Relative Humidity Profiles Research Articles

A Data-Driven Approach to Forecasting Heating and Cooling Energy Demand in an Office Building as an Alternative to Multi-Zone Dynamic Simulation

Nowadays, as more data is now available from an increasing number of installed sensors, load forecasting applied to buildings is being increasingly explored. The amount and quality of resulting information can provide inputs for smarter decisions when managing and operating office buildings. In this article, the authors use two data-driven methods (artificial neural networks and support vector machines) to predict the heating and cooling energy demand in an office building located in Lisbon, Portugal. In the present case-study, these methods prove to be an accurate and appealing alternative to the use of accurate but time-consuming multi-zone dynamic simulation tools, which strongly depend on several parameters to be inserted and user expertise to calibrate the model. Artificial neural networks and support vector machines were developed and parametrized using historical data and different sets of exogenous variables to encounter the best performance combinations for both the heating and cooling periods of a year. In the case of support vector regression, a variation introduced simulated annealing to guide the search for different combinations of hyperparameters. After a feature selection stage for each individual method, the results for the different methods were compared, based on error metrics and distributions. The outputs of the study include the most suitable methodology for each season, and also the features (historical load records, but also exogenous features such as outdoor temperature, relative humidity or occupancy profile) that led to the most accurate models. Results clearly show there is a potential for faster, yet accurate machine-learning based forecasting methods to replace well-established, very accurate but time-consuming multi-zone dynamic simulation tools to forecast building energy consumption.

Measurement of the three-axis vibration, temperature, and relative humidity profiles of commercial transport trailers for pigs.

The objective of this study was to collect and interpret three-axis acceleration, temperature, and relative humidity data from six locations within commercial transport trailers shipping market-weight pigs. Transport was observed in Kansas (n = 15) and North Carolina (n = 20). Prior to loading, three-axis accelerometers were affixed to six locations on the trailers: top fore (TF), top center (TC), top aft (TA), bottom fore (BF), bottom center (BC), and bottom aft (BA) compartments. Data were post-processed to calculate root-mean-square (RMS) accelerations and vibration dose values (VDV) in the vertical direction and the horizontal plane. These values were compared with exposure action values (EAV) and exposure limit values (ELV), vibration levels deemed uncomfortable and potentially dangerous to humans. Additionally, RMS and VDV were compared among the trailer compartments. The vertical RMS accelerations for all compartments exceeded the EAV for loads measured in Kansas, and for the majority of the compartments measured in North Carolina. Many compartments, specifically the BA compartment from all trips, exceeded the vertical ELV. Regardless of where the data were collected, fewer compartments exceeded the EAV in the horizontal orientation. Only BA compartments exceeded the ELV in the horizontal orientation. There were Area × Level interactions for vertical and horizontal RMS and VDV (P < 0.01). The BF compartment had a greater vertical RMS value than the TF, TC, and BC (P < 0.02) compartments, but did not differ (P = 0.06) from the TA compartment. The vertical RMS of the TA compartment did not differ from the TF, TC, and BC compartments (P > 0.13). The BF compartment had a greater (P = 0.02) vertical VDV value than the TC location, but did not differ from the other locations (P > 0.16). All other locations did not differ in vertical VDV (P > 0.12). The BF compartment had greater horizontal RMS than the TC and TA compartments (P < 0.01), but did not differ from TF and BC compartments (P > 0.12). All other compartments did not differ in horizontal RMS (P > 0.34). All compartments, aside from the BA compartment, did not differ in horizontal VDV (P > 0.19). Vibration analyses indicated the BA compartment had the greatest vertical and horizontal vibrations and a large percentage of the compartments exceed the EAV and ELV, which indicated pigs may have experienced uncomfortable trips that could cause discomfort or fatigue.

