The FLUXCOM ensemble of global land-atmosphere energy fluxes

The accurate estimation of carbon and heat fluxes at global scale is paramount for future policy decisions in the context of global climate change. This paper analyzes the relative relevance of potential remote sensing and meteorological drivers of global carbon and energy fluxes over land. The study is done in an indirect way via upscaling both Gross Primary Production (GPP) and latent energy (LE) using Gaussian Process regression (GPR). In summary, GPR is successfully compared to multivariate linear regression (RMSE gain of +4.17% in GPP and +7.63% in LE) and kernel ridge regression (+2.91% in GPP and +3.07% in LE). The best GP models are then studied in terms of explanatory power based on the analysis of the lengthscales of the anisotropic covariance function, sensitivity maps of the predictive mean, and the robustness to distortions in the input variables. It is concluded that GPP is predominantly mediated by several vegetation indices and land surface temperature (LST), while LE is mostly driven by LST, global radiation and vegetation indices.

Parameterizations of the optical properties of black carbon (BC) and organic carbon (OC) aerosols in an external mixture are presented. The parameterizations in terms of look‐up tables are based on exact Mie calculations for a high number of wavelengths and values of the relative humidity. Both the shortwave, and the longwave portions of the atmospheric radiation spectra are considered. The parameterizations are used in the developmental version of the fourth generation Canadian Centre for Climate Modelling and Analysis (CCCma) Atmospheric General Circulation Model (AGCM). Previously, this model neglected the impact of OC and BC on the radiative fluxes. The effect of OC and BC on global radiation and energy fluxes is quantified and compared to other aerosol types. It is found that the fraction of the OC/BC aerosol direct effect is rather high. The OC/BC aerosol is responsible for 25% to 65% of the absolute value of the total direct aerosol effect on various radiation and energy fluxes. At the top of the atmosphere, the change in the net solar flux due to BC and OC is +0.31 W m−2, but the sum of all aerosols except for nitrate but including BC and OC leads to a decrease in the net solar flux of 1.16 W m−2. The sum of all aerosols without nitrate reduces the surface sensible heat flux by 0.84 W m−2 with a BC/OC fraction of 0.55 W m−2. For the surface latent heat flux, these values are 1.05 W m−2 and 0.50 W m−2, respectively.

Here we provide a new assessment of the global mean energy fluxes from a surface perspective and present an associated diagram of the global mean energy balance, adapted from the study by Wild et al. (2013) [1] with two slight modifications as outlined in this paper. The radiative energy exchanges between Sun, Earth and space are now accurately quantified from new satellite missions. Much less has been known about the magnitude of the energy flows within the climate system and at the Earth surface, which cannot be directly measured by satellites. In addition to satellite observations, we make extensive use of the growing number of surface observations to constrain the global energy balance not only from space, but also from the surface. We combine these observations with the latest modeling efforts performed for the 5th IPCC assessment report to infer best estimates for the global mean surface radiative components. Our analyses favor global mean downward surface solar and thermal radiation values near 185 and 342 Wm−2, respectively, which are most compatible with surface observations. Combined with an estimated surface absorbed solar radiation and thermal emission of 161 Wm−2 and 398 Wm−2, respectively, this leaves 105 Wm−2 of surface net radiation available for distribution amongst the non-radiative surface energy balance components. Considering an imbalance of 0.6 Wm−2, the global mean sensible and latent heat fluxes are estimated at 20 and 84 Wm−2, respectively, to close the surface energy balance. The global mean surface radiative fluxes derived here in combination with a latent heat flux of 84 Wm−2 may be able to reconcile currently disputed inconsistencies between energy and water cycle estimates. The findings of this study are compiled into a new global energy balance diagram.

