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NASA NTRS2021

Bhutan Water Resources II: Comparing Phenology, Precipitation, and Temperature Data in Bhutan to Assist the Himalayan Environmental Rhythm Observation and Evaluation System (HEROES) Project

Bhutan is vulnerable to climate fluctuations that can affect vegetation phenology patterns. Changes in the climate have raised concerns from local farmers about altered growing seasons. In response, the DEVELOP team assessed annual vegetation phenology trends across Bhutan from 1981-2014 by comparing vegetation phenology-derived data and meteorological data. The project assessed phenology change using Vegetation Index and Phenology (VIP) Normalized Difference Vegetation Index (NDVI) products from the Advanced Very High-Resolution Radiometer (AVHRR) and the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. We also used Climate Hazards Center Infrared Precipitation with Station (CHIRPS) precipitation data and Famine Early Warning System Network Land Data Assimilation System (FLDAS) temperature data to assess climate trends in the country. The team assessed VIP phenology data for 1981-2014 to assess trends for the start of season, day of peak, and length of season. For the main growing season, the results indicated that the start of season and day of peak were delayed, while the length of season increased by 22 days. Analysis of temperature and precipitation data for the early 1980s to present indicted that Bhutan’s temperature has become warmer and precipitation has increased. Satellite-based precipitation and temperature data were compared to in situ precipitation and temperature data, yielding high correlations for both precipitation (R=0.85) and temperature (R=0.9). The project results and methods were shared with the Ugyen Wangchuck Institute for Conservation and Environmental Research (UWICER) to help assess climate change impacts in Bhutan.

DEVELOP Tech Paper↗

NASA NTRSDate not supplied

166 GHz Ice Scattering Signal in Cold-Season Precipitating Cloud Systems

Surface snowfall can be produced by a variety of forcing mechanisms that are accompanied by different in-cloud physical processes and microphysical composition. For instance, shallow cumuliform snowfall forced by marine cold air outbreaks shows distinct geographic and seasonal signatures and plays in important role in annual snowfall production in many regions worldwide. Coincident CloudSat-CALIPSO observations confirm that oceanic regions exhibiting frequent shallow cumuliform snow are typically composed of mixed-phase cloud and precipitation particles and display passive microwave brightness temperature behavior that is dominated by cloud liquid water emission, while combined Global Precipitation Measurement (GPM) radiometer and surface radar studies of intense shallow cumuliform events indicate significant ice particle scattering signals at the highest GPM radiometer frequencies. Passive microwave imager channels in the 37 to 89 GHz range have long been used to detect precipitation-sized ice particle scattering signatures in clouds. Dual polarization plays an important role in distinguishing between scattering signatures and other background variability. The GPM Microwave Imager (GMI) is the first satellite radiometer to possess dual-polarized channels at 166 GHz. These high-frequency channels are more susceptible to emission and attenuation by cloud liquid water and water vapor than lower-frequency channels, but are also more sensitive to ice scattering. This research studies the ice scattering information contained in the 166 GHz channels compared to the historically used 85/89 GHz channels on previous sensors. A 166 GHz scattering index (SI) will be developed to understand how its correlation with non-precipitating ice scattering at higher altitudes also affects the 166 GHz scattering signature in cold-season precipitating cloud systems. The 166 GHz SI will be used to possibly isolate precipitation scattering signature for different snowfall modes (shallow convective vs. deep stratiform). The supercooled liquid water affecting shallow convective systems and drastically reducing the scattering signal could be detected and quantified, providing additional information for convective snow detection and quantification in solid precipitation retrieval algorithms.

Lisa Milani↗

NASA NTRS2022

Development and Evaluation of Ensemble Consensus Precipitation Estimates over High Mountain Asia

