ALBERT

Description: A unique automated planetary boundary layer (PBL) retrieval algorithm is proposed as a common cross-platform method for use with commercially available ceilometers for implementation under the redesigned U.S. Environmental Protection Agency Photochemical Assessment Monitoring Stations program. This algorithm addresses instrument signal quality and screens for precipitation and cloud layers before the implementation of the retrieval methodology using the Haar wavelet covariance transform method. Layer attribution for the PBL height is supported with the use of continuation and time-tracking parameters, and uncertainties are calculated for individual PBL height retrievals. Commercial ceilometer retrievals are tested against radiosonde PBL height and cloud-base height during morning and late afternoon transition times, critical to air quality model prediction and when retrieval algorithms struggle to identify PBL heights. A total of 58 radiosonde profiles were used and retrievals for nocturnal stable layers, residual layers and mixing layers were assessed. Overall good agreement was found for all comparisons with one system showing limitations for the cases of nighttime surface stable layers and daytime mixing layer. It is recommended that nighttime shallow stable layer retrievals be performed with a recommended minimum height or with additional verification. Retrievals of residual layer heights and mixing layer comparisons revealed overall good correlations to radiosonde heights (correlation coefficients, r2, ranging from 0.89 – 0.96 and bias ranging from ~ -131 to +63 m, and r2 from 0.88 – 0.97 and bias from -119 to +101 m, respectively).

Description: The dynamic origin of the interannual variability of West China autumn rainfall (WCAR), a special weather/climate phenomenon over western-central China in September and October, was investigated via observational diagnosis and numerical simulations. Here we found that the interannual variability of WCAR is closely related to the local horizontal trough, which is passively induced by two lower-level anticyclonic (high pressure) anomalies over East Asia. The anticyclonic anomaly over the south is a Gill-type response to the central and eastern Pacific diabatic cooling, while that over the north is part of the mid- to high-latitude barotropic Rossby wave train, which could be induced by either the thermal forcing of the central and eastern Pacific Ocean sea surface temperature (SST) cooling or that of the subtropical northern Atlantic Ocean SST warming. The quasi-barotropic high pressure anomaly over East Asia acts as an “invisible mountain” that steers the low-level anomalous southwesterly into a southeasterly and hinders the water vapor going farther to the north, leading to enhanced WCAR. However, the real mountain ranges in the region (the Qinglin and Ba Mountains) have no essential impact on the formation and interannual variability of WCAR.

Description: Summer monsoon rainfall supplies over 55% of annual precipitation to global monsoon regions. As shown by more than 70% of models, including 30 models from CMIP5 and 30 models from CMIP6 under high-emission scenarios, North American (NAM) monsoon rainfall decreases in a warmer climate, in sharp contrast to the robust increase in Asian-African monsoon rainfall. A hierarchy of model experiments are analyzed to understand the mechanism for the reduced NAM monsoon rainfall in this study. Modeling evidence shows that the reduction of NAM monsoon rainfall is related to both direct radiative forcing of increased CO2 concentration and SST warming, manifested as fast and slow responses to abrupt CO2 quadrupling in CGCMs. A cyclone anomaly forms over the Eurasian-African continent due to enhanced land-sea thermal contrast under increased CO2 concentration, and this leads to a subsidence anomaly on its western flank, suppressing the NAM monsoon rainfall. The SST warming acts to further reduce the rainfall over the NAM monsoon region, and the El Niño-like SST warming pattern with enhanced SST warming over the equatorial Pacific plays a key role in suppressing NAM rainfall, whereas relative cooling over the subtropical North Atlantic has no contribution. A positive feedback between monsoon precipitation and atmospheric circulation helps to amplify the responses of monsoon rainfall.

Description: The assimilation of L-band surface brightness temperature (Tb) into the land surface model (LSM) component of a numerical weather prediction (NWP) system is generally expected to improve the quality of summertime 2-m air temperature (T2m) forecasts during water-limited surface conditions. However, recent retrospective results from the European Centre for Medium-Range Weather Forecasts (ECMWF) suggest that the assimilation of L-band Tb from the European Space Agency’s (ESA) Soil Moisture Ocean Salinity (SMOS) mission may, under certain circumstances, degrade the accuracy of growing-season 24-h T2m forecasts within the central United States. To diagnose the source of this degradation, we evaluate ECMWF soil moisture (SM) and evapotranspiration (ET) forecasts using both in situ and remote sensing resources. Results demonstrate that the assimilation of SMOS Tb broadly improves the ECMWF SM analysis in the central United States while simultaneously degrading the quality of 24-h ET forecasts. Based on a recently derived map of true global SM–ET coupling and a synthetic fraternal twin data assimilation experiment, we argue that the spatial and temporal characteristics of ECMWF SM analyses and ET forecast errors are consistent with the hypothesis that the ECMWF LSM overcouples SM and ET and, as a result, is unable to effectively convert an improved SM analysis into enhanced ET and T2m forecasts. We demonstrate that this overcoupling is likely linked to the systematic underestimation of root-zone soil water storage capacity by LSMs within the U.S. Corn Belt region.

Description: Recent advances in global ocean prediction systems are fostered by the needs of accurate representation of mesoscale processes. The day-by-day realistic representation of its variability is hampered by the scarcity of observations as well as the capability of assimilation systems to correct the ocean states at the same scale. This work extends a 3dvar system designed for oceanic applications, to cope with global eddy-resolving grid and dense observational datasets in a hybridly parallelized environment. The efficiency of the parallelization is assessed in term of both scalability and accuracy. The scalability is favoured by a weak-constrained formulation of the continuity requirement among the artificial boundaries implied by the domain decomposition. The formulation forces possible boundary discontinuities to be less than a prescribed error, and minimizes the parallel communication compared to standard methods. Theoretically, the exact solution is recovered by decreasing the boundary error towards zero. Practically, it is shown that the accuracy increases until a lower bound arises, due to the presence of the mesh and the finite accuracy of the minimizer. A twin experiment has been set up to estimate the benefit of employing an eddy-resolving grid within the assimilation step compared to an eddy-permitting one, while keeping the eddy-resolving grid within the forecast step. It is shown that the use of coarser grid for data assimilation does not allow an optimal exploitation of the present remote sensing observation network. A global decrease of about 15% in the error statistics is found when assimilating dense surface observations, while no significant improvement is seen for sparser observations (insitu profilers).

Description: Heat stress caused by high air temperature and high humidity is a serious health concern for urban residents. Mobile measurement of these two parameters can complement weather station observations because of its ability to capture data at fine spatial scales and in places where people live and work. In this paper, we describe a smart temperature and humidity sensor (Smart-T) for use on bicycles to characterize intracity variations in human thermal conditions. The sensor has several key characteristics of internet of things (IoT) technology, including lightweight, low cost, low power consumption, ability to communicate and geolocate the data (via the cyclist’s smartphone), and the potential to be deployed in large quantities. The sensor has a reproducibility of 0.03°–0.05°C for temperature and of 0.18%–0.33% for relative humidity (one standard deviation of variation among multiple units). The time constant with a complete radiation shelter and moving at a normal cycling speed is 9.7 and 18.5 s for temperature and humidity, respectively, corresponding to a spatial resolution of 40 and 70 m. Measurements were made with the sensor on street transects in Nanjing, China. Results show that increasing vegetation fraction causes reduction in both air temperature and absolute humidity and that increasing impervious surface fraction has the opposite effect.

Description: Buoy observations from a 1999 Gulf of Mexico field program (GOM99) are used to investigate the relationships among friction velocity u*, wind speed U, and amount of swell present. A U–u*sea parameterization is developed for the case of pure wind sea (denoted by u*sea), which is linear in U over the range of available winds (2–16 m s−1). The curve shows no sign of an inflection point near 7–8 m s−1 as suggested in a 2012 paper by Andreas et al. on the basis of a transition from smooth to rough flow. When observations containing more than minimal swell energy are included, a different U–u* equation for U 〈 8 m s−1 is found, which would intersect the pure wind-sea curve about 7–8 m s−1. These two relationships yield a bilinear curve similar to Andreas et al. with an apparent inflection near 7–8 m s−1. The absence of the inflection in the GOM99 experiment pure wind-sea curve and the similarity of the GOM99 swell-dominated low wind speed to Andreas et al.’s low wind speed relationship suggest that the inflection may be due to the effect of swell and not a flow transition. Swell heights in the range of only 25–50 cm may be sufficient to impact stress at low wind speeds.

Description: Concentrated poleward flows near the eastern boundaries between 2- and 4-km depth have been observed repeatedly, particularly in the Southern Hemisphere. These deep eastern boundary currents (DEBCs) play an important role in setting the large-scale tracer distribution and have nonnegligible contribution to global transports of mass, heat, and tracers, but their dynamics are not well understood. In this paper, we first demonstrate the significant role of DEBCs in the southeastern Atlantic, Indian, and Pacific Oceans, using the Southern Ocean State Estimate (SOSE) data assimilating product, and using high-resolution regional general circulation model configurations. The vorticity balances of these DEBCs reveal that, over most of the width of such currents, they are in an interior-like vorticity budget, with the meridional advection of planetary vorticity βυ and vortex stretching fwz being the largest two terms, and with contributions of nonlinearity and friction that are of smaller spatial scale. The stretching is shown, using a temperature budget, to be largely forced by resolved or parameterized eddy temperature transport. Strongly decaying signals from the eastern boundary in friction and stretching form the dominant balance in a sublayer close to the eastern boundary. The temporal variability of DEBCs is then examined, to help to interpret observations that tend to be sporadic in both time and space. The probability distribution functions of northward velocity in DEBC regions are broad, implying that flow reversals are common. Although the regions of the simulated DEBCs are generally local minima of eddy kinetic energy, they are still constantly releasing westward-propagating Rossby waves.

Description: Global numerical weather prediction (NWP) models have begun to resolve the mesoscale k−5/3 range of the energy spectrum, which is known to impose an inherently finite range of deterministic predictability per se as errors develop more rapidly on these scales than on the larger scales. However, the dynamics of these errors under the influence of the synoptic-scale k−3 range is little studied. Within a perfect-model context, the present work examines the error growth behavior under such a hybrid spectrum in Lorenz’s original model of 1969, and in a series of identical-twin perturbation experiments using an idealized two-dimensional barotropic turbulence model at a range of resolutions. With the typical resolution of today’s global NWP ensembles, error growth remains largely uniform across scales. The theoretically expected fast error growth characteristic of a k−5/3 spectrum is seen to be largely suppressed in the first decade of the mesoscale range by the synoptic-scale k−3 range. However, it emerges once models become fully able to resolve features on something like a 20-km scale, which corresponds to a grid resolution on the order of a few kilometers.

Description: Dust is the major aerosol type over the Tibetan Plateau (TP), and the TP plays an important role in forming the spring dust belt across the Northern Hemisphere in the upper troposphere. Estimated spring dust mass flux (DMF) showed a significant declining trend over the TP during 2007–19. The total spring DMF across the TP (TDMFTP) was mainly affected by DMFs over the Tarim Basin, while the spring DMF across the TP in the midtroposphere was also connected with DMFs over the northwest Indian Peninsula and central Asia. Interannual variability of spring TDMFTP was strongly correlated with the North Atlantic winter sea surface temperature (SST) tripole. A cold preceding winter induced by the North Atlantic winter SST tripole over midlatitude Eurasia promotes dust activities in the subsequent spring. The North Atlantic winter SST tripole anomalies persist into the subsequent spring and induce a corresponding atmosphere response. Enhanced atmospheric baroclinicity develops over northwest China and the northern Indian Peninsula during spring, which is attributed to surface thermal forcing induced by the positive winter SST tripole phase. A strong positive North Atlantic winter SST tripole anomaly strengthens the upper-level westerly jets, enhancing airflow toward the TP midtroposphere; together, these circulation patterns cause anomalous cyclonic conditions in the lower troposphere, especially over the Tarim Basin, via the eastward propagation of a Rossby wave train. These atmospheric circulation conditions are likely to increase the frequency of dust occurrence and promote the transport of dust onto the TP.

Description: The Kiremt rainy season is the foundation of agriculture in the Ethiopian Highlands and a key driver of economic development as well as the instigator of famines that have plagued the country’s history. Despite the importance of these rains, relatively little research exists on predicting the season’s onset; even less research evaluates statistical modeling approaches, in spite of their demonstrated utility for decision-making at local scales. To explore these methods, predictions are generated conditioned on three definitions of onset, at three lead times, using partial least squares (PLS) regression and random forest classification. Results illustrate moderate prediction skill and an ability to avoid false onsets, which may guide planting decisions; however, they are highly sensitive to how onset is defined, suggesting that future prediction approaches should additionally consider local agricultural definitions of onset.

Description: We formulate a new second-order closure turbulence model by employing a recent closure for the pressure–temperature correlation at the equation level. As a result, we obtain new heat flux equations that avoid the long-standing issue of a finite critical Richardson number. The new, structurally simpler model improves on the Mellor–Yamada and Galperin et al. models; a key feature includes enhanced mixing under stable conditions facilitating agreement with observational, experimental, and high-resolution numerical datasets. The model predicts a planetary boundary layer height deeper than predicted by models with low critical Richardson numbers, as demonstrated in single-column model runs of the GISS ModelE general circulation model.

Description: A novel approach to compare airborne observations of solar spectral irradiances measured above clouds with along-track radiative transfer simulations (RTS) is presented. The irradiance measurements were obtained with the Spectral Modular Airborne Radiation Measurement System (SMART) installed on the High Altitude and Long Range Research Aircraft (HALO). The RTS were conducted using the operational ecRad radiation scheme of the Integrated Forecast System (IFS), operated by the European Centre for Medium-Range Weather Forecasts (ECMWF), and a stand-alone radiative transfer solver, the library for Radiative transfer (libRadtran). Profiles of observed and simulated radar reflectivity were provided by the HALO Microwave Package (HAMP) and the Passive and Active Microwave Transfer Model (PAMTRA), respectively. The comparison aims to investigate the capability of the two models to reproduce the observed radiation field. By analyzing spectral irradiances above clouds, different ice cloud optical parameterizations in the models were evaluated. Simulated and observed radar reflectivity fields allowed the vertical representation of the clouds modeled by the IFS to be evaluated, and enabled errors in the IFS analysis data (IFS AD) and the observations to be separated. The investigation of a North Atlantic low pressure system showed that the RTS, in combination with the IFS AD, generally reproduced the observed radiation field. For heterogeneously distributed liquid water clouds, an underestimation of upward irradiance by up to 27% was found. Simulations of ice-topped clouds, using a specific ice optics parameterization, indicated a systematic underestimation of broadband cloud-top albedo, suggesting major deficiencies in the ice optics parameterization between 1242 and 1941 nm wavelength.

