Assimilation of All-sky Geostationary Satellite Infrared Radiances for Convection-Permitting Initialization and Prediction of Hurricane Joaquin(2015)

Intensity forecasting is one of the most challenging aspects of tropical cyclone(TC) forecasting. This work examines the impact of assimilating high-resolution all-sky infrared radiance observations from geostationary satellite GOES-13 on the convection-permitting initialization and prediction of Hurricane Joaquin(2015) with an ensemble Kalman filter(EnKF)based on the Weather Research and Forecasting(WRF) model. Given that almost all operational global and regional models struggled to capture Hurricane Joaquin(2015)'s intensity, this study examines the potential in improving Joaquin's prediction when assimilating all-sky infrared radiances from GOES-13's water vapor channel. It is demonstrated that, after a few 3-hour cycles assimilating all-sky radiance, the WRF model was able to forecast reasonably well Joaquin's intensity,including its rapid intensification(RI). The improvement was largely due to a more realistic initial hurricane structure with a stronger, warmer, and more compact inner-core. Ensemble forecasts were used to further explore the important physical mechanisms driving the hurricane's RI. Results showed that the RI forecasts were greatly impacted by the initial inner-core vortex structure.

Improving the Analyses and Forecasts of a Tropical Squall Line Using Upper Tropospheric Infrared Satellite Observations

The advent of modern geostationary satellite infrared radiance observations has noticeably improved numerical weather forecasts and analyses.However,compared to midlatitude weather systems and tropical cyclones,research into using infrared radiance observations for numerically predicting and analyzing tropical mesoscale convective systems remain mostly fallow.Since tropical mesoscale convective systems play a crucial role in regional and global weather,this deficit should be addressed.This study is the first of its kind to examine the potential impacts of assimilating all-sky upper tropospheric infrared radiance observations on the prediction of a tropical squall line.Even though these all-sky infrared radiance observations are not directly affected by lower-tropospheric winds,the high-frequency assimilation of these all-sky infrared radiance observations improved the analyses of the tropical squall line’s outflow position.Aside from that,the assimilation of all-sky infrared radiance observations improved the analyses and prediction of the squall line’s cloud field.Finally,reducing the frequency of assimilating these all-sky infrared radiance observations weakened these improvements to the analyzed outflow position,as well as the analyses and predictions of cloud fields.

Scale-dependent Regional Climate Predictability over North America Inferred from CMIP3 and CMIP5 Ensemble Simulations

Through the analysis of ensembles of coupled model simulations and projections collected from CMIP3 and CMIP5, we demonstrate that a fundamental spatial scale limit might exist below which useful additional refinement of climate model predictions and projections may not be possible. That limit varies among climate variables and from region to region. We show that the uncertainty（noise） in surface temperature predictions（represented by the spread among an ensemble of global climate model simulations） generally exceeds the ensemble mean（signal） at horizontal scales below 1000 km throughout North America, implying poor predictability at those scales. More limited skill is shown for the predictability of regional precipitation. The ensemble spread in this case tends to exceed or equal the ensemble mean for scales below 2000 km. These findings highlight the challenges in predicting regionally specific future climate anomalies, especially for hydroclimatic impacts such as drought and wetness.

Correlation Structures between Satellite All-Sky Infrared Brightness Temperatures and the Atmospheric State at Storm Scales

This study explores the structures of the correlations between infrared(IR)brightness temperatures(BTs)from the three water vapor channels of the Advanced Baseline Imager(ABI)onboard the GOES-16 satellite and the atmospheric state.Ensemble-based data assimilation techniques such as the ensemble Kalman filter(EnKF)rely on correlations to propagate innovations of BTs to increments of model state variables.Because the three water vapor channels are sensitive to moisture in different layers of the troposphere,the heights of the strongest correlations between these channels and moisture in clear-sky regions are closely related to the peaks of their respective weighting functions.In cloudy regions,the strongest correlations appear at the cloud tops of deep clouds,and ice hydrometeors generally have stronger correlations with BT than liquid hydrometeors.The magnitudes of the correlations decrease from the peak value in a column with both vertical and horizontal distance.Just how the correlations decrease depend on both the cloud scenes and the cloud structures,as well as the model variables.Horizontal correlations between BTs and moisture,as well as hydrometeors,in fully cloudy regions decrease to almost 0 at about 30 km.The horizontal correlations with atmospheric state variables in clear-sky regions are broader,maintaining non-zero values out to~100 km.The results in this study provide information on the proper choice of cut-off radii in horizontal and vertical localization schemes for the assimilation of BTs.They also provide insights on the most efficient and effective use of the different water vapor channels.

