Ground-based Meteorological Data Research Articles

Effective monitoring and warning of Urban Heat Island effect on the indoor thermal risk in Bucharest (Romania)

Extreme hot events and heat waves occur frequently in Bucharest during the warm season, triggering significant heat stress and thermal risks, especially in buildings with inappropriate ventilation, while climate change scenarios agree upon the warming trend along the next decades. This study investigates the impact of the Urban Heat Island (UHI) on the thermal regime of buildings, in order to develop a warning system capable to issue early warnings when the thermal risk reaches high levels in Bucharest. The warnings should be accurate regarding the intensity of the risk, the temporal fit and location, and complex information is compiled (e.g. air and land surface temperature, land cover, buildings and flat characteristics). Ground-based meteorological data and satellite products were used for computing the ambient temperature over several test areas for the summer months, and the indoor climate was dynamically modelled with an hourly resolution. The thermal risk was determined using standardized comfort indices, e.g. Predicted Mean Vote (PMV) and Predicted Percentage of Dissatisfied (PPD), and the specific thermal and functional characteristics of the buildings.

Estimation of Evapotranspiration and Crop Coefficients of Tendone Vineyards Using Multi-Sensor Remote Sensing Data in a Mediterranean Environment

The sustainable management of water resources plays a key role in Mediterranean viticulture, characterized by scarcity and competition of available water. This study focuses on estimating the evapotranspiration and crop coefficients of table grapes vineyards trained on overhead “tendone” systems in the Apulia region (Italy). Maximum vineyard transpiration was estimated by adopting the “direct” methodology for ETp proposed by the Food and Agriculture Organization in Irrigation and Drainage Paper No. 56, with crop parameters estimated from Landsat 8 and RapidEye satellite data in combination with ground-based meteorological data. The modeling results of two growing seasons (2013 and 2014) indicated that canopy growth, seasonal and 10-day sums evapotranspiration values were strictly related to thermal requirements and rainfall events. The estimated values of mean seasonal daily evapotranspiration ranged between 4.2 and 4.1 mm·d−1, while midseason estimated values of crop coefficients ranged from 0.88 to 0.93 in 2013, and 1.02 to 1.04 in 2014, respectively. The experimental evapotranspiration values calculated represent the maximum value in absence of stress, so the resulting crop coefficients should be used with some caution. It is concluded that the retrieval of crop parameters and evapotranspiration derived from remotely-sensed data could be helpful for downscaling to the field the local weather conditions and agronomic practices and thus may be the basis for supporting grape growers and irrigation managers.

Actual Evapotranspiration in the Al-Khazir Gomal Basin (Northern Iraq) Using the Surface Energy Balance Algorithm for Land (SEBAL) and Water Balance

Increasing dependence on groundwater requires a detailed determination of the different outputs and inputs of a basin for better water management. Determination of spatial and temporal actual evapotranspiration (ETa), in this regard, is of vital importance as there is significant water loss from drainage basins. This research paper uses the Surface Energy Balance Algorithm for Land (SEBAL), as well as the water balance, to estimate the spatial and temporal ETa in the Al-Khazir Gomal Basin, Northern Iraq. To compensate for the shortage in rainfall, and to irrigate summer crops, farmers in this basin have been depending, to a large extent, on groundwater extracted from the underlying unconfined aquifer, which is considered the major source for both domestic and agricultural uses in this basin. Rainfed farming of wheat and barley is one of the most important activities in the basin in the winter season, while in the summer season, agricultural activity is limited to small rice fields and narrow strips of vegetable cultivation along the Al-Khazir River. The Landsat Thematic Mapper images (TM5) acquired on 21 November 2006, 9 March 2007, 5 May 2007, 21 July 2007, and 23 September 2007 were used, along with a digital elevation model (DEM) and ground-based meteorological data, measured within the area of interest. Estimation of seasonal ETa from periods between satellite overpasses was computed using the evaporative fraction (Ʌ). The water balance approach was utilized, using meteorological data and river hydrograph analysis, to estimate the ETa as the only missing input in the predefined water balance equation. The results of the two applied methods were comparable. SEBAL results were compared with the land use land cover (LULC) map. The river showed the highest ETa, as evaporation from the free-water surface. Rice fields, irrigated in the summer season, have a high ETa in the images, as these fields are immersed in water during June, July and August. Vegetated corridors along the riverside showed different ETa values, as they contain a mosaic of different crops in different stages of growth. Conglomerate and bare sandstone outcrops showed no ETa, with some exceptions in the mountainous area, where these outcrops are affected by perennial springs. The results indicate the applicability of SEBAL in the study area, and they could be used in further studies to estimate the water budget of the basin.