Synergy of Raman Lidar and Modeled Temperature for Relative Humidity Profiling: Assessment and Uncertainty Analysis

Relative humidity (RH) profiling using Raman lidars requires simultaneous range-resolved temperature and pressure data that are not always available. We propose and assess a method based on the use of a locally retrieved atmospheric model to estimate the temperature and pressure profiles. This model relies on the data from daily radiosonde launches at Barcelona during a five-year-long period (2015–2019). We have computed the range-resolved error of the model compared with the radiosonde “true” temperature profiles. Then, we have calculated the induced uncertainty in the recalculated RH profiles, finding that the standard deviation at 5 km is in situ radiosonde humidity measurements, finding, in this case, bigger differences due to additional sources of error. Uncertainty analysis shows that the temperature model is the most significant error source below 4–5 km. For higher altitudes, the noise of the Raman signals may become the main contribution. We show that the resulting uncertainty (commonly <15% below 5 km) is compatible with the statistical analysis of the model and comparable with the ones obtained using other instruments for temperature profiling. We show that this method permits nocturnal lidar-based RH profiling with uncertainty estimation without the need for measured atmospheric profiles.

Study of PAR interception, energy balance studies and microclimatic profiles in potato (Solanum tuberosum) cultivars under varying planting dates

The crop experiments were carried out during Rabi season 2016-17 & 2017-18. The experiment conducted at Research farm adjacent to agromet observatory (Latitude: 29° 10’ N; Longitude: 75° 46’ E & Altitude: 215 m), Department of Agricultural Meteorology, CCS HAU, Hisar, Haryana. The main aim and objectives of this work were to be accesses the microclimatic condition of potato under varying planting dates and varieties. Results revealed that micrometeorological parameters observed more favourable in 3rd week of October (D2) planted crop as compared to other planting dates. The absorbed PAR was recorded higher in 3rd week of October (D2) sown crop and Kufri Pushkar then other treatments at phenophases, respectively higher in during both seasons. PAR transmitted (watt/m2) at bottom, Soil heat flux pattern was observed in decreasing trend from advanced vegetative stage to tuber bulking stage may be due to more cover of ground and absorption percentage of PAR. The consumption of PAR, bright sun shine and assimilation rate were more in second planting dates. Among planting dates, the net radiation (Rn) was higher at early vegetative stage in 3rd week of October (D2) and 1st week of November (D3) during both crop seasons. The major portion of Rn (Net radiation) was utilized by latent heat of vaporization (LE). The 2nd week of October (D1) was received higher values of soil heat flux (G) during both the crop seasons. The minimum value of G was observed at tuber bulking stage in 1st week of November (D3) during both crop seasons. LE was higher at all phenophases in 3rd week of October (D2) at early vegetative stage during both the crop seasons. G was highest at initiation of tuber and early vegetative stage in 3rd week of November (D4) respectively, during both season. Temperature profiles were inverse throughout the day within the canopy at all phenophases. Over the top of the crop canopy the temperature profile was lapse. The relative humidity profiles were lapse inside the crop canopy throughout the day at 9:00 hours where it was iso-humic. Further concluded that the microclimate profile condition pattern was optimum in second sown crops and produced higher tuber yield.

Comparison of temperature and humidity profiles retrieved from INSAT-3DR sounder with high resolution radiosonde measurements

<abstract> We evaluate temperature and humidity profiles retrieved from an INSAT-3DR sounder against radiosonde measurements for one year during 2017–2018. This evaluation is carried out in terms of slope, intercept, bias, Root Mean Square Error (RMSE), and correlation coefficient in temperature and relative humidity profiles. This comparison provided first-hand information about the performance of INSAT-3DR sounder retrievals. This validation exercise is unique in terms of comparing with the high resolution (1 Hz) radiosonde measurements performed in the afternoon time when there is maximum convection driven by solar radiation. 276 pairs of co-located temperatures have been compared. INSAT-3DR temperature retrievals are strongly linearly correlated to radiosonde measurements, with the slope as 1.001 and correlation coefficient of 0.99, while the mean temperature bias between INSAT-3DR and radiosonde is -0.23°C with RMSE of 1.9°C. Comparison of Relative humidity retrieved from INSAT-3DR to the radiosonde data results in RMSE of 9.8% with a slope of 0.99 with a correlation coefficient of 0.77. The collocation of data points for validation is done matching in space [Latitude, Longitude, Pressure level (height)] and time (±30 minutes). The effect of relaxing the space and time window on the validation statistics is also studied for the first time. </abstract>

