Minimum temperature and lapse rate in complex terrain: Influencing factors and prediction

1982 ◽  
Vol 30 (1-2) ◽  
pp. 141-152 ◽  
Author(s):  
G. P. Laughlin
Keyword(s):  
Influencing Factors ◽  
Minimum Temperature ◽  
Complex Terrain ◽  
Lapse Rate

scholarly journals Identifying the Dynamic Pattern and Influencing Factors of Influenza in Northwest China from 2013 to 2020, Based on Dynamic Regression Model and Wavelet Analysis

2020 ◽  
Author(s):  
Ruonan Wang ◽  
Jiancai Du ◽  
Jiangping Li ◽  
Yajuan Zhang ◽  
Jing Wen ◽  
...  
Keyword(s):  
Wavelet Analysis ◽  
Regression Model ◽  
Influencing Factors ◽  
Minimum Temperature ◽  
Public Awareness ◽  
Arima Model ◽  
Northwest China ◽  
Dynamic Pattern ◽  
Prevention Campaign ◽  
Dynamic Regression Model

Abstract Background: Influenza remains a serious global public health problem and a substantial economic burden. The dynamic pattern of influenza differs considerably among geographic and climatological areas, however, the factors underlying these differences are still uncertain. The aim of this paper is to characterize the dynamic pattern of influenza and its potential influencing factors in Northwest China. Methods: Influenza cases in Ningxia China from Nov. 2013 to Jun. 2020 were served as influenza proxy. Firstly, the baseline seasonal ARIMA model of influenza cases and seasonal pattern were analyzed. Then, the dynamic regression model was used to identifying the potential influencing factors of influenza. In addition, the wavelet analysis was further used to explore the coherence between influenza cases and these significant influencing factors.Results: The high risk periods of influenza in Ningxia presented a winter cycle outbreaks pattern and the fastigium came in January. The seasonal ARIMA(0,0,1)(1,1,0)12 was the optimal baseline forecast model. The dynamic regression models and wavelet analysis indicated that PM2.5 and public awareness are significantly positively associated with influenza, as well as minimum temperature is negatively associated. Conclusion: Meteorological (minimum temperature), pollution (PM2.5) and social (public awareness) factors may significantly associated with influenza in Northwest China. Decreasing PM2.5 concentration or increasing the public awareness prior to the fastigium of influenza may be the serviceable methods to reduce the disease risk of influenza, which have an important implication for policy-makers to choose an optimal time for influenza prevention campaign.

Invasion of tallow tree into southern US forests: influencing factors and implications for mitigation

2009 ◽  
Vol 39 (7) ◽  
pp. 1346-1356 ◽  
Author(s):  
Jianbang Gan ◽  
James H. Miller ◽  
Hsiaohsuan Wang ◽  
John W. Taylor
Keyword(s):  
Influencing Factors ◽  
Tree Species ◽  
Minimum Temperature ◽  
Mitigation Strategies ◽  
Triadica Sebifera ◽  
Climate Trend ◽  
Southern Us ◽  
Warming Climate ◽  
Tallow Tree ◽  
Extreme Minimum Temperature

We identify species–environment relationships to predict the occurrence of Chinese tallow ( Triadica sebifera (L.) Small) on forestlands in the southern US, where it has emerged as the most pervading, stand-replacing, alien tree species. Tallow invasions are more likely to be observed on low and flat lands, areas adjacent to water and roadways, sites recently harvested or disturbed, younger stands, and private forestlands. The winter extreme minimum temperature tends to restrain tallow northward migration. Increases in both range and severity of tallow invasions are predicted with a warming climate trend, and the situation could be worse if the warming is coupled with an increased frequency and intensity of disturbances. Monitoring and mitigation strategies are proposed to assist this region and other countries threatened by tallow invasions.

scholarly journals Observations of the thermodynamic and kinematic state of the atmospheric boundary layer over the San Luis Valley, CO, using the CopterSonde 2 remotely piloted aircraft system in support of the LAPSE-RATE field campaign

2021 ◽  
Vol 13 (2) ◽  
pp. 269-280
Author(s):  
Elizabeth A. Pillar-Little ◽  
Brian R. Greene ◽  
Francesca M. Lappin ◽  
Tyler M. Bell ◽  
Antonio R. Segales ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Complex Terrain ◽  
Lapse Rate ◽  
San Luis Valley ◽  
University Of Oklahoma ◽  
San Luis ◽  
Remotely Piloted Aircraft ◽  
Aircraft System ◽  
Convection Initiation