Monsoonal variations in aerosol optical properties and estimation of aerosol optical depth using ground-based meteorological and air quality data in Peninsular Malaysia

Abstract. Obtaining continuous aerosol-optical-depth (AOD) measurements is a difficult task due to the cloud-cover problem. With the main motivation of overcoming this problem, an AOD-predicting model is proposed. In this study, the optical properties of aerosols in Penang, Malaysia were analyzed for four monsoonal seasons (northeast monsoon, pre-monsoon, southwest monsoon, and post-monsoon) based on data from the AErosol RObotic NETwork (AERONET) from February 2012 to November 2013. The aerosol distribution patterns in Penang for each monsoonal period were quantitatively identified according to the scattering plots of the Ångström exponent against the AOD. A new empirical algorithm was proposed to predict the AOD data. Ground-based measurements (i.e., visibility and air pollutant index) were used in the model as predictor data to retrieve the missing AOD data from AERONET due to frequent cloud formation in the equatorial region. The model coefficients were determined through multiple regression analysis using selected data set from in situ data. The calibrated model coefficients have a coefficient of determination, R2, of 0.72. The predicted AOD of the model was generated based on these calibrated coefficients and compared against the measured data through standard statistical tests, yielding a R2 of 0.68 as validation accuracy. The error in weighted mean absolute percentage error (wMAPE) was less than 0.40% compared with the real data. The results revealed that the proposed model efficiently predicted the AOD data. Performance of our model was compared against selected LIDAR data to yield good correspondence. The predicted AOD can enhance measured short- and long-term AOD and provide supplementary information for climatological studies and monitoring aerosol variation.

Estimation of evapotranspiration from ground-based meteorological data and global land data assimilation system (GLDAS)

Evapotranspiration (ET) is one of the most significant factors in understanding global hydrological budgets, and its accurate estimation is crucial for understanding water balance and developing efficient water resource management plans. For calculation of reference ET (ETref), the meteorological data from weather stations have been widely used for estimation at the point scale; however, meteorological data from the global land data assimilation system (GLDAS) at the regional scale are rarely used for the estimation of ET. In this study, 30 different equations provided in the Reference Evapotranspiration Calculator Software (REF-ET) were utilized for estimating ETref with GLDAS and point scale data collected at 14 observation sites in the Korean Peninsula during 2013. Using ETref calculated from observation and GLDAS, 30 equations were evaluated by estimating the overall rank number, as determined by the correlation coefficient, normalized standard deviation, bias, and root mean square error (RMSE). Results showed that the Penman (Proc R Soc Lond Ser A Math Phys Sci 193:120–145, 1948) FAO-56 Penman–Monteith, 1982 Kpen equation (combination equations), the 1957 Makkink, Priestley–Taylor equation (radiation based equation), and the 1985 Hargreaves equation had a good overall rank. Using the six selected equations, seasonal analysis was conducted and evaluated using the bias and RMSE. Comparison of the ETref gathered from observation and GLDAS revealed that both of them showed similar seasonal variation, although ETref calculated from GLDAS were underestimated. Sensitivity analysis conducted by changing three main climatic variables (i.e., temperature, wind speed, and sunshine hours) by ±1, ±5, ±10, ±15, and ±20 % with one variable fixed also revealed that ETref was more affected by air temperature than sunshine hours and wind speed throughout the 14 selected stations.