CFD modelling of the air conditioning system for a Tier 2 Data Centre

ABSTRACT The management of Air Conditioning Systems (ACS) in Data Centre (DC) facilities has a significant impact not only on energy consumption but also on the performance and safety of the hardware. The main purpose of this work is to detect design and operational flaws of the ACS of a Tier 2 DC located at Universidad de los Andes (Colombia) with the aid of Computational Fluid Dynamics (CFD) tools. To achieve this objective, in situ measurements of air humidity and temperature were taken to develop and validate a CFD model. In addition to the current operation, two different scenarios were proposed, and their performance was evaluated in terms of the global temperature and relative humidity profiles, cooling efficiency with respect to the current operation, and air flow currents. The first scenario contemplated the operation of both AC units at full capacity for a normal 24-hour shift, and the second scenario contemplated an unsteady analysis of the AC’s operation on 12-hour shifts. The CFD and experimental results suggest that the DC’s layout and corridor arrangement have several flaws that cannot be overcome with the current ACS. Moreover, the CFD analysis carried out provides relevant insights into the performance of the operational setups tested.

One‐dimensional maximum‐likelihood estimation for spaceborne precipitation radar data assimilation

AbstractSpaceborne precipitation radar such as Global Precipitation Measurement (GPM)/dual‐frequency precipitation radar (DPR) provides valuable observations of precipitation systems in three dimensions. Assimilation of GPM/DPR data is becoming an important technique for improving the accuracy of forecasting to complement scarce ground‐based observations. This study presents a new, one‐dimensional maximum‐likelihood estimation (1D‐MLE) method developed by the authors that enables the estimation of relative humidity profiles according to a non‐Gaussian probability density function. By assimilating the estimated relative humidity profiles using a four‐dimensional variational (4D‐Var) method, mesoscale precipitation forecasts by the Japan Meteorological Agency (JMA) have been considerably improved. The displacement of forecast precipitation during a severe weather event, in particular, is improved significantly. It was found that forecasting accuracy was maintained for a narrow GPM/DPR swath and low revisit frequency by repeating the assimilation–forecast cycle. Since the effectiveness was confirmed, the JMA began assimilating GPM/DPR data using the 1D‐MLE approach from March 2016.

The effects of exhaust air vent location on thermal comfort inside a residential building equipped with an evaporative cooling system

The location of exhaust air vents of an evaporative cooling system can have significant effects on providing thermal comfort and controlling humidity, temperature and air distribution in buildings. In the current study, four different strategies have been evaluated for exhaust air vent locations to provide the optimum thermal comfort inside a typical residential house. This study provides a numerical solution for temperature and relative humidity profiles in the residential house and within the living space in each room typically at a height of 1.8 m or less. By evaluating different exhaust air vent locations in a room, the best strategy(ies) to provide more appropriate thermal comfort condition and obtained and as a conclusion, the exhaust vents should be located on furthest wall away from the entrance of the room and in the middle. The results provided in the current study can eventually be applied in the design of evaporative cooler exhaust vent systems in residential buildings and lead to improve the performance of these systems.

Growth performance ofAcheta domesticus andGryllus bimaculatus production reared under improvised cage system for increased returns and food security

