Yang C.,Nanjing University of Information Science and Technology |
Yang C.,U.S. National Center for Atmospheric Research |
Liu Z.,U.S. National Center for Atmospheric Research |
Bresch J.,U.S. National Center for Atmospheric Research |
And 3 more authors.
Tellus, Series A: Dynamic Meteorology and Oceanography | Year: 2016
A method to assimilate all-sky radiances from the Advanced Microwave Scanning Radiometer 2 (AMSR2) was developed within the Weather Research and Forecasting (WRF) model's data assimilation (WRFDA) system. The four essential elements are: (1) extending the community radiative transform model's (CRTM) interface to include hydrometeor profiles; (2) using total water Qt as the moisture control variable; (3) using a warm-rain physics scheme for partitioning the Qt increment into individual increments of water vapour, cloud liquid water and rain; and (4) adopting a symmetric observation error model for all-sky radiance assimilation. Compared to a benchmark experiment with no AMSR2 data, the impact of assimilating clear-sky or allsky AMSR2 radiances on the analysis and forecast of Hurricane Sandy (2012) was assessed through analysis/ forecast cycling experiments using WRF and WRFDA's three-dimensional variational (3DVAR) data assimilation scheme. With more cloud/precipitation-affected data being assimilated around tropical cyclone (TC) core areas in the all-sky AMSR2 assimilation experiment, better analyses were obtained in terms of the TC's central sea level pressure (CSLP), warm-core structure and cloud distribution. Substantial (>20 %) error reduction in track and CSLP forecasts was achieved from both clear-sky and all-sky AMSR2 assimilation experiments, and this improvement was consistent from the analysis time to 72-h forecasts. Moreover, the allsky assimilation experiment consistently yielded better track and CSLP forecasts than the clear-sky did for all forecast lead times, due to a better analysis in the TC core areas. Positive forecast impact from assimilating AMSR2 radiances is also seen when verified against the European Center for Medium-Range Weather Forecasts (ECMWF) analysis and the Stage IV precipitation analysis, with an overall larger positive impact from the all-sky assimilation experiment. © 2016 C. Yang et al.
Shi Y.,National Environment Agency |
Liu X.,National Environment Agency |
Kok S.-Y.,National Environment Agency |
Rajarethinam J.,National Environment Agency |
And 10 more authors.
Environmental Health Perspectives | Year: 2016
Background: With its tropical rainforest climate, rapid urbanization, and changing demography and ecology, Singapore experiences endemic dengue; the last large outbreak in 2013 culminated in 22,170 cases. In the absence of a vaccine on the market, vector control is the key approach for prevention. Objectives: We sought to forecast the evolution of dengue epidemics in Singapore to provide early warning of outbreaks and to facilitate the public health response to moderate an impending outbreak. Methods: We developed a set of statistical models using least absolute shrinkage and selection operator (LASSO) methods to forecast the weekly incidence of dengue notifications over a 3-month time horizon. This forecasting tool used a variety of data streams and was updated weekly, including recent case data, meteorological data, vector surveillance data, and population-based national statistics. The forecasting methodology was compared with alternative approaches that have been proposed to model dengue case data (seasonal autoregressive integrated moving average and step-down linear regression) by fielding them on the 2013 dengue epidemic, the largest on record in Singapore. Results: Operationally useful forecasts were obtained at a 3-month lag using the LASSO-derived models. Based on the mean average percentage error, the LASSO approach provided more accurate forecasts than the other methods we assessed. We demonstrate its utility in Singapore’s dengue control program by providing a forecast of the 2013 outbreak for advance preparation of outbreak response. Conclusions: Statistical models built using machine learning methods such as LASSO have the potential to markedly improve forecasting techniques for recurrent infectious disease outbreaks such as dengue. © 2016, Public Health Services, US Dept of Health and Human Services. All rights reserved.
Birch C.E.,University of Leeds |
Webster S.,UK Met Office |
Peatman S.C.,University of Reading |
Parker D.J.,University of Leeds |
And 3 more authors.
Journal of Climate | Year: 2016
State-of-the-art regional climate model simulations that are able to resolve key mesoscale circulations are used, for the first time, to understand the interaction between the large-scale convective environment of the MJO and processes governing the strong diurnal cycle over the islands of the Maritime Continent (MC). Convection is sustained in the late afternoon just inland of the coasts because of sea breeze convergence. Previous work has shown that the variability in MC rainfall associated with the MJO is manifested in changes to this diurnal cycle; land-based rainfall peaks before the active convective envelope of the MJO reaches the MC, whereas oceanic rainfall rates peak while the active envelope resides over the region. The model simulations show that the main controls on oceanic MC rainfall in the early active MJO phases are the large-scale environment and atmospheric stability, followed by high oceanic latent heat flux forced by high near-surface winds in the later active MJO phases. Over land, rainfall peaks before the main convective envelope arrives (in agreement with observations), even though the large-scale convective environment is only moderately favorable for convection. The causes of this early rainfall peak are strong convective triggers from land-sea breeze circulations that result from high surface insolation and surface heating. During the peak MJO phases cloud cover increases and surface insolation decreases, which weakens the strength of the mesoscale circulations and reduces land-based rainfall, even though the large-scale environment remains favorable for convection at this time. Hence, scale interactions are an essential part of the MJO transition across the MC. © 2016 American Meteorological Society.
