scholarly journals Evaluation of the Dropsonde Humidity Sensor Using Data from DYCOMS-II and IHOP_2002

2005 ◽  
Vol 22 (3) ◽  
pp. 247-257 ◽  
Author(s):  
Junhong Wang
Keyword(s):  
Humidity Sensor ◽  
Field Experiments ◽  
Large Time ◽  
Time Lag ◽  
Measured Temperature ◽  
Marine Stratocumulus ◽  
Stratocumulus Clouds ◽  
The Mean ◽  
Using Data ◽  
Dry Bias

Abstract The dropsonde humidity data have not been fully utilized due to lack of knowledge on performance of the dropsonde humidity sensor. This study evaluates the performance of the dropsonde humidity sensor using data collected from two field experiments, the Dynamics and Chemistry of Marine Stratocumulus Phase II: Entrainment Studies (DYCOMS-II) and the International H2O Project (IHOP)_2002. During DYCOMS-II, 63 dropsondes were dropped above marine stratocumulus clouds. It provides a unique opportunity to evaluate the performance of the dropsonde humidity sensor within clouds. Relative humidity (RH) inside clouds did not reach 100% all the time, but the maximum RH reached 100% for 28% of soundings and was within the sensor accuracy range (94%–100%). This suggests that the dropsonde humidity sensor displays no systematic dry bias near saturation. The dropsonde humidity sensor experienced large time-lag errors when it descended from a dry environment above clouds into clouds. The mean estimated time constant of the sensor is 5 s at 15°C, which is much larger than 0.5 s at 20°C given by the manufacturer. The humidity sensor still reported near-saturation RH after it exited clouds because of water on the sensor. The approximately coincident dropsonde and aircraft temperature data during DYCOMS-II show that the dropsonde underestimates temperatures inside and below clouds by averages of 0.21° and 0.93°C, respectively. Seventy-one pairs of dropsonde and radiosonde soundings during IHOP_2002 were launched within a half hour and 50 km and sampled the same air mass based on the visual examination. The comparisons show that the dropsonde and radiosonde RH data agree with each other within ±2% RH, suggesting no systematic dry bias in dropsonde humidity data. However, dropsonde-measured temperature is consistently colder than that by radiosonde by ∼0.4°C.

scholarly journals Relationship between drizzle rate, liquid water path and droplet concentration at the scale of a stratocumulus cloud system

2008 ◽  
Vol 8 (16) ◽  
pp. 4641-4654 ◽  
Author(s):  
O. Geoffroy ◽  
J.-L. Brenguier ◽  
I. Sandu
Keyword(s):  
Liquid Water ◽  
Field Experiments ◽  
Liquid Water Path ◽  
Marine Stratocumulus ◽  
Data Set ◽  
Water Path ◽  
Droplet Concentration ◽  
Stratocumulus Clouds ◽  
Shallow Clouds ◽  
The One

Abstract. The recent ACE-2, EPIC and DYCOMS-II field experiments showed that the drizzle precipitation rate of marine stratocumulus scales with the cloud geometrical thickness or liquid water path, and the droplet concentration, when averaged over a domain typical of a GCM grid. This feature is replicated here with large-eddy-simulations using state-of-the-art bulk parameterizations of precipitation formation in stratocumulus clouds. The set of numerical simulations shows scaling relationships similar to the ones derived from the field experiments, especially the one derived from the DYCOMS-II data set. This result suggests that the empirical relationships were not fortuitous and that they reflect the mean effect of cloud physical processes. Such relationships might be more suited to GCM parameterizations of precipitation from shallow clouds than bulk parameterizations of autoconversion, that were initially developed for cloud resolving models.

Holographic Observations of Centimeter-Scale Nonuniformities within Marine Stratocumulus Clouds

2020 ◽  
Vol 77 (2) ◽  
pp. 499-512
Author(s):  
Susanne Glienke ◽  
Alexander B. Kostinski ◽  
Raymond A. Shaw ◽  
Michael L. Larsen ◽  
Jacob P. Fugal ◽  
...  
Keyword(s):  
High Performance ◽  
Spatial Scales ◽  
Environmental Research ◽  
Droplet Growth ◽  
Marine Stratocumulus ◽  
Size Dependent ◽  
Statistical Confidence ◽  
Spatial Uniformity ◽  
Stratocumulus Clouds ◽  
The Mean

