests that about half of the model uncertainty in the mid-latitude cloud-circulation coupling stems from this impact of the circulation on the large-scale temperature structure of the atmosphere, and thus could be removed by improving the climatological circulation in models. This illustrates how understanding of large-scale dynamics can help reduce uncertainty in clouds and their response to climate change.

Description: Two NASA microwave radiometers, the satellite-borne GPM (Global Precipitation Measurement) Microwave Imager (GMI) and the aircraft-borne CoSMIR (the Conical Scanning Millimeter-wave Imaging Radiometer), measure vertically- and horizontally-polarized microwaves emitted by cloud particles and the Earth below, providing unique information on ice crystal properties in clouds. Their data reveal that non-spherical ice crystals are common and they fall in a preferred horizontally aligned orientation in convective and optically thick clouds especially near cloud top. A bin (particle-size-resolving) microphysical model with an ice crystal shape representation is developed to simulate the evolution of ice crystal properties (i.e., size, shape and orientation), where the radiation effect on microphysics (REM) is taken into account. Since REM represents the effect of all (e.g., both infrared and solar) radiation on ice crystal temperature, it relies upon the ice crystal proprieties that determine how an ice crystal receives radiation. Definitely, REM is different from the radiative effects that cause sensitivity at the microwave frequencies in the GPM and CoSMIR observations. Model results show that horizontally-oriented ice crystals grow faster than vertically-oriented (or spherical) ones due to REM. When both horizontally- and vertically-oriented ice crystals coexist in an air parcel, the model results show that the former grow by vapor deposition whereas the latter shrink by sublimation and disappear eventually. These modeling results are supported by the GMI data and the CoSMIR observations from MC3E (Midlatitude Continental Convective Clouds Experiment) and OLYMPEX (Olympic Mountains Experiment) on the prevalence of horizontally-oriented ice crystals. Moreover, the REM-induced precipitation explains the CloudSat observations of rare thin clouds in the tropical mid-troposphere as well as the common diamond dust in the high latitudes.

Description: The El Nio Southern Oscillation (ENSO) is a coupled Earth system circulation phenomena that reaches all around the globe. The heat added to the atmosphere by increased precipitation produces circulation changes that have global reach and, over time, warms the entire tropical band, and much of the Earth. Many studies have noted that El Nio causes warm and dry (and sometimes drought) conditions over tropical land masses. We develop a composite analysis of El Nio to identify the predominate features of tropical land response. This analysis shows that the lands lagged response is related to a reduction clouds that leads to increase surface shortwave radiation that increases the surface temperature. The precipitation lag is somewhat longer, and then leads to a reduction in soil water and, in concert with increased SW induced surface warming, leads to increased sensible heating of the atmosphere above. The M2AMIP simulation generally captures these features, but the response is strongest with increased temporal and spatial proximity to the El Nio peak warming. The regionality of these features is also discussed, and it is noted that even the strongest individual El Nio events can vary from this composite mechanistic paradigm.

Description: Water vapour in the atmosphere is the source of a major climate feedback mechanism and potential increases in the availability of water vapour could have important consequences for mean and extreme precipitation. Future precipitation changes further depend on how the hydrological cycle responds to different drivers of climate change, such as greenhouse gases and aerosols. Currently, neither the total anthropogenic influence on the hydrological cycle nor that from individual drivers is constrained sufficiently to make solid projections. We investigate how integrated water vapour (IWV) responds to different drivers of climate change. Results from 11 global climate models have been used, based on simulations where CO2, methane, solar irradiance, black carbon (BC), and sulfate have been perturbed separately. While the global-mean IWV is usually assumed to increase by 7% per kelvin of surface temperature change, we find that the feedback response of IWV differs somewhat between drivers. Fast responses, which include the initial radiative effect and rapid adjustments to an external forcing, amplify these differences. The resulting net changes in IWV range from 6.40.9%K(exp -1) for sulfate to 9.82%K(exp -1) for BC. We further calculate the relationship between global changes in IWV and precipitation, which can be characterized by quantifying changes in atmospheric water vapour lifetime. Global climate models simulate a substantial increase in the lifetime, from 8.20.5 to 9.90.7d between 1986-2005 and 2081-2100 under a high-emission scenario, and we discuss to what extent the water vapour lifetime provides additional information compared to analysis of IWV and precipitation separately. We conclude that water vapour lifetime changes are an important indicator of changes in precipitation patterns and that BC is particularly efficient in prolonging the mean time, and therefore likely the distance, between evaporation and precipitation.

Description: The 2017 Atlantic hurricane season was extremely active with six major hurricanes, the third most on record. The sea-surface temperatures (SSTs) over the eastern Main Development Region (EMDR), where many tropical cyclones (TCs) developed during active months of August/September, were ~0.96 C above the 1901-2017 average (warmest on record): about ~0.42 C from a long-term upward trend and the rest (~80%) attributed to the Atlantic Meridional Mode (AMM). The contribution to the SST from the North Atlantic Oscillation (NAO) over the EMDR was a weak warming, while that from El Nio-Southern Oscillation (ENSO) was negligible. Nevertheless, ENSO, the NAO, and the AMM all contributed to favorable wind shear conditions, while the AMM also produced enhanced atmospheric instability. Compared with the strong hurricane years of 2005/2010, the ocean heat content (OHC) during 2017 was larger across the tropics, with higher SST anomalies over the EMDR and Caribbean Sea. On the other hand, the dynamical/thermodynamical atmospheric conditions, while favorable for enhanced TC activity, were less prominent than in 2005/2010 across the tropics. The results suggest that unusually warm SST in the EMDR together with the long fetch of the resulting storms in the presence of record-breaking OHC may be key factors in driving the strong TC activity in 2017.