Cricket farming is emerging as a new venture in Kenya poised to help alleviate protein deficiency and improve household living standards. However, competing, limited and unaffordable rearing systems constrain productivity and optimisation of this new enterprise. This study sought to evaluate the growth performance ofAcheta domesticus andGryllus bimaculatus reared in improvised cage system to assess its technical effectiveness. Twenty-day old of both species of crickets were separately reared in improvised and conventional cage systems for comparison purposes. Whereas an improvised cage system is a set of structure devised using locally available materials especially where the standard materials are limited, a conventional cage system is a set of structure made of standard and ordinary materials. The improvised system comprised of bamboo hideouts, clean scrap blankets for drinking and laying, cut bamboo stem as drinking platter and the plywood-based cages while conventional system comprised of egg carton hideouts, cotton-wool for drinking and laying, plastic petri-dishes, and plastic buckets. Each group of crickets (100 live crickets) was daily provided with equal amount of feed and water. Average weekly temperature and relative humidity profiles were recorded using HOBO data loggers. Further, 49 live crickets per treatment were randomly sampled and weighed weekly. Generalised additive model and analysis of variance were adopted to model the data therefrom using R. The cage system had a significant effect on the growth performance of the crickets. The mean weight of the cricket species differed, but not the interaction with the cage system. Similarly, species, temperature and relative humidity also influenced the growth performance. Compared to the conventional system, improvised cage system showed better results in realising high cricket productivity though there was no significant difference in growth performance between the two systems. The focus therefore should be to evaluate the egg productivity in scrap blanket in relation to cotton wool and cost effectiveness in improvised system to inform future farm decisions.

Estimating and Removing the Sampling Biases of the AIRS Obs4MIPs V2 Data.

The Atmospheric Infrared Sounder (AIRS) Observations for Model Intercomparison Projects (Obs4MIPs) Version 2.0 (V2.0) monthly mean tropospheric air temperature, specific humidity, and relative humidity profile data were designed for climate model evaluation in the context of the Coupled Model Intercomparison Project (CMIP). Due to the limitations of the Aqua satellite orbit and the AIRS retrieval algorithm, the sampling biases of the AIRS Obs4MIPs V2.0 data can be large for certain cases and must be considered when the AIRS Obs4MIPs V2.0 data are used for climate model evaluation. In this study, we estimate the sampling biases of the AIRS Obs4MIPs V2.0 data based on the fifth generation of the European Centre for Medium‐Range Weather Forecasts (ECMWF) (ERA5) reanalysis and cross‐check them using the Modern‐Era Retrospective Analysis for Research and Application, Version 2 (MERRA‐2) reanalysis. We then remove the estimated sampling biases from the AIRS Obs4MIPs V2.0 data and produce the sampling‐bias‐corrected AIRS Obs4MIPs V2.1 data that have been published at the Earth System Grid Federation (ESGF) data centers and should be used in the future for climate model evaluation.

Thermal Management of Edge-Cooled 1 kW Portable Proton Exchange Membrane Fuel Cell Stack

Air-cooled proton exchange membrane (PEM) fuel cell stacks are gaining momentum as power sources for portable applications such as electric bikes, unmanned aerial vehicles (UAVs), forklifts, etc. Usually the power of portable stacks (PS) is up to several kW [1,2]. Most of the heat generated during PS operation is dissipated into the surrounding atmosphere via forced air convection along the cooling channels or edge-cooling fins, while the higher power stacks require liquid cooling. The emphasis during the design phase of PS is primarily directed towards determining the most suitable material for bipolar plates and the accompanying thermal management. Some of the thermal management objectives are: (i) ensuring the appropriate heat transfer from the stack during startup, i.e. accurately determining the required convection flow rate, to achieve sufficiently high operating temperature from startup at ambient temperature, thus preventing flooding (occurring if the flow rate is high and temperature of the stack is low) or membrane dehydration (occurring if the flow rate is low and temperature inside the stack is high); (ii) ensuring sufficiently high heat removal rates via forced air convection during the operation characterized by stable temperature of the stack, i.e. loosely termed steady-state operation; (iii) ensuring as low as possible temperature difference between the inside and outside portions of the stack by choosing the materials with favorable thermal properties; (iv) properly design the stack and edge-cooling fins to ensure sufficiently high heat removal rates; (v) design the frame for the stack which will ensure that the cooling air is directed to uniformly flow along the edge-cooling fins. In previous studies [3,4] it was shown that the operating temperature inside PEM fuel cell is highly non-uniform and it is not accurate to represent the operating temperature with just one parameter, while at the same time if the temperature profile is controlled it can be exploited to result in high performance of the cell by manipulating the water vapor saturation profile, i.e. relative humidity profile inside the cell. The main contributions of this work to the research field are evident in outlining that the commonly used lumped models can be misleading for dynamic analysis of PEM fuel cell performance due to inability to accurately calculate the maximal temperature inside the stack and this work also outlines under which circumstances the lumped models can be used. This work also presents a novel transient CFD model for analysis of thermal management of PS which gives insight in mass and heat transfer both inside and outside of the cell (internal heat and mass transfer and forced air convection edge-cooling), while other works focus on only one aspect and simplify the other to a significant extent.In order to study thermal management influence on the performance od 1kW edge-cooled proton exchange membrane fuel cell stack without external humidification comprehensive numerical analyses are conducted. Two numerical approaches are considered and compared for a prescribed load profile: (i) lumped model and novel (ii) real-time transient computational fluid dynamics model incorporating realistic modeling of forced air convection on the edge-cooling of the stack. The developed computational fluid dynamics model is used to study the influence of (i) bipolar plate materials (ii) operating delta pressure along the flow field and (iii) different cooling fin configurations on the water and heat balance inside the stack. The results indicate that (i) maximal and average temperatures of the stack are almost linearly correlated to the thermal conductivity of bipolar plate materials and maximal temperatures can be significantly higher (ii) the operating delta pressure can be manipulated to increase the performance of the stack and (iii) the cooling fin redesign has major influence on the overall temperature uniformity across the stack. Additionally, the heat transfer between the stack and metal hydride tank is studied.

