Statistical downscaling of hourly and daily climate scenarios for various meteorological variables in South-central Canada

Summary A regression-based methodology was used to downscale hourly and daily station-scale meteorological variables from outputs of large-scale general circulation models (GCMs). Meteorological variables include air temperature, dew point, and west–east and south–north wind velocities at the surface and three upper atmospheric levels (925, 850, and 500 hPa), as well as mean sea-level air pressure and total cloud cover. Different regression methods were used to construct downscaling transfer functions for different weather variables. Multiple stepwise regression analysis was used for all weather variables, except total cloud cover. Cumulative logit regression was employed for analysis of cloud cover, since cloud cover is an ordered categorical data format. For both regression procedures, to avoid multicollinearity between explanatory variables, principal components analysis was used to convert inter-correlated weather variables into uncorrelated principal components that were used as predictors. The results demonstrated that the downscaling method was able to capture the relationship between the premises and the response; for example, most hourly downscaling transfer functions could explain over 95% of the total variance for several variables (e.g. surface air temperature, dew point, and air pressure). Downscaling transfer functions were validated using a cross-validation scheme, and it was concluded that the functions for all weather variables used in the study are reliable. Performance of the downscaling method was also evaluated by comparing data distributions and extreme weather characteristics of downscaled GCM historical runs and observations during the period 1961–2000. The results showed that data distributions of downscaled GCM historical runs for all weather variables are significantly similar to those of observations. In addition, extreme characteristics of the downscaled meteorological variables (e.g. temperature, dew point, air pressure, and total cloud cover) were examined. Authors’ addresses: Chad Shouquan Cheng, Guilong Li, Qian Li, Atmospheric Science and Applications Unit, Meteorological Service of Canada Branch-Ontario, Environment Canada, 4905 Dufferin Street, Toronto, Ontario, Canada M3H 5T4; Heather Auld, Adaptation and Impacts Research Division, MSC Branch, Environment Canada, Toronto, Canada.     

A comparison of two methods of estimating transpiration rates from a Sitka spruce plantation

Estimates of hourly transpiration from a 16–17 yr old Sitka spruce forest were calculated from the Penman-Monteith combination equation and compared with estimates from an eddy correlation/energy balance method.Canopy conductances were estimated from stomatal conductances measured using null balance diffusion porometers and took account of canopy variations of stomatal conductance and needle area index.Vertical heat fluxes were measured by the eddy correlation method; transpiration fluxes were then estimated from an energy balance of the forest.There was not a 1:1 relationship between the estimates of transpiration from the two methods. The major sources of error were concluded to be (i) difficulties of estimating the variation in stomatal conductance and leaf area through the canopy, (ii) errors in the value of total leaf area index, and (iii) errors in stomatal conductance measurements.The eddy correlation method was suggested as the more useful for future studies of the variation of forest transpiration in time or space, because the Penman-Monteith equation requires extensive biological measurements.     

Hourly predictive Levenberg–Marquardt ANN and multi linear regression models for predicting of dew point temperature

In this study, the ability of two models of multi linear regression (MLR) and Levenberg–Marquardt (LM) feed-forward neural network was examined to estimate the hourly dew point temperature. Dew point temperature is the temperature at which water vapor in the air condenses into liquid. This temperature can be useful in estimating meteorological variables such as fog, rain, snow, dew, and evapotranspiration and in investigating agronomical issues as stomatal closure in plants. The availability of hourly records of climatic data (air temperature, relative humidity and pressure) which could be used to predict dew point temperature initiated the practice of modeling. Additionally, the wind vector (wind speed magnitude and direction) and conceptual input of weather condition were employed as other input variables. The three quantitative standard statistical performance evaluation measures, i.e. the root mean squared error, mean absolute error, and absolute logarithmic Nash–Sutcliffe efficiency coefficient $ \left( {\left| {{\text{Log}}({\text{NS}})} \right|} \right) $ were employed to evaluate the performances of the developed models. The results showed that applying wind vector and weather condition as input vectors along with meteorological variables could slightly increase the ANN and MLR predictive accuracy. The results also revealed that LM-NN was superior to MLR model and the best performance was obtained by considering all potential input variables in terms of different evaluation criteria.     

