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This paper presents a validation of outputs from some GCMs of the CMIP6 project when used to assess climate projection and hydrological flows at a catchment scale for the case study area of the Lombardy region (Northern Italy). The modeling chain consists of (i) a choice of climatic scenarios from 10 GCMs of the CMIP6, (ii) the application of a stochastic downscaling procedure to make projections usable at the local scale, and (iii) the use of a semi-distributed physically based hydrological model Poli-Hydro for the generation of hydrological scenarios. Data on observed precipitation and temperature were collected from automatic weather stations, and the hydrological budget of four target catchments within the study area was assessed using Poli-Hydro. An ex-post (back-casting) analysis was performed upon the control data series from the GCMs by comparing statistics of relevant climate variables and model-simulated discharges against observed counterparts during the historical period 2002–2014. Then, during 2015–2021, the goodness of projections was assessed using confidence intervals. Our results show that the accuracy of GCMs in representing regional climate is not always reflected in a credible evaluation of local hydrology. The validation of climate patterns provides somewhat poor results; thus, the interaction among climate and hydrology needs to be explored carefully to warrant the credibility of hydrological scenarios. Overall, the spatial and temporal consistency of GCM projections, as explored here climatically and hydrologically, provides a clue about their dependability for basin scale management. [ABSTRACT FROM AUTHOR]

Global warming has implications for thermal stress for grapevines during ripening, so that wine producers need to adapt their viticultural practices to ensure optimum physiological response to environmental conditions in order to maintain wine quality. The aim of this paper is to assess the ability of the Weather Research and Forecasting (WRF) model to accurately represent atmospheric processes at high resolution (500 m) during two events during the grapevine ripening period in the Stellenbosch Wine of Origin district of South Africa. Two case studies were selected to identify areas of potentially high daytime heat stress when grapevine photosynthesis and grape composition were expected to be affected. The results of high-resolution atmospheric model simulations were compared to observations obtained from an automatic weather station (AWS) network in the vineyard region. Statistical analysis was performed to assess the ability of the WRF model to reproduce spatial and temporal variations of meteorological parameters at 500-m resolution. The model represented the spatial and temporal variation of meteorological variables very well, with an average model air temperature bias of 0.1 °C, while that for relative humidity was −5.0 % and that for wind speed 0.6 m s. Variation in model performance varied between AWS and with time of day, as WRF was not always able to accurately represent effects of nocturnal cooling within the complex terrain. Variations in performance between the two case studies resulted from effects of atmospheric boundary layer processes in complex terrain under the influence of the different synoptic conditions prevailing during the two periods. [ABSTRACT FROM AUTHOR]

This study aimed to assess monthly average daily global solar irradiation ( H g m) estimates in Southeastern Brazil from empirical models and artificial intelligence (AI) techniques using extreme air temperatures (maximum—Tx and minimum—Tn) and extraterrestrial solar irradiation ( H 0 m ) and evaluate the geographic and climate factors in the performance of the models or the AI techniques. The H g m , Tx and Tn data series from 95 automatic weather stations of the Brazilian National Institute of Meteorology (INMET) were used. The Hargreaves-Samani (HS) and Bristow-Campbell (BC) models were fitted, and AI techniques (artificial neural network—ANN and support vector machines—SVM) were trained, and assessed according to local climate conditions. Three input schemes in the AI techniques were assessed: (i) H 0 m , Tx, and Tn; (ii) H 0 m and air temperature amplitude (ΔT); and (iii) H 0 m , Tx, Tn, and ΔT. The coefficients of the HS (0.134 ≤ kr ≤ 0.262) and BC (0.539 ≤ β0 ≤ 0.796; 0.004 ≤ β1 ≤ 0.843; 0.35 ≤ β2 ≤ 2.60) models and their performance were influenced by climate, continentality/maritime effects, altitude and weather systems. The performance of the HS model was inferior to that of BC model and the SVM and ANN techniques. Overall, the SVN and ANN techniques performed better than the BC method. However, BC had similar or superior precision and accuracy to SVM and ANN for some climatic conditions and combinations of input variables. The quality of the H g m series, the combination of input variables, and climate influenced the estimates of the SVM and ANN techniques. [ABSTRACT FROM AUTHOR]

