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The rapid change of wind speed and direction on 21 August 2017 is studied using Doppler lidar measurements at five sites of the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) facility in north-central Oklahoma. The Doppler lidar data were investigated along with meteorological variables such as temperature, humidity, and turbulence available from the large suite of instrumentation deployed at the SGP Central Facility (C1) during the Land-Atmosphere Feedback Experiment in August 2017. Lidar measurements at five sites, separated by 55–70 km, allowed us to document the development and evolution of the wind flow over the SGP area, examine synoptic conditions to understand the mechanism that leads to the ramp event, and estimate the ability of the High-Resolution Rapid Refresh model to reproduce this event. The flow feature in question is an atmospheric bore, a small-scale phenomenon that is challenging to represent in models, that was generated by a thunderstorm outflow northwest of the ARM SGP area. The small-scale nature of bores, its impact on power generation, and the modeling challenges associated with representing bores are discussed in this paper. The results also provide information about model errors between sites of different surface and vegetation types. [ABSTRACT FROM AUTHOR]

Low-level jets (LLJs) are an important nocturnal source of wind energy in the U.S. Great Plains. An August 2017 lidar-based field-measurement campaign [the Land--Atmosphere Feedback Experiment (LAFE)] studied LLJs over the central SGP site in Oklahoma and found nearly equal occurrences of the usual southerly jets and postfrontal northeasterly jets--typically rare during this season--for an opportunity to compare the two types of LLJs during this month. Southerly winds were stronger than the northeasterlies by more than 4 m ss-1 on average, reflecting a significantly higher frequency of winds stronger than 12 m s-1. The analysis of this dataset has been expanded to other SGP Dopplerlidar sites to quantify the variability of winds and LLJ properties between sites of different land use. Geographic variations of winds over the study area were noted: on southerly wind nights, the winds blew stronger at the highest, westernmost sites by 2 m s-1, whereas on the northeasterly flow nights, the easternmost sites had the strongest wind speeds. Lidar measurements at 5 sites during August 2017, contrasted to the 2016-21 summertime data, revealed unusual wind and LLJ conditions. Temporal hodographs using hourly averaged winds at multiple heights revealed unorganized behavior in the turbulent stable boundary layer (SBL) below the jet nose. Above the nose, some nights showed veering qualitatively similar to inertial oscillation (IO) behavior, but at amplitudes much smaller than expected for an IO, whereas other nights showed little veering. Vertical hodographs had a linear shape in the SBL, indicating little directional shear there, and veering above, resulting in a hook-shaped hodograph with height. [ABSTRACT FROM AUTHOR]

We present the new Atmospheric Raman Temperature and Humidity Sounder (ARTHUS). We demonstrate that ARTHUS measurements resolve (1) the strength of the inversion layer at the planetary boundary layer top, (2) elevated lids in the free troposphere during daytime and nighttime, and (3) turbulent fluctuations in water vapor and temperature, simultaneously, also during daytime. Very stable and reliable performance was demonstrably achieved during more than 2,500 hr of operations time experiencing a huge variety of weather conditions. ARTHUS provides temperature profiles with resolutions of 10–60 s and 7.5–100 m vertically in the lower free troposphere. During daytime, the statistical uncertainty of the water vapor mixing ratio is <2 % in the lower troposphere for resolutions of 5 min and 100 m. Temperature statistical uncertainty is <0.5 K even up to the middle troposphere. ARTHUS fulfills the stringent WMO breakthrough requirements on nowcasting and very short range forecasting. Plain Language Summary: The observation of atmospheric moisture and temperature profiles is essential for the understanding and prediction of earth system processes. These are fundamental components of the global and regional energy and water cycles; they determine the radiative transfer through the atmosphere and are critical for the cloud formation and precipitation. Also, it is expected that the assimilation of high‐quality, lower tropospheric WV and T profiles will result in a considerable improvement of the skill of weather forecast models particularly with respect to extreme events. Here we present the Atmospheric Raman Temperature and Humidity Sounder, an exceptional tool for observations in the atmospheric boundary layer during daytime and nighttime with a very short latency. This performance serves very well the next generation of very fast rapid‐update‐cycle data assimilation systems for nowcasting and short‐range weather forecasting. Ground‐based stations and networks can be set up or extended for climate monitoring, verification of weather, climate and earth system models, and data assimilation for improving weather forecasts. Key Points: Fulfills World Meteorological Organization breakthrough requirements for nowcasting/very short range forecasting in the lower troposphereResolves strength of the inversion layer at the planetary boundary layer top and elevated lids above during daytime and nighttimeProvides statistics on turbulent fluctuations in water vapor and temperature simultaneously in the lower troposphere [ABSTRACT FROM AUTHOR]

