Evaluation and Assimilation of FY-3C/D MWHS-2 Radiances in the RMAPS-ST

Currently, humidity information can be obtained from the Microwave Humidity Sounder-2 (MWHS-2) mounted on the polar-orbiting satellites FY-3C and FY-3D. However, making full use of the MWHS-2 data remains a challenge, particularly in the application of regional numerical weather models. This study is the first to include MWHS-2 radiance data in the Rapid-refresh Multi-scale Analysis and Prediction System—Short-term (RMAPS-ST) regional model. The results and impact of MWHS-2 radiance data assimilation were investigated and evaluated. It is found that MWHS-2 radiance data can be effectively assimilated in the RMAPS-ST after a series of quality control and variational bias correction. Benefits could be obtained in the reduction of background departures for each humidity sounding channel. Assimilation experiments over a period of one month were carried out, and the impacts of MWHS-2 radiances were quantitatively analyzed on the forecasts of RMAPS-ST system. The results showed that MWHS-2 saw a small but significant improvement for low-level humidity of short-range forecast, by 16.5% and 3.2% in terms of mean bias and root-mean-square error, respectively. The positive impact on short-range forecast also can be found for middle and low level temperature and wind. For quantitative precipitation forecast, the assimilation of MWHS-2 radiances increased the score skills of different rainfall levels in the first 12 h forecast by an average of 1.4%. There was a slight overall improvement in the 24-h precipitation forecast for over-estimation and false alarm of 3-h accumulated rainfall below 1.0 mm, with 0.75% and 0.36%, respectively. The addition of MWHS-2 radiance data gives a small positive impact on low-level humidity, temperature, and wind in the RMAPS-ST regional model, and it also improves short-range forecast of rainfall, particularly in the first 12 h of the forecast.

Internal tides off the Amazon shelf during two contrasted seasons: Interactions with background circulation and SSH imprints

The Amazon shelf break is a key region for internal tides (IT) generation. The region also shows a large seasonal variation of circulation and associated stratification. The objective of this study is to document how these variations will impact IT generation and propagation properties. A high-resolution regional model (1/36° horizontal resolution), explicitly resolving IT is analyzed to investigate their interactions with the background circulation and stratification, over two seasons: first MAMJJ (March to July), with weaker mesoscale currents, shallower and stronger pycnocline, and second ASOND (August to December) with stronger mesoscale currents, deeper and weaker pycnocline. IT are generated on the shelf break between the 100 and 1800 m isobaths, with a maximum on average at about 10 km offshore. South of 2° N, the conversion from barotropic to baroclinic tide is more efficient in MAMJJ than in ASOND. At the eight main IT generations sites, the local dissipation is higher in MAMJJ (30 %) than in ASOND (22 %). The remaining fraction propagates away from the generation sites and mainly dissipates locally every 90–120 km. The remote dissipation increases slightly during ASOND and the coherent M2 fluxes seem blocked between 4°–6° N west of 47° W. Further analysis of 25 hours mean snapshots of the baroclinic flux shows deviation and branching of the IT when interacting with strong mesoscale and stratification. We evaluated sea surface height (SSH) frequency and wavenumber spectra for subtidal (f < 1/28h−1), tidal (1/28h−1 < f < 1/11h−1) and super tidal (f > 1/11h−1) frequencies. Tidal frequencies explain most of the SSH variability for wavelengths between 300 km and 70 km. Below 70 km, the SSH is mainly incoherent and supertidal. The length scale at which the SSH becomes dominated by unbalanced IT was estimated to be around 250 km. Our results highlight the complexity of correctly predicting IT SSH in order to better observe mesoscale and submesoscale from existing and upcoming altmetrics missions, notably the Surface Water Ocean Topography (SWOT) mission.

Véderdő telepítésének lehetséges jövőbeli hatásai Szeged hőterhelésében

n this study the possible future thermal consequences of a fictional protective forest around Szeged were examined. The aims of this installation are the adaptation to climate change and reducing air pollution. However, the complex effects of local urban climate should be taken into consideration as well. Therefore, the changing of heat load due to the forest was studied by presenting the change of climate indices during the 21st century. In order to simulate the local circumstances of the city, a MUKLIMO_3 local scale model was applied. EURO-CORDEX regional model simulations ensured the climate data for periods 2021–2050 and 2071–2100 using scenarios RCP4.5 and RCP8.5. Our results show that the effect of the protective forest is not favourable in certain parts of the city due to the reduction or block of the ventilation. The forest induces cooling effect mostly during daytime, but the extent of unfavourable effects exceeds the advantages especially at night time.

