How Well Can We Measure the Vertical Wind Speed? Implications for Fluxes of Energy and Mass

Sonic anemometers are capable of measuring the wind speed in all three dimensions at high frequencies (10–50 Hz), and are relied upon to estimate eddy-covariance-based fluxes of mass and energy over a wide variety of surfaces and ecosystems. In this study, wind-velocity measurement errors from a three-dimensional sonic anemometer with a non-orthogonal transducer orientation were estimated for over 100 combinations of angle-of-attack and wind direction using a novel technique to measure the true angle-of-attack and wind speed within the turbulent atmospheric surface layer. Corrections to the vertical wind speed varied from −5 to 37% for all angles-of-attack and wind directions examined. When applied to eddy-covariance data from three NOAA flux sites, the wind-velocity corrections increased the magnitude of CO₂ fluxes, sensible heat fluxes, and latent heat fluxes by ≈11%, with the actual magnitude of flux corrections dependent upon sonic anemometer, surface type, and scalar. A sonic anemometer that uses vertically aligned transducers to measure the vertical wind speed was also tested at four angles-of-attack, and corrections to the vertical wind speed measured using this anemometer were within ±1% of zero. Sensible heat fluxes over a forest canopy measured using this anemometer were 15% greater than sensible heat fluxes measured using a sonic anemometer with a non-orthogonal transducer orientation. These results indicate that sensors with a non-orthogonal transducer orientation, which includes the majority of the research-grade three-dimensional sonic anemometers currently in use, should be redesigned to minimize sine errors by measuring the vertical wind speed using one pair of vertically aligned transducers.     

A Comment on “How Well Can We Measure the Vertical Wind Speed? Implications for Fluxes of Energy and Mass” by Kochendorfer et al.

Kochendorfer et al. (Boundary-Layer Meterol, 145:383–398, 2012) conducted an experiment to evaluate azimuth and angle-of-attack dependent errors of sonic anemometer measurements. Several questions are raised regarding the experimental design and the presented results. The finding that instruments with non-orthogonal sonic paths underestimate fluctuations of vertical wind speed and consequently also scalar fluxes by about 10 % is compared with the results of a hitherto unpublished side-by-side field comparison and other past intercomparison experiments. Scale considerations are presented that raise considerable doubts on the validity of the implicit assumption of Kochendorfer et al. (2012) that the turbulent wind vector is highly correlated across a distance of 1.2 m at a height of 2.5 m over flat grassland, which corresponds to the separation between the sonic anemometers tested in their experiment. Nevertheless, new developments in sonic anemometer design to minimize transducer-shadow effects are desirable.     

Comment on “Dynamical Implications of Block Averaging” by G. Treviño and E.L Andreas

A 2006 article in Boundary-Layer Meteorology by G. Treviño and E.L Andreas presents a derivation that questions the use of time averaging for computing turbulence statistics. Their derivation shows that time averaging over a finite interval always leads to a zero integral time scale. As a result, Treviño and Andreas argue that any turbulence quantities derived from time averaging are tainted and incompatible with the Navier–Stokes equations. While Treviño and Andreas are correct that time averaging does produce integral scales that are quite different from what researchers commonly expect, this comment demonstrates that the theoretical implications are not as dire as they claim.     

Reply to comments on and addenda to “some properties and comparative performance of the semi‐lagrangian method of Robert in the solution of the advection‐diffusion equation”

Abstract

Droughts are major natural disasters for many parts of the world. Dry areas, where the precipitation pattern is markedly seasonal, or is otherwise highly variable, are the most susceptible. The Canadian Prairies, together with the U.S. Great Plains, are one such area. While immediate loss of life is seldom a feature of most droughts, malnutrition and even starvation do follow severe droughts in some parts of the world. In Canada, economic losses, particularly in the agricultural sector, may reach several hundred millions of dollars in a drought year, with major socio‐economic repercussions affecting the entire region. Environmental damages include soil degradation and erosion, vegetation damage, slough and lake deterioration and wildlife loss. Unlike most other natural disasters, drought onset is difficult to identify. Droughts develop slowly, and until human activity begins to be affected by an on‐going reduction of precipitation, their existence is unrecognized. Development and application of specific soil moisture and drought indices based on cumulative precipitation deficits have enhanced drought monitoring programs. These in turn provide guidance on the need for mitigative measures that can be initiated early in the course of a drought. Any improvement in the timely application of these measures is, however, strongly dependent on being able to determine the drought's course, extent and likely severity at the earliest stage possible. The identification of precursor conditions for past drought has raised the possibility that the likelihood of a drought occurring in a particular year or growing season might be predictable. Teleconnections between North American precipitation patterns and ENSO events and other surface boundary conditions in the North Pacific have been detected. Forecasting seasonal temperature and perhaps precipitation anomalies appears to be potentially feasible using a suitable merging of precursor parameters and modelling methodologies. Clearly, future research must focus both on those precursors that have been identified and on a search for possible new ones. Development of better forecasting methodology is also essential. Research activity to identify and evaluate new mitigative measures should also be increased to keep pace with the prospects of drought predictability.     