The momentum flux to the ocean interior is commonly assumed to be identical to the momentum flux lost from the atmosphere in traditional atmosphere, ocean, and coupled models. However, ocean surface gravity waves (hereafter waves) can alter the magnitude and direction of the ocean-side stress (τoc) from the air-side stress (τa). This is rarely considered in coupled climate and forecast models. Based on a 30-yr wave hindcast, the redistribution of the global wind stress and turbulent kinetic energy (TKE) flux by waves was investigated. Waves play a more important role in the windy oceans in middle and high latitudes than that in the oceans in the tropics (i.e., the central portion of the Pacific and Atlantic Oceans). On average, the relative difference between τoc and τa, γτ, can be up to 6% in middle and high latitudes. The frequency of occurrence of γτ > 9% can be up to 10% in the windy extratropics. The directional difference between τoc and τa exceeds 3.5° in the middle and high latitudes 10% of the time. The difference between τoc and τa becomes more significant closer to the coasts of the continents due to strong wind gradients. The friction velocity-based approach overestimates (underestimates) the breaking-induced TKE flux in the tropics (middle and high latitudes). The findings presented in the current study show that coupled climate and Earth system models would clearly benefit from the inclusion of a wave model. Significance Statement The purpose of this study is to investigate the redistribution of the global wind stress and turbulent kinetic energy flux due to surface waves based on a 30-yr wave hindcast. The mean relative difference of the magnitude between the air-side and ocean-side stress is up to 6% with a 90th percentile of more than 9% in the windy extratropics. Due to strong wind gradients, the redistributive role of waves in the stress becomes more significant closer to coasts. The results indicate that we should consider the redistributive role of waves in the momentum and energy fluxes in climate and Earth system models since they are the key elements in the predictability of weather forecasting models and climate models.

Estimation of radiation during fair weather cloudy situations of the MESOGERS-84 experiment has been examined using micrometeorological observations and satellite data. Diurnal variation of cloudiness is empirically determined using satellite information as a function of global radiation, and relationships between net incoming radiation and global radiation are analyzed. Particularly, it has been found that a very simple relationship between global radiation, cloudiness and net radiative heat flux proposed by Nielsenet al. (1981) can be used with satellite data and applied to the Mesogers region in Southwest France. The different relationships between cloudiness and radiation are utilized to modify and to validate Taconet'set al. model (1986) to get fluxes related to a cloudy situation without advection.

Abstract. Spatio-temporal fields of land–atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number of strategies for empirical models with eddy-covariance flux data have been applied, a systematic intercomparison of these methods has been missing so far. In this study, we performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines). We applied two complementary setups: (1) 8-day average fluxes based on remotely sensed data and (2) daily mean fluxes based on meteorological data and a mean seasonal cycle of remotely sensed variables. The patterns of predictions from different ML and experimental setups were highly consistent. There were systematic differences in performance among the fluxes, with the following ascending order: net ecosystem exchange (R2 < 0.5), ecosystem respiration (R2 > 0.6), gross primary production (R2> 0.7), latent heat (R2 > 0.7), sensible heat (R2 > 0.7), and net radiation (R2 > 0.8). The ML methods predicted the across-site variability and the mean seasonal cycle of the observed fluxes very well (R2 > 0.7), while the 8-day deviations from the mean seasonal cycle were not well predicted (R2 < 0.5). Fluxes were better predicted at forested and temperate climate sites than at sites in extreme climates or less represented by training data (e.g., the tropics). The evaluated large ensemble of ML-based models will be the basis of new global flux products.

基于三江平原稻田2005~2007年5~10月涡度相关通量观测数据, 分析了该区稻田能量通量的日变化、季节变化和能量分配特征以及能量平衡状况。结果表明: 三江平原稻田净辐射和潜热通量日变化均表现为明显的单峰特征, 感热通量日变化在水稻发育进入成熟期后才较明显, 而土壤热通量在水稻整个发育期内日变化特征都不明显。稻田净辐射季节变化特征显著, 6月下旬至7月上旬达到最大值18~20 MJ·m^-2·d^-1。潜热通量季节变化与净辐射同步, 最大值为13~19 MJ·m^-2·d^-1。相比之下感热通量较小, 观测期间变化于-3.90~ 3.94 MJ·m^-2·d^-1, 且没有明显的季节变化。5~10月土壤热通量呈下降趋势, 变化于-2.67~3.62 MJ·m^-2·d^-1。三江平原地区稻田能量分配特征明显, 潜热通量占净辐射的比例(<i>LE</i>/<i>R</i>n) 5~10月平均值为0.67, 表明净辐射大部分以潜热通量形式所消耗, 但生长旺季<i>LE</i>/<i>R</i>n略大于生长季初期和末期。感热通量占净辐射的比例(<i>H</i>s/<i>R</i>n)的季节变化特征与<i>LE</i>/<i>R</i>n比值相反, 观测期间平均值为0.10。这导致波文比在水稻生长旺季较小而在初期和末期较大。5~10月土壤热通量占净辐射的比例(<i>G</i>/<i>R</i>n)呈逐渐下降趋势, 其月平均值由5月的0.14下降到10月的-0.08。线性回归法和能量平衡比率均表明三江平原稻田能量明显不闭合, 2005、2006年5~10月能量不闭合度分别为22%和16%, 而2007年能量"过闭合", 能量平衡比率平均值为1.07。

