scholarly journals Regional Difference in the Characteristic of Dust Event in East Asia: Relationship among Dust Outbreak, Surface Wind, and Land Surface Condition

2005 ◽  
Vol 83A ◽  
pp. 1-18 ◽  
Author(s):  
Yasunori KUROSAKI ◽  
Masao MIKAMI
Keyword(s):  
East Asia ◽  
Land Surface ◽  
Regional Difference ◽  
Surface Condition ◽  
Surface Wind ◽  
Dust Event

scholarly journals Impact of Arctic amplification on declining spring dust events in East Asia

2019 ◽  
Vol 54 (3-4) ◽  
pp. 1913-1935 ◽  
Author(s):  
Jun Liu ◽  
Dongyou Wu ◽  
Guangjing Liu ◽  
Rui Mao ◽  
Siyu Chen ◽  
...  
Keyword(s):  
East Asia ◽  
Northern Hemisphere ◽  
Surface Wind ◽  
Northern China ◽  
Temperature Gradients ◽  
Arctic Amplification ◽  
Dust Event ◽  
Snow Cover Extent ◽  
Spring Dust ◽  
Dust Events

AbstractDust aerosols play key roles in affecting regional and global climate through their direct, indirect, and semi-direct effects. Dust events have decreased rapidly since the 1980s in East Asia, particularly over northern China, primarily because of changes in meteorological parameters (e.g. surface wind speed and precipitation). In this study, we found that winter (December–January–February) Arctic amplification associated with weakened temperature gradients along with decreased zonal winds is primarily responsible for the large decline in following spring (March–April–May) dust event occurrences over northern China since the mid-1980s. A dust index was developed for northern China by combining the daily frequency of three types of dust event (dust storm, blowing dust, and floating dust). Using the empirical orthogonal function (EOF) analysis, the first pattern of dust events was obtained for spring dust index anomalies, which accounts for 56.2% of the variability during 1961–2014. Moreover, the enhanced Arctic amplification and stronger Northern Hemisphere annular mode (NAM) in winter can result in the anticyclonic anomalies over Siberia and Mongolia, while cyclonic anomalies over East Europe in spring. These results are significantly correlated with the weakened temperature gradients, increased precipitation and soil moisture, and decreased snow cover extent in the mid-latitude over Northern Hemisphere. Based on the future predictions obtained from the Fifth Climate Models Intercomparison Project (CMIP5), we found that the dust event occurrences may continually decrease over northern China due to the enhanced Arctic amplification in future climate.

Impact of Arctic amplification on declining spring dust events in East Asia

2020 ◽  
Author(s):  
Xin Wang ◽  
Jun Liu
Keyword(s):  
East Asia ◽  
Northern Hemisphere ◽  
Surface Wind ◽  
Northern China ◽  
Temperature Gradients ◽  
Arctic Amplification ◽  
Dust Event ◽  
Snow Cover Extent ◽  
Spring Dust ◽  
Dust Events

<div> <div> <div> <div> <p>Dust aerosols play key roles in affecting the regional and global climate through their direct, indirect, and semi-direct effects. Dust events have decreased rapidly since the 1980s in East Asia, particularly over northern China, primarily because of changes in meteorological parameters (e.g. surface wind speed and precipitation). In this study, we found that winter (December– January–February) Arctic amplification associated with weakened temperature gradients along with decreased zonal winds is primarily responsible for the large decline in following spring (March–April–May) dust event occurrences over northern China since the mid-1980s. A dust index was developed for northern China by combining the daily frequency of three types of dust events (dust storm, blowing dust, and floating dust). Using the empirical orthogonal function (EOF) analysis, the first pattern of dust events was obtained for spring dust index anomalies, which accounts for 56.2% of the variability from 1961–2014. Moreover, the enhanced Arctic amplification and stronger Northern Hemisphere annular mode (NAM) in winter can result in the anticyclonic anomalies over Siberia and Mongolia, while cyclonic anomalies over East Europe in spring. These results are significantly correlated with the weakened temperature gradients, increased precipitation, and soil moisture, and decreased snow cover extent in the mid-latitude over Northern Hemisphere. Based on the future predictions obtained from the Fifth Climate Models Intercomparison Project (CMIP5), we found that the dust event occurrences may continually decrease over northern China due to the enhanced Arctic amplification in future climate.</p> </div> </div> </div> </div>