美国农业气象和农田蒸散研究

美国的农业气象比较强调基础和应用研究，重点为土壤－大气系统中的能量交换，水分交换，物质积累和转化，农业生产模型以及植物与环境相互作用机制等。试验多在大田条件下进行，配有比较完善的数据自动化采集系统，在农田实际蒸散的测定中，中子仪和蒸散仪得了广泛的应用，并用来检验各种蒸散计算公式。潜在蒸攻的计算方法很多，多在Ｐｅｎｍａｎ公式的基础上发展而来，并研制了相应的计算机软件，和其它公式相比，Ｐｅｎｍａｎ－Ｍ     

A cloud layer‐sunshine model for estimating direct,diffuse and total solar radiation

A previous study (Suckling and Hay, 1976a) described a method for calculating hourly values of the direct and diffuse solar radiation for cloudless sky conditions. This paper presents an extension which incorporates the effects of clouds through the use of hourly values of cloud amount and type for up to four layers and hourly bright sunshine totals. The latter data provide a more accurate measure of the length of time the direct radiation of the sun is not attenuated by cloud. On an average, the cloud layer‐sunshine (CLS) model estimated daily total solar radiation at five Canadian locations to within ±15 per cent of the measured values. This was an improvement over an earlier model (Davies et al., 1975) based on cloud data alone, but the relative advantage, as well as the overall errors themselves, were diminished as the averaging period was increased to five and ten days. The CLS model has the additional advantage of calculating the separate direct and diffuse components of the total solar radiation.     

Effect of Macrophysical Parameters of Clouds on Broadband Solar Radiation (295-2800 nm) at a Subtropical Location

The present study describes the effect of clouds(macro-physical parameters) on global solar radiation(G).Data from four years of hourly measurements of G on a horizontal surface were used.These data were collected at the South Valley University(SVU) meteorological research station(26.2°N,32.7°E,96 m above mean see level.In addition,the cloud modification factor for G(CMFG) was estimated in three cases:high-level,mid-level,and low-level clouds.For every level,the variation of hourly CMFG as a function of cloud amount(CA) was illustrated.A third-order polynomial between hourly values of CMFG and CA was established.Furthermore,the effect of CA in the attenuation of G relative to its corresponding value in cloudless conditions is discussed.For cloud cover > 88%,G was reduced by 54%,34%,and 28% by low-,mid-,and high-level clouds,respectively.     

参考作物蒸散模型对比分析及评价

利用山东省6个气象台站45 a(1960-2004年)的逐日气象资料并选用7种参考作物蒸散模型,分别计算了上述各地的参考作物蒸散,对模型结果进行时空分布对比分析;进而以FAO推荐的Penman-Monteith模型为对照,利用最小一乘法对其余6种模型进行优化并对优化前后的模型进行时空比较.结果表明:Makkink模型在6个台站的时空分布模拟效果均最好,Mass-transfer模型在7-8月明显偏低,Net Radiation模型各站全年基本都偏高;根据不同月份的相对偏差情况,采用最小一乘法进行分月优化,优化后的模型预测月参考作物蒸散标准误差小于5 mm,平均相对误差小于8.5%,台站的年参考作物蒸散相对误差也基本小于10%,说明这些含参数较少的模型经优化后基本上可用,当资料缺损时不失为Penman-Monteith模型的替代模型.     

Accuracy evaluation of ClimGen weather generator and daily to hourly disaggregation methods in tropical conditions

