Rawinsonde Observations Research Articles

The Evaluation of Global and Regional Applications of Model for Prediction Across Scales-Atmosphere (MPAS) Against Weather Research Forecast (WRF) Model over California for a Winter (2013 DISCOVER-AQ) and Summer (2016 CABOTS) Episode

The Model for Prediction Across Scales-Atmosphere (MPAS) was used to simulate meteorological conditions for a two-week winter episode during 10–23 January 2013, and a two-week summer episode during 18–31 July 2016, using both as a global model and a regional model with a focus on California. The results of both global and regional applications of MPAS were compared against the surface and upper air rawinsonde observations while the variations of characteristic meteorological variables and modeling errors were evaluated in space, time, and statistical sense. The results of the Advanced Weather Research and Forecast (WRF-ARW, hereafter WRF) model simulations for the same episodes were also used to evaluate the results of both applications of MPAS. The temporal analyses performed at surface stations indicate that both global and regional applications of MPAS and WRF model predict the diurnal evolution of characteristic meteorological parameters reasonably well in both winter and summer episodes studied here. The average diurnal bias in predicting 2 m temperature by MPAS and WRF are about the same with a maximum of 2 °C in winter and 1 °C in summer while that of 2 m mixing ratio is within 1 g/kg for all three modeling applications. The rawinsonde profiles of temperature, dew point temperature, and wind direction agree reasonably well with observations while wind speed is underestimated by all three applications. The comparisons of the spatial distribution of anomaly correlation and mean bias errors calculated from each model results for 2 m temperature, 2 m water vapor mixing ratio, 10 m wind speed and wind direction indicate that all three models have similar magnitudes of agreement with observations as well as errors away from observations throughout California.

Empirical Evidence for the Frontal Modification of Atmospheric Boundary Layer Depth Variability over Land

Abstract Despite many observational studies on the atmospheric boundary layer (ABL) depth zi variability across various time scales (e.g., diurnal, seasonal, annual, and decadal), zi variability before, during, and after frontal passages over land, or simply zi variability as a function of weather patterns, has remained relatively unexplored. In this study, we provide an empirical framework using 5 years (2014–18) of daytime rawinsonde observations and surface analyses over 18 central and southeastern U.S. sites to report zi variability across frontal boundaries. By providing systematic observations of front-relative contrasts in zi (i.e., zi differences between warm and cold sectors, ) and boundary layer moisture (i.e., ABL-q) regimes in summer and winter, we propose a new paradigm to study zi changes across cold-frontal boundaries. For most cases, we found deeper zi over the warm sector than the cold sector in both summer and winter, although with significant site-to-site variability in Δzi. Additionally, our results show a positive ΔqABL (i.e., frontal contrasts in ABL-q) in summer and winter, supporting what is typically observed in midlatitude cyclones. We found that a front-relative ΔqABL of 1 g kg−1 often yielded at least a 100-m Δzi across the frontal boundary in both summer and winter. This work provides a synoptic-scale basis for zi variability and establishes a foundation for model verification to examine the impact of airmass exchange associated with advection on zi. This work will advance our understanding of ABL processes in synoptic environments and help unravel sources of front-relative zi variability. Significance Statement The atmospheric boundary layer (ABL) is the lowermost part of the atmosphere adjacent to Earth’s surface. The irregular motion of air inside the ABL plays an essential role in relocating air near the surface to the free troposphere. Meteorologists use ABL depth in weather forecast models to determine the atmosphere’s ability to dilute or enrich tracers within the ABL. However, knowledge about the changes in ABL depth during stormy conditions remains incomplete. Here, we investigate how the ABL depth varies before and after cold-frontal passages. We found that ABL depths were much deeper before the cold-frontal passages than after. This knowledge will help us develop new approaches to consider how storms modify the ABL in weather forecast models.

Analysis of atmospheric temperature data by 4D spatial\u2013temporal statistical model

The meteorological data such as temperature of the upper atmosphere is ssential for accurate weather forecasting. The Universal Rawinsonde Observation Program (RAOB) establishes an extensive radiosonde network worldwide to observe atmospheric meteorological data from the surface to the low stratosphere. The RAOB data data has very high accuracy but can offer a very limited spatial coverage. Meanwhile, ERA-Interim reanalysis data is widely available but with low-quality. We propose a 4D spatiotemporal statistical model which can make effective inferences from ERA-Interim reanalysis data to RAOB data. Finally, we can obtain a huge amount of RAOB data with high-quality and can offer a very wide spatial coverage. In empirical research, we collected data from 200 launch sites around the world in January 2015. The 4D spatiotemporal statistical model successfully analyzed the observation gaps at different pressure levels.

