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Tobias Goecke and Ekaterina Machulskaya

Abstract

We present a detailed evaluation of the turbulence forecast product EDP (Eddy Dissipation Parameter) used at the Deutscher Wetterdienst (DWD). It is based on the turbulence parameterization scheme TURBDIFF which is operational within the ICON (Icosahedral Nonhydrostatic) numerical weather prediction model used operationally by DWD. For aviation purposes, the procedure provides the cubic root of the eddy dissipation rate ε 1/3 as an overall turbulence index. This quantity is a widely used measure for turbulence intensity as experienced by aircraft. The scheme includes additional sources of turbulent kinetic energy with particular relevance to aviation which are briefly introduced. These sources describe turbulence generation by the subgrid-scale action of wake eddies, mountain waves, convection as well as horizontal shear as found close to fronts or the jet stream. Furthermore, we introduce a post-processing, calibration to an empirical EDR distribution, and we demonstrate the potential as well as limitations of the final EDP-based turbulence forecast by considering several case studies of typical turbulence events. Finally, we reveal the forecasting capability of this product by verifying the model results against one year of aircraft in situ EDR measurements from commercial aircraft. We find that the forecasted EDP performs favorably when compared to the Ellrod index. In particular, the turbulence signal from deep convection, which is accounted for in the EDP product, is advantageous when spatial non-locality is allowed in the verification procedure.

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Chao Zhang, XiaoJing Jia, and Zhiping Wen

Abstract

This study investigated the increased impact of the spring (March-April-May) snow cover extent (SCE) over the western Tibetan Plateau (TP) (SSTP) to the Meiyu rainfall (June-July, JJ) over the Yangtze River valley (YRV) (MRYRV) after 1990s. The correlation between the MRYRV and SSTP is significantly increased from 1970-1992 (P1) to 1993-2015 (P2). In P1, the MRYRV-related SSTP anomalies locate southwest TP which cause a perturbation near the SWJ core and favor an eastward propagation in the form of a wave train. The wave train results in a southward shift of the SWJ over the ocean south of Japan in JJ and exerts a limited effect on the MRYRV. Differently, in P2, the MRYRV-related anomalous SSTP causes an anomalous cooling temperature and upper-level cyclonic system centered over the northwestern TP. The cyclonic system develops and extends eastward to the downstream region with time and reaches coastal East Asia in JJ. The anomalous westerly winds along its south flank cause an enhanced subtropical westerly jet (SWJ) which is accompanied by an anomalous lower-level air convergence and ascent motion near the YRV region, favoring enhanced MRYRV. In addition, the forecast experiments performed with empirical regression models illustrate that the prediction skill of the MRYRV variation is clearly increased in P2 with the additional forecast factor of the SSTP.

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H. A. Titley, H. L. Cloke, S. Harrigan, F. Pappenberger, C. Prudhomme, J. C. Robbins, E. M. Stephens, and E. Zsoter

Abstract

Knowledge of the key drivers of the severity of river flooding from tropical cyclones (TCs) is vital for emergency preparedness and disaster risk reduction activities. This global study examines landfalling TCs in the decade from 2010 to 2019, to identify those characteristics that influence whether a storm has an increased flood hazard. The highest positive correlations are found between flood severity and the total precipitation associated with the TC. Significant negative correlations are found between flood severity and the translation speed of the TC, indicating that slower moving storms, that rain over an area for longer, tend to have higher flood severity. Larger and more intense TCs increase the likelihood of having a larger area affected by severe flooding but not its duration or magnitude, and it is found that the fluvial flood hazard can be severe in all intensity categories of TC, including those of tropical storm strength. Catchment characteristics such as antecedent soil moisture and slope also play a role in modulating flood severity, and severe flooding is more likely in cases where multiple drivers are present. The improved knowledge of the key drivers of fluvial flooding in TCs can help to inform research priorities to help with flood early warning, such as increasing the focus on translation speed in model evaluation and impact-based forecasting.

