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Mingze Ding
,
Zhehui Shen
,
Ruochen Huang
,
Ying Liu
, and
Hao Wu

Abstract

Evaluating the accuracy of various precipitation datasets over ungauged or even sparse-gauge areas is a challenging task. Cross-validation methods can evaluate three or more datasets based on the error independence from input data, without relying on ground reference. Here, the triple collocation (TC) method is employed to evaluate multi-source precipitation datasets: gauge-based CGDPA, model-based ERA5, and satellite-derived IMERG-Early, IMERG-Late, GSMaP-NRT, and GSMaP-MVK over the Tibetan Plateau (TP). TC-based results show that ERA5 has better performances than satellite-only precipitation products over mountainous regions with complex terrains. For purely satellite-derived products, IMERG products outperform GSMaP products. Considering the potential existence of error dependency among input datasets, caution should be exercised. Thus, it is necessary to introduce an alternative cross-validation method (generalized Three-Cornered Hat) and explore the applicability of cross-validation from the perspective of error independence. We found that cross-validation methods have high applicability in most TP regions with sparse-gauge density (accounting for about 80.1% of the total area). Additionally, we conducted simulation experiments to discuss the applicability and robustness of TC. The simulation results substantiated that cross-validation can serve as a robust evaluation method over sparse-gauge regions. Although it is generally known that the cross-validation methods can be served in sparse-gauge regions, the application condition of different evaluation methods for precipitation products is identified quantitatively in TP now.

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Arthur Coquereau
,
Florian Sévellec
,
Thierry Huck
,
Joël J.-M. Hirschi
, and
Antoine Hochet

Abstract

As well as having an impact on the background state of the climate, global warming due to human activities could affect its natural oscillations and internal variability. In this study, we use four initial-condition ensembles from the CMIP6 framework to investigate the potential evolution of internal climate variability under different warming pathways for the 21st century. Our results suggest significant changes in natural climate variability, and point to two distinct regimes driving these changes. First, a decrease of internal variability of surface air temperature at high latitudes and all frequencies, associated with a poleward shift and the gradual disappearance of sea-ice edges, which we show to be an important component of internal variability. Second, an intensification of the interannual variability of surface air temperature and precipitation at low latitudes, which appears to be associated with the El Niño–Southern Oscillation (ENSO). This second regime is particularly alarming because it may contribute to making the climate more unstable and less predictable, with a significant impact on human societies and ecosystems.

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Wojciech W. Grabowski
,
Yongjoon Kim
, and
Seong Soo Yum

Abstract

Numerical simulations of turbulent moist Rayleigh–Bénard convection driving CCN activation and droplet growth in the laboratory Pi chamber are discussed. Supersaturation fluctuations come from isobaric mixing of warm and humid air rising from the lower boundary with colder air featuring lower water vapor concentrations descending from the upper boundary. Lagrangian particle-based microphysics is used to represent growth of haze CCN and cloud droplets with kinetic, solute, and surface tension effects included. Dry CCN spectra in the range between 2 to 200 nm radius from field observations are considered. Increasing the total CCN concentration from pristine to polluted conditions results in the increase of the droplet concentration and reductions of the mean droplet radius and spectral width. These are in agreement with Pi chamber observations and numerical simulations, as well as with numerous past studies of CCN cloud-base activation in natural clouds. The key result is that a relatively small fraction of the available CCN is activated in the Pi chamber fluctuating supersaturations, from about a half in pristine case to only a tenth in the polluted case. The activation fraction as a function of the dry CCN radius is similar in all simulations, close to zero at the CCN small end, increasing to a maximum at CCN radius around 50 nm, and decreasing to close to zero at the large CCN end. This is explained as too small supersaturations to activate small CCN as in natural clouds, and insufficient time to allow large CCN reaching the critical radius.