In previous work, the similarity relationship for the water vapor variance in the interfacial layer (IL) at the top of the convective boundary layer (CBL) was proposed to be proportional to the convective velocity scale and the gradients of the water vapor mixing ratio and the Brunt‐Vaisala frequency in the entrainment zone. In the presence of wind shear in the IL, the similarity relationship was hypothesized to also include a dependence on the gradient Richardson number. Simultaneous measurements of the surface buoyancy flux, wind‐shear profiles from a radar wind profiler, water vapor mixing ratio and temperature measurements and their gradients from a Raman lidar provide a unique opportunity to thoroughly examine the function used in defining the variance and validate it. These observations were made over the Atmospheric Radiation Measurement Southern Great Plains site. We identified 19 cases from 2016 during which the CBL was quasi‐stationary and well mixed for at least 2 hr in the afternoon. Furthermore, we simulated the CBL using a large‐eddy simulation (LES) model for these cases and derived the water vapor variance and other profiles to test the similarity function. Utilizing this unique combination of observations and LES, we demonstrate that the water vapor variance in the IL has little‐to‐no dependence on wind shear. Furthermore, we demonstrate that the predicted variance using the original similarity function matches the observed and LES‐modeled variance very well, with linear correlations between the two variances of 0.82 and 0.95, respectively. Plain Language Summary: Numerical weather prediction and global circulation models need to be able to predict the variance in water vapor in the atmosphere, as this is an important signature of turbulent mixing. However, the variance is something that is not directly resolved by the model and must be approximated using variables that the models actually resolve such as gradients in water vapor, temperature, and wind. This study evaluates a commonly used approximation approach, illustrates its shortcomings, and suggests how the approximation can be improved. Key Points: A similarity relationship is used to predict water vapor variance in the interfacial layer from other variablesWind shear is shown to be unimportant for the prediction of water vapor variance in the interfacial layerThere is very high correlation between the true and predicted variance in both the observations and LES data [ABSTRACT FROM AUTHOR]

Absolute cross sections for collision-induced intramolecular energy transfer from the metastable A 3Σu+ state into the radiating B 3Πg state of N2 have been measured for the first time under single-collision conditions, using a thermal energy molecular beam of N2(A). The collision partners studied were the five rare gases, H2, N2, NO, and O2. The product vibrational levels (B, v’=4–10) were separated using spectrally resolved detection by means of filters as in our earlier related work [R. Bachmann, X. Li, Ch. Ottinger, and A. F. Vilesov, J. Chem. Phys. 96, 5151 (1992)]. In addition, in the present study the contributing reactant state vibrational levels (A,v‘) were labeled, using optical pumping by a specially developed broad-band (∼1 nm) pulsed tunable dye laser. A depletion of up to 30% of a given v‘ level could be achieved, about one-half of the theoretical maximum, at a pump pulse energy of 4 mJ. This quantity was also measured directly using a second synchronized probe laser. Pumping on a particular A,v‘ level reduces the emission from the collisionally coupled B,v’ level by an amount which is a measure of the state-to-state cross section. Quasiresonant energy transfer was found to be strongly preferred, the cross section decreasing exponentially with an increasing energy gap. Absolute cross sections were obtained from a simultaneous measurement of the intensity of the fluorescence induced by the laser pumping of the selected A,v‘ level, with corrections for predissociation of the excited upper state. Cross sections on the order of 0.1 Å2 for He to 15 Å2 for Xe were found for closely resonant (ΔE≊100 cm-1) processes. These results as well as our earlier, absolute measurements of the analogous intramolecular N2(W→B) transfer, are discussed in terms of interaction potential models. [ABSTRACT FROM AUTHOR]

Abstract: On 21 August 2017, a solar eclipse occurred over the continental United States resulting in a rapid reduction and subsequent increase of solar radiation over a large region of the country. The eclipse's effect on the land‐atmosphere system is documented in unprecedented detail using a unique array of sensors deployed at three sites in north‐central Oklahoma. The observations showed that turbulent fluxes of heat and momentum at the surface responded quickly to the change in solar radiation. The decrease in the sensible heat flux resulted in a decrease in the air temperature below 200 m, and a large decrease in turbulent motions throughout the boundary layer. Furthermore, the turbulent mixing in the boundary layer lagged behind the change in the surface fluxes, and this lag depended on the height above the surface. The turbulent motions increased and the convective boundary layer was reestablished as the sensible heat flux recovered. [ABSTRACT FROM AUTHOR]

