Hasil untuk "Meteorology. Climatology"

Nicolas Page, Alireza Gholami, Qian Zhang

In response to the global challenge of climate change, financial institutions are increasingly called upon to assess and disclose their carbon emissions. Various global carbon quantification and reporting standards were developed, such as the Greenhouse Gas (GHG) Protocol, Task Force on Climate-related Financial Disclosures (TCFD), Partnership for Carbon Accounting Financials (PCAF) and others. Unfortunately, the now diverse landscape of standards increases the complexity for institutions seeking to develop voluntary carbon quantification and reporting. This study addresses the complexity issue by developing a criteria-based tool that summarizes the various components and requirements of the carbon standards. We propose eight criteria that summarize the standards’ key elements, requirements and relevance to the financial industry. We analyze seven major carbon quantification and reporting standards, systematically evaluating them against our tool. By doing so, we provide financial institutions with valuable insights in selecting appropriate standards to inform their emissions quantification and reporting decisions.

Karine Sartelet, Jules Kerckhoffs, Eleni Athanasopoulou et al.

Mapping urban pollution is essential for assessing population exposure and addressing associated health impacts. High urban concentrations are due to the proximity of sources such as traffic or residential heating, and to urban density with the presence of buildings that reduce street ventilation. This urban complexity makes fine-scale mapping challenging, even for regulated pollutants such as NO2 and PM2.5. In this study we apply state-of-the-art empirical and deterministic modeling approaches to produce high-resolution (<100 m) pollution maps across five European cities (Paris, Athens, Birmingham, Rotterdam, Bucharest). These methodologies enable full-city mapping capturing intra-urban gradients of concentrations. Depending on the methodology, regulated pollutants (NO2, PM2.5) and/or emerging pollutants (black carbon (BC) and ultrafine particles (UFP characterized here by particulate number concentration PNC)) are considered. For deterministic modelling, different approaches are presented: a multi-scale Eulerian modelling chain down to the street scale with chemistry/aerosol dynamics at all scales, multi-scale hybrid models with Eulerian regional dispersion and Gaussian subgrid dispersion, and a Gaussian-based model. Empirical land use regression models were developed based upon mobile monitoring.To compare the relative performance of the methodologies and to evaluate their performance and limitations, the modelling results are compared to fixed measurement stations. We introduce a standardized metric to quantify spatial and seasonal variability and assess each method’s capacity to reproduce fine-scale urban heterogeneity. We also evaluate how data assimilation affects both concentration accuracy and variability representation—particularly relevant for emerging pollutants where measurement data are sparse. We confirm established seasonal and spatial patterns: spatial variability is more pronounced for PNC, NO2 and BC than PM2.5, and concentrations are higher during the winter periods. We also observe reduced spatial variability in winter for PM2. 5 (linked to residential heating) and for BC in cities with significant wood burning emissions. This study adds unique value by evaluating these patterns using fixed measurement stations, and quantifying them across entire urban areas at very fine spatial resolution (<100 m). Furthermore, important methodological strengths and limitations are pointed out, providing practical guidance for the selection and improvement of urban exposure mapping methods, supporting the implementation of the new EU Air Quality Directive.

Thomas C. Pagano, Elizabeth E. Ebert, Mohammadreza Khanarmuei

ABSTRACT Forecast verification is an essential function of National Meteorological and Hydrological Services (NMHSs), underpinning their ability to deliver accurate, reliable, and actionable weather, climate, and water‐related information. As NMHSs face increasing demands for transparency, accountability, and continuous improvement, they require robust systems to assess and enhance the quality of their forecasts. This article presents a holistic forecast verification capability development framework, built from over a decade of focused effort at the Australian Bureau of Meteorology. The framework integrates best practices in governance, data management, verification metrics, and communication. It acknowledges the importance of user‐centered approaches and highlights areas where verification practices can align with user needs. To support NMHSs in adopting this framework, the article introduces two practical tools: a Verification Planning Template for establishing new verification activities and systems and a Gap Analysis and Maturity Assessment (GAMA) tool for benchmarking and advancing existing practices. These tools provide structured guidance for planning, evaluating, and improving verification within a NMHS, with the ultimate goal of delivering higher quality forecasts that meet diverse stakeholder needs. The Bureau's progress in implementing this framework demonstrates significant benefits, including improved forecast quality, enhanced coordination across verification efforts, and greater trust among users. However, challenges such as data availability, system integration, and resourcing remain pervasive, both within the Bureau and globally. The tools and insights shared in this article offer a pathway for NMHSs to overcome these obstacles, enabling them to better respond to evolving user expectations and operational demands. This work highlights the value of fostering a strong verification culture, supported by collaboration and knowledge sharing across the international meteorological community. By applying the principles and tools presented here, and customizing them to their circumstances, NMHSs can advance toward resilient, evidence‐based verification practices and capabilities that enhance forecast reliability and stakeholder confidence worldwide.