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Thomas C. Pagano
,
Barbara Casati
,
Stephanie Landman
,
Nicholas Loveday
,
Robert Taggart
,
Elizabeth E. Ebert
,
Mohammadreza Khanarmuei
,
Tara L. Jensen
,
Marion Mittermaier
,
Helen Roberts
,
Steve Willington
,
Nigel Roberts
,
Mike Sowko
,
Gordon Strassberg
,
Charles Kluepfel
,
Timothy A. Bullock
,
David D. Turner
,
Florian Pappenberger
,
Neal Osborne
, and
Chris Noble

Abstract

Operational agencies face significant challenges related to the verification and evaluation of weather forecasts. These challenges were investigated in a series of online workshops and polls engaging operational personnel from six countries. Five key themes emerged: inadequate verification approaches for both existing and emerging products; incomplete and uncertain observations; difficulties in accurately capturing users’ real-world experiences using simplified metrics; poor communication and understanding of forecasts and complex verification information; and institutional factors such as limited resources, evolving meteorologist roles, and concerns over reputational damage. We identify nearly 50 operationally relevant scientific questions and suggest calls to action. Addressing these needs includes designing forecast systems with verification as a central consideration, enhancing the availability of observations, and developing and adopting community software systems. Additionally, we propose the establishment of an international community comprising environmental and social science researchers, statisticians, verification practitioners, and users to provide sustained support for this collective endeavor.

Open access
Eun-Pa Lim
,
Harry H. Hendon
,
Amy H. Butler
,
David W. J. Thompson
,
Zachary D. Lawrence
,
Adam A. Scaife
,
Theodore G. Shepherd
,
Inna Polichtchouk
,
Hisashi Nakamura
,
Chiaki Kobayashi
,
Ruth Comer
,
Lawrence Coy
,
Andrew Dowdy
,
Rene D. Garreaud
,
Paul A. Newman
, and
Guomin Wang
Open access
Gabor Vali
and
Russell C. Schnell

Abstract

An overview is given of the path of research that led from asking how hailstones originate to the discovery that ice nucleation can be initiated by bacteria and other microorganisms at temperatures as high as −2°C. The major steps along that path were finding exceptionally effective ice nucleators in soils with a high content of decayed vegetative matter, then in decaying tree leaves, and then in plankton-laden ocean water. Eventually, it was shown that Pseudomonas syringae bacteria were responsible for most of the observed activity. That identification coincided with the demonstration that the same bacteria cause frost damage on plants. Ice nucleation by bacteria meant an unexpected turn in the understanding of ice nucleation and of ice formation in the atmosphere. Subsequent research confirmed the unique effectiveness of ice nucleating particles (INP) of biological origin, referred to as bio-INPs, so that bio-INPs are now considered to be important elements of lower-tropospheric cloud processes. Nonetheless, some of the questions which originally motivated the research are still unresolved, so that revisiting the early work may be helpful to current endeavors. Part I of this manuscript summarizes how the discovery progressed. Part II (Schnell and Vali) shows the relationship between bio-INPs in soils and in precipitation with climate and other findings. The online supplemental material contains a bibliography of recent work about bio-INPs.

Open access
Verónica Martín-Gómez
,
Belén Rodríguez-Fonseca
,
Irene Polo
, and
Marta Martín-Rey

Abstract

In the last decades, many efforts have been made to understand how different tropical oceanic basins are able to impact El Niño Southern Oscillation (ENSO). However, the collective connectivity among the tropical oceans and their associated influence on ENSO is less understood. Using a complex network methodology, the degree of collective connectivity among the tropical oceans is analyzed focusing on the detection of periods when the tropical basins collectively interact and Atlantic and Indian basins influence the equatorial Pacific sea surface temperatures (SST). The background state for the periods of strong collective connectivity is also investigated.

Our results show a marked multidecadal variability in the tropical interbasin connection, with periods of stronger and weaker collective connectivity. These changes seem to be modulated by changes in the North Atlantic ocean mean state a decade in advance. In particular, strong connectivity occurs in periods with colder than average tropical north Atlantic surface ocean. Associated with this cooling an anomalous convergence of the vertical integral of total energy flux (VIEF) takes place over the tropical north-west Atlantic, associated with anomalous divergence of VIEF over the equatorial eastern Pacific. In turn, an anomalous zonal surface pressure gradient over the tropical Pacific weakens the trades over the western equatorial Pacific. Consequently, a shallower thermocline emerges over the western equatorial Pacific, which can enhance thermocline feedbacks, the triggering of ENSO events, and therefore, ENSO variability. By construction, our results put forward opposite conditions for periods of weak tropical basins connectivity. These results have important implications for seasonal to decadal predictions.