Description: The impact of assimilating Global Precipitation Mission (GPM) Microwave Imager (GMI) clear-sky radiance on the track and intensity forecasts of two Atlantic hurricanes during the 2015 and 2016 hurricane seasons is assessed using the NOAA operational Hurricane Weather Research and Forecasting (HWRF) model. The GMI cloud-cleared brightness temperature is assimilated using a Gridpoint Statistical Interpolation (GSI)-based hybrid ensemble-variational data assimilation system, which utilizes the Community Radiative Transfer Model (CRTM) as a forward operator for satellite sensors. A two-step bias correction approach, which combines a linear regression procedure and variational bias correction, is used to remove most of the systematic biases prior to data assimilation. Forecast results show that assimilating GMI clear-sky radiance has positive impacts on both track and intensity forecasts, with the extent depending on the phase of hurricane evolution. Forecast verifications against dropsondings and reanalysis data show that assimilating GMI clear-sky radiance, when it does not overlap with overpasses of other microwave imagers, can lead to improved forecasts of both thermodynamic (e.g., temperature and specific humidity) and dynamic variables (geopotential height and wind field), which in turn lead to better track forecasts and a more realistic hurricane inner-core structure. Even when other microwave imagers are present (e.g., AMSU-A, ATMS, MHS, etc.), the assimilation of GMI still reduces temperature forecast errors in the near-hurricane environment, which has a significant impact on the intensity forecast.

Description: In a series of 10-day campaigns in Ontario and Quebec, Canada, between 2005 and 2007, ozonesondes were launched twice daily in conjunction with continuous high-resolution wind-profiling radar measurements. Windprofilers can measure rapid changes in the height of the tropopause, and in some cases follow stratospheric intrusions. Observed stratospheric intrusions were studied with the aid of a Lagrangian particle dispersion model and the Canadian operational weather forecast system. Definite stratosphere-troposphere transport (STT) events occurred approximately every 23 days during the spring and summer campaigns, whereas during autumn and winter, the frequency was reduced to every 45 days. Although most events reached the lower troposphere, only three events appear to have significantly contributed to ozone amounts in the surface boundary layer. Detailed calculations find that STT, while highly variable, is responsible for an average, over the seven campaigns, of 3.1% of boundary layer ozone (1.2 ppb), but 13% (5.4 ppb) in the lower troposphere and 34% (22 ppb) in the middle and upper troposphere, where these layers are defined as 0-1 km, 1-3 km, and 3-8 km respectively. Estimates based on counting laminae in ozonesonde profiles, with judicious choices of ozone and relative humidity thresholds, compare moderately well, on average, with these values. The lamina detection algorithm is then applied to a large dataset from four summer ozonesonde campaigns at 18 North American sites between 2006 and 2011. The results show some site-to-site and year-to-year variability, but stratospheric ozone contributions average 4.6% (boundary layer), 15% (lower troposphere) and 26% (middle/upper troposphere). Calculations were also performed based on the TOST global 3D trajectory-mapped ozone data product. Maps of STT in the same three layers of the troposphere suggest that the STT ozone flux is greater over the North American continent than Europe, and much greater in winter and spring than in summer or fall. When averaged over all seasons, magnitudes over North America show similar ratios between levels to the previous calculations, but are overall 3-4 times smaller. This may be because of limitations (trajectory length and vertical resolution) to the current TOST-based calculation.

Description: The evolution of a flash drought event, characterized by a period of rapid drought intensification, is assessed using standard drought monitoring datasets and on-the-ground reports obtained via a written survey of agricultural stakeholders after the flash drought occurred. The flash drought impacted agricultural production across a five-state region centered on the Black Hills of South Dakota during the summer of 2016. The survey asked producers to estimate when certain drought impacts, ranging from decreased soil moisture to plant stress and diminished water resources, first occurred on their land. The geographic distribution and timing of the survey responses were compared to the U.S. Drought Monitor and to datasets depicting anomalies in evapotranspiration, precipitation, and soil moisture. Overall, the survey responses showed that this event was a multifaceted drought that caused a variety of impacts across the region. Comparisons of the survey reports to the drought monitoring datasets revealed that the topsoil moisture dataset provided the earliest warning of drought development, but at the expense of a high false alarm rate. Anomalies in evapotranspiration were closely aligned to the survey reports of plant stress and also provided a more focused depiction of where the worst drought conditions were located. This study provides evidence that qualitative reports of drought impacts obtained via written surveys provide valuable information that can be used to assess the accuracy of high-resolution drought monitoring datasets.

Description: Aerosol-cloud interaction continues to be one of the leading uncertain components of the climate models, primarily due to the lack of adequate knowledge of the complex microphysical and radiative processes of the aerosol-cloud system. Situations when the light-absorbing aerosols such as carbonaceous particles and windblown dust overlay low-level cloud decks are commonly found in several regions of the world. Contrary to the known cooling effects of these aerosols in cloud-free scenario over darker surfaces, an overlapping situation of the absorbing aerosols over the cloud can lead to a significant level of atmospheric absorption exerting a positive radiative forcing (warming) at the top-of-atmosphere. We contribute to this topic by introducing a new global product of the above-cloud aerosol optical depth (ACAOD) of absorbing aerosols retrieved from the near-UV observations made by the Ozone Monitoring Instrument (OMI) onboard NASAs Aura platform. Physically based on an unambiguous color ratio effect in the near-UV caused by the aerosol absorption above the cloud, the OMACA (OMI Above-Cloud Aerosols) algorithm simultaneously retrieves the optical depths of aerosols and clouds under a prescribed state of the atmosphere. The OMACA algorithm shares many similarities with the two-channel cloud-free OMAERUV algorithm, including the use of AIRS carbon monoxide for the aerosol type identification, CALIOP-based aerosol layer height dataset, and OMI-based surface albedo database. We present the algorithm architecture, inversion procedure, retrieval quality flags, initial validation results, and results from a 12-year long OMI record (2005-2016) including global climatology of the frequency of occurrence, ACAOD, and aerosol-corrected cloud optical depth. A comparative analysis of the OMACA-retrieved ACAOD collocated with equivalent accurate measurements from the HSRL-2 lidar for the ORACLES phase I operation (August-September 2016) revealed a good agreement (R=0.77, RMSE=0.10). The long-term OMACA record reveals several important regions of the world, including Southeastern Atlantic Ocean, southern Indian Ocean, South-East Asia, tropical Atlantic Ocean off the coast of western Africa, and northern Arabian sea where the carbonaceous aerosols from the seasonal biomass burning and mineral dust originated over the continents are found to overlie low-level cloud decks with moderate (0.3〈ACAOD〈0.5, away from the sources) to higher levels of ACAOD (〉0.8 in the proximity to the sources). No significant long-term trend in the frequency of occurrence of aerosols above the clouds and ACAOD is noticed when OMI observations that are free from the row anomaly throughout the operation are considered. If not accounted, the effects of aerosol absorption above the clouds introduce low bias in the retrieval of cloud optical depth with a profound impact at increasing ACAOD and cloud brightness. The OMACA aerosol product from OMI presented in this paper offers a crucial missing piece of information of the aerosol loading above cloud that will help us to quantify the radiative effects of clouds when overlaid with aerosols and its resultant impact on cloud properties and climate.