Abstract. In July 2018, the University of Oklahoma deployed three CopterSonde remotely piloted aircraft systems (RPASs) to take measurements of the evolving thermodynamic and kinematic state of the atmospheric boundary layer (ABL) over complex terrain in the San Luis Valley, Colorado. A total of 180 flights were completed over 5 d, with teams operating simultaneously at two different sites in the northern half of the valley. A total of 2 d of operations focused on convection initiation studies, 1 d focused on ABL diurnal transition studies, 1 d focused on internal comparison flights, and the last day of operations focused on cold air drainage flows. The data from these coordinated flights provide insight into the horizontal heterogeneity of the atmospheric state over complex terrain. This dataset, along with others collected by other universities and institutions as a part of the LAPSE-RATE campaign, have been submitted to Zenodo (Greene et al., 2020) for free and open access (https://doi.org/10.5281/zenodo.3737087).

Use of an Observation Network in the Great Basin to Evaluate Gridded Climate Data

2014 ◽  
Vol 15 (5) ◽  
pp. 1913-1931 ◽  
Author(s):  
Daniel J. McEvoy ◽  
John F. Mejia ◽  
Justin L. Huntington
Keyword(s):  
Great Basin ◽  
Minimum Temperature ◽  
Complex Terrain ◽  
Daily Minimum Temperature ◽  
Climate Data ◽  
Mountain Ranges ◽  
Dewpoint Temperature ◽  
Observation Network ◽  
Inversion Strength ◽  
Land Data Assimilation System

Abstract Predicting sharp hydroclimatic gradients in the complex terrain of the Great Basin can prove to be challenging because of the lack of climate observations that are gradient focused. Furthermore, evaluating gridded data products (GDPs) of climate in such environments for use in local hydroclimatic assessments is also challenging and typically ignored because of the lack of observations. In this study, independent Nevada Climate-Ecohydrological Assessment Network (NevCAN) observations of temperature, relative humidity, and precipitation collected along large altitudinal gradients of the Snake and Sheep mountain ranges from water-year 2012 (October–September) are utilized to evaluate four GDPs of different spatial resolutions: Parameter–Elevation Regressions on Independent Slopes Model (PRISM) 4 km, PRISM 800 m, Daymet 1 km, and a North American Land Data Assimilation System (NLDAS)–PRISM hybrid 4-km product. Inconsistencies and biases in precipitation measurements due to station siting and gauge type proved to be problematic with respect to comparisons to GDPs. This study highlights a weakness of GDPs in complex terrain: an underestimation of inversion strength and resulting minimum temperature in foothill regions, where cold air regularly drains into neighboring valleys. Results also clearly indicate that for semiarid regions, the assumption that daily average dewpoint temperature Tdew equals daily minimum temperature does not hold true and should not be used to interpolate Tdew spatially. Comparison statistics of GDPs to observations varied depending on the climate variable and grid spatial resolution, highlighting the importance of conducting local evaluations for hydroclimatic assessments.

scholarly journals Observations of the thermodynamic and kinematic state of the atmospheric boundary layer over the San Luis Valley, CO using remotely piloted aircraft systems during the LAPSE-RATE field campaign

2020 ◽  
Author(s):  
Elizabeth A. Pillar-Little ◽  
Brian R. Greene ◽  
Francesca M. Lappin ◽  
Tyler M. Bell ◽  
Antonio R. Segales ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Complex Terrain ◽  
Lapse Rate ◽  
San Luis Valley ◽  
Aircraft Systems ◽  
University Of Oklahoma ◽  
San Luis ◽  
Remotely Piloted Aircraft ◽  
Convection Initiation

Abstract. In July 2018, the University of Oklahoma deployed three CopterSonde 2 remotely piloted aircraft systems (RPAS) to take measurements of the evolving thermodynamic and kinematic state of the atmospheric boundary layer (ABL) over complex terrain in the San Luis Valley, Colorado. A total of 180 flights were completed over five days, with teams operating simultaneously at two different sites in the northern half of the valley. Two days of operations focused on convection initiation studies, one day focused on ABL diurnal transition studies, one day focused on internal comparison flights, and the last day of operations focused on cold air drainage flows. The data from these coordinated flights provides insight into the horizontal heterogeneity of the atmospheric state over complex terrain as well as the expected horizontal footprint of RPAS profiles. This dataset, along with others collected by other universities and institutions as a part of the LAPSE-RATE campaign, have been submitted to Zenodo (Greene et al., 2020) for free and open access (https://doi.org/10.5281/zenodo.3737087).