Daily and sub-daily weather data are often required for hydrological and environmental modeling. Various weather generator programs have been used to generate synthetic climate data where observed climate data are limited. In this study, a weather data generator, ClimGen, was evaluated for generating information on daily precipitation, temperature, and wind speed at four tropical watersheds located in Hawai??i, USA. We also evaluated different daily to sub-daily weather data disaggregation methods for precipitation, air temperature, dew point temperature, and wind speed at M??kaha watershed. The hydrologic significance values of the different disaggregation methods were evaluated using Distributed Hydrology Soil Vegetation Model. MuDRain and diurnal method performed well over uniform distribution in disaggregating daily precipitation. However, the diurnal method is more consistent if accurate estimates of hourly precipitation intensities are desired. All of the air temperature disaggregation methods performed reasonably well, but goodness-of-fit statistics were slightly better for sine curve model with 2?h lag. Cosine model performed better than random model in disaggregating daily wind speed. The largest differences in annual water balance were related to wind speed followed by precipitation and dew point temperature. Simulated hourly streamflow, evapotranspiration, and groundwater recharge were less sensitive to the method of disaggregating daily air temperature. ClimGen performed well in generating the minimum and maximum temperature and wind speed. However, for precipitation, it clearly underestimated the number of extreme rainfall events with an intensity of >100 mm/day in all four locations. ClimGen was unable to replicate the distribution of observed precipitation at three locations (Honolulu, Kahului, and Hilo). ClimGen was able to reproduce the distributions of observed minimum temperature at Kahului and wind speed at Kahului and Hilo. Although the weather data generation and disaggregation methods were concentrated in a few Hawaiian watersheds, the results presented can be used to similar mountainous location settings, as well as any specific locations aimed at furthering the site-specific performance evaluation of these tested models.     

A note on: Estimation of rainfall due to squall lines over West Africa using meteosat imagery

Summary The results of the first step of a project to develop a method to estimate precipitation over the Soudano-Sahelian belt of West Africa are reported.The study has been performed over the period from 10 June to 9 July 1986 using hourly METEOSAT infrared images. 122 individual cloud clusters associated with squall lines or tropical storms have been tracked. For each event, the time variations of a convection index giving the volume of cloud cooler than –40°C has been determined every hour. The convection index exhibits a strong diurnal cycle. From daily rainfall amounts obtained at about 300 stations, and assuming a time apportion of rainfall within a cloud cluster, the time variations of the hourly total rainfall produced by the cluster can be determined and represents the precipitation index. Because of insufficient rainfall, the precipitation index has been determined for only 17 events. For 2/3 of the 17 cases, there is a significant correlation between the two indices. For each of the 17 events, precipitation has been regressed on the associated convective index and relative time variations. In that case, the results indicate that a convective index representing the life history of the cloud cluster can be calibrated with corresponding raingage measurements provided raingage data are available. Then, estimation of rainfall due to that event over data void regions can be obtained. However, this study shows that no universal relationship exists between precipitation: no rainfall can be estimated if there is not enough raingage measurements to construct a precipitation index for a tracked cloud cluster. This represents a limitation to the method.With 9 Figures     

Operational model for direct determination of evapotranspiration for well watered crops in Mediterranean region

Direct calculation of actual evapotranspiration ET_c based on Penman-Monteith type models gives more accurate values than indirect models, which need the determination of reference evapotranspiration and crop coefficient. However, the direct models need the measurement of weather variables above the crop, which is limiting and not easily feasible in practice. An operational version of a known ET_c direct model is described and tested. This new version is based on the determination of the weather variables collected in a standard agro-meteorological station. The original and the operational versions of the ET_c model were validated on two crops with contrasting height: soybean (0.8 m) and sweet sorghum (3 m). For soybean, ET_c calculated with the two versions gave results very similar at both hourly and daily scales. For sweet sorghum, ET_c calculated with the operational version is good at daily scale and not as good, although acceptable, at the hourly scale.     

Evaluation of the profile and the resistance method for estimation of surface fluxes of momentum,sensible and latent heat

Summary Hourly lysimetric and micrometeorological data taken over a grass surface at the Meteorological Research Unit, Cardington U.K. have been analysed. A temperature difference and measurements of wind speed at only one height, combined with an independently estimated effective roughness length allowed sensible heat and momentum fluxes determination by the profile method on an hourly basis. The estimates are compared with direct measurements of sensible heat and friction velocity obtained by the eddy correlation method. The sensible and latent heat fluxes are also modelled by the resistance method. Equations based on the Monin—Obukhov similarity theory are used to account for stability effects through various forms of parameterization Aerodynamic and surface resistances, necessary for the Penman—Monteith equation are calculated from routinely measured meteorological data. The profile method for estimation of sensible heat flux and friction velocity is found to work excellently on the discussed daytime experimental data which correspond mainly to near neutral or slightly unstable conditions.Surface latent and sensible heat fluxes can also be described very well by the resistance method. A slightly better estimate of the sensible heat flux is achieved when stability corrections are taken into account. On the contrary Penman-Monteith equation for estimating latent heat flux is insensitive to adjustments for atmospheric stability.The comparison of the various methods leads to the establishment of empirical relationships which correlate various quantities such as soil heat flux, resistances, evapotranspiration etc. to routinely measured meteorological data.With 8 Figures     