Remote Sensing and Ground-Based Weather Forcing Data Analysis for Streamflow Simulation

Hydrological simulation, based on weather inputs and the physical characterization of the watershed, is a suitable approach to predict the corresponding streamflow. This work, carried out on four different watersheds, analyzed the impacts of using three different meteorological data inputs in the same model to compare the model’s accuracy when simulated and observed streamflow are compared. Meteorological data from the Daily Global Historical Climatology Network (GHCN-D), National Land Data Assimilation Systems (NLDAS) and the National Operation Hydrological Remote Sensing Center’s Interactive Snow Information (NOHRSC-ISI) were used as an input into the Soil and Water Assessment Tool (SWAT) hydrological model and compared as three different scenarios on each watershed. The results showed that meteorological data from an assimilation system like NLDAS achieved better results than simulations performed with ground-based meteorological data, such as GHCN-D. However, further work needs to be done to improve both the datasets and model capabilities, in order to better predict streamflow.

A Method to Use Modis Water Vapor Products For Correction of Atmospheric-Induced Phase in Interferogram

A Method to Use Modis Water Vapor Products For Correction of Atmospheric-Induced Phase in InterferogramDInSAR is a major space-geodetic technique widely used in the study of earth surface deformation. A major source of phase errors in DInSAR technique is heterogeneous phase delay caused mainly by variation of water vapors in troposphere, which is a factor limiting applications of DInSAR mainly to arid areas. This paper presents study results of three methods to correct atmospheric phase errors in DInSAR interferograms formed by TerraSAR-X images. The first method is the use of wet delay derived directly from MODIS precipitable water vapor product. The second method employs ground-based meteorological data to calibrate MODIS PWV before computing phase delays. The third method improves the second method by estimating the expected MODIS PWV value at the time of the TerraSAR-X image acquisitions which over the Bangkok test area is 5 hour earlier than that of MODIS. The time-shifted linear fit model along with the IDW interpolation is used to estimate more realistic phase delays over entire imaging area. From the study of this tropical test area, this time-corrected method provides best results while the second method also achieves a significantly better result than those obtained from direct use of MODIS PWV data.

Regression models for the estimation of carbon exchange in boreal forests

Based on the measurements of the carbon dioxide fluxes at a few sites of the global FLUXNET network, we developed linear regression models for the estimation of the carbon budget of boreal forests. The model estimates satisfactorily agree with the measurement data obtained in the boreal forests of Canada (Manitoba, Thompson) and Russia (Krasnoyarsk krai, Zotino). The correlation coefficient between the calculations and measurements for a coniferous forests exceeds 0.9, with the annually mean model error in the budget estimate, as compared to the experimental results, not exceeding 50 gC/m2/yr. Using satellite and ground-based meteorological data, we calculated the monthly average carbon budget of the coniferous forests of Krasnoyarsk krai in 2001. Based on the satellite classification of the vegetation cover, we plotted monthly and annually average maps of the carbon budget that reflect the spatiotemporal distribution of the CO2 uptake and emission rates. It is shown that the coniferous forests of Krasnoyarsk krai are mostly a carbon sink, uptaking as much as 300 gC/m2 throughout the growing season.

Use of satellite-derived data for characterization of snow cover and simulation of snowmelt runoff through a distributed physically based model of runoff generation

Abstract. A technique of using satellite-derived data for constructing continuous snow characteristics fields for distributed snowmelt runoff simulation is presented. The satellite-derived data and the available ground-based meteorological measurements are incorporated in a physically based snowpack model. The snowpack model describes temporal changes of the snow depth, density and water equivalent (SWE), accounting for snow melt, sublimation, refreezing melt water and snow metamorphism processes with a special focus on forest cover effects. The remote sensing data used in the model consist of products include the daily maps of snow covered area (SCA) and SWE derived from observations of MODIS and AMSR-E instruments onboard Terra and Aqua satellites as well as available maps of land surface temperature, surface albedo, land cover classes and tree cover fraction. The model was first calibrated against available ground-based snow measurements and then applied to calculate the spatial distribution of snow characteristics using satellite data and interpolated ground-based meteorological data. The satellite-derived SWE data were used for assigning initial conditions and the SCA data were used for control of snow cover simulation. The simulated spatial distributions of snow characteristics were incorporated in a distributed physically based model of runoff generation to calculate snowmelt runoff hydrographs. The presented technique was applied to a study area of approximately 200 000 km2 including the Vyatka River basin with catchment area of 124 000 km2. The correspondence of simulated and observed hydrographs in the Vyatka River are considered as an indicator of the accuracy of constructed fields of snow characteristics and as a measure of effectiveness of utilizing satellite-derived SWE data for runoff simulation.