Description: In this presentation we provided an overview of current GPM applications activities, highlighting multiple case studies that describe how GPM satellite data and products have been used to support decision- and policy-making. Understanding how and why stakeholders are using GPM data and products as well as the current challenges, barriers and opportunities for using GPM products within their applications enables us to learn and address the needs of end users as well as improve data usability.

Description: Current scattering look-up tables for snow assume a constant mass density along with a Gamma particle size distribution (PSD). The first assumption is tested against scattering parameters from simulated particle models generated by Dr. Kwo-Sen Kuo at GSFC and Dr. Guosheng Liu at FSU. Good agreement of the scattering parameters is found with the FSU results if the mass is taken to be the same as the mass of the simulated particle and the mass density is taken to be 0.2 g/cm cu. For the GSFC data base, good agreement is found if the mass density is taken to be between 0.1 and 0.2 g/cm cu. The second assumption of a Gamma PSD is tested against measured PSD's along with a m-d (mass-dimension) relationship. The degree of agreement depends on the value of, the 'shape' parameter in the Gamma distribution but to a lesser degree on the m-d relationship (of the three that were examined). A shortcoming of the simulated snow particle data bases is the lack of large particles. As a consequence, larger values of DFR (dual-frequency ratio) that are commonly seen in airborne and spaceborne measurements cannot be reproduced from the tables. This situation is expected to improve as scattering parameters from larger particles are included in the databases.

Description: The algorithm for the Surface Reference Technique (SRT) has been updated from version V6A to version V6X. The modified algorithm is designed to process dual-frequency radar data which are now available over the full swath. Comparisons between V6A and V6X show that the dual-wavelength version of the SRT (DSRT) eliminates some of the overestimates of path attenuation in the outer swath that occurred in the earlier version of the algorithm when dual-frequency data was unavailable in the outer swath. However, the DSRT is not reliable in cases of light rain rates where only the Ku-band channel detects rain, nor is it reliable in high rain rate cases where the Ka-band surface signal is lost through attenuation. A modified hybrid algorithm is planned for version 7 that can combine the best features of single- and dual-frequency path attenuation methods.

Description: The stratospheric age of air (AoA) is a useful measure of the overall capabilities of a general circulation model (GCM) to simulate stratospheric transport. Previous studies have reported a large spread in the simulation of AoA by GCMs and coupled chemistry-climate models (CCMs). Compared to observational estimates, simulated AoA is mostly too low. Here we attempt to untangle the processes that lead to the AoA differences between the models and between models and observations. AoA is influenced by both mean transport by the residual circulation and two-way mixing; we quantify the effects of these processes using data from the CCM inter-comparison projects CCMVal-2 (Chemistry-Climate Model Validation Activity 2) and CCMI-1 (Chemistry-Climate Model Initiative, phase 1). Transport along the residual circulation is measured by the residual circulation transit time (RCTT). We interpret the difference between AoA and RCTT as additional aging by mixing. Aging by mixing thus includes mixing on both the resolved and subgrid scale. We find that the spread in AoA between the models is primarily caused by differences in the effects of mixing and only to some extent by differences in residual circulation strength. These effects are quantified by the mixing efficiency, a measure of the relative increase in AoA by mixing. The mixing efficiency varies strongly between the models from 0.24 to 1.02. We show that the mixing efficiency is not only controlled by horizontal mixing, but by vertical mixing and vertical diffusion as well. Possible causes for the differences in the models' mixing efficiencies are discussed. Differences in subgrid-scale mixing (including differences in advection schemes and model resolutions) likely contribute to the differences in mixing efficiency. However, differences in the relative contribution of resolved versus parameterized wave forcing do not appear to be related to differences in mixing efficiency or AoA.

Description: Understanding the connection between microphysical properties of falling snow and remote sensing observations requires detailed models of snow particles and the related electromagnetic scattering properties. To this end, we have created a database of synthetically-grown snow particles along with electromagnetic scattering properties calculated using advanced computational methods. We showcase the breadth of the catalog, current work, applications of the catalog, and future plans.

Description: The new V06 IMERG is briefly reviewed, then key data visualizations are shown, including the zonal profile of calibration by GPCP, the long-term time series of ocean estimates for the Final Run (with comparison to TMPA and GPCP SG), the time series of tropical ocean rainrate histogram, diurnal cycle, and atoll validation at the monthly time scale.

Description: In 1999, the first sprites were observed above European thunderstorms using sensitive cameras. Since then, Eurosprite campaigns have been conducted to observe sprites and other transient luminous events (TLEs), expanding into a network covering large parts of Europe and coastal areas. In 2009 through 2013, the number of optical observations of TLEs reached a peak of 2000 per year. Because of this unprecedented number of European observations, it was possible to construct a climatology of 8394 TLEs observed above 1018 thunderstorm systems and study for the first time their distribution and seasonal cycle above Europe and parts of the Mediterranean Sea. The number of TLEs per thunderstorm was found to follow a power law, with less than 10 TLEs for 801 thunderstorms and up to 195 TLEs above the most prolific one. The majority of TLEs were classified as sprites, 641 elves, 280 halos, 70 upward lightning, 2 blue jets and 1 gigantic jet. The climatology shows intense TLE activity during summer over continental areas and in late autumn over coastal areas and sea. The two seasons peak, respectively, in August and November, separated by March and April with almost no TLEs, and a relative minimum around September. The observed TLE activity, i.e. mostly sprites, is shown to be largely consistent with lightning activity, with a 1/1000 of observed TLE-to-lightning ratio in regions with most observations. The overall behaviour is consistent among individual years, making the observed seasonal cycle a robust general feature of TLE activity above Europe.