The availability of quality precipitation records in the current climate situation is of great importance in the scientific-technical field but also for the public institutions that manage the meteorological networks. This work has implemented a comprehensive spatial quality control procedure in the semiarid region of Andalusia (Southern Spain), using precipitation time series from 1947 stations from three meteorological networks: Spanish Meteorological Agency (AEMET), Agroclimatic Information Network of Andalusia (RIA), and Phytosanitary Information Alert Network (RAIF). The method consists of three consecutive steps: basic, absolute, and relative quality control processes. The latter step compares data from neighboring stations taking into account their proximity, height difference, and correlation, leading to a complete evaluation of each daily value. Finally, the quality of each year at each station can be declared as acceptable, good, or excellent. The automatic weather station networks RIA and RAIF gave absolute quality index Q above 85% for almost 87% of their stations, while only 57% of AEMET network reached this percentage. However, one of the longest AEMET datasets, San Fernando-Cádiz, obtained, except for 1 year, Q values over 90% in all available years for more than a century of measurements, since 1870 until 2000. From a total of more than 15 million daily records, almost 82% was flagged as correct. Despite the limitations of Andalusia region (low density of stations and its structural water deficit), the complete quality control procedure has been satisfactorily applied. Finally, related to the number of outliers, no temporal trend was found across the region. [ABSTRACT FROM AUTHOR]

Continuous monitoring of the planetary boundary layer (PBL) height was carried out using simultaneous observations of the micro-pulse lidar (MPL) at Kattankulathur (12.83°N, 80.04°E) and radiosonde and surface meteorological observations at Meenambakkam (13.0°N, 80.18°E) during different seasons in the year 2016 over Chennai, in the Indian east coast region. These observations provide excellent data to evaluate the performance of the five different PBL parameterization schemes from the Weather Research and Forecasting (WRF) model simulation of PBL characteristics over the coastal environment. The simulation experiments were run using Asymmetrical Convective Model version 2 (ACM2), Yonsei University (YSU), Mellor-Yamada-Janjić (MYJ), Mellor-Yamada Nakanishi and Nino level 2.5 (MYNN2), and Bougeault–Lacarrere (BouLac) schemes. The first two schemes are the first-order closure schemes, while the last three schemes are the turbulent kinetic energy (TKE) closure schemes. We have conducted the experiments for dry and wet surface conditions on clear sky days during different seasons. Under the dry surface conditions, the comparison of the simulated PBL height with observation reveals that all the schemes perform well during the daytime. However, during night-time, all the schemes except MYNN2 underestimate the observation. MYNN2 simulates the similar PBL diurnal pattern as detected by MPL. The potential temperature and relative humidity (RH) profiles from radiosonde observations at 00Z and 12Z and their surface observations at every 1-h interval from automatic weather station are also compared with simulated results. In the case of surface parameters, the WRF model underestimates the surface temperature by ~ 2 K and surface relative humidity by ~ 10–20% for the dry surface condition. However, under the wet surface condition, simulated PBL height and surface temperature (RH) overestimate (underestimate) the observation first 8 h after the rainfall. [ABSTRACT FROM AUTHOR]

An hour precipitation dataset of 42 automatic weather stations is developed and applied to analyze the temporal and spatial characteristics of light precipitation in urban areas of Beijing City during 2007–2017. The stations are classified into three groups, including 18 sites in central urban area (4th Ring-Road, RR), 10 sites in peri-urban area (4th–5th RR), and 14 sites in suburban area (5th–6th RR). Light precipitation is defined as hourly rainfall of 0.1–0.3 mm. Analysis shows that light precipitation occurred in urban area the whole day, with the peak value in 0600 LST and minimum value in 1600 LST; monthly variation of light precipitation frequency (LPF) was characterized by the highest value in summer and the lowest value in winter; remarkable differences are found for the various urbanized areas, with the annual and seasonal mean LPF being generally small in central urban area and gradually increasing toward suburban area; the hourly mean LPFs during morning and nighttime are higher in summer than those in other seasons in each of the urban areas; relative humidity, aerosol, and wind speed might have been the major influential factors for the observed temporal and spatial pattern of light precipitation. [ABSTRACT FROM AUTHOR]

