Local control on precipitation in a fully coupled climate-hydrology model.

PubMed

Larsen, Morten A D; Christensen, Jens H; Drews, Martin; Butts, Michael B; Refsgaard, Jens C

2016-03-10

The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies.

Local control on precipitation in a fully coupled climate-hydrology model

PubMed Central

Larsen, Morten A. D.; Christensen, Jens H.; Drews, Martin; Butts, Michael B.; Refsgaard, Jens C.

2016-01-01

The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies. PMID:26960564

Land-Climate Feedbacks in Indian Summer Monsoon Rainfall

NASA Astrophysics Data System (ADS)

Asharaf, Shakeel; Ahrens, Bodo

2016-04-01

In an attempt to identify how land surface states such as soil moisture influence the monsoonal precipitation climate over India, a series of numerical simulations including soil moisture sensitivity experiments was performed. The simulations were conducted with a nonhydrostatic regional climate model (RCM), the Consortium for Small-Scale Modeling (COSMO) in climate mode (CCLM) model, which was driven by the European Center for Medium-Range Weather Forecasts (ECMWF) Interim reanalysis (ERA-Interim) data. Results showed that pre-monsoonal soil moisture has a significant impact on monsoonal precipitation formation and large-scale atmospheric circulations. The analysis revealed that even a small change in the processes that influence precipitation via changes in local evapotranspiration was able to trigger significant variations in regional soil moisture-precipitation feedback. It was observed that these processes varied spatially from humid to arid regions in India, which further motivated an examination of soil-moisture memory variation over these regions and determination of the ISM seasonal forecasting potential. A quantitative analysis indicated that the simulated soil-moisture memory lengths increased with soil depth and were longer in the western region than those in the eastern region of India. Additionally, the subsequent precipitation variance explained by soil moisture increased from east to west. The ISM rainfall was further analyzed in two different greenhouse gas emission scenarios: the Special Report on Emissions Scenario (SRES: B1) and the new Representative Concentration Pathways (RCPs: RCP4.5). To that end, the CCLM and its driving global-coupled atmospheric-oceanic model (GCM), ECHAM/MPIOM were used in order to understand the driving processes of the projected inter-annual precipitation variability and associated trends. Results inferred that the projected rainfall changes were the result of two largely compensating processes: increase of remotely induced precipitation and decrease of precipitation efficiency. However, the complementing precipitation components and their simulation uncertainties rendered climate projections of the Indian summer monsoon rainfall as an ongoing, highly ambiguous challenge for both the GCM and the RCM.

The Impact of Parameterized Convection on Climatological Precipitation in Atmospheric Global Climate Models

NASA Astrophysics Data System (ADS)

Maher, Penelope; Vallis, Geoffrey K.; Sherwood, Steven C.; Webb, Mark J.; Sansom, Philip G.

2018-04-01

Convective parameterizations are widely believed to be essential for realistic simulations of the atmosphere. However, their deficiencies also result in model biases. The role of convection schemes in modern atmospheric models is examined using Selected Process On/Off Klima Intercomparison Experiment simulations without parameterized convection and forced with observed sea surface temperatures. Convection schemes are not required for reasonable climatological precipitation. However, they are essential for reasonable daily precipitation and constraining extreme daily precipitation that otherwise develops. Systematic effects on lapse rate and humidity are likewise modest compared with the intermodel spread. Without parameterized convection Kelvin waves are more realistic. An unexpectedly large moist Southern Hemisphere storm track bias is identified. This storm track bias persists without convection schemes, as does the double Intertropical Convergence Zone and excessive ocean precipitation biases. This suggests that model biases originate from processes other than convection or that convection schemes are missing key processes.

Use NU-WRF and GCE Model to Simulate the Precipitation Processes During MC3E Campaign

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Wu, Di; Matsui, Toshi; Li, Xiaowen; Zeng, Xiping; Peter-Lidard, Christa; Hou, Arthur

2012-01-01

One of major CRM approaches to studying precipitation processes is sometimes referred to as "cloud ensemble modeling". This approach allows many clouds of various sizes and stages of their lifecycles to be present at any given simulation time. Large-scale effects derived from observations are imposed into CRMs as forcing, and cyclic lateral boundaries are used. The advantage of this approach is that model results in terms of rainfall and QI and Q2 usually are in good agreement with observations. In addition, the model results provide cloud statistics that represent different types of clouds/cloud systems during their lifetime (life cycle). The large-scale forcing derived from MC3EI will be used to drive GCE model simulations. The model-simulated results will be compared with observations from MC3E. These GCE model-simulated datasets are especially valuable for LH algorithm developers. In addition, the regional scale model with very high-resolution, NASA Unified WRF is also used to real time forecast during the MC3E campaign to ensure that the precipitation and other meteorological forecasts are available to the flight planning team and to interpret the forecast results in terms of proposed flight scenarios. Post Mission simulations are conducted to examine the sensitivity of initial and lateral boundary conditions to cloud and precipitation processes and rainfall. We will compare model results in terms of precipitation and surface rainfall using GCE model and NU-WRF

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

NASA Technical Reports Server (NTRS)

Wu, Di; Dong, Xiquan; Xi, Baike; Feng, Zhe; Kennedy, Aaron; Mullendore, Gretchen; Gilmore, Matthew; Tao, Wei-Kuo

2013-01-01

This study investigates the impact of snow, graupel, and hail processes on simulated squall lines over the Southern Great Plains in the United States. The Weather Research and Forecasting (WRF) model is used to simulate two squall line events in Oklahoma during May 2007, and the simulations are validated against radar and surface observations. Several microphysics schemes are tested in this study, including the WRF 5-Class Microphysics (WSM5), WRF 6-Class Microphysics (WSM6), Goddard Cumulus Ensemble (GCE) Three Ice (3-ice) with graupel, Goddard Two Ice (2-ice), and Goddard 3-ice hail schemes. Simulated surface precipitation is sensitive to the microphysics scheme when the graupel or hail categories are included. All of the 3-ice schemes overestimate the total precipitation with WSM6 having the largest bias. The 2-ice schemes, without a graupel/hail category, produce less total precipitation than the 3-ice schemes. By applying a radar-based convective/stratiform partitioning algorithm, we find that including graupel/hail processes increases the convective areal coverage, precipitation intensity, updraft, and downdraft intensities, and reduces the stratiform areal coverage and precipitation intensity. For vertical structures, simulations have higher reflectivity values distributed aloft than the observed values in both the convective and stratiform regions. Three-ice schemes produce more high reflectivity values in convective regions, while 2-ice schemes produce more high reflectivity values in stratiform regions. In addition, this study has demonstrated that the radar-based convective/stratiform partitioning algorithm can reasonably identify WRF-simulated precipitation, wind, and microphysical fields in both convective and stratiform regions.

Sensitivity of U.S. summer precipitation to model resolution and convective parameterizations across gray zone resolutions

NASA Astrophysics Data System (ADS)

Gao, Yang; Leung, L. Ruby; Zhao, Chun; Hagos, Samson

2017-03-01

Simulating summer precipitation is a significant challenge for climate models that rely on cumulus parameterizations to represent moist convection processes. Motivated by recent advances in computing that support very high-resolution modeling, this study aims to systematically evaluate the effects of model resolution and convective parameterizations across the gray zone resolutions. Simulations using the Weather Research and Forecasting model were conducted at grid spacings of 36 km, 12 km, and 4 km for two summers over the conterminous U.S. The convection-permitting simulations at 4 km grid spacing are most skillful in reproducing the observed precipitation spatial distributions and diurnal variability. Notable differences are found between simulations with the traditional Kain-Fritsch (KF) and the scale-aware Grell-Freitas (GF) convection schemes, with the latter more skillful in capturing the nocturnal timing in the Great Plains and North American monsoon regions. The GF scheme also simulates a smoother transition from convective to large-scale precipitation as resolution increases, resulting in reduced sensitivity to model resolution compared to the KF scheme. Nonhydrostatic dynamics has a positive impact on precipitation over complex terrain even at 12 km and 36 km grid spacings. With nudging of the winds toward observations, we show that the conspicuous warm biases in the Southern Great Plains are related to precipitation biases induced by large-scale circulation biases, which are insensitive to model resolution. Overall, notable improvements in simulating summer rainfall and its diurnal variability through convection-permitting modeling and scale-aware parameterizations suggest promising venues for improving climate simulations of water cycle processes.

A Heuristic Parameterization for the Integrated Vertical Overlap of Cumulus and Stratus

NASA Astrophysics Data System (ADS)

Park, Sungsu

2017-10-01

The author developed a heuristic parameterization to handle the contrasting vertical overlap structures of cumulus and stratus in an integrated way. The parameterization assumes that cumulus is maximum-randomly overlapped with adjacent cumulus; stratus is maximum-randomly overlapped with adjacent stratus; and radiation and precipitation areas at each model interface are grouped into four categories, that is, convective, stratiform, mixed, and clear areas. For simplicity, thermodynamic scalars within individual portions of cloud, radiation, and precipitation areas are assumed to be internally homogeneous. The parameterization was implemented into the Seoul National University Atmosphere Model version 0 (SAM0) in an offline mode and tested over the globe. The offline control simulation reasonably reproduces the online surface precipitation flux and longwave cloud radiative forcing (LWCF). Although the cumulus fraction is much smaller than the stratus fraction, cumulus dominantly contributes to precipitation production in the tropics. For radiation, however, stratus is dominant. Compared with the maximum overlap, the random overlap of stratus produces stronger LWCF and, surprisingly, more precipitation flux due to less evaporation of convective precipitation. Compared with the maximum overlap, the random overlap of cumulus simulates stronger LWCF and weaker precipitation flux. Compared with the control simulation with separate cumulus and stratus, the simulation with a single-merged cloud substantially enhances the LWCF in the tropical deep convection and midlatitude storm track regions. The process-splitting treatment of convective and stratiform precipitation with an independent precipitation approximation (IPA) simulates weaker surface precipitation flux than the control simulation in the tropical region.

A Study of Heavy Precipitation Events in Taiwan During 10-13 August, 1994. Part 2; Mesoscale Model Simulations

NASA Technical Reports Server (NTRS)

Tao, Wei Kuo; Chen, C.-S.; Jia, Y.; Baker, D.; Lang, S.; Wetzel, P.; Lau, W. K.-M.

2001-01-01

Several heavy precipitation episodes occurred over Taiwan from August 10 to 13, 1994. Precipitation patterns and characteristics are quite different between the precipitation events that occurred from August 10 and I I and from August 12 and 13. In Part I (Chen et al. 2001), the environmental situation and precipitation characteristics are analyzed using the EC/TOGA data, ground-based radar data, surface rainfall patterns, surface wind data, and upper air soundings. In this study (Part II), the Penn State/NCAR Mesoscale Model (MM5) is used to study the precipitation characteristics of these heavy precipitation events. Various physical processes (schemes) developed at NASA Goddard Space Flight Center (i.e., cloud microphysics scheme, radiative transfer model, and land-soil-vegetation surface model) have recently implemented into the MM5. These physical packages are described in the paper, Two way interactive nested grids are used with horizontal resolutions of 45, 15 and 5 km. The model results indicated that Cloud physics, land surface and radiation processes generally do not change the location (horizontal distribution) of heavy precipitation. The Goddard 3-class ice scheme produced more rainfall than the 2-class scheme. The Goddard multi-broad-band radiative transfer model reduced precipitation compared to a one-broad band (emissivity) radiation model. The Goddard land-soil-vegetation surface model also reduce the rainfall compared to a simple surface model in which the surface temperature is computed from a Surface energy budget following the "force-re store" method. However, model runs including all Goddard physical processes enhanced precipitation significantly for both cases. The results from these runs are in better agreement with observations. Despite improved simulations using different physical schemes, there are still some deficiencies in the model simulations. Some potential problems are discussed. Sensitivity tests (removing either terrain or radiative processes) are performed to identify the physical processes that determine the precipitation patterns and characteristics for heavy rainfall events. These sensitivity tests indicated that terrain can play a major role in determining the exact location for both precipitation events. The terrain can also play a major role in determining the intensity of precipitation for both events. However, it has a large impact on one event but a smaller one on the other. The radiative processes are also important for determining, the precipitation patterns for one case but. not the other. The radiative processes can also effect the total rainfall for both cases to different extents.

