National Center for Environmental Prediction

Camp Springs, MD, United States

National Center for Environmental Prediction

Camp Springs, MD, United States
Time filter
Source Type

Marti A.,Barcelona Supercomputing Center | Folch A.,Barcelona Supercomputing Center | Jorba O.,Barcelona Supercomputing Center | Janjic Z.,National Center for Environmental Prediction
Atmospheric Chemistry and Physics | Year: 2017

Traditionally, tephra transport and dispersal models have evolved decoupled (offline) from numerical weather prediction models. There is a concern that inconsistencies and shortcomings associated with this coupling strategy might lead to errors in the ash cloud forecast. Despite this concern and the significant progress in improving the accuracy of tephra dispersal models in the aftermath of the 2010 Eyjafjallajökull and 2011 Cordón Caulle eruptions, to date, no operational online dispersal model is available to forecast volcanic ash. Here, we describe and evaluate NMMB-MONARCH-ASH, a new online multi-scale meteorological and transport model that attempts to pioneer the forecast of volcanic aerosols at operational level. The model forecasts volcanic ash cloud trajectories, concentration of ash at relevant flight levels, and the expected deposit thickness for both regional and global configurations. Its online coupling approach improves the current state-of-the-art tephra dispersal models, especially in situations where meteorological conditions are changing rapidly in time, two-way feedbacks are significant, or distal ash cloud dispersal simulations are required. This work presents the model application for the first phases of the 2011 Cordón Caulle and 2001 Mount Etna eruptions. The computational efficiency of NMMB-MONARCH-ASH and its application results compare favorably with other long-range tephra dispersal models, supporting its operational implementation. © The Author(s) 2017.

Abhilash S.,Indian Institute of Tropical Meteorology | Sahai A.K.,Indian Institute of Tropical Meteorology | Goswami B.N.,Indian Institute of Tropical Meteorology | Kumar A.,National Center for Environmental Prediction
International Journal of Climatology | Year: 2014

This study analyses skill of an extended range prediction system to forecast Indian Summer Monsoon Rainfall (ISMR) 3-4 pentads in advance. A series of 45-d forecast integrations starting from 1 May to 29 September at 5-d interval for 7 years from 2001 to 2007 are performed with an ensemble prediction system (EPS) in NCEP Climate Forecast System Version 1 (CFSV1) model. The sensitivity experiments with different amount of perturbation suggest that full tendency perturbation experiment on all basic variables including humidity at all vertical level shows higher dispersion among forecast than other experiments. Spread-error relationship shows that the present EPS system is under-dispersive. The lower bound of predictability is about 10-12 d and upper bound of predictability is found to be 20-25 d for zonal wind at 850 and 200 hPa. The signal-to-noise ratio (SNR) of precipitation (500 hPa geopotential height) reveals that the predictability limit is about 15(18) d over Indian monsoon region. The monsoon zone area averaged precipitation forecasts averaged over 5-d period (pentads) up to 4 pentad lead time are also evaluated and compared with observation. The anomaly correlation coefficients (ACC) reaches zero after pentad 3 (pentad 5) lead for precipitation (dynamical variables). A probabilistic approach is developed from the EPS for extended range forecast applications. The relative operating characteristic (ROC) curves for three categories of precipitation shows that the prediction skill for active and break is slightly higher compared to that of normal category and skillful probabilistic forecasts can be generated for precipitation even beyond pentad 4 lead. © 2013 Royal Meteorological Society.

Xue Y.,University of California at Los Angeles | de Sales F.,San Diego State University | Lau W.K.-M.,University of Maryland University College | Boone A.,French National Center of Weather Research | And 30 more authors.
Climate Dynamics | Year: 2016

The second West African Monsoon Modeling and Evaluation Project Experiment (WAMME II) is designed to improve understanding of the possible roles and feedbacks of sea surface temperature (SST), land use land cover change (LULCC), and aerosols forcings in the Sahel climate system at seasonal to decadal scales. The project’s strategy is to apply prescribed observationally based anomaly forcing, i.e., “idealized but realistic” forcing, in simulations by climate models. The goal is to assess these forcings’ effects in producing/amplifying seasonal and decadal climate variability in the Sahel between the 1950s and the 1980s, which is selected to characterize the great drought period of the last century. This is the first multi-model experiment specifically designed to simultaneously evaluate such relative contributions. The WAMME II models have consistently demonstrated that SST forcing is a major contributor to the twentieth century Sahel drought. Under the influence of the maximum possible SST forcing, the ensemble mean of WAMME II models can produce up to 60 % of the precipitation difference during the period. The present paper also addresses the role of SSTs in triggering and maintaining the Sahel drought. In this regard, the consensus of WAMME II models is that both Indian and Pacific Ocean SSTs greatly contributed to the drought, with the former producing an anomalous displacement of the Intertropical Convergence Zone before the WAM onset, and the latter mainly contributes to the summer WAM drought. The WAMME II models also show that the impact of LULCC forcing on the Sahel climate system is weaker than that of SST forcing, but still of first order magnitude. According to the results, under LULCC forcing the ensemble mean of WAMME II models can produces about 40 % of the precipitation difference between the 1980s and the 1950s. The role of land surface processes in responding to and amplifying the drought is also identified. The results suggest that catastrophic consequences are likely to occur in the regional Sahel climate when SST anomalies in individual ocean basins and in land conditions combine synergistically to favor drought. © 2016 Springer-Verlag Berlin Heidelberg

