Prediction of the diurnal change using a multimodel superensemble. Part I: Precipitation

Modeling the geographical distribution of the phase and amplitude of the diurnal change is a challenging problem. This paper addresses the issues of modeling the diurnal mode of precipitation over the Tropics. Largely an early morning precipitation maximum over the oceans and an afternoon rainfall maximum over land areas describe the first-order diurnal variability. However, large variability in phase and amplitude prevails even within the land and oceanic areas. This paper addresses the importance of a multimodel superensemble for much improved prediction of the diurnal mode as compared to what is possible from individual models. To begin this exercise, the skills of the member models, the ensemble mean of the member models, a unified cloud model, and the superensemble for the prediction of total rain as well as its day versus night distribution were examined. Here it is shown that the distributions of total rain over the earth (tropical belt) and over certain geographical regions are predicted reasonably well (RMSE less than 18) from the construction of a multimodel superensemble. This dataset is well suited for addressing the diurnal change. The large errors in phase of the diurnal modes in individual models usually stem from numerous physical processes such as the cloud radiation, shallow and deep cumulus convection, and the physics of the planetary boundary layer. The multimodel superensemble is designed to reduce such systematic errors and provide meaningful forecasts. That application for the diurnal mode appears very promising. This paper examines some of the regions such as the Tibetan Plateau, the eastern foothills of the Himalayas, and the Amazon region of South America that are traditionally difficult for modeling the diurnal change. In nearly all of these regions, errors in phase and amplitude of the diurnal mode of precipitation increase with the increased length of forecasts. Model forecast errors on the order of 6-12 h for phase and 50 for the amplitude are often seen from the member models. The multimodel superensemble reduces these errors and provides a close match (RMSE < 6 h) to the observed phase. The percent of daily rain and their phases obtained from the multimodel superensemble at 3-hourly intervals for different regions of the Tropics showed a closer match (pattern correlation about 0.4) with the satellite estimates. This is another area where the individual member models conveyed a much lower skill

Prediction of the diurnal cycle using a multimodel superensemble. Part II: Clouds

This study addresses the issue of cloud parameterization in general circulation models utilizing a twofold approach. Four versions of the Florida State University (FSU) global spectral model (GSM) were used, including four different cloud parameterization schemes in order to construct ensemble forecasts of cloud covers. Next, a superensemble approach was used to combine these model forecasts based on their past performance. It was shown that it is possible to substantially reduce the 1-5-day forecast errors of phase and amplitude of the diurnal cycle of clouds from the use of a multimodel superensemble. Further, the statistical information generated in the construction of a superensemble was used to develop a unified cloud parameterization scheme for a single model. This new cloud scheme, when implemented in the FSU GSM, carried a higher forecast accuracy compared to those of the individual cloud schemes and their ensemble mean for the diurnal cycle of cloud cover up to day 5 of the forecasts. This results in a 5-10 W m-2 improvement in the root-mean-square error to the upward longwave and shortwave flux at the top of the atmosphere, especially over deep convective regions. It is shown that while the multimodel superensemble is still the best product in forecasting the diurnal cycle of clouds, a unified cloud parameterization scheme, implemented in a single model, also provides higher forecast accuracy compared to the individual cloud models. Moreover, since this unified scheme is an integral part of the model, the forecast accuracy of the single model improves in terms of radiative fluxes and thus has greater impacts on weather and climate time scales. This new cloud scheme will be tested in real-time simulations

Does currency smirk predict foreign exchange return?