Precipitation estimates are highly uncertain in complex regions such as High-Mountain Asia (HMA), where ground measurements are very difficult to obtain, and atmospheric dynamics poorly understood. Though gridded products derived from satellite-based observations and/or reanalysis can provide temporally and spatially distributed estimates of precipitation, there are significant inconsistencies in these products. As such, to date, there is little agreement in the community on the best and most accurate gridded precipitation product in HMA, which is likely area dependent because of HMA’s strong heterogeneities and complex orography. Targeting these gaps, this article presents the development of a consensus ensemble precipitation product using three gridded precipitation datasets (the Integrated Multi-satellitE Retrieals for Global Precipitation Measurement IMERG, the Climate Hazards group Infrared Precipitation with Stations CHIRPS, and the ECMWF Reanalysis ERA5) with a localized probability matched mean (LPM) approach. We evaluate the performance of the LPM estimate along with a simple ensemble mean (EM) estimate to overcome the differences and disparities of the three selected constituent products on long-term averages and trends in HMA. Our analysis demonstrates that LPM reduces the high biases embedded in the ensemble members and provides more realistic spatial patterns compared to EM. LPM is also a good alternative for merging data products with different spatio-temporal resolutions. By filtering disparities among the individual ensemble members, LPM overcomes the problem of a certain product performing well only in a particular area and provides a consensus estimate with plausible temporal trends.

Fadji Z Maina↗

NASA NTRS2022

Anthropogenic Sulfate Aerosol Pollution in South and East Asia Induces Increased Summer Precipitation Over Arid Central Asia

Precipitation has increased across the arid Central Asia region over recent decades. However, the underlying mechanisms of this trend are poorly understood. Here, we analyze multi-model simulations from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP) to investigate potential drivers of the observed precipitation trend. We find that anthropogenic sulfate aerosols over remote polluted regions in South and East Asia lead to increased summer precipitation, especially convective and extreme precipitation, in arid Central Asia. Elevated concentrations of sulfate aerosols over remote polluted Asia cause an equatorward shift of the Asian Westerly Jet Stream through a fast response to cooling of the local atmosphere at mid-latitudes. This shift favours moisture supply from low-latitudes and moisture flux convergence over arid Central Asia, which is confirmed by a moisture budget analysis. High levels of absorbing black carbon lead to opposing changes in the Asian Westerly Jet Stream and reduced local precipitation, which can mask the impact of sulfate aerosols. This teleconnection between arid Central Asia precipitation and anthropogenic aerosols in remote Asian polluted regions highlights long-range impacts of anthropogenic aerosols on atmospheric circulations and the hydrological cycle.

Atmospheric dynamics↗

NASA NTRS2022

Evaluation of IMERG Satellite Precipitation Over the Land-Coast-Ocean Continuum – Part Ii: Quantification

To understand and manage water systems under a changing climate and meet an increasing demand for water, a quantitative understanding of precipitation is most important in coastal regions. The capabilities of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) V06B product for precipitation quantification are examined over three coastal regions of the United States: the West Coast, the Gulf of Mexico, and the East Coast, all of which are characterized by different topographies and precipitation climatologies. A novel uncertainty analysis of IMERG is proposed that considers environmental and physical parameters such as elevation and distance to the coastline. The IMERG performance is traced back to its components, i.e., passive microwave (PMW), infrared (IR), and morphing-based estimates. The analysis is performed using high-resolution, high-quality Ground Validation Multi-Radar/Multi-Sensor (GV-MRMS) rainfall estimates as ground reference at the native resolution of IMERG of 30 min and 0.1°. IMERG Final (IM-F) quantification performance heavily depends on the respective contribution of PMW, IR, and morph components. IM-F and its components overestimate the contribution of light rainfall (<1 mm h−1) and underestimate the contribution of high rainfall rates (>10 mm h−1) to the total rainfall volume. Strong regional dependencies are highlighted, especially over the West Coast, where the proximity of complex terrain to the coastline challenges precipitation estimates. Other major drivers are the distance from the coastline, elevation, and precipitation types, especially over the land and coast surface types, that highlight the impact of precipitation regimes.

Atmosphere↗

NASA NTRS2024

Central California Disasters: Incorporating Satellite-Derived Precipitation and Soil Moisture Products into Flood Preparedness and Emergency Management in California

Atmospheric rivers are a major contributor to extreme precipitation events and flooding in California. This study assessed the feasibility of using Earth observation data to monitor precipitation, soil moisture, and flooding from atmospheric rivers in the Salinas River Watershed in central California during the winter of 2022-2023. The team analyzed satellite derived precipitation estimates from the Global Precipitation Measurement mission, soil moisture data from the Soil Moisture Active Passive radiometer, and synthetic aperture radar imagery from Sentinel-1 to detect flood inundation. Global Precipitation Measurement precipitation estimates were found to underestimate rainfall by 33% to 52% compared to rain gauge data. The team found the Soil Moisture Active Passive dataset to be a valuable flooding indicator that they could visualize through various graphical representations, although its accuracy still needs verification with in situ flood maps. Sentinel-1 synthetic aperture radar imagery provided mapping of flood inundation extent along the Salinas River and surrounding areas and the Blue Spot model appears to be a good predictor of pluvial flood zones. The findings suggest Earth observations can enhance precipitation and flooding monitoring by the California Department of Water Resources, though further verification is needed. Integration of these datasets with vulnerability indices highlighted communities at highest risk during the 2022-2023 flooding events.