Andrés Alegría, Elvira Poloczanska, Sina Loeschke et al.

Abstract Climate risk assessments are crucial in quantifying and communicating risks in a clear and concise manner. In light of the rapidly proceeding climatic changes, there is a growing need for a more comprehensive integration and a more effective overview of available and relevant data that go into these assessments, particularly on the temporal and spatial dynamics of risk. In this paper, we describe the advantages, challenges and opportunities for increasing the accessibility of temporal and spatial data needed to support climate risk assessments through the development of an Intergovernmental Panel on Climate Change (IPCC) Atlas, integrated across IPCC Working Groups. We propose that using a climate risk framework to organise this Atlas will result in a more practical resource for understanding and informing risk assessments undertaken by the IPCC, and also make methodologies and results more accessible to a wider audience.

Wenjie Tian, Lili Zhang, Tao Yu et al.

CO₂ is one of the primary greenhouse gases impacting global climate change, making it crucial to understand the spatiotemporal variations of CO₂. Currently, commonly used satellites serve as the primary means of CO₂ observation, but they often suffer from striping issues and fail to achieve complete coverage. This paper proposes a method for constructing a comprehensive high-spatiotemporal-resolution XCO₂ dataset based on multiple auxiliary data sources and satellite observations, utilizing multiple simple deep neural network (DNN) models. Global validation results against ground-based TCCON data demonstrate the excellent accuracy of the constructed XCO₂ dataset (R is 0.94, RMSE is 0.98 ppm). Using this method, we analyze the spatiotemporal variations of CO₂ in China and its surroundings (region: 0°–60° N, 70°–140° E) from 2019 to 2020. The gapless and fine-scale CO₂ generation method enhances people’s understanding of CO₂ spatiotemporal variations, supporting carbon-related research.

Halah E. Aljofi, Thomas J. Bannan, Michael Flynn et al.

Low-cost personal exposure monitors (PEMs) to measure personal exposure to air pollution are potentially promising tools for health research. However, their adoption requires robust validation. This study evaluated the performance of twenty-one Plume Lab Flow2s (PLFs) by comparing its air pollutant measurements, particulate matter with a diameter of 2.5 μm or less (PM_2.5), 10 μm or less (PM₁₀), and nitrogen dioxide (NO₂), against several high-quality air pollution monitors under field conditions (at indoor, outdoor, and roadside locations). Correlation and regression analysis were used to evaluate measurements obtained by different PLFs against reference instrumentation. For all measured pollutants, the overall correlation coefficient between the PLFs and the reference instruments was often weak (r < 0.4). Moderate correlation was observed for one PLF unit at the indoor location and two units at the roadside location when measuring PM_2.5, but not for PM₁₀ and NO₂ concentration. During periods of particularly higher pollution, 11 PLF tools showed stronger regression results (R² values > 0.5) with one-hour and 9 PLF units with one-minute time interval. Results show that the PLF cannot be used robustly to determine high and low exposure to poor air. Therefore, the use of PLFs in research studies should be approached with caution if data quality is important to the research outputs.

Ruijia NIU, Lijuan WEN, Mengxiao WANG et al.