Intercomparison of Mesoscale Model Simulations of the Daytime Valley Wind System

2011 ◽  
Vol 139 (5) ◽  
pp. 1389-1409 ◽  
Author(s):  
Juerg Schmidli ◽  
Brian Billings ◽  
Fotini K. Chow ◽  
Stephan F. J. de Wekker ◽  
James Doyle ◽  
...  
Keyword(s):  
Land Surface ◽  
Mesoscale Model ◽  
Numerical Models ◽  
Surface Wind ◽  
Sensible Heat Flux ◽  
Surface Wind Speed ◽  
Time Shift ◽  
Wind System ◽  
Valley Wind ◽  
The Mean

Three-dimensional simulations of the daytime thermally induced valley wind system for an idealized valley–plain configuration, obtained from nine nonhydrostatic mesoscale models, are compared with special emphasis on the evolution of the along-valley wind. The models use the same initial and lateral boundary conditions, and standard parameterizations for turbulence, radiation, and land surface processes. The evolution of the mean along-valley wind (averaged over the valley cross section) is similar for all models, except for a time shift between individual models of up to 2 h and slight differences in the speed of the evolution. The analysis suggests that these differences are primarily due to differences in the simulated surface energy balance such as the dependence of the sensible heat flux on surface wind speed. Additional sensitivity experiments indicate that the evolution of the mean along-valley flow is largely independent of the choice of the dynamical core and of the turbulence parameterization scheme. The latter does, however, have a significant influence on the vertical structure of the boundary layer and of the along-valley wind. Thus, this ideal case may be useful for testing and evaluation of mesoscale numerical models with respect to land surface–atmosphere interactions and turbulence parameterizations.

scholarly journals Fundamental Climate Data Records of Microwave Brightness Temperatures

2018 ◽  
Vol 10 (8) ◽  
pp. 1306 ◽  
Author(s):  
Wesley Berg ◽  
Rachael Kroodsma ◽  
Christian Kummerow ◽  
Darren McKague
Keyword(s):  
Land Surface ◽  
Surface Wind ◽  
Precipitable Water ◽  
Original Data ◽  
Climate Data ◽  
Sea Ice Extent ◽  
Brightness Temperatures ◽  
Precipitation Total ◽  
Data Record ◽  
Microwave Imager

An intercalibrated Fundamental Climate Data Record (FCDR) of brightness temperatures (Tb) has been developed using data from a total of 14 research and operational conical-scanning microwave imagers. This dataset provides a consistent 30+ year data record of global observations that is well suited for retrieving estimates of precipitation, total precipitable water, cloud liquid water, ocean surface wind speed, sea ice extent and concentration, snow cover, soil moisture, and land surface emissivity. An initial FCDR was developed for a series of ten Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) instruments on board the Defense Meteorological Satellite Program spacecraft. An updated version of this dataset, including additional NASA and Japanese sensors, has been developed as part of the Global Precipitation Measurement (GPM) mission. The FCDR development efforts involved quality control of the original data, geolocation corrections, calibration corrections to account for cross-track and time-dependent calibration errors, and intercalibration to ensure consistency with the calibration reference. Both the initial SSMI(S) and subsequent GPM Level 1C FCDR datasets are documented, updated in near real-time, and publicly distributed.

scholarly journals Impact of Parameterization of Physical Processes on Simulation of Track and Intensity of Tropical Cyclone Nargis (2008) with WRF-NMM Model

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Sujata Pattanayak ◽  
U. C. Mohanty ◽  
Krishna K. Osuri
Keyword(s):  
Land Surface ◽  
Mesoscale Model ◽  
Initial Conditions ◽  
Surface Wind ◽  
India Meteorological Department ◽  
Heat Fluxes ◽  
Cumulus Convection ◽  
Cyclonic Storm ◽  
Parameterization Schemes ◽  
Cyclone Nargis