Study of Rain Events over the South China Sea by Synergistic Use of Multi-sensor Satellite and Ground-based Meteorological Data

Rain cells and rain bands over the South China Sea off the coast of Hong Kong are studied by using multi-sensor satellite and ground-based meteorological data. These include synthetic aperture radar (SAR) images acquired by the Advanced Synthetic Aperture Radar (ASAR) onboard the European ENVISAT satellite, weather radar images from the Hong Kong Observatory (HKO), rain rate data acquired by the Special Sensor Microwave Imager (SSM/I) sensor onboard the F15 satellite of the American Defense Meteorological Satellite Program (DMSP) and the rain sensors onboard the Tropical Rainfall Measurement Mission (TRMM) satellite, cloud image of GOES-9 satellite, sea surface wind maps acquired by the scatterometer onboard the QUIKSCAT satellite, and meteorological data from weather stations in Hong Kong. Three rain events, typical of Hong Kong, are studied. The first event consists of a cluster of rain cells associated with the summer monsoon, the second one of rain cells aligned in a rain band generated by an upper-air trough, and the third one consists of small rain cells embedded in a cold front. It is shown that ASAR images, which have a resolution of 30 m in the Image Mode (IM) and 150 m resolution in the Wide Swath Mode (WSM), yield much more detailed information on the spatial structure of rain events over the ocean than data obtained from SSSM/I and the rain sensors onboard the TRMM satellite. The precipitation radar (PR) onboard TRMM, which is the rain measuring instrument flown in space with the next best resolution, has a resolution of only 4 km. However, the disadvantage of SAR is that it is sometimes difficult to identify SAR signatures visible on SAR images of the sea surface unambiguously as caused by rain events. By comparing SAR images with simultaneously acquired weather radar images of the Hong Kong Observatory, a better knowledge of radar signatures on SAR images resulting from rain events over the ocean is obtained. This knowledge then helps greatly in detecting rain events on SAR images which are acquired over ocean areas, which are not in the reach of weather radar stations. SAR images containing radar signature of rain events allow a much more detailed study of fine-scale structures of rain events over the World's ocean, in particular of clusters of rain cells, than any other sensor presently flown in space.

Development of a method for generating operational solar radiation maps from satellite data for a tropical environment

Despite a considerable number of publications which use satellite data to map solar radiation, relatively few studies have been undertaken in a tropical environment. In this study, we have developed a method to produce operational solar radiation maps from satellite data for this environment. The method is based on a physical model which relates the satellite-derived earth–atmospheric reflectivity from visible channel of GMS-4 and GMS-5 to the transmissivity of the atmosphere. Cloud reflectivity was determined from satellite data, while radiation absorbed by water vapour, ozone and aerosols and radiation scattered by aerosols were determined from ground-based meteorological data. Techniques for determining the radiation depleted by these atmospheric constituents over a whole country were also presented. Satellite data of a six-year period (1993–1998) with approximately ten thousand satellite images were used to construct the maps. When tested against an independent data set, monthly average of daily global irradiation calculated from this method agree with that obtained from the measurements with the relative root mean square difference of 6.8% with respect to the mean values. Solar radiation is presented as twelve maps showing the monthly average of global irradiation and one map showing the yearly average of global irradiation. Radiation patterns from the maps show a strong influence of the tropical monsoons.