Many lakes are widely and densely distributed on the Qinghai-Tibet Plateau.Due to the high altitude， the lakes seasonally freeze with a long ice-covered period.Lake ice can significantly affect the local and regional climate and the sub-glacial aquatic ecosystem by changing the transfer process of radiation energy on and in the lakes.However， their characteristics during the ice-covered period still remain unclear.Therefore， from February 6 to 28， 2022， we conducted a systematic observation of water ice air in Qinghai Lake， the largest lake on the Qinghai-Tibet Plateau.Using field observation data， video images and the precipitation data of peripheral observation stations， the influence of different ice cover conditions on the radiation and temperature of the water-ice-atmosphere on Qinghai Lake during the ice-covered period was analyzed.Results showed that different weather processes such as snowfall， sand and gale could remarkably change the property of cover on the ice， leading to variations of ice thickness on Qinghai Lake.Furthermore， the discrepancies of solar radiation absorption and reflection of different covers result in energy equilibrium that directly dictate ice surface temperature at water-ice-atmosphere interface.Bare ice with low albedo and low absorption induced the relatively strong net solar radiation and the correspondingly large diurnal variations of ice temperature.Compared to bare ice， the high reflection of snow cover and the strong absorption of sand and dust make the ability of net short-wave radiation to penetrate ice weaker， and the diurnal variation of lake ice temperature is smaller.

Ido Nevat, Ayu Sukma Adelia

We develop a new model for urban wind corridors analysis and detection of urban wind ventilation potential based on concepts and principles of network theory. Our approach is based solely on data extracted from spatial urban features that are easily obtained from a 3D model of the city. Once the spatial features have been extracted, we embed them onto a graph topology. This allows us to use theories and techniques of network theory, and in particular graph theory. Utilizing such techniques, we perform end-to-end network flow analysis of the wind potential across the city and, in particular, estimate the locations, strengths, and paths of the wind corridors. To calibrate our model, we use a dataset generated by a meso-scale climate model and estimate the model parameters by projecting the wind vector field of the climate model onto a graph, thus providing a meaningful comparison of the two models under a new metric. We illustrate our modeling approach on the city of Singapore and explain how the results are useful for climate-informed urban design.

Chang Lai, Jiyao Xu, Zhishuang Lin et al.

Abstract For the first time, we used the machine learning method to analyze the statistical occurrence and propagation characteristics of nighttime medium‐scale traveling ionospheric disturbances (MSTIDs) from October 2011 to December 2021 observed by the all‐sky airglow imager deployed at Xinglong (40.4°N, 117.6°E, 30.5° MLAT), China. We developed a program code using the algorithms to identify and extract the propagation and morphological features of MSTIDs in 630 nm airglow images automatically. The classification model and detection model have accuracies of 96.9% and 70%–85%, respectively. We identified 611 MSTID events from 749,888 airglow images, and obtained the following statistical results: (a) the MSTIDs occurrence peaked at 2200–2300 local time in summer and 2300–2400 in winter; (b) the annual average of horizontal wavelength and velocity are 160–311 km and 98–133 m/s, respectively; (c) among 611 events, 589 MSTIDs propagated southwestward. Fifteen events are northeastward and all of them are periodic MSTIDs, most of which occurred between April and August; (d) the annual trend of relative intensity perturbation (%) shows a negative correlation with the horizontal phase speed; (e) horizontal wavelengths of MSTIDs are independent of the solar activity. Further analyses found those southwestward propagating MSTIDs are consistent with the Es‐Perkins coupling theory, while those non‐southwestward ones could be related to the atmospheric gravity waves and other possible sources. The northeastward events exhibit morphological and seasonal characteristics, which cannot be explained by the Perkins instability, more simultaneous observations (GPS‐TEC, OH airglow, etc.) are required to reveal the mechanism behind these characteristics.

Mhd. Suhyb Salama, Lazaros Spaias, Kathrin Poser et al.