Measurements of atmospheric aerosol hygroscopic growth based on multi-channel Raman-Mie lidar

In this study, an effective method with a multi-channel Raman-Mie lidar has been proposed to detect the hygroscopic growth of atmospheric aerosol in the boundary layer, and the effect of aerosol hygroscopic growth on the optical and microphysical properties of aerosol particles is studied. The vertical relative humidity profile is obtained by combining calibrated water vapor mixing ratio and temperature profiles from Raman-Mie lidar. Two cases were selected in Hefei to analyze the aerosol hygroscopic growth. Case studies show that the increase of the backscatter coefficient of aerosol is consistent with the increase of relative humidity, and the decrease of Ångstrom exponent indicates the increasing aerosol particle size due to the hygroscopic growth process. The Kasten model is used to fit the aerosol hygroscopic enhancement factor, and the b value from the Kasten parameterization for Case II is much larger than that for Case I, which shows the stronger hygroscopicity in Case II. The results indicate that the multi-channel Raman-Mie lidar has potential in the measurements of the hygroscopic growth of aerosols.

A 1D Var Retrieval of Relative Humidity Using the ERA5 Dataset for the Assimilation of Raman Lidar Measurements

AbstractWe present a one-dimensional variational (1D Var) retrieval of fifth-generation European Centre for Medium-Range Weather Forecast reanalysis (ERA5) temperature and relative humidity profiles above Payerne, Switzerland, assimilating raw backscatter measurements from the MeteoSwiss Raman Lidar for Meteorological Observations (RALMO). Our reanalysis is called ERA5-reRH. We use an optimal estimation method to perform the 1D Var data retrieval. The forward model combines the Raman lidar equation with the Hyland and Wexler expression for water vapor saturation pressure. The error covariance matrix of ERA5 was derived from the differences between ERA5 and a set of 50 special radiosoundings that have not been assimilated into ERA5. We validate ERA5-reRH, ERA5, and RALMO temperature and relative humidity profiles against the same set of special radiosoundings and found the best agreement was with our reanalysis, with a bias of less than 2% relative humidity with respect to water (%RHw) and a spread of less than 8%RHw below 8 km in terms of relative humidity. Improvements for temperature in our reanalysis are only found in the boundary layer, as ERA5 assimilates a large number of upper-air temperature observations. Our retrieval also provides a full uncertainty budget of the reanalyzed temperature and relative humidity including both random and systematic uncertainties.