Based on the meteorological data (2009–2018) acquired by high-density automatic meteorological stations in the central urban area (CUA) of Beijing, this study adopted an urban-rural ratio method to construct a qr to quantify the impact of urbanization on the spatial and temporal distribution of specific humidity (q). And the urban morphological parameters such as building height (BH), building density (BD), floor area ratio (FAR), sky view factor (SVF), and land surface parameters including vegetation coverage (VC) and impervious coverage (IC) with 500-m spatial resolution in CUA were calculated, and furthermore, the relationships between the six spatial layout parameters and another indicator, urban heat island (UHI) intensity, and qr were studied. The results show that q of CUA is 81~114% of that of the suburbs, and the urban dry island (UDI) effect and urban wet island (UWI) effect coexist throughout the year. The maximum UDI occurs during autumn daytime and the maximum UWI appears at night in winter. The UDI effect is prone to occur in areas with VC < 11%, IC >85%, BH > 15 m, and BD > 24%, while the UWI effect is more likely to appear in areas with VC > 35% and FAR < 0.3. The contributions of the six urbanization parameters to the spatial change of qr in different time periods are 6.2 to 33.5%, and VC is the largest (33.5%), followed by BD (31.9%) and SVF (29.9%), and the main factor affecting the annual average qr is BD with the contribution of 18.9%. Compared with the urbanization parameters, the UHI is more important and the contribution to the change of q can be up to 35.7%. The results show that these spatial layout parameters are not sufficient to explain the main change in q, and more other parameters need to be considered. [ABSTRACT FROM AUTHOR]

Net radiation is an important factor in studies of land–atmosphere processes, water resource management, and global climate change. This is particularly true for the Upper Blue Nile (UBN) basin, where significant parts of the basin are dry and evapotranspiration (ET) is a major mechanism for water loss. However, net radiation has not yet been appropriately parameterized in the basin. In this study, we estimated the instantaneous distribution of the net radiation flux in the basin using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra satellite and Automatic Weather Station (AWS) data. Downward shortwave radiation and air temperature usually vary with topography, so we applied residual kriging spatial interpolation techniques to convert AWS data for point locations into gridded surface data. Simulated net radiation outputs were validated through comparison with independent field measurements. Validation results show that our method successfully reproduced the downward shortwave, upward shortwave, and net radiation fluxes. Using AWS data and residual kriging spatial interpolation techniques makes our results robust and comparable to previous works that used satellite data at a finer spatial resolution than MODIS. The estimated net shortwave, longwave, and total radiation fluxes were in close agreement with ground truth measurements, with mean bias (MB) values of − 14.84, 5.7, and 20.53 W m−2 and root mean square error (RMSE) values 83.43, 32.54, and 78.07 W m−2, respectively. The method presented here has potential applications in research focused on energy balance, ET estimation, and weather prediction for regions with similar physiographic features to those of the Nile basin. [ABSTRACT FROM AUTHOR]

Irrigation water management as an essential strategy to prevent water stress in the arid and semiarid regions of the world strongly relies on the appropriate estimation of reference evapotranspiration (ET0). Validated and high-quality meteorological data are required to estimate ET0 appropriately. In this study, to improve ET0 estimations, the data quality control approach was applied to weather parameters obtained from Jafariye agricultural automatic weather station (AWS), Qom, Iran. All parameters were measured from 16 July 2011 to 8 June 2018. After removing outlier data, the integrity of weather data was investigated using the range, step, internal consistency, and persistence tests. Inlier errors that pass all of the quality control procedures were detected. Modifications and adjustment methods were applied to correct weather data, and ET0 calculated with original, modified, and adjusted datasets. Range test flagged 0.85% and 0.6% of solar radiation and wind speed values, respectively. The most suspected data were indicated by the internal consistency test which was 35.6% of wind speed data. Persistence test flagged 2.2% of wind speed values as well. Quality control and adjustment methods increased ET0 values by 21% and 27% on average throughout the entire period, respectively, while the maximum variation due to the application of adjustment methods was 9% that occurred in 2013. Results showed that the proposed quality control procedures could improve the reliability of weather data of automatic weather stations. [ABSTRACT FROM AUTHOR]

