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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. Source

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. Source

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. Source

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. Source

Chen Y.,Nanjing University of Information Science and Technology | Wang H.,Colorado State University | Wang H.,National Oceanic and Atmospheric Administration | Min J.,Nanjing University of Information Science and Technology | And 5 more authors.
Journal of Applied Meteorology and Climatology | Year: 2015

Analysis of the cloud components in numerical weather prediction models using advanced data assimilation techniques has been a prime topic in recent years. In this research, the variational data assimilation (DA) system for the Weather Research and Forecasting (WRF) Model (WRFDA) is further developed to assimilate satellite cloud products that will produce the cloud liquid water and ice water analysis. Observation operators for the cloud liquid water path and cloud ice water path are developed and incorporated into the WRFDA system. The updated system is tested by assimilating cloud liquid water path and cloud ice water path observations from Global Geostationary Gridded Cloud Products at NASA. To assess the impact of cloud liquid/ice water path data assimilation on short-term regional numerical weather prediction (NWP), 3-hourly cycling data assimilation and forecast experiments with and without the use of the cloud liquid/ice water paths are conducted. It is shown that assimilating cloud liquid/ice water paths increases the accuracy of temperature, humidity, and wind analyses at model levels between 300 and 150 hPa after 5 cycles (15 h). It is also shown that assimilating cloud liquid/ice water paths significantly reduces forecast errors in temperature and wind at model levels between 300 and 150 hPa. The precipitation forecast skills are improved as well. One reason that leads to the improved analysis and forecast is that the 3-hourly rapid update cycle carries over the impact of cloud information from the previous cycles spun up by the WRF Model. © 2015 American Meteorological Society. Source

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