Microstructural Evolution and the Precipitation Behavior in X90 Linepipe Steel During Isothermal Processing

NASA Astrophysics Data System (ADS)

Tian, Y.; Wang, H. T.; Wang, Z. D.; Misra, R. D. K.; Wang, G. D.

2018-03-01

Thermomechanical controlled processing of 560-MPa (X90) linepipe steel was simulated in the laboratory using a thermomechanical simulator to study the microstructural evolution and precipitation behavior during isothermal holding. The results indicated that martensite was obtained when the steels were isothermally held for 5 s at 700 °C. Subsequently, granular bainite and acicular ferrite transformation occurred with increased holding time. Different amount of polygonal ferrite formed after isothermally holding for 600-3600 s. Pearlite nucleated after isothermally holding for 3600 s. Precipitation occurred after isothermal holding for 5 s and continuous precipitation occurred at grain boundaries after isothermally holding for 600 s. After isothermally holding for 3600 s, large Nb/Ti carbide precipitated. The presence of MX-type precipitates was confirmed by diffraction pattern. The interphase precipitation (IP) occurred between 5 and 30 s. Maximum hardness was obtained after isothermally holding for 600 s when IP occurred and rapidly decreased to a low value, mainly because polygonal ferrite dominated the microstructure after isothermally holding for 3600 s.

Evaluation of global climate model on performances of precipitation simulation and prediction in the Huaihe River basin

NASA Astrophysics Data System (ADS)

Wu, Yenan; Zhong, Ping-an; Xu, Bin; Zhu, Feilin; Fu, Jisi

2017-06-01

Using climate models with high performance to predict the future climate changes can increase the reliability of results. In this paper, six kinds of global climate models that selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) under Representative Concentration Path (RCP) 4.5 scenarios were compared to the measured data during baseline period (1960-2000) and evaluate the simulation performance on precipitation. Since the results of single climate models are often biased and highly uncertain, we examine the back propagation (BP) neural network and arithmetic mean method in assembling the precipitation of multi models. The delta method was used to calibrate the result of single model and multimodel ensembles by arithmetic mean method (MME-AM) during the validation period (2001-2010) and the predicting period (2011-2100). We then use the single models and multimodel ensembles to predict the future precipitation process and spatial distribution. The result shows that BNU-ESM model has the highest simulation effect among all the single models. The multimodel assembled by BP neural network (MME-BP) has a good simulation performance on the annual average precipitation process and the deterministic coefficient during the validation period is 0.814. The simulation capability on spatial distribution of precipitation is: calibrated MME-AM > MME-BP > calibrated BNU-ESM. The future precipitation predicted by all models tends to increase as the time period increases. The order of average increase amplitude of each season is: winter > spring > summer > autumn. These findings can provide useful information for decision makers to make climate-related disaster mitigation plans.

Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau

DOE PAGES

Liu, Xiaomang; Yang, Tiantian; Hsu, Koulin; ...

2017-01-10

On the Tibetan Plateau, the limited ground-based rainfall information owing to a harsh environment has brought great challenges to hydrological studies. Satellite-based rainfall products, which allow for a better coverage than both radar network and rain gauges on the Tibetan Plateau, can be suitable alternatives for studies on investigating the hydrological processes and climate change. In this study, a newly developed daily satellite-based precipitation product, termed Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks $-$ Climate Data Record (PERSIANN-CDR), is used as input for a hydrologic model to simulate streamflow in the upper Yellow and Yangtze River basinsmore » on the Tibetan Plateau. The results show that the simulated streamflows using PERSIANN-CDR precipitation and the Global Land Data Assimilation System (GLDAS) precipitation are closer to observation than that using limited gauge-based precipitation interpolation in the upper Yangtze River basin. The simulated streamflow using gauge-based precipitation are higher than the streamflow observation during the wet season. In the upper Yellow River basin, gauge-based precipitation, GLDAS precipitation, and PERSIANN-CDR precipitation have similar good performance in simulating streamflow. Finally, the evaluation of streamflow simulation capability in this study partly indicates that the PERSIANN-CDR rainfall product has good potential to be a reliable dataset and an alternative information source of a limited gauge network for conducting long-term hydrological and climate studies on the Tibetan Plateau.« less

Role of Longwave Cloud-Radiation Feedback in the Simulation of the Madden-Julian Oscillation

NASA Technical Reports Server (NTRS)

Kim, Daehyun; Ahn, Min-Seop; Kang, In-Sik; Del Genio, Anthony D.

2015-01-01

The role of the cloud-radiation interaction in the simulation of the Madden-Julian oscillation (MJO) is investigated. A special focus is on the enhancement of column-integrated diabatic heating due to the greenhouse effects of clouds and moisture in the region of anomalous convection. The degree of this enhancement, the greenhouse enhancement factor (GEF), is measured at different precipitation anomaly regimes as the negative ratio of anomalous outgoing longwave radiation to anomalous precipitation. Observations show that the GEF varies significantly with precipitation anomaly and with the MJO cycle. The greenhouse enhancement is greater in weak precipitation anomaly regimes and its effectiveness decreases monotonically with increasing precipitation anomaly. The GEF also amplifies locally when convection is strengthened in association with the MJO, especially in the weak precipitation anomaly regime (less than 5 mm day(exp -1)). A robust statistical relationship is found among CMIP5 climate model simulations between the GEF and the MJO simulation fidelity. Models that simulate a stronger MJO also simulate a greater GEF, especially in the weak precipitation anomaly regime (less than 5 mm day(exp -1)). Models with a greater GEF in the strong precipitation anomaly regime (greater than 30 mm day(-1)) represent a slightly slower MJO propagation speed. Many models that lack the MJO underestimate the GEF in general and in particular in the weak precipitation anomaly regime. The results herein highlight that the cloud-radiation interaction is a crucial process for climate models to correctly represent the MJO.

Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Xiaomang; Yang, Tiantian; Hsu, Koulin

On the Tibetan Plateau, the limited ground-based rainfall information owing to a harsh environment has brought great challenges to hydrological studies. Satellite-based rainfall products, which allow for a better coverage than both radar network and rain gauges on the Tibetan Plateau, can be suitable alternatives for studies on investigating the hydrological processes and climate change. In this study, a newly developed daily satellite-based precipitation product, termed Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks $-$ Climate Data Record (PERSIANN-CDR), is used as input for a hydrologic model to simulate streamflow in the upper Yellow and Yangtze River basinsmore » on the Tibetan Plateau. The results show that the simulated streamflows using PERSIANN-CDR precipitation and the Global Land Data Assimilation System (GLDAS) precipitation are closer to observation than that using limited gauge-based precipitation interpolation in the upper Yangtze River basin. The simulated streamflow using gauge-based precipitation are higher than the streamflow observation during the wet season. In the upper Yellow River basin, gauge-based precipitation, GLDAS precipitation, and PERSIANN-CDR precipitation have similar good performance in simulating streamflow. Finally, the evaluation of streamflow simulation capability in this study partly indicates that the PERSIANN-CDR rainfall product has good potential to be a reliable dataset and an alternative information source of a limited gauge network for conducting long-term hydrological and climate studies on the Tibetan Plateau.« less

Spatial interpolation schemes of daily precipitation for hydrologic modeling

USGS Publications Warehouse

Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.

2012-01-01

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.

A glacier runoff extension to the Precipitation Runoff Modeling System

Treesearch

A. E. Van Beusekom; R. J. Viger

2016-01-01

A module to simulate glacier runoff, PRMSglacier, was added to PRMS (Precipitation Runoff Modeling System), a distributed-parameter, physical-process hydrological simulation code. The extension does not require extensive on-glacier measurements or computational expense but still relies on physical principles over empirical relations as much as is feasible while...

Precipitation in a boiling soup: is microphysics driving the statistical properties of intense turbulent convection?

NASA Astrophysics Data System (ADS)

Parodi, A.; von Hardenberg, J.; Provenzale, A.

2012-04-01

Intense precipitation events are often associated with strong convective phenomena in the atmosphere. A deeper understanding of how microphysics affects the spatial and temporal variability of convective processes is relevant for many hydro-meteorological applications, such as the estimation of rainfall using remote sensing techniques and the ability to predict severe precipitation processes. In this paper, high-resolution simulations (0.1-1 km) of an atmosphere in radiative-convective equilibrium are performed using the Weather Research and Forecasting (WRF) model by prescribing different microphysical parameterizations. The dependence of fine-scale spatio-temporal properties of convective structures on microphysical details are investigated and the simulation results are compared with the known properties of radar maps of precipitation fields. We analyze and discuss similarities and differences and, based also on previous results on the dependence of precipitation statistics on the raindrop terminal velocity, try to draw some general inferences.

Impact of radiation frequency, precipitation radiative forcing, and radiation column aggregation on convection-permitting West African monsoon simulations

NASA Astrophysics Data System (ADS)

Matsui, Toshi; Zhang, Sara Q.; Lang, Stephen E.; Tao, Wei-Kuo; Ichoku, Charles; Peters-Lidard, Christa D.

2018-03-01

In this study, the impact of different configurations of the Goddard radiation scheme on convection-permitting simulations (CPSs) of the West African monsoon (WAM) is investigated using the NASA-Unified WRF (NU-WRF). These CPSs had 3 km grid spacing to explicitly simulate the evolution of mesoscale convective systems (MCSs) and their interaction with radiative processes across the WAM domain and were able to reproduce realistic precipitation and energy budget fields when compared with satellite data, although low clouds were overestimated. Sensitivity experiments reveal that (1) lowering the radiation update frequency (i.e., longer radiation update time) increases precipitation and cloudiness over the WAM region by enhancing the monsoon circulation, (2) deactivation of precipitation radiative forcing suppresses cloudiness over the WAM region, and (3) aggregating radiation columns reduces low clouds over ocean and tropical West Africa. The changes in radiation configuration immediately modulate the radiative heating and low clouds over ocean. On the 2nd day of the simulations, patterns of latitudinal air temperature profiles were already similar to the patterns of monthly composites for all radiation sensitivity experiments. Low cloud maintenance within the WAM system is tightly connected with radiation processes; thus, proper coupling between microphysics and radiation processes must be established for each modeling framework.

Reactive Transport Modeling of Induced Calcite Precipitation Reaction Fronts in Porous Media Using A Parallel, Fully Coupled, Fully Implicit Approach

NASA Astrophysics Data System (ADS)

Guo, L.; Huang, H.; Gaston, D.; Redden, G. D.; Fox, D. T.; Fujita, Y.