A fatal light aircraft crash occurred in the complex mountainous terrain along the coast of the South African Southern Cape in December 2015. An investigation into the meteorological conditions on this day revealed the interaction between mountain waves, gap flow and blocking near a cold front. The crash highlighted the need to equip forecasters with knowledge of the turbulence produced under these circumstances. With this in mind, experiments were conducted in the vicinity of the crash site, with automatic weather stations and radiosondes, to answer this question. Turbulent features were successfully characterised by Froude numbers, the Froude-derived height scale and the thermal wind equation. The Bernoulli equation, which classifies gap flow, was not helpful due to the effect of the upwind blocking area. Phenomena in descending order of wind strength produced compressional effect (44.7 ms−1), blocking (26 ms−1) and lastly, gap flow. Gap flow negatively impacted blocking jet strength. Phenomena in descending order of turbulence intensity gap flow, mountain wave/rotors and lastly, blocking. Gap flow produced greater vertical velocities than mountain waves. These mountain waves produced the highest vertical velocities measured to date in South Africa, associated with the shortest wavelength waves. Blocking jets of 600 m deep, 80 km wide and extending 30 km downwind of its exit region was found to modulate mountain wave characteristics significantly. A combination of mountain waves, gap flow and blocking was most likely responsible for the crash, highlighting that these three features cannot be seen as separate processes. [ABSTRACT FROM AUTHOR]

The Weather Research and Forecasting (WRF) model was employed to simulate the water and energy process over the near surface in the Yellow River source region from July to September 2015. The Rapid Update Cycle (RUC), Noah, Noah-Multi-Physics (Noah-MP), and Community Land Model (CLM) version 4 land surface schemes were selected and evaluated in our experiments. The simulated results were also compared with the Global Land Data Assimilation System (GLDAS) outputs, the ground-based automatic weather stations (AWSs), and the Zoige plateau wetlands ecosystem research flux station data. There was substantial agreement between the results of the simulations and observations in terms of 2-m temperature and relative humidity. However, the simulated values of the 2-m temperature were mostly lower than observations, while the values of relative humidity were higher than the observations. The correlation coefficients (R) between the simulations and observations of air temperature in four experiments were all higher than 0.94, and simulated results of the WRF-RUC experiment had the minimum bias compared with other experiments. The root mean square error (RMSE) and bias of 2-m relative humidity between the WRF-CLM4 simulations and observations were lower than other experiments. Moreover, the simulation of the 10-cm soil temperature was lower than the observations. WRF-CLM4 simulations agreed better with the observations, and WRF-Noah-MP simulations had the largest bias in all of the experiments. The soil moisture increased rapidly when precipitation was occurring and decreased slowly after the precipitation. The four experiments overestimate precipitation leading to higher soil moisture compared with the real situations. The peak value of net radiation was appropriately 850 W/m2 during the summertime in the Zoige plateau area. The simulated net radiation agreed well with the observation except in the WRF-RUC scheme. During the summertime, vegetation grew rapidly, and the latent heat flux transport increased and played a dominant role in surface energy transport in the Zoige area. The RMSE between the simulation and observation of latent heat flux had the minimum value of 98.0 W/m2 in the WRF-CLM4 scheme, and the bias of sensible heat flux had the minimum value of 15.4 W/m2 in the WRF-Noah scheme. This study used the WRF model to explore the applicability of the different land surface schemes in the Zoige plateau area. The research related to this study can be used to understand the water-energy cycle process over the Qinghai-Tibet Plateau wetland and can also provide references for the application of regional meteorological models over this area. [ABSTRACT FROM AUTHOR]