Comment on “application of the Canadian regional climate model to the Laurentian Great Lakes region: Implementation of a lake model”

Abstract

A recently published slab model formulation of lake thermodynamics (Goyette et al., 2000), including an empirical factor to adjust the incoming heat flux so that the modelled lake surface temperature agrees with observed climatology, leads to a distinct lack of energy conservation. The empirical adjustment conceptually represents an exchange of heat between the mixed‐layer water (the slab that is explicitly simulated in the model) and deeper layers of water. It ensures a realistic temporal progression of temperature in the mixed layer, but the thermodynamic balance of the deeper water is not considered. When the deeper water is considered, it is found that the empirical adjustment accounts for the entire heat input to the deeper water, and on an annual mean basis, it is considerably unbalanced. This reveals a flaw in this model concept and, although not entirely invalidating the model, it needs to be included as a caveat in its use.     

Preface to the Special Issue on the “Forecast and Evaluation of Meteorological Disasters”(FEMD)

<正>Meteorological disasters usually exert huge impacts on the development of both human society and the economy.According to statistics from the United Nations International Strategy for Disaster Reduction,the annual mean economic loss caused by meteorological disasters accounts for 3%–6% of the total amount of global GDP.China is a country that has been     

Can the uncertainties of Madden-Jullian Oscillation cause a significant “Spring Predictability Barrier” for ENSO events?

With the Zebiak-Cane model and a parameterized stochastic representation of intraseasonal forcing, the impact of the uncertainties of Madden-Jullian Oscillation (MJO) on the ??Spring Predictability Barrier (SPB)?? for El Ni?o-Southern Oscillation (ENSO) prediction is studied. The parameterized form of MJO forcing is added physically to the Zebiak-Cane model to obtain the so-called Zebiak-Cane-MJO model and then the effects of initial error, stochastic model error, and their joint error mode on the SPB associated with El Ni?o prediction are estimated. The results show that the model errors caused by stochastic MJO forcing could hardly lead to a significant SPB while initial errors can do; furthermore, the joint error mode of initial error and model error associated with the stochastic MJO forcing can also lead to a significant SPB. These demonstrate that the initial error is probably the main error source of the SPB, which may provide a theoretical foundation of data assimilation for ENSO forecasts.     

Comment on: “Corrections to the Mathematical Formulation of a Backwards Lagrangian Particle Dispersion Model” by Gibson and Sailor (2012: Boundary-Layer Meteorology 145, 399–406)

We discuss the results of Gibson and Sailor (Boundary-Layer Meteorol 145:399–406, 2012) who suggest several corrections to the mathematical formulation of the Lagrangian particle dispersion model of Rotach et al. (Q J R Meteorol Soc 122:367–389, 1996). While most of the suggested corrections had already been implemented in the 1990s, one suggested correction raises a valid point, but results in a violation of the well-mixed criterion. Here we improve their idea and test the impact on model results using a well-mixed test and a comparison with wind-tunnel experimental data. The new approach results in similar dispersion patterns as the original approach, while the approach suggested by Gibson and Sailor leads to erroneously reduced concentrations near the ground in convective and especially forced convective conditions.     

Preface to the Special Issue on the “Observation,Prediction and Analysis of severe Convection of China”(OPACC) National “973” Project

正China is a country that is frequently affected by severe convective weather.Here,severe convective weather mainly refers to intense local heavy precipitation,thunderstorm-induced gale-force winds including those from tornadoes and downbursts,and hail and lightning.These types of severe weather are usually small in spatial scale and rapid in their development,and are therefore difficult to capture by observational networks and are poorly resolved in typical operational numerical weather prediction(NWP)models.Furthermore,many of the important dynamic and physical processes involved are not     

Response to comments by Yuan Wang on “Trends of extreme precipitation in Eastern China and their possible causes”

In his comments, Wang cites a number of works to dispute the conclusion in our previous work, which attributes the observed decreases/increases in light/heavy precipitation in eastern China primarily to global warming rather than the regional aerosol effect. However, most of the cited works (admittedly, including our previous work), employ correlation analysis, which has little bearing on the cause-effect relationship. Theoretical analyses and/or modeling studies are needed to ascertain the cause-effect relationship. We argue that theoretical analyses and modeling results show that global warming is the primary cause of the widely observed phenomena of suppression of light precipitation and enhancement of heavy precipitation across the globe, including in eastern China.     

Can the Uncertainties of Madden–Jullian Oscillation Cause a Significant “Spring Predictability Barrier” for ENSO Events?

With the Zebiak-Cane model and a parameterized stochastic representation of intraseasonal forcing,the impact of the uncertainties of Madden–Jullian Oscillation (MJO) on the “Spring Predictability Barrier(SPB)” for El Ni?no–Southern Oscillation (ENSO) prediction is studied. The parameterized form of MJOforcing is added physically to the Zebiak-Cane model to obtain the so-called Zebiak-Cane-MJO model andthen the effects of initial error, stochastic model error, and their joint error mode on the SPB associatedwith El Ni?no prediction are estimated. The results show that the model errors caused by stochastic MJOforcing could hardly lead to a significant SPB while initial errors can do; furthermore, the joint error mode ofinitial error and model error associated with the stochastic MJO forcing can also lead to a significant SPB.These demonstrate that the initial error is probably the main error source of the SPB, which may providea theoretical foundation of data assimilation for ENSO forecasts.     

Preface to the Special Issue on the Program of “Carbon Budget and Relevant Issues”—A Strategic Scientific Pioneering Program of the Chinese Academy of Sciences

<正>Global warming has been one of the biggest issues faced by the world in recent decades.It is closely related to anthropogenic emissions of greenhouse gases(GHGs)—mainly CO_2,CH_4 and N_2O—and the effects of reducing emissions and increasing the carbon fixation capability.China,as a large country with rapid economic and social development,has a major