Global climatology and trends in convective environments from ERA5 and rawinsonde data

Globally, thunderstorms are responsible for a significant fraction of rainfall, and in the mid-latitudes often produce extreme weather, including large hail, tornadoes and damaging winds. Despite this importance, how the global frequency of thunderstorms and their accompanying hazards has changed over the past 4 decades remains unclear. Large-scale diagnostics applied to global climate models have suggested that the frequency of thunderstorms and their intensity is likely to increase in the future. Here, we show that according to ERA5 convective available potential energy (CAPE) and convective precipitation (CP) have decreased over the tropics and subtropics with simultaneous increases in 0–6 km wind shear (BS06). Conversely, rawinsonde observations paint a different picture across the mid-latitudes with increasing CAPE and significant decreases to BS06. Differing trends and disagreement between ERA5 and rawinsondes observed over some regions suggest that results should be interpreted with caution, especially for CAPE and CP across tropics where uncertainty is the highest and reliable long-term rawinsonde observations are missing.

Comparison of Convective Parameters Derived from ERA5 and MERRA-2 with Rawinsonde Data over Europe and North America

AbstractIn this study we compared 3.7 million rawinsonde observations from 232 stations over Europe and North America with proximal vertical profiles from ERA5 and MERRA-2 to examine how well reanalysis depicts observed convective parameters. Larger differences between soundings and reanalysis are found for thermodynamic theoretical parcel parameters, low-level lapse rates, and low-level wind shear. In contrast, reanalysis best represents temperature and moisture variables, midtropospheric lapse rates, and mean wind. Both reanalyses underestimate CAPE, low-level moisture, and wind shear, particularly when considering extreme values. Overestimation is observed for low-level lapse rates, midtropospheric moisture, and the level of free convection. Mixed-layer parcels have overall better accuracy when compared to most-unstable parcels, especially considering convective inhibition and lifted condensation level. Mean absolute error for both reanalyses has been steadily decreasing over the last 39 years for almost every analyzed variable. Compared to MERRA-2, ERA5 has higher correlations and lower mean absolute errors. MERRA-2 is typically drier and less unstable over central Europe and the Balkans, with the opposite pattern over western Russia. Both reanalyses underestimate CAPE and CIN over the Great Plains. Reanalyses are more reliable for lower elevation stations and struggle along boundaries such as coastal zones and mountains. Based on the results from this and prior studies we suggest that ERA5 is likely one of the most reliable available reanalyses for exploration of convective environments, mainly due to its improved resolution. For future studies we also recommend that computation of convective variables should use model levels that provide more accurate sampling of the boundary layer conditions compared to less numerous pressure levels.

Sensitivity of Snowfall Characteristics to Meteorological Conditions in the Yeongdong Region of Korea

This study investigates the characteristics of cold clouds and snowfall in both the Yeongdong coastal and mountainous regions under different meteorological conditions based on the integration of numerical modeling and three-hourly rawinsonde observations with snow crystal photographs for a snowfall event that occurred on 29−30 January 2016. We found that rimed particles predominantly observed turned into dendrite particles in the latter period of the episode when the 850 hPa temperature decreased at the coastal site, whereas the snow crystal habits at the mountainous site were largely needle or rimed needle. Rawinsonde soundings showed a well-defined, two-layered cloud structure along with distinctive wind-directional shear, and an inversion in the equivalent potential temperature above the low-level cloud layer. The first experiment with a decrease in lower-layer temperature showed that the low-level cloud thickness was reduced to less than 1.5 km, and the accumulated precipitation was decreased by 87% compared with the control experiment. The difference in precipitation amount between the single-layered experiment and control experiment (two-layered) was not so significant to attribute it to the effect of the seeder−feeder mechanism. The precipitation in the last experiment by weakening wind-directional shear was increased by 1.4 times greater than the control experiment specifically at the coastal site, with graupel particles accounting for the highest proportion (~62%). The current results would improve snowfall forecasts in complicated geographical environments such as Yeongdong in terms of snow crystal habit as well as snowfall amount in both time and space domains.