Description: Plants are expected to generate more global-scale runoff under increasing atmospheric carbon dioxide concentrations through their influence on surface resistance to evapotranspiration. Recent studies using Earth System Models from phase 5 of the Coupled Model Intercomparison Project ostensibly reaffirm this result, further suggesting that plants will ameliorate the dire reductions in water availability projected by other studies that use aridity metrics. Here we complicate this narrative by analysing the change in precipitation partitioning to plants, runoff and storage in multiple Earth system models under both high carbon dioxide concentrations and warming. We show that projected plant responses directly reduce future runoff across vast swaths of North America, Europe and Asia because bulk canopy water demands increase with additional vegetation growth and longer and warmer growing seasons. These runoff declines occur despite increased surface resistance to evapotranspiration and vegetation total water use efficiency, even in regions with increasing or unchanging precipitation. We demonstrate that constraining the large uncertainty in the multimodel ensemble with regional-scale observations of evapotranspiration partitioning strengthens these results. We conclude that terrestrial vegetation plays a large and unresolved role in shaping future regional freshwater availability, one that will not ubiquitously ameliorate future warming-driven surface drying.

Description: An accurate estimate of global hydroxyl radical (OH) abundance is important for projections of air quality, climate, and stratospheric ozone recovery. As the atmospheric mixing ratios of methyl chloroform (CH3CCl3) (MCF), the commonly used OH reference gas, approaches zero, it is important to find alternative approaches to infer atmospheric OH abundance and variability. The lack of global bottom-up emission inventories is the primary obstacle in choosing a MCF alternative. We illustrate that global emissions of long-lived trace gases can be inferred from their observed mixing ratio differences between the Northern Hemisphere (NH) and Southern Hemisphere (SH), given realistic estimates of their NH-SH exchange time, the emission partitioning between the two hemispheres, and the NH versus SH OH abundance ratio. Using the observed long-term trend and emissions derived from the measured hemispheric gradient, the combination of HFC-32 (CH2F2), HFC-134a (CH2FCF3, HFC-152a (CH3CHF2), and HCFC-22 (CHClF2), instead of a single gas, will be useful as a MCF alternative to infer global and hemispheric OH abundance and trace gas lifetimes. The primary assumption on which this multispecies approach relies is that the OH lifetimes can be estimated by scaling the thermal reaction rates of a reference gas at 272 K on global and hemispheric scales. Thus, the derived hemispheric and global OH estimates are forced to reconcile the observed trends and gradient for all four compounds simultaneously. However, currently, observations of these gases from the surface networks do not provide more accurate OH abundance estimate than that from MCF.

Description: Rainfall production is a fundamental process within the Earth's hydrological cycle because it represents both a principal forcing term in surface water budgets, and its energetics corollary, latent heating, is the principal source of atmospheric diabatic heating. Latent heat release itself is a consequence of phase changes between the vapor, liquid, and frozen states of water. The properties of the vertical distribution of latent heat release modulate large-scale meridional and zonal circulations within the Tropics - as well as modify the energetic efficiencies of mid-latitude weather systems. This paper highlights the retrieval of latent heat release from satellite measurements generated by the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM) satellite observatory, which were launched in November 1997 and February 2014, respectively. Both TRMM and GPM measurements have been providing an accurate four-dimensional account of rainfall over the global Tropics and mid-latitudes: information that can be used to estimate the space-time structure of latent heating. Two sets of latent heating retrieval algorithm methodologies (Goddard Convective-Stratiform or CSH, and Japan Spectral Latent Heating or SLH) have been developed to estimate latent heating based on rain rate profile retrievals obtained from TRMM and GPM measurements. The CSH algorithm will be described followed by a discussion its improvements and performance against the combined derived surface ran rates. We will also present the CSH retrieved LH for TRMM and GPM.

Description: Wheat grain protein concentration is an important determinant of wheat quality for human nutrition that is often overlooked in efforts to improve crop production. We tested and applied a 32multimodel ensemble to simulate global wheat yield and quality in a changing climate. Potential benefits of elevated atmospheric CO2 concentration by 2050 on global wheat grain and protein yield are likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions. Grain and protein yields are expected to be lower and more variable in most lowrainfall regions, with nitrogen availability limiting growth stimulus from elevated CO2. Introducing genotypes adapted to warmer temperatures (and also considering changes in CO2 and rainfall) could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by 1.1 percentage points, representing a relative change of 8.6%. Climate change adaptations that benefit grain yield are not always positive for grain quality, putting additional pressure on global wheat production.

Description: Clouds play a key role in radiation and hence O3 photochemistry by modulating photolysis rates and light-dependent emissions of biogenic volatile organic compounds (BVOCs). It is not well known, however, how much error in O3 predictions can be directly attributed to error in cloud predictions. This study applies the Weather Research and Forecasting with Chemistry (WRF-Chem) model at 12 km horizontal resolution with the Morrison microphysics and Grell 3-D cumulus parameterization to quantify uncertainties in summertime surface O3 predictions associated with cloudiness over the contiguous United States (CONUS). All model simulations are driven by reanalysis of atmospheric data and reinitialized every 2 days. In sensitivity simulations, cloud fields used for photochemistry are corrected based on satellite cloud retrievals. The results show that WRF-Chem predicts about 55 % of clouds in the right locations and generally underpredicts cloud optical depths. These errors in cloud predictions can lead to up to 60 ppb of overestimation in hourly surface O3 concentrations on some days. The average difference in summertime surface O3 concentrations derived from the modeled clouds and satellite clouds ranges from 1 to 5 ppb for maximum daily 8 h average O3 (MDA8 O3) over the CONUS. This represents up to 40 % of the total MDA8 O3 bias under cloudy conditions in the tested model version. Surface O3 concentrations are sensitive to cloud errors mainly through the calculation of photolysis rates (for 80 %), and to a lesser extent to light-dependent BVOC emissions. The sensitivity of surface O3 concentrations to satellite-based cloud corrections is about 2 times larger in VOC-limited than NOx-limited regimes. Our results suggest that the benefits of accurate predictions of cloudiness would be significant in VOC-limited regions, which are typical of urban areas.