Abstract Data collected with a holographic instrument [Holographic Detector for Clouds (HOLODEC)] on board the High-Performance Instrumented Airborne Platform for Environmental Research Gulfstream-V (HIAPER GV) aircraft from marine stratocumulus clouds during the Cloud System Evolution in the Trades (CSET) field project are examined for spatial uniformity. During one flight leg at 1190 m altitude, 1816 consecutive holograms were taken, which were approximately 40 m apart with individual hologram dimensions of 1.16 cm × 0.68 cm × 12.0 cm and with droplet concentrations of up to 500 cm−3. Unlike earlier studies, minimally intrusive data processing (e.g., bypassing calculation of number concentrations, binning, and parametric fitting) is used to test for spatial uniformity of clouds on intra- and interhologram spatial scales (a few centimeters and 40 m, respectively). As a means to test this, measured droplet count fluctuations are normalized with the expected standard deviation from theoretical Poisson distributions, which signifies randomness. Despite the absence of trends in the mean concentration, it is found that the null hypothesis of spatial uniformity on both spatial scales can be rejected with compelling statistical confidence. Monte Carlo simulations suggest that weak clustering explains this signature. These findings also hold for size-resolved analysis but with less certainty. Clustering of droplets caused by, for example, entrainment and turbulence, is size dependent and is likely to influence key processes such as droplet growth and thus cloud lifetime.

scholarly journals Does precipitation susceptibility vary with increasing cloud thickness in marine stratocumulus?

2011 ◽  
Vol 11 (12) ◽  
pp. 33379-33417 ◽  
Author(s):  
C. R. Terai ◽  
R. Wood ◽  
D. C. Leon ◽  
P. Zuidema
Keyword(s):  
Cloud Droplet ◽  
Aerosol Concentration ◽  
Precipitation Rate ◽  
Cloud Base ◽  
Liquid Water Path ◽  
Marine Stratocumulus ◽  
Near Surface ◽  
The Mean ◽  
Using Data ◽  
Cloud Thickness

Abstract. The relationship between precipitation rate and accumulation mode aerosol concentration in marine stratocumulus-topped boundary layers is investigated by applying the precipitation susceptibility metric to aircraft data obtained during the VOCALS Regional Experiment. The mean precipitation rate R over a segment of the data is expressed as the product of a drizzle fraction f multiplied by a drizzle intensity I (mean rate for drizzling columns). The susceptibility Sx is then defined as the fractional decrease in precipitation variable x = {R, f, I} per fractional increase in the concentration of aerosols with dry diameter >0.1 μm, with cloud thickness h held fixed. The precipitation susceptibility SR is calculated using data from both precipitating and non-precipitating cloudy columns to quantify how aerosol concentrations affect the mean precipitation rate of all clouds of a given h range and not just the mean precipitation of clouds that are precipitating. SR systematically decreases with increasing h, and this is largely because Sf decreases with h while SI is approximately independent of h. In a general sense, Sf can be thought of as the effect of aerosols on the probability of precipitation, while SI can be thought of as the effect of aerosols on the intensity of precipitation. Since thicker clouds are likely to precipitate regardless of ambient aerosol concentration, we expect Sf to decrease with increasing h. The results are broadly insensitive to the choice of horizontal averaging scale. Similar susceptibilities are found for both cloud base and near-surface drizzle rates and when the analysis is repeated with cloud liquid water path held fixed instead of cloud thickness. Simple power law relationships relating precipitation rate to aerosol concentration or cloud droplet concentration do not capture this observed behavior.

scholarly journals Does precipitation susceptibility vary with increasing cloud thickness in marine stratocumulus?

2012 ◽  
Vol 12 (10) ◽  
pp. 4567-4583 ◽  
Author(s):  
C. R. Terai ◽  
R. Wood ◽  
D. C. Leon ◽  
P. Zuidema
Keyword(s):  
Cloud Droplet ◽  
Aerosol Concentration ◽  
Precipitation Rate ◽  
Cloud Base ◽  
Liquid Water Path ◽  
Marine Stratocumulus ◽  
Near Surface ◽  
The Mean ◽  
Using Data ◽  
Cloud Thickness