Application of different methodologies for artwork risk assessment and reduction: simulation of a museum room with a validated dynamic model

Temperature and relative humidity are two parameters that can hugely hamper artwork preservation, leading to different types of degradation. In scientific literature and regulatory guidelines, two methodologies are used to assess suitable conditions for artifacts and potential risks. These two methods are generally alternatively applied, missing a comprehensive evaluation of indoor suitability of artwork preservation. The concurrent application of both approaches can help in the choice of the best strategy or design of HVAC systems to improve microclimate to artwork preservation. In this work, a validated dynamic model of a room in an Italian museum is presented as a case study. The analysis of indoor temperature and relative humidity profiles for a typical winter and summer period shows the importance of the application of both methodologies to identify potential risks for artworks. Thus, for both periods, new strategies improving indoor microclimate and leading to a most suitable environment for artwork are tested and successfully identified.

Daytime Evolution of Lower Atmospheric Boundary Layer Structure: Comparative Observations between a 307-m Meteorological Tower and a Rotary-Wing UAV

A 307-m tall meteorological tower was used to evaluate meteorological observation data obtained using a rotary-wing unmanned aerial vehicle (UAV). A comparative study between the tower and UAV observations was conducted during the daytime (06:00 to 19:00 local time (LT)) in the summer of 2017 (16–18th August). Hourly vertical profiles of air temperature, relative humidity, black carbon (BC), and ozone (O3) concentrations were obtained for up to 300 m height. Statistical metrics for evaluating the accuracy of UAV observations against the tower observation showed positive (potential temperature) and negative (relative humidity) biases, which were within acceptable ranges. The daytime evolution of the lower atmospheric boundary layer (ABL) was successfully captured by the hourly UAV observations. During the early morning, a large vertical slope of potential temperature was observed between 100 and 140 m, corresponding to the stable ABL height. The large vertical slope coincided with the large differences in BC and O3 concentrations between altitudes below and above the height. The transition from stable to convective ABL was observed at 10–11 LT, indicated by the ABL height higher than 300 m in the convective ABL. Finally, we provide several recommendations to reduce uncertainties of UAV observation.

Assimilation of Satellite Microwave Observations over the Rainbands of Tropical Cyclones

AbstractA novel Bayesian Monte Carlo integration (BMCI) technique was developed to retrieve geophysical variables from satellite microwave radiometer data in the presence of tropical cyclones. The BMCI technique includes three steps: generating a stochastic database, simulating satellite brightness temperatures using a radiative transfer model, and retrieving geophysical variables such as profiles of temperature, relative humidity, and cloud liquid and ice water content from real observations. The technique also provides uncertainty estimates for each retrieval and can output the error covariance matrix of selected parameters. The measurements from the Advanced Technology Microwave Sounder (ATMS) on board Suomi National Polar-Orbiting Partnership (Suomi NPP) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI) were used as input. A new technique was developed to correct the ATMS and GMI observations for the beam-filling effect, which is due to small-scale variability of precipitation and clouds when compared with the instrument footprint and also the nonlinear relation between the brightness temperature and precipitation. In addition, the assimilation of the BMCI retrievals into the NASA GEOS model is discussed for Hurricane Maria. The results show that assimilating the BMCI retrievals can influence the dynamical features of the cyclone, including a stronger warm core, a symmetric eye, and vertically aligned wind columns. Two possible factors that may limit the impact of the BMCI retrievals include 1) the resolution of the model (about 25 km), which was too coarse to show the potential of the BMCI data in improving the representation of tropical storms in the model forecast, and 2) the data assimilation system not being able to consider vertically correlated observation errors.

Electrospun Hybrid Perfluorosulfonic Acid/Sulfonated Silica Composite Membranes.

Electrospinning was employed to fabricate composite membranes containing perfluorosulfonic acid (PFSA) ionomer, poly(vinylidene fluoride) (PVDF) reinforcement and a sulfonated silica network, where the latter was incorporated either in the PFSA matrix or in the PVDF fibers. The best membrane, in terms of proton conductivity, was made by incorporating the sulfonated silica network in PFSA fibers (Type-A) while the lowest conductivity membrane was obtained when sulfonated silica was incorporated into the reinforcing PVDF fibers (Type-B). A Type-A membrane containing 65 wt.% PFSA with an embedded sulfonated silica network (at 15 wt.%) and with 20 wt.% PVDF reinforcing fibers proved superior to the pristine PFSA membrane in terms of both the proton conductivity in the 30–90% RH at 80 °C (a 25–35% increase) and lateral swelling (a 68% reduction). In addition, it was demonstrated that a Type-A membrane was superior to that of a neat 660 EW perfluoroimide acid (PFIA, from 3M Co.) films with respect to swelling and mechanical strength, while having a similar proton conductivity vs. relative humidity profile. This study demonstrates that an electrospun nanofiber composite membrane with a sulfonated silica network added to moderately low EW PFSA fibers is a viable alternative to an ultra-low EW fluorinated ionomer PEM, in terms of properties relevant to fuel cell applications.