GEO–GEO Stereo-Tracking of Atmospheric Motion Vectors (AMVs) from the Geostationary Ring

Height assignment is an important problem for satellite measurements of atmospheric motion vectors (AMVs) that are interpreted as winds by forecast and assimilation systems. Stereo methods assign heights to AMVs from the parallax observed between observations from different vantage points in orbit while tracking cloud or moisture features. In this paper, we fully develop the stereo method to jointly retrieve wind vectors with their geometric heights from geostationary satellite pairs. Synchronization of observations between observing systems is not required. NASA and NOAA stereo-winds codes have implemented this method and we processed large datasets from GOES-16, -17, and Himawari-8. Our retrievals are validated against rawinsonde observations and demonstrate the potential to improve the forecast skill. Stereo winds also offer an important mitigation for the loop heat pipe anomaly on GOES-17 during times when warm focal plane temperatures cause infrared channels that are needed for operational height assignments to fail. We also examine several application areas, including deep convection in tropical cyclones, planetary boundary layer dynamics, and fire smoke plumes, where stereo methods provide insights into atmospheric processes. The stereo method is broadly applicable across the geostationary ring where systems offering similar image navigation and registration (INR) performance as GOES-R are deployed.

The Impact of Height-Independent Errors in State Variables on the Determination of the Daytime Atmospheric Boundary Layer Depth Using the Bulk Richardson Approach

AbstractRawinsonde observations have long been used to estimate the atmospheric boundary layer depth (BLD), which is an important parameter for monitoring air quality, dispersion studies, weather forecast models, and inversion systems for estimating regional surface–atmosphere fluxes of tracers. Although many approaches exist for deriving the BLDs from rawinsonde observations, the bulk Richardson approach has been found to be most appropriate. However, the impact of errors in the measured thermodynamic and kinematic fields on the estimated BLDs remains unexplored. We argue that quantifying BLD error (δBLD) estimates is equally as important as the BLDs themselves. Here we quantified δBLD by applying the bulk Richardson method to 35 years of rawinsonde data obtained from three stations in the United States: Sterling, Virginia; Amarillo, Texas; and Salt Lake City, Utah. Results revealed similar features in terms of their respective errors. A −2°C bias in temperature yielded a mean δBLD ranging from −15 to 200 m. A +2°C bias in temperature yielded a mean δBLD ranging from −214 to +18 m. For a −5% relative humidity bias, the mean δBLD ranged from −302 to +7 m. For a +5% relative humidity bias, the mean δBLD ranged from +2 to +249 m. Differences of ±2 m s−1 in the winds yielded BLD errors of ~±300 m. The δBLD increased as a function of BLD when introducing errors to the thermodynamic fields and decreased as a function of BLD when introducing errors to the kinematic fields. These findings expand upon previous work evaluating rawinsonde-derived δBLD by quantifying δBLD arising from rawinsonde-derived thermodynamic and kinematic measurements. Knowledge of δBLD is critical in, for example, intercomparison studies where rawinsonde-derived BLDs are used as references.

Adjoint-Derived Impact of Assimilated Observations on Tropical Cyclone Intensity Forecasts of Hurricane Joaquin (2015) and Hurricane Matthew (2016)

AbstractThe adjoint-derived observation impact method is used as a diagnostic to derive the impact of assimilated observations on a metric representing the forecast intensity of a tropical cyclone (TC). Storm-centered composites of observation impact and the model background state are computed across 6-hourly analysis/forecast cycles to compute the composite observation impact throughout the life cycle of Hurricane Joaquin (2015) to evaluate the impact of in situ wind and temperature observations in the upper and lower troposphere, as well as the impact of brightness temperature and precipitable water observations, on intensity forecasts with forecast lengths from 12 to 48 h. The compositing across analysis/forecast cycles allows for the exploration of consistent relationships between the synoptic-scale state of the initial conditions and the impact of observations that are interpreted as flow-dependent interactions between model background bias and correction by assimilated observations on the TC intensity forecast. The track of Hurricane Matthew (2016), with an extended period of time near the coasts of Florida, Georgia, and the Carolinas, allows for a comparison of the impact of aircraft reconnaissance observations with the impact of nearby overland rawinsonde observations available within the same radius of the TC.