Abstract. The relationship between precipitation rate and accumulation mode aerosol concentration in marine stratocumulus-topped boundary layers is investigated by applying the precipitation susceptibility metric to aircraft data obtained during the VOCALS Regional Experiment. A new method to calculate the precipitation susceptibility that incorporates non-precipitating clouds is introduced. The mean precipitation rate R over a segment of the data is expressed as the product of a drizzle fraction f and a drizzle intensity I (mean rate for drizzling columns). The susceptibility Sx is then defined as the fractional decrease in precipitation variable x = {R, f, I} per fractional increase in the concentration of aerosols with dry diameter >0.1 μm, with cloud thickness h held fixed. The precipitation susceptibility SR is calculated using data from both precipitating and non-precipitating cloudy columns to quantify how aerosol concentrations affect the mean precipitation rate of all clouds of a given h range and not just the mean precipitation of clouds that are precipitating. SR systematically decreases with increasing h, and this is largely because Sf decreases with h while SI is approximately independent of h. In a general sense, Sf can be thought of as the effect of aerosols on the probability of precipitation, while SI can be thought of as the effect of aerosols on the intensity of precipitation. Since thicker clouds are likely to precipitate regardless of ambient aerosol concentration, we expect Sf to decrease with increasing h. The results are broadly insensitive to the choice of horizontal averaging scale. Similar susceptibilities are found for both cloud base and near-surface drizzle rates. The analysis is repeated with cloud liquid water path held fixed instead of cloud thickness. Simple power law relationships relating precipitation rate to aerosol concentration or cloud droplet concentration do not capture this observed behavior.

scholarly journals Relationship between drizzle rate, liquid water path and droplet concentration at the scale of a stratocumulus cloud system

2008 ◽  
Vol 8 (1) ◽  
pp. 3921-3959 ◽  
Author(s):  
O. Geoffroy ◽  
J.-L. Brenguier ◽  
I. Sandu
Keyword(s):  
Liquid Water ◽  
Field Experiments ◽  
Liquid Water Path ◽  
Marine Stratocumulus ◽  
Data Set ◽  
Water Path ◽  
Droplet Concentration ◽  
Stratocumulus Clouds ◽  
Shallow Clouds ◽  
The One

Abstract. The recent ACE-2, EPIC and DYCOMS-II field experiments showed that the drizzle precipitation rate of marine stratocumulus scales with the cloud geometrical thickness or liquid water path, and the droplet concentration, when averaged over a domain typical of a GCM grid. This feature is replicated here with large-eddy-simulations using state-of-the-art bulk parameterizations of precipitation formation in stratocumulus clouds. The set of numerical simulations shows scaling relationships similar to the ones derived from the field experiments, especially the one derived from the DYCOMS-II data set. This result suggests that the empirical relationships were not fortuitous and that they reflect the mean effect of cloud physical processes. Such relationships might be more suited to GCM parameterizations of precipitation from shallow clouds than bulk parameterizations of autoconversion, that were initially developed for cloud resolving models.

scholarly journals Factors Controlling Rapid Stratocumulus Cloud Thinning

2014 ◽  
Vol 71 (2) ◽  
pp. 655-664 ◽  
Author(s):  
J. J. van der Dussen ◽  
S. R. de Roode ◽  
A. P. Siebesma
Keyword(s):  
Moisture Flux ◽  
Steady State Solution ◽  
Cloud Layer ◽  
Cloud Base ◽  
Liquid Water Path ◽  
Marine Stratocumulus ◽  
Buoyancy Reversal ◽  
Stratocumulus Clouds ◽  
Budget Equation ◽  
Heat And Moisture

Abstract The relationship between the inversion stability and the liquid water path (LWP) tendency of a vertically well-mixed, adiabatic stratocumulus cloud layer is investigated in this study through the analysis of the budget equation for the LWP. The LWP budget is mainly determined by the turbulent fluxes of heat and moisture at the top and the base of the cloud layer, as well as by the source terms due to radiation and precipitation. Through substitution of the inversion stability parameter κ into the budget equation, it immediately follows that the LWP tendency will become negative for increasing values of κ due to the entrainment of increasingly dry air. Large κ values are therefore associated with strong cloud thinning. Using the steady-state solution for the LWP, an equilibrium value κeq is formulated, beyond which the stratocumulus cloud will thin. The Second Dynamics and Chemistry of Marine Stratocumulus field study (DYCOMS-II) is used to illustrate that, depending mainly on the magnitude of the moisture flux at cloud base, stratocumulus clouds can persist well within the buoyancy reversal regime.

scholarly journals Trends in incidence rate, health care use, and costs due to rib fractures in the Netherlands

