Dependence of mesoscale patterns of Trade-wind clouds on environmental conditions: an investigation using satellite and in-situ observations

2020 ◽  
Author(s):  
Sandrine Bony ◽  
Hauke Schulz ◽  
Jessica Vial ◽  
Bjorn Stevens ◽  
Keyword(s):  
Meteorological Data ◽  
Surface Wind ◽  
Cloud Amount ◽  
Surface Wind Speed ◽  
Trade Wind ◽  
Shallow Convection ◽  
Western Atlantic ◽  
Near Surface ◽  
Cloud Patterns

<p>Trade-wind clouds exhibit a large diversity of spatial organizations at the mesoscale. Over the tropical western Atlantic, a recent study has visually identified four prominent mesoscale patterns of shallow convection, referred to as Flowers, Fish, Gravel and Sugar. By using 19 years of satellite and meteorological data, we show that these four patterns can be identified objectively from satellite observations, and that on daily and interannual timescales, the near-surface wind speed and the strength of the lower-tropospheric stability discriminate the occurrence of the different organization patterns. Moreover, we point out a tight relationship between cloud patterns, low-level cloud amount and cloud-radiative effects. The EUREC4A field study taking place upwind of Barbados in Jan-Feb 2020 offers an opportunity to investigate these relationships from an in-situ and process-oriented perspective. Preliminary results will be discussed.</p>

scholarly journals Numerical Simulation of Near-Surface Wind during a Severe Wind Event in a Complex Terrain by Multisource Data Assimilation and Dynamic Downscaling

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
De Zhang ◽  
Luyuan Chen ◽  
Feimin Zhang ◽  
Juan Tan ◽  
Chenghai Wang
Keyword(s):  
Wind Speed ◽  
Data Assimilation ◽  
Surface Wind ◽  
Wrf Model ◽  
Surface Wind Speed ◽  
Dynamic Downscaling ◽  
Near Surface ◽  
Wind Event ◽  
Weak Wind

Accurate forecast and simulation of near-surface wind is a great challenge for numerical weather prediction models due to the significant transient and intermittent nature of near-surface wind. Based on the analyses of the impact of assimilating in situ and Advanced Tiros Operational Vertical Sounder (ATOVS) satellite radiance data on the simulation of near-surface wind during a severe wind event, using the new generation mesoscale Weather Research and Forecasting (WRF) model and its three-dimensional variational (3DVAR) data assimilation system, the dynamic downscaling of near-surface wind is further investigated by coupling the microscale California Meteorological (CALMET) model with the WRF and its 3DVAR system. Results indicate that assimilating in situ and ATOVS radiance observations strengthens the airflow across the Alataw valley and triggers the downward transport of momentum from the upper atmosphere in the downstream area of the valley in the initial conditions, thus improving near-surface wind simulations. Further investigations indicate that the CALMET model provides more refined microtopographic structures than the WRF model in the vicinity of the wind towers. Although using the CALMET model achieves the best simulation of near-surface wind through dynamic downscaling of the output from the WRF and its 3DVAR assimilation, the simulation improvements of near-surface wind speed are mainly within 1 m s−1. Specifically, the mean improvement proportions of near-surface wind speed are 64.8% for the whole simulation period, 58.7% for the severe wind period, 68.3% for the severe wind decay period, and 75.4% for the weak wind period. The observed near-surface wind directions in the weak wind conditions are better simulated in the coupled model with CALMET downscaling than in the WRF and its 3DVAR system. It is concluded that the simulation improvements of CALMET downscaling are distinct when near-surface winds are weak, and the downscaling effects are mainly manifested in the simulation of near-surface wind directions.

scholarly journals Covariability of Near-Surface Wind Speed Statistics and Mesoscale Sea Surface Temperature Fluctuations

2018 ◽  
Vol 48 (3) ◽  
pp. 465-478 ◽  
Author(s):  
Johannes Gemmrich ◽  
Adam Monahan
Keyword(s):  
Wind Speed ◽  
Cold Water ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Western Boundary ◽  
Near Surface ◽  
Water Entrainment ◽  
Speed Fluctuations ◽  
Coupling Processes

AbstractThe atmospheric (ABL) and ocean (OBL) boundary layers are intimately linked via mechanical and thermal coupling processes. In many regions over the world’s oceans, this results in a strong covariability between anomalies in wind speed and SST. At oceanic mesoscale, this coupling can be driven either from the atmosphere or the ocean. Gridded SST and wind speed data at 0.25° resolution show that over the western North Atlantic, the ABL mainly responds to the OBL, whereas in the eastern North Pacific and in the Southern Ocean, the OBL largely responds to wind speed anomalies. This general behavior is also verified by in situ buoy observations in the Atlantic and Pacific. A stochastic, nondimensional, 1D coupled air–sea boundary layer model is utilized to assess the relative importance of the coupling processes. For regions of little intrinsic SST fluctuations (i.e., most regions of the world’s oceans away from strong temperature fronts), the inclusion of cold water entrainment at the thermocline is crucial. In regions with strong frontal activities (e.g., the western boundary regions), the coupling is dominated by the SST fluctuations, and the frontal variability needs to be included in models. Generally, atmospheric and ocean-driven coupling lead to an opposite relationship between SST and wind speed fluctuations. This effect can be especially important for higher wind speed quantiles.