Gao F.,U.S. National Center for Atmospheric Research |
Huang X.-Y.,Center for Climate Research Singapore |
Jacobs N.A.,Panasonic |
Wang H.,Colorado State University |
Wang H.,National Oceanic and Atmospheric Administration
Tellus, Series A: Dynamic Meteorology and Oceanography | Year: 2015
The assimilation of wind observations in the form of speed and direction (asm_sd) by the Weather Research and Forecasting Model Data Assimilation System (WRFDA) was performed using real data and employing a series of cycling assimilation experiments for a 2-week period, as a follow-up for an idealised post hoc assimilation experiment. The satellite-derived Atmospheric Motion Vectors (AMV) and surface dataset in Meteorological Assimilation Data Ingest System (MADIS) were assimilated. This new method takes into account the observation errors of both wind speed (spd) and direction (dir), and WRFDA background quality control (BKG-QC) influences the choice of wind observations, due to data conversions between (u,v) and (spd, dir). The impacts of BKG-QC, as well as the new method, on the wind analysis were analysed separately. Because the dir observational errors produced by different platforms are not known or tuned well in WRFDA, a practical method, which uses similar assimilation weights in comparative trials, was employed to estimate the spd and dir observation errors. The asm_sd produces positive impacts on analyses and short-range forecasts of spd and dir with smaller root-mean-square errors than the u,v-based system. The bias of spd analysis decreases by 54.8%. These improvements result partly from BKG-QC screening of spd and dir observations in a direct way, but mainly from the independent impact of spd (dir) data assimilation on spd (dir) analysis, which is the primary distinction from the standard WRFDA method. The potential impacts of asm_sd on precipitation forecasts were evaluated. Results demonstrate that the asm_sd is able to indirectly improve the precipitation forecasts by improving the prediction accuracies of key wind-related factors leading to precipitation (e.g. warm moist advection and frontogenesis). © 2015 F. Gao et al.
McBride J.L.,Center for Climate Research Singapore |
Sahany S.,Center for Climate Research Singapore |
Hassim M.E.E.,Center for Climate Research Singapore |
Nguyen C.M.,Center for Climate Research Singapore |
And 3 more authors.
Bulletin of the American Meteorological Society | Year: 2015
The record dry spell over Singapore-Malaysia was caused by the southward contraction of the intertropical convergence zone. Within present evidence, there is no clear attribution to climate change. © 2015 American Meteorological Society.
Lo J.C.-F.,Center for Climate Research Singapore |
Orton T.,Center for Climate Research Singapore |
Orton T.,University of Leeds
Weather | Year: 2016
Sumatra Squalls are common weather phenomena which have a very large impact affecting 85 million people throughout equatorial South East Asia, and many more through trade links with other regions; however, current comprehension behind Sumatra Squalls is not well studied and interpretation is insufficient. The aim of this article is to raise the community interest on Sumatra Squalls and underline the need for increased research. Twenty-two years of observational data has been collated and analysed to create climatologically general features of Sumatra Squalls. These squalls have a clear diurnal cycle and commonly make landfall in the west coast of the Malay Peninsula and Singapore during the pre-dawn and early morning. Additionally, these squalls commonly form during the intermonsoon season (April-May and October-November) and Southwest monsoon (June-September) seasons with average frequencies of 8 and 6 occurrences per month respectively. © 2016 Royal Meteorological Society
Xavier P.,Center for Climate Research Singapore |
Xavier P.,UK Met Office |
Rahmat R.,Center for Climate Research Singapore |
Cheong W.K.,Center for Climate Research Singapore |
Wallace E.,UK Met Office
Geophysical Research Letters | Year: 2014
The influence of Madden-Julian Oscillation (MJO) on the rainfall distribution of Southeast Asia is studied using TRMM satellite-derived rainfall and rain gauge data. It is shown that convectively active (suppressed) phases of MJO can increase (decrease) the probability of extreme rain events over the land regions by about 30-50% (20-25%) during November-March season. The influence of MJO on localized rainfall extremes are also observed both in rainfall intensity and duration. The Met Office Global Seasonal forecasting system seasonal forecasting system is shown to reproduce the MJO influence on rainfall distribution well despite the model biases over land. Skills scores for forecasting 90th percentile extreme rainfall shows significant skills for convective phases. This study demonstrates the feasibility of deriving probabilistic forecasts of extreme rainfall at medium range. © 2014. American Geophysical Union. All Rights Reserved.
Walsh K.J.E.,University of Melbourne |
Mcbride J.L.,Center for Climate Research Singapore |
Klotzbach P.J.,Colorado State University |
Balachandran S.,Cyclone Warning Research Center |
And 7 more authors.