2021 ◽  
Author(s):  
Jonne T. H. Prins ◽  
Mathieu M. E. Wijffels ◽  
Sophie M. Wooldrik ◽  
Martien J. M. Panneman ◽  
Michael H. J. Verhofstad ◽  
...  
Keyword(s):  
Health Care ◽  
Incidence Rate ◽  
Health Care Costs ◽  
Indirect Costs ◽  
Rib Fractures ◽  
Work Absence ◽  
Lost Productivity ◽  
The Mean ◽  
Using Data ◽  
Care Costs

Abstract Purpose This study aimed to examine population-based trends in the incidence rate, health care consumption, and work absence with associated costs in patients with rib fractures. Methods A retrospective nationwide epidemiologic study was performed with data from patients with one or more rib fractures presented or admitted to a hospital in the Netherlands between January 1, 2015 and December 31, 2018 and have been registered in the Dutch Injury Surveillance System (DISS) or the Hospital Discharge Registry (HDR). Incidence rates were calculated using data from Statistics Netherlands. The associated direct health care costs, costs for lost productivity, and years lived with disability (YLD) were calculated using data from a questionnaire. Results In the 4-year study period, a total of 32,124 patients were registered of which 19,885 (61.9%) required hospitalization with a mean duration of 7.7 days. The incidence rate for the total cohort was 47.1 per 100,000 person years and increased with age. The mean associated direct health care costs were €6785 per patient and showed a sharp increase after the age of 75 years. The mean duration of work absence was 44.2 days with associated mean indirect costs for lost productivity of €22,886 per patient. The mean YLD was 0.35 years and decreased with age. Conclusion Rib fractures are common and associated with lengthy HLOS and work absenteeism as well as high direct and indirect costs which appear to be similar between patients with one or multiple rib fractures and mostly affected by admitted patients and age.

Time-to-Build and the Inverse U-Shape Investment-Uncertainty Relationship

2008 ◽  
Vol 8 (1) ◽  
Author(s):  
Yishay D. Maoz
Keyword(s):  
Analytical Solution ◽  
Large Time ◽  
Time Lag ◽  
Time To Build ◽  
Small Uncertainty ◽  
Shape Uncertainty ◽  
Uncertainty Relationship

The effect that investment lags have on the uncertainty-investment relationship is studied by modifying the Bar-Ilan and Strange (1996) model to enable an analytical solution. The following results emerge: (i) If the time lag is sufficiently small, uncertainty affects investment negatively; (ii) A sufficiently large time lag gives rise to an inverse U-shape uncertainty-investment relationship; (iii) When such an inverse U-shape exists, the longer the time lag (or the larger the degree of profit convexity), the wider the range of a positive uncertainty-investment relationship.

scholarly journals Combining Process Modelling and LAI Observations to Diagnose Winter Wheat Nitrogen Status and Forecast Yield

Agronomy ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 314
Author(s):  
Andrew Revill ◽  
Vasileios Myrgiotis ◽  
Anna Florence ◽  
Stephen Hoad ◽  
Robert Rees ◽  
...  
Keyword(s):  
Field Experiments ◽  
Process Models ◽  
Agricultural Technologies ◽  
N Application ◽  
Area Index ◽  
Complex Process ◽  
C Cycle ◽  
The Mean ◽  
Leaf N Content ◽  
Leaf N

Climate, nitrogen (N) and leaf area index (LAI) are key determinants of crop yield. N additions can enhance yield but must be managed efficiently to reduce pollution. Complex process models estimate N status by simulating soil-crop N interactions, but such models require extensive inputs that are seldom available. Through model-data fusion (MDF), we combine climate and LAI time-series with an intermediate-complexity model to infer leaf N and yield. The DALEC-Crop model was calibrated for wheat leaf N and yields across field experiments covering N applications ranging from 0 to 200 kg N ha−1 in Scotland, UK. Requiring daily meteorological inputs, this model simulates crop C cycle responses to LAI, N and climate. The model, which includes a leaf N-dilution function, was calibrated across N treatments based on LAI observations, and tested at validation plots. We showed that a single parameterization varying only in leaf N could simulate LAI development and yield across all treatments—the mean normalized root-mean-square-error (NRMSE) for yield was 10%. Leaf N was accurately retrieved by the model (NRMSE = 6%). Yield could also be reasonably estimated (NRMSE = 14%) if LAI data are available for assimilation during periods of typical N application (April and May). Our MDF approach generated robust leaf N content estimates and timely yield predictions that could complement existing agricultural technologies. Moreover, EO-derived LAI products at high spatial and temporal resolutions provides a means to apply our approach regionally. Testing yield predictions from this approach over agricultural fields is a critical next step to determine broader utility.

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