Estimation of storage heat flux in an urban area using ASTER data

The urban heat island phenomenon occurs as a result of the mixed effects of anthropogenic heat discharge, increased use of artificial impervious surface materials, and decreased vegetation cover. These factors modify the heat balance at the land surface and eventually raise the atmospheric temperature. It is important to quantify the surface heat balance in order to estimate the contributions of these factors. The present authors propose the use of storage heat flux to represent the heat flux between the land surface and the inside of the canopy for the heat balance analysis based on satellite remote sensing data. Surface heat fluxes were estimated around the city of Nagoya, Japan using Terra ASTER data and meteorological data. Seasonal and day-night differences in heat balance were compared using ASTER data acquired in the daytime on July 10, 2000, and January 2, 2004 and in the nighttime on September 26, 2003. In the central business and commercial districts, the storage heat flux was higher than those in the surrounding residential areas. In particular, in winter, the storage heat flux in the central urban area was 240 to 290 W m^− 2, which was much larger than the storage heat fluxes in residential areas, which ranged from 180 to 220 W m^− 2. Moreover, the negative storage heat flux in the central urban area was greater at night. This tendency implies that the urban surface stores heat during the daytime and discharges it at night. Extremely large negative storage heat flux occurred primarily in the industrial areas for both daytime and nighttime as a result of the enormous energy consumption by factories.     

Assimilation of remotely sensed data for improved latent and sensible heat flux prediction: A comparative synthetic study

Predicted latent and sensible heat fluxes from Land Surface Models (LSMs) are important lower boundary conditions for numerical weather prediction. While assimilation of remotely sensed surface soil moisture is a proven approach for improving root zone soil moisture, and presumably latent (LE) and sensible (H) heat flux predictions from LSMs, limitations in model physics and over-parameterisation mean that physically realistic soil moisture in LSMs will not necessarily achieve optimal heat flux predictions. Moreover, the potential for improved LE and H predictions from the assimilation of LE and H observations has received little attention by the scientific community, and is tested here with synthetic twin experiments. A one-dimensional single column LSM was used in 3-month long experiments, with observations of LE, H, surface soil moisture and skin temperature (from which LE and H are typically derived) sampled from truth model run outputs generated with realistic data inputs. Typical measurement errors were prescribed and observation data sets separately assimilated into a degraded model run using an Ensemble Kalman Filter (EnKF) algorithm, over temporal scales representative of available remotely sensed data. Root Mean Squared Error (RMSE) between assimilation and truth model outputs across the experiment period were examined to evaluate LE, H, and root zone soil moisture and temperature retrieval. Compared to surface soil moisture assimilation as will be available from SMOS (every 3 days), assimilation of LE and/or H using a best case MODIS scenario (twice daily) achieved overall better predictions for LE and comparable H predictions, while achieving poorer soil moisture predictions. Twice daily skin temperature assimilation achieved comparable heat flux predictions to LE and/or H assimilation. Fortnightly (Landsat) assimilations of LE, H and skin temperature performed worse than 3-day moisture assimilation. While the different spatial resolutions of these remote sensing data have been ignored, the potential for LE and H assimilation to improve model predicted LE and H is clearly demonstrated.     

Modelling surface energy fluxes over maize using a two-source patch model and radiometric soil and canopy temperature observations

Models estimating surface energy fluxes over partial canopy cover with thermal remote sensing must account for significant differences between the radiometric temperatures and turbulent exchange rates associated with the soil and canopy components of the thermal pixel scene. Recent progress in separating soil and canopy temperatures from dual angle composite radiometric temperature measurements has encouraged the development of two-source (soil and canopy) approaches to estimating surface energy fluxes given observations of component soil and canopy temperatures. A Simplified Two-Source Energy Balance (STSEB) model has been developed using a “patch” treatment of the surface flux sources, which does not allow interaction between the soil and vegetation canopy components. A simple algorithm to predict the net radiation partitioning between the soil and vegetation is introduced as part of the STSEB patch modelling scheme. The feasibility of the STSEB approach under a full range in fractional vegetation cover conditions is explored using data collected over a maize (corn) crop in Beltsville Maryland, USA during the 2004 summer growing season. Measurements of soil and canopy component temperatures as well as the effective composite temperature were collected over the course of the growing season from crop emergence to cob development. Comparison with tower flux measurements yielded root-mean-square-difference values between 15 and 50 W m^− 2 for the retrieval of the net radiation, soil, sensible and latent heat fluxes. A detailed sensitivity analysis of the STSEB approach to typical uncertainties in the required inputs was also conducted indicating greatest model sensitivity to soil and canopy temperature uncertainties with relative errors reaching ∼ 30% in latent heat flux estimates. With algorithms proposed to infer component temperatures from bi-angular satellite observations, the STSEB model has the capability of being applied operationally.     