Description: Current conventional global climate models (GCMs) produce a weak increase in globalmean precipitation with anthropogenic warming in comparison with the lower tropospheric moisture increases. The motive of this study is to understand the differences in the hydrological sensitivity between two multiscale modeling frameworks (MMFs) that arise from the different treatments of turbulence and low clouds in order to aid to the understanding of the model spread among conventional GCMs. We compare the hydrological sensitivity and its energetic constraint from MMFs with (SPCAMIPHOC) or without (SPCAM) an advanced higherorder turbulence closure. SPCAMIPHOC simulates higher global hydrological sensitivity for the slow response but lower sensitivity for the fast response than SPCAM. Their differences are comparable to the spreads of conventional GCMs. The higher sensitivity in SPCAMIPHOC is associated with the higher ratio of the changes in latent heating to those in net atmospheric radiative cooling, which is further related to a stronger decrease in the Bowen ratio with warming than in SPCAM. The higher sensitivity of cloud radiative cooling resulting from the lack of low clouds in SPCAM is another major factor in contributing to the lower precipitation sensitivity. The two MMFs differ greatly in the hydrological sensitivity over the tropical lands, where the simulated sensitivity of surface sensible heat fluxes to surface warming and CO2 increase in SPCAMIPHOC is weaker than in SPCAM. The difference in divergences of dry static energy flux simulated by the two MMFs also contributes to the difference in land precipitation sensitivity between the two models.

Description: Precipitation is a key source of freshwater; therefore, observing global patterns of precipitation and its intensity is important for science, society, and understanding our planet in a changing climate. In 2014, the National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA) launched the Global Precipitation Measurement (GPM) Core Observatory (CO) spacecraft. The GPM CO carries the most advanced precipitation sensors currently in space including a dual-frequency precipitation radar provided by JAXA for measuring the three-dimensional structures of precipitation and a well-calibrated, multifrequency passive microwave radiometer that provides wide-swath precipitation data. The GPM CO was designed to measure rain rates from 0.2 to 110.0 mm h1 and to detect moderate to intense snow events. The GPM CO serves as a reference for unifying the data from a constellation of partner satellites to provide next-generation, merged precipitation estimates globally and with high spatial and temporal resolutions. Through improved measurements of rain and snow, precipitation data from GPM provides new information such as details on precipitation structure and intensity; observations of hurricanes and typhoons as they transition from the tropics to the midlatitudes; data to advance near-real-time hazard assessment for floods, landslides, and droughts; inputs to improve weather and climate models; and insights into agricultural productivity, famine, and public health. Since launch, GPM teams have calibrated satellite instruments, refined precipitation retrieval algorithms, expanded science investigations, and processed and disseminated precipitation data for a range of applications. The current status of GPM, its ongoing science, and its future plans are presented.

Description: We implemented and began to evaluate an alternative convection parameterization for the NASA Goddard Earth Observing System (GEOS) general circulation model (GCM). The proposed parameterization follows the mass flux approach with several closures, for equilibrium and nonequilibrium convection, and includes scale and aerosol aware functionalities. Recently, we extended the scheme to a trimodal spectral size distribution of allowed convective plumes to simulate the transition among shallow, congestus, and deep convection regimes. In addition, the inclusion of a new closure for nonequilibrium convection resulted in a substantial gain of realism in the model representation of the diurnal cycle of convection over the land. We demonstrated the scaledependence functionality with a cascade of globalscale simulations from a nominal horizontal resolution of 50 km down to 6 km. The ability to realistically simulate the diurnal cycle of precipitation over various regions of the earth was verified against several remote sensingderived intradiurnal precipitation estimates. We extended the model performance evaluation for weatherscale applications by bringing together some available operational shortrange weather forecast models and global atmospheric reanalyses. Our results demonstrate that the GEOS GCM with the alternative convective parameterization has good properties and competitive skill in comparison with stateoftheart observations and numerical simulations.

Description: Recent studies have shown the unique value of satellite-observed land surface thermal infrared (TIR) information (e.g., skin temperature) and the feasibility of assimilating land surface temperature (LST) into land surface models (LSMs) to improve the simulation of land-atmosphere water and energy exchanges. In this study, two different types of LST assimilation techniques are implemented and the benefits from the techniques are compared. One of the techniques is to directly assimilate LST using ensemble Kalman filter (EnKF) data assimilation (DA) utilities. The other is to use the Atmosphere-Land Exchange Inversion model (ALEXI) as an "observation operator" that converts LST retrievals into the soil moisture (SM) proxy based on the ratio of actual to potential evapotranspiration (fPET), which is then assimilated into an LSM. While most current studies have shown some success in both directly the assimilating LST and assimilating ALEXI SM proxy into offline LSMs, the potential impact of the assimilation of TIR information through coupled numerical weather prediction (NWP) models is unclear. In this study, a semi-coupled Land Information System (LIS) and Weather Research and Forecast (WRF) system is employed to assess the impact of the two different techniques for assimilating the TIR observations from NOAA GOES satellites on WRF model forecasts. The NASA LIS, equipped with a variety of LSMs and advanced data assimilation tools (e.g., the ensemble Kalman Filter (EnKF)), takes atmospheric forcing data from the WRF model run, generates updated initial land surface conditions with the assimilation of either LST- or TIR-based SM and returns them to WRF for initializing the forecasts. The WRF forecasts using the daily updated initializations with the TIR data assimilation are evaluated against ground weather observations and re-analysis products. It is found that WRF forecasts with the LST-based SM assimilation have better agreement with the ground weather observations than those with the direct LST assimilation or without the land TIR data assimilation.