The rotational Raman lidar (RRL) of the University of Hohenheim (UHOH) measures atmospheric temperature profiles with high resolution (10 s, 109 m). The data contain low-noise errors even in daytime due to the use of strong UV laser light (355 nm, 10 W, 50 Hz) and a very efficient interference-filter-based polychromator. In this paper, the first profiling of the second- to fourth-order moments of turbulent temperature fluctuations is presented. Furthermore, skewness profiles and kurtosis profiles in the convective planetary boundary layer (CBL) including the interfacial layer (IL) are discussed. The results demonstrate that the UHOH RRL resolves the vertical structure of these moments. The data set which is used for this case study was collected in western Germany (50°53'50.56'' N, 6°27'50.39'' E; 110ma.s.l.) on 24 April 2013 during the Intensive Observations Period (IOP) 6 of the HD(CP)² (High-Definition Clouds and Precipitation for advancing Climate Prediction) Observational Prototype Experiment (HOPE). We used the data between 11:00 and 12:00 UTC corresponding to 1 h around local noon (the highest position of the Sun was at 11:33 UTC). First, we investigated profiles of the total noise error of the temperature measurements and compared them with estimates of the temperature measurement uncertainty due to shot noise derived with Poisson statistics. The comparison confirms that the major contribution to the total statistical uncertainty of the temperature measurements originates from shot noise. The total statistical uncertainty of a 20 min temperature measurement is lower than 0.1K up to 1050ma.g.l. (above ground level) at noontime; even for single 10 s temperature profiles, it is smaller than 1K up to 1020ma.g.l. Autocovariance and spectral analyses of the atmospheric temperature fluctuations confirm that a temporal resolution of 10 s was sufficient to resolve the turbulence down to the inertial subrange. This is also indicated by the integral scale of the temperature fluctuations which had a mean value of about 80 s in the CBL with a tendency to decrease to smaller values towards the CBL top. Analyses of profiles of the second-, third-, and fourth-order moments show that all moments had peak values in the IL around the mean top of the CBL which was located at 1230ma.g.l. The maximum of the variance profile in the IL was 0.39K² with 0.07 and 0.11K2 for the sampling error and noise error, respectively. The third-order moment (TOM) was not significantly different from zero in the CBL but showed a negative peak in the IL with a minimum of -0.93K³ and values of 0.05 and 0.16K³ for the sampling and noise errors, respectively. The fourth-order moment (FOM) and kurtosis values throughout the CBL were not significantly different to those of a Gaussian distribution. Both showed also maxima in the IL but these were not statistically significant taking the measurement uncertainties into account. We conclude that these measurements permit the validation of large eddy simulation results and the direct investigation of turbulence parameterizations with respect to temperature. [ABSTRACT FROM AUTHOR]

The temperature measurements of the rotational Raman lidar of the University of Hohenheim (UHOH RRL) during the High Definition of Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observation Prototype Experiment (HOPE) in April and May 2013 are discussed. The lidar consists of a frequency-tripled Nd:YAG laser at 355 nm with 10 W average power at 50 Hz, a two-mirror scanner, a 40 cm receiving telescope, and a highly efficient polychromator with cascading interference filters for separating four signals: the elastic backscatter signal, two rotational Raman signals with different temperature dependence, and the vibrational Raman signal of water vapor. The main measurement variable of the UHOH RRL is temperature. For the HOPE campaign, the lidar receiver was optimized for high and low background levels, with a novel switch for the passband of the second rotational Raman channel. The instrument delivers atmospheric profiles of water vapor mixing ratio as well as particle backscatter coefficient and particle extinction coefficient as further products. As examples for the measurement performance, measurements of the temperature gradient and water vapor mixing ratio revealing the development of the atmospheric boundary layer within 25 h are presented. As expected from simulations, a reduction of the measurement uncertainty of 70% during nighttime was achieved with the new low-background setting. A two-mirror scanner allows for measurements in different directions. When pointing the scanner to low elevation, measurements close to the ground become possible which are otherwise impossible due to the non-total overlap of laser beam and receiving telescope field of view in the near range. An example of a low-level temperature measurement is presented which resolves the temperature gradient at the top of the stable nighttime boundary layer 100 m above the ground. [ABSTRACT FROM AUTHOR]