2010-12-01

Inducing mineral precipitation in the subsurface is one potential strategy for immobilizing trace metal and radionuclide contaminants. Generating mineral precipitates in situ can be achieved by manipulating chemical conditions, typically through injection or in situ generation of reactants. How these reactants transport, mix and react within the medium controls the spatial distribution and composition of the resulting mineral phases. Multiple processes, including fluid flow, dispersive/diffusive transport of reactants, biogeochemical reactions and changes in porosity-permeability, are tightly coupled over a number of scales. Numerical modeling can be used to investigate the nonlinear coupling effects of these processes which are quite challenging to explore experimentally. Many subsurface reactive transport simulators employ a de-coupled or operator-splitting approach where transport equations and batch chemistry reactions are solved sequentially. However, such an approach has limited applicability for biogeochemical systems with fast kinetics and strong coupling between chemical reactions and medium properties. A massively parallel, fully coupled, fully implicit Reactive Transport simulator (referred to as “RAT”) based on a parallel multi-physics object-oriented simulation framework (MOOSE) has been developed at the Idaho National Laboratory. Within this simulator, systems of transport and reaction equations can be solved simultaneously in a fully coupled, fully implicit manner using the Jacobian Free Newton-Krylov (JFNK) method with additional advanced computing capabilities such as (1) physics-based preconditioning for solution convergence acceleration, (2) massively parallel computing and scalability, and (3) adaptive mesh refinements for 2D and 3D structured and unstructured mesh. The simulator was first tested against analytical solutions, then applied to simulating induced calcium carbonate mineral precipitation in 1D columns and 2D flow cells as analogs to homogeneous and heterogeneous porous media, respectively. In 1D columns, calcium carbonate mineral precipitation was driven by urea hydrolysis catalyzed by urease enzyme, and in 2D flow cells, calcium carbonate mineral forming reactants were injected sequentially, forming migrating reaction fronts that are typically highly nonuniform. The RAT simulation results for the spatial and temporal distributions of precipitates, reaction rates and major species in the system, and also for changes in porosity and permeability, were compared to both laboratory experimental data and computational results obtained using other reactive transport simulators. The comparisons demonstrate the ability of RAT to simulate complex nonlinear systems and the advantages of fully coupled approaches, over de-coupled methods, for accurate simulation of complex, dynamic processes such as engineered mineral precipitation in subsurface environments.

Multiscale modeling of dislocation-precipitate interactions in Fe: From molecular dynamics to discrete dislocations.

PubMed

Lehtinen, Arttu; Granberg, Fredric; Laurson, Lasse; Nordlund, Kai; Alava, Mikko J

2016-01-01

The stress-driven motion of dislocations in crystalline solids, and thus the ensuing plastic deformation process, is greatly influenced by the presence or absence of various pointlike defects such as precipitates or solute atoms. These defects act as obstacles for dislocation motion and hence affect the mechanical properties of the material. Here we combine molecular dynamics studies with three-dimensional discrete dislocation dynamics simulations in order to model the interaction between different kinds of precipitates and a 1/2〈111〉{110} edge dislocation in BCC iron. We have implemented immobile spherical precipitates into the ParaDis discrete dislocation dynamics code, with the dislocations interacting with the precipitates via a Gaussian potential, generating a normal force acting on the dislocation segments. The parameters used in the discrete dislocation dynamics simulations for the precipitate potential, the dislocation mobility, shear modulus, and dislocation core energy are obtained from molecular dynamics simulations. We compare the critical stresses needed to unpin the dislocation from the precipitate in molecular dynamics and discrete dislocation dynamics simulations in order to fit the two methods together and discuss the variety of the relevant pinning and depinning mechanisms.

Controlling calcium precipitation in an integrated anaerobic-aerobic treatment system of a "zero-discharge" paper mill.

PubMed

van Lier, J B; Boncz, M A

2002-01-01

The pulp and paper industry uses significant amounts of water and energy for the paper production process. Closing the water cycles in this industry, therefore, promises large benefits for the environment and has the potential of huge cost savings for the industry. Closing the water cycle on the other hand also introduces problems with process water quality, quality of the end-product and scaling, owing to increased water contamination. An inline treatment system is discussed in which anaerobic-aerobic bioreactors perform a central role for removing both organic and inorganic pollutants from the process water cycle. In the proposed set-up, the organic compounds are converted to methane gas and reused for energy supply, while sulphur compounds are stripped from the process cycle and calcium carbonate is removed by precipitation. Improved control of the treatment system will direct the inorganic precipitates to a location where it does not adversely affect paper production and process water treatment. A simulation program for triggering and controlling CaCO3 precipitation was developed that takes both biological conversions and all relevant chemical equilibria in the system into account. Simulation results are in good agreement with data gathered in a full-scale "zero-emission" paper plant and indicate that control of CaCO3 precipitation can be improved, e.g. in the aerobic post-treatment. Alternatively, a separate precipitation unit could be considered.

Simulating the Dependence of Aspen on Redistributed Snow

NASA Astrophysics Data System (ADS)

Soderquist, B.; Kavanagh, K.; Link, T. E.; Seyfried, M. S.; Winstral, A. H.

2013-12-01

In mountainous regions across the western USA, the distribution of aspen (Populus tremuloides) is often directly related to heterogeneous soil moisture subsidies resulting from redistributed snow. With decades of climate and precipitation data across elevational and precipitation gradients, the Reynolds Creek Experimental Watershed (RCEW) in southwest Idaho provides a unique opportunity to study the relationship between aspen and redistributed snow. Within the RCEW, the total amount of precipitation has not changed in the past 50 years, but there are sharp declines in the percentage of the precipitation falling as snow. As shifts in the distribution of available moisture continue, future trends in aspen net primary productivity (NPP) remain uncertain. In order to assess the importance of snowdrift subsidies, NPP of three aspen stands was simulated at sites spanning elevational and precipitation gradients using the biogeochemical process model BIOME-BGC. At the aspen site experiencing the driest climate and lowest amount of precipitation from snow, approximately 400 mm of total precipitation was measured from November to March of 2008. However, peak measured snow water equivalent (SWE) held in drifts directly upslope of this stand was approximately 2100 mm, 5 times more moisture than the uniform winter precipitation layer initially assumed by BIOME-BGC. BIOME-BGC simulations in dry years forced by adjusted precipitation data resulted in NPP values approximately 30% higher than simulations assuming a uniform precipitation layer. Using BIOME-BGC and climate data from 1985-2011, the relationship between simulated NPP and measured basal area increments (BAI) improved after accounting for redistributed snow, indicating increased simulation representation. In addition to improved simulation capabilities, soil moisture data, diurnal branch water potential, and stomatal conductance observations at each site detail the use of soil moisture in the rooting zone and the onset of drought stress occurring in stands located along a precipitation phase gradient. These results further emphasize the importance of redistributed snow in heterogeneous landscapes along with the need to account for temporal shifts in water resource availability when assessing ecosystem vulnerability to climate change.

The response of a simulated mesoscale convective system to increased aerosol pollution: Part I: Precipitation intensity, distribution, and efficiency

NASA Astrophysics Data System (ADS)

Clavner, Michal; Cotton, William R.; van den Heever, Susan C.; Saleeby, Stephen M.; Pierce, Jeffery R.

2018-01-01

Mesoscale Convective Systems (MCSs) are important contributors to rainfall in the High Plains of the United States and elsewhere in the world. It is therefore of interest to understand how different aerosols serving as cloud condensation nuclei (CCN) may impact the total amount, rates and spatial distribution of precipitation produced by MCSs. In this study, different aerosol concentrations and their effects on precipitation produced by an MCS are examined by simulating the 8 May 2009 "Super-Derecho" MCS using the Regional Atmospheric Modeling System (RAMS), a cloud-resolving model (CRM) with sophisticated aerosol and microphysical parameterizations. Three simulations were conducted that differed only in the initial concentration, spatial distribution, and chemical composition of aerosols. Aerosol fields were derived from the output of GEOS-Chem, a 3D chemical transport numerical model. Results from the RAMS simulations show that the total domain precipitation was not significantly affected by variations in aerosol concentrations, however, the pollution aerosols altered the precipitation characteristics. The more polluted simulations exhibited higher precipitation rates, higher bulk precipitation efficiency, a larger area with heavier precipitation, and a smaller area with lighter precipitation. These differences arose as a result of aerosols enhancing precipitation in the convective region of the MCS while suppressing precipitation from the MCS's stratiform-anvil. In the convective region, several processes likely contributed to an increase of precipitation. First, owing to the very humid environment of this storm, the enhanced amount of cloud water available to be collected overwhelmed the reduction in precipitation efficiency associated with the aerosol-induced production of smaller droplets which led to a net increase in the conversion of cloud droplets to precipitation. Second, higher aerosol concentrations led to invigoration of convective updrafts which enhanced precipitation in accordance to the convective invigoration hypothesis. The reduction in stratiform precipitation in the more polluted simulations was found to be attributed to the presence of greater aerosol number concentrations that reduced both collision-coalescence and riming. Analysis of back trajeocty flow showed that the air feeding the stratiform-anvil originated within the free troposphere, by mesoscale ascent. Therefore, increased aerosol pollution at higher elevations impacted the stratiform precipitation formation within the simulated MCS. As a consequence, the more polluted simulations produced the smallest precipitation from the MCS stratiform-anvil region. In Part II the impact of aerosols on the severe winds produced by this storm is examined.

Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

2011-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to use of the multi-satellite simulator tqimproy precipitation processes will be discussed.

Applying the WRF Double-Moment Six-Class Microphysics Scheme in the GRAPES_Meso Model: A Case Study

NASA Astrophysics Data System (ADS)

Zhang, Meng; Wang, Hong; Zhang, Xiaoye; Peng, Yue; Che, Huizheng

2018-04-01

This study incorporated the Weather Research and Forecasting (WRF) model double-moment 6-class (WDM6) microphysics scheme into the mesoscale version of the Global/Regional Assimilation and PrEdiction System (GRAPES_Meso). A rainfall event that occurred during 3-5 June 2015 around Beijing was simulated by using the WDM6, the WRF single-moment 6-class scheme (WSM6), and the NCEP 5-class scheme, respectively. The results show that both the distribution and magnitude of the rainfall simulated with WDM6 were more consistent with the observation. Compared with WDM6, WSM6 simulated larger cloud liquid water content, which provided more water vapor for graupel growth, leading to increased precipitation in the cold-rain processes. For areas with the warmrain processes, the sensitivity experiments using WDM6 showed that an increase in cloud condensation nuclei (CCN) number concentration led to enhanced CCN activation ratio and larger cloud droplet number concentration ( N c) but decreased cloud droplet effective diameter. The formation of more small-size cloud droplets resulted in a decrease in raindrop number concentration ( N r), inhibiting the warm-rain processes, thus gradually decreasing the amount of precipitation. For areas mainly with the cold-rain processes, the overall amount of precipitation increased; however, it gradually decreased when the CCN number concentration reached a certain magnitude. Hence, the effect of CCN number concentration on precipitation exhibits significant differences in different rainfall areas of the same precipitation event.

Effects of combined silicon and molybdenum alloying on the size and evolution of microalloy precipitates in HSLA steels containing niobium and titanium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pavlina, Erik J., E-mail: e.pavlina@deakin.edu.au; Van Tyne, C.J.; Speer, J.G.

2015-04-15

The effects of combined silicon and molybdenum alloying additions on microalloy precipitate formation in austenite after single- and double-step deformations below the austenite no-recrystallization temperature were examined in high-strength low-alloy (HSLA) steels microalloyed with titanium and niobium. The precipitation sequence in austenite was evaluated following an interrupted thermomechanical processing simulation using transmission electron microscopy. Large (~ 105 nm), cuboidal titanium-rich nitride precipitates showed no evolution in size during reheating and simulated thermomechanical processing. The average size and size distribution of these precipitates were also not affected by the combined silicon and molybdenum additions or by deformation. Relatively fine (< 20more » nm), irregular-shaped niobium-rich carbonitride precipitates formed in austenite during isothermal holding at 1173 K. Based upon analysis that incorporated precipitate growth and coarsening models, the combined silicon and molybdenum additions were considered to increase the diffusivity of niobium in austenite by over 30% and result in coarser precipitates at 1173 K compared to the lower alloyed steel. Deformation decreased the size of the niobium-rich carbonitride precipitates that formed in austenite. - Highlights: • We examine combined Si and Mo additions on microalloy precipitation in austenite. • Precipitate size tends to decrease with increasing deformation steps. • Combined Si and Mo alloying additions increase the diffusivity of Nb in austenite.« less

Characterizing the Precipitation Processes in Hurricane Karl (2010) Through Analysis of Airborne Doppler Radar Data and Numerical Simulations

NASA Astrophysics Data System (ADS)

DeHart, J.; Houze, R.