Description: Based on a priori analysis of large-eddy simulations (LESs) of the convective atmospheric boundary layer, improved turbulent mixing and dissipation length scales are proposed for a turbulence kinetic energy (TKE)-based planetary boundary layer (PBL) scheme. The turbulent mixing length incorporates surface similarity and TKE constraints in the surface layer, and makes adjustments for lateral entrainment effects in the mixed layer. The dissipation length is constructed based on balanced TKE budgets accounting for shear, buoyancy, and turbulent mixing. A nongradient term is added to the TKE flux to correct for nonlocal turbulent mixing of TKE. The improved length scales are implemented into a PBL scheme, and are tested with idealized single-column convective boundary layer (CBL) cases. Results exhibit robust applicability across a broad CBL stability range, and are in good agreement with LES benchmark simulations. It is then implemented into a community atmospheric model and further evaluated with 3D real-case simulations. Results of the new scheme are of comparable quality to three other well-established PBL schemes. Comparisons between simulated and radiosonde-observed profiles show favorable performance of the new scheme on a clear day.

Description: This study investigates the northward-propagating quasi-biweekly oscillation (QBWO) in the western North Pacific by examining the composite meridional structures. Using newly released reanalysis and remote sensing data, the northward propagation is understood in terms of the meridional contrasts in the planetary boundary layer (PBL) moisture and the column-integrated moist static energy (MSE). The meridional contrast in the PBL moisture, with larger values north of the convection center, is predominantly attributed to the moisture convergence associated with barotropic vorticity anomalies. A secondary contribution comes from the meridional moisture advection, for which advections by mean and perturbation winds are almost equally important. The meridional contrast in the MSE tendency, due to the recharge in the front of convection and discharge in the rear of convection, is jointly contributed by the meridional and vertical MSE advections. The meridional MSE advection mainly depends on the moisture processes particularly in the PBL, and the vertical MSE advection largely results from the advection of the mean MSE by vertical velocity anomalies, wherein the upper-troposphere ascending motion related to the stratiform heating in the rear of the convection plays the major role. In addition, partial feedback from sea surface temperature (SST) anomalies is evaluated on the basis of MSE budget analysis. SST anomalies tend to enhance the surface turbulent heat fluxes ahead of the convention center and suppress them behind the convention center, thus positively contributing approximately 20% of the meridional contrast in the MSE tendency.

Description: Although the development of supergradient winds is well understood, the importance of supergradient winds in tropical cyclone (TC) intensification is still under debate. One view is that the spinup of the eyewall occurs by the upward advection of high tangential momentum associated with supergradient winds from the boundary layer. The other view argues that the upward advection of supergradient winds by eyewall updrafts results in an outward agradient force, leading to the formation of a shallow outflow layer immediately above the inflow boundary layer. As a result, the spinup of tangential wind in the eyewall by the upward advection of supergradient wind from the boundary layer is largely offset by the spindown of tangential wind due to the outflow resulting from the agradient force. In this study, the net contribution by the upward advection of the supergradient wind component from the boundary layer to the intensification rate and final intensity of a TC are quantified through ensemble sensitivity numerical experiments using an axisymmetric TC model. Results show that consistent with the second view above, the positive upward advection of the supergradient wind component from the boundary layer by eyewall updrafts is largely offset by the negative radial advection due to the outflow resulting from the outward agradient force. As a result, the upward advection of the supergradient wind component contributes little (often less than 4%) to the intensification rate and but it contributes about 10%–15% to the final intensity of the simulated TC due to the enhanced inner-core air–sea thermodynamic disequilibrium.

Description: This study is the first to reach a global view of the precipitation process partitioning, using a combination of satellite and global climate modeling data. The pathways investigated are 1) precipitating ice (ice/snow/graupel) that forms above the freezing level and melts to produce rain (S) followed by additional condensation and collection as the melted precipitating ice falls to the surface (R); 2) growth completely through condensation and collection (coalescence), warm rain (W); and 3) precipitating ice (primarily snow) that falls to the surface (SS). To quantify the amounts, data from satellite-based radar measurements—CloudSat, GPM, and TRMM—are used, as well as climate model simulations from the Community Atmosphere Model (CAM) and the Met Office Unified Model (UM). Total precipitation amounts and the fraction of the total precipitation amount for each of the pathways is examined latitudinally, regionally, and globally. Carefully examining the contributions from the satellite-based products leads to the conclusion that about 57% of Earth’s precipitation follows pathway S, 15% R, 23% W, and 5% SS, each with an uncertainty of ±5%. The percentages differ significantly from the global climate model results, with the UM indicating smaller fractional S, more R, and more SS; and CAM showing appreciably greater S, negative R (indicating net evaporation below the melting layer), a much larger percentage of W and much less SS. Possible reasons for the wide differences between the satellite- and model-based results are discussed.

Description: The emergence of a spatial pattern in the externally forced response (FR) of dynamic sea level (DSL) during the altimeter era has recently been demonstrated using climate models but our understanding of its initial emergence, drivers, and implications for the future is poor. Here the anthropogenic forcings of the DSL pattern are explored using the Community Earth System Model Large Ensemble (CESM-LE) and Single-Forcing Large Ensemble, a newly available set of simulations where values of individual forcing agents remain fixed at 1920 levels, allowing for an estimation of their effects. Statistically significant contributions to the DSL FR are identified for greenhouse gases (GHGs) and industrial aerosols (AERs), with particularly strong contributions resulting from AERs in the mid-twentieth century and GHGs in the late twentieth and twenty-first century. Secondary, but important, contributions are identified for biomass burning aerosols in the equatorial Atlantic Ocean in the mid-twentieth century, and for stratospheric ozone in the Southern Ocean during the late twentieth century. Key to understanding regional DSL patterns are ocean heat content and salinity anomalies, which are driven by surface heat and freshwater fluxes, ocean dynamics, and the spatial structure of seawater thermal expansivity. Potential implications for the interpretation of DSL during the satellite era and the longer records from tide gauges are suggested as a topic for future research.

Description: A sensitivity analysis methodology recently developed by the authors is applied to COAMPS and WRF. The method involves varying model parameters according to Latin Hypercube Sampling, and developing multivariate multiple regression models that map the model parameters to forecasts over a spatial domain. The regression coefficients and p values testing whether the coefficients are zero serve as measures of sensitivity of forecasts with respect to model parameters. Nine model parameters are selected from COAMPS and WRF, and their impact is examined on nine forecast quantities (water vapor, convective and gridscale precipitation, and air temperature and wind speed at three altitudes). Although the conclusions depend on the model parameters and specific forecast quantities, it is shown that sensitivity to model parameters is often accompanied by nontrivial spatial structure, which itself depends on the underlying forecast model (i.e., COAMPS vs WRF). One specific difference between these models is in their sensitivity with respect to a parameter that controls temperature increments in the Kain–Fritsch trigger function; whereas this parameter has a distinct spatial structure in COAMPS, that structure is completely absent in WRF. The differences between COAMPS and WRF also extend to the quality of the statistical models used to assess sensitivity; specifically, the differences are largest over the waters off the southeastern coast of the United States. The implication of these findings is twofold: not only is the spatial structure of sensitivities different between COAMPS and WRF, the underlying relationship between the model parameters and the forecasts is also different between the two models.

Description: An increase in the severity of extreme weather is arguably one of the most important consequences of climate change with immediate and potentially devastating impacts. Recent events, like Hurricane Harvey, stimulated public discourse surrounding the role of climate change in amplifying, or otherwise modifying, the patterns of such events. Within the scientific community, recent years have witnessed considerable progress on “climate attribution”—the use of statistical techniques to assess the probability that climate change is influencing the character of some extreme weather events. Using a novel application of signal detection theory, this article assesses when, and to what extent, laypeople attribute changes in hurricanes to climate change and whether and how certain characteristics predict this decision. The results show that people attribute hurricanes to climate change based on their preexisting climate beliefs and numeracy. Respondents who were more dubious about the existence of climate change (and more numerate) required a greater degree of evidence (i.e., a more extreme world) before they were willing to suggest that an unusual hurricane season might be influenced by climate change. However, those who have doubts were still willing to make these attributions when hurricane behavior becomes sufficiently extreme. In general, members of the public who hold different prior views about climate change are not in complete disagreement about the evidence they perceive, which leaves the possibility for future work to explore ways to bring such judgments back into alignment.

Description: A high-resolution global atmospheric model, the nonhydrostatic icosahedral atmospheric model (NICAM), exhibited underestimation biases in low-level mixed-phase clouds in the midlatitudes and polar regions. The ice-cloud microphysics used in a single-moment bulk cloud microphysics scheme (NSW6) was evaluated and improved using a single-column model by reference to a double-moment bulk cloud microphysics scheme (NDW6). Budget analysis indicated that excessive action of the Bergeron–Findeisen and riming processes crucially reduced supercooled liquid water. In addition, the rapid production of rain directly reduced cloud water and indirectly reduced cloud water through the production of snow and graupel by riming. These biases in growth rates were found to originate from the number concentration diagnosis used in NSW6. The diagnosis based on the midlatitude cloud systems assumption was completely different from the one for low-level mixed-phase clouds. To alleviate underestimation biases, rain production, heterogeneous ice nucleation, vapor deposition by snow and graupel, and riming processes were revised. The sequential revisions of cloud microphysics alleviated the underestimation biases step by step without parameter tuning. The lifetime of cloud layers simulated by NSW6 was reasonably prolonged.

Description: Warm-season rainfall associated with mesoscale convective systems (MCSs) in the central United States is characterized by higher intensity and nocturnal timing compared to rainfall from non-MCS systems, suggesting their potentially different footprints on the land surface. To differentiate the impacts of MCS and non-MCS rainfall on the surface water balance, a water tracer tool embedded in the Noah land surface model with multiparameterization options (WT-Noah-MP) is used to numerically “tag” water from MCS and non-MCS rainfall separately during April–August (1997–2018) and track their transit in the terrestrial system. From the water-tagging results, over 50% of warm-season rainfall leaves the surface–subsurface system through evapotranspiration by the end of August, but non-MCS rainfall contributes a larger fraction. However, MCS rainfall plays a more important role in generating surface runoff. These differences are mostly attributed to the rainfall intensity differences. The higher-intensity MCS rainfall tends to produce more surface runoff through infiltration excess flow and drives a deeper penetration of the rainwater into the soil. Over 70% of the top 10th percentile runoff is contributed by MCS rainfall, demonstrating its important contribution to local flooding. In contrast, lower-intensity non-MCS rainfall resides mostly in the top layer and contributes more to evapotranspiration through soil evaporation. Diurnal timing of rainfall has negligible effects on the flux partitioning for both MCS and non-MCS rainfall. Differences in soil moisture profiles for MCS and non-MCS rainfall and the resultant evapotranspiration suggest differences in their roles in soil moisture–precipitation feedbacks and ecohydrology.

Description: Using 4-yr mooring observations and ocean circulation model experiments, this study characterizes the spatial and temporal variability of the Equatorial Intermediate Current (EIC; 200–1200 m) in the Indian Ocean and investigates the causes. The EIC is dominated by seasonal and intraseasonal variability, with interannual variability being weak. The seasonal component dominates the midbasin with a predominant semiannual period of ~166 days but weakens toward east and west where the EIC generally exhibits large intraseasonal variations. The resonant second and fourth baroclinic modes at the semiannual period make the largest contribution to the EIC, determining the overall EIC structures. The higher baroclinic modes, however, modify the EIC’s vertical structures, forming multiple cores during some time periods. The EIC intensity has an abrupt change near 73°E, which is strong to the east and weak to the west. Model simulation suggests that the abrupt change is caused primarily by the Maldives, which block the propagation of equatorial waves. The Maldives impede the equatorial Rossby waves, reducing the EIC’s standard deviation associated with reflected Rossby waves by ~48% and directly forced waves by 20%. Mode decomposition further demonstrates that the semiannual resonance amplitude of the second baroclinic mode reduces by 39% because of the Maldives. However, resonance amplitude of the four baroclinic mode is less affected, because the Maldives fall in the node region of mode 4’s resonance. The research reveals the spatiotemporal variability of the poorly understood EIC, contributing to our understanding of equatorial wave–current dynamics.

Description: The Early Twentieth Century Warming (ETCW) defined as the period 1921–50 saw a clear increase in actinometrical observations in the Arctic. Nevertheless, information on radiation balance and its components at that time is still very limited in availability, and therefore large discrepancies exist among estimates of total solar irradiance forcing. To eliminate these uncertainties, all available solar radiation data for the Arctic needs to be collected and processed. Better knowledge about incoming solar radiation (direct, diffuse and global) should allow for more reliable estimation of the magnitude of total solar irradiance forcing, which can help in turn, to more precisely and correctly explain the reasons for the ETCW in the Arctic. The paper summarises our research into the availability of solar radiation data for the Arctic. An important part of this work is its detailed inventory of data series (including metadata) for the period before the mid-20th century. Based on the most reliable data series, general solar conditions in the Arctic during the ETCW are described. The character of solar radiation changes between the ETCW and present times, in particular after 2000, is also analyzed. Average annual global solar radiation in the Russian Arctic during the ETCW were slightly greater than in the period 1964–90 (by about 1–2 W·m˗2), and markedly greater than in the period 2001–19 (by about 16 W·m˗2). Our results also reveal that in the period 1920–2019 three phases of solar radiation changes can be distinguished: a brightening phase (1921–50), a stabilisation phase (1951–93) and a dimming phase (after 2000).

Description: Variability in soil moisture has implications for regional terrestrial environments under a warming climate. This paper focuses on the spatiotemporal variability in the intra-annual persistence of soil moisture in China using the fifth-generation reanalysis dataset by the European Centre for Medium-Range Weather Forecasts for the period 1979–2018. The results show that in China, the mean intra-annual persistence in the humid to arid zones increased from 60 to 115 days in the lower layer but decreased from 19 to 13 days and from 25 to 14 days in the upper and root layers, respectively. However, these changes were strongly attenuated in extremely dry and wet regions due to the scarcity of soil moisture anomalies. Large changes in persistence occurred in the lower soil layer in dryland areas, with a mean difference of up to 40 days between the 2010s and the 1980s. Overall increasing trends dominated the large-scale spatial features, despite regional decreases in the eastern arid zone and the North and Northeast China plains. In the root layer, the two plains experienced an expanded decrease while on the Tibetan Plateau it was dominated by decadal variability. These contrasting changes between the lower and root layers along the periphery of the transition zone was a reflection of the enhanced soil hydrological cycle in the root layer. The enhanced persistence in drylands lower layer is an indication of the intensified impacts of soil moisture anomalies (e.g., droughts) on terrestrial water cycle. These findings may help the understanding of climate change impacts on terrestrial environments.