The Influence of Vertical Advection Discretization in the WRF-ARW Model on Capping Inversion Representation in Warm-Season, Thunderstorm-Supporting Environments

Abstract Previous studies have suggested that the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) Model is unable, in its default configuration, to adequately resolve the capping inversions that are commonly found in the warm-season, thunderstorm-supporting environments of the central United States. Since capping inversions typically form in environments of synoptic-scale subsidence, this study tests the hypothesis that this degradation results, in part, from implicit numerical damping of shorter-wavelength features associated with the model-default third-order-accurate vertical advection finite-differencing scheme. To aid in testing this hypothesis, two short-range, deterministic, convection-allowing model forecasts, one using the default third-order-accurate vertical advection finite-differencing scheme and another using a fourth-order-accurate differencing scheme (which lacks implicit damping but is numerically dispersive), are conducted for 25 days during the 2017 NOAA Hazardous Weather Testbed Spring Forecasting Experiment. Model-derived vertical profiles at lead times of 11 and 23 h are validated against available rawinsonde observations released in regions located in the Storm Prediction Center’s 0600 UTC day 1 convection outlook’s “general thunderstorm” forecast area. The fourth-order-accurate vertical advection finite-differencing scheme is shown to not result in statistically significant improvements to model-forecast capping inversions or, more generally, the vertical thermodynamic profile in the lower troposphere. Instead, the fourth-order-accurate differencing scheme primarily impacts the representation of longer-wavelength features already reasonably well resolved by the model. The analysis does, however, provide quantitative evidence over a large sample that, on average, the WRF-ARW model forecasts capping inversions that are too weak, with negative buoyancy spread out over too deep of a vertical layer, compared to observations.

Statistical harmonization and uncertainty assessment in the comparison of satellite and radiosonde climate variables

AbstractSatellite product validation is a key to ensure the delivery of quality products for climate and weather applications. To do this, a fundamental step is the comparison with other instruments, such as radiosonde. This is especially true for essential climate variables such as temperature and humidity.Thanks to a functional data representation, this paper uses a likelihood‐based approach that exploits the measurement uncertainties in a natural way. In particular, the comparison of temperature and humidity radiosonde measurements collected within the network of the Universal Rawinsonde Observation Program (RAOB) and the corresponding atmospheric profiles derived from the infrared atmospheric sounding interferometer aboard MetOp‐A and MetOp‐B satellites is developed with the aim of understanding the vertical smoothing mismatch uncertainty.Moreover, conventional RAOB functional data representation is assessed by means of a comparison with radiosonde reference measurements given by the Global Climate Observing System (GCOS) Reference Upper‐Air Network (GRUAN), which provides high‐resolution fully traceable radio‐sounding profiles. In this way, the uncertainty related to coarse vertical resolution, or sparseness, of the conventional RAOB is assessed.It has been found that the uncertainty of vertical smoothing mismatch averaged along the profile is 0.50 K for temperature and 0.16 g/kg for water‐vapor mixing ratio. Moreover, the uncertainty related to RAOB sparseness, averaged along the profile, is 0.29 K for temperature and 0.13 g/kg for water‐vapor mixing ratio.

Impacts of Modifications to a Local Planetary Boundary Layer Scheme on Forecasts of the Great Plains Low-Level Jet Environment

AbstractThe Great Plains low-level jet (LLJ) is influential in the initiation and evolution of nocturnal convection through the northward advection of heat and moisture, as well as convergence in the region of the LLJ nose. However, accurate numerical model forecasts of LLJs remain a challenge, related to the performance of the planetary boundary layer (PBL) scheme in the stable boundary layer. Evaluated here using a series of LLJ cases from the Plains Elevated Convection at Night (PECAN) program are modifications to a commonly used local PBL scheme, Mellor–Yamada–Nakanishi–Niino (MYNN), available in the Weather Research and Forecasting (WRF) Model. WRF forecast mean absolute error (MAE) and bias are calculated relative to PECAN rawinsonde observations. The first MYNN modification invokes a new set of constants for the scheme closure equations that, in the vicinity of the LLJ, decreases forecast MAEs of wind speed, potential temperature, and specific humidity more than 19%. For comparison, the Yonsei University (YSU) scheme results in wind speed MAEs 22% lower but specific humidity MAEs 17% greater than in the original MYNN scheme. The second MYNN modification, which incorporates the effects of potential kinetic energy and uses a nonzero mixing length in stable conditions as dependent on bulk shear, reduces wind speed MAEs 66% for levels below the LLJ, but increases MAEs at higher levels. Finally, Rapid Refresh analyses, which are often used for forecast verification, are evaluated here and found to exhibit a relatively large average wind speed bias of 3 m s−1 in the region below the LLJ, but with relatively small potential temperature and specific humidity biases.