Evaluation of planetary boundary layer schemes on weather research forecasting by using intensive observation at kototabang

This study examined Weather Research and Forecasting (WRF) simulation with different closure type of Planetary Boundary Layer (PBL) in six PBL schemes. This study aimed to evaluate the performance of PBL scheme in representing the vertical profile of the atmosphere over Kototabang. Intensive observation during boreal spring in 2002 using radiosonde and Automatic Weather Station (AWS) provided were used to verify the results of WRF. Our finding showed that most of PBL scheme successfully simulated diurnal variations of PBL, temperature and relative humidity. However, the bias in magnitude were found during the daytime. This study shows that ACM2, applying mixed local and non-local closure type, performed more realistic temperature and relative humidity profile with minimum bias compared to other schemes.

Índices termodinâmicos durante a campanha GOAmazon2014/5 e comparação com dados da reanálise ERA-Interim

The thermodynamic indexes LCL, LFC, CINE and CAPE characterize atmospheric instability, and allow the study of cloud formation and convection, important phenomena for the hydrologic cycle and the radiative balance. For this reason, this work makes a seasonal analysis of these thermodynamic indexes computed from radiosondes released during the GOAmazon2014/5 experiment. A comparison was made with ERA-Interim reanalysis for both these indexes and the temperature and relative humidity profiles. Analysis of radiosonde data shows that the median vertical profile of relative humidity in the dry season was lower in 2015 when compared to 2014, resulting in higher LCL (~50 hPa at 18 Z) and lower CAPE (~50% lower). The difference stems from a more severe dry season in 2015 when compared with 2014. The comparison with the reanalysis reveals that modeled LCL values are only compatible with observed ones at 18 Z (mean bias -10 hPa). On the other hand, CAPE values are always incompatible (mean bias -750 j/kg). Results indicate that ERA Interim poorly represents the thermodynamic conditions over the Amazon rainforest.

Inter-Comparison of AIRS Temperature and Relative Humidity Profiles with AMMA and DACCIWA Radiosonde Observations over West Africa

The vertical profiles of temperature and water vapour from the Atmospheric InfraRed Sounder (AIRS) have been validated across various regions of the globe as an effort to provide a substitute for radiosonde observations. However, there is a paucity of inter-comparisons over West Africa where local convective processes dominate and radiosonde observations (RAOBs) are limited. This study validates AIRS temperature and relative humidity profiles for selected radiosonde stations in West Africa. Radiosonde data were obtained from the AMMA and DACCIWA campaigns which spanned 2006–2008 and June–July 2016 respectively and offered a period of prolonged radiosonde observations in West Africa. AIRS performance was evaluated with the bias and root mean square difference (RMSD) at seven RAOB stations which were grouped into coastal and inland. Evaluation was performed on diurnal and seasonal timescales, cloud screening conditions and derived thunderstorm instability indices. At all timescales, the temperature RMSD was higher than the AIRS accuracy mission goal of ±1 K. Relative humidity RMSD was satisfactory with deviations &lt;20% and &lt;50% for both lower and upper troposphere respectively. AIRS retrieval of water vapour under cloudy and cloud-free conditions had no significant difference whereas cloud-free temperature was found to be more accurate. The seasonal evolution of some thunderstorm convective indices were also found to be comparable for AIRS and RAOB. The ability of AIRS to capture the evolution of these indices imply it will be a useful dataset for the African Science for Weather Information and Forecasting Techniques (SWIFT) high impact weather studies.