Description: Data assimilation combines forecasts from a numerical model with observations. Most of the current data assimilation algorithms consider the model and observation error terms as additive Gaussian noise, specified by their covariance matrices Q and R, respectively. These error covariances, and specifically their respective amplitudes, determine the weights given to the background (i.e., the model forecasts) and to the observations in the solution of data assimilation algorithms (i.e., the analysis). Consequently, Q and R matrices significantly impact the accuracy of the analysis. This review aims to present and to discuss, with a unified framework, different methods to jointly estimate the Q and R matrices using ensemble-based data assimilation techniques. Most of the methods developed to date use the innovations, defined as differences between the observations and the projection of the forecasts onto the observation space. These methods are based on two main statistical criteria: 1) the method of moments, in which the theoretical and empirical moments of the innovations are assumed to be equal, and 2) methods that use the likelihood of the observations, themselves contained in the innovations. The reviewed methods assume that innovations are Gaussian random variables, although extension to other distributions is possible for likelihood-based methods. The methods also show some differences in terms of levels of complexity and applicability to high-dimensional systems. The conclusion of the review discusses the key challenges to further develop estimation methods for Q and R. These challenges include taking into account time-varying error covariances, using limited observational coverage, estimating additional deterministic error terms, or accounting for correlated noise.

Description: A large midlatitude cyclone occurred over the central United States from 0000 to 1800 UTC 30 April 2017. During this period, there were more than 1100 reports of moderate-or-greater turbulence at commercial aviation cruising altitudes east of the Rocky Mountains. Much of this turbulence was located above or, otherwise, outside the synoptic-scale cloud shield of the cyclone, thus complicating its avoidance. In this study we use two-way nesting in a numerical model with finest horizontal spacing of 370 m to investigate possible mechanisms producing turbulence in two distinct regions of the cyclone. In both regions, model-parameterized turbulence kinetic energy compares well to observed turbulence reports. Despite being outside of hazardous large radar reflectivity locations in deep convection, both regions experienced strong modification of the turbulence environment as a result of upper-tropospheric/lower-stratospheric (UTLS) convective outflow. For one region, where turbulence was isolated and short lived, simulations revealed breaking of ~100-km horizontal-wavelength lower-stratospheric gravity waves in the exit region of a UTLS jet streak as the most likely mechanism for the observed turbulence. Although similar waves occurred in a simulation without convection, the altitude at which wave breaking occurred in the control simulation was strongly affected by UTLS outflow from distant deep convection. In the other analyzed region, turbulence was more persistent and widespread. There, overturning waves of much shorter 5–10-km horizontal wavelengths occurred within layers of gradient Richardson number 〈 0.25, which promoted Kelvin–Helmholtz instability associated with strong vertical shear in different horizontal locations both above and beneath the convectively enhanced UTLS jet.

Description: In this study, we investigate the technical application of the regularized regression method Lasso for identifying systematic biases in decadal precipitation predictions from a high-resolution regional climate model (CCLM) for Europe. The Lasso approach is quite novel in climatological research. We apply Lasso to observed precipitation and a large number of predictors related to precipitation derived from a training simulation, and transfer the trained Lasso regression model to a virtual forecast simulation for testing. Derived predictors from the model include local predictors at a given grid box and EOF predictors that describe large-scale patterns of variability for the same simulated variables. A major added value of the Lasso function is the variation of the so-called shrinkage factor and its ability in eliminating irrelevant predictors and avoiding overfitting. Among 18 different settings, an optimal shrinkage factor is identified that indicates a robust relationship between predictand and predictors. It turned out that large-scale patterns as represented by the EOF predictors outperform local predictors. The bias adjustment using the Lasso approach mainly improves the seasonal cycle of the precipitation prediction and, hence, improves the phase relationship and reduces the root-mean-square error between model prediction and observations. Another goal of the study pertains to the comparison of the Lasso performance with classical model output statistics and with a bivariate bias correction approach. In fact, Lasso is characterized by a similar and regionally higher skill than classical approaches of model bias correction. In addition, it is computationally less expensive. Therefore, we see a large potential for the application of the Lasso algorithm in a wider range of climatological applications when it comes to regression-based statistical transfer functions in statistical downscaling and model bias adjustment.

Description: Using a Lagrangian trajectory model, contributions of moisture from the Indian Ocean (IO), the South China Sea (SCS), the adjacent land region (LD), and the Pacific Ocean (PO) to interannual summer precipitation variations in southwestern China (SWC) are investigated. Results show that, on average, the IO, SCS, LD, and PO contribute 48.8%, 21.1%, 23.6%, and 3.7% of the total moisture release in SWC, respectively. In summers with the above-normal precipitation, moisture release from the IO and SCS increases significantly by 41.4% and 15.1%, respectively. In summers with below-normal precipitation, moisture release from the IO and SCS decreases significantly by 44.2% and 24.6%, respectively. In addition, the moisture anomalies from the four source regions together explain 86.5% of the total interannual variances of SWC summer precipitation, and the IO and SCS only can explain 75.7%. Variations in moisture transport from the IO, SCS, and LD to SWC are not independent of one another and are commonly influenced by the anomalous anticyclone in the western North Pacific Ocean, which enhances the moisture transport from the IO and SCS by the anomalous southwesterlies over its northwestern quadrant but reduces that from the LD east of SWC by the anomalous westerlies along its northern edge. Anomalous warming in the tropical Atlantic Ocean can modify the Walker circulation, induce anomalous descending motion over the central tropical Pacific, and excite the anomalous anticyclone in the western North Pacific as the classic Matsuno–Gill response. The observed impacts of the tropical Atlantic warming on the anomalous anticyclone and summer precipitation in SWC can be well reproduced in an atmospheric general circulation model.

Description: The NOAA Warn-on-Forecast System (WoFS) is an experimental rapidly updating convection-allowing ensemble designed to provide probabilistic operational guidance on high-impact thunderstorm hazards. The current WoFS uses physics diversity to help maintain ensemble spread. We assess the systematic impacts of the three WoFS PBL schemes—YSU, MYJ, and MYNN—using novel, object-based methods tailored to thunderstorms. Very short forecast lead times of 0–3 h are examined, which limits phase errors and thereby facilitates comparisons of observed and model storms that occurred in the same area at the same time. This evaluation framework facilitates assessment of systematic PBL scheme impacts on storms and storm environments. Forecasts using all three PBL schemes exhibit overly narrow ranges of surface temperature, dewpoint, and wind speed. The surface biases do not generally decrease at later forecast initialization times, indicating that systematic PBL scheme errors are not well mitigated by data assimilation. The YSU scheme exhibits the least bias of the three in surface temperature and moisture and in many sounding-derived convective variables. Interscheme environmental differences are similar both near and far from storms and qualitatively resemble the differences analyzed in previous studies. The YSU environments exhibit stronger mixing, as expected of nonlocal PBL schemes; are slightly less favorable for storm intensification; and produce correspondingly weaker storms than the MYJ and MYNN environments. On the other hand, systematic interscheme differences in storm morphology and storm location forecast skill are negligible. Overall, the results suggest that calibrating forecasts to correct for systematic differences between PBL schemes may modestly improve WoFS and other convection-allowing ensemble guidance at short lead times.

Description: The Southern Hemisphere summertime eddy-driven jet and storm tracks have shifted poleward over the recent few decades. In previous studies, explanations have mainly stressed the influence of external forcing in driving this trend. Here we examine the role of internal tropical SST variability in controlling the austral summer jet’s poleward migration, with a focus on interdecadal time scales. The role of external forcing and internal variability are isolated by using a hierarchy of Community Earth System Model version 1 (CESM1) simulations, including the pre-industrial control, large ensemble, and pacemaker runs. Model simulations suggest that in the early twenty-first century, both external forcing and internal tropical Pacific SST variability are important in driving a positive southern annular mode (SAM) phase and a poleward migration of the eddy-driven jet. Tropical Pacific SST variability, associated with the negative phase of the interdecadal Pacific oscillation (IPO), acts to shift the jet poleward over the southern Indian and southwestern Pacific Oceans and intensify the jet in the southeastern Pacific basin, while external forcing drives a significant poleward jet shift in the South Atlantic basin. In response to both external forcing and decadal Pacific SST variability, the transient eddy momentum flux convergence belt in the middle latitudes experiences a poleward migration due to the enhanced meridional temperature gradient, leading to a zonally symmetric southward migration of the eddy-driven jet. This mechanism distinguishes the influence of the IPO on the midlatitude circulation from the dynamical impact of ENSO, with the latter mainly promoting the subtropical wave-breaking critical latitude poleward and pushing the midlatitude jet to higher latitudes.

Description: Heated tipping-bucket (TB) gauges are used broadly in national weather monitoring networks, but their performance for the measurement of solid precipitation has not been well characterized. Manufacturer-provided TB gauges were evaluated at five test sites during the World Meteorological Organization Solid Precipitation Intercomparison Experiment (WMO-SPICE), with most gauge types tested at more than one site. The test results were used to develop and evaluate adjustments for the undercatch of solid precipitation by heated TB gauges. New methods were also developed to address challenges specific to measurements from heated TB gauges. Tipping-bucket transfer functions were created specifically to minimize the sum of errors over the course of the adjusted multiseasonal accumulation. This was based on the hypothesis that the best transfer function produces the most accurate long-term precipitation records, rather than accurate catch efficiency measurements or accurate daily or hourly precipitation measurements. Using this new approach, an adjustment function derived from multiple gauges was developed that performed better than traditional gauge-specific and multigauge catch efficiency derived adjustments. Because this new multigauge adjustment was developed using six different types of gauges tested at five different sites, it may be applicable to solid precipitation measurements from unshielded heated TB gauges that were not evaluated in WMO-SPICE. In addition, this new method of optimizing transfer functions may be useful for other types of precipitation gauges, as it has many practical advantages over the traditional catch efficiency methods used to derive undercatch adjustments.

Description: This article illustrates how multifrequency radar observations can refine the mass–size parameterization of frozen hydrometeors in scattering models and improve the correlation between the radar observations and in situ measurements of microphysical properties of ice and snow. The data presented in this article were collected during the GPM Cold Season Precipitation Experiment (GCPEx) (2012) and Olympic Mountain Experiment (OLYMPEx) (2015) field campaigns, where the true mass–size relationship was not measured. Starting from size and shape distributions of ice particles measured in situ, scattering models are used to simulate an ensemble of reflectivity factors for various assumed mass–size parameterizations (MSP) of the power-law type. This ensemble is then collocated to airborne and ground-based radar observations, and the MSPs are refined by retaining only those that reproduce the radar observations to a prescribed level of accuracy. A versatile “retrieval dashboard” is built to jointly analyze the optimal MSPs and associated retrievals. The analysis shows that the optimality of an MSP depends on the physical assumptions made in the scattering simulators. This work confirms also the existence of a relationship between parameters of the optimal MSPs. Through the MSP optimization, the retrievals of ice water content M and mean diameter Dm seem robust to the change in meteorological regime (between GCPEx and OLYMPEx); whereas the retrieval of the diameter spread Sm seems more campaign dependent.

Description: The filtering properties of the standardized precipitation index (SPI), the Palmer drought severity index (PDSI), and the model calibrated drought index (MCDI) are investigated to determine their relations to past, present, and future precipitation anomalies in regions with a wide diversity of precipitation characteristics. All three indices can be closely approximated by weighted averages of precipitation, but with different weighting. The SPI is well represented by one-sided, uniformly weighted averages; the MCDI is well represented by one-sided, exponentially weighted averages; and the PDSI is well represented by two-sided, exponentially weighted averages with much higher weighting of past and present precipitation than future precipitation. Detailed analyses identify interpretational complications and other undesirable features in the SPI and PDSI. In addition, the PDSI and MCDI are each restricted to single regionally specific “intrinsic” time scales that can significantly differ between the two indices. Inspired by the strengths of the SPI, PDSI, and MCDI, a hybrid index is developed that consists of exponentially weighted averages of past and present precipitation that are implicit in the PDSI and MCDI. The explicit specification of the exponential weighting allows users to control the time scale of the hybrid index to investigate precipitation variability on any time scale of interest. This advantage over the PDSI and MCDI is analogous to the controllability of the time scale of the SPI, but the exponentially fading memory is more physical than the uniform weighting of past and present precipitation in the SPI.

Description: This study investigates the association between summer high temperature extremes (HTEs) over China and the Pacific meridional mode (PMM) that is characterized by an anomalous north–south sea surface temperature gradient and an anomalous surface circulation over the northeastern subtropical Pacific. It is found that the HTE activities over most parts of southern China (particularly eastern China) are prominently intensified during the positive PMM phase and weakened during the negative phase. Further examinations suggest that the PMM is linked with HTEs in China through processes that entail both eastward and westward development of signals emanating from the PMM site. The westward development is associated with the formation of an anomalous low-level cyclone over the western North Pacific (WNP), which may be viewed as a Matsuno–Gill-type response to the off-equatorial heating in the eastern Pacific. This circulation change is accompanied by anomalous ascent over WNP and northern China, and subsidence over eastern China. On the other hand, the eastward development process is linked to the PMM-induced displacement of the East Asian jet stream and the generation of a midlatitude Rossby wave train. In the positive PMM phase, the above circulation changes are accompanied by anomalous air subsidence and enhanced adiabatic heating, reduced precipitation, anomalous lower-level anticyclone, and rising surface pressure over the eastern part of China. Moreover, the land surface of that region receives more solar radiation. Opposite changes are discernible over northern China. These changes are favorable for the occurrence and persistence of HTEs over eastern China and tend to suppress HTEs over northern China.

Description: Currently, major efforts are under way to refine the horizontal resolution of weather and climate models to kilometer-scale grid spacing (Δx). Besides refining the representation of the atmospheric dynamics and enabling the use of explicit convection, this will also provide higher resolution in the representation of orography. This study investigates the influence of these resolution increments on the simulation of orographic moist convection. Nine days of fair-weather thermally driven flow over the Alps are analyzed. Two sets of simulations with the COSMO model are compared, each consisting of three runs at Δx of 4.4, 2.2, and 1.1 km: one set using a fixed representation of orography at a resolution of 8.8 km, and one with varying representation at the resolution of the computational mesh. The spatial distribution of precipitation during daytime is only marginally affected by the orographic details, but nighttime convection to the south of the Alps—triggered by cold-air outflow from the valleys—is very sensitive to orography and precipitation is enhanced if more detailed orography is provided. During daytime, the onset of precipitation is delayed. The amplitude of the diurnal cycle of precipitation is reduced, even though more moisture converges toward the Alpine region during the afternoon. The hereby accumulated moisture sustains precipitation during the evening and nighttime over the surrounding plains. For these differences, the effects of changes in orographic detail are more important than changes in grid spacing. In addition, the individual convective cells are weaker, but their number increases with higher resolved orography.