The present study is carried out to investigate the performance of different cumulus convection, planetary boundary layer, land surface processes, and microphysics parameterization schemes in the simulation of a very severe cyclonic storm (VSCS) Nargis (2008), developed in the central Bay of Bengal on 27 April 2008. For this purpose, the nonhydrostatic mesoscale model (NMM) dynamic core of weather research and forecasting (WRF) system is used. Model-simulated track positions and intensity in terms of minimum central mean sea level pressure (MSLP), maximum surface wind (10 m), and precipitation are verified with observations as provided by the India Meteorological Department (IMD) and Tropical Rainfall Measurement Mission (TRMM). The estimated optimum combination is reinvestigated with six different initial conditions of the same case to have better conclusion on the performance of WRF-NMM. A few more diagnostic fields like vertical velocity, vorticity, and heat fluxes are also evaluated. The results indicate that cumulus convection play an important role in the movement of the cyclone, and PBL has a crucial role in the intensification of the storm. The combination of Simplified Arakawa Schubert (SAS) convection, Yonsei University (YSU) PBL, NMM land surface, and Ferrier microphysics parameterization schemes in WRF-NMM give better track and intensity forecast with minimum vector displacement error.

scholarly journals Assessing the Impact of Changes in Land Surface Conditions on WRF Predictions in Arid Regions

2020 ◽  
Vol 21 (12) ◽  
pp. 2829-2853 ◽  
Author(s):  
Marouane Temimi ◽  
Ricardo Fonseca ◽  
Narendra Nelli ◽  
Michael Weston ◽  
Mohan Thota ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Soil Texture ◽  
Land Surface ◽  
Surface Wind ◽  
Surface Fluxes ◽  
Abu Dhabi ◽  
Horizontal Wind ◽  
Cold Bias ◽  
Near Surface ◽  
The Impact

AbstractA thorough evaluation of the Weather Research and Forecasting (WRF) Model is conducted over the United Arab Emirates, for the period September 2017–August 2018. Two simulations are performed: one with the default model settings (control run), and another one (experiment) with an improved representation of soil texture and land use land cover (LULC). The model predictions are evaluated against observations at 35 weather stations, radiosonde profiles at the coastal Abu Dhabi International Airport, and surface fluxes from eddy-covariance measurements at the inland city of Al Ain. It is found that WRF’s cold temperature bias, also present in the forcing data and seen almost exclusively at night, is reduced when the surface and soil properties are updated, by as much as 3.5 K. This arises from the expansion of the urban areas, and the replacement of loamy regions with sand, which has a higher thermal inertia. However, the model continues to overestimate the strength of the near-surface wind at all stations and seasons, typically by 0.5–1.5 m s−1. It is concluded that the albedo of barren/sparsely vegetated regions in WRF (0.380) is higher than that inferred from eddy-covariance observations (0.340), which can also explain the referred cold bias. At the Abu Dhabi site, even though soil texture and LULC are not changed, there is a small but positive effect on the predicted vertical profiles of temperature, humidity, and horizontal wind speed, mostly between 950 and 750 hPa, possibly because of differences in vertical mixing.

The Probability Distribution of Land Surface Wind Speeds

2011 ◽  
Vol 24 (15) ◽  
pp. 3892-3909 ◽  
Author(s):  
Adam H. Monahan ◽  
Yanping He ◽  
Norman McFarlane ◽  
Aiguo Dai
Keyword(s):  
Boundary Layer ◽  
Weibull Distribution ◽  
Land Surface ◽  
Wind Shear ◽  
Surface Wind ◽  
Nocturnal Boundary Layer ◽  
Global Network ◽  
Strong Wind ◽  
Wind Speeds ◽  
Tropospheric Wind

Abstract The probability density function (pdf) of land surface wind speeds is characterized using a global network of observations. Daytime surface wind speeds are shown to be broadly consistent with the Weibull distribution, while nighttime surface wind speeds are generally more positively skewed than the corresponding Weibull distribution (particularly in summer). In the midlatitudes, these strongly positive skewnesses are shown to be generally associated with conditions of strong surface stability and weak lower-tropospheric wind shear. Long-term tower observations from Cabauw, the Netherlands, and Los Alamos, New Mexico, demonstrate that lower-tropospheric wind speeds become more positively skewed than the corresponding Weibull distribution only in the shallow (~50 m) nocturnal boundary layer. This skewness is associated with two populations of nighttime winds: (i) strongly stably stratified with strong wind shear and (ii) weakly stably or unstably stratified with weak wind shear. Using an idealized two-layer model of the boundary layer momentum budget, it is shown that the observed variability of the daytime and nighttime surface wind speeds can be accounted for through a stochastic representation of intermittent turbulent mixing at the nocturnal boundary layer inversion.