Recurrence Characteristics Analysis of Near-Surface Wind Speed Signal with Different Sampling Frequencies

2014 ◽  
Vol 599-601 ◽  
pp. 1605-1609 ◽  
Author(s):  
Ming Zeng ◽  
Zhan Xie Wu ◽  
Qing Hao Meng ◽  
Jing Hai Li ◽  
Shu Gen Ma
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Recurrence Plot ◽  
Sampling Frequency ◽  
Near Surface ◽  
Gas Leakage ◽  
Time Period ◽  
Characteristics Analysis ◽  
Quantification Analysis

The wind is the main factor to influence the propagation of gas in the atmosphere. Therefore, the wind signal obtained by anemometer will provide us valuable clues for searching gas leakage sources. In this paper, the Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA) are applied to analyze the influence of recurrence characteristics of the wind speed time series under the condition of the same place, the same time period and with the sampling frequency of 1hz, 2hz, 4.2hz, 5hz, 8.3hz, 12.5hz and 16.7hz respectively. Research results show that when the sampling frequency is higher than 5hz, the trends of recurrence nature of different groups are basically unchanged. However, when the sampling frequency is set below 5hz, the original trend of recurrence nature is destroyed, because the recurrence characteristic curves obtained using different sampling frequencies appear cross or overlapping phenomena. The above results indicate that the anemometer will not be able to fully capture the detailed information in wind field when its sampling frequency is lower than 5hz. The recurrence characteristics analysis of the wind speed signals provides an important basis for the optimal selection of anemometer.

scholarly journals Mechanisms of Future Changes in Equatorial Upwelling: CMIP5 Intermodel Analysis

2020 ◽  
Vol 33 (2) ◽  
pp. 497-510 ◽  
Author(s):  
Mio Terada ◽  
Shoshiro Minobe ◽  
Curtis Deutsch
Keyword(s):  
Climate Models ◽  
Eastern Pacific ◽  
Trade Wind ◽  
Pacific Basin ◽  
Ekman Pumping ◽  
Equatorial Atlantic ◽  
Western Atlantic ◽  
Near Surface ◽  
The Pacific ◽  
Equatorial Upwelling

AbstractThe future change in equatorial upwelling between 1971–2000 and 2071–2100 is investigated using data from 24 coupled climate models. The multimodel ensemble (MME) mean exhibits substantial equatorial upwelling decrease in the eastern Pacific and weaker decrease in the western Atlantic Ocean. The MME mean of upwelling change and intermodel variation of that are decomposed into distinct isopycnal and diapycnal components. In the Pacific, the diapycnal upwelling decreases near the surface, associated with a weakened Ekman pumping. The isopycnal upwelling decreases at depths of 75–200 m around the core of the Equatorial Undercurrent (EUC) due to flattening of the density layer in which it flows. Both the weakened Ekman pumping and the EUC flattening are induced by the locally weakened trade wind over the eastern Pacific basin. In the equatorial Atlantic, both the change in MME mean and the intermodel variation of upwellings are significantly related to the weakened trade wind and enhanced stratification, although these drivers are not independent. The results for the Pacific Ocean imply that future reduction in upwelling may have impacts at different depths by different mechanisms. In particular, the rapid warming of sea surface temperature in the eastern Pacific basin may be mainly caused by the near-surface diapycnal upwelling reduction rather than isopycnal upwelling reduction associated EUC flattening, which is important at deeper levels.

A preliminary study on the influence of Beijing urban spatial morphology on near-surface wind speed

Urban Climate ◽  
2020 ◽  
Vol 34 ◽  
pp. 100703
Author(s):  
Yonghong Liu ◽  
Yongming Xu ◽  
Fangmin Zhang ◽  
Wenjun Shu
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Near Surface ◽  
Spatial Morphology ◽  
Preliminary Study

scholarly journals Wind Speed Forecast Based on Post-Processing of Numerical Weather Predictions Using a Gradient Boosting Decision Tree Algorithm

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 738 ◽  
Author(s):  
Wenqing Xu ◽  
Like Ning ◽  
Yong Luo
Keyword(s):  
Wind Speed ◽  
Decision Tree ◽  
Wind Power ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Gradient Boosting ◽  
Post Processing ◽  
Near Surface ◽  
Wind Power Forecasting ◽  
Numerical Weather