Description: Recent studies proposed leading averaged coupled covariance (LACC) as an effective strongly coupled data assimilation (SCDA) method to improve the coupled state estimation over weakly coupled data assimilation (WCDA) in a coupled general circulation model (CGCM). This SCDA method, however, has been previously evaluated only in the perfect model scenario. Here, as a further step toward evaluating LACC for real world data assimilation, LACC is evaluated for the assimilation of reanalysis data in a CGCM. Several criteria are used to evaluate LACC against the benchmark WCDA. It is shown that despite significant model bias, LACC can improve the coupled state estimation over WCDA. Compared to WCDA, LACC increases the globally averaged anomaly correlation coefficients (ACCs) of sea surface temperature (SST) by 0.036 and atmosphere temperature at the bottom level (Ts) by 0.058. However, there also exist regions where WCDA outperforms LACC. Although the reduction in the anomaly root-mean-square error (RMSE) is not as consistently clear as the increase in ACC, LACC can largely correct the biased model climatology.

Description: Under stably stratified conditions, the dissipation rate ε of turbulence kinetic energy (TKE) is related to the structure function parameter for temperature CT2, through the buoyancy frequency and the so-called mixing efficiency. A similar relationship does not exist for convective turbulence. In this paper, we propose an analytical expression relating ε and CT2 in the convective boundary layer (CBL), by taking into account the effects of nonlocal heat transport under convective conditions using the Deardorff countergradient model. Measurements using unmanned aerial vehicles (UAVs) equipped with high-frequency response sensors to measure velocity and temperature fluctuations obtained during the two field campaigns conducted at Shigaraki MU observatory in June 2016 and 2017 are used to test this relationship between ε and CT2 in the CBL. The selection of CBL cases for analysis was aided by auxiliary measurements from additional sensors (mainly radars), and these are described. Comparison with earlier results in the literature suggests that the proposed relationship works, if the countergradient term γD in the Deardorff model, which is proportional to the ratio of the variances of potential temperature θ and vertical velocity w, is evaluated from in situ (airplane and UAV) observational data, but fails if evaluated from large-eddy simulation (LES) results. This appears to be caused by the tendency of the variance of θ in the upper part of the CBL and at the bottom of the entrainment zone to be underestimated by LES relative to in situ measurements from UAVs and aircraft. We discuss this anomaly and explore reasons for it.

Description: The indirect radiative effect of aerosol variability on shallow cumulus clouds is realized in nature with considerable concurrent meteorological variability. Large-eddy simulations constrained by observations at a continental site in Oklahoma are performed to represent the variability of different meteorological states on days with different aerosol conditions. The total radiative effect of this natural covariation between aerosol and other meteorological drivers of total cloud amount and albedo is quantified. The changes to these bulk quantities are used to understand the response of the cloud radiative effect to aerosol–cloud interactions (ACI) in the context of concurrent processes, as opposed to attempting to untangle the effect of individual processes on a case-by-case basis. Mutual information (MI) analysis suggests that meteorological variability masks the strength of the relationship between cloud drop number concentration and the cloud radiative effect. This is shown to be mostly due to variation in solar zenith angle and cloud field horizontal heterogeneity masking the relationship between cloud drop number and cloud albedo. By combining MI and more traditional differential analyses, a framework to identify important modes of covariation between aerosol, clouds, and meteorological conditions is developed. This shows that accounting for solar zenith angle variation and implementing an albedo bias correction increases the detectability of the radiative effects of ACI in simulations of shallow cumulus.

Description: We explore the response of wintertime Arctic sea ice growth to strong cyclones and to large-scale circulation patterns on the daily scale using Earth system model output in phase 5 of the Coupled Model Intercomparison Project (CMIP5). A combined metrics ranking method selects three CMIP5 models that are successful in reproducing the wintertime Arctic dipole (AD) pattern. A cyclone identification method is applied to select strong cyclones in two subregions in the North Atlantic to examine their different impacts on sea ice growth. The total change of sea ice growth rate (SGR) is split into those respectively driven by the dynamic and thermodynamic atmospheric forcing. Three models reproduce the downward longwave radiation anomalies that generally match thermodynamic SGR anomalies in response to both strong cyclones and large-scale circulation patterns. For large-scale circulation patterns, the negative AD outweighs the positive Arctic Oscillation in thermodynamically inhibiting SGR in both impact area and magnitude. Despite the disagreement on the spatial distribution, the three CMIP5 models agree on the weaker response of dynamic SGR than thermodynamic SGR. As the Arctic warms, the thinner sea ice results in more ice production and smaller spatial heterogeneity of thickness, dampening the SGR response to the dynamic forcing. The higher temperature increases the specific heat of sea ice, thus dampening the SGR response to the thermodynamic forcing. In this way, the atmospheric forcing is projected to contribute less to change daily SGR in the future climate.

Description: In this study, remote influence originating from the tropical western Indian Ocean on June precipitation in South China and the Indochina Peninsula is documented. Based on numerical simulation and statistical analysis, it is noted that the warm anomaly in the tropical western Indian Ocean can induce a weaker-than-normal Walker circulation across the tropical Indian Ocean and western Pacific Ocean. This further leads to a northeast–southwest-oriented western North Pacific subtropical high and a weaker-than-normal monsoon trough in the South China Sea. In addition, the weak monsoon trough is concurrent with an anomalous rising motion in South China and a sinking motion in the Indochina Peninsula. This enhances precipitation in South China and suppresses precipitation in the Indochina Peninsula on an interannual time scale. On the other hand, the warming trend in the tropical western Indian Ocean also supports the long-term trends of precipitation in the two regions.

Description: Spanning across the equator with a northwest–southeast orientation, the island of Sumatra can exert significant influences on low-level flow. Under northeasterly flow, in particular, lee vortices can form and some of them may subsequently develop into tropical cyclones (TCs) in the Indian Ocean (IO). Building upon the recent work of Fine et al., this study investigates the roles of the Sumatra topography and other common features on the formation of selected cases for analysis and numerical experiments. Four cases in northern IO were selected for analysis and two of them [Nisha (2008) and Ward 2009)] for simulation at a grid size of 4 km. Sensitivity tests without the Sumatra topography were also performed. Our results indicate that during the lee stage, most pre-TC vortices tend to be stronger with a clearer circulation when the topography is present. However, the island’s terrain is a helpful but not a deciding factor in TC formation. Specifically, the vortices in the no-terrain tests also reach TC status, but just at a later time. Some common ingredients contributing to a favorable environment for TC genesis are identified. They include northeasterly winds near northern Sumatra, westerly wind bursts along the equator, and migratory disturbances (TC remnants or Borneo vortices) to provide additional vorticity/moisture from the South China Sea. These factors also appear in most of the 22 vortices in northern IO during October–December in 2008 and 2009. For the sole case (Cleo) examined in southern IO, the deflection of equatorial westerlies into northwesterlies by Sumatra (on the windward side) is also helpful to TC formation.

Description: Observations across the North Atlantic jet stream with high vertical resolution are used to explore the structure of the jet stream, including the sharpness of vertical wind shear changes across the tropopause and the wind speed. Data were obtained during the North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX) by an airborne Doppler wind lidar, dropsondes, and a ground-based stratosphere–troposphere radar. During the campaign, small wind speed biases throughout the troposphere and lower stratosphere of only −0.41 and −0.15 m s−1 are found, respectively, in the ECMWF and Met Office analyses and short-term forecasts. However, this study finds large and spatially coherent wind errors up to ±10 m s−1 for individual cases, with the strongest errors occurring above the tropopause in upper-level ridges. ECMWF and Met Office analyses indicate similar spatial structures in wind errors, even though their forecast models and data assimilation schemes differ greatly. The assimilation of operational observational data brings the analyses closer to the independent verifying observations, but it cannot fully compensate for the forecast error. Models tend to underestimate the peak jet stream wind, the vertical wind shear (by a factor of 2–5), and the abruptness of the change in wind shear across the tropopause, which is a major contribution to the meridional potential vorticity gradient. The differences are large enough to influence forecasts of Rossby wave disturbances to the jet stream with an anticipated effect on weather forecast skill even on large scales.

Description: In this paper, an extended nonlinear multiscale interaction model is proposed to examine nonlinear behavior of eddy-driven blocking as a Rossby wave packet in a three-dimensional background flow by dividing the background meridional potential vorticity gradient (PVy) into dynamical PVy⁡(PVyD) related to the horizontal (mainly meridional) shear of background westerly wind (BWW) and thermodynamic PVy⁡(PVyT) associated with the meridional temperature gradient (MTG). It is found that eddy-driven baroclinic blocking with large amplitude in the midtroposphere tends to have a longer lifetime (~20 days) in a baroclinic atmosphere with stratification than eddy-driven barotropic blocking without vertical variation (less than 15 days). It is shown that barotropic blocking shows a northwest–southeast orientation and has long lifetime, large retrogression, and slow decay only for weaker barotropic BWW and PVyD in higher latitudes. In a baroclinic atmosphere with stratification, baroclinic blocking shows long lifetime, strong eastward movement, slow decay, weak strength, and less local persistence for large barotropic BWW and PVyD under PVyT=0, but becomes less slow decay, weak retrogression, and large local persistence for small barotropic BWW and PVyD. Such a blocking with a north–south antisymmetric dipole, large amplitude, and long local persistence, characterized by a persistent large meander of westerly jet streams, is easily seen when baroclinic BWW and PVyT are small in the lower to midtroposphere. Comparatively, the magnitude of PVyT plays a larger role in the blocking change than that of PVyD, whereas the vertical variation of MTG is more important for the blocking change than the MTG itself for some cases.

Description: El Niño–Southern Oscillation (ENSO) teleconnections have been recognized as possible negative influences on crop yields in the United States during the summer growing season, especially in a developing La Niña summer. This study examines the physical processes of the ENSO summer teleconnections and remote impacts on the United States during a multiyear La Niña life cycle. Since 1950, a developing La Niña summer is either when an El Niño is transitioning to a La Niña or when a La Niña is persisting. Due to the distinct prior ENSO conditions, the oceanic and atmospheric characteristics in the tropics are dissimilar in these two different La Niña summers, leading to different teleconnection patterns. During the transitioning summer, the decaying El Niño and the developing La Niña induce suppressed deep convection over both the subtropical western Pacific (WP) and the tropical central Pacific (CP). Both of these two suppressed convection regions induce Rossby wave propagation extending toward North America, resulting in a statistically significant anomalous anticyclone over northeastern North America and, therefore, a robust warming signal over the Midwest. In contrast, during the persisting summer, only one suppressed convection region is present over the tropical CP induced by the La Niña SST forcing, resulting in a weak and insignificant extratropical teleconnection. Experiments from a stationary wave model confirm that the suppressed convection over the subtropical WP during the transitioning summer not only contributes substantially to the robust warming over the Midwest but also causes the teleconnections to be different from those in the persisting summer.

Description: The zonostrophic instability that leads to the emergence of zonal jets in barotropic beta-plane turbulence is analyzed through a geometric decomposition of the eddy stress tensor. The stress tensor is visualized by an eddy variance ellipse whose characteristics are related to eddy properties. The tilt of the ellipse principal axis is the tilt of the eddies with respect to the shear, and the eccentricity of the ellipse is related to the eddy anisotropy, and its size is related to the eddy kinetic energy. Changes of these characteristics are directly related to the vorticity fluxes forcing the mean flow. The statistical state dynamics of the turbulent flow closed at second order is employed as it provides an analytic expression for both the zonostrophic instability and the stress tensor. For the linear phase of the instability, the stress tensor is analytically calculated at the stability boundary. For the nonlinear equilibration of the instability the tensor is calculated in the limit of small supercriticality in which the amplitude of the jet velocity follows Ginzburg–Landau dynamics. It is found that, dependent on the characteristics of the forcing, the jet is accelerated either because the jet primarily anisotropizes the eddies so as to produce upgradient fluxes, or because the jet changes the eddy tilt. The instability equilibrates as these changes are partially reversed by the nonlinear jet–eddy dynamics.

Description: The circulation of the Kuroshio northeast of Taiwan is characterized by a large anticyclonic loop of surface intrusion and strong upwelling at the shelfbreak. To study the mechanisms of Kuroshio intrusions, the vorticity balance is examined using a high-resolution nested numerical model. In the 2D depth-averaged vorticity equation, the advection of geostrophic potential vorticity (APV) term and the joint effect of baroclinicity and relief (JEBAR) term are dominant. On the other hand, in the 2D depth-integrated vorticity equation, the main balance is between nonlinear advection and bottom pressure torque. It is shown that JEBAR and APV tend to compensate, and their difference is comparable to bottom pressure torque. Perhaps most significantly, a general framework is provided for examination of vorticity balance over steep slopes through a full 3D depth-dependent vorticity equation. The 3D analysis reveals a well-defined bottom boundary layer over the shelfbreak, about 40 m deep and capped by the vertical velocity maximum. In the upper frictionless layer from the surface to about 100 m, the primary balance is between nonlinear advection and horizontal divergence. In the lower frictional layer, viscous stress is balanced by nonlinear advection and horizontal divergence. The bottom pressure torque, which corresponds to the depth-integrated viscous effect, is a proxy for viscous stress divergence at the bottom. The importance of nonlinear advection is further demonstrated in a sensitivity experiment by removing advective terms from momentum equations. Without nonlinear advection, the bottom pressure torque becomes trivial, the boundary layer vanishes, and the on-shelf intrusion is considerably weakened.

Description: This study developed a daily index to represent the northwest Pacific monsoon trough using westerly related cyclonic vorticity after removing tropical cyclones (TCs) from the reanalysis dataset. This index sufficiently captures the spatial and temporal variations in the monsoon trough. The use of this daily index revealed new features in the monsoon trough, including daily statistical characteristics, the active period over a year, and the main periodicity. A monsoon trough can be identified as active when the daily index is greater than 2.0 × 10−4 s−1. Active monsoon troughs occur during half of the summertime, and these is no monsoon trough on one-third of days, with the remaining days categorized as inactive. The most active month is August, in which approximately 20 days exhibit an active monsoon trough. Using this index, an active monsoon trough period, which is related to vigorous TC activity, was determined by identifying the establishment and decay dates for each year from 1979 to 2016. During most years, the active monsoon trough is established in mid-July and decays in late October, persisting for 3–5 months during the boreal summer. Moreover, spectral and wavelet analyses demonstrated the presence of intraseasonal, interannual, and interdecadal variabilities in the monsoon trough. The dominant periodicity for the interannual variability varied from 1.5 to 4 years in different decades. The relationship between the monsoon trough and TCs is also revealed using this index, showing that approximately 60% of TC formations were related to an active monsoon trough.