Abhinav Banthiya↗

DOE OSTI2012

Precipitation Estimate Using NEXRAD Ground-Based Radar Images: Validation, Calibration and Spatial Analysis

Precipitation is an important input variable for hydrologic and ecological modeling and analysis. Next Generation Radar (NEXRAD) can provide precipitation products that cover most of the continental United States with a high resolution display of approximately 4 × 4 km2. Two major issues concerning the applications of NEXRAD data are (1) lack of a NEXRAD geo-processing and geo-referencing program and (2) bias correction of NEXRAD estimates. In this chapter, a geographic information system (GIS) based software that can automatically support processing of NEXRAD data for hydrologic and ecological models is presented. Some geostatistical approaches to calibrating NEXRAD data using rain gauge data are introduced, and two case studies on evaluating accuracy of NEXRAD Multisensor Precipitation Estimator (MPE) and calibrating MPE with rain-gauge data are presented. The first case study examines the performance of MPE in mountainous region versus south plains and cold season versus warm season, as well as the effect of sub-grid variability and temporal scale on NEXRAD performance. From the results of the first case study, performance of MPE was found to be influenced by complex terrain, frozen precipitation, sub-grid variability, and temporal scale. Overall, the assessment of MPE indicates the importance of removing bias of the MPE precipitation product before its application, especially in the complex mountainous region. The second case study examines the performance of three MPE calibration methods using rain gauge observations in the Little River Experimental Watershed in Georgia. The comparison results show that no one method can perform better than the others in terms of all evaluation coefficients and for all time steps. For practical estimation of precipitation distribution, implementation of multiple methods to predict spatial precipitation is suggested.

Zhang, Xuesong↗

DOE OSTI2019

ARM Cloud and Precipitation Measurements and Science Group Charter

The Atmospheric Radiation Measurement (ARM) Cloud and Precipitation Measurements and Science Group (CPMSG) brings together members of the ARM instrument operations, engineering, and translator teams with the ARM science community for the purpose of improving the performance and science impact of the ARM measurements of clouds and precipitation. The members of the CPMSG work toward this goal by confronting science needs from the broader research community with operational constraints of the ARM facility. The CPMSG replaces the former radar science and engineering group. The CPMSG will continue to include a significant focus on the application of the ARM radar network; however, the focus of ARM is ultimately not on specific instruments but on providing measurements and associated data products that advance atmospheric science. Providing measurements of cloud properties has always been a core activity for ARM, but increasingly, ARM has striven to couple measurements of cloud properties with precipitation to support the full range of research associated with cloud systems. Radar measurements are often central to cloud and precipitation research but often the retrieval of cloud and precipitation properties requires coupling radar measurements with measurements from other instruments or other instruments may provide information in physical regimes where radars do not do well. Therefore, the CPMSG will address issues related to radar performance and applications but will also consider issues related to other passive and active remote sensors as well as ground-based in situ precipitation measurements. A driving consideration for the group should be how resources can best be applied to measurements of cloud and precipitation properties and the development of associated data products to increase the scientific impact of these measurements.

Charter, Infrastructure Management Board, User Exe↗

DOE OSTI2020

Predicting the potential for mineral scale precipitation in unconventional reservoirs due to fluid-rock and fluid mixing geochemical reactions