土地利用变化下北京市热通量的时空演变

探究土地利用变化对城市热通量的影响,对城市用地规划和城市热岛缓解具有重要指导意义。利用混合像元组分排序对比和分层能量切割方法,通过Landsat系列数据反演的地表参数,结合气象再分析资料,估算了2004、2009、2014和2017年4期9月份的北京市地表瞬时热通量,依据同期的北京市土地利用图,分析了北京市热通量随土地利用变化的时空演变。结果表明：①北京市地表温度和热通量分布具有明显的空间异质性,山区和平原、平原不同土地利用类型之间差异明显;②在不同时期,土地利用类型间的地表温度和热通量的高低次序具有一致性,瞬时潜热通量,林地最高,为347.85~546.95 W/m²,其次为耕地、草地,建设用地最小,为225.23~349.03 W/m²,感热通量和地表温度则相反,建筑用地最高,分别为94.06~189.28 W/m²和25.18~32.25 ℃,耕地和草地次之,水体的最低,分别为28.15~102.55 W/m²和19.25~28.38 ℃;③土地利用类型转变引起的城市热通量变化方面,自然表面转为建设用地时,潜热通量急剧减少,感热通量增加,城区周边耕地的潜热通量受城市热辐射影响而增加,城市绿地能有效缓解城市热岛效应。     

基于多传感器数据融合的漏磁信号采集与处理

漏磁检测以其高信噪比、高灵敏度和高检测效率,在无损检测中得到了广泛应用。随着科学技术的发展,传统的信号处理方法越来越不适应现代工业的需要,提出一种基于多传感器数据融合技术的漏磁信号处理方法。采用小波去噪的方法,并利用径向基函数(RBF)神经网络的数据融合技术对缺陷信号进行检测处理。仿真结果表明,采用这种方法可以有效提高系统的检测能力和信号精度。     

Global estimates of evapotranspiration for climate studies using multi-sensor remote sensing data: Evaluation of three process-based approaches

Three process based models are used to estimate terrestrial heat fluxes and evapotranspiration (ET) at the global scale: a single source energy budget model, a Penman-Monteith based approach, and a Priestley-Taylor based approach. All models adjust the surface resistances or provide ecophysiological constraints to account for changing environmental factors. Evaporation (or sublimation) over snow-covered regions is calculated consistently for all models using a modified Penman equation. Instantaneous fluxes of latent heat computed at the time of satellite overpass are linearly scaled to the equivalent daily evapotranspiration using the computed evaporative fraction and the day-time net radiation. A constant fraction (10% of daytime evaporation) is used to account for the night time evaporation. Interception losses are computed using a simple water budget model. We produce daily evapotranspiration and sensible heat flux for the global land surface at 5 km spatial resolution for the period 2003-2006. With the exception of wind and surface pressure, all model inputs and forcings are obtained from satellite remote sensing.Satellite-based inputs and model outputs were first carefully evaluated at the site scale on a monthly-mean basis, then as a four-year mean against a climatological estimate of ET over 26 major basins, and finally in terms of a latitudinal profile on an annual basis. Intercomparison of the monthly model estimates of latent and sensible heat fluxes with 12 eddy-covariance towers across the U.S. yielded mean correlation of 0.57 and 0.54, respectively. Satellite-based meteorological datasets of 2 m temperature (0.83), humidity (0.70), incident shortwave radiation (0.64), incident longwave radiation (0.67) were found to agree well at the tower scale, while estimates of wind speed correlated poorly (0.17). Comparisons of the four year mean annual ET for 26 global river basins and global latitudinal profiles with a climatologically estimated ET resulted in a Kendall's τ > 0.70. The seasonal cycle over the continents is well represented in the Hovmöeller plots and the suppression of ET during major droughts in Europe, Australia and the Amazon are well picked up. This study provides the first ever moderate resolution estimates of ET on a global scale using only remote sensing based inputs and forcings, and furthermore the first ever multi-model comparison of process-based remote sensing estimates using the same inputs.     