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Robert G. Nystrom, Steven J. Greybush, Xingchao Chen, and Fuqing Zhang

Abstract

The tropical cyclone (TC) surface-exchange coefficients of enthalpy (C k) and momentum (C d) at high wind speeds have been notoriously challenging to estimate. This difficulty arises from many factors, including the difficulties in collecting observations within the turbulent TC boundary layer, and the complex coupled physical interactions between the TC boundary layer and ocean surface, which are challenging to accurately model. Motivated by recent studies highlighting the limited practical predictability of TC intensity as a result of uncertainty in the physical representation of the air-sea fluxes of momentum and enthalpy at high wind speeds, we investigate the potential to estimate the surface enthalpy and momentum exchange coefficients through ensemble data assimilation. Significant ensemble correlations between tangential wind, radial wind, and simulated infrared brightness temperatures with parameters controlling the enthalpy and momentum exchange coefficients suggest potential to use all-sky satellite and/or airborne radial velocity observations to estimate these unknown parameters. Using a series of observing system simulation experiments (OSSEs), simulated infrared brightness temperature observations, and a known truth, we demonstrate some potential for simultaneous state and parameter estimation with an ensemble-based data assimilation system to converge toward the correct known parameter values. In all OSSEs with either one or multiple unknown parameters, the initial parameter errors are reduced through simultaneous model state and parameter estimation. However, challenges still exist in converging to the precise true parameter values, as state errors during rapid intensification can project onto the parameter estimates.

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Maxime Turko, Marielle Gosset, Modeste Kacou, Christophe Bouvier, Nanee Chahinian, Aaron Boone, and Matias Alcoba

Abstract

Urban floods due to intense precipitation are a major problem in many tropical regions as in Africa. Rainfall measurement using microwave links from cellular communication networks has been proposed as a cost effective solution to monitor rainfall in these areas where the gauge network is scarce. The method consists in retrieving rainfall from the attenuation estimated along the commercial microwave links (CMLs) thanks to the power levels provided by an operator. In urban areas where the network is dense, rainfall can be estimated and mapped for hydrological prediction. Rainfall estimation from CMLs is subject to uncertainties. This paper analyzes the advantages and limitations of this rainfall data for a distributed hydrological model applied to an urban area. The case study is in West Africa in Ouagadougou where a hydrological model has been set up. The analysis is based on numerical simulations, using high resolution rain maps from a weather radar to emulate synthetic microwave links. Two sources of uncertainty in the rain estimation and on the simulated discharge are analyzed by simulations: i) the precision of the raw information provided by the operator and ii) the density and geometry of the network. A coarse precision (1 dB) in the signal provided by the operator can lead to substantial underestimation of rainfall and discharge, especially for links operating at low frequency (below 10 GHz) or short (less than 1 km). The density of the current mobile networks in urban areas is appropriate to analyze hydrological impact of tropical convective rainfall.

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Jeremiah O. Piersante, Kristen L. Rasmussen, Russ S. Schumacher, Angela K. Rowe, and Lynn A. McMurdie

Abstract

Subtropical South America (SSA) east of the Andes Mountains is a global hotspot for mesoscale convective systems (MCSs). Wide convective cores (WCCs) are typically embedded within mature MCSs, contribute over 40% of SSA’s warm-season rainfall, and are often associated with severe weather. Prior analysis of Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data identified WCCs in SSA and associated synoptic conditions during austral summer. As WCCs also occur during the austral spring, this study uses the 16-year TRMM PR dataset and ERA5 reanalysis to compare anomalies in environmental conditions between austral spring (SON) and summer (DJF) for the largest and smallest WCCs in SSA. During both seasons, large WCCs are associated with an anomalous mid-level trough that slowly crosses the Andes Mountains and a northerly South American low-level jet (SALLJ) over SSA, though the SON trough and SALLJ anomalies are stronger and located farther northeastward than in DJF. A synoptic pattern evolution resembling large WCC environments is illustrated through a multi-day case during the RELAMPAGO field campaign (10-13 November 2018). Unique high-temporal resolution soundings showed strong mid-level vertical wind shear associated with this event, induced by the juxtaposition of the northerly SALLJ and southerly near-surface flow. It is hypothesized that the Andes help create a quasi-stationary trough/ridge pattern such that favorable synoptic conditions for deep convection persist for multiple days. For the smallest WCCs, anomalously weaker synoptic-scale forcing was present compared to the largest events, especially for DJF, pointing to future work exploring MCS formation under weaker synoptic conditions.

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Youjia Zou and Xiangying Xi

Abstract

It is generally accepted that the El Niño-Southern Oscillation (ENSO) dominates interannual climate variability. Yet its genesis and maintenance mechanisms are still under intense debate with no scientific consensus. Some authors argued that the westerly winds originating over the equatorial Indian Ocean significantly enhanced and extended eastward in the western and central equatorial Pacific during El Niño events, thus advecting the warm pool eastward along the equator and causing SST anomalies. However, this assertion is unlikely to be quantitatively supported by observational data. Here we present detailed observational data and modeling evidence to demonstrate that the westerly winds remained little changein intensity in the western equatorial Pacific, with a wider zonal extent only during most El Niño events, and with a slight increase even if in the most pronounced 1997 El Niño. Instead, an eastward equatorial current near the equator has been observed and considered to play a significant role in shifting the eastern edge of the warm pool eastward, elevating SSTs in the central and eastern equatorial Pacific and giving rise to El Niño, with the interactions between the eastward warm pool and the upwelling in the eastern cold tongue ascertaining the amplitudes of SST anomalies.