Radio Acoustic Sounding in Urban Meteorological Observations

Meteorological observations are carried out using a mobile Radio Acoustic Sounding System (RASS), a radiosonde system, and ground-based meteorological measurement systems in order to understand urban meteorological conditions. The newly mobile RASS was operated in the one-shot acoustic pulse (OSAP) mode, allowing the measurement of atmospheric temperature up to about 200 m without causing sound pollution. Based on the temperature profiles obtained using the mobile RASS and radiosondes in the Tokyo metropolitan area during the end of February 2000, a marked decrease in temperature within a short period of time was observed. Rare meteorological phenomena such as this can be analyzed based on temperature profiles and ground-based meteorological data that are observed in Tokyo by government offices at a large number of the sites. As a result, temperatures decreased rapidly due to cold airflow into the measurement sites, and the occurrence of the inversion layer was recognized from RASS temperature profiles within a short time interval.

Spatial Patterns in Surface Energy Balance Components Derived from Remotely Sensed Data

A relatively simple modeling approach for estimating spatially distributed surface energy fluxes was applied to two small watersheds, one in a semi-arid climate region and one in a sub-humid region. This approach utilized a combination of ground-based meteorological data and remotely sensed data to estimate ‘instantaneous’ surface energy fluxes at the time of the satellite or aircraft overpasses. The spatial resolution in the watershed grid cells, which was on the order of 100-400 km, was selected to be compatible with ground measurements used for validation. The model estimates of surface energy fluxes compared well with ground-based measurements of surface flux (typically within approximately 40 Wm−2). The model accuracy may be slightly less for bare soil surfaces due to an overestimation of the soil heat flux. In addition to demonstrating the feasibility of computing spatially distributed values of surface energy fluxes, these maps were used to qualitatively infer the dominant factors controlling the energy fluxes for the time period shortly following precipitation events in the basins. For the semi-arid watershed, values of sensible heat flux varied considerably over the watershed and displayed a pattern very similar to that of the spatially variable cumulative precipitation for at least one to eight days prior to the image acquisition. Due to the large fraction of exposed bare soil in a semi-arid ecosystem, even very small precipitation events had a strong influence on the pattern of sensible heat fluxes observed shortly after the event (less than 24 hours). For the sub-humid watershed, the fluxes tended to be more uniform across the watershed, and were influenced by a combination of precipitation total and land cover type.

Application of a photochemical grid model to milan metropolitan area

High ozone levels are regularly reached during summer period in South-European urban areas, calling for careful design of primary pollutants emission reduction strategies. In this perspective the CALGRID modelling system has been applied to Milan metropolitan area, located in the Po Valley, the most industrialised and populated area in Italy. For the first modelling exercise, a simulation domain of 100×100km2 has been considered and a summer period, characterised by high photochemical activity, has been selected. Hourly emissions have been derived by spatially and temporally disaggregating national inventories data, while standard upper-air and ground-based meteorological data have been used as input to the CALMET pre-processor. A careful analysis of simulation results versus local network monitoring data has revealed some critical points, related to both modelling assumptions and practical data availability. A satisfactory reproduction of daytime ozone behaviour has been, in fact, accomplished, both in urban and suburban sites, while nighttime primary pollutants accumulations and consequent ozone consumption simulated by the model have not found correspondence in the measurements. Nitrogen dioxide has been also successfully modelled, mostly in city surroundings, whereas higher discrepancies have been found in some urban stations. Possible explanations of these facts are discussed in the paper, giving an insight for further work.

Spatially Distributed Sensible Heat Flux over a Semiarid Watershed. Part II: Use of a Variable Resistance Approach with Radiometric Surface Temperatures

Radiometric surface temperature images from aircraft observations over the Walnut Gulch Experimental Watershed, a semiarid rangeland watershed, were used with ground-based meteorological data at a reference site for extrapolating estimates of surface sensible heat flux across the basin. Two approaches were used. One method assumed that the resistance to heat transport and other meteorological data at a reference site were constant over the watershed. This resulted in a simple scheme (constant resistance approach) for computing spatially distributed sensible heat flux since the variation in sensible heat flux was directly proportional to surface temperature differences from the reference site. The second approach (the variable resistance approach) used spatially distributed estimates of the surface roughness for momentum and heat, as well as air temperature and wind speed. The sensible heat flux values derived by both techniques were compared to measurements made at several other locations in the watershed for three different days. The environmental conditions for these days ranged from uniformly dry surface soil moisture to variably wet conditions caused by several high intensity and spatially variable rainfall events. Comparisons between these two schemes with observations indicated that the more detailed method of accounting for changes in surface roughness over the basin gave significantly better agreement than the simpler scheme. The average percentage of difference with measured values was 30% for the constant resistance approach compared to approximately 20% for the variable resistance method.