Measurement and modelling of dew in island,coastal and alpine areas

We compare the characteristics of dew at nearly the same latitude (42–45°N) for the Mediterranean island of Corsica (Ajaccio, France) and two continental locations (Bordeaux, France, Atlantic coastal area; Grenoble, France, alpine valley). Dew amount was measured on a horizontal reference plate made of polymethylmethacrylate (PMMA) and placed at 1 m above the ground. Data are correlated with plate and air temperature, air relative humidity, wind speed and cloud cover during the period from 14-08-1999 to 15-01-2003.General features as well as particularities of the sampling sites are discussed. The average daily dew yield is higher for the island station at Ajaccio (0.070 mm) than the Bordeaux coastal area (0.046 mm) or the Grenoble valley (0.036 mm). However, the accumulated dew yield was highest for the coastal station (9.8 mm/year) as compared to the island (8.4 mm/year), and much larger than in the alpine valley (4 mm/year). The difference between cumulated and average dew yield stems from the greater number of dew days in the coastal area (58%) versus 33% for the island and 30% in the valley. The higher wind speeds at the island station (average wind during dew is 2 m/s) and lower relative humidity explain the smaller number of dew days. The dew rate seasonal variation is negligible in Bordeaux and exhibits during summer a maximum in Ajaccio and a minimum in Grenoble.A computer model that includes simple meteorological data (air temperature and relative humidity, wind speed, cloud cover) is used to determine the thermal balance and fit to dew mass evolution. Two parameters that account for heat and mass exchange can be adjusted. It was found that, within the uncertainties, these two numbers are the same for the two continental sites, thus allowing dew formation on plates to be evaluated from only simple meteorological measurements. Somewhat larger values are found for the island, due to limitations in the model, which are discussed.     

Estimation of dew point temperature using neuro-fuzzy and neural network techniques

This study investigates the ability of two different artificial neural network (ANN) models, generalized regression neural networks model (GRNNM) and Kohonen self-organizing feature maps neural networks model (KSOFM), and two different adaptive neural fuzzy inference system (ANFIS) models, ANFIS model with sub-clustering identification (ANFIS-SC) and ANFIS model with grid partitioning identification (ANFIS-GP), for estimating daily dew point temperature. The climatic data that consisted of 8 years of daily records of air temperature, sunshine hours, wind speed, saturation vapor pressure, relative humidity, and dew point temperature from three weather stations, Daego, Pohang, and Ulsan, in South Korea were used in the study. The estimates of ANN and ANFIS models were compared according to the three different statistics, root mean square errors, mean absolute errors, and determination coefficient. Comparison results revealed that the ANFIS-SC, ANFIS-GP, and GRNNM models showed almost the same accuracy and they performed better than the KSOFM model. Results also indicated that the sunshine hours, wind speed, and saturation vapor pressure have little effect on dew point temperature. It was found that the dew point temperature could be successfully estimated by using T _mean and R _H variables.     

First Surface-based Estimation of the Aerosol Indirect Effect over a Site in Southeastern China

The deployment of the U.S. Atmospheric Radiation Measurement mobile facility in Shouxian from May to December2008 amassed the most comprehensive set of measurements of atmospheric, surface, aerosol, and cloud variables in China.This deployment provided a unique opportunity to investigate the aerosol–cloud interactions, which are most challenging and, to date, have not been examined to any great degree in China. The relationship between cloud droplet effective radius(CER) and aerosol index(AI) is very weak in summer because the cloud droplet growth is least affected by the competition for water vapor. Mean cloud liquid water path(LWP) and cloud optical depth(COD) significantly increase with increasing AI in fall. The sensitivities of CER and LWP to aerosol loading increases are not significantly different under different air mass conditions. There is a significant correlation between the changes in hourly mean AI and the changes in hourly mean CER,LWP, and COD. The aerosol first indirect effect(FIE) is estimated in terms of relative changes in both CER(FIECER) and COD(FIECOD) with changes in AI for different seasons and air masses. FIECODand FIECERare similar in magnitude and close to the typical FIE value of ~ 0.23, and do not change much between summer and fall or between the two different air mass conditions. Similar analyses were done using spaceborne Moderate Resolution Imaging Spectroradiometer data. The satellite-derived FIE is contrary to the FIE estimated from surface retrievals and may have large uncertainties due to some inherent limitations.     

