Incorporation of a dynamic root distribution into CLM4.5: Evaluation of carbon and water fluxes over the Amazon

Roots are responsible for the uptake of water and nutrients by plants and have the plasticity to dynamically respond to different environmental conditions. However, most land surface models currently prescribe rooting profiles as a function only of vegetation type, with no consideration of the surroundings. In this study, a dynamic rooting scheme, which describes root growth as a compromise between water and nitrogen availability, was incorporated into CLM4.5 with carbon–nitrogen(CN) interactions(CLM4.5-CN) to investigate the effects of a dynamic root distribution on eco-hydrological modeling. Two paired numerical simulations were conducted for the Tapajos National Forest km83(BRSa3) site and the Amazon, one using CLM4.5-CN without the dynamic rooting scheme and the other including the proposed scheme. Simulations for the BRSa3 site showed that inclusion of the dynamic rooting scheme increased the amplitudes and peak values of diurnal gross primary production(GPP) and latent heat flux(LE) for the dry season, and improved the carbon(C) and water cycle modeling by reducing the RMSE of GPP by 0.4 g C m~(-2)d~(-1), net ecosystem exchange by 1.96 g C m~(-2)d~(-1), LE by 5.0 W m~(-2), and soil moisture by 0.03 m~3m~(-3), at the seasonal scale, compared with eddy flux measurements, while having little impact during the wet season. For the Amazon, regional analysis also revealed that vegetation responses(including GPP and LE) to seasonal drought and the severe drought of 2005 were better captured with the dynamic rooting scheme incorporated.     

The Upstream “Strong Signals” of the Water Vapor Transport over the Tibetan Plateau during a Heavy Rainfall Event in the Yangtze River Basin

A heavy rainfall event that occurred over the middle and lower reaches of the Yangtze River Basin(YRB) during July11–13 2000 is explored in this study. The potential/stream function is used to analyze the upstream "strong signals" of the water vapor transport in the Tibetan Plateau(TP). The studied time period covers from 2000 LST 5 July to 2000 LST 15 July(temporal resolution: 6 hours). By analyzing the three-dimensional structure of the water vapor flux, vorticity and divergence prior to and during the heavy rainfall event, the upstream "strong signals" related to this heavy rainfall event are revealed. A strong correlation exists between the heavy rainfall event in the YRB and the convective clouds over the TP. The "convergence zone" of the water vapor transport is also identified, based on correlation analysis of the water vapor flux two days and one day prior to, and on the day of, the heavy rainfall. And this "convergence zone" coincides with the migration of the maximum rainfall over the YRB. This specific coupled structure actually plays a key role in generating heavy rainfall over the YRB. The eastward movement of the coupled system with a divergence/convergence center of the potential function at the upper/lower level resembles the spatiotemporal evolution of the heavy rainfall event over the YRB. These upstream "strong signals" are clearly traced in this study through analyzing the three-dimensional structure of the potential/stream function of upstream water vapor transport.     

Identification of forcing mechanisms of convective initiation over mountains through high-resolution numerical simulations

正Convection and its ensuing severe weather,such as heavy rainfall,hail,tornado,and high wind,have significant impacts on our society and economy(e.g.,Cao et al.,2004;Fritsch and Carbone,2004;Verbout et al.,2006;Ashley and Black,2008;Cao,2008;Cao and Ma,2009;Zhang et al.,2014).Due to its localized and transient nature,the initiation of convection or convective initiation remains one of the least     

Possible sources of forecast errors generated by the global/regional assimilation and prediction system for landfalling tropical cyclones. Part I: Initial uncertainties

This paper investigates the possible sources of errors associated with tropical cyclone (TC) tracks forecasted using the Global/Regional Assimilation and Prediction System (GRAPES). The GRAPES forecasts were made for 16 landfalling TCs in the western North Pacific basin during the 2008 and 2009 seasons, with a forecast length of 72 hours, and using the default initial conditions (“initials”, hereafter), which are from the NCEP-FNL dataset, as well as ECMWF initials. The forecasts are compared with ECMWF forecasts. The results show that in most TCs, the GRAPES forecasts are improved when using the ECMWF initials compared with the default initials. Compared with the ECMWF initials, the default initials produce lower intensity TCs and a lower intensity subtropical high, but a higher intensity South Asia high and monsoon trough, as well as a higher temperature but lower specific humidity at the TC center. Replacement of the geopotential height and wind fields with the ECMWF initials in and around the TC center at the initial time was found to be the most efficient way to improve the forecasts. In addition, TCs that showed the greatest improvement in forecast accuracy usually had the largest initial uncertainties in TC intensity and were usually in the intensifying phase. The results demonstrate the importance of the initial intensity for TC track forecasts made using GRAPES, and indicate the model is better in describing the intensifying phase than the decaying phase of TCs. Finally, the limit of the improvement indicates that the model error associated with GRAPES forecasts may be the main cause of poor forecasts of landfalling TCs. Thus, further examinations of the model errors are required.     