2016-12-01

Airborne radar data and numerical simulations are employed to investigate the structure of Hurricane Karl (2010). Karl peaked in intensity as a major hurricane in the Gulf of Mexico before making landfall on the mountainous coast of Veracruz, Mexico. Multiple aircraft extensively sampled Karl during the NASA GRIP campaign, including NASA's DC-8 aircraft instrumented with the Advanced Precipitation Radar 2 (APR-2), which is a high-resolution, dual-frequency Doppler radar. Data from APR-2 provide a unique opportunity to characterize the precipitation structure of Karl as it underwent orographic modification. As Karl made landfall on 17 September 2010, the vertical structure of the precipitation echo varied spatially around the Mexican terrain. The precipitation variation was linked to several factors: landfall, orientation of flow relative to the topographic features, and differing characteristics inherent to the eyewall and rainbands. Despite the differences in the reflectivity intensity across the storm, we show that low-level reflectivity enhancement occurred only where upslope flow was favorable. The radar data indicate that the processes initially contributing to the reflectivity enhancement were warm-cloud processes, either through collection of orographically-generated cloud water or shallow convection. But as Karl weakened, the low-level enhancement processes were overshadowed by deep convection that developed along the terrain. Analysis of the radar data is complemented by a series of numerical simulations, which reasonably reproduce the track, intensity and structure of Karl. The simulated thermodynamic and kinematic patterns provide a holistic view of Karl's evolution during landfall. We use terrain modification experiments to examine the sensitivity of the orographic enhancement processes to the three-dimensional terrain and land surface characteristics. Consistent with the radar analysis, warm-cloud enhancement processes are visible in the spatial pattern of hydrometeor mixing ratios and in a shift towards greater mixing ratios. We link changes in the microphysical patterns with the thermodynamic and kinematic environments in which the patterns are embedded. We also examine the relative contributions of intense convection and forced ascent to the precipitation totals.

The Goddard Cumulus Ensemble Model (GCE): Improvements and Applications for Studying Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Lang, Stephen E.; Zeng, Xiping; Li, Xiaowen; Matsui, Toshi; Mohr, Karen; Posselt, Derek; Chern, Jiundar; Peters-Lidard, Christa; Norris, Peter M.;

Aerosol-cloud interactions in mixed-phase convective clouds - Part 1: Aerosol perturbations

NASA Astrophysics Data System (ADS)

Miltenberger, Annette K.; Field, Paul R.; Hill, Adrian A.; Rosenberg, Phil; Shipway, Ben J.; Wilkinson, Jonathan M.; Scovell, Robert; Blyth, Alan M.

2018-03-01

Changes induced by perturbed aerosol conditions in moderately deep mixed-phase convective clouds (cloud top height ˜ 5 km) developing along sea-breeze convergence lines are investigated with high-resolution numerical model simulations. The simulations utilise the newly developed Cloud-AeroSol Interacting Microphysics (CASIM) module for the Unified Model (UM), which allows for the representation of the two-way interaction between cloud and aerosol fields. Simulations are evaluated against observations collected during the COnvective Precipitation Experiment (COPE) field campaign over the southwestern peninsula of the UK in 2013. The simulations compare favourably with observed thermodynamic profiles, cloud base cloud droplet number concentrations (CDNC), cloud depth, and radar reflectivity statistics. Including the modification of aerosol fields by cloud microphysical processes improves the correspondence with observed CDNC values and spatial variability, but reduces the agreement with observations for average cloud size and cloud top height. Accumulated precipitation is suppressed for higher-aerosol conditions before clouds become organised along the sea-breeze convergence lines. Changes in precipitation are smaller in simulations with aerosol processing. The precipitation suppression is due to less efficient precipitation production by warm-phase microphysics, consistent with parcel model predictions. In contrast, after convective cells organise along the sea-breeze convergence zone, accumulated precipitation increases with aerosol concentrations. Condensate production increases with the aerosol concentrations due to higher vertical velocities in the convective cores and higher cloud top heights. However, for the highest-aerosol scenarios, no further increase in the condensate production occurs, as clouds grow into an upper-level stable layer. In these cases, the reduced precipitation efficiency (PE) dominates the precipitation response and no further precipitation enhancement occurs. Previous studies of deep convective clouds have related larger vertical velocities under high-aerosol conditions to enhanced latent heating from freezing. In the presented simulations changes in latent heating above the 0°C are negligible, but latent heating from condensation increases with aerosol concentrations. It is hypothesised that this increase is related to changes in the cloud field structure reducing the mixing of environmental air into the convective core. The precipitation response of the deeper mixed-phase clouds along well-established convergence lines can be the opposite of predictions from parcel models. This occurs when clouds interact with a pre-existing thermodynamic environment and cloud field structural changes occur that are not captured by simple parcel model approaches.

Calibration of a convective parameterization scheme in the WRF model and its impact on the simulation of East Asian summer monsoon precipitation

DOE PAGES

Yang, Ben; Zhang, Yaocun; Qian, Yun; ...

2014-03-26

Reasonably modeling the magnitude, south-north gradient and seasonal propagation of precipitation associated with the East Asian Summer Monsoon (EASM) is a challenging task in the climate community. In this study we calibrate five key parameters in the Kain-Fritsch convection scheme in the WRF model using an efficient importance-sampling algorithm to improve the EASM simulation. We also examine the impacts of the improved EASM precipitation on other physical process. Our results suggest similar model sensitivity and values of optimized parameters across years with different EASM intensities. By applying the optimal parameters, the simulated precipitation and surface energy features are generally improved.more » The parameters related to downdraft, entrainment coefficients and CAPE consumption time (CCT) can most sensitively affect the precipitation and atmospheric features. Larger downdraft coefficient or CCT decrease the heavy rainfall frequency, while larger entrainment coefficient delays the convection development but build up more potential for heavy rainfall events, causing a possible northward shift of rainfall distribution. The CCT is the most sensitive parameter over wet region and the downdraft parameter plays more important roles over drier northern region. Long-term simulations confirm that by using the optimized parameters the precipitation distributions are better simulated in both weak and strong EASM years. Due to more reasonable simulated precipitation condensational heating, the monsoon circulations are also improved. Lastly, by using the optimized parameters the biases in the retreating (beginning) of Mei-yu (northern China rainfall) simulated by the standard WRF model are evidently reduced and the seasonal and sub-seasonal variations of the monsoon precipitation are remarkably improved.« less

The Challenge of Identifying Controls on Cloud Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E

DOE PAGES

Mechem, David B.; Giangrande, Scott E.

2018-03-01

Here, the controls on precipitation onset and the transition from shallow cumulus to congestus are explored using a suite of 16 large–eddy simulations based on the 25 May 2011 event from the Midlatitude Continental Convective Clouds Experiment (MC3E). The thermodynamic variables in the model are relaxed at various timescales to observationally constrained temperature and moisture profiles in order to better reproduce the observed behavior of precipitation onset and total precipitation. Three of the simulations stand out as best matching the precipitation observations and also perform well for independent comparisons of cloud fraction, precipitation area fraction, and evolution of cloud topmore » occurrence. All three simulations exhibit a destabilization over time, which leads to a transition to deeper clouds, but the evolution of traditional stability metrics by themselves is not able to explain differences in the simulations. Conditionally sampled cloud properties (in particular, mean cloud buoyancy), however, do elicit differences among the simulations. The inability of environmental profiles alone to discern subtle differences among the simulations and the usefulness of conditionally sampled model quantities argue for hybrid observational/modeling approaches. These combined approaches enable a more complete physical understanding of cloud systems by combining observational sampling of time–varying three–dimensional meteorological quantities and cloud properties, along with detailed representation of cloud microphysical and dynamical processes from numerical models.« less

The Challenge of Identifying Controls on Cloud Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mechem, David B.; Giangrande, Scott E.

Here, the controls on precipitation onset and the transition from shallow cumulus to congestus are explored using a suite of 16 large–eddy simulations based on the 25 May 2011 event from the Midlatitude Continental Convective Clouds Experiment (MC3E). The thermodynamic variables in the model are relaxed at various timescales to observationally constrained temperature and moisture profiles in order to better reproduce the observed behavior of precipitation onset and total precipitation. Three of the simulations stand out as best matching the precipitation observations and also perform well for independent comparisons of cloud fraction, precipitation area fraction, and evolution of cloud topmore » occurrence. All three simulations exhibit a destabilization over time, which leads to a transition to deeper clouds, but the evolution of traditional stability metrics by themselves is not able to explain differences in the simulations. Conditionally sampled cloud properties (in particular, mean cloud buoyancy), however, do elicit differences among the simulations. The inability of environmental profiles alone to discern subtle differences among the simulations and the usefulness of conditionally sampled model quantities argue for hybrid observational/modeling approaches. These combined approaches enable a more complete physical understanding of cloud systems by combining observational sampling of time–varying three–dimensional meteorological quantities and cloud properties, along with detailed representation of cloud microphysical and dynamical processes from numerical models.« less

The Challenge of Identifying Controls on Cloud Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E

NASA Astrophysics Data System (ADS)

Mechem, David B.; Giangrande, Scott E.

2018-03-01

Controls on precipitation onset and the transition from shallow cumulus to congestus are explored using a suite of 16 large-eddy simulations based on the 25 May 2011 event from the Midlatitude Continental Convective Clouds Experiment (MC3E). The thermodynamic variables in the model are relaxed at various timescales to observationally constrained temperature and moisture profiles in order to better reproduce the observed behavior of precipitation onset and total precipitation. Three of the simulations stand out as best matching the precipitation observations and also perform well for independent comparisons of cloud fraction, precipitation area fraction, and evolution of cloud top occurrence. All three simulations exhibit a destabilization over time, which leads to a transition to deeper clouds, but the evolution of traditional stability metrics by themselves is not able to explain differences in the simulations. Conditionally sampled cloud properties (in particular, mean cloud buoyancy), however, do elicit differences among the simulations. The inability of environmental profiles alone to discern subtle differences among the simulations and the usefulness of conditionally sampled model quantities argue for hybrid observational/modeling approaches. These combined approaches enable a more complete physical understanding of cloud systems by combining observational sampling of time-varying three-dimensional meteorological quantities and cloud properties, along with detailed representation of cloud microphysical and dynamical processes from numerical models.

Assessing impacts of PBL and surface layer schemes in simulating the surface–atmosphere interactions and precipitation over the tropical ocean using observations from AMIE/DYNAMO

DOE PAGES

Qian, Yun; Yan, Huiping; Berg, Larry K.; ...