The Qinghai Lake is the largest saltwater lake in the Tibetan Plateau and in mainland China. Effects of the lake on surface climate of the coastal areas, however, are not well understood. This article utilizes hourly observation data of warm season from 17 automatic weather stations to analyze the diurnal and seasonal variations in air temperature in different coastal zones of the Qinghai Lake. The EOS/MODIS data was also used to analyze the surface temperature differences between the lake and its surrounding areas. The results show a few unique characteristics of the plateau lake: (1) based on the satellite data, lake surface temperature is lower than its surrounding areas (4.9~25.1 °C and 12.2~35.6 °C respectively) in the daytime, while it is obviously higher than that in the surrounding areas (1.9~10.5 °C and − 13.1~6.3 °C respectively) at the nighttime. Daily mean water surface temperature is higher than that in the surrounding areas, which is 7.8~17.9 °C and − 2.6~17.9 °C respectively; (2) based on data of meteorological stations, coastal zones closer to the shoreline have a higher air temperature during the warm season largely due to the much warmer nighttime near the shoreline than those in deep inland zones. For the on-shore, near-shore, and far-shore zones, mean daytime air temperature is 8.7~9.6 °C, 9.5~11.1 °C, and 10.0~10.7 °C, respectively, and the mean nighttime air temperature is 2.9~4.1 °C, 1.3~12.3 °C, and − 0.2~0.4 °C respectively. The hourly mean diurnal temperature range (DTR) increases with distance to the shoreline, which is 8.6 °C, 10.9 °C, and 12.3 °C in the on-shore, near-shore, and far-shore zones respectively; (3) differences between maximum and minimum 5-day mean daily maximum (minimum) air temperature during the warm season are 20.3 °C (23.3 °C), 21.7 °C (25.6 °C), and 22.6 °C (26.7 °C) for the on-shore, near-shore, and far-shore zones, respectively, indicating an asymmetrical effect on daytime and nighttime air temperature in the on-shore zone; (4) daily maximum air temperature of the on-shore zone is lower before early October, but it is slightly higher afterward and occurs later; (5) daily minimum air temperature of the on-shore zone is on average higher than that of the far-shore zone, especially after the mid-September, and it also appears later in autumn than in summer. [ABSTRACT FROM AUTHOR]

The quality control of weather data is a necessity and a responsibility of meteorological services that store, distribute, and use these data. In the present work, a newly designed quality control procedure for daily rainfall data is presented after it has been adjusted and tested with more than 107 data from 1726 daily rainfall measurement sites in Catalonia. It is applicable to data from different origins (e.g., automatic weather stations or manual historical measurements). The procedure is focused on relative comparison of daily data with reference stations that are automatically selected after an initial estimation of their quality and a proximity study regarding location and correlation. The presented procedure has been verified taking advantage of an available network in the study area that has been routinely quality controlled by technicians of the Meteorological Service of Catalonia. The newly designed quality control procedure for daily precipitation yields good results, especially for extreme values: type I error under 10% is found for values up to 150 mm (error decreasing for lower values) and type II error is under 16% when reported values are twice a measure of 50 mm or more (error decreasing for more extreme values). After the application of the quality control procedure, a selection of series with the minimum desired quality is achieved. [ABSTRACT FROM AUTHOR]