Description: The Z–R relationship is a scaling-law formulation, Z = ARb, connecting the radar reflectivity Z to the rain rate R. However, more than 100 Z–R relationships, with different values of the parameters, have been reported in literature. This abundance of relationships is in itself a strong indication that no one “physical” relationship exists, a state of affairs that we find similar to that of the protagonist of Luigi Pirandello’s novel One, No One and One Hundred Thousand. Nevertheless the “elevation” of a simple linear fit in the (logR, logZ) space to the role of “scaling law” is such a widespread tenet in literature that it eclipses the simple realization that the abundance of different intercepts and slopes reflects the inhomogeneous nature of rain, and, in ultimate analysis, the statistical variability existing between the number of drops and drop size distribution. Here, we “eliminate” the contribution of the number of drops by rescaling both reflectivity and rainfall rate to per unit drop variables, (Z, R) → (z, r), so that the remaining variability is due only to the variability of the drop size distribution. We use a worldwide database of disdrometer data to show that for the rescaled variables (z, r) only “one,” albeit approximate, scaling law exists.

Description: In this paper, a methodology is proposed to quantitatively evaluate precipitation products for multiple purposes. Evaluation mainly focuses on rainfall characteristics relevant to hydrological or agricultural applications: spatial distribution pattern, effect of aggregation over time, the capture of small-scale variability and seasonality, detection of dry spells and wet spells, and timing and volume of heavy rainfall events. Verification statistics were modified and metrics were reported for extreme weather performance, such as flood and drought monitoring. The analysis was performed for different rainfall categories, over regions dominated by different weather systems or with different topographical structures. The latest versions of seven commonly available, high-resolution rainfall estimates have been evaluated by the method against daily data from 16 rain gauge stations over Tanzania, during 1998–2006. They were TRMM 3B42, CHIRPS, TAMSAT, CMORPH_RAW, CMORPH_BLD, WFDEI_CRU, and CPCU. All products, except for CMORPH_BLD and CPCU, were poorly correlated to gauge data at daily time scale with correlation coefficients 〈 0.5. Five-day aggregation was the minimum time scale that can be used for the products to reach an accuracy better than monthly-mean of gauge data. Their performance varied across different climatic or topographical regions and different rainfall seasons. Timing of precipitation was inaccurately estimated by all products, particularly for heavy rains, with less than 40% hits. The results of the evaluation procedure allow discrimination between available products and better selection of the product to be used for a specific application, such as crop insurance or flood early warning, under particular climatic conditions.

Description: Standard meteorological balloons can deliver small scientific payloads to the stratosphere for a few tens of minutes, but achieving multihour level flight in this region is more difficult. We have developed a solar-powered hot-air balloon named the heliotrope that can maintain a nearly constant altitude in the upper troposphere–lower stratosphere as long as the sun is above the horizon. It can accommodate scientific payloads ranging from hundreds of grams to several kilograms. The balloon can achieve float altitudes exceeding 24 km and fly for days in the Arctic summer, although sunset provides a convenient flight termination mechanism at lower latitudes. Two people can build an envelope in about 3.5 h, and the materials cost about $30. The low cost and simplicity of the heliotrope enables a class of missions that is generally out of reach of institutions lacking specialized balloon expertise. Here, we discuss the design history, construction techniques, trajectory characteristics, and flight prediction of the heliotrope balloon. We conclude with a discussion of the physics of solar hot-air balloon flight.

Description: The deep ocean is severely under-sampled. While shipboard measurements provide irregular spatial and temporal records, moored time series establish deep ocean high-resolution time series, but only at limited locations. Here, highlights and challenges of measuring abyssal temperature and salinity on the Kuroshio Extension Observatory (KEO) mooring (32.3°N 144.6°E) from 2013 - 2019 are described. Using alternating SeaBird-37SMP instruments on annual deployments, an apparent fresh drift of 0.03-0.06 PSU was observed, with each newly deployed sensor returning to historical norms near 34.685 PSU. Recurrent salinity discontinuities were pronounced between the termination of each deployment and the initiation of the next, yet consistent pre- and post-deployment calibrations suggested the freshening was “real”. Because abyssal salinities do not vary by 0.03-0.06 PSU between deployment locations, the contradictory salinities during mooring overlap pointed toward a sensor issue that self-corrects prior to post-calibration. A persistent nepheloid layer, unique to KEO and characterized by murky, sediment-filled water, is likely responsible for sediment accretion in the conductivity cell. As sediment (or biofouling) increasingly clogs the instrument, salinity drifts toward a fresh bias. During ascent, the cell is flushed, clearing the clogged instrument. In contrast to salinity, deep ocean temperatures appear to increase from 2013 - 2017 by 0.0059°C, while a comparison to historical deep temperature measurements does not support a secular temperature increase in the region. It is suggested that decadal or interannual variability associated with the Kuroshio Extension may have an imprint on deep temperatures. Recommendations are discussed for future abyssal temperature and salinity measurements.

Description: An investigation of Tropical Cyclone (TC) Kelvin in February 2018 over northeast Australia was conducted to understand the mechanisms of the brown ocean effect (BOE) and to develop a comprehensive analysis framework for landfalling TCs in the process. NASA’s Land Information System (LIS) coupled to the NASA Unified WRF (NU-WRF) system was employed as the numerical model framework for 12 land/soil moisture perturbation experiments. Impacts of soil moisture and surface enthalpy flux conditions on TC Kelvin were investigated by closely evaluating simulated track and intensity, midlevel atmospheric thermodynamic properties, vertical wind shear, total precipitable water (TPW), and surface moisture flux. The results suggest that there were recognized differentiations among the sensitivity simulations as a result of land surface (e.g., soil moisture and texture) conditions. However, the intensification of TC Kelvin over land was more strongly related to atmospheric moisture advection and the diurnal cycle of solar radiation (i.e., radiative cooling) than to overall soil moisture conditions or surface fluxes. The analysis framework employed here for TC Kelvin can serve as a foundation to specifically quantify the factors governing the BOE. It also demonstrates that the BOE is not a binary influence (i.e., all or nothing), but instead operates in a continuum from largely to minimally influential such that it could be utilized to help improve prediction of inland effects for all landfalling TCs.

Description: Extraordinary precipitation events have impacted the United States recently, including Hurricanes Harvey (2017) and Florence (2018), with 3-day precipitation totals larger than any others reported in the United States during the past 70 years. The rainfall category (R-CAT) scaling method is used here to document extreme precipitation events and test for trends nationally. The R-CAT scale uses thresholds of 3-day precipitation total in 100-mm increments (starting with 200 mm) that do not vary temporally or geographically, allowing for simple, intuitive comparisons of extremes over space and time. The paper that introduced the scale only required levels 1–4 to represent historical extremes, finding that R-CATs 3–4 strike the conterminous United States about as frequently as EF 4–5 tornadoes or category 3–5 hurricanes. Remarkably, Florence and Harvey require extending the scale to R-CAT 7 and 9, respectively. Trend analyses of annual maximum 3-day totals (1950–2019) here identify significant increases in the eastern United States, along with declines in Northern California and Oregon. Consistent with these results, R-CAT storms have been more frequent in the eastern, and less frequent in western, United States during the past decade compared to 1950–2008. Tropical storms dominate R-CAT events along the southeastern coast and East Coast with surprising contributions from atmospheric rivers, while atmospheric rivers completely dominate along the West Coast.

Description: The assumption of a stationary global signal linked to El Niño–Southern Oscillation (ENSO) events is often used in paleo-ENSO proxy data interpretation. This paper attempts to investigate whether the assumption is valid during the last glacial maximum (LGM) over the region 60°S–90°N, 60°E−60°W. Using four models within phase 3 of the Paleoclimate Modeling Intercomparison Project framework that well reproduce ENSO-induced variabilities, differences from the preindustrial period to LGM in the ENSO-related sea surface temperature pattern and its impacts are investigated. Compared to the preindustrial period, the ENSO impacts are revealed to weaken and shift eastward during the LGM. According to multimodel medians, ENSO impacts on precipitation and near-surface air temperature are attenuated over most regions of concern, with percentage changes in both parameters averaging −21% for the whole region; the ENSO-induced Pacific–North America (PNA) teleconnection pattern is weakened, manifested by the 41% diminished center over the North Pacific and the almost vanished activity centers over the continent. Spatially, there is a zonal contraction of 13° for the sea surface warming of ENSO, as well as eastward migration over 10° for the ENSO-induced positive precipitation anomaly center over the tropical Pacific and the PNA teleconnection pattern outside the tropics. The aforementioned changes are linked to the altered climatic background during the LGM, which features a 16° eastward shift for the Pacific Walker circulation rising branch and a weakened waveguide in the midlatitudes. The results suggest that the hypothesis of stationary ENSO impacts should be applied cautiously to the past.

Description: Radio occultation (RO) can provide high-vertical-resolution thermodynamic soundings of the planetary boundary layer (PBL). However, sharp moisture gradients and strong temperature inversion lead to large gradients in refractivity N and often cause ducting. Ducting results in systematically negative RO N biases resulting from a nonunique Abel inversion problem. Using 8 years (2006–13) of Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) RO soundings and collocated European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-I) data, we confirm that the large lower-tropospheric negative N biases are mainly located in the subtropical eastern oceans and we quantify the contribution of ducting for the first time. The ducting-contributed N biases in the northeast Pacific Ocean (160°–110°W; 15°–45°N) are isolated from other sources of N biases using a two-step geometric-optics simulation. Negative bending angle biases in this region are also observed in COSMIC RO soundings. Both the negative refractivity and bending angle biases in COSMIC soundings mainly lie below ~2 km. Such bending angle biases introduce N biases that are in addition to those caused by ducting. Following the increasing PBL height from the southern California coast westward to Hawaii, centers of maxima bending angles and N biases tilt southwestward. In areas where ducting conditions prevail, ducting is the major cause of the RO N biases. Ducting-induced N biases with reference to ERA-I compose over 70% of the total negative N biases near the southern California coast, where strongest ducting conditions prevail, and decrease southwestward to less than 20% near Hawaii.

Description: In groundwater-limited settings, such as Puerto Rico and other Caribbean islands, societal, ecological, and agricultural water needs depend on regular rainfall. Though long-range numerical weather predication models explicitly predict precipitation, such quantitative precipitation forecasts (QPF) critically failed to detect the historic 2015 Caribbean drought. Consequently, this work examines the feasibility of developing a drought early warning tool using the Gálvez–Davison index (GDI), a tropical convective potential index, derived from the Climate Forecast System, version 2 (CFSv2). Drought forecasts are focused on Puerto Rico’s early rainfall season (ERS; April–July), which is susceptible to intrusions of strongly stable Saharan air and represents the largest source of hydroclimatic variability for the island. A fully coupled atmosphere–ocean–land model, the CFSv2 can plausibly detect the transatlantic advection of low-GDI Saharan air with multimonth lead times. The mean ERS GDI is calculated from semidaily CFSv2 forecasts beginning 1 January of each year between 2012 and 2018 and monitored as the initialization approaches 1 April. The CFSv2 demonstrates a broad region of statistically significant correlations with observed GDI across the eastern Caribbean up to 30 days prior to the ERS. During 2015, the CFSv2 forecast a low-GDI tongue extending across the Atlantic toward the Caribbean with 60–90 days lead time and placed Puerto Rico’s 2015 ERS beneath the 15th percentile of all 1982–2018 ERS forecasts with up to 30 days lead time. A preliminary GDI-based QPF tool tested herein is a statistically significant improvement over climatology for the driest years.

Description: Using extensive hindcasts from seasonal prediction systems participating in the North American Multi-Model Ensemble (NMME), possible causes for low skill in predicting seasonal mean precipitation over California during December–February (DJF) are investigated. The analysis focuses on investigating two possibilities for low prediction skill: role model biases or inherent predictability limits. The motivation for the analysis was the seasonal prediction during DJF 2015/16 that called for enhanced probability for above normal precipitation over southern California (which was consistent with expected conditions during an extreme El Niño) while the observed precipitation was below normal. Based on various analysis approaches and using hindcast datasets from multiple seasonal prediction systems, we build up the evidence that low skill in predicting seasonal mean precipitation over California is likely to be due to inherent predictability associated with a low signal-to-noise (SNR) regime. For the same set of seasonal prediction systems, the precipitation variability over California is contrasted with that over the southeast United States where prediction skill, as well as the SNR, is higher. The discussion also notes that building a knowledge base that goes beyond the well-known response to ENSO (based on the linear regression or composite techniques) has proven to be difficult and a systematic approach to reaching resolution to some of the overarching questions is required, and toward that end, a pathway is suggested.

Description: Whether distinct wintertime U.S. climate conditions exist for central-Pacific (CP) versus eastern-Pacific (EP) El Niño events is explored using atmospheric and coupled ocean–atmospheric models. Results using the former agree with most prior studies indicating different U.S. temperature and precipitation patterns associated with El Niño flavors. Causes are traced to equatorial rainfall sensitivity to both magnitudes and spatial patterns of sea surface temperatures (SSTs) distinguishing CP and EP cases. Warmer east equatorial Pacific Ocean SSTs during EP than CP events, specifically for strong EP cases, are responsible for greater east equatorial Pacific rainfall, which displaces tropospheric circulation anomalies eastward over the Pacific–North American region. Weak-amplitude EP cases and all CP events since 1980 fail to excite east equatorial Pacific rainfall, thus not initiating the dynamical chain of effects characterizing strong EP cases. Over the contiguous United States, the difference in tropospheric circulations between strong EP and CP events describes a cyclonic pattern that renders the former colder and wetter. Regional signals include notably colder western and warmer eastern U.S. surface temperatures during EP versus CP events, and higher southwestern and southeastern U.S. precipitation during EP events. We demonstrate the important result—new to studies of observed El Niño flavor impacts—that coupled models largely reproduce the sensitivities of atmospheric models. Confirmed hereby is the realism of prior estimates of El Niño flavor impacts that relied on atmospheric models alone. We further examine predictability of El Niño flavors using coupled forecasts, demonstrating that SST distinctions between CP and EP events and their diverse U.S. wintertime impacts are predictable at least a season in advance.