2016-10-28

Accuracy of turbulence parameterization in representing Planetary Boundary Layer (PBL) processes in climate models is critical for predicting the initiation and development of clouds, air quality issues, and underlying surface-atmosphere-cloud interactions. In this study, we 1) evaluate WRF model-simulated spatial patterns of precipitation and surface fluxes, as well as vertical profiles of potential temperature, humidity, moist static energy and moisture tendency terms as simulated by WRF at various spatial resolutions and with PBL, surface layer and shallow convection schemes against measurements, 2) identify model biases by examining the moisture tendency terms contributed by PBL and convection processes through nudging experiments,more » and 3) evaluate the dependence of modeled surface latent heat (LH) fluxes onPBL and surface layer schemes over the tropical ocean. The results show that PBL and surface parameterizations have surprisingly large impacts on precipitation, convection initiation and surface moisture fluxes over tropical oceans. All of the parameterizations tested tend to overpredict moisture in PBL and free atmosphere, and consequently result in larger moist static energy and precipitation. Moisture nudging tends to suppress the initiation of convection and reduces the excess precipitation. The reduction in precipitation bias in turn reduces the surface wind and LH flux biases, which suggests that the model drifts at least partly because of a positive feedback between precipitation and surface fluxes. The updated shallow convection scheme KF-CuP tends to suppress the initiation and development of deep convection, consequently decreasing precipitation. The Eta surface layer scheme predicts more reasonable LH fluxes and the LH-Wind Speed relationship than the MM5 scheme, especially when coupled with the MYJ scheme. By examining various parameterization schemes in WRF, we identify sources of biases and weaknesses of current PBL, surface layer and shallow convection schemes in reproducing PBL processes, the initiation of convection and intra-seasonal variability of precipitation.« less

Impact of Asian Aerosols on Precipitation Over California: An Observational and Model Based Approach

NASA Technical Reports Server (NTRS)

Naeger, Aaron R.; Molthan, Andrew L.; Zavodsky, Bradley T.; Creamean, Jessie M.

2015-01-01

Dust and pollution emissions from Asia are often transported across the Pacific Ocean to over the western United States. Therefore, it is essential to fully understand the impact of these aerosols on clouds and precipitation forming over the eastern Pacific and western United States, especially during atmospheric river events that account for up to half of California's annual precipitation and can lead to widespread flooding. In order for numerical modeling simulations to accurately represent the present and future regional climate of the western United States, we must account for the aerosol-cloud-precipitation interactions associated with Asian dust and pollution aerosols. Therefore, we have constructed a detailed study utilizing multi-sensor satellite observations, NOAA-led field campaign measurements, and targeted numerical modeling studies where Asian aerosols interacted with cloud and precipitation processes over the western United States. In particular, we utilize aerosol optical depth retrievals from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS), NOAA Geostationary Operational Environmental Satellite (GOES-11), and Japan Meteorological Agency (JMA) Multi-functional Transport Satellite (MTSAT) to effectively detect and monitor the trans-Pacific transport of Asian dust and pollution. The aerosol optical depth (AOD) retrievals are used in assimilating the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) in order to provide the model with an accurate representation of the aerosol spatial distribution across the Pacific. We conduct WRF-Chem model simulations of several cold-season atmospheric river events that interacted with Asian aerosols and brought significant precipitation over California during February-March 2011 when the NOAA CalWater field campaign was ongoing. The CalWater field campaign consisted of aircraft and surface measurements of aerosol and precipitation processes that help extensively validate our WRF-Chem model simulations. After validating the capability of the WRF-Chem in realistically simulating the aerosol-cloud precipitation interactions, we conduct sensitivity studies where the AOD is doubled to diagnose whether an increasing concentration of Asian aerosols over the western United States will lead to further impacts on the cloud and precipitation processes over California. We also perform sensitivity studies where the aerosols will be partitioned into dust-only and pollution-only in order to separate the impacts of the differing Asian aerosol species. The results of our WRF-Chem model simulations aim to show that the trans-Pacific transport of Asian aerosols influence the precipitation associated with atmospheric river events that can ultimately impact the regional climate of the western United States. 1 University

Systematic errors in Monsoon simulation: importance of the equatorial Indian Ocean processes

NASA Astrophysics Data System (ADS)

Annamalai, H.; Taguchi, B.; McCreary, J. P., Jr.; Nagura, M.; Miyama, T.

2015-12-01

H. Annamalai1, B. Taguchi2, J.P. McCreary1, J. Hafner1, M. Nagura2, and T. Miyama2 International Pacific Research Center, University of Hawaii, USA Application Laboratory, JAMSTEC, Japan In climate models, simulating the monsoon precipitation climatology remains a grand challenge. Compared to CMIP3, the multi-model-mean (MMM) errors for Asian-Australian monsoon (AAM) precipitation climatology in CMIP5, relative to GPCP observations, have shown little improvement. One of the implications is that uncertainties in the future projections of time-mean changes to AAM rainfall may not have reduced from CMIP3 to CMIP5. Despite dedicated efforts by the modeling community, the progress in monsoon modeling is rather slow. This leads us to wonder: Has the scientific community reached a "plateau" in modeling mean monsoon precipitation? Our focus here is to better understanding of the coupled air-sea interactions, and moist processes that govern the precipitation characteristics over the tropical Indian Ocean where large-scale errors persist. A series idealized coupled model experiments are performed to test the hypothesis that errors in the coupled processes along the equatorial Indian Ocean during inter-monsoon seasons could potentially influence systematic errors during the monsoon season. Moist static energy budget diagnostics has been performed to identify the leading moist and radiative processes that account for the large-scale errors in the simulated precipitation. As a way forward, we propose three coordinated efforts, and they are: (i) idealized coupled model experiments; (ii) process-based diagnostics and (iii) direct observations to constrain model physics. We will argue that a systematic and coordinated approach in the identification of the various interactive processes that shape the precipitation basic state needs to be carried out, and high-quality observations over the data sparse monsoon region are needed to validate models and further improve model physics.

Comparison of spatial interpolation of rainfall with emphasis on extreme events

NASA Astrophysics Data System (ADS)

Amin, Kanwal; Duan, Zheng; Disse, Markus

2017-04-01

The sparse network of rain-gauges has always motivated the scientists to find more robust ways to include the spatial variability of precipitation. Turning Bands Simulation, External Drift Kriging, Copula and Random Mixing are amongst one of them. Remote sensing Technologies i.e., radar and satellite estimations are widely known to provide a spatial profile of the precipitation, however during extreme events the accuracy of the resulted areal precipitation is still under discussion. The aim is to compare the areal hourly precipitation results of a flood event from RADOLAN (Radar online adjustment) with the gridded rainfall obtained via Turning Bands Simulation (TBM) and Inverse Distance Weighting (IDW) method. The comparison is mainly focused on performing the uncertainty analysis of the areal precipitation through the said simulation and remote sensing technique for the Upper Main Catchment. The comparison of the results obtained from TBM, IDW and RADOLAN show considerably similar results near the rain gauge stations, but the degree of ambiguity elevates with the increasing distance from the gauge stations. Future research will be carried out to compare the forecasted gridded precipitation simulations with the real-time rainfall forecast system (RADVOR) to make the flood evacuation process more robust and efficient.

Interdecadal Connection Between Artic Temperature and Summer Precipitation Over the Yangtze River Valley in the CMIP5 Historical Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Yuefeng; Leung, Lai-Yung R.; Xiao, Ziniu

2013-10-01

This study assesses the ability of the Phase 5 Coupled Model Intercomparison Project (CMIP5) simulations in capturing the interdecadal precipitation enhancement over the Yangtze River valley (YRV) and investigates the contributions of Arctic warming to the interdecadal variability of the East Asian summer monsoon rainfall. Six CMIP5 historical simulations including models from Canada (CCCma), China (BCC), Germany (MPI-M), Japan (MRI), United Kingdom (MOHC), and United States (NCAR) are used. The NCEP/NCAR reanalysis and observed precipitation are also used for comparison. Among the six CMIP5 simulations, only CCCma can approximately simulate the enhancement of interdecadal summer precipitation over the YRV inmore » 1990-2005 relative to 1960-1975, and the relationships between the summer precipitation with surface temperature (Ts), the 850hPa winds, and 500hPa height field (H500), and between Ts and H500 using regression, correlation, and SVD analyses. It is found that CCCma can reasonably simulate the interdecadal surface warming over the boreal mid-to high latitudes and the Arctic in winter, spring and summer. The summer Baikal blocking appears to be the bridge that links the winter and spring surface warming over the mid-to high latitude and Arctic with the enhancement of summer precipitation over the YRV. Models that missed some or all of these relationships found in CCCma and the reanalysis failed to simulate the interdecadal enhancement of precipitation over the YRV. This points to the importance of high latitude and Arctic processes on interdecadal variability of the East Asian summer monsoon and the challenge for global climate models to correctly simulate the linkages.« less

Simulations of Precipitate Microstructure Evolution during Heat Treatment

NASA Astrophysics Data System (ADS)

Wu, Kaisheng; Sterner, Gustaf; Chen, Qing; Jou, Herng-Jeng; Jeppsson, Johan; Bratberg, Johan; Engström, Anders; Mason, Paul

Precipitation, a major solid state phase transformation during heat treatment processes, has for more than one century been intensively employed to improve the strength and toughness of various high performance alloys. Recently, sophisticated precipitation reaction models, in assistance with well-developed CALPHAD databases, provide an efficient and cost-effective way to tailor precipitate microstructures that maximize the strengthening effect via the optimization of alloy chemistries and heat treatment schedules. In this presentation, we focus on simulating precipitate microstructure evolution in Nickel-base superalloys under arbitrary heat treatment conditions. The newly-developed TC-PRISMA program has been used for these simulations, with models refined especially for non-isothermal conditions. The effect of different cooling profiles on the formation of multimodal microstructures has been thoroughly examined in order to understand the underlying thermodynamics and kinetics. Meanwhile, validations against several experimental results have been carried out. Practical issues that are critical to the accuracy and applicability of the current simulations, such as modifications that overcome mean-field approximations, compatibility between CALPHAD databases, selection of key parameters (particularly interfacial energy and nucleation site densities), etc., are also addressed.

Simplified data assimilation for simulating wet deposition distribution of radioactive materials in FDNPP accident

NASA Astrophysics Data System (ADS)

Saya, A.; Yoshikane, T.; Chang, E. C.; Yoshimura, K.

2015-12-01

Due to the massive earthquakes and tsunami on March 11th 2011 in Eastern Japan, Fukushima Daiichi Nuclear Power Plant (FDNPP) was severely damaged. Radioactive materials were released and spread out by atmospheric advection-diffusion. Especially on March 21 - 23th when precipitation was observed, "hotspot" where the high concentration was detected locally. This area was formed in the metropolitan area in Kanto region. Thus, pollution at water treatment plants because of the deposition became a concern. Therefore, the reliable information of the hotspot is expected. Currently, atmospheric transport simulations by numerical models are developed for reproduction of the distribution. However, there are some uncertainties in the simulations. In the case of hotspot, accuracy of simulated precipitation have to be well considered because the hotspot seemed to be formed by wet deposition. We modified the stable isotope mode of Regional Spectral Model (IsoRSM) to enable to simulate the transport of the radioactive tracers, namely 131I and 137Cs, by including the dry and wet deposition processes. As the simplified data assimilation, simulated precipitation was replaced with Radar-AMeDAS precipitation data (RAP). RAP was assimilated in the post-process, after running simulations, to redistribute wet deposition of 137Cs. The ratio of 137Cs deposited from the cumulative vertical column with precipitation in the domain was not changed, however its pattern was redistributed corresponding with RAP and simulated concentration. As a result, the redistributed wet deposition was within factor 10 to 2 compared with the fallout data in Kanto region, and further data assimilation would be contributed. In addition, we found that due to the arrival time of the plume in the morning on 21st and the border time of daily observation data of fallout, validation result might be worse even though hourly distributions are well simulated.