The scanning differential absorption lidar (DIAL) of the University of Hohenheim (UHOH) is presented. The UHOH DIAL is equipped with an injection-seeded frequency-stabilized high-power Ti:sapphire laser operated at 818 nm with a repetition rate of 250Hz. A scanning transceiver unit with a 80 cm primary mirror receives the atmospheric backscatter signals. The system is capable of water vapor measurements with temporal resolutions of a few seconds and a range resolution between 30 and 300m at daytime. It allows to investigate surface-vegetation-atmosphere exchange processes with high resolution. In this paper, we present the design of the instrument and illustrate its performance with recent water vapor measurements taken in Stuttgart-Hohenheim and in the frame of the HD(CP)² Observational Prototype Experiment (HOPE). HOPE was located near research center Jülich, in western Germany, in spring 2013 as part of the project "High Definition of Clouds and Precipitation for advancing Climate Prediction" (HD(CP)²). Scanning measurements reveal the 3-dimensional structures of the water vapor field. The influence of uncertainties within the calculation of the absorption cross-section at wavelengths around 818 nm for the WV retrieval is discussed. Radiosonde intercomparisons show a very small bias between the instruments of only (-0.04±0.11) gm-3 or (-1.0±2.3)% in the height range of 0.5 to 3 km. [ABSTRACT FROM AUTHOR]

The rotational Raman lidar of the University of Hohenheim (UHOH) measures atmospheric temperature profiles during daytime with high resolution (10 s, 109m). The data contain low noise errors even in daytime due to the use of strong UV laser light (355 nm, 10W, 50Hz) and a very efficient interference-filter-based polychromator. In this paper, we present the first profiling of the second- to forth-order moments of turbulent temperature fluctuations as well as of skewness and kurtosis in the convective boundary layer (CBL) including the interfacial layer (IL). The results demonstrate that the UHOH RRL resolves the vertical structure of these moments. The data set which is used for this case study was collected in western Germany (50° 53' 50.56" N, 6° 27' 50.39" E, 110ma.s.l.) within one hour around local noon on 24 April 2013 during the Intensive Observations Period (IOP) 6 of the HD(CP)² Observational Prototype Experiment (HOPE), which is embedded in the German project HD(CP)² (High-Definition Clouds and Precipitation for advancing Climate Prediction). First, we investigated profiles of the noise variance and compared it with estimates of the statistical temperature measurement uncertainty ΔT based on Poisson statistics. The agreement confirms that photon count numbers obtained from extrapolated analog signal intensities provide a lower estimate of the statistical errors. The total statistical uncertainty of a 20min temperature measurement is lower than 0.1K up to 1050ma.g.l. at noontime; even for single 10 s temperature profiles, it is smaller than 1K up to 1000ma.g.l.. Then we confirmed by autocovariance and spectral analyses of the atmospheric temperature fluctuations that a temporal resolution of 10 s was sufficient to resolve the turbulence down to the inertial subrange. This is also indicated by the profile of the integral scale of the temperature fluctuations, which was in the range of 40 to 120 s in the CBL. Analyzing then profiles of the second-, third-, and forth-order moments, we found the largest values of all moments in the IL around the mean top of the CBL which was located at 1230ma.g.l.. The maximum of the variance profile in the IL was 0.40 K² with 0.06 and 0.08K² for the sampling error and noise error, respectively. The third-order moment was not significantly different from zero inside the CBL but showed a negative peak in the IL with a minimum of -0.72 K³ and values of 0.06 and 0.14 K³ for the sampling and noise errors, respectively. The forth-order moment and kurtosis values throughout the CBL were quasi-normal. [ABSTRACT FROM AUTHOR]

The temperature measurements of the Rotational Raman Lidar of the University of Hohenheim (UHOH RRL) during the High Definition of Clouds and Precipitation for advancing Climate Prediction (HD(CP)²) Prototype Experiment (HOPE) in April and May 2013 are discussed. The lidar consists of a frequency-tripled Nd:YAG laser at 355 nm with 10W average power at 50Hz, a two-mirror scanner, a 40 cm receiving telescope and a highly efficient polychromator with cascading interference filters for separating four signals: the elastic backscatter signal, two rotational Raman signals with different temperature dependence, and the vibrational Raman signal of water vapor. The main measurement variable of the UHOH RRL is temperature. For the HOPE campaign, the lidar receiver was optimized for high and low background levels, respectively, with a novel switch for the passband of the second rotational Raman channel. The instrument delivers atmospheric profiles of water vapor mixing ratio as well as particle backscatter coefficient and particle extinction coefficient as further products. As examples for the measurement performance, measurements of the temperature gradient and water vapor mixing ratio revealing the development of the atmospheric boundary layer within 25 h are presented. As expected from simulations, a significant advance during nighttime was achieved with the new low-background setting. A two-mirror scanner allows for measurements in different directions. When pointing the scanner to low elevation, measurements close to the ground become possible which are otherwise impossible due to the non-total overlap of laser beam and receiving telescope field-of-view in the near range. We present an example of a low-level temperature measurement which resolves the temperature gradient at the top of the stable nighttime boundary layer a hundred meters above the ground. [ABSTRACT FROM AUTHOR]