This paper finds the predictive power of currency smirk to forecast foreign exchange (FX) return to be convincing. Although the steeper currency smirk appears in the middle of the trading day, the conclusive currency smirks' predictability lasts over the next trading day, as the FX market is highly adept at incorporating the information embedded in the currency smirk. The implication of these fmdings is that the currency smirk is distinctive for forecasting very short-term FX fluctuations, and that day- or overnight FX traders can apply its uniqueness to profit from quick price swings in the 24-hour globalFX market

Cross border mergers and acquisitions and default risk

Using a cross-country sample of mergers and acquisitions, we examine the role of cultural, institutional, geographic and managerial factors on post-merger default risk. We find that cultural factors, especially the relative difference in uncertainty avoidance between the acquiring and target country, play a significant role in affecting post-merger default risk. Furthermore, we find that institutional quality affects the post-merger default risk of acquiring firms. In contrast to the prior research we do not find any evidence indicating that managerial incentives drive post-merger default risk changes. Also, we do not find any evidence indicating the relevance of geographic distance on default risk

Optimizing the Use of Village Treasury Land: A Case Study of Five Villages in Central Java

Village treasury lands (tanah kas desa) originate from the colonial era and usually comprise a few hectares that remain under the control of the village government. Village Law No. 6/2014 allows villages to manage their own assets, including village treasury lands, for common welfare and the benefit of the most vulnerable groups of the village. Ministry of Home Affairs Regulation 1/2016 stipulates three relevant formats of village land use: rental, cooperation in joint ventures, and Build Operate Transfer/Build Transfer Operate (BOT/BTO). Land is a strategic resource on the Indonesian island of Java, which has a large rural population. The most common plot sizes for farmland are small and can hardly sustain the lives of their owners and are increasingly transformed to serve industrial and infrastructure purposes. For this reason, ensuring the optimal use of village treasury lands is an important policy objective. Sidomulyo and Bonorowo Villages in Kebumen District have applied the rental format for their village land and leased the land to poor farming households. Tlogojati and Beran Villages in Wonosobo District engaged in business cooperation, while villagers in Sukoharjo Village in Wonosobo District applied the BOT format when building and operating a local market. A comparative analysis of experiences in these five villages showed that the rental to farmers in Sidomulyo and Bonorowo provides the lowest gross income to the leaseholders—between IDR 2.6 and 2.8 million per year, from which input costs, rental fees, and labor fees must still be subtracted. Incomes from the cooperation with a tea plantation in Tlogojati provided as much as three times the income, and small businesses in Beran provided the village with over 20 times the income of leaseholders. It is therefore recommended that restrictive Articles 14–16 of MoHA Regulation 1/2016, which stipulate that cooperation in joint ventures and BOT/BTO models can only be considered when village budgets are insufficient, be dropped. Instead, the regulation should introduce a new paradigm for village treasury land utilization: encouraging village entrepreneurship. Entrepreneurship efforts might also involve a role for the private sector, especially when the scale of business exceeds the resources owned by a single village

Aerosol and pollutant transport and their impact on radiative forcing over the tropical Indian ocean during the January - February 1996 pre-INDOEX cruise

Measurements of aerosol bulk composition, optical depth, size distribution and the incoming solar radiation flux were carried out over the coastal waters of India, the Arabian sea and the tropical Indian Ocean during a cruise conducted in January 1996. Aerosol concentrations were relatively high throughout much of the cruise, even when the ship was at considerable distances from land. In this paper, we link the observed spatial variations and meridional gradients in the measurements to monsoonal and inter-hemispheric transport across the ITCZ using a high resolution global reanalysis that highlights the winter monsoon. We show that the northeast monsoonal low level flow can transport sulfates, mineral dust and other aerosols from the Indian sub-continent to the ITCZ within 6–7 days. These transports result in an increase the aerosol optical depth (AOD) at the equator by as much as 0.2 and a decrease in the solar radiative forcing at the sea surface by about 10–20 Wm-2. The high concentrations of continental aerosols are a result of three factors: strong (about 6–10 m/s) near-surface northerly flow; a shallow boundary layer of about 400 to 800 m thick, which traps the pollutants; subsidence, associated with the northeast monsoon, which suppresses rainfall over most of the Arabian sea and thus minimizes the wet removal process. In addition dust can be transported in the middle troposphere from the Arabian desert to the cruise region 4000 km away with a transit time of 2–3 days. There is strong evidence of interhemispheric transports effected by eddies that wrap around the ITCZ. These eddies bring clean southern hemisphere air to about 10°N in the Indian Ocean and carry polluted continental air into the southern-hemisphere. In this manner, substantial amounts of aerosols and other pollutants can be routinely transported to the southern-hemisphere Indian Ocean during the northeast monsoon. Thus, in order to understand the connection between continental emissions and impacts over the Indian Ocean, it is necessary to focus on the rôle of the northeast monsoon in the large-scale atmospheric circulation over this region