Evaluation of the HadGEM3-A simulations in view of detection and attribution of human influence on extreme events in Europe

NASA Astrophysics Data System (ADS)

Vautard, Robert; Christidis, Nikolaos; Ciavarella, Andrew; Alvarez-Castro, Carmen; Bellprat, Omar; Christiansen, Bo; Colfescu, Ioana; Cowan, Tim; Doblas-Reyes, Francisco; Eden, Jonathan; Hauser, Mathias; Hegerl, Gabriele; Hempelmann, Nils; Klehmet, Katharina; Lott, Fraser; Nangini, Cathy; Orth, René; Radanovics, Sabine; Seneviratne, Sonia I.; van Oldenborgh, Geert Jan; Stott, Peter; Tett, Simon; Wilcox, Laura; Yiou, Pascal

2018-04-01

A detailed analysis is carried out to assess the HadGEM3-A global atmospheric model skill in simulating extreme temperatures, precipitation and storm surges in Europe in the view of their attribution to human influence. The analysis is performed based on an ensemble of 15 atmospheric simulations forced with observed sea surface temperature of the 54 year period 1960-2013. These simulations, together with dual simulations without human influence in the forcing, are intended to be used in weather and climate event attribution. The analysis investigates the main processes leading to extreme events, including atmospheric circulation patterns, their links with temperature extremes, land-atmosphere and troposphere-stratosphere interactions. It also compares observed and simulated variability, trends and generalized extreme value theory parameters for temperature and precipitation. One of the most striking findings is the ability of the model to capture North-Atlantic atmospheric weather regimes as obtained from a cluster analysis of sea level pressure fields. The model also reproduces the main observed weather patterns responsible for temperature and precipitation extreme events. However, biases are found in many physical processes. Slightly excessive drying may be the cause of an overestimated summer interannual variability and too intense heat waves, especially in central/northern Europe. However, this does not seem to hinder proper simulation of summer temperature trends. Cold extremes appear well simulated, as well as the underlying blocking frequency and stratosphere-troposphere interactions. Extreme precipitation amounts are overestimated and too variable. The atmospheric conditions leading to storm surges were also examined in the Baltics region. There, simulated weather conditions appear not to be leading to strong enough storm surges, but winds were found in very good agreement with reanalyses. The performance in reproducing atmospheric weather patterns indicates that biases mainly originate from local and regional physical processes. This makes local bias adjustment meaningful for climate change attribution.

MJO simulation in CMIP5 climate models: MJO skill metrics and process-oriented diagnosis

NASA Astrophysics Data System (ADS)

Ahn, Min-Seop; Kim, Daehyun; Sperber, Kenneth R.; Kang, In-Sik; Maloney, Eric; Waliser, Duane; Hendon, Harry

2017-12-01

The Madden-Julian Oscillation (MJO) simulation diagnostics developed by MJO Working Group and the process-oriented MJO simulation diagnostics developed by MJO Task Force are applied to 37 Coupled Model Intercomparison Project phase 5 (CMIP5) models in order to assess model skill in representing amplitude, period, and coherent eastward propagation of the MJO, and to establish a link between MJO simulation skill and parameterized physical processes. Process-oriented diagnostics include the Relative Humidity Composite based on Precipitation (RHCP), Normalized Gross Moist Stability (NGMS), and the Greenhouse Enhancement Factor (GEF). Numerous scalar metrics are developed to quantify the results. Most CMIP5 models underestimate MJO amplitude, especially when outgoing longwave radiation (OLR) is used in the evaluation, and exhibit too fast phase speed while lacking coherence between eastward propagation of precipitation/convection and the wind field. The RHCP-metric, indicative of the sensitivity of simulated convection to low-level environmental moisture, and the NGMS-metric, indicative of the efficiency of a convective atmosphere for exporting moist static energy out of the column, show robust correlations with a large number of MJO skill metrics. The GEF-metric, indicative of the strength of the column-integrated longwave radiative heating due to cloud-radiation interaction, is also correlated with the MJO skill metrics, but shows relatively lower correlations compared to the RHCP- and NGMS-metrics. Our results suggest that modifications to processes associated with moisture-convection coupling and the gross moist stability might be the most fruitful for improving simulations of the MJO. Though the GEF-metric exhibits lower correlations with the MJO skill metrics, the longwave radiation feedback is highly relevant for simulating the weak precipitation anomaly regime that may be important for the establishment of shallow convection and the transition to deep convection.

MJO simulation in CMIP5 climate models: MJO skill metrics and process-oriented diagnosis

DOE PAGES

Ahn, Min-Seop; Kim, Daehyun; Sperber, Kenneth R.; ...

2017-03-23

The Madden-Julian Oscillation (MJO) simulation diagnostics developed by MJO Working Group and the process-oriented MJO simulation diagnostics developed by MJO Task Force are applied to 37 Coupled Model Intercomparison Project phase 5 (CMIP5) models in order to assess model skill in representing amplitude, period, and coherent eastward propagation of the MJO, and to establish a link between MJO simulation skill and parameterized physical processes. Process-oriented diagnostics include the Relative Humidity Composite based on Precipitation (RHCP), Normalized Gross Moist Stability (NGMS), and the Greenhouse Enhancement Factor (GEF). Numerous scalar metrics are developed to quantify the results. Most CMIP5 models underestimate MJOmore » amplitude, especially when outgoing longwave radiation (OLR) is used in the evaluation, and exhibit too fast phase speed while lacking coherence between eastward propagation of precipitation/convection and the wind field. The RHCP-metric, indicative of the sensitivity of simulated convection to low-level environmental moisture, and the NGMS-metric, indicative of the efficiency of a convective atmosphere for exporting moist static energy out of the column, show robust correlations with a large number of MJO skill metrics. The GEF-metric, indicative of the strength of the column-integrated longwave radiative heating due to cloud-radiation interaction, is also correlated with the MJO skill metrics, but shows relatively lower correlations compared to the RHCP- and NGMS-metrics. Our results suggest that modifications to processes associated with moisture-convection coupling and the gross moist stability might be the most fruitful for improving simulations of the MJO. Though the GEF-metric exhibits lower correlations with the MJO skill metrics, the longwave radiation feedback is highly relevant for simulating the weak precipitation anomaly regime that may be important for the establishment of shallow convection and the transition to deep convection.« less

MJO simulation in CMIP5 climate models: MJO skill metrics and process-oriented diagnosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahn, Min-Seop; Kim, Daehyun; Sperber, Kenneth R.

The Madden-Julian Oscillation (MJO) simulation diagnostics developed by MJO Working Group and the process-oriented MJO simulation diagnostics developed by MJO Task Force are applied to 37 Coupled Model Intercomparison Project phase 5 (CMIP5) models in order to assess model skill in representing amplitude, period, and coherent eastward propagation of the MJO, and to establish a link between MJO simulation skill and parameterized physical processes. Process-oriented diagnostics include the Relative Humidity Composite based on Precipitation (RHCP), Normalized Gross Moist Stability (NGMS), and the Greenhouse Enhancement Factor (GEF). Numerous scalar metrics are developed to quantify the results. Most CMIP5 models underestimate MJOmore » amplitude, especially when outgoing longwave radiation (OLR) is used in the evaluation, and exhibit too fast phase speed while lacking coherence between eastward propagation of precipitation/convection and the wind field. The RHCP-metric, indicative of the sensitivity of simulated convection to low-level environmental moisture, and the NGMS-metric, indicative of the efficiency of a convective atmosphere for exporting moist static energy out of the column, show robust correlations with a large number of MJO skill metrics. The GEF-metric, indicative of the strength of the column-integrated longwave radiative heating due to cloud-radiation interaction, is also correlated with the MJO skill metrics, but shows relatively lower correlations compared to the RHCP- and NGMS-metrics. Our results suggest that modifications to processes associated with moisture-convection coupling and the gross moist stability might be the most fruitful for improving simulations of the MJO. Though the GEF-metric exhibits lower correlations with the MJO skill metrics, the longwave radiation feedback is highly relevant for simulating the weak precipitation anomaly regime that may be important for the establishment of shallow convection and the transition to deep convection.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsigabu Gebrehiwet; James R. Henriksen; Luanjing Guo

Multi-component mineral precipitation in porous, subsurface environments is challenging to simulate or engineer when in situ reactant mixing is controlled by diffusion. In contrast to well-mixed systems, the conditions that favor mineral precipitation in porous media are distributed along chemical gradients, which evolve spatially due to concurrent mineral precipitation and modification of solute transport in the media. The resulting physical and chemical characteristics of a mixing/precipitation zone are a consequence of coupling between transport and chemical processes, and the distinctive properties of individual chemical systems. We examined the spatial distribution of precipitates formed in “double diffusion” columns for two chemicalmore » systems, calcium carbonate and calcium phosphate. Polyacrylamide hydrogel was used as a low permeability, high porosity medium to maximize diffusive mixing and minimize pressure- and density-driven flow between reactant solutions. In the calcium phosphate system, multiple, visually dense and narrow bands of precipitates were observed that were reminiscent of previously reported Liesegang patterns. In the calcium carbonate system, wider precipitation zones characterized by more sparse distributions of precipitates and a more open channel structure were observed. In both cases, formation of precipitates inhibited, but did not necessarily eliminate, continued transport and mixing of the reactants. A reactive transport model with fully implicit coupling between diffusion, chemical speciation and precipitation kinetics, but where explicit details of nucleation processes were neglected, was able to qualitatively simulate properties of the precipitation zones. The results help to illustrate how changes in the physical properties of a precipitation zone depend on coupling between diffusion-controlled reactant mixing and chemistry-specific details of precipitation kinetics.« less

Assessing the applicability of WRF optimal parameters under the different precipitation simulations in the Greater Beijing Area

NASA Astrophysics Data System (ADS)

Di, Zhenhua; Duan, Qingyun; Wang, Chen; Ye, Aizhong; Miao, Chiyuan; Gong, Wei

2018-03-01

Forecasting skills of the complex weather and climate models have been improved by tuning the sensitive parameters that exert the greatest impact on simulated results based on more effective optimization methods. However, whether the optimal parameter values are still work when the model simulation conditions vary, which is a scientific problem deserving of study. In this study, a highly-effective optimization method, adaptive surrogate model-based optimization (ASMO), was firstly used to tune nine sensitive parameters from four physical parameterization schemes of the Weather Research and Forecasting (WRF) model to obtain better summer precipitation forecasting over the Greater Beijing Area in China. Then, to assess the applicability of the optimal parameter values, simulation results from the WRF model with default and optimal parameter values were compared across precipitation events, boundary conditions, spatial scales, and physical processes in the Greater Beijing Area. The summer precipitation events from 6 years were used to calibrate and evaluate the optimal parameter values of WRF model. Three boundary data and two spatial resolutions were adopted to evaluate the superiority of the calibrated optimal parameters to default parameters under the WRF simulations with different boundary conditions and spatial resolutions, respectively. Physical interpretations of the optimal parameters indicating how to improve precipitation simulation results were also examined. All the results showed that the optimal parameters obtained by ASMO are superior to the default parameters for WRF simulations for predicting summer precipitation in the Greater Beijing Area because the optimal parameters are not constrained by specific precipitation events, boundary conditions, and spatial resolutions. The optimal values of the nine parameters were determined from 127 parameter samples using the ASMO method, which showed that the ASMO method is very highly-efficient for optimizing WRF model parameters.