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T. C. Johns, E. W. Blockley, and J. K. Ridley

Abstract

We present a coupled retrospective forecast (hindcast) study using the Met Office Global Coupled Model version 2 (GC2) in which we identify and mitigate causes of initialization shock that lead to rapid error growth in sea ice forecasts. Sea ice state variables and volume budget terms as a function of forecast lead time are evaluated relative to analyses from an uncoupled Met Office ocean-sea ice analysis system (FOAMv13). Two sources of initialization shock are highlighted and addressed, both of which are related to effective differences in physics between the analysis system and coupled forecast model. The primary shock to sea ice state variables arises from the use of a salinity-independent freezing temperature for sea water in GC2 as opposed to a salinity-dependent formulation in FOAMv13. A secondary effect arises from differences in the sea ice roughness and hence air-ice drag in the GC2 forecast model compared to the FOAMv13 analysis system. Generalizing from the findings of this study, we suggest that using non-native analyses as initial conditions for coupled Numerical Weather Prediction (NWP) studies will likely make them prone to initialization shock in some model components, to the detriment of forecast skill. To reduce the undesirable impacts of initialization shock on short-range forecast skill noted in this study we would therefore recommend the use of initial conditions (analyses) physically consistent with the native model components of the coupled forecast model, a native coupled analysis likely being the optimal initialization method.

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Jeremiah O. Piersante, Russ. S. Schumacher, and Kristen L. Rasmussen

Abstract

Ensemble forecasts using the WRF Model at 20-km grid spacing with varying parameterizations are used to investigate and compare precipitation and atmospheric profile forecast biases in North and South America. By verifying a 19-member ensemble against NCEP Stage IV precipitation analyses, it is shown that the cumulus parameterization (CP), in addition to precipitation amount and season, had the largest influence on precipitation forecast skill in North America during 2016-2017. Verification of an ensemble subset against operational radiosondes in North and South America finds that forecasts in both continents feature a substantial mid-level dry bias, particularly at 700 hPa, during the warm season. Case-by-case analysis suggests that large mid-level error is associated with mesoscale convective systems (MCSs) east of the high terrain and westerly subsident flow from the Rocky and Andes Mountains in North and South America. However, error in South America is consistently greater than North America. This is likely attributed to the complex terrain and higher average altitude of the Andes relative to the Rockies, which allow for a deeper low-level jet and long-lasting MCSs, both of which 20-km simulations struggle to resolve. In the wake of data availability from the RELAMPAGO field campaign, the authors hope that this work motivates further comparison of large precipitating systems in North and South America, given their high impact in both continents.

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Linda Bogerd, Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet

Abstract

Applications like drought monitoring and forecasting can profit from the global and near real-time availability of satellite-based precipitation estimates once their related uncertainties and challenges are identified and treated. To this end, this study evaluates the IMERG V06B Late Run precipitation product from the Global Precipitation Measurement mission (GPM), a multi-satellite product that combines space-based radar, passive microwave (PMW), and infrared (IR) data into gridded precipitation estimates. The evaluation is performed on the spatiotemporal resolution of IMERG (0.1° × 0.1°, 30 min) over the Netherlands over a five-year period. A gauge-adjusted radar precipitation product from the Royal Netherlands Meteorological Institute (KNMI) is used as reference, against which IMERG shows a large positive bias. To find the origin of this systematic overestimation, the data is divided into seasons, rainfall intensity ranges, echo top height (ETH) ranges, and categories based on the relative contributions of IR, morphing, and PMW data to the IMERG estimates. Furthermore, the specific radiometer is identified for each PMW-based estimate. IMERG’s detection performance improves with higher ETH and rainfall intensity, but the associated error and relative bias increase as well. Severe overestimation occurs during low-intensity rainfall events and is especially linked to PMW observations. All individual PMW instruments show the same pattern: overestimation of low-intensity events and underestimation of high-intensity events. IMERG misses a large fraction of shallow rainfall events, which is amplified when IR data is included. Space-based retrieval of shallow and low-intensity precipitation events should improve before IMERG can be implemented over the middle and high-latitudes.

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