Mesoscale surface current fields in the Baltic Sea derived from multi-sensor satellite data

We demonstrate the use of multi-sensor satellite images for the computation of mesoscale surface currents in the Northern and Southern Baltic Proper by enhancing and combining image-processing techniques. The sequential satellite images were acquired by the Thematic Mapper (TM), the ERS-2 Synthetic Aperture Radar (SAR), the Wide-Field Scanner (WiFS) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) during extensive cyanobacterial blooms in July 1997 and in July/August 1999. We also used a pair of Advanced SAR (ASAR) images from May 2005 showing imprints of singular oil spills in the Southern Baltic Proper. Different marine surface films and accumulated algae at the water surface were taken as tracers for the local motion of the sea surface. Data from sensors working at different electromagnetic bands (e.g. TM and SAR) were used to apply high-speed feature-matching (cross-correlation) techniques for motion detection. The sufficiently short time lags between the multiple image acquisitions (from less than 1 h to approximately 1 day) and the high spatial coverage allowed for the calculation of optical flow (i.e. surface motion) fields, which include small-scale turbulent structures that are not resolved by operational numerical models. Our computed surface currents range from 4 to 35 cm s^?1 and are generally larger than those provided by the numerical models for the same dates and areas. We attribute this difference to local wind forcing, causing higher drift velocities at the very sea surface, which is seen from space, but which is not resolved by the numerical models.     

改进BP算法在热流传感器温度补偿中的应用

针对帕尔贴( Peltier)热流传感器存在温度漂移问题,提出了一种基于改进BP神经网络的温度补偿模型.采用BP算法的多层前馈网络建立起热流传感器输出电压、实验温度与输入热流间的映射关系,又通过增加动量因子和自适应调节学习率来提高网络的收敛速度与增强网络平稳性.研究结果表明:动量因子-自适应学习率算法温度补偿模型效果明显.     

Characteristic patterns of QuikScat-based wind stress and turbulent heat flux in the tropical Indian Ocean

Using QuikScat-based vector wind data for 1999-2003, surface wind stress and turbulent heat (Q) have been mapped for the tropical Indian Ocean (IO) to understand their seasonal variability. During July wind stress is enhanced by ∼ 70% in the Arabian Sea compared to that during January. The Arabian Sea experiences a large Q loss (150-200 W/m²) during the summer and winter monsoons, which is nearly 1.3 times of that in the Bay of Bengal. The southeasterlies are strengthened during the southern hemisphere winter. Empirical Orthogonal Function analysis captures different phases of monsoon-induced variability in wind stress and Q, ranging from seasonal to high-frequency perturbations. Coherency between time coefficients of EOF-1 for wind stress and Q suggests that former leads the latter with a temporal lag of 20-40 days for period > 322 days. At high frequencies (< 21 days) Q leads wind stress with a temporal lag of 2 days. Possible explanation for wind stress leading Q over an annual time scale is offered based on the marine atmospheric boundary layer physics and pre-conditioned ocean surface, while on shorter time scales (21 days) ocean thermodynamics through mixed layer processes cause Q to lead wind stress.     

Regional evaporation estimates from flux tower and MODIS satellite data

Two models were evaluated for their ability to estimate land surface evaporation at 16-day intervals using MODIS remote sensing data and surface meteorology as inputs. The first was the aerodynamic resistance-surface energy balance model, and the second was the Penman-Monteith (P-M) equation, where the required surface conductance is estimated from remotely-sensed leaf area index. The models were tested using 3 years of evaporation and meteorological measurements from two contrasting Australian ecosystems, a cool temperate, evergreen Eucalyptus forest and a wet/dry, tropical savanna. The aerodynamic resistance-surface energy balance approach failed because small errors in the radiative surface temperature translate into large errors in sensible heat, and hence into estimates of evaporation. The P-M model adequately estimated the magnitude and seasonal variation in evaporation in both ecosystems (RMSE = 27 W m^− 2, R² = 0.74), demonstrating the validity of the proposed surface conductance algorithm. This, and the ability to constrain evaporation estimates via the energy balance, demonstrates the superiority of the P-M equation over the surface temperature-based model. There was no degradation in the performance of the P-M model when gridded meteorological data at coarser spatial (0.05°) and temporal (daily) resolution were substituted for locally-measured inputs.The P-M approach was used to generate a monthly evaporation climatology for Australia from 2001 to 2004 to demonstrate the potential of this approach for monitoring land surface evaporation and constructing monthly water budgets from 1-km to continental spatial scales.     