It is common in estuarine waters to place fixed monitoring stations, with the advantages of easy maintenance and continuous measurements. These two features make fixed monitoring stations indispensable for understanding the optical complexity of estuarine waters and enable an improved quantification of uncertainties in satellite-derived water quality variables. However, comparing the point-scale measurements of stationary monitoring systems to time-snapshots of satellite pixels suffers from additional uncertainties related to temporal/spatial discrepancies. This research presents a method for validating satellite-derived water quality variables with the continuous measurements of a fixed monitoring station in the Ems Dollard estuary on the Dutch-German borders. The method has two steps; first, similar in-situ measurements are grouped. Second, satellite observations are upscaled to match these point measurements in time and spatial scales. The upscaling approach was based on harmonizing the probability distribution functions of satellite observations and in-situ measurements using the first and second moments. The fixed station provided a continuous record of data on suspended particulate matter (SPM) and chlorophyll-a (Chl-a) concentrations at 1 min intervals for 1 year (2016–2017). Satellite observations were provided by Sentinel-2 (MultiSpectral Instrument, S2-MSI) and Sentinel-3 (Ocean and Land Color Instrument, S3-OLCI) sensors for the same location and time of in-situ measurements. Compared to traditional validation procedures, the proposed method has improved the overall fit and produced valuable information on the ranges of goodness-of-fit measures (slope, intercept, correlation coefficient, and normalized root-mean-square deviation). The correlation coefficient between measured and derived SPM concentrations has improved from 0.16 to 0.52 for S2-MSI and 0.14 to 0.84 for S3-OLCI. For the Chl-a matchup, the improvement was from 0.26 to 0.82 and from 0.14 to 0.63 for S2-MSI and S3-OLCI, respectively. The uncertainty in the derived SPM and Chl-a concentrations was reduced by 30 and 23% for S2-SMI and by 28 and 16% for S3-OLCI. The high correlation and reduced uncertainty signify that the matchup pairs are observing the same fluctuations in the measured variable. These new goodness-of-fit measures correspond to the results of the performed sensitivity analysis, previous literature, and reflect the inherent accuracy of the applied derivation model.

Nathan P. Gillett, Alex J. Cannon, Elizaveta Malinina et al.

A strong atmospheric river made landfall in southwestern British Columbia, Canada on November 14th, 2021, bringing two days of intense precipitation to the region. The resulting floods and landslides led to the loss of at least five lives, cut Vancouver off entirely from the rest of Canada by road and rail, and made this the costliest natural disaster in the province's history. Here we show that when characterised in terms of storm-averaged water vapour transport, the variable typically used to characterise the intensity of atmospheric rivers, westerly atmospheric river events of this magnitude are approximately one in ten year events in the current climate of this region, and that such events have been made at least 60% more likely by the effects of human-induced climate change. Characterised in terms of the associated two-day precipitation, the event is substantially more extreme, approximately a one in fifty to one in a hundred year event, and the probability of events at least this large has been increased by a best estimate of 45% by human-induced climate change. The effects of this precipitation on streamflow were exacerbated by already wet conditions preceding the event, and by rising temperatures during the event that led to significant snowmelt, which led to streamflow maxima exceeding estimated one in a hundred year events in several basins in the region. Based on a large ensemble of simulations with a hydrological model which integrates the effects of multiple climatic drivers, we find that the probability of such extreme streamflow events in October to December has been increased by human-induced climate change by a best estimate of 120–330%. Together these results demonstrate the substantial human influence on this compound extreme event, and help motivate efforts to increase resiliency in the face of more frequent events of this kind in the future.