Description: A satellite-based climatology is presented of 9607 mesoscale convective systems (MCSs) that occurred over the central and southeastern United States from 1996 to 2017. This climatology is constructed with a fully automated algorithm based on their cold cloud shields, as observed from infrared images taken by GOES-East satellites. The geographical, seasonal, and diurnal patterns of MCS frequency are evaluated, as are the frequency distributions and seasonal variability of duration and maximum size. MCS duration and maximum size are found to be strongly correlated, with coefficients greater than 0.7. Although previous literature has subclassified MCSs based on size and duration, we find no obvious threshold that cleanly categorizes MCSs. The Plains and Deep South are identified as two regional modes of maximum MCS frequency, accounting for 21% and 18% of MCSs, respectively, and these are found to differ in the direction and speed of the MCSs (means of 16 and 13 m s−1), their distributions of duration and size (means of 12.2 h, 176 000 km2 and 9.6 h, 108 000 km2), their initial growth rates (means of 7.6 and 6.1 km2 s−1), and many aspects of the seasonal cycle. The lifetime patterns of MCS movement and growth are evaluated for the full domain and for the two regional modes. The growth patterns and strong correlation between size and duration allow for a parabolic function to represent the MCS life cycle quite well in summary statistics. We show that this satellite-based climatology supports previous studies identifying favorable environments for mesoscale convective systems.

Description: A multiscale dynamical model for weather forecasting and climate modeling is developed and evaluated in this study. It extends a previously established layer-averaged, unstructured-mesh nonhydrostatic dynamical core (dycore) to moist dynamics and parameterized physics in a dry-mass vertical coordinate. The dycore and tracer transport components are coupled in a mass-consistent manner, with the dycore providing time-averaged horizontal mass fluxes to passive transport, and tracer transport feeding back to the dycore with updated moisture constraints. The vertical mass flux in the tracer transport is obtained by reevaluating the mass continuity equation to ensure compatibility. A general physics–dynamics coupling workflow is established, and a dycore–tracer–physics splitting strategy is designed to couple these components in a flexible and efficient manner. In this context, two major physics–dynamics coupling strategies are examined. Simple-physics packages from the 2016 Dynamical Core Model Intercomparison Project (DCMIP2016) experimental protocols are used to facilitate the investigation of the model behaviors in idealized moist-physics configurations, including cloud-scale modeling, weather forecasting, and climate modeling, and in a real-world test-case setup. Performance evaluation demonstrates that the model is able to produce reasonable sensitivity and variability at various spatiotemporal scales. The consideration and implications of different physics–dynamics coupling options are discussed within this context. The appendix provides discussion on the energetics in the continuous- and discrete-form equations of motion.

Description: This study investigates the shapes and fall speeds of freezing and frozen raindrops through field observations using an instrument called the high-speed optical disdrometer (HOD) that we developed recently. Our field observations showed that while the shapes of all of the observed freezing raindrops and a portion of the frozen raindrops (39% of the frozen raindrops that are larger than 1.0 mm in volume equivalent diameter D) resemble the shapes of warm raindrops, majority of frozen raindrops (61% of the frozen raindrops with D 〉 1.0 mm) exhibited a distinct feature such as a spicule, bulge, cavity, or aggregation. Field observations of axis ratios (i.e., ratio of the vertical to horizontal chord) and fall speeds were compared with the predictions of available models. Separate empirical axis ratio parameterizations were developed for the freezing and frozen raindrops using the HOD field observations and extensions to an available shape model were also incorporated. For the fall speeds of freezing and frozen raindrops, field observations demonstrated a good agreement with the predictions of the available parameterizations. Frozen raindrops showed a larger scatter of fall speeds around the mean fall speed of a given drop size than those of the freezing raindrops due to the shape variety among the frozen raindrops with the aforementioned distinct features. The drag coefficients for the observed hydrometeors were compared with the predictions of the available drag coefficient models. Separate “drag coefficient–Reynolds number” relationships for freezing and frozen raindrops were developed.

Description: Soil moisture influences precipitation mainly through its impact on land–atmosphere interactions. Understanding and correctly modeling soil moisture–precipitation (SM–P) coupling is crucial for improving weather forecasting and subseasonal to seasonal climate predictions, especially when predicting the persistence and magnitude of drought. However, the sign and spatial structure of SM–P feedback are still being debated in the climate research community, mainly due to the difficulty in establishing causal relationships and the high degree of nonlinearity in land–atmosphere processes. To this end, we developed a causal inference model based on the Granger causality analysis and a nonlinear machine learning model. This model includes three steps: nonlinear anomaly decomposition, nonlinear Granger causality analysis, and evaluation of the quality of SM–P feedback, which eliminates the nonlinear response of interannual and seasonal variability and the memory effects of climatic factors and isolates the causal relationship of local SM–P feedback. We applied this model by using National Climate Assessment–Land Data Assimilation System (NCA-LDAS) datasets over the United States. The results highlight the importance of nonlinear atmosphere responses in land–atmosphere interactions. In addition, the strong feedback over the southwestern United States and the Great Plains both highlight the impacts of topographic factors rather than only the sensitivity of evapotranspiration to soil moisture. Furthermore, the SM–P index defined by our framework is used to benchmark Earth system models (ESMs), which provides a new metric for efficiently identifying potential model biases in modeling local land–atmosphere interactions and may help the development of ESMs in improving simulations of water cycle variability and extremes.

Description: Previous studies linked the increase of the middle and low reaches of the Yangtze River (MLRYR) rainfall to tropical Indian Ocean warming during extreme El Niños’ (e.g., 1982/83 and 1997/98 extreme El Niños) decaying summer. This study finds the linkage to be different for the recent 2015/16 extreme El Niño’s decaying summer, during which the above-normal rainfalls over MLRYR and northern China are respectively linked to southeastern Indian Ocean warming and western tropical Indian Ocean cooling in sea surface temperatures (SSTs). The southeastern Indian Ocean warming helps to maintain the El Niño–induced anomalous lower-level anticyclone over the western North Pacific Ocean and southern China, which enhances moisture transport to increase rainfall over MLRYR. The western tropical Indian Ocean cooling first enhances the rainfall over central-northern India through a regional atmospheric circulation, the latent heating of which further excites a midlatitude Asian teleconnection pattern (part of circumglobal teleconnection) that results in an above-normal rainfall over northern China. The western tropical Indian Ocean cooling during the 2015/16 extreme El Niño is contributed by the increased upward latent heat flux anomalies associated with enhanced surface wind speeds, opposite to the earlier two extreme El Niños.

Description: The adequate simulation of internal climate variability is key for our understanding of climate as it underpins efforts to attribute historical events, predict on seasonal and decadal time scales, and isolate the effects of climate change. Here the skill of models in reproducing observed modes of climate variability is assessed, both across and within the CMIP3, CMIP5, and CMIP6 archives, in order to document model capabilities, progress across ensembles, and persisting biases. A focus is given to the well-observed tropical and extratropical modes that exhibit small intrinsic variability relative to model structural uncertainty. These include El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), the North Atlantic Oscillation (NAO), and the northern and southern annular modes (NAM and SAM). Significant improvements are identified in models’ representation of many modes. Canonical biases, which involve both amplitudes and patterns, are generally reduced across model generations. For example, biases in ENSO-related equatorial Pacific sea surface temperature, which extend too far westward, and associated atmospheric teleconnections, which are too weak, are reduced. Stronger tropical expression of the PDO in successive CMIP generations has characterized their improvement, with some CMIP6 models generating patterns that lie within the range of observed estimates. For the NAO, NAM, and SAM, pattern correlations with observations are generally higher than for other modes and slight improvements are identified across successive model generations. For ENSO and PDO spectra and extratropical modes, changes are small compared to internal variability, precluding definitive statements regarding improvement.

Description: The atmospheric circulation during the South Asian summer monsoon season is analyzed in moist isentropic coordinates. The horizontal mass transport is sorted in terms of its equivalent potential temperature and is separated into the upper- and lower-tropospheric contributions. This technique makes it possible to trace the transport of air parcels over long distances, identify regions of convective motion in the tropics, and assess the impacts of diabatic processes. The goal here is to assess the thermodynamic characteristics of the atmospheric overturning associated with the South Asian monsoon and to connect this thermodynamic structure to horizontal transport. The monsoon is associated with a low-level inflow of warm and moist air, compensated by an upper-tropospheric outflow at high potential temperature. The South Asian monsoon differs, however, from other monsoonal systems in two important ways. First, the ascending air exhibits an unusually high equivalent potential temperature, which results in global lifting of the tropopause during the boreal summer. Second, on a seasonal basis the main monsoon regions appear to be shielded from dry air intrusion from the extratropical regions.

Description: The last comprehensive statistics of tornadoes in northern Eurasia (NE) were published more than 30 years ago. This paper introduces a new database of tornadoes in NE that spans from the tenth century to 2016. The database, compiled using various sources, contains 2879 tornado cases over land and water and includes tornado characteristics. Tornadoes are common for most regions of NE, with a density reaching four cases per 104 km2 in 1900–2016 in some regions. Tornadoes over land have distinct annual and diurnal cycles: they form mostly in May–August, with a maximum in June, and during daytime, with a maximum at 1700–1800 local time. Waterspouts form in all months with a maximum in late summer and mostly at 0900–1300 local time. Most tornadoes are weak and short lived. The Fujita-scale intensity is ≤F1 for 80% and ≥F3 for 3% out of all rated tornadoes. Half last less than 10 min. The average annual number of all tornadoes over land is around 150, including 10 and 2 tornadoes with ≥F2 and ≥F3 intensity, respectively. Annually, 1–2 tornadoes lead to casualties and result in 2.9 fatalities and 36.3 injuries. Despite the incompleteness of the dataset, our results show that tornadoes in NE, although being rare, are not as extremely rare as has been thought before. The results illustrate the substantial underestimation of tornado threat by the general public, researchers, and meteorologists, and unambiguously indicate the need for systematic assessments and forecasting of tornadoes by national weather services.

Description: Proverbs are a part of traditional knowledge that has been increasingly acknowledged to be a valuable source of information for environmental policies. Proverbs on weather convey the cumulated experience of generations that provide guidelines for agricultural practices, everyday decisions, and other situations. Besides the value the proverbs have in their cultural setting, they also serve as an indicator of objective meteorological patterns. This study presents a comprehensive evaluation of the Polish temperature-related proverbs. From the collected corpus of more than 2000 Polish proverbs, 28 were related to temperature and provided concrete predictions and so were selected for further analysis. The proverbs were tested on the basis of temperature (minimum, maximum, and mean) data from 20 weather stations, located in Poland and the neighboring countries, for the period of 1951–2012. Harbingers and forecasts were identified and coded as 0 or 1. Proverb accuracies were then compared using Heidke skill scores and proportions of fulfilled proverbs. The proverbs’ spatial and temporal contingencies were tested via generalized linear mixed models. Some proverbs provided a high proportion (up to 79%) of fulfilled proverbs. Furthermore, the accuracy of the proverbs was reversely proportional to chronological date (decreased with time), with values increasing toward the east and north directions of station locations. The observed changes in proverb accuracies may be attributed to the shift of Polish borders following the Second World War and the respective migration of the population.

Description: The evaluation of the ocean energy balance is crucial for improving the fundamental understanding of the mechanisms sustaining ocean circulation. Based on the outputs of the ROMS ocean model, the energy cycle, eddy–mean flow interactions, and energy pathways of the deep Gulf of Mexico (GoM) have been investigated in this study. The theoretical framework for the analysis is based on the energy equations for the time-mean and time-varying flow, where some of the terms were split into their horizontal and vertical components to monitor the energy pathways. Of the energy maintaining deep kinetic energy (KE), approximately 75% is transferred from the upper layer to the deep layer by vertical pressure work (PW), about 6% by the horizontal PW through the Yucatan and Florida straits, and ~19% is generated through the processes related to baroclinic instabilities. The mean circulation generates eddies in the upper layer, while eddies drive mean circulation in the deep layer. Energy is transferred downward in the eastern and western part of the Gulf, upward in the deep western-central part, and a strong westward energy transport can be observed below 2000-m depth.

Description: The response of a coastal ocean numerical model, typical of eastern boundaries, is investigated under upwelling-favorable wind forcing and with/without the presence of a submarine canyon. Experiments were run over three contrasting shelf depth/slope bathymetries and forced by an upwelling-favorable alongshore wind. Random noise in the wind stress field was used to trigger the onset of frontal instabilities, which formed around the upwelling front. Their development and evolution are enhanced over deeper (and less inclined) shelves. Experiments without a submarine canyon agree well with previous studies of upwelling frontal instabilities; baroclinic instabilities grow along the front in time. The addition of a submarine canyon incising the continental shelf dramatically changes the circulation and frontal characteristics. Intensified upwelling is channeled through the downstream side of the canyon in all depth/slope configurations. Farther downstream a downwelling area is generated, being larger and stronger on a shallow shelf. The canyon affects mainly the location of the southward upwelling jet, which is deflected inshore and accelerated after passing over the canyon. This process is accompanied by a break in the alongshore scale of the instabilities on either side of the canyon. Term balances of the depth-averaged cross-shore momentum equation reaffirm the downstream acceleration of the jet and the increased wavelength of the instabilities, and clarify the dominant balance between the advection and ageostrophic terms around the canyon.

Description: Changes in tropical width can have important consequences in sectors including ecosystems, agriculture, and health. Observations suggest tropical expansion over the past 30 years although studies have not agreed on the magnitude of this change. Climate model projections have also indicated an expansion and show similar uncertainty in its magnitude. This study utilizes an objective, longitudinally varying, tropopause break method to define the extent of the tropics at upper levels. The location of the tropopause break is associated with enhanced stratosphere–troposphere exchange and thus its structure influences the chemical composition of the stratosphere. The method shows regional variations in the width of the upper-level tropics in the past and future. Four modern reanalyses show significant contraction of the tropics over the eastern Pacific between 1981 and 2015, and slight but significant expansion in other regions. The east Pacific narrowing contributes to zonal mean narrowing, contradicting prior work, and is attributed to the use of monthly and zonal mean data in prior studies. Six global climate models perform well in representing the climatological location of the tropical boundary. Future projections show a spread in the width trend (from ~0.5° decade−1 of narrowing to ~0.4° decade−1 of widening), with a narrowing projected across the east Pacific and Northern Hemisphere Americas. This study illustrates that this objective tropopause break method that uses instantaneous data and does not require zonal averaging is appropriate for identifying upper-level tropical width trends and the break location is connected with local and regional changes in precipitation.