Description: Modeling studies have shown that cloud feedbacks are sensitive to the spatial pattern of sea surface temperature (SST) anomalies, while cloud feedbacks themselves strongly influence the magnitude of SST anomalies. Observational counterparts to such patterned interactions are still needed. Here we show that distinct large-scale patterns of SST and low-cloud cover (LCC) emerge naturally from objective analyses of observations and demonstrate their close coupling in a positive local SST-LCC feedback loop that may be important for both internal variability and climate change. The two patterns that explain the maximum amount of covariance between SST and LCC correspond to the Interdecadal Pacific Oscillation (IPO) and the Atlantic Multidecadal Oscillation (AMO), leading modes of multidecadal internal variability. Spatial patterns and time series of SST and LCC anomalies associated with both modes point to a strong positive local SST-LCC feedback. In many current climate models, our analyses suggest that SST-LCC feedback strength is too weak compared to observations. Modeled local SST-LCC feedback strength affects simulated internal variability so that stronger feedback produces more intense and more realistic patterns of internal variability. To the extent that the physics of the local positive SST-LCC feedback inferred from observed climate variability applies to future greenhouse warming, we anticipate significant amount of delayed warming because of SST-LCC feedback when anthropogenic SST warming eventually overwhelm the effects of internal variability that may mute anthropogenic warming over parts of the ocean. We postulate that many climate models may be underestimating both future warming and the magnitude of modeled internal variability because of their weak SST-LCC feedback.

Description: This study presents results of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Global and Regional Assessments (CGRA) of +1.5 and +2.0 C global warming above pre-industrial conditions. This first CGRA application provides multi-discipline, multi-scale, and multi-model perspectives to elucidate major challenges for the agricultural sector caused by direct biophysical impacts of climate changes as well as ramifications of associated mitigation strategies. Agriculture in both target climate stabilizations is characterized by differential impacts across regions and farming systems, with tropical maize (Zea mays) experiencing the largest losses while soy (Glycine max) mostly benefits. The result is upward pressure on prices and area expansion for maize and wheat (Triticum), while soy prices and area decline (results for rice, Oryza sativa, are mixed). An example global mitigation strategy encouraging bioenergy expansion is more disruptive to land use and crop prices than the climate change impacts alone, even in the +2.0 C World which has a larger climate signal and lower mitigation requirement than the +1.5 C World. Coordinated assessments reveal that direct biophysical and economic impacts can be substantially larger for regional farming systems than global production changes. Regional farmers can buffer negative effects or take advantage of new opportunities via mitigation incentives and farm management technologies. Primary uncertainties in the CGRA framework include the extent of CO2 benefits for diverse agricultural systems in crop models, as simulations without CO2 benefits show widespread production losses that raise prices and expand agricultural area

Description: Precipitation represents a life-critical energy and hydrologic exchange between the Earths atmosphere and its surface. As such, knowledge of where, when, and how much rain and snow falls is essential for scientific research and societal applications. Building on the 17-year success of the Tropical Rainfall Measurement Mission (TRMM), the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO) is the first U.S. National Aeronautical and Space Administration (NASA) satellite mission specifically designed with sensors to observe the structure and intensities of both rain and falling snow. The GPM-CO has proved to be a worthy successor to TRMM, extending and improving high-quality active and passive microwave observations across all times of day. The GPM-CO launched in early 2014, is a joint mission between NASA and the Japanese Aerospace Exploration Agency (JAXA), with sensors that include the NASA-provided GPM Microwave Imager and the JAXA-provided Dual-frequency Precipitation Radar. These sensors were devised with high accuracy standards enabling them to be used as a reference for inter-calibrating a constellation of partner satellite data. These intercalibrated partner satellite retrievals are used with infrared data to produce merged precipitation estimates at temporal scales of 30 minutes and spatial scales of 0.1 x 0.1. Precipitation estimates from the GPM-CO and partner constellation satellites, provided in near real time and later reprocessed with all ancillary data, are an indispensable source of precipitation data for operational and scientific users. Advances have been made using GPM data, primarily in improving sensor calibration, retrieval algorithms, and ground validation measurements, and used to further our understanding of the characteristics of liquid and frozen precipitation and the science of water and hydrological cycles for climate/weather forecasting. These advances have extended to societal benefits related to water resources, operational numerical weather prediction, hurricane monitoring, prediction, and disaster response, extremes, and disease.

Description: Drought is one of the most serious climatic and natural disasters inflicting serious impacts on the socio-economy of Morocco, which is characterized both by low-average annual rainfall and high irregularity in the spatial distribution and timing of precipitation across the country. This work aims to develop a comprehensive and integrated method for drought monitoring based on remote sensing techniques. The main input parameters are derived monthly from satellite data at the national scale and are then combined to generate a composite drought index presenting different severity classes of drought. The input parameters are: Standardized Precipitation Index calculated from satellite-based precipitation data since 1981 (CHIRPS), anomalies in the day-night difference of Land Surface Temperature as a proxy for soil moisture, Normalized Difference Vegetation Index anomalies from Moderate Resolution Imaging Spectroradiometer (MODIS) data and Evapotranspiration anomalies from surface energy balance modeling. All of these satellite-based indices are being used to monitor vegetation condition, rainfall and land surface temperature. The weighted combination of these input parameters into one composite indicator takes into account the importance of the rainfall-based parameter (SPI). The composite drought index maps were generated during the growing seasons going back to 2003. These maps have been compared to both the historical, in situ precipitation data across Morocco and with the historical yield data across different provinces with information being available since 2000. The maps are disseminated monthly to several main stakeholders' groups including the Ministry of Agriculture and Department of Water in Morocco.

Description: No abstract available

Description: 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.

Description: Coefficients are derived for computing the polarization-corrected temperature (PCT) for 10-, 19-, 37- and 89-GHz (and similar) frequencies, with applicability to satellites in the Global Precipitation Measurement mission constellation and their predecessors. PCTs for 10- and 19-GHz frequencies have been nonexistent or seldom used in the past; developing those is the main goal of this study. For 37 and 89 GHz, other formulations of PCT have already become well established. We consider those frequencies here in order to test whether the large sample sizes that are readily available now would point to different formulations of PCT. The purpose of the PCT is to reduce the effects of surface emissivity differences in a scene and draw attention to ice scattering signals related to precipitation. In particular, our intention is to develop a PCT formula that minimizes the differences between land and water surfaces, so that signatures resulting from deep convection are not easily confused with water surfaces. The new formulations of PCT for 10- and 19-GHz measurements hold promise for identifying and investigating intense convection. Four examples are shown from relevant cases. The PCT for each frequency is effective at drawing attention to the most intense convection, and removing ambiguous signals that are related to underlying land or water surfaces. For 37 and 89 GHz, the older formulations of PCT from the literature yield generally similar values as ours, with the differences mainly being a few kelvins over oceans. An optimal formulation of PCT can depend on location and season; results are presented here separated by latitude and month.