F. Aemisegger, R. Vogel, P. Graf et al.

<p>The interaction between low-level tropical clouds and the large-scale circulation is a key feedback element in our climate system, but our understanding of it is still fragmentary. In this paper, the role of upper-level extratropical dynamics for the development of contrasting shallow cumulus cloud patterns in the western North Atlantic trade wind region is investigated. Stable water isotopes are used as tracers for the origin of air parcels arriving in the sub-cloud layer above Barbados, measured continuously in water vapour at the Barbados Cloud Observatory during a 24 d measurement campaign (isoTrades, 25 January to 17 February 2018). These data are combined with a detailed air parcel back-trajectory analysis using hourly ERA5 reanalyses of the European Centre for Medium-Range Weather Forecasts. A climatological investigation of the 10 d air parcel history for January and February in the recent decade shows that 55 % of the air parcels arriving in the sub-cloud layer have spent at least 1 d in the extratropics (north of 35<span class="inline-formula">^∘</span> N) before arriving in the eastern Caribbean at about 13<span class="inline-formula">^∘</span> N. In 2018, this share of air parcels with extratropical origin was anomalously large, with 88 %. In two detailed case studies during the campaign, two flow regimes with distinct isotope signatures transporting extratropical air into the Caribbean are investigated. In both regimes, the air parcels descend from the lower part of the midlatitude jet stream towards the Equator, at the eastern edge of subtropical anticyclones, in the context of Rossby wave breaking events. The zonal location of the wave breaking and the surface anticyclone determine the dominant transport regime. The first regime represents the “typical” trade wind situation, with easterly winds bringing moist air from the eastern North Atlantic into the Caribbean, in a deep layer from the surface up to <span class="inline-formula">∼600</span> hPa. The moisture source of the sub-cloud layer water vapour is located on average 2000 km upstream of Barbados. In this regime, Rossby wave breaking and the descent of air from the extratropics occur in the eastern North Atlantic, at about 33<span class="inline-formula">^∘</span> W. The second regime is associated with air parcels descending slantwise by on average 300 hPa (6 d)<span class="inline-formula">⁻¹</span> directly from the north-east, i.e. at about 50<span class="inline-formula">^∘</span> W. These originally dry airstreams experience a more rapid moistening than typical trade wind air parcels when interacting with the subtropical oceanic boundary layer, with moisture sources being located on average 1350 km upstream to the north-east of Barbados. The descent of dry air in the second regime can be steered towards the Caribbean by the interplay of a persistent upper-level cut-off low over the central North Atlantic (about 45<span class="inline-formula">^∘</span> W) and the associated surface cyclone underneath. The zonal location of Rossby wave breaking and, consequently, the pathway of extratropical air towards the Caribbean are shown to be relevant for the sub-cloud layer humidity and shallow-cumulus-cloud-cover properties of the North Atlantic winter trades. Overall, this study highlights the importance of extratropical dynamical processes for the tropical water cycle and reveals that these processes lead to a substantial modulation of stable water isotope signals in the near-surface humidity.</p>

Julian J. Spergel, Jonathan Kingslake, Timothy Creyts et al.

Surface melting on Amery Ice Shelf (AIS), East Antarctica, produces an extensive supraglacial drainage system consisting of hundreds of lakes connected by surface channels. This drainage system forms most summers on the southern portion of AIS, transporting meltwater large distances northward, toward the ice front and terminating in lakes. Here we use satellite imagery, Landsat (1, 4 and 8), MODIS multispectral and Sentinel-1 synthetic aperture radar to examine the seasonal and interannual evolution of the drainage system over nearly five decades (1972–2019). We estimate seasonal meltwater input to one lake by integrating output from the regional climate model [Regional Atmospheric Climate Model (RACMO 2.3p2)] over its catchment defined using the Reference Elevation Model of Antarctica. We find only weak positive relationships between modeled seasonal meltwater input and lake area and between meltwater input and lake volume. Consecutive years of extensive melting lead to year-on-year expansion of the drainage system, potentially through a link between melt production, refreezing in firn and the maximum extent of the lakes at the downstream termini of drainage. These mechanisms are important when evaluating the potential of drainage systems to grow in response to increased melting, delivering meltwater to areas of ice shelves vulnerable to hydrofracture.

M. Savenets, L. Pysarenko, D. Pishniak

The study presents analysis of microclimatic conditions on Galindez Island (western part of the Antarctic Peninsula), in particular: seasonal variability and spatial heterogeneity. Based on land surface temperature (LST) data derived from loggers and MicroClimate Monitoring Station, we analyzed areas with active growth of local plants. Seasonal variations formed mainly under annual and semi-annual cycles, with no dependencies of amplitudes and phases form area location. LST highly correlates with air temperature and total incoming irradiance. It is emphasized that spatial orientation of relief microforms plays the most significant role for LST formation on micro-level. Using cluster analysis, it was found that temperature loggers which are located along shoreline and oriented to the north–north-east could be grouped by similar LST distribution.