Mapping the Impact of Aerosol-Cloud Interactions on Cloud Formation and Warm-season Rainfall in Mountainous Regions Using Observations and Models

NASA Astrophysics Data System (ADS)

Duan, Yajuan

Light rainfall (< 3 mm/hr) amounts to 30-70% of the annual water budget in the Southern Appalachian Mountains (SAM), a mid-latitude mid-mountain system in the SE CONUS. Topographic complexity favors the diurnal development of regional-scale convergence patterns that provide the moisture source for low-level clouds and fog (LLCF). Low-level moisture and cloud condensation nuclei (CCN) are distributed by ridge-valley circulations favoring LLCF formation that modulate the diurnal cycle of rainfall especially the mid-day peak. The overarching objective of this dissertation is to advance the quantitative understanding of the indirect effect of aerosols on the diurnal cycle of LLCF and warm-season precipitation in mountainous regions generally, and in the SAM in particular, for the purpose of improving the representation of orographic precipitation processes in remote sensing retrievals and physically-based models. The research approach consists of integrating analysis of in situ observations from long-term observation networks and an intensive field campaign, multi-sensor satellite data, and modeling studies. In the first part of this dissertation, long-term satellite observations are analyzed to characterize the spatial and temporal variability of LLCF and to elucidate the physical basis of the space-time error structure in precipitation retrievals. Significantly underestimated precipitation errors are attributed to variations in low-level rainfall microstructure undetected by satellites. Column model simulations including observed LLCF microphysics demonstrate that seeder-feeder interactions (SFI) among upper-level precipitation and LLCF contribute to an three-fold increase in observed rainfall accumulation and can enhance surface rainfall by up to ten-fold. The second part of this dissertation examines the indirect effect of aerosols on cloud formation and warm-season daytime precipitation in the SAM. A new entraining spectral cloud parcel model was developed and applied to provide the first assessment of aerosol-cloud interactions in the early development of mid-day cumulus congestus over the inner SAM. Leveraging comprehensive measurements from the Integrated Precipitation and Hydrology Experiment (IPHEx) in 2014, model results indicate that simulated spectra with a low value of condensation coefficient (0.01) are in good agreement with IPHEx aircraft observations. Further, to explore sensitivity of warm-season precipitation processes to CCN characteristics, detailed intercomparisons of Weather Research and Forecasting (WRF) model simulations using IPHEx and standard continental CCN spectra were conducted. The simulated CDNC using the local spectrum show better agreement with IPHEx airborne observations and better replicate the widespread low-level cloudiness around mid-day over the inner region. The local spectrum simulation also indicate suppressed early precipitation, enhanced ice processes tied to more vigorous vertical development of individual storm cells. The studied processes here are representative of dominant moist atmospheric processes in complex terrain and cloud forests in the humid tropics and extra-tropics, thus findings from this research in the SAM are transferable to mountainous areas elsewhere.

Towards an improved ensemble precipitation forecast: A probabilistic post-processing approach

NASA Astrophysics Data System (ADS)

Khajehei, Sepideh; Moradkhani, Hamid

2017-03-01

Recently, ensemble post-processing (EPP) has become a commonly used approach for reducing the uncertainty in forcing data and hence hydrologic simulation. The procedure was introduced to build ensemble precipitation forecasts based on the statistical relationship between observations and forecasts. More specifically, the approach relies on a transfer function that is developed based on a bivariate joint distribution between the observations and the simulations in the historical period. The transfer function is used to post-process the forecast. In this study, we propose a Bayesian EPP approach based on copula functions (COP-EPP) to improve the reliability of the precipitation ensemble forecast. Evaluation of the copula-based method is carried out by comparing the performance of the generated ensemble precipitation with the outputs from an existing procedure, i.e. mixed type meta-Gaussian distribution. Monthly precipitation from Climate Forecast System Reanalysis (CFS) and gridded observation from Parameter-Elevation Relationships on Independent Slopes Model (PRISM) have been employed to generate the post-processed ensemble precipitation. Deterministic and probabilistic verification frameworks are utilized in order to evaluate the outputs from the proposed technique. Distribution of seasonal precipitation for the generated ensemble from the copula-based technique is compared to the observation and raw forecasts for three sub-basins located in the Western United States. Results show that both techniques are successful in producing reliable and unbiased ensemble forecast, however, the COP-EPP demonstrates considerable improvement in the ensemble forecast in both deterministic and probabilistic verification, in particular in characterizing the extreme events in wet seasons.

The Diurnal Cycle in TOGA-COARE: Regional Scale Model Simulations

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Jia, Y.

1999-01-01

The diurnal variation of precipitation processes over the tropics is a well-known phenomenon and has been studied using surface rainfall data, radar reflectivity data, and satellite-derived cloudiness and precipitation. Recently, analyzed observations from Tropical Oceans and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) in the tropical western Pacific ocean to study the relevant mechanisms producing diurnal variation of precipitation. They found that the diurnal Sea surface temperature (SST) cycle is important for afternoon showers in the undisturbed periods and diurnal radiative processes for nocturnal rainfall. Cloud resolving models (CRMS) have been used to determine the mechanisms associated with diurnal variation of precipitating processes. CRMs allow explicit cloud-radiation and air-sea interactive processes. However, CRMs can be only used for idealized simulations (i.e., no feedback between clouds and their embedded large-scale environments; cyclic lateral boundary conditions and idealized initial conditions). In this study, the Penn State/NCAR Mesoscale Model (MM5) with improved physics (i.e., cloud microphysics, radiation, land-soil-vegetation-surface processes, and TOGA COARE flux scheme) and a multiple level nesting technique (covers the TOGA COARE LSA/IFA with a 54 km grid and can nest down to 18, 6 and possibly even 2 km) will be adopted for studying the diurnal variations of rainfall. We will examine precipitation processes over open ocean and over land. We will also perform sensitivity tests to determine how the radiative forcing and diurnal SST cycle affects the development of convection.

Development of An Advanced JP-8 Fuel

DTIC Science & Technology

1993-12-01

included the Microthermal Precipitation Test (MTP), Fuel Reactor Test, Hot Liquid Process Simulator (HLPS), and Isothermal Corrosion Oxidation Test (ICOT... Microthermal Precipitation Test The impetus for this development effort was the need for a screening test that could discriminate between fuels of...varying propensity to produce thermally induced insoluble particulate material in the bulk fuel. The Microthermal Precipitation (MTP) test thermally

PRMS-IV, the precipitation-runoff modeling system, version 4

USGS Publications Warehouse

Markstrom, Steven L.; Regan, R. Steve; Hay, Lauren E.; Viger, Roland J.; Webb, Richard M.; Payn, Robert A.; LaFontaine, Jacob H.

2015-01-01

Computer models that simulate the hydrologic cycle at a watershed scale facilitate assessment of variability in climate, biota, geology, and human activities on water availability and flow. This report describes an updated version of the Precipitation-Runoff Modeling System. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of various combinations of climate and land use on streamflow and general watershed hydrology. Several new model components were developed, and all existing components were updated, to enhance performance and supportability. This report describes the history, application, concepts, organization, and mathematical formulation of the Precipitation-Runoff Modeling System and its model components. This updated version provides improvements in (1) system flexibility for integrated science, (2) verification of conservation of water during simulation, (3) methods for spatial distribution of climate boundary conditions, and (4) methods for simulation of soil-water flow and storage.

Numerical investigation of coupled density-driven flow and hydrogeochemical processes below playas

NASA Astrophysics Data System (ADS)

Hamann, Enrico; Post, Vincent; Kohfahl, Claus; Prommer, Henning; Simmons, Craig T.

2015-11-01

Numerical modeling approaches with varying complexity were explored to investigate coupled groundwater flow and geochemical processes in saline basins. Long-term model simulations of a playa system gain insights into the complex feedback mechanisms between density-driven flow and the spatiotemporal patterns of precipitating evaporites and evolving brines. Using a reactive multicomponent transport model approach, the simulations reproduced, for the first time in a numerical study, the evaporite precipitation sequences frequently observed in saline basins ("bull's eyes"). Playa-specific flow, evapoconcentration, and chemical divides were found to be the primary controls for the location of evaporites formed, and the resulting brine chemistry. Comparative simulations with the computationally far less demanding surrogate single-species transport models showed that these were still able to replicate the major flow patterns obtained by the more complex reactive transport simulations. However, the simulated degree of salinization was clearly lower than in reactive multicomponent transport simulations. For example, in the late stages of the simulations, when the brine becomes halite-saturated, the nonreactive simulation overestimated the solute mass by almost 20%. The simulations highlight the importance of the consideration of reactive transport processes for understanding and quantifying geochemical patterns, concentrations of individual dissolved solutes, and evaporite evolution.

A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

NASA Astrophysics Data System (ADS)

Tao, W. K.

2017-12-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

P2S--Coupled simulation with the Precipitation-Runoff Modeling System (PRMS) and the Stream Temperature Network (SNTemp) Models

USGS Publications Warehouse

Markstrom, Steven L.

2012-01-01

A software program, called P2S, has been developed which couples the daily stream temperature simulation capabilities of the U.S. Geological Survey Stream Network Temperature model with the watershed hydrology simulation capabilities of the U.S. Geological Survey Precipitation-Runoff Modeling System. The Precipitation-Runoff Modeling System is a modular, deterministic, distributed-parameter, physical-process watershed model that simulates hydrologic response to various combinations of climate and land use. Stream Network Temperature was developed to help aquatic biologists and engineers predict the effects of changes that hydrology and energy have on water temperatures. P2S will allow scientists and watershed managers to evaluate the effects of historical climate and projected climate change, landscape evolution, and resource management scenarios on watershed hydrology and in-stream water temperature.

On the potential influence of ice nuclei on surface-forced marine stratocumulus cloud dynamics

NASA Astrophysics Data System (ADS)

Harrington, Jerry Y.; Olsson, Peter Q.

2001-11-01

The mixed phase cloudy boundary layer that occurs during off-ice flow in the marine Arctic was simulated in an environment with a strong surface heat flux (nearly 800 W m-2). A two-dimensional, eddy-resolving model coupled to a detailed cloud microphysical model was used to study both liquid phase and mixed phase stratocumulus clouds and boundary layer (BL) dynamics in this environment. Since ice precipitation may be important to BL dynamics, and ice nuclei (IN) concentrations modulate ice precipitation rates, the role of IN in cloud and BL development was explored. The results of several simulations illustrate how mixed phase microphysical processes affect the evolution of the cloudy BL in this environment. In agreement with past studies, BLs with mixed phase clouds had weaker convection, shallower BL depths, and smaller cloud fractions than BLs with clouds restricted to the liquid phase only. It is shown that the weaker BL convection is due to strong ice precipitation. Ice precipitation reduces convective strength directly by stabilizing downdrafts and more indirectly by sensibly heating the BL and inhibiting vertical mixing of momentum thereby reducing surface heat fluxes by as much as 80 W m-2. This feedback between precipitation and surface fluxes was found to have a significant impact on cloud/BL morphology, producing oscillations in convective strength and cloud fraction that did not occur if surface fluxes were fixed at constant values. Increases in IN concentrations in mixed phase clouds caused a more rapid Bergeron-Findeisen process leading to larger precipitation fluxes, reduced convection and lower cloud fraction. When IN were removed from the BL through precipitation, fewer crystals were nucleated at later simulation times leading to progressively weaker precipitation rates, greater cloud fraction, and stronger convective BL eddies.

Analysis of precipitation teleconnections in CMIP models as a measure of model fidelity in simulating precipitation

NASA Astrophysics Data System (ADS)

Langenbrunner, B.; Neelin, J.; Meyerson, J.