Description: We have collected year-round nanoclimate data for the cryptoendolithic microbial habitat in sandstones of the Ross desert, Antarctica, obtained with an Argos satellite data system. Data for two sites in the McMurdo Dry Valleys are available: Linnaeus Terrace, January 1985 to June 1988, and Battleship Promontory, 1986-1987. The focus of this research is ecological, and hence year-round environmental data have been obtained for the ambient environment as well as for conditions within the rock. Using data from the summer, we compare the conditions inside the rock to the outside weather. This demonstrates how the rock provides a shelter for the endolithic microbial community. The most important property of the rock is that it absorbs the summer sunlight, thereby warming up to temperatures above freezing. This warming allows snowmelt to seep into the rock, and the moisture level in the rocks can remain high for weeks against loss to the dry environment.

Description: Land carbon fluxes, e.g., gross primary production (GPP) and net biome production (NBP), are controlled in part by the responses of terrestrial ecosystems to atmospheric conditions near the Earth's surface. The Coupled Model Intercomparison Project Phase 6 (CMIP6) has recently proposed increased spatial and temporal resolutions for the surface CO2 concentrations used to calculate GPP, and yet a comprehensive evaluation of the consequences of this increased resolution for carbon cycle dynamics is missing. Here, using global offline simulations with a terrestrial biosphere model, the sensitivity of terrestrial carbon cycle fluxes to multiple facets of the spatiotemporal variability in atmospheric CO2 is quantified. Globally, the spatial variability in CO2 is found to increase the mean global GPP by a maximum of 0.05Pg C year(sup 1), as more vegetated land areas benefit from higher CO2 concentrations induced by the inter-hemispheric gradient. The temporal variability in CO2, however, compensates for this increase, acting to reduce overall global GPP; in particular, consideration of the diurnal variability in atmospheric CO2 reduces multi-year mean global annual GPP by 0.5Pg C year (sup 1) and net land carbon uptake by 0.1Pg C year (sup 1). The relative contributions of the different facets of CO2 variability to GPP are found to vary regionally and seasonally, with the seasonal variation in atmospheric CO2, for example, having a notable impact on GPP in boreal regions during fall. Overall, in terms of estimating global GPP, the magnitudes of the sensitivities found here are minor, indicating that the common practice of applying spatially uniform and annually increasing CO2 (without higher-frequency temporal variability) in offline studies is a reasonable approach the small errors induced by ignoring CO2 variability are undoubtedly swamped by other uncertainties in the offline calculations. Still, for certain regional- and seasonal-scale GPP estimations, the proper treatment of spatiotemporal CO2 variability appears important.

Description: A recent attempt to downscale the 50 km MERRA-2 analyses to 7 km revealed an instability associated with the Incremental Analysis Update (IAU) procedure that has thus far gone unnoticed. A theoretical study based on a simple damped harmonic oscillator with complex frequency provides the framework to diagnose the problem and suggests a means to avoid it. Three possible approaches to avoid the instability are to: (i) choose an ``ideal'' ratio of the lengths of the Predictor and Corrector steps of IAU based on a theoretical stability diagram; (ii) time average the background fields used to construct the IAU tendencies with given frequency; or (iii) apply a digital filter modulation to the IAU tendencies. All these are shown to control the instability for a wide range of resolutions when doing up- or down-scaling, experiments with the NASA/GMAO atmospheric general circulation model. Furthermore, it is found that combining IAU with the ensemble re-centering step typical of hybrid ensemble-variational approaches, also results in an instability based on the same mechanisms in the members of the ensemble. An example of such occurrence arises in an experiment performed with the GMAO 12.8 km hybrid 4D-EnVar system. Modulation of the ensemble IAU tendencies with a digital filter is shown to avoid the instability. In addition, the stability of the central member of certain 4DIAU implementations is analyzed and a suggestion is made to improve its results, though a complete study of this subject is postponed to a follow up work.

Description: Ten years of terrestrial water storage anomalies from the Gravity Recovery and Climate Experiment (GRACE) were used to estimate high latitude snowfall accumulation using a mass balance approach. The estimates were used to assess two common gauge-undercatch correction factors (CFs): Legates climatology (CF-L) utilized in the Global Precipitation Climatology Project (GPCP), and Fuchs dynamic correction model (CF-F) used in the Global Precipitation Climatology Centre (GPCC) Monitoring product. The two CFs can be different by more than 50%. CF-L tended to exceed CF-F over northern Asia and Eurasia, while the opposite was observed over North America. Estimates of snowfall from GPCP, GPCC-L (GPCC corrected by CF-L), and GPCC-F (GPCC corrected by CF-F) were 62%, 64%, and 46% more than GPCC over northern Asia and Eurasia. GRACE-based estimate (49% more than GPCC) was the closest to GPCC-F. We found that as near surface air temperature decreases, the products increasingly underestimated the GRACE-based snowfall accumulation. Overall, GRACE showed that CFs are effective in improving GPCC estimates. Furthermore, our case studies and overall statistics suggest that CF-F is likely more effective than CF-L in most of the high latitude regions studied here. GPCP showed generally better skill than GPCC-L, which might be related to the use of satellite data or additional quality controls on gauge inputs to GPCP. This study suggests that GPCP can be improved if it employs CF-L instead of CF-F to correct for gauge undercatch. However, this implementation requires further studies, region-specific analysis, and operational considerations.

Description: This Proceedings contains a collection of the papers which were presented at the Symposium and Workshop on Global Wind Measurements. The objectives and agenda for the Symposium and Workshop were decided during a planning meeting held in Washington, DC, on 5 February 1985. Invited papers were presented at the Symposium by meteorologists and leading experts in wind sensing technology from the United States and Europe on: (1) the meteorological uses and requirements for wind measurements; (2) the latest developments in wind sensing technology; and (3) the status of our understanding of the atmospheric aerosol distribution. A special session was also held on the latest development in wind sensing technology by the United States Air Force.