&amp;#160; &amp;#160; Poleward atmospheric energy transport is determined by the overall equator-to-pole radiative imbalance. As this imbalance is projected to remain fairly constant in end-of-century greenhouse gas forcing scenarios, an increase in poleward latent heat transport must be accompanied by a reduction in dry static energy flux. Since midlatitude energy transport is dominated by the eddy component, changes in the energy budget go hand in hand with changes in cyclone characteristics. From a dynamical perspective, the enhanced condensation due to climate change promotes intensification, prolongs lifetime of cyclones, and can increase stationarity of anticyclones. However, it also tends to increase static stability and thereby reduce baroclinicity, which is another important driver of cyclone development. Additionally, baroclinicity is projected to increase at upper levels due to tropical amplification, to decrease at low levels as a result of Arctic amplification, and to be affected by land-sea temperature contrast changes. As these processes are at play simultaneously, isolating the role of moisture is rather complicated. Therefore, in addition to coupled climate model simulations we use idealized aquaplanet simulations to single out the effects of individual physical mechanisms and address the question: if the overall poleward energy transport remains largely unaffected by global warming, how do cyclone characteristics change in the presence of increased moisture in the atmosphere?&amp;#160; &amp;#160; For bridging the gap between the global energy flux and synoptic-scale features, we analyse the role of increasing moisture for shaping midlatitude storm tracks in present and future climates from both an Eulerian and a Lagrangian perspective. We apply the moist static energy (MSE) framework that allows partitioning atmospheric energy fluxes into eddy and mean, dry and moist components. Here, eddies are related to cyclones and anticyclones, while the mean energy flux is associated with planetary waves and the mean meridional overturning circulation. The goal is to relate the eddy MSE fluxes to feature-based results including extratropical cyclone number, lifetime, intensity, location, and tilt. By combining results from both global-scale eddy energy fluxes and synoptic-scale feature quantities, we aim to improve the understanding of the role of latent heating in shaping the mean properties of extratropical storm tracks. Therefore, a central question of this project is whether and how changes in cyclone quantities can be linked to changes in latent heat transport and release. Building on what we learn from bringing the two perspectives together, we will proceed to investigating the impact of increased latent heating on midlatitude storm tracks.&amp;#160;

Variations in the intensity of the global hydrological cycle can have far-reaching effects on living conditions on our planet. While climate change discussions often revolve around possible consequences of future temperature changes, the adaptation to changes in the hydrological cycle may pose a bigger challenge to societies and ecosystems. Floods and droughts are already today amongst the most damaging natural hazards, with floods being globally the most significant disaster type in terms of loss of human life (Jonkman 2005). From an economic perspective, changes in the hydrological cycle can impose great pressures and damages on a variety of industrial sectors, such as water management, urban planning, agricultural production and tourism. Despite their obvious environmental and societal importance, our understanding of the causes and magnitude of the variations of the hydrological cycle is still unsatisfactory (e.g., Ramanathan et al 2001, Ohmura and Wild 2002, Allen and Ingram 2002, Allan 2007, Wild et al 2008, Liepert and Previdi 2009).

Eddy covariance serves as one the most effective techniques for long-term monitoring of ecosystem fluxes, however long-term data integrations rely on complete timeseries, meaning that any gaps due to missing data must be reliably filled. To date, many gap-filling approaches have been proposed and extensively evaluated for mature and/or less actively managed ecosystems. Random forest regression (RFR) has been shown to be stable and perform better in these systems than alternative approaches, particularly when filling longer gaps. However, the performance of RFR gap filling remains less certain in more challenging ecosystems, e.g., actively managed agri-ecosystems and following recent land-use change due to management disturbances, ecosystems with relatively low fluxes due to low signal to noise ratios, or for trace gases other than carbon dioxide (e.g., methane).In an extension to earlier work on gap filling global carbon dioxide, water, and energy fluxes, we assess the RFR approach for gap filling methane fluxes globally. We then investigate a range of gap-filling methodologies for carbon dioxide, water, energy, and methane fluxes in challenging ecosystems, including European managed pastures, Southeast Asian converted peatlands, and North American drylands.Our findings indicate that RFR is a competent alternative to existing research standard gap-filling algorithms. The marginal distribution sampling (MDS) is still suggested for filling short (< 12 days) gaps in carbon dioxide fluxes, but RFR is better for filling longer (> 30 days) gaps in carbon dioxide fluxes and also for gap filling other fluxes (e.g. sensible heat, latent energy and methane). In addition, using RFR with globally available reanalysis environmental drivers is effective when measured drivers are unavailable. Crucially, RFR was able to reliably fill cumulative fluxes for gaps > 3 moths and, unlike other common approaches, key environment-flux responses were preserved in the gap-filled data.