Ship- and island-based soundings from the 2016 El Niño Rapid Response (ENRR) field campaign

Abstract. As the 2015/2016 El Niño was gathering strength in late 2015, scientists at the Earth System Research Laboratory's Physical Sciences Division proposed and led the implementation of the National Oceanic and Atmospheric Administration's (NOAA's) El Niño Rapid Response (ENRR) Field Campaign. ENRR observations included wind and thermodynamic profiles of the atmosphere over the near-equatorial eastern central Pacific Ocean, many of which were collected from two field sites and transmitted in near-real time for inclusion in global forecasting models. From 26 January to 28 March 2016, twice-daily rawinsonde observations were made from Kiritimati (pronounced Christmas) Island (2.0° N, 157.4° E; call sign CXENRR). From 16 February to 16 March 2016, three to eight radiosondes were launched each day from NOAA Ship Ronald H. Brown (allocated call sign WTEC) as it travelled southeast from Hawaii to service Tropical Atmosphere Ocean (TAO) buoys along longitudes 140 and 125° W and then north to San Diego, California. Both the rapid and remote nature of these deployments created particular difficulties in collecting and disseminating the soundings; these are described together with the methods used to reprocess the data after the field campaign finished. The reprocessed and lightly quality-controlled data have been put into an easy-to-read text format, qualifying them to be termed Level 2 soundings. They are archived and freely available for public access at NOAA's National Centers for Environmental Information (NCEI) in the form of two separate data sets: one consisting of 125 soundings from Kiritimati (https://doi.org/10.7289/V55Q4T5K), the other of 193 soundings from NOAA Ship Ronald H. Brown (https://doi.org/10.7289/V5X63K15). Of the Kiritimati soundings, 94 % reached the tropopause and 88 % reached 40 hPa, while 89 % of the ship's soundings reached the tropopause and 87 % reached 40 hPa. The soundings captured the repeated advance and retreat of the Intertropical Convergence Zone (ITCZ) at Kiritimati, a variety of marine tropospheric environments encountered by the ship, and lower-stratospheric features of the 2015–2016 QBO (quasi-biennial oscillation), all providing a rich view of the local atmosphere's response to the eastern central Pacific's extremely warm waters during the 2015/16 El Niño.

Low‐Level Baroclinic Jets Over the New Arctic Ocean

AbstractDuring the Sea State cruise in the fall of 2015, in the Chukchi/Beaufort Sea region, there were five strong (>10 m s−1) surface wind events associated with low‐level atmospheric jets. These jets were analyzed using rawinsonde observations, ship measurements, and a numerical forecast model. The jets occurred when easterly winds aligned with the ice edge, generating low‐level baroclinicity in a direction favorable for increasing the geostrophic wind speed toward the surface. The maximum wind speed usually occurred at the top of the atmospheric boundary layer with wind speeds greater than 8 m s−1 extending through the capping inversion to 2,000–3,000 m elevation, with winds decreasing toward the surface in the boundary layer due to friction. The width (crosswind) dimensions of the jets were 250–400 km and they existed downwind for as long as the winds remained generally parallel to the ice edges, typically several hundred kilometers. Thermal winds calculated from crosswind‐oriented rawinsonde temperature profiles matched the observed vertical wind speed gradients in the inversion regions, indicating that the jets were in quasi‐geostrophic (inversion layer) or quasi‐frictional (boundary layer) balance, with low Rossby numbers. We define these as “baroclinic” type jets, which are distinct from “ice/sea breeze” type jets which flow more down the pressure and density gradients, and have high Rossby numbers. The operational model analyses matched the observations quite well, giving confidence that these types of jets can be simulated and predicted as long as the models have sufficient resolution and accurately parameterize vertical heat fluxes.