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Description: We consider the formation of a potential drop over the Earth's polar cap duringgeomagnetically quiet daytime. The observed potential drop is primarily defined by the hydrogen,photoelectron, and polar rain fluxes ratios and depends strongly on the energy distribution of thephotoelectron flux. Polar rain is an essential component of the model required for plasma quasineutrality.The potential distribution along the magnetic field line has two regions, with a small, gradual, potentialdrop of 34 V and a potential jump. The value of the potential jump depends on the hydrogen ion tophotoelectron flux ratio and is also controlled by polar rain electrons. With quasineutrality required at itsupper boundary, the jump only occurs in the presence of polar rain and its location depends on the polarrain flux. Model predictions compare well with FAST observations presented by Kitamura et al.(2012, https://doi.org/10.1029/2011JA017459).

Description: Climate change is estimated to exacerbate existing challenges faced by smallholder farmers in Sub-Sahara Africa. However, limited studies quantify the extent of variation in climate change impact under these systems at the local scale. The Decision Support System for Agro-technological Transfer (DSSAT) was used to quantify variation in climate change impacts on maize yield under current agricultural practices in semi-arid regions of Senegal (Nioro du Rip) and Ghana (Navrongo and Tamale). Multi-benchmark climate models (Mid-Century, 20402069 for two Representative Concentration Pathways, RCP4.5 and RCP8.5), and multiple soil and management information from agronomic surveys were used as input for DSSAT. The average impact of climate scenarios on grain yield among farms ranged between 9% and 39% across sites. Substantial variation in climate response exists across farms in the same farming zone with relative standard deviations from 8% to 117% at Nioro du Rip, 13% to 64% in Navrongo and 9% to 37% in Tamale across climate models. Variations in fertilizer application, planting dates and soil types explained the variation in the impact among farms. This study provides insight into the complexities of the impact of climate scenarios on maize yield and the need for better representation of heterogeneous farming systems for optimized outcomes in adaptation and resilience planning in smallholder systems.

Description: No abstract available

Description: Land use and climate changes both affect terrestrial ecosystems. Here, we used three combinations of Shared Socioeconomic Pathways and Representative Concentration Pathways (SSP1xRCP26, SSP3xRCP60, and SSP5xRCP85) as input to three dynamic global vegetation models to assess the impacts and associated uncertainty on several ecosystem functions: terrestrial carbon storage and fluxes, evapotranspiration, surface albedo, and runoff. We also performed sensitivity simulations in which we kept either land use or climate (including atmospheric CO2) constant from year 2015 on to calculate the isolated land use versus climate effects. By the 20802099 period, carbon storage increases by up to 87 47 Gt (SSP1xRCP26) compared to present day, with large spatial variance across scenarios and models. Most of the carbon uptake is attributed to drivers beyond future land use and climate change, particularly the lagged effects of historic environmental changes. Future climate change typically increases carbon stocks in vegetation but not soils, while future land use change causes carbon losses, even for net agricultural abandonment (SSP1xRCP26). Evapotranspiration changes are highly variable across scenarios, and models do not agree on the magnitude or even sign of change of the individual effects. A calculated decrease in January and July surface albedo (up to 0.021 0.007 and 0.004 0.004 for SSP5xRCP85) and increase in runoff (+67 6 mm/year) is largely driven by climate change. Overall, our results show that future land use and climate change will both have substantial impacts on ecosystem functioning. However, future changes can often not be fully explained by these two drivers and legacy effects have to be considered.

Description: The spring dry season occurring in an arid region of the Southwest United States, which receives both winter storm track and summer monsoon precipitation, is investigated. Bimodal precipitation and vegetation growth provide an opportunity to assess multiple climate mechanisms and their impact on hydroclimate and ecosystems.We detect multiple shifts from wet to drier conditions in the observational record and land surface model output. Focusing on the recent dry period, a shift in the late 1990s resulted in earlier and greater spring soil moisture draw down, and later and reduced spring vegetation green-up, compared to a prior wet period (1979 - 1997). A simple soil moisture balance model shows this shift is driven by changes in winter precipitation.The recent post-1999 dry period, as well as an earlier one from 1948 - 1966, are both related to the cool tropics phase of Pacific decadal variability which influences winter precipitation. In agreement with other studies for the Southwest United States, we find the recent drought cannot be explained in terms of precipitation alone, but also is due to the rising influence of temperature, thus highlighting the sensitivity of this region to warming temperatures. Future changes in the spring dry season will therefore be affected by how tropical decadal variability evolves, and also by emerging trends due to human-driven warming.

Description: Fire emissions are critical for carbon and nutrient cycles, climate, and air quality. Dynamic Global Vegetation Models (DGVMs) with interactive fire modeling provide important estimates for long-term and large-scale changes of fire emissions. Here we present the first multi-model estimates of global gridded historical fire emissions for 1700-2012, including carbon and 33 species of trace gases and aerosols. The dataset is based on simulations of nine DGVMs with different state-of-the-art global fire models that participated in the Fire Modeling Intercomparison Project (FireMIP), using the same and standardized protocols and forcing data, and the most up-to-date fire emission factor table from field and laboratory studies over various land cover types. We evaluate the simulations of present-day fire emissions by comparing them with satellite-based products. Evaluation results show that most DGVMs simulate present-day global fire emission totals within the range of satellite-based products, and can capture the high emissions over the tropical savannas, low emissions over the arid and sparsely vegetated regions, and the main features of seasonality. However, most of the models fail to simulate the interannual variability, partly due to a lack of modeling peat fires and tropical deforestation fires. Historically, all models show only a weak trend in global fire emissions before ~1850s, consistent with multi-source merged historical reconstructions. The long-term trends among DGVMs are quite different for the 20th century, with some models showing an increase and others a decrease in fire emissions, mainly as a result of the discrepancy in their simulated responses to human population density change and land-use and land-cover change (LULCC). Our study provides a basic dataset for developing regional and global multi-source merged historical reconstructions and merging methods, and analyzing historical changes of fire emissions and their uncertainties as well as their role in the Earth system. It also highlights the importance of accurately modeling the responses of fire emissions to LULCC and population density change in reducing uncertainties in historical reconstructions of fire emissions and providing more reliable future projections.