According to Dooge (1986) intermediate-scale catchments are systems of organized complexity, being too organized and yet too small to be characterized on a statistical/ conceptual basis, but too large and too heterogeneous to be characterized in a deterministic manner. A key requirement for building structurally adequate models precisely for this intermediate scale is a better understanding of how different forms of spatial organization affect storage and release of water and energy. Here, we propose that a combination of the concept of hydrological response units (HRUs) and thermodynamics offers several helpful and partly novel perspectives for gaining this improved understanding. Our key idea is to define functional similarity based on similarity of the terrestrial controls of gradients and resistance terms controlling the land surface energy balance, rainfall runoff transformation, and groundwater storage and release. This might imply that functional similarity with respect to these specific forms of water release emerges at different scales, namely the small field scale, the hillslope, and the catchment scale. We thus propose three different types of "functional units" -- specialized HRUs, so to speak -- which behave similarly with respect to one specific form of water release and with a characteristic extent equal to one of those three scale levels. We furthermore discuss an experimental strategy based on exemplary learning and replicate experiments to identify and delineate these functional units, and as a promising strategy for characterizing the interplay and organization of water and energy fluxes across scales. We believe the thermodynamic perspective to be well suited to unmask equifinality as inherent in the equations governing water, momentum, and energy fluxes: this is because several combinations of gradients and resistance terms yield the same mass or energy flux and the terrestrial controls of gradients and resistance terms are largely independent. We propose that structurally adequate models at this scale should consequently disentangle driving gradients and resistance terms, because this optionally allows equifinality to be partly reduced by including available observations, e.g., on driving gradients. Most importantly, the thermodynamic perspective yields an energy-centered perspective on rainfall-runoff transformation and evapotranspiration, including fundamental limits for energy fluxes associated with these processes. This might additionally reduce equifinality and opens up opportunities for testing thermodynamic optimality principles within independent predictions of rainfall-runoff or land surface energy exchange. This is pivotal to finding out whether or not spatial organization in catchments is in accordance with a fundamental organizing principle. [ABSTRACT FROM AUTHOR]

EURO-CORDEX is an international climate downscaling initiative that aims to provide high-resolution climate scenarios for Europe. Here an evaluation of the ERA-Interim- driven EURO-CORDEX regional climate model (RCM) ensemble is presented. The study documents the performance of the individual models in representing the basic spatiotemporal patterns of the European climate for the period 1989–2008. Model evaluation focuses on near-surface air temperature and precipitation, and uses the E-OBS data set as observational reference. The ensemble consists of 17 simulations carried out by seven different models at grid resolutions of 12 km (nine experiments) and 50 km (eight experiments). Several performance metrics computed from monthly and seasonal mean values are used to assess model performance over eight subdomains of the European continent. Results are compared to those for the ERA40-driven ENSEMBLES simulations. The analysis confirms the ability of RCMs to capture the basic features of the European climate, including its variability in space and time. But it also identifies nonnegligible deficiencies of the simulations for selected metrics, regions and seasons. Seasonally and regionally averaged temperature biases are mostly smaller than 1.5 _C, while precipitation biases are typically located in the ±40% range. Some bias characteristics, such as a predominant cold and wet bias in most seasons and over most parts of Europe and a warm and dry summer bias over southern and southeastern Europe reflect common model biases. For seasonal mean quantities averaged over large European subdomains, no clear benefit of an increased spatial resolution (12 vs. 50 km) can be identified. The bias ranges of the EURO-CORDEX ensemble mostly correspond to those of the ENSEMBLES simulations, but some improvements in model performance can be identified (e.g., a less pronounced southern European warm summer bias). The temperature bias spread across different configurations of one individual model can be of a similar magnitude as the spread across different models, demonstrating a strong influence of the specific choices in physical parameterizations and experimental setup on model performance. Based on a number of simply reproducible metrics, the present study quantifies the currently achievable accuracy of RCMs used for regional climate simulations over Europe and provides a quality standard for future model developments. [ABSTRACT FROM AUTHOR]