Description: Global surface warming since 1850 has consisted of a series of slowdowns (hiatus) followed by surges. Knowledge of a mechanism to explain how this occurs would aid development and testing of interannual to decadal climate forecasts. In this paper a global climate model is forced to adopt an ocean state corresponding to a hiatus [with negative interdecadal Pacific oscillation (IPO) and other surface features typical of a hiatus] by artificially increasing the background diffusivity for a decade before restoring it to its normal value and allowing the model to evolve freely. This causes the model to develop a decadal surge that overshoots equilibrium (resulting in a positive IPO state), leaving behind a modified, warmer climate for decades. Water-mass transformation diagnostics indicate that the heat budget of the tropical Pacific Ocean is a balance between large opposite-signed terms: surface heating/cooling resulting from air–sea heat flux is balanced by vertical mixing and ocean heat transport divergence. During the artificial hiatus, excess heat becomes trapped just above the thermocline and there is a weak vertical thermal gradient (due to the high artificial background mixing). When the hiatus is terminated, by returning the background diffusivity to normal, the thermal gradient strengthens to prehiatus values so that the mixing (diffusivity × thermal gradient) remains roughly constant. However, since the base layer just above the thermocline remains anomalously warm, this implies a warming of the entire water column above the trapped heat, which results in a surge followed by a prolonged period of elevated surface temperatures.

Description: The Atmospheric Infrared Sounder (AIRS) on board NASA’s Aqua satellite provides more than 16 years of data. Its monthly gridded (Level 3) product has been widely used for climate research and applications. Since counts of successful soundings in a grid cell are used to derive monthly averages, this averaged by observations (ABO) approach effectively gives equal importance to all participating soundings within a month. It is conceivable then that days with more observations due to day-to-day orbit shift and regimes with better retrieval skills will contribute disproportionately to the monthly average within a cell. Alternatively, the AIRS Level 3 monthly product can be produced through an averaged by days (ABD) approach, where the monthly mean in a grid cell is a simple average of the daily means. The effects of these averaging methods on the AIRS version 6 monthly product are assessed quantitatively using temperature and water vapor at the surface and 500 hPa. The ABO method results in a warmer (slightly colder) global mean temperature at the surface (500 hPa) and a drier global mean water vapor than ABD method. The AIRS multiyear monthly mean temperature and water vapor from both methods are also compared with the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) product and evaluated with a simulation experiment, indicating the ABD method has lower error and is more closely correlated with MERRA-2. In summary, the ABD method is recommended for future versions of the AIRS Level 3 monthly product and more data services supporting Level 3 aggregation are needed.

Description: An ensemble-based linearized forecast model has been developed for data assimilation applications for numerical weather prediction. Previous studies applied this local ensemble tangent linear model (LETLM) to various models, from simple one-dimensional models to a low-resolution (~2.5°) version of the Navy Global Environmental Model (NAVGEM) atmospheric forecast model. This paper applies the LETLM to NAVGEM at higher resolution (~1°), which required overcoming challenges including 1) balancing the computational stencil size with the ensemble size, and 2) propagating fast-moving gravity modes in the upper atmosphere. The first challenge is addressed by introducing a modified local influence volume, introducing computations on a thin grid, and using smaller time steps. The second challenge is addressed by applying nonlinear normal mode initialization, which damps spurious fast-moving modes and improves the LETLM errors above ~100 hPa. Compared to a semi-Lagrangian tangent linear model (TLM), the LETLM has superior skill in the lower troposphere (below 700 hPa), which is attributed to better representation of moist physics in the LETLM. The LETLM skill slightly lags in the upper troposphere and stratosphere (700–2 hPa), which is attributed to nonlocal aspects of the TLM including spectral operators converting from winds to vorticity and divergence. Several ways forward are suggested, including integrating the LETLM in a hybrid 4D variational solver for a realistic atmosphere, combining a physics LETLM with a conventional TLM for the dynamics, and separating the LETLM into a sequence of local and nonlocal operators.

Description: In data assimilation for NWP, accurate estimation of error covariance matrices (ECMs) and their use are essential to improve NWP accuracy. The objective of this study is to estimate ECMs of all observations and background variables using sampling statistics, and improve global NWP accuracy by using them. This study presents the first results of such all ECM refinement. ECM diagnostics combining multiple methods, and analysis and forecast cycle experiments were performed on the JMA global NWP system, where diagonal components of all ECMs and off-diagonal components of radiance observations are refined. The ECM diagnostic results are as follows: 1) the diagnosed error standard deviations (SDs) are generally much smaller than those of the JMA operational system (CNTL); 2) interchannel correlations in humidity-sensitive radiance errors are much larger than 0.2; and 3) horizontal correlation distances of AMSU-A are ~50 km, excluding channel 4. The experimental results include the following: 1) the diagnosed ECMs generally improve forecast accuracy over CNTL even without additional tunings; 2) the supplemental tuning parameter, which is the deflation factor (0.6 in SD) applied for the estimated ECMs of nonsatellite conventional data and GPS radio occultation data, statistically significantly improves forecast accuracy; 3) this value 0.6 is set as the same value as the ratio of the estimated background error SD to that in CNTL; 4) high-density assimilation (10 times) of AMSU-A is better than CNTL, not better than that with 5 times; and 5) ECMs estimated using boreal summer data can improve forecast accuracy in winter, which indicates their robustness.

Description: In the beginning of the twenty-first century, weather and climate extremes occurred more and more in extratropical summer, linked to the magnified amplitudes of quasi-stationary waves and external forcing. The study analyzes the relations between multidecadal extratropical extremes in boreal late summer and the North Atlantic (NA; 35°–65°N, 40°W–0°) multidecadal variability (NAMV) in the mid- to high latitudes. The results show that multidecadal extratropical extremes link with the intensified NAMV and the related positive–negative–positive (+ − +) zonal mode of sea surface temperature (SST). 1) The SST mode favors the eastward shift of the negative-phase NA oscillation (NNAO), with a latitudinal pattern of cyclone anomalies over the western European coast and anticyclones over Greenland; NNAO is helpful to baroclinic energy transfer and a longitudinal wavelike pattern. 2) The SST mode and the eddy-driven jet of NNAO are conducive to a southeast extension of the NA jet in close conjunction with the Afro-Asian jet, thereby enhancing the jet waveguide and barotropic energy transfer for the maintenance of a low-frequency wave. 3) The effect of the intensified NAMV on warming Europe contributes to the longitudinal temperature gradient–like “cooling ocean and warming land” pattern, which enhances the meridional wind and wave amplitude of the low-frequency wave. Based on these causes, the intensified NAMV and the + − + SST mode favor the enhancement of the low-frequency wave and quasi-resonant probability, which magnifies the amplitude of the quasi-stationary wave and enhances extratropical extremes on the decadal time scale.

Description: An extensive urban agglomeration has occurred over the Yangtze River delta (YRD) region of East China as a result of rapid urbanization since the middle 1990s. In this study, a 44-yr (i.e., 1975–2018) climatology of the summertime extreme hourly precipitation (EXHP; greater than the 90th percentile) over the YRD is analyzed, using historical land-use data, surface temperature, and hourly rain gauge observations, and then the relationship between rapid urbanization and EXHP changes is examined. Results show significant EXHP contrasts in diurnal variation and storm type roughly before and after middle July. That is, tropical cyclones (TCs) account for 16.4% of the total EXHP hours, 80.5% of which occur during the late summer, whereas non-TC EXHP accounts for 94.7% and 66.2% during the early and late summer, respectively. Increasing trends in occurrence frequency and amount of the non-TC and TC-induced EXHP are detected over the urban agglomeration. Statistically significant larger increasing trends in both the EXHP and surface temperature are observed at urban stations than those at the nearby rural stations. An analysis of 113 locally developed non-TC extreme rainfall events during 2011–18 summers also suggests the contribution of the urban heat island effects to the more occurrences of EXHP, especially over a band-shaped urban region where several major cities are distributed. This study reveals a significant correlation between rapid urbanization and increased EXHP during the past two decades over the YRD region. The results have important implications for understanding the impact of urbanization on EXHP changes in a warming climate.

Description: This study examines climatological potential vorticity streamer (PVS) activity associated with Rossby wave breaking (RWB), which can impact TC activity in the subtropical North Atlantic (NATL) basin via moisture and wind anomalies. PVSs are identified along the 2-PVU (1 PVU = 10−6 K kg−1 m2 s−1) contour on the 350-K isentropic surface, using a unique identification technique that combines previous methods. In total, 21 149 individual PVS instances are identified from the ERA-Interim (ERAI) climatology during June–November over 1979–2015 with a peak in July–August. The total number of PVSs identified in this study is more than previous PVS climatologies for this region, since the new technique identifies a wider range of cases. Variations in PVS size and intensity prompt the development of a new PVS activity index (PVSI), which provides an integrated measure of PVS activity that can improve comparisons with TC activity. For instance, PVSI has a stronger negative correlation with seasonal TC activity (r = −0.55) relative to PVS frequency, size, or intensity alone. PVSI in June–July is also positively correlated with PVSI in August–November (r = 0.67), suggesting predictive capability. Compared to the ERAI and Japan Meteorological Agency 55-Year Reanalysis (JRA-55) climatology, there are more PVSs in the Climate Forecast System Reanalysis (CFSR) but these have weaker average intensity overall. While no long-term trend in PVSI is observed in the ERAI or JRA-55 climatologies, a negative trend is observed in CFSR, which could be related to differences in near tropopause static stability early in the climatological period (1979–86) between the CFSR and ERAI datasets.

Description: This study has developed a rigorous and efficient maximum likelihood method for estimating the parameters in stochastic energy balance models (with any k 〉 0 number of boxes) given time series of surface temperature and top-of-the-atmosphere net downward radiative flux. The method works by finding a state-space representation of the linear dynamic system and evaluating the likelihood recursively via the Kalman filter. Confidence intervals for estimated parameters are straightforward to construct in the maximum likelihood framework, and information criteria may be used to choose an optimal number of boxes for parsimonious k-box emulation of atmosphere–ocean general circulation models (AOGCMs). In addition to estimating model parameters the method enables hidden state estimation for the unobservable boxes corresponding to the deep ocean, and also enables noise filtering for observations of surface temperature. The feasibility, reliability, and performance of the proposed method are demonstrated in a simulation study. To obtain a set of optimal k-box emulators, models are fitted to the 4 × CO2 step responses of 16 AOGCMs in CMIP5. It is found that for all 16 AOGCMs three boxes are required for optimal k-box emulation. The number of boxes k is found to influence, sometimes strongly, the impulse responses of the fitted models.

Description: Initial abstraction (Ia) is a sensitive parameter in hydrological models, and its value directly determines the amount of runoff. Ia, which is influenced by many factors related to antecedent watershed condition (AWC), is difficult to estimate due to lack of observed data. In the Soil Conservation Service curve number (SCS-CN) method, it is often assumed that Ia is 0.2 times the potential maximum retention S. Yet this assumption has frequently been questioned. In this paper, Ia/S and factors potentially influencing Ia were collected from rainfall–runoff events. Soil moisture and evaporation data were extracted from GLDAS-Noah datasets to represent AWC. Based on the driving factors of Ia, identified using the Pearson correlation coefficient and maximal information coefficient, artificial neural network (ANN)-estimated Ia was applied to simulate the selected flood events in the Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) model. The results indicated that Ia/S varies over different events and different watersheds. Over 75% of the Ia/S values are less than 0.2 in the two study areas. The driving factors affecting Ia vary over different watersheds, and the antecedent precipitation index appears to be the most influential factor. Flood simulation by the HEC-HMS model using statistical Ia gives the best fitness, whereas applying ANN-estimated Ia outperforms the simulation with median Ia/S. For over 60% of the flood events, ANN-estimated Ia provided better fitness in flood peak and depth, with an average Nash–Sutcliffe efficiency coefficient of 0.76 compared to 0.71 for median Ia/S. The proposed ANN-estimated Ia is physically based and can be applied without calibration, saving time in constructing hydrological models.

Description: Both to reconcile the large range in satellite-based estimates of the aerosol direct radiative effect (DRE) and to optimize the design of future observing systems, this study builds a framework for assessing aerosol DRE uncertainty. Shortwave aerosol DRE radiative kernels (Jacobians) were derived using the MERRA-2 reanalysis data. These radiative kernels give the differential response of the aerosol DRE to perturbations in the aerosol extinction coefficient, aerosol single-scattering albedo, aerosol asymmetry factor, surface albedo, cloud fraction, and cloud optical depth. This comprehensive set of kernels provides a convenient way to consistently and accurately assess the aerosol DRE uncertainties that result from observational or model-based uncertainties. The aerosol DRE kernels were used to test the effect of simplifying the full vertical profile of aerosol scattering properties into column-integrated quantities. This analysis showed that, although the clear-sky aerosol DRE can be had fairly accurately, more significant errors occur for the all-sky DRE. The sensitivity in determining the broadband spectral dependencies of the aerosol scattering properties directly from a limited set of wavelengths was quantified. These spectral dependencies can be reasonably constrained using column-integrated aerosol scattering properties in the midvisible and near-infrared wavelengths. Separating the aerosol DRE and its kernels by scene type shows that accurate aerosol properties in the clear sky are the most crucial component of the global aerosol DRE. In cloudy skies, determining aerosol properties in the presence of optically thin cloud is more radiatively important than doing so when optically thick cloud is present.

Description: Observations and climate models are combined to identify an anthropogenic warming signature in the upper ocean heat content changes (OHC) since 1971. We apply a new detection and attribution analysis developed by Ribes et al. (2017) which uses a symmetric treatment of the magnitude and the pattern of the climate response to each radiative forcing. A first estimate of the OHC response to natural, anthropogenic, greenhouse gas and other forcing is derived from a large ensemble of CMIP5 simulations. Observational datasets from historical reconstructions are then used to constrain this estimate. A spatio-temporal observational mask is applied to compare simulations with actual observations and to overcome reconstruction biases. Results on the 0-700 m layer from 1971 to 2005 show that the global OHC would have increased since 1971 by 2.12±0.21 10 7 J/ m 2/ y in response to GHG emissions alone. But this has been compensated for by other anthropogenic influences (mainly aerosol), which induced an OHC decrease of 0.84±0.18 10 7 J/ m 2/ y. The natural forcing has induced a slight global OHC decrease since 1971 of 0.13±0.09 10 7 J/ m 2/ y. Compared to previous studies we have separated the effect of the GHG forcing from the effect of the other anthropogenic forcing on OHC changes. This has been possible by using a new D&A method and by analyzing simultaneously the global OHC trends over 1957-1980 and over 1971-2005. This bivariate method takes advantage of the different time variation of the GHG forcing and the aerosol forcing since 1957 to separate both effects and reduce the uncertainty on their estimates.