With the large-scale development of wind energy, wind power forecasting plays a key role in power dispatching in the electric power grid, as well as in the operation and maintenance of wind farms. The most important technology for wind power forecasting is forecasting wind speed. The current mainstream methods for wind speed forecasting involve the combination of mesoscale numerical meteorological models with a post-processing system. Our work uses the WRF model to obtain the numerical weather forecast and the gradient boosting decision tree (GBDT) algorithm to improve the near-surface wind speed post-processing results of the numerical weather model. We calculate the feature importance of GBDT in order to find out which feature most affects the post-processing wind speed results. The results show that, after using about 300 features at different height and pressure layers, the GBDT algorithm can output more accurate wind speed forecasts than the original WRF results and other post-processing models like decision tree regression (DTR) and multi-layer perceptron regression (MLPR). Using GBDT, the root mean square error (RMSE) of wind speed can be reduced from 2.7–3.5 m/s in the original WRF result by 1–1.5 m/s, which is better than DTR and MLPR. While the index of agreement (IA) can be improved by 0.10–0.20, correlation coefficient be improved by 0.10–0.18, Nash–Sutcliffe efficiency coefficient (NSE) be improved by −0.06–0.6. It also can be found that the feature which most affects the GBDT results is the near-surface wind speed. Other variables, such as forecast month, forecast time, and temperature, also affect the GBDT results.

scholarly journals Characteristics and Applications of the Ground-Based X Band Low Elevation Angle Brightness Temperatures under Low Sea State Based on Measured Data

2020 ◽  
Vol 12 (11) ◽  
pp. 1736
Author(s):  
Zhongqing Cao ◽  
Lixin Guo ◽  
Shifeng Kang ◽  
Xianhai Cheng ◽  
Qingliang Li ◽  
...  
Keyword(s):  
Wind Speed ◽  
Meteorological Data ◽  
Surface Wind ◽  
Elevation Angle ◽  
Surface Wind Speed ◽  
Sea Surface ◽  
Sea State ◽  
Sea Surface Wind Speed ◽  
Sea Surface Wind ◽  
X Band

In ground-based microwave radiometer remote sensing, low-elevation-angle (−3°~3°) radiation data are often discarded because they are considered to be of little value and are often difficult to model due to the complicated mechanism. Based on the observed X-band horizontal polarization low elevation angle microwave radiation data and the meteorological data at the same time, this study investigated the generation mechanism of low elevation angle brightness temperature (LEATB) and its relationship with meteorological data, i.e., temperature, humidity, and wind speed, under low sea state. As a result, one could find that the LEATB was sensitive to the atmosphere at the elevation angle between 1° to 3°, and a diurnal variation of the LEATB reached up to 10 K. This study also found a linear relationship between the LEATB and sea surface wind speed under low sea state at an elevation range from −3° to 0°, i.e., the brightness temperature decreased as the wind speed increased, which was inconsistent with the observations at the elevation angle from −10° to −5°. The variation of the LEATB difference according to the change in the over-the-horizon detection capability (OTHDC) of the shipborne microwave radar was examined to identify the reason for this phenomenon theoretically. The results showed that the LEATB difference was significantly influenced by a change in the OTHDC. Further, this study examined a remote sensing method to extract the sea surface wind speed data from experimental LEATB data under low sea state. The results demonstrated that the X-band horizontal polarization LEATBs were useful to retrieve the sea surface wind speed data at a reasonable accuracy—the root mean square error of 0.02408 m/s. Overall, this study proved the promising potential of the LEATB data for retrieving temperature profiles, humidity profiles, sea surface winds, and the OTHDC.

scholarly journals A Method to Estimate Open Pack-Ice Thickness from Two-Day Sequences of Side-Lapping Satellite Images

1987 ◽  
Vol 9 ◽  
pp. 69-71 ◽  
Author(s):  
Uri Feldman
Keyword(s):  
Surface Wind ◽  
Microwave Remote Sensing ◽  
Surface Wind Speed ◽  
Ice Thickness ◽  
In Situ Observation ◽  
Pack Ice ◽  
Upper Limits ◽  
Ice Floes ◽  
Active Microwave Remote Sensing

A method to estimate open pack ice thickness drifting in a marginal ice zone (MIZ) is presented, The estimates are obtained from two-day sequences of sidelapping Landsat-1 MSS images and two-day sequences of wind field data by four steps: estimating the surface wind speed, estimating the angle of sea ice deflection, estimating three ratios between ice parameters and estimating the lower and upper limits of pack ice thickness. The method has been applied to six groups of open pack ice floes drifting in the MIZ of the Beaufort Sea during 1973–1975. In the absence of simultaneous in-situ observation, the results have not been tested, The method presented may be applied to any MIZ. Rather than using Landsat-1 MSS images, data from a high resolution active microwave remote sensing system should be employed in the future as its data will be independent of sun illumination and cloud cover.

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