Variational Quality Control of Non-Gaussian Innovations in the GRAPES m3DVAR System: Mass Field Evaluation of Assimilation Experiments

The existence of outliers can seriously influence the analysis of variational data assimilation.Quality control allows us to effectively eliminate or absorb these outliers to produce better analysis fields.In particular,variational quality control(VarQC) can process gray zone outliers and is thus broadly used in variational data assimilation systems.In this study,governing equations are derived for two VarQC algorithms that utilize different contaminated Gaussian distributions(CGDs): Gaussian plus flat distribution and Huber norm distribution.As such,these VarQC algorithms can handle outliers that have non-Gaussian innovations.Then,these VarQC algorithms are implemented in the Global/Regional Assimilation and PrEdiction System(GRAPES) model-level three-dimensional variational data assimilation(m3 DVAR) system.Tests using artificial observations indicate that the VarQC method using the Huber distribution has stronger robustness for including outliers to improve posterior analysis than the VarQC method using the Gaussian plus flat distribution.Furthermore,real observation experiments show that the distribution of observation analysis weights conform well with theory,indicating that the application of VarQC is effective in the GRAPES m3 DVAR system.Subsequent case study and longperiod data assimilation experiments show that the spatial distribution and amplitude of the observation analysis weights are related to the analysis increments of the mass field(geopotential height and temperature).Compared to the control experiment,VarQC experiments have noticeably better posterior mass fields.Finally,the VarQC method using the Huber distribution is superior to the VarQC method using the Gaussian plus flat distribution,especially at the middle and lower levels.

Correction to:Correlation Structures between Satellite All-Sky Infrared Brightness Temperatures and the Atmospheric State at Storm Scales

The article“Correlation Structures between Satellite All-Sky Infrared Brightness Temperatures and the Atmospheric State at Storm Scales”,written by Yunji ZHANG,Eugene E.CLOTHIAUX,and David J.STENSRUD was originally pub-lished electronically on the publisher’s internet portal on 30 of April 2021 without open access.With the author(s)’decision to opt for Open Choice,the copyright of the article changed on 26 of October 2021 to©The Author(s),2021 and the article is forthwith distributed under a Creative Commons Attribution 4.0 International License,which permits use,sharing,adapta-tion,distribution and reproduction in any medium or format,as long as you give appropriate credit to the original author(s)and the source,provide a link to the Creative Commons licence,and indicate if changes were made.The images or other third party material in this article are included in the article’s Creative Commons licence,unless indicated otherwise in a credit line to the material.If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use,you will need to obtain permission directly from the copyright holder.To view a copy of this licence,visit http://creativecommons.org/licenses/by/4.0.The original article has been corrected.

Modeling Arctic Boundary Layer Cloud Streets at Grey-zone Resolutions

To better understand how model resolution affects the formation of Arctic boundary layer clouds,we investigated the influence of grid spacing on simulating cloud streets that occurred near Utqiaġvik(formerly Barrow),Alaska,on 2 May 2013 and were observed by MODIS(the Moderate Resolution Imaging Spectroradiometer).The Weather Research and Forecasting model was used to simulate the clouds using nested domains with increasingly fine resolution ranging from a horizontal grid spacing of 27 km in the boundary-layer-parameterized mesoscale domain to a grid spacing of 0.111 km in the large-eddy-permitting domain.We investigated the model-simulated mesoscale environment,horizontal and vertical cloud structures,boundary layer stability,and cloud properties,all of which were subsequently used to interpret the observed roll-cloud case.Increasing model resolution led to a transition from a more buoyant boundary layer to a more shear-driven turbulent boundary layer.The clouds were stratiform-like in the mesoscale domain,but as the model resolution increased,roll-like structures,aligned along the wind field,appeared with ever smaller wavelengths.A stronger vertical water vapor gradient occurred above the cloud layers with decreasing grid spacing.With fixed model grid spacing at 0.333 km,changing the model configuration from a boundary layer parameterization to a large-eddy-permitting scheme produced a more shear-driven and less unstable environment,a stronger vertical water vapor gradient below the cloud layers,and the wavelengths of the rolls decreased slightly.In this study,only the large-eddy-permitting simulation with gird spacing of 0.111 km was sufficient to model the observed roll clouds.