Description: Open-ocean convection is a common phenomenon that regulates mixed layer depth and ocean ventilation in the high-latitude oceans. However, many climate model simulations overestimate mixed layer depth during open-ocean convection, resulting in excessive formation of dense water in some regions. The physical processes controlling transient mixed layer depth during open-ocean convection are examined using two different numerical models: a high-resolution, turbulence-resolving nonhydrostatic model and a large-scale hydrostatic ocean model. An isolated destabilizing buoyancy flux is imposed at the surface of both models and a quasi-equilibrium flow is allowed to develop. Mixed layer depth in the turbulence-resolving and large-scale models closely aligns with existing scaling theories. However, the large-scale model has an anomalously deep mixed layer prior to quasi-equilibrium. This transient mixed layer depth bias is a consequence of the lack of resolved turbulent convection in the model, which delays the onset of baroclinic instability. These findings suggest that in order to reduce mixed layer biases in ocean simulations, parameterizations of the connection between baroclinic instability and convection need to be addressed.

Description: Stratocumulus clouds constitute one of the largest negative climate forcings in the global radiation budget. This forcing is determined, inter alia, by the cloud liquid water path (LWP), which we analyze using a combination of Gaussian process emulation and mixed-layer theory. For nocturnal, nonprecipitating stratocumuli, we show that LWP steady states constitute an equilibrium primarily between radiative cooling and entrainment warming and drying. These steady states are approached from lower LWPs due to reduced entrainment, while higher LWPs are depleted by stronger entrainment. An analytical solution for the LWP steady state reveals not only the environmental conditions in which a stratocumulus cloud can be maintained, but also distinct analytical properties of the entrainment velocity that are required for a stable LWP steady state that opposes perturbations. In particular, the results highlight the importance of an entrainment velocity that increases strictly monotonically with the LWP if stratocumuli are to attain a stable LWP steady state. This is demonstrated through analysis of two commonly used mixed-layer entrainment parameterizations.

Description: This study presents a high-precision method, using a preconcentrator–gas chromatograph with microelectron capture detector (GC-μECD), to measure SF6 at ambient levels. Carboxen 1000 was used as an adsorbent for the preconcentrator and exhibited a high adsorption efficiency for N2O and SF6 and low adsorption efficiency for O2. This enabled the selective removal of atmospheric O2 from analytes and improved repeatability of the SF6 peak that followed the O2 peak, in a separation column of activated alumina F1. In addition, the increased sensitivity resulting from preconcentrated SF6 improved the signal-to-noise ratio. This led to better analytical precision in comparison with other measurement methods including the conventional and forecut–backflush (FCBF) methods. The precision-to-drift ratios of the conventional, FCBF, and preconcentration methods were 0.11, 0.10, and 0.03, respectively. Analytical precision of the preconcentration method was 0.08% for 10 consecutive injections; this was the best among the three methods. The long-term drift of the SF6 response was inversely proportional to the laboratory pressure. Based on this finding, room pressure can be used to correct for ECD signal drift, with an uncertainty of 0.14% over a 48-h period, using the preconcentration method. Another advantage of the preconcentration method was the excellent linearity of the SF6 response to a wide range of concentrations, including its ambient concentration.

Description: This paper describes the development and analysis of an objective climatology of warm and cold fronts over North America from 1979 to 2018. Fronts are detected by a convolutional neural network (CNN), trained to emulate fronts drawn by human meteorologists. Predictors for the CNN are surface and 850-hPa fields of temperature, specific humidity, and vector wind from the ERA5 reanalysis. Gridded probabilities from the CNN are converted to 2D frontal regions, which are used to create the climatology. Overall, warm and cold fronts are most common in the Pacific and Atlantic cyclone tracks and the lee of the Rockies. In contrast with prior research, we find that the activity of warm and cold fronts is significantly modulated by the phase and intensity of El Niño–Southern Oscillation. The influence of El Niño is significant for winter warm fronts, winter cold fronts, and spring cold fronts, with activity decreasing over the continental United States and shifting northward with the Pacific and Atlantic cyclone tracks. Long-term trends are generally not significant, although we find a poleward shift in frontal activity during the winter and spring, consistent with prior research. We also identify a number of regional patterns, such as a significant long-term increase in warm fronts in the eastern tropical Pacific Ocean, which are characterized almost entirely by moisture gradients rather than temperature gradients.

Description: Tropical Rainfall Measuring Mission (TRMM) satellite products constitute valuable precipitation datasets over regions with sparse rain gauge networks. Downscaling is an effective approach to estimating the precipitation over ungauged areas with high spatial resolution. However, a large bias and low resolution of original TRMM satellite images constitute constraints for practical hydrologic applications of TRMM precipitation products. This study contributes two precipitation downscaling algorithms by exploring the nonstationarity relations between precipitation and various environment factors [daytime surface temperature (LTD), terrain slope, normalized difference vegetation index (NDVI), altitude, longitude, and latitude] to overcome bias and low-resolution constraints of TRMM precipitation. Downscaling of precipitation is achieved with the geographically weighted regression model (GWR) and the backward-propagation artificial neural networks (BP_ANN). The probability density function (PDF) algorithm corrects the bias of satellite precipitation data with respect to spatial and temporal scales prior to downscaling. The principal component analysis algorithm (PCA) provides an alternative method of obtaining accurate monthly rainfall estimates during the wet rainfall season that minimizes the temporal uncertainties and upscaling effects introduced by direct accumulation (DA) of precipitation. The performances of the proposed downscaling algorithms are assessed by downscaling the latest version of TRMM3B42 V7 datasets within Hubei Province from 0.25° (about 25 km) to 1-km spatial resolution at the monthly scale. The downscaled datasets are systematically evaluated with in situ observations at 27 rain gauges from the years 2005 through 2010. This paper’s results demonstrate the bias correction is necessary before downscaling. The high-resolution precipitation datasets obtained with the proposed downscaling model with GWR relying on the NDVI and slope are shown to improve the accuracy of precipitation estimates. GWR exhibits more accurate downscaling results than BP_ANN coupled with the genetic algorithm (GA) in most dry and wet seasons.

Description: Seasonal changes in grass cover impact the generation of surface runoff due to the effects of grass roots on soil hydrologic properties and processes (i.e., infiltration). Using a rainfall simulator in a grass field site, we broadly investigated the influence of different initial conditions of soil moisture and grass growth stages on rainfall–runoff transformations. To parameterize the stages of grass growth, we used the height of the vegetation hveg, which is related to the leaf area index. Surprisingly, typical characteristics of runoff formation (peak flow and time to peak flow) were conditioned mainly by hveg. The runoff coefficient decreased about 40% when grass reached its maximum growth and was inversely and significantly related to the height of grass in general. Using the rainfall simulator experiments, we estimated the saturated soil hydraulic conductivity ks, a key parameter of infiltration models. We found strong relationships between ks and hveg when the Philip infiltration model was used, and we proposed a linear relationship between ks and hveg, making ks vary in time with grass growth (i.e., hveg). We compared predictions of hydrologic models at plot scale using ks varying with grass growth with predictions using a constant ks, as hydrological models commonly assume. Neglecting ks variability with grass growth can lead to errors up to 100% in surface runoff predictions at an event time scale and up to 87% at a monthly time scale. Ecohydrological models for runoff predictions should take into account the influence of grass growth dynamics on soil infiltration parameters.

Description: Recent success in assimilating cloud- and precipitation-affected satellite observations using the “all-sky” approach is thought to have benefitted from variational data assimilation, particularly its ability to handle moderate nonlinearity and non-Gaussianity and to extract wind information through the generalized tracer effect. Ensemble assimilation relies on assumptions including linearity and Gaussianity that might cause difficulties when using all-sky observations. Here, all-sky assimilation is evaluated in a global ensemble Kalman filter (EnKF) system of near-operational quality, derived from an operational four-dimensional variational (4D-Var) system. To get EnKF working successfully required a new all-sky observation error model (the most successful approach was to inflate error as a multiple of the ensemble spread) and adjustments to localization. With these improvements, assimilation of eight microwave humidity instruments gave 2%–4% improvement in forecast scores whether using EnKF or 4D-Var. Correlations from the ensemble showed that all-sky observations generated sensitivity to wind, temperature, and humidity. EnKF increments shared many similarities with those in 4D-Var. Hence both 4D-Var and ensemble data assimilation were able to make good use of all-sky observations, including the extraction of wind information. In absolute terms the EnKF forecast performance in the troposphere was still worse than that that with 4D-Var, although the gap could be reduced by going from 50 to 100 ensemble members. EnKF errors were larger in the stratosphere, where there are excessive gravity wave increments that are not connected with all-sky assimilation.

Description: The aim of this study is to investigate extreme precipitation events caused by atmospheric rivers and compare their flood impact in a warmer climate to current climate using an event-based storyline approach. The study was set up by selecting four high-precipitation events from 30 years of present and future climate simulations of the high-resolution global climate model EC-Earth. The two most extreme precipitation events within the selection area for the present and future climate were identified, and EC-Earth was rerun creating 10 perturbed realizations for each event. All realizations were further downscaled with the regional weather prediction model, AROME-MetCoOp. The events were thereafter used as input to the operational Norwegian flood-forecasting model for 37 selected catchments in western Norway, and the magnitude and the spatial pattern of floods were analyzed. The role of the hydrological initial conditions, which are important for the total flooding, were analyzed with a special emphasis on snow and soil moisture excess. The results show that the selected future extreme precipitation events affected more catchments with larger floods, compared to the events from present climate. In addition, multiple realizations of the meteorological forcing and four different hydrological initial conditions, for example, soil saturation and snow storage, were important for the estimation of the maximum flood level. The meteorological forcing (e.g., the internal variability/perturbed output) accounts for the highest contribution to the spread in flood magnitude; however, for some events and catchments the hydrological initial conditions affected the magnitudes of floods more than the meteorological forcing.

Description: We analyzed 24-h accumulated precipitation forecasts over the 4-month period from 1 May to 31 August 2013 over an area located in East Asia covering the region 15.05°–58.95°N, 70.15°–139.95°E generated with the ensemble prediction systems (EPS) from ECMWF, NCEP, UKMO, JMA, and CMA contained in the TIGGE dataset. The forecasts are first evaluated with the Method for Object-Based Diagnostic Evaluation (MODE). Then a multimodel ensemble (MME) forecast technique that is based on weights derived from object-based scores is investigated and compared with the equally weighted MME and the traditional gridpoint-based MME forecast using weights derived from the point-to-point metric, mean absolute error (MAE). The object-based evaluation revealed that attributes of objects derived from the ensemble members of the five individual EPS forecasts and the observations differ consistently. For instance, their predicted centroid location is more southwestward, their shape is more circular, and their orientation is more meridional than in the observations. The sensitivity of the number of objects and their attributes to methodological parameters is also investigated. An MME prediction technique that is based on weights computed from the object-based scores, median of maximum interest, and object-based threat score is explored and the results are compared with the ensemble forecasts of the individual EPS, the equally weighted MME forecast, and the traditional superensemble forecast. When using MODE statistics for the forecast evaluation, the object-based MME prediction outperforms all other predictions. This is mainly because of a better prediction of the objects’ centroid locations. When using the precipitation-based fractions skill score, which is not used in either of the weighted MME forecasts, the object-based MME forecasts are slightly better than the equally weighted MME forecasts but are inferior to the traditional superensemble forecast that is based on weights derived from the point-to-point metric MAE.

Description: The upper Indus River basin is characterized by biseasonal heavy precipitation falling on the foothills of major mountain ranges (Hindu Kush, Karakorm, Himalayas). Numerical studies have confirmed the importance of topography for the triggering of precipitation and investigated the processes responsible for specific events, but a systematic and cross-seasonal analysis has yet to be conducted. Using ERA5 reanalysis data and statistical methods, we show that more than 80% of the precipitation variability is explained by southerly moisture transport at 850 and 700 hPa, along the Himalayan foothills. We conclude that most of the precipitation is generated by the forced uplift of a cross-barrier flow. This process explains both wet seasons, despite different synoptic conditions, but is more important in winter. The precipitation signal is decomposed into the contribution of each altitude and each variable (wind and moisture), which exhibit different seasonality. The winter wet season is dominated by moisture transport at higher altitude, and is triggered by an increase in wind. By contrast, the summer wet season is explained by an increase in moisture at both altitudes, while wind is of secondary importance. Selected CMIP6 climate models are able to represent the observed links between precipitation and southerly moisture transport, despite important seasonal biases that are due to a misrepresentation of the seasonality in the magnitude of the southerly wind component.

Description: The Pacific–North American (PNA) teleconnection pattern has been linked both to tropical phenomena, including the Madden–Julian oscillation (MJO) and El Niño–Southern Oscillation (ENSO), and to internal extratropical processes, including interactions with the zonally varying basic state and synoptic eddies. Many questions remain, however, concerning how these various relationships act, both separately and together, to yield observed PNA variability. Using linear inverse modeling (LIM), this study finds that the development and amplification of PNA anomalies largely results from the interference of modes strongly coupled to sea surface temperatures (SST), such as ENSO, and modes internal to the atmosphere, including the MJO. These SST-coupled and “internal atmospheric” modes form subspaces that are not orthogonal, and PNA growth is shown to occur via non-normal interactions. An internal atmospheric space LIM is developed to examine growth beyond this interference by removing the SST-coupled modes, effectively removing ENSO and retaining MJO variability. Optimal PNA growth in the internal atmospheric space LIM is driven by MJO heating, particularly over the Indian Ocean, and a retrograding northeast Pacific streamfunction anomaly. Additionally, the individual contributions of tropical heating and the extratropical circulation on PNA growth are investigated. The non-normal PNA growth is an important result, demonstrating the difficulty in partitioning PNA variance into contributions from different phenomena. This cautionary result is likely applicable to many geophysical phenomena and should be considered in attribution studies.

Description: Meridional overturning circulation (MOC) is vital to distributing heat, freshwater, and dissolved matter in semienclosed deep marginal seas such as the East Sea (ES) (Sea of Japan). As our understanding of the ES MOC remains incomplete, we attempted to fill this research gap. We analyzed the ES MOC and its decadal change (1993–2012), employing Hybrid Coordinate Ocean Model (HYCOM) global reanalysis. We found that the ES MOC, consisting of two counterrotating overturning cells in the late 1990s, changed into a single full-depth cell in the 2000s and reverted to two cells in the 2010s. The decadal change relates to weakening of the southward western boundary current at the intermediate layer and northward eastern boundary currents at the deep abyssal layer. We propose that surface warming and salinification favored reduced intermediate water formation and enhanced bottom water formation in the northwestern ES in the 2000s and were, therefore, key to the decadal change. Conditions unfavorable to intermediate water formation and favorable to bottom water formation in the winters of the 2000s, compared with the late 1990s, enhanced northward (westward) Ekman transport in the southern (northeastern) ES, successive advection of surface warm, saline water into water formation areas, and air–sea heat and freshwater exchanges linked to the January Arctic Oscillation. Our results indicated that the ES MOC is sensitive to both external atmospheric forcing and internal ES processes, which have implications for significant changes in the response of other marginal seas and global oceans to future climate variability.