A one-layer resistance model for estimating regional evapotranspiration using remote sensing data

A methodology has been developed for estimating regional evapotranspiration using remote sensing data. The transfer of sensible and latent heat is described by an aerodynamic resistance and a surface resistance. The aerodynamic resistance is formulated on the basis of the Monin-Obukhov similarity theory and the surface resistance is determined from the energy balance equation using remotely sensed surface temperature. The regional evapotranspiration is then calculated with a one-layer resistance model. The overall surface transfer characteristics at regional scale are characterized by an effective roughness length and this parameter was determined from local roughness length with the aid of remote sensing measurements. The model was validated by using the data obtained during the HAPEX-MOBILHY (Hydrologic Atmospheric Pilot Experiment and Modelisation du Bilan Hydrique) experiment. At local scale with homogeneous surface conditions, good agreement ( r = 0.90, RMSE = 50 W m −2) was obtained between model estimates and the measurements at ground stations. The regional evapotranspiration from the agricultural part of the HAPEX-MOBILHY was also calculated with the one-layer resistance model by combining the NOAA-AVHRR with ground-based meteorological data. The calculated regional evapotranspiration was compared with the area averages of the evapotranspiration measured by the ground-based stations. The two techniques agreed fairly well and the average difference was only 28 W m −2.

Mapping surface energy balance components by combining landsat thematic mapper and ground-based meteorological data

Surface energy balance components were evaluated by combining satellite-based spectral data with on-site measurements of solar irradiance, air temperature, wind speed, and vapor pressure. Maps of latent heat flux density (λE) and net radiant flux density (R n) were produced using Landsat Thematic Mapper (TM) data for three dates: 23 July 1985, 5 April 1986, and 24 June 1986. On each date, a Bowen-ratio apparatus, located in a vegetated field, was used to measure λE and R n at a point within the field. Estimates of λE and R n were also obtained using radiometers aboard an aircraft flown at 150 m above ground level. The TM-based estimates differed from the Bowen-ratio and aircraft-based estimates by less than 12 % over mature fields of cotton, wheat, and alfalfa, where λE and R n ranged from 400 to 700 Wm −2.

Evaluating evaporation from field crops using airborne radiometry and ground-based meteorological data

Airborne measurements of reflected solar and emitted thermal radiation were combined with ground-based measurements of incoming solar radiation, air temperature, windspeed, and vapor pressure to calculate instantaneous evaporation (LE) rates using a form of the Penman equation. Estimates of evaporation over cotton, wheat, and alfalfa fields were obtained on 5 days during a one-year period. A Bowen ratio apparatus, employed simultaneously, provided ground-based measurements of evaporation. Comparison of the airborne and ground techniques showed good agreement, with the greatest difference being about 12% for the instantaneous values. Estimates of daily (24 h) evaporation were made from the instantaneous data. On three of the five days, the difference between the two techniques was less than 8%, with the greatest difference being 25%. The results demonstrate that airborne remote sensing techniques can be used to obtain spatially distributed values of evaporation over agricultural fields.

Evaluating evapotranspiration at local and regional scales

Combining remotely sensed data with ground-based meteorological data allows the evaluation of evapotranspiration (the evaporation of water from soil and plant surfaces) at local and regional scales. Remote sensors can provide information on reflected solar radiation and surface temperatures. The remaining variables in the energy balance equations must be measured at ground level, estimated, modeled, or ignored. It is how these variables are evaluated that distinguish the several approaches to estimating evapotranspiration. In general, regional scale methods would apply to part or all of a satellite image, and use meteorological data from local weather stations. Local scale techniques would rely largely on airborne remote sensors and on-site measurements of the pertinent meteorological factors at the time of remote-data collection. In this paper, methods for estimating evapotranspiration on both local and regional scales are reviewed, and some factors that complicate its measurement are discussed.