Xue Y.,University of California at Los Angeles | e Sales F.,University of California at Los Angeles | Lau W.K.-M.,NASA | Boone A.,French National Center of Weather Research | And 22 more authors.
Climate Dynamics | Year: 2010

This paper briefly presents the West African Monsoon (WAM) Modeling and Evaluation Project (WAMME) and evaluates WAMME general circulation models' (GCM) performances in simulating variability of WAM precipitation, surface temperature, and major circulation features at seasonal and intraseasonal scales in the first WAMME experiment. The analyses indicate that models with specified sea surface temperature generally have reasonable simulations of the pattern of spatial distribution of WAM seasonal mean precipitation and surface temperature as well as the averaged zonal wind in latitude-height cross-section and low level circulation. But there are large differences among models in simulating spatial correlation, intensity, and variance of precipitation compared with observations. Furthermore, the majority of models fail to produce proper intensities of the African Easterly Jet (AEJ) and the tropical easterly jet. AMMA Land Surface Model Intercomparison Project (ALMIP) data are used to analyze the association between simulated surface processes and the WAM and to investigate the WAM mechanism. It has been identified that the spatial distributions of surface sensible heat flux, surface temperature, and moisture convergence are closely associated with the simulated spatial distribution of precipitation; while surface latent heat flux is closely associated with the AEJ and contributes to divergence in AEJ simulation. Common empirical orthogonal functions (CEOF) analysis is applied to characterize the WAM precipitation evolution and has identified a major WAM precipitation mode and two temperature modes (Sahara mode and Sahel mode). Results indicate that the WAMME models produce reasonable temporal evolutions of major CEOF modes but have deficiencies/uncertainties in producing variances explained by major modes. Furthermore, the CEOF analysis shows that WAM precipitation evolution is closely related to the enhanced Sahara mode and the weakened Sahel mode, supporting the evidence revealed in the analysis using ALMIP data. An analysis of variability of CEOF modes suggests that the Sahara mode leads the WAM evolution, and divergence in simulating this mode contributes to discrepancies in the precipitation simulation. © 2010 The Author(s).

Xue Y.,University of California at Los Angeles | Oaida C.M.,University of California at Los Angeles | Diallo I.,University of California at Los Angeles | Neelin J.D.,University of California at Los Angeles | And 8 more authors.
Environmental Research Letters | Year: 2016

Recurrent drought and associated heatwave episodes are important features of the US climate. Many studies have examined the connection between ocean surface temperature changes and conterminous US droughts. However, remote effects of large-scale land surface temperature variability, over shorter but still considerable distances, on US regional droughts have been largely ignored. The present study combines two types of evidence to address these effects: climate observations and model simulations. Our analysis of observational data shows that springtime land temperature in northwest US is significantly correlated with summer rainfall and surface temperature changes in the US Southern Plains and its adjacent areas. Our model simulations of the 2011 Southern Plains drought using a general circulation model and a regional climate model confirm the observed relationship between land temperature anomaly and drought, and suggest that the long-distance effect of land temperature changes in the northwest US on Southern Plains droughts is probably as large as the more familiar effects of ocean surface temperatures and atmospheric internal variability. We conclude that the cool 2011 springtime climate conditions in the northwest US increased the probability of summer drought and abnormal heat in the Southern Plains. The present study suggests a strong potential for more skillful intra-seasonal predictions of US Southern Plains droughts when such facts as ones presented here are considered. © 2016 IOP Publishing Ltd.