The extra-tropical Australian cities of Melbourne, Adelaide, and Perth are all affected by summer heatwaves and the urban heat island (UHI) effect. While research has been undertaken on both phenomena individually, they have not been studied in tandem in Australia. This research investigates the relationship between warm season heatwaves (November to March) and the UHI from January 1995 to March 2014. Observational temperature data from six or seven Bureau of Meteorology Automatic Weather Stations in each of Melbourne, Adelaide, and Perth are used to determine the strength of the UHI during heatwave periods and these are compared to non-heatwave periods. Melbourne and Adelaide both experience an exacerbated (warmer than normal) UHI at night during heatwaves. The night-time UHI in Perth is diminished (cooler than normal) during heatwaves and often changes to an urban cool island (UCI), when compared to non-heatwave periods. Environmental factors that might affect the strength of the UHI are investigated, including wind speed and direction, and station location. Despite the proximity of all stations to the coast, coastal influences on UHI strength are minimal during heatwave conditions. Station choice is found to not affect our results, with the characteristic pattern of the UHI during heatwaves remaining consistent across all three cities in a leave-one-out sensitivity analysis. [ABSTRACT FROM AUTHOR]

Air temperature is one of the most important meteorological factors that affect melting of glaciers, distribution of snowfall and rain at higher altitudes in the Himalaya. However, studies on spatio-temporal variability of air temperature in the central Himalaya are limited. In the present study, seasonal and annual characteristics (July 2011 to December 2015) of near-surface temperature and lapse rate in the Dokriani glacier catchment (DGC) of the central Himalaya are investigated using data from three automatic weather stations (AWSs). An attempt is also made to quantify 0 °C isotherm and temperate sustainability over the glacierized area. The results reveal that the average near-surface temperature lapse rate (NSTLR) of the catchment varies from 4.6 to 7.5 °C km−1 during all measurement seasons, suggesting that the standard environmental lapse rate (SELR, 6.5 °C km−1) is not a promising input for realistic glacio-hydrological modeling. The seasonal variability of the NSTLR indicates that the monsoon (warm and humid period) lowers the temperature lapse rate in this catchment due to the presence of high moisture content in the air. The steepest lapse rate is investigated during the pre-monsoon season due to clear and drier weather conditions. In addition to this, the results reveal strong variability in NSTLR at diurnal and sub-diurnal levels, with high variability in the day time and low in the night-time hours. A higher air temperature is examined in the ablation zone of the Dokriani Glacier during the monsoon season (i.e., JJAS: June, July, August, September), while other seasons (pre-monsoon, post-monsoon, winter) show both higher as well as lower temperatures. A large variation in 0 °C isotherm is also observed ranging from 5000 to 5500 m asl during 2012–2015. The present work emphasizes that the study of monthly, seasonal, and annual variability of the NSTLR are very important for glacio-hydrological research in the central Himalaya. [ABSTRACT FROM AUTHOR]

The aim of this study was to analyse the effect of slope aspect on the response of snowpack to climate warming in the Pyrenees. For this purpose, data available from five automatic weather stations were used to simulate the energy and mass balance of snowpack, assuming different magnitudes of an idealized climate warming (upward shifting of 1, 2 and 3 °C the temperature series). Snow energy and mass balance were simulated using the Cold Regions Hydrological Modelling platform (CRHM). CRHM was used to create a model that enabled correction of the all-wave incoming radiation fluxes from the observation sites for various slope aspects (N, NE, E, SE, S, SW,W,NW and flat areas), which enabled assessment of the differential impact of climate warming on snow processes on mountain slopes. The results showed that slope aspect was responsible for substantial variability in snow accumulation and the duration of the snowpack. Simulated variability markedly increased with warmer temperature conditions. Annual maximum snow accumulation (MSA) and annual snowpack duration (ASD) showed marked sensitivity to a warming of 1 °C. Thus, the sensitivity of the MSA in flat areas ranged from 11 to 17 % per degree C amongst the weather stations, and the ASD ranged from 11 to 20 days per degree C. There was a clear increase in the sensitivity of the snowpack to climate warming on those slopes that received intense solar radiation (S, SE and SW slopes) compared with those slopes where the incident radiation was more limited (N, NE and NW slopes). The sensitivity of the MSA and the ASD increased as the temperature increased, particularly on the most irradiated slopes. Large interannual variability was also observed. Thus, with more snow accumulation and longer duration the sensitivity of the snowpack to temperature decreased, especially on south-facing slopes. [ABSTRACT FROM AUTHOR]