A new approach to identify the sensitivity and importance of physical parameters combination within numerical models using the Lund–Potsdam–Jena (LPJ) model as an example

Daily global solar irradiation (R _s) is one of the main inputs in environmental modeling. Because of the lack of its measuring facilities, high-quality and long-term data are limited. In this research, R _s values were estimated based on measured sunshine duration and cloud cover of our synoptic meteorological stations in central and southern Iran during 2008, 2009, and 2011. Clear sky solar irradiation was estimated from linear regression using extraterrestrial solar irradiation as the independent variable with normalized root mean square error (NRMSE) of 4.69 %. Daily R _s was calibrated using measured sunshine duration and cloud cover data under different sky conditions during 2008 and 2009. The 2011 data were used for model validation. According to the results, in the presence of clouds, the R _s model using sunshine duration data was more accurate when compared with the model using cloud cover data (NRMSE = 11. 69 %). In both models, with increasing sky cloudiness, the accuracy decreased. In the study region, more than 92 % of sunshine durations were clear or partly cloudy, which received close to 95 % of total solar irradiation. Hence, it was possible to estimate solar irradiation with a good accuracy in most days with the measurements of sunshine duration.     

Calculation of solar irradiances for inclined surfaces: Validation of selected hourly and daily models

Abstract

Irradiance data obtained over a long period at Vancouver and Toronto, Canada, and covering a range of slope orientations are used to validate four models that estimate either the direct or diffuse solar irradiances for inclined surfaces. Evaluations are initially performed for daily and hourly time integrals. A simple parametrization of the diffuse sky radiance dramatically improves estimates of the diffuse irradiance. Both of the direct irradiance models have difficulty accommodating the diurnal characteristics of the irradiance, and consequently modelling errors are substantial for slopes not directly facing the equator. For equator‐facing slopes a saving in data requirements and computational effort through the use of daily integrals can be achieved with little additional error. A substantial portion of the differences between the measured and estimated irradiances is non‐systematic in nature and is therefore reduced through temporal averaging.     

Evaluation of cloud vertical structure simulated by recent BCC_AGCM versions through comparison with CALIPSO-GOCCP data

ABSTRACT The abilities of BCC-AGCM2.1 and BCC_AGCM2.2 to simulate the annual-mean cloud vertical structure （CVS） were evaluated through comparison with GCM-Oriented CALIPSO Cloud Product （CALIPSO-GOCCP） data. BCC-AGCM2.2 has a dynamical core and physical processes that are consistent with BCC-AGCM2.1, but has a higher horizontal resolution. Results showed that both BCC-AGCM versions underestimated the global-mean total cloud cover （TCC）, middle cloud cover （MCC） and low cloud cover （LCC）, and that BCC_AGCM2.2 underestimated the global-mean high cloud cover （HCC）. The global-mean cloud cover shows a systematic decrease from BCCA-GCM2.1 to BCC_AGCM2.2, especially for HCC. Geographically, HCC is significantly overestimated in the tropics, particularly by BCC_AGCM2,1, while LCC is generally overestimated over extra-tropical lands, but significantly underestimated over most of the oceans, especially for subtropical marine stratocumulus clouds. The leading EOF modes of CVS were extracted. The BCC_AGCMs perform well in reproducing EOF1, but with a larger variance explained. The two models also capture the basic features of EOF3, except an obvious deficiency in eigen- vector peaks. EOF2 has the largest simulation biases in both position and strength of eigenvector peaks. Furthermore, we investigated the effects of CVS on relative shortwave and longwave cloud radiative forcing （RSCRF and RLCRF）. Both BCC_AGCM versions successfully reproduce the sign of regression coefficients, except for RLCRF in PC1. However, the RSCRF relative contributions from PC1 and PC2 are overestimated, while the relative contribution from PC3 is underes timated in both BCC_AGCM versions. The RLCRF relative contribution is underestimated for PC2 and overestimated for PC3.     