Three-dimensional analysis of a cohesive crack coupled with heat flux through the crack

This paper presents an algorithm for coupling cohesive crack modeling with non-stationary heat flow. Firstly, the nonlinear system of equation, based on global formulations, for such a computational model is derived. The nonlinearity here comes from nonlinear relations in the crack. The relations refer to cohesion forces and to heat flux which both depend of crack opening and additionally are dependent of temperature difference between both sides of the crack. In the paper the discontinuities of displacement field and temperature field are both approximated using XFEM. All the analysis concerning crack surface is performed using local coordinate systems for each integration point. The local coordinate system is two-dimensional for both 2D and 3D analysis. The paper is illustrated with non-stationary thermo-mechanical examples for a domain with propagating crack.     

Application of a simple algorithm to estimate daily evapotranspiration from NOAA-AVHRR images for the Iberian Peninsula

Evapotranspiration (ET) is a key process in land surface-atmosphere studies. It mainly depends on water availability and incoming solar radiation and then reflects the interactions between surface water processes and climate. In this paper, a methodology for retrieving ET from low spatial resolution remote sensing data is presented. It is based on the evaporative fraction concept, and it has been applied to Advanced Very High Resolution Radiometer (AHVRR) data acquired over the Iberian Peninsula. The methodology does not require other data than the data provided by the satellite and may be applied to areas with almost spatially constant atmospheric conditions and which include wet and dry sub-areas. The comparison with high resolution ET estimation shows a root mean square error (RMSE) of 1.4 mm d^− 1 which is in agreement with the sensitivity analysis of the method. Finally, the methodology has been applied to temporal NOAA-AVHRR images acquired from 1997 to 2002 in order to analyze the seasonal evolution of the daily ET. The temporal study of the ET values realized in this paper shows that the highest ET values are associated with the higher development crops, while the lowest values are related with lower development or null crop. As a conclusion, it is shown that the ET values obtained with the proposed model evolve according to the variations presented in parameters such as surface temperature or vegetation index.     

Mapping solar ultraviolet radiation from satellite data in a tropical environment

This paper presents a technique for mapping erythemally-weighted solar ultraviolet (EUV) radiation from satellite data in a tropical environment. A satellite-based EUV radiation model was formulated for calculating the EUV daily dose from satellite-derived earth-atmospheric albedo, total column ozone and other ground-based ancillary data. The earth-atmospheric albedo was obtained from a geostationary satellite (GMS5) while the total column ozone was retrieved from a polar orbiting satellite (EP/TOMS). The model was validated against the monthly average EUV daily dose from the measurements at four solar radiation monitoring stations located in the tropical environment of Thailand. The monthly average EUV daily dose calculated from the model was in reasonable agreement with that obtained from the measurement, with root mean square difference (RMSD) and mean bias difference (MBD) of 12.3% and 0.7%, respectively. After the validation, the model was used to calculate the monthly average EUV daily dose over Thailand employing an 8-year period of data from GMS5, EP/TOMS and other ancillary surface data. Values of the monthly average of EUV daily dose were presented as monthly and yearly maps. These maps reveal that the tropical monsoons have a strong influence on the EUV in this region.     

Comparison of the performance of latent heat flux products over southern hemisphere forest ecosystems: estimating latent heat flux error structure using in situ measurements and the triple collocation method

ABSTRACT

In this study, we compared different remote-sensing (RS)-based land surface models (LSM) and reanalysis latent heat flux (LE) products over different forest ecosystems. We analysed the performance of three RS products, the MOD16A2, the Breathing Earth System Simulator (BESS) model, and a combined optical-microwave model (COM) in their ability to replicate eddy covariance (EC) flux observations of LE at eight southern hemisphere forest ecosystems and compared their results to simulated LE from the offline LSM (GLDAS/NOAH) and a reanalysis LE dataset (MERRA). To determine spatial uncertainties, we used the triple collocation (TC) method, which does not require a priori knowledge of the true LE value, at selected Australian EC locations and over an area without in situ measurement (the Dry Chaco Forest (DCF), Argentina). The spatial pattern of the TC results was commensurable with uncertainties calculated using EC observations, indicating that the TC method is a robust technique to estimate spatial uncertainties. As global products have been validated with EC measurement from Ozflux stations, we hypothesized and found, using the TC model, that LE products achieve a better performance over areas with EC from networks than over sites without ground-based measurements and may reflect over-calibration of models or a need for a more diverse representation of ecosystems at flux tower networks.     