scholarly journals Evaluation of a Regional Reanalysis and ERA-Interim over East Asia Using In Situ Observations during 2013–14

2017 ◽  
Vol 56 (10) ◽  
pp. 2821-2844 ◽  
Author(s):  
Eun-Gyeong Yang ◽  
Hyun Mee Kim
Keyword(s):  
Relative Humidity ◽  
East Asia ◽  
Geopotential Height ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Surface Wind ◽  
Lower Troposphere ◽  
Near Surface ◽  
Skill Scores ◽  
Regional Reanalysis

AbstractIn this study, the East Asia Regional Reanalysis (EARR) is developed for the period 2013–14 and characteristics of the EARR are examined in comparison with ERA-Interim (ERA-I) reanalysis. The EARR is based on the Unified Model with 12-km horizontal resolution, which has been an operational numerical weather prediction model at the Korea Meteorological Administration since being adopted from the Met Office in 2011. Relative to the ERA-I, in terms of skill scores, the EARR performance for wind, temperature, relative humidity, and geopotential height improves except for mean sea level pressure, the lower-troposphere geopotential height, and the upper-air relative humidity. In a similar way, RMSEs of the EARR are smaller than those of ERA-I for wind, temperature, and relative humidity, except for the upper-air meridional wind and the upper-air relative humidity in January. With respect to the near-surface variables, the triple collocation analysis and the correlation coefficients confirm that EARR provides a much improved representation when compared with ERA-I. In addition, EARR reproduces the finescale features of near-surface variables in greater detail than ERA-I does, and the kinetic energy (KE) spectra of EARR agree more with the canonical atmospheric KE spectra than do the ERA-I KE spectra. On the basis of the fractions skill score, the near-surface wind of EARR is statistically significantly better simulated than that of ERA-I for all thresholds, except for the higher threshold at smaller spatial scales. Therefore, although special care needs to be taken when using the upper-air relative humidity from EARR, the near-surface variables of the EARR that were developed are found to be more accurate than those of ERA-I.

Irrigation in JULES Land-Only Simulations over South and East Asia

2021 ◽  
Author(s):  
Markus Todt ◽  
Pier Luigi Vidale ◽  
Patrick C. McGuire ◽  
Omar V. Müller
Keyword(s):  
Soil Moisture ◽  
East Asia ◽  
Land Surface ◽  
River Flow ◽  
Heat Fluxes ◽  
Global Climate Models ◽  
Irrigated Agriculture ◽  
Irrigation Season ◽  
Irrigation Scheme ◽  
The Impact

<p>Capturing soil moisture-atmosphere feedbacks in a weather or climate model requires realistic simulation of various land surface processes. However, irrigation and other water management methods are still missing in most global climate models today, despite irrigated agriculture being the dominant land use in parts of Asia. In this study, we test the irrigation scheme available in the land model JULES (Joint UK Land Environment Simulator) by running land-only simulations over South and East Asia driven by WFDEI (WATCH Forcing Data ERA-Interim) forcing data. Irrigation in JULES is applied on a daily basis by replenishing soil moisture in the upper soil layers to field capacity, and we use a version of the irrigation scheme that extracts water for irrigation from groundwater and rivers, which physically limits the amount of irrigation that can be applied. We prescribe irrigation for C3 grasses in order to simulate the effects of agriculture, albeit retaining the simpler, widely used 5-PFT (plant functional type) configuration in JULES. Irrigation generally increases soil moisture and evapotranspiration, which results in increasing latent heat fluxes and decreasing sensible heat fluxes. Comparison with combined observational/machine-learning products for turbulent fluxes shows that while irrigation can reduce biases, other biases in JULES, unrelated to irrigation, are larger than improvements due to the inclusion of irrigation. Irrigation also affects water fluxes within the soil, e.g. runoff and drainage into the groundwater level, as well as soil moisture outside of the irrigation season. We find that the irrigation scheme, at least in the uncoupled land-atmosphere setting, can rapidly deplete groundwater to the point that river flow becomes the main source of irrigation (over the North China Plain and the Indus region) and can have the counterintuitive effect of decreasing annual average soil moisture (over the Ganges plain). Subsequently, we will explore the impact of irrigation on regional climate by conducting coupled land-atmosphere simulations.</p>

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