High temporal and vertical resolution water vapor measurements by Raman and differential absorption lidar systems have been used to characterize the turbulent fluctuations in the water vapor mixing ratio field in convective mixed layers. Since daytime Raman lidar measurements are inherently noisy (due to solar background and weak signal strengths), the analysis approach needs to quantify and remove the contribution of the instrument noise in order to derive the desired atmospheric water vapor mixing ratio variance and skewness profiles. This is done using the approach outlined by Lenschow et al.; however, an intercomparison with in situ observations was not performed. Water vapor measurements were made by a diode laser hygrometer flown on a Twin Otter aircraft during the Routine Atmospheric Radiation Measurement (ARM) Program Aerial Facility Clouds with Low Optical Water Depths Optical Radiative Observations (RACORO) field campaign over the ARM Southern Great Plains (SGP) site in 2009. Two days with Twin Otter flights were identified where the convective mixed layer was quasi stationary, and hence the 10-s, 75-m data from the SGP Raman lidar could be analyzed to provide profiles of water vapor mixing ratio variance and skewness. Airborne water vapor observations measured during level flight legs were compared to the Raman lidar data, demonstrating good agreement in both variance and skewness. The results also illustrate the challenges of comparing a point sensor making measurements over time to a moving platform making similar measurements horizontally. [ABSTRACT FROM AUTHOR]

A large irrigated biomass plantation was simulated in an arid region of Israel within the WRF-NOAH coupled atmospheric/land surface model in order to assess land surface atmosphere feedbacks. Simulations were carried out for the 2012 summer season (JJA). The irrigated plantations were simulated by prescribing tailored land surface and soil/plant parameters, and by implementing a newly devised, controllable subsurface irrigation scheme within NOAH. Two model cases studies were considered and compared -- Impact and Control. Impact simulates a hypothetical 10 km x10 km irrigated plantation. Control represents a baseline and uses the existing land surface data, where the predominant land surface type in the area is bare desert soil. Central to the study is model validation against observations collected for the study over the same period. Surface meteorological and soil observations were made at a desert site and from a 400 ha Simmondsia chinensis (Jojoba) plantation. Control was validated with data from the desert, and Impact from the Jojoba. Finally, estimations were made of the energy balance, applying two Penman--Monteith based methods along with observed meteorological data. These estimations were compared with simulated energy fluxes. Control simulates the daytime desert surface 2m air temperatures (T2) with less than 0.2 °C deviation and the vapour pressure deficit (VPD) to within 0.25 hPa. Desert wind speed (U) is simulated to within 0.5ms and the net surface radiation (Rn) to 25Wm-2. Soil heat flux (G) is not so accurately simulated by Control (up to 30Wm-2 deviation) and 5 cm soil temperatures (ST5) are simulated to within 1.5 °C. Impact simulates daytime T2 over irrigated vegetation to within 1-1.5 °C, the VPD to 0.5 hPa, Rn to 50Wm-2. and ST5 to within 2 °C. Simulated Impact G deviates up to 40Wm-2, highlighting a need for re-parameterisation or better soil classification, but the overall contribution to the energy balance is small (5-6%). During the night, significant T2 and ST5 cold biases of 2-4 C are present. Diurnal latent heat values from WRF Impact correspond closely with Penman--Monteith estimation curves, and latent heat magnitudes of 160Wm over the plantation are usual. Simulated plantation sensible heat fluxes are high (450Wm -2) -- around 100-110Wm-2 higher than over the surrounding desert. The high relative HFX over the vegetation, driven by high Rn and high surface resistances, indicate that low Bowen ratios should not necessarily be assumed when irrigated plantations are implemented in, and optimized for arid regions. Furthermore, the high plantation T2 magnitudes highlight the importance of considering diurnal dynamics, which drive the evolution of boundary layers, rather than only on daily mean statistics which often indicate an irrigation cooling effect. [ABSTRACT FROM AUTHOR]

We present a comprehensive, interdisciplinary project which demonstrates that large-scale plantations of Jatropha curcas - if established in hot, dry coastal areas around the world - could capture 17-25 t of carbon dioxide per hectare per year from the atmosphere (over a 20 yr period). Based on recent farming results it is confirmed that the Jatropha curcas plant is well adapted to harsh environments and is capable of growing alone or in combination with other tree and shrub species with minimal irrigation in hot deserts where rain occurs only sporadically. Our investigations indicate that there is sufficient unused and marginal land for the widespread cultivation of Jatropha curcas to have a significant impact on atmospheric CO2 levels at least for several decades. In a system in which desalinated seawater is used for irrigation and for delivery of mineral nutrients, the sequestration costs were estimated to range from 42-63EUR per tonne CO2. This result makes carbon farming a technology that is competitive with carbon capture and storage (CCS). In addition, high-resolution simulations using an advanced land-surface-atmosphere model indicate that a 10 000 km2 plantation could produce a reduction in mean surface temperature and an onset or increase in rain and dew fall at a regional level. In such areas, plant growth and CO2 storage could continue until permanent woodland or forest had been established. In other areas, salinization of the soil may limit plant growth to 2-3 decades whereupon irrigation could be ceased and the captured carbon stored as woody biomass. [ABSTRACT FROM AUTHOR]