L. Båserud, C. Lussana, T. N. Nipen et al.

<p>In science, poor quality input data will invariably lead to faulty conclusions, as in the spirit of the saying “garbage in, garbage out”. Atmospheric sciences make no exception and correct data is crucial to obtain a useful representation of the real world in meteorological, climatological and hydrological applications. Titan is a computer program for the automatic quality control of meteorological data that has been designed to serve real-time operational applications that process massive amounts of observations measured by networks of automatic weather stations. The need to quality control third-party data, such as citizen observations, within a station network that is constantly changing was an important motivation that led to the development of Titan. The quality control strategy adopted is a sequence of tests, where several of them utilize the expected spatial consistency between nearby observations. The spatial continuity can also be evaluated against independent data sources, such as numerical model output and remote sensing measurements. Examples of applications of Titan for the quality control of near-surface hourly temperature and precipitation over Scandinavia are presented. In the case of temperature, this specific application has been integrated into the operational production chain of automatic weather forecasts at the Norwegian Meteorological Institute (MET Norway). Titan is an open source project and it is made freely available for public download. One of the objectives of the Titan project is to establish a community working on common tools for automatic quality control, and the Titan program represents a first step in that direction for MET Norway. Further developments are necessary to achieve a solution that satisfies more users, for this reason we are currently working on transforming Titan into a more flexible library of functions.</p>

D. I. Benn, A. C. Fowler, I. Hewitt et al.

We present the first general theory of glacier surging that includes both temperate and polythermal glacier surges, based on coupled mass and enthalpy budgets. Enthalpy (in the form of thermal energy and water) is gained at the glacier bed from geothermal heating plus frictional heating (expenditure of potential energy) as a consequence of ice flow. Enthalpy losses occur by conduction and loss of meltwater from the system. Because enthalpy directly impacts flow speeds, mass and enthalpy budgets must simultaneously balance if a glacier is to maintain a steady flow. If not, glaciers undergo out-of-phase mass and enthalpy cycles, manifest as quiescent and surge phases. We illustrate the theory using a lumped element model, which parameterizes key thermodynamic and hydrological processes, including surface-to-bed drainage and distributed and channelized drainage systems. Model output exhibits many of the observed characteristics of polythermal and temperate glacier surges, including the association of surging behaviour with particular combinations of climate (precipitation, temperature), geometry (length, slope) and bed properties (hydraulic conductivity). Enthalpy balance theory explains a broad spectrum of observed surging behaviour in a single framework, and offers an answer to the wider question of why the majority of glaciers do not surge.

Shuixin Zhong, Zitong Chen

Warm Sector Torrential Rains (WSTRs) occurring during the outbreak of the monsoon in May of 2015 in South China were studied using surface automatic weather observational data, sounding, European Centre for Medium-Range Weather Forecasts Reanalysis interim Data (ERA-interim), satellite and radar data, and a four-level nested grid simulation with the finest grid spacing of 1 km using the Weather Research and Forecasting model (WRF). The results show that the extreme precipitation event, which had maximum rainfall amounts of 406.3 mm in 10 h and 542.2 mm in 24 h on 20 May 2015, and was characterized by its rapid development and its highly concentrated and long duration of heavy rainfall, occurred over the trumpet-shaped topography of Haifeng. The simulation results indicated that the South China Sea (SCS) atmospheric moisture transportation (AMT) was crucial in triggering the precipitation of the WSTR over South China. The simulation of the WSTR was conducted by using the total energy-mass flux scheme (TEMF), which provided a reasonable simulation of the circulation and the vertical profile in the Planetary Boundary Layer (PBL) as well as the estimation of the precipitation. The AMT, which extends from the Beibu Gulf and the South China Sea to the coastal areas and provides Shanwei with a considerable amount of moisture in the boundary layer, and the effects within the PBL, which include orographic effects, an extra low-level jet, and a high-energy tongue characterized by a high-potential pseudo-equivalent temperature tongue with a warm and moist southwesterly wind, were the important large-scale factors causing the WSTR.