Wiley Interdisciplinary Reviews: Climate Change | Year: 2016
Recent research has strengthened the understanding of the links between climate and tropical cyclones (TCs) on various timescales. Geological records of past climates have shown century-long variations in TC numbers. While no significant trends have been identified in the Atlantic since the late 19th century, significant observed trends in TC numbers and intensities have occurred in this basin over the past few decades, and trends in other basins are increasingly being identified. However, understanding of the causes of these trends is incomplete, and confidence in these trends continues to be hampered by a lack of consistent observations in some basins. A theoretical basis for maximum TC intensity appears now to be well established, but a climate theory of TC formation remains elusive. Climate models mostly continue to predict future decreases in global TC numbers, projected increases in the intensities of the strongest storms and increased rainfall rates. Sea level rise will likely contribute toward increased storm surge risk. Against the background of global climate change and sea level rise, it is important to carry out quantitative assessments on the potential risk of TC-induced storm surge and flooding to densely populated cities and river deltas. Several climate models are now able to generate a good distribution of both TC numbers and intensities in the current climate. Inconsistent TC projection results emerge from modeling studies due to different downscaling methodologies and warming scenarios, inconsistencies in projected changes of large-scale conditions, and differences in model physics and tracking algorithms. WIREs Clim Change 2016, 7:65-89. doi: 10.1002/wcc.371 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.
Newman K.M.,U.S. National Center for Atmospheric Research |
Schwartz C.S.,U.S. National Center for Atmospheric Research |
Liu Z.,U.S. National Center for Atmospheric Research |
Shao H.,U.S. National Center for Atmospheric Research |
Huang X.-Y.,Center for Climate Research Singapore
Weather and Forecasting | Year: 2015
This study examines the impact of assimilating Microwave Humidity Sounder (MHS) radiances in a limited-area ensemble Kalman filter (EnKF) data assimilation system. Two experiments spanning 11 August-13 September 2008 were run over a domain featuring the Atlantic basin using a 6-h full cycling analysis and forecast system. Deterministic 72-h forecasts were initialized at 0000 and 1200 UTC for a comparison of forecast impact. The two experiments were configured identically with the exception of the inclusion of the MHS radiances (AMHS) in the second to isolate the impacts of the MHS radiance data. The results were verified against several sources, and statistical significance tests indicate the most notable differences are in the midlevel moisture fields. Both configurations were characterized by high moisture biases when compared to the European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim, also known as ERA-I) specific humidity fields, as well as precipitable water vapor from an observationally based product. However, the AMHS experiment has midlevel moisture fields closer to the ERA-I and observation datasets. When reducing the verification domain to focus on the subtropical and easterly wave regions of the North Atlantic Ocean, larger improvements in midlevel moisture at nearly all lead times is seen in the AMHS simulation. Finally, when considering tropical cyclone forecasts, the AMHS configuration shows improvement in intensity forecasts at several lead times as well as improvements at early to intermediate lead times for minimum sea level pressure forecasts. © 2015 American Meteorological Society.
Hassim M.E.E.,University of Melbourne |
Hassim M.E.E.,Center for Climate Research Singapore |
Lane T.P.,University of Melbourne |
Grabowski W.W.,U.S. National Center for Atmospheric Research
Atmospheric Chemistry and Physics | Year: 2016
In this study, we examine the diurnal cycle of rainfall over New Guinea using a series of convection-permitting numerical simulations with the Weather Research and Forecasting (WRF) model. We focus our simulations on a period of suppressed regional-scale conditions (February 2010) during which local diurnal forcings are maximised. Additionally, we focus our study on the occurrence and dynamics of offshore-propagating convective systems that contribute to the observed early-morning rainfall maximum north-east of New Guinea. In general, modelled diurnal precipitation shows good agreement with satellite-observed rainfall, albeit with some timing and intensity differences. The simulations also reproduce the occurrence and variability of overnight convection that propagate offshore as organised squall lines northeast of New Guinea. The occurrence of these offshore systems is largely controlled by background conditions. Days with offshore-propagating convection have more middle tropospheric moisture, larger convective available potential energy, and greater low-level moisture convergence. Convection has similar characteristics over the terrain on days with and without offshore propagation. The offshore-propagating convection manifests via a multi-stage evolutionary process. First, scattered convection over land, which is remnant of the daytime maximum, moves towards the coast and becomes reorganised near the region of coastal convergence associated with the land breeze. The convection then moves offshore in the form of a squall line at 5ms-1. In addition, cool anomalies associated with gravity waves generated by precipitating land convection propagate offshore at a dry hydrostatic gravity wave speed (of 15ms-1) and act to destabilise the coastal/offshore environment prior to the arrival of the squall line. Although the gravity wave does not appear to initiate the convection or control its propagation, it should contribute to its longevity and maintenance. The results highlight the importance of terrain and coastal effects along with gravity waves in contributing to the diurnal cycle over the Maritime Continent, especially the offshore precipitation maxima adjacent to quasi-linear coastlines. © Author(s) 2016.