The total solar eclipse of 11 August 1999 over Central Europe was also visible in Baden-Wuerttemberg, a state in south-west Germany. To investigate the impact of the total solar eclipse on the lower planetary boundary layer, meteorological and air quality data extracted from routine measurements at six sites in BadenWuerttemberg were examined. The meteorological data were recorded at the Plittersdorf meteorological station (in the path of totality of the total solar eclipse) and at the Forestmeteorological Site Hartheim (outside the path of totality of the total solar eclipse). The air quality data were obtained from four ofe cial air quality monitoring stations located at Freudenstadt, Karlsruhe-West, Rastatt and Welzheimer Wald, all of which lie within the path of totality of the total solar eclipse. Due to cloudiness, weather conditions on 11 August 1999 were not optimal in south-west Germany. However, the transient reduction (followed by a rise) induced by the total solar eclipse on meteorological variables including global solar radiation, upward longwave radiation, net radiation, air temperature, horizontal wind speed, elevation angle of the three-dimensional wind vector as well as turbulent sensible and latent heat e uxes was quite obvious. Despite unfavourable weather conditions, half-hourly mean values of ozone routinely measured at the above-mentioned standard ofe cial air quality monitoring stations showed a varying decline up to 27% at the urban station Rastatt and 37% at the background station Welzheimer Wald. This decline was owing mainly to the fall in global radiation during the total solar eclipse. However, additional ine uences by advection and deposition can not be precluded. Zusammenfassung

It is believed that large‐scale oceanic thermohaline circulation is strongly influenced by small‐scale ocean mixing processes. In order to satisfy the large‐scale advective‐diffusive balance of the meridional overturning circulation, about 2.1 TW (1 TW = 1012 W) of power is required for the ocean mixing processes. This power is thought to be supplied by internal tides as well as wind stress fluctuations. Although the global energy flux from internal tides is estimated to be about 0.9 TW based on astronomical measurements, direct estimate of the global energy flux from wind stress fluctuations has not been made so far. In this study, using a simple numerical model, we estimate the wind‐induced global energy flux to inertial motions in the surface mixed layer. The calculated results show that the estimated global energy flux falls short of the required value.

Net radiation estimates are frequently required in watershed research, e.g., in calculating evapotranspiration and snowmelt. In mountainous areas, the effective net radiation, i.e., the horizontal projection of the flux through a surface parallel to the slope, is a more accurate measure of the available energy than that measured with a horizontal sensor. In a non-homogeneous area, however, a basin average of effective net radiation is difficult to estimate. The annual curves for net and global solar radiation under clear skies at one point in the Marmot Creek Experimental Watershed in Alberta, Canada, show variations from 55 to 650 lyday-' for net radiation, and from 100 to 760 ly day-' for global radiation. A factor to convert measured net radiation at the point to a basin average of effective net radiation is obtained by comparing these curves with that for effective clear sky global radiation for the basin, and by considering the ratio of net to global radiation over the various types of vegetation in the basin. This conversion factor varies throughout the year with the elevation of the Sun and the basin albedo, ranging from a maximum of 1.27 in December to a minimum of 0.93 in April, and averaging 1.06 for the year. In watershed research there may be some dispute with the statement by Geiger (1965) that "radiation is undoubtedly the most important of all meteorologic elements" because of the importance of precipitation, but there can be no denying that radiation is of prime importance in studies of evapotranspiration and snowmelt. The problem which confronts the researcher is: which element in the radiation field should be used and how should it to be measured or calculated? Net radiation is the most useful element because it integrates all wavelengths of both incoming and out- going energy. The World Meteorological Organization (1961) defines net radiation as "the net radiant flux through a horizontal surface", but in mountainous terrain, the "effective net radiation", hereby defined as "the horizontal projection of the flux through a surface parallel to the slope", is a more meaningful measure of the available energy. The difference between radiation measured with a horizontal sensor and one parallel to the slope may be positive or negative, and is of course greatest when slopes are steep and the sun is low in the sky. The problem has been studied for incoming short-wave radiation by Lee (1963), Ohmura (1968), Rouse and Wilson (1969), Fergu- son et al. (1971), and others. Kondrat'yev (1965) discussed the radiation balance of a slope, and Hay (1971) presented a complex model for computing the mean monthly intensities of the component fluxes of net radiation for drainage basins. This paper presents a simple method of estimating a basin average of effective net radiation for periods as short as one day from net global radiation data measured by horizontal sensors, along with calculated effective global solar radiation.