A comprehensive classification of anomalous circulation patterns responsible for persistent precipitation extremes in South China

Based on observational precipitation at 63 stations in South China and NCEP NCAR reanalysis data during 1951 2010,a cluster analysis is performed to classify large-scale circulation patterns responsible for persistent precipitation extremes(PPEs) that are independent of the influence of tropical cyclones(TCs).Conceptual schematics depicting configurations among planetary-scale systems at different levels are established for each type.The PPEs free from TCs account for 38.6%of total events,and they tend to occur during April August and October,with the highest frequency observed in June.Corresponding circulation patterns during June August can be mainly categorized into two types,i.e.,summer-Ⅰ type and summer-Ⅱtype.In summer-Ⅰ type,the South Asian high takes the form of a zonal-belt type.The axis of upstream westerly jets is northwest-oriented.At the middle level,the westerly jets at midlatitudes extend zonally.Along the southern edge of the westerly jet,synoptic eddies steer cold air to penetrate southward;the Bay of Bengal(BOB) trough is located to the north;a shallow trough resides over coastal areas of western South China;and an intensified western Pacific subtropical high(WPSH) extends westward.The anomalous moisture is mainly contributed by horizontal advection via southwesterlies around 20°N and southeasterlies from the southern flange of the WPSH.Moisture convergence maximizes in coastal regions of eastern South China,which is the very place recording extreme precipitation.In summer-Ⅱ type,the South Asian high behaves as a western-center type.The BOB trough is much deeper,accompanied by a cyclone to its north;and a lower-level trough appears in northwestern parts of South China.Different to summer-Ⅰ type,moisture transport via southwesterlies is mostly responsible for the anomalous moisture in this type.The moisture convergence zones cover Guangdong,Guangxi,and Hainan,matching well with the areas of flooding.It is these set combinations among different systems at different levels that trigger PPEs in South China.     

Retrieval of atmospheric temperature and moisture vertical profiles from satellite Advanced Infrared Sounder radiances with a new regularization parameter selecting method

Considering the characteristics of nonlinear problems, a new method based on the L-curve method and including the concept of entropy was designed to select the regularization parameter in the one-dimensional variational analysis-based sounding retrieval method. In the first iteration, this method uses an empirical regularization parameter derived by minimizing the entropy of variables. During subsequent iterations, it uses the L-curve method to select the regularization parameter in the vicinity of the regularization parameter selected in the last iteration. The new method was employed to select the regularization parameter in retrieving atmospheric temperature and moisture profiles from Atmospheric Infrared Sounder radiance measurements selected from the first day of each month in 2008. The results show that compared with the original L-curve method, the new method yields 5.5% and 2.5% improvements on temperature and relative humidity profiles, respectively. Compared with the discrepancy principle method, the improvements on temperature and relative humidity profiles are 1.6% and 2.0%, respectively.     

An algorithm to retrieve precipitation with synthetic aperture radar

This paper presents a new type of rainfall retrieval algorithm, called the model-oriented statistical and Volterra integration. It is a combination of the model-oriented statistical (MOS) and Volterra integral equation (VIE) approaches. The steps involved in this new algorithm can be briefly illustrated as follows. Firstly, information such as the start point and width of the rain is obtained through pre-analysis of the data received by synthetic aperture radar (SAR). Secondly, the VIE retrieval algorithm is employed over a short distance to obtain information on the shape of the rain. Finally, the rain rate can be calculated by using the MOS retrieval algorithm. Simulation results show that the proposed algorithm is effective and simple, and can lead to time savings of nearly 50% compared with MOS. An example of application of SAR data is also discussed, involving the retrieval of precipitation information over the South China Sea.     

Factors controlling the interannual variations of MJO intensity

The interannual variations of intensity of the Madden-Julian Oscillation (MJO) during boreal winter are investigated by using the observed outgoing longwave radiation (OLR) and the reanalysis data of ECMWF and NCEP. The standard deviation of 20-80-day filtered OLR anomaly is used to measure the MJO intensity. The dominant spatial structure of the interannual variability is revealed by an EOF analysis of the MJO intensity field. It is found that the leading mode is associated with eastern Pacific type ENSO, whereas the second mode is related to central Pacific type ENSO. A simple atmospheric model is used to investigate the relative roles of background moisture and wind changes in affecting the overall strength of MJO. The numerical experiments indicate that the background moisture effect is dominant while the background wind change has a minor effect.     

A timescale decomposed threshold regression downscaling approach to forecasting South China early summer rainfall

A timescale decomposed threshold regression(TSDTR) downscaling approach to forecasting South China early summer rainfall(SCESR) is described by using long-term observed station rainfall data and NOAA ERSST data. It makes use of two distinct regression downscaling models corresponding to the interannual and interdecadal rainfall variability of SCESR.The two models are developed based on the partial least squares(PLS) regression technique, linking SCESR to SST modes in preceding months on both interannual and interdecadal timescales. Specifically, using the datasets in the calibration period 1915–84, the variability of SCESR and SST are decomposed into interannual and interdecadal components. On the interannual timescale, a threshold PLS regression model is fitted to interannual components of SCESR and March SST patterns by taking account of the modulation of negative and positive phases of the Pacific Decadal Oscillation(PDO). On the interdecadal timescale, a standard PLS regression model is fitted to the relationship between SCESR and preceding November SST patterns. The total rainfall prediction is obtained by the sum of the outputs from both the interannual and interdecadal models. Results show that the TSDTR downscaling approach achieves reasonable skill in predicting the observed rainfall in the validation period 1985–2006, compared to other simpler approaches. This study suggests that the TSDTR approach,considering different interannual SCESR-SST relationships under the modulation of PDO phases, as well as the interdecadal variability of SCESR associated with SST patterns, may provide a new perspective to improve climate predictions.     

Erratum to: Climate change projections over India by a downscaling approach using PRECIS

The author “Bhaski Bhaskaran” and his affiliation “Fujitsu Laboratory of Europe, Middlesex, UK” should be replaced by “Balakrishnan Bhaskaran”, “Fujitsu Laboratories of Europe Limited, Hayes Park, Middlesex, UK”, respectively.The corrected name and affiliation are shown in this erratum.