Assimilation of a Coordinated Fleet of Uncrewed Aircraft System Observations in Complex Terrain: EnKF System Design and Preliminary Assessment

2021 ◽  
Vol 149 (5) ◽  
pp. 1459-1480
Author(s):  
Anders A. Jensen ◽  
James O. Pinto ◽  
Sean C. C. Bailey ◽  
Ryan A. Sobash ◽  
Gijs de Boer ◽  
...  
Keyword(s):  
High Resolution ◽  
Complex Terrain ◽  
Lapse Rate ◽  
Limited Area ◽  
San Luis ◽  
Remotely Piloted Aircraft ◽  
Northern Portion ◽  
Independent Observations ◽  
Aircraft System ◽  
The Impact

AbstractUncrewed aircraft system (UAS) observations collected during the 2018 Lower Atmospheric Process Studies at Elevation—a Remotely Piloted Aircraft Team Experiment (LAPSE-RATE) field campaign were assimilated into a high-resolution configuration of the Weather Research and Forecasting Model using an ensemble Kalman filter. The benefit of UAS observations was assessed for a terrain-driven (drainage and upvalley) flow event that occurred within Colorado’s San Luis Valley (SLV) using independent observations. The analysis and prediction of the strength, depth, and horizontal extent of drainage flow from the Saguache Canyon and the subsequent transition to upvalley and up-canyon flow were improved relative to that obtained both without data assimilation (benchmark) and when only surface observations were assimilated. Assimilation of UAS observations greatly improved the analyses of vertical variations in temperature, relative humidity, and winds at multiple locations in the northern portion of the SLV, with reductions in both bias and the root-mean-square error of roughly 40% for each variable relative to the benchmark run. Despite these noted improvements, some biases remain that were tied to measurement error and/or the impact of the boundary layer parameterization on vertically spreading the observations, both of which require further exploration. The results presented here highlight how observations obtained with a fleet of profiling UAS improve limited-area, high-resolution analyses and short-term forecasts in complex terrain.

scholarly journals Assessing filtering of mountaintop CO<sub>2</sub> mixing ratios for application to inverse models of biosphere-atmosphere carbon exchange

2011 ◽  
Vol 11 (9) ◽  
pp. 25327-25369 ◽  
Author(s):  
B.-G. J. Brooks ◽  
A. R. Desai ◽  
B. B. Stephens ◽  
D. R. Bowling ◽  
S. P. Burns ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Atmospheric Transport ◽  
Model Atmosphere ◽  
The United States ◽  
Lapse Rate ◽  
Mixing Ratio ◽  
Test Results ◽  
Diurnal Variability ◽  
Sliding Windows ◽  
Mixing Ratios

Abstract. There is a widely recognized need to improve our understanding of biosphere-atmosphere carbon exchanges in areas of complex terrain including the United States Mountain West. CO2 fluxes over mountainous terrain are difficult to measure often due to unusual and complicated influences associated with atmospheric transport in complex terrain. Using five years of CO2 mixing ratio observations from the Regional Atmospheric Continuous CO2 Network in the Rocky Mountains (Rocky RACCOON), five statistical (subsetting) filters are used to investigate a range of approaches for identifying regionally representative CO2 mixing ratios. Test results from three filters indicate that subsets based on short-term variance and local CO2 gradients across tower inlet heights retain nine-tenths of the total observations and are able to define representative diurnal variability and seasonal cycles even for difficult-to-model sites where the influence of local fluxes is much larger than regional mixing ratio variations. Test results from two other filters that consider measurements from previous and following days using spline fitting or sliding windows are overly selective. Case study examples showed that even when standardized to common subset sizes these windowing-filters rejected measurements representing synoptic changes in CO2, which suggests that they are not well suited to filtering continental CO2 measurements. We present a novel CO2 lapse rate filter that uses CO2 differences between levels in the model atmosphere to constrain subsets of site measurements that are representative on model scales.

scholarly journals The five main influencing factors on lidar errors in complex terrain

2021 ◽  
Author(s):  
Tobias Klaas ◽  
Stefan Emeis
Keyword(s):  
Influencing Factors ◽  
Error Estimation ◽  
Complex Terrain ◽  
Atmospheric Stability ◽  
Opening Angle ◽  
Parameter Study ◽  
Flow Models ◽  
Measurement Height ◽  
Error Estimations ◽  
Half Cone