Mineral precipitation within hydraulically fractured shale may affect fluid flow pathways and impact longterm hydrocarbon production. The ability to predict geochemical reactions that lead to problematic mineral precipitation will lead to active reservoir management strategies to improve overall production. Using the Marcellus Shale as a case study, a combination of laboratory experiments and reaction path modeling was applied to determine which reactions are likely to occur upon introduction of hydraulic fracturing fluid into the shale reservoir. Experimental results indicate that contact between fracturing fluid and shale will result in dissolution of primary minerals (quartz, feldspars, kaolinite, chlorite, pyrite) and secondary mineral precipitation over time periods of less than one week. Precipitation of barite, Fe-oxides, feldspars, amorphous silica and clay is likely to occur within the reservoir during shut in and early flowback due to mixing between fracturing fluid and reservoir brine as based on modeling saturation indices using experimental fluid data. Reaction path modeling of the experimental scenarios corroborates the specific dissolution and precipitation reactions observed experimentally. Comparison of the results to injected and produced waters from a Marcellus Shale well pad in Greene County, PA, USA, shows that the mineral reactions occur during the hydraulic fracturing, shut in, and early flowback periods. The results presented in this paper demonstrate the value in applying experimental approaches to identify mineral precipitation/dissolution reactions that may significantly impact reservoir performance. The good agreement between geochemical models and experimental results provides confidence that numerical models can be applied to screen the potential fluid-mineral and fluid-mixing reactions in unconventional reservoirs that result in undesired mineral scale precipitation.

58 GEOSCIENCES↗

DOE OSTI2011

Microstructural and magnetic characterization of iron precipitation in Ni-Fe-Al alloys

The influence of annealing on the microstructural evolution and magnetic properties of Ni{sub 50}Fe{sub x}Al{sub 50-x} alloys for x = 20, 25, and 30 has been investigated. Solidification microstructures of as-cast alloys reveal coarse grains of a single B2 type {beta}-phase and typical off eutectic microstructure consisting of proeutectic B2 type {beta} dendrites and interdendritic eutectic for x = 20 and x > 20 at.% Fe respectively. However, annealing at 1073 K results in the formation of FCC {gamma}-phase particles along the grain boundaries as well as grain interior in x = 20 at.% Fe alloy. The volume fraction of interdentritic eutectic regions tend to decrease and their morphologies start to degenerate by forming FCC {gamma}-phase for x > 20 at.% Fe alloys with increasing annealing temperatures. Increasing Fe content of alloys induce an enhancement in magnetization and a rise in the Curie transition temperature (T{sub C}). Temperature scan magnetic measurements and transmission electron microscopy reveal that a transient rise in the magnetization at temperatures well above the T{sub C} of the alloys would be attributed to the precipitation of a nano-scale ferromagnetic BCC {alpha}-Fe phase. Retained magnetization above the Curie transition temperature of alloy matrix, together with enhanced room temperature saturation magnetization of alloys annealed at favorable temperatures support the presence of ferromagnetic precipitates. These nano-scale precipitates are shown to induce significant precipitation hardening of the {beta}-phase in conjunction with enhanced room temperature saturation magnetization in particular when an annealing temperature of 673 K is used. - Research Highlights: {yields} Evolution of microstructure and magnetic properties with varying Fe content. {yields} Transient rise in magnetization via the formation of ferromagnetic phase. {yields} Enhancements in saturation magnetization owing to precipitated ferromagnetic phase. {yields} Nanoscale precipitation of ferromagnetic BCC {alpha}-Fe confirmed by TEM. {yields} Hardness of the {beta}-phase correlates with room temperature saturation magnetization.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Evaluation of historical CMIP6 model simulations of extreme precipitation over contiguous US regions

Simulated historical precipitation is evaluated for Coupled Model Intercomparison Project Phase 6 (CMIP6) models using precipitation indices defined by the Expert Team on Climate Change Detection and Indices. The model indices are evaluated against corresponding indices from the CPC unified gauge-based analyses of precipitation over seven geographical regions across the contiguous US (CONUS). The regions assessed match those in recent US National Climate Assessment Reports. To estimate observational uncertainty, precipitation indices for three other observational datasets (HadEx2, Livneh and PRISM) are evaluated against the CPC analyses. Both the moderate and extreme mean precipitation intensities are overestimated over the western CONUS and underestimated in the areas of the Central Great Plains (CGP) in most CMIP6 models tested. Most CMIP6 models overestimate the mean and variability of wet spell durations and underestimate the mean and variability of dry spell durations across the CONUS. Biases in interannual variability of most of the indices have similar patterns to those in corresponding mean biases. The median and interquartile model spreads in CMIP6 model biases are clearly smaller than those in CMIP5 model biases for wet spell durations. Multimodel medians of CMIP6 (CMIP6-MMM) and CMIP5 (CMIP5-MMM) have similar biases in climatology and variability but biases tend to be smaller in CMIP6-MMM. Depending on the index, extreme precipitation is slightly better in parts of the eastern half of the CONUS in CMIP6-MMM, otherwise, the biases in climatology and variability are similar to CMIP5-MMM. CMIP6-MMM performs better than individual models and even observational datasets in some cases. Differences between observational datasets for most indices are comparable to the CMIP6 interquartile model spread. The better-performing observational and model datasets are different in different parts of the CONUS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Improved Diurnal Cycle of Precipitation in E3SM With a Revised Convective Triggering Function