Climate change in the Paraná state,Brazil: responses to increasing atmospheric CO 2 in reference evapotranspiration

The hydrological variable evapotranspiration (ET) is challenging to estimate because it cannot be measured directly in natural environments (except in small plots). The uncertainties associated with the models used for its prediction have increased under climate change conditions. We studied the influence of stomatal resistance on ET estimates using the Penman-Monteith method as projected by three general circulation models in two emission scenarios (RCP4.5 and RCP8.5) for future climates throughout the twenty-first century (2010–2039, 2040–2069, and 2070–2099). We also investigated the probable ET rate changes in relation to the current (30 years average, 1980–2009) climate conditions for the Paraná state in the southern region of Brazil. The results were regionalized to help policymakers assess climate change impacts and design adaptation measures. ET increases of up to 15% were found in future climate conditions, which may lead to a significant increase in the water demand for agricultural crops. However, we believe that plant morphophysiological changes may occur under atmospheric CO2 enrichment conditions and that a possible reduction in stomatal conductance will result in lower ET increases than those obtained with the traditional Penman-Monteith method. When considering future climate scenarios, we propose the equation be adjusted to consider stomatal resistance as a function of CO2 concentrations.     

Cloud Transmission Estimates of UV-B Erythemal Irradiance

Summary Two UV-Biometer 501A instruments were used to estimate global erythemal irradiance at two locations in southwest Sweden; the Earth Sciences Centre, University of G?teborg (57.69° N; 11.92° E) and the island of Nordkoster, 200 km to the north (58.83° N; 10.72° E). A semi-empirical radiative transfer model was used to calculate the global erythemally effective irradiance under clear skies. A ratio of the hourly measured to clear-sky modelled irradiance was then derived for zenith angles 35–70°. Subsequent comparisons were then made with routine measurements of sunshine duration at G?teborg and sunshine duration, cloud cover, type and height at Nordkoster. Cloud transmission of UV-B irradiance decreases with increasing solar zenith angle, with cloud attenuation being 8% stronger at Nordkoster Island for zenith angles >>;60°. Transmission also decreases with increasing cloud cover such that overcast cloud conditions reduce transmissions by an average of 75%. In addition, cloud type affects the amount of ground incident irradiant flux. Fractus cloud afforded the least UV-B transmission (0.16), while cirrus filaments afforded the most (0.95). The spatial and temporal distribution of clouds appears tobe non-random. Under conditions of 1 to 3 octas, sky cover, clouds appear to be concentrated in line with the sensor and Sun on more occasions than that expected given a random cloud distribution. The same cloud cover condition also resulted in many instances of ground incident irradiance above clear-sky values. The presence of cumuliform clouds appears to increase the likelihood of the latter phenomena. Received January 4, 1998     

基于碳水通量耦合原理改进Penman-Monteith蒸散发模型

陆地蒸散(ET)涵括地表和潮湿叶片的蒸发和植物的蒸散发,是陆地水循环的重要组成部分。Penman-Monteith方程是估算陆地蒸散的重要方法,方程中的叶片或冠层气孔导度是提高估算精度的关键因子。根据碳水循环的耦合原理,植物光合作用模型可用于估算叶片或冠层气孔导度。植物光合作用模型可分为三类:1)使用总冠层导度的大叶模型(BL),2)区别阴、阳叶冠层导度的双大叶模型(TBL),3)区别阴、阳叶叶片导度的双叶模型(TL)。与这三类光合作用模型相对应,衍生出基于不同导度计算方法的三种蒸散估算模型。三种蒸散模型之间的主要区别在于是否进行从叶片尺度到冠层尺度的气孔导度集成。这三种模型中,双叶模型使用叶片尺度的气孔导度,集成度最低。反之,大叶模型使用冠层尺度的气孔导度,集成度最高。由于在Penman-Monteith中,蒸腾和气孔导度之间的关系是非线性的,气孔导度的集合会导致负偏差。因此,与通量测量相比,大叶蒸散模型的估算偏差最大,而双叶蒸散模型的估算偏差最小。