Computer acquisition and analysis of skin temperature and heat flow data from heat flux transducers

A computer-controlled system for the collection and analysis of skin temperature and heat flow data originating from an array of heat flux transducers is describe. The systems is based on a program (‘THERMAL’) that reads, stores, prints and displays skin temperatures and heat flow data every 2 min for up to 4 h. It also simultaneously calculates important environmental physiology parameters such as mean skin and mean body temperatures as well as mean heat flow according to four different combinations of transducers such as the established 3-, 4-, 7- and 12-point (site) formulae. Core temperature, heart rate and environmental condition indices such as dry bulb, wet bulb and globe temperatures are also continuously monitored.     

Determination of the time-dependent reaction coefficient and the heat flux in a nonlinear inverse heat conduction problem

ABSTRACT

Diffusion processes with reaction generated by a nonlinear source are commonly encountered in practical applications related to ignition, pyrolysis and polymerization. In such processes, determining the intensity of reaction in time is of crucial importance for control and monitoring purposes. Therefore, this paper is devoted to such an identification problem of determining the time-dependent coefficient of a nonlinear heat source together with the unknown heat flux at an inaccessible boundary of a one-dimensional slab from temperature measurements at two sensor locations in the context of nonlinear transient heat conduction. Local existence and uniqueness results for the inverse coefficient problem are proved when the first three derivatives of the nonlinear source term are Lipschitz continuous functions. Furthermore, the conjugate gradient method (CGM) for separately reconstructing the reaction coefficient and the heat flux is developed. The ill-posedness is overcome by using the discrepancy principle to stop the iteration procedure of CGM when the input data is contaminated with noise. Numerical results show that the inverse solutions are accurate and stable.     

On the Earth's surface energy exchange determination from ERS satellite ATSR data: Part 3. Turbulent heat flux on open sea

This is the third in a series of papers which discusses determination of the Earth's surface energy exchange from ERS satellite Along-Track Scanning Radiometer (ATSR) data. This paper focuses on estimation of turbulence heat flux exchange by using ATSR data in areas of open sea. In this paper, we present results of net longwave radiation, latent heat flux and sensible heat flux. The results of net longwave radiation are from the first paper in the series (Xue et al., 1998, International Journal of Remote Sensing, 19, 2561-2583). We use monthly average tropical-ocean-global-atmosphere (TOGA) data and ATSR sea surface temperature (SST) data to calculate two years' (1992 and 1993) heat fluxes in the TOGA area. A comparison with published results indicates good qualitative agreement. Also, we compared the results of heat flux exchange by using ATSR SST data and by using the TOGA bucket SST data. The ATSR SST dataset has been shown to be useful in helping to estimate the large space scale heat flux exchange.     

The relationship between multi-sensor satellite data and Bayesian estimates for skipjack tuna catches in the South Brazil Bight

In this study we tested a Bayesian model based on a conjugate gamma/Poisson pair associated with environmental variables derived from satellite data such as sea surface temperature (SST) and its derived gradient fields from Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra, chlorophyll-a concentration from Sea Viewing Wide field of View Sensor (SEAWiFS)/SeaStar and surface winds and Ekman pumping from SeaWinds/Quick Scatterometer (QuikSCAT) to predict weekly catch estimates of the skipjack tuna in the South Brazil Bight. This was achieved by confronting the fishery data with model estimates and regressing the results on the satellite data. The fishery data were expressed by an index of catch per unit effort (CPUE) calculated as the weight of fish caught (in tonnes) by fishing week, and were divided into two series, called historical series (1996–1998; 2001), and validation year (2002). The output of model CPUE estimates is in good agreement with the historical weekly CPUE and generated updated weekly estimates that explained up to 62% of weekly CPUE from 2002. In general, the best proxy for the Bayesian weekly estimates is the gradient zonal SST field. The results refined previous knowledge of the influence of SST on the occurrence of skipjack tuna.