Abstract We revise the convective triggering function in Department of Energy's Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1) by introducing a dynamic constraint on the initiation of convection that emulates the collective dynamical effects to prevent convection from being triggered too frequently and allowing air parcels to launch above the boundary layer to capture nocturnal elevated convection. The former is referred to as the dynamic Convective Available Potential Energy (dCAPE) trigger and the latter as the Unrestricted Launch Level (ULL) trigger. Compared to the original trigger in EAMv1 that initiates convection whenever CAPE is larger than a threshold, the revised trigger substantially improves the simulated diurnal cycle of precipitation over both midlatitude and tropical lands. The nocturnal peak of precipitation and the eastward propagation of convection downstream of the Rockies and over the adjacent Great Plains are much better captured than those in the default model. The overall impact on mean precipitation is minor with some notable improvements over the Indo‐Western Pacific, subtropical Pacific and Atlantic, and South America. In general, the dCAPE trigger helps to better capture late afternoon rainfall peak, while ULL is key to capturing nocturnal elevated convection and the eastward propagation of convection. The dCAPE trigger also primarily contributes to the considerable reduction of convective precipitation over subtropical regions and the frequency of light‐to‐moderate precipitation occurrence. However, no clear improvement is seen in intense convection and the amplitude of diurnal precipitation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

A Comprehensive Precipitation Data Set for Global Land Areas (TR-051)

An expanded and updated compilation of long-term station precipitation data, together with a new set of gridded monthly mean fields for global land areas, are described. The present data set contains 5328 station records of monthly total precipitation, covering the period from the mid-1800s to the late 1980s. The station data were individually tested and visually inspected for the presence of spurious trends, jumps, and other measurement biases. The quality control procedure which was used to check the station records for nonclimatic discontinuities and other biases is detailed. We also discuss some of the problems which typically contribute to potential inhomogeneities in precipitation records. The station data were interpolated onto a 4° latitude by 5° longitude uniform grid. Comparisons of these data with two other global-scale precipitation climatologies are presented. We find good agreement among the three global-scale climatologies over the common areas in each set. Three different indices of long-term precipitation variations over the global land areas all indicate a general increase of annual precipitation since the 1940s, although a decline is evident over the last decade. There is some indication that the last few decades of the 19th century may have been as wet as the recent ones. An interesting feature of this study is the presence of relatively large differences in seasonal trends, with March-May and September-November becoming wetter in the last few decades. The December-February and June-August seasons exhibit smaller overall trends, although the northern winter season does exhibit large decadal-scale fluctuations.For access to the data files, click this link to the CDIAC data transition website: http://cdiac.ess-dive.lbl.gov/ndps/tr051.htmlThis dataset was transferred from the CDIAC Archive and published on ESS-DIVE in 2018 under the project title "Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Univ. of Colorado, Boulder, CO (United States). Cooperative Inst. for Research in Environmental Sciences (CIRES)". In 2023, the project title was updated to "Carbon Dioxide Information Analysis Center (CDIAC); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)" to enable consistent management of all datasets previously hosted by the CDIAC Archive that are now published on ESS-DIVE.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

ARM Cloud-Aerosol-Precipitation Experiment (ACAPEX) Field Campaign Report

The U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility’s ARM Cloud-Aerosol-Precipitation Experiment (ACAPEX) field campaign contributes to CalWater 2015, a multi-agency field campaign that aims to improve understanding of atmospheric rivers and aerosol sources and transport that influence cloud and precipitation processes. The ultimate goal is to reduce uncertainties in weather predictions and climate projections of droughts and floods in California. With the DOE G-1 aircraft and ARM Mobile Facility 2 (AMF2) well equipped for making aerosol and cloud measurements, ACAPEX focuses specifically on understanding how aerosols from local pollution and long-range transport affect the amount and phase of precipitation associated with atmospheric rivers. ACAPEX took place between January 12, 2015 and March 8, 2015 as part of CalWater 2015, which included four aircraft (DOE G-1, National Oceanic and Atmospheric Administration [NOAA] G-IV and P-3, and National Aeronautics and Space Administration [NASA] ER-2), the NOAA research ship Ron Brown, carrying onboard the AMF2, National Science Foundation (NSF)-sponsored aerosol and precipitation measurements at Bodega Bay, and the California Department of Water Resources extreme precipitation network.