Despite considerable progress in recent years, output of both global and regional circulation models is still afflicted with biases to a degree that precludes its direct use, especially in climate change impact studies. This is well known, and to overcome this problem, bias correction (BC; i.e. the correction of model output towards observations in a post-processing step) has now become a standard procedure in climate change impact studies. In this paper we argue that BC is currently often used in an invalid way: it is added to the GCM/RCM model chain without sufficient proof that the consistency of the latter (i.e. the agreement between model dynamics/model output and our judgement) as well as the generality of its applicability increases. BC methods often impair the advantages of circulation models by altering spatiotemporal field consistency, relations among variables and by violating conservation principles. Currently used BC methods largely neglect feedback mechanisms, and it is unclear whether they are time-invariant under climate change conditions. Applying BC increases agreement of climate model output with observations in hindcasts and hence narrows the uncertainty range of simulations and predictions without, however, providing a satisfactory physical justification. This is in most cases not transparent to the end user. We argue that this hides rather than reduces uncertainty, which may lead to avoidable forejudging of end users and decision makers. We present here a brief overview of state-of-the-art bias correction methods, discuss the related assumptions and implications, draw conclusions on the validity of bias correction and propose ways to cope with biased output of circulation models in the short term and how to reduce the bias in the long term. The most promising strategy for improved future global and regional circulation model simulations is the increase in model resolution to the convection-permitting scale in combination with ensemble predictions based on sophisticated approaches for ensemble perturbation. With this article, we advocate communicating the entire uncertainty range associated with climate change predictions openly and hope to stimulate a lively discussion on bias correction among the atmospheric and hydrological community and end users of climate change impact studies. [ABSTRACT FROM AUTHOR]

The article discusses study on the carbon farming in dry, hot coastal areas as an option for the mitigation of climate change. The study uses Jatropha curcas plant, due to its role in reduction of atmospheric carbon dioxide level and its ability to grow alone to a harsh environments or hot desserts. It mentions that desalinated water that is used for mineral nutrients delivery and irrigation makes carbon farming a carbon capture and storage (CCS) technology.

Despite considerable progress in recent years, output of both Global and Regional Circulation Models is still afflicted with biases to a degree that precludes its direct use, especially in climate change impact studies. This is well known, and to overcome this problem bias correction (BC), i.e. the correction of model output towards observations in a post processing step for its subsequent application in climate change impact studies has now become a standard procedure. In this paper we argue that bias correction, which has a considerable influence on the results of impact studies, is not a valid procedure in the way it is currently used: it impairs the advantages of Circulation Models which are based on established physical laws by altering spatiotemporal field consistency, relations among variables and by violating conservation principles. Bias correction largely neglects feedback mechanisms and it is unclear whether bias correction methods are time-invariant under climate change conditions. Applying bias correction increases agreement of Climate Model output with observations in hind casts and hence narrows the uncertainty range of simulations and predictions without, however, providing a satisfactory physical justification. This is in most cases not transparent to the end user. We argue that this masks rather than reduces uncertainty, which may lead to avoidable forejudging of end users and decision makers. We present here a brief overview of state-of-the-art bias correction methods, discuss the related assumptions and implications, draw conclusions on the validity of bias correction and propose ways to cope with biased output of Circulation Models in the short term and how to reduce the bias in the long term. The most promising strategy for improved future Global and Regional Circulation Model simulations is the increase in model resolution to the convection-permitting scale in combination with ensemble predictions based on sophisticated approaches for ensemble perturbation. With this article, we advocate communicating the entire uncertainty range associated with climate change predictions openly and hope to stimulate a lively discussion on bias correction among the atmospheric and hydrological community and end users of climate change impact studies. [ABSTRACT FROM AUTHOR]