A 1998–2013 climatology of Kyushu, Japan: seasonal variations of stability and rainfall

ABSTRACTThe seasonal variation of the atmospheric structure, vertical shear, stability, and rainfall distribution over the island of Kyushu, southern Japan, is studied using 16 years of observational data, from 1998 to 2013. Over 20 000 twice‐daily rawinsonde observations from the cities of Kagoshima (southern Kyushu) and Fukuoka (northern Kyushu) are utilized along with daily precipitation data from 120 Japan Meteorological Agency stations located across the island. Understanding the local atmospheric circulation and climatological behaviour of the island is important both locally due to the island's large population and regionally, due to its position in relation to the tracks of typhoons generated annually over the Pacific ocean and make landfall here, the rainy season associated with the Asian monsoon, and the large number of active volcanoes located on or near the island, emitting volcanic gases and ash on a daily basis.Using a categorisation based on convective available potential energy and precipitable water, three sounding categories are distinguished, described using the origins of the air masses involved, as seen from trajectory modelling: continental (dry), oceanic (moist/unstable), and mixed (moist/stable). Mean soundings for each category are examined, along with information on their annual and seasonal variability. Each sounding category is linked with a rainfall response: low amounts of rainfall, heavy convective rainfall, and heavy, non‐convective rainfall, respectively. Despite the large difference in the potential for heavy rainfall rates, average daily rainfall rate is similar for the two moist categories, but peak rainfall rates for convective rainfall are twice as large as those for non‐convective. Despite the simplicity of the criteria, the three sounding categories are statistically robust and exhibit a relatively small amount of variability. The monthly combination of the sounding categories is shown to be a deciding factor in the seasonal variation of the atmospheric circulation, weather, and precipitation over the island.

Estimating Daytime Planetary Boundary Layer Heights over a Valley from Rawinsonde Observations at a Nearby Airport: An Application to the Page Valley in Virginia, United States

AbstractThe planetary boundary layer (PBL) height is an essential parameter required for many applications, including weather forecasting and dispersion modeling for air quality. Estimates of PBL height are not easily available and often come from twice-daily rawinsonde observations at airports, typically at 0000 and 1200 UTC. Questions often arise regarding the applicability of PBL heights retrieved from these twice-daily observations to surrounding locations. Obtaining this information requires knowledge of the spatial variability of PBL heights. This knowledge is particularly limited in regions with mountainous terrain. The goal of this study is to develop a method for estimating daytime PBL heights in the Page Valley, located in the Blue Ridge Mountains of Virginia. The approach includes using 1) rawinsonde observations from the nearest sounding station [Dulles Airport (IAD)], which is located 90 km northeast of the Page Valley, 2) North American Regional Reanalysis (NARR) output, and 3) simulations with the Weather Research and Forecasting (WRF) Model. When selecting days on which PBL heights from NARR compare well to PBL heights determined from the IAD soundings, it is found that PBL heights are higher (on the order of 200–400 m) over the Page Valley than at IAD and that these differences are typically larger in summer than in winter. WRF simulations indicate that larger sensible heat fluxes and terrain-following characteristics of PBL height both contribute to PBL heights being higher over the Page Valley than at IAD.

Evaluation of the southerly low‐level jet climatology for the central United States as simulated by NARCCAP regional climate models

An ensemble of simulations from four regional climate models (RCMs) driven by a global reanalysis was obtained from the North American Regional Climate Change Assessment Program (NARCCAP) and used to evaluate the ability of the RCMs to simulate the long-term (1979–2000) climatology of southerly low-level jets (S-LLJs) in the central United States. The RCM-derived S-LLJ climatologies were evaluated against rawinsonde observations for the same period. The use of a small ensemble of RCM simulations helped to identify model differences and assisted with interpretation. The RCMs generally reproduced the broad spatial patterns and temporal variations of jet frequency and average jet height and speed. No model consistently outperformed the others in all aspects of the evaluation, although differences existed between models in the placement, migration and relative strength of ‘hotspots’ of more frequent jet activity. In particular, three of the four models placed the centre of greatest nocturnal S-LLJ activity during the warm season in northern and central Texas, whereas for the other model the greatest jet activity was located in the south-central plains (Kansas/Oklahoma). The magnitude of a S-LLJ frequency maximum over south Texas also varied between models, with simulated frequencies exceeding observed frequencies for some models but substantially underestimating for others. The evaluation presented here highlights the potential applications of RCMs in S-LLJ research for future climate and other assessment studies that require three-dimensional data with relatively high spatial and temporal resolutions. The overall performance of the models in reproducing the long-term S-LLJ climatology supports the use of NARCCAP RCM simulations in climate assessments for the central United States where S-LLJs are an important contributor to the regional climatology.