Attitudes and Beliefs of African-Americans Toward Genetics, Genetic Testing, and Sickle Cell Disease Education and Awareness

Research among African-Americans indicates this population perceives sickle cell (SCD) to be a serious disease and sickle cell trait (SCT) screening an important intervention. However, studies have consistently demonstrated a lower than desired uptake of SCD education, inadequate knowledge regarding personal and family trait status, and a low perceived susceptibility of giving birth to a child with the disease. We examined general attitudes and beliefs regarding genetics and genetic testing including prenatal testing and newborn screening; we used this information as the foundation to more specifically assess attitudes and beliefs regarding SCD and perceived barriers to SCD education and awareness. Thirty-five African-American adult men and women participated in one of four focus groups. Thematic analysis identified that both prenatal testing and newborn screening are acceptable forms of genetic testing. Based largely on their personal experiences, participants possessed an understanding of the natural progression of SCD but had a limited understanding of the inheritance and probable risk of giving birth to a child with the disease. Barriers to education and greater awareness of SCD were classified as personal, familial, and societal. Community based interventions focused on sharing the stories of individuals with first-hand experiences with SCD should be considered

ENSEMBLES: a new multi-model ensemble for seasonal-to-annual predictions: Skill and progress beyond DEMETER in forecasting tropical Pacific SSTs

A new 46-year hindcast dataset for seasonal-to-annual ensemble predictions has been created using a multi-model ensemble of 5 state-of-the-art coupled atmosphere-ocean circulation models. The multi-model outperforms any of the single-models in forecasting tropical Pacific SSTs because of reduced RMS errors and enhanced ensemble dispersion at all lead-times. Systematic errors are considerably reduced over the previous generation (DEMETER). Probabilistic skill scores show higher skill for the new multi-model ensemble than for DEMETER in the 4–6 month forecast range. However, substantially improved models would be required to achieve strongly statistical significant skill increases. The combination of ENSEMBLES and DEMETER into a grand multi-model ensemble does not improve the forecast skill further. Annual-range hindcasts show anomaly correlation skill of ∼0.5 up to 14 months ahead. A wide range of output from the multi-model simulations is becoming publicly available and the international community is invited to explore the full scientific potential of these data

Experimental real-time multi-model ensemble (MME) prediction of rainfall during monsoon 2008: Large-scale medium-range aspects

Realistic simulation/prediction of the Asian summer monsoon rainfall on various space-time scales is a challenging scientific task. Compared to mid-latitudes, a proportional skill improvement in the prediction of monsoon rainfall in the medium range has not happened in recent years. Global models and data assimilation techniques are being improved for monsoon/tropics. However, multimodel ensemble (MME) forecasting is gaining popularity, as it has the potential to provide more information for practical forecasting in terms of making a consensus forecast and handling model uncertainties. As major centers are exchanging model output in near real-time, MME is a viable inexpensive way of enhancing the forecasting skill and information content. During monsoon 2008, on an experimental basis, an MME forecasting of large-scale monsoon precipitation in the medium range was carried out in real-time at National Centre for Medium Range Weather Forecasting (NCMRWF), India. Simple ensemble mean (EMN) giving equal weight to member models, biascorrected ensemble mean (BCEMn) and MME forecast, where different weights are given to member models, are the products of the algorithm tested here. In general, the aforementioned products from the multi-model ensemble forecast system have a higher skill than individual model forecasts. The skill score for the Indian domain and other sub-regions indicates that the BCEMn produces the best result, compared to EMN and MME. Giving weights to different models to obtain an MME product helps to improve individual member models only marginally. It is noted that for higher rainfall values, the skill of the global model rainfall forecast decreases rapidly beyond day-3, and hence for day-4 and day-5, the MME products could not bring much improvement over member models. However, up to day-3, the MME products were always better than individual member models