We applied a ground-based vertically-pointing aerosol lidar to investigate the evolution of the instantaneous atmospheric boundary layer depth, its growth rate, associated entrainment processes, and turbulence characteristics. We used lidar measurements with range resolution of 3m and time resolution of up to 0.033 s obtained in the course of a sunny day (26 June 2004) over an urban valley (central Stuttgart, 48° 470 N, 9°120 E, 240m above sea level). The lidar system uses a wavelength of 1064 nm and has a poweraperture product of 2.1Wm2. Three techniques are examined for determining the instantaneous convective boundary layer (CBL) depth from the high-resolution lidar measurements: the logarithm gradient method, the inflection point method, and the Haar wavelet transform method. The Haar wavelet-based approach is found to be the most robust technique for the automated detection of the CBL depth. Two different regimes of the CBL are discussed in detail: a quasi-stationary CBL in the afternoon and a CBL with rapid growth during morning transition in the presence of dust layers atop. Two different growth rates were found: 3-5 m/min for the growing CBL in the morning and 0.5-2 m/min during the quasisteady regime. The mean entrainment zone thickness for the quasi-steady CBL was found to be ∼75m while the CBL top during the entire day varied between 0.7 km and 2.3 km. A fast Fourier-transform-based spectral analysis of the instantaneous CBL depth time series gave a spectral exponent value of 1.50±0.04, confirming non-stationary CBL behavior in the morning while for the other regime a value of 1.00±0.06 was obtained indicating a quasi-stationary state of the CBL. Assuming that the spatio-temporal variation of the particle backscatter cross-section of the aerosols in the scattering volume is due to number density fluctuations (negligible hygroscopic growth), the particle backscatter coefficient profiles can be used to investigate boundary layer turbulence since the aerosols act as tracers. We demonstrate that with our lidar measurements, vertical profiles of variance, skewness, and kurtosis of the fluctuations of the particle backscatter coefficient can be determined. The variance spectra at different altitudes inside the quasi-steady CBL showed an f -5/3 dependency. The integral scale varied from 40 to 90 s (depending on height), which was significantly larger than the temporal resolution of the lidar data. Thus, the major part of the inertial subrange was detected and turbulent fluctuations could be resolved. For the quasi-stationary case, negative values of skewness were found inside the CBL while positive values were observed in the entrainment zone near the top of the CBL. For the case of the rapidly growing CBL, the skewness profile showed both positive and negative values even inside the CBL. [ABSTRACT FROM AUTHOR]

The article presents a study on soil moisture analysis with the use of streamflow data assimilation. It states that an Ensemble Kalman Filter for streamflow time series assimilation into the TERRAML multi-layer land surface model of the COSMO regional weather forecast model is used. It concludes that numerical weather forecasting and climate modeling requires accurate soil moisture initialization for land surface models with improved soil moisture needed to improve water stimulation fluxes.

For high-resolution measurements of temperature fields in the atmospheric boundary layer and the lower free troposphere a scanning eye-safe lidar which deploys the rotational Raman technique at 355 nm was developed. To optimize the filters of the receiver for both high nighttime and daytime performance, detailed simulation studies have been performed. The receiver is fiber-coupled to a sequential setup of multicavity interference filters used under small angles of incidence. Examples of nighttime and daytime measurements with the system which has a total power-aperture efficiency product of 0.006 Wm2 are presented. Noontime temperature measurements with a temporal resolution of 60 s result in 1-sigma statistical temperature uncertainty of <1K up to 1 km height and <2K up to 2 km height. With an integration time of 60min and a gliding average of 750 m a 1-sigma statistical temperature uncertainty of <1K up to 14 km height is achieved during night. [ABSTRACT FROM AUTHOR]

The NASA GSFC Scanning Raman Lidar (SRL) participated in the International H2O Project (IHOP) that occurred in May and June 2002 in the midwestern part of the United States. The SRL system configuration and methods of data analysis were described in Part I of this paper. In this second part, comparisons of SRL water vapor measurements and those of Lidar Atmospheric Sensing Experiment (LASE) airborne water vapor lidar and chilled-mirror radiosonde are performed. Two case studies are then presented: one for daytime and one for nighttime. The daytime case study is of a convectively driven boundary layer event and is used to characterize the daytime SRL water vapor random error characteristics. The nighttime case study is of a thunderstorm-generated cirrus cloud case that is studied in its meteorological context. Upper-tropospheric humidification due to precipitation from the cirrus cloud is quantified as is the cirrus cloud optical depth, extinction-to-backscatter ratio, ice water content, cirrus particle size, and both particle and volume depolarization ratios. A stability and back-trajectory analysis is performed to study the origin of wave activity in one of the cloud layers. These unprecedented cirrus cloud measurements are being used in a cirrus cloud modeling study. [ABSTRACT FROM AUTHOR]

Presents high resolution water vapor and wind measurements in the lower troposphere within the scope of the Baltic Sea Experiment (BALTEX). Measurements performed using differential absorption lidar (DIAL) system and a radar-radio acoustic sounding system (radar-RASS); Major goals of BALTEX; Transport processes essential for the improvement of weather forecast.

Presents differential absorption lidar (DIAL) measurements of humidity variance and skewness profiles. Comparison between the water vapor variance profiles and results from a large eddy simulation (LES) model; Estimation of surface and latent heat fluxes; Use of active remote sensing instruments; Relevance of humidity skewness profiles for transport processes.