&amp;lt;p&amp;gt;Global land-atmosphere energy and carbon fluxes are key drivers of the Earth&amp;amp;#8217;s climate system. Their assessment over a wide range of climates and biomes is therefore essential (i) for a better understanding and characterization of land-atmosphere exchanges and feedbacks and (ii) for examining the effect of climate change on the global water, energy and carbon cycles.&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Large-sample datasets such as the FLUXNET2015 dataset (Pastorello et al., 2020) foster the use of machine learning (ML) techniques as a powerful addition to existing physically-based modelling approaches. Several studies have investigated ML techniques for assessing energy and carbon fluxes, and while across-site variability and the mean seasonal cycle are typically well predicted, deviations from mean seasonal behaviour remains challenging (Tramontana et al., 2016).&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In this study we examine the importance of memory effects for predicting energy and carbon fluxes at half-hourly and daily temporal resolutions. To this end, we train a Long Short-Term Memory (LSTM, Hochreiter and Schmidthuber, 1997), a recurrent neural network with explicit memory, that is particularly suited for time series predictions due to its capability to store information over longer (time) sequences. We train the LSTM on a large number of FLUXNET sites part of the FLUXNET2015 dataset using local meteorological forcings and static site attributes derived from remote sensing and reanalysis data.&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We evaluate model performance out-of-sample (leaving out individual sites) in a 10-fold cross-validation. Additionally, we compare results from the LSTM with results from another ML technique, XGBoost (Chen and Guestrin, 2016), that does not contain system memory. By analysing the differences in model performances of both approaches across various biomes, we investigate under which conditions the inclusion of memory might be beneficial for modelling energy and carbon fluxes.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;

A regional climate model based on the Penn State/NCAR Mesoscale Model (MM5) was used to simulate the 1998 and 1999 East Asian summer monsoon conditions. Simulations were performed for 1 April-31 August of each year, with initial and lateral boundary conditions provided by the ECMWF analysis. Observations from the 1998 and 1999 GAME/HUBEX experiments were used to evaluate the regional climate simulations. Based on observations, large differences can be found between the 1998 and 1999 meteorological conditions and surface energy budgets at the Shouxian station during the IOPs, with much higher rain intensity but only slightly higher rain frequency in 1998 than 1999. For 1998, although the regional climate model was able to reproduce the general spatial distribution of monthly mean rainfall quite well during the summer monsoon season, large discrepancies can be found in comparing the observed and simulated surface climate and energy fluxes in the HUBEX region. By using Four Dimensional Data Assimilation (FDDA) technique, which constrains the simulated large-scale circulation with observations from 21 soundings in the HUBEX α-scale region, both the root mean square error and mean bias in rainfall were greatly reduced. The improvements in simulating rainfall were related to both reduction in errors of precipitation amount and timing. In the control simulation, a mean bias of −63 W/m² (−36%) was found in the simulated surface net radiation at Shouxian, which suggest large errors in simulating clouds in the region. With FDDA, the bias was significantly reduced to −23 W/m² (−13%), with corresponding reduction of bias in the latent heat flux. This suggests that at least part of the model bias in simulating net radiation is related to errors in simulating the large-scale circulation, which can affect cloud amount and vertical distribution.Comparing the 1998 and 1999 simulations, both without FDDA, smaller biases were found in the surface fluxes during 1999. Percentage biases in the net radiation and latent heat flux were −18% and −33% in 1999 and −36% and −50% in 1998 respectively. Based on observations, large differences in the net surface radiation, and small differences in cloud fraction between the two years suggest that cloud optical depth and/or vertical distribution were very different, with more cloudy conditions observed during 1999. Although the 1999 simulations were sensitive to the cumulus convective parameterizations (Grell scheme versus Kain-Fritsch scheme) as shown by the sensitivity experiments, the large differences in simulation skill between the 1998 and 1999 cases, regardless of the convection schemes used, suggest possible dependence of model errors on cloud properties that deserve further investigations.