Microlearning and microteaching: prospects of improvement in regions within crosscultural education

The research article explores the evolving trends in modern education, which are microlearning and microteaching. The authors analyze microlearning and microteaching as the most progressive and up-to-date approach. This article brings up the role of the globalization in the process of education encompassing crosscultural education. Although micro learning and teaching embrace many demands of modern learning and teaching, the approaches catering to the needs of students from different regions, have not been developed yet. Therefore, the main objective is to demonstrate the opportunities which microlearning offers within crosscultural education. The authors consider theoretical and empirical revie w of the literature and a conceptual framework to be the basic methods. The results obtained can be formulated as follows: a regional model of the micro-learning education (learning and teaching) with a set of specific character traits of students to facilitate the ideas of microeducation has been developed. This article is aimed to discuss the evolvement, current perceptions, basic principles and tools of microteaching and microlearning; to analyze their efficiency in the modern world and to suggest its further development through analysis of cross-culturalism in education using Hoffstede's dimensions including the model for regional program developing within crosscultural education.

North and South: A Regional Model of the UK

We set up a two-region model to study the policy challenge of bringing the North’s income up to the level of the South in the UK. The model focuses on labour costs as the driver of output gains through the international competitiveness channel; and on tax/regulative costs to entrepreneurs as the driver of productivity growth. The empirical results show that the regional model behaviour fits the regional UK data behaviour over the period of 1986Q1 and 2019Q4, using the demanding Indirect Inference method. We also carry out a Monte Carlo power test, which shows the empirical results we obtain are trustworthy and can provide us a reliable guide for policy reform. The results suggest that in response to tax cuts and labour market reforms GDP in the North increases almost twice as much as GDP in the South. Given that a broad programme of tax cuts and regulatory reform would more than pay for itself in the long run, it must be considered as a highly attractive political agenda.

Understanding the surface temperature response and its uncertainty to CO₂, CH₄, black carbon, and sulfate

Understanding the regional surface temperature responses to different anthropogenic climate forcing agents, such as greenhouse gases and aerosols, is crucial for understanding past and future regional climate changes. In modern climate models, the regional temperature responses vary greatly for all major forcing agents, but the causes of this variability are poorly understood. Here, we analyze how changes in atmospheric and oceanic energy fluxes due to perturbations in different anthropogenic climate forcing agents lead to changes in global and regional surface temperatures. We use climate model data on idealized perturbations in four major anthropogenic climate forcing agents (CO2, CH4, sulfate, and black carbon aerosols) from Precipitation Driver Response Model Intercomparison Project (PDRMIP) climate experiments for six climate models (CanESM2, HadGEM2-ES, NCAR-CESM1-CAM4, NorESM1, MIROC-SPRINTARS, GISS-E2). Particularly, we decompose the regional energy budget contributions to the surface temperature responses due to changes in longwave and shortwave fluxes under clear-sky and cloudy conditions, surface albedo changes, and oceanic and atmospheric energy transport. We also analyze the regional model-to-model temperature response spread due to each of these components. The global surface temperature response stems from changes in longwave emissivity for greenhouse gases (CO2 and CH4) and mainly from changes in shortwave clear-sky fluxes for aerosols (sulfate and black carbon). The global surface temperature response normalized by effective radiative forcing is nearly the same for all forcing agents (0.63, 0.54, 0.57, 0.61 K W−1 m2). While the main physical processes driving global temperature responses vary between forcing agents, for all forcing agents the model-to-model spread in temperature responses is dominated by differences in modeled changes in longwave clear-sky emissivity. Furthermore, in polar regions for all forcing agents the differences in surface albedo change is a key contributor to temperature responses and its spread. For black carbon, the modeled differences in temperature response due to shortwave clear-sky radiation are also important in the Arctic. Regional model-to-model differences due to changes in shortwave and longwave cloud radiative effect strongly modulate each other. For aerosols, clouds play a major role in the model spread of regional surface temperature responses. In regions with strong aerosol forcing, the model-to-model differences arise from shortwave clear-sky responses and are strongly modulated by combined temperature responses to oceanic and atmospheric heat transport in the models.