Andrea Lammert, Felix Ament

Remote sensing sensors on board of research aircraft provide detailed measurements of clouds and precipitation which can be used as reference data to validate satellite products. Such satellite derived precipitation data using passive microwave radiometers with a resolution of typically 50×50km2$50\times50\,\text{km}^2$ stands against high spatial and temporal resolved airborne measurements, but only along a chosen line. This paper focuses on analysis on the uncertainty arising from the different spatial resolution and coverage. Therefore we use a perfect model approach, with a high resolved forecast model yielding perfect virtual aircraft and satellite observations. The mean precipitation and standard deviation per satellite box were estimated with a Gaussian approach. The comparison of the mean values shows a high correlation of 0.92, but a very wide spread. As criterion to define good agreement between satellite mean and reference, we choose a deviation of one standard deviation of the virtual aircraft as threshold. Considering flight tracks in the range of 50 km (one overflight), the perfect agreement of satellite and aircraft observations is only detected in 65 % of the cases. To increase this low reliability the precipitation distributions of the virtual aircraft were fitted by a gamma density function. Using the same quality criterion, the usage of gamma density fit yields an improvement of the Aircraft reliability up to 80 %.

Emmanuel Lubango Ndetto, Andreas Matzarakis

A long-term simulation of urban climate was done using the easily available long-term meteorological data from a nearby synoptic station in a tropical coastal city of Dar es Salaam, Tanzania. The study aimed at determining the effects of buildings’ height and street orientations on human thermal conditions at pedestrian level. The urban configuration was represented by a typical urban street and a small urban park near the seaside. The simulations were conducted in the microscale applied climate model of RayMan, and results were interpreted in terms of the thermal comfort parameters of mean radiant (Tmrt) and physiologically equivalent (PET) temperatures. PET values, high as 34°C, are observed to prevail during the afternoons especially in the east-west oriented streets, and buildings’ height of 5 m has less effect on the thermal comfort. The optimal reduction of Tmrt and PET values for pedestrians was observed on the nearly north-south reoriented streets and with increased buildings’ height especially close to 100 m. Likewise, buildings close to the park enhance comfort conditions in the park through additional shadow. The study provides design implications and management of open spaces like urban parks in cities for the sake of improving thermal comfort conditions for pedestrians.

Renata Weissmann Borges Mendonça, José Paulo Bonatti

O desempenho do Modelo Global do Centro de Previsão de Tempo e Estudos Climáticos (CPTEC) em simular a energética modal para um composto de sete episódios de Zona de Convergência do Atlântico Sul (ZCAS) é avaliado, enfatizando-se a influência da resolução espacial do modelo e de três diferentes parametrizações de convecção profunda: Kuo, Relaxed Arakawa-Schubert (RAS) e Grell na partição vertical de energia entre os modos externos e internos, e as trocas de energia entre os modos horizontais de oscilação Rossby, Kelvin, Misto Rossby-Gravidade, Gravidade Oeste e Leste. Os resultados mostraram que as previsões utilizando os esquemas de convecção profunda Kuo, RAS e Grell foram semelhantes entre si e apresentaram uma boa concordância em relação aos padrões obtidos na parte observacional (Parte I deste artigo). O emprego de diferentes esquemas de convecção profunda não apresentou impactos significativos na partição e interação de energia entre os modos verticais e horizontais. Um impacto maior foi obtido com o aumento da resolução vertical das análises e do modelo, de 28 para 42 níveis, em que um maior número de modos internos apresenta um papel relevante nas trocas horizontais e verticais de energia.<br>The performance of the CPTEC Global Model in simulating the modal energetics for a composite of seven South Atlantic Convergence Zone (SACZ) episodes was evaluated, emphasizing the influence of the model resolution and the three different deep convection parameterizations: Kuo, Relaxed Arakawa-Schubert (RAS) and Grell on the vertical energy partition between external and internal modes and on the energy interactions within and between various horizontal oscillation modes: Rossby, Kelvin, Mixed Rossby-Gravity and West and East Gravity. The results showed that the model predictions using the Kuo, RAS and Grell deep convection schemes were similar with each other, and had a good agreement with the patterns obtained in the observational part (Part I of this paper). The use of different deep convection schemes did not present significant impact in the partition and interaction of energy between vertical and horizontal modes. A greater impact was obtained when increasing the vertical resolution of the analyses and the model from 28 to 42 levels. A greater number of internal modes show a relevant role in the horizontal and vertical energy exchanges, in terms of representing the observed characteristics.