Northern Hemisphere winter storm track trends since 1959 derived from multiple reanalysis datasets

In this study, a comprehensive comparison of Northern Hemisphere winter storm track trend since 1959 derived from multiple reanalysis datasets and rawinsonde observations has been conducted. In addition, trends in terms of variance and cyclone track statistics have been compared. Previous studies, based largely on the National Center for Environmental Prediction–National Center for Atmospheric Research Reanalysis (NNR), have suggested that both the Pacific and Atlantic storm tracks have significantly intensified between the 1950s and 1990s. Comparison with trends derived from rawinsonde observations suggest that the trends derived from NNR are significantly biased high, while those from the European Center for Medium Range Weather Forecasts 40-year Reanalysis and the Japanese 55-year Reanalysis are much less biased but still too high. Those from the two twentieth century reanalysis datasets are most consistent with observations but may exhibit slight biases of opposite signs. Between 1959 and 2010, Pacific storm track activity has likely increased by 10 % or more, while Atlantic storm track activity has likely increased by <10 %. Our analysis suggests that trends in Pacific and Atlantic basin wide storm track activity prior to the 1950s derived from the two twentieth century reanalysis datasets are unlikely to be reliable due to changes in density of surface observations. Nevertheless, these datasets may provide useful information on interannual variability, especially over the Atlantic.

Evolution of precipitation and convective echo top heights observed by TRMM radar over the Indian Ocean during DYNAMO

AbstractRadar data from the Tropical Rainfall Measuring Mission show the evolution of echo tops of convective elements over the Indian Ocean and Maritime Continent during the Dynamics of the Madden‐Julian Oscillation (DYNAMO) field campaign of 2011–2012. Echo top heights exhibited a bimodal distribution wherein cumulonimbi of moderate height constituted a “congestus mode” while vertically extensive cumulonimbus made up a “deep mode.” An intraseasonal time scale dominated variability in these modes from October to January over much of the Indian Ocean. Over the Maritime Continent, there was no clear intraseasonal signal in convective echo top heights. Where the intraseasonal oscillation was detected, radar echoes evolved from being dominated by the congestus mode to being characterized by more deep mode convection on time scales of less than 1 week. The areal coverage of congestus echoes began to increase 2–8 days prior to the rise in area of deep echoes. These satellite‐derived results confirm that the time scale for convective deepening seen at individual DYNAMO observational sites is consistent with that of convection on the large scale over the Indian Ocean. Intraseasonal variability of zonal wind, temperature, and humidity as depicted by reanalysis is also consistent with that derived from rawinsonde observations during DYNAMO. Thus, the gradual buildup of convection as depicted by recent versions of the “discharge‐recharge” hypothesis does not accurately describe evolutions of convection prior to MJO events observed during DYNAMO, although cloud moistening processes may still be relevant on time scales of 1 week or less.

Water vapor motion signal extraction from FY-2E longwave infrared window images for cloud-free regions: The temporal difference technique

The aim of this study is to calculate the low-level atmospheric motion vectors (AMVs) in clear areas with FY-2E IR2 window (11.59–12.79 μm) channel imagery, where the traditional cloud motion wind technique fails. A new tracer selection procedure, which we call the temporal difference technique, is demonstrated in this paper. This technique makes it possible to infer low-level wind by tracking features in the moisture pattern that appear as brightness temperature (T B) differences between consecutive sequences of 30-min-interval FY-2E IR2 images over cloud-free regions. The T B difference corresponding to a 10% change in water vapor density is computed with the Moderate Resolution Atmospheric Transmission (MODTRAN4) radiative transfer model. The total contribution from each of the 10 layers is analyzed under four typical atmospheric conditions: tropical, midlatitude summer, U.S. standard, and midlatitude winter. The peak level of the water vapor weighting function for the four typical atmospheres is assigned as a specific height to the T B “wind”. This technique is valid over cloud-free ocean areas. The proposed algorithm exhibits encouraging statistical results in terms of vector difference (VD), speed bias (BIAS), mean vector difference (MVD), standard deviation (SD), and root-mean-square error (RMSE), when compared with the wind field of NCEP reanalysis data and rawinsonde observations.