2011-12-01

The accurate representation of precipitation is a recurring issue in global climate models, especially in the tropics. Poor skill in modeling the variability and climate teleconnections associated with El Niño/Southern Oscillation (ENSO) also persisted in the latest Climate Model Intercomparison Project (CMIP) campaigns. Observed ENSO precipitation teleconnections provide a standard by which we can judge a given model's ability to reproduce precipitation and dynamic feedback processes originating in the tropical Pacific. Using CMIP3 Atmospheric Model Intercomparison Project (AMIP) runs as a baseline, we compare precipitation teleconnections between models and observations, and we evaluate these results against available CMIP5 historical and AMIP runs. Using AMIP simulations restricts evaluation to the atmospheric response, as sea surface temperatures (SSTs) in AMIP are prescribed by observations. We use a rank correlation between ENSO SST indices and precipitation to define teleconnections, since this method is robust to outliers and appropriate for non-Gaussian data. Spatial correlations of the modeled and observed teleconnections are then evaluated. We look at these correlations in regions of strong precipitation teleconnections, including equatorial S. America, the "horseshoe" region in the western tropical Pacific, and southern N. America. For each region and season, we create a "normalized projection" of a given model's teleconnection pattern onto that of the observations, a metric that assesses the quality of regional pattern simulations while rewarding signals of correct sign over the region. Comparing this to an area-averaged (i.e., more generous) metric suggests models do better when restrictions on exact spatial dependence are loosened and conservation constraints apply. Model fidelity in regional measures remains far from perfect, suggesting intrinsic issues with the models' regional sensitivities in moist processes.

Intensive precipitation observation greatly improves hydrological modelling of the poorly gauged high mountain Mabengnong catchment in the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Wang, Li; Zhang, Fan; Zhang, Hongbo; Scott, Christopher A.; Zeng, Chen; Shi, Xiaonan

2018-01-01

Precipitation is one of the most critical inputs for models used to improve understanding of hydrological processes. In high mountain areas, it is challenging to generate a reliable precipitation data set capturing the spatial and temporal heterogeneity due to the harsh climate, extreme terrain and the lack of observations. This study conducts intensive observation of precipitation in the Mabengnong catchment in the southeast of the Tibetan Plateau during July to August 2013. Because precipitation is greatly influenced by altitude, the observed data are used to characterize the precipitation gradient (PG) and hourly distribution (HD), showing that the average PG is 0.10, 0.28 and 0.26 mm/d/100 m and the average duration is around 0.1, 0.8 and 5.2 h for trace, light and moderate rain, respectively. A distributed biosphere hydrological model based on water and energy budgets with improved physical process for snow (WEB-DHM-S) is applied to simulate the hydrological processes with gridded precipitation data derived from a lower altitude meteorological station and the PG and HD characterized for the study area. The observed runoff, MODIS/Terra snow cover area (SCA) data, and MODIS/Terra land surface temperature (LST) data are used for model calibration and validation. Runoff, SCA and LST simulations all show reasonable results. Sensitivity analyses illustrate that runoff is largely underestimated without considering PG, indicating that short-term intensive precipitation observation has the potential to greatly improve hydrological modelling of poorly gauged high mountain catchments.

Monte-Carlo simulation of defect-cluster nucleation in metals during irradiation

NASA Astrophysics Data System (ADS)

Nakasuji, Toshiki; Morishita, Kazunori; Ruan, Xiaoyong

2017-02-01

A multiscale modeling approach was applied to investigate the nucleation process of CRPs (copper rich precipitates, i.e., copper-vacancy clusters) in α-Fe containing 1 at.% Cu during irradiation. Monte-Carlo simulations were performed to investigate the nucleation process, with the rate theory equation analysis to evaluate the concentration of displacement defects, along with the molecular dynamics technique to know CRP thermal stabilities in advance. Our MC simulations showed that there is long incubation period at first, followed by a rapid growth of CRPs. The incubation period depends on irradiation conditions such as the damage rate and temperature. CRP's composition during nucleation varies with time. The copper content of CRPs shows relatively rich at first, and then becomes poorer as the precipitate size increases. A widely-accepted model of CRP nucleation process is finally proposed.

Diurnal cycle of precipitation at Dakar in the model LMDZ

NASA Astrophysics Data System (ADS)

Sane, Y.; Bonazzola, M.; Hourdin, F.; Diongue-Niang, A.

2009-04-01

Most diurnal cycles of precipitation are not well represented in general circulation models (GCMs). It is a concern for climate modeling because of the key role of clouds in the radiative and water budgets. The diurnal phasing of deep convection is a challenge, the pact of deep convection being generally simulated too early in the day (Guichard et al., 2004). Thus a "thermal plume model" - a mass flux scheme combined with a classical diffusive approach - originally developed to represent turbulent transport in the dry convective boundary layer, is extented to the representation of cloud processes. The modified parametrization was validated in a 1D configuration against results of large eddy simulations (Rio, 2008). It is here validated in a 3D configuration against in situ precipitation measurements of the AMMA campaign. A data analysis of the diurnal cycle of precipitation as measured by the pluviometers net in the Dakar area is performed. The improvement of the diurnal cyle of convection in the GCM is demonstrated, and the involved processes are analysed.

Scale Dependence of Land Atmosphere Interactions in Wet and Dry Regions as Simulated with NU-WRF over the Southwestern and Southeast US

NASA Technical Reports Server (NTRS)

Zhou, Yaping; Wu, Di; Lau, K.- M.; Tao, Wei-Kuo

2016-01-01

Large-scale forcing and land-atmosphere interactions on precipitation are investigated with NASA-Unified WRF (NU-WRF) simulations during fast transitions of ENSO phases from spring to early summer of 2010 and 2011. The model is found to capture major precipitation episodes in the 3-month simulations without resorting to nudging. However, the mean intensity of the simulated precipitation is underestimated by 46% and 57% compared with the observations in dry and wet regions in the southwestern and south-central United States, respectively. Sensitivity studies show that large-scale atmospheric forcing plays a major role in producing regional precipitation. A methodology to account for moisture contributions to individual precipitation events, as well as total precipitation, is presented under the same moisture budget framework. The analysis shows that the relative contributions of local evaporation and large-scale moisture convergence depend on the dry/wet regions and are a function of temporal and spatial scales. While the ratio of local and large-scale moisture contributions vary with domain size and weather system, evaporation provides a major moisture source in the dry region and during light rain events, which leads to greater sensitivity to soil moisture in the dry region and during light rain events. The feedback of land surface processes to large-scale forcing is well simulated, as indicated by changes in atmospheric circulation and moisture convergence. Overall, the results reveal an asymmetrical response of precipitation events to soil moisture, with higher sensitivity under dry than wet conditions. Drier soil moisture tends to suppress further existing below-normal precipitation conditions via a positive soil moisture-land surface flux feedback that could worsen drought conditions in the southwestern United States.

The response of a simulated Mesoscale Convective System to increased aerosol pollution

NASA Astrophysics Data System (ADS)

Clavner, Michal

This work focuses on the impacts of aerosols on the total precipitation amount, rates and spatial distribution of precipitation produced by a Mesoscale Convective System (MCS), as well as the characteristics of a derecho event. Past studies have shown that the impacts on MCS-produced precipitation to changes in aerosol concentration are strongly dependent on environmental conditions, primarily humidity and environmental wind shear. Changes in aerosol concentrations were found to alter MCS-precipitation production directly by modifying precipitation processes and indirectly by affecting the efficiency of the storm's self-propagation. Observational and numerical studies have been conducted that have examined the dynamics responsible for the generation of widespread convectively-induced windstorms, primarily focusing on environmental conditions and the MCS features that generate a derecho event. While the sensitivity of the formation of bow-echoes, the radar signature associated with derecho events, to changes in microphysics has been examined, a study on a derecho-producing MCS characteristics to aerosol concentrations has not. In this study different aerosol concentrations and their effects on precipitation and a derecho produced by an MCS are examined by simulating the 8 May 2009 "Super-Derecho" MCS. The MCS was simulated using the Regional Atmospheric Modeling System (RAMS), a cloud-resolving model (CRM) with sophisticated aerosol and microphysical parameterizations. Three simulations were conducted that varied in their initial aerosol concentration, distribution and hygroscopicity as determined by their emission sources. The first simulation contained aerosols from only natural sources and the second with aerosols sourced from both natural and anthropogenic emissions The third simulation contained the same aerosol distribution as in the second simulation, however multiplied by a factor of 5 in order to represent a highly polluted scenario. In all three of the simulations aerosol concentrations were derived from the output of GEOS-Chem, a 3D chemical transport model. In the simulated MCS, the formation and propagation of the storm was not fundamentally modified by changes in the aerosol concentration, and the total MCS-produced precipitation was not significantly affected. However, the precipitation distribution (convective vs stratiform) and derecho-strength surface wind characteristics did vary among the simulations. The more polluted simulations exhibited higher precipitation rates, higher bulk precipitation efficiency, a larger area with heavier convective precipitation and a smaller area with lighter stratiform precipitation. These differences arose because aerosol pollution enhanced precipitation in the convective region while suppressing precipitation from the stratiform-anvil. Higher aerosol concentrations led to the invigoration of convective updrafts which supported the formation of larger rain drops, and lofted more liquid cloud mass to higher levels, thereby increasing both collision-coalescence and riming processes. The presence of greater aerosol concentrations in the free troposphere, as well as in the boundary layer, reduced both collision-coalescence and riming within the stratiform-anvil region. As a consequence, the more polluted simulations produced the smallest precipitation from the MCS stratiform-anvil region. In order to understand the impact of changes in aerosol concentrations on the derecho characteristics, the dynamical processes which produced the strong surface wind were determined by performing back-trajectory analysis during different periods of the simulated storm. The analysis showed that two main air flows contributed to the formation of the derecho winds at the surface; a rear-inflow jet and an up-down downdraft associated with a mesovortex at the gust font. The changes in aerosol concentrations impacted the simulated derecho event by altering the main flow contributing to the formation of the derecho winds though the amount of melting and evaporation of hydrometeors. Earlier in the storm, changes in melting and evaporation altered the intensity of the storm-produced cold pool. This, in turn, modified the balance between the horizontal relative vertical vorticity generated by the cold pool and that of the low-level environmental shear. The smaller hail and rain hydrometeors in the cleaner simulation exhibited higher melting and evaporation rates due to the larger surface area, which contributed to the formation of a stronger cold pool and led to the tilting of the convective updraft upshear. This, in turn, shifted the flow associated with the derecho event to be predominantly from a Rear-Inflow Jet (RIJ). An increase in aerosol concentration led to a weaker cold pool and therefore an upright convective updraft which promoted the formation of a stronger mesovortex, and subsequently shifting the flow to be predominantly from strong downdrafts following an up-down downdraft (UDD) trajectory. The shift from a RIJ flow to a UDD led to stronger surface winds over a smaller area. As the storm matured, the derecho winds were found to be associated with the formation of a mesovortex at the gust front. At this time, a non-linear trend between aerosol concentrations to derecho intensity was apparent and was attributed to the non-linear trend in mesovortex strength. (Abstract shortened by UMI.).

Uncertain soil moisture feedbacks in model projections of Sahel precipitation

NASA Astrophysics Data System (ADS)

Berg, Alexis; Lintner, Benjamin R.; Findell, Kirsten; Giannini, Alessandra

2017-06-01

Given the uncertainties in climate model projections of Sahel precipitation, at the northern edge of the West African Monsoon, understanding the factors governing projected precipitation changes in this semiarid region is crucial. This study investigates how long-term soil moisture changes projected under climate change may feedback on projected changes of Sahel rainfall, using simulations with and without soil moisture change from five climate models participating in the Global Land Atmosphere Coupling Experiment-Coupled Model Intercomparison Project phase 5 experiment. In four out of five models analyzed, soil moisture feedbacks significantly influence the projected West African precipitation response to warming; however, the sign of these feedbacks differs across the models. These results demonstrate that reducing uncertainties across model projections of the West African Monsoon requires, among other factors, improved mechanistic understanding and constraint of simulated land-atmosphere feedbacks, even at the large spatial scales considered here.