Daily extreme precipitation and trends over China

Based on daily precipitation data of more than 2000 Chinese stations and more than 50 yr, we constructed time series of extreme precipitation based on six different indices for each station: annual and summer maximum(top-1) precipitation,accumulated amount of 10 precipitation maxima(annual, summer; top-10), and total annual and summer precipitation.Furthermore, we constructed the time series of the total number of stations based on the total number of stations with top-1 and top-10 annual extreme precipitation for the whole data period, the whole country, and six subregions, respectively. Analysis of these time series indicate three regions with distinct trends of extreme precipitation:(1) a positive trend region in Southeast China,(2) a positive trend region in Northwest China, and(3) a negative trend region in North China. Increasing(decreasing)ratios of 10–30% or even >30% were observed in these three regions. The national total number of stations with top-1 and top-10 precipitation extremes increased respectively by 2.4 and 15 stations per decade on average but with great inter-annual variations.There have been three periods with highly frequent precipitation extremes since 1960:(1) early 1960 s,(2) middle and late 1990 s,and(3) early 21 st century. There are significant regional differences in trends of regional total number of stations with top-1 and top-10 precipitation. The most significant increase was observed over Northwest China. During the same period, there are significant changes in the atmospheric variables that favor the decrease of extreme precipitation over North China: an increase in the geopotential height over North China and its upstream regions, a decrease in the low-level meridional wind from South China coast to North China, and the corresponding low moisture content in North China. The extreme precipitation values with a50-year empirical return period are 400–600 mm at the South China coastal regions and gradually decrease to less than 50 mm in Northwest China. The mean increase rate in comparison with 20-year empirical return levels is 6.8%. The historical maximum precipitation is more than twice the 50-year return levels.

中国日极端降水和趋势

利用中国2000多站50年以上的日降水资料,提取各站6个极端降水指数,即历年最大值(top-1)、历年10个最大值(top-10)累积量、历年总降水量、历年夏季top-1、历年夏季top-10累积量、历年夏季总降水量,分别形成各站各极端降水指数时间序列.统计了历年全国及6个子区域整个研究资料时段内出现top-1和top-10值的总站次,分别形成历年全国及6个子区域极端降水总站次时间序列.各极端降水指数时间序列的趋势分析表明,中国各站top-1和top-10累积量时间序列趋势分布存在较为一致的3个明显趋势区域,即中国东南正趋势区、西北正趋势区和华北负趋势区,但各时间序列的趋势分布区域特征和趋势幅度增减程度不尽相同;正负趋势明显地区的大多数站点趋势增(减)幅度比(趋势幅度与平均值的比值)达10~30%,部分站点达30%以上.top-1和top-10降水全国年总站次时间序列表明了一致的线性增加趋势,平均每十年分别增加2.4站和15站,但年际差别较大;极端降水年总站次表现为三段极端降水多发期,分别出现在20世纪60年代初、90年代中后期和21世纪初,6个区域极端降水年总站次趋势特征与全国年总站次不尽相同,极端降水全国年总站次出现较多的年份在区域上表现不一样.与降水有关的环流形势要素的时间序列趋势分析表明,华北及上游蒙古高原地区呈现明显的位势高度增加趋势,而低层从中国南部沿海地区到华北地区呈现一条南风风速减弱的趋势带和华北地区水汽含量减少的趋势区,这些趋势特征有利于华北地区极端降水的减少.经验回归水平分析表明,50年一遇重现水平从南部沿海的400~600mm减少到西北地区的50mm以下,相比20年一遇重现水平提升率平均达6.8%,但比降水最大值可小一倍以上.

Rising future tropical cyclone-induced extreme winds in the Mekong River Basin

热带气旋引起的极端风速对社会的影响使得它成为湄公河流域的最大隐患之一.西北太平洋是影响湄公河流域热带气旋的重要源地之一.从20世纪70年代开始,在越南沿岸登陆的热带气旋强度没有呈现明显的变化趋势.然而,气候模式模拟预测显示西北太平洋的热带气旋强度将会在21世纪内增强,届时将很可能影响到湄公河流域.目前为止,未来湄公河流域的热带气旋活动引起的极端风速将会如何变化尚不明确.因此,本文采用了1个基于海洋大气耦合模型的降尺度技术和5个全球气候模式的输出结果对未来湄公河流域的热带气旋活动进行了模拟.结果显示,相比于1981~2000年,在RCP8.5的情境下,2081~2100年湄公河流域热带气旋的最大风速的重现期将显著缩短.这意味着该区域的热带气旋强度将明显增强.此结果预示着未来热带气旋活动将增加相关灾害的发生,并且这可能会在地区乃至全球范围威胁可持续发展、影响粮食供应和加剧冲突.