aerosol transport↗

DOE OSTI2014

The Robust Dynamical Contribution to Precipitation Extremes in Idealized Warming Simulations across Model Resolutions

The impact of the circulation shift under climate warming on the distribution of precipitation extremes and the associated sensitivity to model resolution are investigated using the aquaplanet Community Atmosphere Model CAM3. The response of the probability density function of the precipitation to a uniform SST warming can be interpreted as superimposition of a dynamically induced poleward shift and a thermodynamically induced upward shift toward higher intensities, which give rise to manyfold increase in the frequency of the most extreme categories of the precipitation events at the poleward side of the midlatitude storm track. Meanwhile, the thermodynamic contribution to the intensification of the precipitation extremes is substantially less than expected from the Clausius-Clapeyron relation, implicative of significant change in the vertical structure of the precipitation processes. While coarser resolutions underestimate the dynamical contribution to the increase of precipitation extremes, a modest increase of the equator-to-pole SST warming gradient can have a significant opposite effect.

dynamical↗

DOE OSTI2016

A study of cloud microphysics and precipitation over the Tibetan Plateau by radar observations and cloud-resolving model simulations

Cloud microphysical properties and precipitation over the Tibetan Plateau (TP) are unique because of the high terrains, clean atmosphere, and sufficient water vapor. With dual-polarization precipitation radar and cloud radar measurements during the Third Tibetan Plateau Atmospheric Scientific Experiment (TIPEX-III), the simulated microphysics and precipitation by the Weather Research and Forecasting model (WRF) with the Chinese Academy of Meteorological Sciences (CAMS) microphysics and other microphysical schemes are investigated through a typical plateau rainfall event on 22 July 2014. Results show that the WRF-CAMS simulation reasonably reproduces the spatial distribution of 24-h accumulated precipitation, but has limitations in simulating time evolution of precipitation rates. Here, the model-calculated polarimetric radar variables have biases as well, suggesting bias in modeled hydrometeor types. The raindrop sizes in convective region are larger than those in stratiform region indicated by the small intercept of raindrop size distribution in the former. The sensitivity experiments show that precipitation processes are sensitive to the changes of warm rain processes in condensation and nucleated droplet size (but less sensitive to evaporation process). Increasing droplet condensation produces the best area-averaged rain rate during weak convection period compared with the observation, suggesting a considerable bias in thermodynamics in the baseline simulation. Increasing the initial cloud droplet size causes the rain rate reduced by half, an opposite effect to that of increasing droplet condensation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Sensitivity of the summertime tropical Atlantic precipitation distribution to convective parameterization and model resolution in ECHAM6

A realistic simulation of the tropical Atlantic precipitation distribution remains a challenge for atmospheric general circulation models, owing to their too coarse resolution that makes it necessary to parameterize convection. During boreal summer, models tend to underestimate the northward shift of the tropical Atlantic rain belt, leading to deficient precipitation over land and an anomalous precipitation maximum over the west Atlantic ocean. In this study, the model ECHAM6 is used to test the sensitivity of the precipitation biases to convective parameterization and horizontal resolution. Two sets of sensitivity experiments are performed. In the first set of experiments, modifications are applied to the convection scheme in order to investigate the relative roles of the trigger, entrainment, and closure formulations. In the second set, the model is run at high resolution with low-resolution boundary conditions in order to identify the relative contributions of a high-resolution atmosphere, orography, and surface. Results show that the dry bias over land in the model can be reduced by weakening the entrainment rate over land. Over ocean, it is found that the anomalous precipitation maximum occurs because of model choices that decrease the sensitivity of convection to the monsoon circulation in the east Atlantic. A reduction of the west Atlantic precipitation bias can be achieved by (i) using a moisture convergence closure, (ii) increasing the resolution of orography, or (iii) enhancing the production of deep convection in the east Atlantic. As a result, the biases over land and over ocean do not impact each other.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Impacts of Microphysical Scheme on Convective and Stratiform Characteristics in Two High Precipitation Squall Line Events

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

characteristics↗