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Xavier Chartrand
,
Louis-Philippe Nadeau
, and
Antoine Venaille

Abstract

The Quasi-Biennial Oscillation (QBO) is understood to result from wave-mean-flow interactions, but the reasons for its relative stability remain a subject of ongoing debate. In addition, consensus has yet to be reached regarding the respective roles of different equatorial wave types in shaping the QBO’s characteristics. Here we employ Holton-Lindzen-Plumb’s quasilinear model to shed light on the robustness of periodic behavior in the presence of multiple wave forcings. A comprehensive examination of the various dynamical regimes in this model reveals that increased vertical wave propagation at higher altitudes favors periodicity. In the case of single standing wave forcing, enhanced vertical propagation is controlled by the wave attenuation length scale. The occurrence of non-periodic states at high forcing amplitudes is explained by the excitation of high vertical unstable modes. Increasing the attenuation length scale prevents the emergence of such modes. When multiple wave forcing is considered, the mean flow generated by a dominant primary wave facilitates greater vertical propagation of a perturbation wave. Raising the altitude where most of the wave damping occurs favors periodicity by preventing the development of secondary jets responsible for the aperiodic behavior. This mechanism underscores the potential role of internal gravity waves in supporting the periodicity of a QBO primarily driven by planetary waves.

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Zhehui Shen
,
Bin Yong
, and
Hao Wu

Abstract

Climatological calibration algorithm (CCA) and satellite–gauge combination (SG) are two official bias adjustments for satellite precipitation estimates (SPE) in the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA). The CCA is designed for the near-real-time SPEs, while the SG procedure is a final step to merge pure SPEs with gauge observations. This study explored the impacts of CCA and SG on the systematic and random errors of TMPA SPEs. The errors of TMPA version-7 near-real-time products before and after CCA (RT_UC, RT_C), and the research product TMPA 3B42 (V7), were decomposed into systematic and random components, benchmarked by the China Gauge-based Daily Precipitation Analysis (CGDPA). After being calibrated by CCA, RT_C reduced the systematic errors relative to RT_UC over the Chinese mainland, except in the Tibetan Plateau and Tianshan Mountains. However, CCA did not aid in reducing random errors; instead, it even exacerbated the random errors. On the other hand, the SG merging is more effective in reducing systematic errors of SPEs than CCA calibration because of the direct inclusion of simultaneous gauge data from the Global Precipitation Climatology Centre (GPCC). We also found that SG merging reduced the random errors of pure SPEs over regions with relatively higher elevations. Despite lower random errors in V7 over the complex terrain region, the SG unfavorably increased the random errors over southeastern China. The results reported here may offer valuable insights into the effects of CCA and SG techniques drawn from TMPA, with the potential to advance the development of bias-adjusting algorithms for SPEs in the future.

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Ming Cai
,
Xiaoming Hu
,
Jie Sun
,
Feng Ding
, and
Jing Feng

Abstract

This paper introduces a climate feedback kernel, referred to as the “energy gain kernel” (EGK). EGK allows for separating the net longwave radiative energy perturbations given by a Planck feedback matrix explicitly into thermal energy emission perturbations of individual layers, and thermal radiative energy flux convergence perturbations at individual layers resulting from the coupled atmosphere-surface temperature changes in response to the unit forcing in individual layers. The former is represented by the diagonal matrix of a Planck feedback matrix and the latter by EGK. Elements of EGK are all positive, representing amplified energy perturbations at a layer where forcing is imposed and energy gained at other layers, both of which are achieved through radiative thermal coupling within an atmosphere-surface column.

Applying EGK to input energy perturbations, whether external or internal due to responses of non-temperature feedback processes to external energy perturbations, such as water vapor and albedo feedbacks, yields their total energy perturbations amplified through radiative thermal coupling within an atmosphere-surface column.

As the strength of EGK depends exclusively on climate mean states, it offers a solution for effectively and objectively separating control climate state information from climate perturbations for climate feedback studies. Given that an EGK comprises critical climate mean state information on mean temperature, water vapor, clouds, and surface pressure, we envision that the diversity of EGK across different climate models could provide insight into the inquiry of why, under the same anthropogenic greenhouse gas increase scenario, different models yield varying degrees of global mean surface warming.

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