Abstract. Light detection and ranging (notably Doppler lidar), has become a valuable technology to assess the wind resource at hub height of modern wind turbines. However, because of their measurement principle, common wind profile Doppler lidars suffer from errors at complex terrain sites. This study analyses the impact of the five main influencing factors at lidar measurement errors in complex terrain, i.e. orographic complexity, measurement height, surface roughness and forest, atmospheric stability and half-cone opening angle, in a non-dimensional, model-based parameter study. In a novel approach, the lidar error ε is split up into a part εc, caused by flow curvature at the measurement points of the lidar and a part εs, caused by the local speed-up effects between the measurement points. This approach, e.g., allows for a systematic and complete interpretation of the influence of the half-cone opening angle φ of the lidar. It also provides information about the uncertainty of simple lidar error estimations that are based on inflow and outflow angles at the measurement points. The model-based parameter study is limited to two-dimensional Gaussian hills with hill height H and hill half-width L. H/L and z/L, with z being the measurement height, are identified as the main scaling factors for the lidar error. Three flow models of different complexity are used to estimate the lidar errors. The outcome of the study provides manifold findings that enable an assessment of the applicability of these flow models. The study clearly shows that orographic complexity, roughness and forest characteristics, as well as atmospheric stability, have a significant influence on lidar error estimation. Based on the error separation approach it furthermore allows for an in-depth analysis of the influence of reduced half-cone opening angles. The choice and parameterization of flow models and the design of methods for lidar error estimation are found to be essential to achieve accurate results. The use of a RANS CFD model in conjunction with an appropriate forest model is highly recommended for lidar error estimations in complex terrain. If atmospheric stability variation at a measurement site plays a vital role, it should also be considered in the modelling. When planning a measurement campaign, an accurate estimation of the prospective lidar error should be carried out in advance to decrease measurement uncertainties and maximize the value.

Cloud-top Structure of Tornadic Storms on 10 April 1979 from Rapid Scan and Stereo Satellite Observations1

1982 ◽  
Vol 63 (10) ◽  
pp. 1151-1159 ◽  
Author(s):  
Andrew J. Negri
Keyword(s):  
Cross Sections ◽  
Minimum Temperature ◽  
Interval Data ◽  
Rate Of Change ◽  
Radar Reflectivity ◽  
Field Of View ◽  
Lapse Rate ◽  
Data Set ◽  
Severe Storms ◽  
Tornadic Storms

The cloud top structure of the Wichita Falls tornadic storm of 10 April 1979 (and other severe storms on this day) is studied using remotely-sensed observations from radar and satellite. A comprehensive data set included 3 min interval visible (0.6 μm) and infrared (11 μm) radiances from the eastern GOES and similar 30 min interval data from the western GOES. The near synchronization of these two satellites allowed for the stereoscopic determination of cloud top heights. In addition, at 2048 GMT, TIROS-N scanned the storms within one minute of the geosynchronous stereo and provided 1 km resolution infrared blackbody temperatures. Because internal storm dynamics are hidden from the view of the satellite, storm updraft intensity must be inferred from cloud-top minimum temperature and its rate of change. The Wichita Falls, Tex. tornadic storm could be defined in the satellite data by a point of minimum temperature which displayed temporal continuity and achieved a temperature of 208 K. A cloud-top cooling rate above the tropopause of 7 K/21 min preceded tornadogenesis. An adjacent warm area (221 K) developed downwind and was surrounded by a “V”-shaped pattern of lower temperatures. The warm area is postulated as due to subsidence in the lee of an ascending tower. The measured stereo height of the Wichita Falls storm was 15.6 km at 2349 GMT, 1.5 km higher than severe storms 150 km downwind, although its minimum blackbody temperature was 9 K higher than that of these downwind storms. In addition, unrealistic fluctuations in the time sequence of temperature 30 min prior to the Wichita Falls tornado indicate that the IR measurements are affected by sensor response and/or field of view limitations, at least close to the anvil edge. Cross sections of stereo heights, IR temperature, and radar reflectivity at 2349 GMT demonstrate that while there is, in general, a co-location of high tops, low temperatures, and high low-level radar reflectivity, significant variations can exist in height/rainfall relationships. A comparison of data sets at 2048 GMT between stereo height measurements and IR temperatures from GOES-East and TIROS-N revealed that anvil top features can be up to 10 K warmer in the GOES field of view (100 km2) than from TIROS-N (1 km2), and that this difference can reach 20 K for young thunderstorms, with perhaps 4 K explained by calibration differences. The lapse rate for tops penetrating the tropopause was substantially closer to the adiabatic lapse rate when TIROS-N temperature minima, rather than GOES minima, were plotted as a function of stereo determined height.

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