Joseph S.,Indian Institute of Tropical Meteorology | Sahai A.K.,Indian Institute of Tropical Meteorology | Sharmila S.,Indian Institute of Tropical Meteorology | Abhilash S.,Indian Institute of Tropical Meteorology | And 5 more authors.
Climate Dynamics | Year: 2015

The Indian summer monsoon of 2013 covered the entire country by 16 June, one month earlier than its normal date. Around that period, heavy rainfall was experienced in the north Indian state of Uttarakhand, which is situated on the southern slope of Himalayan Ranges. The heavy rainfall and associated landslides caused serious damages and claimed many lives. This study investigates the scientific rationale behind the incidence of the extreme rainfall event in the backdrop of large scale monsoon environment. It is found that a monsoonal low pressure system that provided increased low level convergence and abundant moisture, and a midlatitude westerly trough that generated strong upper level divergence, interacted with each other and helped monsoon to cover the entire country and facilitated the occurrence of the heavy rainfall event in the orographic region. The study also examines the skill of an ensemble prediction system (EPS) in predicting the Uttarakhand event on extended range time scale. The EPS is implemented on both high (T382) and low (T126) resolution versions of the coupled general circulation model CFSv2. Although the models predicted the event 10–12 days in advance, they failed to predict the midlatitude influence on the event. Possible reasons for the same are also discussed. In both resolutions of the model, the event was triggered by the generation and northwestward movement of a low pressure system developed over the Bay of Bengal. The study advocates the usefulness of high resolution models in predicting extreme events. © 2014, Springer-Verlag Berlin Heidelberg.

Kumar A.,U.S. National Center for Atmospheric Research | Kumar A.,Purdue University | Kumar A.,NASA | Chen F.,U.S. National Center for Atmospheric Research | And 5 more authors.
Boundary-Layer Meteorology | Year: 2011

Accurately representing complex land-surface processes balancing complexity and realism remains one challenge that the weather modelling community is facing nowadays. In this study, a photosynthesis-based Gas-exchange Evapotranspiration Model (GEM) is integrated into the Noah land-surface model replacing the traditional Jarvis scheme for estimating the canopy resistance and transpiration. Using 18-month simulations from the High Resolution Land Data Assimilation System (HRLDAS), the impact of the photosynthesis-based approach on the simulated canopy resistance, surface heat fluxes, soil moisture, and soil temperature over different vegetation types is evaluated using data from the Atmospheric Radiation Measurement (ARM) site, Oklahoma Mesonet, 2002 International H2O Project (IHOP_2002), and three Ameriflux sites. Incorporation of GEM into Noah improves the surface energy fluxes as well as the associated diurnal cycle of soil moisture and soil temperature during both wet and dry periods. An analysis of midday, average canopy resistance shows similar day-to-day trends in the model fields as seen in observed patterns. Bias and standard deviation analyses for soil temperature and surface fluxes show that GEM responds somewhat better than the Jarvis scheme, mainly because the Jarvis approach relies on a parametrised minimum canopy resistance and meteorological variables such as air temperature and incident radiation. The analyses suggest that adding a photosynthesis-based transpiration scheme such as GEM improves the ability of the land-data assimilation system to simulate evaporation and transpiration under a range of soil and vegetation conditions. © 2010 Springer Science+Business Media B.V.

Abhilash S.,Indian Institute of Tropical Meteorology | Sahai A.K.,Indian Institute of Tropical Meteorology | Borah N.,Indian Institute of Tropical Meteorology | Chattopadhyay R.,Indian Institute of Tropical Meteorology | And 5 more authors.
Climate Dynamics | Year: 2014

An ensemble prediction system (EPS) is devised for the extended range prediction (ERP) of monsoon intraseasonal oscillations (MISO) of Indian summer monsoon (ISM) using National Centers for Environmental Prediction Climate Forecast System model version 2 at T126 horizontal resolution. The EPS is formulated by generating 11 member ensembles through the perturbation of atmospheric initial conditions. The hindcast experiments were conducted at every 5-day interval for 45 days lead time starting from 16th May to 28th September during 2001-2012. The general simulation of ISM characteristics and the ERP skill of the proposed EPS at pentad mean scale are evaluated in the present study. Though the EPS underestimates both the mean and variability of ISM rainfall, it simulates the northward propagation of MISO reasonably well. It is found that the signal-to-noise ratio of the forecasted rainfall becomes unity by about 18 days. The potential predictability error of the forecasted rainfall saturates by about 25 days. Though useful deterministic forecasts could be generated up to 2nd pentad lead, significant correlations are found even up to 4th pentad lead. The skill in predicting large-scale MISO, which is assessed by comparing the predicted and observed MISO indices, is found to be ~17 days. It is noted that the prediction skill of actual rainfall is closely related to the prediction of large-scale MISO amplitude as well as the initial conditions related to the different phases of MISO. An analysis of categorical prediction skills reveals that break is more skillfully predicted, followed by active and then normal. The categorical probability skill scores suggest that useful probabilistic forecasts could be generated even up to 4th pentad lead. © 2014 Springer-Verlag Berlin Heidelberg.

Loading National Center for Environmental Prediction collaborators
Loading National Center for Environmental Prediction collaborators